Memory integration in amnesia: prior knowledge supports verbal short-term memory.

PubMed

Race, Elizabeth; Palombo, Daniela J; Cadden, Margaret; Burke, Keely; Verfaellie, Mieke

2015-04-01

Short-term memory (STM) and long-term memory (LTM) have traditionally been considered cognitively distinct. However, it is known that STM can improve when to-be-remembered information appears in contexts that make contact with prior knowledge, suggesting a more interactive relationship between STM and LTM. The current study investigated whether the ability to leverage LTM in support of STM critically depends on the integrity of the hippocampus. Specifically, we investigated whether the hippocampus differentially supports between-domain versus within-domain STM-LTM integration given prior evidence that the representational domain of the elements being integrated in memory is a critical determinant of whether memory performance depends on the hippocampus. In Experiment 1, we investigated hippocampal contributions to within-domain STM-LTM integration by testing whether immediate verbal recall of words improves in MTL amnesic patients when words are presented in familiar verbal contexts (meaningful sentences) compared to unfamiliar verbal contexts (random word lists). Patients demonstrated a robust sentence superiority effect, whereby verbal STM performance improved in familiar compared to unfamiliar verbal contexts, and the magnitude of this effect did not differ from that in controls. In Experiment 2, we investigated hippocampal contributions to between-domain STM-LTM integration by testing whether immediate verbal recall of digits improves in MTL amnesic patients when digits are presented in a familiar visuospatial context (a typical keypad layout) compared to an unfamiliar visuospatial context (a random keypad layout). Immediate verbal recall improved in both patients and controls when digits were presented in the familiar compared to the unfamiliar keypad array, indicating a preserved ability to integrate activated verbal information with stored visuospatial knowledge. Together, these results demonstrate that immediate verbal recall in amnesia can benefit from two distinct types of semantic support, verbal and visuospatial, and that the hippocampus is not critical for leveraging stored semantic knowledge to improve memory performance. Copyright © 2015 Elsevier Ltd. All rights reserved.

Memory integration in amnesia: Prior knowledge supports verbal short-term memory

PubMed Central

Race, Elizabeth; Palombo, Daniela J.; Cadden, Margaret; Burke, Keely; Verfaellie, Mieke

2015-01-01

Short-term memory (STM) and long-term memory (LTM) have traditionally been considered cognitively distinct. However, it is known that STM can improve when to-be-remembered information appears in contexts that make contact with prior knowledge, suggesting a more interactive relationship between STM and LTM. The current study investigated whether the ability to leverage LTM in support of STM critically depends on the integrity of the hippocampus. Specifically, we investigated whether the hippocampus differentially supports between-domain versus within-domain STM–LTM integration given prior evidence that the representational domain of the elements being integrated in memory is a critical determinant of whether memory performance depends on the hippocampus. In Experiment 1, we investigated hippocampal contributions to within-domain STM–LTM integration by testing whether immediate verbal recall of words improves in MTL amnesic patients when words are presented in familiar verbal contexts (meaningful sentences) compared to unfamiliar verbal contexts (random word lists). Patients demonstrated a robust sentence superiority effect, whereby verbal STM performance improved in familiar compared to unfamiliar verbal contexts, and the magnitude of this effect did not differ from that in controls. In Experiment 2, we investigated hippocampal contributions to between-domain STM–LTM integration by testing whether immediate verbal recall of digits improves in MTL amnesic patients when digits are presented in a familiar visuospatial context (a typical keypad layout) compared to an unfamiliar visuospatial context (a random keypad layout). Immediate verbal recall improved in both patients and controls when digits were presented in the familiar compared to the unfamiliar keypad array, indicating a preserved ability to integrate activated verbal information with stored visuospatial knowledge. Together, these results demonstrate that immediate verbal recall in amnesia can benefit from two distinct types of semantic support, verbal and visuospatial, and that the hippocampus is not critical for leveraging stored semantic knowledge to improve memory performance. PMID:25752585

Designing computer learning environments for engineering and computer science: The scaffolded knowledge integration framework

NASA Astrophysics Data System (ADS)

Linn, Marcia C.

