Learning-Related Changes in Adolescents' Neural Networks during Hypothesis-Generating and Hypothesis-Understanding Training

ERIC Educational Resources Information Center

Lee, Jun-Ki; Kwon, Yongju

2012-01-01

Fourteen science high school students participated in this study, which investigated neural-network plasticity associated with hypothesis-generating and hypothesis-understanding in learning. The students were divided into two groups and participated in either hypothesis-generating or hypothesis-understanding type learning programs, which were…

Discriminative Learning with Markov Logic Networks

DTIC Science & Technology

2009-10-01

Discriminative Learning with Markov Logic Networks Tuyen N. Huynh Department of Computer Sciences University of Texas at Austin Austin, TX 78712...emerging area of research that addresses the problem of learning from noisy structured/relational data. Markov logic networks (MLNs), sets of weighted...TASK NUMBER 5f. WORK UNIT NUMBER 7. PERFORMING ORGANIZATION NAME(S) AND ADDRESS(ES) University of Texas at Austin,Department of Computer

Teaching Triple Science: GCSE Biology

ERIC Educational Resources Information Center

Learning and Skills Network (NJ3), 2007

2007-01-01

The Department for Children, Schools and Families (DCSF) has contracted with the Learning and Skills Network to support awareness and take-up of Triple Science GCSEs through the Triple Science Support Programme. This publication provides an introduction to teaching and learning approaches for the extension topics within GCSE Biology. It highlights…

Using Mobile Phones in Support of Student Learning in Secondary Science Inquiry Classrooms

ERIC Educational Resources Information Center

Khoo, Elaine; Otrel-Cass, Kathrin

2017-01-01

This paper reports on findings from a research project concerned with how electronic networking tools (e-networked tools), such as the Internet, online forums, and mobile technologies, can support authentic science inquiry in junior secondary classrooms. It focuses on three qualitative case studies involving science teachers from two high schools…

Deep learning for computational chemistry

DOE Office of Scientific and Technical Information (OSTI.GOV)

Goh, Garrett B.; Hodas, Nathan O.; Vishnu, Abhinav

The rise and fall of artificial neural networks is well documented in the scientific literature of both the fields of computer science and computational chemistry. Yet almost two decades later, we are now seeing a resurgence of interest in deep learning, a machine learning algorithm based on “deep” neural networks. Within the last few years, we have seen the transformative impact of deep learning the computer science domain, notably in speech recognition and computer vision, to the extent that the majority of practitioners in those field are now regularly eschewing prior established models in favor of deep learning models. Inmore » this review, we provide an introductory overview into the theory of deep neural networks and their unique properties as compared to traditional machine learning algorithms used in cheminformatics. By providing an overview of the variety of emerging applications of deep neural networks, we highlight its ubiquity and broad applicability to a wide range of challenges in the field, including QSAR, virtual screening, protein structure modeling, QM calculations, materials synthesis and property prediction. In reviewing the performance of deep neural networks, we observed a consistent outperformance against non neural networks state-of-the-art models across disparate research topics, and deep neural network based models often exceeded the “glass ceiling” expectations of their respective tasks. Coupled with the maturity of GPU-accelerated computing for training deep neural networks and the exponential growth of chemical data on which to train these networks on, we anticipate that deep learning algorithms will be a useful tool and may grow into a pivotal role for various challenges in the computational chemistry field.« less

Turning Visitors into Citizens: Using Social Science for Civic Engagement in Informal Science Education Centers

ERIC Educational Resources Information Center

Bunten, Alexis; Arvizu, Shannon

2013-01-01

How can museums and other informal learning institutions cultivate greater civic engagement among the visiting public around important social issues? This case study of the National Network of Ocean and Climate Change Interpreters' (NNOCCI) professional learning community illustrates how insights from the social sciences can be productively…

Building Ocean Learning Communities: A COSEE Science and Education Partnership

NASA Astrophysics Data System (ADS)

Robigou, V.; Bullerdick, S.; Anderson, A.

2007-12-01

The core mission of the Centers for Ocean Sciences Education Excellence (COSEE) is to promote partnerships between research scientists and educators through a national network of regional and thematic centers. In addition, the COSEEs also disseminate best practices in ocean sciences education, and promote ocean sciences as a charismatic interdisciplinary vehicle for creating a more scientifically literate workforce and citizenry. Although each center is mainly funded through a peer-reviewed grant process by the National Science Foundation (NSF), the centers form a national network that fosters collaborative efforts among the centers to design and implement initiatives for the benefit of the entire network and beyond. Among these initiatives the COSEE network has contributed to the definition, promotion, and dissemination of Ocean Literacy in formal and informal learning settings. Relevant to all research scientists, an Education and Public Outreach guide for scientists is now available at www.tos.org. This guide highlights strategies for engaging scientists in Ocean Sciences Education that are often applicable in other sciences. To address the challenging issue of ocean sciences education informed by scientific research, the COSEE approach supports centers that are partnerships between research institutions, formal and informal education venues, advocacy groups, industry, and others. The COSEE Ocean Learning Communities, is a partnership between the University of Washington College of Ocean and Fishery Sciences and College of Education, the Seattle Aquarium, and a not-for-profit educational organization. The main focus of the center is to foster and create Learning Communities that cultivate contributing, and ocean sciences-literate citizens aware of the ocean's impact on daily life. The center is currently working with volunteer groups around the Northwest region that are actively involved in projects in the marine environment and to empower these diverse groups including research scientists, formal and informal educators, business representatives, and non-profit groups to identify ocean-related problems, and develop solutions to share with their own communities. COSEE OLC practices and studies the skills of developing these collaborations.

Artificial Neural Networks for Modeling Knowing and Learning in Science.

ERIC Educational Resources Information Center

Roth, Wolff-Michael

2000-01-01

Advocates artificial neural networks as models for cognition and development. Provides an example of how such models work in the context of a well-known Piagetian developmental task and school science activity: balance beam problems. (Contains 59 references.) (Author/WRM)

A Collaborative Learning Network Approach to Improvement: The CUSP Learning Network.

PubMed

Weaver, Sallie J; Lofthus, Jennifer; Sawyer, Melinda; Greer, Lee; Opett, Kristin; Reynolds, Catherine; Wyskiel, Rhonda; Peditto, Stephanie; Pronovost, Peter J

2015-04-01

Collaborative improvement networks draw on the science of collaborative organizational learning and communities of practice to facilitate peer-to-peer learning, coaching, and local adaption. Although significant improvements in patient safety and quality have been achieved through collaborative methods, insight regarding how collaborative networks are used by members is needed. Improvement Strategy: The Comprehensive Unit-based Safety Program (CUSP) Learning Network is a multi-institutional collaborative network that is designed to facilitate peer-to-peer learning and coaching specifically related to CUSP. Member organizations implement all or part of the CUSP methodology to improve organizational safety culture, patient safety, and care quality. Qualitative case studies developed by participating members examine the impact of network participation across three levels of analysis (unit, hospital, health system). In addition, results of a satisfaction survey designed to evaluate member experiences were collected to inform network development. Common themes across case studies suggest that members found value in collaborative learning and sharing strategies across organizational boundaries related to a specific improvement strategy. The CUSP Learning Network is an example of network-based collaborative learning in action. Although this learning network focuses on a particular improvement methodology-CUSP-there is clear potential for member-driven learning networks to grow around other methods or topic areas. Such collaborative learning networks may offer a way to develop an infrastructure for longer-term support of improvement efforts and to more quickly diffuse creative sustainment strategies.

The Intellectual Structure of Research on Educational Technology in Science Education (ETiSE): A Co-citation Network Analysis of Publications in Selected Journals (2008-2013)

NASA Astrophysics Data System (ADS)

Tang, Kai-Yu; Tsai, Chin-Chung

2016-01-01

The main purpose of this paper is to investigate the intellectual structure of the research on educational technology in science education (ETiSE) within the most recent years (2008-2013). Based on the criteria for educational technology research and the citation threshold for educational co-citation analysis, a total of 137 relevant ETiSE papers were identified from the International Journal of Science Education, the Journal of Research in Science Teaching, Science Education, and the Journal of Science Education and Technology. Then, a series of methodologies were performed to analyze all 137 source documents, including document co-citation analysis, social network analysis, and exploratory factor analysis. As a result, 454 co-citation ties were obtained and then graphically visualized with an undirected network, presenting a global structure of the current ETiSE research network. In addition, four major underlying intellectual subfields within the main component of the ETiSE network were extracted and named as: (1) technology-enhanced science inquiry, (2) simulation and visualization for understanding, (3) technology-enhanced chemistry learning, and (4) game-based science learning. The most influential co-citation pairs and cross-boundary phenomena were then analyzed and visualized in a co-citation network. This is the very first attempt to illuminate the core ideas underlying ETiSE research by integrating the co-citation method, factor analysis, and the networking visualization technique. The findings of this study provide a platform for scholarly discussion of the dissemination and research trends within the current ETiSE literature.

Quantitative learning strategies based on word networks

NASA Astrophysics Data System (ADS)

Zhao, Yue-Tian-Yi; Jia, Zi-Yang; Tang, Yong; Xiong, Jason Jie; Zhang, Yi-Cheng

2018-02-01

Learning English requires a considerable effort, but the way that vocabulary is introduced in textbooks is not optimized for learning efficiency. With the increasing population of English learners, learning process optimization will have significant impact and improvement towards English learning and teaching. The recent developments of big data analysis and complex network science provide additional opportunities to design and further investigate the strategies in English learning. In this paper, quantitative English learning strategies based on word network and word usage information are proposed. The strategies integrate the words frequency with topological structural information. By analyzing the influence of connected learned words, the learning weights for the unlearned words and dynamically updating of the network are studied and analyzed. The results suggest that quantitative strategies significantly improve learning efficiency while maintaining effectiveness. Especially, the optimized-weight-first strategy and segmented strategies outperform other strategies. The results provide opportunities for researchers and practitioners to reconsider the way of English teaching and designing vocabularies quantitatively by balancing the efficiency and learning costs based on the word network.

Learning Networks: Iran and the Effects of Sanctions

DTIC Science & Technology

2013-03-27

synthesizes and summarizes our research efforts. 15. SUBJECT TERMS Network Science, Social Network Analysis, Dynamic Networks 16. SECURITY...www.ecssr.com/ECSSR/appmanager/portal/ecssr?_nfpb=true. Klebnikov, Paul. " Millionaire Mullahs." Forbes. Forbes Magazine, 21 July 2003. Web. http

Teen Science Cafés: A Model for Addressing Broader Impacts, Diversity, and Recruitment

NASA Astrophysics Data System (ADS)

Hall, M.; Mayhew, M. A.

2017-12-01

Teen Science Café programs (TeenScienceCafe.org) are a free and fun way for teens to explore science and technology affecting their lives. Through lively presentations, conversation, and activities to explore a topic deeply, Café programs open doors for teens to learn from experts about exciting and rewarding STEM career pathways. The programs are local and led by teens with the help of an adult mentor. The Teen Science Café Network (teensciencecafe.org) provides mentoring and resources, including small grants, to help organizations get started with and then maintain successful "teen café" programs. Through membership in the Network, more than 80 Teen Science Cafés have sprung up across the country, from rural towns to major cities. They serve a critical need for teens - meeting and engaging with STEM professionals, learning about their career paths, and seeing their passion for the work they do. Teen Science Café programs can offer geoscience departments a substantive, yet low cost, way to meet the challenges many of them face: finding ways to increase enrollment, helping faculty satisfy the broader impacts requirements of funding agencies, connecting with the surrounding communities, and providing opportunities for faculty and graduate students to learn how to communicate their science effectively to the public audience. The typical experience of scientists who have presented in teen cafés throughout the Network is that the communication skills learned spill over into their courses, proposals, and presentations to administrators and program officers. A department might partner with one or more organizations in their surrounding communities—libraries, for example—and engage its faculty and its graduate students—and even its undergraduates—in providing geoscience programming across multiple disciplines to local teens. Besides the internal benefits to the department's personnel and the value of establishing connections with community organizations, the impact of such engagement might well be attracting students to the department. We seek geoscience departments that are interested in this concept and willing to join the Teen Science Café Network (TeenScienceCafe.org) and participate in a study of how Teen Science Cafés may impact undergraduate recruitment to their departments.

After-School Spaces: Looking for Learning in All the Right Places

NASA Astrophysics Data System (ADS)

Schnittka, Christine G.; Evans, Michael A.; Won, Samantha G. L.; Drape, Tiffany A.

2016-06-01

After-school settings provide youth with homework support, social outlets and fun activities, and help build self-confidence. They are safe places for forming relationships with caring adults. More after-school settings are starting to integrate Science, Technology, Engineering, and Mathematics (STEM) topics. What science skills and concepts might youth learn in engineering design-based after-school settings? Traditional assessments often fail to capture the ways youth learn in informal settings, and deep science understandings are notoriously difficult to measure. In this study, we examined three after-school settings where 65 youth were learning science through engineering design challenges. In this informal setting, we examined storyboards, social networking forum (SNF) chat logs, videos of whole-class interactions, interviews with groups and single participants, and traditional multiple-choice pre- and posttest results. As we looked for evidence of learning, we found that the social networking forum was rich with data. Interviews were even more informative, much more so than traditional pencil and paper multiple-choice tests. We found that different kinds of elicitation strategies adopted by site leaders and facilitators played an important role in the ways youth constructed knowledge. These elicitation strategies also helped us find evidence of learning. Based on findings, future iterations of the curricula will involve tighter integration of social networking forums, continued use of videotaped interviews for data collection, an increased focus on training site leaders and facilitators in elicitation strategies, and more open-ended pencil and paper assessments in order to facilitate the process of looking for learning.

Networking Skills as a Career Development Practice: Lessons from the Earth Science Women's Network (ESWN)

NASA Astrophysics Data System (ADS)

Hastings, M. G.; Kontak, R.; Holloway, T.; Marin-Spiotta, E.; Steiner, A. L.; Wiedinmyer, C.; Adams, A. S.; de Boer, A. M.; Staudt, A. C.; Fiore, A. M.

2010-12-01

Professional networking is often cited as an important component of scientific career development, yet there are few resources for early career scientists to develop and build networks. Personal networks can provide opportunities to learn about organizational culture and procedures, expectations, advancement opportunities, and best practices. They provide access to mentors and job placement opportunities, new scientific collaborations, speaker and conference invitations, increased scientific visibility, reduced isolation, and a stronger feeling of community. There is evidence in the literature that a sense of community positively affects the engagement and retention of underrepresented groups, including women, in science. Thus women scientists may particularly benefit from becoming part of a network. The Earth Science Women’s Network (ESWN) began in 2002 as an informal peer-to-peer mentoring initiative among a few recent Ph.D.s. The network has grown exponentially to include over 1000 women scientists across the globe. Surveys of our membership about ESWN report positive impacts on the careers of women in Earth sciences, particularly those in early career stages. Through ESWN, women share both professional and personal advice, establish research collaborations, communicate strategies on work/life balance, connect with women at various stages of their careers, and provide perspectives from cultures across the globe. We present lessons learned through the formal and informal activities promoted by ESWN in support of the career development of women Earth scientists.

A Collaborative Diagonal Learning Network: The role of formal and informal professional development in elementary science reform

NASA Astrophysics Data System (ADS)

Cooke-Nieves, Natasha Anika

Science education research has consistently shown that elementary teachers have a low self-efficacy and background knowledge to teach science. When they teach science, there is a lack of field experiences and inquiry-based instruction at the elementary level due to limited resources, both material and pedagogical. This study focused on an analysis of a professional development (PD) model designed by the author known as the Collaborative Diagonal Learning Network (CDLN). The purpose of this study was to examine elementary school teacher participants pedagogical content knowledge related to their experiences in a CDLN model. The CDLN model taught formal and informal instruction using a science coach and an informal educational institution. Another purpose for this research included a theoretical analysis of the CDLN model to see if its design enabled teachers to expand their resource knowledge of available science education materials. The four-month-long study used qualitative data obtained during an in-service professional development program facilitated by a science coach and educators from a large natural history museum. Using case study as the research design, four elementary school teachers were asked to evaluate the effectiveness of their science coach and museum educator workshop sessions. During the duration of this study, semi-structured individual/group interviews and open-ended pre/post PD questionnaires were used. Other data sources included researcher field notes from lesson observations, museum field trips, audio-recorded workshop sessions, email correspondence, and teacher-created artifacts. The data were analyzed using a constructivist grounded theory approach. Themes that emerged included increased self-efficacy; increased pedagogical content knowledge; increased knowledge of museum education resources and access; creation of a professional learning community; and increased knowledge of science notebooking. Implications for formal and informal professional development in elementary science reform are offered. It is suggested that researchers investigate collaborative coaching through the lenses of organizational learning network theory, and develop professional learning communities with formal and informal educators; and that professional developers in city school systems and informal science institutions work in concert to produce more effective elementary teachers who not only love science but love teaching it.

Multilayer Networks of Self-Interested Adaptive Units.

DTIC Science & Technology

1987-07-01

T. J. Sejnowski. A learning algorithm for Boltzmann machines. Cognitive Science, 9:147-169, 1985. 121 S. Amarel. Problems of Representation in...Barto and C. W. Anderson. Structural learning in connectionist sys- tems. In Proceedings of the Seventh Annual Conference of the Cognitive Science...E. Hinton and T. J. Sejnowski. Analyzing cooperative computation. In Proceedings of the Fifth Annual Conference of the Cognitive Science Society

The networked student: A design-based research case study of student constructed personal learning environments in a middle school science course

NASA Astrophysics Data System (ADS)

Drexler, Wendy

This design-based research case study applied a networked learning approach to a seventh grade science class at a public school in the southeastern United States. Students adapted emerging Web applications to construct personal learning environments for in-depth scientific inquiry of poisonous and venomous life forms. The personal learning environments constructed used Application Programming Interface (API) widgets to access, organize, and synthesize content from a number of educational Internet resources and social network connections. This study examined the nature of personal learning environments; the processes students go through during construction, and patterns that emerged. The project was documented from both an instructional and student-design perspective. Findings revealed that students applied the processes of: practicing digital responsibility; practicing digital literacy; organizing content; collaborating and socializing; and synthesizing and creating. These processes informed a model of the networked student that will serve as a framework for future instructional designs. A networked learning approach that incorporates these processes into future designs has implications for student learning, teacher roles, professional development, administrative policies, and delivery. This work is significant in that it shifts the focus from technology innovations based on tools to student empowerment based on the processes required to support learning. It affirms the need for greater attention to digital literacy and responsibility in K12 schools as well as consideration for those skills students will need to achieve success in the 21st century. The design-based research case study provides a set of design principles for teachers to follow when facilitating student construction of personal learning environments.

Education on the Electronic Frontier: Teleapprentices in Globally Distributed Educational Contexts.

ERIC Educational Resources Information Center

Levin, James A.; And Others

1987-01-01

The Inter-cultural Network is an electronic communication network connecting faculty and upper elementary through graduate students in the U.S., Mexico, Japan, and Israel. The students address the problem of water shortage, while learning science concepts and transferring learning. A new form of instruction, teleapprenticeships, is suggested. (GDC)

Computers as Media for Communication: Learning and Development in a Whole Earth Context.

ERIC Educational Resources Information Center

Levin, James A.

Educationally successful electronic network activities involving microcomputers and long-distance networks include a student newswire, joint social science projects, and joint science projects. A newswire activity, such as "The Computer Chronicles," can provide a wide range of audiences for writing, a functional environment for reading, and a…

The HSP, the QCN, and the Dragon: Developing inquiry-based QCN instructional modules in Taiwan

NASA Astrophysics Data System (ADS)

Chen, K. H.; Liang, W.; Chang, C.; Yen, E.; Lin, C.; Lin, G.

2012-12-01

High Scope Program (HSP) is a long-term project funded by NSC in Taiwan since 2006. It is designed to elevate the quality of science education by means of incorporating emerging science and technology into the traditional curricula in senior high schools. Quake-Catcher Network (QCN), a distributed computing project initiated by Stanford University and UC Riverside, encourages the volunteers to install the low-cost, novel sensors at home and school to build a seismic network. To meet both needs, we have developed a model curriculum that introduces QCN, earthquake science, and cloud computing into high school classrooms. Through professional development workshops, Taiwan cloud-based earthquake science learning platform, and QCN club on Facebook, we have worked closely with Lan-Yang Girl's Senior High School teachers' team to design workable teaching plans through a practical operation of seismic monitoring at home or school. However, some obstacles to learning appear including QCN installation/maintain problems, high self-noise of the sensor, difficulty of introducing earthquake sciences for high school teachers. The challenges of QCN outreach in Taiwan bring out our future plans: (1) development of easy, frequently updated, physics-based QCN-experiments for high school teachers, and (2) design of an interactive learning platform with social networking function for students.

The Effect of Scaffolding Strategies for Inscriptions and Argumentation in a Science Cyberlearning Environment

ERIC Educational Resources Information Center

Kern, Cindy L.; Crippen, Kent J.

2017-01-01

Scientific inscriptions--graphs, diagrams, and data--and argumentation are integral to learning and communicating science and are common elements in cyberlearning environments--those involving the use of networked learning technologies. However, previous research has indicated that learners struggle to use inscriptions and when they engage in…

Exploring Complex Engineering Learning over Time with Epistemic Network Analysis

ERIC Educational Resources Information Center

Svarovsky, Gina Navoa

2011-01-01

Recently, K-12 engineering education has received increased attention as a pathway to building stronger foundations in math and science and introducing young people to the profession. However, the National Academy of Engineering found that many K-12 engineering programs focus heavily on engineering design and science and math learning while…

A Strategy to Learn How to Build Scientific-Education and Outreach Partnerships in the Ocean Sciences: COSEE Ocean Learning Communities.

NASA Astrophysics Data System (ADS)

Keil, R. G.; Bell, P. L.; Bittner, M. S.; Robigou, V.; Sider, K.

2005-12-01

The College of Ocean and Fishery Sciences and the College of Education at the University of Washington, the Seattle Aquarium, and the California Maritime Academy formed a partnership to establish a Center for Ocean Sciences Education Excellence (COSEE) labeled "Ocean Learning Communities." The COSEE-OLC will join the national network of NSF-funded centers that provide a catalytic environment in which partnerships between ocean researchers and educators flourish. The COSEE network contributes to the national advancement of ocean science education by sharing high-quality K-12 or informal education programs, best practices and methodologies, and offering exemplary courses through the network and at national professional meetings. Building on the successes and lessons of the existing COSEE centers, the COSEE-OLC will foster collaborations among the oceanography research community, the science of learning community, informal and formal educators, the general public, and the maritime industry in the Northwest region and the West coast. The concept for this partnership is based on reaching out to traditionally underserved populations (from the businesses that use the sea or for which economic success depends on the oceans to the united native tribes), listening to their concerns and needs and how these can be addressed within the context of ocean-based research. The challenges of integrating education and outreach with scientific research programs are addressed by the center's main catalytic activity to create Ocean Learning Communities. These communities will be gatherings of traditionally disparate stakeholders including scientists, educators, representatives of businesses with a connection to the oceans, and citizens who derive economic or recreational sustenance from the oceans. The center's principal goal is to, through time and structured learning activities, support various communities 1) to develop a common language and 2) to make a commitment to creating collaborations that will improve ocean research and public awareness at the regional scale. Researchers in the science of learning will evaluate and study the successes and challenges of these regional approaches to better understand the development and sustainability of productive partnerships and to develop learning models to share and apply at the national level.

An Online Social Networking Approach to Reinforce Learning of Rocks and Minerals

ERIC Educational Resources Information Center

Kennelly, Patrick

2009-01-01

Numerous and varied methods are used in introductory Earth science and geology classes to help students learn about rocks and minerals, such as classroom lectures, laboratory specimen identification, and field trips. This paper reports on a method using online social networking. The choice of this forum was based on two criteria. First, many…

The Collaboratory Notebook: A Networked Knowledge-Building Environment for Project Learning.

ERIC Educational Resources Information Center

O'Neill, D. Kevin; Gomez, Louis M.

The Collaboratory Notebook, developed as part of the Learning Through Collaborative Visualization Project (CoVis), is a networked, multimedia knowledge-building environment which has been designed to help students, teachers and scientists share inquiry over the boundaries of time and space. CoVis is an attempt to change the way that science is…

Merging Social Networking Environments and Formal Learning Environments to Support and Facilitate Interprofessional Instruction

PubMed Central

King, Sharla; Greidanus, Elaine; Carbonaro, Michael; Drummond, Jane; Patterson, Steven

2009-01-01

This study describes the redesign of an interprofessional team development course for health science students. A theoretical model is hypothesized as a framework for the redesign process, consisting of two themes: 1) the increasing trend among post-secondary students to participate in social networking (e.g., Facebook, Second Life) and 2) the need for healthcare educators to provide interprofessional training that results in effective communities of practice and better patient care. The redesign focused on increasing the relevance of the course through the integration of custom-designed technology to facilitate social networking during their interprofessional education. Results suggest that students in an educationally structured social networking environment can be guided to join learning communities quickly and access course materials. More research and implementation work is required to effectively develop interprofessional health sciences communities in a combined face-to-face and on-line social networking context. PMID:20165519

Merging social networking environments and formal learning environments to support and facilitate interprofessional instruction.

PubMed

King, Sharla; Greidanus, Elaine; Carbonaro, Michael; Drummond, Jane; Patterson, Steven

2009-04-28

This study describes the redesign of an interprofessional team development course for health science students. A theoretical model is hypothesized as a framework for the redesign process, consisting of two themes: 1) the increasing trend among post-secondary students to participate in social networking (e.g., Facebook, Second Life) and 2) the need for healthcare educators to provide interprofessional training that results in effective communities of practice and better patient care. The redesign focused on increasing the relevance of the course through the integration of custom-designed technology to facilitate social networking during their interprofessional education. Results suggest that students in an educationally structured social networking environment can be guided to join learning communities quickly and access course materials. More research and implementation work is required to effectively develop interprofessional health sciences communities in a combined face-to-face and on-line social networking context.

A Network for Integrated Science and Mathematics Teaching and Learning. NCSTL Monograph Series, #2.

ERIC Educational Resources Information Center

Berlin, Donna F.; White, Arthur L.

This monograph presents a summary of the results of the Wingspread Conference in April, 1991 concerning the viability and future of the concept of integration of mathematics and science teaching and learning. The conference focused on three critical issues: (1) development of definitions of integration and a rationale for integrated teaching and…

CoCoRaHS (The Community Collaborative Rain, Hail and Snow Network): Analysis of Participant Survey Data to Uncover Learning through Participation

NASA Astrophysics Data System (ADS)

Holzer, M. A.; Zimmerman, T.; Doesken, N. J.; Reges, H. W.; Newman, N.; Turner, J.; Schwalbe, Z.

2010-12-01

CoCoRaHS (The Community Collaborative Rain, Hail and Snow network) is based out of Fort Collins Colorado and is an extremely successful citizen science project with over 15,000 volunteers collecting valuable precipitation data. Forecasters and scientists use data from this dense network to illuminate and illustrate the high small-scale variability of precipitation across the nation. This presentation will discuss the results of a survey of CoCoRaHS participants as related to 1) citizen scientists’ motivation and learning; 2) the challenges of identifying how people learn science in citizen science projects; and 3) a potential research-based framework for how people learn through engaging in the data collection within in a citizen science project. A comprehensive survey of 14,500 CoCoRaHS observers was recently conducted to uncover participant perceptions of numerous aspects of the CoCoRaHS program, including its goal of increasing climate literacy. The survey yielded a response rate of over 50%, and included measures of motivation, engagement and learning. In relationship to motivation and learning, the survey revealed that most (57.1%) observers would make precipitation observations regardless of being a CoCoRaHS volunteer, therefore their motivation is related to their inherent level of interest in weather. Others are motivated by their desire to learn more about weather and climate, they want to contribute to a scientific project, they think its fun, and/or it provides a sense of community. Because so many respondents already had knowledge and interest in weather and climate, identifying how and what people learn through participating was a challenge. However, the narrow project focus of collecting and reporting of local precipitation assisted in identifying aspects of learning. For instance, most (46.4%) observers said they increased their knowledge about the local variability in precipitation even though they had been collecting precipitation data for many years. Because the focus of the survey was to solicit participant opinions and not question their content knowledge, we were limited in our ability to unpack the issue of how people learn while engaging in the project. The next phase of this study will use a theoretical framework shaped from research in the learning sciences and based on social cognition and conceptual change to question a small subset of the volunteers about the data they collect. Citizen science projects such as CoCoRaHS provide a win-win situation for project scientists and participants. Project scientists gather necessary data for their studies, and motivated participants gain skills and knowledge related to the science content and science practices employed in the project. We discuss how these survey results can be applied to similar projects where learning is a key goal for their volunteers. We also discuss pathways for future research to identify aspects of scientific learning in the context of citizen science projects.

A sparse structure learning algorithm for Gaussian Bayesian Network identification from high-dimensional data.

PubMed

Huang, Shuai; Li, Jing; Ye, Jieping; Fleisher, Adam; Chen, Kewei; Wu, Teresa; Reiman, Eric

2013-06-01

Structure learning of Bayesian Networks (BNs) is an important topic in machine learning. Driven by modern applications in genetics and brain sciences, accurate and efficient learning of large-scale BN structures from high-dimensional data becomes a challenging problem. To tackle this challenge, we propose a Sparse Bayesian Network (SBN) structure learning algorithm that employs a novel formulation involving one L1-norm penalty term to impose sparsity and another penalty term to ensure that the learned BN is a Directed Acyclic Graph--a required property of BNs. Through both theoretical analysis and extensive experiments on 11 moderate and large benchmark networks with various sample sizes, we show that SBN leads to improved learning accuracy, scalability, and efficiency as compared with 10 existing popular BN learning algorithms. We apply SBN to a real-world application of brain connectivity modeling for Alzheimer's disease (AD) and reveal findings that could lead to advancements in AD research.

A Sparse Structure Learning Algorithm for Gaussian Bayesian Network Identification from High-Dimensional Data

PubMed Central

Huang, Shuai; Li, Jing; Ye, Jieping; Fleisher, Adam; Chen, Kewei; Wu, Teresa; Reiman, Eric

2014-01-01

Structure learning of Bayesian Networks (BNs) is an important topic in machine learning. Driven by modern applications in genetics and brain sciences, accurate and efficient learning of large-scale BN structures from high-dimensional data becomes a challenging problem. To tackle this challenge, we propose a Sparse Bayesian Network (SBN) structure learning algorithm that employs a novel formulation involving one L1-norm penalty term to impose sparsity and another penalty term to ensure that the learned BN is a Directed Acyclic Graph (DAG)—a required property of BNs. Through both theoretical analysis and extensive experiments on 11 moderate and large benchmark networks with various sample sizes, we show that SBN leads to improved learning accuracy, scalability, and efficiency as compared with 10 existing popular BN learning algorithms. We apply SBN to a real-world application of brain connectivity modeling for Alzheimer’s disease (AD) and reveal findings that could lead to advancements in AD research. PMID:22665720

The Navajo Learning Network and the NASA Life Sciences/AFOSR Infrastructure Development Project

NASA Technical Reports Server (NTRS)

1999-01-01

The NSF-funded Navajo Learning Network project, with help from NASA Life Sciences and AFOSR, enabled Dine College to take a giant leap forward technologically - in a way that could never had been possible had these projects been managed separately. The combination of these and other efforts created a network of over 500 computers located at ten sites across the Navajo reservation. Additionally, the college was able to install a modern telephone system which shares network data, and purchase a new higher education management system. The NASA Life Sciences funds further allowed the college library system to go online and become available to the entire campus community. NSF, NASA and AFOSR are committed to improving minority access to higher education opportunities and promoting faculty development and undergraduate research through infrastructure support and development. This project has begun to address critical inequalities in access to science, mathematics, engineering and technology for Navajo students and educators. As a result, Navajo K-12 education has been bolstered and Dine College will therefore better prepare students to transfer successfully to four-year institutions. Due to the integration of the NSF and NASA/AFOSR components of the project, a unified project report is appropriate.

Evolution, learning, and cognition

DOE Office of Scientific and Technical Information (OSTI.GOV)

Lee, Y.C.

1988-01-01

The book comprises more than fifteen articles in the areas of neural networks and connectionist systems, classifier systems, adaptive network systems, genetic algorithm, cellular automata, artificial immune systems, evolutionary genetics, cognitive science, optical computing, combinatorial optimization, and cybernetics.

Social networks as a tool for science communication and public engagement: focus on Twitter.

PubMed

López-Goñi, Ignacio; Sánchez-Angulo, Manuel

2018-02-01

Social networks have been used to teach and engage people about the importance of science. The integration of social networks in the daily routines of faculties and scientists is strongly recommended to increase their personal brand, improve their skills, enhance their visibility, share and communicate science to society, promote scientific culture, and even as a tool for teaching and learning. Here we review the use of Twitter in science and comment on our previous experience of using this social network as a platform for a Massive Online Open Course (MOOC) in Spain and Latin America. We propose to extend this strategy to a pan-European Microbiology MOOC in the near future. © FEMS 2017. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Process Challenges and Learning-Based Interactions in Stage 2 of Doctoral Education: Implications from Two Applied Social Science Fields

ERIC Educational Resources Information Center

Baker, Vicki L.; Pifer, Meghan J.; Flemion, Blair

2013-01-01

This article reports on an exploratory study that examined the transition to independence in Stage 2 of the doctoral student experience in two applied social science fields. We rely on an interdisciplinary framework that integrates developmental networks and sociocultural perspectives of learning to better understand the connection between the…

Students' Awareness of Science Teachers' Leadership, Attitudes toward Science, and Positive Thinking

ERIC Educational Resources Information Center

Lu, Ying-Yan; Chen, Hsiang-Ting; Hong, Zuway-R.; Yore, Larry D.

2016-01-01

There appears to be a complex network of cognitive and affective factors that influence students' decisions to study science and motivate their choices to engage in science-oriented careers. This study explored 330 Taiwanese senior high school students' awareness of their science teacher's learning leadership and how it relates to the students'…

Galileo Educational Network: Creating, Researching, and Supporting 21st Century Learning

ERIC Educational Resources Information Center

Friesen, Sharon

2009-01-01

School and classroom structures designed to meet the needs of the industrial past cannot "maintain the temperature required for sustaining life." Recent learning sciences research findings compel educators to invent new learning environments better suited to meet the demands of the 21st century. These new learning environments require…

Visualising the Invisible: A Network Approach to Reveal the Informal Social Side of Student Learning

ERIC Educational Resources Information Center

Hommes, J.; Rienties, B.; de Grave, W.; Bos, G.; Schuwirth, L.; Scherpbier, A.

2012-01-01

World-wide, universities in health sciences have transformed their curriculum to include collaborative learning and facilitate the students' learning process. Interaction has been acknowledged to be the synergistic element in this learning context. However, students spend the majority of their time outside their classroom and interaction does not…

Investigating Student Communities with Network Analysis of Interactions in a Physics Learning Center

NASA Astrophysics Data System (ADS)

Brewe, Eric; Kramer, Laird; O'Brien, George

2009-11-01

We describe our initial efforts at implementing social network analysis to visualize and quantify student interactions in Florida International University's Physics Learning Center. Developing a sense of community among students is one of the three pillars of an overall reform effort to increase participation in physics, and the sciences more broadly, at FIU. Our implementation of a research and learning community, embedded within a course reform effort, has led to increased recruitment and retention of physics majors. Finn and Rock [1997] link the academic and social integration of students to increased rates of retention. To identify these interactions, we have initiated an investigation that utilizes social network analysis to identify primary community participants. Community interactions are then characterized through the network's density and connectivity, shedding light on learning communities and participation. Preliminary results, further research questions, and future directions utilizing social network analysis are presented.

Snail Tales

ERIC Educational Resources Information Center

Phelps, Cynthia L.; Willcockson, Irmgard U.; Houtz, Lynne

2004-01-01

A team of teachers, scientists, and high school students at the University of Texas Health Science Center at Houston has developed activities to teach concepts in learning through an inquiry-based laboratory method. The Learning Education and Research Network (LEARN) activities were field tested at the Society for Neuroscience Conference, in the…

Discriminative Cooperative Networks for Detecting Phase Transitions

NASA Astrophysics Data System (ADS)

Liu, Ye-Hua; van Nieuwenburg, Evert P. L.

2018-04-01

The classification of states of matter and their corresponding phase transitions is a special kind of machine-learning task, where physical data allow for the analysis of new algorithms, which have not been considered in the general computer-science setting so far. Here we introduce an unsupervised machine-learning scheme for detecting phase transitions with a pair of discriminative cooperative networks (DCNs). In this scheme, a guesser network and a learner network cooperate to detect phase transitions from fully unlabeled data. The new scheme is efficient enough for dealing with phase diagrams in two-dimensional parameter spaces, where we can utilize an active contour model—the snake—from computer vision to host the two networks. The snake, with a DCN "brain," moves and learns actively in the parameter space, and locates phase boundaries automatically.

Scalable training of artificial neural networks with adaptive sparse connectivity inspired by network science.

PubMed

Mocanu, Decebal Constantin; Mocanu, Elena; Stone, Peter; Nguyen, Phuong H; Gibescu, Madeleine; Liotta, Antonio

2018-06-19

Through the success of deep learning in various domains, artificial neural networks are currently among the most used artificial intelligence methods. Taking inspiration from the network properties of biological neural networks (e.g. sparsity, scale-freeness), we argue that (contrary to general practice) artificial neural networks, too, should not have fully-connected layers. Here we propose sparse evolutionary training of artificial neural networks, an algorithm which evolves an initial sparse topology (Erdős-Rényi random graph) of two consecutive layers of neurons into a scale-free topology, during learning. Our method replaces artificial neural networks fully-connected layers with sparse ones before training, reducing quadratically the number of parameters, with no decrease in accuracy. We demonstrate our claims on restricted Boltzmann machines, multi-layer perceptrons, and convolutional neural networks for unsupervised and supervised learning on 15 datasets. Our approach has the potential to enable artificial neural networks to scale up beyond what is currently possible.

Dissertation Leadership Knowledge Transfer Using Sparsely Connected Networks with Bidirectional Edges: Case Study of Chester Hayden McCall Jr., His Dissertation Advisors, and His Students

ERIC Educational Resources Information Center

Mallette, Leo A.

2012-01-01

There are many modes of information flow in the sciences: books, journals, conferences, research and development, acquisition of companies, co-workers, students, and professors in schools of higher learning. In the sciences, dissertation students learn from their dissertation advisor (or chairperson or mentor) and the other dissertation committee…

The AGING Initiative experience: a call for sustained support for team science networks.

PubMed

Garg, Tullika; Anzuoni, Kathryn; Landyn, Valentina; Hajduk, Alexandra; Waring, Stephen; Hanson, Leah R; Whitson, Heather E

2018-05-18

Team science, defined as collaborative research efforts that leverage the expertise of diverse disciplines, is recognised as a critical means to address complex healthcare challenges, but the practical implementation of team science can be difficult. Our objective is to describe the barriers, solutions and lessons learned from our team science experience as applied to the complex and growing challenge of multiple chronic conditions (MCC). MCC is the presence of two or more chronic conditions that have a collective adverse effect on health status, function or quality of life, and that require complex healthcare management, decision-making or coordination. Due to the increasing impact on the United States society, MCC research has been identified as a high priority research area by multiple federal agencies. In response to this need, two national research entities, the Healthcare Systems Research Network (HCSRN) and the Claude D. Pepper Older Americans Independence Centers (OAIC), formed the Advancing Geriatrics Infrastructure and Network Growth (AGING) Initiative to build nationwide capacity for MCC team science. This article describes the structure, lessons learned and initial outcomes of the AGING Initiative. We call for funding mechanisms to sustain infrastructures that have demonstrated success in fostering team science and innovation in translating findings to policy change necessary to solve complex problems in healthcare.

Investigating student communities with network analysis of interactions in a physics learning center

NASA Astrophysics Data System (ADS)

Brewe, Eric; Kramer, Laird; Sawtelle, Vashti

2012-06-01

Developing a sense of community among students is one of the three pillars of an overall reform effort to increase participation in physics, and the sciences more broadly, at Florida International University. The emergence of a research and learning community, embedded within a course reform effort, has contributed to increased recruitment and retention of physics majors. We utilize social network analysis to quantify interactions in Florida International University’s Physics Learning Center (PLC) that support the development of academic and social integration. The tools of social network analysis allow us to visualize and quantify student interactions and characterize the roles of students within a social network. After providing a brief introduction to social network analysis, we use sequential multiple regression modeling to evaluate factors that contribute to participation in the learning community. Results of the sequential multiple regression indicate that the PLC learning community is an equitable environment as we find that gender and ethnicity are not significant predictors of participation in the PLC. We find that providing students space for collaboration provides a vital element in the formation of a supportive learning community.

The application of network teaching in applied optics teaching

NASA Astrophysics Data System (ADS)

Zhao, Huifu; Piao, Mingxu; Li, Lin; Liu, Dongmei

2017-08-01

Network technology has become a creative tool of changing human productivity, the rapid development of it has brought profound changes to our learning, working and life. Network technology has many advantages such as rich contents, various forms, convenient retrieval, timely communication and efficient combination of resources. Network information resources have become the new education resources, get more and more application in the education, has now become the teaching and learning tools. Network teaching enriches the teaching contents, changes teaching process from the traditional knowledge explanation into the new teaching process by establishing situation, independence and cooperation in the network technology platform. The teacher's role has shifted from teaching in classroom to how to guide students to learn better. Network environment only provides a good platform for the teaching, we can get a better teaching effect only by constantly improve the teaching content. Changchun university of science and technology introduced a BB teaching platform, on the platform, the whole optical classroom teaching and the classroom teaching can be improved. Teachers make assignments online, students learn independently offline or the group learned cooperatively, this expands the time and space of teaching. Teachers use hypertext form related knowledge of applied optics, rich cases and learning resources, set up the network interactive platform, homework submission system, message board, etc. The teaching platform simulated the learning interest of students and strengthens the interaction in the teaching.

We Engage, Therefore They Trust? A Study of Social Media Engagement and Public Trust in Science

NASA Astrophysics Data System (ADS)

Hwong, Y. L.; Oliver, C.; Van Kranendonk, M. J.

2017-12-01

Our society relies heavily on the trust that the public places in science to work. Given science's importance, the growing distrust in science is a cause for concern. Thanks to their participatory nature, social media have been touted as the promising tool for public engagement to restore public trust in science. These digital platforms have transformed the landscape of science communication yet little is known about their impact on public trust in science. This study probed several aspects of public trust in science as expressed on Twitter, focusing on two related science issues: space science and climate change. Our datasets comprised of 10,000 randomly sampled tweets over a month's period in 2016. We used human annotation and machine learning as our approach. Results indicated that the perceived contentiousness of a science issue has a significant impact on public trust. The level of distrust is higher in the climate change tweets than in the space science tweets, despite climate scientists being almost four times as active as space scientists in engaging with sceptics. However, people who engaged with scientists in the climate change network displayed a higher level of trust in science compared with those who did not. This effect was not observed in the space science network - in this network, there is no significant difference in trust levels between people who engaged with scientists and those who did not. Additionally, our machine learning study revealed that trust in science (as conveyed by tweets) can be predicted. The supervised learning algorithm that we developed was able to predict the trust labels of tweets in our sample with an accuracy of 84%. A further feature analysis indicated that similarity, presence of URL and authenticity are the properties of trust-inspiring tweets. Based on these findings, we argue that social media science communication is not as straightforward as `we engage, therefore they trust'. Public attitude towards science is often issue-dependent, and the way scientists communicate on social media has a significant impact on public perception.

What A Long Strange Trip It's Been: Lessons Learned From NASA EOS, LTER, NEON, CZO And On To The Future With Sustainable Research Networks

NASA Astrophysics Data System (ADS)

Williams, M. W.

2014-12-01

The traditional, small-scale, incremental approach to environmental science is changing as researchers embrace a more integrated and multi-disciplinary approach to understanding how our natural systems work today and how they may respond in the future to forcings such as climate change. In situ networks are evolving in response to these challenges so as to provide the appropriate measurements to develop high-resolution spatial and temporal data sets across a wide range of platforms from microbial measurements to remote sensing. These large programs provide a unique set of challenges when compared to more traditional programs. Here I provide insights learned from my participation in a number of large programs, including NASA EOS, LTER, CZO, NEON, and WSC and how those experiences in environmental science can help us move forward towards more applied applications of environmental science, including sustainability initiatives. I'll chat about the importance of managerial and management skills, which most of us scientists prefer to avoid. I'll also chat about making decisions about what long-term measurements to make and when to stop. Data management is still the weakest part of environmental networks; what needs to be done. We have learned that these networks provide an important knowledge base that can lead to informed decisions leading to environmental, energy, social and cultural sustainability.

Tensor Basis Neural Network v. 1.0 (beta)

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ling, Julia; Templeton, Jeremy

This software package can be used to build, train, and test a neural network machine learning model. The neural network architecture is specifically designed to embed tensor invariance properties by enforcing that the model predictions sit on an invariant tensor basis. This neural network architecture can be used in developing constitutive models for applications such as turbulence modeling, materials science, and electromagnetism.

The Future of Electronic Educational Networks: Some Ethical Issues.

ERIC Educational Resources Information Center

Johnson, Dell

Institutions of higher education in the United States are making use of educational communication networks, such as the National Science Foundation's INTERNET system, to enhance research and learning. Such information networks are used to exchange information electronically, and exist not only in the United States, but also in other countries.…

Idm@ti Network: An Innovative Proposal for Improving Teaching and Learning in Spanish Universities

ERIC Educational Resources Information Center

Salan, Nuria; Cabedo, Luis; Segarra, Mercedes; Guraya, Teresa; Lopez, Pascal; Sales, David; Gamez, Jose

2017-01-01

IdM@ti network members concurred in the diagnosis of the difficulties and opportunities arising from Bologna process implementation and teaching methodologies improvement in Materials Science and Engineering (MSE) teaching. This network has been created with the aim of improving efficiency of underway and future collaborations.The main objectives…

"It Takes a Network": Building National Capacity for Climate Change Interpretation

NASA Astrophysics Data System (ADS)

Spitzer, W.

2014-12-01

Since 2007, the New England Aquarium has led a national effort to increase the capacity of informal science venues to effectively communicate about climate change. We are now leading the NSF-funded National Network for Ocean and Climate Change Interpretation (NNOCCI), partnering with the Association of Zoos and Aquariums, FrameWorks Institute, Woods Hole Oceanographic Institution, Monterey Bay Aquarium, and National Aquarium, with evaluation conducted by the New Knowledge Organization, Pennsylvania State University, and Ohio State University. More than 1,500 informal science venues (science centers, museums, aquariums, zoos, nature centers, national parks) are visited annually by 61% of the U.S. population. These visitors expect reliable information about environmental issues and solutions. NNOCCI enables teams of informal science interpreters across the country to serve as "communication strategists" - beyond merely conveying information they can influence public perceptions, given their high level of commitment, knowledge, public trust, social networks, and visitor contact. Beyond providing in-depth training, we have found that our "alumni network" is assuming an increasingly important role in achieving our goals: 1. Ongoing learning - Training must be ongoing given continuous advances in climate and social science research. 2. Implementation support - Social support is critical as interpreters move from learning to practice, given complex and potentially contentious subject matter. 3. Leadership development - We rely on a national cadre of interpretive leaders to conduct workshops, facilitate study circle trainings, and support alumni. 4. Coalition building - A peer network helps to build and maintain connections with colleagues, and supports further dissemination through the informal science community. We are experimenting with a variety of online and face to face strategies to support the growing alumni network. Our goals are to achieve a systemic national impact, embed our work within multiple ongoing regional and national climate change education networks, and leave an enduring legacy.

Social learning strategies modify the effect of network structure on group performance.

PubMed

Barkoczi, Daniel; Galesic, Mirta

2016-10-07

The structure of communication networks is an important determinant of the capacity of teams, organizations and societies to solve policy, business and science problems. Yet, previous studies reached contradictory results about the relationship between network structure and performance, finding support for the superiority of both well-connected efficient and poorly connected inefficient network structures. Here we argue that understanding how communication networks affect group performance requires taking into consideration the social learning strategies of individual team members. We show that efficient networks outperform inefficient networks when individuals rely on conformity by copying the most frequent solution among their contacts. However, inefficient networks are superior when individuals follow the best member by copying the group member with the highest payoff. In addition, groups relying on conformity based on a small sample of others excel at complex tasks, while groups following the best member achieve greatest performance for simple tasks. Our findings reconcile contradictory results in the literature and have broad implications for the study of social learning across disciplines.

Social learning strategies modify the effect of network structure on group performance

NASA Astrophysics Data System (ADS)

Barkoczi, Daniel; Galesic, Mirta

2016-10-01

The structure of communication networks is an important determinant of the capacity of teams, organizations and societies to solve policy, business and science problems. Yet, previous studies reached contradictory results about the relationship between network structure and performance, finding support for the superiority of both well-connected efficient and poorly connected inefficient network structures. Here we argue that understanding how communication networks affect group performance requires taking into consideration the social learning strategies of individual team members. We show that efficient networks outperform inefficient networks when individuals rely on conformity by copying the most frequent solution among their contacts. However, inefficient networks are superior when individuals follow the best member by copying the group member with the highest payoff. In addition, groups relying on conformity based on a small sample of others excel at complex tasks, while groups following the best member achieve greatest performance for simple tasks. Our findings reconcile contradictory results in the literature and have broad implications for the study of social learning across disciplines.

Review of the Contribution of the Scottish Science Centres Network to Formal and Informal Science Education: Report of Follow-Through Visits by HM Inspectorate of Education--June 2009

ERIC Educational Resources Information Center

Her Majesty's Inspectorate of Education, 2009

2009-01-01

In 2006, the Scottish Executive's Enterprise, Transport and Lifelong Learning Department (SEETLLD) asked HM Inspectorate of Education (HMIE) to carry out a review of the four Scottish science centres--Glasgow Science Centre (GSC), Our Dynamic Earth (ODE) in Edinburgh, Satrosphere Science Centre in Aberdeen, and Sensation Science Centre in Dundee.…

Family Science and Community-Based Learning: Using Speed Networking

ERIC Educational Resources Information Center

Payne, Pamela B.; Hubler, Daniel S.

2017-01-01

Students in Family Science often feel that they have an uphill battle to finding career opportunities that maximize their experiences from degree programs. The hallmark of successful programs in Family Science needs to be the development and maintenance of high-quality field experiences for students that align with national standards and…

Science and Math in the Library Media Center Using GLOBE.

ERIC Educational Resources Information Center

Aquino, Teresa L.; Levine, Elissa R.

2003-01-01

Describes the Global Learning and Observations to Benefit the Environment (GLOBE) program which helps school library media specialists and science and math teachers bring earth science, math, information literacy, information technology, and student inquiry into the classroom. Discusses use of the Internet to create a global network to study the…

WATERS - Integrating Science and Education Through the Development of an Education & Outreach Program that Engages Scientists, Students and Citizens

NASA Astrophysics Data System (ADS)

Eschenbach, E. A.; Conklin, M. H.

2007-12-01

The need to train students in hydrologic science and environmental engineering is well established. Likewise, the public requires a raised awareness of the seriousness of water quality and availability problems. The WATERS Network (WATer and Environmental Research Systems Network ) has the potential to significantly change the way students, researchers, citizens, policy makers and industry members learn about environmental problems and solutions regarding water quality, quantity and distribution. This potential can be met if the efforts of water scientists, computer scientists, and educators are integrated appropriately. Successful pilot projects have found that cyberinfrastructure for education and outreach needs to be developed in parallel with research related cyberinfrastructure. We propose further integration of research, education and outreach activities. Through the use of technology that connects students, faculty, researchers, policy makers and others, WATERS Network can provide learning opportunities and teaching efficiencies that can revolutionize environmental science and engineering education. However, there are a plethora of existing environmental science and engineering educational programs. In this environment, WATERS can make a greater impact through careful selection of activities that build upon its unique strengths, that have high potential for engaging the members, and that meet identified needs: (i) modernizing curricula and pedagogy (ii) integrating science and education, (iii) sustainable professional development, and (iv) training the next generation of interdisciplinary water and social scientists and environmental engineers. National and observatory-based education facilities would establish the physical infrastructure necessary to coordinate education and outreach activities. Each observatory would partner with local educators and citizens to develop activities congruent with the scientific mission of the observatory. An unprecedented opportunity exists for educational research of both formal and informal environmental science and engineering education in order to understand how the Network can be efficiently used to create effective technology-based learning environments for all participants.

An Evaluation of the Network Efficiency Required in Order to Support Multicast and Synchronous Distributed Learning Network Traffic

DTIC Science & Technology

2003-09-01

This restriction limits the deployment to small and medium sized enterprises. The Internet cannot universally use DVMRP for this reason. In addition...20503. 1. AGENCY USE ONLY (Leave blank) 2. REPORT DATE September 2003 3. REPORT TYPE AND DATES COVERED Master’s Thesis 4. TITLE... University , 1996 Submitted in partial fulfillment of the requirements for the degree of MASTER OF SCIENCE IN COMPUTER SCIENCE from

A Network Neuroscience of Human Learning: Potential To Inform Quantitative Theories of Brain and Behavior

PubMed Central

Bassett, Danielle S.; Mattar, Marcelo G.

2017-01-01

Humans adapt their behavior to their external environment in a process often facilitated by learning. Efforts to describe learning empirically can be complemented by quantitative theories that map changes in neurophysiology to changes in behavior. In this review we highlight recent advances in network science that offer a sets of tools and a general perspective that may be particularly useful in understanding types of learning that are supported by distributed neural circuits. We describe recent applications of these tools to neuroimaging data that provide unique insights into adaptive neural processes, the attainment of knowledge, and the acquisition of new skills, forming a network neuroscience of human learning. While promising, the tools have yet to be linked to the well-formulated models of behavior that are commonly utilized in cognitive psychology. We argue that continued progress will require the explicit marriage of network approaches to neuroimaging data and quantitative models of behavior. PMID:28259554

A Network Neuroscience of Human Learning: Potential to Inform Quantitative Theories of Brain and Behavior.

PubMed

Bassett, Danielle S; Mattar, Marcelo G

2017-04-01

Humans adapt their behavior to their external environment in a process often facilitated by learning. Efforts to describe learning empirically can be complemented by quantitative theories that map changes in neurophysiology to changes in behavior. In this review we highlight recent advances in network science that offer a sets of tools and a general perspective that may be particularly useful in understanding types of learning that are supported by distributed neural circuits. We describe recent applications of these tools to neuroimaging data that provide unique insights into adaptive neural processes, the attainment of knowledge, and the acquisition of new skills, forming a network neuroscience of human learning. While promising, the tools have yet to be linked to the well-formulated models of behavior that are commonly utilized in cognitive psychology. We argue that continued progress will require the explicit marriage of network approaches to neuroimaging data and quantitative models of behavior. Copyright © 2017 Elsevier Ltd. All rights reserved.

Building Trust-Based Sustainable Networks

DTIC Science & Technology

2013-06-05

entities to build sustainable networks with limited resources or misbehaving entities by learning from the lessons in the social sciences. We discuss...their individuality); and ■ Misbehaving nodes in terms of environmental, economic, and social perspectives. The sustainable network concerns...equitable access to particular services which are otherwise abused by misbehaving or malicious users. Such approaches provide a fair and

Science Education and Technology: Opportunities to Enhance Student Learning.

ERIC Educational Resources Information Center

Woolsey, Kristina; Bellamy, Rachel

1997-01-01

Describes how technological capabilities such as calculation, imaging, networking, and portability support a range of pedagogical approaches, such as inquiry-based science and dynamic modeling. Includes as examples software products created at Apple Computer and others available in the marketplace. (KDFB)

The ADL Registry and CORDRA. Volume 1: General Overview

DTIC Science & Technology

2008-08-01

and problems encountered by others in related fields, such as library science , computer and network systems design, and publishing. As ADL...in and exist in isolated islands, limiting their visibility, access, and reuse. 4 Compared to publishing and library science , the learning

Parallel Distributed Processing Theory in the Age of Deep Networks.

PubMed

Bowers, Jeffrey S

2017-12-01

Parallel distributed processing (PDP) models in psychology are the precursors of deep networks used in computer science. However, only PDP models are associated with two core psychological claims, namely that all knowledge is coded in a distributed format and cognition is mediated by non-symbolic computations. These claims have long been debated in cognitive science, and recent work with deep networks speaks to this debate. Specifically, single-unit recordings show that deep networks learn units that respond selectively to meaningful categories, and researchers are finding that deep networks need to be supplemented with symbolic systems to perform some tasks. Given the close links between PDP and deep networks, it is surprising that research with deep networks is challenging PDP theory. Copyright © 2017. Published by Elsevier Ltd.

Geometrical structure of Neural Networks: Geodesics, Jeffrey's Prior and Hyper-ribbons

NASA Astrophysics Data System (ADS)

Hayden, Lorien; Alemi, Alex; Sethna, James

2014-03-01

Neural networks are learning algorithms which are employed in a host of Machine Learning problems including speech recognition, object classification and data mining. In practice, neural networks learn a low dimensional representation of high dimensional data and define a model manifold which is an embedding of this low dimensional structure in the higher dimensional space. In this work, we explore the geometrical structure of a neural network model manifold. A Stacked Denoising Autoencoder and a Deep Belief Network are trained on handwritten digits from the MNIST database. Construction of geodesics along the surface and of slices taken from the high dimensional manifolds reveal a hierarchy of widths corresponding to a hyper-ribbon structure. This property indicates that neural networks fall into the class of sloppy models, in which certain parameter combinations dominate the behavior. Employing this information could prove valuable in designing both neural network architectures and training algorithms. This material is based upon work supported by the National Science Foundation Graduate Research Fellowship under Grant No . DGE-1144153.

The Challenges and Opportunities for International Cooperative Radio Science; Experience with Mars Express and Venus Express Missions

NASA Technical Reports Server (NTRS)

Holmes, Dwight P.; Thompson, Tommy; Simpson, Richard; Tyler, G. Leonard; Dehant, Veronique; Rosenblatt, Pascal; Hausler, Bernd; Patzold, Martin; Goltz, Gene; Kahan, Daniel;

Future Scenarios for Mobile Science Learning

NASA Astrophysics Data System (ADS)

Burden, Kevin; Kearney, Matthew

2016-04-01

This paper adopts scenario planning as a methodological approach and tool to help science educators reconceptualise their use of mobile technologies across various different futures. These `futures' are set out neither as predictions nor prognoses but rather as stimuli to encourage greater discussion and reflection around the use of mobile technologies in science education. Informed by the literature and our empirical data, we consider four alternative futures for science education in a mobile world, with a particular focus on networked collaboration and student agency. We conclude that `seamless learning', whereby students are empowered to use their mobile technologies to negotiate across physical and virtual boundaries (e.g. between school and out-of-school activities), may be the most significant factor in encouraging educators to rethink their existing pedagogical patterns, thereby realizing some of the promises of contextualised participatory science learning.

Learning in Stochastic Bit Stream Neural Networks.

PubMed

van Daalen, Max; Shawe-Taylor, John; Zhao, Jieyu

1996-08-01

This paper presents learning techniques for a novel feedforward stochastic neural network. The model uses stochastic weights and the "bit stream" data representation. It has a clean analysable functionality and is very attractive with its great potential to be implemented in hardware using standard digital VLSI technology. The design allows simulation at three different levels and learning techniques are described for each level. The lowest level corresponds to on-chip learning. Simulation results on three benchmark MONK's problems and handwritten digit recognition with a clean set of 500 16 x 16 pixel digits demonstrate that the new model is powerful enough for the real world applications. Copyright 1996 Elsevier Science Ltd

Philomaths, Herschel, and the myth of the self-taught man

PubMed Central

Winterburn, Emily

2014-01-01

The role of technicians and background characters in the historical practice of science is slowly gaining recognition. This paper looks at the collective effort involved in learning science, using as my case study the eighteenth-century musician turned astronomer, William Herschel. Lacking a university education, Herschel, like many contemporaries, presented himself as self-taught, thereby hiding his engagement with a rich network of didactic resources. Placing Herschel's story within the history of pedagogy, I argue that this network, previously discussed only in the context of popular or marketplace science, was an important resource for science education at its highest level. PMID:25254276

Analysis of the “naming game” with learning errors in communications

NASA Astrophysics Data System (ADS)

Lou, Yang; Chen, Guanrong

2015-07-01

Naming game simulates the process of naming an objective by a population of agents organized in a certain communication network. By pair-wise iterative interactions, the population reaches consensus asymptotically. We study naming game with communication errors during pair-wise conversations, with error rates in a uniform probability distribution. First, a model of naming game with learning errors in communications (NGLE) is proposed. Then, a strategy for agents to prevent learning errors is suggested. To that end, three typical topologies of communication networks, namely random-graph, small-world and scale-free networks, are employed to investigate the effects of various learning errors. Simulation results on these models show that 1) learning errors slightly affect the convergence speed but distinctively increase the requirement for memory of each agent during lexicon propagation; 2) the maximum number of different words held by the population increases linearly as the error rate increases; 3) without applying any strategy to eliminate learning errors, there is a threshold of the learning errors which impairs the convergence. The new findings may help to better understand the role of learning errors in naming game as well as in human language development from a network science perspective.

Analysis of the "naming game" with learning errors in communications.

PubMed

Lou, Yang; Chen, Guanrong

2015-07-16

Naming game simulates the process of naming an objective by a population of agents organized in a certain communication network. By pair-wise iterative interactions, the population reaches consensus asymptotically. We study naming game with communication errors during pair-wise conversations, with error rates in a uniform probability distribution. First, a model of naming game with learning errors in communications (NGLE) is proposed. Then, a strategy for agents to prevent learning errors is suggested. To that end, three typical topologies of communication networks, namely random-graph, small-world and scale-free networks, are employed to investigate the effects of various learning errors. Simulation results on these models show that 1) learning errors slightly affect the convergence speed but distinctively increase the requirement for memory of each agent during lexicon propagation; 2) the maximum number of different words held by the population increases linearly as the error rate increases; 3) without applying any strategy to eliminate learning errors, there is a threshold of the learning errors which impairs the convergence. The new findings may help to better understand the role of learning errors in naming game as well as in human language development from a network science perspective.

Learning Orthographic Structure With Sequential Generative Neural Networks.

PubMed

Testolin, Alberto; Stoianov, Ivilin; Sperduti, Alessandro; Zorzi, Marco

2016-04-01

Learning the structure of event sequences is a ubiquitous problem in cognition and particularly in language. One possible solution is to learn a probabilistic generative model of sequences that allows making predictions about upcoming events. Though appealing from a neurobiological standpoint, this approach is typically not pursued in connectionist modeling. Here, we investigated a sequential version of the restricted Boltzmann machine (RBM), a stochastic recurrent neural network that extracts high-order structure from sensory data through unsupervised generative learning and can encode contextual information in the form of internal, distributed representations. We assessed whether this type of network can extract the orthographic structure of English monosyllables by learning a generative model of the letter sequences forming a word training corpus. We show that the network learned an accurate probabilistic model of English graphotactics, which can be used to make predictions about the letter following a given context as well as to autonomously generate high-quality pseudowords. The model was compared to an extended version of simple recurrent networks, augmented with a stochastic process that allows autonomous generation of sequences, and to non-connectionist probabilistic models (n-grams and hidden Markov models). We conclude that sequential RBMs and stochastic simple recurrent networks are promising candidates for modeling cognition in the temporal domain. Copyright © 2015 Cognitive Science Society, Inc.

Teaching an Interdisciplinary Graduate-Level Methods Course in an Openly-Networked Connected Learning Environment: A Glass Half-Full

ERIC Educational Resources Information Center

Secret, Mary; Bryant, Nita L.; Cummings, Cory R.

2017-01-01

Our paper describes the design and delivery of an online interdisciplinary social science research methods course (ISRM) for graduate students in sociology, education, social work, and public administration. Collaborative activities and learning took place in two types of computer-mediated learning environments: a closed Blackboard course…

Teachers in an Interdisciplinary Learning Community: Engaging, Integrating, and Strengthening K-12 Education

ERIC Educational Resources Information Center

Hardré, Patricia L.; Ling, Chen; Shehab, Randa L.; Nanny, Mark A.; Nollert, Matthias U.; Refai, Hazem; Ramseyer, Christopher; Herron, Jason; Wollega, Ebisa D.

