Designing for Discovery: Interactive Multimedia Learning Environments at Bank Street College. Technical Report No. 15.

ERIC Educational Resources Information Center

Wilson, Kathleen; Tally, William

This report discusses "multimedia" instruction as it applies to successful learning environments at Bank Street College of Education (New York), ranging from pre-electronic to electronic. In four of the interviews detailed, a Bank Street College professor, researcher, and two Bank Street School for Children teachers offer different perspectives…

Student Learning Centre (SLC) Embraces the New Melbourne Model of Teaching: Facilitating Collaborative Learning

ERIC Educational Resources Information Center

Ball, Sarah

2010-01-01

Learning is about discovery and change. As schools and universities look to the future, it is fundamental that they provide environments that facilitate collaborative learning and act as points for interaction and social activity. The redevelopment of the existing Engineering Library into a Student Learning Centre (SLC) embraces the new Melbourne…

Using Learning Analytics to Identify Medical Student Misconceptions in an Online Virtual Patient Environment

ERIC Educational Resources Information Center

Poitras, Eric G.; Naismith, Laura M.; Doleck, Tenzin; Lajoie, Susanne P.

2016-01-01

This study aimed to identify misconceptions in medical student knowledge by mining user interactions in the MedU online learning environment. Data from 13000 attempts at a single virtual patient case were extracted from the MedU MySQL database. A subgroup discovery method was applied to identify patterns in learner-generated annotations and…

Discovery of Action Patterns and User Correlations in Task-Oriented Processes for Goal-Driven Learning Recommendation

ERIC Educational Resources Information Center

Zhou, Xiaokang; Chen, Jian; Wu, Bo; Jin, Qun

2014-01-01

With the high development of social networks, collaborations in a socialized web-based learning environment has become increasing important, which means people can learn through interactions and collaborations in communities across social networks. In this study, in order to support the enhanced collaborative learning, two important factors, user…

A constructivist approach to studying the bullwhip effect by simulating the supply chain

NASA Astrophysics Data System (ADS)

González-Torre, Pilar L.; Adenso-Díaz, B.; Moreno, Plácido

2015-11-01

The Cider Game is a simulator for a supply chain-related learning environment. Its main feature is that it provides support to students in the constructivist discovery process when learning how to make logistics decisions, at the same time as noting the occurrence of the bullwhip phenomenon. This learning environment seeks a balance between direct instruction in the learning process on the part of the tutor, and a suitable and sufficient degree of freedom to regulate independent learning on the part of students. This article describes the basic learning mechanisms using the Cider Game and the graphical learning environments that it provides. We describe the functionality provided by this application, and analyse the effect over the rational understanding of the bullwhip phenomenon by the students and whether they are able to make decisions to minimise its impact, studying the differences when that decision-making learning is done individually or in groups.

Movement Education-Past-Present-Future.

ERIC Educational Resources Information Center

Fowler, John S.

Physical education in England at the secondary school level was dominated in the 1950's by a formal, disciplinary method of teaching known as the "Swedish Drill," developed from the remedial gymnastics of P. H. Ling. However, at the elementary education level, a change towards informality, discovery learning, learning environments, and…

Scaffolding for Discovery in the Third Plane

ERIC Educational Resources Information Center

Ewert-Krocker, Laurie

2015-01-01

Laurie Ewert-Krocker emphasizes the teacher's role in nature's prepared environment. Without directing or controlling the child's work, learning spaces can be maximized for concentration by connecting the adolescent's intrinsic learning to the beauty and order of the natural world. The most artful balance is the global understanding of the…

Individual Differences in Learning from an Intelligent Discovery World: Smithtown.

ERIC Educational Resources Information Center

Shute, Valerie J.

"Smithtown" is an intelligent computer program designed to enhance an individual's scientific inquiry skills as well as to provide an environment for learning principles of basic microeconomics. It was hypothesized that intelligent computer instruction on applying effective interrogative skills (e.g., changing one variable at a time…

A Role for Neuroscience in Shaping Contemporary Education Policy

ERIC Educational Resources Information Center

Shore, Rebecca; Bryant, Joel

2011-01-01

Advanced technologies have made it possible for neuroscientists to make remarkable discoveries regarding how our brains learn. This research should provide new insights into the designs of learning environments. This essay is an attempt to suggest how the possibilities of neuroscience might be employed to meet contemporary educational demands,…

Learning Processes and Learning Outcomes

DTIC Science & Technology

1992-06-01

establish and maintain activation levels) may process information faster because the relevant traces in long - term memory are already activated...drill and practice, and discovery. Finally, implications for the design of computerized instructional environments are indicated. 14. SUBJECT TERMS lI...outcome. This impact may be direct, or may interact with characteristics of the learner to effect learning outcome. INITIAL STATES Conative and cognitive

Interactive Videodisc: the "Why" and the "How." CALICO Monograph Volume 2, Spring 1991.

ERIC Educational Resources Information Center

Bush, Michael D.; And Others

This monograph presents articles on interactive videodisc technology in language learning, ranging from the importance of a theoretical framework, the transition from theory to practice, getting started, design considerations, hypermedia, discovery environments, authoring software, workstation environments, and a look at the future of optical disc…

Subgroup Discovery with User Interaction Data: An Empirically Guided Approach to Improving Intelligent Tutoring Systems

ERIC Educational Resources Information Center

Poitras, Eric G.; Lajoie, Susanne P.; Doleck, Tenzin; Jarrell, Amanda

2016-01-01

Learner modeling, a challenging and complex endeavor, is an important and oft-studied research theme in computer-supported education. From this perspective, Educational Data Mining (EDM) research has focused on modeling and comprehending various dimensions of learning in computer-based learning environments (CBLE). Researchers and designers are…

Beyond adaptive-critic creative learning for intelligent mobile robots

NASA Astrophysics Data System (ADS)

Liao, Xiaoqun; Cao, Ming; Hall, Ernest L.

2001-10-01

Intelligent industrial and mobile robots may be considered proven technology in structured environments. Teach programming and supervised learning methods permit solutions to a variety of applications. However, we believe that to extend the operation of these machines to more unstructured environments requires a new learning method. Both unsupervised learning and reinforcement learning are potential candidates for these new tasks. The adaptive critic method has been shown to provide useful approximations or even optimal control policies to non-linear systems. The purpose of this paper is to explore the use of new learning methods that goes beyond the adaptive critic method for unstructured environments. The adaptive critic is a form of reinforcement learning. A critic element provides only high level grading corrections to a cognition module that controls the action module. In the proposed system the critic's grades are modeled and forecasted, so that an anticipated set of sub-grades are available to the cognition model. The forecasting grades are interpolated and are available on the time scale needed by the action model. The success of the system is highly dependent on the accuracy of the forecasted grades and adaptability of the action module. Examples from the guidance of a mobile robot are provided to illustrate the method for simple line following and for the more complex navigation and control in an unstructured environment. The theory presented that is beyond the adaptive critic may be called creative theory. Creative theory is a form of learning that models the highest level of human learning - imagination. The application of the creative theory appears to not only be to mobile robots but also to many other forms of human endeavor such as educational learning and business forecasting. Reinforcement learning such as the adaptive critic may be applied to known problems to aid in the discovery of their solutions. The significance of creative theory is that it permits the discovery of the unknown problems, ones that are not yet recognized but may be critical to survival or success.

Learning in the Out-of-Doors: Motivation, Discovery, Inquiry, Exploration, Investigation.

ERIC Educational Resources Information Center

Burtnett, Nancy, Ed.

Methods for use by teachers of elementary-school-age children in utilizing outdoor experiences in the study of various subjects are presented in this guide. Learning activities are described in 3 units: (1) language arts, in which students are stimulated to communicate ideas they have about the natural environment and to understand their…

Personalization of Learning Activities within a Virtual Environment for Training Based on Fuzzy Logic Theory

ERIC Educational Resources Information Center

Mohamed, Fahim; Abdeslam, Jakimi; Lahcen, El Bermi

2017-01-01

Virtual Environments for Training (VET) are useful tools for visualization, discovery as well as for training. VETs are based on virtual reality technique to put learners in training situations that emulate genuine situations. VETs have proven to be advantageous in putting learners into varied training situations to acquire knowledge and…

How to Support Learners in Developing Usable and Lasting Knowledge of STEM

ERIC Educational Resources Information Center

Krajcik, Joseph; Delen, Ibrahim

2017-01-01

All students need to experience the joy of discovery and innovation. In this study we discussed how STEM education that focuses on design can provide students with these opportunities. Learning environments that focus on STEM questions and engage students in design have the potential help students learn core ideas related to STEM as well as engage…

An analysis of K--5 teachers' beliefs regarding the uses of direct instruction, the discovery method, and the inquiry method in elementary science education

NASA Astrophysics Data System (ADS)

Kowalczyk, Donna Lee

The purpose of this study was to examine K--5 elementary teachers' reported beliefs about the use, function, and importance of Direct Instruction, the Discovery Method, and the Inquiry Method in the instruction of science in their classrooms. Eighty-two teachers completed questionnaires about their beliefs, opinions, uses, and ideas about each of the three instructional methods. Data were collected and analyzed using the Statistical Package of the Social Sciences (SPSS). Descriptive statistics and Chi-Square analyses indicated that the majority of teachers reported using all three methods to varying degrees in their classrooms. Guided Discovery was reported by the teachers as being the most frequently used method to teach science, while Pure Discovery was reportedly used the least frequently. The majority of teachers expressed the belief that a blend of all three instructional methods is the most effective strategy for teaching science at the elementary level. The teachers also reported a moderate level of confidence in teaching science. Students' ability levels, learning styles, and time/class schedule were identified as factors that most influence teachers' instructional choice. Student participation in hands-on activities, creative thinking ability, and developing an understanding of scientific concepts were reported as the learning behaviors most associated with student success in science. Data obtained from this study provide information about the nature and uses of Direct Instruction, the Discovery Method, and the Inquiry Method and teachers' perceptions and beliefs about each method's use in science education. Learning more about the science teaching and learning environment may help teachers, administrators, curriculum developers, and researchers gain greater insights about student learning, instructional effectiveness, and science curriculum development at the elementary level.

How does non-formal marine education affect student attitude and knowledge? A case study using SCDNR's Discovery program

NASA Astrophysics Data System (ADS)

McGovern, Mary Francis

Non-formal environmental education provides students the opportunity to learn in ways that would not be possible in a traditional classroom setting. Outdoor learning allows students to make connections to their environment and helps to foster an appreciation for nature. This type of education can be interdisciplinary---students not only develop skills in science, but also in mathematics, social studies, technology, and critical thinking. This case study focuses on a non-formal marine education program, the South Carolina Department of Natural Resources' (SCDNR) Discovery vessel based program. The Discovery curriculum was evaluated to determine impact on student knowledge about and attitude toward the estuary. Students from two South Carolina coastal counties who attended the boat program during fall 2014 were asked to complete a brief survey before, immediately after, and two weeks following the program. The results of this study indicate that both student knowledge about and attitude significantly improved after completion of the Discovery vessel based program. Knowledge and attitude scores demonstrated a positive correlation.

Discovery learning with SAVI approach in geometry learning

NASA Astrophysics Data System (ADS)

Sahara, R.; Mardiyana; Saputro, D. R. S.

2018-05-01

Geometry is one branch of mathematics that an important role in learning mathematics in the schools. This research aims to find out about Discovery Learning with SAVI approach to achievement of learning geometry. This research was conducted at Junior High School in Surakarta city. Research data were obtained through test and questionnaire. Furthermore, the data was analyzed by using two-way Anova. The results showed that Discovery Learning with SAVI approach gives a positive influence on mathematics learning achievement. Discovery Learning with SAVI approach provides better mathematics learning outcomes than direct learning. In addition, students with high self-efficacy categories have better mathematics learning achievement than those with moderate and low self-efficacy categories, while student with moderate self-efficacy categories are better mathematics learning achievers than students with low self-efficacy categories. There is an interaction between Discovery Learning with SAVI approach and self-efficacy toward student's mathematics learning achievement. Therefore, Discovery Learning with SAVI approach can improve mathematics learning achievement.

Habituation based synaptic plasticity and organismic learning in a quantum perovskite.

PubMed

Zuo, Fan; Panda, Priyadarshini; Kotiuga, Michele; Li, Jiarui; Kang, Mingu; Mazzoli, Claudio; Zhou, Hua; Barbour, Andi; Wilkins, Stuart; Narayanan, Badri; Cherukara, Mathew; Zhang, Zhen; Sankaranarayanan, Subramanian K R S; Comin, Riccardo; Rabe, Karin M; Roy, Kaushik; Ramanathan, Shriram

2017-08-14

A central characteristic of living beings is the ability to learn from and respond to their environment leading to habit formation and decision making. This behavior, known as habituation, is universal among all forms of life with a central nervous system, and is also observed in single-cell organisms that do not possess a brain. Here, we report the discovery of habituation-based plasticity utilizing a perovskite quantum system by dynamical modulation of electron localization. Microscopic mechanisms and pathways that enable this organismic collective charge-lattice interaction are elucidated by first-principles theory, synchrotron investigations, ab initio molecular dynamics simulations, and in situ environmental breathing studies. We implement a learning algorithm inspired by the conductance relaxation behavior of perovskites that naturally incorporates habituation, and demonstrate learning to forget: a key feature of animal and human brains. Incorporating this elementary skill in learning boosts the capability of neural computing in a sequential, dynamic environment.Habituation is a learning mechanism that enables control over forgetting and learning. Zuo, Panda et al., demonstrate adaptive synaptic plasticity in SmNiO 3 perovskites to address catastrophic forgetting in a dynamic learning environment via hydrogen-induced electron localization.

Area Studies and Special Collections: Shared Challenges, Shared Strength

ERIC Educational Resources Information Center

Carter, Lisa R.; Whittaker, Beth M.

2015-01-01

Special collections and area studies librarians face similar challenges in the changing academic library environment, including the need to articulate the value of these specialized collections and to mainstream processes and practices into larger discovery, teaching, learning, and research efforts. For some institutions, these similarities have…

Does Discovery-Based Instruction Enhance Learning?

ERIC Educational Resources Information Center

Alfieri, Louis; Brooks, Patricia J.; Aldrich, Naomi J.; Tenenbaum, Harriet R.

2011-01-01

Discovery learning approaches to education have recently come under scrutiny (Tobias & Duffy, 2009), with many studies indicating limitations to discovery learning practices. Therefore, 2 meta-analyses were conducted using a sample of 164 studies: The 1st examined the effects of unassisted discovery learning versus explicit instruction, and the…

Do individual differences in children's curiosity relate to their inquiry-based learning?

NASA Astrophysics Data System (ADS)

van Schijndel, Tessa J. P.; Jansen, Brenda R. J.; Raijmakers, Maartje E. J.

2018-06-01

This study investigates how individual differences in 7- to 9-year-olds' curiosity relate to the inquiry-learning process and outcomes in environments differing in structure. The focus on curiosity as individual differences variable was motivated by the importance of curiosity in science education, and uncertainty being central to both the definition of curiosity and the inquiry-learning environment. Curiosity was assessed with the Underwater Exploration game (Jirout, J., & Klahr, D. (2012). Children's scientific curiosity: In search of an operational definition of an elusive concept. Developmental Review, 32, 125-160. doi:10.1016/j.dr.2012.04.002), and inquiry-based learning with the newly developed Scientific Discovery task, which focuses on the principle of designing informative experiments. Structure of the inquiry-learning environment was manipulated by explaining this principle or not. As intelligence relates to learning and possibly curiosity, it was taken into account. Results showed that children's curiosity was positively related to their knowledge acquisition, but not to their quality of exploration. For low intelligent children, environment structure positively affected their quality of exploration, but not their knowledge acquisition. There was no interaction between curiosity and environment structure. These results support the existence of two distinct inquiry-based learning processes - the designing of experiments, on the one hand, and the reflection on performed experiments, on the other - and link children's curiosity to the latter process.

Open Classes to Local Communities: A Reflection Analysis of a School Environmental Project

ERIC Educational Resources Information Center

Kalathaki, Maria

2017-01-01

School projects of environmental education promote discovery learning, through teamwork, by involving local communities, scientists, organizations, authorities, and bodies and are carried out largely online in virtual environments. This research aimed to identify and highlight those characteristics of local communities that can be exploited by…

Paintbrush of Discovery: Using Java Applets to Enhance Mathematics Education

ERIC Educational Resources Information Center

Eason, Ray; Heath, Garrett

2004-01-01

This article addresses the enhancement of the learning environment by using Java applets in the mathematics classroom. Currently, the first year mathematics program at the United States Military Academy involves one semester of modeling with discrete dynamical systems (DDS). Several faculty members from the Academy have integrated Java applets…

Discovery Learning Strategies in English

ERIC Educational Resources Information Center

Singaravelu, G.

2012-01-01

The study substantiates that the effectiveness of Discovery Learning method in learning English Grammar for the learners at standard V. Discovery Learning is particularly beneficial for any student learning a second language. It promotes peer interaction and development of the language and the learning of concepts with content. Reichert and…

Theory Versus Experiment: The Case of the Positron

NASA Astrophysics Data System (ADS)

Leone, Matteo

The history of positron discovery is an interesting case-study of complex relationship between theory and experiment, and therefore could promote understanding of a key issue on the nature of science (NoS) within a learning environment. As it is well known we had indeed a theory, P.A.M. Dirac's theory of the anti-electron (1931), before the beginning of the experiments leading to the experimental discovery of the positive electron (Anderson 1932). Yet, this case is not merely an instance of successful corroboration of a theoretical prediction since, as it will be shown, the man who made the discovery, Anderson, actually did not know from the start what to look for.

Making Games after School: Participatory Game Design in Non-Formal Learning Environments

ERIC Educational Resources Information Center

Clark, Kevin; Brandt, Jami; Hopkins, Rhonda; Wilhelm, Jason

2009-01-01

Participatory design principles were used with primarily African-American and Latino children in the Washington, DC area in the development of sports-themed digital game prototypes in an after-school program. The three stages in participatory design are the discovery stage, the evaluative stage, and prototyping. Within the participatory design…

Discovery and Broad Relevance May Be Insignificant Components of Course-Based Undergraduate Research Experiences (CUREs) for Non-Biology Majors.

PubMed

Ballen, Cissy J; Thompson, Seth K; Blum, Jessamina E; Newstrom, Nicholas P; Cotner, Sehoya

2018-01-01

Course-based undergraduate research experiences (CUREs) are a type of laboratory learning environment associated with a science course, in which undergraduates participate in novel research. According to Auchincloss et al. (CBE Life Sci Educ 2104; 13:29-40), CUREs are distinct from other laboratory learning environments because they possess five core design components, and while national calls to improve STEM education have led to an increase in CURE programs nationally, less work has specifically focused on which core components are critical to achieving desired student outcomes. Here we use a backward elimination experimental design to test the importance of two CURE components for a population of non-biology majors: the experience of discovery and the production of data broadly relevant to the scientific or local community. We found nonsignificant impacts of either laboratory component on students' academic performance, science self-efficacy, sense of project ownership, and perceived value of the laboratory experience. Our results challenge the assumption that all core components of CUREs are essential to achieve positive student outcomes when applied at scale.

The effect of discovery learning and problem-based learning on middle school students’ self-regulated learning

NASA Astrophysics Data System (ADS)

Miatun, A.; Muntazhimah

2018-01-01

The aim of this research was to determine the effect of learning models on mathematics achievement viewed from student’s self-regulated learning. The learning model compared were discovery learning and problem-based learning. The population was all students at the grade VIII of Junior High School in Boyolali regency. The samples were students of SMPN 4 Boyolali, SMPN 6 Boyolali, and SMPN 4 Mojosongo. The instruments used were mathematics achievement tests and self-regulated learning questionnaire. The data were analyzed using unbalanced two-ways Anova. The conclusion was as follows: (1) discovery learning gives better achievement than problem-based learning. (2) Achievement of students who have high self-regulated learning was better than students who have medium and low self-regulated learning. (3) For discovery learning, achievement of students who have high self-regulated learning was better than students who have medium and low self-regulated learning. For problem-based learning, students who have high and medium self-regulated learning have the same achievement. (4) For students who have high self-regulated learning, discovery learning gives better achievement than problem-based learning. Students who have medium and low self-regulated learning, both learning models give the same achievement.

Fostering First-Graders' Reasoning Strategies with the Most Basic Sums

ERIC Educational Resources Information Center

Purpura, David J.; Baroody, Arthur J.; Eiland, Michael D.; Reid, Erin E.

2012-01-01

In a meta-analysis of 164 studies, Alfieri, Brooks, Aldrich, and Tenenbaum (2010) found that assisted discovery learning was more effective than explicit instruction or unassisted discovery learning and that explicit instruction resulted in more favorable outcomes than unassisted discovery learning. In other words, "unassisted discovery does…

A View of the Science Education Research Literature: Scientific Discovery Learning with Computer Simulations.

ERIC Educational Resources Information Center

Robinson, William R.

2000-01-01

Describes a review of research that addresses the effectiveness of simulations in promoting scientific discovery learning and the problems that learners may encounter when using discovery learning. (WRM)

Habituation based synaptic plasticity and organismic learning in a quantum perovskite

DOE PAGES

Zuo, Fan; Panda, Priyadarshini; Kotiuga, Michele; ...

2017-08-14

A central characteristic of living beings is the ability to learn from and respond to their environment leading to habit formation and decision making. This behavior, known as habituation, is universal among all forms of life with a central nervous system, and is also observed in single-cell organisms that do not possess a brain. Here, we report the discovery of habituation-based plasticity utilizing a perovskite quantum system by dynamical modulation of electron localization. Microscopic mechanisms and pathways that enable this organismic collective charge-lattice interaction are elucidated by first-principles theory, synchrotron investigations, ab initio molecular dynamics simulations, and in situ environmentalmore » breathing studies. In conclusion, we implement a learning algorithm inspired by the conductance relaxation behavior of perovskites that naturally incorporates habituation, and demonstrate learning to forget: a key feature of animal and human brains. Incorporating this elementary skill in learning boosts the capability of neural computing in a sequential, dynamic environment.« less

Habituation based synaptic plasticity and organismic learning in a quantum perovskite

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

Zuo, Fan; Panda, Priyadarshini; Kotiuga, Michele

A central characteristic of living beings is the ability to learn from and respond to their environment leading to habit formation and decision making. This behavior, known as habituation, is universal among all forms of life with a central nervous system, and is also observed in single-cell organisms that do not possess a brain. Here, we report the discovery of habituation-based plasticity utilizing a perovskite quantum system by dynamical modulation of electron localization. Microscopic mechanisms and pathways that enable this organismic collective charge-lattice interaction are elucidated by first-principles theory, synchrotron investigations, ab initio molecular dynamics simulations, and in situ environmentalmore » breathing studies. In conclusion, we implement a learning algorithm inspired by the conductance relaxation behavior of perovskites that naturally incorporates habituation, and demonstrate learning to forget: a key feature of animal and human brains. Incorporating this elementary skill in learning boosts the capability of neural computing in a sequential, dynamic environment.« less

Effect of Similarity-Based Guided Discovery Learning on Conceptual Performance

ERIC Educational Resources Information Center

Mandrin, Pierre-A; Preckel, Daniel

2009-01-01

Analogies are known to foster concept learning, whereas discovery learning is effective for transfer. By combining discovery learning and analogies or similarities of concepts, attractive new arrangements emerge, but do they maintain both concept and transfer effects? Unfortunately, there is a lack of data confirming such combined effectiveness.…

Surviving as an underrepresented minority scientist in a majority environment

PubMed Central

Jarvis, Erich D.

2015-01-01

I believe the evidence will show that the science we conduct and discoveries we make are influenced by our cultural experience, whether they be positive, negative, or neutral. I grew up as a person of color in the United States of America, faced with challenges that many had as members of an underrepresented minority group. I write here about some of the lessons I have learned that have allowed me to survive as an underrepresented minority ­scientist in a majority environment. PMID:26515973

Towards Detection of Learner Misconceptions in a Medical Learning Environment: A Subgroup Discovery Approach

ERIC Educational Resources Information Center

Poitras, Eric G.; Doleck, Tenzin; Lajoie, Susanne P.

2018-01-01

Ill-structured problems, by definition, have multiple paths to a solution and are multifaceted making automated assessment and feedback a difficult challenge. Diagnostic reasoning about medical cases meet the criteria of ill-structured problem solving since there are multiple solution paths. The goal of this study was to develop an adaptive…

An Investigation of the Effects of Relevant Samples and a Comparison of Verification versus Discovery Based Lab Design

ERIC Educational Resources Information Center

Rieben, James C., Jr.

2010-01-01

This study focuses on the effects of relevance and lab design on student learning within the chemistry laboratory environment. A general chemistry conductivity of solutions experiment and an upper level organic chemistry cellulose regeneration experiment were employed. In the conductivity experiment, the two main variables studied were the effect…

Mathematics in the lower primary years: A research-based perspective on curricula and teaching practice

NASA Astrophysics Data System (ADS)

Wright, Bob

1994-07-01

Drawing on current research the author explicates twelve assertions relating to curricula, teaching, learners and learning environments in lower primary school mathematics. Topics discussed include: unchanging and under-challenging curricula; the need for greater emphasis on developing children's verbal number strategies and number sense, and on activities specifically suited to prenumerical children; curriculum constraints on teachers; the role of problem solving and differing interpretations of problem solving; the need for a better understanding of how children learn mathematics; differences in children's knowledge; "anti-interventionism," discovery learning, constructivism, children's autonomy and developmental learning; the need for compensatory programs; and learning in collaborative settings. The author concludes that learning and teaching lower primary mathematics continues to be an important area of focus and challenge for teachers and researchers.

From machine learning to deep learning: progress in machine intelligence for rational drug discovery.

PubMed

Zhang, Lu; Tan, Jianjun; Han, Dan; Zhu, Hao

2017-11-01

Machine intelligence, which is normally presented as artificial intelligence, refers to the intelligence exhibited by computers. In the history of rational drug discovery, various machine intelligence approaches have been applied to guide traditional experiments, which are expensive and time-consuming. Over the past several decades, machine-learning tools, such as quantitative structure-activity relationship (QSAR) modeling, were developed that can identify potential biological active molecules from millions of candidate compounds quickly and cheaply. However, when drug discovery moved into the era of 'big' data, machine learning approaches evolved into deep learning approaches, which are a more powerful and efficient way to deal with the massive amounts of data generated from modern drug discovery approaches. Here, we summarize the history of machine learning and provide insight into recently developed deep learning approaches and their applications in rational drug discovery. We suggest that this evolution of machine intelligence now provides a guide for early-stage drug design and discovery in the current big data era. Copyright © 2017 Elsevier Ltd. All rights reserved.

Simulated drug discovery process to conduct a synoptic assessment of pharmacy students.

PubMed

Richardson, Alan; Curtis, Anthony D M; Moss, Gary P; Pearson, Russell J; White, Simon; Rutten, Frank J M; Perumal, Dhaya; Maddock, Katie

2014-03-12

OBJECTIVE. To implement and assess a task-based learning exercise that prompts pharmacy students to integrate their understanding of different disciplines. DESIGN. Master of pharmacy (MPharm degree) students were provided with simulated information from several preclinical science and from clinical trials and asked to synthesize this into a marketing authorization application for a new drug. Students made a link to pharmacy practice by creating an advice leaflet for pharmacists. ASSESSMENT. Students' ability to integrate information from different disciplines was evaluated by oral examination. In 2 successive academic years, 96% and 82% of students demonstrated an integrated understanding of their proposed new drug. Students indicated in a survey that their understanding of the links between different subjects improved. CONCLUSION. Simulated drug discovery provides a learning environment that emphasizes the connectivity of the preclinical sciences with each other and the practice of pharmacy.

Simulated Drug Discovery Process to Conduct a Synoptic Assessment of Pharmacy Students

PubMed Central

Curtis, Anthony D.M.; Moss, Gary P.; Pearson, Russell J.; White, Simon; Rutten, Frank J.M.; Perumal, Dhaya; Maddock, Katie

2014-01-01

Objective. To implement and assess a task-based learning exercise that prompts pharmacy students to integrate their understanding of different disciplines. Design. Master of pharmacy (MPharm degree) students were provided with simulated information from several preclinical science and from clinical trials and asked to synthesize this into a marketing authorization application for a new drug. Students made a link to pharmacy practice by creating an advice leaflet for pharmacists. Assessment. Students’ ability to integrate information from different disciplines was evaluated by oral examination. In 2 successive academic years, 96% and 82% of students demonstrated an integrated understanding of their proposed new drug. Students indicated in a survey that their understanding of the links between different subjects improved. Conclusion. Simulated drug discovery provides a learning environment that emphasizes the connectivity of the preclinical sciences with each other and the practice of pharmacy. PMID:24672074

The Impact of Students' Exploration Strategies on Discovery Learning Using Computer-Based Simulations

ERIC Educational Resources Information Center

Dalgarno, Barney; Kennedy, Gregor; Bennett, Sue

2014-01-01

Discovery-based learning designs incorporating active exploration are common within instructional software. However, researchers have highlighted empirical evidence showing that "pure" discovery learning is of limited value and strategies which reduce complexity and provide guidance to learners are important if potential learning…

Writing from Within: A Guide to Creativity and Life Story Writing. Third Edition.

ERIC Educational Resources Information Center

Selling, Bernard

Based on the idea that telling personal life stories can be a voyage of self discovery, freeing up images and memories that have long remained hidden, this book explains techniques to help individuals learn to write vivid autobiographical stories and life narratives. Whether used at home, in a classroom, or in a therapy environment, the techniques…

An Inquiry-Based Biochemistry Laboratory Structure Emphasizing Competency in the Scientific Process: A Guided Approach with an Electronic Notebook Format

ERIC Educational Resources Information Center

Hall, Mona L.; Vardar-Ulu, Didem

2014-01-01

The laboratory setting is an exciting and gratifying place to teach because you can actively engage the students in the learning process through hands-on activities; it is a dynamic environment amenable to collaborative work, critical thinking, problem-solving and discovery. The guided inquiry-based approach described here guides the students…

Cognitive Tutoring based on Intelligent Decision Support in the PENTHA Instructional Design Model

NASA Astrophysics Data System (ADS)

dall'Acqua, Luisa

2010-06-01

The research finality of this paper is how to support Authors to develop rule driven—subject oriented, adaptable course content, meta-rules—representing the disciplinary epistemology, model of teaching, Learning Path structure, and assessment parameters—for intelligent Tutoring actions in a personalized, adaptive e-Learning environment. The focus is to instruct the student to be a decision manager for himself, able to recognize the elements of a problem, select the necessary information with the perspective of factual choices. In particular, our research intends to provide some fundamental guidelines for the definition of didactical rules and logical relations, that Authors should provide to a cognitive Tutoring system through the use of an Instructional Design method (PENTHA Model) which proposes an educational environment, able to: increase productivity and operability, create conditions for a cooperative dialogue, developing participatory research activities of knowledge, observations and discoveries, customizing the learning design in a complex and holistic vision of the learning / teaching processes.

Self Assessment and Discovery Learning

ERIC Educational Resources Information Center

McDonald, Betty

2011-01-01

Discovery learning in higher education has been reported to be effective in assisting learners to understand difficult concepts and retain long term information. This paper seeks to illustrate how one self assessment model may be used to demonstrate discovery learning in a collaborative atmosphere of students sharing and getting to know each…

Effectiveness of discovery learning model on mathematical problem solving

NASA Astrophysics Data System (ADS)

Herdiana, Yunita; Wahyudin, Sispiyati, Ririn

2017-08-01

This research is aimed to describe the effectiveness of discovery learning model on mathematical problem solving. This research investigate the students' problem solving competency before and after learned by using discovery learning model. The population used in this research was student in grade VII in one of junior high school in West Bandung Regency. From nine classes, class VII B were randomly selected as the sample of experiment class, and class VII C as control class, which consist of 35 students every class. The method in this research was quasi experiment. The instrument in this research is pre-test, worksheet and post-test about problem solving of mathematics. Based on the research, it can be conclude that the qualification of problem solving competency of students who gets discovery learning model on level 80%, including in medium category and it show that discovery learning model effective to improve mathematical problem solving.

Learning classifier systems for single and multiple mobile robots in unstructured environments

NASA Astrophysics Data System (ADS)

Bay, John S.

1995-12-01

The learning classifier system (LCS) is a learning production system that generates behavioral rules via an underlying discovery mechanism. The LCS architecture operates similarly to a blackboard architecture; i.e., by posted-message communications. But in the LCS, the message board is wiped clean at every time interval, thereby requiring no persistent shared resource. In this paper, we adapt the LCS to the problem of mobile robot navigation in completely unstructured environments. We consider the model of the robot itself, including its sensor and actuator structures, to be part of this environment, in addition to the world-model that includes a goal and obstacles at unknown locations. This requires a robot to learn its own I/O characteristics in addition to solving its navigation problem, but results in a learning controller that is equally applicable, unaltered, in robots with a wide variety of kinematic structures and sensing capabilities. We show the effectiveness of this LCS-based controller through both simulation and experimental trials with a small robot. We then propose a new architecture, the Distributed Learning Classifier System (DLCS), which generalizes the message-passing behavior of the LCS from internal messages within a single agent to broadcast massages among multiple agents. This communications mode requires little bandwidth and is easily implemented with inexpensive, off-the-shelf hardware. The DLCS is shown to have potential application as a learning controller for multiple intelligent agents.

Comparison between project-based learning and discovery learning toward students' metacognitive strategies on global warming concept

NASA Astrophysics Data System (ADS)

Tumewu, Widya Anjelia; Wulan, Ana Ratna; Sanjaya, Yayan

2017-05-01

The purpose of this study was to know comparing the effectiveness of learning using Project-based learning (PjBL) and Discovery Learning (DL) toward students metacognitive strategies on global warming concept. A quasi-experimental research design with a The Matching-Only Pretest-Posttest Control Group Design was used in this study. The subjects were students of two classes 7th grade of one of junior high school in Bandung City, West Java of 2015/2016 academic year. The study was conducted on two experimental class, that were project-based learning treatment on the experimental class I and discovery learning treatment was done on the experimental class II. The data was collected through questionnaire to know students metacognitive strategies. The statistical analysis showed that there were statistically significant differences in students metacognitive strategies between project-based learning and discovery learning.

High-School Chemistry Students' Performance and Gender Differences in a Computerized Molecular Modeling Learning Environment

NASA Astrophysics Data System (ADS)

Barnea, Nitza; Dori, Yehudit J.

1999-12-01

Computerized molecular modeling (CMM) contributes to the development of visualization skills via vivid animation of three dimensional representations. Its power to illustrate and explore phenomena in chemistry teaching stems from the convenience and simplicity of building molecules of any size and color in a number of presentation styles. A new CMM-based learning environment for teaching and learning chemistry in Israeli high schools has been designed and implemented. Three tenth grade experimental classes used this discovery CMM approach, while two other classes, who studied the same topic in the customary approach, served as a control group. We investigated the effects of using molecular modeling on students' spatial ability, understanding of new concepts related to geometric and symbolic representations and students' perception of the model concept. Each variable was examined for gender differences. Students of the experimental group performed better than control group students in all three performance aspects. Experimental group students scored higher than the control group students in the achievement test on structure and bonding. Students' spatial ability improved in both groups, but students from the experimental group scored higher. For the average students in the two groups the improvement in all three spatial ability sub-tests —paper folding, card rotation, and cube comparison—was significantly higher for the experimental group. Experimental group students gained better insight into the model concept than the control group and could explain more phenomena with the aid of a variety of models. Hence, CMM helps in particular to improve the examined cognitive aspects of the average student population. In most of the achievement and spatial ability tests no significant differences between the genders were found, but in some aspects of model perception and verbal argumentation differences still exist. Experimental group females improved their model perception more than the control group females in understanding ways to create models and in the role of models as mental structures and prediction tools. Teachers' and students' feedback on the CMM learning environment was found to be positive, as it helped them understand concepts in molecular geometry and bonding. The results of this study suggest that teaching/learning of topics in chemistry that are related to three dimensional structures can be improved by using a discovery approach in a computerized learning environment.

The Relation between Prior Knowledge and Students' Collaborative Discovery Learning Processes

ERIC Educational Resources Information Center

Gijlers, Hannie; de Jong, Ton

2005-01-01

In this study we investigate how prior knowledge influences knowledge development during collaborative discovery learning. Fifteen dyads of students (pre-university education, 15-16 years old) worked on a discovery learning task in the physics field of kinematics. The (face-to-face) communication between students was recorded and the interaction…

Foreign language learning in immersive virtual environments

NASA Astrophysics Data System (ADS)

Chang, Benjamin; Sheldon, Lee; Si, Mei; Hand, Anton

2012-03-01

Virtual reality has long been used for training simulations in fields from medicine to welding to vehicular operation, but simulations involving more complex cognitive skills present new design challenges. Foreign language learning, for example, is increasingly vital in the global economy, but computer-assisted education is still in its early stages. Immersive virtual reality is a promising avenue for language learning as a way of dynamically creating believable scenes for conversational training and role-play simulation. Visual immersion alone, however, only provides a starting point. We suggest that the addition of social interactions and motivated engagement through narrative gameplay can lead to truly effective language learning in virtual environments. In this paper, we describe the development of a novel application for teaching Mandarin using CAVE-like VR, physical props, human actors and intelligent virtual agents, all within a semester-long multiplayer mystery game. Students travel (virtually) to China on a class field trip, which soon becomes complicated with intrigue and mystery surrounding the lost manuscript of an early Chinese literary classic. Virtual reality environments such as the Forbidden City and a Beijing teahouse provide the setting for learning language, cultural traditions, and social customs, as well as the discovery of clues through conversation in Mandarin with characters in the game.

Child Predictors of Learning to Control Variables via Instruction or Self-Discovery

ERIC Educational Resources Information Center

Wagensveld, Barbara; Segers, Eliane; Kleemans, Tijs; Verhoeven, Ludo

2015-01-01

We examined the role child factors on the acquisition and transfer of learning the control of variables strategy (CVS) via instruction or self-discovery. Seventy-six fourth graders and 43 sixth graders were randomly assigned to a group receiving direct CVS instruction or a discovery learning group. Prior to the intervention, cognitive, scientific,…

Using Just-in-Time Information to Support Scientific Discovery Learning in a Computer-Based Simulation

ERIC Educational Resources Information Center

Hulshof, Casper D.; de Jong, Ton

2006-01-01

Students encounter many obstacles during scientific discovery learning with computer-based simulations. It is hypothesized that an effective type of support, that does not interfere with the scientific discovery learning process, should be delivered on a "just-in-time" base. This study explores the effect of facilitating access to…

Teaching Slope of a Line Using the Graphing Calculator as a Tool for Discovery Learning

ERIC Educational Resources Information Center

Nichols, Fiona Costello

2012-01-01

Discovery learning is one of the instructional strategies sometimes used to teach Algebra I. However, little research is available that includes investigation of the effects of incorporating the graphing calculator technology with discovery learning. This study was initiated to investigate two instructional approaches for teaching slope of a line…

Space Station Freedom Gateway to the Future

NASA Technical Reports Server (NTRS)

1992-01-01

The first inhabited outpost on the frontier of space will be a place to live, work, and discover. Experiments conducted on Freedom will advance scientific knowledge about our world, our environment, and ourselves. We will learn how to adapt to the space environment and to build and operate new spacecraft with destinations far beyond Earth, continuing the tradition of exploration that began with a journey to the Moon. What we learn from living and working on Freedom will strengthen our expertise in science and engineering, promote national research and development initiatives and inspire another generation of Americans to push forward and onward. On the eve of the 21st century, Space Station Freedom will be our gateway to the future. This material covers gateways to space, research, discovery, utilization, benefits, and NASA.

The equivalence of learning paths in early science instruction: effect of direct instruction and discovery learning.

PubMed

Klahr, David; Nigam, Milena

2004-10-01

In a study with 112 third- and fourth-grade children, we measured the relative effectiveness of discovery learning and direct instruction at two points in the learning process: (a) during the initial acquisition of the basic cognitive objective (a procedure for designing and interpreting simple, unconfounded experiments) and (b) during the subsequent transfer and application of this basic skill to more diffuse and authentic reasoning associated with the evaluation of science-fair posters. We found not only that many more children learned from direct instruction than from discovery learning, but also that when asked to make broader, richer scientific judgments, the many children who learned about experimental design from direct instruction performed as well as those few children who discovered the method on their own. These results challenge predictions derived from the presumed superiority of discovery approaches in teaching young children basic procedures for early scientific investigations.

The Development of Discovery-Inquiry Learning Model to Reduce the Science Misconceptions of Junior High School Students

ERIC Educational Resources Information Center

Tompo, Basman; Ahmad, Arifin; Muris, Muris

2016-01-01

The main objective of this research was to develop discovery inquiry (DI) learning model to reduce the misconceptions of Science student level of secondary school that is valid, practical, and effective. This research was an R&D (research and development). The trials of discovery inquiry (DI) learning model were carried out in two different…

Development of Scientific Approach Based on Discovery Learning Module

NASA Astrophysics Data System (ADS)

Ellizar, E.; Hardeli, H.; Beltris, S.; Suharni, R.

2018-04-01

Scientific Approach is a learning process, designed to make the students actively construct their own knowledge through stages of scientific method. The scientific approach in learning process can be done by using learning modules. One of the learning model is discovery based learning. Discovery learning is a learning model for the valuable things in learning through various activities, such as observation, experience, and reasoning. In fact, the students’ activity to construct their own knowledge were not optimal. It’s because the available learning modules were not in line with the scientific approach. The purpose of this study was to develop a scientific approach discovery based learning module on Acid Based, also on electrolyte and non-electrolyte solution. The developing process of this chemistry modules use the Plomp Model with three main stages. The stages are preliminary research, prototyping stage, and the assessment stage. The subject of this research was the 10th and 11th Grade of Senior High School students (SMAN 2 Padang). Validation were tested by the experts of Chemistry lecturers and teachers. Practicality of these modules had been tested through questionnaire. The effectiveness had been tested through experimental procedure by comparing student achievement between experiment and control groups. Based on the findings, it can be concluded that the developed scientific approach discovery based learning module significantly improve the students’ learning in Acid-based and Electrolyte solution. The result of the data analysis indicated that the chemistry module was valid in content, construct, and presentation. Chemistry module also has a good practicality level and also accordance with the available time. This chemistry module was also effective, because it can help the students to understand the content of the learning material. That’s proved by the result of learning student. Based on the result can conclude that chemistry module based on discovery learning and scientific approach in electrolyte and non-electrolyte solution and Acid Based for the 10th and 11th grade of senior high school students were valid, practice, and effective.

Incremental learning of skill collections based on intrinsic motivation

PubMed Central

Metzen, Jan H.; Kirchner, Frank

2013-01-01

Life-long learning of reusable, versatile skills is a key prerequisite for embodied agents that act in a complex, dynamic environment and are faced with different tasks over their lifetime. We address the question of how an agent can learn useful skills efficiently during a developmental period, i.e., when no task is imposed on him and no external reward signal is provided. Learning of skills in a developmental period needs to be incremental and self-motivated. We propose a new incremental, task-independent skill discovery approach that is suited for continuous domains. Furthermore, the agent learns specific skills based on intrinsic motivation mechanisms that determine on which skills learning is focused at a given point in time. We evaluate the approach in a reinforcement learning setup in two continuous domains with complex dynamics. We show that an intrinsically motivated, skill learning agent outperforms an agent which learns task solutions from scratch. Furthermore, we compare different intrinsic motivation mechanisms and how efficiently they make use of the agent's developmental period. PMID:23898265

Quantifying Learning in Young Infants: Tracking Leg Actions During a Discovery-learning Task.

PubMed

Sargent, Barbara; Reimann, Hendrik; Kubo, Masayoshi; Fetters, Linda

2015-06-01

Task-specific actions emerge from spontaneous movement during infancy. It has been proposed that task-specific actions emerge through a discovery-learning process. Here a method is described in which 3-4 month old infants learn a task by discovery and their leg movements are captured to quantify the learning process. This discovery-learning task uses an infant activated mobile that rotates and plays music based on specified leg action of infants. Supine infants activate the mobile by moving their feet vertically across a virtual threshold. This paradigm is unique in that as infants independently discover that their leg actions activate the mobile, the infants' leg movements are tracked using a motion capture system allowing for the quantification of the learning process. Specifically, learning is quantified in terms of the duration of mobile activation, the position variance of the end effectors (feet) that activate the mobile, changes in hip-knee coordination patterns, and changes in hip and knee muscle torque. This information describes infant exploration and exploitation at the interplay of person and environmental constraints that support task-specific action. Subsequent research using this method can investigate how specific impairments of different populations of infants at risk for movement disorders influence the discovery-learning process for task-specific action.

A Cybernetic Design Methodology for 'Intelligent' Online Learning Support

NASA Astrophysics Data System (ADS)

Quinton, Stephen R.

The World Wide Web (WWW) provides learners and knowledge workers convenient access to vast stores of information, so much that present methods for refinement of a query or search result are inadequate - there is far too much potentially useful material. The problem often encountered is that users usually do not recognise what may be useful until they have progressed some way through the discovery, learning, and knowledge acquisition process. Additional support is needed to structure and identify potentially relevant information, and to provide constructive feedback. In short, support for learning is needed. The learning envisioned here is not simply the capacity to recall facts or to recognise objects. The focus is on learning that results in the construction of knowledge. Although most online learning platforms are efficient at delivering information, most do not provide tools that support learning as envisaged in this chapter. It is conceivable that Web-based learning environments can incorporate software systems that assist learners to form new associations between concepts and synthesise information to create new knowledge. This chapter details the rationale and theory behind a research study that aims to evolve Web-based learning environments into 'intelligent thinking' systems that respond to natural language human input. Rather than functioning simply as a means of delivering information, it is argued that online learning solutions will 1 day interact directly with students to support their conceptual thinking and cognitive development.

Automated discovery systems and the inductivist controversy

NASA Astrophysics Data System (ADS)

Giza, Piotr

2017-09-01

The paper explores possible influences that some developments in the field of branches of AI, called automated discovery and machine learning systems, might have upon some aspects of the old debate between Francis Bacon's inductivism and Karl Popper's falsificationism. Donald Gillies facetiously calls this controversy 'the duel of two English knights', and claims, after some analysis of historical cases of discovery, that Baconian induction had been used in science very rarely, or not at all, although he argues that the situation has changed with the advent of machine learning systems. (Some clarification of terms machine learning and automated discovery is required here. The key idea of machine learning is that, given data with associated outcomes, software can be trained to make those associations in future cases which typically amounts to inducing some rules from individual cases classified by the experts. Automated discovery (also called machine discovery) deals with uncovering new knowledge that is valuable for human beings, and its key idea is that discovery is like other intellectual tasks and that the general idea of heuristic search in problem spaces applies also to discovery tasks. However, since machine learning systems discover (very low-level) regularities in data, throughout this paper I use the generic term automated discovery for both kinds of systems. I will elaborate on this later on). Gillies's line of argument can be generalised: thanks to automated discovery systems, philosophers of science have at their disposal a new tool for empirically testing their philosophical hypotheses. Accordingly, in the paper, I will address the question, which of the two philosophical conceptions of scientific method is better vindicated in view of the successes and failures of systems developed within three major research programmes in the field: machine learning systems in the Turing tradition, normative theory of scientific discovery formulated by Herbert Simon's group and the programme called HHNT, proposed by J. Holland, K. Holyoak, R. Nisbett and P. Thagard.

Learning to Love Your Discovery Tool: Strategies for Integrating a Discovery Tool in Face-to-Face, Synchronous, and Asynchronous Instruction

ERIC Educational Resources Information Center

Fawley, Nancy; Krysak, Nikki

2014-01-01

Some librarians embrace discovery tools while others refuse to use them. This lack of consensus can have consequences for student learning when there is inconsistent use, especially in large-scale instruction programs. The authors surveyed academic librarians whose institutions have a discovery tool and who teach information literacy classes in…

From Residency to Lifelong Learning.