1995-06-01

Designing effective curricula for complex topics and incorporating technological tools is an evolving process. One important way to foster effective design is to synthesize successful practices. This paper describes a framework called scaffolded knowledge integration and illustrates how it guided the design of two successful course enhancements in the field of computer science and engineering. One course enhancement, the LISP Knowledge Integration Environment, improved learning and resulted in more gender-equitable outcomes. The second course enhancement, the spatial reasoning environment, addressed spatial reasoning in an introductory engineering course. This enhancement minimized the importance of prior knowledge of spatial reasoning and helped students develop a more comprehensive repertoire of spatial reasoning strategies. Taken together, the instructional research programs reinforce the value of the scaffolded knowledge integration framework and suggest directions for future curriculum reformers.

Indicators and measurement tools for health system integration: a knowledge synthesis protocol.

PubMed

Oelke, Nelly D; Suter, Esther; da Silva Lima, Maria Alice Dias; Van Vliet-Brown, Cheryl

2015-07-29

Health system integration is a key component of health system reform with the goal of improving outcomes for patients, providers, and the health system. Although health systems continue to strive for better integration, current delivery of health services continues to be fragmented. A key gap in the literature is the lack of information on what successful integration looks like and how to measure achievement towards an integrated system. This multi-site study protocol builds on a prior knowledge synthesis completed by two of the primary investigators which identified 10 key principles that collectively support health system integration. The aim is to answer two research questions: What are appropriate indicators for each of the 10 key integration principles developed in our previous knowledge synthesis and what measurement tools are used to measure these indicators? To enhance generalizability of the findings, a partnership between Canada and Brazil was created as health system integration is a priority in both countries and they share similar contexts. This knowledge synthesis will follow an iterative scoping review process with emerging information from knowledge-user engagement leading to the refinement of research questions and study selection. This paper describes the methods for each phase of the study. Research questions were developed with stakeholder input. Indicator identification and prioritization will utilize a modified Delphi method and patient/user focus groups. Based on priority indicators, a search of the literature will be completed and studies screened for inclusion. Quality appraisal of relevant studies will be completed prior to data extraction. Results will be used to develop recommendations and key messages to be presented through integrated and end-of-grant knowledge translation strategies with researchers and knowledge-users from the three jurisdictions. This project will directly benefit policy and decision-makers by providing an easy accessible set of indicators and tools to measure health system integration across different contexts and cultures. Being able to evaluate the success of integration strategies and initiatives will lead to better health system design and improved health outcomes for patients.

A computational modeling of semantic knowledge in reading comprehension: Integrating the landscape model with latent semantic analysis.

PubMed

Yeari, Menahem; van den Broek, Paul

2016-09-01

It is a well-accepted view that the prior semantic (general) knowledge that readers possess plays a central role in reading comprehension. Nevertheless, computational models of reading comprehension have not integrated the simulation of semantic knowledge and online comprehension processes under a unified mathematical algorithm. The present article introduces a computational model that integrates the landscape model of comprehension processes with latent semantic analysis representation of semantic knowledge. In three sets of simulations of previous behavioral findings, the integrated model successfully simulated the activation and attenuation of predictive and bridging inferences during reading, as well as centrality estimations and recall of textual information after reading. Analyses of the computational results revealed new theoretical insights regarding the underlying mechanisms of the various comprehension phenomena.

Integration of prior knowledge into dense image matching for video surveillance

NASA Astrophysics Data System (ADS)

Menze, M.; Heipke, C.