2013-01-01

This study examines the inputs (processes and strategies) and outputs (perceptions, skill development, classroom transfer, disciplinary integration, social networking, and community development) of a yearlong, interdisciplinary teacher learning and development experience. Eleven secondary math and science teachers partnered with an…

Assessing the Linguistic Productivity of Unsupervised Deep Neural Networks

DOE Office of Scientific and Technical Information (OSTI.GOV)

Phillips, Lawrence A.; Hodas, Nathan O.

Increasingly, cognitive scientists have demonstrated interest in applying tools from deep learning. One use for deep learning is in language acquisition where it is useful to know if a linguistic phenomenon can be learned through domain-general means. To assess whether unsupervised deep learning is appropriate, we first pose a smaller question: Can unsupervised neural networks apply linguistic rules productively, using them in novel situations. We draw from the literature on determiner/noun productivity by training an unsupervised, autoencoder network measuring its ability to combine nouns with determiners. Our simple autoencoder creates combinations it has not previously encountered, displaying a degree ofmore » overlap similar to actual children. While this preliminary work does not provide conclusive evidence for productivity, it warrants further investigation with more complex models. Further, this work helps lay the foundations for future collaboration between the deep learning and cognitive science communities.« less

Looking at Earth from Space: Teacher's Guide with Activities for Earth and Space Science.

ERIC Educational Resources Information Center

National Aeronautics and Space Administration, Washington, DC.

The Maryland Pilot Earth Science and Technology Education Network (MAPS-NET) project was sponsored by the National Aeronautics and Space Administration (NASA) to enrich teacher preparation and classroom learning in the area of Earth system science. This publication includes a teacher's guide that replicates material taught during a graduate-level…

Efficient Algorithms for Bayesian Network Parameter Learning from Incomplete Data

DTIC Science & Technology

2015-07-01

Efficient Algorithms for Bayesian Network Parameter Learning from Incomplete Data Guy Van den Broeck∗ and Karthika Mohan∗ and Arthur Choi and Adnan ...notwithstanding any other provision of law , no person shall be subject to a penalty for failing to comply with a collection of information if it does...Wasserman, L. (2011). All of Statistics. Springer Science & Business Media. Yaramakala, S., & Margaritis, D. (2005). Speculative markov blanket discovery for optimal feature selection. In Proceedings of ICDM.

Deep learning for computational chemistry.

PubMed

Goh, Garrett B; Hodas, Nathan O; Vishnu, Abhinav

2017-06-15

The rise and fall of artificial neural networks is well documented in the scientific literature of both computer science and computational chemistry. Yet almost two decades later, we are now seeing a resurgence of interest in deep learning, a machine learning algorithm based on multilayer neural networks. Within the last few years, we have seen the transformative impact of deep learning in many domains, particularly in speech recognition and computer vision, to the extent that the majority of expert practitioners in those field are now regularly eschewing prior established models in favor of deep learning models. In this review, we provide an introductory overview into the theory of deep neural networks and their unique properties that distinguish them from traditional machine learning algorithms used in cheminformatics. By providing an overview of the variety of emerging applications of deep neural networks, we highlight its ubiquity and broad applicability to a wide range of challenges in the field, including quantitative structure activity relationship, virtual screening, protein structure prediction, quantum chemistry, materials design, and property prediction. In reviewing the performance of deep neural networks, we observed a consistent outperformance against non-neural networks state-of-the-art models across disparate research topics, and deep neural network-based models often exceeded the "glass ceiling" expectations of their respective tasks. Coupled with the maturity of GPU-accelerated computing for training deep neural networks and the exponential growth of chemical data on which to train these networks on, we anticipate that deep learning algorithms will be a valuable tool for computational chemistry. © 2017 Wiley Periodicals, Inc. © 2017 Wiley Periodicals, Inc.

Neurale Netwerken en Radarsystemen (Neural Networks and Radar Systems)

DTIC Science & Technology

1989-08-01

general issues in cognitive science", Parallel distributed processing, Vol 1: Foundations, Rumelhart et al. 1986 pp 110-146 THO rapport Pagina 151 36 D.E...34Neural networks (part 2)",Expert Focus, IEEE Expert, Spring 1988. 61 J.A. Anderson, " Cognitive and Psychological Computations with Neural Models", IEEE...Pagina 154 69 David H. Ackley, Geoffrey E. Hinton and Terrence J. Sejnowski, "A Learning Algorithm for Boltzmann machines", cognitive science 9, 147-169

Defence Adademies and Colleges 2009 International Conference. Network Centric Learning: Towards Authentic ePractices, 25 - 27 March 2009

DTIC Science & Technology

2009-03-27

to learning and collaborative working • Developing more immersive learning where learning is promoted through experiencing the style of thinking of... Student Talk in Promoting Quality Learning in Science Classroom”, MS. Morrison, P., Barlow, M., Bethel, G. and Clothier, S. (2005), “Proficient Soldier...on student perceptions of learning effectiveness. 1 Computer self-efficacy: “The learner’s perception of their ability to carry out a series of

An Argument for Learning. Science Teachers and Students Build Literacy through Text-Based Investigations

ERIC Educational Resources Information Center

Greenleaf, Cynthia; Brown, Willard R.

2017-01-01

This article describes how participants in the California Teacher Inquiry Network learn the art of making their invisible thinking processes visible, helping them see more clearly that they have internal resources to help students master similar kinds of thinking processes.

CosmoQuest Collaborative: Galvanizing a Dynamic Professional Learning Network

NASA Astrophysics Data System (ADS)

Cobb, Whitney; Bracey, Georgia; Buxner, Sanlyn; Gay, Pamela L.; Noel-Storr, Jacob; CosmoQuest Team

2016-10-01

The CosmoQuest Collaboration offers in-depth experiences to diverse audiences around the nation and the world through pioneering citizen science in a virtual research facility. An endeavor between universities, research institutes, and NASA centers, CosmoQuest brings together scientists, educators, researchers, programmers—and citizens of all ages—to explore and make sense of our solar system and beyond. Leveraging human networks to expand NASA science, scaffolded by an educational framework that inspires lifelong learners, CosmoQuest engages citizens in analyzing and interpreting real NASA data, inspiring questions and defining problems.The QuestionLinda Darling-Hammond calls for professional development to be: "focused on the learning and teaching of specific curriculum content [i.e. NGSS disciplinary core ideas]; organized around real problems of practice [i.e. NGSS science and engineering practices] … [and] connected to teachers' collaborative work in professional learning community...." (2012) In light of that, what is the unique role CosmoQuest's virtual research facility can offer NASA STEM education?A Few AnswersThe CosmoQuest Collaboration actively engages scientists in education, and educators (and learners) in science. CosmoQuest uses social channels to empower and expand NASA's learning community through a variety of media, including science and education-focused hangouts, virtual star parties, and social media. In addition to creating its own supportive, standards-aligned materials, CosmoQuest offers a hub for excellent resources and materials throughout NASA and the larger astronomy community.In support of CosmoQuest citizen science opportunities, CQ initiatives (Learning Space, S-ROSES, IDEASS, Educator Zone) will be leveraged and shared through the CQPLN. CosmoQuest can be present and alive in the awareness its growing learning community.Finally, to make the CosmoQuest PLN truly relevant, it aims to encourage partnerships between scientists and educators, and offer "just-in-time" opportunities to support constituents exploring emerging NASA STEM education, from diverse educators to the curious learner of any age.

STAR Library Education Network: a hands-on learning program for libraries and their communities

NASA Astrophysics Data System (ADS)

Dusenbery, P.

2010-12-01

Science and technology are widely recognized as major drivers of innovation and industry (e.g. Rising above the Gathering Storm, 2006). While the focus for education reform is on school improvement, there is considerable research that supports the role that out-of-school experiences can play in student achievement and public understanding of STEM disciplines. Libraries provide an untapped resource for engaging underserved youth and their families in fostering an appreciation and deeper understanding of science and technology topics. Designed spaces, like libraries, allow lifelong, life-wide, and life-deep learning to take place though the research basis for learning in libraries is not as developed as other informal settings like science centers. The Space Science Institute’s National Center for Interactive Learning (NCIL) in partnership with the American Library Association (ALA), the Lunar and Planetary Institute (LPI), and the National Girls Collaborative Project (NGCP) have received funding from NSF to develop a national education project called the STAR Library Education Network: a hands-on learning program for libraries and their communities (or STAR-Net for short). STAR stands for Science-Technology, Activities and Resources. The overarching goal of the project is to reach underserved youth and their families with informal STEM learning experiences. This project will deepen our knowledge of informal/lifelong learning that takes place in libraries and establish a learning model that can be compared to the more established free-choice learning model for science centers and museums. The project includes the development of two STEM hands-on exhibits on topics that are of interest to library staff and their patrons: Discover Earth and Discover Tech. In addition, the project will produce resources and inquiry-based activities that libraries can use to enrich the exhibit experience. Additional resources will be provided through partnerships with relevant professional science and technology organizations (e.g. American Geophysical Union; National Academy of Engineering) that will provide speakers for host library events and webinars. Online and in-person workshops will be conducted for library staff with a focus on increasing content knowledge and improving facilitation expertise. This presentation will report on strategic planning activities for STAR-Net, a Community of Practice model, and the evaluation/research components of this national education program.

Evolving Best Practice in Learning About Air Quality and Climate Change Science in ACCENT

NASA Astrophysics Data System (ADS)

Schuepbach, E.

2008-12-01

Learning about air quality and climate change science has developed into a transdisciplinary impact generator, moulded by academic-stakeholder partnerships, where complementary skills and competences lead to a culture of dialogue, mutual learning and decision-making. These sweeping changes are mirrored in the evolving best practice within the European Network of Excellence on Atmospheric Composition Change (ACCENT). The Training and Education Programme in ACCENT pursues an integrated approach and innovative avenues to sharing knowledge and communicating air quality and climate change science to various end-user groups, including teachers, policy makers, stakeholders, and the general public. Early career scientists are involved in the process, and are trained to acquire new knowledge in a variety of learning communities and environments. Here, examples of both the open system of teaching within ACCENT training workshops for early career scientists, and the engagement of non-academic audiences in the joint learning process are presented.

Management Challenges in an Information Communication Technology (ICT) Network in Rural Schools

ERIC Educational Resources Information Center

Mihai, Maryke; Nieuwenhuis, Jan

2015-01-01

This study concerns the management of an interactive whiteboard (IWB) network started in April 2008 in Mpumalanga, with a leading school partnered with several disadvantaged schools, transmitting lessons in Mathematics and Science. Many educational institutions try to provide learners with better learning opportunities by equipping schools with…

Simulating Issue Networks in Small Classes using the World Wide Web.

ERIC Educational Resources Information Center

Josefson, Jim; Casey, Kelly

2000-01-01

Provides background information on simulations and active learning. Discusses the use of simulations in political science courses. Describes a simulation exercise where students performed specific institutional role playing, simulating the workings of a single congressional issue network, based on the reauthorization of the Endangered Species Act.…

Building National Capacity for Climate Change Interpretation: The Role of Leaders, Partnerships, and Networks

NASA Astrophysics Data System (ADS)

Spitzer, W.

2015-12-01

Since 2007, the New England Aquarium has led a national effort to increase the capacity of informal science venues to effectively communicate about climate change. We are now leading the NSF-funded National Network for Ocean and Climate Change Interpretation (NNOCCI), partnering with the Association of Zoos and Aquariums, FrameWorks Institute, Woods Hole Oceanographic Institution, Monterey Bay Aquarium, and National Aquarium, with evaluation conducted by the New Knowledge Organization, Pennsylvania State University, and Ohio State University. NNOCCI enables teams of informal science interpreters across the country to serve as "communication strategists" - beyond merely conveying information they can influence public perceptions, given their high level of commitment, knowledge, public trust, social networks, and visitor contact. We provide in-depth training as well as an alumni network for ongoing learning, implementation support, leadership development, and coalition building. Our goals are to achieve a systemic national impact, embed our work within multiple ongoing regional and national climate change education networks, and leave an enduring legacy. Our project represents a cross-disciplinary partnership among climate scientists, social and cognitive scientists, and informal education practitioners. We have built a growing national network of more than 250 alumni, including approximately 15-20 peer leaders who co-lead both in-depth training programs and introductory workshops. We have found that this alumni network has been assuming increasing importance in providing for ongoing learning, support for implementation, leadership development, and coalition building. As we look toward the future, we are exploring potential partnerships with other existing networks, both to sustain our impact and to expand our reach. This presentation will address what we have learned in terms of network impacts, best practices, factors for success, and future directions.

Improving Science Instruction in Southwestern Illinois and Metro East St. Louis: Students Learning Science through a Sustained Network of Teachers

ERIC Educational Resources Information Center

Voss, Eric J.; Khazaeli, Sadegh; Eder, Douglas; Gardner, Dianne C.

2011-01-01

This article describes the specific methods of a regional partnership that has lasted more than twenty-five years. Southern Illinois University Edwardsville has partnered with public and private schools in the southwestern portion of Illinois, and in metro St. Louis, in the Hands-On Science project, which provides instruction development for…

NASA’s Universe of Learning: Connecting Scientists, Educators, and Learners

NASA Astrophysics Data System (ADS)

Smith, Denise A.; Lestition, Kathleen; Squires, Gordon K.; Greene, W. M.; Biferno, Anya A.; Cominsky, Lynn R.; Goodman, Irene; Walker, Allyson; Universe of Learning Team

2017-01-01

NASA’s Universe of Learning (UoL) is one of 27 competitively awarded education programs selected by NASA’s Science Mission Directorate (SMD) in its newly restructured education effort. Through these 27 programs, SMD aims to infuse NASA science experts and content more effectively and efficiently into learning environments serving audiences of all ages. UoL is a unique partnership between the Space Telescope Science Institute, Chandra X-ray Center, IPAC at Caltech, Jet Propulsion Laboratory Exoplanet Exploration Program, and Sonoma State University that will connect the scientists, engineers, science, technology and adventure of NASA Astrophysics with audience needs, proven infrastructure, and a network of partners to advance SMD education objectives. External evaluation is provided through a partnership with Goodman Research Group and Cornerstone Evaluation Associates. The multi-institutional team is working to develop and deliver a unified, consolidated and externally evaluated suite of education products, programs, and professional development offerings that spans the full spectrum of NASA Astrophysics, including the Cosmic Origins, Physics of the Cosmos, and Exoplanet Exploration themes. Products and programs focus on out-of-school-time learning environments and include enabling educational use of Astrophysics mission data and offering participatory experiences; creating multimedia and immersive experiences; designing exhibits and community programs; and producing resources for special needs and underserved/underrepresented audiences. The UoL team also works with a network of partners to provide professional learning experiences for informal educators, pre-service educators, and undergraduate instructors. This presentation will provide an overview of the UoL team’s approach to partnering scientists and educators to engage learners in Astrophysics discoveries and data; progress to date; and pathways for science community involvement.

An International Haze-Monitoring Network for Students.

ERIC Educational Resources Information Center

Mims, Forrest M.

1999-01-01

Describes the haze-monitoring program that was added to the protocols of the Global Learning and Observations to Benefit the Environment (GLOBE) Program. Finds that sun photometry provides a convenient means for allowing students to perform hands-on science while learning about various topics in history, electronics, algebra, statistics, graphing,…

Are Computer Science Students Ready for the Real World.

ERIC Educational Resources Information Center

Elliot, Noreen

The typical undergraduate program in computer science includes an introduction to hardware and operating systems, file processing and database organization, data communication and networking, and programming. However, many graduates may lack the ability to integrate the concepts "learned" into a skill set and pattern of approaching problems that…

Reducing cost with autonomous operations of the Deep Space Network radio science receiver

NASA Technical Reports Server (NTRS)

Asmar, S.; Anabtawi, A.; Connally, M.; Jongeling, A.

2003-01-01

This paper describes the Radio Science Receiver system and the savings it has brought to mission operations. The design and implementation of remote and autonomous operations will be discussed along with the process of including user feedback along the way and lessons learned and procedures avoided.

IPY Education, Outreach and Communication - Some Lessons Learned (Invited)

NASA Astrophysics Data System (ADS)

Carlson, D. J.; Salmon, R.; Munro, N.

2009-12-01

IPY Education, Outreach and Communications planning and implementation occurred with a minimum of staff and resources and a maximum of international volunteer enthusiasm and energy. Although many relatively well-funded and remarkable national activities occurred, sharing and promoting these internationally depended entirely on the volunteer networks of individuals and institutions. Through these partnerships we have learned valuable lessons about impact and distribution, and challenged several assumptions about educational partnerships. For example, we learned the importance of regular pre-scheduled events, and how to use networks of volunteer translators and free geobrowser tools. We have learned how best to conduct planning meetings and live events across time zones and hemispheres, and shown how the best concepts and ideas of science education can propagate across age groups and among languages. We have learned the optimal times of year for international events, and the most effective means for international distribution and communication. We have established a rapid-response help desk without home or staff, and sustained active and high-impact interactions with journalists largely without press releases. We have shown that, in general, wide-spread distribution of freely accessible materials produces a better impact than embargoes and restrictions. Most fundamentally, we have exposed a pervasive interest in polar science and a hunger for climate information, and responded with an active, flexible, and efficient network of partners and products.

A Network for Integrated Science and Mathematics Teaching and Learning Conference Plenary Papers. NSF/SSMA Wingspread Conference (Racine, Wisconsin, April 1991). School Science and Mathematics Association Topics for Teachers Series Number 7.

ERIC Educational Resources Information Center

Berlin, Donna F., Ed.

The integration of mathematics and science is not a new concept. However, during recent years it has been a major focus in education reform. A Wingspread conference promoted discussion regarding the integration of mathematics and science and explored ways to improve science and mathematics education in grades K-12. Papers from the conference…

Dissociable changes in functional network topology underlie early category learning and development of automaticity

PubMed Central

Soto, Fabian A.; Bassett, Danielle S.; Ashby, F. Gregory

2016-01-01

Recent work has shown that multimodal association areas–including frontal, temporal and parietal cortex–are focal points of functional network reconfiguration during human learning and performance of cognitive tasks. On the other hand, neurocomputational theories of category learning suggest that the basal ganglia and related subcortical structures are focal points of functional network reconfiguration during early learning of some categorization tasks, but become less so with the development of automatic categorization performance. Using a combination of network science and multilevel regression, we explore how changes in the connectivity of small brain regions can predict behavioral changes during training in a visual categorization task. We find that initial category learning, as indexed by changes in accuracy, is predicted by increasingly efficient integrative processing in subcortical areas, with higher functional specialization, more efficient integration across modules, but a lower cost in terms of redundancy of information processing. The development of automaticity, as indexed by changes in the speed of correct responses, was predicted by lower clustering (particularly in subcortical areas), higher strength (highest in cortical areas) and higher betweenness centrality. By combining neurocomputational theories and network scientific methods, these results synthesize the dissociative roles of multimodal association areas and subcortical structures in the development of automaticity during category learning. PMID:27453156

Social networking in nursing education: integrative literature review.

PubMed

Kakushi, Luciana Emi; Évora, Yolanda Dora Martinez

2016-01-01

to identify the use of social networking in nursing education. integrative literature review in the databases: LILACS, IBECS, Cochrane, BDENF, SciELO, CINAHL, Scopus, PubMed, CAPES Periodicals Portal and Web of Science, using the descriptors: social networking and nursing education and the keywords: social networking sites and nursing education, carried out in April 2015. of the 489 articles found, only 14 met the inclusion and exclusion criteria. Most studies were published after 2013 (57%), originating from the United States and United Kingdom (77.8%). It was observed the use of social networking among nursing students, postgraduate students, mentors and nurses, in undergraduate programmes, hybrid education (blended-learning) and in interprofessional education. The social networking sites used in the teaching and learning process were Facebook (42.8%), Ning (28.5%), Twitter (21.4%) and MySpace (7.1%), by means of audios, videos, quizzes, animations, forums, guidance, support, discussions and research group. few experiences of the use of social networking in nursing education were found and their contributions show the numerous benefits and difficulties faced, providing resourses for the improvement and revaluation of their use in the teaching and learning process.

Citizen social science: a methodology to facilitate and evaluate workplace learning in continuing interprofessional education.

PubMed

Dadich, Ann

2014-05-01

Workplace learning in continuing interprofessional education (CIPE) can be difficult to facilitate and evaluate, which can create a number of challenges for this type of learning. This article presents an innovative method to foster and investigate workplace learning in CIPE - citizen social science. Citizen social science involves clinicians as co-researchers in the systematic examination of social phenomena. When facilitated by an open-source online social networking platform, clinicians can participate via computer, smartphone, or tablet in ways that suit their needs and preferences. Furthermore, as co-researchers they can help to reveal the dynamic interplay that facilitates workplace learning in CIPE. Although yet to be tested, citizen social science offers four potential benefits: it recognises and accommodates the complexity of workplace learning in CIPE; it has the capacity to both foster and evaluate the phenomena; it can be used in situ, capturing and having direct relevance to the complexity of the workplace; and by advancing both theoretical and methodological debates on CIPE, it may reveal opportunities to improve and sustain workplace learning. By describing an example situated in the youth health sector, this article demonstrates how these benefits might be realised.

The Power of Large Scale Partnerships to Increase Climate Awareness and Literacy Around the World

NASA Astrophysics Data System (ADS)

Murphy, T.; Andersen, T. J.; Wegner, K.

2016-12-01

The Global Learning and Observations to Benefit the Environment (GLOBE) Program is an international science and education program that connects a network of communities around the world and gives them the opportunity to participate in data collection and the scientific process, and contribute meaningfully to our understanding of the Earth system and global environment. In the last few years, there has been an infusion of energy in the program as a result of a change to a more community focus. GLOBE was one of the first attempts at a citizen science program at the K-12 level proposed on a global scale. An initial ramp-up of the program was followed by the establishment of a network of partners in countries and within the U.S. One hundred and seventeen countries have participated in the program since its establishment in 1994. These countries are divided into six regions: Africa (23 countries); Asia and Pacific (18); Europe and Eurasia (41); Latin America and Caribbean (20); Near East and North Africa (13); and North America (2). The community within these regions has reached a maturity level that allows it to organize its own science campaigns ranging from aerosols to phenology…all of which increase awareness of climate issues. In addition, some countries within the regions have established science fairs, GLOBE proved to be the impetus for these fairs. The program's partnership network provides students and teachers with a platform for learning about climate issues in their local and global environment, as well as providing scientists with a network to organize data collection and analysis campaigns. Within the U.S., over 130 educational organizations (universities, science museums, nature centers) are members of a partner network divided into six geographical areas: Northwest; Midwest; Northeast and Mid-Atlantic; Southeast; Southwest; and Pacific. For the first time ever, the U.S. held GLOBE science fairs with considerable input and support from the community, the U.S. Partner Forum members, and U.S. Country Coordinator. GLOBE students exhibited their research and learned about climate issues at these fairs. GLOBE has evolved in 20 years and its strength is the community of partners that has helped moved climate literacy forward on a global scale.

Design Patterns for Learning and Assessment: Facilitating the Introduction of a Complex Simulation-Based Learning Environment into a Community of Instructors

NASA Astrophysics Data System (ADS)

Frezzo, Dennis C.; Behrens, John T.; Mislevy, Robert J.

2010-04-01

Simulation environments make it possible for science and engineering students to learn to interact with complex systems. Putting these capabilities to effective use for learning, and assessing learning, requires more than a simulation environment alone. It requires a conceptual framework for the knowledge, skills, and ways of thinking that are meant to be developed, in order to design activities that target these capabilities. The challenges of using simulation environments effectively are especially daunting in dispersed social systems. This article describes how these challenges were addressed in the context of the Cisco Networking Academies with a simulation tool for computer networks called Packet Tracer. The focus is on a conceptual support framework for instructors in over 9,000 institutions around the world for using Packet Tracer in instruction and assessment, by learning to create problem-solving scenarios that are at once tuned to the local needs of their students and consistent with the epistemic frame of "thinking like a network engineer." We describe a layered framework of tools and interfaces above the network simulator that supports the use of Packet Tracer in the distributed community of instructors and students.

Holography as deep learning

NASA Astrophysics Data System (ADS)

Gan, Wen-Cong; Shu, Fu-Wen

Quantum many-body problem with exponentially large degrees of freedom can be reduced to a tractable computational form by neural network method [G. Carleo and M. Troyer, Science 355 (2017) 602, arXiv:1606.02318.] The power of deep neural network (DNN) based on deep learning is clarified by mapping it to renormalization group (RG), which may shed lights on holographic principle by identifying a sequence of RG transformations to the AdS geometry. In this paper, we show that any network which reflects RG process has intrinsic hyperbolic geometry, and discuss the structure of entanglement encoded in the graph of DNN. We find the entanglement structure of DNN is of Ryu-Takayanagi form. Based on these facts, we argue that the emergence of holographic gravitational theory is related to deep learning process of the quantum-field theory.

Networking for Leadership, Inquiry, and Systemic Thinking: A New Approach to Inquiry-Based Learning.

ERIC Educational Resources Information Center

Byers, Al; Fitzgerald, Mary Ann

2002-01-01

Points out difficulties with a change from traditional teaching methods to a more inquiry-centered approach. Presents theoretical and empirical foundations for the Networking for Leadership, Inquiry, and Systemic Thinking (NLIST) initiative sponsored by the Council of State Science Supervisors (CSSS) and NASA, describes its progress, and outlines…

An Evaluation of a Professional Learning Network for Computer Science Teachers

ERIC Educational Resources Information Center

Cutts, Quintin; Robertson, Judy; Donaldson, Peter; O'Donnell, Laurie

2017-01-01

This paper describes and evaluates aspects of a professional development programme for existing CS teachers in secondary schools (PLAN C) which was designed to support teachers at a time of substantial curricular change. The paper's particular focus is on the formation of a teacher professional development network across several hundred teachers…

Cognitive Affordances of the Cyberinfrastructure for Science and Math Learning

ERIC Educational Resources Information Center

Martinez, Michael E.; Peters Burton, Erin E.

2011-01-01

The "cyberinfrastucture" is a broad informational network that entails connections to real-time data sensors as well as tools that permit visualization and other forms of analysis, and that facilitates access to vast scientific databases. This multifaceted network, already a major boon to scientific discovery, now shows exceptional promise in…

Social Network Perspectives Reveal Strength of Academic Developers as Weak Ties

ERIC Educational Resources Information Center

Matthews, Kelly E.; Crampton, Andrea; Hill, Matthew; Johnson, Elizabeth D.; Sharma, Manjula D.; Varsavsky, Cristina

2015-01-01

Social network perspectives acknowledge the influence of disciplinary cultures on academics' teaching beliefs and practices with implications for academic developers. The contribution of academic developers in 18 scholarship of teaching and learning (SoTL) projects situated in the sciences are explored by drawing on data from a two-year national…

Creating and Using a Computer Networking and Systems Administration Laboratory Built under Relaxed Financial Constraints

ERIC Educational Resources Information Center

Conlon, Michael P.; Mullins, Paul

2011-01-01

The Computer Science Department at Slippery Rock University created a laboratory for its Computer Networks and System Administration and Security courses under relaxed financial constraints. This paper describes the department's experience designing and using this laboratory, including lessons learned and descriptions of some student projects…

Semantic Web, Reusable Learning Objects, Personal Learning Networks in Health: Key Pieces for Digital Health Literacy.

PubMed

Konstantinidis, Stathis Th; Wharrad, Heather; Windle, Richard; Bamidis, Panagiotis D

2017-01-01

The knowledge existing in the World Wide Web is exponentially expanding, while continuous advancements in health sciences contribute to the creation of new knowledge. There are a lot of efforts trying to identify how the social connectivity can endorse patients' empowerment, while other studies look at the identification and the quality of online materials. However, emphasis has not been put on the big picture of connecting the existing resources with the patients "new habits" of learning through their own Personal Learning Networks. In this paper we propose a framework for empowering patients' digital health literacy adjusted to patients' currents needs by utilizing the contemporary way of learning through Personal Learning Networks, existing high quality learning resources and semantics technologies for interconnecting knowledge pieces. The framework based on the concept of knowledge maps for health as defined in this paper. Health Digital Literacy needs definitely further enhancement and the use of the proposed concept might lead to useful tools which enable use of understandable health trusted resources tailored to each person needs.

Summit of the Research Coordination Networks for Undergraduate Biology Education

PubMed Central

Eaton, Carrie Diaz; Allen, Deborah; Anderson, Laurel J.; Bowser, Gillian; Pauley, Mark A.; Williams, Kathy S.; Uno, Gordon E.

2016-01-01

The first summit of projects funded by the National Science Foundation’s Research Coordination Networks for Undergraduate Biology Education (RCN-UBE) program was held January 14–16, 2016, in Washington, DC. Sixty-five scientists and science educators from 38 of the 41 Incubator and Full RCN-UBE awards discussed the value and contributions of RCNs to the national biology education reform effort. The summit illustrated the progress of this innovative UBE track, first awarded in 2009. Participants shared experiences regarding network development and growth, identified best practices and challenges faced in network management, and discussed work accomplished. We report here on key aspects of network evaluation, characteristics of successful networks, and how to sustain and broaden participation in networks. Evidence from successful networks indicates that 5 years (the length of a Full RCN-UBE) may be insufficient time to produce a cohesive and effective network. While online communication promotes the activities of a network and disseminates effective practices, face-to-face meetings are critical for establishing ties between network participants. Creation of these National Science Foundation–funded networks may be particularly useful for consortia of faculty working to address problems or exchange novel solutions discovered while introducing active-learning methods and/or course-based research into their curricula.

An Interdisciplinary Network Making Progress on Climate Change Communication

NASA Astrophysics Data System (ADS)

Spitzer, W.; Anderson, J. C.; Bales, S.; Fraser, J.; Yoder, J. A.

2012-12-01

Public understanding of climate change continues to lag far behind the scientific consensus not merely because the public lacks information, but because there is in fact too much complex and contradictory information available. Fortunately, we can now (1) build on careful empirical cognitive and social science research to understand what people already value, believe, and understand; and then (2) design and test strategies for translating complex science so that people can examine evidence, make well-informed inferences, and embrace science-based solutions. Informal science education institutions can help bridge the gap between climate scientists and the public. In the US, more than 1,500 informal science venues (science centers, museums, aquariums, zoos, nature centers, national parks, etc.) are visited annually by 61% of the population. Extensive research shows that these visitors are receptive to learning about climate change and trust these institutions as reliable sources. Ultimately, we need to take a strategic approach to the way climate change is communicated. An interdisciplinary approach is needed to bring together three key areas of expertise (as recommended by Pidgeon and Fischhoff, 2011): 1. Climate and decision science experts - who can summarize and explain what is known, characterize risks, and describe appropriate mitigation and adaptation strategies; 2. Social scientists - who can bring to bear research, theory, and best practices from cognitive, communication, knowledge acquisition, and social learning theory; and 3. Informal educators and program designers - who bring a practitioner perspective and can exponentially facilitate a learning process for additional interpreters. With support from an NSF CCEP Phase I grant, we have tested this approach, bringing together Interdisciplinary teams of colleagues for a five month "study circles" to develop skills to communicate climate change based on research in the social and cognitive sciences. In 2011, social scientists, Ph.D. students studying oceanography, and staff from more than 20 institutions that teach science to the public came together in these learning groups. Most participants were motivated to create new or revised training or public programs based on lessons learned together. The success of this program rests on a twofold approach that combines collaborative learning with a cognitive and social sciences research based approach to communications. The learning process facilitated trust and experimentation among co-learners to practice applications for communications that has continued beyond the study circle experience through the networks established during the process. Examples drawn from the study circle outputs suggest that this approach could have a transformative impact on informal science education on a broad scale. Ultimately, we envision informal science interpreters as "vectors" for effective science communication, ocean and climate scientists with enhanced communication skills, and increased public demand for explanation and dialogue about global issues.

International distance-learning outreach: the APEC EINet experience.

PubMed

Kimball, A M; Shih, L; Brown, J; Harris, T G; Pautler, N; Jamieson, R W; Bolles, J; Horwitch, C

2003-01-01

The Emerging Infections Network is a mature electronic network that links Public Health professionals in the Asia Pacific through regular e-mail bulletins and an extensive Web site (http://www.apec.org/infectious). Emerging infections is a new area of study; learning materials help foster education. Our objective is to quantify the response of the network to the introduction of distance-learning materials on the Web site. Distance-learning materials, developed by the University of Washington School of Public Health, were field tested and launched on the site. Publicity was carried out prior to the launch of the materials. Access was tracked prospectively using server counts of page downloads. Web access increased substantially during the month after the materials were launched, especially among Asia based computers. The effect was isolated to the distance-learning pages, and not general to the site. This Web site appears to be responsive to the advertisement and to the materials. Prospective Web-site monitoring proved useful. Copyright 2002 Elsevier Science Ireland Ltd.

Commentary: Biochemistry and Molecular Biology Educators Launch National Network

ERIC Educational Resources Information Center

Bailey, Cheryl; Bell, Ellis; Johnson, Margaret; Mattos, Carla; Sears, Duane; White, Harold B.

2010-01-01

The American Society of Biochemistry and Molecular Biology (ASBMB) has launched an National Science Foundation (NSF)-funded 5 year project to support biochemistry and molecular biology educators learning what and how students learn. As a part of this initiative, hundreds of life scientists will plan and develop a rich central resource for…

"The Teacher Education Conversation": A Network of Cooperating Teachers

ERIC Educational Resources Information Center

Nielsen, Wendy S.; Triggs, Valerie; Clarke, Anthony; Collins, John

2010-01-01

This study investigated a professional learning community of cooperating teachers and university-based teacher educators. To examine our roles and perspectives as colleagues in teacher education, we drew on frameworks in teacher learning and complexity science. Monthly group meetings of this inquiry community were held over two school years in a…

The Metadata Education and Research Information Commons (MERIC): A Collaborative Teaching and Research Initiative

ERIC Educational Resources Information Center

Vellucci, Sherry L.; Hsieh-Yee, Ingrid; Moen, William E.

2007-01-01

The networked environment forced a sea change in Library and Information Science (LIS) education. Most LIS programs offer a mixed-mode of instruction that integrates online learning materials with more traditional classroom pedagogical methods and faculty are now responsible for developing content and digital learning objects. The teaching commons…

Virtual Office Hours as Cyberinfrastructure: The Case Study of Instant Messaging

ERIC Educational Resources Information Center

Balayeva, Jeren; Quan-Haase, Anabel

2009-01-01

Although out-of-class communication enhances students' learning experience, students' use of office hours has been limited. As the learning infrastructures of the social sciences and humanities have undergone a range of changes since the diffusion of digital networks, new opportunities emerge to increase out-of-class communication. Hence, it is…

Knowledge Structures of Entering Computer Networking Students and Their Instructors

ERIC Educational Resources Information Center

DiCerbo, Kristen E.

2007-01-01

Students bring prior knowledge to their learning experiences. This prior knowledge is known to affect how students encode and later retrieve new information learned. Teachers and content developers can use information about students' prior knowledge to create more effective lessons and materials. In many content areas, particularly the sciences,…

Transforming the Undergraduate Research Experience through Sustained Mentoring: Creating a Strong Support Network and a Collaborative Learning Environment

ERIC Educational Resources Information Center

Camacho, Erika T.; Holmes, Raquell M.; Wirkus, Stephen A.

2015-01-01

This chapter describes how sustained mentoring together with rigorous collaborative learning and community building contributed to successful mathematical research and individual growth in the Applied Mathematical Sciences Summer Institute (AMSSI), a program that focused on women, underrepresented minorities, and individuals from small teaching…

Effects of Response-Driven Feedback in Computer Science Learning

ERIC Educational Resources Information Center

Fernandez Aleman, J. L.; Palmer-Brown, D.; Jayne, C.

2011-01-01

This paper presents the results of a project on generating diagnostic feedback for guided learning in a first-year course on programming and a Master's course on software quality. An online multiple-choice questions (MCQs) system is integrated with neural network-based data analysis. Findings about how students use the system suggest that the…

Teacher and Student Reflections on ICT-Rich Science Inquiry

ERIC Educational Resources Information Center

Williams, P. John; Otrel-Cass, Kathrin

2017-01-01

Background: Inquiry learning in science provides authentic and relevant contexts in which students can create knowledge to solve problems, make decisions and find solutions to issues in today's world. The use of electronic networks can facilitate this interaction, dialogue and sharing, and adds a new dimension to classroom pedagogy. Purpose: This…

A Community-Building Framework for Collaborative Research Coordination across the Education and Biology Research Disciplines

ERIC Educational Resources Information Center

Pelaez, Nancy; Anderson, Trevor R.; Gardner, Stephanie M.; Yin, Yue; Abraham, Joel K.; Barlett, Edward L.; Gormally, Cara; Hurney, Carol A.; Long, Tammy M.; Newman, Dina L.; Sirum, Karen; Stevens, Michael T.

2018-01-01

Since 2009, the U.S. National Science Foundation Directorate for Biological Sciences has funded Research Coordination Networks (RCN) aimed at collaborative efforts to improve participation, learning, and assessment in undergraduate biology education (UBE). RCN-UBE projects focus on coordination and communication among scientists and educators who…

Evaluation of GALAXY Classroom Science for Grades 3-5. Final Report. Executive Summary.

ERIC Educational Resources Information Center

Guth, Gloria J. A.; Austin, Susan; DeLong, Bo; Pasta, David J.; Block, Clifford

The GALAXY Classroom is a package of integrated curricular and instructional approaches, supported by the first U.S. interactive satellite communications network designed to facilitate the introduction of innovative curricula to improve student learning in elementary schools. GALAXY Classroom Science for grades 3-5 features the organization of…

Data Acquisition and Preparation for Social Network Analysis Based on Email: Lessons Learned

DTIC Science & Technology

2009-06-01

Mrvar , A., and Batagelj , V. (2005), Exploratory Social Network Analysis with Pajek (Structural Analysis in the Social Sciences series). Cambridge, New...visualization of large networks. This program was developed by Vladimir Batagelj and Andrej Mrvar of the University of Ljubljana in Slovenia. Pajek evolved...theory, presumes Wasserman & Faust as foundation Amazon: 55% purchase rate among viewers 5. de Nooy, W., Mrvar , A., and Batagelj , V. (2005

Principles and Policies for International Coordination of Research Data Networks

NASA Astrophysics Data System (ADS)

Parsons, M. A.; Mokrane, M.; Sorvari, S.; Treloar, A.; Smith, C.

2017-12-01

International data networks enable the sharing of data within and between scientific disciplines and countries and thus provide the foundation for Open Science. Developing effective and sustainable international research data networks is critical for progress in many areas of research and for science to address complex global societal challenges. However, the development and maintenance of effective networks is not always easy, particularly in a context where public resources for science are limited and international cooperation is not a priority for many countries. The global landscape for data sharing in science is complex; many international data networks already exist and have highly variable structures. Some are linked to large intergovernmental research infrastructures, have highly developed centralized services and deal mainly with the data needs of single disciplines. Some are highly distributed, have much less rigid governance structures and provide access to data from many different domains. Most are somewhere between these two extremes and they cover different geographic regions, from regional to global. All provide a mix of data and associated data services which meets the needs of the research community to various extents and this provision depends on a mix of hardware, software, standards and protocols and human skills. These come together, working across national boundaries, in technical and social networks. In all of this, what makes a network function effectively or not is unclear. This means that there is also no simple answer to what can usefully be done at the policy level to promote the development of effective and sustainable data networks. Hence the rational for the present project - to study a variety of currently successful networks, explore the challenges that they are facing and the lessons that can be learned from confronting these challenges, and, where applicable, to translate this analysis into potential policy actions. Detailed descriptive, operational and reflective information was collected on a total of 31 international data networks including several in the geosciences domain. This presentation will summarize the lessons learned and overall conclusions and recommendations from the project.

Parallel Distributed Processing at 25: further explorations in the microstructure of cognition.

PubMed

Rogers, Timothy T; McClelland, James L

2014-08-01

This paper introduces a special issue of Cognitive Science initiated on the 25th anniversary of the publication of Parallel Distributed Processing (PDP), a two-volume work that introduced the use of neural network models as vehicles for understanding cognition. The collection surveys the core commitments of the PDP framework, the key issues the framework has addressed, and the debates the framework has spawned, and presents viewpoints on the current status of these issues. The articles focus on both historical roots and contemporary developments in learning, optimality theory, perception, memory, language, conceptual knowledge, cognitive control, and consciousness. Here we consider the approach more generally, reviewing the original motivations, the resulting framework, and the central tenets of the underlying theory. We then evaluate the impact of PDP both on the field at large and within specific subdomains of cognitive science and consider the current role of PDP models within the broader landscape of contemporary theoretical frameworks in cognitive science. Looking to the future, we consider the implications for cognitive science of the recent success of machine learning systems called "deep networks"-systems that build on key ideas presented in the PDP volumes. Copyright © 2014 Cognitive Science Society, Inc.

Simple Activities for Powerful Impact

NASA Astrophysics Data System (ADS)

LaConte, K.; Shupla, C. B.; Dusenbery, P.; Harold, J. B.; Holland, A.

2016-12-01

STEM education is having a transformational impact on libraries across the country. The STAR Library Education Network (STAR_Net) provides free Science-Technology Activities & Resources that are helping libraries to engage their communities in STEM learning experiences. Hear the results of a national 2015 survey of library and STEM professionals and learn what STEM programming is currently in place in public libraries and how libraries approach and implement STEM programs. Experience hands-on space science activities that are being used in library programs with multiple age groups. Through these hands-on activities, learners explore the nature of science and employ science and engineering practices, including developing and using models, planning and carrying out investigations, and engaging in argument from evidence (NGSS Lead States, 2013). Learn how STAR_Net can help you print (free!) mini-exhibits and educator guides. Join STAR_Net's online community and access STEM resources and webinars to work with libraries in your local community.

From dioramas to the dinner table: An ethnographic case study of the role of science museums in family life

NASA Astrophysics Data System (ADS)

Ellenbogen, Kirsten M.

What we know about learning in museums tends to come from studies of single museum visits evaluating success according to the museum's agenda, neglecting the impressive cooperative learning strategies and resources that families bring to their museum experiences. This is a report of an ethnographic case study of four families that visit science museums frequently. The study used ethnographic research and discourse analysis as combined methodological approaches, and was grounded in a sociocultural perspective that frames science as a socially and culturally constituted activity. Over eighteen months, data were collected during observations of the families in science museums, at home, and at other leisure sites. The study generated two types of findings. First, macroanalysis based on established frameworks for understanding learning in museums revealed differences in the orientation and extent of the museum visits. Additionally, a hierarchical framework for measuring science learning in museums proved insensitive. These findings underscore limitations of some of the traditional frameworks for understanding family learning in science museums. Second, microanalysis of interactions around science objects at home and in museums revealed that parents provided children with opportunities to understand the "middle ground" of science. Analysis also revealed that families adapted the science content of the museum to renegotiate family identities. Interestingly, the types of discourse most valued in science education were least important for establishing family identity. These frequent museumgoers eliminated the distance between them and science objects by transforming their meanings to establish family identity. This study demonstrates that the families' mediating strategies shape not just an understanding of science, but also a family identity that is constructed in and through interactions with science. The results of this study provide a foundation for examining how families use museums over time and the network of learning resources that support family life. This study suggests possible ways for museum professionals to reconsider the design of learning activities, museum environments, and a shift in focus from the learning institution of the science museum to the learning institution of the family.

On Location Learning: Authentic Applied Science with Networked Augmented Realities

NASA Astrophysics Data System (ADS)

Rosenbaum, Eric; Klopfer, Eric; Perry, Judy

2007-02-01

The learning of science can be made more like the practice of science through authentic simulated experiences. We have created a networked handheld Augmented Reality environment that combines the authentic role-playing of Augmented Realities and the underlying models of Participatory Simulations. This game, known as Outbreak @ The Institute, is played across a university campus where players take on the roles of doctors, medical technicians, and public health experts to contain a disease outbreak. Players can interact with virtual characters and employ virtual diagnostic tests and medicines. They are challenged to identify the source and prevent the spread of an infectious disease that can spread among real and/or virtual characters according to an underlying model. In this paper, we report on data from three high school classes who played the game. We investigate students' perception of the authenticity of the game in terms of their personal embodiment in the game, their experience playing different roles, and their understanding of the dynamic model underlying the game.

Networking Theories on Giftedness--What We Can Learn from Synthesizing Renzulli's Domain General and Krutetskii's Mathematics-Specific Theory

ERIC Educational Resources Information Center

Schindler, Maike; Rott, Benjamin

2017-01-01

Giftedness is an increasingly important research topic in educational sciences and mathematics education in particular. In this paper, we contribute to further theorizing mathematical giftedness through illustrating how networking processes can be conducted and illustrating their potential benefits. The paper focuses on two theories: Renzulli's…

Learning about a Fish from an ANT: Actor Network Theory and Science Education in the Postgenomic Era

ERIC Educational Resources Information Center

Pierce, Clayton

2015-01-01

This article uses actor network theory (ANT) to develop a more appropriate model of scientific literacy for students, teachers, and citizens in a society increasingly populated with biotechnological and bioscientific nonhumans. In so doing, I take the recent debate surrounding the first genetically engineered animal food product under review by…

News Education: Physics Education Networks meeting has global scale Competition: Competition seeks the next Brian Cox Experiment: New measurement of neutrino time-of-flight consistent with the speed of light Event: A day for all those who teach physics Conference: Students attend first Anglo-Japanese international science conference Celebration: Will 2015 be the 'Year of Light'? Teachers: Challenging our intuition in spectacular fashion: the fascinating world of quantum physics awaits Research: Science sharpens up sport Learning: Kittinger and Baumgartner: on a mission to the edge of space International: London International Youth Science Forum calls for leading young scientists Competition: Physics paralympian challenge needs inquisitive, analytical, artistic and eloquent pupils Forthcoming events

NASA Astrophysics Data System (ADS)

2012-05-01

Education: Physics Education Networks meeting has global scale Competition: Competition seeks the next Brian Cox Experiment: New measurement of neutrino time-of-flight consistent with the speed of light Event: A day for all those who teach physics Conference: Students attend first Anglo-Japanese international science conference Celebration: Will 2015 be the 'Year of Light'? Teachers: Challenging our intuition in spectacular fashion: the fascinating world of quantum physics awaits Research: Science sharpens up sport Learning: Kittinger and Baumgartner: on a mission to the edge of space International: London International Youth Science Forum calls for leading young scientists Competition: Physics paralympian challenge needs inquisitive, analytical, artistic and eloquent pupils Forthcoming events

The Galileo Teacher Training Program Global Efforts

NASA Astrophysics Data System (ADS)

Doran, R.; Pennypacker, C.; Ferlet, R.

2012-08-01

The Galileo Teacher Training Program (GTTP) successfully named representatives in nearly 100 nations in 2009, the International Year of Astronomy (IYA2009). The challenge had just begun. The steps ahead are how to reach educators that might benefit from our program and how to help build a more fair and science literate society, a society in which good tools and resources for science education are not the privilege of a few. From 2010 on our efforts have been to strengthen the newly formed network and learn how to equally help educators and students around the globe. New partnerships with other strong programs and institutions are being formed, sponsorship schemes being outlined, new tools and resources being publicized, and on-site and video conference training conducted all over the world. Efforts to officially accredit a GTTP curriculum are on the march and a stronger certification process being outlined. New science topics are being integrated in our effort and we now seek to discuss the path ahead with experts in this field and the community of users, opening the network to all corners of our beautiful blue dot. The main aim of this article is to open the discussion regarding the urgent issue of how to reawaken student interest in science, how to solve the gender inequality in science careers, and how to reach the underprivileged students and open to them the same possibilities. Efforts are in strengthening the newly formed network and learning how to equally help educators and students around the globe.

Exploring MEDLINE Space with Random Indexing and Pathfinder Networks

PubMed Central

Cohen, Trevor

2008-01-01

The integration of disparate research domains is a prerequisite for the success of the translational science initiative. MEDLINE abstracts contain content from a broad range of disciplines, presenting an opportunity for the development of methods able to integrate the knowledge they contain. Latent Semantic Analysis (LSA) and related methods learn human-like associations between terms from unannotated text. However, their computational and memory demands limits their ability to address a corpus of this size. Furthermore, visualization methods previously used in conjunction with LSA have limited ability to define the local structure of the associative networks LSA learns. This paper explores these issues by (1) processing the entire MEDLINE corpus using Random Indexing, a variant of LSA, and (2) exploring learned associations using Pathfinder Networks. Meaningful associations are inferred from MEDLINE, including a drug-disease association undetected by PUBMED search. PMID:18999236

Exploring MEDLINE space with random indexing and pathfinder networks.

PubMed

Cohen, Trevor

2008-11-06

The integration of disparate research domains is a prerequisite for the success of the translational science initiative. MEDLINE abstracts contain content from a broad range of disciplines, presenting an opportunity for the development of methods able to integrate the knowledge they contain. Latent Semantic Analysis (LSA) and related methods learn human-like associations between terms from unannotated text. However, their computational and memory demands limits their ability to address a corpus of this size. Furthermore, visualization methods previously used in conjunction with LSA have limited ability to define the local structure of the associative networks LSA learns. This paper explores these issues by (1) processing the entire MEDLINE corpus using Random Indexing, a variant of LSA, and (2) exploring learned associations using Pathfinder Networks. Meaningful associations are inferred from MEDLINE, including a drug-disease association undetected by PUBMED search.

Investigating Student Communities with Network Analysis of Interactions in a Physics Learning Center

ERIC Educational Resources Information Center

Brewe, Eric; Kramer, Laird; Sawtelle, Vashti

2012-01-01

Developing a sense of community among students is one of the three pillars of an overall reform effort to increase participation in physics, and the sciences more broadly, at Florida International University. The emergence of a research and learning community, embedded within a course reform effort, has contributed to increased recruitment and…

Fostering science literacy, environmental stewardship, and collaboration: Assessing a garden-based approach to teaching life science

NASA Astrophysics Data System (ADS)

Fisher-Maltese, Carley B.

Recently, schools nationwide have expressed a renewed interest in school gardens (California School Garden Network, 2010), viewing them as innovative educational tools. Most of the scant studies on these settings investigate the health/nutritional impacts, environmental attitudes, or emotional dispositions of students. However, few studies examine the science learning potential of a school garden from an informal learning perspective. Those studies that do examine learning emphasize individual learning of traditional school content (math, science, etc.) (Blaire, 2009; Dirks & Orvis, 2005; Klemmer, Waliczek & Zajicek, 2005a & b; Smith & Mostenbocker, 2005). My study sought to demonstrate the value of school garden learning through a focus on measures of learning typically associated with traditional learning environments, as well as informal learning environments. Grounded in situated, experiential, and contextual model of learning theories, the purpose of this case study was to examine the impacts of a school garden program at a K-3 elementary school. Results from pre/post tests, pre/post surveys, interviews, recorded student conversations, and student work reveal a number of affordances, including science learning, cross-curricular lessons in an authentic setting, a sense of school community, and positive shifts in attitude toward nature and working collaboratively with other students. I also analyzed this garden-based unit as a type curriculum reform in one school in an effort to explore issues of implementing effective practices in schools. Facilitators and barriers to implementing a garden-based science curriculum at a K-3 elementary school are discussed. Participants reported a number of implementation processes necessary for success: leadership, vision, and material, human, and social resources. However, in spite of facilitators, teachers reported barriers to implementing the garden-based curriculum, specifically lack of time and content knowledge.

Seven Years of Linking Scottish Schools and Industry with SSTN

ERIC Educational Resources Information Center

Whittington, Gary; Lowson, Sandra

2007-01-01

The Scottish Science and Technology Network (SSTN) is a major collaboration between Careers Scotland and Scottish industry to promote science and technology via an on-line and integrated learning programme. An initial two-year pilot project has grown considerably and has now been running for over 7 years. The SSTN programme is a web-based…

Community based monitoring: engaging and empowering Alberta ranchers

Treesearch

Michael S. Quinn; Jennifer E. Dubois

2005-01-01

Community based monitoring (CBM), a form of citizen science, is presented as a potential contributor to ecosystem management and sustainable development. A conceptual model for CBM and lessons learned from a Canadian national pilot program, the Canadian Community Monitoring Network, are summarized along with a description of the European university-based “science shop...

Social networking in nursing education: integrative literature review

PubMed Central

Kakushi, Luciana Emi; Évora, Yolanda Dora Martinez

2016-01-01

Abstract Objective: to identify the use of social networking in nursing education. Method: integrative literature review in the databases: LILACS, IBECS, Cochrane, BDENF, SciELO, CINAHL, Scopus, PubMed, CAPES Periodicals Portal and Web of Science, using the descriptors: social networking and nursing education and the keywords: social networking sites and nursing education, carried out in April 2015. Results: of the 489 articles found, only 14 met the inclusion and exclusion criteria. Most studies were published after 2013 (57%), originating from the United States and United Kingdom (77.8%). It was observed the use of social networking among nursing students, postgraduate students, mentors and nurses, in undergraduate programmes, hybrid education (blended-learning) and in interprofessional education. The social networking sites used in the teaching and learning process were Facebook (42.8%), Ning (28.5%), Twitter (21.4%) and MySpace (7.1%), by means of audios, videos, quizzes, animations, forums, guidance, support, discussions and research group. Conclusion: few experiences of the use of social networking in nursing education were found and their contributions show the numerous benefits and difficulties faced, providing resourses for the improvement and revaluation of their use in the teaching and learning process. PMID:27384465

Visualising the invisible: a network approach to reveal the informal social side of student learning.

PubMed

Hommes, J; Rienties, B; de Grave, W; Bos, G; Schuwirth, L; Scherpbier, A

2012-12-01

World-wide, universities in health sciences have transformed their curriculum to include collaborative learning and facilitate the students' learning process. Interaction has been acknowledged to be the synergistic element in this learning context. However, students spend the majority of their time outside their classroom and interaction does not stop outside the classroom. Therefore we studied how informal social interaction influences student learning. Moreover, to explore what really matters in the students learning process, a model was tested how the generally known important constructs-prior performance, motivation and social integration-relate to informal social interaction and student learning. 301 undergraduate medical students participated in this cross-sectional quantitative study. Informal social interaction was assessed using self-reported surveys following the network approach. Students' individual motivation, social integration and prior performance were assessed by the Academic Motivation Scale, the College Adaption Questionnaire and students' GPA respectively. A factual knowledge test represented student' learning. All social networks were positively associated with student learning significantly: friendships (β = 0.11), providing information to other students (β = 0.16), receiving information from other students (β = 0.25). Structural equation modelling revealed a model in which social networks increased student learning (r = 0.43), followed by prior performance (r = 0.31). In contrast to prior literature, students' academic motivation and social integration were not associated with students' learning. Students' informal social interaction is strongly associated with students' learning. These findings underline the need to change our focus from the formal context (classroom) to the informal context to optimize student learning and deliver modern medics.

Application of Student Book Based On Integrated Learning Model Of Networked Type With Heart Electrical Activity Theme For Junior High School

NASA Astrophysics Data System (ADS)

Gusnedi, G.; Ratnawulan, R.; Triana, L.

2018-04-01

The purpose of this study is to determine the effect of the use of Integrated Science IPA books Using Networked Learning Model of knowledge competence through improved learning outcomes obtained. The experimental design used is one group pre test post test design to know the results before and after being treated. The number of samples used is one class that is divided into two categories of initial ability to see the improvement of knowledge competence. The sample used was taken from the students of grade VIII SMPN 2 Sawahlunto, Indonesia. The results of this study indicate that most students have increased knowledge competence.

Sharing is Winning: Cooperative Learning about Atmospheric Composition Change

NASA Astrophysics Data System (ADS)

Schuepbach, E.

2010-09-01

This contribution presents evolving good practice in disseminating the body of know-how, skills and competencies within the networked community of atmospheric scientists as established in ACCENT. The promotion of early-career scientists, and encouraging the next generation to move into the field were among the key issues addressed by the "Training and Education" programme in the European Network of Excellence in Atmospheric Composition Change (ACCENT). Dissemination avenues include a virtual knowledge train carrying the wealth of high-quality scientific learning material developed with experts involved in the ACCENT network. Learning opportunities on current research in atmospheric composition change in Europe were also created during face-to-face training workshops. Real-life examples of pressing air quality issues were addressed in meetings with stakeholder groups that offered opportunities for mutual learning in inspiring partnerships. In order to increase the expertise in atmospheric composition change across Europe, activities were organized with the general public (e.g., Café Scientifique), where the participating early-career scientists were confronted with questions from lay people. For interested teachers, didactic translations of compact overviews on air quality science topics developed in ACCENT offer links with the typical European science curriculum and go beyond school book content. Some of the educational events, methods and tools are described in a booklet published in 2009 ("We Care for Clean Air!", ISBN 978-88-95665-01-6). The electronic version and all training material can be downloaded from www.accent-network.org/portal/education - a valuable resource for teachers and learners around the globe.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Scott, Bari

SoundVision held a post-workshop teleconference for our 2011 graduates (as we have done for all participants) to consolidate what they'd learned during the workshop. To maximize the Science Literacy Project's impact after it ends, we strengthened and reinforced our alumni's vibrant networking infrastructure so they can continue to connect and support each other, and updated our archive system to ensure all of our science and science journalism resources and presentations will be easy to access and use over time.

RELM: developing a serious game to teach evidence-based medicine in an academic health sciences setting.

PubMed

Gleason, Ann Whitney

2015-01-01

Gaming as a means of delivering online education continues to gain in popularity. Online games provide an engaging and enjoyable way of learning. Gaming is especially appropriate for case-based teaching, and provides a conducive environment for adult independent learning. With funding from the National Network of Libraries of Medicine, Pacific Northwest Region (NN/LM PNR), the University of Washington (UW) Health Sciences Library, and the UW School of Medicine are collaborating to create an interactive, self-paced online game that teaches players to employ the steps in practicing evidence-based medicine. The game encourages life-long learning and literacy skills and could be used for providing continuing medical education.

A Science Information Infrastructure for Access to Earth and Space Science Data through the Nation's Science Museums

NASA Technical Reports Server (NTRS)

Murray, S.

1999-01-01

In this project, we worked with the University of California at Berkeley/Center for Extreme Ultraviolet Astrophysics and five science museums (the National Air and Space Museum, the Science Museum of Virginia, the Lawrence Hall of Science, the Exploratorium., and the New York Hall of Science) to formulate plans for computer-based laboratories located at these museums. These Science Learning Laboratories would be networked and provided with real Earth and space science observations, as well as appropriate lesson plans, that would allow the general public to directly access and manipulate the actual remote sensing data, much as a scientist would.

Excellence in Social Science: International Knowledge and Innovation Networks for European Integration, Cohesion, and Enlargement

ERIC Educational Resources Information Center

Cappellin, Riccardo

2004-01-01

Nowadays, it is widely accepted that knowledge and learning are the core of competitiveness, international division of labour and agglomeration and exclusion phenomena. Yet we are still in need of a better understanding of the processes which allow access by individual regions both to codified knowledge and RTD networks as well as tacit knowledge…

Neural Models of Spatial Orientation in Novel Environments

DTIC Science & Technology

1994-01-01

tool use, the problem of self-organizing body -centered spatial representations for movement planning and spatial orientation, and the problem of...meeting of the American Association for the Advancement of Science, Boston, February, 1993. 23. Grossberg, S., annual Linnaeus Lecture, Uppsala...Congress on Neural Networks entitled --A self-organizing neural network for learning a body -centered invariant representa- tion of 3-D target

Visual thinking networking promotes long-term meaningful learning and achievement for 9th grade earth science students

NASA Astrophysics Data System (ADS)

Longo, Palma Joni

2001-12-01

An experimental and interview-based design was used to test the efficacy of visual thinking networking (VTN), a new generation of metacognitive learning strategies. Students constructed network diagrams using semantic and figural elements to represent knowledge relationships. The findings indicated the importance of using color in VTN strategies. The use of color promoted the encoding and reconstruction of earth science knowledge in memory and enhanced higher order thinking skills of problem solving. Fifty-six ninth grade earth science students (13--15 years of age) in a suburban school district outside New York City were randomly assigned to three classes with the same instructor. Five major positive findings emerged in the areas of problem solving achievement, organization of knowledge in memory, problem solving strategy dimensionality, conceptual understanding, and gender differences. A multi-covariate analysis was conducted on the pre-post gain scores of the AGI/NSTA Earth Science Examination (Part 1). Students who used the color VTN strategies had a significantly higher mean gain score on the problem solving criterion test items than students who used the black/white VTN (p = .003) and the writing strategies for learning science (p < .001). During a think-out-loud problem solving interview, students who used the color VTN strategies: (1) significantly recalled more earth science knowledge than students who used the black/white VTN (p = .021) and the writing strategies (p < .001); (2) significantly recalled more interrelated earth science knowledge than students who used black/white VTN strategies (p = .048) and the writing strategy (p < .001); (3) significantly used a greater number of action verbs than students who used the writing strategy (p = .033). Students with low abstract reasoning aptitude who used the color VTNs had a significantly higher mean number of conceptually accurate propositions than students who used the black/white VTN (p = .018) and the writing strategies (p = .010). Gender influenced the choice of VTN strategy. Females used significantly more color VTN strategies, while males used predominately black/white VTN strategies (p = .01). A neurocognitive model, the encoding activation theory of the anterior cingulate (ENACT-AC), is proposed as an explanation for these findings.

Students' awareness of science teachers' leadership, attitudes toward science, and positive thinking

NASA Astrophysics Data System (ADS)

Lu, Ying-Yan; Chen, Hsiang-Ting; Hong, Zuway-R.; Yore, Larry D.

2016-09-01

There appears to be a complex network of cognitive and affective factors that influence students' decisions to study science and motivate their choices to engage in science-oriented careers. This study explored 330 Taiwanese senior high school students' awareness of their science teacher's learning leadership and how it relates to the students' attitudes toward science and positive thinking. Initial results revealed that the optimism of positive thinking is highly and positively correlated with the future participation in science and learning science in school attitudes toward science and self-concept in science. Moreover, structural equation modelling (SEM) results indicated that the subscale of teachers' leadership with idealised influence was the most predictive of students' attitudes toward science (β = .37), and the leadership with laissez-faire was predictive of students' positive thinking (β = .21). In addition, the interview results were consistent with the quantitative findings. The correlation and SEM results indicate some of the associations and potential relationships amongst the motivational and affective factors studied and students' attitudes toward and intentions to study science, which will increase their likelihood of future involvement in science careers.

A Risk Stratification Model for Lung Cancer Based on Gene Coexpression Network and Deep Learning

PubMed Central

2018-01-01

Risk stratification model for lung cancer with gene expression profile is of great interest. Instead of previous models based on individual prognostic genes, we aimed to develop a novel system-level risk stratification model for lung adenocarcinoma based on gene coexpression network. Using multiple microarray, gene coexpression network analysis was performed to identify survival-related networks. A deep learning based risk stratification model was constructed with representative genes of these networks. The model was validated in two test sets. Survival analysis was performed using the output of the model to evaluate whether it could predict patients' survival independent of clinicopathological variables. Five networks were significantly associated with patients' survival. Considering prognostic significance and representativeness, genes of the two survival-related networks were selected for input of the model. The output of the model was significantly associated with patients' survival in two test sets and training set (p < 0.00001, p < 0.0001 and p = 0.02 for training and test sets 1 and 2, resp.). In multivariate analyses, the model was associated with patients' prognosis independent of other clinicopathological features. Our study presents a new perspective on incorporating gene coexpression networks into the gene expression signature and clinical application of deep learning in genomic data science for prognosis prediction. PMID:29581968

Student Agency: An Analysis of Students' Networked Relations across the Informal and Formal Learning Domains

ERIC Educational Resources Information Center

Rappa, Natasha Anne; Tang, Kok-Sing

2017-01-01

Agency is a construct facilitating our examination of when and how young people extend their own learning across contexts. However, little is known about the role played by adolescent learners' sense of agency. This paper reports two cases of students' agentively employing and developing science literacy practices--one in Singapore and the other…

Supervised machine learning algorithms to diagnose stress for vehicle drivers based on physiological sensor signals.