PubMed

Brandt, Keith

2015-11-01

The residency training experience is the perfect environment for learning. The university/institution patient population provides a never-ending supply of patients with unique management challenges. Resources abound that allow the discovery of knowledge about similar situations. Senior teachers provide counseling and help direct appropriate care. Periodic testing and evaluations identify deficiencies, which can be corrected with future study. What happens, however, when the resident graduates? Do they possess all the knowledge they'll need for the rest of their career? Will medical discovery stand still limiting the need for future study? If initial certification establishes that the physician has the skills and knowledge to function as an independent physician and surgeon, how do we assure the public that plastic surgeons will practice lifelong learning and remain safe throughout their career? Enter Maintenance of Certification (MOC). In an ideal world, MOC would provide many of the same tools as residency training: identification of gaps in knowledge, resources to correct those deficiencies, overall assessment of knowledge, feedback about communication skills and professionalism, and methods to evaluate and improve one's practice. This article discusses the need; for education and self-assessment that extends beyond residency training and a commitment to lifelong learning. The American Board of Plastic Surgery MOC program is described to demonstrate how it helps the diplomate reach the goal of continuous practice improvement.

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.

Discovery Garden -- Physics and Architecture Meet Outside to Talk

NASA Astrophysics Data System (ADS)

Tabor-Morris, Anne; Briles, Timothy; Froriep, Kathleen; McGuire, Catherine

2012-02-01

The purpose of Georgian Court University's "Discovery Garden" is to create an experience of the physical sciences for students, both science and non-science majors, in a place of serenity: an outdoor garden. Why a garden? Consider that the traditional laboratory experience for students is one of stark rooms ventilated with noisy hoods and endemic with lab coats and safety glasses, an alien environment that can be a source of anxiety for some students studying science, while the idea of a garden excites the imagination and conjures peace. The garden also serves as a reminder that ideas learned in the classroom apply to the everyday world. In addition, the garden is a model of informal learning, which can be especially interesting for pre-service teachers. Outlined here are some general suggestions for the design of a science garden, applicability of educational philosophy to full-body experiences, and activities suggested for students and future teachers in such a garden, as well as a mini-tour of our garden.

Going Virtual… or Not: Development and Testing of a 3D Virtual Astronomy Environment

NASA Astrophysics Data System (ADS)

Ruzhitskaya, L.; Speck, A.; Ding, N.; Baldridge, S.; Witzig, S.; Laffey, J.

2013-04-01

We present our preliminary results of a pilot study of students' knowledge transfer of an astronomy concept into a new environment. We also share our discoveries on what aspects of a 3D environment students consider being motivational and discouraging for their learning. This study was conducted among 64 non-science major students enrolled in an astronomy laboratory course. During the course, students learned the concept and applications of Kepler's laws using a 2D interactive environment. Later in the semester, the students were placed in a 3D environment in which they were asked to conduct observations and to answers a set of questions pertaining to the Kepler's laws of planetary motion. In this study, we were interested in observing scrutinizing and assessing students' behavior: from choices that they made while creating their avatars (virtual representations) to tools they choose to use, to their navigational patterns, to their levels of discourse in the environment. These helped us to identify what features of the 3D environment our participants found to be helpful and interesting and what tools created unnecessary clutter and distraction. The students' social behavior patterns in the virtual environment together with their answers to the questions helped us to determine how well they understood Kepler's laws, how well they could transfer the concepts to a new situation, and at what point a motivational tool such as a 3D environment becomes a disruption to the constructive learning. Our founding confirmed that students construct deeper knowledge of a concept when they are fully immersed in the environment.

Improving Mathematics Achievement of Indonesian 5th Grade Students through Guided Discovery Learning

ERIC Educational Resources Information Center

Yurniwati; Hanum, Latipa

2017-01-01

This research aims to find information about the improvement of mathematics achievement of grade five student through guided discovery learning. This research method is classroom action research using Kemmis and Taggart model consists of three cycles. Data used in this study is learning process and learning results. Learning process data is…

Reception Learning and Self-Discovery Learning in Histology: Students' Perceptions and Their Implications for Assessing the Effectiveness of Different Learning Modalities

ERIC Educational Resources Information Center

Campos-Sanchez, Antonio; Martin-Piedra, Miguel-Angel; Carriel, Victor; Gonzalez-Andrades, Miguel; Garzon, Ingrid; Sanchez-Quevedo, Maria-Carmen; Alaminos, Miguel

2012-01-01

Two questionnaires were used to investigate students' perceptions of their motivation to opt for reception learning (RL) or self-discovery learning (SDL) in histology and their choices of complementary learning strategies (CLS). The results demonstrated that the motivation to attend RL sessions was higher than the motivation to attend SDL to gain…

Gaze training enhances laparoscopic technical skill acquisition and multi-tasking performance: a randomized, controlled study.

PubMed

Wilson, Mark R; Vine, Samuel J; Bright, Elizabeth; Masters, Rich S W; Defriend, David; McGrath, John S

2011-12-01

The operating room environment is replete with stressors and distractions that increase the attention demands of what are already complex psychomotor procedures. Contemporary research in other fields (e.g., sport) has revealed that gaze training interventions may support the development of robust movement skills. This current study was designed to examine the utility of gaze training for technical laparoscopic skills and to test performance under multitasking conditions. Thirty medical trainees with no laparoscopic experience were divided randomly into one of three treatment groups: gaze trained (GAZE), movement trained (MOVE), and discovery learning/control (DISCOVERY). Participants were fitted with a Mobile Eye gaze registration system, which measures eye-line of gaze at 25 Hz. Training consisted of ten repetitions of the "eye-hand coordination" task from the LAP Mentor VR laparoscopic surgical simulator while receiving instruction and video feedback (specific to each treatment condition). After training, all participants completed a control test (designed to assess learning) and a multitasking transfer test, in which they completed the procedure while performing a concurrent tone counting task. Not only did the GAZE group learn more quickly than the MOVE and DISCOVERY groups (faster completion times in the control test), but the performance difference was even more pronounced when multitasking. Differences in gaze control (target locking fixations), rather than tool movement measures (tool path length), underpinned this performance advantage for GAZE training. These results suggest that although the GAZE intervention focused on training gaze behavior only, there were indirect benefits for movement behaviors and performance efficiency. Additionally, focusing on a single external target when learning, rather than on complex movement patterns, may have freed-up attentional resources that could be applied to concurrent cognitive tasks.

Building Faculty Capacity through the Learning Sciences

ERIC Educational Resources Information Center

Moy, Elizabeth; O'Sullivan, Gerard; Terlecki, Melissa; Jernstedt, Christian

2014-01-01

Discoveries in the learning sciences (especially in neuroscience) have yielded a rich and growing body of knowledge about how students learn, yet this knowledge is only half of the story. The other half is "know how," i.e. the application of this knowledge. For faculty members, that means applying the discoveries of the learning sciences…

Triple Scheme of Learning Support Design for Scientific Discovery Learning Based on Computer Simulation: Experimental Research

ERIC Educational Resources Information Center

Zhang, Jianwei; Chen, Qi; Sun, Yanquing; Reid, David J.

2004-01-01

Learning support studies involving simulation-based scientific discovery learning have tended to adopt an ad hoc strategies-oriented approach in which the support strategies are typically pre-specified according to learners' difficulties in particular activities. This article proposes a more integrated approach, a triple scheme for learning…

Enhancing health leadership performance using neurotherapy.

PubMed

Swingle, Paul G; Hartney, Elizabeth

2018-05-01

The discovery of neuroplasticity means the brain can change, functionally, in response to the environment and to learning. While individuals can develop harmful patterns of brain activity in response to stressors, they can also learn to modify or control neurological conditions associated with specific behaviors. Neurotherapy is one way of changing brain functioning to modify troubling conditions which can impair leadership performance, through responding to feedback on their own brain activity, and enhancing optimal leadership functioning through learning to maximize such cognitive strengths as mental efficiency, focus, creativity, perseverance, and executive functioning. The present article outlines the application of the concept of optimal performance training to organizational leadership in a healthcare context, by describing approaches to neurotherapy and illustrating their application through a case study of a health leader learning to overcome the neurological and emotional sequelae of workplace stress and trauma.

System Architecture Development for Energy and Water Infrastructure Data Management and Geovisual Analytics

NASA Astrophysics Data System (ADS)

Berres, A.; Karthik, R.; Nugent, P.; Sorokine, A.; Myers, A.; Pang, H.

2017-12-01

Building an integrated data infrastructure that can meet the needs of a sustainable energy-water resource management requires a robust data management and geovisual analytics platform, capable of cross-domain scientific discovery and knowledge generation. Such a platform can facilitate the investigation of diverse complex research and policy questions for emerging priorities in Energy-Water Nexus (EWN) science areas. Using advanced data analytics, machine learning techniques, multi-dimensional statistical tools, and interactive geovisualization components, such a multi-layered federated platform is being developed, the Energy-Water Nexus Knowledge Discovery Framework (EWN-KDF). This platform utilizes several enterprise-grade software design concepts and standards such as extensible service-oriented architecture, open standard protocols, event-driven programming model, enterprise service bus, and adaptive user interfaces to provide a strategic value to the integrative computational and data infrastructure. EWN-KDF is built on the Compute and Data Environment for Science (CADES) environment in Oak Ridge National Laboratory (ORNL).

NASA Advanced Computing Environment for Science and Engineering

NASA Technical Reports Server (NTRS)

Biswas, Rupak

2017-01-01

Vision: To reach for new heights and reveal the unknown so that what we do and learn will benefit all humankind. Mission: To pioneer the future in space exploration, scientific discovery, and aeronautics research. Aeronautics Research (ARMD): Pioneer and prove new flight technologies for safer, more secure, efficient, and environmental friendly air transportation. Human Exploration and Operations (HEOMD): Focus on ISS operations; and develop new spacecraft and other capabilities for affordable, sustainable exploration beyond low Earth orbit. Science (SCMD): Explore the Earth, solar system, and universe beyond; chart best route for discovery; and reap the benefits of Earth and space exploration for society. Space Technology (STMD): Rapidly develop, demonstrate, and infuse revolutionary, high-payoff technologies through collaborative partnerships, expanding the boundaries of aerospace enterprise.

The influence of discovery learning model application to the higher order thinking skills student of Srijaya Negara Senior High School Palembang on the animal kingdom subject matter

NASA Astrophysics Data System (ADS)

Riandari, F.; Susanti, R.; Suratmi

2018-05-01

This study aimed to find out the information in concerning the influence of discovery learning model application to the higher order thinking skills at the tenth grade students of Srijaya Negara senior high school Palembang on the animal kingdom subject matter. The research method used was pre-experimental with one-group pretest-posttest design. The researchconducted at Srijaya Negara senior high school Palembang academic year 2016/2017. The population sample of this research was tenth grade students of natural science 2. Purposive sampling techniquewas applied in this research. Data was collected by(1) the written test, consist of pretest to determine the initial ability and posttest to determine higher order thinking skills of students after learning by using discovery learning models. (2) Questionnaire sheet, aimed to investigate the response of the students during the learning process by using discovery learning models. The t-test result indicated there was significant increasement of higher order thinking skills students. Thus, it can be concluded that the application of discovery learning modelhad a significant effect and increased to higher order thinking skills students of Srijaya Negara senior high school Palembang on the animal kingdom subject matter.

Low Data Drug Discovery with One-Shot Learning.

PubMed

Altae-Tran, Han; Ramsundar, Bharath; Pappu, Aneesh S; Pande, Vijay

2017-04-26

Recent advances in machine learning have made significant contributions to drug discovery. Deep neural networks in particular have been demonstrated to provide significant boosts in predictive power when inferring the properties and activities of small-molecule compounds (Ma, J. et al. J. Chem. Inf. 2015, 55, 263-274). However, the applicability of these techniques has been limited by the requirement for large amounts of training data. In this work, we demonstrate how one-shot learning can be used to significantly lower the amounts of data required to make meaningful predictions in drug discovery applications. We introduce a new architecture, the iterative refinement long short-term memory, that, when combined with graph convolutional neural networks, significantly improves learning of meaningful distance metrics over small-molecules. We open source all models introduced in this work as part of DeepChem, an open-source framework for deep-learning in drug discovery (Ramsundar, B. deepchem.io. https://github.com/deepchem/deepchem, 2016).

From Information Center to Discovery System: Next Step for Libraries?

ERIC Educational Resources Information Center

Marcum, James W.

2001-01-01

Proposes a discovery system model to guide technology integration in academic libraries that fuses organizational learning, systems learning, and knowledge creation techniques with constructivist learning practices to suggest possible future directions for digital libraries. Topics include accessing visual and continuous media; information…

Cheminformatics in Drug Discovery, an Industrial Perspective.

PubMed

Chen, Hongming; Kogej, Thierry; Engkvist, Ola

2018-05-18

Cheminformatics has established itself as a core discipline within large scale drug discovery operations. It would be impossible to handle the amount of data generated today in a small molecule drug discovery project without persons skilled in cheminformatics. In addition, due to increased emphasis on "Big Data", machine learning and artificial intelligence, not only in the society in general, but also in drug discovery, it is expected that the cheminformatics field will be even more important in the future. Traditional areas like virtual screening, library design and high-throughput screening analysis are highlighted in this review. Applying machine learning in drug discovery is an area that has become very important. Applications of machine learning in early drug discovery has been extended from predicting ADME properties and target activity to tasks like de novo molecular design and prediction of chemical reactions. © 2018 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.

Analysis student self efficacy in terms of using Discovery Learning model with SAVI approach

NASA Astrophysics Data System (ADS)

Sahara, Rifki; Mardiyana, S., Dewi Retno Sari

2017-12-01

Often students are unable to prove their academic achievement optimally according to their abilities. One reason is that they often feel unsure that they are capable of completing the tasks assigned to them. For students, such beliefs are necessary. The term belief has called self efficacy. Self efficacy is not something that has brought about by birth or something with permanent quality of an individual, but is the result of cognitive processes, the meaning one's self efficacy will be stimulated through learning activities. Self efficacy has developed and enhanced by a learning model that can stimulate students to foster confidence in their capabilities. One of them is by using Discovery Learning model with SAVI approach. Discovery Learning model with SAVI approach is one of learning models that involves the active participation of students in exploring and discovering their own knowledge and using it in problem solving by utilizing all the sensory devices they have. This naturalistic qualitative research aims to analyze student self efficacy in terms of use the Discovery Learning model with SAVI approach. The subjects of this study are 30 students focused on eight students who have high, medium, and low self efficacy obtained through purposive sampling technique. The data analysis of this research used three stages, that were reducing, displaying, and getting conclusion of the data. Based on the results of data analysis, it was concluded that the self efficacy appeared dominantly on the learning by using Discovery Learning model with SAVI approach is magnitude dimension.

The roots of physics students' motivations: Fear and integrity

NASA Astrophysics Data System (ADS)

Van Dusen, Ben

Too often, physics students are beset by feelings of failure and isolation rather than experiencing the creative joys of discovery that physics has to offer. This dissertation research was founded on the desire of a teacher to make physics class exciting and motivating to his students. This work explores how various aspects of learning environments interact with student motivation. This work uses qualitative and quantitative methods to explore how students are motivated to engage in physics and how they feel about themselves while engaging in physics. The collection of four studies in this dissertation culminates in a sociocultural perspective on motivation and identity. This perspective uses two extremes of how students experience physics as a lens for understanding motivation: fear and self-preservation versus integrity and self-expression. Rather than viewing motivation as a property of the student, or viewing students as inherently interested or disinterested in physics, the theoretical perspective on motivation and identity helps examine features of the learning environments that determine how students' experience themselves through physics class. This perspective highlights the importance of feeling a sense of belonging in the context of physics and the power that teachers have in shaping students' motivation through the construction of their classroom learning environments. Findings demonstrate how different ways that students experience themselves in physics class impact their performance and interest in physics. This dissertation concludes with a set of design principles that can foster integration and integrity among students in physics learning environments.

Support for Learning with Computer Simulations: Giving Hints, Supporting Learning Processes, and Providing Hypotheses.

ERIC Educational Resources Information Center

Njoo, Melanie; de Jong, Ton

This paper contains the results of a study on the importance of discovery learning using computer simulations. The purpose of the study was to identify what constitutes discovery learning and to assess the effects of instructional support measures. College students were observed working with an assignment and a computer simulation in the domain of…

Using Rocks: A Discovery Approach to Multi-faceted Learning.

ERIC Educational Resources Information Center

Thomas, John I.

Pupils' natural questioning attitudes lead them to discovery in a learning center, in contrast to the lecture method, by which information is forced on students regardless of their interests. This paper describes learning experiences built around rocks. Materials placed in a rock center (rocks, stones, pebbles, magnifying glasses hammers, and…

An investigation of the effects of relevant samples and a comparison of verification versus discovery based lab design

NASA Astrophysics Data System (ADS)

Rieben, James C., Jr.

This study focuses on the effects of relevance and lab design on student learning within the chemistry laboratory environment. A general chemistry conductivity of solutions experiment and an upper level organic chemistry cellulose regeneration experiment were employed. In the conductivity experiment, the two main variables studied were the effect of relevant (or "real world") samples on student learning and a verification-based lab design versus a discovery-based lab design. With the cellulose regeneration experiment, the effect of a discovery-based lab design vs. a verification-based lab design was the sole focus. Evaluation surveys consisting of six questions were used at three different times to assess student knowledge of experimental concepts. In the general chemistry laboratory portion of this study, four experimental variants were employed to investigate the effect of relevance and lab design on student learning. These variants consisted of a traditional (or verification) lab design, a traditional lab design using "real world" samples, a new lab design employing real world samples/situations using unknown samples, and the new lab design using real world samples/situations that were known to the student. Data used in this analysis were collected during the Fall 08, Winter 09, and Fall 09 terms. For the second part of this study a cellulose regeneration experiment was employed to investigate the effects of lab design. A demonstration creating regenerated cellulose "rayon" was modified and converted to an efficient and low-waste experiment. In the first variant students tested their products and verified a list of physical properties. In the second variant, students filled in a blank physical property chart with their own experimental results for the physical properties. Results from the conductivity experiment show significant student learning of the effects of concentration on conductivity and how to use conductivity to differentiate solution types with the use of real world samples. In the organic chemistry experiment, results suggest that the discovery-based design improved student retention of the chain length differentiation by physical properties relative to the verification-based design.

Using Innovative Tools to Teach Computer Application to Business Students--A Hawthorne Effect or Successful Implementation Here to Stay

ERIC Educational Resources Information Center

Khan, Zeenath Reza

2014-01-01

A year after the primary study that tested the impact of introducing blended learning and guided discovery to help teach computer application to business students, this paper looks into the continued success of using guided discovery and blended learning with learning management system in and out of classrooms to enhance student learning.…

Evaluation of National Institute for Learning Development and Discovery Educational Therapy Program

ERIC Educational Resources Information Center

Frimpong, Prince Christopher

2014-01-01

In Maryland, some Christian schools have enrolled students with learning disabilities (LDs) but do not have any interventional programs at the school to help them succeed academically. The purpose of this qualitative program evaluation was to evaluate the National Institute for Learning Development (NILD) and Discovery Therapy Educational Program…

A Guided Discovery Approach for Learning Metabolic Pathways

ERIC Educational Resources Information Center

Schultz, Emeric

2005-01-01

Learning the wealth of information in metabolic pathways is both challenging and overwhelming for students. A step-by-step guided discovery approach to the learning of the chemical steps in gluconeogenesis and the citric acid cycle is described. This approach starts from concepts the student already knows, develops these further in a logical…

Low Data Drug Discovery with One-Shot Learning

PubMed Central

2017-01-01

Recent advances in machine learning have made significant contributions to drug discovery. Deep neural networks in particular have been demonstrated to provide significant boosts in predictive power when inferring the properties and activities of small-molecule compounds (Ma, J. et al. J. Chem. Inf. Model.2015, 55, 263–27425635324). However, the applicability of these techniques has been limited by the requirement for large amounts of training data. In this work, we demonstrate how one-shot learning can be used to significantly lower the amounts of data required to make meaningful predictions in drug discovery applications. We introduce a new architecture, the iterative refinement long short-term memory, that, when combined with graph convolutional neural networks, significantly improves learning of meaningful distance metrics over small-molecules. We open source all models introduced in this work as part of DeepChem, an open-source framework for deep-learning in drug discovery (Ramsundar, B. deepchem.io. https://github.com/deepchem/deepchem, 2016). PMID:28470045

Non-traditional approaches to teaching GPS online

NASA Astrophysics Data System (ADS)

Matias, A.; Wolf, D. F., II

2009-12-01

Students are increasingly turning to the web for quality education that fits into their lives. Nonetheless, online learning brings challenges as well as a fresh opportunity for exploring pedagogical practices not present on traditional higher education programs, particularly in the sciences. A team of two dozen Empire State College-State University of New York instructional designers, faculty, and other staff are working on making science relevant to non-majors who may initially have anxiety about general education science courses. One of these courses, GPS and the New Geography, focuses on how Global Positioning System (GPS) technology provides a base for inquiry and scientific discovery from a range of environmental issues with local, regional, and global scope. GPS and the New Geography is an introductory level course developed under a grant supported by the Charitable Leadership Foundation. Taking advantage of the proliferation of tools currently available for online learning management systems, we explore current trends in Web 2.0 applications to aggregate and leverage data to create a nontraditional, interactive learning environment. Using our best practices to promote on-line discussion and interaction, these tools help engage students and foster deep learning. During the 15-week term students learn through case studies, problem-based exercises, and the use of scientific data; thus, expanding their spatial literacy and gain experience using real spatial technology tools to enhance their understanding of real-world issues. In particular, we present how the use of Mapblogs an in-house developed blogging platform that uses GIS interplaying with GPS units, interactive data presentations, intuitive visual working environments, harnessing RSS feeds, and other nontraditional Web 2.0 technology has successfully promoted active learning in the virtual learning environment.

Synthetic Beta-Lactam Antibiotics as a Selective Breast Cancer Cell Apoptosis Inducer: Significance in Breast Cancer Prevention and Treatment

DTIC Science & Technology

2008-03-01

Learned from Diet-Gene-Environment Interaction. Environmental Toxicology Graduate Program and Department of Chemistry , University of California at...College of Chemistry , Central China Normal University, Wuhan, China, June 29, 2007 Dou QP. Invited Speaker. Molecular Prevention of Human Cancer: Role of...Discovery Today 2002; 7: 471-8. 3. Morin RB and Gorman M. Chemistry and Biology of beta-Lactam Antibiotics, Vol. 1-3. New York: Academic Press, 1982. 4

Evaluation of Malware Target Recognition Deployed in a Cloud-Based Fileserver Environment

DTIC Science & Technology

2012-03-01

many of these detection techniques could be evaded with simple obfuscation. Kolter and Maloof extend Schultz’s research in [KM04] and [KM06]. Their...69 [KM04] Jeremy Z. Kolter and Marcus A. Maloof. Learning to detect malicious executables in the wild. In Proceedings of the tenth ACM SIGKDD...international conference on Knowledge discovery and data mining, KDD ’04, pages 470–478, New York, NY, USA, 2004. ACM. [KM06] J.Z. Kolter and M.A. Maloof

Corpus of High School Academic Texts (COHAT): Data-Driven, Computer Assisted Discovery in Learning Academic English

ERIC Educational Resources Information Center

Bohát, Róbert; Rödlingová, Beata; Horáková, Nina

2015-01-01

Corpus of High School Academic Texts (COHAT), currently of 150,000+ words, aims to make academic language instruction a more data-driven and student-centered discovery learning as a special type of Computer-Assisted Language Learning (CALL), emphasizing students' critical thinking and metacognition. Since 2013, high school English as an additional…

Pre-Service Teachers' Cognitive Competencies to Use the Approaches in Mathematics Teaching: Discovery Learning

ERIC Educational Resources Information Center

Yilmaz, Rezan

2014-01-01

This study aims to present the cognitive competences of the pre-service teacher about discovery learning approach in mathematical education. The study was conducted with 37 mathematics pre-service teachers who study Special Teaching Methods lesson in a state university in Turkey. Throughout the lesson, the approaches used in learning were examined…

Online Pedagogical Tutorial Tactics Optimization Using Genetic-Based Reinforcement Learning

PubMed Central

Lin, Hsuan-Ta; Lee, Po-Ming; Hsiao, Tzu-Chien

2015-01-01

Tutorial tactics are policies for an Intelligent Tutoring System (ITS) to decide the next action when there are multiple actions available. Recent research has demonstrated that when the learning contents were controlled so as to be the same, different tutorial tactics would make difference in students' learning gains. However, the Reinforcement Learning (RL) techniques that were used in previous studies to induce tutorial tactics are insufficient when encountering large problems and hence were used in offline manners. Therefore, we introduced a Genetic-Based Reinforcement Learning (GBML) approach to induce tutorial tactics in an online-learning manner without basing on any preexisting dataset. The introduced method can learn a set of rules from the environment in a manner similar to RL. It includes a genetic-based optimizer for rule discovery task by generating new rules from the old ones. This increases the scalability of a RL learner for larger problems. The results support our hypothesis about the capability of the GBML method to induce tutorial tactics. This suggests that the GBML method should be favorable in developing real-world ITS applications in the domain of tutorial tactics induction. PMID:26065018

Online Pedagogical Tutorial Tactics Optimization Using Genetic-Based Reinforcement Learning.

PubMed

Lin, Hsuan-Ta; Lee, Po-Ming; Hsiao, Tzu-Chien

2015-01-01

Tutorial tactics are policies for an Intelligent Tutoring System (ITS) to decide the next action when there are multiple actions available. Recent research has demonstrated that when the learning contents were controlled so as to be the same, different tutorial tactics would make difference in students' learning gains. However, the Reinforcement Learning (RL) techniques that were used in previous studies to induce tutorial tactics are insufficient when encountering large problems and hence were used in offline manners. Therefore, we introduced a Genetic-Based Reinforcement Learning (GBML) approach to induce tutorial tactics in an online-learning manner without basing on any preexisting dataset. The introduced method can learn a set of rules from the environment in a manner similar to RL. It includes a genetic-based optimizer for rule discovery task by generating new rules from the old ones. This increases the scalability of a RL learner for larger problems. The results support our hypothesis about the capability of the GBML method to induce tutorial tactics. This suggests that the GBML method should be favorable in developing real-world ITS applications in the domain of tutorial tactics induction.

Substructure Discovery of Macro-Operators

DTIC Science & Technology

1988-05-01

Aspects of Scientific Discovery," in Machine Learning: An Artifcial Intelligence Approach, Vol. II. R. S. Michalski, J. G. Carbonell and T. M. Mitchell (ed... intelligent robot using this system could learn how to perform new tasks by watching tasks being performed by someone else. even if the robot does not possess...Substructure Discovery of Macro-Operators* Bradley L. Whitehall Artificial Intelligence Research Group Coordinated Science Laboratory ’University of Illinois at

An Evaluation of Active Learning Causal Discovery Methods for Reverse-Engineering Local Causal Pathways of Gene Regulation

PubMed Central

Ma, Sisi; Kemmeren, Patrick; Aliferis, Constantin F.; Statnikov, Alexander

2016-01-01

Reverse-engineering of causal pathways that implicate diseases and vital cellular functions is a fundamental problem in biomedicine. Discovery of the local causal pathway of a target variable (that consists of its direct causes and direct effects) is essential for effective intervention and can facilitate accurate diagnosis and prognosis. Recent research has provided several active learning methods that can leverage passively observed high-throughput data to draft causal pathways and then refine the inferred relations with a limited number of experiments. The current study provides a comprehensive evaluation of the performance of active learning methods for local causal pathway discovery in real biological data. Specifically, 54 active learning methods/variants from 3 families of algorithms were applied for local causal pathways reconstruction of gene regulation for 5 transcription factors in S. cerevisiae. Four aspects of the methods’ performance were assessed, including adjacency discovery quality, edge orientation accuracy, complete pathway discovery quality, and experimental cost. The results of this study show that some methods provide significant performance benefits over others and therefore should be routinely used for local causal pathway discovery tasks. This study also demonstrates the feasibility of local causal pathway reconstruction in real biological systems with significant quality and low experimental cost. PMID:26939894

Closing the Loop: Automated Data-Driven Cognitive Model Discoveries Lead to Improved Instruction and Learning Gains

ERIC Educational Resources Information Center

Liu, Ran; Koedinger, Kenneth R.

2017-01-01

As the use of educational technology becomes more ubiquitous, an enormous amount of learning process data is being produced. Educational data mining seeks to analyze and model these data, with the ultimate goal of improving learning outcomes. The most firmly grounded and rigorous evaluation of an educational data mining discovery is whether it…

Learning from the past for TB drug discovery in the future

PubMed Central

Mikušová, Katarína; Ekins, Sean

2016-01-01

Tuberculosis drug discovery has shifted in recent years from a primarily target-based approach to one that uses phenotypic high-throughput screens. As examples of this, through our EU-funded FP7 collaborations, New Medicines for Tuberculosis was target-based and our more-recent More Medicines for Tuberculosis project predominantly used phenotypic screening. From these projects we have examples of success (DprE1) and failure (PimA) going from drug to target and from target to drug, respectively. It is clear that we still have much to learn about the drug targets and the complex effects of the drugs on Mycobacterium tuberculosis. We propose a more integrated approach that learns from earlier drug discovery efforts that could help to move drug discovery forward. PMID:27717850

GeoGebra Assist Discovery Learning Model for Problem Solving Ability and Attitude toward Mathematics

NASA Astrophysics Data System (ADS)

Murni, V.; Sariyasa, S.; Ardana, I. M.

2017-09-01

This study aims to describe the effet of GeoGebra utilization in the discovery learning model on mathematical problem solving ability and students’ attitude toward mathematics. This research was quasi experimental and post-test only control group design was used in this study. The population in this study was 181 of students. The sampling technique used was cluster random sampling, so the sample in this study was 120 students divided into 4 classes, 2 classes for the experimental class and 2 classes for the control class. Data were analyzed by using one way MANOVA. The results of data analysis showed that the utilization of GeoGebra in discovery learning can lead to solving problems and attitudes towards mathematics are better. This is because the presentation of problems using geogebra can assist students in identifying and solving problems and attracting students’ interest because geogebra provides an immediate response process to students. The results of the research are the utilization of geogebra in the discovery learning can be applied in learning and teaching wider subject matter, beside subject matter in this study.

The Johns Hopkins Hunterian Laboratory Philosophy: Mentoring Students in a Scientific Neurosurgical Research Laboratory.

PubMed

Tyler, Betty M; Liu, Ann; Sankey, Eric W; Mangraviti, Antonella; Barone, Michael A; Brem, Henry

2016-06-01

After over 50 years of scientific contribution under the leadership of Harvey Cushing and later Walter Dandy, the Johns Hopkins Hunterian Laboratory entered a period of dormancy between the 1960s and early 1980s. In 1984, Henry Brem reinstituted the Hunterian Neurosurgical Laboratory, with a new focus on localized delivery of therapies for brain tumors, leading to several discoveries such as new antiangiogenic agents and Gliadel chemotherapy wafers for the treatment of malignant gliomas. Since that time, it has been the training ground for 310 trainees who have dedicated their time to scientific exploration in the lab, resulting in numerous discoveries in the area of neurosurgical research. The Hunterian Neurosurgical Laboratory has been a unique example of successful mentoring in a translational research environment. The laboratory's philosophy emphasizes mentorship, independence, self-directed learning, creativity, and people-centered collaboration, while maintaining productivity with a focus on improving clinical outcomes. This focus has been served by the diverse backgrounds of its trainees, both in regard to educational status as well as culturally. Through this philosophy and strong legacy of scientific contribution, the Hunterian Laboratory has maintained a positive and productive research environment that supports highly motivated students and trainees. In this article, the authors discuss the laboratory's training philosophy, linked to the principles of adult learning (andragogy), as well as the successes and the limitations of including a wide educational range of students in a neurosurgical translational laboratory and the phenomenon of combining clinical expertise with rigorous scientific training.

Student Analysis of Handout Development based on Guided Discovery Method in Process Evaluation and Learning Outcomes of Biology

NASA Astrophysics Data System (ADS)

Nerita, S.; Maizeli, A.; Afza, A.

2017-09-01

Process Evaluation and Learning Outcomes of Biology subjects discusses the evaluation process in learning and application of designed and processed learning outcomes. Some problems found during this subject was the student difficult to understand the subject and the subject unavailability of learning resources that can guide and make students independent study. So, it necessary to develop a learning resource that can make active students to think and to make decisions with the guidance of the lecturer. The purpose of this study is to produce handout based on guided discovery method that match the needs of students. The research was done by using 4-D models and limited to define phase that is student requirement analysis. Data obtained from the questionnaire and analyzed descriptively. The results showed that the average requirement of students was 91,43%. Can be concluded that students need a handout based on guided discovery method in the learning process.

Bruno Braunerde und die Bodentypen - Learning about soil diversity and soil functions with cartoon characters

NASA Astrophysics Data System (ADS)

Hofmann, Anett

2015-04-01

"Bruno Braunerde und die Bodentypen" is a German-language learning material that fosters discovery of soil diversity and soil functions in kids, teens and adults who enjoy interactive learning activities. The learning material consists of (i) a large poster (dimensions 200 x 120 cm) showing an imaginative illustrated landscape that could be situated in Austria, Switzerland or southern Germany and (ii) a set of 15 magnetic cards that show different soil cartoon characters, e.g. Bruno Braunerde (Cambisol), Stauni Pseudogley (Stagnic Luvisol) or Heidi Podsol (Podzol) on the front and a fun profession and address (linked to the respective soil functions) on the back side. The task is to place the soil cartoon characters to their 'home' in the landscape. This learning material was developed as a contribution to the International Year of Soils 2015 and is supported by the German, Austrian and Swiss Soil Sciences Societies and the Swiss Federal Office for the Environment. The soil cartoon characters are an adaptation of the original concept by the James Hutton Institute, Aberdeen, Scotland (www.hutton.ac.uk/learning/dirt-doctor).

Museums, Adventures, Discovery Activities: Gifted Curriculum Intrinsically Differentiated.

ERIC Educational Resources Information Center

Haensly, Patricia A.

This paper discusses how museums, adventure programs, and discovery activities can become an intrinsically differentiated gifted curriculum for gifted learners. Museums and adventure programs are a forum for meaningful learning activities. The contextual characteristics of effectively designed settings for learning activities can, if the…

Formal and Informal Context Factors as Contributors to Student Engagement in a Guided Discovery-Based Program of Game Design Learning

ERIC Educational Resources Information Center

Reynolds, Rebecca; Chiu, Ming Ming

2013-01-01

This paper explored informal (after-school) and formal (elective course in-school) learning contexts as contributors to middle-school student attitudinal changes in a guided discovery-based and blended e-learning program in which students designed web games and used social media and information resources for a full school year. Formality of the…

Learning in the context of distribution drift

DTIC Science & Technology

2017-05-09

published in the leading data mining journal, Data Mining and Knowledge Discovery (Webb et. al., 2016)1. We have shown that the previous qualitative...learner Low-bias learner Aggregated classifier Figure 7: Architecture for learning fr m streaming data in th co text of variable or unknown...Learning limited dependence Bayesian classifiers, in Proceedings of the Second International Conference on Knowledge Discovery and Data Mining (KDD

Seafloor Science and Remotely Operated Vehicle (SSROV) Day Camp: A Week-Long, Hands-On STEM Summer Camp

NASA Astrophysics Data System (ADS)

Wheat, C. G.; Fournier, T.; Monahan, K.; Paul, C.

2015-12-01

RETINA (Robotic Exploration Technologies IN Astrobiology) has developed a program geared towards stimulating our youth with innovative and relevant hands-on learning modules under a STEM umbrella. Given the breadth of potential science and engineering topics that excite children, the RETINA Program focuses on interactive participation in the design and development of simple robotic and sensor systems, providing a range of challenges to engage students through project-based learning (PBL). Thus, young students experience scientific discovery through the use and understanding of technology. This groundwork serves as the foundation for SSROV Camp, a week-long, summer day camp for 6th-8th grade students. The camp is centered on the sensors and platforms that guide seafloor exploration and discovery and builds upon the notion that transformative discoveries in the deep sea result from either sampling new environments or making new measurements with sensors adapted to this extreme environment. These technical and scientific needs are folded into the curriculum. Each of the first four days of the camp includes four team-based, hands-on technical challenges, communication among peer groups, and competition. The fifth day includes additional activities, culminating in camper-led presentations to describe a planned mission based on a given geologic setting. Presentations include hypotheses, operational requirements and expected data products. SSROV Camp was initiated last summer for three sessions, two in Monterey, CA and one in Oxford, MS. Campers from both regions grasped key elements of the program, based on written responses to questions before and after the camp. On average, 32% of the pre-test questions were answered correctly compared with 80% of the post-test questions. Additional confirmation of gains in campers' knowledge, skills, and critical thinking on environmental issues and engineering problems were apparent during the "jeopardy" competition, nightly homework, and mission presentations. On the basis of this successful effort, we hope to expand to other towns.

Guided discovery learning in geometry learning

NASA Astrophysics Data System (ADS)

Khasanah, V. N.; Usodo, B.; Subanti, S.

2018-03-01

Geometry is a part of the mathematics that must be learned in school. The purpose of this research was to determine the effect of Guided Discovery Learning (GDL) toward geometry learning achievement. This research had conducted at junior high school in Sukoharjo on academic years 2016/2017. Data collection was done based on student’s work test and documentation. Hypothesis testing used two ways analysis of variance (ANOVA) with unequal cells. The results of this research that GDL gave positive effect towards mathematics learning achievement. GDL gave better mathematics learning achievement than direct learning. There was no difference of mathematics learning achievement between male and female. There was no an interaction between sex differences and learning models toward student’s mathematics learning achievement. GDL can be used to improve students’ mathematics learning achievement in geometry.

Envisioning engineering education and practice in the coming intelligence convergence era — a complex adaptive systems approach

NASA Astrophysics Data System (ADS)

Noor, Ahmed K.

2013-12-01

Some of the recent attempts for improving and transforming engineering education are reviewed. The attempts aim at providing the entry level engineers with the skills needed to address the challenges of future large-scale complex systems and projects. Some of the frontier sectors and future challenges for engineers are outlined. The major characteristics of the coming intelligence convergence era (the post-information age) are identified. These include the prevalence of smart devices and environments, the widespread applications of anticipatory computing and predictive / prescriptive analytics, as well as a symbiotic relationship between humans and machines. Devices and machines will be able to learn from, and with, humans in a natural collaborative way. The recent game changers in learnscapes (learning paradigms, technologies, platforms, spaces, and environments) that can significantly impact engineering education in the coming era are identified. Among these are open educational resources, knowledge-rich classrooms, immersive interactive 3D learning, augmented reality, reverse instruction / flipped classroom, gamification, robots in the classroom, and adaptive personalized learning. Significant transformative changes in, and mass customization of, learning are envisioned to emerge from the synergistic combination of the game changers and other technologies. The realization of the aforementioned vision requires the development of a new multidisciplinary framework of emergent engineering for relating innovation, complexity and cybernetics, within the future learning environments. The framework can be used to treat engineering education as a complex adaptive system, with dynamically interacting and communicating components (instructors, individual, small, and large groups of learners). The emergent behavior resulting from the interactions can produce progressively better, and continuously improving, learning environment. As a first step towards the realization of the vision, intelligent adaptive cyber-physical ecosystems need to be developed to facilitate collaboration between the various stakeholders of engineering education, and to accelerate the development of a skilled engineering workforce. The major components of the ecosystems include integrated knowledge discovery and exploitation facilities, blended learning and research spaces, novel ultra-intelligent software agents, multimodal and autonomous interfaces, and networked cognitive and tele-presence robots.

Towards a 21 century paradigm of chiropractic: stage 1, redesigning clinical learning.

PubMed

Ebrall, Phillip; Draper, Barry; Repka, Adrian

2008-01-01

To describe a formal process designed to determine the nature and extent of change that may enhance the depth of student learning in the pre-professional, clinical chiropractic environment. Project teams in the Royal Melbourne Institute of Technology (RMIT) School of Health Sciences and the Division of Chiropractic explored questions of clinical assessment in several health care disciplines of the School and the issue of implementing change in a manner that would be embraced by the clinicians who supervise student-learning in the clinical environment. The teams applied to RMIT for grant funding within the Learning and Teaching Investment Fund to support two proposed studies. Both research proposals were fully funded and are in process. The genesis of this work is the discovery that the predominant management plan in the chiropractic teaching clinics is based on diagnostic reductionism. It is felt this is counter-productive to the holistic dimensions of chiropractic practice taught in the classroom and non-supportive of chiropractic's paradigm shift towards wellness. A need is seen to improve processes around student assessment in the contemporary work-integrated learning that is a prime element of learning within the clinical disciplines of the School of Health Sciences, including chiropractic. Any improvements in the manner of clinical assessment within the chiropractic discipline will need to be accompanied by improvement in the training and development of the clinicians responsible for managing the provision of quality patient care by Registered Chiropractic Students.

Cosmic Concepts: A Video Series for Scaffolded Learning

NASA Astrophysics Data System (ADS)

Eisenhamer, Bonnie; Summers, Frank; Maple, John

2016-01-01

Scaffolding is widely considered to be an essential element of effective teaching and is used to help bridge knowledge gaps for learners. Scaffolding is especially important for distance-learning programs and computer-based learning environments. Preliminary studies are showing that when students learn about complex topics within computer-based learning environments without scaffolding, they fail to gain a conceptual understanding of the topic. As a result, researchers have begun to emphasize the importance of scaffolding for web-based as well as in-person instruction.To support scaffolded teaching practices and techniques, while addressing the needs of life-long learners, we have created the Cosmic Concepts video series. The series consists of short, one-topic videos that address scientific concepts with a special emphasis on those that traditionally cause confusion or are layered with misconceptions. Each video focuses on one idea at a time and provides a clear explanation of phenomena that is succinct enough for on-demand reference usage by all types of learners. Likewise, the videos can be used by educators to scaffold the scientific concepts behind astronomical images, or can be sequenced together to create well-structured pathways for presenting deeper and more layered ideas. This approach is critical for communicating information about astronomical discoveries that are often dense with unfamiliar concepts, complex ideas, and highly technical details. Additionally, learning tools in video formats support multi-sensory presentation approaches that can make astronomy more accessible to a variety of learners.

Making connections: Where STEM learning and Earth science data services meet

NASA Astrophysics Data System (ADS)

Bugbee, K.; Ramachandran, R.; Maskey, M.; Gatlin, P. N.; Weigel, A. M.

2016-12-01

STEM learning is most effective when students are encouraged to see the connections between science, technology and real world problems. Helping to make these connections has become an increasingly important aspect of Earth science data research. The Global Hydrology Resource Center (GHRC), one of NASA's 12 EOSDIS data centers, has developed a new type of documentation called the micro article to facilitate making connections between data and Earth science research problems. Micro articles are short academic texts that enable a reader to quickly understand a scientific phenomena, a case study, or an instrument used to collect data. While originally designed to increase data discovery and usability, micro articles also serve as a reliable starting point for project-based learning, an educational approach in STEM education, for high school and higher education environments. This presentation will highlight micro articles at the Global Hydrology Resource Center data center and will demonstrate the potential applications of micro articles in project-based learning.

PCM-SABRE: a platform for benchmarking and comparing outcome prediction methods in precision cancer medicine.

PubMed

Eyal-Altman, Noah; Last, Mark; Rubin, Eitan

2017-01-17

Numerous publications attempt to predict cancer survival outcome from gene expression data using machine-learning methods. A direct comparison of these works is challenging for the following reasons: (1) inconsistent measures used to evaluate the performance of different models, and (2) incomplete specification of critical stages in the process of knowledge discovery. There is a need for a platform that would allow researchers to replicate previous works and to test the impact of changes in the knowledge discovery process on the accuracy of the induced models. We developed the PCM-SABRE platform, which supports the entire knowledge discovery process for cancer outcome analysis. PCM-SABRE was developed using KNIME. By using PCM-SABRE to reproduce the results of previously published works on breast cancer survival, we define a baseline for evaluating future attempts to predict cancer outcome with machine learning. We used PCM-SABRE to replicate previous work that describe predictive models of breast cancer recurrence, and tested the performance of all possible combinations of feature selection methods and data mining algorithms that was used in either of the works. We reconstructed the work of Chou et al. observing similar trends - superior performance of Probabilistic Neural Network (PNN) and logistic regression (LR) algorithms and inconclusive impact of feature pre-selection with the decision tree algorithm on subsequent analysis. PCM-SABRE is a software tool that provides an intuitive environment for rapid development of predictive models in cancer precision medicine.

Inference and Discovery in an Exploratory Laboratory. Technical Report No. 10.

ERIC Educational Resources Information Center

Shute, Valerie; And Others

This paper describes the results of a study done as part of a research program investigating the use of computer-based laboratories to support self-paced discovery learning in related to microeconomics, electricity, and light refraction. Program objectives include maximizing the laboratories' effectiveness in helping students learn content…

Scientific Discoveries the Year I Was Born

ERIC Educational Resources Information Center

Cherif, Abour

2012-01-01

The author has successfully used a learning activity titled "The Year I Was Born" to motivate students to conduct historical research and present key scientific discoveries from their birth year. The activity promotes writing, helps students enhance their scientific literacy, and also improves their attitude toward the learning of science. As one…

Instructional and Learning Modes in Math. Module CMM:006:02.

ERIC Educational Resources Information Center

Rexroat, Melvin E.

This is the second module in a series on mathematics methods and materials for preservice elementary teachers. This module focuses on three instructional and learning modes: expository, guided discovery, and inquiry (pure discovery). Objectives for the module are listed, the prerequisites are stated, pre- and post-assessment standards are…

A renaissance of neural networks in drug discovery.

PubMed

Baskin, Igor I; Winkler, David; Tetko, Igor V

2016-08-01

Neural networks are becoming a very popular method for solving machine learning and artificial intelligence problems. The variety of neural network types and their application to drug discovery requires expert knowledge to choose the most appropriate approach. In this review, the authors discuss traditional and newly emerging neural network approaches to drug discovery. Their focus is on backpropagation neural networks and their variants, self-organizing maps and associated methods, and a relatively new technique, deep learning. The most important technical issues are discussed including overfitting and its prevention through regularization, ensemble and multitask modeling, model interpretation, and estimation of applicability domain. Different aspects of using neural networks in drug discovery are considered: building structure-activity models with respect to various targets; predicting drug selectivity, toxicity profiles, ADMET and physicochemical properties; characteristics of drug-delivery systems and virtual screening. Neural networks continue to grow in importance for drug discovery. Recent developments in deep learning suggests further improvements may be gained in the analysis of large chemical data sets. It's anticipated that neural networks will be more widely used in drug discovery in the future, and applied in non-traditional areas such as drug delivery systems, biologically compatible materials, and regenerative medicine.

40 CFR 22.19 - Prehearing information exchange; prehearing conference; other discovery.

Code of Federal Regulations, 2010 CFR

2010-07-01

... method of discovery sought, provide the proposed discovery instruments, and describe in detail the nature... finding that: (i) The information sought cannot reasonably be obtained by alternative methods of discovery... promptly supplement or correct the exchange when the party learns that the information exchanged or...

The Discovery Method in Training.

ERIC Educational Resources Information Center

Belbin, R. M.