2014-08-01

Three-dimensional information from dense image matching is a valuable input for a broad range of vision applications. While reliable approaches exist for dedicated stereo setups they do not easily generalize to more challenging camera configurations. In the context of video surveillance the typically large spatial extent of the region of interest and repetitive structures in the scene render the application of dense image matching a challenging task. In this paper we present an approach that derives strong prior knowledge from a planar approximation of the scene. This information is integrated into a graph-cut based image matching framework that treats the assignment of optimal disparity values as a labelling task. Introducing the planar prior heavily reduces ambiguities together with the search space and increases computational efficiency. The results provide a proof of concept of the proposed approach. It allows the reconstruction of dense point clouds in more general surveillance camera setups with wider stereo baselines.

Cooperative Education, Experiential Learning, and Personal Knowledge.

ERIC Educational Resources Information Center

Abrahamsson, Kenneth, Ed.

Cooperative education, experiential learning, and personal knowledge are addressed in nine conference papers. Kenneth Abrahamsson considers the nature of experiential learning, the recognition of prior learning, educational design and the assessment of quality, and policy and practice for integrating learning and experience. Harry Hienemann…

The Second Prototype of the Development of a Technological Pedagogical Content Knowledge Based Instructional Design Model: An Implementation Study in a Technology Integration Course

ERIC Educational Resources Information Center

Lee, Chia-Jung; Kim, ChanMin

2014-01-01

This study presents a refined technological pedagogical content knowledge (also known as TPACK) based instructional design model, which was revised using findings from the implementation study of a prior model. The refined model was applied in a technology integration course with 38 preservice teachers. A case study approach was used in this…

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

Zhu, Yitan; Xu, Yanxun; Helseth, Donald L.

Background: Genetic interactions play a critical role in cancer development. Existing knowledge about cancer genetic interactions is incomplete, especially lacking evidences derived from large-scale cancer genomics data. The Cancer Genome Atlas (TCGA) produces multimodal measurements across genomics and features of thousands of tumors, which provide an unprecedented opportunity to investigate the interplays of genes in cancer. Methods: We introduce Zodiac, a computational tool and resource to integrate existing knowledge about cancer genetic interactions with new information contained in TCGA data. It is an evolution of existing knowledge by treating it as a prior graph, integrating it with a likelihood modelmore » derived by Bayesian graphical model based on TCGA data, and producing a posterior graph as updated and data-enhanced knowledge. In short, Zodiac realizes “Prior interaction map + TCGA data → Posterior interaction map.” Results: Zodiac provides molecular interactions for about 200 million pairs of genes. All the results are generated from a big-data analysis and organized into a comprehensive database allowing customized search. In addition, Zodiac provides data processing and analysis tools that allow users to customize the prior networks and update the genetic pathways of their interest. Zodiac is publicly available at www.compgenome.org/ZODIAC. Conclusions: Zodiac recapitulates and extends existing knowledge of molecular interactions in cancer. It can be used to explore novel gene-gene interactions, transcriptional regulation, and other types of molecular interplays in cancer.« less

INCORPORATING PRIOR KNOWLEDGE IN ENVIRONMENTAL SAMPLING: RANKED SET SAMPLING AND OTHER DOUBLE SAMPLING PROCEDURES

EPA Science Inventory

Environmental sampling can be difficult and expensive to carry out. Those taking the samples would like to integrate their knowledge of the system of study or their judgment about the system into the sample selection process to decrease the number of necessary samples. However,...

Prior knowledge guided active modules identification: an integrated multi-objective approach.