PubMed

Barua, Shaibal; Begum, Shahina; Ahmed, Mobyen Uddin

2015-01-01

Machine learning algorithms play an important role in computer science research. Recent advancement in sensor data collection in clinical sciences lead to a complex, heterogeneous data processing, and analysis for patient diagnosis and prognosis. Diagnosis and treatment of patients based on manual analysis of these sensor data are difficult and time consuming. Therefore, development of Knowledge-based systems to support clinicians in decision-making is important. However, it is necessary to perform experimental work to compare performances of different machine learning methods to help to select appropriate method for a specific characteristic of data sets. This paper compares classification performance of three popular machine learning methods i.e., case-based reasoning, neutral networks and support vector machine to diagnose stress of vehicle drivers using finger temperature and heart rate variability. The experimental results show that case-based reasoning outperforms other two methods in terms of classification accuracy. Case-based reasoning has achieved 80% and 86% accuracy to classify stress using finger temperature and heart rate variability. On contrary, both neural network and support vector machine have achieved less than 80% accuracy by using both physiological signals.

The National Climate Assessment: A Treasure Trove for Education, Communications and Outreach

NASA Astrophysics Data System (ADS)

McCaffrey, M.; Berbeco, M.; Connolly, R.; Niepold, F., III; Poppleton, K. L. I.; Cloyd, E.; Ledley, T. S.

2014-12-01

Required by Congress under the Global Change Act of 1990 to inform the nation on the findings of current climate research, the Third U.S. National Climate Assessment (NCA), released in May 2014, is a rich resource for climate change education, communications and outreach (ECO). Using a website design with mobile applications in mind, NCA takes advantage of mobile learning technology which is revolutionizing how, when and where learning occurs. In an effort to maximize the "teachable moments" inherent in the assessment, a community of experts from the National Center for Science Education and the CLEAN Network, working under the auspices of the National Climate Assessment Network (NCAnet) Education Affinity Group, have developed a series of NCA Learning Pathways that match key NCA messages and resources with reviewed educational materials and trusted online information sources, thereby adding pedagogical depth to the assessment. The NCA Learning Pathways, which focus on the regional chapters of the report, are designed make climate change science more local, human, relevant and, if properly framed by educators and communicators, hopeful for learners. This paper touches on the challenges and opportunities of infusing climate education, communications and outreach into curriculum and society, and details the development and content of NCA Learning Pathways, which are available online through NOAA's Climate.gov website: http://www.climate.gov/teaching

The Relative Influence of Formal Learning Opportunities versus Indicators of Professional Community on Changes in Science Teaching in Urban Schools

ERIC Educational Resources Information Center

McGee, Steven

2016-01-01

Previous research has shown that professional communities have the potential to be a powerful lever for continuous improvement in school settings. This research seeks to extend previous research by investigating the indicators of professional community that influence science teaching practice. This study took place in a network of urban…

The Third Annual NASA Science Internet User Working Group Conference

NASA Technical Reports Server (NTRS)

Lev, Brian S. (Editor); Gary, J. Patrick (Editor)

1993-01-01

The NASA Science Internet (NSI) User Support Office (USO) sponsored the Third Annual NSI User Working Group (NSIUWG) Conference March 30 through April 3, 1992, in Greenbelt, MD. Approximately 130 NSI users attended to learn more about the NSI, hear from projects which use NSI, and receive updates about new networking technologies and services. This report contains material relevant to the conference; copies of the agenda, meeting summaries, presentations, and descriptions of exhibitors. Plenary sessions featured a variety of speakers, including NSI project management, scientists, and NSI user project managers whose projects and applications effectively use NSI, and notable citizens of the larger Internet community. The conference also included exhibits of advanced networking applications; tutorials on internetworking, computer security, and networking technologies; and user subgroup meetings on the future direction of the conference, networking, and user services and applications.

What Happens to Student Learning When Color Is Added to a New Knowledge Representation Strategy? Implications from Visual Thinking Networking.

ERIC Educational Resources Information Center

Longo, Palma J.

A long-term study was conducted to test the effectiveness of visual thinking networking (VTN), a new generation of knowledge representation strategies with 56 ninth grade earth science students. The recent findings about the brain's organization and processing conceptually ground VTN as a new cognitive tool used by learners when making their…

Enhancing Postgraduate Learning and Teaching: Postgraduate Summer School in Dairy Science

PubMed Central

Gabai, Gianfranco; Morgante, Massimo; Gallo, Luigi

2014-01-01

Dairy science is a multidisciplinary area of scientific investigation and Ph.D. students aiming to do research in the field of animal and/or veterinary sciences must be aware of this. Ph.D. students often have vast spectra of research interests, and it is quite challenging to satisfy the expectation of all of them. The aim of this study was to establish an international Ph.D. training program based on research collaboration between the University of Sydney and the University of Padova. The core component of this program was a two-week Postgraduate Summer School in Dairy Science, which was held at the University of Padova, for Ph.D. students of both universities. Therefore, we designed a program that encompassed seminars, workshops, laboratory practical sessions, and farm visits. Participants were surveyed using a written questionnaire. Overall, participants have uniformly praised the Summer School calling it a rewarding and valuable learning experience. The Ph.D. Summer School in Dairy Science provided its participants a positive learning experience, provided them the opportunity to establish an international network, and facilitated the development of transferable skills. PMID:24575312

AcademyHealth's Delivery System Science Fellowship: Training Embedded Researchers to Design, Implement, and Evaluate New Models of Care.

PubMed

Kanani, Nisha; Hahn, Erin; Gould, Michael; Brunisholz, Kimberly; Savitz, Lucy; Holve, Erin

2017-07-01

AcademyHealth's Delivery System Science Fellowship (DSSF) provides a paid postdoctoral pragmatic learning experience to build capacity within learning healthcare systems to conduct research in applied settings. The fellowship provides hands-on training and professional leadership opportunities for researchers. Since its inception in 2012, the program has grown rapidly, with 16 health systems participating in the DSSF to date. In addition to specific projects conducted within health systems (and numerous publications associated with those initiatives), the DSSF has made several broader contributions to the field, including defining delivery system science, identifying a set of training objectives for researchers working in delivery systems, and developing a national collaborative network of care delivery organizations, operational leaders, and trainees. The DSSF is one promising approach to support higher-value care by promoting continuous learning and improvement in health systems. © 2017 Society of Hospital Medicine.

Social learning within a community of practice: Investigating interactions about evaluation among zoo education professionals.

PubMed

Khalil, Kathayoon; Ardoin, Nicole M; Wojcik, Deborah

2017-04-01

The accessibility and ubiquity of zoos and aquariums-which reach over 700 million people worldwide annually-make them critical sites for science and environmental learning. Through educational offerings, these sites can generate excitement and curiosity about nature and motivate stewardship behavior, but only if their programs are high quality and meet the needs of their audiences. Evaluation is, therefore, critical: knowing what works, for whom, and under what conditions must be central to these organizations. Yet, many zoo and aquarium educators find evaluation to be daunting, and they are challenged to implement evaluations and/or use the findings iteratively in program development and improvement. This article examines how zoo education professionals engage with one another in a learning community related to evaluation. We use a communities of practice lens and social network analysis to understand the structure of this networked learning community, considering changes over time. Our findings suggest that individuals' roles in a networked learning community are influenced by factors such as communicative convenience and one's perceptions of others' evaluation expertise, which also contribute to forming and sustaining professional relationships. This study illuminates how project-based professional networks can become communities of practice. Copyright © 2016 Elsevier Ltd. All rights reserved.

Cyanobacteria Assessment Network (CyAN) - 2017 NASA ...

EPA Pesticide Factsheets

Presentation on the Cyanobacteria Assessment Network (CYAN) and how is supports the environmental management and public use of the U.S. lakes and estuaries by providing a capability of detecting and quantifying algal blooms and related water quality using satellite data records. To be presented to the NASA Science Mission Directorate Earth Science Division Applied Sciences Program at the NASA Water Resources PI Meeting. The meeting had over 65 attendees, including currently funded PIs, participants from Western States Water Council, UCAR, California Department of Water Resources, and Navajo Nation. Some highlights from the meeting included discussions around impact assessment, with a session moderated by VALUABLES as well as a water manager needs panel, lead by WWAO. Each PI presentation also included lessons learned about how to work in applied sciences, ensure partner engagement, and pave the path towards transition.

Collaborative networks for both improvement and research.

PubMed

Clancy, Carolyn M; Margolis, Peter A; Miller, Marlene

2013-06-01

Moving significant therapeutic discoveries beyond early biomedical translation or T1 science and into practice involves: (1) T2 science, identifying "the right treatment for the right patient in the right way at the right time" (eg, patient-centered outcomes research) and tools to implement this knowledge (eg, guidelines, registries); and (2) T3 studies addressing how to achieve health care delivery change. Collaborative improvement networks can serve as large-scale, health system laboratories to engage clinicians, researchers, patients, and parents in testing approaches to translate research into practice. Improvement networks are of particular importance for pediatric T2 and T3 research, as evidence to establish safety and efficacy of therapeutic interventions in children is often lacking. Networks for improvement and research are also consistent with the Institute of Medicine's Learning Healthcare Systems model in which learning networks provide a system for improving care and outcomes and generate new knowledge in near real-time. Creation of total population registries in collaborative network sites provides large, representative study samples with high-quality data that can be used to generate evidence and to inform clinical decision-making. Networks use collaboration, data, and quality-improvement methods to standardize practice. Therefore, variation in outcomes due to unreliable and unnecessary care delivery is reduced, increasing statistical power, and allowing a consistent baseline from which to test new strategies. In addition, collaborative networks for improvement and research offer the opportunity to not only make improvements but also to study improvements to determine which interventions and combination of strategies work best in what settings.

Using Bayesian Networks to Understand Relationships among Math Anxiety, Genders, Personality Types, and Study Habits at a University in Jordan

ERIC Educational Resources Information Center

Smail, Linda

2017-01-01

Mathematics is the foundation of all sciences, but most students have problems learning math. Although students' success in life related to their success in learning, many would not take a math course unless it is their university's core requirements. Multiple reasons exist for students' poor performance in mathematics, but one prevalent variable…

Development of the Novel e-Learning System, "SPES NOVA" (Scalable Personality-Adapted Education System with Networking of Views and Activities)

ERIC Educational Resources Information Center

Takeuchi, Ken; Murakami, Manabu; Kato, Atsushi; Akiyama, Ryuichi; Honda, Hirotaka; Nozawa, Hajime; Sato, Ki-ichiro

2009-01-01

The Faculty of Industrial Science and Technology at Tokyo University of Science developed a two-campus system to produce well-trained engineers possessing both technical and humanistic traits. In their first year of study, students reside in dormitories in the natural setting of the Oshamambe campus located in Hokkaido, Japan. The education…

Scientific Modeling for Inquiring Teachers Network (SMIT'N): The Influence on Elementary Teachers' Views of Nature of Science, Inquiry, and Modeling

ERIC Educational Resources Information Center

Akerson, Valarie L.; Townsend, J. Scott; Donnelly, Lisa A.; Hanson, Deborah L.; Tira, Praweena; White, Orvil

2009-01-01

This paper summarizes the findings from a K-6 professional development program that emphasized scientific inquiry and nature of science within the theme of scientific modeling. During the 2-week summer workshop and follow up school year workshops, the instruction modeled a 5-E learning cycle approach. Pre and posttesting measured teachers' views…

Building A National Network for Ocean and Climate Change Interpretation (Invited)

NASA Astrophysics Data System (ADS)

Spitzer, W.; Anderson, J.

2013-12-01

In the US, more than 1,500 informal science venues (science centers, museums, aquariums, zoos, nature centers, national parks) are visited annually by 61% of the population. Research shows that these visitors are receptive to learning about climate change, and expect these institutions to provide reliable information about environmental issues and solutions. Given that we spend less than 5% of our lifetime in a classroom, informal science venues play a critical role in shaping public understanding. Since 2007, the New England Aquarium (NEAq) has led a national effort to increase the capacity of informal science education institutions (ISEIs) to effectively communicate about the impacts of climate change on the oceans. NEAq is now leading the NSF-funded National Network for Ocean and Climate Change Interpretation (NNOCCI), partnering with the Association of Zoos and Aquariums, FrameWorks Institute, Woods Hole Oceanographic Institution, Monterey Bay Aquarium, and National Aquarium, with evaluation conducted by the New Knowledge Organization, Pennsylvania State University, and Ohio State University. NNOCCI's design is based on best practices in informal science learning, cognitive/social psychology, community and network building: Interpreters as Communication Strategists - Interpreters can serve not merely as educators disseminating information, but can also be leaders in influencing public perceptions, given their high level of commitment, knowledge, public trust, social networks, and visitor contact. Communities of Practice - Learning is a social activity that is created through engagement in a supportive community context. Social support is particularly important in addressing a complex, contentious and distressing subject. Diffusion of Innovation - Peer networks are of primary importance in spreading innovations. Leaders serve as 'early adopters' and influence others to achieve a critical mass of implementation. Over the next five years, NNOCCI will achieve a systemic national impact across the ISE community, embed its work within multiple ongoing regional and national climate change education networks, and leave an enduring legacy: 1. An evidence-based core story and supporting training materials will be incorporated in an e-Workshop, which will be widely disseminated via AZA, other professional networks and climateinterpreter.org. 2. A national network of regional interpretive leaders will continue to convene and collaborate, as part of NNOCCI's ongoing participation in the national AZA community. 3. An online community at climateinterpreter.org will continue to serve the 150 ISEIs that NNOCCI reaches over the course of the project -- a critical mass with a broad national reach -- and help to support further dissemination through the ISE community. 4. Ongoing research will document the lasting impact of this project on promoting effective public engagement in climate change. 5. The next generation of ocean scientists will gain new perspective and communication skills, enabling them to broaden the impact of their research. We believe that the NNOCCI project can serve as a model for how ISEIs can address other complex environmental, scientific, and policy topics as well.

Lights, camera, action research: The effects of didactic digital movie making on students' twenty-first century learning skills and science content in the middle school classroom

NASA Astrophysics Data System (ADS)

Ochsner, Karl

Students are moving away from content consumption to content production. Short movies are uploaded onto video social networking sites and shared around the world. Unfortunately they usually contain little to no educational value, lack a narrative and are rarely created in the science classroom. According to new Arizona Technology standards and ISTE NET*S, along with the framework from the Partnership for 21st Century Learning Standards, our society demands students not only to learn curriculum, but to think critically, problem solve effectively, and become adept at communicating and collaborating. Didactic digital movie making in the science classroom may be one way that these twenty-first century learning skills may be implemented. An action research study using a mixed-methods approach to collect data was used to investigate if didactic moviemaking can help eighth grade students learn physical science content while incorporating 21st century learning skills of collaboration, communication, problem solving and critical thinking skills through their group production. Over a five week period, students researched lessons, wrote scripts, acted, video recorded and edited a didactic movie that contained a narrative plot to teach a science strand from the Arizona State Standards in physical science. A pretest/posttest science content test and KWL chart was given before and after the innovation to measure content learned by the students. Students then took a 21st Century Learning Skills Student Survey to measure how much they perceived that communication, collaboration, problem solving and critical thinking were taking place during the production. An open ended survey and a focus group of four students were used for qualitative analysis. Three science teachers used a project evaluation rubric to measure science content and production values from the movies. Triangulating the science content test, KWL chart, open ended questions and the project evaluation rubric, it appeared that science content was gained from this project. Students felt motivated to learn and had positive experience. Students also felt that the repetition of production and watching their movies helped them remember science. Students also perceived that creating the didactic digital movie helped them use collaboration, communication, problem solving and critical thinking skills throughout their production.

Machine learning topological states

NASA Astrophysics Data System (ADS)

Deng, Dong-Ling; Li, Xiaopeng; Das Sarma, S.

2017-11-01

Artificial neural networks and machine learning have now reached a new era after several decades of improvement where applications are to explode in many fields of science, industry, and technology. Here, we use artificial neural networks to study an intriguing phenomenon in quantum physics—the topological phases of matter. We find that certain topological states, either symmetry-protected or with intrinsic topological order, can be represented with classical artificial neural networks. This is demonstrated by using three concrete spin systems, the one-dimensional (1D) symmetry-protected topological cluster state and the 2D and 3D toric code states with intrinsic topological orders. For all three cases, we show rigorously that the topological ground states can be represented by short-range neural networks in an exact and efficient fashion—the required number of hidden neurons is as small as the number of physical spins and the number of parameters scales only linearly with the system size. For the 2D toric-code model, we find that the proposed short-range neural networks can describe the excited states with Abelian anyons and their nontrivial mutual statistics as well. In addition, by using reinforcement learning we show that neural networks are capable of finding the topological ground states of nonintegrable Hamiltonians with strong interactions and studying their topological phase transitions. Our results demonstrate explicitly the exceptional power of neural networks in describing topological quantum states, and at the same time provide valuable guidance to machine learning of topological phases in generic lattice models.

Not Only Size Matters: Early-Talker and Late-Talker Vocabularies Support Different Word-Learning Biases in Babies and Networks.

PubMed

Colunga, Eliana; Sims, Clare E

2017-02-01

In typical development, word learning goes from slow and laborious to fast and seemingly effortless. Typically developing 2-year-olds seem to intuit the whole range of things in a category from hearing a single instance named-they have word-learning biases. This is not the case for children with relatively small vocabularies (late talkers). We present a computational model that accounts for the emergence of word-learning biases in children at both ends of the vocabulary spectrum based solely on vocabulary structure. The results of Experiment 1 show that late-talkers' and early-talkers' noun vocabularies have different structures and that neural networks trained on the vocabularies of individual late talkers acquire different word-learning biases than those trained on early-talker vocabularies. These models make novel predictions about the word-learning biases in these two populations. Experiment 2 tests these predictions on late- and early-talking toddlers in a novel noun generalization task. Copyright © 2016 Cognitive Science Society, Inc.

To Trust or Not to Trust? What Drives Public Trust in Science in Social Media Engagement

NASA Astrophysics Data System (ADS)

Hwong, Y. L.; Oliver, C.; Van Kranendonk, M. J.

2017-12-01

The erosion of public trust in science is a serious concern today. This climate of distrust has real consequences, from the anti-vaccination movement to climate change denials. The age of social media promises opportunities for improved interactivity between scientists and the public, which experts hope will help improve public confidence in science. However, evidence linking social media engagement and public attitude towards science is scarce. Our study aimed to help fill this gap. We examined Twitter engagement and its impact on public trust in science, focusing on two related science issues: space science and climate change. Our datasets comprised of 10,000 randomly sampled tweets over a month's period in 2016. We used human annotation and machine learning to analyse the tweets. Results revealed the level of distrust was significantly higher in the climate change tweets. However, in the climate change network, people who engaged with science personalities trust science more than those who did not. This difference in trust levels was not present in the space science network. There the two clusters of people displayed similar levels of trust in science. Additionally, we used machine learning to predict the trust labels of tweets and conducted feature analysis to find the properties of trust-inspiring tweets. Our supervised learning algorithm was able to predict trust in science in our sample tweets with 84% accuracy. The strongest predictors of trust in science (as conveyed by tweets) were similarity, presence of URL and authenticity. Contrast this with the findings of our previous study investigating the features of highly engaging space science related social media messages, authenticity is the only feature that also inspires trust. This indicates that what works to promote engagement (e.g. `retweets', `Likes') does not necessarily build trust in science. Social media science communication is not as simple as `we engage, therefore they trust'. We suggest that social media science communication is more effective when scientists are aware of the nuances that characterise communications on virtual platforms. It may be that by being open, authentic and sensitive to the worldview of their audiences, scientists stand to get the most out of the opportunities offered by social media to improve public perception of science.

Growing a National Learning Environments and Resources Network for Science, Mathematics, Engineering, and Technology Education: Current Issues and Opportunities for the NSDL Program; Open Linking in the Scholarly Information Environment Using the OpenURL Framework; The HeadLine Personal Information Environment: Evaluation Phase One.

ERIC Educational Resources Information Center

Zia, Lee L.; Van de Sompel, Herbert; Beit-Arie, Oren; Gambles, Anne

2001-01-01

Includes three articles that discuss the National Science Foundation's National Science, Mathematics, Engineering, and Technology Education Digital Library (NSDL) program; the OpenURL framework for open reference linking in the Web-based scholarly information environment; and HeadLine (Hybrid Electronic Access and Delivery in the Library Networked…

Assessment and Classification of Service Learning: A Case Study of CS/EE Students

PubMed Central

Wang, Yu-Tseng; Lai, Pao-Lien; Chen, Jen-Yeu

2014-01-01

This study investigates the undergraduate students in computer science/electric engineering (CS/EE) in Taiwan to measure their perceived benefits from the experiences in service learning coursework. In addition, the confidence of their professional disciplines and its correlation with service learning experiences are examined. The results show that students take positive attitudes toward service learning and their perceived benefits from service learning are correlated with their confidence in professional disciplines. Furthermore, this study designs the knowledge model by Bayesian network (BN) classifiers and term frequency-inverse document frequency (TFIDF) for counseling students on the optimal choice of service learning. PMID:25295294

STENCIL: Science Teaching European Network for Creativity and Innovation in Learning

NASA Astrophysics Data System (ADS)

Cattadori, M.; Magrefi, F.

2013-12-01

STENCIL is an european educational project funded with support of the European Commission within the framework of LLP7 (Lifelong Learning Programme) for a period of 3 years (2011 - 2013). STENCIL includes 21 members from 9 European countries (Bulgaria, Germany, Greece, France, Italy, Malta, Portugal, Slovenia, Turkey.) working together to contribute to the general objective of improving science teaching, by promoting innovative methodologies and creative solutions. Among the innovative methods adept a particolar interest is a joint partnership between a wide spectrum of type of institutions such as schools, school authorities, research centres, universities, science museums, and other organizations, representing differing perspectives on science education. STENCIL offers to practitioners in science education from all over Europe, a platform; the web portal - www.stencil-science.eu - that provides high visibility to schools and institutions involved in Comenius and other similar European funded projects in science education. STENCIL takes advantage of the positive results achieved by the former European projects STELLA - Science Teaching in a Lifelong Learning Approach (2007 - 2009) and GRID - Growing interest in the development of teaching science (2004-2006). The specific objectives of the project are : 1) to identify and promote innovative practices in science teaching through the publication of Annual Reports on Science Education; 2) to bring together science education practitioners to share different experiences and learn from each other through the organisation of periodical study visits and workshops; 3) to disseminate materials and outcomes coming from previous EU funded projects and from isolated science education initiatives through the STENCIL web portal, as well as through international conferences and national events. This contribution aims at explaining the main features of the project together with the achieved results during the project's 3 year lifetime-span.

Contemporary machine learning: techniques for practitioners in the physical sciences

NASA Astrophysics Data System (ADS)

Spears, Brian

2017-10-01

Machine learning is the science of using computers to find relationships in data without explicitly knowing or programming those relationships in advance. Often without realizing it, we employ machine learning every day as we use our phones or drive our cars. Over the last few years, machine learning has found increasingly broad application in the physical sciences. This most often involves building a model relationship between a dependent, measurable output and an associated set of controllable, but complicated, independent inputs. The methods are applicable both to experimental observations and to databases of simulated output from large, detailed numerical simulations. In this tutorial, we will present an overview of current tools and techniques in machine learning - a jumping-off point for researchers interested in using machine learning to advance their work. We will discuss supervised learning techniques for modeling complicated functions, beginning with familiar regression schemes, then advancing to more sophisticated decision trees, modern neural networks, and deep learning methods. Next, we will cover unsupervised learning and techniques for reducing the dimensionality of input spaces and for clustering data. We'll show example applications from both magnetic and inertial confinement fusion. Along the way, we will describe methods for practitioners to help ensure that their models generalize from their training data to as-yet-unseen test data. We will finally point out some limitations to modern machine learning and speculate on some ways that practitioners from the physical sciences may be particularly suited to help. This work was performed by Lawrence Livermore National Laboratory under Contract DE-AC52-07NA27344.

Fireballs in the Sky: an Augmented Reality Citizen Science Program

NASA Astrophysics Data System (ADS)

Day, B. H.; Bland, P.; Sayers, R.

2017-12-01

Fireballs in the Sky is an innovative Australian citizen science program that connects the public with the research of the Desert Fireball Network (DFN). This research aims to understand the early workings of the solar system, and Fireballs in the Sky invites people around the world to learn about this science, contributing fireball sightings via a user-friendly augmented reality mobile app. Tens of thousands of people have downloaded the app world-wide and participated in the science of meteoritics. The Fireballs in the Sky app allows users to get involved with the Desert Fireball Network research, supplementing DFN observations and providing enhanced coverage by reporting their own meteor sightings to DFN scientists. Fireballs in the Sky reports are used to track the trajectories of meteors - from their orbit in space to where they might have landed on Earth. Led by Phil Bland at Curtin University in Australia, the Desert Fireball Network (DFN) uses automated observatories across Australia to triangulate trajectories of meteorites entering the atmosphere, determine pre-entry orbits, and pinpoint their fall positions. Each observatory is an autonomous intelligent imaging system, taking 1000×36Megapixel all-sky images throughout the night, using neural network algorithms to recognize events. They are capable of operating for 12 months in a harsh environment, and store all imagery collected. We developed a completely automated software pipeline for data reduction, and built a supercomputer database for storage, allowing us to process our entire archive. The DFN currently stands at 50 stations distributed across the Australian continent, covering an area of 2.5 million km^2. Working with DFN's partners at NASA's Solar System Exploration Research Virtual Institute, the team is expanding the network beyond Australia to locations around the world. Fireballs in the Sky allows a growing public base to learn about and participate in this exciting research.

Fireballs in the Sky: An Augmented Reality Citizen Science Program

NASA Technical Reports Server (NTRS)

Day, Brian

2017-01-01

Fireballs in the Sky is an innovative Australian citizen science program that connects the public with the research of the Desert Fireball Network (DFN). This research aims to understand the early workings of the solar system, and Fireballs in the Sky invites people around the world to learn about this science, contributing fireball sightings via a user-friendly augmented reality mobile app. Tens of thousands of people have downloaded the app world-wide and participated in the science of meteoritics. The Fireballs in the Sky app allows users to get involved with the Desert Fireball Network research, supplementing DFN observations and providing enhanced coverage by reporting their own meteor sightings to DFN scientists. Fireballs in the Sky reports are used to track the trajectories of meteors - from their orbit in space to where they might have landed on Earth. Led by Phil Bland at Curtin University in Australia, the Desert Fireball Network (DFN) uses automated observatories across Australia to triangulate trajectories of meteorites entering the atmosphere, determine pre-entry orbits, and pinpoint their fall positions. Each observatory is an autonomous intelligent imaging system, taking 1000 by 36 megapixel all-sky images throughout the night, using neural network algorithms to recognize events. They are capable of operating for 12 months in a harsh environment, and store all imagery collected. We developed a completely automated software pipeline for data reduction, and built a supercomputer database for storage, allowing us to process our entire archive. The DFN currently stands at 50 stations distributed across the Australian continent, covering an area of 2.5 million square kilometers. Working with DFN's partners at NASA's Solar System Exploration Research Virtual Institute, the team is expanding the network beyond Australia to locations around the world. Fireballs in the Sky allows a growing public base to learn about and participate in this exciting research.

The graph neural network model.

PubMed

Scarselli, Franco; Gori, Marco; Tsoi, Ah Chung; Hagenbuchner, Markus; Monfardini, Gabriele

2009-01-01

Many underlying relationships among data in several areas of science and engineering, e.g., computer vision, molecular chemistry, molecular biology, pattern recognition, and data mining, can be represented in terms of graphs. In this paper, we propose a new neural network model, called graph neural network (GNN) model, that extends existing neural network methods for processing the data represented in graph domains. This GNN model, which can directly process most of the practically useful types of graphs, e.g., acyclic, cyclic, directed, and undirected, implements a function tau(G,n) is an element of IR(m) that maps a graph G and one of its nodes n into an m-dimensional Euclidean space. A supervised learning algorithm is derived to estimate the parameters of the proposed GNN model. The computational cost of the proposed algorithm is also considered. Some experimental results are shown to validate the proposed learning algorithm, and to demonstrate its generalization capabilities.

Geoscience Education Research: A Brief History, Context and Opportunities

NASA Astrophysics Data System (ADS)

Mogk, D. W.; Manduca, C. A.; Kastens, K. A.

2011-12-01

DBER combines knowledge of teaching and learning with deep knowledge of discipline-specific science content. It describes the discipline-specific difficulties learners face and the specialized intellectual and instructional resources that can facilitate student understanding (NRC, 2011). In the geosciences, content knowledge derives from all the "spheres, the complex interactions of components of the Earth system, applications of first principles from allied sciences, an understanding of "deep time", and approaches that emphasize the interpretive and historical nature of geoscience. Insights gained from the theory and practice of the cognitive and learning sciences that demonstrate how people learn, as well as research on learning from other STEM disciplines, have helped inform the development of geoscience curricular initiatives. The Earth Science Curriculum Project (1963) was strongly influenced by Piaget and emphasized hands-on, experiential learning. Recognizing that education research was thriving in related STEM disciplines a NSF report (NSF 97-171) recommended "... that GEO and EHR both support research in geoscience education, helping geoscientists to work with colleagues in fields such as educational and cognitive psychology, in order to facilitate development of a new generation of geoscience educators." An NSF sponsored workshop, Bringing Research on Learning to the Geosciences (2002) brought together geoscience educators and cognitive scientists to explore areas of mutual interest, and identified a research agenda that included study of spatial learning, temporal learning, learning about complex systems, use of visualizations in geoscience learning, characterization of expert learning, and learning environments. Subsequent events have focused on building new communities of scholars, such as the On the Cutting Edge faculty professional development workshops, extensive collections of online resources, and networks of scholars that have addressed teaching with visualizations, the affective domain, observing and assessing student learning, metacognition, and understanding complex systems. Geoscience education research is a growing and thriving field of scholarship that includes new PhD programs in geocognition (e.g. Michigan State Univ., Purdue Univ., Arizona State Univ., North Carolina State Univ.), and numerous collaborative research consortia (e.g. Synthesis of Research on Learning in the Geosciences; Spatial Intelligence and Learning Center, Geoscience Affective Research Network). The results of geoscience education research are presently being incorporated into the geoscience curriculum through teaching activities and textbooks. These many contributions reveal the need for sustained research on related topics: assessments of student learning, learning environments (lab and field), "what works" for different learning audiences, learning in upper division disciplinary courses, the nature of geoscience expertise. The National Research Council is currently reviewing the Status, Contributions, and Future Direction of Discipline-Based Education Research (DBER), see: http://www7.nationalacademies.org/bose/DBER_Homepage.html

Improvement Science and NetworkED Improvement Communities: An Interview with Dr. Anthony Bryk. An ExpandED Schools Resource Guide

ERIC Educational Resources Information Center

ExpandED Schools, 2016

2016-01-01

During the summer, we interviewed Tony Bryk, Author of Learning to Improve: How America's Schools Can Get Better at Getting Better and head of the Carnegie Foundation for the Advancement of Teaching. His work was seminal in the creation of the Framework for Great Schools, which has spurred New York City schools to rethink the structures and…

Active Control of Complex Systems via Dynamic (Recurrent) Neural Networks

DTIC Science & Technology

1992-05-30

course, to on-going changes brought about by learning processes. As research in neurodynamics proceeded, the concept of reverberatory information flows...Microstructure of Cognition . Vol. 1: Foundations, M.I.T. Press, Cambridge, Massachusetts, pp. 354-361, 1986. 100 I Schwarz, G., "Estimating the dimension of a...Continually Running Fully Recurrent Neural Networks, ICS Report 8805, Institute of Cognitive Science, University of California at San Diego, 1988. 10 II

Fireballs in the Sky

NASA Astrophysics Data System (ADS)

Day, B. H.; Bland, P.

2016-12-01

Fireballs in the Sky is an innovative Australian citizen science program that connects the public with the research of the Desert Fireball Network (DFN). This research aims to understand the early workings of the solar system, and Fireballs in the Sky invites people around the world to learn about this science, contributing fireball sightings via a user-friendly app. To date, more than 23,000 people have downloaded the app world-wide and participated in planetary science. The Fireballs in the Sky app allows users to get involved with the Desert Fireball Network research, supplementing DFN observations and providing enhanced coverage by reporting their own meteor sightings to DFN scientists. Fireballs in the Sky reports are used to track the trajectories of meteors - from their orbit in space to where they might have landed on Earth. Led by Phil Bland at Curtin University in Australia, the Desert Fireball Network (DFN) uses automated observatories across Australia to triangulate trajectories of meteorites entering the atmosphere, determine pre-entry orbits, and pinpoint their fall positions. Each observatory is an autonomous intelligent imaging system, taking 1000×36Megapixel all-sky images throughout the night, using neural network algorithms to recognize events. They are capable of operating for 12 months in a harsh environment, and store all imagery collected. We developed a completely automated software pipeline for data reduction, and built a supercomputer database for storage, allowing us to process our entire archive. The DFN currently stands at 50 stations distributed across the Australian continent, covering an area of 2.5 million km^2. Working with DFN's partners at NASA's Solar System Exploration Research Virtual Institute, the team is expanding the network beyond Australia to locations around the world. Fireballs in the Sky allows a growing public base to learn about and participate in this exciting research.

Specialization and Universals in the Development of Reading Skill: How Chinese Research Informs a Universal Science of Reading

PubMed Central

Perfetti, Charles; Cao, Fan; Booth, James

2014-01-01

Understanding Chinese reading is important for identifying the universal aspects of reading, separated from those aspects that are specific to alphabetic writing or to English in particular. Chinese and alphabetic writing make different demands on reading and learning to read, despite reading procedures and their supporting brain networks that are partly universal. Learning to read accommodates the demands of a writing system through the specialization of brain networks that support word identification. This specialization increases with reading development, leading to differences in the brain networks for alphabetic and Chinese reading. We suggest that beyond reading procedures that are partly universal and partly writing-system specific, functional reading universals arise across writing systems in their adaptation to human cognitive abilities. PMID:24744605

A National Strategy to Develop Pragmatic Clinical Trials Infrastructure

PubMed Central

Guise, Jeanne‐Marie; Dolor, Rowena J.; Meissner, Paul; Tunis, Sean; Krishnan, Jerry A.; Pace, Wilson D.; Saltz, Joel; Hersh, William R.; Michener, Lloyd; Carey, Timothy S.

2014-01-01

Abstract An important challenge in comparative effectiveness research is the lack of infrastructure to support pragmatic clinical trials, which compare interventions in usual practice settings and subjects. These trials present challenges that differ from those of classical efficacy trials, which are conducted under ideal circumstances, in patients selected for their suitability, and with highly controlled protocols. In 2012, we launched a 1‐year learning network to identify high‐priority pragmatic clinical trials and to deploy research infrastructure through the NIH Clinical and Translational Science Awards Consortium that could be used to launch and sustain them. The network and infrastructure were initiated as a learning ground and shared resource for investigators and communities interested in developing pragmatic clinical trials. We followed a three‐stage process of developing the network, prioritizing proposed trials, and implementing learning exercises that culminated in a 1‐day network meeting at the end of the year. The year‐long project resulted in five recommendations related to developing the network, enhancing community engagement, addressing regulatory challenges, advancing information technology, and developing research methods. The recommendations can be implemented within 24 months and are designed to lead toward a sustained national infrastructure for pragmatic trials. PMID:24472114

The Effect of Scaffolding Strategies for Inscriptions and Argumentation in a Science Cyberlearning Environment

NASA Astrophysics Data System (ADS)

Kern, Cindy L.; Crippen, Kent J.

2017-02-01

Scientific inscriptions—graphs, diagrams, and data—and argumentation are integral to learning and communicating science and are common elements in cyberlearning environments—those involving the use of networked learning technologies. However, previous research has indicated that learners struggle to use inscriptions and when they engage in argumentation, the learning of science content becomes secondary to the learning of argumentation skills. The purpose of this study was to evaluate two scaffolding strategies for these elements in a secondary school context: (1) self- explanation prompts paired with a scientific inscription and (2) faded worked examples for the evaluation and development of scientific arguments. Participants consisted of ninth and tenth grade students (age 13-16 years; N = 245) enrolled in state-mandated biology courses taught by four different teachers. A three-factor mixed model analysis of variance with two between factors (self-explanation prompts and faded worked examples) and one within factor (pre-, post-, delayed posttest) was used to evaluate the effects on the acquisition and retention of domain-specific content knowledge. Results indicated that neither strategy influenced the acquisition and retention of science content in a positive (i.e., learning) or negative (i.e., expertise reversal effect) way. Thus, general prompts were as effective as either of the scaffolding conditions. These unanticipated results suggest that additional research is warranted for learning scaffolds with pre-college populations where the gains were established with college-aged participants.

Improving Learning of Markov Logic Networks using Transfer and Bottom-Up Induction

DTIC Science & Technology

2007-05-01

Texas at Austin Austin, TX 78712 lilyanam@cs.utexas.edu Doctoral Dissertation Proposal Supervising Professor: Raymond J. Mooney Abstract Statistical...maxima and plateaus. It is therefore an important research problem to develop learning algorithms that improve the speed and accuracy of this process. The...of Texas at Austin,Department of Computer Sciences,Austin,TX,78712 8. PERFORMING ORGANIZATION REPORT NUMBER 9. SPONSORING/MONITORING AGENCY NAME(S

Acquisition of Joint Attention by a Developmental Learning Model based on Interactions between a Robot and a Caregiver

NASA Astrophysics Data System (ADS)

Nagai, Yukie; Asada, Minoru; Hosoda, Koh

This paper presents a developmental learning model for joint attention between a robot and a human caregiver. The basic idea of the proposed model comes from the insight of the cognitive developmental science that the development can help the task learning. The model consists of a learning mechanism based on evaluation and two kinds of developmental mechanisms: a robot's development and a caregiver's one. The former means that the sensing and the actuating capabilities of the robot change from immaturity to maturity. On the other hand, the latter is defined as a process that the caregiver changes the task from easy situation to difficult one. These two developments are triggered by the learning progress. The experimental results show that the proposed model can accelerate the learning of joint attention owing to the caregiver's development. Furthermore, it is observed that the robot's development can improve the final task performance by reducing the internal representation in the learned neural network. The mechanisms that bring these effects to the learning are analyzed in line with the cognitive developmental science.

Lights, Camera, Action Research: The Effects of Didactic Digital Movie Making on Students' Twenty-First Century Learning Skills and Science Content in the Middle School Classroom

ERIC Educational Resources Information Center

Ochsner, Karl

2010-01-01

Students are moving away from content consumption to content production. Short movies are uploaded onto video social networking sites and shared around the world. Unfortunately they usually contain little to no educational value, lack a narrative and are rarely created in the science classroom. According to new Arizona Technology standards and…

Review of Statistical Learning Methods in Integrated Omics Studies (An Integrated Information Science).

PubMed

Zeng, Irene Sui Lan; Lumley, Thomas

2018-01-01

Integrated omics is becoming a new channel for investigating the complex molecular system in modern biological science and sets a foundation for systematic learning for precision medicine. The statistical/machine learning methods that have emerged in the past decade for integrated omics are not only innovative but also multidisciplinary with integrated knowledge in biology, medicine, statistics, machine learning, and artificial intelligence. Here, we review the nontrivial classes of learning methods from the statistical aspects and streamline these learning methods within the statistical learning framework. The intriguing findings from the review are that the methods used are generalizable to other disciplines with complex systematic structure, and the integrated omics is part of an integrated information science which has collated and integrated different types of information for inferences and decision making. We review the statistical learning methods of exploratory and supervised learning from 42 publications. We also discuss the strengths and limitations of the extended principal component analysis, cluster analysis, network analysis, and regression methods. Statistical techniques such as penalization for sparsity induction when there are fewer observations than the number of features and using Bayesian approach when there are prior knowledge to be integrated are also included in the commentary. For the completeness of the review, a table of currently available software and packages from 23 publications for omics are summarized in the appendix.

Educating Through Exploration: Emerging Evidence for Improved Learning Outcomes Using a New Theory of Digital Learning Design

NASA Astrophysics Data System (ADS)

Anbar, Ariel; Center for Education Through eXploration

2018-01-01

Advances in scientific visualization and public access to data have transformed science outreach and communication, but have yet to realize their potential impacts in the realm of education. Computer-based learning is a clear bridge between visualization and education that benefits students through adaptative personalization and enhanced access. Building this bridge requires close partnerships among scientists, technologists, and educators.The Infiniscope project fosters such partnerships to produce exploration-driven online learning experiences that teach basic science concepts using a combination of authentic space science narratives, data, and images, and a personalized guided inquiry approach. Infiniscope includes a web portal to host these digital learning experiences, as well as a teaching network of educators using and modifying these experiences. Infiniscope experiences are built around a new theory of digital learning design that we call “education through exploration” (ETX) developed during the creation of successful online, interactive science courses offered at ASU and other institutions. ETX builds on the research-based practices of active learning and guided inquiry to provide a set of design principles that aim to develop higher order thinking skills in addition to understanding of content. It is employed in these experiences by asking students to solve problems and actively discover relationships, supported by an intelligent tutoring system which provides immediate, personalized feedback and scaffolds scientific thinking and methods. The project is led by ASU’s School of Earth and Space Exploration working with learning designers in the Center for Education Through eXploration, with support from NASA’s Science Mission Directorate as part of the NASA Exploration Connection program.We will present an overview of ETX design, the Infinscope project, and emerging evidence of effectiveness.

Resident Space Object Characterization and Behavior Understanding via Machine Learning and Ontology-based Bayesian Networks

NASA Astrophysics Data System (ADS)

Furfaro, R.; Linares, R.; Gaylor, D.; Jah, M.; Walls, R.

2016-09-01

In this paper, we present an end-to-end approach that employs machine learning techniques and Ontology-based Bayesian Networks (BN) to characterize the behavior of resident space objects. State-of-the-Art machine learning architectures (e.g. Extreme Learning Machines, Convolutional Deep Networks) are trained on physical models to learn the Resident Space Object (RSO) features in the vectorized energy and momentum states and parameters. The mapping from measurements to vectorized energy and momentum states and parameters enables behavior characterization via clustering in the features space and subsequent RSO classification. Additionally, Space Object Behavioral Ontologies (SOBO) are employed to define and capture the domain knowledge-base (KB) and BNs are constructed from the SOBO in a semi-automatic fashion to execute probabilistic reasoning over conclusions drawn from trained classifiers and/or directly from processed data. Such an approach enables integrating machine learning classifiers and probabilistic reasoning to support higher-level decision making for space domain awareness applications. The innovation here is to use these methods (which have enjoyed great success in other domains) in synergy so that it enables a "from data to discovery" paradigm by facilitating the linkage and fusion of large and disparate sources of information via a Big Data Science and Analytics framework.

ENERGY-NET (Energy, Environment and Society Learning Network): Best Practices to Enhance Informal Geoscience Learning

NASA Astrophysics Data System (ADS)

Rossi, R.; Elliott, E. M.; Bain, D.; Crowley, K. J.; Steiner, M. A.; Divers, M. T.; Hopkins, K. G.; Giarratani, L.; Gilmore, M. E.

2014-12-01

While energy links all living and non-living systems, the integration of energy, the environment, and society is often not clearly represented in 9 - 12 classrooms and informal learning venues. However, objective public learning that integrates these components is essential for improving public environmental literacy. ENERGY-NET (Energy, Environment and Society Learning Network) is a National Science Foundation funded initiative that uses an Earth Systems Science framework to guide experimental learning for high school students and to improve public learning opportunities regarding the energy-environment-society nexus in a Museum setting. One of the primary objectives of the ENERGY-NET project is to develop a rich set of experimental learning activities that are presented as exhibits at the Carnegie Museum of Natural History in Pittsburgh, Pennsylvania (USA). Here we detail the evolution of the ENERGY-NET exhibit building process and the subsequent evolution of exhibit content over the past three years. While preliminary plans included the development of five "exploration stations" (i.e., traveling activity carts) per calendar year, the opportunity arose to create a single, larger topical exhibit per semester, which was assumed to have a greater impact on museum visitors. Evaluative assessments conducted to date reveal important practices to be incorporated into ongoing exhibit development: 1) Undergraduate mentors and teen exhibit developers should receive additional content training to allow richer exhibit materials. 2) The development process should be distributed over as long a time period as possible and emphasize iteration. This project can serve as a model for other collaborations between geoscience departments and museums. In particular, these practices may streamline development of public presentations and increase the effectiveness of experimental learning activities.

Project STONE: A Partnership Between Academia, Business and Government to Build a Pathway to STEM Careers for K-12 Students

NASA Astrophysics Data System (ADS)

Slattery, W.; Jacomet, P.; Lunsford, S.; Suttle, C.; Grove, R. L.; Teed, R. E.

2011-12-01

In the US, more than 1,500 informal science venues (science centers, museums, aquariums, zoos, nature centers, national parks) are visited annually by 61% of the population. Research shows that these visitors are receptive to learning about climate change, and expect these institutions to provide reliable information about environmental issues and solutions. Given that we spend less than 5% of our lifetime in a classroom, informal science venues play a critical role in shaping public understanding. Since 2007, the New England Aquarium (NEAq) has led a national effort to increase the capacity of informal science education institutions (ISEIs) to effectively communicate about the impacts of climate change on the oceans. NEAq is now leading the NSF-funded National Network for Ocean and Climate Change Interpretation (NNOCCI), partnering with the Association of Zoos and Aquariums, FrameWorks Institute, Woods Hole Oceanographic Institution, Monterey Bay Aquarium, and National Aquarium, with evaluation conducted by the New Knowledge Organization, Pennsylvania State University, and Ohio State University. NNOCCI's design is based on best practices in informal science learning, cognitive/social psychology, community and network building: Interpreters as Communication Strategists - Interpreters can serve not merely as educators disseminating information, but can also be leaders in influencing public perceptions, given their high level of commitment, knowledge, public trust, social networks, and visitor contact. Communities of Practice - Learning is a social activity that is created through engagement in a supportive community context. Social support is particularly important in addressing a complex, contentious and distressing subject. Diffusion of Innovation - Peer networks are of primary importance in spreading innovations. Leaders serve as 'early adopters' and influence others to achieve a critical mass of implementation. Over the next five years, NNOCCI will achieve a systemic national impact across the ISE community, embed its work within multiple ongoing regional and national climate change education networks, and leave an enduring legacy: 1. An evidence-based core story and supporting training materials will be incorporated in an e-Workshop, which will be widely disseminated via AZA, other professional networks and climateinterpreter.org. 2. A national network of regional interpretive leaders will continue to convene and collaborate, as part of NNOCCI's ongoing participation in the national AZA community. 3. An online community at climateinterpreter.org will continue to serve the 150 ISEIs that NNOCCI reaches over the course of the project -- a critical mass with a broad national reach -- and help to support further dissemination through the ISE community. 4. Ongoing research will document the lasting impact of this project on promoting effective public engagement in climate change. 5. The next generation of ocean scientists will gain new perspective and communication skills, enabling them to broaden the impact of their research. We believe that the NNOCCI project can serve as a model for how ISEIs can address other complex environmental, scientific, and policy topics as well.

Statistical mechanics of complex neural systems and high dimensional data

NASA Astrophysics Data System (ADS)

Advani, Madhu; Lahiri, Subhaneil; Ganguli, Surya

2013-03-01

Recent experimental advances in neuroscience have opened new vistas into the immense complexity of neuronal networks. This proliferation of data challenges us on two parallel fronts. First, how can we form adequate theoretical frameworks for understanding how dynamical network processes cooperate across widely disparate spatiotemporal scales to solve important computational problems? Second, how can we extract meaningful models of neuronal systems from high dimensional datasets? To aid in these challenges, we give a pedagogical review of a collection of ideas and theoretical methods arising at the intersection of statistical physics, computer science and neurobiology. We introduce the interrelated replica and cavity methods, which originated in statistical physics as powerful ways to quantitatively analyze large highly heterogeneous systems of many interacting degrees of freedom. We also introduce the closely related notion of message passing in graphical models, which originated in computer science as a distributed algorithm capable of solving large inference and optimization problems involving many coupled variables. We then show how both the statistical physics and computer science perspectives can be applied in a wide diversity of contexts to problems arising in theoretical neuroscience and data analysis. Along the way we discuss spin glasses, learning theory, illusions of structure in noise, random matrices, dimensionality reduction and compressed sensing, all within the unified formalism of the replica method. Moreover, we review recent conceptual connections between message passing in graphical models, and neural computation and learning. Overall, these ideas illustrate how statistical physics and computer science might provide a lens through which we can uncover emergent computational functions buried deep within the dynamical complexities of neuronal networks.

A review of machine learning in obesity.

PubMed

DeGregory, K W; Kuiper, P; DeSilvio, T; Pleuss, J D; Miller, R; Roginski, J W; Fisher, C B; Harness, D; Viswanath, S; Heymsfield, S B; Dungan, I; Thomas, D M

2018-05-01

Rich sources of obesity-related data arising from sensors, smartphone apps, electronic medical health records and insurance data can bring new insights for understanding, preventing and treating obesity. For such large datasets, machine learning provides sophisticated and elegant tools to describe, classify and predict obesity-related risks and outcomes. Here, we review machine learning methods that predict and/or classify such as linear and logistic regression, artificial neural networks, deep learning and decision tree analysis. We also review methods that describe and characterize data such as cluster analysis, principal component analysis, network science and topological data analysis. We introduce each method with a high-level overview followed by examples of successful applications. The algorithms were then applied to National Health and Nutrition Examination Survey to demonstrate methodology, utility and outcomes. The strengths and limitations of each method were also evaluated. This summary of machine learning algorithms provides a unique overview of the state of data analysis applied specifically to obesity. © 2018 World Obesity Federation.

Supporting students' learning in the domain of computer science

NASA Astrophysics Data System (ADS)

Gasparinatou, Alexandra; Grigoriadou, Maria

2011-03-01

Previous studies have shown that students with low knowledge understand and learn better from more cohesive texts, whereas high-knowledge students have been shown to learn better from texts of lower cohesion. This study examines whether high-knowledge readers in computer science benefit from a text of low cohesion. Undergraduate students (n = 65) read one of four versions of a text concerning Local Network Topologies, orthogonally varying local and global cohesion. Participants' comprehension was examined through free-recall measure, text-based, bridging-inference, elaborative-inference, problem-solving questions and a sorting task. The results indicated that high-knowledge readers benefited from the low-cohesion text. The interaction of text cohesion and knowledge was reliable for the sorting activity, for elaborative-inference and for problem-solving questions. Although high-knowledge readers performed better in text-based and in bridging-inference questions with the low-cohesion text, the interaction of text cohesion and knowledge was not reliable. The results suggest a more complex view of when and for whom textual cohesion affects comprehension and consequently learning in computer science.

U.S. Department of the Interior Climate Science Centers and U.S. Geological Survey National Climate Change and Wildlife Science Center—Annual report for 2015

USGS Publications Warehouse

Varela Minder, Elda; Padgett, Holly A.

2016-04-07

2015 was another great year for the Department of the Interior (DOI) Climate Science Centers (CSCs) and U.S. Geological Survey (USGS) National Climate Change and Wildlife Science Center (NCCWSC) network. The DOI CSCs and USGS NCCWSC continued their mission of providing the science, data, and tools that are needed for on-the-ground decision making by natural and cultural resource managers to address the effects of climate change on fish, wildlife, ecosystems, and communities. Our many accomplishments in 2015 included initiating a national effort to understand the influence of drought on wildlife and ecosystems; providing numerous opportunities for students and early career researchers to expand their networks and learn more about climate change effects; and working with tribes and indigenous communities to expand their knowledge of and preparation for the impacts of climate change on important resources and traditional ways of living. Here we illustrate some of these 2015 activities from across the CSCs and NCCWSC.

Citizen Science and Event-Based Science Education with the Quake-Catcher Network

NASA Astrophysics Data System (ADS)

DeGroot, R. M.; Sumy, D. F.; Benthien, M. L.

2017-12-01

The Quake-Catcher Network (QCN, quakecatcher.net) is a collaborative, citizen-science initiative to develop the world's largest, low-cost strong-motion seismic network through the utilization of sensors in laptops and smartphones or small microelectromechanical systems (MEMS) accelerometers attached to internet-connected computers. The volunteer computers monitor seismic motion and other vibrations and send the "triggers" in real-time to the QCN server hosted at the University of Southern California. The QCN servers sift through these signals and determine which ones represent earthquakes and which ones represent cultural noise. Data collected by the Quake-Catcher Network can contribute to better understanding earthquakes, provide teachable moments for students, and engage the public with authentic science experiences. QCN partners coordinate sensor installations, develop QCN's scientific tools and engagement activities, and create next generation online resources. In recent years, the QCN team has installed sensors in over 225 K-12 schools and free-choice learning institutions (e.g. museums) across the United States and Canada. One of the current goals of the program in the United States is to establish several QCN stations in K-12 schools around a local museum hub as a means to provide coordinated and sustained educational opportunities leading up to the yearly Great ShakeOut Earthquake Drill, to encourage citizen science, and enrich STEM curriculum. Several school districts and museums throughout Southern California have been instrumental in the development of QCN. For educators QCN fulfills a key component of the Next Generation Science Standards where students are provided an opportunity to utilize technology and interface with authentic scientific data and learn about emerging programs such as the ShakeAlert earthquake early warning system. For example, Sunnylands Center in Rancho Mirage, CA leads Coachella Valley Hub, which serves 31 K-12 schools, many of which are within kilometers of the San Andreas fault. Sunnylands established contact with the schools and organized the installations. Since 2016, representatives from the Incorporated Research Institutions for Seismology (IRIS), the Southern California Earthquake Center (SCEC), and the U.S. Geological Survey manage QCN.

International Observe the Moon Night: Eight Years of Engaging Scientists, Educators, and Citizen Enthusiasts in NASA Science

NASA Astrophysics Data System (ADS)

Buxner, Sanlyn; Jones, Andrea; Bleacher, Lora; Wasser, Molly; Day, Brian; Bakerman, Maya; Shaner, Andrew; Joseph, Emily; International Observe the Moon Night Coordinating Committee

2018-01-01

International Observe the Moon Night (InOMN) is an annual worldwide event, held in the fall, that celebrates lunar and planetary science and exploration. InOMN is sponsored by NASA’s Lunar Reconnaissance Orbiter (LRO) in collaboration with NASA’s Solar System Exploration Research Virtual Institute (SSERVI), the NASA’s Heliophysics Education Consortium, CosmoQuest, Night Sky Network, and Science Festival Alliance. Other key partners include the NASA Museum Alliance, Night Sky Network, and NASA Solar System Ambassadors.In 2017 InOMN will be held on October 28th, and will engage thousands of people across the globe to observe and learn about the Moon and its connection to planetary science. This year, we have partnered with the NASA Science Mission Directorate total solar eclipse team to highlight InOMN as an opportunity to harness and sustain the interest and momentum in space science and observation following the August 21st eclipse. Since 2010, over 3,800 InOMN events have been registered engaging over 550,000 visitors worldwide. Most InOMN events are held in the United States, with strong representation from many other countries. We will present current results from the 2017 InOMN evaluation.Through InOMN, we annually provide resources such as event-specific Moon maps, presentations, advertising materials, and certificates of participation. Additionally, InOMN highlights partner resources such as online interfaces including Moon Trek (https://moontrek.jpl.nasa.gov) and CosmoQuest (https://cosmoquest.org/x/) to provide further opportunities to engage with NASA science.Learn more about InOMN at http://observethemoonnight.org.

The experiences of science teachers' particpation in an inquiry-based professional development

NASA Astrophysics Data System (ADS)

Jackson, Emily A.

Once a leader in science, technology, engineering, and mathematics (STEM) education, the United States (U.S.) is now far behind many countries. There is growing concern that the U.S. is not preparing a sufficient number of students in the areas of STEM. Despite advancement of inquiry learning in science, the extent to which inquiry learning has been implemented on a classroom level falls short. The purpose of this study was to learn about the experiences of science teachers' participation in an inquiry-based professional development. A mixed method research design was used for this study to collect data from ten Project MISE participants. The qualitative data was collected using semi-structured, in-depth individual interviews, focus group interviews, observations, and document analysis of teacher portfolios and analyzed using constant comparative method. The quantitative data were collected through administration of a pretest and posttest instrument that measures the content knowledge of the science teachers and analyzed using descriptive statistics and paired t-test. The participants of this mixed methods study provided compelling evidence that Project MISE has a profound impact on their instructional practice, networking abilities, opportunities for reflection, and content knowledge.

Using rock art as an alternative science pedagogy

NASA Astrophysics Data System (ADS)

Allen, Casey D.

College-level and seventh-grade science students were studied to understand the power of a field index, the Rock Art Stability Index (RASI), for student learning about complex biophysical environmental processes. In order to determine if the studied population was representative, 584 college and seventh-grade students undertook a concept mapping exercise after they had learned basic weathering science via in-class lecture. Of this large group, a subset of 322 college students and 13 seventh-grade students also learned RASI through a field experience involving the analysis of rock weathering associated with petroglyphs. After learning weathering through RASI, students completed another concept map. This was a college population where roughly 46% had never taken a "lab science" course and nearly 22% were from minority (non-white) populations. Analysis of student learning through the lens of actor-network theory revealed that when landscape is viewed as process (i.e. many practices), science education embodies both an alternative science philosophy and an alternative materialistic worldview. When RASI components were analyzed after only lecture, student understanding of weathering displayed little connection between weathering form and weathering process. After using RASI in the field however, nearly all students made illustrative concept maps rich in connections between weathering form and weathering process for all subcomponents of RASI. When taken as an aggregate, and measured by an average concept map score, learning increased by almost 14%, Among college minority students, the average score increase approached 23%. Among female students, the average score increase was 16%. For seventh-grade students, scores increased by nearly 36%. After testing for normalcy with Kolmogorov-Smirnov, t-tests reveal that all of these increases were highly statistically significant at p<0.001. The growth in learning weathering science by minority students, as compared to non-minority students, was also statistically significant at p<0.01. These findings reveal the power of field work through RASI to strengthen cognitive linkages between complex biophysical processes and the corresponding rock weathering forms.

Coding Classroom Interactions for Collective and Individual Engagement

ERIC Educational Resources Information Center

Ryu, Suna; Lombardi, Doug

2015-01-01

This article characterizes "engagement in science learning" from a sociocultural perspective and offers a mixed method approach to measuring engagement that combines critical discourse analysis (CDA) and social network analysis (SNA). Conceptualizing engagement from a sociocultural perspective, the article discusses the advantages of a…

Building machines that learn and think like people.

PubMed

Lake, Brenden M; Ullman, Tomer D; Tenenbaum, Joshua B; Gershman, Samuel J

2017-01-01

Recent progress in artificial intelligence has renewed interest in building systems that learn and think like people. Many advances have come from using deep neural networks trained end-to-end in tasks such as object recognition, video games, and board games, achieving performance that equals or even beats that of humans in some respects. Despite their biological inspiration and performance achievements, these systems differ from human intelligence in crucial ways. We review progress in cognitive science suggesting that truly human-like learning and thinking machines will have to reach beyond current engineering trends in both what they learn and how they learn it. Specifically, we argue that these machines should (1) build causal models of the world that support explanation and understanding, rather than merely solving pattern recognition problems; (2) ground learning in intuitive theories of physics and psychology to support and enrich the knowledge that is learned; and (3) harness compositionality and learning-to-learn to rapidly acquire and generalize knowledge to new tasks and situations. We suggest concrete challenges and promising routes toward these goals that can combine the strengths of recent neural network advances with more structured cognitive models.

Real Science for Real Science Teachers: Providing Astrobiology Science Content and Contemporary Pedagogy for Today's Educators Online

NASA Astrophysics Data System (ADS)

Offerdahl, E. G.; Prather, E. E.; Slater, T. F.

2003-12-01

As teachers strive to improve the way science is taught in the classroom, many are turning to the interdisciplinary science of astrobiology as a way integrate inquiry effectively in the science classroom. However, it is generally recognized that teachers do not often have easy access to understandable and usable cutting-edge science to enrich their science lessons. Through the generous support of the NASA Astrobiology Institute (NAI), middle and high school teachers have the opportunity to learn current and provocative scientific results within the context of astrobiology as well as receive training in pedagogically sound methods of incorporating astrobiology appropriately in the classroom. In Astrobiology for Teachers, a 15-week on-line distance learning course co-sponsored by NAI, the National Science Teachers Association (NSTA) Professional Development Institute, National Teachers Enhancement Network (NTEN), Montana State University, and the Department of Astronomy at University of Arizona, teachers engage in a virtual classroom facilitated by an integrated teaching team of educators and scientists using a standards-based, inquiry curriculum. The collaborative nature of the course encourages, demonstrates, and enhances a professional exchange among scientists and educators which, in turn, fosters implementation of innovative science teaching in today's classroom.

EEG-based research on brain functional networks in cognition.

PubMed

Wang, Niannian; Zhang, Li; Liu, Guozhong

2015-01-01

Recently, exploring the cognitive functions of the brain by establishing a network model to understand the working mechanism of the brain has become a popular research topic in the field of neuroscience. In this study, electroencephalography (EEG) was used to collect data from subjects given four different mathematical cognitive tasks: recite numbers clockwise and counter-clockwise, and letters clockwise and counter-clockwise to build a complex brain function network (BFN). By studying the connectivity features and parameters of those brain functional networks, it was found that the average clustering coefficient is much larger than its corresponding random network and the average shortest path length is similar to the corresponding random networks, which clearly shows the characteristics of the small-world network. The brain regions stimulated during the experiment are consistent with traditional cognitive science regarding learning, memory, comprehension, and other rational judgment results. The new method of complex networking involves studying the mathematical cognitive process of reciting, providing an effective research foundation for exploring the relationship between brain cognition and human learning skills and memory. This could help detect memory deficits early in young and mentally handicapped children, and help scientists understand the causes of cognitive brain disorders.

Time-lagged autoencoders: Deep learning of slow collective variables for molecular kinetics

NASA Astrophysics Data System (ADS)

Wehmeyer, Christoph; Noé, Frank

2018-06-01

Inspired by the success of deep learning techniques in the physical and chemical sciences, we apply a modification of an autoencoder type deep neural network to the task of dimension reduction of molecular dynamics data. We can show that our time-lagged autoencoder reliably finds low-dimensional embeddings for high-dimensional feature spaces which capture the slow dynamics of the underlying stochastic processes—beyond the capabilities of linear dimension reduction techniques.

New Educational Video Series From AGU

NASA Astrophysics Data System (ADS)

Adamec, Bethany Holm; Sollosi, Derek

2013-04-01

A new video series entitled Live Education Activity Resource Network (LEARN) With AGU was recently launched. This series of short Earth and space science-related videos is designed to give K-12 formal and informal educators the tools they need to try new hands-on activities with their students. Research indicates that hands-on learning and problem solving are important ways for students to learn, but educators do not always know where to begin or think that they need a lot of materials to do a hands-on activity (which often is not the case).

Lessons Learned from Cosmic Serpent: A Professional Development Project for Informal Educators on Science and Native Ways of Knowing

NASA Astrophysics Data System (ADS)

Peticolas, L. M.; Maryboy, N.; Begay, D.; Paglierani, R.; Frappier, R.; Teren, A.

2011-09-01

How can one engage native communities and the public alike in understanding nature and our universe? Our approach has been to bring together practitioners at informal science centers, cultural museums, and tribal museums to develop relationships cross-culturally, to learn about different ways of studying and learning about nature and our universe, and to start to develop informal education programs or exhibits at their institution through their new understandings and peer networks. The design of this National Science Foundation (NSF) grant has been to provide an initial week-long professional development workshop in a region in the Western U.S. with a follow-up workshop in that region the following year, culminating in a final conference for all participants. We focus on three regions: the southwest (Utah, Arizona, New Mexico, and Colorado), the northwest (Alaska, Washington, and Oregon); and California. We are in our third year of our four-year grant and have in this time organized and run three regional week-long workshops and a follow-up workshop in the southwest. We have learned many lessons through this work, including: the importance of incorporating workshop participants as presenters in the workshop agenda; how the content of astronomy, ecology, and health resonates with these museum professionals and can easily be discussed with different world views in this type of cross-cultural science education; and how to best present different ways of knowing how nature and our universe work (science) in a manner that provides a context for science educators and museum professionals. In this article, we share these and other lessons we have learned from the leadership perspective of bringing together such a diverse and under-represented-in-science group of educators.