In the form of a discussion between faceless people, this booklet concerns discovery learning and its advantages. Subjects covered in the discussions are: Introducing the Discovery Method; An Experiment with British Railways; The OECD Research Projects in U.S.A., Austria, and Sweden; How the Discovery Method Differs from Other Methods; Discovery…

A survey of automated methods for sensemaking support

NASA Astrophysics Data System (ADS)

Llinas, James

2014-05-01

Complex, dynamic problems in general present a challenge for the design of analysis support systems and tools largely because there is limited reliable a priori procedural knowledge descriptive of the dynamic processes in the environment. Problem domains that are non-cooperative or adversarial impute added difficulties involving suboptimal observational data and/or data containing the effects of deception or covertness. The fundamental nature of analysis in these environments is based on composite approaches involving mining or foraging over the evidence, discovery and learning processes, and the synthesis of fragmented hypotheses; together, these can be labeled as sensemaking procedures. This paper reviews and analyzes the features, benefits, and limitations of a variety of automated techniques that offer possible support to sensemaking processes in these problem domains.

A meta-learning system based on genetic algorithms

NASA Astrophysics Data System (ADS)

Pellerin, Eric; Pigeon, Luc; Delisle, Sylvain

2004-04-01

The design of an efficient machine learning process through self-adaptation is a great challenge. The goal of meta-learning is to build a self-adaptive learning system that is constantly adapting to its specific (and dynamic) environment. To that end, the meta-learning mechanism must improve its bias dynamically by updating the current learning strategy in accordance with its available experiences or meta-knowledge. We suggest using genetic algorithms as the basis of an adaptive system. In this work, we propose a meta-learning system based on a combination of the a priori and a posteriori concepts. A priori refers to input information and knowledge available at the beginning in order to built and evolve one or more sets of parameters by exploiting the context of the system"s information. The self-learning component is based on genetic algorithms and neural Darwinism. A posteriori refers to the implicit knowledge discovered by estimation of the future states of parameters and is also applied to the finding of optimal parameters values. The in-progress research presented here suggests a framework for the discovery of knowledge that can support human experts in their intelligence information assessment tasks. The conclusion presents avenues for further research in genetic algorithms and their capability to learn to learn.

Student Responses Toward Student Worksheets Based on Discovery Learning for Students with Intrapersonal and Interpersonal Intelligence

NASA Astrophysics Data System (ADS)

Yerizon, Y.; Putra, A. A.; Subhan, M.

2018-04-01

Students have a low mathematical ability because they are used to learning to hear the teacher's explanation. For that students are given activities to sharpen his ability in math. One way to do that is to create discovery learning based work sheet. The development of this worksheet took into account specific student learning styles including in schools that have classified students based on multiple intelligences. The dominant learning styles in the classroom were intrapersonal and interpersonal. The purpose of this study was to discover students’ responses to the mathematics work sheets of the junior high school with a discovery learning approach suitable for students with Intrapersonal and Interpersonal Intelligence. This tool was developed using a development model adapted from the Plomp model. The development process of this tools consists of 3 phases: front-end analysis/preliminary research, development/prototype phase and assessment phase. From the results of the research, it is found that students have good response to the resulting work sheet. The worksheet was understood well by students and its helps student in understanding the concept learned.

Enhancing the Therapy Experience Using Principles of Video Game Design.

PubMed

Folkins, John Wm; Brackenbury, Tim; Krause, Miriam; Haviland, Allison

2016-02-01

This article considers the potential benefits that applying design principles from contemporary video games may have on enhancing therapy experiences. Six principles of video game design are presented, and their relevance for enriching clinical experiences is discussed. The motivational and learning benefits of each design principle have been discussed in the education literature as having positive impacts on student motivation and learning and are related here to aspects of clinical practice. The essential experience principle suggests connecting all aspects of the experience around a central emotion or cognitive connection. The discovery principle promotes indirect learning in focused environments. The risk-taking principle addresses the uncertainties clients face when attempting newly learned skills in novel situations. The generalization principle encourages multiple opportunities for skill transfer. The reward system principle directly relates to the scaffolding of frequent and varied feedback in treatment. Last, the identity principle can assist clients in using their newly learned communication skills to redefine self-perceptions. These principles highlight areas for research and interventions that may be used to reinforce or advance current practice.

Searching for Buried Treasure: Uncovering Discovery in Discovery-Based Learning

ERIC Educational Resources Information Center

Chase, Kiera; Abrahamson, Dor

2018-01-01

Forty 4th and 9th grade students participated individually in tutorial interviews centered on a problem-solving activity designed for learning basic algebra mechanics through diagrammatic modeling of an engaging narrative about a buccaneering giant burying and unearthing her treasure on a desert island. Participants were randomly assigned to…

Effects of Discovery Learning and Student Assessment on Academic Success

ERIC Educational Resources Information Center

Suphi, Nilgün; Yaratan, Hüseyin

2016-01-01

In this study the effect of Discovery Learning and course evaluation based on Bloom's Taxonomy on the academic success of undergraduate students in Northern Cyprus was investigated. One demographic questionnaire was distributed to 829 students and two questionnaires were distributed to these students' instructors in order to collect information on…

Re-Vitalizing the First Year Class through Student Engagement and Discovery Learning

ERIC Educational Resources Information Center

Steuter, Erin; Doyle, Judith

2010-01-01

The first year course in Sociology at Mount Allison University introduced students to social issues via dynamic class interactions and assignments that are designed to build conceptual and applied skills. Developments to the course organization have maximized the opportunities for discovery learning and have made the class an enjoyable teaching…

Discovery Curriculum: For Use with Middle Grade Students in or out of the Classroom.

ERIC Educational Resources Information Center

Wickless, Mimi

This teaching guide contains the Discovery Curriculum which was extensively field tested at The National Arbor Day Foundation's Discovery Camp. The Discovery Curriculum is designed to promote wise environmental stewardship through relevant, active learning opportunities. Goals for each participant include: (1) be aware of and able to cite examples…

Machine Learning to Discover and Optimize Materials

NASA Astrophysics Data System (ADS)

Rosenbrock, Conrad Waldhar

For centuries, scientists have dreamed of creating materials by design. Rather than discovery by accident, bespoke materials could be tailored to fulfill specific technological needs. Quantum theory and computational methods are essentially equal to the task, and computational power is the new bottleneck. Machine learning has the potential to solve that problem by approximating material behavior at multiple length scales. A full end-to-end solution must allow us to approximate the quantum mechanics, microstructure and engineering tasks well enough to be predictive in the real world. In this dissertation, I present algorithms and methodology to address some of these problems at various length scales. In the realm of enumeration, systems with many degrees of freedom such as high-entropy alloys may contain prohibitively many unique possibilities so that enumerating all of them would exhaust available compute memory. One possible way to address this problem is to know in advance how many possibilities there are so that the user can reduce their search space by restricting the occupation of certain lattice sites. Although tools to calculate this number were available, none performed well for very large systems and none could easily be integrated into low-level languages for use in existing scientific codes. I present an algorithm to solve these problems. Testing the robustness of machine-learned models is an essential component in any materials discovery or optimization application. While it is customary to perform a small number of system-specific tests to validate an approach, this may be insufficient in many cases. In particular, for Cluster Expansion models, the expansion may not converge quickly enough to be useful and reliable. Although the method has been used for decades, a rigorous investigation across many systems to determine when CE "breaks" was still lacking. This dissertation includes this investigation along with heuristics that use only a small training database to predict whether a model is worth pursuing in detail. To be useful, computational materials discovery must lead to experimental validation. However, experiments are difficult due to sample purity, environmental effects and a host of other considerations. In many cases, it is difficult to connect theory to experiment because computation is deterministic. By combining advanced group theory with machine learning, we created a new tool that bridges the gap between experiment and theory so that experimental and computed phase diagrams can be harmonized. Grain boundaries in real materials control many important material properties such as corrosion, thermal conductivity, and creep. Because of their high dimensionality, learning the underlying physics to optimizing grain boundaries is extremely complex. By leveraging a mathematically rigorous representation for local atomic environments, machine learning becomes a powerful tool to approximate properties for grain boundaries. But it also goes beyond predicting properties by highlighting those atomic environments that are most important for influencing the boundary properties. This provides an immense dimensionality reduction that empowers grain boundary scientists to know where to look for deeper physical insights.

Computational biology for cardiovascular biomarker discovery.

PubMed

Azuaje, Francisco; Devaux, Yvan; Wagner, Daniel

2009-07-01

Computational biology is essential in the process of translating biological knowledge into clinical practice, as well as in the understanding of biological phenomena based on the resources and technologies originating from the clinical environment. One such key contribution of computational biology is the discovery of biomarkers for predicting clinical outcomes using 'omic' information. This process involves the predictive modelling and integration of different types of data and knowledge for screening, diagnostic or prognostic purposes. Moreover, this requires the design and combination of different methodologies based on statistical analysis and machine learning. This article introduces key computational approaches and applications to biomarker discovery based on different types of 'omic' data. Although we emphasize applications in cardiovascular research, the computational requirements and advances discussed here are also relevant to other domains. We will start by introducing some of the contributions of computational biology to translational research, followed by an overview of methods and technologies used for the identification of biomarkers with predictive or classification value. The main types of 'omic' approaches to biomarker discovery will be presented with specific examples from cardiovascular research. This will include a review of computational methodologies for single-source and integrative data applications. Major computational methods for model evaluation will be described together with recommendations for reporting models and results. We will present recent advances in cardiovascular biomarker discovery based on the combination of gene expression and functional network analyses. The review will conclude with a discussion of key challenges for computational biology, including perspectives from the biosciences and clinical areas.

The Effect of Discovery Learning Method Application on Increasing Students' Listening Outcome and Social Attitude

ERIC Educational Resources Information Center

Hanafi

2016-01-01

Curriculum of 2013 has been started in schools appointed as the implementer. This curriculum, for English subject demands the students to improve their skills. To reach this one of the suggested methods is discovery learning since this method is considered appropriate to implement for increasing the students' ability especially to fulfill minimum…

Discovery Learning: Zombie, Phoenix, or Elephant?

ERIC Educational Resources Information Center

Bakker, Arthur

2018-01-01

Discovery learning continues to be a topic of heated debate. It has been called a zombie, and this special issue raises the question whether it may be a phoenix arising from the ashes to which the topic was burnt. However, in this commentary I propose it is more like an elephant--a huge topic approached by many people who address different…

Augmented Reality-Based Simulators as Discovery Learning Tools: An Empirical Study

ERIC Educational Resources Information Center

Ibáñez, María-Blanca; Di-Serio, Ángela; Villarán-Molina, Diego; Delgado-Kloos, Carlos

2015-01-01

This paper reports empirical evidence on having students use AR-SaBEr, a simulation tool based on augmented reality (AR), to discover the basic principles of electricity through a series of experiments. AR-SaBEr was enhanced with knowledge-based support and inquiry-based scaffolding mechanisms, which proved useful for discovery learning in…

The Relation of Learners' Motivation with the Process of Collaborative Scientific Discovery Learning

ERIC Educational Resources Information Center

Saab, Nadira; van Joolingen, Wouter R.; van Hout-Wolters, B. H. A. M.

2009-01-01

In this study, we investigated the influence of individual learners' motivation on the collaborative discovery learning process. In this we distinguished the motivation of the individual learners and had eye for the composition of groups, which could be homogeneous or heterogeneous in terms of motivation. The study involved 73 dyads of 10th-grade…

The analysis of student’s critical thinking ability on discovery learning by using hand on activity based on the curiosity

NASA Astrophysics Data System (ADS)

Sulistiani, E.; Waluya, S. B.; Masrukan

2018-03-01

This study aims to determine (1) the effectiveness of Discovery Learning model by using Hand on Activity toward critical thinking abilities, and (2) to describe students’ critical thinking abilities in Discovery Learning by Hand on Activity based on curiosity. This study is mixed method research with concurrent embedded design. Sample of this study are students of VII A and VII B of SMP Daarul Qur’an Ungaran. While the subject in this study is based on the curiosity of the students groups are classified Epistemic Curiosity (EC) and Perceptual Curiosity (PC). The results showed that the learning of Discovery Learning by using Hand on Activity is effective toward mathematics critical thinking abilities. Students of the EC type are able to complete six indicators of mathematics critical thinking abilities, although there are still two indicators that the result is less than the maximum. While students of PC type have not fully been able to complete the indicator of mathematics critical thinking abilities. They are only strong on indicators formulating questions, while on the other five indicators they are still weak. The critical thinking abilities of EC’s students is better than the critical thinking abilities of the PC’s students.

Effectiveness of Discovery Learning-Based Transformation Geometry Module

NASA Astrophysics Data System (ADS)

Febriana, R.; Haryono, Y.; Yusri, R.

2017-09-01

Development of transformation geometry module is conducted because the students got difficulties to understand the existing book. The purpose of the research was to find out the effectiveness of discovery learning-based transformation geometry module toward student’s activity. Model of the development was Plomp model consisting preliminary research, prototyping phase and assessment phase. The research was focused on assessment phase where it was to observe the designed product effectiveness. The instrument was observation sheet. The observed activities were visual activities, oral activities, listening activities, mental activities, emotional activities and motor activities. Based on the result of the research, it is found that visual activities, learning activities, writing activities, the student’s activity is in the criteria very effective. It can be concluded that the use of discovery learning-based transformation geometry module use can increase the positive student’s activity and decrease the negative activity.

Learning and Relevance in Information Retrieval: A Study in the Application of Exploration and User Knowledge to Enhance Performance

ERIC Educational Resources Information Center

Hyman, Harvey

2012-01-01

This dissertation examines the impact of exploration and learning upon eDiscovery information retrieval; it is written in three parts. Part I contains foundational concepts and background on the topics of information retrieval and eDiscovery. This part informs the reader about the research frameworks, methodologies, data collection, and…

Using Discovery Maps as a Free-Choice Learning Process Can Enhance the Effectiveness of Environmental Education in a Botanical Garden

ERIC Educational Resources Information Center

Yang, Xi; Chen, Jin

2017-01-01

Botanical gardens (BGs) are important agencies that enhance human knowledge and attitude towards flora conservation. By following free-choice learning model, we developed a "Discovery map" and distributed the map to visitors at the Xishuangbanna Tropical Botanical Garden in Yunnan, China. Visitors, who did and did not receive discovery…

Improving Junior High School Students' Mathematical Analogical Ability Using Discovery Learning Method

ERIC Educational Resources Information Center

Maarif, Samsul

2016-01-01

The aim of this study was to identify the influence of discovery learning method towards the mathematical analogical ability of junior high school's students. This is a research using factorial design 2x2 with ANOVA-Two ways. The population of this research included the entire students of SMPN 13 Jakarta (State Junior High School 13 of Jakarta)…

40 CFR 27.21 - Discovery.

Code of Federal Regulations, 2012 CFR

2012-07-01

... 40 Protection of Environment 1 2012-07-01 2012-07-01 false Discovery. 27.21 Section 27.21... Discovery. (a) The following types of discovery are authorized: (1) Requests for production of documents for..., discovery is available only as ordered by the presiding officer. The presiding officer shall regulate the...

40 CFR 27.21 - Discovery.

Code of Federal Regulations, 2014 CFR

2014-07-01

... 40 Protection of Environment 1 2014-07-01 2014-07-01 false Discovery. 27.21 Section 27.21... Discovery. (a) The following types of discovery are authorized: (1) Requests for production of documents for..., discovery is available only as ordered by the presiding officer. The presiding officer shall regulate the...

40 CFR 27.21 - Discovery.

Code of Federal Regulations, 2013 CFR

2013-07-01

... 40 Protection of Environment 1 2013-07-01 2013-07-01 false Discovery. 27.21 Section 27.21... Discovery. (a) The following types of discovery are authorized: (1) Requests for production of documents for..., discovery is available only as ordered by the presiding officer. The presiding officer shall regulate the...

40 CFR 27.21 - Discovery.

Code of Federal Regulations, 2011 CFR

2011-07-01

... 40 Protection of Environment 1 2011-07-01 2011-07-01 false Discovery. 27.21 Section 27.21... Discovery. (a) The following types of discovery are authorized: (1) Requests for production of documents for..., discovery is available only as ordered by the presiding officer. The presiding officer shall regulate the...

40 CFR 27.21 - Discovery.

Code of Federal Regulations, 2010 CFR

2010-07-01

... 40 Protection of Environment 1 2010-07-01 2010-07-01 false Discovery. 27.21 Section 27.21... Discovery. (a) The following types of discovery are authorized: (1) Requests for production of documents for..., discovery is available only as ordered by the presiding officer. The presiding officer shall regulate the...

Feature Discovery by Competitive Learning.

ERIC Educational Resources Information Center

Rumelhart, David E.; Zipser, David

1985-01-01

Reports results of studies with an unsupervised learning paradigm called competitive learning which is examined using computer simulation and formal analysis. When competitive learning is applied to parallel networks of neuron-like elements, many potentially useful learning tasks can be accomplished. (Author)

Postgenomic strategies in antibacterial drug discovery.

PubMed

Brötz-Oesterhelt, Heike; Sass, Peter

2010-10-01

During the last decade the field of antibacterial drug discovery has changed in many aspects including bacterial organisms of primary interest, discovery strategies applied and pharmaceutical companies involved. Target-based high-throughput screening had been disappointingly unsuccessful for antibiotic research. Understanding of this lack of success has increased substantially and the lessons learned refer to characteristics of targets, screening libraries and screening strategies. The 'genomics' approach was replaced by a diverse array of discovery strategies, for example, searching for new natural product leads among previously abandoned compounds or new microbial sources, screening for synthetic inhibitors by targeted approaches including structure-based design and analyses of focused libraries and designing resistance-breaking properties into antibiotics of established classes. Furthermore, alternative treatment options are being pursued including anti-virulence strategies and immunotherapeutic approaches. This article summarizes the lessons learned from the genomics era and describes discovery strategies resulting from that knowledge.

Discovery Reconceived: Product before Process

ERIC Educational Resources Information Center

Abrahamson, Dor

2012-01-01

Motivated by the question, "What exactly about a mathematical concept should students discover, when they study it via discovery learning?", I present and demonstrate an interpretation of discovery pedagogy that attempts to address its criticism. My approach hinges on decoupling the solution process from its resultant product. Whereas theories of…

Use of Simulation Learning Experiences in Physical Therapy Entry-to-Practice Curricula: A Systematic Review

PubMed Central

Carnahan, Heather; Herold, Jodi

2015-01-01

ABSTRACT Purpose: To review the literature on simulation-based learning experiences and to examine their potential to have a positive impact on physiotherapy (PT) learners' knowledge, skills, and attitudes in entry-to-practice curricula. Method: A systematic literature search was conducted in the MEDLINE, CINAHL, Embase Classic+Embase, Scopus, and Web of Science databases, using keywords such as physical therapy, simulation, education, and students. Results: A total of 820 abstracts were screened, and 23 articles were included in the systematic review. While there were few randomized controlled trials with validated outcome measures, some discoveries about simulation can positively affect the design of the PT entry-to-practice curricula. Using simulators to provide specific output feedback can help students learn specific skills. Computer simulations can also augment students' learning experience. Human simulation experiences in managing the acute patient in the ICU are well received by students, positively influence their confidence, and decrease their anxiety. There is evidence that simulated learning environments can replace a portion of a full-time 4-week clinical rotation without impairing learning. Conclusions: Simulation-based learning activities are being effectively incorporated into PT curricula. More rigorously designed experimental studies that include a cost–benefit analysis are necessary to help curriculum developers make informed choices in curriculum design. PMID:25931672

40 CFR 164.51 - Other discovery.

Code of Federal Regulations, 2014 CFR

2014-07-01

... 40 Protection of Environment 24 2014-07-01 2014-07-01 false Other discovery. 164.51 Section 164.51... (Other Than Expedited Hearings) Prehearing Procedures and Discovery § 164.51 Other discovery. (a) General. Except as so provided by § 164.50(b) supra, further discovery, under this subpart, shall be permitted...

40 CFR 164.51 - Other discovery.

Code of Federal Regulations, 2011 CFR

2011-07-01

... 40 Protection of Environment 24 2011-07-01 2011-07-01 false Other discovery. 164.51 Section 164.51... (Other Than Expedited Hearings) Prehearing Procedures and Discovery § 164.51 Other discovery. (a) General. Except as so provided by § 164.50(b) supra, further discovery, under this subpart, shall be permitted...

Problems of Primary Education Today

ERIC Educational Resources Information Center

Dubova, M. V.

2014-01-01

Primary education in Russia has failed to adapt to the needs of post-Soviet society, and is still based on rote learning and memorization instead of learning through discovery and learning to use and apply what is learned.

Science Policy: Behind the Scenes

NASA Astrophysics Data System (ADS)

Barnett, Travis

2011-04-01

I served nine weeks as an intern in the House of Representatives Committee on Science and Technology. For the majority of the summer I served in the Research and Science Education Subcommittee, researching, among other things, cyber-enabled learning, cybersecurity, and alternate energy costs. I learned a great deal about the workings of the American government and how to contribute to a professional office environment. During these nine weeks, my personal communication skills were greatly improved. My internship was created and funded by the John and Jane Mather Foundation for the Arts and Sciences, and as the only merit-based science committee intern, I felt a great responsibility to prove my worth in the Committee. It is important to have scientists involved in the policy of our government in order to keep our nation on a progressive track, and to preserve current scientific discoveries for posterity. Immersed in government and science policy, I feel very learned and prepared to participate in these fields.

Guided Versus Unguided Learning: Which One To Choose?

NASA Astrophysics Data System (ADS)

Speck, Angela; Ruzhitskaya, L.

2011-01-01

We present the results of a study that measures the effectiveness of two types of computer-based tutorials for teaching the concept of stellar parallax to non-science major students in a college-level introductory astronomy course. A number of previous studies on the use of computer technology in education suggested that a method of inquiry-based learning rooted in a discovery method must prevail over direct instruction. At the same time, a number of researchers raised a concern that the discovery approach especially in combination with interactive computer-based environments may present students with additional distractions and thus hinder the educational value of such interactions. This study was set to test the both approaches and to identify the preferable method for engaging students in active and meaningful learning. The study consisted of guided and unguided computer-based tutorials and used a control group in which students were engaged in paper-based exercises. The guided tutorial was an adaptive tutorial that was designed to respond to students’ input and to provide them with the next step: an exercise, an animated visualization, or a set of additional questions. The unguided tutorial allowed students to explore any part of the tutorial in any order. Both tutorials consisted of four parts and reviewed simple geometry, trigonometric parallax, angular sizes in astronomy, resolution and conversion of units, and had a concluding chapter on finding distance to a star. The control group used Lecture-Tutorials (Prather, et al) to learn angular sizes and stellar parallax. The efficacy of each treatment was validated through a 14-question pretest and two posttests to evaluate and contrast students’ immediate recall and their long-term knowledge and corroborated by a number of interviews with selected students. We present our preliminary results based on analyzed work of over 200 participants.

A Discovery Chemistry Experiment on Buffers

ERIC Educational Resources Information Center

Kulevich, Suzanne E.; Herrick, Richard S.; Mills, Kenneth V.

2014-01-01

The Holy Cross Chemistry Department has designed and implemented an experiment on buffers as part of our Discovery Chemistry curriculum. The pedagogical philosophy of Discovery Chemistry is to make the laboratory the focal point of learning for students in their first two years of undergraduate instruction. We first pose questions in prelaboratory…

Collected Notes on the Workshop for Pattern Discovery in Large Databases

NASA Technical Reports Server (NTRS)

Buntine, Wray (Editor); Delalto, Martha (Editor)

1991-01-01

These collected notes are a record of material presented at the Workshop. The core data analysis is addressed that have traditionally required statistical or pattern recognition techniques. Some of the core tasks include classification, discrimination, clustering, supervised and unsupervised learning, discovery and diagnosis, i.e., general pattern discovery.

Intelligent Discovery for Learning Objects Using Semantic Web Technologies

ERIC Educational Resources Information Center

Hsu, I-Ching

2012-01-01

The concept of learning objects has been applied in the e-learning field to promote the accessibility, reusability, and interoperability of learning content. Learning Object Metadata (LOM) was developed to achieve these goals by describing learning objects in order to provide meaningful metadata. Unfortunately, the conventional LOM lacks the…

Contextual Approach with Guided Discovery Learning and Brain Based Learning in Geometry Learning

NASA Astrophysics Data System (ADS)

Kartikaningtyas, V.; Kusmayadi, T. A.; Riyadi

2017-09-01

The aim of this study was to combine the contextual approach with Guided Discovery Learning (GDL) and Brain Based Learning (BBL) in geometry learning of junior high school. Furthermore, this study analysed the effect of contextual approach with GDL and BBL in geometry learning. GDL-contextual and BBL-contextual was built from the steps of GDL and BBL that combined with the principles of contextual approach. To validate the models, it uses quasi experiment which used two experiment groups. The sample had been chosen by stratified cluster random sampling. The sample was 150 students of grade 8th in junior high school. The data were collected through the student’s mathematics achievement test that given after the treatment of each group. The data analysed by using one way ANOVA with different cell. The result shows that GDL-contextual has not different effect than BBL-contextual on mathematics achievement in geometry learning. It means both the two models could be used in mathematics learning as the innovative way in geometry learning.

SemaTyP: a knowledge graph based literature mining method for drug discovery.

PubMed

Sang, Shengtian; Yang, Zhihao; Wang, Lei; Liu, Xiaoxia; Lin, Hongfei; Wang, Jian

2018-05-30

Drug discovery is the process through which potential new medicines are identified. High-throughput screening and computer-aided drug discovery/design are the two main drug discovery methods for now, which have successfully discovered a series of drugs. However, development of new drugs is still an extremely time-consuming and expensive process. Biomedical literature contains important clues for the identification of potential treatments. It could support experts in biomedicine on their way towards new discoveries. Here, we propose a biomedical knowledge graph-based drug discovery method called SemaTyP, which discovers candidate drugs for diseases by mining published biomedical literature. We first construct a biomedical knowledge graph with the relations extracted from biomedical abstracts, then a logistic regression model is trained by learning the semantic types of paths of known drug therapies' existing in the biomedical knowledge graph, finally the learned model is used to discover drug therapies for new diseases. The experimental results show that our method could not only effectively discover new drug therapies for new diseases, but also could provide the potential mechanism of action of the candidate drugs. In this paper we propose a novel knowledge graph based literature mining method for drug discovery. It could be a supplementary method for current drug discovery methods.

The Development of Learning Devices Based Guided Discovery Model to Improve Understanding Concept and Critical Thinking Mathematically Ability of Students at Islamic Junior High School of Medan

ERIC Educational Resources Information Center

Yuliani, Kiki; Saragih, Sahat

2015-01-01

The purpose of this research was to: 1) development of learning devices based guided discovery model in improving of understanding concept and critical thinking mathematically ability of students at Islamic Junior High School; 2) describe improvement understanding concept and critical thinking mathematically ability of students at MTs by using…

PERSONAL AND CIRCUMSTANTIAL FACTORS INFLUENCING THE ACT OF DISCOVERY.

ERIC Educational Resources Information Center

OSTRANDER, EDWARD R.

HOW STUDENTS SAY THEY LEARN WAS INVESTIGATED. INTERVIEWS WITH A RANDOM SAMPLE OF 74 WOMEN STUDENTS POSED QUESTIONS ABOUT THE NATURE, FREQUENCY, PATTERNS, AND CIRCUMSTANCES UNDER WHICH ACTS OF DISCOVERY TAKE PLACE IN THE ACADEMIC SETTING. STUDENTS WERE ASSIGNED DISCOVERY RATINGS BASED ON READINGS OF TYPESCRIPTS. EACH STUDENT WAS CLASSIFIED AND…

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.

Wains: a pattern-seeking artificial life species.

PubMed

de Buitléir, Amy; Russell, Michael; Daly, Mark

2012-01-01

We describe the initial phase of a research project to develop an artificial life framework designed to extract knowledge from large data sets with minimal preparation or ramp-up time. In this phase, we evolved an artificial life population with a new brain architecture. The agents have sufficient intelligence to discover patterns in data and to make survival decisions based on those patterns. The species uses diploid reproduction, Hebbian learning, and Kohonen self-organizing maps, in combination with novel techniques such as using pattern-rich data as the environment and framing the data analysis as a survival problem for artificial life. The first generation of agents mastered the pattern discovery task well enough to thrive. Evolution further adapted the agents to their environment by making them a little more pessimistic, and also by making their brains more efficient.

The rise of deep learning in drug discovery.

PubMed

Chen, Hongming; Engkvist, Ola; Wang, Yinhai; Olivecrona, Marcus; Blaschke, Thomas

2018-06-01

Over the past decade, deep learning has achieved remarkable success in various artificial intelligence research areas. Evolved from the previous research on artificial neural networks, this technology has shown superior performance to other machine learning algorithms in areas such as image and voice recognition, natural language processing, among others. The first wave of applications of deep learning in pharmaceutical research has emerged in recent years, and its utility has gone beyond bioactivity predictions and has shown promise in addressing diverse problems in drug discovery. Examples will be discussed covering bioactivity prediction, de novo molecular design, synthesis prediction and biological image analysis. Copyright © 2018 The Authors. Published by Elsevier Ltd.. All rights reserved.

Teaching Technology Applied in the Main Stream: The Supermarket Discovery Center

ERIC Educational Resources Information Center

Filep, Robert T.; Gillette, Pearl

1969-01-01

Describes the approach and results of the Supermarket Discovery Center Demonstration Project, a program attempting to provide pre-school children with meaningful learning experiences while their parents are shopping. (LS)

40 CFR 300.300 - Phase I-Discovery or notification.

Code of Federal Regulations, 2014 CFR

2014-07-01

... 40 Protection of Environment 28 2014-07-01 2014-07-01 false Phase I-Discovery or notification. 300.300 Section 300.300 Protection of Environment ENVIRONMENTAL PROTECTION AGENCY (CONTINUED) SUPERFUND, EMERGENCY PLANNING, AND COMMUNITY RIGHT-TO-KNOW PROGRAMS NATIONAL OIL AND HAZARDOUS SUBSTANCES POLLUTION...

40 CFR 300.300 - Phase I-Discovery or notification.

Code of Federal Regulations, 2011 CFR

2011-07-01

... 40 Protection of Environment 28 2011-07-01 2011-07-01 false Phase I-Discovery or notification. 300.300 Section 300.300 Protection of Environment ENVIRONMENTAL PROTECTION AGENCY (CONTINUED) SUPERFUND, EMERGENCY PLANNING, AND COMMUNITY RIGHT-TO-KNOW PROGRAMS NATIONAL OIL AND HAZARDOUS SUBSTANCES POLLUTION...

40 CFR 300.300 - Phase I-Discovery or notification.

Code of Federal Regulations, 2012 CFR

2012-07-01

... 40 Protection of Environment 29 2012-07-01 2012-07-01 false Phase I-Discovery or notification. 300.300 Section 300.300 Protection of Environment ENVIRONMENTAL PROTECTION AGENCY (CONTINUED) SUPERFUND, EMERGENCY PLANNING, AND COMMUNITY RIGHT-TO-KNOW PROGRAMS NATIONAL OIL AND HAZARDOUS SUBSTANCES POLLUTION...

40 CFR 300.300 - Phase I-Discovery or notification.

Code of Federal Regulations, 2013 CFR

2013-07-01

... 40 Protection of Environment 29 2013-07-01 2013-07-01 false Phase I-Discovery or notification. 300.300 Section 300.300 Protection of Environment ENVIRONMENTAL PROTECTION AGENCY (CONTINUED) SUPERFUND, EMERGENCY PLANNING, AND COMMUNITY RIGHT-TO-KNOW PROGRAMS NATIONAL OIL AND HAZARDOUS SUBSTANCES POLLUTION...

Computational Analysis of Behavior.

PubMed

Egnor, S E Roian; Branson, Kristin

2016-07-08

In this review, we discuss the emerging field of computational behavioral analysis-the use of modern methods from computer science and engineering to quantitatively measure animal behavior. We discuss aspects of experiment design important to both obtaining biologically relevant behavioral data and enabling the use of machine vision and learning techniques for automation. These two goals are often in conflict. Restraining or restricting the environment of the animal can simplify automatic behavior quantification, but it can also degrade the quality or alter important aspects of behavior. To enable biologists to design experiments to obtain better behavioral measurements, and computer scientists to pinpoint fruitful directions for algorithm improvement, we review known effects of artificial manipulation of the animal on behavior. We also review machine vision and learning techniques for tracking, feature extraction, automated behavior classification, and automated behavior discovery, the assumptions they make, and the types of data they work best with.

Changes in Instructional System Design (ISD): Improving Training Product Delivery to United States Army Soldiers

DTIC Science & Technology

2005-03-18

simulation. This model is a basis of what is called discovery learning. Discovery learning is constructionist method of instruction, which is a concept in...2005 PAGES: 48 CLASSIFICATION: Unclassified The purpose of this study is to identify methods that could speed up the instructional system design...became obvious as the enemy attacked using asymmetric means and methods . For instance: during the war, a mine identification-training product was

Computer-Aided Drug Discovery: Molecular Docking of Diminazene Ligands to DNA Minor Groove

ERIC Educational Resources Information Center

Kholod, Yana; Hoag, Erin; Muratore, Katlynn; Kosenkov, Dmytro

2018-01-01

The reported project-based laboratory unit introduces upper-division undergraduate students to the basics of computer-aided drug discovery as a part of a computational chemistry laboratory course. The students learn to perform model binding of organic molecules (ligands) to the DNA minor groove with computer-aided drug discovery (CADD) tools. The…

Metadata Effectiveness in Internet Discovery: An Analysis of Digital Collection Metadata Elements and Internet Search Engine Keywords

ERIC Educational Resources Information Center

Yang, Le

2016-01-01

This study analyzed digital item metadata and keywords from Internet search engines to learn what metadata elements actually facilitate discovery of digital collections through Internet keyword searching and how significantly each metadata element affects the discovery of items in a digital repository. The study found that keywords from Internet…

Understanding Fluorescence Measurements through a Guided-Inquiry and Discovery Experiment in Advanced Analytical Laboratory

ERIC Educational Resources Information Center

Wilczek-Vera, Grazyna; Salin, Eric Dunbar

2011-01-01

An experiment on fluorescence spectroscopy suitable for an advanced analytical laboratory is presented. Its conceptual development used a combination of the expository and discovery styles. The "learn-as-you-go" and direct "hands-on" methodology applied ensures an active role for a student in the process of visualization and discovery of concepts.…

Discovery learning model with geogebra assisted for improvement mathematical visual thinking ability

NASA Astrophysics Data System (ADS)

Juandi, D.; Priatna, N.

2018-05-01

The main goal of this study is to improve the mathematical visual thinking ability of high school student through implementation the Discovery Learning Model with Geogebra Assisted. This objective can be achieved through study used quasi-experimental method, with non-random pretest-posttest control design. The sample subject of this research consist of 62 senior school student grade XI in one of school in Bandung district. The required data will be collected through documentation, observation, written tests, interviews, daily journals, and student worksheets. The results of this study are: 1) Improvement students Mathematical Visual Thinking Ability who obtain learning with applied the Discovery Learning Model with Geogebra assisted is significantly higher than students who obtain conventional learning; 2) There is a difference in the improvement of students’ Mathematical Visual Thinking ability between groups based on prior knowledge mathematical abilities (high, medium, and low) who obtained the treatment. 3) The Mathematical Visual Thinking Ability improvement of the high group is significantly higher than in the medium and low groups. 4) The quality of improvement ability of high and low prior knowledge is moderate category, in while the quality of improvement ability in the high category achieved by student with medium prior knowledge.

Developing computer-based training programs for basic mammalian histology: Didactic versus discovery-based design

NASA Astrophysics Data System (ADS)

Fabian, Henry Joel

Educators have long tried to understand what stimulates students to learn. The Swiss psychologist and zoologist, Jean Claude Piaget, suggested that students are stimulated to learn when they attempt to resolve confusion. He reasoned that students try to explain the world with the knowledge they have acquired in life. When they find their own explanations to be inadequate to explain phenomena, students find themselves in a temporary state of confusion. This prompts students to seek more plausible explanations. At this point, students are primed for learning (Piaget 1964). The Piagetian approach described above is called learning by discovery. To promote discovery learning, a teacher must first allow the student to recognize his misconception and then provide a plausible explanation to replace that misconception (Chinn and Brewer 1993). One application of this method is found in the various learning cycles, which have been demonstrated to be effective means for teaching science (Renner and Lawson 1973, Lawson 1986, Marek and Methven 1991, and Glasson & Lalik 1993). In contrast to the learning cycle, tutorial computer programs are generally not designed to correct student misconceptions, but rather follow a passive, didactic method of teaching. In the didactic or expositional method, the student is told about a phenomenon, but is neither encouraged to explore it, nor explain it in his own terms (Schneider and Renner 1980).

When drug discovery meets web search: Learning to Rank for ligand-based virtual screening.

PubMed

Zhang, Wei; Ji, Lijuan; Chen, Yanan; Tang, Kailin; Wang, Haiping; Zhu, Ruixin; Jia, Wei; Cao, Zhiwei; Liu, Qi

2015-01-01

The rapid increase in the emergence of novel chemical substances presents a substantial demands for more sophisticated computational methodologies for drug discovery. In this study, the idea of Learning to Rank in web search was presented in drug virtual screening, which has the following unique capabilities of 1). Applicable of identifying compounds on novel targets when there is not enough training data available for these targets, and 2). Integration of heterogeneous data when compound affinities are measured in different platforms. A standard pipeline was designed to carry out Learning to Rank in virtual screening. Six Learning to Rank algorithms were investigated based on two public datasets collected from Binding Database and the newly-published Community Structure-Activity Resource benchmark dataset. The results have demonstrated that Learning to rank is an efficient computational strategy for drug virtual screening, particularly due to its novel use in cross-target virtual screening and heterogeneous data integration. To the best of our knowledge, we have introduced here the first application of Learning to Rank in virtual screening. The experiment workflow and algorithm assessment designed in this study will provide a standard protocol for other similar studies. All the datasets as well as the implementations of Learning to Rank algorithms are available at http://www.tongji.edu.cn/~qiliu/lor_vs.html. Graphical AbstractThe analogy between web search and ligand-based drug discovery.

Science Meets Literacy and Art at the Library

NASA Astrophysics Data System (ADS)

LaConte, K. M.; Shipp, S. S.; Halligan, E.

2011-12-01

The Lunar and Planetary Institute's Explore! program is designed to engage and inspire children in Earth and space science in the library and other informal learning environments. Eight online thematic Explore! modules make up-to-date science accessible to rural communities - often where the library is the closest center of public learning - and other underserved audiences. The program prepares librarians to engage their communities in science through experiences with the modules, interactions with scientists, exploration of the resources available within the library learning environment, and development of local partnerships. Through hands-on science activities, art, and reading, Explore! reaches library patrons between the ages of 8 and 13 through librarian-led, locally facilitated programs across the nation. For example, NASA Lunar Science Institute research into lunar formation, evolution, and orbital dynamics are woven into a comic book that serves as a journal and art piece for participants in Marvel Moon programs (http://www.lpi.usra.edu/explore/marvelMoon). In another example, children compare cloud types and atmospheric structure on Earth and Jupiter, and then they consider artwork of Jupiter's clouds and the future discoveries of NASA's upcoming Juno mission as they write "Jovian Poetry" (http://www.lpi.usra.edu/explore/solar_system/activities/weatherStations). Explore! program facilitators are provided resources for making use of children's science books and local professional scientists and engineers.

Marketed Marine Natural Products in the Pharmaceutical and Cosmeceutical Industries: Tips for Success

PubMed Central

Martins, Ana; Vieira, Helena; Gaspar, Helena; Santos, Susana

2014-01-01

The marine environment harbors a number of macro and micro organisms that have developed unique metabolic abilities to ensure their survival in diverse and hostile habitats, resulting in the biosynthesis of an array of secondary metabolites with specific activities. Several of these metabolites are high-value commercial products for the pharmaceutical and cosmeceutical industries. The aim of this review is to outline the paths of marine natural products discovery and development, with a special focus on the compounds that successfully reached the market and particularly looking at the approaches tackled by the pharmaceutical and cosmetic companies that succeeded in marketing those products. The main challenges faced during marine bioactives discovery and development programs were analyzed and grouped in three categories: biodiversity (accessibility to marine resources and efficient screening), supply and technical (sustainable production of the bioactives and knowledge of the mechanism of action) and market (processes, costs, partnerships and marketing). Tips to surpass these challenges are given in order to improve the market entry success rates of highly promising marine bioactives in the current pipelines, highlighting what can be learned from the successful and unsuccessful stories that can be applied to novel and/or ongoing marine natural products discovery and development programs. PMID:24549205

MLViS: A Web Tool for Machine Learning-Based Virtual Screening in Early-Phase of Drug Discovery and Development

PubMed Central

Korkmaz, Selcuk; Zararsiz, Gokmen; Goksuluk, Dincer

2015-01-01

Virtual screening is an important step in early-phase of drug discovery process. Since there are thousands of compounds, this step should be both fast and effective in order to distinguish drug-like and nondrug-like molecules. Statistical machine learning methods are widely used in drug discovery studies for classification purpose. Here, we aim to develop a new tool, which can classify molecules as drug-like and nondrug-like based on various machine learning methods, including discriminant, tree-based, kernel-based, ensemble and other algorithms. To construct this tool, first, performances of twenty-three different machine learning algorithms are compared by ten different measures, then, ten best performing algorithms have been selected based on principal component and hierarchical cluster analysis results. Besides classification, this application has also ability to create heat map and dendrogram for visual inspection of the molecules through hierarchical cluster analysis. Moreover, users can connect the PubChem database to download molecular information and to create two-dimensional structures of compounds. This application is freely available through www.biosoft.hacettepe.edu.tr/MLViS/. PMID:25928885

Field Studies—Essential Cognitive Foundations for Geoscience Expertise

NASA Astrophysics Data System (ADS)

Goodwin, C.; Mogk, D. W.

2010-12-01

Learning in the field has traditionally been one of the fundamental components of the geoscience curriculum. Field experiences have been attributed to having positive impacts on cognitive, affective, metacognitive, mastery of skills and social components of learning geoscience. The development of geoscience thinking, and of geoscience expertise, encompasses a number of learned behaviors that contribute to the progress of Science and the development of scientists. By getting out into Nature, students necessarily engage active and experiential learning. The open, dynamic, heterogeneous and complex Earth system provides ample opportunities to learn by inquiry and discovery. Learning in this environment requires that students make informed decisions and to think critically about what is important to observe, and what should be excluded in the complex overload of information provided by Nature. Students must learn to employ the full range of cognitive skills that include observation, description, interpretation, analysis and synthesis that lead to “deep learning”. They must be able to integrate and rationalize observations of Nature with modern experimental, analytical, theoretical, and modeling approaches to studying the Earth system, and they must be able to iterate between what is known and what is yet to be discovered. Immersion in the field setting provides students with a sense of spatial and temporal scales of natural phenomena that can not be derived in other learning environments. The field setting provides strong sensory inputs that stimulate cognition and memories that will be available for future application. The field environment also stimulates strong affective responses related to motivation, curiosity, a sense of “ownership” of field projects, and inclusion in shared experiences that carry on throughout professional careers. The nature of field work also contains a strong metacognitive component, as students learn to be aware of what and how they are learning in the field, regulate and modify their activities, and plan for future work.Embodied practice in the field shows students how to explore and interrogate nature, and how to interact and learn from other scientists. Learning geoscience is a social enterprise, requiring a long apprenticeship through which newcomers learn about Nature by working with competent senior practitioners in the settings where relevant nature is systematically studied. Learned social practices include the ability to enhance understanding of natural phenomena by constructing appropriate representations (inscriptions), knowing how to select and use appropriate tools, engaging the accepted community of practice, adopting professional standards and values, and the ability to contribute to geoscience discourse about the complex world. Both tools and the ability to locate perspicuous sites in the environment must be mastered so that representations can be made of structures in the landscape that cannot actually be seen from any single point of view to obtain a holistic and integrated interpretation of Earth history and processes. Sustained development of these cognitive strategies and skills is essential to the professional development of all geoscientists.

40 CFR 209.22 - Other discovery.

Code of Federal Regulations, 2013 CFR

2013-07-01

... 40 Protection of Environment 26 2013-07-01 2013-07-01 false Other discovery. 209.22 Section 209.22... Orders Issued Under Section 11(d) of the Noise Control Act § 209.22 Other discovery. (a) Further discovery under this section shall be undertaken only upon order of the administrative law judge or upon...

40 CFR 209.22 - Other discovery.

Code of Federal Regulations, 2014 CFR

2014-07-01

... 40 Protection of Environment 25 2014-07-01 2014-07-01 false Other discovery. 209.22 Section 209.22... Orders Issued Under Section 11(d) of the Noise Control Act § 209.22 Other discovery. (a) Further discovery under this section shall be undertaken only upon order of the administrative law judge or upon...

40 CFR 209.22 - Other discovery.

Code of Federal Regulations, 2011 CFR

2011-07-01

... 40 Protection of Environment 25 2011-07-01 2011-07-01 false Other discovery. 209.22 Section 209.22... Orders Issued Under Section 11(d) of the Noise Control Act § 209.22 Other discovery. (a) Further discovery under this section shall be undertaken only upon order of the administrative law judge or upon...

40 CFR 209.22 - Other discovery.

Code of Federal Regulations, 2010 CFR

2010-07-01

... 40 Protection of Environment 24 2010-07-01 2010-07-01 false Other discovery. 209.22 Section 209.22... Orders Issued Under Section 11(d) of the Noise Control Act § 209.22 Other discovery. (a) Further discovery under this section shall be undertaken only upon order of the administrative law judge or upon...

Open discovery: An integrated live Linux platform of Bioinformatics tools.

PubMed

Vetrivel, Umashankar; Pilla, Kalabharath

2008-01-01

Historically, live linux distributions for Bioinformatics have paved way for portability of Bioinformatics workbench in a platform independent manner. Moreover, most of the existing live Linux distributions limit their usage to sequence analysis and basic molecular visualization programs and are devoid of data persistence. Hence, open discovery - a live linux distribution has been developed with the capability to perform complex tasks like molecular modeling, docking and molecular dynamics in a swift manner. Furthermore, it is also equipped with complete sequence analysis environment and is capable of running windows executable programs in Linux environment. Open discovery portrays the advanced customizable configuration of fedora, with data persistency accessible via USB drive or DVD. The Open Discovery is distributed free under Academic Free License (AFL) and can be downloaded from http://www.OpenDiscovery.org.in.

A "Simple Query Interface" Adapter for the Discovery and Exchange of Learning Resources

ERIC Educational Resources Information Center

Massart, David

2006-01-01

Developed as part of CEN/ISSS Workshop on Learning Technology efforts to improve interoperability between learning resource repositories, the Simple Query Interface (SQI) is an Application Program Interface (API) for querying heterogeneous repositories of learning resource metadata. In the context of the ProLearn Network of Excellence, SQI is used…

The prominent role of the cerebellum in the learning, origin and advancement of culture.

PubMed

Vandervert, Larry

2016-01-01

Vandervert described how, in collaboration with the cerebral cortex, unconscious learning of cerebellar internal models leads to enhanced executive control in working memory in expert music performance and in scientific discovery. Following Vandervert's arguments, it is proposed that since music performance and scientific discovery, two pillars of cultural learning and advancement, are learned through in cerebellar internal models, it is reasonable that additional if not all components of culture may be learned in the same way. Within this perspective strong evidence is presented that argues that the learning, maintenance, and advancement of culture are accomplished primarily by recently-evolved (the last million or so years) motor/cognitive functions of the cerebellum and not primarily by the cerebral cortex as previously assumed. It is suggested that the unconscious cerebellar mechanism behind the origin and learning of culture greatly expands Ito's conception of the cerebellum as "a brain for an implicit self." Through the mechanism of predictive sequence detection in cerebellar internal models related to the body, other persons, or the environment, it is shown how individuals can unconsciously learn the elements of culture and yet, at the same time, be in social sync with other members of culture. Further, this predictive, cerebellar mechanism of socialization toward the norms of culture is hypothesized to be diminished among children who experience excessive television viewing, which results in lower grades, poor socialization, and diminished executive control. It is concluded that the essential components of culture are learned and sustained not by the cerebral cortex alone as many traditionally believe, but are learned through repetitious improvements in prediction and control by internal models in the cerebellum. From this perspective, the following new explanations of culture are discussed: (1) how culture can be learned unconsciously but yet be socially in sync with others, (2) how the recent evolutionary expansion of the cerebellum was involved in the co-evolution of earliest stone tools and language-leading to the cerebellum-driven origin of culture, (3) how cerebellar internal models are blended to produce the creative, forward advances in culture, (4) how the blending of cerebellar internal models led to human, multi-component, infinitely partitionable and communicable working memory, (5) how excessive television viewing may represent a cultural shift that diminishes the observational learning of internal models of the behavior of others and thus may result in a mild, parallel version of Schmahmann's cerebellar cognitive affective syndrome.