PubMed

Chen, Weiqi; Liu, Jing; He, Shan

2017-03-14

Active module, defined as an area in biological network that shows striking changes in molecular activity or phenotypic signatures, is important to reveal dynamic and process-specific information that is correlated with cellular or disease states. A prior information guided active module identification approach is proposed to detect modules that are both active and enriched by prior knowledge. We formulate the active module identification problem as a multi-objective optimisation problem, which consists two conflicting objective functions of maximising the coverage of known biological pathways and the activity of the active module simultaneously. Network is constructed from protein-protein interaction database. A beta-uniform-mixture model is used to estimate the distribution of p-values and generate scores for activity measurement from microarray data. A multi-objective evolutionary algorithm is used to search for Pareto optimal solutions. We also incorporate a novel constraints based on algebraic connectivity to ensure the connectedness of the identified active modules. Application of proposed algorithm on a small yeast molecular network shows that it can identify modules with high activities and with more cross-talk nodes between related functional groups. The Pareto solutions generated by the algorithm provides solutions with different trade-off between prior knowledge and novel information from data. The approach is then applied on microarray data from diclofenac-treated yeast cells to build network and identify modules to elucidate the molecular mechanisms of diclofenac toxicity and resistance. Gene ontology analysis is applied to the identified modules for biological interpretation. Integrating knowledge of functional groups into the identification of active module is an effective method and provides a flexible control of balance between pure data-driven method and prior information guidance.

Central tendency effects in time interval reproduction in autism

PubMed Central

Karaminis, Themelis; Cicchini, Guido Marco; Neil, Louise; Cappagli, Giulia; Aagten-Murphy, David; Burr, David; Pellicano, Elizabeth

2016-01-01

Central tendency, the tendency of judgements of quantities (lengths, durations etc.) to gravitate towards their mean, is one of the most robust perceptual effects. A Bayesian account has recently suggested that central tendency reflects the integration of noisy sensory estimates with prior knowledge representations of a mean stimulus, serving to improve performance. The process is flexible, so prior knowledge is weighted more heavily when sensory estimates are imprecise, requiring more integration to reduce noise. In this study we measure central tendency in autism to evaluate a recent theoretical hypothesis suggesting that autistic perception relies less on prior knowledge representations than typical perception. If true, autistic children should show reduced central tendency than theoretically predicted from their temporal resolution. We tested autistic and age- and ability-matched typical children in two child-friendly tasks: (1) a time interval reproduction task, measuring central tendency in the temporal domain; and (2) a time discrimination task, assessing temporal resolution. Central tendency reduced with age in typical development, while temporal resolution improved. Autistic children performed far worse in temporal discrimination than the matched controls. Computational simulations suggested that central tendency was much less in autistic children than predicted by theoretical modelling, given their poor temporal resolution. PMID:27349722

A Fast Variant of 1H Spectroscopic U-FLARE Imaging Using Adjusted Chemical Shift Phase Encoding

NASA Astrophysics Data System (ADS)

Ebel, Andreas; Dreher, Wolfgang; Leibfritz, Dieter

2000-02-01

So far, fast spectroscopic imaging (SI) using the U-FLARE sequence has provided metabolic maps indirectly via Fourier transformation (FT) along the chemical shift (CS) dimension and subsequent peak integration. However, a large number of CS encoding steps Nω is needed to cover the spectral bandwidth and to achieve sufficient spectral resolution for peak integration even if the number of resonance lines is small compared to Nω and even if only metabolic images are of interest and not the spectra in each voxel. Other reconstruction algorithms require extensive prior knowledge, starting values, and/or model functions. An adjusted CS phase encoding scheme (APE) can be used to overcome these drawbacks. It incorporates prior knowledge only about the resonance frequencies present in the sample. Thus, Nω can be reduced by a factor of 4 for many 1H in vivo studies while no spectra have to be reconstructed, and no additional user interaction, prior knowledge, starting values, or model function are required. Phantom measurements and in vivo experiments on rat brain have been performed at 4.7 T to test the feasibility of the method for proton SI.

Knowledge Contribution in Virtual Communities: Accounting for Multiple Dimensions of Social Presence through Social Identity

ERIC Educational Resources Information Center

Shen, Kathy Ning; Yu, Angela Yan; Khalifa, Mohamed

2010-01-01

Integrating social presence theory and social identity theory, this study brings system design and social influence aspects together to explain their joint effects on knowledge contribution in virtual communities (VCs). Different from most prior information systems (IS) research that adopts a uni-dimensional approach and restricts social presence…

Processing and memory of information presented in narrative or expository texts.