Projective simulation for artificial intelligence

NASA Astrophysics Data System (ADS)

Briegel, Hans J.; de Las Cuevas, Gemma

2012-05-01

We propose a model of a learning agent whose interaction with the environment is governed by a simulation-based projection, which allows the agent to project itself into future situations before it takes real action. Projective simulation is based on a random walk through a network of clips, which are elementary patches of episodic memory. The network of clips changes dynamically, both due to new perceptual input and due to certain compositional principles of the simulation process. During simulation, the clips are screened for specific features which trigger factual action of the agent. The scheme is different from other, computational, notions of simulation, and it provides a new element in an embodied cognitive science approach to intelligent action and learning. Our model provides a natural route for generalization to quantum-mechanical operation and connects the fields of reinforcement learning and quantum computation.

Projective simulation for artificial intelligence

PubMed Central

Briegel, Hans J.; De las Cuevas, Gemma

2012-01-01

We propose a model of a learning agent whose interaction with the environment is governed by a simulation-based projection, which allows the agent to project itself into future situations before it takes real action. Projective simulation is based on a random walk through a network of clips, which are elementary patches of episodic memory. The network of clips changes dynamically, both due to new perceptual input and due to certain compositional principles of the simulation process. During simulation, the clips are screened for specific features which trigger factual action of the agent. The scheme is different from other, computational, notions of simulation, and it provides a new element in an embodied cognitive science approach to intelligent action and learning. Our model provides a natural route for generalization to quantum-mechanical operation and connects the fields of reinforcement learning and quantum computation. PMID:22590690

Network Science for Deterrence: Sheathing the Sword of the Terrorism/Nuclear Horseman

NASA Astrophysics Data System (ADS)

Carley, Kathleen

2010-03-01

After 9/11, network analysis became popular as a way to connect and disconnect the dots. It was heralded as the new science with intrinsic value for understanding and breaking up terrorist groups, insurgencies and hostile foreign governments. The limit of the initially forwarded approach was that it focused on only the social network -- who talked to whom. However ,the networks of war, terror or nuclear or cyber, are complex networks composed of people, organizations, resources, and capabilities connected in a geo-temporal web that constrains and enables activities that are ``hidden'' in the web of everyday life. Identifying these networks requires extraction and fusion of information from cyber-mediated realms resulting in a network map of the hostile groups and their relations to the populations in which they are embedded. These data are at best a sample, albeit a very large sample, replete with missing and incomplete data. Geo-temporal considerations in addition to information loss and error called into question the value of traditional network approaches. In this talk, a new approaches and associated technologies that integrate scientific advances in machine learning, network statistics, and the social and organizational science with traditional graph theoretic approaches to social networks are presented. Then, examples, of how these technologies can be used as part of a deterrence strategy are described. Examples related to terrorism and groups such as al-Qaida and Hamas, cyber and nuclear deterrence are described. By taking this meta-network approach, embracing the complexity and simultaneously examining not just one network, but the connections among networks, it is possible to identify emergent leaders, locate changes in activities, and forecast the potential impact of various interventions. Key challenges, such as data-streaming and deception, that need to be addressed scientifically are referenced.

Detecting trends in academic research from a citation network using network representation learning

PubMed Central

Mori, Junichiro; Ochi, Masanao; Sakata, Ichiro

2018-01-01

Several network features and information retrieval methods have been proposed to elucidate the structure of citation networks and to detect important nodes. However, it is difficult to retrieve information related to trends in an academic field and to detect cutting-edge areas from the citation network. In this paper, we propose a novel framework that detects the trend as the growth direction of a citation network using network representation learning(NRL). We presume that the linear growth of citation network in latent space obtained by NRL is the result of the iterative edge additional process of a citation network. On APS datasets and papers of some domains of the Web of Science, we confirm the existence of trends by observing that an academic field grows in a specific direction linearly in latent space. Next, we calculate each node’s degree of trend-following as an indicator called the intrinsic publication year (IPY). As a result, there is a correlation between the indicator and the number of future citations. Furthermore, a word frequently used in the abstracts of cutting-edge papers (high-IPY paper) is likely to be used often in future publications. These results confirm the validity of the detected trend for predicting citation network growth. PMID:29782521

Geographical topic learning for social images with a deep neural network

NASA Astrophysics Data System (ADS)

Feng, Jiangfan; Xu, Xin

2017-03-01

The use of geographical tagging in social-media images is becoming a part of image metadata and a great interest for geographical information science. It is well recognized that geographical topic learning is crucial for geographical annotation. Existing methods usually exploit geographical characteristics using image preprocessing, pixel-based classification, and feature recognition. How to effectively exploit the high-level semantic feature and underlying correlation among different types of contents is a crucial task for geographical topic learning. Deep learning (DL) has recently demonstrated robust capabilities for image tagging and has been introduced into geoscience. It extracts high-level features computed from a whole image component, where the cluttered background may dominate spatial features in the deep representation. Therefore, a method of spatial-attentional DL for geographical topic learning is provided and we can regard it as a special case of DL combined with various deep networks and tuning tricks. Results demonstrated that the method is discriminative for different types of geographical topic learning. In addition, it outperforms other sequential processing models in a tagging task for a geographical image dataset.

Enticing New Growth

ERIC Educational Resources Information Center

Raby, June

2014-01-01

As an artist, designer and cultural historian, my work is concerned with integrating thought with material creativity. By relating science to methodology and learning strategies, somatic, experiential awareness comes to the fore. New scientific evidence about our neural network enables us to return to the body of experience we already have;…

Reframing Teachers' Work for Educational Innovation

ERIC Educational Resources Information Center

Kunnari, Irma; Ilomäki, Liisa

2016-01-01

The universities of applied sciences in Finland aim to support students in achieving work life competences by integrating authentic research, development and innovation (RDI) practices into learning. However, pursuing an educational change from a traditional higher education culture to a networked model of working is challenging for teachers. This…

Integrating Research, Teaching and Learning: Preparing the Future National STEM Faculty

NASA Astrophysics Data System (ADS)

Hooper, E. J.; Pfund, C.; Mathieu, R.

2010-08-01

A network of universities (Howard, Michigan State, Texas A&M, University of Colorado at Boulder, University of Wisconsin-Madison, Vanderbilt) have created a National Science Foundation-funded network to prepare a future national STEM (science, technology, engineering, mathematics) faculty committed to learning, implementing, and advancing teaching techniques that are effective for the wide range of students enrolled in higher education. The Center for the Integration of Research, Teaching and Learning (CIRTL; http://www.cirtl.net) develops, implements and evaluates professional development programs for future and current faculty. The programs comprise graduate courses, internships, and workshops, all integrated within campus learning communities. These elements are unified and guided by adherence to three core principles, or pillars: "Teaching as Research," whereby research skills are applied to evaluating and advancing undergraduate learning; "Learning through Diversity," in which the diversity of students' backgrounds and experiences are used as a rich resource to enhance teaching and learning; and "Learning Communities" that foster shared learning and discovery among students, and between future and current faculty within a department or institution. CIRTL established a laboratory for testing its ideas and practices at the University of Wisconsin-Madison, known as the Delta Program in Research, Teaching and Learning (http://www.delta.wisc.edu). The program offers project-based graduate courses, research mentor training, and workshops for post-docs, staff, and faculty. In addition, graduate students and post-docs can partner with a faculty member in a teaching-as-research internship to define and tackle a specific teaching and learning problem. Finally, students can obtain a Delta Certificate as testimony to their engagement in and commitment to teaching and learning. Delta has proved very successful, having served over 1500 UW-Madison instructors from graduate students to full professors. UW-Madison values the program to the point of now funding it internally.

The Denali EarthScope Education Partnership: Creating Opportunities for Learning About Solid Earth Processes in Alaska and Beyond.

NASA Astrophysics Data System (ADS)

Roush, J. J.; Hansen, R. A.

2003-12-01

The Geophysical Institute of the University of Alaska Fairbanks, in partnership with Denali National Park and Preserve, has begun an education outreach program that will create learning opportunities in solid earth geophysics for a wide sector of the public. We will capitalize upon a unique coincidence of heightened public interest in earthquakes (due to the M 7.9 Denali Fault event of Nov. 3rd, 2002), the startup of the EarthScope experiment, and the construction of the Denali Science & Learning Center, a premiere facility for science education located just 43 miles from the epicenter of the Denali Fault earthquake. Real-time data and current research results from EarthScope installations and science projects in Alaska will be used to engage students and teachers, national park visitors, and the general public in a discovery process that will enhance public understanding of tectonics, seismicity and volcanism along the boundary between the Pacific and North American plates. Activities will take place in five program areas, which are: 1) museum displays and exhibits, 2) outreach via print publications and electronic media, 3) curriculum development to enhance K-12 earth science education, 4) teacher training to develop earth science expertise among K-12 educators, and 5) interaction between scientists and the public. In order to engage the over 1 million annual visitors to Denali, as well as people throughout Alaska, project activities will correspond with the opening of the Denali Science and Learning Center in 2004. An electronic interactive kiosk is being constructed to provide public access to real-time data from seismic and geodetic monitoring networks in Alaska, as well as cutting edge visualizations of solid earth processes. A series of print publications and a website providing access to real-time seismic and geodetic data will be developed for park visitors and the general public, highlighting EarthScope science in Alaska. A suite of curriculum modules will be developed for middle school classrooms to enrich earth science curricula by taking students into the field, and by providing opportunities to interact with scientists using real EarthScope data and research results. Curriculum modules will take advantage of Denali's new "Nature Area Network", an IEEE 802.11b wireless network serving the backcountry areas of the Park where students can engage in hands on learning about geology and geophysics and share their experiences with students worldwide via the Internet. Curricula will also focus on the new field of digital story telling, in which students will develop their own understanding of solid earth processes by creating digital stories using readily available digital moviemaking technology. A training course will be developed to enhance K-12 educators' ability to teach earth science utilizing real data and research results. And a series of public lectures both at Denali and in communities across Alaska will engage Geophysical Institute researchers with the public and foster wider participation in the EarthScope Experiment. The anticipated benefits of this project are many. An increase in public awareness and understanding of solid earth processes will lead to better preparedness, and improved decision making regarding the mitigation of risk from seismic and volcanic hazards. Earth science education will be made more vital and engaging for both students and teachers. And Alaska's visitors and residents will gain a better understand and greater appreciation for the dynamic tectonic processes that have created the rugged landscape of the state and its national parklands.

A Collaborative Education Network for Advancing Climate Literacy using Data Visualization Technology

NASA Astrophysics Data System (ADS)

McDougall, C.; Russell, E. L.; Murray, M.; Bendel, W. B.

2013-12-01

One of the more difficult issues in engaging broad audiences with scientific research is to present it in a way that is intuitive, captivating and up-to-date. Over the past ten years, the National Oceanic and Atmospheric Administration (NOAA) has made significant progress in this area through Science On a Sphere(R) (SOS). SOS is a room-sized, global display system that uses computers and video projectors to display Earth systems data onto a six-foot diameter sphere, analogous to a giant animated globe. This well-crafted data visualization system serves as a way to integrate and display global change phenomena; including polar ice melt, projected sea level rise, ocean acidification and global climate models. Beyond a display for individual data sets, SOS provides a holistic global perspective that highlights the interconnectedness of Earth systems, nations and communities. SOS is now a featured exhibit at more than 100 science centers, museums, universities, aquariums and other institutions around the world reaching more than 33 million visitors every year. To facilitate the development of how this data visualization technology and these visualizations could be used with public audiences, we recognized the need for the exchange of information among the users. To accomplish this, we established the SOS Users Collaborative Network. This network consists of the institutions that have an SOS system or partners who are creating content and educational programming for SOS. When we began the Network in 2005, many museums had limited capacity to both incorporate real-time, authentic scientific data about the Earth system and interpret global change visualizations. They needed not only the visualization platform and the scientific content, but also assistance with methods of approach. We needed feedback from these users on how to craft understandable visualizations and how to further develop the SOS platform to support learning. Through this Network and the collaboration among members, we have, collectively, been able to advance all of our efforts. The member institutions, through regular face-to-face workshops and an online community, share practices in creation and cataloging of datasets, new methods for delivering content via SOS, and updates on the SOS system and software. One hallmark of the SOS Users Collaborative Network is that it exemplifies an ideal partnership between federal science agencies and informal science education institutions. The science agencies (including NOAA, NASA, and the Department of Energy) provide continuously updated global datasets, scientific expertise, funding, and support. In turn, museums act as trusted public providers of scientific information, provide audience-appropriate presentations, localized relevance to global phenomena and a forum for discussing the complex science and repercussions of global change. We will discuss the characteristics of this Network that maximize collaboration and what we're learning as a community to improve climate literacy.

Relationships between music training, speech processing, and word learning: a network perspective.

PubMed

Elmer, Stefan; Jäncke, Lutz

2018-03-15

Numerous studies have documented the behavioral advantages conferred on professional musicians and children undergoing music training in processing speech sounds varying in the spectral and temporal dimensions. These beneficial effects have previously often been associated with local functional and structural changes in the auditory cortex (AC). However, this perspective is oversimplified, in that it does not take into account the intrinsic organization of the human brain, namely, neural networks and oscillatory dynamics. Therefore, we propose a new framework for extending these previous findings to a network perspective by integrating multimodal imaging, electrophysiology, and neural oscillations. In particular, we provide concrete examples of how functional and structural connectivity can be used to model simple neural circuits exerting a modulatory influence on AC activity. In addition, we describe how such a network approach can be used for better comprehending the beneficial effects of music training on more complex speech functions, such as word learning. © 2018 New York Academy of Sciences.

Schemas in Problem Solving: An Integrated Model of Learning, Memory, and Instruction

DTIC Science & Technology

1992-01-01

article: "Hybrid Computation in Cognitive Science: Neural Networks and Symbols" (J. A. Anderson, 1990). And, Marvin Minsky echoes the sentiment in his...distributed processing: A handbook of models, programs, and exercises. Cambridge, MA: The MIT Press. Minsky , M. (1991). Logical versus analogical or symbolic

Software Development Outsourcing Decision Support Tool with Neural Network Learning

DTIC Science & Technology

2004-03-01

science, the first neuro-computer was built in 1954 by Marvin Minsky . In 1956, Dartmouth established a new research field of NN. Shortly after...04-16 50 This system was capable of recognizing letters and received much attention until 1969 when the Minsky and Papert paper discussed the

Undergraduate Students' Development of Social, Cultural, and Human Capital in a Networked Research Experience

ERIC Educational Resources Information Center

Thompson, Jennifer Jo; Conaway, Evan; Dolan, Erin L.

2016-01-01

Recent calls for reform in undergraduate biology education have emphasized integrating research experiences into the learning experiences of all undergraduates. Contemporary science research increasingly demands collaboration across disciplines and institutions to investigate complex research questions, providing new contexts and models for…

Learning to teach in a coteaching community of practice

NASA Astrophysics Data System (ADS)

Gallo-Fox, Jennifer

2009-12-01

As a result of the standards and accountability reforms of the past two decades, heightened attention has been focused upon student learning in the K-12 classrooms, classroom teacher practice, and teacher preparation. This has led to the acknowledgement of limitations of traditional field practicum and that these learning experiences are not well understood (Bullough et al., 2003; Clift & Brady, 2005). Alternative models for student teaching, including those that foster social learning experiences, have been developed. However, research is necessary to understand the implications of these models for preservice teacher learning. Drawing on sociocultural theoretical frameworks and ethnographic perspectives (Gee and Green, 1998), this qualitative research study examined the learning experiences of a cohort of eight undergraduate preservice secondary science teachers who cotaught with eight cooperating teachers for their full practicum semester. In this model, interns planned and taught alongside multiple cooperating teachers and other interns. This study centers on the social and cultural learning that occurred within this networked model and the ways that the interns developed as high school science teachers within a coteaching community of practice (Wenger, 1998). This study utilized the following data sources: Intern and cooperating teachers interviews, field observations, meeting recordings, and program documentation. Analysis focused on community and interpersonal planes of development (Rogoff, 1995) in order understand of the nature of the learning experiences and the learning that was afforded through participant interactions. Several conclusions were made after the data were analyzed. On a daily basis, the interns participated in a wide range of cultural practices and in the activities of the community. The coteaching model challenged the idiosyncratic nature of traditional student teaching models by creating opportunities to learn across various classroom contexts. In different classrooms, there were markedly different constructions of teacher practice and participant roles. The implementation of the coteaching model also resulted in the creation of an interconnected network of colleagues. In the resulting learning community, coteachers supported one another's developing practice and critically examined their shared practice.

Fostering Synergies Among Organizations to put Climate in Context for Use in Decision Making

NASA Astrophysics Data System (ADS)

Garfin, G. M.; Parris, A.; Dow, K.; Meyer, R.; Close, S.

2016-12-01

Making science usable for decision making requires a knowledge of the social and institutional contexts of decision making, an ability to develop or tap into networks for sharing information and developing knowledge, a capacity for innovating or providing services, and a program for social learning to inform decisions and improve the processes of engagement and collaboration (i.e., mechanisms for feedback, evaluation, and changes in policy or practices). Active participation by and partnerships between researchers, practitioners, and decision-makers provides a foundation for making progress in each of the aforementioned areas of endeavor. In twenty years of incubating experimental climate services, the NOAA Regional Integrated Sciences and Assessments program offers not a few ideas and examples of practices to foster synergies among organizations, that result in tangible benefits to decision-makers. Strategies include (a) designing explicit mutual learning through temporary institutions, such as workshop series, in order to develop social capital and knowledge networks (e.g., to co-develop and disseminate experimental forecasts); (b) articulating ground rules, roles, and responsibilities in managing the boundary between scientists and practitioners (e.g., in multi-partner climate adaptation planning processes); and (c) cross-training between scientists and practitioners, by embedding team members in other organizations or recruiting members from those organizations (e.g., Cooperative Extension). A promising strategy is boundary chaining, pioneered by the Great Lakes Integrated Sciences and Assessments, in which science information and service providers partner with other boundary organizations, to leverage networks, expertise, resources, and to reduce transaction costs. Partners with complementary strengths and roles can then, work iteratively and synergize to mediate the co-production of a combination of services for decision making, such as data and information, facilitation, and evaluation.

Learning to teach science in a professional development school program

NASA Astrophysics Data System (ADS)

Hildreth, David P.

1997-09-01

The purpose of this study was to determine the effects of learning to teach science in a Professional Development School (PDS) program on university elementary education preservice teachers' (1) attitudes toward science, (2) science process skills achievement, and (3) sense of science teaching efficacy. Data were collected and analyzed using both quantitative and qualitative methods. Quantitative data were collected using the Science Attitude Inventory (North Carolina Math and Science Education Network (1994), the Test of Integrated Process Skills, TIPS, (Dillashaw & Okey, 1980), and the Science Teaching Efficacy Belief Instrument, STEBI, form B (Enochs & Riggs, 1990). A pretest posttest research design was used for the attitude and process skills constructs. These results were analyzed using paired t test procedures. A pre-experimental group comparison group research design was used for the efficacy construct. Results from this comparison were analyzed using unpaired t test procedures. Qualitative data were collected through students' responses to open-ended questionnaires, narrative interviews, journal entries, small messages, and unsolicited conversations. These data were analyzed via pattern analysis. Posttest scores were significantly higher than pretests scores on both the Science Attitude Inventory and the TIPS. This indicated that students had improved attitudes toward science and science teaching and higher process skills achievement after three semesters in the science-focused PDS program. Scores on the STEBI were significantly higher for students in the pre-experimental group when compared to students in the comparison group. This indicates that students in the science-focused PDS program possessed more efficacious beliefs about science teaching than did the comparison group. Quantitative data were supported by analysis of qualitative data. Implications from this study point to the effectiveness of learning to teach science in a science-focused PDS program with respect to attitudes toward science, science process skills achievement, and sense of science teaching efficacy. In addition, qualitative data indicated that the most effective components of the science-focused PDS program rests largely on the fact that students learned to teach in a collaborative cohort team and that students spent extended periods of time in clinical internships and student teaching.

Outcomes from the GLEON fellowship program. Training graduate students in data driven network science.

NASA Astrophysics Data System (ADS)

Dugan, H.; Hanson, P. C.; Weathers, K. C.

2016-12-01

In the water sciences there is a massive need for graduate students who possess the analytical and technical skills to deal with large datasets and function in the new paradigm of open, collaborative -science. The Global Lake Ecological Observatory Network (GLEON) graduate fellowship program (GFP) was developed as an interdisciplinary training program to supplement the intensive disciplinary training of traditional graduate education. The primary goal of the GFP was to train a diverse cohort of graduate students in network science, open-web technologies, collaboration, and data analytics, and importantly to provide the opportunity to use these skills to conduct collaborative research resulting in publishable scientific products. The GFP is run as a series of three week-long workshops over two years that brings together a cohort of twelve students. In addition, fellows are expected to attend and contribute to at least one international GLEON all-hands' meeting. Here, we provide examples of training modules in the GFP (model building, data QA/QC, information management, bayesian modeling, open coding/version control, national data programs), as well as scientific outputs (manuscripts, software products, and new global datasets) produced by the fellows, as well as the process by which this team science was catalyzed. Data driven education that lets students apply learned skills to real research projects reinforces concepts, provides motivation, and can benefit their publication record. This program design is extendable to other institutions and networks.

HoloNetwork: communicating science through holography

NASA Astrophysics Data System (ADS)

Pombo, Pedro; Santos, Emanuel; Magalhães, Carolina

2017-03-01

Since 1997 a program dedicated to holography has been developed and implemented in Portugal. This program started with focus on schools and science education. The HoloNetwork was created and it has been spread at a National level, involving a group of thirty schools and hundreds of students and teachers. In 2009 this network started to work to achieve a new target, the general public. With this goal, a larger program was developed with focus on science and society and on science communication through holography. For the implementation of this new program, special holography outreach activities were built, dedicated to informal learning and seven Science Centers around Portugal were add into the HoloNetwork. During last years, we have been working on holography, based on two main branches, one dedicated to schools and with the aimed to promote physics teaching and to teach how to make holograms, and another dedicated to society and with the aimed to promote holography and to increase scientific literacy. This paper would analyze the educational program, all holography outreach activities, exhibitions or events, all equipments, materials and setups used and it would present the holographic techniques explored with students or with the public. Finally, the results obtained in this work would be present and explored, with focus on students impact and outcomes, taking into account the public engagement on holography and its effect into scientific culture and analyzing the quality of holograms made by students and by the general public. subject.

Investigating the Potential Impacts of Energy Production in the Marcellus Shale Region Using the Shale Network Database and CUAHSI-Supported Data Tools

NASA Astrophysics Data System (ADS)

Brazil, L.

2017-12-01

The Shale Network's extensive database of water quality observations enables educational experiences about the potential impacts of resource extraction with real data. Through open source tools that are developed and maintained by the Consortium of Universities for the Advancement of Hydrologic Science, Inc. (CUAHSI), researchers, educators, and citizens can access and analyze the very same data that the Shale Network team has used in peer-reviewed publications about the potential impacts of hydraulic fracturing on water. The development of the Shale Network database has been made possible through collection efforts led by an academic team and involving numerous individuals from government agencies, citizen science organizations, and private industry. Thus far, CUAHSI-supported data tools have been used to engage high school students, university undergraduate and graduate students, as well as citizens so that all can discover how energy production impacts the Marcellus Shale region, which includes Pennsylvania and other nearby states. This presentation will describe these data tools, how the Shale Network has used them in developing educational material, and the resources available to learn more.

Crossing boundaries: the design of an interdisciplinary training program to improve care for the frail elderly.

PubMed

Kolomitro, Klodiana; Stockley, Denise; Egan, Rylan; MacDonald, Michelle L

2015-01-01

The Technology Evaluation in the Elderly Network (TVN) was funded in July 2012 under the Canadian Networks of Centres of Excellence program. This article highlights the development and preliminary evaluation of the TVN Interdisciplinary Training Program. This program is based on an experiential learning approach that crosses a multitude of disciplines including health sciences, law, social sciences, and ethical aspects of working with the frail elderly. Opportunities within the program include mentorship, interdisciplinary online collaborative projects, external placements, academic products, pre-grant submission, trainee-driven requirements, Network meetings, online modules/webinars, and most importantly active involvement with patients, families, and their support systems. The authors have 120 trainees from approximately 23 different disciplines including law, ethics, public policy, social work, and engineering engaged in the program. Based on our evaluation this program has been perceived as highly valuable by the participants and the community.

The Application of Cognitive Diagnostic Approaches via Neural Network Analysis of Serious Educational Games

NASA Astrophysics Data System (ADS)

Lamb, Richard L.

Serious Educational Games (SEGs) have been a topic of increased popularity within the educational realm since the early millennia. SEGs are generalized form of Serious Games to mean games for purposes other than entertainment but, that also specifically include training, educational purpose and pedagogy within their design. This rise in popularity (for SEGs) has occurred at a time when school systems have increased the type, number, and presentations of student achievement tests for decision-making purposes. These tests often task the form of end of course (year) tests and periodic benchmark testing. As the use of these tests, has increased policymakers have suggested their use as a measure for teacher accountability. The change in testing resulted from a push by school districts and policy makers at various component levels for a data-driven decision-making (D3M) approach. With the data-driven decision making approaches by school districts, there has been an increased focus on the measurement and assessment of student content knowledge with little focus on the contributing factors and cognitive attributes within learning that cross multiple-content areas. One-way to increase the focus on these aspects of learning (factors and attributes) that are additional to content learning is through assessments based in cognitive diagnostics. Cognitive diagnostics are a family of methodological approaches in which tasks tie to specific cognitive attributes for analytical purposes. This study explores data derived from computer data logging (n=158,000) in an observational design, using traditional statistical techniques such as clustering (exploratory and confirmatory), item response theory and through data mining techniques such as artificial neural network analysis. From these analyses, a model of student learning emerges illustrating student thinking and learning while engaged in SEG Design. This study seeks to use cognitive diagnostic type approaches to measure student learning while designing science task based SEGs. In addition, the study suggests that it may be possible to use SEGs to provide a means to administer cognitive diagnostic based assessments in real time. Results of this study suggest the confirmation of four families (factors) of traits illustrating a simple factor loading structure. Item response theory (IRT) results illustrate a 2-parameter logistic model (2PLM) fit allowing for parameterization using the IRT-True Score Method (chi2=1.70, df=1, p=0.19). Finally, fit statistics for the artificial neural network suggest the developed model adequately fits the current data set and provides a means to explore cognitive attributes and their effect on task outcomes. This study has developed a justification for combining and developing two distinct areas of research related to student learning. The first is the use of cognitive diagnostic approaches to assess student learning as it relates to the cognitive attributes used during science processing. The second area is an examination and modeling of the relationship between attributes as propagated in an artificial neural network. Results of the study provide for an ANN model of student cognition while designing science based SEGs (r 2=0.73, RMSE= 0.21) at a convergence of 1000 training iterations. The literature presented in this dissertation work integrates work from multiple field areas. Fields represented in this work range from science education, educational psychology, measurement, and computational psychology.

SUPPORTING TEACHERS IN IMPLEMENTING FORMATIVE ASSESSMENT PRACTICES IN EARTH SYSTEMS SCIENCE

NASA Astrophysics Data System (ADS)

Harris, C. J.; Penuel, W. R.; Haydel Debarger, A.; Blank, J. G.

2009-12-01

An important purpose of formative assessment is to elicit student thinking to use in instruction to help all students learn and inform next steps in teaching. However, formative assessment practices are difficult to implement and thus present a formidable challenge for many science teachers. A critical need in geoscience education is a framework for providing teachers with real-time assessment tools as well as professional development to learn how to use formative assessment to improve instruction. Here, we describe a comprehensive support system, developed for our NSF-funded Contingent Pedagogies project, for addressing the challenge of helping teachers to use formative assessment to enhance student learning in middle school Earth Systems science. Our support system is designed to improve student understanding about the geosphere by integrating classroom network technology, interactive formative assessments, and contingent curricular activities to guide teachers from formative assessment to instructional decision-making and improved student learning. To accomplish this, we are using a new classroom network technology, Group Scribbles, in the context of an innovative middle-grades Earth Science curriculum called Investigating Earth Systems (IES). Group Scribbles, developed at SRI International, is a collaborative software tool that allows individual students to compose “scribbles” (i.e., drawings and notes), on “post-it” notes in a private workspace (a notebook computer) in response to a public task. They can post these notes anonymously to a shared, public workspace (a teacher-controlled large screen monitor) that becomes the centerpiece of group and class discussion. To help teachers implement formative assessment practices, we have introduced a key resource, called a teaching routine, to help teachers take advantage of Group Scribbles for more interactive assessments. Routine refers to a sequence of repeatable interactions that, over time, become automatic to teachers and students. Routines function as classroom norms, governing how students and teachers interact with subject matter (i.e., the way ideas are elicited, taken up, and revised). We use the qualifier teaching because we view good classroom assessment as seamless with instruction. Each teaching routine defines a sequence of instructional moves, supported by classroom network technology, for creating formative assessment opportunities that address 3 goals: (1) Increase student-teacher and student-student communication;(2) Motivate students to participate and learn from discussion, investigation, and reading; and (3) Provide real-time feedback for the teacher who can then adjust instruction. We report on key features of our support system for helping teachers develop proficiency with using formative assessment to inform instruction and advance learning in Earth Systems science. We also present preliminary findings from the implementation of the support system with a test group of teachers in a large, urban school district. Findings highlight the promise of teaching routines as an important resource for structuring student opportunities to showcase their thinking.

Inspiring Climate Education Excellence (ICEE): Developing self-directed professional development modules for secondary science teachers

NASA Astrophysics Data System (ADS)

Buhr, S. M.; Lynds, S. E.; McCaffrey, M. S.; Morton, E.

2010-12-01

Inspiring Climate Education Excellence (ICEE) is a NASA-funded project to develop online course modules and self-directed learning resources aligned with the Essential Principles of Climate Science. Following a national needs assessment survey and a face to face workshop to pilot test topics, a suite of online modules is being developed suitable for self-directed learning by secondary science teachers. Modules are designed around concepts and topics in which teachers express the most interest and need for instruction. Module design also includes attention to effective teaching strategies, such as awareness of student misconceptions, strategies for forestalling controversy and advice from master teachers on implementation and curriculum development. The resources are being developed in partnership with GLOBE, and the National Science Digital Library (NSDL) and is informed by the work of the Climate Literacy and Energy Awareness Network (CLEAN) project. ICEE will help to meet the professional development needs of teachers, including those participating in the GLOBE Student Climate Research Campaign. Modules and self-directed learning resources will be developed and disseminated in partnership with the National Science Digital Library (NSDL). This presentation introduces the needs assessment and pilot workshop data upon which the modules are based, and describes the modules that are available and in development.

Ge Detector Data Classification with Neural Networks

NASA Astrophysics Data System (ADS)

Wilson, Carly; Martin, Ryan; Majorana Collaboration

2014-09-01

The Majorana Demonstrator experiment is searching for neutrinoless double beta-decay using p-type point contact PPC germanium detectors at the Sanford Underground Research Facility, in South Dakota. Pulse shape discrimination can be used in PPC detectors to distinguish signal-like events from backgrounds. This research program explored the possibility of building a self-organizing map that takes data collected from germanium detectors and classifies the events as either signal or background. Self organizing maps are a type of neural network that are self-learning and less susceptible to being biased from imperfect training data. We acknowledge support from the Office of Nuclear Physics in the DOE Office of Science, the Particle and Nuclear Astrophysics Program of the National Science Foundation and the Russian Foundation for Basic Research.

Distributed data networks: a blueprint for Big Data sharing and healthcare analytics.

PubMed

Popovic, Jennifer R

2017-01-01

This paper defines the attributes of distributed data networks and outlines the data and analytic infrastructure needed to build and maintain a successful network. We use examples from one successful implementation of a large-scale, multisite, healthcare-related distributed data network, the U.S. Food and Drug Administration-sponsored Sentinel Initiative. Analytic infrastructure-development concepts are discussed from the perspective of promoting six pillars of analytic infrastructure: consistency, reusability, flexibility, scalability, transparency, and reproducibility. This paper also introduces one use case for machine learning algorithm development to fully utilize and advance the portfolio of population health analytics, particularly those using multisite administrative data sources. © 2016 New York Academy of Sciences.

Lighting the Blue Touchpaper for UK e-Science - Closing Conference of ESLEA Project. ESLEA, March 26-28, 2007, Edinburgh

NASA Astrophysics Data System (ADS)

Clarke, Peter; Davenhall, Clive; Greenwood, Colin; Strong, Matthew

ESLEA, an EPSRC-funded project, aims to demonstrate the potential benefits of circuit-switched optical networks (lightpaths) to the UK e-Science community. This is being achieved by running a number of "proof of benefit" pilot applications over UKLight, the UK's first national optical research network. UKLight provides a new way for researchers to obtain dedicated "lightpaths" between remote sites and to deploy and test novel networking methods and technologies. It facilitates collaboration on global projects by providing a point of access to the fast growing international optical R&D infrastructure. A diverse range of data-intensive fields of academic endeavour are participating in the ESLEA project; all these groups require the integration of high-bandwidth switched lightpath circuits into their experimental and analysis infrastructure for international transport of high-volume applications data. In addition, network protocol research and development of circuit reservation mechanisms has been carried out to help the pilot applications to exploit the UKLight infrastructure effectively. Further information about ESLEA can be viewed at www.eslea.uklight.ac.uk. ESLEA activities are now coming to an end and work will finish from February to July 2007, depending upon the terms of funding of each pilot application. The first quarter of 2007 is considered the optimum time to hold a closing conference for the project. The objectives of the conference are to: 1. Provide a forum for the dissemination of research findings and learning experiences from the ESLEA project. 2. Enable colleagues from the UK and international e-Science communities to present, discuss and learn about the latest developments in networking technology. 3. Raise awareness about the deployment of the UKLight infrastructure and its relationship to SuperJANET 5. 4. Identify potential uses of UKLight by existing or future research projects

Undergraduate students' development of social, cultural, and human capital in a networked research experience

NASA Astrophysics Data System (ADS)

Thompson, Jennifer Jo; Conaway, Evan; Dolan, Erin L.

2016-12-01

Recent calls for reform in undergraduate biology education have emphasized integrating research experiences into the learning experiences of all undergraduates. Contemporary science research increasingly demands collaboration across disciplines and institutions to investigate complex research questions, providing new contexts and models for involving undergraduates in research. In this study, we examined the experiences of undergraduates participating in a multi-institution and interdisciplinary biology research network. Unlike the traditional apprenticeship model of research, in which a student participates in research under the guidance of a single faculty member, students participating in networked research have the opportunity to develop relationships with additional faculty and students working in other areas of the project, at their own and at other institutions. We examined how students in this network develop social ties and to what extent a networked research experience affords opportunities for students to develop social, cultural, and human capital. Most studies of undergraduate involvement in science research have focused on documenting student outcomes rather than elucidating how students gain access to research experiences or how elements of research participation lead to desired student outcomes. By taking a qualitative approach framed by capital theories, we have identified ways that undergraduates utilize and further develop various forms of capital important for success in science research. In our study of the first 16 months of a biology research network, we found that undergraduates drew upon a combination of human, cultural, and social capital to gain access to the network. Within their immediate research groups, students built multidimensional social ties with faculty, peers, and others, yielding social capital that can be drawn upon for information, resources, and support. They reported developing cultural capital in the form of learning to think and work like a scientist—a scientific habitus. They reported developing human capital in the forms of technical, analytical, and communication skills in scientific research. Most of the students had little, direct interaction with network members in other research groups and thus developed little cross-institutional capital. The exception to this trend was at one institution that housed three research groups. Because proximity facilitated shared activities, students across research groups at this institution developed cross-lab ties with faculty and peers through which they developed social, cultural, and human capital. An important long-term concern is whether the capital students have developed will help them access opportunities in science beyond the network. At this point, many undergraduates have had limited opportunities to actually draw on capital beyond the network. Nevertheless, a number of students demonstrated awareness that they had developed resources that they could use in other scientific contexts.

Enlarging the STEM pipeline working with youth-serving organizations

NASA Astrophysics Data System (ADS)

Porro, I.

2005-12-01

The After-School Astronomy Project (ASAP) is a comprehensive initiative to promote the pursuit of science learning among underrepresented youth. To this end ASAP specifically aims at building the capacity of urban community-based centers to deliver innovative science out-of-school programming to their youth. ASAP makes use of a modular curriculum consisting of a combination of hands-on activities and youth-led explorations of the night sky using MicroObservatory. Through project-based investigations students reinforce learning in astronomy and develop an understanding of science as inquiry, while also develop communication and computer skills. Through MicroObservatory students gain access to a network of educational telescopes, that they control over the Internet, software analysis tools and an online community of users. An integral part of ASAP is to provide professional development opportunities for after-school workers. This promotes a self-sustainable implementation of ASAP long-term and fosters the creation of a cadre of after-school professionals dedicated to facilitating science-based programs.

Network structure and influence of the climate change counter-movement

NASA Astrophysics Data System (ADS)

Farrell, Justin

2016-04-01

Anthropogenic climate change represents a global threat to human well-being and ecosystem functioning. Yet despite its importance for science and policy, our understanding of the causes of widespread uncertainty and doubt found among the general public remains limited. The political and social processes driving such doubt and uncertainty are difficult to rigorously analyse, and research has tended to focus on the individual-level, rather than the larger institutions and social networks that produce and disseminate contrarian information. This study presents a new approach by using network science to uncover the institutional and corporate structure of the climate change counter-movement, and machine-learning text analysis to show its influence in the news media and bureaucratic politics. The data include a new social network of all known organizations and individuals promoting contrarian viewpoints, as well as the entirety of all written and verbal texts about climate change from 1993-2013 from every organization, three major news outlets, all US presidents, and every occurrence on the floor of the US Congress. Using network and computational text analysis, I find that the organizational power within the contrarian network, and the magnitude of semantic similarity, are both predicted by ties to elite corporate benefactors.

Bringing Astronomy Directly to New Audiences (50,000 People) at Outdoor Concerts and Music Festivals

NASA Astrophysics Data System (ADS)

Lubowich, D.

2014-07-01

My NASA-funded Music and Astronomy Under the Stars (MAUS) has brought astronomy to 50,000 music lovers at the National Mall (co-sponsor OSTP); Central Park Jazz, Newport Folk, Ravinia, or Tanglewood music festivals; and classical, folk, pop/rock, opera, Caribbean, or county-western concerts in parks assisted by astronomy clubs (55 events since 2009). Yo-Yo-Ma, the Chicago and Boston Symphony Orchestras, Ravi Coltrane, Esperanza Spalding, Phish, Blood Sweat and Tears, Deep Purple, Tony Orlando, and Wilco performed at these events. MAUS combines solar, optical, and radio telescope observations; large posters/banners (From the Earth to the Universe; Visions of the Universe); videos; hands-on activities (Night Sky Network; Harvard-Smithsonian CfA); imaging with a cell phone mount; and hand-outs (info on science museums, astronomy clubs, and citizen science) before and after the concerts or at intermission. MAUS reached underserved groups and attracted large enthusiastic crowds. Many young children participated in this family learning experience-often the first time they looked through a telescope. Outcomes: While < 50% of the participants took part in a science museum or activity in the past year (survey result), they found MAUS enjoyable and understandable; learned about astronomy; wanted to learn more; and increased their interest in science (ave. rating 3.6/4). Taking science directly to people is effective in promoting science education!

Research summary, January 1989 - June 1990

NASA Technical Reports Server (NTRS)

1990-01-01

The Research Institute for Advanced Computer Science (RIACS) was established at NASA ARC in June of 1983. RIACS is privately operated by the Universities Space Research Association (USRA), a consortium of 62 universities with graduate programs in the aerospace sciences, under a Cooperative Agreement with NASA. RIACS serves as the representative of the USRA universities at ARC. This document reports our activities and accomplishments for the period 1 Jan. 1989 - 30 Jun. 1990. The following topics are covered: learning systems, networked systems, and parallel systems.

The Region 4 collaborative virtual reference project.

PubMed

Parker, Sandi K; Johnson, E Diane

2003-01-01

In May 2002, the Denison Memorial Library at the University of Colorado Health Sciences Center and the J. Otto Lottes Health Sciences Library at the University of Missouri-Columbia, with funding from the National Network of Libraries of Medicine-Midcontinental Region, embarked on a collaborative, real-time reference project using the 24/7 Reference, Inc., software package. This paper describes how the project was conceived, and includes details on the service hours, staffing, training, marketing, lessons learned, and future plans for the service.

News

NASA Astrophysics Data System (ADS)

2005-01-01

Einstein year: Einstein is brought back to life for a year of educational events Workshop: Students reach out for the Moon Event: Masterclasses go with a bang Workshop: Students search for asteroids on Einstein's birthday Scotland: Curriculum for Excellence takes holistic approach Conference: Reporting from a mattress in Nachod Conference: 'Change' is key objective at ICPE conference 2005 Lecture: Institute of Physics Schools Lecture series Conference: Experience showcase science in Warwick National network: Science Learning Centre opens Meeting: 30th Stirling Physics Meeting breaks records Competition: Win a digital camera! Forthcoming Events

Learning the wrong lessons? Science and fisheries management in the Chesapeake Bay blue crab fishery.

PubMed

Beem, Betsi

2012-05-01

This paper argues that information produced and then taken up for policy decision making is a function of a complex interplay within the scientific community and between scientists and the broader policy network who are all grappling with issues in a complex environment with a high degree of scientific uncertainty. The dynamics of forming and re-forming the scientific community are shaped by political processes, as are the directions and questions scientists attend to in their roles as policy advisors. Three factors: 1) social construction of scientific communities, 2) the indeterminacy of science, and 3) demands by policy makers to have concrete information for decision making; are intertwined in the production and dissemination of information that may serve as the basis for policy learning. Through this process, however, what gets learned may not be what is needed to mitigate the problem, be complete in terms of addressing multiple causations, or be correct.

The Arizona Journey Schools Program: A Strategy for Change. Final Report.

ERIC Educational Resources Information Center

Laughran, Laura J.; Shaw, Jerome M.

The Arizona Journey Schools Program (JSP) was a two-year professional development experience whose stated purpose was to build the leadership capacity of school/community teams and establish a network of professionals to support teams as they bring about systemic change in mathematics and science teaching, learning, and assessment. This report…

The Digital Agora: Interaction and Learning in Political Science.

ERIC Educational Resources Information Center

Watters, Carolyn; Conley, Marshall; Alexander, Cynthia

Acadia University is the first "laptop" university in Canada. The Acadia Advantage program has each incoming student and each faculty member equipped with a laptop computer. In addition, classrooms, library, residence rooms, and common areas are wired so that the network is accessible both in and out of classrooms. This initiative has…

Leadership in a Network of Communities: A Phenomenographic Study

ERIC Educational Resources Information Center

MacGillivray, Alice

2010-01-01

Purpose: Canada's Chemical, Biological, Radiological, and Nuclear Research and Technology Initiative (CRTI) uses an operating model that is unusual in government. It is created to enable cross-boundary capability and capacity building and learning. Some consider it a model for other federal science initiatives. The purpose of this paper is to…

Reality Is Our Laboratory: Communities of Practice in Applied Computer Science

ERIC Educational Resources Information Center

Rohde, M.; Klamma, R.; Jarke, M.; Wulf, V.

2007-01-01

The present paper presents a longitudinal study of the course "High-tech Entrepreneurship and New Media." The course design is based on socio-cultural theories of learning and considers the role of social capital in entrepreneurial networks. By integrating student teams into the communities of practice of local start-ups, we offer…

Modelling for Prediction vs. Modelling for Understanding: Commentary on Musso et al. (2013)

ERIC Educational Resources Information Center

Edelsbrunner, Peter; Schneider, Michael

2013-01-01

Musso et al. (2013) predict students' academic achievement with high accuracy one year in advance from cognitive and demographic variables, using artificial neural networks (ANNs). They conclude that ANNs have high potential for theoretical and practical improvements in learning sciences. ANNs are powerful statistical modelling tools but they can…

Second Annual Technology Showcase Fosters Camaraderie and Collaboration | Poster

Cancer.gov

“Collaboration” was the word of the day at the second annual Technology Showcase, held June 13 at the Advanced Technology Research Facility (ATRF). Hundreds of science and business professionals gathered to network and learn about technologies at the National Cancer Institute (NCI) and Frederick National Laboratory that are available for licensing and partnering.

Adding Interactivity to a Non-Interative Class

ERIC Educational Resources Information Center

Rogers, Gary; Krichen, Jack

2004-01-01

The IT 3050 course at Capella University is an introduction to fundamental computer networking. This course is one of the required courses in the Bachelor of Science in Information Technology program. In order to provide a more enriched learning environment for learners, Capella has significantly modified this class (and others) by infusing it…

Schemas in Problem Solving: An Integrated Model of Learning, Memory, and Instruction

DTIC Science & Technology

1992-01-01

reflected in the title of a recent article: "lybid Coupation, in Cognitive Science: Neural Networks ad Symbl (3. A Andesson, 1990). And, Marvin Mtuky...Rumneihart, D. E (1989). Explorations in parallel distributed processing: A handbook of models, programs, and exercises. Cambridge, MA: The MrT Press. Minsky

International Study Tours: A Key to 21st Century Academic and Industry Exchanges

ERIC Educational Resources Information Center

Hol, Ana; Simiana, Danielle; Lieu, Gilbert; Ong, Ivan; Feder, Josh; Dawre, Nimat; Almazi, Wakil

2016-01-01

This paper is based on the retrospective reviews of the Information Systems study group who went on the international study tour to India to learn, network and collaborate with academics, students and industry professionals overseas. The paper addresses concerns of local Australian Science, Technology, Engineering and Mathematics recruiters and…

Promoting Instructional Change: Using Social Network Analysis to Understand the Informal Structure of Academic Departments

ERIC Educational Resources Information Center

Quardokus, Kathleen; Henderson, Charles

2015-01-01

Calls for improvement of undergraduate science education have resulted in numerous initiatives that seek to improve student learning outcomes by promoting changes in faculty teaching practices. Although many of these initiatives focus on individual faculty, researchers consider the academic department to be a highly productive focus for creating…

A storied-identity analysis approach to teacher candidates learning to teach in an urban setting

NASA Astrophysics Data System (ADS)

Ibourk, Amal

While many studies have investigated the relationship between teachers' identity work and their developing practices, few of these identity focused studies have honed in on teacher candidates' learning to teach in an urban setting. Drawing upon narrative inquiry methodology and a "storied identity" analytic framework, I examined how the storied identities of science learning and becoming a science teacher shape teacher candidates' developing practice. In particular, I examined the stories of three interns, Becky, David, and Ashley, and I tell about their own experiences as science learners, their transitions to science teachers, and the implications this has for the identity work they did as they navigated the challenges of learning to teach in high-needs schools. Initially, each of the interns highlighted a feeling of being an outsider, and having a difficult time becoming a fully valued member of their classroom community in their storied identities of becoming a science teacher in the beginning of their internship year. While the interns named specific challenges, such as limited lab materials and different math abilities, I present how they adapted their lesson plans to address these challenges while drawing from their storied identities of science learning. My study reveals that the storied identities of becoming a science teacher informed how they framed their initial experiences teaching in an urban context. In addition, my findings reveal that the more their storied identities of science learning and becoming a science teacher overlapped, the more they leveraged their storied identity of science learning in order to implement teaching strategies that helped them make sense of the challenges that surfaced in their classroom contexts. Both Becky and Ashley leveraged their storied identities of science learning more than David did in their lesson planning and learning to teach. David's initial storied identity of becoming a science teacher revealed how he highlighted his struggle with navigating talkativeness in the class, but also his struggle being an authority figure in his classroom. At present, only Becky and Ashley pursued teaching in a high needs setting. A storied identity analysis provided as well an insight into their storied strategies, or the teaching strategies shaped by the stories the interns told about how they made sense of the challenges they faced in their teaching practice. There were five teaching strategies the interns named that were important in supporting their learning to teach were (1) building relationships with their students, (2) being resourceful and creative when faced with limited lab materials, (3) making science relevant to their students, (4) scaffolding their students in their learning, and (5) having a network of people as resources in helping them be better teachers and helping their students learn. Out of these five teaching strategies, I called those they named and highlighted as helping them teach in ways they valued and that connected back to their storied identity of science learning their storied strategies. Implications for further pushing storied identities as a tool for teacher educators to help pinpoint priorities that surface in teacher candidates' practice are discussed. An insight into the priorities that teacher candidates highlight in their practice as well as the storied strategies they name and use to deal with challenges that surface in their practice has potential in better helping teacher candidates navigate their developing practice.

Science in the community: An ethnographic account of social material transformation

NASA Astrophysics Data System (ADS)

Lee, Stuart Henry

This dissertation is about the learning and use of science at the level of local community. It is an ethnographic account, and its theoretical approach draws on actor-network theory as well as neo-Marxist practice theory and the related notion of situated cognition. This theoretical basis supports a work that focuses on the many heterogeneous transformations that materials and people undergo as science is used to help bring about social and political change in a quasi-rural community. The activities that science becomes involved in, and the hybrid formations as it encounters local issues are stressed. Learning and knowing as outcomes of community action are theorized. The dissertation links four major themes throughout its narrative: scientific literacy, representations, relationships and participatory democracy. These four themes are not treated in isolation. Different facets of their relation to each other are stressed in different chapters, each of which analyze different particular case studies. This dissertation argues for the conception of a local scientific praxis, one that is markedly different than the usual notion of science, yet is necessary for the uptake of scientific information into a community.

Complementary learning systems within the hippocampus: a neural network modelling approach to reconciling episodic memory with statistical learning.

PubMed

Schapiro, Anna C; Turk-Browne, Nicholas B; Botvinick, Matthew M; Norman, Kenneth A

2017-01-05

A growing literature suggests that the hippocampus is critical for the rapid extraction of regularities from the environment. Although this fits with the known role of the hippocampus in rapid learning, it seems at odds with the idea that the hippocampus specializes in memorizing individual episodes. In particular, the Complementary Learning Systems theory argues that there is a computational trade-off between learning the specifics of individual experiences and regularities that hold across those experiences. We asked whether it is possible for the hippocampus to handle both statistical learning and memorization of individual episodes. We exposed a neural network model that instantiates known properties of hippocampal projections and subfields to sequences of items with temporal regularities. We found that the monosynaptic pathway-the pathway connecting entorhinal cortex directly to region CA1-was able to support statistical learning, while the trisynaptic pathway-connecting entorhinal cortex to CA1 through dentate gyrus and CA3-learned individual episodes, with apparent representations of regularities resulting from associative reactivation through recurrence. Thus, in paradigms involving rapid learning, the computational trade-off between learning episodes and regularities may be handled by separate anatomical pathways within the hippocampus itself.This article is part of the themed issue 'New frontiers for statistical learning in the cognitive sciences'. © 2016 The Author(s).

Honeycomb: Visual Analysis of Large Scale Social Networks

NASA Astrophysics Data System (ADS)

van Ham, Frank; Schulz, Hans-Jörg; Dimicco, Joan M.

The rise in the use of social network sites allows us to collect large amounts of user reported data on social structures and analysis of this data could provide useful insights for many of the social sciences. This analysis is typically the domain of Social Network Analysis, and visualization of these structures often proves invaluable in understanding them. However, currently available visual analysis tools are not very well suited to handle the massive scale of this network data, and often resolve to displaying small ego networks or heavily abstracted networks. In this paper, we present Honeycomb, a visualization tool that is able to deal with much larger scale data (with millions of connections), which we illustrate by using a large scale corporate social networking site as an example. Additionally, we introduce a new probability based network metric to guide users to potentially interesting or anomalous patterns and discuss lessons learned during design and implementation.

K-4 Keepers Collection: A Service Learning Teacher Professional Development Program

NASA Astrophysics Data System (ADS)

Schwerin, T. G.; Blaney, L.; Myers, R. J.

2011-12-01

This poster focuses on the K-4 Keepers Collection, a service-learning program developed for the Earth System Science Education Alliance (ESSEA). ESSEA is a NOAA-, NASA- and NSF-supported program of teacher professional development that increases teachers' pedagogical content knowledge of climate-related Earth system science. The ESSEA program -- whether used in formal higher education courses or frequented by individual teachers who look for classroom activities in the environmental sciences -- provides a full suite of activities, lessons and units for teachers' use. The ESSEA network consists of 45 universities and education centers addressing climate and environment issues. K-4 Keepers Collection - ESSEA K-4 module collections focus on five specific themes of content development: spheres, Polar Regions, oceans, climate and service learning. The K-4 Keepers collection provides the opportunity for teachers to explore topics and learning projects promoting stewardship of the Earth's land, water, air and living things. Examination of the impacts of usage and pollution on water, air, land and living things through service-learning projects allows students to become informed stewards. All of the modules include short-term sample projects that either educate or initiate action involving caring for the environment. The K-4 Keepers course requires teachers to develop similar short or long-term projects for implementation in their classrooms. Objectives include: 1. Increase elementary teachers' environmental literacy addressing ocean, coastal, Great Lakes, stewardship, weather and climate science standards and using NOAA and NASA resources. 2. Develop elementary teachers' efficacy in employing service learning projects focused on conserving and preserving Earth's land, air, water and living things. 3. Prepare college faculty to incorporate service learning and environmental literacy into their courses through professional development and modules on the ESSEA website.

The Impact of an Authentic Science Experience on STEM Identity: A Preliminary Analysis of YouthAstroNet and MicroObservatory Telescope Network Participant Data

NASA Astrophysics Data System (ADS)

Dussault, Mary E.; Wright, Erika A.; Sadler, Philip; Sonnert, Gerhard; ITEAMS II Team

2018-01-01

Encouraging students to pursue careers in science, technology, engineering, and mathematics (STEM) is a high priority for national K-12 education improvement initiatives in the United States. Many educators have claimed that a promising strategy for nurturing early student interest in STEM is to engage them in authentic inquiry experiences. “Authentic” refers to investigations in which the questions are of genuine interest and importance to students, and the inquiry more closely resembles the way real science is done. Science education researchers and practitioners at the Harvard-Smithsonian Center for Astrophysics have put this theory into action with the development of YouthAstroNet, a nationwide online learning community of middle-school aged students, educators, and STEM professionals that features the MicroObservatory Robotic Telescope Network, professional image analysis software, and complementary curricula for use in a variety of learning settings. This preliminary study examines factors that influence YouthAstroNet participants' Science Affinity, STEM Identity, and STEM Career Interest, using the matched pre/post survey results of 261 participants as the data source. The pre/post surveys included some 40 items measuring affinity, identity, knowledge, and career interest. In addition, the post intervention instrument included a number of items in which students reported the instructional strategies they experienced as part of the program. A simple analysis of pre-post changes in affinity and interest revealed very little significant change, and for those items where a small pre-post effect was observed, the average change was most often negative. However, after accounting for students' different program treatment experiences and for their prior attitudes and interests, a predictor of significant student gains in Affinity, STEM Identity, Computer/Math Identity, and STEM Career Interest could be identified. This was the degree to which students reported using and experiencing the primary "authentic" learning activities of the YouthAstroNet program.

Planning Mars Memory: Learning from the Mer Mission

NASA Technical Reports Server (NTRS)

Linde, Charlotte

2004-01-01

Knowledge management for space exploration is part of a multi-generational effort at recognizing, preserving and transmitting learning. Each mission should be built on the learning, of both successes and failures, derived from previous missions. Knowledge management begins with learning, and the recognition that this learning has produced knowledge. The Mars Exploration Rover mission provides us with an opportunity to track how learning occurs, how it is recorded, and whether the representations of this learning will be optimally useful for subsequent missions. This paper focuses on the MER science and engineering teams during Rover operations. A NASA team conducted an observational study of the ongoing work and learning of the these teams. Learning occurred in a wide variety of areas: how to run two teams on Mars time for three months; how to use the instruments within the constraints of the martian environment, the deep space network and the mission requirements; how to plan science strategy; how best to use the available software tools. This learning is preserved in many ways. Primarily it resides in peoples memories, to be carried on to the next mission. It is also encoded in stones, in programming sequences, in published reports, and in lessons learned activities, Studying learning and knowledge development as it happens allows us to suggest proactive ways of capturing and using it across multiple missions and generations.

Connected Worlds: Connecting the public with complex environmental systems

NASA Astrophysics Data System (ADS)

Uzzo, S. M.; Chen, R. S.; Downs, R. R.

2016-12-01

Among the most important concepts in environmental science learning is the structure and dynamics of coupled human and natural systems (CHANS). But the fundamental epistemology for understanding CHANS requires systems thinking, interdisciplinarity, and complexity. Although the Next Generation Science Standards mandate connecting ideas across disciplines and systems, traditional approaches to education do not provide more than superficial understanding of this concept. Informal science learning institutions have a key role in bridging gaps between the reductive nature of classroom learning and contemporary data-driven science. The New York Hall of Science, in partnership with Design I/O and Columbia University's Center for International Earth Science Information Network, has developed an approach to immerse visitors in complex human nature interactions and provide opportunities for those of all ages to elicit and notice environmental consequences of their actions. Connected Worlds is a nearly 1,000 m2 immersive, playful environment in which students learn about complexity and interconnectedness in ecosystems and how ecosystems might respond to human intervention. It engages students through direct interactions with fanciful flora and fauna within and among six biomes: desert, rainforest, grassland, mountain valley, reservoir, and wetlands, which are interconnected through stocks and flows of water. Through gestures and the manipulation of a dynamic water system, Connected Worlds enables students, teachers, and parents to experience how the ecosystems of planet Earth are connected and to observe relationships between the behavior of Earth's inhabitants and our shared world. It is also a cyberlearning platform to study how visitors notice and scaffold their understanding of complex environmental processes and the responses of these processes to human intervention, to help inform the improvement of education practices in complex environmental science.

Constructing "Authentic" Science: Results from a University/High School Collaboration Integrating Digital Storytelling and Social Networking

NASA Astrophysics Data System (ADS)

Olitsky, Stacy; Becker, Elizabeth A.; Jayo, Ignacio; Vinogradov, Philip; Montcalmo, Joseph

2018-02-01

This study explores the implications of a redesign of a college course that entailed a new partnership between a college neuroscience classroom and a high school. In this course, the college students engaged in original research projects which included conducting brain surgery and behavioural tests on rats. They used digital storytelling and social networking to communicate with high school students and were visited by the students during the semester. The aims of the redesign were to align the course with science conducted in the field and to provide opportunities to disseminate scientific knowledge through emerging technologies. This study investigates the impact of these innovations on the college and high school students' perceptions of authentic science, including their relationship with science-centred communities. We found that these collaborative tools increased college students' perceptions that authentic science entailed communication with the general public, in addition to supporting prior perceptions of the importance of conducting experiments and presenting results to experts. In addition, the view of science as high-status knowledge was attenuated as students integrated non-formal communication practices into presentations, showing the backstage process of learning, incorporating music and youth discourse styles, and displaying emotional engagement. An impact of these hybrid presentation approaches was an increase in the high school students' perceptions of the accessibility of laboratory science. We discuss how the use of technologies that are familiar to youth, such as iPads, social networking sites, and multimedia presentations, has the potential to prioritize students' voices and promote a more inclusive view of science.

Study on Electro-polymerization Nano-micro Wiring System Imitating Axonal Growth of Artificial Neurons towards Machine Learning

NASA Astrophysics Data System (ADS)

Dang, Nguyen Tuan; Akai-Kasada, Megumi; Asai, Tetsuya; Saito, Akira; Kuwahara, Yuji; Hokkaido University Collaboration

2015-03-01

Machine learning using the artificial neuron network research is supposed to be the best way to understand how the human brain trains itself to process information. In this study, we have successfully developed the programs using supervised machine learning algorithm. However, these supervised learning processes for the neuron network required the very strong computing configuration. Derivation from the necessity of increasing in computing ability and in reduction of power consumption, accelerator circuits become critical. To develop such accelerator circuits using supervised machine learning algorithm, conducting polymer micro/nanowires growing process was realized and applied as a synaptic weigh controller. In this work, high conductivity Polypyrrole (PPy) and Poly (3, 4 - ethylenedioxythiophene) PEDOT wires were potentiostatically grown crosslinking the designated electrodes, which were prefabricated by lithography, when appropriate square wave AC voltage and appropriate frequency were applied. Micro/nanowire growing process emulated the neurotransmitter release process of synapses inside a biological neuron and wire's resistance variation during the growing process was preferred to as the variation of synaptic weigh in machine learning algorithm. In a cooperation with Graduate School of Information Science and Technology, Hokkaido University.

Architecture and biological applications of artificial neural networks: a tuberculosis perspective.

PubMed

Darsey, Jerry A; Griffin, William O; Joginipelli, Sravanthi; Melapu, Venkata Kiran

2015-01-01

Advancement of science and technology has prompted researchers to develop new intelligent systems that can solve a variety of problems such as pattern recognition, prediction, and optimization. The ability of the human brain to learn in a fashion that tolerates noise and error has attracted many researchers and provided the starting point for the development of artificial neural networks: the intelligent systems. Intelligent systems can acclimatize to the environment or data and can maximize the chances of success or improve the efficiency of a search. Due to massive parallelism with large numbers of interconnected processers and their ability to learn from the data, neural networks can solve a variety of challenging computational problems. Neural networks have the ability to derive meaning from complicated and imprecise data; they are used in detecting patterns, and trends that are too complex for humans, or other computer systems. Solutions to the toughest problems will not be found through one narrow specialization; therefore we need to combine interdisciplinary approaches to discover the solutions to a variety of problems. Many researchers in different disciplines such as medicine, bioinformatics, molecular biology, and pharmacology have successfully applied artificial neural networks. This chapter helps the reader in understanding the basics of artificial neural networks, their applications, and methodology; it also outlines the network learning process and architecture. We present a brief outline of the application of neural networks to medical diagnosis, drug discovery, gene identification, and protein structure prediction. We conclude with a summary of the results from our study on tuberculosis data using neural networks, in diagnosing active tuberculosis, and predicting chronic vs. infiltrative forms of tuberculosis.

Youth Science Ambassadors: Connecting Indigenous communities with Ocean Networks Canada tools to inspire future ocean scientists and marine resource managers

NASA Astrophysics Data System (ADS)

Pelz, M.; Hoeberechts, M.; Hale, C.; McLean, M. A.

2017-12-01

This presentation describes Ocean Networks Canada's (ONC) Youth Science Ambassador Program. The Youth Science Ambassadors are a growing network of youth in Canadian coastal communities whose role is to connect ocean science, ONC data, and Indigenous knowledge. By directly employing Indigenous youth in communities in which ONC operates monitoring equipment, ONC aims to encourage wider participation and interest in ocean science and exploration. Further, the Youth Science Ambassadors act as role models and mentors to other local youth by highlighting connections between Indigenous and local knowledge and current marine science efforts. Ocean Networks Canada, an initiative of the University of Victoria, develops, operates, and maintains cabled ocean observatory systems. These include technologies developed on the world-leading NEPTUNE and VENUS observatories as well as community observatories in the Arctic and coastal British Columbia. These observatories, large and small, enable communities, users, scientists, teachers, and students to monitor real-time and historical data from the local marine environment from anywhere on the globe. Youth Science Ambassadors are part of the Learning and Engagement team whose role includes engaging Indigenous communities and schools in ocean science through ONC's K-12 Ocean Sense education program. All of the data collected by ONC are freely available over the Internet for non-profit use, including disaster planning, community-based decision making, and education. The Youth Science Ambassadors support collaboration with Indigenous communities and schools by facilitating educational programming, encouraging participation in ocean data collection and analysis, and fostering interest in ocean science. In addition, the Youth Science Ambassadors support community collaboration in decision-making for instrument deployment locations and identify ways in which ONC can help to address any areas of concern raised by the community. This presentation will share the successes and challenges of the Youth Science Ambassador program in engaging both rural and urban Indigenous communities. We will share activities and experiences, discuss how we have adapted to meet the needs of each community, and outline ideas we have for the future development of the program.

Abstracts for the symposium on the Application of neural networks to the earth sciences

USGS Publications Warehouse

Singer, Donald A.