Causal discovery in the geosciences-Using synthetic data to learn how to interpret results

NASA Astrophysics Data System (ADS)

Ebert-Uphoff, Imme; Deng, Yi

2017-02-01

Causal discovery algorithms based on probabilistic graphical models have recently emerged in geoscience applications for the identification and visualization of dynamical processes. The key idea is to learn the structure of a graphical model from observed spatio-temporal data, thus finding pathways of interactions in the observed physical system. Studying those pathways allows geoscientists to learn subtle details about the underlying dynamical mechanisms governing our planet. Initial studies using this approach on real-world atmospheric data have shown great potential for scientific discovery. However, in these initial studies no ground truth was available, so that the resulting graphs have been evaluated only by whether a domain expert thinks they seemed physically plausible. The lack of ground truth is a typical problem when using causal discovery in the geosciences. Furthermore, while most of the connections found by this method match domain knowledge, we encountered one type of connection for which no explanation was found. To address both of these issues we developed a simulation framework that generates synthetic data of typical atmospheric processes (advection and diffusion). Applying the causal discovery algorithm to the synthetic data allowed us (1) to develop a better understanding of how these physical processes appear in the resulting connectivity graphs, and thus how to better interpret such connectivity graphs when obtained from real-world data; (2) to solve the mystery of the previously unexplained connections.

Data Pooling in a Chemical Kinetics Experiment: The Aquation of a Series of Cobalt(III) Complexes--A Discovery Chemistry Experiment

ERIC Educational Resources Information Center

Herrick, Richard S.; Mills, Kenneth V.; Nestor, Lisa P.

2008-01-01

An experiment in chemical kinetics as part of our Discovery Chemistry curriculum is described. Discovery Chemistry is a pedagogical philosophy that makes the laboratory the key center of learning for students in their first two years of undergraduate instruction. Questions are posed in the pre-laboratory discussion and assessed using pooled…

Teaching the Fundamentals of Biological Research with Primary Literature: Learning from the Discovery of the Gastric Proton Pump

ERIC Educational Resources Information Center

Zhu, Lixin

2011-01-01

For the purpose of teaching collegians the fundamentals of biological research, literature explaining the discovery of the gastric proton pump was presented in a 50-min lecture. The presentation included detailed information pertaining to the discovery process. This study was chosen because it demonstrates the importance of having a broad range of…

Workshops without Walls: Sharing Scientific Research through Educator Professional Development

NASA Astrophysics Data System (ADS)

Weir, H. M.; Edmonds, J. P.; Hallau, K.; Asplund, S. E.; Cobb, W. H.; Nittler, L. R.; Solomon, S. C.

2013-12-01

Scientific discoveries, large and small, are constantly being made. Whether it is the discovery of a new species or a new comet, it is a challenge to keep up. The media provide some assistance in getting the word out about the discoveries, but not the details or the challenges of the discovery. Professional development is essential for science educators to keep them abreast of the fascinating discoveries that are occurring. The problem is that not every educator has the opportunity to attend a workshop on the most recent findings. NASA's Discovery and New Frontiers Education and Public Outreach program has offered a series of multi-site professional development workshops that have taken place at four physical locations sites: The Johns Hopkins University Applied Physics Laboratory, the Jet Propulsion Laboratory, NASA Johnson Space Center, and the University of Arizona, as well as over the internet. All sites were linked via the Digital Learning Network, on which scientists and educator specialists shared information about their missions and activities. Participants interacted with speakers across the country to learn about Discovery and New Frontiers class missions. The third such annual workshop without walls, 'Challenge of Discovery,' was held on 9 April 2013. Educators from across the country delved into the stories behind some amazing NASA missions, from conception to science results. They learned how scientists, engineers, and mission operators collaborate to meet the challenges of complex missions to assure that science goals are met. As an example of science and engineering coming together, an Instrument Scientist and a Payload Operations Manager from the MESSENGER mission discussed the steps needed to observe Mercury's north polar region, gather data, and finally come to the conclusion that water ice is present in permanently shadowed areas inside polar impact craters. The participating educators were able to work with actual data and experience how the conclusion was reached. This example and others highlight the potential of such workshops to inform and engage educators.

Visualizing Complex Environments in the Geo- and BioSciences

NASA Astrophysics Data System (ADS)

Prabhu, A.; Fox, P. A.; Zhong, H.; Eleish, A.; Ma, X.; Zednik, S.; Morrison, S. M.; Moore, E. K.; Muscente, D.; Meyer, M.; Hazen, R. M.

2017-12-01

Earth's living and non-living components have co-evolved for 4 billion years through numerous positive and negative feedbacks. Earth and life scientists have amassed vast amounts of data in diverse fields related to planetary evolution through deep time-mineralogy and petrology, paleobiology and paleontology, paleotectonics and paleomagnetism, geochemistry and geochrononology, genomics and proteomics, and more. Integrating the data from these complimentary disciplines is very useful in gaining an understanding of the evolution of our planet's environment. The integrated data however, represent many extremely complex environments. In order to gain insights and make discoveries using this data, it is important for us to model and visualize these complex environments. As part of work in understanding the "Co-Evolution of Geo and Biospheres using Data Driven Methodologies," we have developed several visualizations to help represent the information stored in the datasets from complimentary disciplines. These visualizations include 2D and 3D force directed Networks, Chord Diagrams, 3D Klee Diagrams. Evolving Network Diagrams, Skyline Diagrams and Tree Diagrams. Combining these visualizations with the results of machine learning and data analysis methods leads to a powerful way to discover patterns and relationships about the Earth's past and today's changing environment.

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.

E-Learning for Depth in the Semantic Web

ERIC Educational Resources Information Center

Shafrir, Uri; Etkind, Masha

2006-01-01

In this paper, we describe concept parsing algorithms, a novel semantic analysis methodology at the core of a new pedagogy that focuses learners attention on deep comprehension of the conceptual content of learned material. Two new e-learning tools are described in some detail: interactive concept discovery learning and meaning equivalence…

Discovery and Use of Online Learning Resources: Case Study Findings

ERIC Educational Resources Information Center

Recker, Mimi M.; Dorward, James; Nelson, Laurie Miller

2004-01-01

Much recent research and funding have focused on building Internet-based repositories that contain collections of high-quality learning resources, often called "learning objects." Yet little is known about how non-specialist users, in particular teachers, find, access, and use digital learning resources. To address this gap, this article…

Process for Discovery

ERIC Educational Resources Information Center

Miller, Andrew

2017-01-01

Project-based learning is a successful way to engage students in learning in the classroom, and research reports increases in student achievement data. This article asks: If both students and teachers are more engaged when project-based learning is used, why aren't the elements of project-based learning being used to engage teachers in…

Assuring Integrity of Information Utility in Cyber-Learning Formats.

ERIC Educational Resources Information Center

Morrison, James L.; Stein, Linda L.

1999-01-01

Describes a cyber-learning project for the World Wide Web developed by faculty and librarians at the University of Delaware that combined discovery learning with problem-based learning to develop critical thinking and quality management for information. Undergraduates were to find, evaluate, and use information to generate an Internet marketing…

ATLes: the strategic application of Web-based technology to address learning objectives and enhance classroom discussion in a veterinary pathology course.

PubMed

Hines, Stephen A; Collins, Peggy L; Quitadamo, Ian J; Brahler, C Jayne; Knudson, Cameron D; Crouch, Gregory J

2005-01-01

A case-based program called ATLes (Adaptive Teaching and Learning Environments) was designed for use in a systemic pathology course and implemented over a four-year period. Second-year veterinary students working in small collaborative learning groups used the program prior to their weekly pathology laboratory. The goals of ATLes were to better address specific learning objectives in the course (notably the appreciation of pathophysiology), to solve previously identified problems associated with information overload and information sorting that commonly occur as part of discovery-based processes, and to enhance classroom discussion. The program was also designed to model and allow students to practice the problem-oriented approach to clinical cases, thereby enabling them to study pathology in a relevant clinical context. Features included opportunities for students to obtain additional information on the case by requesting specific laboratory tests and/or diagnostic procedures. However, students were also required to justify their diagnostic plans and to provide mechanistic analyses. The use of ATLes met most of these objectives. Student acceptance was high, and students favorably reviewed the online ''Content Links'' that made useful information more readily accessible and level appropriate. Students came to the lab better prepared to engage in an in-depth and high-quality discussion and were better able to connect clinical problems to underlying changes in tissue (lesions). However, many students indicated that the required time on task prior to lab might have been excessive relative to what they thought they learned. The classroom discussion, although improved, was not elevated to the expected level-most likely reflecting other missing elements of the learning environment, including the existing student culture and the students' current discussion skills. This article briefly discusses the lessons learned from ATLes and how similar case-based exercises might be combined with other approaches to enhance and enliven classroom discussions in the veterinary curriculum.

Accelerating Chemical Discovery with Machine Learning: Simulated Evolution of Spin Crossover Complexes with an Artificial Neural Network.

PubMed

Janet, Jon Paul; Chan, Lydia; Kulik, Heather J

2018-03-01

Machine learning (ML) has emerged as a powerful complement to simulation for materials discovery by reducing time for evaluation of energies and properties at accuracy competitive with first-principles methods. We use genetic algorithm (GA) optimization to discover unconventional spin-crossover complexes in combination with efficient scoring from an artificial neural network (ANN) that predicts spin-state splitting of inorganic complexes. We explore a compound space of over 5600 candidate materials derived from eight metal/oxidation state combinations and a 32-ligand pool. We introduce a strategy for error-aware ML-driven discovery by limiting how far the GA travels away from the nearest ANN training points while maximizing property (i.e., spin-splitting) fitness, leading to discovery of 80% of the leads from full chemical space enumeration. Over a 51-complex subset, average unsigned errors (4.5 kcal/mol) are close to the ANN's baseline 3 kcal/mol error. By obtaining leads from the trained ANN within seconds rather than days from a DFT-driven GA, this strategy demonstrates the power of ML for accelerating inorganic material discovery.

Genome-Scale Discovery of Cell Wall Biosynthesis Genes in Populus (JGI Seventh Annual User Meeting 2012: Genomics of Energy and Environment)

ScienceCinema

Muchero, Wellington

2018-01-15

Wellington Muchero from Oak Ridge National Laboratory gives a talk titled "Discovery of Cell Wall Biosynthesis Genes in Populus" at the JGI 7th Annual Users Meeting: Genomics of Energy & Environment Meeting on March 22, 2012 in Walnut Creek, California.

40 CFR 300.300 - Phase I-Discovery or notification.

Code of Federal Regulations, 2010 CFR

2010-07-01

... 40 Protection of Environment 27 2010-07-01 2010-07-01 false Phase I-Discovery or notification. 300.300 Section 300.300 Protection of Environment ENVIRONMENTAL PROTECTION AGENCY (CONTINUED) SUPERFUND... person in charge of a vessel or a facility shall, as soon as he or she has knowledge of any discharge...

Using the iPlant collaborative discovery environment.

PubMed

Oliver, Shannon L; Lenards, Andrew J; Barthelson, Roger A; Merchant, Nirav; McKay, Sheldon J

2013-06-01

The iPlant Collaborative is an academic consortium whose mission is to develop an informatics and social infrastructure to address the "grand challenges" in plant biology. Its cyberinfrastructure supports the computational needs of the research community and facilitates solving major challenges in plant science. The Discovery Environment provides a powerful and rich graphical interface to the iPlant Collaborative cyberinfrastructure by creating an accessible virtual workbench that enables all levels of expertise, ranging from students to traditional biology researchers and computational experts, to explore, analyze, and share their data. By providing access to iPlant's robust data-management system and high-performance computing resources, the Discovery Environment also creates a unified space in which researchers can access scalable tools. Researchers can use available Applications (Apps) to execute analyses on their data, as well as customize or integrate their own tools to better meet the specific needs of their research. These Apps can also be used in workflows that automate more complicated analyses. This module describes how to use the main features of the Discovery Environment, using bioinformatics workflows for high-throughput sequence data as examples. © 2013 by John Wiley & Sons, Inc.

Progress in Biomedical Knowledge Discovery: A 25-year Retrospective

PubMed Central

Sacchi, L.

2016-01-01

Summary Objectives We sought to explore, via a systematic review of the literature, the state of the art of knowledge discovery in biomedical databases as it existed in 1992, and then now, 25 years later, mainly focused on supervised learning. Methods We performed a rigorous systematic search of PubMed and latent Dirichlet allocation to identify themes in the literature and trends in the science of knowledge discovery in and between time periods and compare these trends. We restricted the result set using a bracket of five years previous, such that the 1992 result set was restricted to articles published between 1987 and 1992, and the 2015 set between 2011 and 2015. This was to reflect the current literature available at the time to researchers and others at the target dates of 1992 and 2015. The search term was framed as: Knowledge Discovery OR Data Mining OR Pattern Discovery OR Pattern Recognition, Automated. Results A total 538 and 18,172 documents were retrieved for 1992 and 2015, respectively. The number and type of data sources increased dramatically over the observation period, primarily due to the advent of electronic clinical systems. The period 1992-2015 saw the emergence of new areas of research in knowledge discovery, and the refinement and application of machine learning approaches that were nascent or unknown in 1992. Conclusions Over the 25 years of the observation period, we identified numerous developments that impacted the science of knowledge discovery, including the availability of new forms of data, new machine learning algorithms, and new application domains. Through a bibliometric analysis we examine the striking changes in the availability of highly heterogeneous data resources, the evolution of new algorithmic approaches to knowledge discovery, and we consider from legal, social, and political perspectives possible explanations of the growth of the field. Finally, we reflect on the achievements of the past 25 years to consider what the next 25 years will bring with regard to the availability of even more complex data and to the methods that could be, and are being now developed for the discovery of new knowledge in biomedical data. PMID:27488403

Progress in Biomedical Knowledge Discovery: A 25-year Retrospective.

PubMed

Sacchi, L; Holmes, J H

2016-08-02

We sought to explore, via a systematic review of the literature, the state of the art of knowledge discovery in biomedical databases as it existed in 1992, and then now, 25 years later, mainly focused on supervised learning. We performed a rigorous systematic search of PubMed and latent Dirichlet allocation to identify themes in the literature and trends in the science of knowledge discovery in and between time periods and compare these trends. We restricted the result set using a bracket of five years previous, such that the 1992 result set was restricted to articles published between 1987 and 1992, and the 2015 set between 2011 and 2015. This was to reflect the current literature available at the time to researchers and others at the target dates of 1992 and 2015. The search term was framed as: Knowledge Discovery OR Data Mining OR Pattern Discovery OR Pattern Recognition, Automated. A total 538 and 18,172 documents were retrieved for 1992 and 2015, respectively. The number and type of data sources increased dramatically over the observation period, primarily due to the advent of electronic clinical systems. The period 1992- 2015 saw the emergence of new areas of research in knowledge discovery, and the refinement and application of machine learning approaches that were nascent or unknown in 1992. Over the 25 years of the observation period, we identified numerous developments that impacted the science of knowledge discovery, including the availability of new forms of data, new machine learning algorithms, and new application domains. Through a bibliometric analysis we examine the striking changes in the availability of highly heterogeneous data resources, the evolution of new algorithmic approaches to knowledge discovery, and we consider from legal, social, and political perspectives possible explanations of the growth of the field. Finally, we reflect on the achievements of the past 25 years to consider what the next 25 years will bring with regard to the availability of even more complex data and to the methods that could be, and are being now developed for the discovery of new knowledge in biomedical data.

Open discovery: An integrated live Linux platform of Bioinformatics tools

PubMed Central

Vetrivel, Umashankar; Pilla, Kalabharath

2008-01-01

Historically, live linux distributions for Bioinformatics have paved way for portability of Bioinformatics workbench in a platform independent manner. Moreover, most of the existing live Linux distributions limit their usage to sequence analysis and basic molecular visualization programs and are devoid of data persistence. Hence, open discovery ‐ a live linux distribution has been developed with the capability to perform complex tasks like molecular modeling, docking and molecular dynamics in a swift manner. Furthermore, it is also equipped with complete sequence analysis environment and is capable of running windows executable programs in Linux environment. Open discovery portrays the advanced customizable configuration of fedora, with data persistency accessible via USB drive or DVD. Availability The Open Discovery is distributed free under Academic Free License (AFL) and can be downloaded from http://www.OpenDiscovery.org.in PMID:19238235

50 CFR 221.42 - When must a party supplement or amend information it has previously provided?

Code of Federal Regulations, 2010 CFR

2010-10-01

... PRESCRIPTIONS IN FERC HYDROPOWER LICENSES Hearing Process Prehearing Conferences and Discovery § 221.42 When... promptly supplement or amend any prior response to a discovery request if it learns that the response: (1...

Open-ended Laboratory Investigations in a High School Physics Course: The difficulties and rewards of implementing inquiry-based learning in a physics lab

NASA Astrophysics Data System (ADS)

Szott, Aaron

2014-01-01

often closed-ended. The outcomes are known in advance and students replicate procedures recommended by the teacher. Over the years, I have come to appreciate the great opportunities created by allowing students investigative freedom in physics laboratories. I have realized that a laboratory environment in which students are free to conduct investigations using procedures of their own design can provide them with varied and rich opportunities for discovery. This paper describes what open-ended laboratory investigations have added to my high school physics classes. I will provide several examples of open-ended laboratories and discuss the benefits they conferred on students and teacher alike.

Discovering Mendeleev's Model.

ERIC Educational Resources Information Center

Sterling, Donna

1996-01-01

Presents an activity that introduces the historical developments in science that led to the discovery of the periodic table and lets students experience scientific discovery firsthand. Enables students to learn about patterns among the elements and experience how scientists analyze data to discover patterns and build models. (JRH)

Improving Middle School Students’ Critical Thinking Skills Through Reading Infusion-Loaded Discovery Learning Model in the Science Instruction

NASA Astrophysics Data System (ADS)

Nuryakin; Riandi

2017-02-01

A study has been conducted to obtain a depiction of middle school students’ critical thinking skills improvement through the implementation of reading infusion-loaded discovery learning model in science instruction. A quasi-experimental study with the pretest-posttest control group design was used to engage 55 eighth-year middle school students in Tasikmalaya, which was divided into the experimental and control group respectively were 28 and 27 students. Critical thinking skills were measured using a critical thinking skills test in multiple-choice with reason format questions that administered before and after a given instruction. The test was 28 items encompassing three essential concepts, vibration, waves and auditory senses. The critical thinking skills improvement was determined by using the normalized gain score and statistically analyzed by using Mann-Whitney U test.. The findings showed that the average of students’ critical thinking skills normalized gain score of both groups were 59 and 43, respectively for experimental and control group in the medium category. There were significant differences between both group’s improvement. Thus, the implementation of reading infusion-loaded discovery learning model could further improve middle school students’ critical thinking skills than conventional learning.

Investigating the Link between Self Directed Learning Readiness and Project-Based Learning Outcomes: The Case of International Masters Students in an Engineering Management Course

ERIC Educational Resources Information Center

Stewart, Rodney A.

2007-01-01

Modern learning approaches increasingly have fewer structured learning activities and more self-directed learning tasks guided through consultation with academics. Such tasks are predominately project-/problem-based where the student is required to follow a freely guided road map to self discovery while simultaneously achieving desired learning…

Personalized Learning Objects Recommendation Based on the Semantic-Aware Discovery and the Learner Preference Pattern

ERIC Educational Resources Information Center

Wang, Tzone I; Tsai, Kun Hua; Lee, Ming Che; Chiu, Ti Kai

2007-01-01

With vigorous development of the Internet, especially the web page interaction technology, distant E-learning has become more and more realistic and popular. Digital courses may consist of many learning units or learning objects and, currently, many learning objects are created according to SCORM standard. It can be seen that, in the near future,…

How Are Television Networks Involved in Distance Learning?

ERIC Educational Resources Information Center

Bucher, Katherine

1996-01-01

Reviews the involvement of various television networks in distance learning, including public broadcasting stations, Cable in the Classroom, Arts and Entertainment Network, Black Entertainment Television, C-SPAN, CNN (Cable News Network), The Discovery Channel, The Learning Channel, Mind Extension University, The Weather Channel, National Teacher…

A Piagetian Learning Cycle for Introductory Chemical Kinetics.

ERIC Educational Resources Information Center

Batt, Russell H.

1980-01-01

Described is a Piagetian learning cycle based on Monte Carlo modeling of several simple reaction mechanisms. Included are descriptions of learning cycle phases (exploration, invention, and discovery) and four BASIC-PLUS computer programs to be used in the explanation of chemical reacting systems. (Author/DS)

Comparison of Deep Learning With Multiple Machine Learning Methods and Metrics Using Diverse Drug Discovery Data Sets.

PubMed

Korotcov, Alexandru; Tkachenko, Valery; Russo, Daniel P; Ekins, Sean

2017-12-04

Machine learning methods have been applied to many data sets in pharmaceutical research for several decades. The relative ease and availability of fingerprint type molecular descriptors paired with Bayesian methods resulted in the widespread use of this approach for a diverse array of end points relevant to drug discovery. Deep learning is the latest machine learning algorithm attracting attention for many of pharmaceutical applications from docking to virtual screening. Deep learning is based on an artificial neural network with multiple hidden layers and has found considerable traction for many artificial intelligence applications. We have previously suggested the need for a comparison of different machine learning methods with deep learning across an array of varying data sets that is applicable to pharmaceutical research. End points relevant to pharmaceutical research include absorption, distribution, metabolism, excretion, and toxicity (ADME/Tox) properties, as well as activity against pathogens and drug discovery data sets. In this study, we have used data sets for solubility, probe-likeness, hERG, KCNQ1, bubonic plague, Chagas, tuberculosis, and malaria to compare different machine learning methods using FCFP6 fingerprints. These data sets represent whole cell screens, individual proteins, physicochemical properties as well as a data set with a complex end point. Our aim was to assess whether deep learning offered any improvement in testing when assessed using an array of metrics including AUC, F1 score, Cohen's kappa, Matthews correlation coefficient and others. Based on ranked normalized scores for the metrics or data sets Deep Neural Networks (DNN) ranked higher than SVM, which in turn was ranked higher than all the other machine learning methods. Visualizing these properties for training and test sets using radar type plots indicates when models are inferior or perhaps over trained. These results also suggest the need for assessing deep learning further using multiple metrics with much larger scale comparisons, prospective testing as well as assessment of different fingerprints and DNN architectures beyond those used.

Children Studying the Sea.

ERIC Educational Resources Information Center

Hoile, Tim

1999-01-01

Describes the Marine Discovery Center (MDC) which emphasizes conservation of the marine environment, adaptations and features of various creatures, and the discovery of marine creatures in their habitat. (CCM)

Bringing your tools to CyVerse Discovery Environment using Docker

PubMed Central

Devisetty, Upendra Kumar; Kennedy, Kathleen; Sarando, Paul; Merchant, Nirav; Lyons, Eric

2016-01-01

Docker has become a very popular container-based virtualization platform for software distribution that has revolutionized the way in which scientific software and software dependencies (software stacks) can be packaged, distributed, and deployed. Docker makes the complex and time-consuming installation procedures needed for scientific software a one-time process. Because it enables platform-independent installation, versioning of software environments, and easy redeployment and reproducibility, Docker is an ideal candidate for the deployment of identical software stacks on different compute environments such as XSEDE and Amazon AWS. CyVerse’s Discovery Environment also uses Docker for integrating its powerful, community-recommended software tools into CyVerse’s production environment for public use. This paper will help users bring their tools into CyVerse Discovery Environment (DE) which will not only allows users to integrate their tools with relative ease compared to the earlier method of tool deployment in DE but will also help users to share their apps with collaborators and release them for public use. PMID:27803802

Bringing your tools to CyVerse Discovery Environment using Docker.

PubMed

Devisetty, Upendra Kumar; Kennedy, Kathleen; Sarando, Paul; Merchant, Nirav; Lyons, Eric

2016-01-01

Docker has become a very popular container-based virtualization platform for software distribution that has revolutionized the way in which scientific software and software dependencies (software stacks) can be packaged, distributed, and deployed. Docker makes the complex and time-consuming installation procedures needed for scientific software a one-time process. Because it enables platform-independent installation, versioning of software environments, and easy redeployment and reproducibility, Docker is an ideal candidate for the deployment of identical software stacks on different compute environments such as XSEDE and Amazon AWS. CyVerse's Discovery Environment also uses Docker for integrating its powerful, community-recommended software tools into CyVerse's production environment for public use. This paper will help users bring their tools into CyVerse Discovery Environment (DE) which will not only allows users to integrate their tools with relative ease compared to the earlier method of tool deployment in DE but will also help users to share their apps with collaborators and release them for public use.

40 CFR 22.52 - Information exchange and discovery.

Code of Federal Regulations, 2010 CFR

2010-07-01

... Procedure Act § 22.52 Information exchange and discovery. Respondent's information exchange pursuant to § 22.19(a) shall include information on any economic benefit resulting from any activity or failure to act... 40 Protection of Environment 1 2010-07-01 2010-07-01 false Information exchange and discovery. 22...

Video Game Learning Dynamics: Actionable Measures of Multidimensional Learning Trajectories

ERIC Educational Resources Information Center

Reese, Debbie Denise; Tabachnick, Barbara G.; Kosko, Robert E.

2015-01-01

Valid, accessible, reusable methods for instructional video game design and embedded assessment can provide actionable information enhancing individual and collective achievement. Cyberlearning through game-based, metaphor-enhanced learning objects (CyGaMEs) design and embedded assessment quantify player behavior to study knowledge discovery and…

Career Activity File K-12: School-Based Enterprise.

ERIC Educational Resources Information Center

2000

School-Based Enterprises or SBEs provide work-based learning opportunities to students in communities lacking business and industry involvement. SBEs promote discovery learning and student responsibility in the learning process. They expose students to creative thinking, problem solving, planning and organizational skills, and teamwork. SBEs help…

How Effective Is Instructional Support for Learning with Computer Simulations?

ERIC Educational Resources Information Center

Eckhardt, Marc; Urhahne, Detlef; Conrad, Olaf; Harms, Ute

2013-01-01

The study examined the effects of two different instructional interventions as support for scientific discovery learning using computer simulations. In two well-known categories of difficulty, data interpretation and self-regulation, instructional interventions for learning with computer simulations on the topic "ecosystem water" were developed…

INDEPENDENT AND GROUP LEARNING.

ERIC Educational Resources Information Center

DICKINSON, MARIE B.

IN CONTRAST TO THE TRADITIONAL EMPHASES ON ROTE LEARNING AND FACT ACCUMULATION, RECENT TRENDS EMERGING FROM EDUCATIONAL RESEARCH STRESS THE DEVELOPMENT OF THINKING PROCESSES SUCH AS THE ABILITY TO REASON ABSTRACTLY AND TO SYNTHESIZE. CHILDREN WORKING INDEPENDENTLY OR IN GROUPS MOVE THROUGH A DISCOVERY LEARNING CURRICULUM IN WHICH THE TEACHER…

Describing Online Learning Content to Facilitate Resource Discovery and Sharing: The Development of the RU LOM Core

ERIC Educational Resources Information Center

Krull, G. E.; Mallinson, B. J.; Sewry, D. A.

2006-01-01

The development of Internet technologies has the ability to provide a new era of easily accessible and personalised learning, facilitated through the flexible deployment of small, reusable pieces of digital learning content over networks. Higher education institutions can share and reuse digital learning resources in order to improve their…

Shades of Pink: Preschoolers Make Meaning in a Reggio-Inspired Classroom

ERIC Educational Resources Information Center

Kim, Bo Sun

2012-01-01

Shades of Pink study describes how six preschoolers and their teacher engaged in a collaborative learning project through which they learned about the shades of a color--in this case, pink. As the children learned through experimenting and discussing their theories, they represented ideas using art as a tool for discovery and learning. The study…

Scientific Assistant Virtual Laboratory (SAVL)

NASA Astrophysics Data System (ADS)

Alaghband, Gita; Fardi, Hamid; Gnabasik, David

2007-03-01

The Scientific Assistant Virtual Laboratory (SAVL) is a scientific discovery environment, an interactive simulated virtual laboratory, for learning physics and mathematics. The purpose of this computer-assisted intervention is to improve middle and high school student interest, insight and scores in physics and mathematics. SAVL develops scientific and mathematical imagination in a visual, symbolic, and experimental simulation environment. It directly addresses the issues of scientific and technological competency by providing critical thinking training through integrated modules. This on-going research provides a virtual laboratory environment in which the student directs the building of the experiment rather than observing a packaged simulation. SAVL: * Engages the persistent interest of young minds in physics and math by visually linking simulation objects and events with mathematical relations. * Teaches integrated concepts by the hands-on exploration and focused visualization of classic physics experiments within software. * Systematically and uniformly assesses and scores students by their ability to answer their own questions within the context of a Master Question Network. We will demonstrate how the Master Question Network uses polymorphic interfaces and C# lambda expressions to manage simulation objects.

Scientific Discoveries: What Is Required for Lasting Impact.

PubMed

Lømo, Terje

2016-01-01

I have been involved in two scientific discoveries of some impact. One is the discovery of long-term potentiation (LTP), the phenomenon that brief, high-frequency impulse activity at synapses in the brain can lead to long-lasting increases in their efficiency of transmission. This finding demonstrated that synapses are plastic, a property thought to be necessary for learning and memory. The other discovery is that nerve-evoked muscle impulse activity, rather than putative trophic factors, controls the properties of muscle fibers. Here I describe how these two discoveries were made, the unexpected difficulties of reproducing the first discovery, and the controversies that followed the second discovery. I discuss why the first discovery took many years to become generally recognized, whereas the second caused an immediate sensation and entered textbooks and major reviews but is now largely forgotten. In the long run, discovering a new phenomenon has greater impact than falsifying a popular hypothesis.

Cognitive Neuroscience Discoveries and Educational Practices

ERIC Educational Resources Information Center

Sylwester, Robert

2006-01-01

In this article, the author describes seven movement-related areas of cognitive neuroscience research that will play key roles in shifting the current behavioral orientation of teaching and learning to an orientation that also incorporates cognitive neuroscience discoveries. These areas of brain research include: (1) mirroring system; (2) plastic…

The Parallelism between Scientists' and Students' Resistance to New Scientific Ideas.

ERIC Educational Resources Information Center

Campanario, Juan Miguel

2002-01-01

Compares resistance by scientists to new ideas in scientific discovery with students' resistance to conceptual change in scientific learning. Studies the resistance by students to abandoning their misconceptions concerning scientific topics and the resistance by scientists to scientific discovery. (Contains 64 references.) (Author/YDS)

Doors to Discovery [TM]. WWC Intervention Report

ERIC Educational Resources Information Center

What Works Clearinghouse, 2009

2009-01-01

Doors to Discovery[TM], an early childhood curriculum, focuses on the development of children's vocabulary and expressive and receptive language through a learning process called "shared literacy," where adults and children work together to develop literacy-related skills. Literacy activities, organized into thematic units, encourage children's…

Historical milestones and discoveries that shaped the toxicology sciences.

PubMed

Hayes, Antoinette N; Gilbert, Steven G

2009-01-01

Knowledge of the toxic and healing properties of plants, animals, and minerals has shaped civilization for millennia. The foundations of modern toxicology are built upon the significant milestones and discoveries of serendipity and crude experimentation. Throughout the ages, toxicological science has provided information that has shaped and guided society. This chapter examines the development of the discipline of toxicology and its influence on civilization by highlighting significant milestones and discoveries related to toxicology. The examples shed light on the beginnings of toxicology, as well as examine lessons learned and re-learned. This chapter also examines how toxicology and the toxicologist have interacted with other scientific and cultural disciplines, including religion, politics, and the government. Toxicology has evolved to a true scientific discipline with its own dedicated scientists, educational institutes, sub-disciplines, professional societies, and journals. It now stands as its own entity while traversing such fields as chemistry, physiology, pharmacology, and molecular biology. We invite you to join us on a path of discovery and to offer our suggestions as to what are the most significant milestones and discoveries in toxicology. Additional information is available on the history section of Toxipedia (www.toxipedia.org).

Metacognitive components in smart learning environment

NASA Astrophysics Data System (ADS)

Sumadyo, M.; Santoso, H. B.; Sensuse, D. I.

2018-03-01

Metacognitive ability in digital-based learning process helps students in achieving learning goals. So that digital-based learning environment should make the metacognitive component as a facility that must be equipped. Smart Learning Environment is the concept of a learning environment that certainly has more advanced components than just a digital learning environment. This study examines the metacognitive component of the smart learning environment to support the learning process. A review of the metacognitive literature was conducted to examine the components involved in metacognitive learning strategies. Review is also conducted on the results of study smart learning environment, ranging from design to context in building smart learning. Metacognitive learning strategies certainly require the support of adaptable, responsive and personalize learning environments in accordance with the principles of smart learning. The current study proposed the role of metacognitive component in smart learning environment, which is useful as the basis of research in building environment in smart learning.

The Psychophysics of Algebra Expertise: Mathematics Perceptual Learning Interventions Produce Durable Encoding Changes

ERIC Educational Resources Information Center

Bufford, Carolyn A.; Mettler, Everett; Geller, Emma H.; Kellman, Philip J.

2014-01-01

Mathematics requires thinking but also pattern recognition. Recent research indicates that perceptual learning (PL) interventions facilitate discovery of structure and recognition of patterns in mathematical domains, as assessed by tests of mathematical competence. Here we sought direct evidence that a brief perceptual learning module (PLM)…

Globalization of Knowledge Discovery and Information Retrieval in Teaching and Learning

ERIC Educational Resources Information Center

Zaidel, Mark; Guerrero, Osiris

2008-01-01

Developments in communication and information technologies in the last decade have had a significant impact on instructional and learning activities. For many students and educators, the Internet became the significant medium for sharing instruction, learning and communication. Access to knowledge beyond boundaries and cultures has an impact on…

Teacher-Student Communication Games: Some Experiments on Instruction.

ERIC Educational Resources Information Center

Olson, David R.; And Others

This inquiry began with the observation that learning from instruction is radically more efficient for obtaining information than learning by discovery. A series of seven experiments was conducted to determine some of the factors involved in learning from verbal instruction. The perspective adopted was that of communication theory, in which the…

The Discovery of Personal Meaning: Affective Factors in Learning.

ERIC Educational Resources Information Center

Gorrell, Jeffrey

Learner-centered principles espoused by the American Psychological Association (APA) built on research of the last three decades suggest that learning does not simply entail coordinated cognitive processes. These 12 principles portray factors associated with learning as essential parts of the portrayal of learners as active creators of their own…

The Biological Basis of Learning and Individuality.

ERIC Educational Resources Information Center

Kandel, Eric R.; Hawkins, Robert D.

1992-01-01

Describes the biological basis of learning and individuality. Presents an overview of recent discoveries that suggest learning engages a simple set of rules that modify the strength of connection between neurons in the brain. The changes are cited as playing an important role in making each individual unique. (MCO)

Writing-to-Learn Activities to Provoke Deeper Learning in Calculus

ERIC Educational Resources Information Center

Jaafar, Reem

2016-01-01

For students with little experience in mathematical thinking and conceptualization, writing-to-learn activities (WTL) can be particularly effective in promoting discovery and understanding. For community college students embarking on a first calculus course in particular, writing activities can help facilitate the transition from an "apply…

A Guided Discovery Approach for Learning Glycolysis.

ERIC Educational Resources Information Center

Schultz, Emeric

1997-01-01

Argues that more attention should be given to teaching students how to learn the rudiments of specific metabolic pathways. This approach describes a unique way of learning the glycolytic pathway in stepwise fashion. The pedagogy involves clear rote components that are connected to a set of generalizations that develop and enhance important…

School Garden Wizard: Home

Science.gov Websites

! Gardening and plant-based learning open a door to discovery of the living world. It stimulates even as it achieve learning goals in ways that are recommended by the National Science Standards and most state and Learning Inspiring Stories A Teacher's Perspective Gardening Tools Seasonal Considerations Special Needs

Learned Helplessness: A Theory for the Age of Personal Control.

ERIC Educational Resources Information Center

Peterson, Christopher; And Others

Experiences with uncontrollable events may lead to the expectation that future events will elude control, resulting in disruptions in motivation, emotion, and learning. This text explores this phenomenon, termed learned helplessness, tracking it from its discovery to its entrenchment in the psychological canon. The volume summarizes and integrates…

Mechanisms of Hierarchical Reinforcement Learning in Corticostriatal Circuits 1: Computational Analysis

PubMed Central

Badre, David

2012-01-01

Growing evidence suggests that the prefrontal cortex (PFC) is organized hierarchically, with more anterior regions having increasingly abstract representations. How does this organization support hierarchical cognitive control and the rapid discovery of abstract action rules? We present computational models at different levels of description. A neural circuit model simulates interacting corticostriatal circuits organized hierarchically. In each circuit, the basal ganglia gate frontal actions, with some striatal units gating the inputs to PFC and others gating the outputs to influence response selection. Learning at all of these levels is accomplished via dopaminergic reward prediction error signals in each corticostriatal circuit. This functionality allows the system to exhibit conditional if–then hypothesis testing and to learn rapidly in environments with hierarchical structure. We also develop a hybrid Bayesian-reinforcement learning mixture of experts (MoE) model, which can estimate the most likely hypothesis state of individual participants based on their observed sequence of choices and rewards. This model yields accurate probabilistic estimates about which hypotheses are attended by manipulating attentional states in the generative neural model and recovering them with the MoE model. This 2-pronged modeling approach leads to multiple quantitative predictions that are tested with functional magnetic resonance imaging in the companion paper. PMID:21693490

Using machine learning to identify factors that govern amorphization of irradiated pyrochlores

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

Pilania, Ghanshyam; Whittle, Karl R.; Jiang, Chao

Structure–property relationships are a key materials science concept that enables the design of new materials. In the case of materials for application in radiation environments, correlating radiation tolerance with fundamental structural features of a material enables materials discovery. Here, we use a machine learning model to examine the factors that govern amorphization resistance in the complex oxide pyrochlore (A 2B 2O 7) in a regime in which amorphization occurs as a consequence of defect accumulation. We examine the fidelity of predictions based on cation radii and electronegativities, the oxygen positional parameter, and the energetics of disordering and amorphizing the material.more » No one factor alone adequately predicts amorphization resistance. We find that when multiple families of pyrochlores (with different B cations) are considered, radii and electronegativities provide the best prediction, but when the machine learning model is restricted to only the B = Ti pyrochlores, the energetics of disordering and amorphization are critical factors. We discuss how these static quantities provide insight into an inherently kinetic property such as amorphization resistance at finite temperature. Lastly, this work provides new insight into the factors that govern the amorphization susceptibility and highlights the ability of machine learning approaches to generate that insight.« less

Using machine learning to identify factors that govern amorphization of irradiated pyrochlores

DOE PAGES

Pilania, Ghanshyam; Whittle, Karl R.; Jiang, Chao; ...

2017-02-10

Structure–property relationships are a key materials science concept that enables the design of new materials. In the case of materials for application in radiation environments, correlating radiation tolerance with fundamental structural features of a material enables materials discovery. Here, we use a machine learning model to examine the factors that govern amorphization resistance in the complex oxide pyrochlore (A 2B 2O 7) in a regime in which amorphization occurs as a consequence of defect accumulation. We examine the fidelity of predictions based on cation radii and electronegativities, the oxygen positional parameter, and the energetics of disordering and amorphizing the material.more » No one factor alone adequately predicts amorphization resistance. We find that when multiple families of pyrochlores (with different B cations) are considered, radii and electronegativities provide the best prediction, but when the machine learning model is restricted to only the B = Ti pyrochlores, the energetics of disordering and amorphization are critical factors. We discuss how these static quantities provide insight into an inherently kinetic property such as amorphization resistance at finite temperature. Lastly, this work provides new insight into the factors that govern the amorphization susceptibility and highlights the ability of machine learning approaches to generate that insight.« less

Primary Care Practice Development: A Relationship-Centered Approach

PubMed Central

Miller, William L.; Crabtree, Benjamin F.; Nutting, Paul A.; Stange, Kurt C.; Jaén, Carlos Roberto

2010-01-01

PURPOSE Numerous primary care practice development efforts, many related to the patient-centered medical home (PCMH), are emerging across the United States with few guides available to inform them. This article presents a relationship-centered practice development approach to understand practice and to aid in fostering practice development to advance key attributes of primary care that include access to first-contact care, comprehensive care, coordination of care, and a personal relationship over time. METHODS Informed by complexity theory and relational theories of organizational learning, we built on discoveries from the American Academy of Family Physicians’ National Demonstration Project (NDP) and 15 years of research to understand and improve primary care practice. RESULTS Primary care practices can fruitfully be understood as complex adaptive systems consisting of a core (a practice’s key resources, organizational structure, and functional processes), adaptive reserve (practice features that enhance resilience, such as relationships), and attentiveness to the local environment. The effectiveness of these attributes represents the practice’s internal capability. With adequate motivation, healthy, thriving practices advance along a pathway of slow, continuous developmental change with occasional rapid periods of transformation as they evolve better fits with their environment. Practice development is enhanced through systematically using strategies that involve setting direction and boundaries, implementing sensing systems, focusing on creative tensions, and fostering learning conversations. CONCLUSIONS Successful practice development begins with changes that strengthen practices’ core, build adaptive reserve, and expand attentiveness to the local environment. Development progresses toward transformation through enhancing primary care attributes. PMID:20530396

Leadership Decision Making and the Use of Data

ERIC Educational Resources Information Center

Guerra-Lopez, Ingrid; Blake, Anne M.

2011-01-01

Intelligence gathering, or data collection, is a preliminary and critical stage of decision making. Two key approaches to intelligence gathering are "discovery" and "idea imposition." The discovery approach allows us to learn about possibilities by gathering intelligence in order to identify and weigh options. The idea imposition approach limits…

The Discovery Approach to Mathematics.

ERIC Educational Resources Information Center

Wilson, Lois Fair

Summarized are presentations made at a one-day teachers' workshop organized by the Bicultural Socialization Project to discuss the materials to be used in mathematics learning centers in the project classrooms. The first chapter discusses the basic philosophy, whereby pupils are to be encouraged to enjoy the discovery of mathematical relationships…

Preoperative learning goals set by surgical residents and faculty.

PubMed

Pernar, Luise I M; Breen, Elizabeth; Ashley, Stanley W; Peyre, Sarah E

2011-09-01

The operating room (OR) remains the main teaching venue for surgical trainees. The OR is considered a pure-discovery learning environment; the downsides of this can be putatively overcome when faculty and trainee arrive at a shared understanding of learning. This study aimed to better understand preoperative learning goals to identify areas of commonalities and potential barrier to intraoperative teaching. Brief, structured preoperative interviews were conducted outside the OR with the resident and faculty member who were scheduled to operate together. Answers were analyzed and grouped using grounded theory. Twenty-seven resident-faculty pairs were interviewed. Nine residents (33.3%) were junior (PGY 1 and 2) and 18 (66.7%) were senior (PGY 3 through 5). Learning goal categories that emerged from the response analysis were anatomy, basic and advanced surgical skills, general and specific procedural tasks, technical autonomy, and pre-, intra-, and postoperative considerations. Residents articulated fewer learning goals than faculty (1.5 versus 2.4; P = 0.024). The most frequently identified learning goal by both groups was one classifiable under general procedural tasks; the greatest divergence was seen regarding perioperative considerations, which were identified frequently by faculty members but rarely by residents. Faculty articulate significantly more learning goals for the residents they will operate with than residents articulate for themselves. Our data suggest that residents and faculty align on some learning goals for the OR but residents tend to be more limited, focusing predominantly on technical aspects of the operation. Faculty members tend to hold a broader view of the learning potential of the OR. These discrepancies may present barriers to effective intraoperative teaching. Copyright © 2011 Elsevier Inc. All rights reserved.

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.

The Heuristic Method, Precursor of Guided Inquiry: Henry Armstrong and British Girls' Schools, 1890-1920

ERIC Educational Resources Information Center

Rayner-Canham, Geoff; Rayner-Canham, Marelene

2015-01-01

Though guided-inquiry learning, discovery learning, student-centered learning, and problem-based learning are commonly believed to be recent new approaches to the teaching of chemistry, in fact, the concept dates back to the late 19th century. Here, we will show that it was the British chemist, Henry Armstrong, who pioneered this technique,…

University Research Initiative Research Program Summaries

DTIC Science & Technology

1987-06-01

application to intelligent tutoring systems (John Anderson), o Autonomous learning systems (Jaime Carbonell), o Learning algorithms for parallel processing...test them. The primary project will be: o Learning mechanisms in scientific discovery (Herbert Simon). Tutoring systems. These projects are aimed at...near-term results. They 19 will produce tutors for training specific subject matter areas. These projects will push theories of learning forward by

Using an improved association rules mining optimization algorithm in web-based mobile-learning system

NASA Astrophysics Data System (ADS)

Huang, Yin; Chen, Jianhua; Xiong, Shaojun

2009-07-01

Mobile-Learning (M-learning) makes many learners get the advantages of both traditional learning and E-learning. Currently, Web-based Mobile-Learning Systems have created many new ways and defined new relationships between educators and learners. Association rule mining is one of the most important fields in data mining and knowledge discovery in databases. Rules explosion is a serious problem which causes great concerns, as conventional mining algorithms often produce too many rules for decision makers to digest. Since Web-based Mobile-Learning System collects vast amounts of student profile data, data mining and knowledge discovery techniques can be applied to find interesting relationships between attributes of learners, assessments, the solution strategies adopted by learners and so on. Therefore ,this paper focus on a new data-mining algorithm, combined with the advantages of genetic algorithm and simulated annealing algorithm , called ARGSA(Association rules based on an improved Genetic Simulated Annealing Algorithm), to mine the association rules. This paper first takes advantage of the Parallel Genetic Algorithm and Simulated Algorithm designed specifically for discovering association rules. Moreover, the analysis and experiment are also made to show the proposed method is superior to the Apriori algorithm in this Mobile-Learning system.

The Human Mind As General Problem Solver

NASA Astrophysics Data System (ADS)

Gurr, Henry

2011-10-01

Since leaving U Cal Irvine Neutrino Research, I have been a University Physics Teacher, and an Informal Researcher Of Human Functionality. My talk will share what I discovered about the best ways to learn, many of which are regularities that are to be expected from the Neuronal Network Properties announced in the publications of physicist John Joseph Hopfield. Hopfield's Model of mammalian brain-body, provides solid instructive understanding of how best Learn, Solve Problems, Live! With it we understand many otherwise puzzling features of our intellect! Examples Why 1) Analogies and metaphors powerful in class instruction, ditto poems. 2) Best learning done in physical (Hands-On) situations with tight immediate dynamical feedback such as seen in learning to ride bike, drive car, speak language, etc. 3) Some of the best learning happens in seeming random exploration, bump around, trial and error. 4) Scientific discoveries happen, with no apparent effort, at odd moments. 5) Important discoveries DEPEND on considerable frustrating effort, then Flash of Insight AHA EURIKA.

Data mining and education.