2002-01-01

Artificial neural networks are a group of mathematical methods that attempt to mimic some of the processes in the human mind. Although the foundations for these ideas were laid as early as 1943 (McCulloch and Pitts, 1943), it wasn't until 1986 (Rumelhart and McClelland, 1986; Masters, 1995) that applications to practical problems became possible. It is the acknowledged superiority of the human mind at recognizing patterns that the artificial neural networks are trying to imitate with their interconnected neurons. Interconnections used in the methods that have been developed allow robust learning. Capabilities of neural networks fall into three kinds of applications: (1) function fitting or prediction, (2) noise reduction or pattern recognition, and (3) classification or placing into types. Because of these capabilities and the powerful abilities of artificial neural networks, there have been increasing applications of these methods in the earth sciences. The abstracts in this document represent excellent samples of the range of applications. Talks associated with the abstracts were presented at the Symposium on the Application of Neural Networks to the Earth Sciences: Seventh International Symposium on Mineral Exploration (ISME–02), held August 20–21, 2002, at NASA Moffett Field, Mountain View, California. This symposium was sponsored by the Mining and Materials Processing Institute of Japan (MMIJ), the U.S. Geological Survey, the Circum-Pacific Council, and NASA. The ISME symposia have been held every two years in order to bring together scientists actively working on diverse quantitative methods applied to the earth sciences. Although the title, International Symposium on Mineral Exploration, suggests exclusive focus on mineral exploration, interests and presentations have always been wide-ranging—abstracts presented here are no exception.

Prioritizing recovery of urban lifelines in the aftermath of hazards: Transportation in post-Harvey Houston

NASA Astrophysics Data System (ADS)

Warner, M. E.; Bhatia, U.; Sela, L.; Wang, R.; Kodra, E.; Ganguly, A. R.

2017-12-01

A well-designed recovery strategy for lifeline infrastructure networks can lead to faster and more reliable restoration of essential services in the aftermath of natural catastrophes such as hurricanes or earthquakes. Urban and regional lifelines impact one another, while the recovery of urban lifelines in turn impacts regional infrastructural resilience, owing to the interdependence of lifelines across scales. Prior work by our team, often in collaboration, has led to the development of new recovery approaches based on network science and engineering, including centrality measures from network science, information theoretic metrics, and network optimization approaches. We have developed proof-of-concept demonstrations at both regional scales, such as for the Indian Railways Network and the US National Airspace System both subjected to multiple hazards, and to urban settings, such as the post-Hurricane recovery of combined power-subway system-of-systems in Boston and the New York City MTA after Hurricane Sandy. Here we make an attempt to understand how such methods may have been, or continue to be, applicable to the transportation network in Houston post-Harvey, and more broadly, how and to what extent lessons learned in urban and regional resilience may generalize across cases. We make an assessment of the state of the literature, process understanding, simulation models, data science methods, and best practices, necessary to address problems of this nature, with a particular focus on post-Harvey recovery of transportation services in Houston.

Comparative Studies of Prediction Strategies for Solar X-ray Time Series

NASA Astrophysics Data System (ADS)

Muranushi, T.; Hattori, T.; Jin, Q.; Hishinuma, T.; Tominaga, M.; Nakagawa, K.; Fujiwara, Y.; Nakamura, T.; Sakaue, T.; Takahashi, T.; Seki, D.; Namekata, K.; Tei, A.; Ban, M.; Kawamura, A. D.; Hada-Muranushi, Y.; Asai, A.; Nemoto, S.; Shibata, K.

2016-12-01

Crucial virtues for operational space weather forecast are real-timeforecast ability, forecast precision and customizability to userneeds. The recent development of deep-learning makes it veryattractive to space weather, because (1) it learns gradually incomingdata, (2) it exhibits superior accuracy over conventional algorithmsin many fields, and (3) it makes the customization of the forecasteasier because it accepts raw images.However, the best deep-learning applications are only attainable bycareful human designers that understands both the mechanism of deeplearning and the application field. Therefore, we need to foster youngresearchers to enter the field of machine-learning aided forecast. So,we have held a seminar every Monday with undergraduate and graduatestudents from May to August 2016.We will review the current status of space weather science and theautomated real-time space weather forecast engine UFCORIN. Then, weintroduce the deep-learning space weather forecast environments wehave set up using Python and Chainer on students' laptop computers.We have started from simple image classification neural network, thenimplemented space-weather neural network that predicts future X-rayflux of the Sun based on the past X-ray lightcurve and magnetic fieldline-of-sight images.In order to perform each forecast faster, we have focused on simplelightcurve-to-lightcurve forecast, and performed comparative surveysby changing following parameters: The size and topology of the neural network Batchsize Neural network hyperparameters such as learning rates to optimize the preduction accuracy, and time for prediction.We have found how to design compact, fast but accurate neural networkto perform forecast. Our forecasters can perform predictionexperiment for four-year timespan in a few minutes, and achieveslog-scale errors of the order of 1. Our studies is ongoing, and inour talk we will review our progress till December.

Astronomical Network for Teachers in Thailand

NASA Astrophysics Data System (ADS)

Kramer Hutawarakorn, Busaba; Soonthornthum, Boonraksar; Poshyachinda, Saran

We report the latest development of a pilot project in establishing the astronomical network for teachers in Thailand. The project has been recently granted by the Institute for the Promotion of Teaching Science and Technology Thailand and operated by Sirindhorn Observatory Chiangmai University. The objectives of the project are (1) to establish a16-inch semi-robotic telescope which can be accessed from schools nationwide; and (2) to establish an educational website in Thai language which contains electronic textbook of astronomy online encyclopedia of astronomy observing projects astronomical database and links to other educational websites worldwide. The network will play important role in the development of teaching and learning astronomy in Thailand.

A deep learning framework for causal shape transformation.

PubMed

Lore, Kin Gwn; Stoecklein, Daniel; Davies, Michael; Ganapathysubramanian, Baskar; Sarkar, Soumik

2018-02-01

Recurrent neural network (RNN) and Long Short-term Memory (LSTM) networks are the common go-to architecture for exploiting sequential information where the output is dependent on a sequence of inputs. However, in most considered problems, the dependencies typically lie in the latent domain which may not be suitable for applications involving the prediction of a step-wise transformation sequence that is dependent on the previous states only in the visible domain with a known terminal state. We propose a hybrid architecture of convolution neural networks (CNN) and stacked autoencoders (SAE) to learn a sequence of causal actions that nonlinearly transform an input visual pattern or distribution into a target visual pattern or distribution with the same support and demonstrated its practicality in a real-world engineering problem involving the physics of fluids. We solved a high-dimensional one-to-many inverse mapping problem concerning microfluidic flow sculpting, where the use of deep learning methods as an inverse map is very seldom explored. This work serves as a fruitful use-case to applied scientists and engineers in how deep learning can be beneficial as a solution for high-dimensional physical problems, and potentially opening doors to impactful advance in fields such as material sciences and medical biology where multistep topological transformations is a key element. Copyright © 2017 Elsevier Ltd. All rights reserved.

Characteristics of High School Students' and Science Teachers' Cognitive Frame about Effective Teaching Method for High School Science Subject

NASA Astrophysics Data System (ADS)

Chung, Duk Ho; Park, Kyeong-Jin; Cho, Kyu Seong

2016-04-01

We investigated the cognitive frame of high school students and inservice high school science teachers about effective teaching method, and we also explored how they understood about the teaching methods suggested by the 2009 revised Science Curriculum. Data were collected from 275 high school science teachers and 275 high school students. We analyzed data in terms of the words and the cognitive frame using the Semantic Network Analysis. The results were as follows. First, the teachers perceived that an activity oriented class was the effective science class that helped improve students'' problem-solving abilities and their inquiry skills. The students had the cognitive frame that their teacher had to present relevant and enough teaching materials to students, and that they should also receive assistance from teachers in science class to better prepare for college entrance exam. Second, both students and teachers retained the cognitive frame about the efficient science class that was not reflected 2009 revised Science Curriculum exactly. Especially, neither groups connected the elements of ''convergence'' as well as ''integration'' embedded across science subject areas to their cognitive frame nor cognized the fact that many science learning contents were closed related to one another. Therefore, various professional development opportunities should be offered so that teachers succinctly comprehend the essential features and the intents of the 2009 revised Science Curriculum and thereby implement it in their science lessons effectively. Keywords : semantic network analysis, cognitive frame, teaching method, science lesson

Deep learning for single-molecule science

NASA Astrophysics Data System (ADS)

Albrecht, Tim; Slabaugh, Gregory; Alonso, Eduardo; Al-Arif, SM Masudur R.

2017-10-01

Exploring and making predictions based on single-molecule data can be challenging, not only due to the sheer size of the datasets, but also because a priori knowledge about the signal characteristics is typically limited and poor signal-to-noise ratio. For example, hypothesis-driven data exploration, informed by an expectation of the signal characteristics, can lead to interpretation bias or loss of information. Equally, even when the different data categories are known, e.g., the four bases in DNA sequencing, it is often difficult to know how to make best use of the available information content. The latest developments in machine learning (ML), so-called deep learning (DL) offer interesting, new avenues to address such challenges. In some applications, such as speech and image recognition, DL has been able to outperform conventional ML strategies and even human performance. However, to date DL has not been applied much in single-molecule science, presumably in part because relatively little is known about the ‘internal workings’ of such DL tools within single-molecule science as a field. In this Tutorial, we make an attempt to illustrate in a step-by-step guide how one of those, a convolutional neural network (CNN), may be used for base calling in DNA sequencing applications. We compare it with a SVM as a more conventional ML method, and discuss some of the strengths and weaknesses of the approach. In particular, a ‘deep’ neural network has many features of a ‘black box’, which has important implications on how we look at and interpret data.

Outcomes of a Self-Regulated Learning Curriculum Model

NASA Astrophysics Data System (ADS)

Peters-Burton, Erin E.

2015-10-01

The purpose of this study was to describe connections among students' views of nature of science in relation to the goals of a curriculum delivered in a unique setting, one where a researcher and two teachers collaborated to develop a course devoted to teaching students about how knowledge is built in science. Students proceeded through a cycle of self-regulated phases, forethought, performance, and self-reflection, during each segment of the curriculum: (a) independent research, (b) knowledge building in the discipline of science, and (c) a citizen science project. Student views were measured at the beginning and end of the course using epistemic network analysis. The pretest map reported student understanding of science as experimentation and indicated three clusters representing the durability of knowledge, empirical evidence, and habits of mind, which were loosely connected and represented knowledge generation as external to personal thinking. The posttest map displayed a broader understanding of scientific endeavors beyond experimentation, a shift toward personal knowledge generation, and indicated a larger number of connections among three more tightly oriented clusters: empirical evidence, habits of mind, and tentativeness. Implications include the potential to build curriculum that purposefully considers reinforcing cycles of learning of the nature of science in different contexts.

Quality resource networks for young women in science: The role of Internet-facilitated ties

NASA Astrophysics Data System (ADS)

Gillette, Shana Cecile

In communications, a new approach to the study of online interaction has been suggested by social network analysts. Garton, Haythornthwaite, and Wellman (1997) have outlined the importance of using network analysis to study how media are interconnected with other social aspects of a media user's world. As applied here, this approach to communication when combined with recent network studies from the fields of education and rural development, provides a method for looking at the role of Internet-facilitated ties in the development of resource networks in the learning communities of young women from seven rural schools across the state of Washington. Twenty-six young women (ages 14-16) from diverse cultural and ethnic backgrounds (approximately half of the participants are Hispanic or Native American, the other half are White) participated in the research. Participants were selected because they shared a common educational orientation through Rural Girls in Science, a NSF-funded program at the Northwest Center for Research on Women at the University of Washington. As part of the school-based component of the Rural Girls in Science program, all 26 participants designed and conducted year-long, community-based research projects in science. Each school in the program was provided an Internet workstation for communication and research. Through the Internet, students could conceivably maintain distant ties with mentors and research scientists whom they met at summer camp as well as seek additional information resources. Toward the conclusion of the long-term research projects, each student participant was interviewed using a participatory form of network analysis that included a combined qualitative and quantitative approach. Given the small number of participants and schools in the sample, the results from the analysis can not be generalized to a larger population. However the study of the structure and composition of networks among individuals and school groups provided insight into how media are implicated in the development of resource networks, in particular for a subset of students who have been underrepresented in science--young ethnic minority women.

Scaffolding scientific discussion using socially relevant representations in networked multimedia

NASA Astrophysics Data System (ADS)

Hoadley, Christopher M.

1999-11-01

How do students make use of social cues when learning on the computer? This work examines how students in a middle-school science course learned through on-line peer discussion. Cognitive accounts of collaboration stress interacting with ideas, while socially situated accounts stress the interpersonal context. The design of electronic environments allows investigation into the interrelation of cognitive and social dimensions. I use on-line peer discussion to investigate how socially relevant representations in interfaces can aid learning. First, I identify some of the variables that affect individual participation in on-line discussion, including interface features. Individual participation is predicted by student attitudes towards learning from peers. Second, I describe the range of group outcomes for these on-line discussions. There is a large effect of discussion group on learning outcomes which is not reducible to group composition or gross measures of group process. Third, I characterize how students (individually) construct understanding from these group discussions. Learning in the on-line discussions is shown to be a result of sustained interaction over time, not merely encountering or expressing ideas. Experimental manipulations in the types of social cues available to students suggest that many students do use socially relevant representations to support their understanding of multiple viewpoints and science reasoning. Personalizing scientific disputes can afford reflection on the nature of scientific discovery and advance. While there are many individual differences in how social representations are used by students in learning, overall learning benefits for certain social representations can be shown. This work has profound implications for design of collaborative instructional methods, equitable access to science learning, design of instructional technology, and understanding of learning and cognition in social settings.

Online and in-person networking among women in the Earth Sciences Women's Network at www.ESWNonline.org

NASA Astrophysics Data System (ADS)

Kontak, R.; Adams, A. S.; De Boer, A. M.; Hastings, M. G.; Holloway, T.; Marin-Spiotta, E.; Steiner, A. L.; Wiedinmyer, C.

2012-12-01

The Earth Science Women's Network is an international peer-mentoring network of women in the Earth Sciences, many of whom are in the early stages of their careers. Membership is free and has grown through "word of mouth," and includes upper-level undergraduates, graduate students, professionals in a range of environmental fields, scientists working in public and private institutions. Our mission is to promote career development, build community, provide informal mentoring and support, and facilitate professional collaborations. Since 2002 we have accomplished this trough online networking, including over email and a listserv, on facebook, in-person networking events, and professional development workshops. Now in our 10th year, ESWN is debuting a new web-center that creates an online space exclusively for women in any discipline of the Earth (including planetary) sciences. ESWN members can connect and create an online community of support and encouragement for themselves as women in a demanding career. Many women in Earth Science fields feel isolated and are often the only woman in their department or work environments. ESWN is a place to meet others, discuss issues faced in creating work-life balance and professional success and share best practices through peer mentoring. Now on ESWN's new web-center, members can create and personalize their profiles and search for others in their field, nearby, or with similar interests. Online discussions in the members-only area can also be searched. Members can create groups for discussion or collaboration, with document sharing and password protection. Publicly, we can share gained knowledge with a broader audience, like lessons learned at our professional development workshops and collected recommendations from members. The new web center allows for more connectivity among other online platforms used by our members, including linked-in, facebook, and twitter. Built in Wordpress with a Buddpress members-only section, the new ESWN website is supported by AGU and a NSF ADVANCE grant.;

Climate Voices: Bridging Scientist Citizens and Local Communities across the United States

NASA Astrophysics Data System (ADS)

Wegner, K.; Ristvey, J. D., Jr.

2016-12-01

Based out of the University Corporation for Atmospheric Research (UCAR), the Climate Voices Science Speakers Network (climatevoices.org) has more than 400 participants across the United States that volunteer their time as scientist citizens in their local communities. Climate Voices experts engage in nonpartisan conversations about the local impacts of climate change with groups such as Rotary clubs, collaborate with faith-based groups on climate action initiatives, and disseminate their research findings to K-12 teachers and classrooms through webinars. To support their participants, Climate Voices develops partnerships with networks of community groups, provides trainings on how to engage these communities, and actively seeks community feedback. In this presentation, we will share case studies of science-community collaborations, including meta-analyses of collaborations and lessons learned.

Pencil-and-Paper Neural Networks: An Undergraduate Laboratory Exercise in Computational Neuroscience

PubMed Central

Crisp, Kevin M.; Sutter, Ellen N.; Westerberg, Jacob A.

2015-01-01

Although it has been more than 70 years since McCulloch and Pitts published their seminal work on artificial neural networks, such models remain primarily in the domain of computer science departments in undergraduate education. This is unfortunate, as simple network models offer undergraduate students a much-needed bridge between cellular neurobiology and processes governing thought and behavior. Here, we present a very simple laboratory exercise in which students constructed, trained and tested artificial neural networks by hand on paper. They explored a variety of concepts, including pattern recognition, pattern completion, noise elimination and stimulus ambiguity. Learning gains were evident in changes in the use of language when writing about information processing in the brain. PMID:26557791

Building effective learning experiences around visualizations: NASA Eyes on the Solar System and Infiniscope

NASA Astrophysics Data System (ADS)

Tamer, A. J. J.; Anbar, A. D.; Elkins-Tanton, L. T.; Klug Boonstra, S.; Mead, C.; Swann, J. L.; Hunsley, D.

2017-12-01

Advances in scientific visualization and public access to data have transformed science outreach and communication, but have yet to realize their potential impacts in the realm of education. Computer-based learning is a clear bridge between visualization and education, but creating high-quality learning experiences that leverage existing visualizations requires close partnerships among scientists, technologists, and educators. The Infiniscope project is working to foster such partnerships in order to produce exploration-driven learning experiences around NASA SMD data and images, leveraging the principles of ETX (Education Through eXploration). The visualizations inspire curiosity, while the learning design promotes improved reasoning skills and increases understanding of space science concepts. Infiniscope includes both a web portal to host these digital learning experiences, as well as a teaching network of educators using and modifying these experiences. Our initial efforts to enable student discovery through active exploration of the concepts associated with Small Worlds, Kepler's Laws, and Exoplanets led us to develop our own visualizations at Arizona State University. Other projects focused on Astrobiology and Mars geology led us to incorporate an immersive Virtual Field Trip platform into the Infiniscope portal in support of virtual exploration of scientifically significant locations. Looking to apply ETX design practices with other visualizations, our team at Arizona State partnered with the Jet Propulsion Lab to integrate the web-based version of NASA Eyes on the Eclipse within Smart Sparrow's digital learning platform in a proof-of-concept focused on the 2017 Eclipse. This goes a step beyond the standard features of "Eyes" by wrapping guided exploration, focused on a specific learning goal into standards-aligned lesson built around the visualization, as well as its distribution through Infiniscope and it's digital teaching network. Experience from this development effort has laid the groundwork to explore future integrations with JPL and other NASA partners.

Detecting causality in policy diffusion processes.

PubMed

Grabow, Carsten; Macinko, James; Silver, Diana; Porfiri, Maurizio

2016-08-01

A universal question in network science entails learning about the topology of interaction from collective dynamics. Here, we address this question by examining diffusion of laws across US states. We propose two complementary techniques to unravel determinants of this diffusion process: information-theoretic union transfer entropy and event synchronization. In order to systematically investigate their performance on law activity data, we establish a new stochastic model to generate synthetic law activity data based on plausible networks of interactions. Through extensive parametric studies, we demonstrate the ability of these methods to reconstruct networks, varying in size, link density, and degree heterogeneity. Our results suggest that union transfer entropy should be preferred for slowly varying processes, which may be associated with policies attending to specific local problems that occur only rarely or with policies facing high levels of opposition. In contrast, event synchronization is effective for faster enactment rates, which may be related to policies involving Federal mandates or incentives. This study puts forward a data-driven toolbox to explain the determinants of legal activity applicable to political science, across dynamical systems, information theory, and complex networks.

Detecting causality in policy diffusion processes

NASA Astrophysics Data System (ADS)

Grabow, Carsten; Macinko, James; Silver, Diana; Porfiri, Maurizio

2016-08-01

A universal question in network science entails learning about the topology of interaction from collective dynamics. Here, we address this question by examining diffusion of laws across US states. We propose two complementary techniques to unravel determinants of this diffusion process: information-theoretic union transfer entropy and event synchronization. In order to systematically investigate their performance on law activity data, we establish a new stochastic model to generate synthetic law activity data based on plausible networks of interactions. Through extensive parametric studies, we demonstrate the ability of these methods to reconstruct networks, varying in size, link density, and degree heterogeneity. Our results suggest that union transfer entropy should be preferred for slowly varying processes, which may be associated with policies attending to specific local problems that occur only rarely or with policies facing high levels of opposition. In contrast, event synchronization is effective for faster enactment rates, which may be related to policies involving Federal mandates or incentives. This study puts forward a data-driven toolbox to explain the determinants of legal activity applicable to political science, across dynamical systems, information theory, and complex networks.

Birth of an abstraction: a dynamical systems account of the discovery of an elsewhere principle in a category learning task.

PubMed

Tabor, Whitney; Cho, Pyeong W; Dankowicz, Harry

2013-01-01

Human participants and recurrent ("connectionist") neural networks were both trained on a categorization system abstractly similar to natural language systems involving irregular ("strong") classes and a default class. Both the humans and the networks exhibited staged learning and a generalization pattern reminiscent of the Elsewhere Condition (Kiparsky, 1973). Previous connectionist accounts of related phenomena have often been vague about the nature of the networks' encoding systems. We analyzed our network using dynamical systems theory, revealing topological and geometric properties that can be directly compared with the mechanisms of non-connectionist, rule-based accounts. The results reveal that the networks "contain" structures related to mechanisms posited by rule-based models, partly vindicating the insights of these models. On the other hand, they support the one mechanism (OM), as opposed to the more than one mechanism (MOM), view of symbolic abstraction by showing how the appearance of MOM behavior can arise emergently from one underlying set of principles. The key new contribution of this study is to show that dynamical systems theory can allow us to explicitly characterize the relationship between the two perspectives in implemented models. © 2013 Cognitive Science Society, Inc.

Implementing Role-Changing Versus Time-Changing Innovations in Health Care: Differences in Helpfulness of Staff Improvement Teams, Management, and Network for Learning.

PubMed

Nembhard, Ingrid M; Morrow, Christopher T; Bradley, Elizabeth H

2015-12-01

Health care organizations often fail in their effort to implement care-improving innovations. This article differentiates role-changing innovations, altering what workers do, from time-changing innovations, altering when tasks are performed or for how long. We examine our hypothesis that the degree to which access to groups that can alter organizational learning--staff, management, and external network--facilitates implementation depends on innovation type. Our longitudinal study using ordinal logistic regression and survey data on 517 hospitals' implementation of evidence-based practices for treating heart attack confirmed our thesis for factors granting access to each group: improvement team's representativeness (of affected staff), senior management engagement, and network membership. Although team representativeness and network membership were positively associated with implementing role-changing practices, senior management engagement was not. In contrast, senior management engagement was positively associated with implementing time-changing practices, whereas team representativeness was not, and network membership was not unless there was limited management engagement. These findings advance implementation science by explaining mixed results across past studies: Nature of change for workers alters potential facilitators' effects on implementation. © The Author(s) 2015.

Network Analysis of Beliefs About the Scientific Enterprise: A comparison of scientists, middle school science teachers and eighth-grade science students

NASA Astrophysics Data System (ADS)

Peters-Burton, Erin; Baynard, Liz R.

2013-11-01

An understanding of the scientific enterprise is useful because citizens need to make systematic, rational decisions about projects involving scientific endeavors and technology, and a clearer understanding of scientific epistemology is beneficial because it could encourage more public engagement with science. The purpose of this study was to capture beliefs for three groups, scientists, secondary science teachers, and eighth-grade science students, about the ways scientific knowledge is generated and validated. Open-ended questions were framed by formal scientific epistemology and dimensions of epistemology recognized in the field of educational psychology. The resulting statements were placed in a card sort and mapped in a network analysis to communicate interconnections among ideas. Maps analyzed with multidimensional scaling revealed robust connections among students and scientists but not among teachers. Student and teacher maps illustrated the strongest connections among ideas about experiments while scientist maps present more descriptive and well-rounded ideas about the scientific enterprise. The students' map was robust in terms of numbers of ideas, but were lacking in a hierarchical organization of ideas. The teachers' map displayed an alignment with the learning standards of the state, but not a broader view of science. The scientists map displayed a hierarchy of ideas with elaboration of equally valued statements connected to several foundational statements. Network analysis can be helpful in forwarding the study of views of the nature of science because of the technique's ability to capture verbatim statements from participants and to display the strength of connections among the statements.

A Community-Building Framework for Collaborative Research Coordination across the Education and Biology Research Disciplines.

PubMed

Pelaez, Nancy; Anderson, Trevor R; Gardner, Stephanie M; Yin, Yue; Abraham, Joel K; Bartlett, Edward L; Gormally, Cara; Hurney, Carol A; Long, Tammy M; Newman, Dina L; Sirum, Karen; Stevens, Michael T

2018-06-01

Since 2009, the U.S. National Science Foundation Directorate for Biological Sciences has funded Research Coordination Networks (RCN) aimed at collaborative efforts to improve participation, learning, and assessment in undergraduate biology education (UBE). RCN-UBE projects focus on coordination and communication among scientists and educators who are fostering improved and innovative approaches to biology education. When faculty members collaborate with the overarching goal of advancing undergraduate biology education, there is a need to optimize collaboration between participants in order to deeply integrate the knowledge across disciplinary boundaries. In this essay we propose a novel guiding framework for bringing colleagues together to advance knowledge and its integration across disciplines, the "Five 'C's' of Collaboration: Commitment, Collegiality, Communication, Consensus, and Continuity." This guiding framework for professional network practice is informed by both relevant literature and empirical evidence from community-building experience within the RCN-UBE Advancing Competencies in Experimentation-Biology (ACE-Bio) Network. The framework is presented with practical examples to illustrate how it might be used to enhance collaboration between new and existing participants in the ACE-Bio Network as well as within other interdisciplinary networks.

The Development of Pre-Service Science Teachers' Professional Knowledge in Utilizing ICT to Support Professional Lives

ERIC Educational Resources Information Center

Arnold, Savittree Rochanasmita; Padilla, Michael J.; Tunhikorn, Bupphachart

2009-01-01

In the rapidly developing digital world, technology is and will be a force in workplaces, communities, and everyday lives in the 21st century. Information and Communication Technology (ICT) including computer hardware/software, networking and other technologies such as audio, video, and other multimedia tools became learning tools for students in…

Using Facebook Groups to Encourage Science Discussions in a Large-Enrollment Biology Class

ERIC Educational Resources Information Center

Pai, Aditi; McGinnis, Gene; Bryant, Dana; Cole, Megan; Kovacs, Jennifer; Stovall, Kyndra; Lee, Mark

2017-01-01

This case study reports the instructional development, impact, and lessons learned regarding the use of Facebook as an educational tool within a large enrollment Biology class at Spelman College (Atlanta, GA). We describe the use of this social networking site to (a) engage students in active scientific discussions, (b) build community within the…

Enhancing the Internationalisation of Distance Education in the Biological Sciences: The DUNE Project and Genetic Engineering.

ERIC Educational Resources Information Center

Leach, C. K.; And Others

1997-01-01

Describes the Distance Educational Network of Europe (DUNE) project that aims at enhancing the development of distance education in an international context. Highlights issues relating to the delivery of distance-learning courses in a transnational forum. Describes the genetic engineering course that aims at explaining the core techniques of…

Teaching Energy as Part of Education for Sustainability

ERIC Educational Resources Information Center

Tas, Maarten; McKeon, Frankie; Charnley, Fiona; Fleming, Margaret

2014-01-01

This article describes how energy issues and education for sustainable development (ESD) are part of the agenda for two current European projects, CoDeS and SUSTAIN. The latter is mainly concerned with the development of inquiry-based primary and lower secondary science education while the former is a network that aims to learn more about…

Towards Meaningful Learning through Digital Video Supported, Case Based Teaching

ERIC Educational Resources Information Center

Hakkarainen, Paivi; Saarelainen, Tarja; Ruokamo, Heli

2007-01-01

This paper reports an action research case study in which a traditional lecture based, face to face "Network Management" course at the University of Lapland's Faculty of Social Sciences was developed into two different course versions resorting to case based teaching: a face to face version and an online version. In the face to face…

Nature's Notebook and Extension: Engaging Citizen-Scientists and 4-H Youth to Observe a Changing Environment

ERIC Educational Resources Information Center

Posthumus, Erin E.; Barnett, LoriAnne; Crimmins, Theresa M.; Kish, George R.; Sheftall, Will; Stancioff, Esperanza; Warren, Peter

2013-01-01

Extension, with its access to long-term volunteers, has the unique ability to teach citizen scientists about the connection between climate variability and the resulting effects on plants, animals, and thus, humans. The USA National Phenology Network's Nature's Notebook on-line program provides a science learning tool for Extension's Master…

What Can Graph Theory Tell Us about Word Learning and Lexical Retrieval?

ERIC Educational Resources Information Center

Vitevitch, Michael S.

2008-01-01

Purpose: Graph theory and the new science of networks provide a mathematically rigorous approach to examine the development and organization of complex systems. These tools were applied to the mental lexicon to examine the organization of words in the lexicon and to explore how that structure might influence the acquisition and retrieval of…

Reimagining the Role of School Libraries in STEM Education: Creating Hybrid Spaces for Exploration

ERIC Educational Resources Information Center

Subramaniam, Mega M.; Ahn, June; Fleischmann, Kenneth R.; Druin, Allison

2012-01-01

In recent years, many technological interventions have surfaced, such as virtual worlds, games, and digital labs, that aspire to link young people's interest in media technology and social networks to learning about science, technology, engineering, and math (STEM) areas. Despite the tremendous interest surrounding young people and STEM education,…

Developing an NGSS Pedagogy for Climate Literacy and Energy Awareness Using the CLEAN Collection

NASA Astrophysics Data System (ADS)

Manning, C. L. B.; Taylor, J.; Oonk, D.; Sullivan, S. M.; Kirk, K.; Niepold, F., III

2017-12-01

The Next Generation Science Standards and A Framework for K-12 Science Education have introduced us to 3-dimensional science instruction. Together, these provide infinite opportunities to generate interesting problems inspiring instruction and motivating student learning. Finding good resources to support 3-dimensional learning is challenging. The Climate Literacy and Energy Awareness Network (CLEAN) as a comprehensive source of high-quality, NGSS-aligned resources that can be quickly and easily searched. Furthermore, teachers new to NGSS are asked to do the following: synthesize high quality, scientifically vetted resources to engage students in relevant phenomena, problems and projects develop place-awareness for where students live and learn encourage data analysis, modeling, and argumentation skills energize students to participate in finding possible solutions to the problems we face. These challenges are intensified when teaching climate science and energy technology, some of the most rapidly changing science and engineering fields. Educators can turn to CLEAN to find scientifically and pedagogically vetted resources to integrate into their lessons. In this presentation, we will introduce the newly developed Harmonics Planning Template, Guidance Videos and Flowchart that guide the development of instructionally-sound, NGSS-style units using the CLEAN collection of resources. To illustrate the process, three example units will be presented: Phenology - a place-based investigation, Debating the Grid - a deliberation on optimal energy grid solutions, and History of Earth's Atmosphere and Oceans - a data-rich collaborative investigation.

Learning Effectiveness of the NASA Digital Learning Network

NASA Technical Reports Server (NTRS)

Hix, Billy

2005-01-01

Student participation in actual investigations which develop inquiry and intellectual skills has long been regarded as an essential component of science instructions (Schwab, 1962; White, 1999). Such investigations give students an opportunity to appreciate the spirit of science and promote an understanding of the nature of science. However, classroom research conducted over the past 20 years describes science teaching as primarily teacher centered. Typical instruction consists of whole class, noninteractive activities in which individual seatwork has constituted the bulk of classroom interactions (Tobin and Gallagher, 1997). Students typically learn science from textbooks and lectures. Their main motivation is to do reasonably well on tests and examinations (Layman, 1999). During the past five years, infrastructure constraints have reduced to the point that many schools systems can now afford low cost, high quality video conferencing equipment (International Society for Technology in Education, 2003). This study investigates the use of interactive video conferencing vs. face to face interaction with hands-on, inquiry based activities. Some basic questions to be addressed are: How does the delivery method impact the students understanding of the goals of the experiment? Are students explanation of the strategies of experimentation different based on the method of instruction that was provided. Do students engaged in a workshop with the instructor in the room vs. an instructor over video conferencing have different perception of the understanding of the subject materials?

Art in Science Promoting Interest in Research and Exploration (ASPIRE)

NASA Astrophysics Data System (ADS)

Fillingim, M.; Zevin, D.; Thrall, L.; Croft, S.; Raftery, C.; Shackelford, R.

2015-11-01

Led by U.C. Berkeley's Center for Science Education at the Space Sciences Laboratory in partnership with U.C. Berkeley Astronomy, the Lawrence Hall of Science, and the YMCA of the Central Bay Area, Art in Science Promoting Interest in Research and Exploration (ASPIRE) is a NASA EPOESS-funded program mainly for high school students that explores NASA science through art and highlights the need for and uses of art and visualizations in science. ASPIRE's aim is to motivate more diverse young people (especially African Americans) to learn about Science, Technology, Engineering, and Mathematics (STEM) topics and careers, via 1) Intensive summer workshops; 2) Drop-in after school workshops; 3) Astronomy visualization-focused outreach programming at public venues including a series of free star parties where the students help run the events; and 5) A website and a number of social networking strategies that highlight our youth's artwork.

International Observe the Moon Night: A Worldwide Public Observing Event that Annually Engages Scientists, Educators, and Citizen Enthusiasts in NASA Science

NASA Astrophysics Data System (ADS)

Buxner, S.; Jones, A. P.; Bleacher, L.; Wasser, M. L.; Day, B. H.; Shaner, A. J.; Bakerman, M. N.; Joseph, E.

2017-12-01

International Observe the Moon Night (InOMN) is an annual worldwide event, held in the fall, that celebrates lunar and planetary science and exploration. InOMN is sponsored by NASA's Lunar Reconnaissance Orbiter (LRO) in collaboration with NASA's Solar System Exploration Research Virtual Institute (SSERVI), the NASA's Heliophysics Education Consortium, CosmoQuest, Night Sky Network, and Science Festival Alliance. Other key partners include the NASA Museum Alliance, Night Sky Network, and NASA Solar System Ambassadors. In 2017, InOMN will bring together thousands of people across the globe to observe and learn about the Moon and its connection to planetary science. We are partnering with the NASA Science Mission Directorate total solar eclipse team to highlight InOMN as an opportunity to harness and sustain the interest and momentum in space science and observation following the August 21st eclipse. This is part of a new partnership with the Sun-Earth Day team, through the Heliophysics Education Consortium, to better connect the two largest NASA-sponsored public engagement events, increase participation in both events, and share best practices in implementation and evaluation between the teams. Over 3,800 InOMN events have been registered between 2010 and 2016, engaging over 550,000 visitors worldwide. Most InOMN events are held in the United States, with strong representation from many other countries. InOMN events are evaluated to determine the value of the events and to allow us to improve the experience for event hosts and visitors. Our results show that InOMN events are hosted by scientists, educators, and citizen enthusiasts around the world who leverage InOMN to bring communities together, get visitors excited and learn about the Moon - and beyond, and share resources to extend engagement in lunar and planetary science and observation. Through InOMN, we annually provide resources such as event-specific Moon maps, presentations, advertising materials, and certificates of participation. Additionally, InOMN highlights partner resources such as online interfaces including Moon Trek (https://moontrek.jpl.nasa.gov) and CosmoQuest (https://cosmoquest.org/x/) to provide further opportunities to engage with NASA science. Learn more about InOMN at http://observethemoonnight.org.

Learning from Massive Distributed Data Sets (Invited)

NASA Astrophysics Data System (ADS)

Kang, E. L.; Braverman, A. J.

2013-12-01

Technologies for remote sensing and ever-expanding computer experiments in climate science are generating massive data sets. Meanwhile, it has been common in all areas of large-scale science to have these 'big data' distributed over multiple different physical locations, and moving large amounts of data can be impractical. In this talk, we will discuss efficient ways for us to summarize and learn from distributed data. We formulate a graphical model to mimic the main characteristics of a distributed-data network, including the size of the data sets and speed of moving data. With this nominal model, we investigate the trade off between prediction accurate and cost of data movement, theoretically and through simulation experiments. We will also discuss new implementations of spatial and spatio-temporal statistical methods optimized for distributed data.

NASA's Universe of Learning: Engaging Learners in Discovery

NASA Astrophysics Data System (ADS)

Cominsky, L.; Smith, D. A.; Lestition, K.; Greene, M.; Squires, G.

2016-12-01

NASA's Universe of Learning is one of 27 competitively awarded education programs selected by NASA's Science Mission Directorate (SMD) to enable scientists and engineers to more effectively engage with learners of all ages. The NASA's Universe of Learning program is created through a partnership between the Space Telescope Science Institute, Chandra X-ray Center, IPAC at Caltech, Jet Propulsion Laboratory Exoplanet Exploration Program, and Sonoma State University. The program will connect the scientists, engineers, science, technology and adventure of NASA Astrophysics with audience needs, proven infrastructure, and a network of over 500 partners to advance the objectives of SMD's newly restructured education program. The multi-institutional team will develop and deliver a unified, consolidated suite of education products, programs, and professional development offerings that spans the full spectrum of NASA Astrophysics, including the Exoplanet Exploration theme. Program elements include enabling educational use of Astrophysics mission data and offering participatory experiences; creating multimedia and immersive experiences; designing exhibits and community programs; providing professional development for pre-service educators, undergraduate instructors, and informal educators; and, producing resources for special needs and underserved/underrepresented audiences. This presentation will provide an overview of the program and process for mapping discoveries to products and programs for informal, lifelong, and self-directed learning environments.

Community, Collective or Movement? Evaluating Theoretical Perspectives on Network Building

NASA Astrophysics Data System (ADS)

Spitzer, W.

2015-12-01

Since 2007, the New England Aquarium has led a national effort to increase the capacity of informal science venues to effectively communicate about climate change. We are now leading the NSF-funded National Network for Ocean and Climate Change Interpretation (NNOCCI), partnering with the Association of Zoos and Aquariums, FrameWorks Institute, Woods Hole Oceanographic Institution, Monterey Bay Aquarium, and National Aquarium, with evaluation conducted by the New Knowledge Organization, Pennsylvania State University, and Ohio State University. NNOCCI enables teams of informal science interpreters across the country to serve as "communication strategists" - beyond merely conveying information they can influence public perceptions, given their high level of commitment, knowledge, public trust, social networks, and visitor contact. We provide in-depth training as well as an alumni network for ongoing learning, implementation support, leadership development, and coalition building. Our goals are to achieve a systemic national impact, embed our work within multiple ongoing regional and national climate change education networks, and leave an enduring legacy. What is the most useful theoretical model for conceptualizing the work of the NNOCCI community? This presentation will examine the pros and cons of three perspectives -- community of practice, collective impact, and social movements. The community of practice approach emphasizes use of common tools, support for practice, social learning, and organic development of leadership. A collective impact model focuses on defining common outcomes, aligning activities toward a common goal, structured collaboration. A social movement emphasizes building group identity and creating a sense of group efficacy. This presentation will address how these models compare in terms of their utility in program planning and evaluation, their fit with the unique characteristics of the NNOCCI community, and their relevance to our program goals.

Changes in visual and sensory-motor resting-state functional connectivity support motor learning by observing.

PubMed

McGregor, Heather R; Gribble, Paul L

2015-07-01

Motor learning occurs not only through direct first-hand experience but also through observation (Mattar AA, Gribble PL. Neuron 46: 153-160, 2005). When observing the actions of others, we activate many of the same brain regions involved in performing those actions ourselves (Malfait N, Valyear KF, Culham JC, Anton JL, Brown LE, Gribble PL. J Cogn Neurosci 22: 1493-1503, 2010). Links between neural systems for vision and action have been reported in neurophysiological (Strafella AP, Paus T. Neuroreport 11: 2289-2292, 2000; Watkins KE, Strafella AP, Paus T. Neuropsychologia 41: 989-994, 2003), brain imaging (Buccino G, Binkofski F, Fink GR, Fadiga L, Fogassi L, Gallese V, Seitz RJ, Zilles K, Rizzolatti G, Freund HJ. Eur J Neurosci 13: 400-404, 2001; Iacoboni M, Woods RP, Brass M, Bekkering H, Mazziotta JC, Rizzolatti G. Science 286: 2526-2528, 1999), and eye tracking (Flanagan JR, Johansson RS. Nature 424: 769-771, 2003) studies. Here we used a force field learning paradigm coupled with resting-state fMRI to investigate the brain areas involved in motor learning by observing. We examined changes in resting-state functional connectivity (FC) after an observational learning task and found a network consisting of V5/MT, cerebellum, and primary motor and somatosensory cortices in which changes in FC were correlated with the amount of motor learning achieved through observation, as assessed behaviorally after resting-state fMRI scans. The observed FC changes in this network are not due to visual attention to motion or observation of movement errors but rather are specifically linked to motor learning. These results support the idea that brain networks linking action observation and motor control also facilitate motor learning. Copyright © 2015 the American Physiological Society.

Changes in visual and sensory-motor resting-state functional connectivity support motor learning by observing

PubMed Central

McGregor, Heather R.

2015-01-01

Motor learning occurs not only through direct first-hand experience but also through observation (Mattar AA, Gribble PL. Neuron 46: 153–160, 2005). When observing the actions of others, we activate many of the same brain regions involved in performing those actions ourselves (Malfait N, Valyear KF, Culham JC, Anton JL, Brown LE, Gribble PL. J Cogn Neurosci 22: 1493–1503, 2010). Links between neural systems for vision and action have been reported in neurophysiological (Strafella AP, Paus T. Neuroreport 11: 2289–2292, 2000; Watkins KE, Strafella AP, Paus T. Neuropsychologia 41: 989–994, 2003), brain imaging (Buccino G, Binkofski F, Fink GR, Fadiga L, Fogassi L, Gallese V, Seitz RJ, Zilles K, Rizzolatti G, Freund HJ. Eur J Neurosci 13: 400–404, 2001; Iacoboni M, Woods RP, Brass M, Bekkering H, Mazziotta JC, Rizzolatti G. Science 286: 2526–2528, 1999), and eye tracking (Flanagan JR, Johansson RS. Nature 424: 769–771, 2003) studies. Here we used a force field learning paradigm coupled with resting-state fMRI to investigate the brain areas involved in motor learning by observing. We examined changes in resting-state functional connectivity (FC) after an observational learning task and found a network consisting of V5/MT, cerebellum, and primary motor and somatosensory cortices in which changes in FC were correlated with the amount of motor learning achieved through observation, as assessed behaviorally after resting-state fMRI scans. The observed FC changes in this network are not due to visual attention to motion or observation of movement errors but rather are specifically linked to motor learning. These results support the idea that brain networks linking action observation and motor control also facilitate motor learning. PMID:25995349

Teaching adults-best practices that leverage the emerging understanding of the neurobiology of learning.

PubMed

Mahan, John D; Stein, David S

2014-07-01

It is important in teaching adults to recognize the essential characteristics of adult learners and how these characteristics define their learning priorities and activities. The seven key premises and practices for teaching adults provide a good guide for those interested in helping adults learn. The emerging science of the neurobiology of learning provides powerful new insights into how learning occurs in the complex integrated neural network that characterizes the adult. Differentiation of the two types of thinking: System 1 (fast, intuitive, and, often, emotional) and System 2 (slower, deliberate, and logical). System 1 thinking helps explain the basis for quick decisions and reliance of humans on heuristics (or rules of thumb) that leads to the type of convenient thinking associated with errors of thinking and judgment. We now know that the learning experience has an objective location-in the temporal and parietal lobes-as persistent dynamic networks of neurons and neuronal connections. Learning is initially stored in transient working memory (relatively limited capacity and time frame) and then moved under the right conditions to more long-lasting/stable memory (with larger capacity) that is stored for future access and development. It is clear that memories are not static and are not destined, once developed, to forever remain as stable constructs; rather, memories are dynamic, always available for modulation and alteration, and heavily invested with context, emotion, and other operant factors. The framework for such neural networks involves new neuronal connections, enhanced neuronal synaptic transmission, and neuron generation. Ten key teaching and learning concepts derived from recent neurobiology studies on learning and memory are presented. As the neurobiology of learning is better defined, the basis for how adults best learn, and even the preferences they display, can be employed as the physiological foundation for our best methods to effectively teach adults and facilitate their learning. Copyright © 2014 Mosby, Inc. All rights reserved.

Critical issues in medical education and the implications for telemedicine technology.

PubMed

Mahapatra, Ashok Kumar; Mishra, Saroj Kanta; Kapoor, Lily; Singh, Indra Pratap

2009-01-01

Ensuring quality medical education in all the medical colleges across India based on uniform curriculum prescribed by a regulatory body and maintaining a uniform standard are dependent on availability of an excellent infrastructure. Such infrastructure includes qualified teachers, knowledge resources, learning materials, and advanced education technology, which is a challenge in developing countries due to financial and logistic constraints. Advancement in telecommunication, information science, and technology provides an opportunity to exchange knowledge and skill across geographically dispersed organizations by networking academic medical centers of excellence with medical colleges and institutes to practice distance learning using information and communication technology (ICT)-based tools. These may be as basic as commonly used Web-based tools or may be as advanced as virtual reality, simulation, and telepresence-based collaborative learning environment. The scenario in India is no different from any developing country, but there is considerable progress due to technical advancement in these sectors. Telemedicine and tele-education in health science, is gradually getting adopted into the Indian Health System after decade-long pilot studies across the country. A recent recommendation of the National Knowledge Commission, once implemented, would ensure a gigabyte network across all the educational institutions of the country including medical colleges. Availability of indigenous satellite communication technology and the government policy of free bandwidth provision for societal development sector have added strength to set up infrastructure to pilot several telemedicine educational projects across the country.

Obtaining big data of vegetation using artificial neural network

NASA Astrophysics Data System (ADS)

Ise, T.; Minagawa, M.; Onishi, M.

2017-12-01

To carry out predictive studies concerning ecosystems, obtaining appropriate datasets is one of the key factors. Recently, applications of neural network such as deep learning have successfully overcome difficulties in data acquisition and added large datasets for predictive science. For example, deep learning is very powerful in identifying and counting people, cars, etc. However, for vegetation science, deep learning has not been widely used. In general, differing from animals, plants have characteristics of modular growth. For example, numbers of leaves and stems which one individual plant typically possesses are not predetermined but change flexibly according to environmental conditions. This is clearly different from that the standard model of human face has predetermined numbers of parts, such as two eyes, one mouth, and so on. This characteristics of plants can make object identification difficult. In this study, a simple but effective technique was used to overcome the difficulty of visual identification of plants, and automated classification of plant types and quantitative analyses were become possible. For instance, when our method was applied to classify bryophytes, one of the most difficult plant types for computer vision due to their amorphous shapes, the performance of identification model was typically over 90% success. With this technology, it may be possible to obtain the big data of plant type, size, density etc. from satellite and/or drone imageries, in a quantitative manner. this will allow progress in predictive biogeosciences.

Metaheuristic Algorithms for Convolution Neural Network

PubMed Central

Fanany, Mohamad Ivan; Arymurthy, Aniati Murni

2016-01-01

A typical modern optimization technique is usually either heuristic or metaheuristic. This technique has managed to solve some optimization problems in the research area of science, engineering, and industry. However, implementation strategy of metaheuristic for accuracy improvement on convolution neural networks (CNN), a famous deep learning method, is still rarely investigated. Deep learning relates to a type of machine learning technique, where its aim is to move closer to the goal of artificial intelligence of creating a machine that could successfully perform any intellectual tasks that can be carried out by a human. In this paper, we propose the implementation strategy of three popular metaheuristic approaches, that is, simulated annealing, differential evolution, and harmony search, to optimize CNN. The performances of these metaheuristic methods in optimizing CNN on classifying MNIST and CIFAR dataset were evaluated and compared. Furthermore, the proposed methods are also compared with the original CNN. Although the proposed methods show an increase in the computation time, their accuracy has also been improved (up to 7.14 percent). PMID:27375738

Metaheuristic Algorithms for Convolution Neural Network.

PubMed

Rere, L M Rasdi; Fanany, Mohamad Ivan; Arymurthy, Aniati Murni

2016-01-01

A typical modern optimization technique is usually either heuristic or metaheuristic. This technique has managed to solve some optimization problems in the research area of science, engineering, and industry. However, implementation strategy of metaheuristic for accuracy improvement on convolution neural networks (CNN), a famous deep learning method, is still rarely investigated. Deep learning relates to a type of machine learning technique, where its aim is to move closer to the goal of artificial intelligence of creating a machine that could successfully perform any intellectual tasks that can be carried out by a human. In this paper, we propose the implementation strategy of three popular metaheuristic approaches, that is, simulated annealing, differential evolution, and harmony search, to optimize CNN. The performances of these metaheuristic methods in optimizing CNN on classifying MNIST and CIFAR dataset were evaluated and compared. Furthermore, the proposed methods are also compared with the original CNN. Although the proposed methods show an increase in the computation time, their accuracy has also been improved (up to 7.14 percent).

Public Participation, Education, and Engagement in Drought Planning

NASA Astrophysics Data System (ADS)

Bathke, D. J.; Wall, N.; Haigh, T.; Smith, K. H.; Bernadt, T.

2014-12-01

Drought is a complex problem that typically goes beyond the capacity, resources, and jurisdiction of any single person, program, organization, political boundary, or sector. Thus, by nature, monitoring, planning for, and reducing drought risk must be a collaborative process. The National Drought Mitigation Center, in partnership with the National Integrated Drought Information System (NIDIS) Program Office and others, provides active engagement and education drought professionals, stakeholders, and the general public about managing drought-related risks through resilience planning, monitoring, and education. Using case studies, we discuss recruitment processes, network building, participation techniques, and educational methods as they pertain to a variety of unique audiences with distinct objectives. Examples include collaborative decision-making at a World Meteorological Organization conference; planning, and peer-learning among drought professionals in a community of practice; drought condition monitoring through citizen science networks; research and education dissemination with stakeholder groups; and informal learning activities for all ages. Finally, we conclude with evaluation methods, indicators of success, and lessons learned for increasing the effectiveness of our programs in increasing drought resilience.

Topological self-organization and prediction learning support both action and lexical chains in the brain.

PubMed

Chersi, Fabian; Ferro, Marcello; Pezzulo, Giovanni; Pirrelli, Vito

2014-07-01

A growing body of evidence in cognitive psychology and neuroscience suggests a deep interconnection between sensory-motor and language systems in the brain. Based on recent neurophysiological findings on the anatomo-functional organization of the fronto-parietal network, we present a computational model showing that language processing may have reused or co-developed organizing principles, functionality, and learning mechanisms typical of premotor circuit. The proposed model combines principles of Hebbian topological self-organization and prediction learning. Trained on sequences of either motor or linguistic units, the network develops independent neuronal chains, formed by dedicated nodes encoding only context-specific stimuli. Moreover, neurons responding to the same stimulus or class of stimuli tend to cluster together to form topologically connected areas similar to those observed in the brain cortex. Simulations support a unitary explanatory framework reconciling neurophysiological motor data with established behavioral evidence on lexical acquisition, access, and recall. Copyright © 2014 Cognitive Science Society, Inc.

The etiology of social change.

PubMed

Carley, Kathleen M; Martin, Michael K; Hirshman, Brian R

2009-10-01

A fundamental aspect of human beings is that they learn. The process of learning and what is learned are impacted by a number of factors, both cognitive and social; that is, humans are boundedly rational. Cognitive and social limitations interact, making it difficult to reason about how to provide information to impact what humans know, believe, and do. Herein, we use a multi-agent dynamic-network simulation system, Construct, to conduct such reasoning. In particular, we ask, What media should be used to provide information to most impact what people know, believe, and do, given diverse social structures? All simulated agents are boundedly rational both at the cognitive and social level, and so are subject to factors such as literacy, education, and the breadth of their social network. We find that there is no one most effective intervention; rather, to be effective, messages and the media used to spread the message need to be selected for the population being addressed. Typically, a multimedia campaign is critical. Copyright © 2009 Cognitive Science Society, Inc.

Network analysis of physics discussion forums and links to course success

NASA Astrophysics Data System (ADS)

Traxler, Adrienne; Gavrin, Andrew; Lindell, Rebecca

2017-01-01

Large introductory science courses tend to isolate students, with negative consequences for long-term retention in college. Many active learning courses build collaboration and community among students as an explicit goal, and social network analysis has been used to track the development and beneficial effects of these collaborations. Here we supplement such work by conducting network analysis of online course discussion forums in two semesters of an introductory physics class. Online forums provide a tool for engaging students with each other outside of class, and offer new opportunities to commuter or non-traditional students with limited on-campus time. We look for correlations between position in the forum network (centrality) and final course grades. Preliminary investigation has shown weak correlations in the very dense full-semester network, so we will consider reduced ''backbone'' networks that highlight the most consistent links between students. Future work and implications for instruction will also be discussed.

From biological and social network metaphors to coupled bio-social wireless networks

PubMed Central

Barrett, Christopher L.; Eubank, Stephen; Anil Kumar, V.S.; Marathe, Madhav V.

2010-01-01

Biological and social analogies have been long applied to complex systems. Inspiration has been drawn from biological solutions to solve problems in engineering products and systems, ranging from Velcro to camouflage to robotics to adaptive and learning computing methods. In this paper, we present an overview of recent advances in understanding biological systems as networks and use this understanding to design and analyse wireless communication networks. We expand on two applications, namely cognitive sensing and control and wireless epidemiology. We discuss how our work in these two applications is motivated by biological metaphors. We believe that recent advances in computing and communications coupled with advances in health and social sciences raise the possibility of studying coupled bio-social communication networks. We argue that we can better utilise the advances in our understanding of one class of networks to better our understanding of the other. PMID:21643462

Conceptual Blending Monitoring Students' Use of Metaphorical Concepts to Further the Learning of Science

NASA Astrophysics Data System (ADS)

Fredriksson, Alexandra; Pelger, Susanne

2018-03-01

The aim of this study is to explore how tertiary science students' use of metaphors in their popular science article writing may influence their understanding of subject matter. For this purpose, six popular articles written by students in physics or geology were analysed by means of a close textual analysis and a metaphor analysis. In addition, semi-structured interviews were conducted with the students. The articles showed variation regarding the occurrence of active (non-conventional) metaphors, and metaphorical concepts, i.e. metaphors relating to a common theme. In addition, the interviews indicated that students using active metaphors and metaphorical concepts reflected more actively upon their use of metaphors. These students also discussed the possible relationship between subject understanding and creation of metaphors in terms of conceptual blending. The study suggests that students' process of creating metaphorical concepts could be described and visualised through integrated networks of conceptual blending. Altogether, the study argues for using conceptual blending as a tool for monitoring and encouraging the use of adequate metaphorical concepts, thereby facilitating students' opportunities of understanding and influencing the learning of science.

Learning Physics-based Models in Hydrology under the Framework of Generative Adversarial Networks

NASA Astrophysics Data System (ADS)

Karpatne, A.; Kumar, V.

2017-12-01

Generative adversarial networks (GANs), that have been highly successful in a number of applications involving large volumes of labeled and unlabeled data such as computer vision, offer huge potential for modeling the dynamics of physical processes that have been traditionally studied using simulations of physics-based models. While conventional physics-based models use labeled samples of input/output variables for model calibration (estimating the right parametric forms of relationships between variables) or data assimilation (identifying the most likely sequence of system states in dynamical systems), there is a greater opportunity to explore the full power of machine learning (ML) methods (e.g, GANs) for studying physical processes currently suffering from large knowledge gaps, e.g. ground-water flow. However, success in this endeavor requires a principled way of combining the strengths of ML methods with physics-based numerical models that are founded on a wealth of scientific knowledge. This is especially important in scientific domains like hydrology where the number of data samples is small (relative to Internet-scale applications such as image recognition where machine learning methods has found great success), and the physical relationships are complex (high-dimensional) and non-stationary. We will present a series of methods for guiding the learning of GANs using physics-based models, e.g., by using the outputs of physics-based models as input data to the generator-learner framework, and by using physics-based models as generators trained using validation data in the adversarial learning framework. These methods are being developed under the broad paradigm of theory-guided data science that we are developing to integrate scientific knowledge with data science methods for accelerating scientific discovery.

Mapping Out-of-School-Time Youth Science Programs: Organizational Patterns and Possibilities

NASA Astrophysics Data System (ADS)

Laursen, S. L.; Archie, T.; Thiry, H.

2012-12-01

Out-of-school-time (OST) experiences promise to enrich young (K-12) people's experience of science, technology and engineering. Belief is widespread that OST programs are ideal locations to learn science, and that youth participation may enhance the science workforce and increase access to science for girls and minorities. Yet we know little about the scope or nature of science-focused OST youth programming. Variety poses a challenge for researchers, with OST sites in schools, museums, zoos, science and nature centers, aquariums, planetariums, and community centers; and formats including after-school clubs, camps, workshops, festivals, research apprenticeships, and more. Moreover, there is no single national network through which researchers might reach and recruit nationally representative samples of programs. Thus, to date there has been no systematic study of the broader national landscape of OST STEM programming. Our national study, Mapping Out-of-School-Time Science (MOST-Science), examines a national sample of OST programs focused on science, engineering, and/or technology. Here we describe first findings about the characteristics of these programs and their home organizations, including aspects of program design, structure, funding, staffing, and youth audience. Using an electronic survey, we collected data from 417 programs and classified their host institutions into eight organizational types: aquariums and zoos, museums, non-profits, national youth organizations, K-12 school districts, colleges and universities, government labs, and private sector organizations. We then examine key attributes of the youth programs hosted by these institution and discuss differences based on organizational types, including scientific organizations that are especially well equipped to offer research and field experiences. Programs engaging youth in research and field experiences are offered across all organizational types. Yet they vary notably in the size and demographics of the youth populations they serve, and their interest or ability to target particular youth groups. We observe that organizations implementing youth OST science programs are often networked to other organizations similar to themselves, but unaware of related work in other sectors. Therefore, understanding the characteristics of organizations that host youth science programs may help organizations to achieve general goals such as increasing diversity, increasing accessibility, improving funding, improving program evaluation, and improving program content. For example, smaller organizations with limited resources could adopt proven strategies to increase diversity and access from larger organizations with more resources to initially develop these strategies. University programs might draw effectively upon best practices of similar programs offered by museums or non-profits. By providing a better picture of the strengths of different organizations as youth OST science providers, we hope to suggest unfilled niches for practitioners to pursue, and to highlight potential networking opportunities among organizations that can enhance youth research and field-based learning programs.

Distributed Bayesian Computation and Self-Organized Learning in Sheets of Spiking Neurons with Local Lateral Inhibition

PubMed Central

Bill, Johannes; Buesing, Lars; Habenschuss, Stefan; Nessler, Bernhard; Maass, Wolfgang; Legenstein, Robert

2015-01-01

During the last decade, Bayesian probability theory has emerged as a framework in cognitive science and neuroscience for describing perception, reasoning and learning of mammals. However, our understanding of how probabilistic computations could be organized in the brain, and how the observed connectivity structure of cortical microcircuits supports these calculations, is rudimentary at best. In this study, we investigate statistical inference and self-organized learning in a spatially extended spiking network model, that accommodates both local competitive and large-scale associative aspects of neural information processing, under a unified Bayesian account. Specifically, we show how the spiking dynamics of a recurrent network with lateral excitation and local inhibition in response to distributed spiking input, can be understood as sampling from a variational posterior distribution of a well-defined implicit probabilistic model. This interpretation further permits a rigorous analytical treatment of experience-dependent plasticity on the network level. Using machine learning theory, we derive update rules for neuron and synapse parameters which equate with Hebbian synaptic and homeostatic intrinsic plasticity rules in a neural implementation. In computer simulations, we demonstrate that the interplay of these plasticity rules leads to the emergence of probabilistic local experts that form distributed assemblies of similarly tuned cells communicating through lateral excitatory connections. The resulting sparse distributed spike code of a well-adapted network carries compressed information on salient input features combined with prior experience on correlations among them. Our theory predicts that the emergence of such efficient representations benefits from network architectures in which the range of local inhibition matches the spatial extent of pyramidal cells that share common afferent input. PMID:26284370

Real Science, Real Learning: Bridging the Gap Between Scientists, Educators and Students

NASA Astrophysics Data System (ADS)

Lewis, Y.

2006-05-01

Today as never before, America needs its citizens to be literate in science and technology. Not only must we only inspire a new generation of scientists and engineers and technologists, we must foster a society capable of meeting complex, 21st-century challenges. Unfortunately, the need for creative, flexible thinkers is growing at a time when our young students are lagging in science interest and performance. Over the past 17 years, the JASON Project has worked to link real science and scientists to the classroom. This link provide viable pipeline to creating the next generation scientists and researchers. Ultimately, JASON's mission is to improve the way science is taught by enabling students to learn directly from leading scientists. Through partnerships with agencies such as NOAA and NASA, JASON creates multimedia classroom products based on current scientific research. Broadcasts of science expeditions, hosted by leading researchers, are coupled with classroom materials that include interactive computer-based simulations, video- on-demand, inquiry-based experiments and activities, and print materials for students and teachers. A "gated" Web site hosts online resources and provides a secure platform to network with scientists and other classrooms in a nationwide community of learners. Each curriculum is organized around a specific theme for a comprehensive learning experience. It may be taught as a complete package, or individual components can be selected to teach specific, standards-based concepts. Such thematic units include: Disappearing Wetlands, Mysteries of Earth and Mars, and Monster Storms. All JASON curriculum units are grounded in "inquiry-based learning." The highly interactive curriculum will enable students to access current, real-world scientific research and employ the scientific method through reflection, investigation, identification of problems, sharing of data, and forming and testing hypotheses. JASON specializes in effectively applying technology in science education by designing animated interactive visualizations that promote student understanding of complex scientific concepts and systems (Rieber, 1990, 1996). JASON's experience in utilizing the power of simulation technology has been widely recognized for its effectiveness in exciting and engaging students in science learning by independent evaluations of JASON's multimedia science curriculum (Ba et al., 2001; Goldenberg et al., 2003). The data collected indicates that JASON's science products have had a positive impact on students' science learning, have positively influenced their perceptions of scientists and of becoming scientists, and have helped diverse students grasp a deeper understanding of complex scientific content, concepts and technologies.

Neural Network Machine Learning and Dimension Reduction for Data Visualization

NASA Technical Reports Server (NTRS)

Liles, Charles A.

2014-01-01

Neural network machine learning in computer science is a continuously developing field of study. Although neural network models have been developed which can accurately predict a numeric value or nominal classification, a general purpose method for constructing neural network architecture has yet to be developed. Computer scientists are often forced to rely on a trial-and-error process of developing and improving accurate neural network models. In many cases, models are constructed from a large number of input parameters. Understanding which input parameters have the greatest impact on the prediction of the model is often difficult to surmise, especially when the number of input variables is very high. This challenge is often labeled the "curse of dimensionality" in scientific fields. However, techniques exist for reducing the dimensionality of problems to just two dimensions. Once a problem's dimensions have been mapped to two dimensions, it can be easily plotted and understood by humans. The ability to visualize a multi-dimensional dataset can provide a means of identifying which input variables have the highest effect on determining a nominal or numeric output. Identifying these variables can provide a better means of training neural network models; models can be more easily and quickly trained using only input variables which appear to affect the outcome variable. The purpose of this project is to explore varying means of training neural networks and to utilize dimensional reduction for visualizing and understanding complex datasets.

Learning from the Mars Rover Mission: Scientific Discovery, Learning and Memory

NASA Technical Reports Server (NTRS)

Linde, Charlotte

2005-01-01

Purpose: Knowledge management for space exploration is part of a multi-generational effort. Each mission builds on knowledge from prior missions, and learning is the first step in knowledge production. This paper uses the Mars Exploration Rover mission as a site to explore this process. Approach: Observational study and analysis of the work of the MER science and engineering team during rover operations, to investigate how learning occurs, how it is recorded, and how these representations might be made available for subsequent missions. Findings: Learning occurred in many areas: planning science strategy, using instrumen?s within the constraints of the martian environment, the Deep Space Network, and the mission requirements; using software tools effectively; and running two teams on Mars time for three months. This learning is preserved in many ways. Primarily it resides in individual s memories. It is also encoded in stories, procedures, programming sequences, published reports, and lessons learned databases. Research implications: Shows the earliest stages of knowledge creation in a scientific mission, and demonstrates that knowledge management must begin with an understanding of knowledge creation. Practical implications: Shows that studying learning and knowledge creation suggests proactive ways to capture and use knowledge across multiple missions and generations. Value: This paper provides a unique analysis of the learning process of a scientific space mission, relevant for knowledge management researchers and designers, as well as demonstrating in detail how new learning occurs in a learning organization.

Launching Light: Beyond the Bulb for the United Nations' International Year of Light 2015

NASA Astrophysics Data System (ADS)

Arcand, K. K.; Watzke, M.

2015-09-01

In astronomy, light is the language used to understand the Universe. From radio waves to gamma rays, light in all its forms delivers information that helps astronomers learn about the Universe. When the United Nations declared 2015 to be the International Year of Light and Light-based Technologies (IYL2015), it presented an opportunity to share the role that light plays in astronomy and beyond. The IYL2015 also offered a chance to build on experiences and sustain networks from the International Year of Astronomy in 2009. Light: Beyond the Bulb is an IYL2015 project that melds both of these goals. The project takes the form of an exhibit that showcases what light can do, from here on Earth and across the vastness of space, hosted by volunteer networks in public spaces for informal science learning.

Synthetic biology: exploring and exploiting genetic modularity through the design of novel biological networks.

PubMed

Agapakis, Christina M; Silver, Pamela A

2009-07-01

Synthetic biology has been used to describe many biological endeavors over the past thirty years--from designing enzymes and in vitro systems, to manipulating existing metabolisms and gene expression, to creating entirely synthetic replicating life forms. What separates the current incarnation of synthetic biology from the recombinant DNA technology or metabolic engineering of the past is an emphasis on principles from engineering such as modularity, standardization, and rigorously predictive models. As such, synthetic biology represents a new paradigm for learning about and using biological molecules and data, with applications in basic science, biotechnology, and medicine. This review covers the canonical examples as well as some recent advances in synthetic biology in terms of what we know and what we can learn about the networks underlying biology, and how this endeavor may shape our understanding of living systems.

The Use of Facebook to Build a Community for Distance Learning Students: A Case Study from the Open University

ERIC Educational Resources Information Center

Callaghan, George; Fribbance, Ian

2016-01-01

Social media platforms such as Facebook are commonplace throughout society. However, within higher education institutions such networking environments are still in the developmental stage. This paper describes and discusses case study data from the Open University's Faculty of Social Science Facebook page. It starts by giving an overview of the…

Learning to Reason and Communicate in College: Initial Report of Findings from the CLA Longitudinal Study

ERIC Educational Resources Information Center

Arum, Richard; Roksa, Josipa

2008-01-01

This research emerged from the Social Science Research Council's collaborative partnership with the Pathways for College Network, with technical assistance in data collection provided by the Council for Aid to Education. The project has followed over 2,300 students at 24 institutions over time to examine what factors are associated with learning…

Introducing Network Analysis into Science Education: Methodological Research Examining Secondary School Students' Understanding of "Decomposition"

ERIC Educational Resources Information Center

Schizas, Dimitrios; Katrana, Evagelia; Stamou, George

2013-01-01

In the present study we used the technique of word association tests to assess students' cognitive structures during the learning period. In particular, we tried to investigate what students living near a protected area in Greece (Dadia forest) knew about the phenomenon of decomposition. Decomposition was chosen as a stimulus word because it…

Transforming Your Regional Economy through Uncertainty and Surprise: Learning from Complexity Science, Network Theory and the Field

NASA Astrophysics Data System (ADS)

Holley, June

The field of regional development blossomed in the last decade, as researchers and practitioners increasingly asserted that the region was the most effective geographic unit for supporting the excellence and innovation of entrepreneurs. See, for example, the many studies by the European Union and the work by Michael Porter.

The Creation of New International Networks in Education: The League of Nations and Educational Organizations in the 1920s

ERIC Educational Resources Information Center

Fuchs, Eckhardt

2007-01-01

There is hardly any doubt that the First World War interrupted most of the international educational relations that had reached their peak in the two decades before the outbreak of the war. In virtually all areas of education--the educational system, educational science, teaching and learning, child welfare, and the educational…

The Effect of Interactive, Three Dimensional, High Speed Simulations on High School Science Students' Conceptions of the Molecular Structure of Water.

ERIC Educational Resources Information Center

Hakerem, Gita; And Others

The Water and Molecular Networks (WAMNet) Project uses graduate student written Reduced Instruction Set Computing (RISC) computer simulations of the molecular structure of water to assist high school students learn about the nature of water. This study examined: (1) preconceptions concerning the molecular structure of water common among high…

Transforming Science Teaching Environment for the 21st Century Primary School Pupils

ERIC Educational Resources Information Center

Sheikh Abdullah, Siti Hendon

2016-01-01

The transformation of technology in the 21st century has produced children who are technology savvy and exposed to the internet and social networking at a very young age. These children are already in our school system. Thus teachers too need to use technology and transform the learning environment to meet the requirements of these children. This…

Metrological Traceability in the Social Sciences: A Model from Reading Measurement

NASA Astrophysics Data System (ADS)

Stenner, A. Jackson; Fisher, William P., Jr.

2013-09-01

The central importance of reading ability in learning makes it the natural place to start in formative and summative assessments in education. The Lexile Framework for Reading constitutes a commercial metrological traceability network linking books, test results, instructional materials, and students in elementary and secondary English and Spanish language reading education in the U.S., Canada, Mexico, and Australia.

Facilitating and Learning at the Edge of Chaos: Expanding the Context of Experiential Education.

ERIC Educational Resources Information Center

Oekerman, Carl

Significant recent discoveries within a number of scientific disciplines, collectively referred to as the science of complexity, are creating a major shift in how human beings understand the complex, adaptive systems that make up the world. A complex adaptive system consists of networks of large numbers of agents that interact with each other and…

Creating Successful Scientist-Teacher-Student Collaborations: Examples From the GLOBE Program

NASA Astrophysics Data System (ADS)

Geary, E.; Wright, E.; Yule, S.; Randolph, G.; Larsen, J.; Smith, D.

2007-12-01

Actively engaging students in research on the environment at local, regional, and globe scales is a primary objective of the GLOBE (Global Learning and Observations to Benefit the Environment) Program. During the past 18 months, GLOBE, an international education and science program in 109 countries and tens of thousands of schools worldwide, has been working with four NSF-funded Earth System Science Projects to involve K-12 students, teachers, and scientists in collaborative research investigations of Seasons and Biomes, the Carbon Cycle, Local and Extreme Environments, and Watersheds. This talk will discuss progress to date in each of these investigation areas and highlight successes and challenges in creating effective partnerships between diverse scientific and educational stakeholders. More specifically we will discuss lessons learned in the following areas: (a) mutual goal and responsibility setting, (b) resource allocation, (c) development of adaptable learning activities, tools, and services, (d) creation of scientist and school networks, and (e) development of evaluation metrics, all in support of student research.

Climate Literacy Partnership in the Southeast (CLiPSE): A Focus on Climate Change-related Dialogs with Faith-Based Groups as a form of Network Building in the Southeast United States - Lessons Learned

NASA Astrophysics Data System (ADS)

Carroll, F. J.; McNeal, K. S.; Hammerman, J.; Christiansen, J.

2013-05-01

The Climate Literacy Partnership in the Southeast (CLiPSE, http://CLiPSE-project.org), funded through the National Science Foundation Climate Change Education Partnership program, is dedicated to improving climate literacy in the Southeastern United States (SE US). By promoting science-based formal and informal educational resources, CLiPSE works through a diverse network of key partner organizations in the SE US to conduct effective public dialogues that address diverse audiences and support learning about climate, climate change, and its impact on human and environmental systems. The CLiPSE project successfully created partnerships with more than fifty key stakeholders, including agriculture, education, leisure, and religious organizations, along with culturally diverse communities. This presentation will explain the CLiPSE model for reaching key publics who hold traditional ideologies typically perceived as incompatible with climate change science. We will discuss the results of our interactions with the leaders of our partnering organizations, their knowledge, perceptions, needs, and input in crafting effective messages for their audiences, through addressing both learners' affective and cognitive domains. For the informal education sector, CLiPSE utilized several open discussion and learning forums aimed to promote critical thinking and civil conversation about climate change. Focusing on Faith-based audiences, a key demographic, in the Southeast US, CLiPSE also conducted an online, moderated, author-attended book study, discussing the thoughts and ideas contained in the work, "Green Like God," by Jonathan Merritt. We will share the questions we faced as we focused on and learned about faith-based audiences, such as: What are the barriers and opportunities?; How do we break out of the assumptions that we have to find the common ground?; How do the audiences understand the issues?; How do we understand the issues?; What common language can we find?; What happens when we bringing the multiple the multiple identities of faith and science together within ourselves and those we are trying to build relationships with? We will also share the lessons we learned while attempting to answer these questions, such as the role of trust and key influentials/leaders in talking with target audiences, the importance of face-to-face dialog and relationships in trust building.

Team Science Approach to Developing Consensus on Research Good Practices for Practice-Based Research Networks: A Case Study.

PubMed

Campbell-Voytal, Kimberly; Daly, Jeanette M; Nagykaldi, Zsolt J; Aspy, Cheryl B; Dolor, Rowena J; Fagnan, Lyle J; Levy, Barcey T; Palac, Hannah L; Michaels, LeAnn; Patterson, V Beth; Kano, Miria; Smith, Paul D; Sussman, Andrew L; Williams, Robert; Sterling, Pamela; O'Beirne, Maeve; Neale, Anne Victoria

2015-12-01

Using peer learning strategies, seven experienced PBRNs working in collaborative teams articulated procedures for PBRN Research Good Practices (PRGPs). The PRGPs is a PBRN-specific resource to facilitate PBRN management and staff training, to promote adherence to study protocols, and to increase validity and generalizability of study findings. This paper describes the team science processes which culminated in the PRGPs. Skilled facilitators used team science strategies and methods from the Technology of Participation (ToP®), and the Consensus Workshop Method to support teams to codify diverse research expertise in practice-based research. The participatory nature of "sense-making" moved through identifiable stages. Lessons learned include (1) team input into the scope of the final outcome proved vital to project relevance; (2) PBRNs with diverse domains of research expertise contributed broad knowledge on each topic; and (3) ToP® structured facilitation techniques were critical for establishing trust and clarifying the "sense-making" process. © 2015 Wiley Periodicals, Inc.

Team Science Approach to Developing Consensus on Research Good Practices for Practice‐Based Research Networks: A Case Study

PubMed Central

Daly, Jeanette M.; Nagykaldi, Zsolt J.; Aspy, Cheryl B.; Dolor, Rowena J.; Fagnan, Lyle J.; Levy, Barcey T.; Palac, Hannah L.; Michaels, LeAnn; Patterson, V. Beth; Kano, Miria; Smith, Paul D.; Sussman, Andrew L.; Williams, Robert; Sterling, Pamela; O'Beirne, Maeve; Neale, Anne Victoria

2015-01-01

Abstract Using peer learning strategies, seven experienced PBRNs working in collaborative teams articulated procedures for PBRN Research Good Practices (PRGPs). The PRGPs is a PBRN‐specific resource to facilitate PBRN management and staff training, to promote adherence to study protocols, and to increase validity and generalizability of study findings. This paper describes the team science processes which culminated in the PRGPs. Skilled facilitators used team science strategies and methods from the Technology of Participation (ToP®), and the Consensus Workshop Method to support teams to codify diverse research expertise in practice‐based research. The participatory nature of “sense‐making” moved through identifiable stages. Lessons learned include (1) team input into the scope of the final outcome proved vital to project relevance; (2) PBRNs with diverse domains of research expertise contributed broad knowledge on each topic; and (3) ToP® structured facilitation techniques were critical for establishing trust and clarifying the “sense‐making” process. PMID:26602516

A Statewide Partnership for Implementing Inquiry Science

NASA Astrophysics Data System (ADS)

Lytle, Charles

The North Carolina Infrastructure for Science Education (NC-ISE) is a statewide partnership for implementing standards-based inquiry science using exemplary curriculum materials in the public schools of North Carolina. North Carolina is the 11th most populous state in the USA with 8,000,000 residents, 117 school districts and a geographic area of 48,718 miles. NC-ISE partners include the state education agency, local school systems, three branches of the University of North Carolina, the state mathematics and science education network, businesses, and business groups. The partnership, based upon the Science for All Children model developed by the National Science Resources Centre, was initiated in 1997 for improvement in teaching and learning of science and mathematics. This research-based model has been successfully implemented in several American states during the past decade. Where effectively implemented, the model has led to significant improvements in student interest and student learning. It has also helped reduce the achievement gap between minority and non-minority students and among students from different economic levels. A key program element of the program is an annual Leadership Institute that helps teams of administrators and teachers develop a five-year strategic plan for their local systems. Currently 33 of the117 local school systems have joined the NC-ISE Program and are in various stages of implementation of inquiry science in grades K-8.

Machine learning and social network analysis applied to Alzheimer's disease biomarkers.

PubMed

Di Deco, Javier; González, Ana M; Díaz, Julia; Mato, Virginia; García-Frank, Daniel; Álvarez-Linera, Juan; Frank, Ana; Hernández-Tamames, Juan A

2013-01-01

Due to the fact that the number of deaths due Alzheimer is increasing, the scientists have a strong interest in early stage diagnostic of this disease. Alzheimer's patients show different kind of brain alterations, such as morphological, biochemical, functional, etc. Currently, using magnetic resonance imaging techniques is possible to obtain a huge amount of biomarkers; being difficult to appraise which of them can explain more properly how the pathology evolves instead of the normal ageing. Machine Learning methods facilitate an efficient analysis of complex data and can be used to discover which biomarkers are more informative. Moreover, automatic models can learn from historical data to suggest the diagnostic of new patients. Social Network Analysis (SNA) views social relationships in terms of network theory consisting of nodes and connections. The resulting graph-based structures are often very complex; there can be many kinds of connections between the nodes. SNA has emerged as a key technique in modern sociology. It has also gained a significant following in medicine, anthropology, biology, information science, etc., and has become a popular topic of speculation and study. This paper presents a review of machine learning and SNA techniques and then, a new approach to analyze the magnetic resonance imaging biomarkers with these techniques, obtaining relevant relationships that can explain the different phenotypes in dementia, in particular, different stages of Alzheimer's disease.

The Interactions of Relationships, Interest, and Self-Efficacy in Undergraduate Physics

NASA Astrophysics Data System (ADS)

Dou, Remy

This collected papers dissertation explores students' academic interactions in an active learning, introductory physics settings as they relate to the development of physics self-efficacy and interest. The motivation for this work extends from the national call to increase participation of students in the pursuit of science, technology, engineering, and mathematics (STEM) careers. Self-efficacy and interest are factors that play prominent roles in popular, evidence-based, career theories, including the Social cognitive career theory (SCCT) and the identity framework. Understanding how these constructs develop in light of the most pervasive characteristic of the active learning introductory physics classroom (i.e., peer-to-peer interactions) has implications on how students learn in a variety of introductory STEM classrooms and settings structured after constructivist and sociocultural learning theories. I collected data related to students' in-class interactions using the tools of social network analysis (SNA). Social network analysis has recently been shown to be an effective and useful way to examine the structure of student relationships that develop in and out of STEM classrooms. This set of studies furthers the implementation of SNA as a tool to examine self-efficacy and interest formation in the active learning physics classroom. Here I represent a variety of statistical applications of SNA, including bootstrapped linear regression (Chapter 2), structural equation modeling (Chapter 3), and hierarchical linear modeling for longitudinal analyses (Chapter 4). Self-efficacy data were collected using the Sources of Self-Efficacy for Science Courses - Physics survey (SOSESC-P), and interest data were collected using the physics identity survey. Data for these studies came from the Modeling Instruction sections of Introductory Physics with Calculus offered at Florida International University in the fall of 2014 and 2015. Analyses support the idea that students' perceptions of one another impact the development of their social network centrality, which in turn affects their self-efficacy building experiences and their overall self-efficacy. It was shown that unlike career theories that emphasize causal relationships between the development of self-efficacy and the subsequent growth of student interest, in this context student interest takes precedence before the development of student self-efficacy. This outcome also has various implications for career theories.

Integration of classroom science performance assessment tasks by participants of the Wisconsin Performance Assessment Development Project (WPADP)

NASA Astrophysics Data System (ADS)

Tonnis, Dorothy Ann

The goals of this interpretive study were to examine selected Wisconsin science teachers' perceptions of teaching and learning science, to describe the scope of classroom performance assessment practices, and to gain an understanding of teachers' personal and professional experiences that influenced their belief systems of teaching, learning and assessment. The study was designed to answer the research questions: (1) How does the integration of performance assessment relate to the teachers' views of teaching and learning? (2) How are the selected teachers integrating performance assessment in their teaching? (3) What past personal and professional experiences have influenced teachers' attitudes and beliefs related to their classroom performance assessment practices? Purposeful sampling was used to select seven Wisconsin elementary, middle and high school science teachers who participated in the WPADP initiative from 1993-1995. Data collection methods included a Teaching Practices Inventory (TPI), semi-structured interviews, teacher developed portfolios, portfolio conferences, and classroom observations. Four themes and multiple categories emerged through data analysis to answer the research questions and to describe the results. Several conclusions were drawn from this research. First, science teachers who appeared to effectively integrate performance assessment, demonstrated transformational thinking in their attitudes and beliefs about teaching and learning science. In addition, these teachers viewed assessment and instructional practices as interdependent. Third, transformational teachers generally used well defined criteria to judge student work and made it public to the students. Transformational teachers provided students with real-world performance assessment tasks that were also learning events. Furthermore, student task responses informed the transformational teachers about effectiveness of instruction, students' complex thinking skills, quality of assessment instruments, students' creativity, and students' self-assessment skills. Finally, transformational teachers maintained integration of performance assessment practices through sustaining teacher support networks, engaging in professional development programs, and reflecting upon past personal and professional experiences related to teaching, learning and assessment. Salient conflicts overcome or minimized by transformational teachers include the conflict between assessment scoring and grading issues, validity and reliability concerns about the performance assessment tasks used, and the difficulty for teachers to consistently provide public criteria to students before task administration.

A qualitative study of middle school students' perceptions of factors facilitating the learning of science: Grounded theory and existing theory

NASA Astrophysics Data System (ADS)

Spector, Barbara S.; Gibson, Charles W.

The purpose of this study was to explore middle school students' perceptions of what factors facilitated their learning of science. Florida's Educational Reform Act of 1983 funded programs providing the state's precollege students with summer learning opportunities in science. mathematics, and computers. The programs were intended to encourage the development of creative approaches to the teaching of these disciplines. Under this program, between 50 and 60 high-achieving middle school students were in residence on the University of South Florida campus for 12 consecutive days of study in the World of Water (WOW) program. There were two sessions per summer involving a total of 572 participants. Eighi specially trained teachers were in residence with the students. Between 50 and 70 experts from the university, government. business, and industry interacted with the students each year in an innovative science/technology/society (STS) program. An assignment toward the close of the program asked students to reflect on their experiences in residence at the university and write an essay comparing learning in the WOW program to learning in their schools. Those essays were the base for this study. This was a qualitative study using a discursive approach to emergent design to generate grounded theory. Document review, participant observation, and open-ended interviews were used to gather and triangulate data in five phases. Some of the factors that middle school students perceived as helpful to learning science were (a) experiencing the situations about which they were learning; (b) having live presentations by professional experts; (c) doing hands-on activities: (d) being active learners; (e) using inductive reasoning to generate new knowledge; (f) exploring transdisciplinary approaches to problem solving; (g) having adult mentors; (h) interacting with peers and adults; (i) establishing networks; (j) having close personal friends who shared their interest in learning; (k) trusting the individuals in their learning environment, including adults and students; and (1) experiencing a sense of self-reliance. The preceding information was used to generate a series of hypotheses which were woven into a theoretical model. This model suggests that middle school science teacher education would be enhanced by helping prospective and in-service teachers develop and implement strategies that build trust, provide immersion in learning, and use inductive reasoning. This model is currently being used as the theoretical base to convert a traditional junior high school in the South to a middle school.

Learning in networks: individual teacher learning versus organizational learning in a regional health-promoting schools network.

PubMed

Flaschberger, Edith; Gugglberger, Lisa; Dietscher, Christina

2013-12-01

To change a school into a health-promoting organization, organizational learning is required. The evaluation of an Austrian regional health-promoting schools network provides qualitative data on the views of the different stakeholders on learning in this network (steering group, network coordinator and representatives of the network schools; n = 26). Through thematic analysis and deep-structure analyses, the following three forms of learning in the network were identified: (A) individual learning through input offered by the network coordination, (B) individual learning between the network schools, i.e. through exchange between the representatives of different schools and (C) learning within the participating schools, i.e. organizational learning. Learning between (B) or within the participating schools (C) seems to be rare in the network; concepts of individual teacher learning are prevalent. Difficulties detected relating to the transfer of information from the network to the member schools included barriers to organizational learning such as the lack of collaboration, coordination and communication in the network schools, which might be effects of the school system in which the observed network is located. To ensure connectivity of the information offered by the network, more emphasis should be put on linking health promotion to school development and the core processes of schools.

Sampling in the Snow: High School Winter Field Experiences Provide Relevant, Real World Connections Between Scientific Practices and Disciplinary Core Ideas

NASA Astrophysics Data System (ADS)

Hanson, E. W.; Burakowski, E. A.

2014-12-01

For much of the northern United States, the months surrounding the winter solstice are times of increased darkness, low temperatures, and frozen landscapes. It's a time when many high school science educators, who otherwise would venture outside with their classes, hunker down and are wary of the outdoors. However, a plethora of learning opportunities lies just beyond the classroom. Working collaboratively, a high school science teacher and a snow scientist have developed multiple activities to engage students in the scientific process of collecting, analyzing and interpreting the winter world using snow data to (1) learn about the insulative properties of snow, and (2) to learn about the role of snow cover on winter climate through its reflective properties while participating in a volunteer network that collects snow depth, albedo (reflectivity), and density data. These outdoor field-based snow investigations incorporate Next Generation Science Standards (NGSS) and disciplinary core ideas, including ESS2.C: The roles of water in Earth's surface processes and ESS2.D: Weather and Climate. Additionally, the lesson plans presented address Common Core State Standards (CCSS) in Mathematics, including the creation and analysis of bar graphs and time series plots (CCSS.Math.HSS-ID.A.1) and xy scatter plots (CCSS.Math.HSS-ID.B.6). High school students participating in the 2013/2014 snow sampling season described their outdoor learning experience as "authentic" and "hands-on" as compared to traditional class indoors. They emphasized that learning outdoors was essential to their understanding of underlying content and concepts because they "learn through actual experience."

Remote observing with NASA's Deep Space Network

NASA Astrophysics Data System (ADS)

Kuiper, T. B. H.; Majid, W. A.; Martinez, S.; Garcia-Miro, C.; Rizzo, J. R.

2012-09-01

The Deep Space Network (DSN) communicates with spacecraft as far away as the boundary between the Solar System and the interstellar medium. To make this possible, large sensitive antennas at Canberra, Australia, Goldstone, California, and Madrid, Spain, provide for constant communication with interplanetary missions. We describe the procedures for radioastronomical observations using this network. Remote access to science monitor and control computers by authorized observers is provided by two-factor authentication through a gateway at the Jet Propulsion Laboratory (JPL) in Pasadena. To make such observations practical, we have devised schemes based on SSH tunnels and distributed computing. At the very minimum, one can use SSH tunnels and VNC (Virtual Network Computing, a remote desktop software suite) to control the science hosts within the DSN Flight Operations network. In this way we have controlled up to three telescopes simultaneously. However, X-window updates can be slow and there are issues involving incompatible screen sizes and multi-screen displays. Consequently, we are now developing SSH tunnel-based schemes in which instrument control and monitoring, and intense data processing, are done on-site by the remote DSN hosts while data manipulation and graphical display are done at the observer's host. We describe our approaches to various challenges, our experience with what worked well and lessons learned, and directions for future development.

Creating a Partnering Community Aimed to Foster Climate Literacy in the Southeastern United States

NASA Astrophysics Data System (ADS)

Rutherford, D.; McNeal, K. S.; Smith, R.; Hare, D.; Nair, U. S.

2011-12-01

The Climate Literacy Partnership in the Southeast (CLiPSE) is a part of the Climate Change Education Program supported by the National Science Foundation (http://CLiPSE-project.org). The established CLiPSE partnership is dedicated to improving climate literacy in the southeast through crafting a shared vision and strategic plan among stakeholders that promotes scientific formal and informal educational resources, materials and programs; a diverse network of key partnering organizations throughout the Southeastern United States (SE US); and effective public dialogues that address diverse learners and audiences and supports learning of climate, climate change, and its relevance upon human and environmental systems. The CLiPSE project has been successful in creating partnerships with more than fifty key stakeholders that stem from a few key publics such as agriculture, education, leisure, religious organizations, and culturally diverse communities. These key publics in the SE US frequently consist of individuals that place great trust in local, private efforts, and CLiPSE has realized the importance of the role of the partnering organizations in providing information through a trusted source. A second unique characteristic of the SE US is the predominately conservative and Protestant citizenry in the region. Working with and through these communities enhances climate change education outreach to this citizenry. The CLiPSE project rests on solid climate science and learning science research in order to formulate an effective plan with desired learning outcomes of critical thinking and civil conversation through effective communication strategies. This paper will present the CLiPSE model in reaching the key publics that traditionally hold ideologies that are traditionally perceived as incompatible with climate change science. We will present the strategies utilized to bring together experts and researchers in climate science, learning science, and social science with practitioners and leaders of key stakeholder groups to formulate a shared climate change education plan in the SE US that is uniquely formatted for each target audience. We will also share what we have learned from interacting with the leaders of our partnering organizations in crafting effective messages for their audiences and addressing learners' affective and cognitive domains.

Astronautics degrees for the space industry

NASA Astrophysics Data System (ADS)

Gruntman, M.; Brodsky, R. F.; Erwin, D. A.; Kunc, J. A.

2004-01-01

The Astronautics Program (http://astronautics.usc.edu) of the University of Southern California (USC) offers a full set of undergraduate and graduate degree programs in Aerospace Engineering with emphasis in Astronautics. The Bachelor of Science and Master of Science degree programs in Astronautics combine basic science and engineering classes with specialized classes in space technology. The Certificate in Astronautics targets practicing engineers and scientists who enter space-related fields and/or who want to obtain training in specific space-related areas. Many specialized graduate classes are taught by adjunct faculty working at the leading space companies. The Master of Science degree and Certificate are available entirely through the USC Distance Education Network (DEN). Today, the Internet allows us to reach students anywhere in the world through webcasting. The majority of our graduate students, as well as those pursuing the Certificate, work full time as engineers in the space industry and government research and development centers while earning their degrees. The new world of distance learning presents new challenges and opens new opportunities. Distance learning, and particularly the introduction of webcasting, transform the organization of the graduate program and class delivery. We describe in detail the program's academic focus, student reach, and structure of program components. Program development is illustrated by the student enrollment dynamics and related industrial trends; the lessons learned emphasize the importance of feedback from the students and from the space industry.

Sustaining a Stakeholder-Scientists Partnership in Co-producing Locally Relevant Data, Methods, and Tools

NASA Astrophysics Data System (ADS)

Asefa, T.

2017-12-01

This case study presents the experiences of two of the most successful boundary organizations that are engaged in co-producing decision relevant climate information for water resources management. The Water Utilities Climate Alliance (www.wucaonline.org) is a coalition of 11 of the nation's largest water utilities with customers base over 50 million. Whereas Florida Water and Climate Alliance (www.floridaWCA.org) is a state level collaborative Learning network that is engaged in co-exploration and co-development of actionable climate science. Lesson learned from these two structurally different organizations will be shared.

Equation-free and variable free modeling for complex/multiscale systems. Coarse-grained computation in science and engineering using fine-grained models

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kevrekidis, Ioannis G.

The work explored the linking of modern developing machine learning techniques (manifold learning and in particular diffusion maps) with traditional PDE modeling/discretization/scientific computation techniques via the equation-free methodology developed by the PI. The result (in addition to several PhD degrees, two of them by CSGF Fellows) was a sequence of strong developments - in part on the algorithmic side, linking data mining with scientific computing, and in part on applications, ranging from PDE discretizations to molecular dynamics and complex network dynamics.

E-Learning in Photogrammetry, Remote Sensing and Spatial Information Science

NASA Astrophysics Data System (ADS)

Vyas, Anjana; König, Gerhard

2016-06-01

Science and technology are evolving leaps and bounds. The advancements in GI-Science for natural and built environment helps in improving the quality of life. Learning through education and training needs to be at par with those advancements, which plays a vital role in utilization of technology. New technologies that creates new opportunities have enabled Geomatics to broaden the horizon (skills and competencies). Government policies and decisions support the use of geospatial science in various sectors of governance. Mapping, Land management, Urban planning, Environmental planning, Industrialization are some of the areas where the geomatics has become a baseline for decision making at national level. There is a need to bridge the gap between developments in geospatial science and its utilization and implementation. To prepare a framework for standardisation it is important to understand the theories of education and prevailing practices, with articulate goals exploring variety of teaching techniques. E-Learning is an erudition practice shaped for facilitating learning and improving performance by creating, using and managing appropriate technological processes and resources through digital and network-enabled technology. It is a shift from traditional education or training to ICT-based flexible and collaborative learning based on the community of learners, academia, professionals, experts and facilitators. Developments in e-learning is focussed on computer assisted learning which has become popular because of its potential for providing more flexible access to content and instruction at any time, from any place (Means et al, 2009). With the advent of the geo-spatial technology, fast development in the software and hardware, the demand for skilled manpower is increasing and the need is for training, education, research and dissemination. It suggests inter-organisational cooperation between academia, industry, government and international collaboration. There is a nascent need to adopt multi-specialisation approach to examine the issues and challenges of research in such a valued topic of education and training in multi-disciplinary areas. Learning involve a change in an individual's knowledge, ability to perform a skill, participate and communicate. There is considerable variation among the theories about the nature of this change. This paper derives from a scientific research grant received from ISPRS, reveals a summary result from assessing various theories and methods of evaluation of learning through education, system and structure of it for GeoInformatics.

Network biology: Describing biological systems by complex networks. Comment on "Network science of biological systems at different scales: A review" by M. Gosak et al.

NASA Astrophysics Data System (ADS)

Jalili, Mahdi

2018-03-01

I enjoyed reading Gosak et al. review on analysing biological systems from network science perspective [1]. Network science, first started within Physics community, is now a mature multidisciplinary field of science with many applications ranging from Ecology to biology, medicine, social sciences, engineering and computer science. Gosak et al. discussed how biological systems can be modelled and described by complex network theory which is an important application of network science. Although there has been considerable progress in network biology over the past two decades, this is just the beginning and network science has a great deal to offer to biology and medical sciences.

Teaching the bioinformatics of signaling networks: an integrated approach to facilitate multi-disciplinary learning.

PubMed

Korcsmaros, Tamas; Dunai, Zsuzsanna A; Vellai, Tibor; Csermely, Peter

2013-09-01

The number of bioinformatics tools and resources that support molecular and cell biology approaches is continuously expanding. Moreover, systems and network biology analyses are accompanied more and more by integrated bioinformatics methods. Traditional information-centered university teaching methods often fail, as (1) it is impossible to cover all existing approaches in the frame of a single course, and (2) a large segment of the current bioinformation can become obsolete in a few years. Signaling network offers an excellent example for teaching bioinformatics resources and tools, as it is both focused and complex at the same time. Here, we present an outline of a university bioinformatics course with four sample practices to demonstrate how signaling network studies can integrate biochemistry, genetics, cell biology and network sciences. We show that several bioinformatics resources and tools, as well as important concepts and current trends, can also be integrated to signaling network studies. The research-type hands-on experiences we show enable the students to improve key competences such as teamworking, creative and critical thinking and problem solving. Our classroom course curriculum can be re-formulated as an e-learning material or applied as a part of a specific training course. The multi-disciplinary approach and the mosaic setup of the course have the additional benefit to support the advanced teaching of talented students.

Cooperative strategies for forest science management and leadership in an increasingly complex and globalized world: Proceedings of a workshop; 23- 26 August 1998; Quebec City, Quebec, Canada

Treesearch

Lane G. Eskew; David R. DeYoe; Denver P. Burns; Jean-Claude Mercier

1999-01-01

The purpose of this workshop was to develop organizational networks to help achieve best practices in management and leadership of forest research and foster continuous learning toward that goal through organizational benchmarking. The papers and notes herein document the presentations and discussions of the workshop.

Music-therapy analyzed through conceptual mapping

NASA Astrophysics Data System (ADS)

Martinez, Rodolfo; de la Fuente, Rebeca

2002-11-01

Conceptual maps have been employed lately as a learning tool, as a modern study technique, and as a new way to understand intelligence, which allows for the development of a strong theoretical reference, in order to prove the research hypothesis. This paper presents a music-therapy analysis based on this tool to produce a conceptual mapping network, which ranges from magic through the rigor of the hard sciences.

On Enthusing Students about Big Data and Social Media Visualization and Analysis Using R, RStudio, and RMarkdown

ERIC Educational Resources Information Center

Stander, Julian; Dalla Valle, Luciana

2017-01-01

We discuss the learning goals, content, and delivery of a University of Plymouth intensive module delivered over four weeks entitled MATH1608PP Understanding Big Data from Social Networks, aimed at introducing students to a broad range of techniques used in modern Data Science. This module made use of R, accessed through RStudio, and some popular…

Outdoor Learning Can Help Children Flourish in Science and across the Curriculum--The FSC Takes a Lead

ERIC Educational Resources Information Center

Rose, Hannah; Kempton, Anneke

2014-01-01

The recent explosive growth of the Wild Network, which exists to champion and support connection with nature and wildness in children and young people, suggests that there is a groundswell of support for getting young people outdoors. Hannah Rose and Anneke Kempton of the Field Studies Council (FSC) explain why the outdoors is such an important…

Evaluation of Facebook© to Create an Online Learning Community in an Undergraduate Animal Science Class

ERIC Educational Resources Information Center

Whittaker, Alexandra L.; Howarth, Gordon S.; Lymn, Kerry A.

2014-01-01

There has been widespread comment on the use and impact of Web 2.0 technologies in education. Given the use of such technologies, particularly social networking sites such as Facebook amongst the student body, it would be remiss of educators to not consider their use as part of a pedagogical strategy. This paper provides a preliminary…

Student Agency: an Analysis of Students' Networked Relations Across the Informal and Formal Learning Domains

NASA Astrophysics Data System (ADS)

Rappa, Natasha Anne; Tang, Kok-Sing

2017-06-01

Agency is a construct facilitating our examination of when and how young people extend their own learning across contexts. However, little is known about the role played by adolescent learners' sense of agency. This paper reports two cases of students' agentively employing and developing science literacy practices—one in Singapore and the other in the USA. The paper illustrates how these two adolescent learners in different ways creatively accessed, navigated and integrated in-school and out-of-school discourses to support and nurture their learning of physics. Data were gleaned from students' work and interviews with students participating in a physics curricular programme in which they made linkages between their chosen out-of-school texts and several physics concepts learnt in school. The students' agentive moves were identified by means of situational mapping, which involved a relational analysis of the students' chosen artefacts and discourses across time and space. This relational analysis enabled us to address questions of student agency—how it can be effected, realised, construed and examined. It highlights possible ways to intervene in these networked relations to facilitate adolescents' agentive moves in their learning endeavours.

The Teen Science Café Network

NASA Astrophysics Data System (ADS)

Hall, M.; Mayhew, M. A.

2013-12-01

The 'Teen Cafè' phenomenon grew out of an NSF-funded experiment to bring the Cafè Scientifique model for engagement of the public with science and scientists to high school teenagers. Cafè Scientifique New Mexico (cafènm.org), now in its seventh year, has proven highly popular with high school teens for much the same reason as for adult Cafè programs: the blend of socializing in an attractive venue and interaction with a scientist on an interesting science topic. Teen Cafés also include exploration of the topic with hands-on activities. The success of the model has led to the creation of the national Teen Science Cafè Network (teensciencecafe.org. This first year of the new program, four 'Founding Members' of the Network-- in Florida, Colorado, North Carolina, and the St. Louis, Missouri region--started up Teen Cafè programs. Each applied the model with a unique flair appropriate to local institutions and demographics. Each Member in the Network runs Cafès in multiple local venues. We are now gearing up for our second year, and the Network is growing. Our Teen Cafè topics have covered a very wide range, from belly-button biodiversity to cyber-security to patterns of mega-earthquakes to a day in the life of a teen dolphin to corals on acid to emergency room medicine to alternative fuel cars. Presenters have come from a great variety of local institutions. Though they are popular with teens because they are fun and interesting, our evaluations have demonstrated that the programs are having a significant impact on participating teens' understanding of the nature of science, the work that scientists do, and the importance of science to their daily lives. We are also having success in training scientists to communicate effectively with this public audience. Presenters report strong satisfaction with their resulting quality of science communication. A surprising number have reported that their experience with the program has led them to think in a new way about the significance of their own research and how best to communicate it. In addition to Members who offer Teen Cafés, we have Affiliate Organizations, including professional societies and research centers, which are actively helping us introduce the Teen Science Café model to their membership. Rather than being a collection of static, independent entities, Network Members and Affiliate Organizations are part of a dynamic network, a community of practice with active sharing of lessons learned, ideas for Café topics and formats, professional development in communicating with the public, expertise in social media, and many other resources. We want the Network as a whole to be much greater than the sum of its parts. To ensure the integrity of the Network, we are exploring strategies for effective growth, mechanisms for continual professional development for Café leaders, and collaborative approaches to sustainability. Any organization wishing to start a Teen Cafè can do so by registering on the Teen Science Café Network website and agreeing to adhere to five 'Core Design Principles.' We have resources to help others start a Teen Café, as it is part of the ethic of the Network that existing Members will actively help new Members start and successfully run a Teen Café program.

An investigation of the relationships between junior high school students' (8th and 9th grades) background variables and structure of knowledge recall of biological content

NASA Astrophysics Data System (ADS)

Demetrius, Olive Joyce

The purpose of this study was to examine the relationships between Junior High School students' (8th and 9th grades) background variables (e.g. cognitive factors, prior knowledge, preference for science versus non-science activities, formal and informal activities) and structure of information recall of biological content. In addition, this study will illustrate how flow maps, a graphic display, designed to represent the sequential flow and cross linkage of ideas in information recalled by the learner can be used as a tool for analyzing science learning data. The participants (46 junior high school students) were taught a lesson on the human digestive system during which they were shown a model of the human torso. Their pattern of information recall was determined by using an interview technique to elicit their understanding of the functional anatomy of the human digestive system. The taped responses were later transcribed for construction of the flow map. The interview was also used to assess knowledge recall of biological content. The flow map, science interest questionnaire and the cognitive operations (based on content analysis of student's narrative) were used to analyze data from each respondent. This is a case study using individual subjects and interview techniques. The findings of this study are: (1) Based on flow map data higher academic ability students have more networking of ideas than low ability students. (2) A large percentage of 9th grade low ability students intend to pursue science/applied science course work after leaving school but they lack well organized ways of representing science knowledge in memory. (3) Content analysis of the narratives shows that students with more complex ideational networks use higher order cognitive thought processes compared to those with less networking of ideas. If students are to make a successful transition from low academic performance to high academic performance it seems that more emphasis should be placed on information networking skills. This is specifically likely to be productive for student currently performing on low academic ability levels and yet have high aspirations for pursuing science as a career.

Machine learning landscapes and predictions for patient outcomes

NASA Astrophysics Data System (ADS)

Das, Ritankar; Wales, David J.

2017-07-01

The theory and computational tools developed to interpret and explore energy landscapes in molecular science are applied to the landscapes defined by local minima for neural networks. These machine learning landscapes correspond to fits of training data, where the inputs are vital signs and laboratory measurements for a database of patients, and the objective is to predict a clinical outcome. In this contribution, we test the predictions obtained by fitting to single measurements, and then to combinations of between 2 and 10 different patient medical data items. The effect of including measurements over different time intervals from the 48 h period in question is analysed, and the most recent values are found to be the most important. We also compare results obtained for neural networks as a function of the number of hidden nodes, and for different values of a regularization parameter. The predictions are compared with an alternative convex fitting function, and a strong correlation is observed. The dependence of these results on the patients randomly selected for training and testing decreases systematically with the size of the database available. The machine learning landscapes defined by neural network fits in this investigation have single-funnel character, which probably explains why it is relatively straightforward to obtain the global minimum solution, or a fit that behaves similarly to this optimal parameterization.

Digital Learning Network Education Events for the Desert Research and Technology Studies

NASA Technical Reports Server (NTRS)

Paul, Heather L.; Guillory, Erika R.

2007-01-01

NASA s Digital Learning Network (DLN) reaches out to thousands of students each year through video conferencing and webcasting. As part of NASA s Strategic Plan to reach the next generation of space explorers, the DLN develops and delivers educational programs that reinforce principles in the areas of science, technology, engineering and mathematics. The DLN has created a series of live education videoconferences connecting the Desert Research and Technology Studies (RATS) field test to students across the United States. The programs are also extended to students around the world via live webcasting. The primary focus of the events is the Vision for Space Exploration. During the programs, Desert RATS engineers and scientists inform and inspire students about the importance of exploration and share the importance of the field test as it correlates with plans to return to the Moon and explore Mars. This paper describes the events that took place in September 2006.

An evaluation of a professional learning network for computer science teachers

NASA Astrophysics Data System (ADS)

Cutts, Quintin; Robertson, Judy; Donaldson, Peter; O'Donnell, Laurie

2017-01-01

This paper describes and evaluates aspects of a professional development programme for existing CS teachers in secondary schools (PLAN C) which was designed to support teachers at a time of substantial curricular change. The paper's particular focus is on the formation of a teacher professional development network across several hundred teachers and a wide geographical area. Evidence from a series of observations and teacher surveys over a two-year period is analysed with respect to the project's programme theory in order to illustrate not only whether it worked as intended, by why. Results indicate that the PLAN C design has been successful in increasing teachers' professional confidence and appears to have catalysed powerful change in attitudes to learning. Presentation of challenging pedagogical content knowledge and conceptual frameworks, high-quality teacher-led professional dialogue, along with the space for reflection and classroom trials, triggered examination of the teachers' own current practices.

Social Network and Content Analysis of the North American Carbon Program as a Scientific Community of Practice

NASA Technical Reports Server (NTRS)

Brown, Molly E.; Ihli, Monica; Hendrick, Oscar; Delgado-Arias, Sabrina; Escobar, Vanessa M.; Griffith, Peter

2015-01-01

The North American Carbon Program (NACP) was formed to further the scientific understanding of sources, sinks, and stocks of carbon in Earth's environment. Carbon cycle science integrates multidisciplinary research, providing decision-support information for managing climate and carbon-related change across multiple sectors of society. This investigation uses the conceptual framework of com-munities of practice (CoP) to explore the role that the NACP has played in connecting researchers into a carbon cycle knowledge network, and in enabling them to conduct physical science that includes ideas from social science. A CoP describes the communities formed when people consistently engage in shared communication and activities toward a common passion or learning goal. We apply the CoP model by using keyword analysis of abstracts from scientific publications to analyze the research outputs of the NACP in terms of its knowledge domain. We also construct a co-authorship network from the publications of core NACP members, describe the structure and social pathways within the community. Results of the content analysis indicate that the NACP community of practice has substantially expanded its research on human and social impacts on the carbon cycle, contributing to a better understanding of how human and physical processes interact with one another. Results of the co-authorship social network analysis demonstrate that the NACP has formed a tightly connected community with many social pathways through which knowledge may flow, and that it has also expanded its network of institutions involved in carbon cycle research over the past seven years.

Education Through Exploration: Evaluating the Unknown

NASA Astrophysics Data System (ADS)

Anbar, A. D.

2015-12-01

Mastery of the peculiar and powerful practices of science is increasingly important for the average citizen. With the rise of the Internet, most of human knowledge is at our fingertips. As content becomes a commodity, success and survival aren't about who knows the most, but who is better able to explore the unknown, actively applying and extending knowledge through critical thinking and hypothesis-driven problem-solving. This applies to the economic livelihoods of individuals and to society at large as we grapple with climate change and other science-infused challenges. Unfortunately, science is too often taught as an encyclopedic collection of settled facts to be mastered rather than as a process of exploration that embraces curiosity, inquiry, testing, and communication to reduce uncertainty about the unknown. This problem is exacerbated by the continued prevalence of teacher-centric pedagogy, which promotes learning-from-authority and passive learning. The initial wave of massively open online courses (MOOCs) generally mimic this teaching style in virtual form. It is hypothesized that emerging digital teaching technologies can help address this challenge at Internet scale in "next generation" MOOCs and flipped classroom experiences. Interactive simulations, immersive virtual field trips, gamified elements, rapid adaptive feedback, intelligent tutoring systems, and personalized pathways, should motivate and enhance learning. Through lab-like projects and tutorials, students should be able to construct knowledge from interactive experiences, modeling the authentic practice of science while mastering complex concepts. Freed from lecturing, teaching staff should be available for direct and intense student-teacher interactions. These claims are difficult to evaluate with traditional assessment instruments, but digital technologies provide powerful new ways to evaluate student learning and learn from student behaviors. We will describe ongoing experiences with such technologies, and future plans, drawing from the experiences of > 2500 students who have taken the Habitable Worlds fully online general education class at ASU, and as part of the new Inspark Science Teaching Network.

The need to connect: on the cell biology of synapses, behaviors, and networks in science

PubMed Central

Colón-Ramos, Daniel A.

2016-01-01

My laboratory is interested in the cell biology of the synapse. Synapses, which are points of cellular communication between neurons, were first described by Santiago Ramón y Cajal as “protoplasmic kisses that appear to constitute the final ecstasy of an epic love story.” Who would not want to work on that?! My lab examines the biological mechanisms neurons use to find and connect to each other. How are synapses formed during development, maintained during growth, and modified during learning? In this essay, I reflect about my scientific journey to the synapse, the cell biological one, but also a metaphorical synapse—my role as a point of contact between the production of knowledge and its dissemination. In particular, I discuss how the architecture of scientific networks propels knowledge production but can also exclude certain groups in science. PMID:27799494

Citizen Science in Libraries: Results and Insights from a Unique NASA Collaboration

NASA Astrophysics Data System (ADS)

Janney, D. W.; Schwerin, T. G.; Riebeek Kohl, H.; Dusenbery, P.; LaConte, K.; Taylor, J.; Weaver, K. L. K.

2017-12-01

Libraries are local community centers and hubs for learning, with more and more libraries responding to the need to increase science literacy and support 21st century skills by adding STEM programs and resources for patrons of all ages. A collaboration has been developed between two NASA Science Mission Directorate projects - the NASA Earth Science Education Collaborative and NASA@ My Library - each bringing unique STEM assets and networks to support library staff and bring authentic STEM experiences and resources to learners in public library settings. The collaboration used Earth Day 2017 as a high profile event to engage and support 100 libraries across the U.S. (>50% serving rural communities), in developing locally-relevant programs and events that incorporated cloud observing and resources using NASA GLOBE Observer (GO) citizen science program. GO cloud observations are helping NASA scientists understand clouds from below (the ground) and above (from space). Clouds play an important role in transferring energy from the Sun to different parts of the Earth system. Because clouds can change rapidly, scientists need frequent observations from citizen scientists. Insights from the library focus groups and evaluation include promising practices, requested resources, programming ideas and approaches, particularly approaches to leveraging NASA subject matter experts and networks, to support local library programming.

A Person-Centered, Registry-Based Learning Health System for Palliative Care: A Path to Coproducing Better Outcomes, Experience, Value, and Science

PubMed Central

Kamal, Arif H.; Kirkland, Kathryn B.; Meier, Diane E.; Nelson, Eugene C.; Pantilat, Steven Z.

2018-01-01

Abstract Background: Palliative care offers an approach to the care of people with serious illness that focuses on quality of life and aligning care with individual and family goals, and values in the context of what is medically achievable. Objective: Measurement of the impact of palliative care is critical for determining what works for which patients in what settings, to learn, improve care, and ensure access to high value care for people with serious illness. Methods: A learning health system that includes patients and families partnering with clinicians and care teams, is directly linked to a registry to support networks for improvement and research, and offers an ideal framework for measuring what matters to a range of stakeholders interested in improving care for this population. Measurements: Measurement focuses on the individual patient and family experience as the fundamental outcome of interest around which all care delivery is organized. Results: We describe an approach to codesigning and implementing a palliative care registry that functions as a learning health system, by combining patient and family inputs and clinical data to support person-centered care, quality improvement, accountability, transparency, and scientific research. Discussion: The potential for a palliative care learning health system that, by design, brings together enriched information environments to support coproduction of healthcare and facilitated peer networks to support patients and families, collaborative clinician networks to support palliative care program improvement, and collaboratories to support research and the application of research to benefit individual patients is immense. PMID:29091509

Understanding Classrooms through Social Network Analysis: A Primer for Social Network Analysis in Education Research.

PubMed

Grunspan, Daniel Z; Wiggins, Benjamin L; Goodreau, Steven M

2014-01-01

Social interactions between students are a major and underexplored part of undergraduate education. Understanding how learning relationships form in undergraduate classrooms, as well as the impacts these relationships have on learning outcomes, can inform educators in unique ways and improve educational reform. Social network analysis (SNA) provides the necessary tool kit for investigating questions involving relational data. We introduce basic concepts in SNA, along with methods for data collection, data processing, and data analysis, using a previously collected example study on an undergraduate biology classroom as a tutorial. We conduct descriptive analyses of the structure of the network of costudying relationships. We explore generative processes that create observed study networks between students and also test for an association between network position and success on exams. We also cover practical issues, such as the unique aspects of human subjects review for network studies. Our aims are to convince readers that using SNA in classroom environments allows rich and informative analyses to take place and to provide some initial tools for doing so, in the process inspiring future educational studies incorporating relational data. © 2014 D. Z. Grunspan et al. CBE—Life Sciences Education © 2014 The American Society for Cell Biology. This article is distributed by The American Society for Cell Biology under license from the author(s). It is available to the public under an Attribution–Noncommercial–Share Alike 3.0 Unported Creative Commons License (http://creativecommons.org/licenses/by-nc-sa/3.0).

Citizen Science & MPA Monitoring: Informing adaptive management through enriched local knowledge systems

NASA Astrophysics Data System (ADS)

Meyer, R.; Freitag, A.; McGregor, A.; Whiteman, E.

2013-12-01

Along the California coast, a wealth of capacity exists among individuals, groups and organizations collecting scientific data. This citizen science can take many forms, from spontaneous observations of seabirds to organized surveys of nearshore reefs. Yet, as is often the case, state resource managers have struggled to find ways to access and use this scientific information in decision-making. A unique opportunity exists to alter this status-quo. California has the largest network of marine protected areas (MPAs) in the nation with more than 100 MPAs statewide. Monitoring is essential to inform adaptive management of this network. Traditionally, MPA monitoring has been the purview of academic or agency scientists. Yet, there is increasing recognition that this approach, while playing an important role, is unlikely by itself to provide a sustainable path forward. An opportunity therefore exists to understand how to sustainably and cost-effectively expand the capacity or human capital invested in monitoring and ocean stewardship. In this presentation we will share our collaborative approach to development of a new framework for incorporating citizen science into a partnerships-based portfolio of MPA monitoring in California. We will present initial findings and lessons learned from a broad review of published and gray literature, as well as reflections from interviews and participant observations with citizen science groups in the Central Coast region of California's MPA network. Through research, engagement with existing citizen science programs, and involvement of natural resource managers, we are identifying general best practices and specific opportunities for these groups to collaborate effectively, and for citizen science to play a constructive ongoing role in adaptive management of MPAs.

Cryosphere Communication from Knowledge to Action: Polar Educators International

NASA Astrophysics Data System (ADS)

Crowley, S.

2012-12-01

Evidence from the recent IPY meetings shows that education and outreach of the 2007-08 IPY touched 24 million people; we intend to grow that number. As a legacy of IPY and as a direct action of IPY Montreal, we announced the establishment of Polar Educators International - a global professional network for those that educate in, for, and about the Polar Regions. We intend to move polar science forward by connecting the cultures and enthusiasm of polar education across the globe. The founding members come from polar and non-polar nations around the world. The new group draws together museums, schools, universities, science centers, formal and informal education, expeditions, NGOs, companies, governmental organizations, and non-profits. Working across national, disciplinary, and age group boundaries, we want to improve polar science & education for the next generation of policy makers, entrepreneurs, explorers, citizen scientists, journalists and educators; as well as the the public. The new network of more than 200 leading educators, scientists, and community members will develop innovative resources to communicate polar science. We intend to engage those learning and teaching about the polar regions, and thereby change the terms of debate, and the framework of education to rekindle student and public engagement with global environmental changes. We are committed to engaging our membership and have clear directions from our recent survey and report from the community. This presentation will address the needs put forth from our membership and where the organization will go in the future to inform a professional network on science and outreach in the polar regions.

Human category learning 2.0.

PubMed

Ashby, F Gregory; Maddox, W Todd

2011-04-01

During the 1990s and early 2000s, cognitive neuroscience investigations of human category learning focused on the primary goal of showing that humans have multiple category-learning systems and on the secondary goals of identifying key qualitative properties of each system and of roughly mapping out the neural networks that mediate each system. Many researchers now accept the strength of the evidence supporting multiple systems, and as a result, during the past few years, work has begun on the second generation of research questions-that is, on questions that begin with the assumption that humans have multiple category-learning systems. This article reviews much of this second generation of research. Topics covered include (1) How do the various systems interact? (2) Are there different neural systems for categorization and category representation? (3) How does automaticity develop in each system? and (4) Exactly how does each system learn? © 2010 New York Academy of Sciences.

The Worldviews Network: Transformative Global Change Education in Immersive Environments

NASA Astrophysics Data System (ADS)

Hamilton, H.; Yu, K. C.; Gardiner, N.; McConville, D.; Connolly, R.; "Irving, Lindsay", L. S.

2011-12-01

Our modern age is defined by an astounding capacity to generate scientific information. From DNA to dark matter, human ingenuity and technologies create an endless stream of data about ourselves and the world of which we are a part. Yet we largely founder in transforming information into understanding, and understanding into rational action for our society as a whole. Earth and biodiversity scientists are especially frustrated by this impasse because the data they gather often point to a clash between Earth's capacity to sustain life and the decisions that humans make to garner the planet's resources. Immersive virtual environments offer an underexplored link in the translation of scientific data into public understanding, dialogue, and action. The Worldviews Network is a collaboration of scientists, artists, and educators focused on developing best practices for the use of immersive environments for science-based ecological literacy education. A central tenet of the Worldviews Network is that there are multiple ways to know and experience the world, so we are developing scientifically accurate, geographically relevant, and culturally appropriate programming to promote ecological literacy within informal science education programs across the United States. The goal of Worldviews Network is to offer transformative learning experiences, in which participants are guided on a process integrating immersive visual explorations, critical reflection and dialogue, and design-oriented approaches to action - or more simply, seeing, knowing, and doing. Our methods center on live presentations, interactive scientific visualizations, and sustainability dialogues hosted at informal science institutions. Our approach uses datasets from the life, Earth, and space sciences to illuminate the complex conditions that support life on earth and the ways in which ecological systems interact. We are leveraging scientific data from federal agencies, non-governmental organizations, and our own research to develop a library of immersive visualization stories and templates that explore ecological relationships across time at cosmic, global, and bioregional scales, with learning goals aligned to climate and earth science literacy principles. These experiential narratives are used to increase participants' awareness of global change issues as well as to engage them in dialogues and design processes focused on steps they can take within their own communities to systemically address these interconnected challenges. More than 600 digital planetariums in the U.S. collectively represent a pioneering opportunity for distributing Earth systems messages over large geographic areas. By placing the viewer-and Earth itself-within the context of the rest of the universe, digital planetariums can uniquely provide essential transcalar perspectives on the complex interdependencies of Earth's interacting physical and biological systems. The Worldviews Network is creating innovative, data-driven approaches for engaging the American public in dialogues about human-induced global changes.

Virtual working systems to support R&D groups

NASA Astrophysics Data System (ADS)

Dew, Peter M.; Leigh, Christine; Drew, Richard S.; Morris, David; Curson, Jayne

1995-03-01

The paper reports on the progress at Leeds University to build a Virtual Science Park (VSP) to enhance the University's ability to interact with industry, grow its applied research and workplace learning activities. The VSP exploits the advances in real time collaborative computing and networking to provide an environment that meets the objectives of physically based science parks without the need for the organizations to relocate. It provides an integrated set of services (e.g. virtual consultancy, workbased learning) built around a structured person- centered information model. This model supports the integration of tools for: (a) navigating around the information space; (b) browsing information stored within the VSP database; (c) communicating through a variety of Person-to-Person collaborative tools; and (d) the ability to the information stored in the VSP including the relationships to other information that support the underlying model. The paper gives an overview of a generic virtual working system based on X.500 directory services and the World-Wide Web that can be used to support the Virtual Science Park. Finally the paper discusses some of the research issues that need to be addressed to fully realize a Virtual Science Park.

An inclusive Research Education Community (iREC): Impact of the SEA-PHAGES program on research outcomes and student learning.

PubMed

Hanauer, David I; Graham, Mark J; Betancur, Laura; Bobrownicki, Aiyana; Cresawn, Steven G; Garlena, Rebecca A; Jacobs-Sera, Deborah; Kaufmann, Nancy; Pope, Welkin H; Russell, Daniel A; Jacobs, William R; Sivanathan, Viknesh; Asai, David J; Hatfull, Graham F

2017-12-19

Engaging undergraduate students in scientific research promises substantial benefits, but it is not accessible to all students and is rarely implemented early in college education, when it will have the greatest impact. An inclusive Research Education Community (iREC) provides a centralized scientific and administrative infrastructure enabling engagement of large numbers of students at different types of institutions. The Science Education Alliance-Phage Hunters Advancing Genomics and Evolutionary Science (SEA-PHAGES) is an iREC that promotes engagement and continued involvement in science among beginning undergraduate students. The SEA-PHAGES students show strong gains correlated with persistence relative to those in traditional laboratory courses regardless of academic, ethnic, gender, and socioeconomic profiles. This persistent involvement in science is reflected in key measures, including project ownership, scientific community values, science identity, and scientific networking. Copyright © 2017 the Author(s). Published by PNAS.

The Upper Midwest Aerospace Consortium Environmental Information Network: Building ‘Learning Communities’ in the Northern Great Plains

USGS Publications Warehouse

Welling, Leigh; Seielstad, George; McClurg, Pat; Fagre, Daniel B.

2000-01-01

In the last two decades alone, the U.S. and large portions of the world have witnessed what can be aptly be described as an explosion of scientific information and technological innovations that has permeated almost every aspect of our lives. Given these trends, it is clear that science and the understanding of science are becoming increasingly more relevant and essential to decision-makers and the decision-making process. Every environmental issue confronting society has an undisputed scientific underpinning. Understanding the implications of the science underpinning issues of particular importance to the health and well being of society constitutes the basis for making more informed and enlightened decisions. However obvious this linkage may be, many factors continue to serve as impediments to the broader understanding and incorporation of science into policy- and decision-making processes, as perhaps is best exemplified by the case of climate science.

An inclusive Research Education Community (iREC): Impact of the SEA-PHAGES program on research outcomes and student learning

PubMed Central

Hanauer, David I.; Graham, Mark J.; Betancur, Laura; Bobrownicki, Aiyana; Cresawn, Steven G.; Garlena, Rebecca A.; Jacobs-Sera, Deborah; Kaufmann, Nancy; Pope, Welkin H.; Russell, Daniel A.; Jacobs, William R.; Sivanathan, Viknesh; Asai, David J.

2017-01-01

Engaging undergraduate students in scientific research promises substantial benefits, but it is not accessible to all students and is rarely implemented early in college education, when it will have the greatest impact. An inclusive Research Education Community (iREC) provides a centralized scientific and administrative infrastructure enabling engagement of large numbers of students at different types of institutions. The Science Education Alliance–Phage Hunters Advancing Genomics and Evolutionary Science (SEA-PHAGES) is an iREC that promotes engagement and continued involvement in science among beginning undergraduate students. The SEA-PHAGES students show strong gains correlated with persistence relative to those in traditional laboratory courses regardless of academic, ethnic, gender, and socioeconomic profiles. This persistent involvement in science is reflected in key measures, including project ownership, scientific community values, science identity, and scientific networking. PMID:29208718

Use of a virtual human performance laboratory to improve integration of mathematics and biology in sports science curricula in Sweden and the United States.

PubMed

Garza, D; Besier, T; Johnston, T; Rolston, B; Schorsch, A; Matheson, G; Annerstedt, C; Lindh, J; Rydmark, M

2007-01-01

New fields such as bioengineering are exploring the role of the physical sciences in traditional biological approaches to problems, with exciting results in device innovation, medicine, and research biology. The integration of mathematics, biomechanics, and material sciences into the undergraduate biology curriculum will better prepare students for these opportunities and enhance cooperation among faculty and students at the university level. We propose the study of sports science as the basis for introduction of this interdisciplinary program. This novel integrated approach will require a virtual human performance laboratory dual-hosted in Sweden and the United States. We have designed a course model that involves cooperative learning between students at Göteborg University and Stanford University, utilizes new technologies, encourages development of original research and will rely on frequent self-assessment and reflective learning. We will compare outcomes between this course and a more traditional didactic format as well as assess the effectiveness of multiple web-hosted virtual environments. We anticipate the grant will result in a network of original faculty and student research in exercise science and pedagogy as well as provide the opportunity for implementation of the model in more advance training levels and K-12 programs.

Proceedings of the Seventh International Symposium on Methodologies for Intelligent Systems (Poster Session)

DOE Office of Scientific and Technical Information (OSTI.GOV)

Harber, K.S.

1993-05-01

This report contains the following papers: Implications in vivid logic; a self-learning bayesian expert system; a natural language generation system for a heterogeneous distributed database system; competence-switching'' managed by intelligent systems; strategy acquisition by an artificial neural network: Experiments in learning to play a stochastic game; viewpoints and selective inheritance in object-oriented modeling; multivariate discretization of continuous attributes for machine learning; utilization of the case-based reasoning method to resolve dynamic problems; formalization of an ontology of ceramic science in CLASSIC; linguistic tools for intelligent systems; an application of rough sets in knowledge synthesis; and a relational model for imprecise queries.more » These papers have been indexed separately.« less

Proceedings of the Seventh International Symposium on Methodologies for Intelligent Systems (Poster Session)

DOE Office of Scientific and Technical Information (OSTI.GOV)

Harber, K.S.

1993-05-01

This report contains the following papers: Implications in vivid logic; a self-learning Bayesian Expert System; a natural language generation system for a heterogeneous distributed database system; ``competence-switching`` managed by intelligent systems; strategy acquisition by an artificial neural network: Experiments in learning to play a stochastic game; viewpoints and selective inheritance in object-oriented modeling; multivariate discretization of continuous attributes for machine learning; utilization of the case-based reasoning method to resolve dynamic problems; formalization of an ontology of ceramic science in CLASSIC; linguistic tools for intelligent systems; an application of rough sets in knowledge synthesis; and a relational model for imprecise queries.more » These papers have been indexed separately.« less

SkWwatch: Introducing European Youth to the World of Scientific Research through Interactive Utilisation of a Global Network of Robotic Telescopes

NASA Astrophysics Data System (ADS)

Sotiriou, M.; Vrazopoulos, H.; Ioannou, P.; Sotiriou, S.; Vagenas, E.