PubMed

Koedinger, Kenneth R; D'Mello, Sidney; McLaughlin, Elizabeth A; Pardos, Zachary A; Rosé, Carolyn P

2015-01-01

An emerging field of educational data mining (EDM) is building on and contributing to a wide variety of disciplines through analysis of data coming from various educational technologies. EDM researchers are addressing questions of cognition, metacognition, motivation, affect, language, social discourse, etc. using data from intelligent tutoring systems, massive open online courses, educational games and simulations, and discussion forums. The data include detailed action and timing logs of student interactions in user interfaces such as graded responses to questions or essays, steps in rich problem solving environments, games or simulations, discussion forum posts, or chat dialogs. They might also include external sensors such as eye tracking, facial expression, body movement, etc. We review how EDM has addressed the research questions that surround the psychology of learning with an emphasis on assessment, transfer of learning and model discovery, the role of affect, motivation and metacognition on learning, and analysis of language data and collaborative learning. For example, we discuss (1) how different statistical assessment methods were used in a data mining competition to improve prediction of student responses to intelligent tutor tasks, (2) how better cognitive models can be discovered from data and used to improve instruction, (3) how data-driven models of student affect can be used to focus discussion in a dialog-based tutoring system, and (4) how machine learning techniques applied to discussion data can be used to produce automated agents that support student learning as they collaborate in a chat room or a discussion board. © 2015 John Wiley & Sons, Ltd.

Validity and Practitality of Acid-Base Module Based on Guided Discovery Learning for Senior High School

NASA Astrophysics Data System (ADS)

Yerimadesi; Bayharti; Jannah, S. M.; Lufri; Festiyed; Kiram, Y.

2018-04-01

This Research and Development(R&D) aims to produce guided discovery learning based module on topic of acid-base and determine its validity and practicality in learning. Module development used Four D (4-D) model (define, design, develop and disseminate).This research was performed until development stage. Research’s instruments were validity and practicality questionnaires. Module was validated by five experts (three chemistry lecturers of Universitas Negeri Padang and two chemistry teachers of SMAN 9 Padang). Practicality test was done by two chemistry teachers and 30 students of SMAN 9 Padang. Kappa Cohen’s was used to analyze validity and practicality. The average moment kappa was 0.86 for validity and those for practicality were 0.85 by teachers and 0.76 by students revealing high category. It can be concluded that validity and practicality was proven for high school chemistry learning.

Discovery Planetary Mission Operations Concepts

NASA Technical Reports Server (NTRS)

Coffin, R.

1994-01-01

The NASA Discovery Program of small planetary missions will provide opportunities to continue scientific exploration of the solar system in today's cost-constrained environment. Using a multidisciplinary team, JPL has developed plans to provide mission operations within the financial parameters established by the Discovery Program. This paper describes experiences and methods that show promise of allowing the Discovery Missions to operate within the program cost constraints while maintaining low mission risk, high data quality, and reponsive operations.

Innovations in Undergraduate Chemical Biology Education.

PubMed

Van Dyke, Aaron R; Gatazka, Daniel H; Hanania, Mariah M

2018-01-19

Chemical biology derives intellectual vitality from its scientific interface: applying chemical strategies and perspectives to biological questions. There is a growing need for chemical biologists to synergistically integrate their research programs with their educational activities to become holistic teacher-scholars. This review examines how course-based undergraduate research experiences (CUREs) are an innovative method to achieve this integration. Because CUREs are course-based, the review first offers strategies for creating a student-centered learning environment, which can improve students' outcomes. Exemplars of CUREs in chemical biology are then presented and organized to illustrate the five defining characteristics of CUREs: significance, scientific practices, discovery, collaboration, and iteration. Finally, strategies to overcome common barriers in CUREs are considered as well as future innovations in chemical biology education.

Enablers of innovation in digital public health surveillance: lessons from Flutracking.

PubMed

Dalton, Craig B

2017-05-01

Opportunities for digital innovation in public health surveillance have never been greater. Social media data streams, Open Data initiatives, mHealth geotagged data, and the 'internet of things' are ripe for development. To embrace these opportunities we need to provide public health professionals with environments that support experimentation with new technology. Innovative practitioners will lead discovery, adaption, trialling and deployment of new technological solutions mostly developed outside their organisation. To enhance innovation agencies will need to learn from 'startup culture' and the practices of large organisations that ring fence innovative teams to protect them and allow them to 'break rules', 'fail fast', and innovate. © The Author 2017. Published by Oxford University Press on behalf of Royal Society of Tropical Medicine and Hygiene.

Concept Formation in Scientific Knowledge Discovery from a Constructivist View

NASA Astrophysics Data System (ADS)

Peng, Wei; Gero, John S.

The central goal of scientific knowledge discovery is to learn cause-effect relationships among natural phenomena presented as variables and the consequences their interactions. Scientific knowledge is normally expressed as scientific taxonomies and qualitative and quantitative laws [1]. This type of knowledge represents intrinsic regularities of the observed phenomena that can be used to explain and predict behaviors of the phenomena. It is a generalization that is abstracted and externalized from a set of contexts and applicable to a broader scope. Scientific knowledge is a type of third-person knowledge, i.e., knowledge that independent of a specific enquirer. Artificial intelligence approaches, particularly data mining algorithms that are used to identify meaningful patterns from large data sets, are approaches that aim to facilitate the knowledge discovery process [2]. A broad spectrum of algorithms has been developed in addressing classification, associative learning, and clustering problems. However, their linkages to people who use them have not been adequately explored. Issues in relation to supporting the interpretation of the patterns, the application of prior knowledge to the data mining process and addressing user interactions remain challenges for building knowledge discovery tools [3]. As a consequence, scientists rely on their experience to formulate problems, evaluate hypotheses, reason about untraceable factors and derive new problems. This type of knowledge which they have developed during their career is called “first-person” knowledge. The formation of scientific knowledge (third-person knowledge) is highly influenced by the enquirer’s first-person knowledge construct, which is a result of his or her interactions with the environment. There have been attempts to craft automatic knowledge discovery tools but these systems are limited in their capabilities to handle the dynamics of personal experience. There are now trends in developing approaches to assist scientists applying their expertise to model formation, simulation, and prediction in various domains [4], [5]. On the other hand, first-person knowledge becomes third-person theory only if it proves general by evidence and is acknowledged by a scientific community. Researchers start to focus on building interactive cooperation platforms [1] to accommodate different views into the knowledge discovery process. There are some fundamental questions in relation to scientific knowledge development. What aremajor components for knowledge construction and how do people construct their knowledge? How is this personal construct assimilated and accommodated into a scientific paradigm? How can one design a computational system to facilitate these processes? This chapter does not attempt to answer all these questions but serves as a basis to foster thinking along this line. A brief literature review about how people develop their knowledge is carried out through a constructivist view. A hydrological modeling scenario is presented to elucidate the approach.

Concept Formation in Scientific Knowledge Discovery from a Constructivist View

NASA Astrophysics Data System (ADS)

Peng, Wei; Gero, John S.

The central goal of scientific knowledge discovery is to learn cause-effect relationships among natural phenomena presented as variables and the consequences their interactions. Scientific knowledge is normally expressed as scientific taxonomies and qualitative and quantitative laws [1]. This type of knowledge represents intrinsic regularities of the observed phenomena that can be used to explain and predict behaviors of the phenomena. It is a generalization that is abstracted and externalized from a set of contexts and applicable to a broader scope. Scientific knowledge is a type of third-person knowledge, i.e., knowledge that independent of a specific enquirer. Artificial intelligence approaches, particularly data mining algorithms that are used to identify meaningful patterns from large data sets, are approaches that aim to facilitate the knowledge discovery process [2]. A broad spectrum of algorithms has been developed in addressing classification, associative learning, and clustering problems. However, their linkages to people who use them have not been adequately explored. Issues in relation to supporting the interpretation of the patterns, the application of prior knowledge to the data mining process and addressing user interactions remain challenges for building knowledge discovery tools [3]. As a consequence, scientists rely on their experience to formulate problems, evaluate hypotheses, reason about untraceable factors and derive new problems. This type of knowledge which they have developed during their career is called "first-person" knowledge. The formation of scientific knowledge (third-person knowledge) is highly influenced by the enquirer's first-person knowledge construct, which is a result of his or her interactions with the environment. There have been attempts to craft automatic knowledge discovery tools but these systems are limited in their capabilities to handle the dynamics of personal experience. There are now trends in developing approaches to assist scientists applying their expertise to model formation, simulation, and prediction in various domains [4], [5]. On the other hand, first-person knowledge becomes third-person theory only if it proves general by evidence and is acknowledged by a scientific community. Researchers start to focus on building interactive cooperation platforms [1] to accommodate different views into the knowledge discovery process. There are some fundamental questions in relation to scientific knowledge development. What aremajor components for knowledge construction and how do people construct their knowledge? How is this personal construct assimilated and accommodated into a scientific paradigm? How can one design a computational system to facilitate these processes? This chapter does not attempt to answer all these questions but serves as a basis to foster thinking along this line. A brief literature review about how people develop their knowledge is carried out through a constructivist view. A hydrological modeling scenario is presented to elucidate the approach.

Enhancing the Impact of NASA Astrophysics Education and Public Outreach: Community Collaborations

NASA Astrophysics Data System (ADS)

Smith, Denise A.; Lawton, B. L.; Bartolone, L.; Schultz, G. R.; Blair, W. P.; Astrophysics E/PO Community, NASA; NASA Astrophysics Forum Team

2013-01-01

The NASA Astrophysics Science Education and Public Outreach Forum is one of four scientist-educator teams that support NASA's Science Mission Directorate and its nationwide education and public outreach community in increasing the coherence, efficiency, and effectiveness of their education and public outreach efforts. NASA Astrophysics education and outreach teams collaborate with each other through the Astrophysics Forum to place individual programs in context, connect with broader education and public outreach activities, learn and share successful strategies and techniques, and develop new partnerships. This poster highlights examples of collaborative efforts designed to engage youth and adults across the full spectrum of learning environments, from public outreach venues, to centers of informal learning, to K-12 and higher education classrooms. These include coordinated efforts to support major outreach events such as the USA Science and Engineering Festival; pilot "Astro4Girls" activities in public libraries to engage girls and their families in science during Women’s History Month; and a pilot "NASA's Multiwavelength Universe" online professional development course for middle and high school educators. Resources to assist scientists and Astro101 instructors in incorporating NASA Astrophysics discoveries into their education and public outreach efforts are also discussed.

Order priors for Bayesian network discovery with an application to malware phylogeny

DOE PAGES

Oyen, Diane; Anderson, Blake; Sentz, Kari; ...

2017-09-15

Here, Bayesian networks have been used extensively to model and discover dependency relationships among sets of random variables. We learn Bayesian network structure with a combination of human knowledge about the partial ordering of variables and statistical inference of conditional dependencies from observed data. Our approach leverages complementary information from human knowledge and inference from observed data to produce networks that reflect human beliefs about the system as well as to fit the observed data. Applying prior beliefs about partial orderings of variables is an approach distinctly different from existing methods that incorporate prior beliefs about direct dependencies (or edges)more » in a Bayesian network. We provide an efficient implementation of the partial-order prior in a Bayesian structure discovery learning algorithm, as well as an edge prior, showing that both priors meet the local modularity requirement necessary for an efficient Bayesian discovery algorithm. In benchmark studies, the partial-order prior improves the accuracy of Bayesian network structure learning as well as the edge prior, even though order priors are more general. Our primary motivation is in characterizing the evolution of families of malware to aid cyber security analysts. For the problem of malware phylogeny discovery, we find that our algorithm, compared to existing malware phylogeny algorithms, more accurately discovers true dependencies that are missed by other algorithms.« less

Order priors for Bayesian network discovery with an application to malware phylogeny

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

Oyen, Diane; Anderson, Blake; Sentz, Kari

Here, Bayesian networks have been used extensively to model and discover dependency relationships among sets of random variables. We learn Bayesian network structure with a combination of human knowledge about the partial ordering of variables and statistical inference of conditional dependencies from observed data. Our approach leverages complementary information from human knowledge and inference from observed data to produce networks that reflect human beliefs about the system as well as to fit the observed data. Applying prior beliefs about partial orderings of variables is an approach distinctly different from existing methods that incorporate prior beliefs about direct dependencies (or edges)more » in a Bayesian network. We provide an efficient implementation of the partial-order prior in a Bayesian structure discovery learning algorithm, as well as an edge prior, showing that both priors meet the local modularity requirement necessary for an efficient Bayesian discovery algorithm. In benchmark studies, the partial-order prior improves the accuracy of Bayesian network structure learning as well as the edge prior, even though order priors are more general. Our primary motivation is in characterizing the evolution of families of malware to aid cyber security analysts. For the problem of malware phylogeny discovery, we find that our algorithm, compared to existing malware phylogeny algorithms, more accurately discovers true dependencies that are missed by other algorithms.« less

Learning Outdoors: Leader Guide, Grade 3. 4-H Discovery.

ERIC Educational Resources Information Center

Abell, John R.; Newman, Jerry A.

The United States has a rich natural resource heritage. It is important to educate students in the principles of conservation so that these natural resources may endure for generations. This guide is designed to help leaders to learn to organize groups of children and conduct successful meetings; provide fun, safe, outdoor learning experiences for…

The Effect of Simulation Games on the Learning of Computational Problem Solving

ERIC Educational Resources Information Center

Liu, Chen-Chung; Cheng, Yuan-Bang; Huang, Chia-Wen

2011-01-01

Simulation games are now increasingly applied to many subject domains as they allow students to engage in discovery processes, and may facilitate a flow learning experience. However, the relationship between learning experiences and problem solving strategies in simulation games still remains unclear in the literature. This study, thus, analyzed…

The Science of Learning Meets the Art of Teaching

ERIC Educational Resources Information Center

Park, Beverley

2006-01-01

Through the discoveries of neuroscience, educators have moved beyond the intuitive knowledge of how and when learning occurs to a demonstrated scientific understanding of the learning process itself. These new understandings have a two-fold appeal to educators: they allow them to design better, research-based teaching practices, and they help them…

Open the Door, Let's Explore More! Field Trips of Discovery for Young Children.

ERIC Educational Resources Information Center

Redleaf, Rhoda

Designed as a resource for teachers and parents, this guide contains activities to help children in primary grades learn from walks and field trips. Chapter 1, "Experience and Learning," discusses general information about how young children learn and the contribution of field trips to children's perception, language, memory, and logical…

Supporting Creativity and Imagination in the Early Years. Supporting Early Learning

ERIC Educational Resources Information Center

Duffy, Bernadette

2006-01-01

Learning through the arts has the potential to stimulate open ended activity that encourages discovery, exploration, experimentation and invention, thus contributing to children's development in all areas of learning and helping to make the curriculum meaningful to them. In this book, the author draws on her extensive experience of promoting young…

Issues in Researching Self-Regulated Learning as Patterns of Events

ERIC Educational Resources Information Center

Winne, Philip H.

2014-01-01

New methods for gathering and analyzing data about events that comprise self-regulated learning (SRL) support discoveries about patterns among events and tests of hypotheses about roles patterns play in learning. Five such methodologies are discussed in the context of four key questions that shape investigations into patterns in SRL. A framework…

Active Learning Strategies and Assessment in World Geography Classes

ERIC Educational Resources Information Center

Klein, Phil

2003-01-01

Active learning strategies include a variety of methods, such as inquiry and discovery, in which students are actively engaged in the learning process. This article describes several strategies that can be used in secondary-or college-level world geography courses. The goal of these activities is to foster development of a spatial perspective in…

Perspective: Interactive material property databases through aggregation of literature data

NASA Astrophysics Data System (ADS)

Seshadri, Ram; Sparks, Taylor D.

2016-05-01

Searchable, interactive, databases of material properties, particularly those relating to functional materials (magnetics, thermoelectrics, photovoltaics, etc.) are curiously missing from discussions of machine-learning and other data-driven methods for advancing new materials discovery. Here we discuss the manual aggregation of experimental data from the published literature for the creation of interactive databases that allow the original experimental data as well additional metadata to be visualized in an interactive manner. The databases described involve materials for thermoelectric energy conversion, and for the electrodes of Li-ion batteries. The data can be subject to machine-learning, accelerating the discovery of new materials.

How Big Data, Comparative Effectiveness Research, and Rapid-Learning Health-Care Systems Can Transform Patient Care in Radiation Oncology.

PubMed

Sanders, Jason C; Showalter, Timothy N

2018-01-01

Big data and comparative effectiveness research methodologies can be applied within the framework of a rapid-learning health-care system (RLHCS) to accelerate discovery and to help turn the dream of fully personalized medicine into a reality. We synthesize recent advances in genomics with trends in big data to provide a forward-looking perspective on the potential of new advances to usher in an era of personalized radiation therapy, with emphases on the power of RLHCS to accelerate discovery and the future of individualized radiation treatment planning.

Modalities, Relations, and Learning

NASA Astrophysics Data System (ADS)

Müller, Martin Eric

While the popularity of statistical, probabilistic and exhaustive machine learning techniques still increases, relational and logic approaches are still a niche market in research. While the former approaches focus on predictive accuracy, the latter ones prove to be indispensable in knowledge discovery.

Anthropology, tooth wear, and occlusion ab origine.

PubMed

Young, W G

1998-11-01

The purpose of this essay is to emphasize that anthropology, the study of man in his environments, is a potent tool for scientific discovery and inspiration in dental science. It attempts to capture flashes of creative anthropological insight which have illuminated studies of tooth wear and occlusion in the past. While it documents contributions, understandings, and misunderstandings from Australian and New Zealand dentists, it is not a hagiography. The real saint of this essay is the Australian aborigine. For when men and women are understood in their environments, much is learned from them which challenges preconceptions of our dental science culture. The essay concludes that new, contemporary Australian culture needs to be studied by anthropological approaches if we are to understand how dental erosion is exacerbating tooth wear and damaging the occlusions of contemporary Australians. Much remains to be discovered about contemporary lifestyles, habits, and diets that lead to dental erosion, the principal cause of contemporary tooth wear in this part of the world.

FindIt@Flinders: User Experiences of the Primo Discovery Search Solution

ERIC Educational Resources Information Center

Jarrett, Kylie

2012-01-01

In September 2011, Flinders University Library launched FindIt@Flinders, the Primo discovery layer search to provide simultaneous results from the Library's collections and subscription databases. This research project was an exploratory case study which aimed to show whether students were finding relevant information for their course learning and…

Paraphrasing and Prediction with Self-Explanation as Generative Strategies for Learning Science Principles in a Simulation

ERIC Educational Resources Information Center

Morrison, Jennifer R.; Bol, Linda; Ross, Steven M.; Watson, Ginger S.

2015-01-01

This study examined the incorporation of generative strategies for the guided discovery of physics principles in a simulation. Participants who either paraphrased or predicted and self-explained guided discovery assignments exhibited improved performance on an achievement test as compared to a control group. Calibration accuracy (the…

ATOMIC PHYSICS, AN AUTOINSTRUCTIONAL PROGRAM, VOLUME 2, SUPPLEMENT.

ERIC Educational Resources Information Center

DETERLINE, WILLIAM A.; KLAUS, DAVID J.

THE AUTOINSTRUCTIONAL MATERIALS IN THIS TEXT WERE PREPARED FOR USE IN AN EXPERIMENTAL STUDY, OFFERING SELF-TUTORING MATERIAL FOR LEARNING ATOMIC PHYSICS. THE TOPICS COVERED ARE (1) ISOTOPES AND MASS NUMBERS, (2) MEASURING ATOMIC MASS, (3) DISCOVERY OF THE NUCLEUS, (4) STRUCTURE OF THE NUCLEUS, (5) DISCOVERY OF THE NEUTRON, (6) NUCLEAR REACTIONS,…

Interacting with… What? Exploring Children's Social and Sensory Practices in a Science Discovery Centre

ERIC Educational Resources Information Center

Dicks, Bella

2013-01-01

This paper presents findings from a qualitative UK study exploring the social practices of schoolchildren visiting an interactive science discovery centre. It is promoted as a place for "learning through doing", but the multi-modal, ethnographic methods adopted suggest that children were primarily engaged in (1) sensory pleasure-taking…

Teaching Tip: Using Rapid Game Prototyping for Exploring Requirements Discovery and Modeling

ERIC Educational Resources Information Center

Dalal, Nikunj

2012-01-01

We describe the use of rapid game prototyping as a pedagogic technique to experientially explore and learn requirements discovery, modeling, and specification in systems analysis and design courses. Students have a natural interest in gaming that transcends age, gender, and background. Rapid digital game creation is used to build computer games…

Workshop on Discovery Lessons-Learned

NASA Technical Reports Server (NTRS)

Saunders, M. (Editor)

1995-01-01

As part of the Discovery Program's continuous improvement effort, a Discovery Program Lessons-Learned workshop was designed to review how well the Discovery Program is moving toward its goal of providing low-cost research opportunities to the planetary science community while ensuring continued U.S. leadership in solar system exploration. The principal focus of the workshop was on the recently completed Announcement of Opportunity (AO) cycle, but the program direction and program management were also open to comment. The objective of the workshop was to identify both the strengths and weaknesses of the process up to this point, with the goal of improving the process for the next AO cycle. The process for initializing the workshop was to solicit comments from the communities involved in the program and to use the feedback as the basis for establishing the workshop agenda. The following four sessions were developed after reviewing and synthesizing both the formal feedback received and informal feedback obtained during discussions with various participants: (1) Science and Return on Investment; (2) Technology vs. Risk; Mission Success and Other Factors; (3) Cost; and (4) AO.AO Process Changes and Program Management.

University of Washington's eScience Institute Promotes New Training and Career Pathways in Data Science

NASA Astrophysics Data System (ADS)

Stone, S.; Parker, M. S.; Howe, B.; Lazowska, E.

2015-12-01

Rapid advances in technology are transforming nearly every field from "data-poor" to "data-rich." The ability to extract knowledge from this abundance of data is the cornerstone of 21st century discovery. At the University of Washington eScience Institute, our mission is to engage researchers across disciplines in developing and applying advanced computational methods and tools to real world problems in data-intensive discovery. Our research team consists of individuals with diverse backgrounds in domain sciences such as astronomy, oceanography and geology, with complementary expertise in advanced statistical and computational techniques such as data management, visualization, and machine learning. Two key elements are necessary to foster careers in data science: individuals with cross-disciplinary training in both method and domain sciences, and career paths emphasizing alternative metrics for advancement. We see persistent and deep-rooted challenges for the career paths of people whose skills, activities and work patterns don't fit neatly into the traditional roles and success metrics of academia. To address these challenges the eScience Institute has developed training programs and established new career opportunities for data-intensive research in academia. Our graduate students and post-docs have mentors in both a methodology and an application field. They also participate in coursework and tutorials to advance technical skill and foster community. Professional Data Scientist positions were created to support research independence while encouraging the development and adoption of domain-specific tools and techniques. The eScience Institute also supports the appointment of faculty who are innovators in developing and applying data science methodologies to advance their field of discovery. Our ultimate goal is to create a supportive environment for data science in academia and to establish global recognition for data-intensive discovery across all fields.

Understanding How Young Children Learn: Bringing the Science of Child Development to the Classroom

ERIC Educational Resources Information Center

Ostroff, Wendy

2012-01-01

Because little kids can't tell you how their minds work and what makes them learn, you need this book about new scientific discoveries that explain how young children learn and what teachers can do to use those findings to enhance classroom teaching. Discover where the desire to learn comes from and what occurs during children's development to…

A Conceptual Paper on the Application of the Picture Word Inductive Model Using Bruner's Constructivist View of Learning and the Cognitive Load Theory

ERIC Educational Resources Information Center

Jiang, Xuan; Perkins, Kyle

2013-01-01

Bruner's constructs of learning, specifically the structure of learning, spiral curriculum, and discovery learning, in conjunction with the Cognitive Load Theory, are used to evaluate the Picture Word Inductive Model (PWIM), an inquiry-oriented inductive language arts strategy designed to teach K-6 children phonics and spelling. The PWIM reflects…

Introducing social cues in multimedia learning: The role of pedagogic agents' image and language in a scientific lesson

NASA Astrophysics Data System (ADS)

Moreno, Roxana Arleen

The present dissertation tested the hypothesis that software pedagogical agents can promote constructivist learning in a discovery-based multimedia environment. In a preliminary study, students who received a computer-based lesson on environmental science performed better on subsequent tests of problem solving and motivation when they learned with the mediation of a fictional agent compared to when they learned the same material from text. In order to investigate further the basis for this personal agent effect, I varied whether the agent's words were presented as speech or on-screen text and whether or not the agent's image appeared on the screen. Both with a fictional agent (Experiment 1) and a video of a human face (Experiment 2), students performed better on tests of retention, problem-solving transfer, and program ratings when words were presented as speech rather than on-screen text (producing a modality effect) but visual presence of the agent did not affect test performance (producing no image effect). Next, I varied whether or not the agent's words were presented in conversational style (i.e., as dialogue) or formal style (i.e., as monologue) both using speech (Experiment 3) and on-screen text (Experiment 4). In both experiments, there was a dialogue effect in which conversational-style produced better retention and transfer performance. Students who learned with conversational-style text rated the program more favorably than those who learned with monologue-style text. The results support cognitive principles of multimedia learning which underlie the understanding of a computer lesson about a complex scientific system.

Closed-Loop Multitarget Optimization for Discovery of New Emulsion Polymerization Recipes

PubMed Central

2015-01-01

Self-optimization of chemical reactions enables faster optimization of reaction conditions or discovery of molecules with required target properties. The technology of self-optimization has been expanded to discovery of new process recipes for manufacture of complex functional products. A new machine-learning algorithm, specifically designed for multiobjective target optimization with an explicit aim to minimize the number of “expensive” experiments, guides the discovery process. This “black-box” approach assumes no a priori knowledge of chemical system and hence particularly suited to rapid development of processes to manufacture specialist low-volume, high-value products. The approach was demonstrated in discovery of process recipes for a semibatch emulsion copolymerization, targeting a specific particle size and full conversion. PMID:26435638

A behavioral task for investigating action discovery, selection and switching: comparison between types of reinforcer

PubMed Central

Fisher, Simon D.; Gray, Jason P.; Black, Melony J.; Davies, Jennifer R.; Bednark, Jeffery G.; Redgrave, Peter; Franz, Elizabeth A.; Abraham, Wickliffe C.; Reynolds, John N. J.

2014-01-01

Action discovery and selection are critical cognitive processes that are understudied at the cellular and systems neuroscience levels. Presented here is a new rodent joystick task suitable to test these processes due to the range of action possibilities that can be learnt while performing the task. Rats learned to manipulate a joystick while progressing through task milestones that required increasing degrees of movement accuracy. In a switching phase designed to measure action discovery, rats were repeatedly required to discover new target positions to meet changing task demands. Behavior was compared using both food and electrical brain stimulation reward (BSR) of the substantia nigra as reinforcement. Rats reinforced with food and those with BSR performed similarly overall, although BSR-treated rats exhibited greater vigor in responding. In the switching phase, rats learnt new actions to adapt to changing task demands, reflecting action discovery processes. Because subjects are required to learn different goal-directed actions, this task could be employed in further investigations of the cellular mechanisms of action discovery and selection. Additionally, this task could be used to assess the behavioral flexibility impairments seen in conditions such as Parkinson's disease and obsessive-compulsive disorder. The versatility of the task will enable cross-species investigations of these impairments. PMID:25477795

Effects of congruence between preferred and perceived learning environments in nursing education in Taiwan: a cross-sectional study.

PubMed

Yeh, Ting-Kuang; Huang, Hsiu-Mei; Chan, Wing P; Chang, Chun-Yen

2016-05-20

To investigate the effects of congruence between preferred and perceived learning environments on learning outcomes of nursing students. A nursing course at a university in central Taiwan. 124 Taiwanese nursing students enrolled in a 13-week problem-based Fundamental Nursing curriculum. Students' preferred learning environment, perceptions about the learning environment and learning outcomes (knowledge, self-efficacy and attitudes) were assessed. On the basis of test scores measuring their preferred and perceived learning environments, students were assigned to one of two groups: a 'preferred environment aligned with perceived learning environment' group and a 'preferred environment discordant with perceived learning environment' group. Learning outcomes were analysed by group. Most participants preferred learning in a classroom environment that combined problem-based and lecture-based instruction. However, a mismatch of problem-based instruction with students' perceptions occurred. Learning outcomes were significantly better when students' perceptions of their instructional activities were congruent with their preferred learning environment. As problem-based learning becomes a focus of educational reform in nursing, teachers need to be aware of students' preferences and perceptions of the learning environment. Teachers may also need to improve the match between an individual student's perception and a teacher's intention in the learning environment, and between the student's preferred and actual perceptions of the learning environment. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://www.bmj.com/company/products-services/rights-and-licensing/

Computer-aided drug discovery research at a global contract research organization

NASA Astrophysics Data System (ADS)

Kitchen, Douglas B.

2017-03-01

Computer-aided drug discovery started at Albany Molecular Research, Inc in 1997. Over nearly 20 years the role of cheminformatics and computational chemistry has grown throughout the pharmaceutical industry and at AMRI. This paper will describe the infrastructure and roles of CADD throughout drug discovery and some of the lessons learned regarding the success of several methods. Various contributions provided by computational chemistry and cheminformatics in chemical library design, hit triage, hit-to-lead and lead optimization are discussed. Some frequently used computational chemistry techniques are described. The ways in which they may contribute to discovery projects are presented based on a few examples from recent publications.

Computer-aided drug discovery research at a global contract research organization.

PubMed

Kitchen, Douglas B

2017-03-01

Computer-aided drug discovery started at Albany Molecular Research, Inc in 1997. Over nearly 20 years the role of cheminformatics and computational chemistry has grown throughout the pharmaceutical industry and at AMRI. This paper will describe the infrastructure and roles of CADD throughout drug discovery and some of the lessons learned regarding the success of several methods. Various contributions provided by computational chemistry and cheminformatics in chemical library design, hit triage, hit-to-lead and lead optimization are discussed. Some frequently used computational chemistry techniques are described. The ways in which they may contribute to discovery projects are presented based on a few examples from recent publications.

3 CFR 8435 - Proclamation 8435 of October 7, 2009. Leif Erikson Day, 2009

Code of Federal Regulations, 2010 CFR

2010-01-01

... determined not to turn back, in order to learn what lay beyond the setting sun. This same spirit lived within... their pioneering spirit continues to embody our Nation’s unbounded enthusiasm for discovery and learning...

Effects of congruence between preferred and perceived learning environments in nursing education in Taiwan: a cross-sectional study

PubMed Central

Yeh, Ting-Kuang; Huang, Hsiu-Mei; Chan, Wing P; Chang, Chun-Yen

2016-01-01

Objective To investigate the effects of congruence between preferred and perceived learning environments on learning outcomes of nursing students. Setting A nursing course at a university in central Taiwan. Participants 124 Taiwanese nursing students enrolled in a 13-week problem-based Fundamental Nursing curriculum. Design and methods Students' preferred learning environment, perceptions about the learning environment and learning outcomes (knowledge, self-efficacy and attitudes) were assessed. On the basis of test scores measuring their preferred and perceived learning environments, students were assigned to one of two groups: a ‘preferred environment aligned with perceived learning environment’ group and a ‘preferred environment discordant with perceived learning environment’ group. Learning outcomes were analysed by group. Outcome measures Most participants preferred learning in a classroom environment that combined problem-based and lecture-based instruction. However, a mismatch of problem-based instruction with students' perceptions occurred. Learning outcomes were significantly better when students' perceptions of their instructional activities were congruent with their preferred learning environment. Conclusions As problem-based learning becomes a focus of educational reform in nursing, teachers need to be aware of students' preferences and perceptions of the learning environment. Teachers may also need to improve the match between an individual student's perception and a teacher's intention in the learning environment, and between the student's preferred and actual perceptions of the learning environment. PMID:27207620

"Re"storying the Present by "Re"visiting the Past: Unexpected Moments of Discovery and Illumination through Museum Learning

ERIC Educational Resources Information Center

Kawalilak, Colleen; Groen, Janet

2016-01-01

Two adult educators, guided by autoethnography as methodology, share the restorying of their own lifelong learning narratives and unexpected insights gained from having experienced the powerful potential of museum learning and culture. Having previously regarded museum visits as an experience that primarily tapped the intellectual, cognitive…

Active Learning for Discovery and Innovation in Criminology with Chinese Learners

ERIC Educational Resources Information Center

Li, Jessica C. M.; Wu, Joseph

2015-01-01

Whereas a great deal of literature based upon the context of Western societies has concluded criminology is an ideal discipline for active learning approach, it remains uncertain if this learning approach is applicable to Chinese learners in the discipline of criminology. This article describes and provides evidence of the benefits of using active…

Reconceptualizing Teacher Education Programs: Applying Dewey's Theories to Service-Learning with Early Childhood Preservice Teachers

ERIC Educational Resources Information Center

Lake, Vickie E.; Winterbottom, Christian; Ethridge, Elizabeth A.; Kelly, Loreen

2015-01-01

Dewey's concept of enabling children to explore based on their own interests has evolved into investigations and projects using methods of exploration, experimentation, and discovery--three tenets of service-learning. Using mixed methodology, the authors examined the implementation of service-learning in a teacher education program. A total of 155…

The Future of Music Education in Kenya: Implementation of Curriculum and Instructional Teaching Strategies

ERIC Educational Resources Information Center

Mochere, Joyce M.

2017-01-01

This paper is an evaluation of the parameters of the concept of music curriculum that examines principles underlying the teaching and learning of music. The paper also discusses the practical nature of music education and the need for experiential learning. Music educators worldwide advocate for methods that allow for discovery learning and hence…

Writing for Mathematics Discovery-Learning: A Model for Composition Courses.

ERIC Educational Resources Information Center

Weaver, Laura H.

Focusing on how expert writers in various disciplines convey complex ideas, this paper shows how the techniques used by the mathematician, Clark Kimberling, in various writings can (1) be transferred to other disciplines, (2) show learning taking place, and (3) provide models for students to re-enact learning in all subject areas. The paper…

Designing Instruction for the Web: Incorporating New Conceptions of the Learning Process.

ERIC Educational Resources Information Center

Hunt, Nancy P.

New technologies such as Magnetic Resonance Imaging (MRI) and Positron Emission Tomography (PET) have led to recent discoveries about how the brain works and how people learn. The interactive capabilities of World Wide Web-based instructional strategies can be employed to better match how we teach with how we know students learn. This paper…

Integrated Warfighter Biodefense Program (IWBP)

DTIC Science & Technology

2011-05-26

empower the non-statistical subject matter expert to rapidly obtain insight into their data for discovery, forecasting and decision making. LeapWorks...Support for Time Series Pattern discovery in temporal data environments is important for many forecasting types of applications. For example, does the...as well as the forecasting horizon for the purposes of patterns discovery. Beta Testing During the period of performance for this report

Discovery sequence and the nature of low permeability gas accumulations

USGS Publications Warehouse

Attanasi, E.D.

2005-01-01

There is an ongoing discussion regarding the geologic nature of accumulations that host gas in low-permeability sandstone environments. This note examines the discovery sequence of the accumulations in low permeability sandstone plays that were classified as continuous-type by the U.S. Geological Survey for the 1995 National Oil and Gas Assessment. It compares the statistical character of historical discovery sequences of accumulations associated with continuous-type sandstone gas plays to those of conventional plays. The seven sandstone plays with sufficient data exhibit declining size with sequence order, on average, and in three of the seven the trend is statistically significant. Simulation experiments show that both a skewed endowment size distribution and a discovery process that mimics sampling proportional to size are necessary to generate a discovery sequence that consistently produces a statistically significant negative size order relationship. The empirical findings suggest that discovery sequence could be used to constrain assessed gas in untested areas. The plays examined represent 134 of the 265 trillion cubic feet of recoverable gas assessed in undeveloped areas of continuous-type gas plays in low permeability sandstone environments reported in the 1995 National Assessment. ?? 2005 International Association for Mathematical Geology.

Science Learning Outcomes in Alignment with Learning Environment Preferences

NASA Astrophysics Data System (ADS)

Chang, Chun-Yen; Hsiao, Chien-Hua; Chang, Yueh-Hsia

2011-04-01

This study investigated students' learning environment preferences and compared the relative effectiveness of instructional approaches on students' learning outcomes in achievement and attitude among 10th grade earth science classes in Taiwan. Data collection instruments include the Earth Science Classroom Learning Environment Inventory and Earth Science Learning Outcomes Inventory. The results showed that most students preferred learning in a classroom environment where student-centered and teacher-centered instructional approaches coexisted over a teacher-centered learning environment. A multivariate analysis of covariance also revealed that the STBIM students' cognitive achievement and attitude toward earth science were enhanced when the learning environment was congruent with their learning environment preference.

Science for the 21st Century

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

Not Available

2004-07-01

The Federal government plays a key role in supporting the country's science infrastructure, a national treasure, and scientific research, an investment in our future. Scientific discoveries transform the way we think about our universe and ourselves, from the vastness of space to molecular-level biology. In innovations such as drugs derived through biotechnology and new communications technologies we see constant evidence of the power of science to improve lives and address national challenges. We had not yet learned to fly at the dawn of the 20th century, and could not have imagined the amazing 20th century inventions that we now takemore » for granted. As we move into the 21st century, we eagerly anticipate new insights, discoveries, and technologies that will inspire and enrich us for many decades to come. This report presents the critical responsibilities of our Federal science enterprise and the actions taken by the Federal research agencies, through the National Science and Technology Council, to align our programs with scientific opportunity and with national needs. The many examples show how our science enterprise has responded to the President's priorities for homeland and national security, economic growth, health research, and the environment. In addition, we show how the science agencies work together to set priorities; coordinate related research programs; leverage investments to promote discovery, translate science into national benefits, and sustain the national research enterprise; and promote excellence in math and science education and work force development.« less

Implementation of a deidentified federated data network for population-based cohort discovery

PubMed Central

Abend, Aaron; Mandel, Aaron; Geraghty, Estella; Gabriel, Davera; Wynden, Rob; Kamerick, Michael; Anderson, Kent; Rainwater, Julie; Tarczy-Hornoch, Peter

2011-01-01

Objective The Cross-Institutional Clinical Translational Research project explored a federated query tool and looked at how this tool can facilitate clinical trial cohort discovery by managing access to aggregate patient data located within unaffiliated academic medical centers. Methods The project adapted software from the Informatics for Integrating Biology and the Bedside (i2b2) program to connect three Clinical Translational Research Award sites: University of Washington, Seattle, University of California, Davis, and University of California, San Francisco. The project developed an iterative spiral software development model to support the implementation and coordination of this multisite data resource. Results By standardizing technical infrastructures, policies, and semantics, the project enabled federated querying of deidentified clinical datasets stored in separate institutional environments and identified barriers to engaging users for measuring utility. Discussion The authors discuss the iterative development and evaluation phases of the project and highlight the challenges identified and the lessons learned. Conclusion The common system architecture and translational processes provide high-level (aggregate) deidentified access to a large patient population (>5 million patients), and represent a novel and extensible resource. Enhancing the network for more focused disease areas will require research-driven partnerships represented across all partner sites. PMID:21873473

Implementation of a deidentified federated data network for population-based cohort discovery.

PubMed

Anderson, Nicholas; Abend, Aaron; Mandel, Aaron; Geraghty, Estella; Gabriel, Davera; Wynden, Rob; Kamerick, Michael; Anderson, Kent; Rainwater, Julie; Tarczy-Hornoch, Peter

2012-06-01

The Cross-Institutional Clinical Translational Research project explored a federated query tool and looked at how this tool can facilitate clinical trial cohort discovery by managing access to aggregate patient data located within unaffiliated academic medical centers. The project adapted software from the Informatics for Integrating Biology and the Bedside (i2b2) program to connect three Clinical Translational Research Award sites: University of Washington, Seattle, University of California, Davis, and University of California, San Francisco. The project developed an iterative spiral software development model to support the implementation and coordination of this multisite data resource. By standardizing technical infrastructures, policies, and semantics, the project enabled federated querying of deidentified clinical datasets stored in separate institutional environments and identified barriers to engaging users for measuring utility. The authors discuss the iterative development and evaluation phases of the project and highlight the challenges identified and the lessons learned. The common system architecture and translational processes provide high-level (aggregate) deidentified access to a large patient population (>5 million patients), and represent a novel and extensible resource. Enhancing the network for more focused disease areas will require research-driven partnerships represented across all partner sites.

Exoplanet Science in the Classroom: Learning Activities for an Introductory Physics Course

ERIC Educational Resources Information Center

Della-Rose, Devin; Carlson, Randall; de La Harpe, Kimberly; Novotny, Steven; Polsgrove, Daniel

2018-01-01

Discovery of planets outside our solar system, known as extra-solar planets or exoplanets for short, has been at the forefront of astronomical research for over 25 years. Reports of new discoveries have almost become routine; however, the excitement surrounding them has not. Amazingly, as groundbreaking as exoplanet science is, the basic physics…

Invention versus Direct Instruction: For Some Content, It's a Tie

ERIC Educational Resources Information Center

Chase, Catherine C.; Klahr, David

2017-01-01

An important, but as yet unresolved pedagogical question is whether discovery-oriented or direct instruction methods lead to greater learning and transfer. We address this issue in a study with 101 fourth and fifth grade students that contrasts two distinct instructional methods. One is a blend of discovery and direct instruction called…

The Discovery Method; An International Experiment in Retraining. Employment of Older Workers, 6.

ERIC Educational Resources Information Center

Belbin, R.M.

Several demonstration programs were used in training older workers in four member countries of the Organisation for Economic Co-operation and Development. The Austrian program was a stonemasonry course for persons aged 18 to 55, one group using traditional methods and the other, the discovery (discrimination learning) method. In the United…

Knowledge Discovery Process: Case Study of RNAV Adherence of Radar Track Data

NASA Technical Reports Server (NTRS)

Matthews, Bryan

2018-01-01

This talk is an introduction to the knowledge discovery process, beginning with: identifying the problem, choosing data sources, matching the appropriate machine learning tools, and reviewing the results. The overview will be given in the context of an ongoing study that is assessing RNAV adherence of commercial aircraft in the national airspace.

Evaluation Tool for the Application of Discovery Teaching Method in the Greek Environmental School Projects

ERIC Educational Resources Information Center

Kalathaki, Maria

2015-01-01

Greek school community emphasizes on the discovery direction of teaching methodology in the school Environmental Education (EE) in order to promote Education for the Sustainable Development (ESD). In ESD school projects the used methodology is experiential teamwork for inquiry based learning. The proposed tool checks whether and how a school…

Climate Discovery Online Courses for Educators from NCAR

NASA Astrophysics Data System (ADS)

Henderson, S.; Ward, D. L.; Meymaris, K. K.; Johnson, R. M.; Gardiner, L.; Russell, R.

2008-12-01

The National Center for Atmospheric Research (NCAR) has responded to the pressing need for professional development in climate and global change sciences by creating the Climate Discovery online course series. This series was designed with the secondary geoscience educator in mind. The online courses are based on current and credible climate change science. Interactive learning techniques are built into the online course designs with assignments that encourage active participation. A key element of the online courses is the creation of a virtual community of geoscience educators who exchange ideas related to classroom implementation, student assessment, and lessons plans. Geoscience educators from around the country have participated in the online courses. The ongoing interest from geoscience educators strongly suggests that the NCAR Climate Discovery online courses are a timely and needed professional development opportunity. The intent of NCAR Climate Discovery is to positively impact teachers' professional development scientifically authentic information, (2) experiencing guided practice in conducting activities and using ancillary resources in workshop venues, (3) gaining access to standards-aligned lesson plans, kits that promote hands-on learning, and scientific content that are easily implemented in their classrooms, and (4) becoming a part of a community of educators with whom they may continue to discuss the challenges of pedagogy and content comprehension in teaching climate change in the Earth system context. Three courses make up the Climate Discovery series: Introduction to Climate Change; Earth System Science - A Climate Change Perspective; and Understanding Climate Change Today. Each course, instructed by science education specialists, combines geoscience content, information about current climate research, hands-on activities, and group discussion. The online courses use the web-based Moodle courseware system (open- source software similar to Blackboard and webCT), utilizing its features to promote dialogue as well as provide rich online content and media. A key element of the online courses is the development and support of an online learning community, an essential component in successful online courses. Interactive learning techniques are built into the course designs with assignments that encourage active participation. Educators (both formal and informal) use the courses as a venue to exchange ideas and teaching resources. A unique feature of the courses is the emphasis on hands-on activities, a hallmark of our professional development efforts. This presentation will focus on the lessons learned in the development of the three online courses and our successful recruitment and retention efforts.

Towards adaptive, streaming analysis of x-ray tomography data

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

Thomas, Mathew; Kleese van Dam, Kerstin; Marshall, Matthew J.

2015-03-04

Temporal and spatial resolution of chemical imaging methodologies such as x-ray tomography are rapidly increasing, leading to more complex experimental procedures and fast growing data volumes. Automated analysis pipelines and big data analytics are becoming essential to effectively evaluate the results of such experiments. Offering those data techniques in an adaptive, streaming environment can further substantially improve the scientific discovery process, by enabling experimental control and steering based on the evaluation of emerging phenomena as they are observed by the experiment. Pacific Northwest National Laboratory (PNNL)’ Chemical Imaging Initiative (CII - http://imaging.pnnl.gov/ ) has worked since 2011 towards developing amore » framework that allows users to rapidly compose and customize high throughput experimental analysis pipelines for multiple instrument types. The framework, named ‘Rapid Experimental Analysis’ (REXAN) Framework [1], is based on the idea of reusable component libraries and utilizes the PNNL developed collaborative data management and analysis environment ‘Velo’, to provide a user friendly analysis and data management environment for experimental facilities. This article will, discuss the capabilities established for X-Ray tomography, discuss lessons learned, and provide an overview of our more recent work in the Analysis in Motion Initiative (AIM - http://aim.pnnl.gov/ ) at PNNL to provide REXAN capabilities in a streaming environment.« less

Integrated Computational Analysis of Genes Associated with Human Hereditary Insensitivity to Pain. A Drug Repurposing Perspective

PubMed Central

Lötsch, Jörn; Lippmann, Catharina; Kringel, Dario; Ultsch, Alfred

2017-01-01

Genes causally involved in human insensitivity to pain provide a unique molecular source of studying the pathophysiology of pain and the development of novel analgesic drugs. The increasing availability of “big data” enables novel research approaches to chronic pain while also requiring novel techniques for data mining and knowledge discovery. We used machine learning to combine the knowledge about n = 20 genes causally involved in human hereditary insensitivity to pain with the knowledge about the functions of thousands of genes. An integrated computational analysis proposed that among the functions of this set of genes, the processes related to nervous system development and to ceramide and sphingosine signaling pathways are particularly important. This is in line with earlier suggestions to use these pathways as therapeutic target in pain. Following identification of the biological processes characterizing hereditary insensitivity to pain, the biological processes were used for a similarity analysis with the functions of n = 4,834 database-queried drugs. Using emergent self-organizing maps, a cluster of n = 22 drugs was identified sharing important functional features with hereditary insensitivity to pain. Several members of this cluster had been implicated in pain in preclinical experiments. Thus, the present concept of machine-learned knowledge discovery for pain research provides biologically plausible results and seems to be suitable for drug discovery by identifying a narrow choice of repurposing candidates, demonstrating that contemporary machine-learned methods offer innovative approaches to knowledge discovery from available evidence. PMID:28848388

Deep Learning for Drug Design: an Artificial Intelligence Paradigm for Drug Discovery in the Big Data Era.

PubMed

Jing, Yankang; Bian, Yuemin; Hu, Ziheng; Wang, Lirong; Xie, Xiang-Qun Sean

2018-03-30

Over the last decade, deep learning (DL) methods have been extremely successful and widely used to develop artificial intelligence (AI) in almost every domain, especially after it achieved its proud record on computational Go. Compared to traditional machine learning (ML) algorithms, DL methods still have a long way to go to achieve recognition in small molecular drug discovery and development. And there is still lots of work to do for the popularization and application of DL for research purpose, e.g., for small molecule drug research and development. In this review, we mainly discussed several most powerful and mainstream architectures, including the convolutional neural network (CNN), recurrent neural network (RNN), and deep auto-encoder networks (DAENs), for supervised learning and nonsupervised learning; summarized most of the representative applications in small molecule drug design; and briefly introduced how DL methods were used in those applications. The discussion for the pros and cons of DL methods as well as the main challenges we need to tackle were also emphasized.