2005-12-01

The SkyWatch project is co-fi nanced by the European Community, within the FP6 framework of Science and Society, The SkyWatch consortium is composed by the following partners: Q-PLAN (GR), EDEN - Open Classroom (UK), Astrophysics Research Institute - Liverpool John Moores University (UK), European Physical Society (FR), Ellinogermaniki Agogi (GR), Stockholm University (SE), SCIENCE PROJECTS (UK) and University of Duisburg-Essen (DE). The aim of the SkyWatch project is to build up the number of youngsters involved in a series of science projects to create a virtual community of prospective young researchers promoting scientifi c culture. The project will allow young people to access and use robotic telescopes remotely in real-time, perform observations, analyze data and results and fi nally to develop and suggest solutions to selected research/scientifi c topics, all achieved through an innovative web-based learning environment. The dissemination of the project's activities is also served by a European Science Contest on science topics and projects, a series of popular science distance learning courses (Science Days) for European youth, promotion of concepts and ideas of science of a multidisciplinary nature: astronomy, physics, mathematics, chemistry, etc. The young participants are prompted to organize teams (school classes, groups of students, etc.) and to design, develop and implement projects and activities with the use of robotic telescopes under the guidance and the continuous support of a team of experts.

The Virtual Learning Commons: Supporting Science Education with Emerging Technologies

NASA Astrophysics Data System (ADS)

Pennington, D. D.; Gandara, A.; Gris, I.

2012-12-01

The Virtual Learning Commons (VLC), funded by the National Science Foundation Office of Cyberinfrastructure CI-Team Program, is a combination of Semantic Web, mash up, and social networking tools that supports knowledge sharing and innovation across scientific disciplines in research and education communities and networks. The explosion of scientific resources (data, models, algorithms, tools, and cyberinfrastructure) challenges the ability of educators to be aware of resources that might be relevant to their classes. Even when aware, it can be difficult to understand enough about those resources to develop classroom materials. Often emerging data and technologies have little documentation, especially about their application. The VLC tackles this challenge by providing mechanisms for individuals and groups of educators to organize Web resources into virtual collections, and engage each other around those collections in order to a) learn about potentially relevant resources that are available; b) design classes that leverage those resources; and c) develop course syllabi. The VLC integrates Semantic Web functionality for structuring distributed information, mash up functionality for retrieving and displaying information, and social media for discussing/rating information. We are working to provide three views of information that support educators in different ways: 1. Innovation Marketplace: supports users as they find others teaching similar courses, where they are located, and who they collaborate with; 2. Conceptual Mapper: supports educators as they organize their thinking about the content of their class and related classes taught by others; 3. Curriculum Designer: supports educators as they generate a syllabus and find Web resources that are relevant. This presentation will discuss the innovation and learning theories that have informed design of the VLC, hypotheses about the use of emerging technologies to support innovation in classrooms, and will include a brief demonstration of these capabilities.

NASA Applied Sciences' DEVELOP National Program: a unique model cultivating capacity in the geosciences

NASA Astrophysics Data System (ADS)

Ross, K. W.; Favors, J. E.; Childs-Gleason, L. M.; Ruiz, M. L.; Rogers, L.; Allsbrook, K. N.

2013-12-01

The NASA DEVELOP National Program takes a unique approach to cultivating the next generation of geoscientists through interdisciplinary research projects that address environmental and public policy issues through the application of NASA Earth observations. Competitively selected teams of students, recent graduates, and early career professionals take ownership of project proposals outlining basic application concepts and have ten weeks to research core scientific challenges, engage partners and end-users, demonstrate prototypical solutions, and finalize and document their results and outcomes. In this high pressure, results-driven environment emerging geoscience professionals build strong networks, hone effective communication skills, and learn how to call on the varied strengths of a multidisciplinary team to achieve difficult objectives. The DEVELOP approach to workforce development has a variety of advantages over classic apprenticeship-style internship systems. Foremost is the experiential learning of grappling with real-world applied science challenges as a primary actor instead of as an observer or minor player. DEVELOP participants gain experience that fosters personal strengths and service to others, promoting a balance of leadership and teamwork in order to successfully address community needs. The program also advances understanding of Earth science data and technology amongst participants and partner organizations to cultivate skills in managing schedules, risks and resources to best optimize outcomes. Individuals who come through the program gain experience and networking opportunities working within NASA and partner organizations that other internship and academic activities cannot replicate providing not only skill development but an introduction to future STEM-related career paths. With the competitive nature and growing societal role of science and technology in today's global community, DEVELOP fosters collaboration and advances environmental understanding by promoting and improving the ability of the future geoscience workforce to recognize, understand, and address environmental issues facing the Earth.

Engaging the broader community in biodiversity research: the concept of the COMBER pilot project for divers in ViBRANT

PubMed Central

Arvanitidis, Christos; Faulwetter, Sarah; Chatzigeorgiou, Georgios; Penev, Lyubomir; Bánki, Olaf; Dailianis, Thanos; Pafilis, Evangelos; Kouratoras, Michail; Chatzinikolaou, Eva; Fanini, Lucia; Vasileiadou, Aikaterini; Pavloudi, Christina; Vavilis, Panagiotis; Koulouri, Panayota; Dounas, Costas

2011-01-01

Abstract This paper discusses the design and implementation of a citizen science pilot project, COMBER (Citizens’ Network for the Observation of Marine BiodivERsity, http://www.comber.hcmr.gr), which has been initiated under the ViBRANT EU e-infrastructure. It is designed and implemented for divers and snorkelers who are interested in participating in marine biodiversity citizen science projects. It shows the necessity of engaging the broader community in the marine biodiversity monitoring and research projects, networks and initiatives. It analyses the stakeholders, the industry and the relevant markets involved in diving activities and their potential to sustain these activities. The principles, including data policy and rewards for the participating divers through their own data, upon which this project is based are thoroughly discussed. The results of the users analysis and lessons learned so far are presented. Future plans include promotion, links with citizen science web developments, data publishing tools, and development of new scientific hypotheses to be tested by the data collected so far. PMID:22207815

Science in the Public Eye: Leveraging Partnerships-An Introduction.

PubMed

Merson, Martha; Allen, Louise C; Hristov, Nickolay I

2018-06-22

With stories of struggle and dramatic breakthroughs, science has incredible potential to interest the public. However, as the rhetoric of outrage surrounds controversies over science policy there is an urgent need for credible, trusted voices that frame science issues in a way that resonates with a diverse public. A network of informal educators, park rangers, museum docents and designers, and zoo and aquarium interpreters are prepared to do so during millions of visits a year; just where science stories are most meaningfully told-in the places where members of the public are open to learning. Scientific researchers can benefit from partnerships with these intermediaries who are accorded status for their trustworthiness and good will, who have expertise in translating the science using language, metaphors, encounters, and experiences that are appropriate for non-experts. In this volume, we describe and probe examples wherein scientists work productively with informal educators and designers, artists, staff of federal agencies, citizen scientists, and volunteers who bring science into the public eye.

Design and Evaluation of Dedicated Smartphone Applications for Collaborative Science Education

NASA Astrophysics Data System (ADS)

Fertitta, John A., Jr.

2011-12-01

Over the past several years, the use of scientific probes is becoming more common in science classrooms. The goal of teaching with these science probes is to engage students in inquiry-based learning. However, they are often complicated and stationary, forcing experiments to remain in the classroom and limiting their use. The Internet System for Networked Sensor Experimentation (iSENSE) was created to address these limitations. iSENSE is a web-system for storing and visualizing sensor data. The project also includes a hardware package, the PINPoint, that interfaces to existing probes, and acts as a probe itself. As the mobile phone industry continues to advance, we are beginning to see smartphones that are just as powerful, if not more powerful, than many desktop computers. These devices are often equipped with advanced sensors, making them as capable as some science probes at a lower cost. With this background, this thesis explores the use of smartphones in secondary school science classrooms. By collaborating with one teacher, three custom applications were developed for four separate curriculum-based learning activities. The smartphones replaced existing traditional tools and science probes. Some data collected with the smartphones were uploaded to the iSENSE web-system for analysis. Student use of the smartphones and the subsequent scientific visualizations using the iSENSE web-system were observed. A teacher interview was conducted afterward. It was found that a collaborative design process involving the teacher resulted in the successful integration of smartphone applications into learning activities. In one case, the smartphones and use of iSENSE did not improve the students' understanding of the learning objectives. In several others, however, the smartphones out-performed traditional probeware as a data collector, and with the classroom teachers guidance, the iSENSE web-system facilitated more in-depth discussions of the data.

Analyzing the Watershed Dynamics project as an example of successful science and education partnerships

NASA Astrophysics Data System (ADS)

Buzby, C. K.; Jona, K.

2009-12-01

The Watershed Dynamics project is a partnership between Northwestern University, the Consortium of Universities for the Advancement of Hydrologic Science (CUAHSI), and the GLOBE Program (Global Learning and Observations to Benefit the Environment). The goal of the project is to develop inquiry-based educational materials that use authentic scientific data and analysis techniques to teach students about the watershed. The relationship between Northwestern, CUAHSI, and GLOBE allows each partner to contribute to the development of the project in the area of their expertise. Science researchers from CUAHSI share science content knowledge and data access through the development of their Hydrologic Information System (HIS). Curriculum developers at Northwestern write inquiry-based curriculum using GIS technology to access and analyze live data. The GLOBE Program is a worldwide hands-on, primary and secondary school-based science education program that provides teacher training opportunities to a network of teachers around the world. This partnership allows each partner to bring their area of expertise to the project and make the best use of one another's resources. The Watershed Dynamics project can serve as a model for future partnerships between the science and education communities. The Office of Science, Technology, Engineering, and Math Education Partnerships (OSEP) at Northwestern is a service organization that supports Northwestern researchers in developing proposals and implementing research projects that incorporate K-12 educational components, particularly in the fields of science, technology, engineering and mathematics (STEM). OSEP assists faculty with the development of sound plans for education and outreach that reflect current research on learning and educational reform and provides expertise in STEM education materials development, learning technologies, and professional development for K-12 teachers and facilitators in informal education institutions. Resources such as OSEP can pair scientists with educational organizations so that science outreach programs can be sustainable.

From Atmospheric Scientist to Data Scientist

NASA Astrophysics Data System (ADS)

Knuth, S. L.

2015-12-01

Most of my career has been spent analyzing data from research projects in the atmospheric sciences. I spent twelve years researching boundary layer interactions in the polar regions, which included five field seasons in the Antarctic. During this time, I got both a M.S. and Ph.D. in atmospheric science. I learned most of my data science and programming skills throughout this time as part of my research projects. When I graduated with my Ph.D., I was looking for a new and fresh opportunity to enhance the skills I already had while learning more advanced technical skills. I found a position at the University of Colorado Boulder as a Data Research Specialist with Research Computing, a group that provides cyber infrastructure services, including high-speed networking, large-scale data storage, and supercomputing, to university students and researchers. My position is the perfect merriment between advanced technical skills and "softer" skills, while at the same time understanding exactly what the busy scientist needs to understand about their data. I have had the opportunity to help shape our university's data education system, a development that is still evolving. This presentation will detail my career story, the lessons I have learned, my daily work in my new position, and some of the exciting opportunities that opened up in my new career.

Large-scale deep learning for robotically gathered imagery for science

NASA Astrophysics Data System (ADS)

Skinner, K.; Johnson-Roberson, M.; Li, J.; Iscar, E.

2016-12-01

With the explosion of computing power, the intelligence and capability of mobile robotics has dramatically increased over the last two decades. Today, we can deploy autonomous robots to achieve observations in a variety of environments ripe for scientific exploration. These platforms are capable of gathering a volume of data previously unimaginable. Additionally, optical cameras, driven by mobile phones and consumer photography, have rapidly improved in size, power consumption, and quality making their deployment cheaper and easier. Finally, in parallel we have seen the rise of large-scale machine learning approaches, particularly deep neural networks (DNNs), increasing the quality of the semantic understanding that can be automatically extracted from optical imagery. In concert this enables new science using a combination of machine learning and robotics. This work will discuss the application of new low-cost high-performance computing approaches and the associated software frameworks to enable scientists to rapidly extract useful science data from millions of robotically gathered images. The automated analysis of imagery on this scale opens up new avenues of inquiry unavailable using more traditional manual or semi-automated approaches. We will use a large archive of millions of benthic images gathered with an autonomous underwater vehicle to demonstrate how these tools enable new scientific questions to be posed.

Cyberlearning for Climate Literacy: Challenges and Opportunities

NASA Astrophysics Data System (ADS)

McCaffrey, M. S.; Buhr, S. M.; Gold, A. U.; Ledley, T. S.; Mooney, M. E.; Niepold, F.

2010-12-01

Cyberlearning tools provide cost and carbon-efficient avenues for fostering a climate literate society through online engagement with learners. With climate change education becoming a Presidential Priority in 2009, funding for grants from NSF, NASA and NOAA is leading to a new generation of cyberlearning resources that supplement existing online resources. This paper provides an overview of challenges and opportunities relating to the online delivery of high quality, often complex climate science by examining several existing and emerging efforts, including the Climate Literacy and Energy Awareness Network (CLEAN,) a National Science Digital Library Pathway, the development by CIRES Education and Outreach of the Inspiring Climate Education Excellence (ICEE) online course, TERC’s Earth Exploration Toolbook (EET,) DataTools, and EarthLab modules, the NOAA Climate Stewards Education Program (CSEP) that utilizes the NSTA E-Learning Center, online efforts by members of the Federation of Earth Science Information Partners (ESIP), UCAR’s Climate Discovery program, and the Climate Adaptation, Mitigation e-Learning (CAMeL) project. In addition, we will summarize outcomes of the Cyberlearning for Climate Literacy workshop held in Washington DC in the Fall of 2009 and examine opportunities for teachers to develop and share their own lesson plans based on climate-related web resources that currently lack built-in learning activities, assessments or teaching tips.

Growing scientists: A partnership between a university and a school district

NASA Astrophysics Data System (ADS)

Woods, Teresa Marie

Precollege science education in the United States has virtually always been influenced by university scientists to one degree or another. Partnership models for university scientist---school district collaborations are being advocated to replace outreach models. Although the challenges for such partnerships are well documented, the means of fostering successful and sustainable science education partnerships are not well studied. This study addresses this need by empirically researching a unique scientist-educator partnership between a university and a school district utilizing case study methods. The development of the partnership, emerging issues, and multiple perspectives of participants were examined in order to understand the culture of the partnership and identify means of fostering successful science education partnerships. The findings show the partnership was based on a strong network of face-to-face relationships that fostered understanding, mutual learning and synergy. Specific processes instituted ensured equity and respect, and created a climate of trust so that an evolving common vision was maintained. The partnership provided synergy and resilience during the recent economic crisis, indicating the value of partnerships when public education institutions must do more with less. High staff turnover, however, especially of a key leader, threatened the partnership, pointing to the importance of maintaining multiple-level integration between institutions. The instrumental roles of a scientist-educator coordinator in bridging cultures and nurturing the collaborative environment are elucidated. Intense and productive collaborations between teams of scientists and educators helped transform leading edge disciplinary science content into school science learning. The innovative programs that resulted not only suggest important roles science education partnerships can play in twenty-first century learning, but they also shed light on the processes of educational innovation itself. Further, the program and curriculum development revealed insights into areas of teaching and learning. Multiple perspectives of participants were considered in this study, with student perspectives demonstrating the critical importance of investigating student views in future studies. When educational institutions increasingly need to address a diverse population, and scientists increasingly want to recruit diverse students into the fields of science, partnerships show promise in creating a seamless K-20+ continuum of science education.

Learning Science, Learning about Science, Doing Science: Different Goals Demand Different Learning Methods

ERIC Educational Resources Information Center

Hodson, Derek

2014-01-01

This opinion piece paper urges teachers and teacher educators to draw careful distinctions among four basic learning goals: learning science, learning about science, doing science and learning to address socio-scientific issues. In elaboration, the author urges that careful attention is paid to the selection of teaching/learning methods that…

Educational Technology in the 21st Century. Joint Hearing before the Committee on Science and the Committee on Economic and Educational Opportunities. House of Representatives, One Hundred Fourth Congress, First Session.

ERIC Educational Resources Information Center

Congress of the U.S., Washington, DC. House Committee on Science and Technology.

This document presents witness testimony and supplemental materials from a Congressional hearing addressing the potential as well as the affordability of educational technology and the classroom of the future, where computers and computer networks will increasingly aid teachers and facilitate learning. Those presenting prepared statements are…

The Challenge of the Seamless Force: The Role of Informal Networks in Battlespace

DTIC Science & Technology

2005-06-01

10th International Command and Control Research and Technology Symposium THE FUTURE OF C2 Symposium Theme: Lessons Learned Title: The... Technology Organisation Fern Hill Park Department of Defence Canberra ACT 2600 AUSTRALIA Phone +61 2 6256 6219 Fax +61 2 6256 6233...Email Leoni.Warne@dsto.defence.gov.au Derek Bopping Defence Science and Technology Organisation Fern Hill Park Department of Defence Canberra

Processing NASA Earth Science Data on Nebula Cloud

NASA Technical Reports Server (NTRS)

Chen, Aijun; Pham, Long; Kempler, Steven

2012-01-01

Three applications were successfully migrated to Nebula, including S4PM, AIRS L1/L2 algorithms, and Giovanni MAPSS. Nebula has some advantages compared with local machines (e.g. performance, cost, scalability, bundling, etc.). Nebula still faces some challenges (e.g. stability, object storage, networking, etc.). Migrating applications to Nebula is feasible but time consuming. Lessons learned from our Nebula experience will benefit future Cloud Computing efforts at GES DISC.

Disseminating NASA-based science through NASA's Universe of Learning: Girls STEAM Ahead

NASA Astrophysics Data System (ADS)

Marcucci, E.; Meinke, B. K.; Smith, D. A.; Ryer, H.; Slivinski, C.; Kenney, J.; Arcand, K.; Cominsky, L.

2017-12-01

The Girls STEAM Ahead with NASA (GSAWN) initiative partners the NASA's Universe of Learning (UoL) resources with public libraries to provide NASA-themed activities for girls and their families. The program expands upon the legacy program, NASA Science4Girls and Their Families, in celebration of National Women's History Month. Program resources include hands-on activities for engaging girls, such as coding experiences and use of remote telescopes, complementary exhibits, and professional development for library partner staff. The science-institute-embedded partners in NASA's UoL are uniquely poised to foster collaboration between scientists with content expertise and educators with pedagogy expertise. The thematic topics related to NASA Astrophysics enable audiences to experience the full range of NASA scientific and technical disciplines and the different career skills each requires. For example, an activity may focus on understanding exoplanets, methods of their detection, and characteristics that can be determined remotely. The events focus on engaging underserved and underrepresented audiences in Science, Technology, Engineering, and Mathematics (STEM) via use of research-based best practices, collaborations with libraries, partnerships with local and national organizations (e.g. National Girls Collaborative Project or NGCP), and remote engagement of audiences. NASA's UoL collaborated with another NASA STEM Activation partner, NASA@ My Library, to announce GSAWN to their extensive STAR_Net network of libraries. This partnership between NASA SMD-funded Science learning and literacy teams has included NASA@ My Library hosting a professional development webinar featuring a GSAWN activity, a newsletter and blog post about the program, and plans for future exhibit development. This presentation will provide an overview of the program's progress to engage girls and their families through the development and dissemination of NASA-based science programming.

The Sea Floor: A Living Learning Residential Community

NASA Astrophysics Data System (ADS)

Guentzel, J. L.; Rosch, E.; Stoughton, M. A.; Bowyer, R.; Mortensen, K.; Smith, M.

2016-02-01

Living learning communities are collaborations between university housing and academic departments designed to enhance the overall student experience by integrating classroom/laboratory learning, student life and extracurricular activities. At Coastal Carolina University, the residential community associated with the Marine Science program is known as the Sea Floor. Students selected to become members of the Sea Floor remain "in residence" for two consecutive semesters. These students are first-time freshman that share a common course connection. This course is usually Introduction to Marine Science (MSCI 111) or MSCI 399s, which are one credit field/laboratory centered internships. The common course connection is designed so residents can establish and maintain an educational dialog with their peers. Activities designed to enhance the students' networking skills and educational and social development skills include monthly lunches with marine science faculty and dinner seminars with guest speakers from academia, industry and government. Additionally, each semester several activities outside the classroom are planned so that students can more frequently interact with themselves and their faculty and staff partners. These activities include field trips to regional aquariums, local boat trips that include water sample collection and analysis, and an alternative spring break trip to the Florida Keys to study the marine environment firsthand. The resident advisor that supervises the Sea Floor is usually a sophomore or junior marine science major. This provides the residents with daily communication and mentoring from a marine science major that is familiar with the marine science program and residence life. Assessment activities include: a university housing community living survey, student interest housing focus groups, fall to spring and fall to fall retention, and evaluation of program advisors and program activities.

Choose Your Own Adventure: Designing an Environment that Supports NASA Scientists' Goals in Education, Outreach, and Inreach

NASA Astrophysics Data System (ADS)

DeWitt, S.

2015-12-01

What is your communication goal? That is the opening question asked in NASA's first agency-wide science communication leadership development program. Many scientists know what they want to communicate, some know to whom they'd like to communicate, but few can clearly express why they want to do it. So what? First, being clear about one's goal is critical in being able to measure success. Second, when asked to think critically about communication goals, some scientists may shift their communication behaviors and practices to better achieve those goals. To that end, NASA has designed a deep learning experience for scientists (and engineers and others) to: critically examine their communication goals; learn techniques for getting to know their intended audience; and develop and apply specific communication skills to a project of their choice. Participants in this program come into the classroom with projects that span a wide spectrum including: formal and informal education, public outreach, media interviews, public speaking, stakeholder briefings, and internal awareness-building. Through expert advisors, professional coaches and peer networks, this program provides a supportive environment for individuals to workshop their project in the classroom and receive feedback before, during, and after the project is complete. This program also provides an opportunity for scientists and other participants to learn more about communication at NASA, and to directly influence the agency's science communication culture through action learning. In this presentation, I will summarize NASA's dual-design science communication leadership development program and present some lessons-learned, participant feedback and evaluation data from the initial course offerings.

Collaborative learning in networks.

PubMed

Mason, Winter; Watts, Duncan J

2012-01-17

Complex problems in science, business, and engineering typically require some tradeoff between exploitation of known solutions and exploration for novel ones, where, in many cases, information about known solutions can also disseminate among individual problem solvers through formal or informal networks. Prior research on complex problem solving by collectives has found the counterintuitive result that inefficient networks, meaning networks that disseminate information relatively slowly, can perform better than efficient networks for problems that require extended exploration. In this paper, we report on a series of 256 Web-based experiments in which groups of 16 individuals collectively solved a complex problem and shared information through different communication networks. As expected, we found that collective exploration improved average success over independent exploration because good solutions could diffuse through the network. In contrast to prior work, however, we found that efficient networks outperformed inefficient networks, even in a problem space with qualitative properties thought to favor inefficient networks. We explain this result in terms of individual-level explore-exploit decisions, which we find were influenced by the network structure as well as by strategic considerations and the relative payoff between maxima. We conclude by discussing implications for real-world problem solving and possible extensions.

Collaborative learning in networks

PubMed Central

Mason, Winter; Watts, Duncan J.

2012-01-01

Complex problems in science, business, and engineering typically require some tradeoff between exploitation of known solutions and exploration for novel ones, where, in many cases, information about known solutions can also disseminate among individual problem solvers through formal or informal networks. Prior research on complex problem solving by collectives has found the counterintuitive result that inefficient networks, meaning networks that disseminate information relatively slowly, can perform better than efficient networks for problems that require extended exploration. In this paper, we report on a series of 256 Web-based experiments in which groups of 16 individuals collectively solved a complex problem and shared information through different communication networks. As expected, we found that collective exploration improved average success over independent exploration because good solutions could diffuse through the network. In contrast to prior work, however, we found that efficient networks outperformed inefficient networks, even in a problem space with qualitative properties thought to favor inefficient networks. We explain this result in terms of individual-level explore-exploit decisions, which we find were influenced by the network structure as well as by strategic considerations and the relative payoff between maxima. We conclude by discussing implications for real-world problem solving and possible extensions. PMID:22184216

Quantum Entanglement in Neural Network States

NASA Astrophysics Data System (ADS)

Deng, Dong-Ling; Li, Xiaopeng; Das Sarma, S.

2017-04-01

Machine learning, one of today's most rapidly growing interdisciplinary fields, promises an unprecedented perspective for solving intricate quantum many-body problems. Understanding the physical aspects of the representative artificial neural-network states has recently become highly desirable in the applications of machine-learning techniques to quantum many-body physics. In this paper, we explore the data structures that encode the physical features in the network states by studying the quantum entanglement properties, with a focus on the restricted-Boltzmann-machine (RBM) architecture. We prove that the entanglement entropy of all short-range RBM states satisfies an area law for arbitrary dimensions and bipartition geometry. For long-range RBM states, we show by using an exact construction that such states could exhibit volume-law entanglement, implying a notable capability of RBM in representing quantum states with massive entanglement. Strikingly, the neural-network representation for these states is remarkably efficient, in the sense that the number of nonzero parameters scales only linearly with the system size. We further examine the entanglement properties of generic RBM states by randomly sampling the weight parameters of the RBM. We find that their averaged entanglement entropy obeys volume-law scaling, and the meantime strongly deviates from the Page entropy of the completely random pure states. We show that their entanglement spectrum has no universal part associated with random matrix theory and bears a Poisson-type level statistics. Using reinforcement learning, we demonstrate that RBM is capable of finding the ground state (with power-law entanglement) of a model Hamiltonian with a long-range interaction. In addition, we show, through a concrete example of the one-dimensional symmetry-protected topological cluster states, that the RBM representation may also be used as a tool to analytically compute the entanglement spectrum. Our results uncover the unparalleled power of artificial neural networks in representing quantum many-body states regardless of how much entanglement they possess, which paves a novel way to bridge computer-science-based machine-learning techniques to outstanding quantum condensed-matter physics problems.

Radio frequency interference mitigation using deep convolutional neural networks

NASA Astrophysics Data System (ADS)

Akeret, J.; Chang, C.; Lucchi, A.; Refregier, A.

2017-01-01

We propose a novel approach for mitigating radio frequency interference (RFI) signals in radio data using the latest advances in deep learning. We employ a special type of Convolutional Neural Network, the U-Net, that enables the classification of clean signal and RFI signatures in 2D time-ordered data acquired from a radio telescope. We train and assess the performance of this network using the HIDE &SEEK radio data simulation and processing packages, as well as early Science Verification data acquired with the 7m single-dish telescope at the Bleien Observatory. We find that our U-Net implementation is showing competitive accuracy to classical RFI mitigation algorithms such as SEEK's SUMTHRESHOLD implementation. We publish our U-Net software package on GitHub under GPLv3 license.

Communal Cooperation in Sensor Networks for Situation Management

NASA Technical Reports Server (NTRS)

Jones, Kennie H.; Lodding, Kenneth N.; Olariu, Stephan; Wilson, Larry; Xin,Chunsheng

2006-01-01

Situation management is a rapidly evolving science where managed sources are processed as realtime streams of events and fused in a way that maximizes comprehension, thus enabling better decisions for action. Sensor networks provide a new technology that promises ubiquitous input and action throughout an environment, which can substantially improve information available to the process. Here we describe a NASA program that requires improvements in sensor networks and situation management. We present an approach for massively deployed sensor networks that does not rely on centralized control but is founded in lessons learned from the way biological ecosystems are organized. In this approach, fully distributed data aggregation and integration can be performed in a scalable fashion where individual motes operate based on local information, making local decisions that achieve globally-meaningful results. This exemplifies the robust, fault-tolerant infrastructure required for successful situation management systems.

Artificial neural networks in evaluation and optimization of modified release solid dosage forms.

PubMed

Ibrić, Svetlana; Djuriš, Jelena; Parojčić, Jelena; Djurić, Zorica

2012-10-18

Implementation of the Quality by Design (QbD) approach in pharmaceutical development has compelled researchers in the pharmaceutical industry to employ Design of Experiments (DoE) as a statistical tool, in product development. Among all DoE techniques, response surface methodology (RSM) is the one most frequently used. Progress of computer science has had an impact on pharmaceutical development as well. Simultaneous with the implementation of statistical methods, machine learning tools took an important place in drug formulation. Twenty years ago, the first papers describing application of artificial neural networks in optimization of modified release products appeared. Since then, a lot of work has been done towards implementation of new techniques, especially Artificial Neural Networks (ANN) in modeling of production, drug release and drug stability of modified release solid dosage forms. The aim of this paper is to review artificial neural networks in evaluation and optimization of modified release solid dosage forms.

Artificial Neural Networks in Evaluation and Optimization of Modified Release Solid Dosage Forms

PubMed Central

Ibrić, Svetlana; Djuriš, Jelena; Parojčić, Jelena; Djurić, Zorica

2012-01-01

Implementation of the Quality by Design (QbD) approach in pharmaceutical development has compelled researchers in the pharmaceutical industry to employ Design of Experiments (DoE) as a statistical tool, in product development. Among all DoE techniques, response surface methodology (RSM) is the one most frequently used. Progress of computer science has had an impact on pharmaceutical development as well. Simultaneous with the implementation of statistical methods, machine learning tools took an important place in drug formulation. Twenty years ago, the first papers describing application of artificial neural networks in optimization of modified release products appeared. Since then, a lot of work has been done towards implementation of new techniques, especially Artificial Neural Networks (ANN) in modeling of production, drug release and drug stability of modified release solid dosage forms. The aim of this paper is to review artificial neural networks in evaluation and optimization of modified release solid dosage forms. PMID:24300369

Learning Science and the Science of Learning. Science Educators' Essay Collection.

ERIC Educational Resources Information Center

Bybee, Rodger W., Ed.

This yearbook addresses critical issues in science learning and teaching. Contents are divided into four sections: (1) "How Do Students Learn Science?"; (2) "Designing Curriculum for Student Learning"; (3) "Teaching That Enhances Student Learning"; and (4) "Assessing Student Learning." Papers include: (1) "How Students Learn and How Teachers…

Quantifying Cyber-Resilience Against Resource-Exhaustion Attacks

DOE Office of Scientific and Technical Information (OSTI.GOV)

Fink, Glenn A.; Griswold, Richard L.; Beech, Zachary W.

2014-07-11

Resilience in the information sciences is notoriously difficult to define much less to measure. But in mechanical engi- neering, the resilience of a substance is mathematically defined as the area under the stress vs. strain curve. We took inspiration from mechanics in an attempt to define resilience precisely for information systems. We first examine the meaning of resilience in language and engineering terms and then translate these definitions to information sciences. Then we tested our definitions of resilience for a very simple problem in networked queuing systems. We discuss lessons learned and make recommendations for using this approach in futuremore » work.« less

Learning Analytics for Networked Learning Models

ERIC Educational Resources Information Center

Joksimovic, Srecko; Hatala, Marek; Gaševic, Dragan

2014-01-01

Teaching and learning in networked settings has attracted significant attention recently. The central topic of networked learning research is human-human and human-information interactions occurring within a networked learning environment. The nature of these interactions is highly complex and usually requires a multi-dimensional approach to…

EarthCache as a Tool to Promote Earth-Science in Public School Classrooms

NASA Astrophysics Data System (ADS)

Gochis, E. E.; Rose, W. I.; Klawiter, M.; Vye, E. C.; Engelmann, C. A.

2011-12-01

Geoscientists often find it difficult to bridge the gap in communication between university research and what is learned in the public schools. Today's schools operate in a high stakes environment that only allow instruction based on State and National Earth Science curriculum standards. These standards are often unknown by academics or are written in a style that obfuscates the transfer of emerging scientific research to students in the classroom. Earth Science teachers are in an ideal position to make this link because they have a background in science as well as a solid understanding of the required curriculum standards for their grade and the pedagogical expertise to pass on new information to their students. As part of the Michigan Teacher Excellence Program (MiTEP), teachers from Grand Rapids, Kalamazoo, and Jackson school districts participate in 2 week field courses with Michigan Tech University to learn from earth science experts about how the earth works. This course connects Earth Science Literacy Principles' Big Ideas and common student misconceptions with standards-based education. During the 2011 field course, we developed and began to implement a three-phase EarthCache model that will provide a geospatial interactive medium for teachers to translate the material they learn in the field to the students in their standards based classrooms. MiTEP participants use GPS and Google Earth to navigate to Michigan sites of geo-significance. At each location academic experts aide participants in making scientific observations about the locations' geologic features, and "reading the rocks" methodology to interpret the area's geologic history. The participants are then expected to develop their own EarthCache site to be used as pedagogical tool bridging the gap between standards-based classroom learning, contemporary research and unique outdoor field experiences. The final phase supports teachers in integrating inquiry based, higher-level learning student activities to EarthCache sites near their own urban communities, or in regional areas such as nature preserves and National Parks. By working together, MiTEP participants are developing a network of regional EarthCache sites and shared lesson plans which explore places that are meaningful to students while simultaneously connecting them to geologic concepts they are learning in school. We believe that the MiTEP EarthCaching model will help participants emerge as leaders of inquiry style, and virtual place-based educators within their districts.

Astronautics Degrees for Space Industry

NASA Astrophysics Data System (ADS)

Gruntman, M.; Brodsky, R.; Erwin, D.; Kunc, J.

The Astronautics Program (http://astronautics.usc.edu) of the University of Southern California (USC) offers a full set of undergraduate and graduate degree programs in Aerospace Engineering with emphasis in Astronautics. The Bachelor of Science degree program in Astronautics combines basic science and engineering classes with specialized astronautics classes. The Master of Science degree program in Astronautics offers classes in various areas of space technology. The Certificate in Astronautics targets practicing engineers and scientists who enter space-related fields and/or who want to obtain training in specific space-related areas. Many specialized graduate classes are taught by adjunct faculty working at the leading space companies. The Master of Science degree and Certificate are available through the USC Distance Education Network (DEN). Today, the Internet allows us to reach students anywhere in the world through webcasting. The majority of our graduate students, as well as those pursuing the Certificate, work full time as engineers in the space industry and government research and development centers. The new world of distance learning presents new challenges and opens new opportunities. We show how the transformation of distance learning and particularly the introduction of webcasting transform organization of the program and class delivery. We will describe in detail the academic focus of the program, student reach, and structure of program components. Program development is illustrated by the student enrollment dynamics and related industrial trends; the lessons learned emphasize the importance of feedback from the students and from the space industry.

Image Quality Assessment of JPEG Compressed Mars Science Laboratory Mastcam Images using Convolutional Neural Networks

NASA Astrophysics Data System (ADS)

Kerner, H. R.; Bell, J. F., III; Ben Amor, H.

2017-12-01

The Mastcam color imaging system on the Mars Science Laboratory Curiosity rover acquires images within Gale crater for a variety of geologic and atmospheric studies. Images are often JPEG compressed before being downlinked to Earth. While critical for transmitting images on a low-bandwidth connection, this compression can result in image artifacts most noticeable as anomalous brightness or color changes within or near JPEG compression block boundaries. In images with significant high-frequency detail (e.g., in regions showing fine layering or lamination in sedimentary rocks), the image might need to be re-transmitted losslessly to enable accurate scientific interpretation of the data. The process of identifying which images have been adversely affected by compression artifacts is performed manually by the Mastcam science team, costing significant expert human time. To streamline the tedious process of identifying which images might need to be re-transmitted, we present an input-efficient neural network solution for predicting the perceived quality of a compressed Mastcam image. Most neural network solutions require large amounts of hand-labeled training data for the model to learn the target mapping between input (e.g. distorted images) and output (e.g. quality assessment). We propose an automatic labeling method using joint entropy between a compressed and uncompressed image to avoid the need for domain experts to label thousands of training examples by hand. We use automatically labeled data to train a convolutional neural network to estimate the probability that a Mastcam user would find the quality of a given compressed image acceptable for science analysis. We tested our model on a variety of Mastcam images and found that the proposed method correlates well with image quality perception by science team members. When assisted by our proposed method, we estimate that a Mastcam investigator could reduce the time spent reviewing images by a minimum of 70%.

Building Capacity: The National Network for Ocean and Climate Change Interpretation

NASA Astrophysics Data System (ADS)

Spitzer, W.

2014-12-01

In the US, more than 1,500 informal science venues (science centers, museums, aquariums, zoos, nature centers, national parks) are visited annually by 61% of the population. Research shows that these visitors are receptive to learning about climate change, and expect these institutions to provide reliable information about environmental issues and solutions. These informal science venues play a critical role in shaping public understanding. Since 2007, the New England Aquarium has led a national effort to increase the capacity of informal science venues to effectively communicate about climate change. We are now leading the NSF-funded National Network for Ocean and Climate Change Interpretation (NNOCCI), partnering with the Association of Zoos and Aquariums, FrameWorks Institute, Woods Hole Oceanographic Institution, Monterey Bay Aquarium, and National Aquarium, with evaluation conducted by the New Knowledge Organization, Pennsylvania State University, and Ohio State University. After two years of project implementation, key findings include: 1. Importance of adaptive management - We continue to make ongoing changes in training format, content, and roles of facilitators and participants. 2. Impacts on interpreters - We have multiple lines of evidence for changes in knowledge, skills, attitudes, and behaviors. 3. Social radiation - Trained interpreters have a significant influence on their friends, family and colleagues. 4. Visitor impacts - "Exposure to "strategically framed" interpretation does change visitors' perceptions about climate change. 5. Community of practice - We are seeing evidence of growing participation, leadership, and sustainability. 6. Diffusion of innovation - Peer networks are facilitating dissemination throughout the informal science education community. Over the next five years, NNOCCI will achieve a systemic national impact across the ISE community, embed its work within multiple ongoing regional and national climate change education networks, and leave an enduring legacy of impact. We believe that the NNOCCI project can serve as a model for how ISEIs can address other complex environmental, scientific, and policy topics as well.

Learning Science, Learning about Science, Doing Science: Different goals demand different learning methods

NASA Astrophysics Data System (ADS)

Hodson, Derek

2014-10-01

This opinion piece paper urges teachers and teacher educators to draw careful distinctions among four basic learning goals: learning science, learning about science, doing science and learning to address socio-scientific issues. In elaboration, the author urges that careful attention is paid to the selection of teaching/learning methods that recognize key differences in learning goals and criticizes the common assertion that 'current wisdom advocates that students best learn science through an inquiry-oriented teaching approach' on the grounds that conflating the distinction between learning by inquiry and engaging in scientific inquiry is unhelpful in selecting appropriate teaching/learning approaches.

Impact of the Cancer Prevention and Control Research Network

PubMed Central

Ribisl, Kurt M.; Fernandez, Maria E.; Friedman, Daniela B.; Hannon, Peggy; Leeman, Jennifer; Moore, Alexis; Olson, Lindsay; Ory, Marcia; Risendal, Betsy; Sheble, Laura; Taylor, Vicky; Williams, Rebecca; Weiner, Bryan J.

2018-01-01

The Cancer Prevention and Control Research Network (CPCRN) is a thematic network dedicated to accelerating the adoption of evidence-based cancer prevention and control practices in communities by advancing dissemination and implementation science. Funded by the Centers for Disease Control and Prevention and National Cancer Institute, CPCRN has operated at two levels: Each participating Network Center conducts research projects with primarily local partners as well as multicenter collaborative research projects with state and national partners. Through multicenter collaboration, thematic networks leverage the expertise, resources, and partnerships of participating centers to conduct research projects collectively that might not be feasible individually. Although multicenter collaboration often is advocated, it is challenging to promote and assess. Using bibliometric network analysis and other graphical methods, this paper describes CPCRN’s multicenter publication progression from 2004 to 2014. Searching PubMed, Scopus, and Web of Science in 2014 identified 249 peer-reviewed CPCRN publications involving two or more centers out of 6,534 total. The research and public health impact of these multicenter collaborative projects initiated by CPCRN during that 10-year period were then examined. CPCRN established numerous workgroups around topics such as: 2-1-1, training and technical assistance, colorectal cancer control, federally qualified health centers, cancer survivorship, and human papillomavirus. The paper discusses the challenges that arise in promoting multicenter collaboration and the strategies that CPCRN uses to address those challenges. The lessons learned should broadly interest those seeking to promote multisite collaboration to address public health problems, such as cancer prevention and control. PMID:28215371

Neural Networks for Modeling and Control of Particle Accelerators

DOE Office of Scientific and Technical Information (OSTI.GOV)

Edelen, A. L.; Biedron, S. G.; Chase, B. E.

Myriad nonlinear and complex physical phenomena are host to particle accelerators. They often involve a multitude of interacting systems, are subject to tight performance demands, and should be able to run for extended periods of time with minimal interruptions. Often times, traditional control techniques cannot fully meet these requirements. One promising avenue is to introduce machine learning and sophisticated control techniques inspired by artificial intelligence, particularly in light of recent theoretical and practical advances in these fields. Within machine learning and artificial intelligence, neural networks are particularly well-suited to modeling, control, and diagnostic analysis of complex, nonlinear, and time-varying systems,more » as well as systems with large parameter spaces. Consequently, the use of neural network-based modeling and control techniques could be of significant benefit to particle accelerators. For the same reasons, particle accelerators are also ideal test-beds for these techniques. Moreover, many early attempts to apply neural networks to particle accelerators yielded mixed results due to the relative immaturity of the technology for such tasks. For the purpose of this paper is to re-introduce neural networks to the particle accelerator community and report on some work in neural network control that is being conducted as part of a dedicated collaboration between Fermilab and Colorado State University (CSU). We also describe some of the challenges of particle accelerator control, highlight recent advances in neural network techniques, discuss some promising avenues for incorporating neural networks into particle accelerator control systems, and describe a neural network-based control system that is being developed for resonance control of an RF electron gun at the Fermilab Accelerator Science and Technology (FAST) facility, including initial experimental results from a benchmark controller.« less

Neural Networks for Modeling and Control of Particle Accelerators

NASA Astrophysics Data System (ADS)

Edelen, A. L.; Biedron, S. G.; Chase, B. E.; Edstrom, D.; Milton, S. V.; Stabile, P.

2016-04-01

Particle accelerators are host to myriad nonlinear and complex physical phenomena. They often involve a multitude of interacting systems, are subject to tight performance demands, and should be able to run for extended periods of time with minimal interruptions. Often times, traditional control techniques cannot fully meet these requirements. One promising avenue is to introduce machine learning and sophisticated control techniques inspired by artificial intelligence, particularly in light of recent theoretical and practical advances in these fields. Within machine learning and artificial intelligence, neural networks are particularly well-suited to modeling, control, and diagnostic analysis of complex, nonlinear, and time-varying systems, as well as systems with large parameter spaces. Consequently, the use of neural network-based modeling and control techniques could be of significant benefit to particle accelerators. For the same reasons, particle accelerators are also ideal test-beds for these techniques. Many early attempts to apply neural networks to particle accelerators yielded mixed results due to the relative immaturity of the technology for such tasks. The purpose of this paper is to re-introduce neural networks to the particle accelerator community and report on some work in neural network control that is being conducted as part of a dedicated collaboration between Fermilab and Colorado State University (CSU). We describe some of the challenges of particle accelerator control, highlight recent advances in neural network techniques, discuss some promising avenues for incorporating neural networks into particle accelerator control systems, and describe a neural network-based control system that is being developed for resonance control of an RF electron gun at the Fermilab Accelerator Science and Technology (FAST) facility, including initial experimental results from a benchmark controller.

Neural Networks for Modeling and Control of Particle Accelerators

DOE PAGES

Edelen, A. L.; Biedron, S. G.; Chase, B. E.; ...

2016-04-01

Myriad nonlinear and complex physical phenomena are host to particle accelerators. They often involve a multitude of interacting systems, are subject to tight performance demands, and should be able to run for extended periods of time with minimal interruptions. Often times, traditional control techniques cannot fully meet these requirements. One promising avenue is to introduce machine learning and sophisticated control techniques inspired by artificial intelligence, particularly in light of recent theoretical and practical advances in these fields. Within machine learning and artificial intelligence, neural networks are particularly well-suited to modeling, control, and diagnostic analysis of complex, nonlinear, and time-varying systems,more » as well as systems with large parameter spaces. Consequently, the use of neural network-based modeling and control techniques could be of significant benefit to particle accelerators. For the same reasons, particle accelerators are also ideal test-beds for these techniques. Moreover, many early attempts to apply neural networks to particle accelerators yielded mixed results due to the relative immaturity of the technology for such tasks. For the purpose of this paper is to re-introduce neural networks to the particle accelerator community and report on some work in neural network control that is being conducted as part of a dedicated collaboration between Fermilab and Colorado State University (CSU). We also describe some of the challenges of particle accelerator control, highlight recent advances in neural network techniques, discuss some promising avenues for incorporating neural networks into particle accelerator control systems, and describe a neural network-based control system that is being developed for resonance control of an RF electron gun at the Fermilab Accelerator Science and Technology (FAST) facility, including initial experimental results from a benchmark controller.« less

Snow, Ice, & Satellites: An Early Career Researcher's Experience with Twitter

NASA Astrophysics Data System (ADS)

Pope, A.; Scambos, T. A.

2014-12-01

As a doctoral student, I was lucky enough to be able to experiment with a variety of communication and outreach activities (classroom visits, museum events, science festivals, blogging, social media, etc.) to build communication skills and learn how to talk about my science without writing a journal article. More importantly, the wide range of experience helped me identify what worked for me. My favorite way to share my science now? Twitter. To many, Twitter is a frivolous platform for sharing snippets 140 characters or less. To me, however, it is how I can connect directly with the elusive "wider public" and share my science. Specifically, I use satellite imagery (mostly Landsat 8) to study glaciers around the world. I look at long-term change related to climate, and I also investigate new, innovative ways to use satellite imagery to better understand glaciers and ice sheets. Luckily for me, my research is very visual. Whether fieldwork snapshots or satellite data, images make for great, shareable, accessible tweets. In this presentation, I propose to share my experience of tweeting as an early career researcher. I will include successful strategies (e.g. particular #hashtags, creating new content, using story-telling, timely tweets), as well as some not-so-successful attempts. I will also talk about how I built my Twitter network. In addition to anecdotes, I will include evaluation of my Twitter activity using available metrics and analytics (e.g. followers, favorites, re-tweets, Klout score, etc.). While misunderstood by many in the scientific community, Twitter is a platform increasingly being adopted by researchers. Used correctly, it can be a great tool for connecting directly with an interested, non-technical audience eager to learn about your research. With my experiences and evaluation, I will show how both scientists and the networks that they join and create can benefit by using Twitter as a platform for science communication.

Revisiting the silence of Asian immigrant students: The negotiation of Korean immigrant students' identities in science classrooms

NASA Astrophysics Data System (ADS)

Ryu, Minjung

This dissertation is a study about Korean immigrant students' identities, including academic identities related to science learning and identities along various social dimensions. I explore how Korean immigrant students participate in science classrooms and how they enact and negotiate their identities in their classroom discursive participation. My dissertation is motivated by the increasing attention in educational research to the intersectionality between science learning and various dimensions of identities (e.g., gender, race, ethnicity, social networks) and a dearth of such research addressing Asian immigrant students. Asian immigrant students are stereotyped as quiet and successful learners, particularly in science and mathematics classes, and their success is often explained by cultural differences. I confront this static and oversimplified notion of cultural differences and Asians' academic success and examine the intersectionality between science learning and identities of Asian immigrant students, with the specific case of Korean immigrants. Drawing upon cultural historical and sociolinguistic perspectives of identity, I propose a theoretical framework that underscores multiple levels of contexts (macro level, meso level, personal, and micro level contexts) in understanding and analyzing students' identities. Based on a year-long ethnographic study in two high school Advanced Placement Biology classes in a public high school, I present the meso level contexts of the focal school and biology classes, and in-depth analyses of three focal students. The findings illustrate: (1) how meso level contexts play a critical role in these students' identities and science classroom participation, (2) how the meso level contexts are reinterpreted and have different meanings to different students depending on their personal contexts, and (3) how students negotiated their positions to achieve certain identity goals. I discuss the implications of the findings for the science education of racially, ethnically, and linguistically diverse students, particularly given the increasing number of immigrant students in U.S. classrooms, and for the education of Asian immigrant students.

Multiple brain networks underpinning word learning from fluent speech revealed by independent component analysis.

PubMed

López-Barroso, Diana; Ripollés, Pablo; Marco-Pallarés, Josep; Mohammadi, Bahram; Münte, Thomas F; Bachoud-Lévi, Anne-Catherine; Rodriguez-Fornells, Antoni; de Diego-Balaguer, Ruth

2015-04-15

Although neuroimaging studies using standard subtraction-based analysis from functional magnetic resonance imaging (fMRI) have suggested that frontal and temporal regions are involved in word learning from fluent speech, the possible contribution of different brain networks during this type of learning is still largely unknown. Indeed, univariate fMRI analyses cannot identify the full extent of distributed networks that are engaged by a complex task such as word learning. Here we used Independent Component Analysis (ICA) to characterize the different brain networks subserving word learning from an artificial language speech stream. Results were replicated in a second cohort of participants with a different linguistic background. Four spatially independent networks were associated with the task in both cohorts: (i) a dorsal Auditory-Premotor network; (ii) a dorsal Sensory-Motor network; (iii) a dorsal Fronto-Parietal network; and (iv) a ventral Fronto-Temporal network. The level of engagement of these networks varied through the learning period with only the dorsal Auditory-Premotor network being engaged across all blocks. In addition, the connectivity strength of this network in the second block of the learning phase correlated with the individual variability in word learning performance. These findings suggest that: (i) word learning relies on segregated connectivity patterns involving dorsal and ventral networks; and (ii) specifically, the dorsal auditory-premotor network connectivity strength is directly correlated with word learning performance. Copyright © 2015 Elsevier Inc. All rights reserved.

Enhancing Diversity in the Geosciences through National Dissemination of the AMS Online Weather Studies Distance Learning Course

NASA Astrophysics Data System (ADS)

Weinbeck, R. S.; Geer, I. W.; Mills, E. W.; Porter, W. A.; Moran, J. M.

2002-12-01

Our nation faces a serious challenge in attracting young people to science and science-related careers (including teaching). This is particularly true for members of groups underrepresented in science, mathematics, engineering, and technology and is especially acute in the number of minority college students majoring in the geosciences. A formidable obstacle in attracting undergraduates to the geosciences is lack of access, that is, no opportunity to enroll in an introductory geoscience course simply because none is offered at their college or university. Often introductory or survey courses are a student's first exposure to the geosciences. To help alleviate this problem, the American Meteorological Society (AMS) through its Education Program developed and implemented nationally an introductory weather and climate course, Online Weather Studies, which can be added to an institution's menu of general education course offerings. This highly successful course will be offered at 130 colleges and universities nationwide, including 30 minority-serving institutions, 20 of which have joined the AMS Online Weather Studies Diversity Program during 2002. The AMS encourages course adoption by more institutions serving large numbers of minority students through support from the National Science Foundation (NSF) Opportunities for Enhancing Diversity in the Geosciences (OEDG) and Course, Curriculum and Laboratory Improvement-National Dissemination (CCLI-ND) programs. Online Weather Studies is an innovative, 12- to 15-week introductory college-level, online distance-learning course on the fundamentals of atmospheric science. Learner-formatted current weather data are delivered via the Internet and coordinated with investigations keyed to the day's weather. The principal innovation of Online Weather Studies is that students learn about weather as it happens in near real-time-a highly motivational learning experience. The AMS Education Program designed and services this course and makes it available to colleges and universities as a user-friendly turnkey package with electronic and printed components. The AMS Diversity Program, in cooperation with the National Weather Service (NWS) facilitates institutional participation in Online Weather Studies. Prior to an instructor's initial offering of the course, he or she is invited to attend a one-week course implementation workshop at the NWS Training Center at Kansas City, MO. Participants then join an interactive network to share best practices ideas in science content and teaching strategies related to their offering of Online Weather Studies. They participate in a mentoring program that networks students with professional meteorologists and provides opportunities for internships, summer research, and career counseling. Meteorologists-in-Charge at NWS Weather Forecast Offices across the nation have volunteered their time to help make these opportunities possible. Also, participants are invited to attend the Educational Symposium of the AMS Annual Meeting where they will attend a special Diversity Session and are encouraged to present a paper or poster.

Monitoring Seasons Through Global Learning Communities

NASA Astrophysics Data System (ADS)

Sparrow, E. B.; Robin, J. H.; Jeffries, M. O.; Gordon, L. S.; Verbyla, D. L.; Levine, E. R.

2006-12-01

Monitoring Seasons through Global Learning Communities (MSTGLC) is an inquiry- and project-based project that monitors seasons, specifically their interannual variability, in order to increase K-12 students' understanding of the Earth system by providing teacher professional development in Earth system science and inquiry, and engaging K-12 students in Earth system science research relevant to their local communities that connect globally. MSTGLC connects GLOBE students, teachers, and communities, with educators and scientists from three integrated Earth systems science programs: the International Arctic Research Center, and NASA Landsat Data Continuity and Terra Satellite Missions. The project organizes GLOBE schools by biomes into eight Global Learning Communities (GLCs) and students monitor their seasons through regional based field campaigns. The project expands the current GLOBE phenology network by adapting current protocols and making them biome-specific. In addition, ice and mosquito phenology protocols will be developed for Arctic and Tropical regions, respectively. Initially the project will focus on Tundra and Taiga biomes as phenological changes are so pronounced in these regions. However, our long-term goal is to determine similar changes in other biomes (Deciduous Forest, Desert, Grasslands, Rain Forest, Savannah and Shrubland) based upon what we learn from these two biomes. This project will also contribute to critically needed Earth system science data such as in situ ice, mosquito, and vegetation phenology measurements for ground validations of remotely sensed data, which are essential for regional climate change impact assessments. Additionally it will contribute environmental data critical to prevention and management of diseases such as malaria in Asian, African, and other countries. Furthermore, this project will enable students to participate in the International Polar Year (IPY) (2007-2009) through field campaigns conducted by students in polar regions, and web chats between IPY scientists and GLOBE students from all eight GLCs that include non-polar countries.

STFM Behavioral Science/Family Systems Educator Fellowship: Evaluation of the First 4 Years.

PubMed

Gorski, Victoria; Taylor, Deborah A; Fletcher, Jason; Burge, Sandra K

2015-01-01

The discipline of family medicine has long valued the behavioral sciences. Most residency training programs employ a clinical psychologist, social worker, or family therapist to deliver behavioral science curriculum to their residents. However, the cultures and content of training for behavioral sciences and medical professions are quite different, leaving the lone behavioral scientist feeling professionally isolated and unprepared to translate knowledge and skills into tools for the family physician. In response to this need, a group of family medicine educators developed an STFM-sponsored fellowship for behavioral science faculty. The goals of the program were to improve fellows' understanding of the culture of family medicine, provide a curricular toolbox for the behavioral sciences, promote scholarship, and develop a supportive professional network. Senior behavioral science faculty at STFM developed a 1-year fellowship program, featuring "classroom learning" at relevant conferences, mentored small-group interactions, and scholarly project requirements. Achievement of program goals was evaluated annually with pre- and post-fellowship surveys. From 2010 to 2014, 59 fellows completed the program; most were psychologists or social workers; two thirds were women. One month after graduation, fellows reported significant increases in understanding the culture of medicine, improved confidence in their curricula and scholarship, and expanded professional networks, compared to pre-fellowship levels. The program required many hours of volunteer time by leaders, faculty, and mentors plus modest support from STFM staff. Leaders in family medicine education, confronted by the need for inter-professional development, designed and implemented a successful training program for behavioral science faculty.

Promoting Lifelong Ocean Education: Shaping Tomorrow's Earth Stewards and the Science and Technology Workforce

NASA Technical Reports Server (NTRS)

Meeson, Blanche

2006-01-01

The coming ocean observing systems provide an unprecedented opportunity to change both the public perception of our oceans, and to inspire, captivate and motivate our children, our young adults and even our fellow adults to pursue careers allied with the oceans and to become stewards of our Planet's last unexplored environment. Education plans for the operational component, the Integrated Ocean Observing System (IOOS), and for the research component, Ocean Research Interactive Observatory Networks (ORION), are designed to take advantage of this opportunity. In both cases, community recommendations were developed within the context of the following assumptions: 1. Utilize research on how people learn, especially the four-pronged model of simultaneous learner-centered, knowledge-center, assessment-centered and community-centered learning 2. Strive for maximum impact on national needs in science and technology learning 3. Build on the best of what is already in place 4. Pay special attention to quality, sustainability, and scalability of efforts 5. Use partnerships across federal, state and local government, academia, and industry. Community recommendations for 100s and ORION education have much in common and offer the opportunity to create a coherent education effort allied with ocean observing systems. Both efforts focus on developing the science and technology workforce of the future, and the science and technology literacy of the public within the context of the Earth system and the role of the oceans and Great Lakes in that system. Both also recognize that an organized education infrastructure that supports sustainability and scalability of education efforts is required if ocean observing education efforts are to achieve a small but measurable improvement in either of these areas. Efforts have begun to develop the education infrastructure by beginning to form a community of educators from existing ocean and aquatic education networks and by exploring needs and issues associated with using ocean observing information assets in education. Likewise efforts are underway to address workforce issues by a systematic analysis of current and future workforce and educational needs. These activities will be described as will upcoming opportunities for the community to participate in these efforts.

The ENGAGE Workshop: Encouraging Networks between Geoscientists and Geoscience Education Researchers

NASA Astrophysics Data System (ADS)

Hubenthal, M.; LaDue, N.; Taber, J.

2015-12-01

The geoscience education community has made great strides in the study of teaching and learning at the undergraduate level, particularly with respect to solid earth geology. Nevertheless, the 2012 National Research Council report, Discipline-based Education Research: Understanding and Improving Learning in Undergraduate Science and Engineering suggests that the geosciences lag behind other science disciplines in the integration of education research within the discipline and the establishment of a broad research base. In January 2015, early career researchers from earth, atmospheric, ocean, and polar sciences and geoscience education research (GER) gathered for the ENGAGE workshop. The primary goal of ENGAGE was to broaden awareness of discipline-based research in the geosciences and catalyze relationships and understanding between these groups of scientists. An organizing committee of geoscientists and GERs designed a two-day workshop with a variety of activities to engage participants in the establishment of a shared understanding of education research and the development of project ideas through collaborative teams. Thirty-three participants were selected from over 100 applicants, based on disciplinary diversity and demonstrated interest in geoscience education research. Invited speakers and panelists also provided examples of successful cross-disciplinary collaborations. As a result of this workshop, participants indicated that they gained new perspectives on geoscience education and research, networked outside of their discipline, and are likely to increase their involvement in geoscience education research. In fact, 26 of 28 participants indicated they are now better prepared to enter into cross-disciplinary collaborations within the next year. The workshop evaluation revealed that the physical scientists particularly valued opportunities for informal networking and collaborative work developing geoscience education research projects. Meanwhile, GERs valued opportunities to discuss the boundaries of outreach, evaluation, and research and the potential next steps to advance geoscience education. Recommendations from the workshop are well aligned with earlier reports, and along with those documents, contributes to a path forward for geoscience education.

Science of learning is learning of science: why we need a dialectical approach to science education research

NASA Astrophysics Data System (ADS)

Roth, Wolff-Michael

2012-06-01

Research on learning science in informal settings and the formal (sometimes experimental) study of learning in classrooms or psychological laboratories tend to be separate domains, even drawing on different theories and methods. These differences make it difficult to compare knowing and learning observed in one paradigm/context with those observed in the other. Even more interestingly, the scientists studying science learning rarely consider their own learning in relation to the phenomena they study. A dialectical, reflexive approach to learning, however, would theorize the movement of an educational science (its learning and development) as a special and general case—subject matter and method—of the phenomenon of learning (in/of) science. In the dialectical approach to the study of science learning, therefore, subject matter, method, and theory fall together. This allows for a perspective in which not only disparate fields of study—school science learning and learning in everyday life—are integrated but also where the progress in the science of science learning coincides with its topic. Following the articulation of a contradictory situation on comparing learning in different settings, I describe the dialectical approach. As a way of providing a concrete example, I then trace the historical movement of my own research group as it simultaneously and alternately studied science learning in formal and informal settings. I conclude by recommending cultural-historical, dialectical approaches to learning and interaction analysis as a context for fruitful interdisciplinary research on science learning within and across different settings.

Deep learning of unsteady laminar flow over a cylinder

NASA Astrophysics Data System (ADS)

Lee, Sangseung; You, Donghyun

2017-11-01

Unsteady flow over a circular cylinder is reconstructed using deep learning with a particular emphasis on elucidating the potential of learning the solution of the Navier-Stokes equations. A deep neural network (DNN) is employed for deep learning, while numerical simulations are conducted to produce training database. Instantaneous and mean flow fields which are reconstructed by deep learning are compared with the simulation results. Fourier transform of flow variables has been conducted to validate the ability of DNN to capture both amplitudes and frequencies of flow motions. Basis decomposition of learned flow is performed to understand the underlying mechanisms of learning flow through DNN. The present study suggests that a deep learning technique can be utilized for reconstruction and, potentially, for prediction of fluid flow instead of solving the Navier-Stokes equations. This work was supported by the National Research Foundation of Korea(NRF) Grant funded by the Korea government(Ministry of Science, ICT and Future Planning) (No. 2014R1A2A1A11049599, No. 2015R1A2A1A15056086, No. 2016R1E1A2A01939553).

LeaRN: A Collaborative Learning-Research Network for a WLCG Tier-3 Centre

NASA Astrophysics Data System (ADS)

Pérez Calle, Elio

2011-12-01

The Department of Modern Physics of the University of Science and Technology of China is hosting a Tier-3 centre for the ATLAS experiment. A interdisciplinary team of researchers, engineers and students are devoted to the task of receiving, storing and analysing the scientific data produced by the LHC. In order to achieve the highest performance and to develop a knowledge base shared by all members of the team, the research activities and their coordination are being supported by an array of computing systems. These systems have been designed to foster communication, collaboration and coordination among the members of the team, both face-to-face and remotely, and both in synchronous and asynchronous ways. The result is a collaborative learning-research network whose main objectives are awareness (to get shared knowledge about other's activities and therefore obtain synergies), articulation (to allow a project to be divided, work units to be assigned and then reintegrated) and adaptation (to adapt information technologies to the needs of the group). The main technologies involved are Communication Tools such as web publishing, revision control and wikis, Conferencing Tools such as forums, instant messaging and video conferencing and Coordination Tools, such as time management, project management and social networks. The software toolkit has been deployed by the members of the team and it has been based on free and open source software.

Lessons learned about coordinating academic partnerships from an international network for health education.

PubMed

Luo, Airong; Omollo, Kathleen Ludewig

2013-11-01

There is a growing trend of academic partnerships between U.S., Canadian, and European health science institutions and academic health centers in low- and middle-income countries. These partnerships often encounter challenges such as resource disparities and power differentials, which affect the motivations, expectations, balance of benefits, and results of the joint projects. Little has been discussed in previous literature regarding the communication and project management processes that affect the success of such partnerships. To fill the gap in the literature, the authors present lessons learned from the African Health Open Educational Resources Network, a multicountry, multiorganizational partnership established in May 2008. The authors introduce the history of the network, then discuss actively engaging stakeholders throughout the project's life cycle (design, planning, execution, and closure) through professional development, relationship building, and assessment activities. They focus on communication and management practices used to identify mutually beneficial project goals, ensure timely completion of deliverables, and develop sustainable sociotechnical infrastructure for future collaborative projects. These activities yielded an interactive process of action, assessment, and reflection to ensure that project goals and values were aligned with implementation. The authors conclude with a discussion of lessons learned and how the partnership project may serve as a model for other universities and academic health centers in high-income countries and low- and middle-income countries that are interested in or currently pursuing international academic partnerships.

Robust Learning of High-dimensional Biological Networks with Bayesian Networks

NASA Astrophysics Data System (ADS)

Nägele, Andreas; Dejori, Mathäus; Stetter, Martin

Structure learning of Bayesian networks applied to gene expression data has become a potentially useful method to estimate interactions between genes. However, the NP-hardness of Bayesian network structure learning renders the reconstruction of the full genetic network with thousands of genes unfeasible. Consequently, the maximal network size is usually restricted dramatically to a small set of genes (corresponding with variables in the Bayesian network). Although this feature reduction step makes structure learning computationally tractable, on the downside, the learned structure might be adversely affected due to the introduction of missing genes. Additionally, gene expression data are usually very sparse with respect to the number of samples, i.e., the number of genes is much greater than the number of different observations. Given these problems, learning robust network features from microarray data is a challenging task. This chapter presents several approaches tackling the robustness issue in order to obtain a more reliable estimation of learned network features.

Where High-Tech Meets High-Touch: an example of effective cross-disciplinary collaboration in education

NASA Astrophysics Data System (ADS)

Holzhauer, B.; Mooney, M. E.

2012-12-01

How can non-formal education programs effectively blend hands-on, place-based field science lessons with technology and digital media to teach abstract global concepts in a local setting? Using climate change as an overarching concept, the Aldo Leopold Nature Center (ALNC) in Madison, WI, is developing exhibits and digital curricula, strengthened through partnerships with local and national experts from scientific and education fields, to effectively increase the public's interest in and understanding of science and technology, how the world works, and what we can do to adapt, mitigate, and innovate sustainable solutions. The exhibits and multimedia content, centered on topics such as climate, energy, weather, and phenology, have been developed in consultation with partners like the National Academy of Sciences and various departments at the University of Wisconsin (UW). Outdoor "high-touch" programs are complemented with "high-tech" exhibits and media, including touchscreen kiosks and the National Oceanic and Atmospheric Administration's (NOAA) Science On a Sphere® global display system, tying together multimedia experiences with peer-reviewed cutting-edge science to ensure maximum comprehension by appealing and connecting to learners of all ages and learning modalities. The curriculum is being developed in alignment with local and national education standards and science and climate literacy frameworks (such as "The Essential Principles of Climate Sciences," U.S. Global Change Research Program / U.S. Climate Change Science Program). Its digital format allows it to be easily adapted to visitors' learning styles and cognitive levels and updated with relevant new content such as real-time climate data or current visualizations from the UW Cooperative Institute for Meteorological Satellite Studies. Drawing upon ALNC's award-winning environmental education experiences, professional development networks such as NOAA's Climate Stewards Education Program, and existing resources for teaching through formal STEM education, ALNC has combined the unique benefits of place-based outdoor citizen-science in the community setting with digital, multimedia, and interactive components to address local, regional, and global scientific concepts with all audiences of all ages. This innovative, replicable and broadly accessible approach, geared towards formal school groups and the general public in a non-formal educational setting, is being piloted, evaluated, and disseminated through a variety of networks and professional development in order to serve as a model of continued collaborative education.;

Investigating the Potential Impacts of Energy Production in the Marcellus Shale Region Using the Shale Network Database

NASA Astrophysics Data System (ADS)

Brantley, S.; Brazil, L.

2017-12-01

The Shale Network's extensive database of water quality observations enables educational experiences about the potential impacts of resource extraction with real data. Through tools that are open source and free to use, researchers, educators, and citizens can access and analyze the very same data that the Shale Network team has used in peer-reviewed publications about the potential impacts of hydraulic fracturing on water. The development of the Shale Network database has been made possible through efforts led by an academic team and involving numerous individuals from government agencies, citizen science organizations, and private industry. Thus far, these tools and data have been used to engage high school students, university undergraduate and graduate students, as well as citizens so that all can discover how energy production impacts the Marcellus Shale region, which includes Pennsylvania and other nearby states. This presentation will describe these data tools, how the Shale Network has used them in developing lesson plans, and the resources available to learn more.

Textbooks vs. techbooks: Effectiveness of digital textbooks on elementary student motivation for learning

NASA Astrophysics Data System (ADS)

Oman, Auna

This action research project investigated fourth grade students¡¦ motivation to learn science using a digital science techbook. Participants in the study included 29 fourth grade students in two different classrooms. One classroom of 16 students used a digital science techbook to learn science while the other classroom of 13 students used a traditional paper science textbook to learn science. Students in both classrooms answered five sets of questions regarding their experience using a digital science techbook and a paper science techbook to understand science, find science information, solve science problems, learn science, and assess learning science was fun. Results were compiled and coded based on positive and negative responses to conditions. A chi-square was used to analyze the ordinal data. Overall differences between techbooks vs. textbook were significant, X2 (1, N = 29) = 23.84, p = .000, justifying further examination of individual survey items. Three items had statistically significant difference for finding science information, solving science problems, and learning science. A gender difference was also found in one item. Females preferred to use paper science textbooks to understand science, while males preferred digital techbooks to learn science. The fourth graders in this study indicated that digital techbooks were a powerful learning tool for increasing interest, excitement and learning science. Even though students reported paper science textbooks as easy to use, they found using digital science techbooks a far more appealing way to learn science.

Improving Memory for Optimization and Learning in Dynamic Environments

DTIC Science & Technology

2011-07-01

algorithm uses simple, in- cremental clustering to separate solutions into memory entries. The cluster centers are used as the models in the memory. This is...entire days of traffic with realistic traffic de - mands and turning ratios on a 32 intersection network modeled on downtown Pittsburgh, Pennsyl- vania...early/tardy problem. Management Science, 35(2):177–191, 1989. [78] Daniel Parrott and Xiaodong Li. A particle swarm model for tracking multiple peaks in

Partnership in Innovative Preparation for Educators and Students (PIPES)

DTIC Science & Technology

2013-12-23

it? Sign up for this workshop to find out! You will construct a working wind generator to find out which turbine generates the most electricity...program an advanced robot that will accomplish a greater number of amazing tasks using additional sensors and commands. Requires some previous NXT...tech wireless networks and cell phones to solve a cyber-bullying mystery . Learn ways to stay safe online. 19 Kitchen Chemistry – Science and

Characterizing the Networks of Digital Information that Support Collaborative Adaptive Forest Management in Sierra Nevada Forests.

PubMed

Lei, Shufei; Iles, Alastair; Kelly, Maggi

2015-07-01

Some of the factors that can contribute to the success of collaborative adaptive management--such as social learning, open communication, and trust--are built upon a foundation of the open exchange of information about science and management between participants and the public. Despite the importance of information transparency, the use and flow of information in collaborative adaptive management has not been characterized in detail in the literature, and currently there exist opportunities to develop strategies for increasing the exchange of information, as well as to track information flow in such contexts. As digital information channels and networks have been increased over the last decade, powerful new information monitoring tools have also been evolved allowing for the complete characterization of information products through their production, transport, use, and monitoring. This study uses these tools to investigate the use of various science and management information products in a case study--the Sierra Nevada Adaptive Management Project--using a mixed method (citation analysis, web analytics, and content analysis) research approach borrowed from the information processing and management field. The results from our case study show that information technologies greatly facilitate the flow and use of digital information, leading to multiparty collaborations such as knowledge transfer and public participation in science research. We conclude with recommendations for expanding information exchange in collaborative adaptive management by taking advantage of available information technologies and networks.

Characterizing the Networks of Digital Information that Support Collaborative Adaptive Forest Management in Sierra Nevada Forests

NASA Astrophysics Data System (ADS)

Lei, Shufei; Iles, Alastair; Kelly, Maggi

2015-07-01

Some of the factors that can contribute to the success of collaborative adaptive management—such as social learning, open communication, and trust—are built upon a foundation of the open exchange of information about science and management between participants and the public. Despite the importance of information transparency, the use and flow of information in collaborative adaptive management has not been characterized in detail in the literature, and currently there exist opportunities to develop strategies for increasing the exchange of information, as well as to track information flow in such contexts. As digital information channels and networks have been increased over the last decade, powerful new information monitoring tools have also been evolved allowing for the complete characterization of information products through their production, transport, use, and monitoring. This study uses these tools to investigate the use of various science and management information products in a case study—the Sierra Nevada Adaptive Management Project—using a mixed method (citation analysis, web analytics, and content analysis) research approach borrowed from the information processing and management field. The results from our case study show that information technologies greatly facilitate the flow and use of digital information, leading to multiparty collaborations such as knowledge transfer and public participation in science research. We conclude with recommendations for expanding information exchange in collaborative adaptive management by taking advantage of available information technologies and networks.

Accelerating Research Impact in a Learning Health Care System

PubMed Central

Elwy, A. Rani; Sales, Anne E.; Atkins, David

2017-01-01

Background: Since 1998, the Veterans Health Administration (VHA) Quality Enhancement Research Initiative (QUERI) has supported more rapid implementation of research into clinical practice. Objectives: With the passage of the Veterans Access, Choice and Accountability Act of 2014 (Choice Act), QUERI further evolved to support VHA’s transformation into a Learning Health Care System by aligning science with clinical priority goals based on a strategic planning process and alignment of funding priorities with updated VHA priority goals in response to the Choice Act. Design: QUERI updated its strategic goals in response to independent assessments mandated by the Choice Act that recommended VHA reduce variation in care by providing a clear path to implement best practices. Specifically, QUERI updated its application process to ensure its centers (Programs) focus on cross-cutting VHA priorities and specify roadmaps for implementation of research-informed practices across different settings. QUERI also increased funding for scientific evaluations of the Choice Act and other policies in response to Commission on Care recommendations. Results: QUERI’s national network of Programs deploys effective practices using implementation strategies across different settings. QUERI Choice Act evaluations informed the law’s further implementation, setting the stage for additional rigorous national evaluations of other VHA programs and policies including community provider networks. Conclusions: Grounded in implementation science and evidence-based policy, QUERI serves as an example of how to operationalize core components of a Learning Health Care System, notably through rigorous evaluation and scientific testing of implementation strategies to ultimately reduce variation in quality and improve overall population health. PMID:27997456

The Impacts of Network Centrality and Self-Regulation on an E-Learning Environment with the Support of Social Network Awareness

ERIC Educational Resources Information Center

Lin, Jian-Wei; Huang, Hsieh-Hong; Chuang, Yuh-Shy

2015-01-01

An e-learning environment that supports social network awareness (SNA) is a highly effective means of increasing peer interaction and assisting student learning by raising awareness of social and learning contexts of peers. Network centrality profoundly impacts student learning in an SNA-related e-learning environment. Additionally,…

Professional Development for Early Childhood Educators: Efforts to Improve Math and Science Learning Opportunities in Early Childhood Classrooms.

PubMed

Piasta, Shayne B; Logan, Jessica A R; Pelatti, Christina Yeager; Capps, Janet L; Petrill, Stephen A

2015-05-01

Because recent initiatives highlight the need to better support preschool-aged children's math and science learning, the present study investigated the impact of professional development in these domains for early childhood educators. Sixty-five educators were randomly assigned to experience 10.5 days (64 hours) of training on math and science or on an alternative topic. Educators' provision of math and science learning opportunities were documented, as were the fall-to-spring math and science learning gains of children ( n = 385) enrolled in their classrooms. Professional development significantly impacted provision of science, but not math, learning opportunities. Professional development did not directly impact children's math or science learning, although science learning was indirectly affected via the increase in science learning opportunities. Both math and science learning opportunities were positively associated with children's learning. Results suggest that substantive efforts are necessary to ensure that children have opportunities to learn math and science from a young age.

Professional Development for Early Childhood Educators: Efforts to Improve Math and Science Learning Opportunities in Early Childhood Classrooms

PubMed Central

Piasta, Shayne B.; Logan, Jessica A. R.; Pelatti, Christina Yeager; Capps, Janet L.; Petrill, Stephen A.

2014-01-01

Because recent initiatives highlight the need to better support preschool-aged children’s math and science learning, the present study investigated the impact of professional development in these domains for early childhood educators. Sixty-five educators were randomly assigned to experience 10.5 days (64 hours) of training on math and science or on an alternative topic. Educators’ provision of math and science learning opportunities were documented, as were the fall-to-spring math and science learning gains of children (n = 385) enrolled in their classrooms. Professional development significantly impacted provision of science, but not math, learning opportunities. Professional development did not directly impact children’s math or science learning, although science learning was indirectly affected via the increase in science learning opportunities. Both math and science learning opportunities were positively associated with children’s learning. Results suggest that substantive efforts are necessary to ensure that children have opportunities to learn math and science from a young age. PMID:26257434

Teachers' Motives for Learning in Networks: Costs, Rewards and Community Interest

ERIC Educational Resources Information Center

van den Beemt, Antoine; Ketelaar, Evelien; Diepstraten, Isabelle; de Laat, Maarten

2018-01-01

Background: This paper discusses teachers' perspectives on learning networks and their motives for participating in these networks. Although it is widely held that teachers' learning may be developed through learning networks, not all teachers participate in such networks. Purpose: The theme of reciprocity, central to studies in the area of…

Up the ANTe: Understanding Entrepreneurial Leadership Learning through Actor-Network Theory

ERIC Educational Resources Information Center

Smith, Sue; Kempster, Steve; Barnes, Stewart

2017-01-01

This article explores the role of educators in supporting the development of entrepreneurial leadership learning by creating peer learning networks of owner-managers of small businesses. Using actor-network theory, the authors think through the process of constructing and maintaining a peer learning network (conceived of as an actor-network) and…

Machine learning methods in chemoinformatics

PubMed Central

Mitchell, John B O

2014-01-01

Machine learning algorithms are generally developed in computer science or adjacent disciplines and find their way into chemical modeling by a process of diffusion. Though particular machine learning methods are popular in chemoinformatics and quantitative structure–activity relationships (QSAR), many others exist in the technical literature. This discussion is methods-based and focused on some algorithms that chemoinformatics researchers frequently use. It makes no claim to be exhaustive. We concentrate on methods for supervised learning, predicting the unknown property values of a test set of instances, usually molecules, based on the known values for a training set. Particularly relevant approaches include Artificial Neural Networks, Random Forest, Support Vector Machine, k-Nearest Neighbors and naïve Bayes classifiers. WIREs Comput Mol Sci 2014, 4:468–481. How to cite this article: WIREs Comput Mol Sci 2014, 4:468–481. doi:10.1002/wcms.1183 PMID:25285160

A model of professional development for urban teachers

NASA Astrophysics Data System (ADS)

Narasimhan, C.

Over the past five years, DePaul University has established a network of urban teachers who are focused on linking the learning of fundamental concepts of physics, chemistry, and biology to relevant and current discoveries in space science. One component of this effort has been a series of annual space science symposia for Chicago-area teachers. These symposia are mixtures of space science presentations by national and local scientists and discussions in areas such as curriculum and professional development, NASA resources, and communication. Since the first symposium, planning has been done in partnership with a small group of teachers who have moved into leadership positions in advancing space science in the Chicago area. This presentation will describe the evolution of the annual symposium as a professional development activity and give the results of a recent assessment project designed to measure the impact of these symposia on Chicago teachers and their classroom practices.

Science-policy processes for transboundary water governance.

PubMed

Armitage, Derek; de Loë, Rob C; Morris, Michelle; Edwards, Tom W D; Gerlak, Andrea K; Hall, Roland I; Huitema, Dave; Ison, Ray; Livingstone, David; MacDonald, Glen; Mirumachi, Naho; Plummer, Ryan; Wolfe, Brent B

2015-09-01

In this policy perspective, we outline several conditions to support effective science-policy interaction, with a particular emphasis on improving water governance in transboundary basins. Key conditions include (1) recognizing that science is a crucial but bounded input into water resource decision-making processes; (2) establishing conditions for collaboration and shared commitment among actors; (3) understanding that social or group-learning processes linked to science-policy interaction are enhanced through greater collaboration; (4) accepting that the collaborative production of knowledge about hydrological issues and associated socioeconomic change and institutional responses is essential to build legitimate decision-making processes; and (5) engaging boundary organizations and informal networks of scientists, policy makers, and civil society. We elaborate on these conditions with a diverse set of international examples drawn from a synthesis of our collective experiences in assessing the opportunities and constraints (including the role of power relations) related to governance for water in transboundary settings.

Learning by stimulation avoidance: A principle to control spiking neural networks dynamics

PubMed Central

Sinapayen, Lana; Ikegami, Takashi

2017-01-01

Learning based on networks of real neurons, and learning based on biologically inspired models of neural networks, have yet to find general learning rules leading to widespread applications. In this paper, we argue for the existence of a principle allowing to steer the dynamics of a biologically inspired neural network. Using carefully timed external stimulation, the network can be driven towards a desired dynamical state. We term this principle “Learning by Stimulation Avoidance” (LSA). We demonstrate through simulation that the minimal sufficient conditions leading to LSA in artificial networks are also sufficient to reproduce learning results similar to those obtained in biological neurons by Shahaf and Marom, and in addition explains synaptic pruning. We examined the underlying mechanism by simulating a small network of 3 neurons, then scaled it up to a hundred neurons. We show that LSA has a higher explanatory power than existing hypotheses about the response of biological neural networks to external simulation, and can be used as a learning rule for an embodied application: learning of wall avoidance by a simulated robot. In other works, reinforcement learning with spiking networks can be obtained through global reward signals akin simulating the dopamine system; we believe that this is the first project demonstrating sensory-motor learning with random spiking networks through Hebbian learning relying on environmental conditions without a separate reward system. PMID:28158309

Learning by stimulation avoidance: A principle to control spiking neural networks dynamics.

PubMed

Sinapayen, Lana; Masumori, Atsushi; Ikegami, Takashi

2017-01-01

Learning based on networks of real neurons, and learning based on biologically inspired models of neural networks, have yet to find general learning rules leading to widespread applications. In this paper, we argue for the existence of a principle allowing to steer the dynamics of a biologically inspired neural network. Using carefully timed external stimulation, the network can be driven towards a desired dynamical state. We term this principle "Learning by Stimulation Avoidance" (LSA). We demonstrate through simulation that the minimal sufficient conditions leading to LSA in artificial networks are also sufficient to reproduce learning results similar to those obtained in biological neurons by Shahaf and Marom, and in addition explains synaptic pruning. We examined the underlying mechanism by simulating a small network of 3 neurons, then scaled it up to a hundred neurons. We show that LSA has a higher explanatory power than existing hypotheses about the response of biological neural networks to external simulation, and can be used as a learning rule for an embodied application: learning of wall avoidance by a simulated robot. In other works, reinforcement learning with spiking networks can be obtained through global reward signals akin simulating the dopamine system; we believe that this is the first project demonstrating sensory-motor learning with random spiking networks through Hebbian learning relying on environmental conditions without a separate reward system.

Shaping the Public Dialogue on Climate Change

NASA Astrophysics Data System (ADS)

Spitzer, W.; Anderson, J. C.

2012-12-01

In order to broaden the public dialogue about climate change, climate scientists need to leverage the potential of informal science education and recent advances in social and cognitive science. In the US, more than 1,500 informal science venues (science centers, museums, aquariums, zoos, nature centers, national parks, etc.) are visited annually by 61% of the population. Extensive research shows that these visitors are receptive to learning about climate change and trust these institutions as reliable sources. Given that we spend less than 5% of our lifetime in a classroom, and only a fraction of that is focused on science, informal science venues will continue to play a critical role in shaping public understanding of environmental issues in the years ahead. Public understanding of climate change continues to lag far behind the scientific consensus not merely because the public lacks information, but because there is in fact too much complex and contradictory information available. Fortunately, we can now (1) build on careful empirical cognitive and social science research to understand what people already value, believe, and understand; and then (2) design and test strategies for translating complex science so that people can examine evidence, make well-informed inferences, and embrace science-based solutions. The New England Aquarium is leading a national effort to enable informal science education institutions to effectively communicate the impacts of climate change and ocean acidification on marine ecosystems. This NSF-funded partnership, the National Network for Ocean and Climate Change Interpretation (NNOCCI), involves the Association of Zoos and Aquariums, FrameWorks Institute, Woods Hole Oceanographic Institution, Monterey Bay Aquarium, and National Aquarium, with evaluation conducted by the New Knowledge Organization, Pennsylvania State University, and Ohio State University. We believe that skilled interpreters can serve as "communication strategists" by engaging in conversations with visitors based on audience research, role playing, and reflective feedback on their practice. From our NSF Phase I CCEP project, we have learned that in-depth training can help interpreters increase their confidence, self-efficacy, and a sense of hope in their ability to effectively communicate about climate change. This sense of hope and optimism has a powerful "ripple effect" on colleagues at their own institution, as well as others in their social and professional networks. In the next phase of our work, we hope to expand our reach to provide professional development for interpretive staff from additional institutions, in collaboration with climate scientists and cognitive/social scientists. Regional leaders will participate in recruiting and in planning and leading additional workshops. For youth interpreters, we plan to develop and implement special training methods. For scientists, we will offer workshops on strategic framing and communication. We will conduct and incorporate new social science research into a widely disseminated e-Workshop. For the growing network of participants, we will facilitate ongoing dialogue and an online community. Ultimately, we envision informal science interpreters as "vectors" for effective science communication, ocean and climate scientists with enhanced communication skills, and increased public demand for explanation and dialogue about global issues.

Improving Environmental Literacy through GO3 Citizen Science Project

NASA Astrophysics Data System (ADS)

Wilkening, B.

2011-12-01

In the Global Ozone (GO3) Project students measure ground-level ozone on a continuous basis and upload their results to a global network used by atmospheric scientists and schools. Students learn important concepts such as chemical measurement methods; instrumentation; calibration; data acquisition using computers; data quality; statistics; data analysis and graphing; posting of data to the web; the chemistry of air pollution; stratospheric ozone depletion and global climate change. Students collaborate with researchers and other students globally in the GO3 network. Wilson K-8 School is located in a suburban area in Pima County, Arizona. Throughout the year we receive high ozone alert days. Prior to joining the GO3 project, my students were unaware of air pollution alerts, risks and causes. In the past when Pima County issued alerts to the school, they were posted on signs around the school. No explanation was provided to the students and the signs were often left up for days. This discounted the potential health effects of the situation, resulting in the alerts effectively being ignored. The GO3 project is transforming both my students and our school community. Now my students are:

• Performing science research
• Utilizing technology and increasing their skills
• Collaborating in a responsible manner on the global GO3 social network
• Communicating their work to the community
• Issuing their own ozone alerts to their school
• Advocating for actions that will improve air quality

Psychology and social networks: a dynamic network theory perspective.

PubMed

Westaby, James D; Pfaff, Danielle L; Redding, Nicholas

2014-04-01

Research on social networks has grown exponentially in recent years. However, despite its relevance, the field of psychology has been relatively slow to explain the underlying goal pursuit and resistance processes influencing social networks in the first place. In this vein, this article aims to demonstrate how a dynamic network theory perspective explains the way in which social networks influence these processes and related outcomes, such as goal achievement, performance, learning, and emotional contagion at the interpersonal level of analysis. The theory integrates goal pursuit, motivation, and conflict conceptualizations from psychology with social network concepts from sociology and organizational science to provide a taxonomy of social network role behaviors, such as goal striving, system supporting, goal preventing, system negating, and observing. This theoretical perspective provides psychologists with new tools to map social networks (e.g., dynamic network charts), which can help inform the development of change interventions. Implications for social, industrial-organizational, and counseling psychology as well as conflict resolution are discussed, and new opportunities for research are highlighted, such as those related to dynamic network intelligence (also known as cognitive accuracy), levels of analysis, methodological/ethical issues, and the need to theoretically broaden the study of social networking and social media behavior. (PsycINFO Database Record (c) 2014 APA, all rights reserved).

ESIP Federation: A Case Study on Enabling Collaboration Infrastructure to Support Earth Science Informatics Communities

NASA Astrophysics Data System (ADS)

Robinson, E.; Meyer, C. B.; Benedict, K. K.

2013-12-01

A critical part of effective Earth science data and information system interoperability involves collaboration across geographically and temporally distributed communities. The Federation of Earth Science Information Partners (ESIP) is a broad-based, distributed community of science, data and information technology practitioners from across science domains, economic sectors and the data lifecycle. ESIP's open, participatory structure provides a melting pot for coordinating around common areas of interest, experimenting on innovative ideas and capturing and finding best practices and lessons learned from across the network. Since much of ESIP's work is distributed, the Foundation for Earth Science was established as a non-profit home for its supportive collaboration infrastructure. The infrastructure leverages the Internet and recent advances in collaboration web services. ESIP provides neutral space for self-governed groups to emerge around common Earth science data and information issues, ebbing and flowing as the need for them arises. As a group emerges, the Foundation quickly equips the virtual workgroup with a set of ';commodity services'. These services include: web meeting technology (Webex), a wiki and an email listserv. WebEx allows the group to work synchronously, dynamically viewing and discussing shared information in real time. The wiki is the group's primary workspace and over time creates organizational memory. The listserv provides an inclusive way to email the group and archive all messages for future reference. These three services lower the startup barrier for collaboration and enable automatic content preservation to allow for future work. While many of ESIP's consensus-building activities are discussion-based, the Foundation supports an ESIP testbed environment for exploring and evaluating prototype standards, services, protocols, and best practices. After community review of testbed proposals, the Foundation provides small seed funding and a toolbox of collaborative development resources including Amazon Web Services to quickly spin-up the testbed instance and a GitHub account for maintaining testbed project code enabling reuse. Recently, the Foundation supported development of the ESIP Commons (http://commons.esipfed.org), a Drupal-based knowledge repository for non-traditional publications to preserve community products and outcomes like white papers, posters and proceedings. The ESIP Commons adds additional structured metadata, provides attribution to contributors and allows those unfamiliar with ESIP a straightforward way to find information. The success of ESIP Federation activities is difficult to measure. The ESIP Commons is a step toward quantifying sponsor return on investment and is one dataset used in network map analysis of the ESIP community network, another success metric. Over the last 15 years, ESIP has continually grown and attracted experts in the Earth science data and informatics field becoming a primary locus of research and development on the application and evolution of Earth science data standards and conventions. As funding agencies push toward a more collaborative approach, the lessons learned from ESIP and the collaboration services themselves are a crucial component of supporting science research.

NASA and Public Libraries: Enhancing STEM Literacy in Underserved Communities

NASA Astrophysics Data System (ADS)

Dusenbery, P.; LaConte, K.; Harold, J. B.; Randall, C.

2016-12-01

NASA research programs are helping humanity understand the origin and evolution of galaxies, stars, and planets, and defining the conditions necessary to support life beyond Earth. The Space Science Institute's (SSI) National Center for Interactive Learning (NCIL) was recently funded by NASA`s Science Mission Directorate (SMD) to develop and implement a project called NASA@ My Library: A National Earth and Space Science Initiative That Connects NASA, Public Libraries and Their Communities. As places that offer their services for free, public libraries have become the "public square" by providing a place where members of a community can gather for information, educational programming, and policy discussions. Libraries are developing new ways to engage their patrons in STEM learning, and NCIL's STAR Library Education Network (STAR_Net) has been supporting their efforts for the last eight years, including through a vibrant community of practice that serves both librarians and STEM professionals. Project stakeholders include public library staff, state libraries, the earth and space science education community at NASA, subject matter experts, and informal science educators. The project will leverage high-impact SMD and library events to catalyze partnerships through dissemination of SMD assets and professional development. It will also develop frameworks for public libraries to increase STEM interest pathways in their communities (with supports for reaching underserved audiences). This presentation will summarize the key activities and expected outcomes of the 5-year project.

Effective Broader Impacts - Lessons Learned by the Ocean Science Community

NASA Astrophysics Data System (ADS)

Scowcroft, G.

2014-12-01

Effective broader impact activities have the potential for scientists to engage with educators, students, and the public in meaningful ways that lead to increased scientific literacy. These interactions provide opportunities for the results and discoveries of federally funded research projects, along with their implications for society, to reach non-scientist audiences. This is especially important for climate, ocean, and environmental science research that will aid citizens in better understanding how they affect Earth's systems and how these systems affect their daily lives. The National Centers for Ocean Sciences Excellence (COSEE) Network has over 12 years of experience in conducting successful broader impact activities and has provided thousands of ocean scientists the opportunity to share the fruits of their research well beyond the scientific enterprise. COSEE evaluators and principal investigators collaborated over several years to determine the impacts of COSEE broader impact activities and to identify best practices. The lessons learned by the ocean science community can help to inform other disciplines. Fruitful broader impact activities require key elements, no matter the composition of the audience. For example, a high degree of success can be achieved when a "bridge builder" facilitates the interactions between scientists and non-science audiences. This presentation will offer other examples of best practices and successful strategies for engaging scientists in broader impact activities, increasing societal impacts of scientific research, and providing opportunities for collaboration on a national scale. http://www.cosee.net

Modular, Hierarchical Learning By Artificial Neural Networks

NASA Technical Reports Server (NTRS)

Baldi, Pierre F.; Toomarian, Nikzad

1996-01-01

Modular and hierarchical approach to supervised learning by artificial neural networks leads to neural networks more structured than neural networks in which all neurons fully interconnected. These networks utilize general feedforward flow of information and sparse recurrent connections to achieve dynamical effects. The modular organization, sparsity of modular units and connections, and fact that learning is much more circumscribed are all attractive features for designing neural-network hardware. Learning streamlined by imitating some aspects of biological neural networks.

Investigating the interrelationships among conceptions of, approaches to, and self-efficacy in learning science

NASA Astrophysics Data System (ADS)

Zheng, Lanqin; Dong, Yan; Huang, Ronghuai; Chang, Chun-Yen; Bhagat, Kaushal Kumar

2018-01-01

The purpose of this study was to examine the relations between primary school students' conceptions of, approaches to, and self-efficacy in learning science in Mainland China. A total of 1049 primary school students from Mainland China participated in this study. Three instruments were adapted to measure students' conceptions of learning science, approaches to learning science, and self-efficacy. The exploratory factor analysis and confirmatory factor analysis were adopted to validate three instruments. The path analysis was employed to understand the relationships between conceptions of learning science, approaches to learning science, and self-efficacy. The findings indicated that students' lower level conceptions of learning science positively influenced their surface approaches in learning science. Higher level conceptions of learning science had a positive influence on deep approaches and a negative influence on surface approaches to learning science. Furthermore, self-efficacy was also a hierarchical construct and can be divided into the lower level and higher level. Only students' deep approaches to learning science had a positive influence on their lower and higher level of self-efficacy in learning science. The results were discussed in the context of the implications for teachers and future studies.

Undergraduate students' earth science learning: relationships among conceptions, approaches, and learning self-efficacy in Taiwan

NASA Astrophysics Data System (ADS)

Shen, Kuan-Ming; Lee, Min-Hsien; Tsai, Chin-Chung; Chang, Chun-Yen

2016-06-01

In the area of science education research, studies have attempted to investigate conceptions of learning, approaches to learning, and self-efficacy, mainly focusing on science in general or on specific subjects such as biology, physics, and chemistry. However, few empirical studies have probed students' earth science learning. This study aimed to explore the relationships among undergraduates' conceptions of, approaches to, and self-efficacy for learning earth science by adopting the structural equation modeling technique. A total of 268 Taiwanese undergraduates (144 females) participated in this study. Three instruments were modified to assess the students' conceptions of, approaches to, and self-efficacy for learning earth science. The results indicated that students' conceptions of learning made a significant contribution to their approaches to learning, which were consequently correlated with their learning self-efficacy. More specifically, students with stronger agreement that learning earth science involves applying the knowledge and skills learned to unknown problems were prone to possess higher confidence in learning earth science. Moreover, students viewing earth science learning as understanding earth science knowledge were more likely to adopt meaningful strategies to learn earth science, and hence expressed a higher sense of self-efficacy. Based on the results, practical implications and suggestions for future research are discussed.

Building Learning Communities for Research Collaboration and Cross-Cultural Enrichment in Science Education

NASA Astrophysics Data System (ADS)

Sparrow, E. B.

2003-12-01

The GLOBE program has provided opportunities for environmental science research and education collaborations among scientists, teachers and K-12 students, and for cross-cultural enrichment nationally and abroad. In Alaska, GLOBE has also provided funding leverage in some cases, and a base for several other science education programs that share a common goal of increasing student interest, understanding, process skills and achievement in science, through involvement in ongoing research investigations. These programs that use GLOBE methodologies (standardized scientific measurements and learning activities developed by scientists and educators) are: Global Change Education Using Western Science and Native Knowledge also known as "Observing Locally, Connecting Globally" (OLCG); Alaska Earth System Science Education Alliance: Improving Understanding of Climate Variability and Its Relevance to Rural Alaska; Schoolyard Long Term Ecological Research; Alaska Rural Research Partnership; Alaska Partnership for Teacher Enhancement; Alaska Lake Ice and Snow Observatory Network; Alaska Boreal Forest Council Education Outreach; Calypso Farm and Ecology Center; Environmental Education Outreach; and also GLOBE Arctic POPs (persistent organic pollutants) a program that involves countries in the circumpolar North. The University of Alaska GLOBE Partnership has collaborated with the BLM Campbell Creek Science Center Globe Partnership in facilitating GLOBE Training Workshops and providing teacher support. GLOBE's extensive website including data entry, archive, analysis and visualization capabilities; GLOBE Teacher Guide, videos and other materials provided; excellent GLOBE science research and education staff, training support office, GLOBE help desk, alignment of GLOBE curriculum with national science education standards and GLOBE certification of teachers trained on even just one GLOBE investigation, have made it easier to implement GLOBE in the classroom. Using GLOBE, whole classes of students have engaged in and contributed data to science investigations. In Alaska, classes and individual students have conducted their own inquiry studies and have successfully presented their investigations and competed at science fairs and statewide high school science symposium and international conferences. Two students presented their research investigations at the GLOBE Learning Expedition in Croatia and four students presented their study at the GLOBE Arctic POPs Conference in Sweden. These students increased not only their understanding and knowledge of science but also in appreciation of people in other countries and their cultures. Friendships have also bloomed. The learning community in Alaska has expanded to include family and community members including Native elders (using OLCG), teachers, scientists and students from other countries. The following challenges remain: 1) getting funds to be able to provide GLOBE equipment and continuous support to GLOBE teachers and students throughout the year, 2) reaching teachers and students in remote areas, 3) rapid teacher turn-over rate in rural areas, 4) using inquiry-based pedagogies during GLOBE professional development workshops including the opportunity for teacher participants to conduct their own inquiries during the workshop, 5) time, school curriculum and national education requirement constraints, 6) involving school administrators, and more local scientists and community members, and 7) providing culturally relevant and responsive science education programs and life-long learning communities.

Enhancing Spatial Resolution of Remotely Sensed Imagery Using Deep Learning

NASA Astrophysics Data System (ADS)

Beck, J. M.; Bridges, S.; Collins, C.; Rushing, J.; Graves, S. J.

2017-12-01

Researchers at the Information Technology and Systems Center at the University of Alabama in Huntsville are using Deep Learning with Convolutional Neural Networks (CNNs) to develop a method for enhancing the spatial resolutions of moderate resolution (10-60m) multispectral satellite imagery. This enhancement will effectively match the resolutions of imagery from multiple sensors to provide increased global temporal-spatial coverage for a variety of Earth science products. Our research is centered on using Deep Learning for automatically generating transformations for increasing the spatial resolution of remotely sensed images with different spatial, spectral, and temporal resolutions. One of the most important steps in using images from multiple sensors is to transform the different image layers into the same spatial resolution, preferably the highest spatial resolution, without compromising the spectral information. Recent advances in Deep Learning have shown that CNNs can be used to effectively and efficiently upscale or enhance the spatial resolution of multispectral images with the use of an auxiliary data source such as a high spatial resolution panchromatic image. In contrast, we are using both the spatial and spectral details inherent in low spatial resolution multispectral images for image enhancement without the use of a panchromatic image. This presentation will discuss how this technology will benefit many Earth Science applications that use remotely sensed images with moderate spatial resolutions.

Interactive instruction of cellular physiology for remote learning.

PubMed

Huang, C; Huang, H K

2003-12-01

The biomedical sciences are a rapidly changing discipline that have adapted to innovative technological advances. Despite these many advances, we face two major challenges: a) the number of experts in the field is vastly outnumbered by the number of students, many of whom are separated geographically or temporally and b) the teaching methods used to instruct students and learners have not changed. Today's students have adapted to technology--they use the web as a source of information and communicate via email and chat rooms. Teaching in the biomedical sciences should adopt these new information technologies (IT), but has thus far failed to capitalize on technological opportunity. Creating a "digital textbook" of the traditional learning material is not sufficient for dynamic processes such as cellular physiology. This paper describes innovative teaching techniques that incorporate familiar IT and high-quality interactive learning content with user-centric instruction design models. The Virtual Labs Project from Stanford University has created effective interactive online teaching modules in physiology (simPHYSIO) and delivered them over broadband networks to their undergraduate and medical students. Evaluation results of the modules are given as a measure of success of such innovative teaching method. This learning media strategically merges IT innovations with pedagogy to produce user-driven animations of processes and engaging interactive simulations.

NASA's Swift Education and Public Outreach Program

NASA Astrophysics Data System (ADS)

Cominsky, L. R.; Graves, T.; Plait, P.; Silva, S.; Simonnet, A.

2004-08-01

Few astronomical objects excite students more than big explosions and black holes. Gamma Ray Bursts (GRBs) are both: powerful explosions that signal the births of black holes. NASA's Swift satellite mission, set for launch in Fall 2004, will detect hundreds of black holes over its two-year nominal mission timeline. The NASA Education and Public Outreach (E/PO) group at Sonoma State University is leading the Swift E/PO effort, using the Swift mission to engage students in science and math learning. We have partnered with the Lawrence Hall of Science to create a ``Great Explorations in Math and Science" guide entitled ``Invisible Universe: from Radio Waves to Gamma Rays," which uses GRBs to introduce students to the electromagnetic spectrum and the scale of energies in the Universe. We have also created new standards-based activities for grades 9-12 using GRBs: one activity puts the students in the place of astronomers 20 years ago, trying to sort out various types of stellar explosions that create high-energy radiation. Another mimics the use of the Interplanetary Network to let students figure out the direction to a GRB. Post-launch materials will include magazine articles about Swift and GRBs, and live updates of GRB information to the Swift E/PO website that will excite and inspire students to learn more about space science.

The NASA Science Internet: An integrated approach to networking

NASA Technical Reports Server (NTRS)

Rounds, Fred

1991-01-01

An integrated approach to building a networking infrastructure is an absolute necessity for meeting the multidisciplinary science networking requirements of the Office of Space Science and Applications (OSSA) science community. These networking requirements include communication connectivity between computational resources, databases, and library systems, as well as to other scientists and researchers around the world. A consolidated networking approach allows strategic use of the existing science networking within the Federal government, and it provides networking capability that takes into consideration national and international trends towards multivendor and multiprotocol service. It also offers a practical vehicle for optimizing costs and maximizing performance. Finally, and perhaps most important to the development of high speed computing is that an integrated network constitutes a focus for phasing to the National Research and Education Network (NREN). The NASA Science Internet (NSI) program, established in mid 1988, is structured to provide just such an integrated network. A description of the NSI is presented.

Professional development in photonics: the advanced technology education projects of the New England Board of Education

NASA Astrophysics Data System (ADS)

Donnelly, Judith; Hanes, Fenna; Massa, Nicholas

2007-09-01

Since 1995, the New England Board of Education (NEBHE) has been providing curriculum and professional development as well as laboratory improvement in optics/photonics to middle school and high school teachers and college faculty across the United States. With funding from the National Science Foundation's Advanced Technology Education program, NEBHE's optics/photonics education projects have created a national network of educational and industry alliances resulting in opportunities in optics and photonics for students at participating schools and colleges. The cornerstone of NEBHE projects is collaboration among educational levels, career counselors and teachers/faculty, and industry and academia. In such a rich atmosphere of cooperation, participants have been encouraged to create their own regional projects and activities involving students from middle school through four-year universities. In this paper we will describe the evolution of teacher/faculty professional development from a traditional week-long summer workshop to a collaborative distance learning laboratory course based on adult learning principles and supported by a national network of industry mentors.

Climate Literacy and Cyberlearning: Emerging Platforms and Programs

NASA Astrophysics Data System (ADS)

McCaffrey, M. S.; Wise, S. B.; Buhr, S. M.

2009-12-01

With the release of the Essential Principles of Climate Science Literacy: A Guide for Individuals and Communities in the Spring of 2009, an important step toward an shared educational and communication framework about climate science was achieved. Designed as a living document, reviewed and endorsed by the thirteen federal agencies in the U.S. Climate Change Science Program (now U.S. Global Change Research Program), the Essential Principles of Climate Literacy complement other Earth system literacy efforts. A variety of emerging efforts have begun to build on the framework using a variety of cyberlearning tools, including an online Climate Literacy course developed by Education and Outreach group at CIRES, the Cooperative Institute for Research in Environmental Sciences, and the Independent Learning program of the Continuing Education Division at the University of Colorado at Boulder. The online course, piloted during the Summer of 2009 with formal classroom teachers and informal science educators, made use of the online Climate Literacy Handbook, which was developed by CIRES Education and Outreach and the Encyclopedia of Earth, which is supported by the National Council for Science and the Environment and hosted by Boston University. This paper will explore challenges and opportunities in the use of cyberlearning tools to support climate literacy efforts, highlight the development of the online course and handbook, and note related emerging cyberlearning platforms and programs for climate literacy, including related efforts by the Climate Literacy Network, the NASA Global Climate Change Education programs, the National STEM Education Distributed Learning (NSDL) and AAAS Project 2061.

A Stochastic Sprint in the Vague Direction of Data Science: Perspectives from a Graduate Student and Aspiring Data Scientist.

NASA Astrophysics Data System (ADS)

Barberie, S. R.

2015-12-01

Since data science does not exist as a stand-alone discipline within major universities, learning data science, or even learning that data science exists is, for an aspiring researcher at the graduate or undergraduate level, something that only happens by accident. Here I present my own series of accidents that transformed me from a somewhat aimless graduate student into an aspiring data scientist and the challenges that that aspiration has created in fitting into traditional academic programs and finding a coherent path forward. I also present my current conundrum: with the clear intention of pursuing data science but an academic background in other subjects, where do I go from here? Do I start my education over, pursue professional certification courses and bootcamp programs, or engage in not-very-marketable self study? This career chasm creates a strange environment for aspiring data scientists where we have a destination, but not a clear road to get there. I also discuss how joining a data focused interest group called The Federation of Earth Science Information Partners (ESIP) bridged some of the gap left by Academia in allowing me to network and collaborate with real data scientists from a variety of backgrounds. Organizations like this may someday play an important role in helping aspiring data scientists find their place, although for the moment many gaps and obstacles still remain, and the path forward is far from clear.

Blending Formal and Informal Learning Networks for Online Learning

ERIC Educational Resources Information Center

Czerkawski, Betül C.

2016-01-01

With the emergence of social software and the advance of web-based technologies, online learning networks provide invaluable opportunities for learning, whether formal or informal. Unlike top-down, instructor-centered, and carefully planned formal learning settings, informal learning networks offer more bottom-up, student-centered participatory…

The Next Generation of NASA Night Sky Network: A Searchable Nationwide Database of Astronomy Events

NASA Astrophysics Data System (ADS)

Ames, Z.; Berendsen, M.; White, V.

2010-08-01

With support from NASA, the Astronomical Society of the Pacific (ASP) first developed the Night Sky Network (NSN) in 2004. The NSN was created in response to research conducted by the Institute for Learning Innovation (ILI) to determine what type of support amateur astronomers could use to increase the efficiency and extent of their educational outreach programs. Since its creation, the NSN has grown to include an online searchable database of toolkit resources, Presentation Skills Videos covering topics such as working with kids and how to answer difficult questions, and a searchable nationwide calendar of astronomy events that supports club organization. The features of the NSN have allowed the ASP to create a template that amateur science organizations might use to create a similar support network for their members and the public.

Investigating the Potential Impacts of Energy Production in the Marcellus Shale Region Using the Shale Network Database

NASA Astrophysics Data System (ADS)

Brantley, S.; Pollak, J.

2016-12-01

The Shale Network's extensive database of water quality observations in the Marcellus Shale region enables educational experiences about the potential impacts of resource extraction and energy production with real data. Through tools that are open source and free to use, interested parties can access and analyze the very same data that the Shale Network team has used in peer-reviewed publications about the potential impacts of hydraulic fracturing on water. The development of the Shale Network database has been made possible through efforts led by an academic team and involving numerous individuals from government agencies, citizen science organizations, and private industry. With these tools and data, the Shale Network team has engaged high school students, university undergraduate and graduate students, as well as citizens so that all can discover how energy production impacts the Marcellus Shale region, which includes Pennsylvania and other nearby states. This presentation will describe these data tools, how the Shale Network has used them in educational settings, and the resources available to learn more.

The Potential for Double-Loop Learning to Enable Landscape Conservation Efforts

NASA Astrophysics Data System (ADS)

Petersen, Brian; Montambault, Jensen; Koopman, Marni

2014-10-01

As conservation increases its emphasis on implementing change at landscape-level scales, multi-agency, cross-boundary, and multi-stakeholder networks become more important. These elements complicate traditional notions of learning. To investigate this further, we examined structures of learning in the Landscape Conservation Cooperatives (LCCs), which include the entire US and its territories, as well as parts of Canada, Mexico, and Caribbean and Pacific island states. We used semi-structured interviews, transcribed and analyzed using NVivo, as well as a charrette-style workshop to understand the difference between the original stated goals of individual LCCs and the values and purposes expressed as the collaboration matured. We suggest double-loop learning as a theoretical framework appropriate to landscape-scale conservation, recognizing that concerns about accountability are among the valid points of view that must be considered in multi-stakeholder collaborations. Methods from the social sciences and public health sectors provide insights on how such learning might be actualized.

Project Kaleidoscope: Advancing What Works in Undergraduate STEM Education

NASA Astrophysics Data System (ADS)

Elrod, S.

2011-12-01

In 1989, Project Kaleidoscope (PKAL) published its first report, What Works: Building Natural Science Communities, on reforming undergraduate STEM (science, technology, engineering and mathematics) education. Since then, PKAL has grown into a national organization comprised of a diverse group of over 6500 STEM educators who are committed to advancing "what works." The PKAL mission is to be a national leader in catalyzing the efforts of people, institutions, organizations and networks to move from analysis to action in significantly improving undergraduate student learning and achievement in STEM (science, technology, engineering and mathematics). Specifically, PKAL's strategic goals are to: 1) Promote the development and wider use of evidence-based teaching, learning and assessment approaches, 2) Build individual and organizational capacity to lead change in STEM education, and 3) Engage the broader community of external stakeholders - professional and disciplinary societies, business and industry groups, accreditation organizations, educational associations, governmental agencies, philanthropic organizations - in achieving our mission. PKAL achieves these goals by serving as the nexus of an interconnected and multidisciplinary web of people, ideas, strategies, evidence and resources focused on systemic change in undergraduate STEM education. PKAL also provides resources on critical issues, such as teaching using pedagogies of engagement, and engages interested faculty, campuses and professional societies in national projects and programs focused on cutting edge issues in STEM education. One of these projects - Mobilizing Disciplinary Societies for a Sustainable Future - is engaging eleven disciplinary societies, including the National Association of Geoscience Teachers, in defining specific resources, faculty development programs and goals focused on promoting undergraduate STEM courses that: 1) provide more knowledge about real-world issues; 2) connect these real-world issues to the concepts of sustainability; 3) offer students opportunities to analyze and implement choices that can help solve societal problems so they are better able to act on their choices both immediately and as future citizens and professionals. PKAL has also been offering leadership institutes for STEM faculty members to develop their knowledge and skills as change agents who have the capacity to lead educational reform at their institutions. Since 1996, over 200 faculty members from across the STEM disciplines have attended the institutes. An analysis of leadership alumni indicates that nearly 40% have moved on to administrative leadership positions. Alumni of these institutes are now leading regional STEM reform networks in five locations around the U.S. Since 2007, PKAL networks have engaged nearly 650 STEM faculty and campus leaders from over 100 diverse institutions in professional development workshops focused on STEM reform teaching and learning to effect a wider reach of STEM education transformation on campuses where it matters most. Network expertise and resources are disseminated on PKAL's website and national meetings. These programs illustrate PKAL's efforts to build community and disseminate resources that have a national impact on advancing undergraduate STEM teaching, learning and success for all students.

International institute for collaborative cell biology and biochemistry--history and memoirs from an international network for biological sciences.

PubMed

Cameron, L C

2013-01-01

I was invited to write this essay on the occasion of my selection as the recipient of the 2012 Bruce Alberts Award for Excellence in Science Education from the American Society for Cell Biology (ASCB). Receiving this award is an enormous honor. When I read the email announcement for the first time, it was more than a surprise to me, it was unbelievable. I joined ASCB in 1996, when I presented a poster and received a travel award. Since then, I have attended almost every ASCB meeting. I will try to use this essay to share with readers one of the best experiences in my life. Because this is an essay, I take the liberty of mixing some of my thoughts with data in a way that it not usual in scientific writing. I hope that this sacrifice of the format will achieve the goal of conveying what I have learned over the past 20 yr, during which time a group of colleagues and friends created a nexus of knowledge and wisdom. We have worked together to build a network capable of sharing and inspiring science all over the world.

[Thirty years of US long-term ecological research: characteristics, results, and lessons learned of--taking the Virginia Coast Reserve as an example].

PubMed

Zhu, Gao-Ru; Porter, John H; Xu, Xue-Gong

2011-06-01

In order to observe and understand long-term and large-scale ecological changes, the US National Science Foundation initiated a Long-Term Ecological Research (LTER) program in 1980. Over the past 30 years, the US LTER program has achieved advances in ecological and social science research, and in the development of site-based research infrastructure. This paper attributed the success of the program to five characteristics, i.e., 1) consistency of research topics and data across the network, 2) long-term time scale of both the research and the program, 3) flexibility in research content and funding procedures, 4) growth of LTER to include international partners, new disciplines such as social science, advanced research methods, and cooperation among sites, and 5) sharing of data and educational resources. The Virginia Coast Reserve LTER site was taken as an example to illustrate how the US LTER works at site level. Some suggestions were made on the China long-term ecological research, including strengthening institution construction, improving network and inter-site cooperation, emphasizing data quality, management, and sharing, reinforcing multidisciplinary cooperation, and expanding public influence.

The Future of the New Media in the Communication of Science

NASA Astrophysics Data System (ADS)

Hanson, Joseph

2014-03-01

New media, that which is based around social networks, ubiquitous consumer technology, and today's near-universal access to information, has transformed the way that science is communicated to the scientist and non-scientist alike. We may be in the midst of mankind's greatest shift in information consumption and distribution since the invention of the printing press. Or maybe not. The problem with predicting the future is that it's very hard, and unless you're Isaac Asimov, it's very easy to be wrong. When one predicts the future regarding the internet, that risk becomes almost a certainty. Still, we can apply lessons learned from the near and distant history of science communication to put today's new media evolution into perspective, and to give us clues as to where social media, digital journalism, open access, and online education will lead science communication in years to come. Most importantly, it remains to be seen whether this new media evolution will translate into a shift in how science is viewed by citizens and their policymakers.

Constructing of Research-Oriented Learning Mode Based on Network Environment

ERIC Educational Resources Information Center

Wang, Ying; Li, Bing; Xie, Bai-zhi

2007-01-01

Research-oriented learning mode that based on network is significant to cultivate comprehensive-developing innovative person with network teaching in education for all-around development. This paper establishes a research-oriented learning mode by aiming at the problems existing in research-oriented learning based on network environment, and…

The 2017 Solar Eclipse Community Impacts through Public Library Engagement

NASA Astrophysics Data System (ADS)

Dusenbery, P.; Holland, A.; LaConte, K.; Mosshammer, G.; Harold, J. B.; Fraknoi, A.; Schatz, D.; Duncan, D. K.

2017-12-01

More than two million pairs of eclipse glasses were distributed free through public libraries in the U.S. for the solar eclipse of the Sun taking place on August 21, 2017. About 7,000 organizations, including public library branches, bookmobiles, tribal libraries, library consortia, and state libraries took part in the celestial event of the century. Many organizations received a package of free safe-viewing glasses, plus a 24-page information booklet about eclipse viewing and suggested program ideas. An educational video was also produced on how best to do public outreach programs about the eclipse. The project was supported, in part, by the Gordon and Betty Moore Foundation, with additional help from Google, NASA, the Research Corporation, and the National Science Foundation (NSF). The program was managed through the Space Science Institute's National Center for Interactive Learning as part of its STAR Library Network (STAR_Net). Resources developed by STAR_Net for this event included an Eclipse Resource Center; a newsletter for participating libraries to learn about eclipses and how to implement an effective and safe eclipse program; eclipse program activities on its STEM Activity Clearinghouse; webinars; and connections to subject matter experts from NASA's and the American Astronomical Society's volunteer networks. This presentation will provide an overview of the extensive collaboration that made this program possible as well as highlight the national impact that public libraries made in their communities.

From Local to EXtreme Environments (FLEXE) Student-Scientist Online Forums: hypothesis-based research examining ways to involve scientists in effective science education

NASA Astrophysics Data System (ADS)

Goehring, L.; Carlsen, W.; Fisher, C. R.; Kerlin, S.; Trautmann, N.; Petersen, W.

2011-12-01

Science education reform since the mid-1990's has called for a "new way of teaching and learning about science that reflects how science itself is done, emphasizing inquiry as a way of achieving knowledge and understanding about the world" (NRC, 1996). Scientists and engineers, experts in inquiry thinking, have been called to help model these practices for students and demonstrate scientific habits of mind. The question, however, is "how best to involve these experts?" given the very real challenges of limited availability of scientists, varying experience with effective pedagogy, widespread geographic distribution of schools, and the sheer number of students involved. Technology offers partial solutions to enable Student-Scientist Interactions (SSI). The FLEXE Project has developed online FLEXE Forums to support efficient, effective SSIs, making use of web-based and database technology to facilitate communication between students and scientists. More importantly, the FLEXE project has approached this question of "how best to do this?" scientifically, combining program evaluation with hypothesis-based research explicitly testing the effects of such SSIs on student learning and attitudes towards science. FLEXE Forums are designed to showcase scientific practices and habits of mind through facilitated interaction between students and scientists. Through these Forums, students "meet" working scientists and learn about their research and the environments in which they work. Scientists provide students with intriguing "real-life" datasets and challenge students to analyze and interpret the data through guiding questions. Students submit their analyses to the Forum, and scientists provide feedback and connect the instructional activity with real-life practice, showcasing their activities in the field. In the FLEXE project, Forums are embedded within inquiry-based instructional units focused on essential learning concepts, and feature the deep-sea environment in contrast to students' local environments to deepen students' understanding of earth systems processes. This presentation will provide an overview of the FLEXE project, a partnership between the Ridge2000 research scientists, science learning researchers, and educators, and will report findings from pilot studies implemented in collaboration with the GLOBE program, a worldwide network of scientists, science educators, and their students. FLEXE Forums have been tested with approximately 1400 students in the US, Germany, Australia and Thailand in 2009, and 1100 students in the US, Thailand, England and Costa Rica in 2010. Description of research methods (e.g., educational hypotheses, assessment of student learning and attitudes through analysis of student writing, and "quick question" surveys) and results will be shared, along with current tests examining the transferability of the approach to other scientists/science educator teams.

System level mechanisms of adaptation, learning, memory formation and evolvability: the role of chaperone and other networks.

PubMed

Gyurko, David M; Soti, Csaba; Stetak, Attila; Csermely, Peter

2014-05-01

During the last decade, network approaches became a powerful tool to describe protein structure and dynamics. Here, we describe first the protein structure networks of molecular chaperones, then characterize chaperone containing sub-networks of interactomes called as chaperone-networks or chaperomes. We review the role of molecular chaperones in short-term adaptation of cellular networks in response to stress, and in long-term adaptation discussing their putative functions in the regulation of evolvability. We provide a general overview of possible network mechanisms of adaptation, learning and memory formation. We propose that changes of network rigidity play a key role in learning and memory formation processes. Flexible network topology provides ' learning-competent' state. Here, networks may have much less modular boundaries than locally rigid, highly modular networks, where the learnt information has already been consolidated in a memory formation process. Since modular boundaries are efficient filters of information, in the 'learning-competent' state information filtering may be much smaller, than after memory formation. This mechanism restricts high information transfer to the 'learning competent' state. After memory formation, modular boundary-induced segregation and information filtering protect the stored information. The flexible networks of young organisms are generally in a 'learning competent' state. On the contrary, locally rigid networks of old organisms have lost their 'learning competent' state, but store and protect their learnt information efficiently. We anticipate that the above mechanism may operate at the level of both protein-protein interaction and neuronal networks.

Machine-learning approach for local classification of crystalline structures in multiphase systems

NASA Astrophysics Data System (ADS)

Dietz, C.; Kretz, T.; Thoma, M. H.

2017-07-01

Machine learning is one of the most popular fields in computer science and has a vast number of applications. In this work we will propose a method that will use a neural network to locally identify crystal structures in a mixed phase Yukawa system consisting of fcc, hcp, and bcc clusters and disordered particles similar to plasma crystals. We compare our approach to already used methods and show that the quality of identification increases significantly. The technique works very well for highly disturbed lattices and shows a flexible and robust way to classify crystalline structures that can be used by only providing particle positions. This leads to insights into highly disturbed crystalline structures.

Conceptual Change in Understanding the Nature of Science Learning: An Interpretive Phenomenological Analysis

NASA Astrophysics Data System (ADS)

DiBenedetto, Christina M.

This study is the first of its kind to explore the thoughts, beliefs, attitudes and values of secondary educators as they experience conceptual change in their understanding of the nature of science learning vis a vis the Framework for K-12 Science Education published by the National Research Council. The study takes aim at the existing gap between the vision for science learning as an active process of inquiry and current pedagogical practices in K-12 science classrooms. For students to understand and explain everyday science ideas and succeed in science studies and careers, the means by which they learn science must change. Focusing on this change, the study explores the significance of educator attitudes, beliefs and values to science learning through interpretive phenomenological analysis around the central question, "In what ways do educators understand and articulate attitudes and beliefs toward the nature of science learning?" The study further explores the questions, "How do educators experience changes in their understanding of the nature of science learning?" and "How do educators believe these changes influence their pedagogical practice?" Study findings converge on four conceptions that science learning: is the action of inquiry; is a visible process initiated by both teacher and learner; values student voice and changing conceptions is science learning. These findings have implications for the primacy of educator beliefs, attitudes and values in reform efforts, science teacher leadership and the explicit instruction of both Nature of Science and conceptual change in educator preparation programs. This study supports the understanding that the nature of science learning is cognitive and affective conceptual change. Keywords: conceptual change, educator attitudes and beliefs, framework for K-12 science education, interpretive phenomenological analysis, nature of science learning, next generation science standards, science professional development, secondary science education.

Health Detectives: Uncovering the Mysteries of Disease (LBNL Science at the Theater)

ScienceCinema

Bissell, Mina; Canaria, Christie; Celnicker, Susan; Karpen, Gary

2018-06-20

In this April 23, 2012 Science at the Theater event, Berkeley Lab scientists discuss how they uncover the mysteries of disease in unlikely places. Speakers and topics include: World-renowned cancer researcher Mina Bissell's pioneering research on the role of the cellular microenvironment in breast cancer has changed the conversation about the disease. How does DNA instability cause disease? To find out, Christie Canaria images neural networks to study disorders such as Huntington's disease. Fruit flies can tell us a lot about ourselves. Susan Celniker explores the fruit fly genome to learn how our genome works. DNA is not destiny. Gary Karpen explores how environmental factors shape genome function and disease through epigenetics.

Health Promotion for Adolescent Childhood Leukemia Survivors: Building on Prevention Science and eHealth

PubMed Central

Elliot, Diane L.; Lindemulder, Susan J.; Goldberg, Linn; Stadler, Diane D.; Smith, Jennifer

2014-01-01

Teenage survivors of childhood acute lymphoblastic leukemia (ALL) have increased morbidity likely due to their prior multicomponent treatment. Habits established in adolescence can impact individuals’ subsequent adult behaviors. Accordingly, healthy lifestyles, avoiding harmful actions, and appropriate disease surveillance are of heightened importance among teenage survivors. We review the findings from prevention science and their relevance to heath promotion. The capabilities and current uses of eHealth components including e-learning, serious video games, exergaming, behavior tracking, individual messaging, and social networking are briefly presented. The health promotion needs of adolescent survivors are aligned with those eHealth aspects to propose a new paradigm to enhance the wellbeing of adolescent ALL survivors. PMID:23109253

The Identification of Major Factors in the Deployment of a Science DMZ at Small Institutions

ERIC Educational Resources Information Center

Valcourt, Scott A.

2017-01-01

The Science DMZ is a network research tool offering superior large science data transmission between two locations. Through a network design that places the Science DMZ at the edge of the campus network, the Science DMZ defines a network path that avoids packet inspecting devices (firewalls, packet shapers) and produces near line-rate transmission…

Accelerating Learning By Neural Networks

NASA Technical Reports Server (NTRS)

Toomarian, Nikzad; Barhen, Jacob

1992-01-01

Electronic neural networks made to learn faster by use of terminal teacher forcing. Method of supervised learning involves addition of teacher forcing functions to excitations fed as inputs to output neurons. Initially, teacher forcing functions are strong enough to force outputs to desired values; subsequently, these functions decay with time. When learning successfully completed, terminal teacher forcing vanishes, and dynamics or neural network become equivalent to those of conventional neural network. Simulated neural network with terminal teacher forcing learned to produce close approximation of circular trajectory in 400 iterations.

Mission EarthFusing GLOBE with NASA Assets to Build SystemicInnovation in STEM Education

NASA Astrophysics Data System (ADS)

Czajkowski, K. P.; Garik, P.; Padgett, D.; Darche, S.; Struble, J.; Adaktilou, N.

2016-12-01

Mission Earth is a project funded through the NASA CAN that is developing a systematic embedding of NASA assets that is being implemented by a partnership of organizations across the US. Mission Earth brings together scientists and science educators to develop a K-12 "Earth as a system" curriculum progression following research-based best practices. GLOBE and NASA assets will be infused into the curricula of schools along the K-12 continuum, leveraging existing partnerships and networks and supported through state departments of education and targeting underrepresented groups, as a systemic, effective, and sustainable approach to meeting NASA's science education objectives. This presentation will discuss plans for the Mission Earth project and successes and lessons learned in the first year. Mission Earth is developing curricular materials to support vertically integrated learning progressions. It develops models of professional development utilizing sustainable infrastructures. It will support STEM careers focusing on career technical education (CTE). And, it will engage undergraduate education majors through pre-service courses and engineering students through engineering challenges.

Spitzer Space Telescope Sequencing Operations Software, Strategies, and Lessons Learned

NASA Technical Reports Server (NTRS)

Bliss, David A.

2006-01-01

The Space Infrared Telescope Facility (SIRTF) was launched in August, 2003, and renamed to the Spitzer Space Telescope in 2004. Two years of observing the universe in the wavelength range from 3 to 180 microns has yielded enormous scientific discoveries. Since this magnificent observatory has a limited lifetime, maximizing science viewing efficiency (ie, maximizing time spent executing activities directly related to science observations) was the key operational objective. The strategy employed for maximizing science viewing efficiency was to optimize spacecraft flexibility, adaptability, and use of observation time. The selected approach involved implementation of a multi-engine sequencing architecture coupled with nondeterministic spacecraft and science execution times. This approach, though effective, added much complexity to uplink operations and sequence development. The Jet Propulsion Laboratory (JPL) manages Spitzer s operations. As part of the uplink process, Spitzer s Mission Sequence Team (MST) was tasked with processing observatory inputs from the Spitzer Science Center (SSC) into efficiently integrated, constraint-checked, and modeled review and command products which accommodated the complexity of non-deterministic spacecraft and science event executions without increasing operations costs. The MST developed processes, scripts, and participated in the adaptation of multi-mission core software to enable rapid processing of complex sequences. The MST was also tasked with developing a Downlink Keyword File (DKF) which could instruct Deep Space Network (DSN) stations on how and when to configure themselves to receive Spitzer science data. As MST and uplink operations developed, important lessons were learned that should be applied to future missions, especially those missions which employ command-intensive operations via a multi-engine sequence architecture.

Network congestion control algorithm based on Actor-Critic reinforcement learning model

NASA Astrophysics Data System (ADS)

Xu, Tao; Gong, Lina; Zhang, Wei; Li, Xuhong; Wang, Xia; Pan, Wenwen

2018-04-01

Aiming at the network congestion control problem, a congestion control algorithm based on Actor-Critic reinforcement learning model is designed. Through the genetic algorithm in the congestion control strategy, the network congestion problems can be better found and prevented. According to Actor-Critic reinforcement learning, the simulation experiment of network congestion control algorithm is designed. The simulation experiments verify that the AQM controller can predict the dynamic characteristics of the network system. Moreover, the learning strategy is adopted to optimize the network performance, and the dropping probability of packets is adaptively adjusted so as to improve the network performance and avoid congestion. Based on the above finding, it is concluded that the network congestion control algorithm based on Actor-Critic reinforcement learning model can effectively avoid the occurrence of TCP network congestion.