Active-learning strategies in computer-assisted drug discovery.

PubMed

Reker, Daniel; Schneider, Gisbert

2015-04-01

High-throughput compound screening is time and resource consuming, and considerable effort is invested into screening compound libraries, profiling, and selecting the most promising candidates for further testing. Active-learning methods assist the selection process by focusing on areas of chemical space that have the greatest chance of success while considering structural novelty. The core feature of these algorithms is their ability to adapt the structure-activity landscapes through feedback. Instead of full-deck screening, only focused subsets of compounds are tested, and the experimental readout is used to refine molecule selection for subsequent screening cycles. Once implemented, these techniques have the potential to reduce costs and save precious materials. Here, we provide a comprehensive overview of the various computational active-learning approaches and outline their potential for drug discovery. Copyright © 2014 Elsevier Ltd. All rights reserved.

Toward a critical approach to the study of learning environments in science classrooms

NASA Astrophysics Data System (ADS)

Lorsbach, Anthony; Tobin, Kenneth

1995-03-01

Traditional learning environment research in science classrooms has been built on survey methods meant to measure students' and teachers' perceptions of variables used to define the learning environment. This research has led mainly to descriptions of learning environments. We argue that learning environment research should play a transformative role in science classrooms; that learning environment research should take into account contemporary post-positivist ways of thinking about learning and teaching to assist students and teachers to construct a more emancipatory learning environment. In particular, we argue that a critical perspective could lead to research playing a larger role in the transformation of science classroom learning environments. This argument is supplemented with an example from a middle school science classroom.

A Community Roadmap for Discovery of Geosciences Data

NASA Astrophysics Data System (ADS)

Baru, C.

2012-12-01

This talk will summarize on-going discussions and deliberations related to data discovery undertaken as part of the EarthCube initiative and in the context of current trends and technologies in search and discovery of scientific data and information. The goal of the EarthCube initiative is to transform the conduct of research by supporting the development of community-guided cyberinfrastructure to integrate data and information for knowledge management across the Geosciences. The vision of EarthCube is to provide a coherent framework for finding and using information about the Earth system across the entire research enterprise that will allow for substantial improved collaboration between specialties using each other's data (e.g. subdomains of geo- and biological sciences). Indeed, data discovery is an essential prerequisite to any action that an EarthCube user would undertake. The community roadmap activity addresses challenges in data discovery, beginning with an assessment of the state-of-the-art, and then identifying issues, challenges, and risks in reaching the data discovery vision. Many of the lessons learned are general and applicable not only to the geosciences but also to a variety of other science communities. The roadmap considers data discovery issues in Geoscience that include but are not limited to metadata-based discovery and the use of semantic information and ontologies; content-based discovery and integration with data mining activities; integration with data access services; and policy and governance issues. Furthermore, many geoscience use cases require access to heterogeneous data from multiple disciplinary sources in order to analyze and make intelligent connections between data to advance research frontiers. Examples include, say, assessing the rise of sea surface temperatures; modeling geodynamical earth systems from deep time to present; or, examining in detail the causes and consequences of global climate change. It has taken the past one to two decades for the community to arrive at a few commonly understood and commonly agreed upon standards for metadata and services. There have been significant advancements in the development of prototype systems in the area of metadata-based data discovery, including efforts such as OpenDAP and THREDDS catalogs, the GEON Portal and Catalog Services (www.geongrid.org), OGC standards, and development of systems like OneGeology (onegeology.org), the USGIN (usgin.org), the Earth System Grid, and EOSDIS. Such efforts have set the stage now for the development of next generation, production-quality, advanced discovery services. The next challenge is in converting these into robust, sustained services for the community and developing capabilities such as content-based search and ontology-enabled search, and ensuring that the long tail of geoscience data are fully included in any future discovery services. As EarthCube attempts to pursue these challenges, the key question to pose is whether we will be able to establish a cultural environment that is able to sustain, extend, and manage an infrastructure that will last 50, 100 years?

Data Mining Student Answers with Moodle to Investigate Learning Pathways in an Introductory Geohazards Course

NASA Astrophysics Data System (ADS)

Sit, S. M.; Brudzinski, M. R.; Colella, H. V.

2012-12-01

The recent growth of online learning in higher education is primarily motivated by a desire to (a) increase the availability of learning experiences for learners who cannot, or choose not, to attend traditional face-to-face offerings, (b) assemble and disseminate instructional content more cost-efficiently, or (c) enable instructors to handle more students while maintaining a learning outcome quality that is equivalent to that of comparable face-to-face instruction. However, a less recognized incentive is that online learning also provides an opportunity for data mining, or efficient discovery of non-obvious valuable patterns from a large collection of data, that can be used to investigate learning pathways as opposed to focusing solely on assessing student outcomes. Course management systems that enable online courses provide a means to collect a vast amount of information to analyze students' behavior and the learning process in general. One of the most commonly used is Moodle (modular object-oriented developmental learning environment), a free learning management system that enables creation of powerful, flexible, and engaging online courses and experiences. In order to examine student learning pathways, the online learning modules we are constructing take advantage of Moodle capabilities to provide immediate formative feedback, verifying answers as correct or incorrect and elaborating on knowledge components to guide students towards the correct answer. By permitting multiple attempts in which credit is diminished for each incorrect answer, we provide opportunities to use data mining strategies to assess thousands of students' actions for evidence of problem solving strategies and mastery of concepts. We will show preliminary results from application of this approach to a ~90 student introductory geohazard course that is migrating toward online instruction. We hope more continuous assessment of students' performances will help generate cognitive models that can inform instructional redesign, improve overall efficiency of student learning, and, potentially, be used to create an intelligent tutoring system.

What and how do students learn in an interprofessional student-run clinic? An educational framework for team-based care

PubMed Central

Lie, Désirée A.; Forest, Christopher P.; Walsh, Anne; Banzali, Yvonne; Lohenry, Kevin

2016-01-01

Background The student-run clinic (SRC) has the potential to address interprofessional learning among health professions students. Purpose To derive a framework for understanding student learning during team-based care provided in an interprofessional SRC serving underserved patients. Methods The authors recruited students for a focus group study by purposive sampling and snowballing. They constructed two sets of semi-structured questions for uniprofessional and multiprofessional groups. Sessions were audiotaped, and transcripts were independently coded and adjudicated. Major themes about learning content and processes were extracted. Grounded theory was followed after data synthesis and interpretation to establish a framework for interprofessional learning. Results Thirty-six students from four professions (medicine, physician assistant, occupational therapy, and pharmacy) participated in eight uniprofessional groups; 14 students participated in three multiprofessional groups (N = 50). Theme saturation was achieved. Six common themes about learning content from uniprofessional groups were role recognition, team-based care appreciation, patient experience, advocacy-/systems-based models, personal skills, and career choices. Occupational therapy students expressed self-advocacy, and medical students expressed humility and self-discovery. Synthesis of themes from all groups suggests a learning continuum that begins with the team huddle and continues with shared patient care and social interactions. Opportunity to observe and interact with other professions in action is key to the learning process. Discussion Interprofessional SRC participation promotes learning ‘with, from, and about’ each other. Participation challenges misconceptions and sensitizes students to patient experiences, health systems, advocacy, and social responsibility. Learning involves interprofessional interactions in the patient encounter, reinforced by formal and informal communications. Participation is associated with interest in serving the underserved and in primary care careers. The authors proposed a framework for interprofessional learning with implications for optimal learning environments to promote team-based care. Future research is suggested to identify core faculty functions and best settings to advance and enhance student preparation for future collaborative team practice. PMID:27499364

What and how do students learn in an interprofessional student-run clinic? An educational framework for team-based care.

PubMed

Lie, Désirée A; Forest, Christopher P; Walsh, Anne; Banzali, Yvonne; Lohenry, Kevin

2016-01-01

Background The student-run clinic (SRC) has the potential to address interprofessional learning among health professions students. Purpose To derive a framework for understanding student learning during team-based care provided in an interprofessional SRC serving underserved patients. Methods The authors recruited students for a focus group study by purposive sampling and snowballing. They constructed two sets of semi-structured questions for uniprofessional and multiprofessional groups. Sessions were audiotaped, and transcripts were independently coded and adjudicated. Major themes about learning content and processes were extracted. Grounded theory was followed after data synthesis and interpretation to establish a framework for interprofessional learning. Results Thirty-six students from four professions (medicine, physician assistant, occupational therapy, and pharmacy) participated in eight uniprofessional groups; 14 students participated in three multiprofessional groups (N = 50). Theme saturation was achieved. Six common themes about learning content from uniprofessional groups were role recognition, team-based care appreciation, patient experience, advocacy-/systems-based models, personal skills, and career choices. Occupational therapy students expressed self-advocacy, and medical students expressed humility and self-discovery. Synthesis of themes from all groups suggests a learning continuum that begins with the team huddle and continues with shared patient care and social interactions. Opportunity to observe and interact with other professions in action is key to the learning process. Discussion Interprofessional SRC participation promotes learning 'with, from, and about' each other. Participation challenges misconceptions and sensitizes students to patient experiences, health systems, advocacy, and social responsibility. Learning involves interprofessional interactions in the patient encounter, reinforced by formal and informal communications. Participation is associated with interest in serving the underserved and in primary care careers. The authors proposed a framework for interprofessional learning with implications for optimal learning environments to promote team-based care. Future research is suggested to identify core faculty functions and best settings to advance and enhance student preparation for future collaborative team practice.

What and how do students learn in an interprofessional student-run clinic? An educational framework for team-based care.

PubMed

Lie, Désirée A; Forest, Christopher P; Walsh, Anne; Banzali, Yvonne; Lohenry, Kevin

2016-01-01

The student-run clinic (SRC) has the potential to address interprofessional learning among health professions students. To derive a framework for understanding student learning during team-based care provided in an interprofessional SRC serving underserved patients. The authors recruited students for a focus group study by purposive sampling and snowballing. They constructed two sets of semi-structured questions for uniprofessional and multiprofessional groups. Sessions were audiotaped, and transcripts were independently coded and adjudicated. Major themes about learning content and processes were extracted. Grounded theory was followed after data synthesis and interpretation to establish a framework for interprofessional learning. Thirty-six students from four professions (medicine, physician assistant, occupational therapy, and pharmacy) participated in eight uniprofessional groups; 14 students participated in three multiprofessional groups (N = 50). Theme saturation was achieved. Six common themes about learning content from uniprofessional groups were role recognition, team-based care appreciation, patient experience, advocacy-/systems-based models, personal skills, and career choices. Occupational therapy students expressed self-advocacy, and medical students expressed humility and self-discovery. Synthesis of themes from all groups suggests a learning continuum that begins with the team huddle and continues with shared patient care and social interactions. Opportunity to observe and interact with other professions in action is key to the learning process. Interprofessional SRC participation promotes learning 'with, from, and about' each other. Participation challenges misconceptions and sensitizes students to patient experiences, health systems, advocacy, and social responsibility. Learning involves interprofessional interactions in the patient encounter, reinforced by formal and informal communications. Participation is associated with interest in serving the underserved and in primary care careers. The authors proposed a framework for interprofessional learning with implications for optimal learning environments to promote team-based care. Future research is suggested to identify core faculty functions and best settings to advance and enhance student preparation for future collaborative team practice.

Ontogeny of Manipulative Behavior and Nut-Cracking in Young Tufted Capuchin Monkeys ("Cebus Apella"): A Perception-Action Perspective

ERIC Educational Resources Information Center

de Resende, Briseida Dogo; Ottoni, Eduardo B.; Fragaszy, Dorothy M.

2008-01-01

How do capuchin monkeys learn to use stones to crack open nuts? Perception-action theory posits that individuals explore producing varying spatial and force relations among objects and surfaces, thereby learning about affordances of such relations and how to produce them. Such learning supports the discovery of tool use. We present longitudinal…

Semantic Features of Math Problems: Relationships to Student Learning and Engagement

ERIC Educational Resources Information Center

Slater, Stefan; Baker, Ryan; Ocumpaugh, Jaclyn; Inventado, Paul; Scupelli, Peter; Heffernan, Neil

2016-01-01

The creation of crowd-sourced content in learning systems is a powerful method for adapting learning systems to the needs of a range of teachers in a range of domains, but the quality of this content can vary. This study explores linguistic differences in teacher-created problem content in ASSISTments using a combination of discovery with models…

Undergraduate Research in Agriculture: Constructivism and the Scholarship of Discovery

ERIC Educational Resources Information Center

Splan, Rebecca K.; Porr, C. A. Shea; Broyles, Thomas W.

2011-01-01

Experiential learning is a hallmark of undergraduate education programs in the agricultural sciences, and is aligned with constructivist learning theory. This interpretivist qualitative study used historical research methodology to analyze the epistemological underpinnings of constructivism and explore the construct's relationship to undergraduate…

Locate, Plan, Develop, Use An Outdoor Classroom.

ERIC Educational Resources Information Center

Soil Conservation Service (USDA), Upper Darby, PA.

Designed to aid educational institutions and community organizations in selecting, planning, developing and using outdoor learning areas as outdoor classrooms, this guide includes: (1) Learning by Discovery (scientific, cultural, and recreational goals); (2) The Initial Planning Effort (use of: a planning committee including teachers,…

Birding with Children: A Nest of Activities.

ERIC Educational Resources Information Center

Ard, Linda; Wilkerson, Kristen

1996-01-01

Describes hummingbirds and how they can serve as sources of learning and enjoyment for young children. Gives information on feeding, breeding, and behavior of hummingbirds, and on their natural predators. Outlines activities for "discovery," making feeders, watching and charting hummingbirds, and other creative learning activities. (BGC)

When Does Provision of Instruction Promote Learning?

ERIC Educational Resources Information Center

Lee, Hee Seung; Anderson, Abraham; Betts, Shawn; Anderson, John R.

2011-01-01

Contradictory evidence has been reported on the effects of discovery learning approach and the role of instructional explanations. By manipulating the presence of instruction (verbal explanation) and transparency of problem structures, we investigated how effects of instructional explanations differed depending on the transparency of problem…

Building Knowledge Graphs for NASA's Earth Science Enterprise

NASA Astrophysics Data System (ADS)

Zhang, J.; Lee, T. J.; Ramachandran, R.; Shi, R.; Bao, Q.; Gatlin, P. N.; Weigel, A. M.; Maskey, M.; Miller, J. J.

2016-12-01

Inspired by Google Knowledge Graph, we have been building a prototype Knowledge Graph for Earth scientists, connecting information and data in NASA's Earth science enterprise. Our primary goal is to advance the state-of-the-art NASA knowledge extraction capability by going beyond traditional catalog search and linking different distributed information (such as data, publications, services, tools and people). This will enable a more efficient pathway to knowledge discovery. While Google Knowledge Graph provides impressive semantic-search and aggregation capabilities, it is limited to search topics for general public. We use the similar knowledge graph approach to semantically link information gathered from a wide variety of sources within the NASA Earth Science enterprise. Our prototype serves as a proof of concept on the viability of building an operational "knowledge base" system for NASA Earth science. Information is pulled from structured sources (such as NASA CMR catalog, GCMD, and Climate and Forecast Conventions) and unstructured sources (such as research papers). Leveraging modern techniques of machine learning, information retrieval, and deep learning, we provide an integrated data mining and information discovery environment to help Earth scientists to use the best data, tools, methodologies, and models available to answer a hypothesis. Our knowledge graph would be able to answer questions like: Which articles discuss topics investigating similar hypotheses? How have these methods been tested for accuracy? Which approaches have been highly cited within the scientific community? What variables were used for this method and what datasets were used to represent them? What processing was necessary to use this data? These questions then lead researchers and citizen scientists to investigate the sources where data can be found, available user guides, information on how the data was acquired, and available tools and models to use with this data. As a proof of concept, we focus on a well-defined domain - Hurricane Science linking research articles and their findings, data, people and tools/services. Modern information retrieval, natural language processing machine learning and deep learning techniques are applied to build the knowledge network.

Pre-service Teachers Learn the Nature of Science in Simulated Worlds

NASA Astrophysics Data System (ADS)

Marshall, Jill

2007-10-01

Although the Texas Essential Knowledge and Skills include an understanding of the nature of science as an essential goal of every high school science course, few students report opportunities to explore essential characteristics of science in their previous classes. A simulated-world environment (Erickson, 2005) allows students to function as working scientists and discover these essential elements for themselves (i.e. that science is evidence-based and involves testable conjectures, that theories have limitations and are constantly being modified based on new discoveries to more closely reflect the natural world.) I will report on pre-service teachers' exploration of two simulated worlds and resulting changes in their descriptions of the nature of science. Erickson (2005). Simulating the Nature of Science. Presentation at the 2005 Summer AAPT Meeting, Salt Lake City, UT.

Biomedical Informatics on the Cloud: A Treasure Hunt for Advancing Cardiovascular Medicine.

PubMed

Ping, Peipei; Hermjakob, Henning; Polson, Jennifer S; Benos, Panagiotis V; Wang, Wei

2018-04-27

In the digital age of cardiovascular medicine, the rate of biomedical discovery can be greatly accelerated by the guidance and resources required to unearth potential collections of knowledge. A unified computational platform leverages metadata to not only provide direction but also empower researchers to mine a wealth of biomedical information and forge novel mechanistic insights. This review takes the opportunity to present an overview of the cloud-based computational environment, including the functional roles of metadata, the architecture schema of indexing and search, and the practical scenarios of machine learning-supported molecular signature extraction. By introducing several established resources and state-of-the-art workflows, we share with our readers a broadly defined informatics framework to phenotype cardiovascular health and disease. © 2018 American Heart Association, Inc.

Prediction of bacterial small RNAs in the RsmA (CsrA) and ToxT pathways: a machine learning approach.

PubMed

Fakhry, Carl Tony; Kulkarni, Prajna; Chen, Ping; Kulkarni, Rahul; Zarringhalam, Kourosh

2017-08-22

Small RNAs (sRNAs) constitute an important class of post-transcriptional regulators that control critical cellular processes in bacteria. Recent research using high-throughput transcriptomic approaches has led to a dramatic increase in the discovery of bacterial sRNAs. However, it is generally believed that the currently identified sRNAs constitute a limited subset of the bacterial sRNA repertoire. In several cases, sRNAs belonging to a specific class are already known and the challenge is to identify additional sRNAs belonging to the same class. In such cases, machine-learning approaches can be used to predict novel sRNAs in a given class. In this work, we develop novel bioinformatics approaches that integrate sequence and structure-based features to train machine-learning models for the discovery of bacterial sRNAs. We show that features derived from recurrent structural motifs in the ensemble of low energy secondary structures can distinguish the RNA classes with high accuracy. We apply this approach to predict new members in two broad classes of bacterial small RNAs: 1) sRNAs that bind to the RNA-binding protein RsmA/CsrA in diverse bacterial species and 2) sRNAs regulated by the master regulator of virulence, ToxT, in Vibrio cholerae. The involvement of sRNAs in bacterial adaptation to changing environments is an increasingly recurring theme in current research in microbiology. It is likely that future research, combining experimental and computational approaches, will discover many more examples of sRNAs as components of critical regulatory pathways in bacteria. We have developed a novel approach for prediction of small RNA regulators in important bacterial pathways. This approach can be applied to specific classes of sRNAs for which several members have been identified and the challenge is to identify additional sRNAs.

An Examination through Conjoint Analysis of the Preferences of Students Concerning Online Learning Environments According to Their Learning Styles

ERIC Educational Resources Information Center

Daghan, Gökhan; Akkoyunlu, Buket

2012-01-01

This study examines learning styles of students receiving education via online learning environments, and their preferences concerning the online learning environment. Maggie McVay Lynch Learning Style Inventory was used to determine learning styles of the students. The preferences of students concerning online learning environments were detected…

Network-based discovery through mechanistic systems biology. Implications for applications--SMEs and drug discovery: where the action is.

PubMed

Benson, Neil

2015-08-01

Phase II attrition remains the most important challenge for drug discovery. Tackling the problem requires improved understanding of the complexity of disease biology. Systems biology approaches to this problem can, in principle, deliver this. This article reviews the reports of the application of mechanistic systems models to drug discovery questions and discusses the added value. Although we are on the journey to the virtual human, the length, path and rate of learning from this remain an open question. Success will be dependent on the will to invest and make the most of the insight generated along the way. Copyright © 2015 Elsevier Ltd. All rights reserved.

7 CFR 1.642 - When must a party supplement or amend information it has previously provided?

Code of Federal Regulations, 2010 CFR

2010-01-01

... 7 Agriculture 1 2010-01-01 2010-01-01 false When must a party supplement or amend information it... When must a party supplement or amend information it has previously provided? (a) Discovery. A party must promptly supplement or amend any prior response to a discovery request if it learns that the...

Discovery Lab in the Chemistry Lecture Room: Design and Evaluation of Audio-Visual Constructivist Methodology of Teaching Descriptive Inorganic Chemistry.

ERIC Educational Resources Information Center

Young, Barbara N.; Hoffman, Lyubov

Demonstration of chemical reactions is a tool used in the teaching of inorganic descriptive chemistry to enable students to understand the fundamental concepts of chemistry through the use of concrete examples. For maximum benefit, students need to learn through discovery to observe, interpret, hypothesize, and draw conclusions; however, chemical…

On Line Instruction: An Opportunity to Re-Examine and Re-Invent Pedagogy

ERIC Educational Resources Information Center

Rosenthal, Irene

2010-01-01

Author recounts ten discoveries she made about on-line instruction that were beyond her field of vision when she was still viewing it though the lens of traditional classroom instruction. The discoveries include what she learned by reviewing the research in effective course design and a discourse analysis she conducted of the number and types of…

Video mining using combinations of unsupervised and supervised learning techniques

NASA Astrophysics Data System (ADS)

Divakaran, Ajay; Miyahara, Koji; Peker, Kadir A.; Radhakrishnan, Regunathan; Xiong, Ziyou

2003-12-01

We discuss the meaning and significance of the video mining problem, and present our work on some aspects of video mining. A simple definition of video mining is unsupervised discovery of patterns in audio-visual content. Such purely unsupervised discovery is readily applicable to video surveillance as well as to consumer video browsing applications. We interpret video mining as content-adaptive or "blind" content processing, in which the first stage is content characterization and the second stage is event discovery based on the characterization obtained in stage 1. We discuss the target applications and find that using a purely unsupervised approach are too computationally complex to be implemented on our product platform. We then describe various combinations of unsupervised and supervised learning techniques that help discover patterns that are useful to the end-user of the application. We target consumer video browsing applications such as commercial message detection, sports highlights extraction etc. We employ both audio and video features. We find that supervised audio classification combined with unsupervised unusual event discovery enables accurate supervised detection of desired events. Our techniques are computationally simple and robust to common variations in production styles etc.

Pre-Service English Teachers in Blended Learning Environment in Respect to Their Learning Approaches

ERIC Educational Resources Information Center

Yilmaz, M. Betul; Orhan, Feza

2010-01-01

Blended learning environment (BLE) is increasingly used in the world, especially in university degrees and it is based on integrating web-based learning and face-to-face (FTF) learning environments. Besides integrating different learning environments, BLE also addresses to students with different learning approaches. The "learning…

A Virtual Bioinformatics Knowledge Environment for Early Cancer Detection

NASA Technical Reports Server (NTRS)

Crichton, Daniel; Srivastava, Sudhir; Johnsey, Donald

2003-01-01

Discovery of disease biomarkers for cancer is a leading focus of early detection. The National Cancer Institute created a network of collaborating institutions focused on the discovery and validation of cancer biomarkers called the Early Detection Research Network (EDRN). Informatics plays a key role in enabling a virtual knowledge environment that provides scientists real time access to distributed data sets located at research institutions across the nation. The distributed and heterogeneous nature of the collaboration makes data sharing across institutions very difficult. EDRN has developed a comprehensive informatics effort focused on developing a national infrastructure enabling seamless access, sharing and discovery of science data resources across all EDRN sites. This paper will discuss the EDRN knowledge system architecture, its objectives and its accomplishments.

STS-102 MPLM Leonardo is transferred from the PCR into Discovery's payload bay

NASA Technical Reports Server (NTRS)

2001-01-01

KENNEDY SPACE CENTER, Fla. - The Multi-Purpose Logistics Module Leonardo is moved into Space Shuttle Discovery'''s payload bay. The primary delivery system used to resupply and return Station cargo requiring a pressurized environment, Leonardo will deliver up to 10 tons of laboratory racks filled with equipment, experiments and supplies for outfitting the newly installed U.S. Laboratory Destiny. Discovery is scheduled to launch March 8 at 6:42 a.m. EST on mission STS-102, the eighth construction flight to the International Space Station.

Data Science Priorities for a University Hospital-Based Institute of Infectious Diseases: A Viewpoint.

PubMed

Valleron, Alain-Jacques

2017-08-15

Automation of laboratory tests, bioinformatic analysis of biological sequences, and professional data management are used routinely in a modern university hospital-based infectious diseases institute. This dates back to at least the 1980s. However, the scientific methods of this 21st century are changing with the increased power and speed of computers, with the "big data" revolution having already happened in genomics and environment, and eventually arriving in medical informatics. The research will be increasingly "data driven," and the powerful machine learning methods whose efficiency is demonstrated in daily life will also revolutionize medical research. A university-based institute of infectious diseases must therefore not only gather excellent computer scientists and statisticians (as in the past, and as in any medical discipline), but also fully integrate the biologists and clinicians with these computer scientists, statisticians, and mathematical modelers having a broad culture in machine learning, knowledge representation, and knowledge discovery. © The Author 2017. Published by Oxford University Press for the Infectious Diseases Society of America. All rights reserved. For permissions, e-mail: journals.permissions@oup.com.

Interdisciplinary Aspects of Learning: Physics and Psychology

ERIC Educational Resources Information Center

Oleg, Yavoruk

2015-01-01

The article deals with interdisciplinary aspects of learning in the case of physics and psychology. It describes the lab-based academic course focused on: observation and experimentation; discovery of new scientific facts; measurement; identification of errors; the study of psychological characteristics of people (time perception, the reaction…

ZAPs: Using Interactive Programs for Learning Psychology

ERIC Educational Resources Information Center

Hulshof, Casper D.; Eysink, Tessa H. S.; Loyens, Sofie; de Jong, Ton

2005-01-01

ZAPs are short, self-contained computer programs that encourage students to experience psychological phenomena in a vivid, self-explanatory way, and that are meant to evoke enthusiasm about psychological topics. ZAPs were designed according to principles that originate from experiential and discovery learning theories. The interactive approach…

Systems Engineering Using Heritage Spacecraft Technology: Lessons Learned from Discovery and New Frontiers Deep Space Missions

NASA Technical Reports Server (NTRS)

Barley, Bryan; Newhouse, Marilyn; Clardy, Dennon

2011-01-01

In the design and development of complex spacecraft missions, project teams frequently assume the use of advanced technology or heritage systems to enable a mission or reduce the overall mission risk and cost. As projects proceed through the development life cycle, increasingly detailed knowledge of the advanced or heritage systems and the system environment identifies unanticipated issues that result in cost overruns or schedule impacts. The Discovery & New Frontiers (D&NF) Program Office recently studied cost overruns and schedule delays resulting from advanced technology or heritage assumptions for 6 D&NF missions. The goal was to identify the underlying causes for the overruns and delays, and to develop practical mitigations to assist the D&NF projects in identifying potential risks and controlling the associated impacts to proposed mission costs and schedules. The study found that the cost and schedule growth did not result from technical hurdles requiring significant technology development. Instead, systems engineering processes did not identify critical issues early enough in the design cycle to ensure project schedules and estimated costs address the inherent risks. In general, the overruns were traceable to: inadequate understanding of the heritage system s behavior within the proposed spacecraft design and mission environment; an insufficient level of experience with the heritage system; or an inadequate scoping of the system-wide impacts necessary to implement the heritage or advanced technology. This presentation summarizes the study s findings and offers suggestions for improving the project s ability to identify and manage the risks inherent in the technology and heritage design solution.

Integrating Learning, Problem Solving, and Engagement in Narrative-Centered Learning Environments

ERIC Educational Resources Information Center

Rowe, Jonathan P.; Shores, Lucy R.; Mott, Bradford W.; Lester, James C.

2011-01-01

A key promise of narrative-centered learning environments is the ability to make learning engaging. However, there is concern that learning and engagement may be at odds in these game-based learning environments. This view suggests that, on the one hand, students interacting with a game-based learning environment may be engaged but unlikely to…

Development of Transcriptomics-based Biomarkers for Selected Endocrine Disrupting Chemicals in Zebrafish (Danio rerio)

EPA Science Inventory

Genome-wide transcriptional profiling by microarrays provides a powerful platform for gene expression-based biomarker discovery. After their wide acceptance in human disease diagnosis, prognosis, and drug discovery, these gene signatures are increasingly being adopted for environ...

Development of transcriptomics-based biomarkers for selected endocrine disrupting chemicals in zebrafish (Danio rerio)

EPA Science Inventory

Genome-wide transcriptional profiling by microarrays provides a powerful platform for gene expression-based biomarker discovery. After their wide acceptance in human disease diagnosis, prognosis, and drug discovery, these gene signatures are increasingly being adopted for environ...

Knowledge Discovery in Databases.

ERIC Educational Resources Information Center

Norton, M. Jay

1999-01-01

Knowledge discovery in databases (KDD) revolves around the investigation and creation of knowledge, processes, algorithms, and mechanisms for retrieving knowledge from data collections. The article is an introductory overview of KDD. The rationale and environment of its development and applications are discussed. Issues related to database design…

Factors Influencing Learning Environments in an Integrated Experiential Program

NASA Astrophysics Data System (ADS)

Koci, Peter

The research conducted for this dissertation examined the learning environment of a specific high school program that delivered the explicit curriculum through an integrated experiential manner, which utilized field and outdoor experiences. The program ran over one semester (five months) and it integrated the grade 10 British Columbian curriculum in five subjects. A mixed methods approach was employed to identify the students' perceptions and provide richer descriptions of their experiences related to their unique learning environment. Quantitative instruments were used to assess changes in students' perspectives of their learning environment, as well as other supporting factors including students' mindfulness, and behaviours towards the environment. Qualitative data collection included observations, open-ended questions, and impromptu interviews with the teacher. The qualitative data describe the factors and processes that influenced the learning environment and give a richer, deeper interpretation which complements the quantitative findings. The research results showed positive scores on all the quantitative measures conducted, and the qualitative data provided further insight into descriptions of learning environment constructs that the students perceived as most important. A major finding was that the group cohesion measure was perceived by students as the most important attribute of their preferred learning environment. A flow chart was developed to help the researcher conceptualize how the learning environment, learning process, and outcomes relate to one another in the studied program. This research attempts to explain through the consideration of this case study: how learning environments can influence behavioural change and how an interconnectedness among several factors in the learning process is influenced by the type of learning environment facilitated. Considerably more research is needed in this area to understand fully the complexity learning environments and how they influence learning and behaviour. Keywords: learning environments; integrated experiential programs; environmental education.

Immersive Theater - a Proven Way to Enhance Learning Retention

NASA Astrophysics Data System (ADS)

Reiff, P. H.; Zimmerman, L.; Spillane, S.; Sumners, C.

2014-12-01

The portable immersive theater has gone from our first demonstration at fall AGU 2003 to a product offered by multiple companies in various versions to literally millions of users per year. As part of our NASA funded outreach program, we conducted a test of learning in a portable Discovery Dome as contrasted with learning the same materials (visuals and sound track) on a computer screen. We tested 200 middle school students (primarily underserved minorities). Paired t-tests and an independent t-test were used to compare the amount of learning that students achieved. Interest questionnaires were administered to participants in formal (public school) settings and focus groups were conducted in informal (museum camp and educational festival) settings. Overall results from the informal and formal educational setting indicated that there was a statistically significant increase in test scores after viewing We Choose Space. There was a statistically significant increase in test scores for students who viewed We Choose Space in the portable Discovery Dome (9.75) as well as with the computer (8.88). However, long-term retention of the material tested on the questionnaire indicated that for students who watched We Choose Space in the portable Discovery Dome, there was a statistically significant long-term increase in test scores (10.47), whereas, six weeks after learning on the computer, the improvements over the initial baseline (3.49) were far less and were not statistically significant. The test score improvement six weeks after learning in the dome was essentially the same as the post test immediately after watching the show, demonstrating virtually no loss of gained information in the six week interval. In the formal educational setting, approximately 34% of the respondents indicated that they wanted to learn more about becoming a scientist, while 35% expressed an interest in a career in space science. In the informal setting, 26% indicated that they were interested in pursuing a career in space science.

Computational phenotype discovery using unsupervised feature learning over noisy, sparse, and irregular clinical data.

PubMed

Lasko, Thomas A; Denny, Joshua C; Levy, Mia A

2013-01-01

Inferring precise phenotypic patterns from population-scale clinical data is a core computational task in the development of precision, personalized medicine. The traditional approach uses supervised learning, in which an expert designates which patterns to look for (by specifying the learning task and the class labels), and where to look for them (by specifying the input variables). While appropriate for individual tasks, this approach scales poorly and misses the patterns that we don't think to look for. Unsupervised feature learning overcomes these limitations by identifying patterns (or features) that collectively form a compact and expressive representation of the source data, with no need for expert input or labeled examples. Its rising popularity is driven by new deep learning methods, which have produced high-profile successes on difficult standardized problems of object recognition in images. Here we introduce its use for phenotype discovery in clinical data. This use is challenging because the largest source of clinical data - Electronic Medical Records - typically contains noisy, sparse, and irregularly timed observations, rendering them poor substrates for deep learning methods. Our approach couples dirty clinical data to deep learning architecture via longitudinal probability densities inferred using Gaussian process regression. From episodic, longitudinal sequences of serum uric acid measurements in 4368 individuals we produced continuous phenotypic features that suggest multiple population subtypes, and that accurately distinguished (0.97 AUC) the uric-acid signatures of gout vs. acute leukemia despite not being optimized for the task. The unsupervised features were as accurate as gold-standard features engineered by an expert with complete knowledge of the domain, the classification task, and the class labels. Our findings demonstrate the potential for achieving computational phenotype discovery at population scale. We expect such data-driven phenotypes to expose unknown disease variants and subtypes and to provide rich targets for genetic association studies.

Computational Phenotype Discovery Using Unsupervised Feature Learning over Noisy, Sparse, and Irregular Clinical Data

PubMed Central

Lasko, Thomas A.; Denny, Joshua C.; Levy, Mia A.

2013-01-01

Inferring precise phenotypic patterns from population-scale clinical data is a core computational task in the development of precision, personalized medicine. The traditional approach uses supervised learning, in which an expert designates which patterns to look for (by specifying the learning task and the class labels), and where to look for them (by specifying the input variables). While appropriate for individual tasks, this approach scales poorly and misses the patterns that we don’t think to look for. Unsupervised feature learning overcomes these limitations by identifying patterns (or features) that collectively form a compact and expressive representation of the source data, with no need for expert input or labeled examples. Its rising popularity is driven by new deep learning methods, which have produced high-profile successes on difficult standardized problems of object recognition in images. Here we introduce its use for phenotype discovery in clinical data. This use is challenging because the largest source of clinical data – Electronic Medical Records – typically contains noisy, sparse, and irregularly timed observations, rendering them poor substrates for deep learning methods. Our approach couples dirty clinical data to deep learning architecture via longitudinal probability densities inferred using Gaussian process regression. From episodic, longitudinal sequences of serum uric acid measurements in 4368 individuals we produced continuous phenotypic features that suggest multiple population subtypes, and that accurately distinguished (0.97 AUC) the uric-acid signatures of gout vs. acute leukemia despite not being optimized for the task. The unsupervised features were as accurate as gold-standard features engineered by an expert with complete knowledge of the domain, the classification task, and the class labels. Our findings demonstrate the potential for achieving computational phenotype discovery at population scale. We expect such data-driven phenotypes to expose unknown disease variants and subtypes and to provide rich targets for genetic association studies. PMID:23826094

The Power of Inquiry as a Way of Learning in Undergraduate Education at a Large Research University

ERIC Educational Resources Information Center

Fowler, Debra A.; Matthews, Pamela R.; Schielack, Jane F.; Webb, Robert C.; Wu, X. Ben

2012-01-01

Inquiry-guided learning (IGL) is not new to Texas A&M University, a large research-extensive institution. The ideas of asking questions and seeking answers have always been associated at this university with both learning and discovery. In this article the authors present how, as a natural extension, Texas A&M University infuses IGL more…

Learning Management Systems: Practical Considerations for the Selection and Implementation of an E-learning Platform for the Navy

DTIC Science & Technology

2007-01-28

is interested in B2B and B2C e-commerce, enterprise resource planning, e-procurement, supply-chain management, data mining, and knowledge discovery... social networking tools, collaborative spaces, knowledge management, “connecting-enabling” protocols like RSS, and other tools. The intent of the ILE...delivered to them, what learning pedagogy is appropriate for them, the optimal level of social interaction for learning, and available resources

Guidelines for Developing and Reporting Machine Learning Predictive Models in Biomedical Research: A Multidisciplinary View

PubMed Central

2016-01-01

Background As more and more researchers are turning to big data for new opportunities of biomedical discoveries, machine learning models, as the backbone of big data analysis, are mentioned more often in biomedical journals. However, owing to the inherent complexity of machine learning methods, they are prone to misuse. Because of the flexibility in specifying machine learning models, the results are often insufficiently reported in research articles, hindering reliable assessment of model validity and consistent interpretation of model outputs. Objective To attain a set of guidelines on the use of machine learning predictive models within clinical settings to make sure the models are correctly applied and sufficiently reported so that true discoveries can be distinguished from random coincidence. Methods A multidisciplinary panel of machine learning experts, clinicians, and traditional statisticians were interviewed, using an iterative process in accordance with the Delphi method. Results The process produced a set of guidelines that consists of (1) a list of reporting items to be included in a research article and (2) a set of practical sequential steps for developing predictive models. Conclusions A set of guidelines was generated to enable correct application of machine learning models and consistent reporting of model specifications and results in biomedical research. We believe that such guidelines will accelerate the adoption of big data analysis, particularly with machine learning methods, in the biomedical research community. PMID:27986644

Perceptual learning modules in mathematics: enhancing students' pattern recognition, structure extraction, and fluency.

PubMed

Kellman, Philip J; Massey, Christine M; Son, Ji Y

2010-04-01

Learning in educational settings emphasizes declarative and procedural knowledge. Studies of expertise, however, point to other crucial components of learning, especially improvements produced by experience in the extraction of information: perceptual learning (PL). We suggest that such improvements characterize both simple sensory and complex cognitive, even symbolic, tasks through common processes of discovery and selection. We apply these ideas in the form of perceptual learning modules (PLMs) to mathematics learning. We tested three PLMs, each emphasizing different aspects of complex task performance, in middle and high school mathematics. In the MultiRep PLM, practice in matching function information across multiple representations improved students' abilities to generate correct graphs and equations from word problems. In the Algebraic Transformations PLM, practice in seeing equation structure across transformations (but not solving equations) led to dramatic improvements in the speed of equation solving. In the Linear Measurement PLM, interactive trials involving extraction of information about units and lengths produced successful transfer to novel measurement problems and fraction problem solving. Taken together, these results suggest (a) that PL techniques have the potential to address crucial, neglected dimensions of learning, including discovery and fluent processing of relations; (b) PL effects apply even to complex tasks that involve symbolic processing; and (c) appropriately designed PL technology can produce rapid and enduring advances in learning. Copyright © 2009 Cognitive Science Society, Inc.

Behavioral studies on anxiety and depression in a drug discovery environment: keys to a successful future.

PubMed

Bouwknecht, J Adriaan

2015-04-15

The review describes a personal journey through 25 years of animal research with a focus on the contribution of rodent models for anxiety and depression to the development of new medicines in a drug discovery environment. Several classic acute models for mood disorders are briefly described as well as chronic stress and disease-induction models. The paper highlights a variety of factors that influence the quality and consistency of behavioral data in a laboratory setting. The importance of meta-analysis techniques for study validation (tolerance interval) and assay sensitivity (Monte Carlo modeling) are demonstrated by examples that use historic data. It is essential for successful discovery of new potential drugs to maintain a high level of control in animal research and to bridge knowledge across in silico modeling, and in vitro and in vivo assays. Today, drug discovery is a highly dynamic environment in search of new types of treatments and new animal models which should be guided by enhanced two-way translation between bench and bed. Although productivity has been disappointing in the search of new and better medicines in psychiatry over the past decades, there has been and will always be an important role for in vivo models in-between preclinical discovery and clinical development. The right balance between good science and proper judgment versus a decent level of innovation, assay development and two-way translation will open the doors to a very bright future. Copyright © 2014 Elsevier B.V. All rights reserved.

Science is Cool with NASA's "Space School Musical"

NASA Astrophysics Data System (ADS)

Asplund, S.

2011-10-01

To help young learners understand basic solar system science concepts and retain what they learn, NASA's Discovery and New Frontiers Programs have collaborated with KidTribe to create "Space School Musical," an innovative approach for teaching about the solar system. It's an educational "hip-hopera" that raps, rhymes, moves and grooves its way into the minds and memories of students and educators alike. The solar system comes alive, combining science content with music, fun lyrics, and choreography. Kids can watch the videos, learn the songs, do the cross-curricular activities, and perform the show themselves. The videos, songs, lyrics, and guides are available to all with free downloads at http://discovery.nasa.gov/

Effective Learning of Probabilistic Models for Clinical Predictions from Longitudinal Data

ERIC Educational Resources Information Center

Yang, Shuo

2017-01-01

With the expeditious advancement of information technologies, health-related data presented unprecedented potentials for medical and health discoveries but at the same time significant challenges for machine learning techniques both in terms of size and complexity. Those challenges include: the structured data with various storage formats and…

Making the Science Literacy Connection: After-School Science Clubs

ERIC Educational Resources Information Center

Moore-Hart, Margaret A.; Liggit, Peggy; Daisey, Peggy

2004-01-01

Children make discoveries spontaneously while participating in hands-on science learning experiences. The students in this study were attending an after-school science program that was organized around authentic literacy activities and hands-on science learning experiences related to the theme of wetlands. Literacy connections formed natural…

A Dynamic Community of Discovery: Planning, Learning, and Change

ERIC Educational Resources Information Center

Gordon, Michelle; Ireland, Martha; Wong, Mina

2011-01-01

Ryerson University's Prior Learning and Competency Evaluation and Documentation (PLACED) program is funded by the Government of Ontario to engage internationally educated professionals (IEPs), employers, and regulatory/occupational bodies in the use of competency-based practices. In 2008, the authors created a self-assessment tool for IEPs that…

Putting the Laboratory at the Center of Teaching Chemistry

ERIC Educational Resources Information Center

Bopegedera, A. M. R. P.

2011-01-01

This article describes an effective approach to teaching chemistry by bringing the laboratory to the center of teaching, to bring the excitement of discovery to the learning process. The lectures and laboratories are closely integrated to provide a holistic learning experience. The laboratories progress from verification to open-inquiry and…

Expeditionary Learning in Information Systems: Definition, Implementation, and Assessment

ERIC Educational Resources Information Center

Abrahams, Alan S.; Singh, Tirna

2013-01-01

In the natural sciences, collecting, cataloguing, and comparing living specimens have long been a popular, collaborative mode of discovery and learning. New species are discovered, and the relationships between species are theorized. From Aristotle's "History of Animals" to Darwin's "On the Origin of Species", and beyond, this…

Animals without Backbones: The Invertebrate Story. Grade Level 5-9.

ERIC Educational Resources Information Center

Jerome, Brian; Fuqua, Paul

This guide, when used in tandem with the videotape "Animals Without Backbones," helps students learn about invertebrates. These materials promote hands-on discovery and learning. The guide is composed of six curriculum-based teaching units: (1) "Getting Started"; (2) "Porifera"; (3) "Cnidarians"; (4) "Worms"; (5) "Mollusks"; (6) "Arthropods"; and…

A Practice-Oriented Review of Learning Objects

ERIC Educational Resources Information Center

Sinclair, J.; Joy, M.; Yau, J. Y.-K.; Hagan, S.

2013-01-01

Reusable learning objects support packaging of educational materials allowing their discovery and reuse. Open educational resources emphasize the need for open licensing and promote sharing and community involvement. For both teachers and learners, finding appropriate tried and tested resources on a topic of interest and being able to incorporate…

A Comparison of the Effects of Two Instructional Sequences Involving Science Laboratory Activities.

ERIC Educational Resources Information Center

Ivins, Jerry Edward

This study attempted to determine if students learn science concepts better when laboratories are used to verify concepts already intorduced through lectures and textbooks (verification laboratories or whether achievement and retention are improved when laboratories are used to introduce new concepts (directed discovery learning laboratories). The…

Hypermedia in Vocational Learning: A Hypermedia Learning Environment for Training Management Skills

ERIC Educational Resources Information Center

Konradt, Udo

2004-01-01

A learning environment is defined as an arrangement of issues, methods, techniques, and media in a given domain. Besides temporal and spatial features a learning environment considers the social situation in which learning takes place. In (hypermedia) learning environments the concept of exploration and the active role of the learner is…

Using Wikis as a Support and Assessment Tool in Collaborative Digital Game-Based Learning Environments

ERIC Educational Resources Information Center

Samur, Yavuz

2011-01-01

In computer-supported collaborative learning (CSCL) environments, there are many researches done on collaborative learning activities; however, in game-based learning environments, more research and literature on collaborative learning activities are required. Actually, both game-based learning environments and wikis enable us to use new chances…

Assessing culturally sensitive factors in the learning environment of science classrooms

NASA Astrophysics Data System (ADS)

Fisher, Darrell L.; Waldrip, Bruce G.

1997-03-01

As schools are becoming increasingly diverse in their scope and clientele, any examination of the interaction of culturally sensitive factors of students' learning environments with learning science assumes critical importance. The purpose of this exploratory study was to develop an instrument to assess learning environment factors that are culturally sensitive, to provide initial validation information on the instrument and to examine associations between students' perceptions of their learning environments and their attitudes towards science and achievement of enquiry skills. A measure of these factors of science student's learning environment, namely the Cultural Learning Environment Questionnaire (CLEQ), was developed from past learning environment instruments and influenced by Hofstede's four dimensions of culture (Power Distance, Uncertainty Avoidance, Individualism, and Masculinity/Femininity). The reliability and discriminant validity for each scale were obtained and associations between learning environment, attitude to science and enquiry skills achievement were found.

Outsourcing drug discovery to India and China: from surviving to thriving.

PubMed

Subramaniam, Swaminathan; Dugar, Sundeep

2012-10-01

Global pharmaceutical companies face an increasingly harsh environment for their primary business of selling medicines. They have to contend with a spiraling decline in the productivity of their R&D programs that is guaranteed to severely diminish their growth prospects. Outsourcing of drug discovery activities to low-cost locations is a growing response to this crisis. However, the upsides to outsourcing are capped by the failure of global pharmaceutical companies to take advantage of the full range of possibilities that this model provides. Companies that radically rethink and transform the way they conduct R&D, such as seeking the benefits of low-cost locations in India and China will be the ones that thrive in this environment. In this article we present our views on how the outsourcing model in drug discovery should go beyond increasing the efficiency of existing drug discovery processes to a fundamental rethink and re-engineering of these processes. Copyright © 2012. Published by Elsevier Ltd.

The Effects of the Compasslearning Odyssey Spiral-Up Program on Discovery Education Scores of Sixth-Grade Gifted and High-Performing Language Arts Students

ERIC Educational Resources Information Center

Kelsey, Carmen Freeman

2012-01-01

The purpose of this study was to examine the relationship between the implementation of the Response to Intervention (RTI) model CompassLearning Odyssey and the performance of middle school language arts students on the Discovery Education Test B and Tennessee Comprehensive Assessment Program (TCAP) along with examining teacher perceptions of high…

[Use of hypertext as information and training tools in the prevention of occupational risk].

PubMed

Franco, G

1998-01-01

Modern medical education is based on a variety of teaching techniques, by means of which individuals learn most effectively. The availability of the new technologies together with the diffusion of personal computers is favouring the spreading of the use of hypertexts through the World Wide Web. This contribution describes 2 hypertexts ("Human Activities and Health Risk"; "Occupation, Risk and Disease. A Problem-Oriented Hypertext-Tool to Learn Occupational Medicine") and the prototype "Virtual Hospital". Assuming that prevention of health risks is based upon their knowledge, they have been created with the aim of providing users with problem-oriented tools, whose retorical aspects (content, information organization, user interface) are analysed. The "Human Activities and Health Risk" deals with the description of working activities and allows user to recognize health risks. The "Occupation, Risk and Disease. A Problem-Oriented Hypertext-Tool to Learn Occupational Medicine" embodies a case report containing the clustered information about the patient and the library including educational material (risk factors, symptoms and signs, organ system diseases, jobs, occupational risk factors, environment related diseases. The "Virtual Hospital" has been conceived assuming that an appropriate information can change workers' behaviour in hospital, where health risks can be often underevaluated. It consists of a variety of structured and unstructured information, which can be browsed by users, allowing the discovery of links and providing the awareness of the semantic relationship between related information elements (including environment, instruments, drugs, job analysis, situations at risk for health, preventive means). The "Virtual Hospital" aims making the understanding of the working situations at risk easier and more interesting, stimulating the awareness of the relationship between jobs and risks.

An Analysis Pipeline with Statistical and Visualization-Guided Knowledge Discovery for Michigan-Style Learning Classifier Systems

PubMed Central

Urbanowicz, Ryan J.; Granizo-Mackenzie, Ambrose; Moore, Jason H.

2014-01-01

Michigan-style learning classifier systems (M-LCSs) represent an adaptive and powerful class of evolutionary algorithms which distribute the learned solution over a sizable population of rules. However their application to complex real world data mining problems, such as genetic association studies, has been limited. Traditional knowledge discovery strategies for M-LCS rule populations involve sorting and manual rule inspection. While this approach may be sufficient for simpler problems, the confounding influence of noise and the need to discriminate between predictive and non-predictive attributes calls for additional strategies. Additionally, tests of significance must be adapted to M-LCS analyses in order to make them a viable option within fields that require such analyses to assess confidence. In this work we introduce an M-LCS analysis pipeline that combines uniquely applied visualizations with objective statistical evaluation for the identification of predictive attributes, and reliable rule generalizations in noisy single-step data mining problems. This work considers an alternative paradigm for knowledge discovery in M-LCSs, shifting the focus from individual rules to a global, population-wide perspective. We demonstrate the efficacy of this pipeline applied to the identification of epistasis (i.e., attribute interaction) and heterogeneity in noisy simulated genetic association data. PMID:25431544

Information flow through threespine stickleback networks without social transmission

PubMed Central

Atton, N.; Hoppitt, W.; Webster, M. M.; Galef, B. G.; Laland, K. N.

2012-01-01

Social networks can result in directed social transmission of learned information, thus influencing how innovations spread through populations. Here we presented shoals of threespine sticklebacks (Gasterosteous aculeatus) with two identical foraging tasks and applied network-based diffusion analysis (NBDA) to determine whether the order in which individuals in a social group contacted and solved the tasks was affected by the group's network structure. We found strong evidence for a social effect on discovery of the foraging tasks with individuals tending to discover a task sooner when others in their group had previously done so, and with the spread of discovery of the foraging tasks influenced by groups' social networks. However, the same patterns of association did not reliably predict spread of solution to the tasks, suggesting that social interactions affected the time at which the tasks were discovered, but not the latency to its solution following discovery. The present analysis, one of the first applications of NBDA to a natural animal system, illustrates how NBDA can lead to insight into the mechanisms supporting behaviour acquisition that more conventional statistical approaches might miss. Importantly, we provide the first compelling evidence that the spread of novel behaviours can result from social learning in the absence of social transmission, a phenomenon that we refer to as an untransmitted social effect on learning. PMID:22896644

Relationship between learning environment characteristics and academic engagement.

PubMed

Opdenakker, Marie-Christine; Minnaert, Alexander

2011-08-01

The relationship between learning environment characteristics and academic engagement of 777 Grade 6 children located in 41 learning environments was explored. Questionnaires were used to tap learning environment perceptions of children, their academic engagement, and their ethnic-cultural background. The basis of the learning environment questionnaire was the International System for Teacher Observation and Feedback (ISTOF). Factor analysis indicated three factors: the teacher as a helpful and good instructor (having good instructional skills, clear instruction), the teacher as promoter of active learning and differentiation, and the teacher as manager and organizer of classroom activities. Multilevel analysis indicated that about 12% of the differences in engagement between children was related to the learning environment. All the mentioned learning environment characteristics mattered, but the teacher as a helpful, good instructor was most important followed by the teacher as promoter of active learning and differentiation.

Nigerian Physiotherapy Clinical Students' Perception of Their Learning Environment Measured by the Dundee Ready Education Environment Measure Inventory

ERIC Educational Resources Information Center

Odole, Adesola C.; Oyewole, Olufemi O.; Ogunmola, Oluwasolape T.

2014-01-01

The identification of the learning environment and the understanding of how students learn will help teacher to facilitate learning and plan a curriculum to achieve the learning outcomes. The purpose of this study was to investigate undergraduate physiotherapy clinical students' perception of University of Ibadan's learning environment. Using the…

Supporting cognitive engagement in a learning-by-doing learning environment: Case studies of participant engagement and social configurations in Kitchen Science Investigators

NASA Astrophysics Data System (ADS)

Gardner, Christina M.

Learning-by-doing learning environments support a wealth of physical engagement in activities. However, there is also a lot of variability in what participants learn in each enactment of these types of environments. Therefore, it is not always clear how participants are learning in these environments. In order to design technologies to support learning in these environments, we must have a greater understanding of how participants engage in learning activities, their goals for their engagement, and the types of help they need to cognitively engage in learning activities. To gain a greater understanding of participant engagement and factors and circumstances that promote and inhibit engagement, this dissertation explores and answers several questions: What are the types of interactions and experiences that promote and /or inhibit learning and engagement in learning-by-doing learning environments? What are the types of configurations that afford or inhibit these interactions and experiences in learning-by-doing learning environments? I explore answers to these questions through the context of two enactments of Kitchen Science Investigators (KSI), a learning-by-doing learning environment where middle-school aged children learn science through cooking from customizing recipes to their own taste and texture preferences. In small groups, they investigate effects of ingredients through the design of cooking and science experiments, through which they experience and learn about chemical, biological, and physical science phenomena and concepts (Clegg, Gardner, Williams, & Kolodner, 2006). The research reported in this dissertation sheds light on the different ways participant engagement promotes and/or inhibits cognitive engagement in by learning-by-doing learning environments through two case studies. It also provides detailed descriptions of the circumstances (social, material, and physical configurations) that promote and/or inhibit participant engagement in these learning environments through cross-case analyses of these cases. Finally, it offers suggestions about structuring activities, selecting materials and resources, and designing facilitation and software-realized scaffolding in the design of these types of learning environments. These design implications focus on affording participant engagement in science content and practices learning. Overall, the case studies, cross-case analyses, and empirically-based design implications begin to bridge the gap between theory and practice in the design and implementation of these learning environments. This is demonstrated by providing detailed and explanatory examples and factors that affect how participants take up the affordances of the learning opportunities designed into these learning environments.

How People Learn in an Asynchronous Online Learning Environment: The Relationships between Graduate Students' Learning Strategies and Learning Satisfaction

ERIC Educational Resources Information Center

Choi, Beomkyu

2016-01-01

The purpose of this study was to examine the relationships between learners' learning strategies and learning satisfaction in an asynchronous online learning environment. In an attempt to shed some light on how people learn in an online learning environment, one hundred and sixteen graduate students who were taking online learning courses…

40 CFR 164.51 - Other discovery.

Code of Federal Regulations, 2010 CFR

2010-07-01

... 40 Protection of Environment 23 2010-07-01 2010-07-01 false Other discovery. 164.51 Section 164.51... GOVERNING HEARINGS, UNDER THE FEDERAL INSECTICIDE, FUNGICIDE, AND RODENTICIDE ACT, ARISING FROM REFUSALS TO... OTHER HEARINGS CALLED PURSUANT TO SECTION 6 OF THE ACT General Rules of Practice Concerning Proceedings...

What songbirds teach us about learning

NASA Astrophysics Data System (ADS)

Brainard, Michael S.; Doupe, Allison J.

2002-05-01

Bird fanciers have known for centuries that songbirds learn their songs. This learning has striking parallels to speech acquisition: like humans, birds must hear the sounds of adults during a sensitive period, and must hear their own voice while learning to vocalize. With the discovery and investigation of discrete brain structures required for singing, songbirds are now providing insights into neural mechanisms of learning. Aided by a wealth of behavioural observations and species diversity, studies in songbirds are addressing such basic issues in neuroscience as perceptual and sensorimotor learning, developmental regulation of plasticity, and the control and function of adult neurogenesis.

Knowledge discovery based on experiential learning corporate culture management

NASA Astrophysics Data System (ADS)

Tu, Kai-Jan

2014-10-01

A good corporate culture based on humanistic theory can make the enterprise's management very effective, all enterprise's members have strong cohesion and centripetal force. With experiential learning model, the enterprise can establish an enthusiastic learning spirit corporate culture, have innovation ability to gain the positive knowledge growth effect, and to meet the fierce global marketing competition. A case study on Trend's corporate culture can offer the proof of industry knowledge growth rate equation as the contribution to experiential learning corporate culture management.

Scaffolding in Connectivist Mobile Learning Environment

ERIC Educational Resources Information Center

Ozan, Ozlem

2013-01-01

Social networks and mobile technologies are transforming learning ecology. In this changing learning environment, we find a variety of new learner needs. The aim of this study is to investigate how to provide scaffolding to the learners in connectivist mobile learning environment: (1) to learn in a networked environment; (2) to manage their…

Online Resource-Based Learning Environment: Case Studies in Primary Classrooms

ERIC Educational Resources Information Center

So, Winnie Wing Mui; Ching, Fiona Ngai Ying

2012-01-01

This paper discusses the creation of learning environments with online resources by three primary school teachers for pupil's learning of science-related topics with reference to the resource-based e-learning environments (RBeLEs) framework. Teachers' choice of contexts, resources, tools, and scaffolds in designing the learning environments are…

The Predicaments of Language Learners in Traditional Learning Environments

ERIC Educational Resources Information Center

Shafie, Latisha Asmaak; Mansor, Mahani

2009-01-01

Some public universities in developing countries have traditional language learning environments such as classrooms with only blackboards and furniture which do not provide conducive learning environments. These traditional environments are unable to cater for digital learners who need to learn with learning technologies. In order to create…

The Integration of Personal Learning Environments & Open Network Learning Environments

ERIC Educational Resources Information Center

Tu, Chih-Hsiung; Sujo-Montes, Laura; Yen, Cherng-Jyh; Chan, Junn-Yih; Blocher, Michael

2012-01-01

Learning management systems traditionally provide structures to guide online learners to achieve their learning goals. Web 2.0 technology empowers learners to create, share, and organize their personal learning environments in open network environments; and allows learners to engage in social networking and collaborating activities. Advanced…

Experiential Learning and Learning Environments: The Case of Active Listening Skills

ERIC Educational Resources Information Center

Huerta-Wong, Juan Enrique; Schoech, Richard

2010-01-01

Social work education research frequently has suggested an interaction between teaching techniques and learning environments. However, this interaction has never been tested. This study compared virtual and face-to-face learning environments and included active listening concepts to test whether the effectiveness of learning environments depends…

STS-102 MPLM Leonardo is transferred from the PCR into Discovery's payload bay

NASA Technical Reports Server (NTRS)

2001-01-01

KENNEDY SPACE CENTER, Fla. - In the Payload Changeout Room, Launch Pad 39B, the Multi-Purpose Logistics Module Leonardo is ready to be transferred into Space Shuttle Discovery'''s payload bay. Discovery is scheduled to launch March 8 at 6:42 a.m. EST on mission STS-102, the eighth construction flight to the International Space Station. The primary delivery system used to resupply and return Station cargo requiring a pressurized environment, Leonardo will deliver up to 10 tons of laboratory racks filled with equipment, experiments and supplies for outfitting the newly installed U.S. Laboratory Destiny.

The role of the basal ganglia in learning and memory: Insight from Parkinson's disease

PubMed Central

2013-01-01

It has long been known that memory is not a single process. Rather, there are different kinds of memory that are supported by distinct neural systems. This idea stemmed from early findings of dissociable patterns of memory impairments in patients with selective damage to different brain regions. These studies highlighted the role of the basal ganglia in non-declarative memory, such as procedural or habit learning, contrasting it with the known role of the medial temporal lobes in declarative memory. In recent years, major advances across multiple areas of neuroscience have revealed an important role for the basal ganglia in motivation and decision making. These findings have led to new discoveries about the role of the basal ganglia in learning and highlighted the essential role of dopamine in specific forms of learning. Here we review these recent advances with an emphasis on novel discoveries from studies of learning in patients with Parkinson's disease. We discuss how these findings promote the development of current theories away from accounts that emphasize the verbalizability of the contents of memory and towards a focus on the specific computations carried out by distinct brain regions. Finally, we discuss new challenges that arise in the face of accumulating evidence for dynamic and interconnected memory systems that jointly contribute to learning. PMID:21945835

Critical role for the mediodorsal thalamus in permitting rapid reward-guided updating in stochastic reward environments

PubMed Central

Chakraborty, Subhojit; Kolling, Nils; Walton, Mark E; Mitchell, Anna S

2016-01-01

Adaptive decision-making uses information gained when exploring alternative options to decide whether to update the current choice strategy. Magnocellular mediodorsal thalamus (MDmc) supports adaptive decision-making, but its causal contribution is not well understood. Monkeys with excitotoxic MDmc damage were tested on probabilistic three-choice decision-making tasks. They could learn and track the changing values in object-reward associations, but they were severely impaired at updating choices after reversals in reward contingencies or when there were multiple options associated with reward. These deficits were not caused by perseveration or insensitivity to negative feedback though. Instead, monkeys with MDmc lesions exhibited an inability to use reward to promote choice repetition after switching to an alternative option due to a diminished influence of recent past choices and the last outcome to guide future behavior. Together, these data suggest MDmc allows for the rapid discovery and persistence with rewarding options, particularly in uncertain or changing environments. DOI: http://dx.doi.org/10.7554/eLife.13588.001 PMID:27136677

Earth System Grid II, Turning Climate Datasets into Community Resources

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

Middleton, Don

2006-08-01

The Earth System Grid (ESG) II project, funded by the Department of Energy’s Scientific Discovery through Advanced Computing program, has transformed climate data into community resources. ESG II has accomplished this goal by creating a virtual collaborative environment that links climate centers and users around the world to models and data via a computing Grid, which is based on the Department of Energy’s supercomputing resources and the Internet. Our project’s success stems from partnerships between climate researchers and computer scientists to advance basic and applied research in the terrestrial, atmospheric, and oceanic sciences. By interfacing with other climate science projects,more » we have learned that commonly used methods to manage and remotely distribute data among related groups lack infrastructure and under-utilize existing technologies. Knowledge and expertise gained from ESG II have helped the climate community plan strategies to manage a rapidly growing data environment more effectively. Moreover, approaches and technologies developed under the ESG project have impacted datasimulation integration in other disciplines, such as astrophysics, molecular biology and materials science.« less

Scalable non-negative matrix tri-factorization.

PubMed

Čopar, Andrej; Žitnik, Marinka; Zupan, Blaž

2017-01-01

Matrix factorization is a well established pattern discovery tool that has seen numerous applications in biomedical data analytics, such as gene expression co-clustering, patient stratification, and gene-disease association mining. Matrix factorization learns a latent data model that takes a data matrix and transforms it into a latent feature space enabling generalization, noise removal and feature discovery. However, factorization algorithms are numerically intensive, and hence there is a pressing challenge to scale current algorithms to work with large datasets. Our focus in this paper is matrix tri-factorization, a popular method that is not limited by the assumption of standard matrix factorization about data residing in one latent space. Matrix tri-factorization solves this by inferring a separate latent space for each dimension in a data matrix, and a latent mapping of interactions between the inferred spaces, making the approach particularly suitable for biomedical data mining. We developed a block-wise approach for latent factor learning in matrix tri-factorization. The approach partitions a data matrix into disjoint submatrices that are treated independently and fed into a parallel factorization system. An appealing property of the proposed approach is its mathematical equivalence with serial matrix tri-factorization. In a study on large biomedical datasets we show that our approach scales well on multi-processor and multi-GPU architectures. On a four-GPU system we demonstrate that our approach can be more than 100-times faster than its single-processor counterpart. A general approach for scaling non-negative matrix tri-factorization is proposed. The approach is especially useful parallel matrix factorization implemented in a multi-GPU environment. We expect the new approach will be useful in emerging procedures for latent factor analysis, notably for data integration, where many large data matrices need to be collectively factorized.

The Role of the Constructivist Learning Theory and Collaborative Learning Environment on Wiki Classroom, and the Relationship between Them

ERIC Educational Resources Information Center

Alzahrani, Ibraheem; Woollard, John

2013-01-01

This paper seeks to discover the relationship between both the social constructivist learning theory and the collaborative learning environment. This relationship can be identified by giving an example of the learning environment. Due to wiki characteristics, Wiki technology is one of the most famous learning environments that can show the…

Practice education learning environments: the mismatch between perceived and preferred expectations of undergraduate health science students.

PubMed

Brown, Ted; Williams, Brett; McKenna, Lisa; Palermo, Claire; McCall, Louise; Roller, Louis; Hewitt, Lesley; Molloy, Liz; Baird, Marilyn; Aldabah, Ligal

2011-11-01

Practical hands-on learning opportunities are viewed as a vital component of the education of health science students, but there is a critical shortage of fieldwork placement experiences. It is therefore important that these clinical learning environments are well suited to students' perceptions and expectations. To investigate how undergraduate students enrolled in health-related education programs view their clinical learning environments and specifically to compare students' perception of their 'actual' clinical learning environment to that of their 'preferred/ideal' clinical learning environment. The Clinical Learning Environment Inventory (CLEI) was used to collect data from 548 undergraduate students (55% response rate) enrolled in all year levels of paramedics, midwifery, radiography and medical imaging, occupational therapy, pharmacy, nutrition and dietetics, physiotherapy and social work at Monash University via convenience sampling. Students were asked to rate their perception of the clinical learning environment at the completion of their placements using the CLEI. Satisfaction of the students enrolled in the health-related disciplines was closely linked with the five constructs measured by the CLEI: Personalization, Student Involvement, Task Orientation, Innovation, and Individualization. Significant differences were found between the student's perception of their 'actual' clinical learning environment and their 'ideal' clinical learning environment. The study highlights the importance of a supportive clinical learning environment that places emphasis on effective two-way communication. A thorough understanding of students' perceptions of their clinical learning environments is essential. Copyright © 2010 Elsevier Ltd. All rights reserved.

Open Drug Discovery Toolkit (ODDT): a new open-source player in the drug discovery field.

PubMed

Wójcikowski, Maciej; Zielenkiewicz, Piotr; Siedlecki, Pawel

2015-01-01

There has been huge progress in the open cheminformatics field in both methods and software development. Unfortunately, there has been little effort to unite those methods and software into one package. We here describe the Open Drug Discovery Toolkit (ODDT), which aims to fulfill the need for comprehensive and open source drug discovery software. The Open Drug Discovery Toolkit was developed as a free and open source tool for both computer aided drug discovery (CADD) developers and researchers. ODDT reimplements many state-of-the-art methods, such as machine learning scoring functions (RF-Score and NNScore) and wraps other external software to ease the process of developing CADD pipelines. ODDT is an out-of-the-box solution designed to be easily customizable and extensible. Therefore, users are strongly encouraged to extend it and develop new methods. We here present three use cases for ODDT in common tasks in computer-aided drug discovery. Open Drug Discovery Toolkit is released on a permissive 3-clause BSD license for both academic and industrial use. ODDT's source code, additional examples and documentation are available on GitHub (https://github.com/oddt/oddt).

Next-Generation Machine Learning for Biological Networks.

PubMed

Camacho, Diogo M; Collins, Katherine M; Powers, Rani K; Costello, James C; Collins, James J

2018-06-14

Machine learning, a collection of data-analytical techniques aimed at building predictive models from multi-dimensional datasets, is becoming integral to modern biological research. By enabling one to generate models that learn from large datasets and make predictions on likely outcomes, machine learning can be used to study complex cellular systems such as biological networks. Here, we provide a primer on machine learning for life scientists, including an introduction to deep learning. We discuss opportunities and challenges at the intersection of machine learning and network biology, which could impact disease biology, drug discovery, microbiome research, and synthetic biology. Copyright © 2018 Elsevier Inc. All rights reserved.

Transforming Education Research through Open Video Data Sharing

ERIC Educational Resources Information Center

Gilmore, Rick O.; Adolph, Karen E.; Millman, David S.; Gordon, Andrew

2016-01-01

Open data sharing promises to accelerate the pace of discovery in the developmental and learning sciences, but significant technical, policy, and cultural barriers have limited its adoption. As a result, most research on learning and development remains shrouded in a culture of isolation. Data sharing is the rare exception (Gilmore, 2016). Many…

Pennies and Eggs: Initiation into Inquiry Learning for Preservice Elementary Education Teachers

ERIC Educational Resources Information Center

Wink, Donald J.; Hwang-Choe, Jeong Hye

2008-01-01

Two labs incorporating the Science Writing Heuristic are described that introduce scientific inquiry in a course for preservice students majoring in elementary education. One lab adapts a previously described discovery learning opportunity involving the change in composition and mass of pennies in 1982. The other involves the use of flotation…

The Impact of Guidance during Problem-Solving Prior to Instruction on Students' Inventions and Learning Outcomes

ERIC Educational Resources Information Center

Loibl, Katharina; Rummel, Nikol

2014-01-01

Multiple studies have shown benefits of problem-solving prior to instruction (cf. Productive Failure, Invention) in comparison to direct instruction. However, students' solutions prior to instruction are usually erroneous or incomplete. In analogy to "guided" discovery learning, it might therefore be fruitful to lead students…

Renewing Liberal Education as Vocational Discernment

ERIC Educational Resources Information Center

Sullivan, William M.

2014-01-01

A major discovery, or rediscovery, of this time is that an education that matters--an education that enhances capacities and expands outlooks--is one that engages the whole student. Research in learning has shown that making sense of the world and learning to use knowledge and skills in responsible and engaged ways--long the developmental goals of…

The Embodied Narrative Nature of Learning: Nurture in School

ERIC Educational Resources Information Center

Delafield-Butt, Jonathan T.; Adie, Jillian

2016-01-01

Learning is participatory and embodied. It requires active participation from both teacher and learner to come together to co-create shared projects of discovery that allow meaning to unfold and develop between them. This article advances theory on the intersubjective and embodied nature of cognition and meaning-making as constituted by co-created…

Defence of Foreign Language Teaching in Secondary Schools

ERIC Educational Resources Information Center

Van Passel, F. J. A.

1974-01-01

Shows the necessity of foreign language education for cognitive and attitudinal purposes as well as for utilitarian reasons. Foreign language learning/teaching can be of great educational value when it follows the thread of the logical and psychological steps in the creative/discovery procedure. A learning algorithm is mapped on page 61. See FL…

Has the Construct "Intelligence" Determined Our Perception of Cognitive Hierarchy?

ERIC Educational Resources Information Center

Fuller, Renee

The discovery that retarded children can learn to read with comprehension suggests a critique of current educational testing and teaching practices. IQ tests, consisting of segmental, out-of-context tasks, originally were based on turn-of-the-century educational techniques that emphasized rote and segmental learning. Currently, most IQ tests still…

Students' Individual Schematization Pathways--Empirical Reconstructions for the Case of Part-of-Part Determination for Fractions

ERIC Educational Resources Information Center

Glade, Matthias; Prediger, Susanne

2017-01-01

According to the design principle of progressive schematization, learning trajectories towards procedural rules can be organized as independent discoveries when the learning arrangement invites the students first to develop models for mathematical concepts and model-based informal strategies; then to explore the strategies and to discover pattern…

Technologically and Artistically Enhanced Multi-Sensory Computer-Programming Education

ERIC Educational Resources Information Center

Katai, Zoltan; Toth, Laszlo

2010-01-01

Over the last decades more and more research has analysed relatively new or rediscovered teaching-learning concepts like blended, hybrid, multi-sensory or technologically enhanced learning. This increased interest in these educational forms can be explained by new exciting discoveries in brain research and cognitive psychology, as well as by the…

Designing a WebQuest

ERIC Educational Resources Information Center

Salsovic, Annette R.

2009-01-01

A WebQuest is an inquiry-based lesson plan that uses the Internet. This article explains what a WebQuest is, shows how to create one, and provides an example. When engaged in a WebQuest, students use technology to experience cooperative learning and discovery learning while honing their research, writing, and presentation skills. It has been found…

Dissociable roles of medial and lateral PFC in rule learning.

PubMed

Cao, Bihua; Li, Wei; Li, Fuhong; Li, Hong

2016-11-01

Although the neural basis of rule learning is of great interest to cognitive neuroscientists, the pattern of transient brain activation during rule discovery remains to be investigated. In this study, we measured event-related functional magnetic resonance imaging (fMRI) during distinct phases of rule learning. Twenty-one healthy human volunteers were presented with a series of cards, each containing a clock-like display of 12 circles numbered sequentially. Participants were instructed that a fictitious animal would move from one circle to another either in a regular pattern (according to a rule hidden in consecutive trials) or randomly. Participants were then asked to judge whether a given step followed a rule. While the rule-search phase evoked more activation in the posterior lateral prefrontal cortex (LPFC), the rule-following phase caused stronger activation in the anterior medial prefrontal cortex (MPFC). Importantly, the intermediate phase, the rule-discovery phase evoked more activations in MPFC and dorsal anterior cingulate cortex (dACC) than rule search, and more activations in LPFC than rule following. Therefore, we can conclude that the medial and lateral PFC have dissociable contributions in rule learning.

Active Learning in an Introductory Meteorology Class

NASA Astrophysics Data System (ADS)

Marchese, P. J.; Bluestone, C.

2007-12-01

Active learning modules were introduced to the primarily minority population in the introductory meteorology class at Queensborough Community College (QCC). These activities were developed at QCC and other 4 year colleges and designed to reinforce basic meteorological concepts. The modules consisted of either Interactive Lecture Demonstrations (ILD) or discovery-based activities. During the ILD the instructor would describe an experiment that would be demonstrated in class. Students would predict what the outcome would be and compare their expected results to the actual outcome of the experiment. In the discovery-based activities students would learn about physical concepts by performing basic experiments. These activities differed from the traditional lab in that it avoided "cookbook" procedures and emphasized having the students learn about the concept using the scientific method. As a result of these activities student scores measuring conceptual understanding, as well as factual knowledge, increased as compared to student scores in a more affluent community college. Students also had higher self- efficacy scores. Lower scoring students demonstrated the greatest benefit, while the better students had little (or no) changes.

Challenges in reproducibility of genetic association studies: lessons learned from the obesity field.

PubMed

Li, A; Meyre, D

2013-04-01

A robust replication of initial genetic association findings has proved to be difficult in human complex diseases and more specifically in the obesity field. An obvious cause of non-replication in genetic association studies is the initial report of a false positive result, which can be explained by a non-heritable phenotype, insufficient sample size, improper correction for multiple testing, population stratification, technical biases, insufficient quality control or inappropriate statistical analyses. Replication may, however, be challenging even when the original study describes a true positive association. The reasons include underpowered replication samples, gene × gene, gene × environment interactions, genetic and phenotypic heterogeneity and subjective interpretation of data. In this review, we address classic pitfalls in genetic association studies and provide guidelines for proper discovery and replication genetic association studies with a specific focus on obesity.

A Web interface generator for molecular biology programs in Unix.

PubMed

Letondal, C

2001-01-01

Almost all users encounter problems using sequence analysis programs. Not only are they difficult to learn because of the parameters, syntax and semantic, but many are different. That is why we have developed a Web interface generator for more than 150 molecular biology command-line driven programs, including: phylogeny, gene prediction, alignment, RNA, DNA and protein analysis, motif discovery, structure analysis and database searching programs. The generator uses XML as a high-level description language of the legacy software parameters. Its aim is to provide users with the equivalent of a basic Unix environment, with program combination, customization and basic scripting through macro registration. The program has been used for three years by about 15000 users throughout the world; it has recently been installed on other sites and evaluated as a standard user interface for EMBOSS programs.

Implementing the Army NetCentric Data Strategy in a ServiceOriented Environment

DTIC Science & Technology

2009-04-23

a Data Subscriptionc c e s s Federated Search Data Search D a t a A b s t r a c t i o n Adapter Configuration Adapter Data Service D a t a S e r...across t e enterpr se.  • Patterns • Search • Status • Receive – Services • Federated   Search • Artifact Discovery • Data Discovery 17 Data Discovery

Applying a Framework for Student Modeling in Exploratory Learning Environments: Comparing Data Representation Granularity to Handle Environment Complexity

ERIC Educational Resources Information Center

Fratamico, Lauren; Conati, Cristina; Kardan, Samad; Roll, Ido

2017-01-01

Interactive simulations can facilitate inquiry learning. However, similarly to other Exploratory Learning Environments, students may not always learn effectively in these unstructured environments. Thus, providing adaptive support has great potential to help improve student learning with these rich activities. Providing adaptive support requires a…

A Simultaneous Mobile E-Learning Environment and Application

ERIC Educational Resources Information Center

Karal, Hasan; Bahcekapili, Ekrem; Yildiz, Adil

2010-01-01

The purpose of the present study was to design a mobile learning environment that enables the use of a teleconference application used in simultaneous e-learning with mobile devices and to evaluate this mobile learning environment based on students' views. With the mobile learning environment developed in the study, the students are able to follow…

Using Scenarios to Design Complex Technology-Enhanced Learning Environments

ERIC Educational Resources Information Center

de Jong, Ton; Weinberger, Armin; Girault, Isabelle; Kluge, Anders; Lazonder, Ard W.; Pedaste, Margus; Ludvigsen, Sten; Ney, Muriel; Wasson, Barbara; Wichmann, Astrid; Geraedts, Caspar; Giemza, Adam; Hovardas, Tasos; Julien, Rachel; van Joolingen, Wouter R.; Lejeune, Anne; Manoli, Constantinos C.; Matteman, Yuri; Sarapuu, Tago; Verkade, Alex; Vold, Vibeke; Zacharia, Zacharias C.

2012-01-01

Science Created by You (SCY) learning environments are computer-based environments in which students learn about science topics in the context of addressing a socio-scientific problem. Along their way to a solution for this problem students produce many types of intermediate products or learning objects. SCY learning environments center the entire…

Form-Focused Discovery Activities in English Classes

ERIC Educational Resources Information Center

Ogeyik, Muhlise Cosgun

2011-01-01

Form-focused discovery activities allow language learners to grasp various aspects of a target language by contributing implicit knowledge by using discovered explicit knowledge. Moreover, such activities can assist learners to perceive and discover the features of their language input. In foreign language teaching environments, they can be used…

Learned modesty and the first lady's comet: a commentary on Caroline Herschel (1787) 'An account of a new comet'.

PubMed

Winterburn, Emily

2015-04-13

Long before women were allowed to become Fellows of the Royal Society, or obtain university degrees, one woman managed to get her voice heard, her discovery verified and her achievement celebrated. That woman was Caroline Herschel, who, as this paper will discuss, managed to find ways to fit comet discoveries into her domestic life, and present them in ways that were socially acceptable. Caroline lived in a time when strict rules dictated how women (and men) should behave and present themselves and their work. Caroline understood these rules, and used them carefully as she announced each discovery, starting with this comet which she found in 1786. Caroline discovered her comets at a time when astronomers were mainly concerned with position, identifying where things were and how they were moving. Since her discoveries, research has moved on, as astronomers, using techniques from other fields, and most recently sending experiments into space, have learned more about what comets are and what they can tell us about our solar system. Caroline's paper marks one small, early step in this much bigger journey to understand comets. This commentary was written to celebrate the 350th anniversary of the journal Philosophical Transactions of the Royal Society.

Learning Environments Designed According to Learning Styles and Its Effects on Mathematics Achievement

ERIC Educational Resources Information Center

Özerem, Aysen; Akkoyunlu, Buket

2015-01-01

Problem Statement: While designing a learning environment it is vital to think about learner characteristics (learning styles, approaches, motivation, interests… etc.) in order to promote effective learning. The learning environment and learning process should be designed not to enable students to learn in the same manner and at the same level,…

Near-Field Cosmology with Resolved Stellar Populations Around Local Volume LMC Stellar-Mass Galaxies

NASA Astrophysics Data System (ADS)

Carlin, Jeffrey L.; Sand, David J.; Willman, Beth; Brodie, Jean P.; Crnojevic, Denija; Forbes, Duncan; Hargis, Jonathan R.; Peter, Annika; Pucha, Ragadeepika; Romanowsky, Aaron J.; Spekkens, Kristine; Strader, Jay

2018-06-01

We discuss our ongoing observational program to comprehensively map the entire virial volumes of roughly LMC stellar mass galaxies at distances of ~2-4 Mpc. The MADCASH (Magellanic Analog Dwarf Companions And Stellar Halos) survey will deliver the first census of the dwarf satellite populations and stellar halo properties within LMC-like environments in the Local Volume. Our results will inform our understanding of the recent DES discoveries of dwarf satellites tentatively affiliated with the LMC/SMC system. This program has already yielded the discovery of the faintest known dwarf galaxy satellite of an LMC stellar-mass host beyond the Local Group, based on deep Subaru+HyperSuprimeCam imaging reaching ~2 magnitudes below its TRGB, and at least two additional candidate satellites. We will summarize the survey results and status to date, highlighting some challenges encountered and lessons learned as we process the data for this program through a prototype LSST pipeline. Our program will examine whether LMC stellar mass dwarfs have extended stellar halos, allowing us to assess the relative contributions of in-situ stars vs. merger debris to their stellar populations and halo density profiles. We outline the constraints on galaxy formation models that will be provided by our observations of low-mass galaxy halos and their satellites.

Research and Discovery Science and the Future of Dental Education and Practice.

PubMed

Polverini, Peter J; Krebsbach, Paul H

2017-09-01

Dental graduates of 2040 will face new and complex challenges. If they are to meet these challenges, dental schools must develop a research and discovery mission that will equip graduates with the new knowledge required to function in a modern health care environment. The dental practitioner of 2040 will place greater emphasis on risk assessment, disease prevention, and health maintenance; and the emerging discipline of precision medicine and systems biology will revolutionize disease diagnosis and reveal new targeted therapies. The dental graduate of 2040 will be expected to function effectively in a collaborative, learning health care system and to understand the impact of health care policy on local, national, and global communities. Emerging scientific fields such as big data analytics, stem cell biology, tissue engineering, and advanced biomimetics will impact dental practice. Despite all the warning signs indicating how the changing scientific and heath care landscape will dramatically alter dental education and dental practice, dental schools have yet to reconsider their research and educational priorities and clinical practice objectives. Until dental schools and the practicing community come to grips with these challenges, this persistent attitude of complacency will likely be at the dental profession's peril. This article was written as part of the project "Advancing Dental Education in the 21 st Century."

Incidental findings in data-intensive postgenomics science and legal liability of clinician-researchers: ready for vaccinomics?

PubMed

Zawati, Ma'n H; Hendy, Matthew; Joly, Yann

2011-09-01

Vaccinomics encompasses a host of multiomics approaches to characterize variability in host-environment (including pathogens) interactions, with a view to a more directed or personalized use of vaccine-based health interventions. Although vaccinomics has the potential to reduce adverse effects and increase efficacy of vaccines, the use of high-throughput, data-intensive technologies may also lead to unanticipated discoveries beyond the initial aims of a vaccinomics study--discoveries that could be highly significant to the health of the research participants. How do clinician-researchers faced with such information have to act? What are the attendant legal duties in such circumstances and how do they differ from the duties of non-clinician researchers? Together with a critical analysis of the international laws and policies framing researchers' duties with regard to incidental findings, this article also draws from Quebec's civil law--with its rich jurisprudence on clinician and researcher liability--as a case study to evaluate the potential legal implications associated with vaccinomics investigations. Given previous lessons learned from other data-intensive sciences, the education of clinician-researchers with regard to their roles, limitations, and legal obligations remains an important strategy to prevent potential legal complications and civil liability in vaccinomics research in the postgenomics era.

Web-Based Learning Environment Based on Students’ Needs

NASA Astrophysics Data System (ADS)

Hamzah, N.; Ariffin, A.; Hamid, H.

2017-08-01

Traditional learning needs to be improved since it does not involve active learning among students. Therefore, in the twenty-first century, the development of internet technology in the learning environment has become the main needs of each student. One of the learning environments to meet the needs of the teaching and learning process is a web-based learning environment. This study aims to identify the characteristics of a web-based learning environment that supports students’ learning needs. The study involved 542 students from fifteen faculties in a public higher education institution in Malaysia. A quantitative method was used to collect the data via a questionnaire survey by randomly. The findings indicate that the characteristics of a web-based learning environment that support students’ needs in the process of learning are online discussion forum, lecture notes, assignments, portfolio, and chat. In conclusion, the students overwhelmingly agreed that online discussion forum is the highest requirement because the tool can provide a space for students and teachers to share knowledge and experiences related to teaching and learning.

Phasic dopamine as a prediction error of intrinsic and extrinsic reinforcements driving both action acquisition and reward maximization: a simulated robotic study.

PubMed

Mirolli, Marco; Santucci, Vieri G; Baldassarre, Gianluca

2013-03-01

An important issue of recent neuroscientific research is to understand the functional role of the phasic release of dopamine in the striatum, and in particular its relation to reinforcement learning. The literature is split between two alternative hypotheses: one considers phasic dopamine as a reward prediction error similar to the computational TD-error, whose function is to guide an animal to maximize future rewards; the other holds that phasic dopamine is a sensory prediction error signal that lets the animal discover and acquire novel actions. In this paper we propose an original hypothesis that integrates these two contrasting positions: according to our view phasic dopamine represents a TD-like reinforcement prediction error learning signal determined by both unexpected changes in the environment (temporary, intrinsic reinforcements) and biological rewards (permanent, extrinsic reinforcements). Accordingly, dopamine plays the functional role of driving both the discovery and acquisition of novel actions and the maximization of future rewards. To validate our hypothesis we perform a series of experiments with a simulated robotic system that has to learn different skills in order to get rewards. We compare different versions of the system in which we vary the composition of the learning signal. The results show that only the system reinforced by both extrinsic and intrinsic reinforcements is able to reach high performance in sufficiently complex conditions. Copyright © 2013 Elsevier Ltd. All rights reserved.

Distributing vs. Blocking Learning Questions in a Web-Based Learning Environment

ERIC Educational Resources Information Center

Kapp, Felix; Proske, Antje; Narciss, Susanne; Körndle, Hermann

2015-01-01

Effective studying in web-based learning environments (web-LEs) requires cognitive engagement and demands learners to regulate their learning activities. One way to support learners in web-LEs is to provide interactive learning questions within the learning environment. Even though research on learning questions has a long tradition, there are…

Learning with Collaborative Inquiry: A Science Learning Environment for Secondary Students

ERIC Educational Resources Information Center

Sun, Daner; Looi, Chee-Kit; Xie, Wenting

2017-01-01

When inquiry-based learning is designed for a collaborative context, the interactions that arise in the learning environment can become fairly complex. While the learning effectiveness of such learning environments has been reported in the literature, there have been fewer studies on the students' learning processes. To address this, the article…

Learning in a u-Museum: Developing a Context-Aware Ubiquitous Learning Environment

ERIC Educational Resources Information Center

Chen, Chia-Chen; Huang, Tien-Chi

2012-01-01

Context-awareness techniques can support learners in learning without time or location constraints by using mobile devices and associated learning activities in a real learning environment. Enrichment of context-aware technologies has enabled students to learn in an environment that integrates learning resources from both the real world and the…

Assessing the Impact of Student Learning Style Preferences

NASA Astrophysics Data System (ADS)

Davis, Stacey M.; Franklin, Scott V.

2004-09-01

Students express a wide range of preferences for learning environments. We are trying to measure the manifestation of learning styles in various learning environments. In particular, we are interested in performance in an environment that disagrees with the expressed learning style preference, paying close attention to social (group vs. individual) and auditory (those who prefer to learn by listening) environments. These are particularly relevant to activity-based curricula which typically emphasize group-work and de-emphasize lectures. Our methods include multiple-choice assessments, individual student interviews, and a study in which we attempt to isolate the learning environment.

NASA Space Science Day Events-Engaging Students in Science

NASA Technical Reports Server (NTRS)

Foxworth, S.; Mosie, A.; Allen, J.; Kent, J.; Green, A.

2015-01-01

The NASA Space Science Day Event follows the same format of planning and execution at all host universities and colleges. These institutions realized the importance of such an event and sought funding to continue hosting NSSD events. In 2014, NASA Johnson Space Center ARES team has supported the following universities and colleges that have hosted a NSSD event; the University of Texas at Brownsville, San Jacinto College, Georgia Tech University and Huston-Tillotson University. Other universities and colleges are continuing to conduct their own NSSD events. NASA Space Science Day Events are supported through continued funding through NASA Discovery Program. Community Night begins with a NASA speaker and Astromaterials display. The entire community surrounding the host university or college is invited to the Community Night. This year at the Huston-Tillotson (HTU) NSSD, we had Dr. Laurie Carrillo, a NASA Engineer, speak to the public and students. She answered questions, shared her experiences and career path. The speaker sets a tone of adventure and discovery for the NSSD event. After the speaker, the public is able to view Lunar and Meteorite samples and ask questions from the ARES team. The students and teachers from nearby schools attended the NSSD Event the following day. Students are able to see the university or college campus and the university or college mentors are available for questions. Students rotate through hour long Science Technology Engineering and Mathematics (STEM) sessions and a display area. These activities are from the Discovery Program activities that tie in directly with k- 12 instruction. The sessions highlight the STEM in exploration and discovery. The Lunar and Meteorite display is again available for students to view and ask questions. In the display area, there are also other interactive displays. Angela Green, from San Jacinto College, brought the Starlab for students to watch a planetarium exhibit for the NSSD at Huston-Tillotson University. Many HTU mentors were leading activities in the display room such as build a comet, volcano layering and robotics manipulation. Students were exposed to a variety STEM career possibilities and information. The students could relate the displays and sessions to what they were learning in school. The HTU mentors made the connection clear for the students. The students ended the event with a mission design presentation. They were able to take what they had learned during the day and were able to create a mission. Students presented their Mission Design and gained confidence in STEM. Conclusion: NASA Space Science Day Events provides an out of school experiential learning environment for students to enhance their STEM curriculum and let students see a college campus. The experiences students gain from attending NSSD gives them the confidence to see themselves on a college campus, possibly majoring in a STEM degree, and understand the importance of completing school.

Construction of a Digital Learning Environment Based on Cloud Computing

ERIC Educational Resources Information Center

Ding, Jihong; Xiong, Caiping; Liu, Huazhong

2015-01-01

Constructing the digital learning environment for ubiquitous learning and asynchronous distributed learning has opened up immense amounts of concrete research. However, current digital learning environments do not fully fulfill the expectations on supporting interactive group learning, shared understanding and social construction of knowledge.…

A Well Designed School Environment Facilitates Brain Learning.

ERIC Educational Resources Information Center

Chan, Tak Cheung; Petrie, Garth

2000-01-01

Examines how school design facilitates learning by complementing how the brain learns. How the brain learns is discussed and how an artistic environment, spaciousness in the learning areas, color and lighting, and optimal thermal and acoustical environments aid student learning. School design suggestions conclude the article. (GR)

Perceptual learning and human expertise

NASA Astrophysics Data System (ADS)

Kellman, Philip J.; Garrigan, Patrick

2009-06-01

We consider perceptual learning: experience-induced changes in the way perceivers extract information. Often neglected in scientific accounts of learning and in instruction, perceptual learning is a fundamental contributor to human expertise and is crucial in domains where humans show remarkable levels of attainment, such as language, chess, music, and mathematics. In Section 2, we give a brief history and discuss the relation of perceptual learning to other forms of learning. We consider in Section 3 several specific phenomena, illustrating the scope and characteristics of perceptual learning, including both discovery and fluency effects. We describe abstract perceptual learning, in which structural relationships are discovered and recognized in novel instances that do not share constituent elements or basic features. In Section 4, we consider primary concepts that have been used to explain and model perceptual learning, including receptive field change, selection, and relational recoding. In Section 5, we consider the scope of perceptual learning, contrasting recent research, focused on simple sensory discriminations, with earlier work that emphasized extraction of invariance from varied instances in more complex tasks. Contrary to some recent views, we argue that perceptual learning should not be confined to changes in early sensory analyzers. Phenomena at various levels, we suggest, can be unified by models that emphasize discovery and selection of relevant information. In a final section, we consider the potential role of perceptual learning in educational settings. Most instruction emphasizes facts and procedures that can be verbalized, whereas expertise depends heavily on implicit pattern recognition and selective extraction skills acquired through perceptual learning. We consider reasons why perceptual learning has not been systematically addressed in traditional instruction, and we describe recent successful efforts to create a technology of perceptual learning in areas such as aviation, mathematics, and medicine. Research in perceptual learning promises to advance scientific accounts of learning, and perceptual learning technology may offer similar promise in improving education.

Mars-Learning AN Open Access Educational Database

NASA Astrophysics Data System (ADS)

Kolankowski, S. M.; Fox, P. A.

2016-12-01

Schools across America have begun focusing more and more on science and technology, giving their students greater opportunities to learn about planetary science and engineering. With the development of rovers and advanced scientific instrumentation, we are learning about Mars' geologic history on a daily basis. These discoveries are crucial to our understanding of Earth and our solar system. By bringing these findings into the classroom, students can learn key concepts about Earth and Planetary sciences while focusing on a relevant current event. However, with an influx of readily accessible information, it is difficult for educators and students to find accurate and relevant material. Mars-Learning seeks to unify these discoveries and resources. This site will provide links to educational resources, software, and blogs with a focus on Mars. Activities will be grouped by grade for the middle and high school levels. Programs and software will be labeled, open access, free, or paid to ensure users have the proper tools to get the information they need. For new educators or those new to the subject, relevant blogs and pre-made lesson plans will be available so instructors can ensure their success. The expectation of Mars-Learning is to provide stress-free access to learning materials that falls within a wide range of curriculum. By providing a thorough and encompassing site, Mars-Learning hopes to further our understanding of the Red Planet and equip students with the knowledge and passion to continue this research.

Learning Relational Policies from Electronic Health Record Access Logs

PubMed Central

Malin, Bradley; Nyemba, Steve; Paulett, John

2011-01-01

Modern healthcare organizations (HCOs) are composed of complex dynamic teams to ensure clinical operations are executed in a quick and competent manner. At the same time, the fluid nature of such environments hinders administrators' efforts to define access control policies that appropriately balance patient privacy and healthcare functions. Manual efforts to define these policies are labor-intensive and error-prone, often resulting in systems that endow certain care providers with overly broad access to patients' medical records while restricting other providers from legitimate and timely use. In this work, we propose an alternative method to generate these policies by automatically mining usage patterns from electronic health record (EHR) systems. EHR systems are increasingly being integrated into clinical environments and our approach is designed to be generalizable across HCOs, thus assisting in the design and evaluation of local access control policies. Our technique, which is grounded in data mining and social network analysis theory, extracts a statistical model of the organization from the access logs of its EHRs. In doing so, our approach enables the review of predefined policies, as well as the discovery of unknown behaviors. We evaluate our approach with five months of access logs from the Vanderbilt University Medical Center and confirm the existence of stable social structures and intuitive business operations. Additionally, we demonstrate that there is significant turnover in the interactions between users in the HCO and that policies learned at the department level afford greater stability over time. PMID:21277996

Students' perception of the learning environment in a distributed medical programme.

PubMed

Veerapen, Kiran; McAleer, Sean

2010-09-24

The learning environment of a medical school has a significant impact on students' achievements and learning outcomes. The importance of equitable learning environments across programme sites is implicit in distributed undergraduate medical programmes being developed and implemented. To study the learning environment and its equity across two classes and three geographically separate sites of a distributed medical programme at the University of British Columbia Medical School that commenced in 2004. The validated Dundee Ready Educational Environment Survey was sent to all students in their 2nd and 3rd year (classes graduating in 2009 and 2008) of the programme. The domains of the learning environment surveyed were: students' perceptions of learning, students' perceptions of teachers, students' academic self-perceptions, students' perceptions of the atmosphere, and students' social self-perceptions. Mean scores, frequency distribution of responses, and inter- and intrasite differences were calculated. The perception of the global learning environment at all sites was more positive than negative. It was characterised by a strongly positive perception of teachers. The work load and emphasis on factual learning were perceived negatively. Intersite differences within domains of the learning environment were more evident in the pioneer class (2008) of the programme. Intersite differences consistent across classes were largely related to on-site support for students. Shared strengths and weaknesses in the learning environment at UBC sites were evident in areas that were managed by the parent institution, such as the attributes of shared faculty and curriculum. A greater divergence in the perception of the learning environment was found in domains dependent on local arrangements and social factors that are less amenable to central regulation. This study underlines the need for ongoing comparative evaluation of the learning environment at the distributed sites and interaction between leaders of these sites.

Active and Interactive Discovery of Goal Selection Knowledge

DTIC Science & Technology

2011-01-01

Generator retrieves the goal ct.g of the most similar case ct and outputs it to the Goal Manager. 5.3 Retention and Maintenance: Active Learning Figure...pp. 202-206). Seattle, WA: AAAI Press. Hu, R., Delaney, S.J., & Mac Namee, B. (2010). EGAL: Exploration guided active learning for TCBR. Proceedings...Sculley, D. (2007). Online active learning methods for fast label- efficient spam filtering. In Proceedings of the Fourth Conference on Email and Anti

Sublgacial Antarctic Lake Environments (SALE)

NASA Astrophysics Data System (ADS)

Kennicutt, M. C.; Bell, R. E.; Priscu, J. C.

2004-12-01

Subglacial Antarctic lake environments are emerging as one of the new frontiers targeted for exploration during the IPY 2007-2009. Several campaigns by various nations are in the early stages of planning and implementation with timelines that will coincide with the IPY. The ambitious interdisciplinary objectives will best be realized by multiple exploration programs investigating diverse subglacial environments continent-wide over the next decade or more. A concerted, multi-target approach wil be taken to advance our understanding of the range of possible lake evolutionary histories; the character of the physical, chemical, and biological niches; the interconnectivity of subglacial lake environments; the coupling of the ice sheet, climate and the evolution of life under the ice; the tectonic settings; and the interplay of biogeochemical cycles. Research and exploration programs spanning the continent will investigate subglacial lake environments of differing ages, evolutionary histories, and biogeochemical settings. The combined efforts will provide a holistic view of these environments over millions of years and under changing climatic conditions. The IPY will provide an opportunity for an intense period of initial exploration that will advance scientific discoveries in glaciology, biogeochemistry, paleoclimate, biology, geology and tectonics, and ecology. While early discoveries and exciting findings are expected during the IPY 2007-2009, a long term sustained program of research and exploration will continue far beyond the IPY. Within the five year period that spans the IPY, specific accomplishments will be targeted, accelerating the research agenda and setting a framework for follow-on studies. Four phases of exploration and discovery are envisioned.

Personal Learning Environments: A Solution for Self-Directed Learners

ERIC Educational Resources Information Center

Haworth, Ryan

2016-01-01

In this paper I discuss "personal learning environments" and their diverse benefits, uses, and implications for life-long learning. Personal Learning Environments (PLEs) are Web 2.0 and social media technologies that enable individual learners the ability to manage their own learning. Self-directed learning is explored as a foundation…

Ubiquitous Learning Environments in Higher Education: A Scoping Literature Review

ERIC Educational Resources Information Center

Virtanen, Mari Aulikki; Haavisto, Elina; Liikanen, Eeva; Kääriäinen, Maria

2018-01-01

Ubiquitous learning and the use of ubiquitous learning environments heralds a new era in higher education. Ubiquitous learning environments enhance context-aware and seamless learning experiences available from any location at any time. They support smooth interaction between authentic and digital learning resources and provide personalized…

Co-Regulation of Learning in Computer-Supported Collaborative Learning Environments: A Discussion

ERIC Educational Resources Information Center

Chan, Carol K. K.

2012-01-01

This discussion paper for this special issue examines co-regulation of learning in computer-supported collaborative learning (CSCL) environments extending research on self-regulated learning in computer-based environments. The discussion employs a socio-cognitive perspective focusing on social and collective views of learning to examine how…

Trajectories of the home learning environment across the first 5 years: associations with children's vocabulary and literacy skills at prekindergarten.

PubMed

Rodriguez, Eileen T; Tamis-LeMonda, Catherine S

2011-01-01

Children's home learning environments were examined in a low-income sample of 1,852 children and families when children were 15, 25, 37, and 63 months. During home visits, children's participation in literacy activities, the quality of mothers' engagements with their children, and the availability of learning materials were assessed, yielding a total learning environment score at each age. At 63 months, children's vocabulary and literacy skills were assessed. Six learning environment trajectories were identified, including environments that were consistently low, environments that were consistently high, and environments characterized by varying patterns of change. The skills of children at the extremes of learning environment trajectories differed by more than 1 SD and the timing of learning experiences related to specific emerging skills. © 2011 The Authors. Child Development © 2011 Society for Research in Child Development, Inc.

The Interplay of Perceptions of the Learning Environment, Personality and Learning Strategies: A Study amongst International Business Studies Students

ERIC Educational Resources Information Center

Nijhuis, Jan; Segers, Mien; Gijselaers, Wim

2007-01-01

Previous research on students' learning strategies has examined the relationships between either perceptions of the learning environment or personality and learning strategies. The focus of this study was on the joint relationships between the students' perceptions of the learning environment, their personality, and the learning strategies they…

Do quality improvement collaboratives' educational components match the dominant learning style preferences of the participants?

PubMed

Weggelaar-Jansen, Anne Marie; van Wijngaarden, Jeroen; Slaghuis, Sarah-Sue

2015-06-20

Quality improvement collaboratives are used to improve healthcare by various organizations. Despite their popularity literature shows mixed results on their effectiveness. A quality improvement collaborative can be seen as a temporary learning organization in which knowledge about improvement themes and methods is exchanged. In this research we studied: Does the learning approach of a quality improvement collaborative match the learning styles preferences of the individual participants and how does that affect the learning process of participants? This research used a mixed methods design combining a validated learning style questionnaire with data collected in the tradition of action research methodology to study two Dutch quality improvement collaboratives. The questionnaire is based on the learning style model of Ruijters and Simons, distinguishing five learning style preferences: Acquisition of knowledge, Apperception from others, Discovery of new insights, Exercising in fictitious situations and Participation with others. The most preferred learning styles of the participants were Discovery and Participation. The learning style Acquisition was moderately preferred and Apperception and Exercising were least preferred. The educational components of the quality improvement collaboratives studied (national conferences, half-day learning sessions, faculty site visits and use of an online tool) were predominantly associated with the learning styles Acquisition and Apperception. We observed a decrease in attendance to the learning activities and non-conformance with the standardized set goals and approaches. We conclude that the participants' satisfaction with the offered learning approach changed over time. The lacking match between these learning style preferences and the learning approach in the educational components of the quality improvement collaboratives studied might be the reason why the participants felt they did not gain new insights and therefore ceased their participation in the collaborative. This study provides guidance for future organisers and participants of quality improvement collaboratives about which learning approaches will best suit the participants and enhance improvement work.

Hundreds of Cruises, Thousands of People, Endless Discoveries - Education and Outreach in the Integrated Ocean Drilling Program

NASA Astrophysics Data System (ADS)

Peart, L.; Niemitz, M.; Boa, S.; Corsiglia, J.; Klaus, A.; Petronotis, K.; Iturrino, G.

2005-12-01

For 37 years, scientific ocean drilling programs have sponsored hundreds of expeditions, drilled at over 1,800 sites and recovered over 200 miles of core. The discoveries of these programs have led to important realizations of how our earth works. Past expeditions have validated the theory of plate tectonics, provided unparalleled ancient climate records and recovered evidence of the asteroid impact that wiped out the dinosaurs 65 million years ago - and new discoveries occur with every expedition. By producing education materials and programs and encouraging mass media journalists' interest in our news, we strive to fulfill our commitment to communicate our programs' scientific discoveries to the public, in a way that people - not just other scientists - understand. With the advent of the Integrated Ocean Drilling Program (IODP), education and outreach efforts have expanded to pursue new opportunities and engage wider audiences. Through our strategy of Teaching for Science, Learning for LifeTM, our education efforts seek to utilize the interdisciplinary nature of scientific ocean drilling to teach career awareness, scientific methods, teamwork, and problem solving techniques for a lifetime of learning, decision making and good citizenship. In pursuit of this goal, we have implemented professional and resource development programs and expanded our outreach at education-focused conferences to help teachers use IODP science to satiate the student's need to learn the methods of science that apply to everyday life. We believe that this message also applies to life-long learners and thus we have focused our efforts on news media outreach and education opportunities surrounding ports of call of the JOIDES Resolution, permanent and traveling museum exhibits. In addition, our outreach to undergraduate and graduate audiences, through a lecture series, research fellowships and internships, helps to create future generations of science leaders.

Potential of Cognitive Computing and Cognitive Systems

NASA Astrophysics Data System (ADS)

Noor, Ahmed K.

2015-01-01

Cognitive computing and cognitive technologies are game changers for future engineering systems, as well as for engineering practice and training. They are major drivers for knowledge automation work, and the creation of cognitive products with higher levels of intelligence than current smart products. This paper gives a brief review of cognitive computing and some of the cognitive engineering systems activities. The potential of cognitive technologies is outlined, along with a brief description of future cognitive environments, incorporating cognitive assistants - specialized proactive intelligent software agents designed to follow and interact with humans and other cognitive assistants across the environments. The cognitive assistants engage, individually or collectively, with humans through a combination of adaptive multimodal interfaces, and advanced visualization and navigation techniques. The realization of future cognitive environments requires the development of a cognitive innovation ecosystem for the engineering workforce. The continuously expanding major components of the ecosystem include integrated knowledge discovery and exploitation facilities (incorporating predictive and prescriptive big data analytics); novel cognitive modeling and visual simulation facilities; cognitive multimodal interfaces; and cognitive mobile and wearable devices. The ecosystem will provide timely, engaging, personalized / collaborative, learning and effective decision making. It will stimulate creativity and innovation, and prepare the participants to work in future cognitive enterprises and develop new cognitive products of increasing complexity. http://www.aee.odu.edu/cognitivecomp

Designing for Change: Interoperability in a scaling and adapting environment

NASA Astrophysics Data System (ADS)

Yarmey, L.

2015-12-01

The Earth Science cyberinfrastructure landscape is constantly changing. Technologies advance and technical implementations are refined or replaced. Data types, volumes, packaging, and use cases evolve. Scientific requirements emerge and mature. Standards shift while systems scale and adapt. In this complex and dynamic environment, interoperability remains a critical component of successful cyberinfrastructure. Through the resource- and priority-driven iterations on systems, interfaces, and content, questions fundamental to stable and useful Earth Science cyberinfrastructure arise. For instance, how are sociotechnical changes planned, tracked, and communicated? How should operational stability balance against 'new and shiny'? How can ongoing maintenance and mitigation of technical debt be managed in an often short-term resource environment? The Arctic Data Explorer is a metadata brokering application developed to enable discovery of international, interdisciplinary Arctic data across distributed repositories. Completely dependent on interoperable third party systems, the Arctic Data Explorer publicly launched in 2013 with an original 3000+ data records from four Arctic repositories. Since then the search has scaled to 25,000+ data records from thirteen repositories at the time of writing. In the final months of original project funding, priorities shift to lean operations with a strategic eye on the future. Here we present lessons learned from four years of Arctic Data Explorer design, development, communication, and maintenance work along with remaining questions and potential directions.

Metagenomic Analysis of Upwelling-Affected Brazilian Coastal Seawater Reveals Sequence Domains of Type I PKS and Modular NRPS

PubMed Central

Cuadrat, Rafael R. C.; Cury, Juliano C.; Dávila, Alberto M. R.

2015-01-01

Marine environments harbor a wide range of microorganisms from the three domains of life. These microorganisms have great potential to enable discovery of new enzymes and bioactive compounds for industrial use. However, only ~1% of microorganisms from the environment can currently be identified through cultured isolates, limiting the discovery of new compounds. To overcome this limitation, a metagenomics approach has been widely adopted for biodiversity studies on samples from marine environments. In this study, we screened metagenomes in order to estimate the potential for new natural compound synthesis mediated by diversity in the Polyketide Synthase (PKS) and Nonribosomal Peptide Synthetase (NRPS) genes. The samples were collected from the Praia dos Anjos (Angel’s Beach) surface water—Arraial do Cabo (Rio de Janeiro state, Brazil), an environment affected by upwelling. In order to evaluate the potential for screening natural products in Arraial do Cabo samples, we used KS (keto-synthase) and C (condensation) domains (from PKS and NRPS, respectively) to build Hidden Markov Models (HMM) models. From both samples, a total of 84 KS and 46 C novel domain sequences were obtained, showing the potential of this environment for the discovery of new genes of biotechnological interest. These domains were classified by phylogenetic analysis and this was the first study conducted to screen PKS and NRPS genes in an upwelling affected sample PMID:26633360

CLEW: A Cooperative Learning Environment for the Web.

ERIC Educational Resources Information Center

Ribeiro, Marcelo Blois; Noya, Ricardo Choren; Fuks, Hugo

This paper outlines CLEW (collaborative learning environment for the Web). The project combines MUD (Multi-User Dimension), workflow, VRML (Virtual Reality Modeling Language) and educational concepts like constructivism in a learning environment where students actively participate in the learning process. The MUD shapes the environment structure.…

Evaluating and Implementing Learning Environments: A United Kingdom Experience.

ERIC Educational Resources Information Center

Ingraham, Bruce; Watson, Barbara; McDowell, Liz; Brockett, Adrian; Fitzpatrick, Simon

2002-01-01

Reports on ongoing work at five universities in northeastern England that have been evaluating and implementing online learning environments known as virtual learning environments (VLEs) or managed learning environments (MLEs). Discusses do-it-yourself versus commercial systems; transferability; Web-based versus client-server; integration with…

Probabilistic machine learning and artificial intelligence.

PubMed

Ghahramani, Zoubin

2015-05-28

How can a machine learn from experience? Probabilistic modelling provides a framework for understanding what learning is, and has therefore emerged as one of the principal theoretical and practical approaches for designing machines that learn from data acquired through experience. The probabilistic framework, which describes how to represent and manipulate uncertainty about models and predictions, has a central role in scientific data analysis, machine learning, robotics, cognitive science and artificial intelligence. This Review provides an introduction to this framework, and discusses some of the state-of-the-art advances in the field, namely, probabilistic programming, Bayesian optimization, data compression and automatic model discovery.

Probabilistic machine learning and artificial intelligence

NASA Astrophysics Data System (ADS)

Ghahramani, Zoubin

2015-05-01

How can a machine learn from experience? Probabilistic modelling provides a framework for understanding what learning is, and has therefore emerged as one of the principal theoretical and practical approaches for designing machines that learn from data acquired through experience. The probabilistic framework, which describes how to represent and manipulate uncertainty about models and predictions, has a central role in scientific data analysis, machine learning, robotics, cognitive science and artificial intelligence. This Review provides an introduction to this framework, and discusses some of the state-of-the-art advances in the field, namely, probabilistic programming, Bayesian optimization, data compression and automatic model discovery.

Group Modeling in Social Learning Environments

ERIC Educational Resources Information Center

Stankov, Slavomir; Glavinic, Vlado; Krpan, Divna

2012-01-01

Students' collaboration while learning could provide better learning environments. Collaboration assumes social interactions which occur in student groups. Social theories emphasize positive influence of such interactions on learning. In order to create an appropriate learning environment that enables social interactions, it is important to…

The clinical learning environment in nursing education: a concept analysis.

PubMed

Flott, Elizabeth A; Linden, Lois

2016-03-01

The aim of this study was to report an analysis of the clinical learning environment concept. Nursing students are evaluated in clinical learning environments where skills and knowledge are applied to patient care. These environments affect achievement of learning outcomes, and have an impact on preparation for practice and student satisfaction with the nursing profession. Providing clarity of this concept for nursing education will assist in identifying antecedents, attributes and consequences affecting student transition to practice. The clinical learning environment was investigated using Walker and Avant's concept analysis method. A literature search was conducted using WorldCat, MEDLINE and CINAHL databases using the keywords clinical learning environment, clinical environment and clinical education. Articles reviewed were written in English and published in peer-reviewed journals between 1995-2014. All data were analysed for recurring themes and terms to determine possible antecedents, attributes and consequences of this concept. The clinical learning environment contains four attribute characteristics affecting student learning experiences. These include: (1) the physical space; (2) psychosocial and interaction factors; (3) the organizational culture and (4) teaching and learning components. These attributes often determine achievement of learning outcomes and student self-confidence. With better understanding of attributes comprising the clinical learning environment, nursing education programmes and healthcare agencies can collaborate to create meaningful clinical experiences and enhance student preparation for the professional nurse role. © 2015 John Wiley & Sons Ltd.

iPTF Discoveries of Recent Type Ia Supernovae

NASA Astrophysics Data System (ADS)

Papadogiannakis, S.; Taddia, F.; Petrushevska, T.; Ferretti, R.; Fremling, C.; Karamehmetoglu, E.; Nyholm, A.; Roy, R.; Hangard, L.; Vreeswijk, P.; Horesh, A.; Manulis, I.; Rubin, A.; Yaron, O.; Leloudas, G.; Khazov, D.; Soumagnac, M.; Knezevic, S.; Johansson, J.; Nir, G.; Cao, Y.; Blagorodnova, N.; Kulkarni, S.

2016-05-01

The intermediate Palomar Transient Factory (ATel #4807) reports the discovery and classification of the following Type Ia SNe. Our automated candidate vetting to distinguish a real astrophysical source (1.0) from bogus artefacts (0.0) is powered by three generations of machine learning algorithms: RB2 (Brink et al. 2013MNRAS.435.1047B), RB4 (Rebbapragada et al. 2015AAS...22543402R) and RB5 (Wozniak et al. 2013AAS...22143105W).

iPTF Discoveries of Recent Core-Collapse Supernovae

NASA Astrophysics Data System (ADS)

Taddia, F.; Ferretti, R.; Papadogiannakis, S.; Petrushevska, T.; Fremling, C.; Karamehmetoglu, E.; Nyholm, A.; Roy, R.; Hangard, L.; Horesh, A.; Khazov, D.; Knezevic, S.; Johansson, J.; Leloudas, G.; Manulis, I.; Rubin, A.; Soumagnac, M.; Vreeswijk, P.; Yaron, O.; Bar, I.; Cao, Y.; Kulkarni, S.; Blagorodnova, N.

2016-05-01

The intermediate Palomar Transient Factory (ATel #4807) reports the discovery and classification of the following core-collapse SNe. Our automated candidate vetting to distinguish a real astrophysical source (1.0) from bogus artifacts (0.0) is powered by three generations of machine learning algorithms: RB2 (Brink et al. 2013MNRAS.435.1047B), RB4 (Rebbapragada et al. 2015AAS...22543402R) and RB5 (Wozniak et al. 2013AAS...22143105W).

iPTF Discoveries of Recent Core-Collapse Supernovae

NASA Astrophysics Data System (ADS)

Taddia, F.; Ferretti, R.; Fremling, C.; Karamehmetoglu, E.; Nyholm, A.; Papadogiannakis, S.; Petrushevska, T.; Roy, R.; Hangard, L.; De Cia, A.; Vreeswijk, P.; Horesh, A.; Manulis, I.; Sagiv, I.; Rubin, A.; Yaron, O.; Leloudas, G.; Khazov, D.; Soumagnac, M.; Bilgi, P.

2015-04-01

The intermediate Palomar Transient Factory (ATel #4807) reports the discovery and classification of the following Core-Collapse SNe. Our automated candidate vetting to distinguish a real astrophysical source (1.0) from bogus artifacts (0.0) is powered by three generations of machine learning algorithms: RB2 (Brink et al. 2013MNRAS.435.1047B), RB4 (Rebbapragada et al. 2015AAS...22543402R) and RB5 (Wozniak et al. 2013AAS...22143105W).

iPTF Discoveries of Recent Type Ia Supernova

NASA Astrophysics Data System (ADS)

Petrushevska, T.; Ferretti, R.; Fremling, C.; Hangard, L.; Karamehmetoglu, E.; Nyholm, A.; Papadogiannakis, S.; Roy, R.; Horesh, A.; Khazov, D.; Knezevic, S.; Johansson, J.; Leloudas, G.; Manulis, I.; Rubin, A.; Soumagnac, M.; Vreeswijk, P.; Yaron, O.; Bilgi, P.; Cao, Y.; Duggan, G.; Lunnan, R.; Andreoni, I.

2015-10-01

The intermediate Palomar Transient Factory (ATel #4807) reports the discovery and classification of the following Type Ia SNe. Our automated candidate vetting to distinguish a real astrophysical source (1.0) from bogus artifacts (0.0) is powered by three generations of machine learning algorithms: RB2 (Brink et al. 2013MNRAS.435.1047B), RB4 (Rebbapragada et al. 2015AAS...22543402R) and RB5 (Wozniak et al. 2013AAS...22143105W).

iPTF Discoveries of Recent SNe Ia

NASA Astrophysics Data System (ADS)

Ferretti, R.; Fremling, C.; Johansson, J.; Karamehmetoglu, E.; Migotto, K.; Nyholm, A.; Papadogiannakis, S.; Taddia, F.; Petrushevska, T.; Roy, R.; Ben-Ami, S.; De Cia, A.; Dzigan, Y.; Horesh, A.; Khazov, D.; Manulis, I.; Rubin, A.; Sagiv, I.; Vreeswijk, P.; Yaron, O.; Bilgi, P.; Cao, Y.; Duggan, G.

2015-02-01

The intermediate Palomar Transient Factory (ATel #4807) reports the discovery and classification of the following Type Ia SNe. Our automated candidate vetting to distinguish a real astrophysical source (1.0) from bogus artifacts (0.0) is powered by three generations of machine learning algorithms: RB2 (Brink et al. 2013MNRAS.435.1047B), RB4 (Rebbapragada et al. 2015AAS...22543402R) and RB5 (Wozniak et al. 2013AAS...22143105W).

iPTF Discoveries of Recent Type Ia Supernovae

NASA Astrophysics Data System (ADS)

Papadogiannakis, S.; Taddia, F.; Ferretti, R.; Fremling, C.; Karamehmetoglu, E.; Petrushevska, T.; Nyholm, A.; Roy, R.; Hangard, L.; Vreeswijk, P.; Horesh, A.; Manulis, I.; Rubin, A.; Yaron, O.; Leloudas, G.; Khazov, D.; Soumagnac, M.; Knezevic, S.; Johansson, J.; Lunnan, R.; Blagorodnova, N.; Cao, Y.; Cenk, S. B.

2016-01-01

The intermediate Palomar Transient Factory (ATel #4807) reports the discovery and classification of the following Type Ia SNe. Our automated candidate vetting to distinguish a real astrophysical source (1.0) from bogus artifacts (0.0) is powered by three generations of machine learning algorithms: RB2 (Brink et al. 2013MNRAS.435.1047B), RB4 (Rebbapragada et al. 2015AAS...22543402R) and RB5 (Wozniak et al. 2013AAS...22143105W).

iPTF Discoveries of Recent Type Ia Supernovae

NASA Astrophysics Data System (ADS)

Ferretti, R.; Fremling, C.; Hangard, L.; Karamehmetoglu, E.; Nyholm, A.; Papadogiannakis, S.; Petrushevska, T.; Roy, R.; Taddia, F.; Horesh, A.; Khazov, D.; Knezevic, S.; Leloudas, G.; Manulis, I.; Rubin, A.; Soumagnac, M.; Vreeswijk, P.; Yaron, O.; Cao, Y.; Duggan, G.; Lunnan, R.; Blagorodnova, N.

2015-11-01

The intermediate Palomar Transient Factory (ATel #4807) reports the discovery and classification of the following Type Ia SNe. Our automated candidate vetting to distinguish a real astrophysical source (1.0) from bogus artifacts (0.0) is powered by three generations of machine learning algorithms: RB2 (Brink et al. 2013MNRAS.435.1047B), RB4 (Rebbapragada et al. 2015AAS...22543402R) and RB5 (Wozniak et al. 2013AAS...22143105W).

iPTF Discoveries of Recent Core-Collapse Supernovae

NASA Astrophysics Data System (ADS)

Taddia, F.; Ferretti, R.; Fremling, C.; Karamehmetoglu, E.; Nyholm, A.; Papadogiannakis, S.; Petrushevska, T.; Roy, R.; Hangard, L.; Vreeswijk, P.; Horesh, A.; Manulis, I.; Rubin, A.; Yaron, O.; Leloudas, G.; Khazov, D.; Soumagnac, M.; Knezevic, S.; Johansson, J.; Duggan, G.; Lunnan, R.; Cao, Y.

2015-09-01

The intermediate Palomar Transient Factory (ATel #4807) reports the discovery and classification of the following Core-Collapse SNe. Our automated candidate vetting to distinguish a real astrophysical source (1.0) from bogus artifacts (0.0) is powered by three generations of machine learning algorithms: RB2 (Brink et al. 2013MNRAS.435.1047B), RB4 (Rebbapragada et al. 2015AAS...22543402R) and RB5 (Wozniak et al. 2013AAS...22143105W).

iPTF Discovery of Recent Type Ia Supernovae

NASA Astrophysics Data System (ADS)

Hangard, L.; Ferretti, R.; Fremling, C.; Karamehmetoglu, E.; Nyholm, A.; Papadogiannakis, S.; Petrushevska, T.; Roy, R.; Bar, I.; Horesh, A.; Johansson, J.; Khazov, D.; Knezevic, S.; Leloudas, G.; Manulis, I.; Rubin, A.; Soumagnac, M.; Vreeswijk, P.; Yaron, O.; Cao, Y.; Kulkarni, S.; Lunnan, R.; Ravi, V.; Vedantham, H. K.; Yan, L.

2016-04-01

The intermediate Palomar Transient Factory (ATel #4807) reports the discovery and classification of the following Type Ia SNe. Our automated candidate vetting to distinguish a real astrophysical source (1.0) from bogus artifacts (0.0) is powered by three generations of machine learning algorithms: RB2 (Brink et al. 2013MNRAS.435.1047B), RB4 (Rebbapragada et al. 2015AAS...22543402R) and RB5 (Wozniak et al. 2013AAS...22143105W).

iPTF Discoveries of Recent Core-Collapse Supernovae

NASA Astrophysics Data System (ADS)

Taddia, F.; Ferretti, R.; Fremling, C.; Karamehmetoglu, E.; Nyholm, A.; Papadogiannakis, S.; Petrushevska, T.; Roy, R.; Hangard, L.; Vreeswijk, P.; Horesh, A.; Manulis, I.; Rubin, A.; Yaron, O.; Leloudas, G.; Khazov, D.; Soumagnac, M.; Knezevic, S.; Johansson, J.; Lunnan, R.; Cao, Y.; Miller, A.

2015-11-01

The intermediate Palomar Transient Factory (ATel #4807) reports the discovery and classification of the following Core-Collapse SNe. Our automated candidate vetting to distinguish a real astrophysical source (1.0) from bogus artifacts (0.0) is powered by three generations of machine learning algorithms: RB2 (Brink et al. 2013MNRAS.435.1047B), RB4 (Rebbapragada et al. 2015AAS...22543402R) and RB5 (Wozniak et al. 2013AAS...22143105W).

iPTF Discoveries of Recent Type Ia Supernovae

NASA Astrophysics Data System (ADS)

Petrushevska, T.; Ferretti, R.; Fremling, C.; Hangard, L.; Karamehmetoglu, E.; Nyholm, A.; Papadogiannakis, S.; Roy, R.; Horesh, A.; Khazov, D.; Knezevic, S.; Johansson, J.; Leloudas, G.; Manulis, I.; Rubin, A.; Soumagnac, M.; Vreeswijk, P.; Yaron, O.; Bilgi, P.; Cao, Y.; Duggan, G.; Lunnan, R.

2016-02-01

The intermediate Palomar Transient Factory (ATel #4807) reports the discovery and classification of the following Type Ia SNe. Our automated candidate vetting to distinguish a real astrophysical source (1.0) from bogus artifacts (0.0) is powered by three generations of machine learning algorithms: RB2 (Brink et al. 2013MNRAS.435.1047B), RB4 (Rebbapragada et al. 2015AAS...22543402R) and RB5 (Wozniak et al. 2013AAS...22143105W).

iPTF Discovery of Recent Type Ia Supernovae

NASA Astrophysics Data System (ADS)

Hangard, L.; Taddia, F.; Ferretti, R.; Papadogiannakis, S.; Petrushevska, T.; Fremling, C.; Karamehmetoglu, E.; Nyholm, A.; Roy, R.; Horesh, A.; Khazov, D.; Knezevic, S.; Johansson, J.; Leloudas, G.; Manulis, I.; Rubin, A.; Soumagnac, M.; Vreeswijk, P.; Yaron, O.; Bar, I.; Lunnan, R.; Cenk, S. B.

2016-02-01

The intermediate Palomar Transient Factory (ATel #4807) reports the discovery and classification of the following Type Ia SNe. Our automated candidate vetting to distinguish a real astrophysical source (1.0) from bogus artifacts (0.0) is powered by three generations of machine learning algorithms: RB2 (Brink et al. 2013MNRAS.435.1047B), RB4 (Rebbapragada et al. 2015AAS...22543402R) and RB5 (Wozniak et al. 2013AAS...22143105W).

iPTF Discoveries of Recent Type Ia Supernovae

NASA Astrophysics Data System (ADS)

Papadogiannakis, S.; Fremling, C.; Hangard, L.; Karamehmetoglu, E.; Nyholm, A.; Ferretti, R.; Petrushevska, T.; Roy, R.; Taddia, F.; Bar, I.; Horesh, A.; Johansson, J.; Knezevic, S.; Leloudas, G.; Manulis, I.; Nir, G.; Rubin, A.; Soumagnac, M.; Vreeswijk, P.; Yaron, O.; Arcavi, I.; Howell, D. A.; McCully, C.; Hosseinzadeh, G.; Valenti, S.; Blagorodnova, N.; Cao, Y.; Duggan, G.; Ravi, V.; Lunnan, R.

2016-03-01

The intermediate Palomar Transient Factory (ATel #4807) reports the discovery and classification of the following Type Ia SNe. Our automated candidate vetting to distinguish a real astrophysical source (1.0) from bogus artifacts (0.0) is powered by three generations of machine learning algorithms: RB2 (Brink et al. 2013MNRAS.435.1047B), RB4 (Rebbapragada et al. 2015AAS...22543402R) and RB5 (Wozniak et al. 2013AAS...22143105W).

iPTF discoveries of recent type Ia supernovae

NASA Astrophysics Data System (ADS)

Papadogiannakis, S.; Ferretti, R.; Fremling, C.; Hangard, L.; Karamehmetoglu, E.; Nyholm, A.; Petrushevska, T.; Roy, R.; De Cia, A.; Vreeswijk, P.; Horesh, A.; Manulis, I.; Sagiv, I.; Rubin, A.; Yaron, O.; Leloudas, G.; Khazov, D.; Soumagnac, M.; Knezevic, S.; Cenko, S. B.; Capone, J.; Bartakk, M.

2015-09-01

The intermediate Palomar Transient Factory (ATel #4807) reports the discovery and classification of the following Type Ia SNe. Our automated candidate vetting to distinguish a real astrophysical source (1.0) from bogus artifacts (0.0) is powered by three generations of machine learning algorithms: RB2 (Brink et al. 2013MNRAS.435.1047B), RB4 (Rebbapragada et al. 2015AAS...22543402R) and RB5 (Wozniak et al. 2013AAS...22143105W).

iPTF Discovery of Recent Type Ia Supernova

NASA Astrophysics Data System (ADS)

Hangard, L.; Petrushevska, T.; Papadogiannakis, S.; Ferretti, R.; Fremling, C.; Karamehmetoglu, E.; Nyholm, A.; Roy, R.; Horesh, A.; Khazov, D.; Knezevic, S.; Johansson, J.; Leloudas, G.; Manulis, I.; Rubin, A.; Soumagnac, M.; Vreeswijk, P.; Yaron, O.; Kasliwal, M.

2015-10-01

The intermediate Palomar Transient Factory (ATel #4807) reports the discovery and classification of the following Type Ia SNe. Our automated candidate vetting to distinguish a real astrophysical source (1.0) from bogus artifacts (0.0) is powered by three generations of machine learning algorithms: RB2 (Brink et al. 2013MNRAS.435.1047B), RB4 (Rebbapragada et al. 2015AAS...22543402R) and RB5 (Wozniak et al. 2013AAS...22143105W).

iPTF Discoveries of Recent Type Ia Supernovae

NASA Astrophysics Data System (ADS)

Petrushevska, T.; Ferretti, R.; Fremling, C.; Hangard, L.; Karamehmetoglu, E.; Nyholm, A.; Papadogiannakis, S.; Roy, R.; Horesh, A.; Khazov, D.; Knezevic, S.; Johansson, J.; Leloudas, G.; Manulis, I.; Rubin, A.; Soumagnac, M.; Vreeswijk, P.; Yaron, O.; Bilgi, P.; Cao, Y.; Duggan, G.; Lunnan, R.; Neill, J. D.; Walters, R.

2016-04-01

The intermediate Palomar Transient Factory (ATel #4807) reports the discovery and classification of the following Type Ia SNe. Our automated candidate vetting to distinguish a real astrophysical source (1.0) from bogus artifacts (0.0) is powered by three generations of machine learning algorithms: RB2 (Brink et al. 2013MNRAS.435.1047B), RB4 (Rebbapragada et al. 2015AAS...22543402R) and RB5 (Wozniak et al. 2013AAS...22143105W).

iPTF Discoveries of Recent Type Ia Supernovae

NASA Astrophysics Data System (ADS)

Papadogiannakis, S.; Taddia, F.; Petrushevska, T.; Fremling, C.; Hangard, L.; Johansson, J.; Karamehmetoglu, E.; Migotto, K.; Nyholm, A.; Roy, R.; Ben-Ami, S.; De Cia, A.; Dzigan, Y.; Horesh, A.; Khazov, D.; Soumagnac, M.; Manulis, I.; Rubin, A.; Sagiv, I.; Vreeswijk, P.; Yaron, O.; Bond, H.; Bilgi, P.; Cao, Y.; Duggan, G.

2015-03-01

The intermediate Palomar Transient Factory (ATel #4807) reports the discovery and classification of the following Type Ia SNe. Our automated candidate vetting to distinguish a real astrophysical source (1.0) from bogus artifacts (0.0) is powered by three generations of machine learning algorithms: RB2 (Brink et al. 2013MNRAS.435.1047B), RB4 (Rebbapragada et al. 2015AAS...22543402R) and RB5 (Wozniak et al. 2013AAS...22143105W).

iPTF Discovery of Recent Type Ia Supernovae

NASA Astrophysics Data System (ADS)

Hangard, L.; Ferretti, R.; Papadogiannakis, S.; Petrushevska, T.; Fremling, C.; Karamehmetoglu, E.; Nyholm, A.; Roy, R.; Horesh, A.; Khazov, D.; Knezevic, S.; Johansson, J.; Leloudas, G.; Manulis, I.; Rubin, A.; Soumagnac, M.; Vreeswijk, P.; Yaron, O.; Cook, D.

2015-12-01

The intermediate Palomar Transient Factory (ATel #4807) reports the discovery and classification of the following Type Ia SNe. Our automated candidate vetting to distinguish a real astrophysical source (1.0) from bogus artifacts (0.0) is powered by three generations of machine learning algorithms: RB2 (Brink et al. 2013MNRAS.435.1047B), RB4 (Rebbapragada et al. 2015AAS...22543402R) and RB5 (Wozniak et al. 2013AAS...22143105W).

iPTF Discoveries of Recent Type Ia Supernova

NASA Astrophysics Data System (ADS)

Petrushevska, T.; Ferretti, R.; Fremling, C.; Hangard, L.; Karamehmetoglu, E.; Nyholm, A.; Papadogiannakis, S.; Roy, R.; Horesh, A.; Khazov, D.; Knezevic, S.; Johansson, J.; Leloudas, G.; Manulis, I.; Rubin, A.; Soumagnac, M.; Vreeswijk, P.; Yaron, O.; Bilgi, P.; Cao, Y.; Duggan, G.; Lunnan, R.; Jencson, J.

2015-11-01

The intermediate Palomar Transient Factory (ATel #4807) reports the discovery and classification of the following Type Ia SNe. Our automated candidate vetting to distinguish a real astrophysical source (1.0) from bogus artifacts (0.0) is powered by three generations of machine learning algorithms: RB2 (Brink et al. 2013MNRAS.435.1047B), RB4 (Rebbapragada et al. 2015AAS...22543402R) and RB5 (Wozniak et al. 2013AAS...22143105W).

Learning styles and teaching/learning strategy preferences: implications for educating nurses in critical care, the operating room, and infection control.

PubMed

Goldrick, B; Gruendemann, B; Larson, E

1993-01-01

To assess the learning styles and educational strategy preferences among critical care nurses, operating room nurses, and infection control practitioners. Descriptive multicenter survey using a self-report questionnaire. 108 hospitals from nine geographic regions of the United States. A random sample of 303 (93%) nurses in the three specialties responded to the survey questionnaires. The majority of participants (64%) had an abstract learning style and preferred the self-directed, discovery approach to learning. Nurses may be more abstract in their learning styles than previously reported. Experiential learning theory is an effective means of identifying nurses' learning styles and teaching/learning preferences, which can then be used to plan basic and continuing educational programs.

Unidata Workshop: Demonstrating Democratization of Numerical Weather Prediction Capabilities Using Linked Environments for Atmospheric Discovery (LEAD) Capabilities

NASA Astrophysics Data System (ADS)

Baltzer, T.; Wilson, A.; Marru, S.; Rossi, A.; Christi, M.; Hampton, S.; Gannon, D.; Alameda, J.; Ramamurthy, M.; Droegemeier, K.

2006-12-01

On July 13th 2006 during the triannual Unidata Workshop, members of the Unidata community got their first experience with capabilities being developed under the Linked Environments for Atmospheric Discovery (LEAD) project (see: http://lead.ou.edu). The key LEAD goal demonstrated during the workshop was that of "Democratization," that is, providing capabilities that typically have a high barrier to entry to the larger meteorological community. At the workshop, participants worked with software that demonstrated the specific concepts of: 1) Lowering the barrier to entry by making it easy for users to: - Experiment using meteorological tools - Create meteorological forecasts - Perform mesoscale modeling and forecasting - Access data (source and product) - Make use of large scale cyberinfrastructure (E.g. TeraGrid) 2) Giving users the freedom from technological issues such as: - Hassle-free access to supercomputing resources - Hassle-free execution of forecast models and related tools - Data format independence This talk will overview the capabilities presented to the Unidata workshop participants as well as capabilities developed since the workshop. There will also be a lessons-learned section. This overview will be accomplished with a live demonstration of some of the capabilities. Capabilities that will be discussed and demonstrated have applicability across many disciplines e.g. discovering, acquiring and using data and orchestrating of complex workflow. Acknowledgement: The LEAD project involves the work of nearly 100 individuals whose dedication has resulted in the capabilities that will be shown here. The authors would like to recognize all of them, but in particular we'd like to recognize: John Caron, Rich Clark, Ethan Davis, Charles Hart, Yuan Ho, Scott Jenson, Rob Kambic, Brian Kelly, Ning Liu, Jeff McWhirter, Don Murray, Beth Plale, Rahul Ramachandran, Yogesh Simmhan, Kevin Thomas, Nithya Vijayakumar, Yunheng Wang, Dan Weber, and Bob Wilhelmson.

IPY Storytelling

NASA Astrophysics Data System (ADS)

Linder, C. A.; Lippsett, L.; Carlowicz, M.

2007-12-01

"Live from the Poles" tells the stories of science on ice. This NSF-sponsored education and outreach project (polardiscovery.whoi.edu) aims to go beyond results and sound bites to convey the full experience of polar research with all its trials, triumphs, and nuances. It uses a multimedia approach, including online photo essays posted daily during expeditions, along with videos, interviews, podcasts, animations, and audio clips-plus live satellite phone calls to audiences in major museums and science centers throughout the country. Our media team, typically a science writer and photographer, are embedded into the research program for the duration of the project. They live in the polar environment with the science party, bolstering their ability to convey the "human side" of the story that engages the public: What inspired the researchers to study the Arctic? What do they eat for dinner? How do they cope with the environment and being away from home? What other unexpected challenges will arise and how will they be overcome? The first expedition, in April 2007, shared the excitement of working in Nunavut, Canada, as researchers prepared to deploy instruments at the North Pole Environmental Observatory. The second followed an international scientific team's search for hydrothermal vents aboard the Swedish icebreaker Oden in July-August 2007. The Polar Discovery Web site has attracted more than 74,000 online visitors in its first eight months of operation. During the first two expeditions, the project facilitated 15 live audio talks to museum audiences, media outlets, and teacher workshops. This presentation will focus on lessons learned from the first two expeditions, with perspectives on science reporting and writing in the field from a science writer at AGU, and on the art of documentary photography, from photographer and project manager Chris Linder, who will speak via satellite phone from the third Polar Discovery expedition in Antarctica.

Educational environment and approaches to learning of undergraduate nursing students in an Indonesian school of nursing.

PubMed

Rochmawati, Erna; Rahayu, Gandes Retno; Kumara, Amitya

2014-11-01

The aims of this study were to assess students' perceptions of their educational environment and approaches to learning, and determine if perceptions of learning environment associates with approaches to learning. A survey was conducted to collect data from a regional private university in Indonesia. A total of 232 nursing students completed two questionnaires that measured their perceptions of educational environment and approaches to learning. The measurement was based on Dundee Ready Education Environment Measurement (DREEM) and Approaches and Study Skills Inventory for Students (ASSIST). Five learning environments dimensions and three learning approaches dimensions from two measures were measured. The overall score of DREEM was 131.03/200 (SD 17.04), it was in the range considered to be favourable. The overall score is different significantly between years of study (p value = 0.01). This study indicated that the majority of undergraduate nursing students' adopt strategic approach (n = 139. 59.9%). The finding showed that perceived educational environment significantly associated with approaches to learning. This study implicated the need to maintain conducive learning environment. There is also a need to improve the management of learning activities that reflect the use of student-centered learning. Copyright © 2014 Elsevier Ltd. All rights reserved.

Accidental Discovery of Information on the User-Defined Social Web: A Mixed-Method Study

ERIC Educational Resources Information Center

Lu, Chi-Jung

2012-01-01

Frequently interacting with other people or working in an information-rich environment can foster the "accidental discovery of information" (ADI) (Erdelez, 2000; McCay-Peet & Toms, 2010). With the increasing adoption of social web technologies, online user-participation communities and user-generated content have provided users the…

Implementing a Discovery Layer: A Rookie's Season

ERIC Educational Resources Information Center

Brubaker, Noah; Leach-Murray, Susan; Parker, Sherri

2012-01-01

The year 2011 was the PALNI (Private Academic Library Network of Indiana) consortium's "rookie season" for the implementation of Primo, the 2010 Discovery Layer 500 race winner. In this article, the authors report on their transition to the cloud within Ex Libris Ltd.'s Primo TotalCare environment: their preparation, the steps involved…

In the Context of Multiple Intelligences Theory, Intelligent Data Analysis of Learning Styles Was Based on Rough Set Theory

ERIC Educational Resources Information Center

Narli, Serkan; Ozgen, Kemal; Alkan, Huseyin

2011-01-01

The present study aims to identify the relationship between individuals' multiple intelligence areas and their learning styles with mathematical clarity using the concept of rough sets which is used in areas such as artificial intelligence, data reduction, discovery of dependencies, prediction of data significance, and generating decision…

Teaching APA Style Documentation: Discovery Learning, Scaffolding and Procedural Knowledge

ERIC Educational Resources Information Center

Skeen, Thomas; Zafonte, Maria

2015-01-01

Students struggle with learning correct documentation style as found in the Publication Manual of the American Psychological Association and teachers are often at a loss for how to best instruct students in correct usage of APA style. As such, the first part of this paper discusses the current research on teaching documentation styles as well as…

Blending Problem-Based Learning and Peer-Led Team Learning, in an Open Ended "Home-Grown" Pharmaceutical Chemistry Case Study

ERIC Educational Resources Information Center

Veale, Clinton G. L.; Krause, Rui W. M.; Sewry, Joyce D.

2018-01-01

Pharmaceutical chemistry, medicinal chemistry and the drug discovery process require experienced practitioners to employ reasoned speculation in generating creative ideas, which can be used to evolve promising molecules into drugs. The ever-evolving world of pharmaceutical chemistry requires university curricula that prepare graduates for their…

Current Research on the Relative Effectiveness of Selected Media Characteristics.

ERIC Educational Resources Information Center

Gulliford, Nancy L.

The literature of research and theory on media, the psychology of learning, and the technology of instruction is reviewed. The focus is on discovering what is currently known about the intersection of these fields. Current thoughts and discoveries about brain structure and processing are discussed. The management of learning as a system is another…

"I'm Just Playing iPad": Comparing Prekindergarteners' and Preservice Teachers' Social Interactions While Using Tablets for Learning

ERIC Educational Resources Information Center

Moore, Holly Carrell; Adair, Jennifer Keys

2015-01-01

In this article we share descriptive findings from two qualitative, grounded theory (Glaser, 1978, 1992, 1998) studies on how two distinct groups of learners--prekindergarteners and preservice teachers in early childhood education coursework--used touch-screen tablets in their playful, discovery-based learning processes. We found similarities…

Librarians Lead the Growth of Information Literacy and Global Digital Citizens

ERIC Educational Resources Information Center

Crockett, Lee Watanabe

2018-01-01

Librarians are leaders in growing global digital citizens. The libraries of the future are more than just housing centers for books and media. They are invigorating meeting places and communities where truly meaningful learning and discovery take place. As technology has transformed reading and learning, it has also transformed the vision of the…

What More Has Been Learned? the Science of Early Childhood Development 15 Years after "Neurons to Neighborhoods"

ERIC Educational Resources Information Center

Thompson, Ross A.

2016-01-01

The new Institute of Medicine/National Research Council report, "Transforming the Workforce for Children From Birth Through Age 8: A Unifying Foundation" (2015), begins with a summary of the science of early development and learning, with particular attention to discoveries during the past 15 years since the publication of "From…