PubMed

Wolfe, Michael B W; Woodwyk, Joshua M

2010-09-01

Previous research suggests that narrative and expository texts differ in the extent to which they prompt students to integrate to-be-learned content with relevant prior knowledge during comprehension. We expand on previous research by examining on-line processing and representation in memory of to-be-learned content that is embedded in narrative or expository texts. We are particularly interested in how differences in the use of relevant prior knowledge leads to differences in terms of levels of discourse representation (textbase vs. situation model). A total of 61 university undergraduates in Expt 1, and 160 in Expt 2. In Expt 1, subjects thought out loud while comprehending circulatory system content embedded in a narrative or expository text, followed by free recall of text content. In Expt 2, subjects read silently and completed a sentence recognition task to assess memory. In Expt 1, subjects made more associations to prior knowledge while reading the expository text, and recalled more content. Content recall was also correlated with amount of relevant prior knowledge for subjects who read the expository text but not the narrative text. In Expt 2, subjects reading the expository text (compared to the narrative text) had a weaker textbase representation of the to-be-learned content, but a marginally stronger situation model. Results suggest that in terms of to-be-learned content, expository texts trigger students to utilize relevant prior knowledge more than narrative texts.

The Design and Assessment of a Hypermedia Course on Semiconductor Manufacturing.

ERIC Educational Resources Information Center

Schank, Patrick K.; Rowe, Lawrence A.

1993-01-01

Describes the design and evaluation of a multimedia course on integrated circuit manufacturing that was developed at the University of California at Berkeley using IC-HIP (Integrated Circuit-Hypermedia in PICASSO), a hypermedia-based instructional system. Learning effects based on prior knowledge, methods of navigation, and other factors are…

Visual representations in science education: The influence of prior knowledge and cognitive load theory on instructional design principles

NASA Astrophysics Data System (ADS)

Cook, Michelle Patrick

2006-11-01

Visual representations are essential for communicating ideas in the science classroom; however, the design of such representations is not always beneficial for learners. This paper presents instructional design considerations providing empirical evidence and integrating theoretical concepts related to cognitive load. Learners have a limited working memory, and instructional representations should be designed with the goal of reducing unnecessary cognitive load. However, cognitive architecture alone is not the only factor to be considered; individual differences, especially prior knowledge, are critical in determining what impact a visual representation will have on learners' cognitive structures and processes. Prior knowledge can determine the ease with which learners can perceive and interpret visual representations in working memory. Although a long tradition of research has compared experts and novices, more research is necessary to fully explore the expert-novice continuum and maximize the potential of visual representations.

Autistic traits, but not schizotypy, predict increased weighting of sensory information in Bayesian visual integration.

PubMed

Karvelis, Povilas; Seitz, Aaron R; Lawrie, Stephen M; Seriès, Peggy

2018-05-14

Recent theories propose that schizophrenia/schizotypy and autistic spectrum disorder are related to impairments in Bayesian inference that is, how the brain integrates sensory information (likelihoods) with prior knowledge. However existing accounts fail to clarify: (i) how proposed theories differ in accounts of ASD vs. schizophrenia and (ii) whether the impairments result from weaker priors or enhanced likelihoods. Here, we directly address these issues by characterizing how 91 healthy participants, scored for autistic and schizotypal traits, implicitly learned and combined priors with sensory information. This was accomplished through a visual statistical learning paradigm designed to quantitatively assess variations in individuals' likelihoods and priors. The acquisition of the priors was found to be intact along both traits spectra. However, autistic traits were associated with more veridical perception and weaker influence of expectations. Bayesian modeling revealed that this was due, not to weaker prior expectations, but to more precise sensory representations. © 2018, Karvelis et al.

The Problems of Validation in a Competency-Based Preservice Reading Education Program.

ERIC Educational Resources Information Center

Bergquist, Sidney R.

A problem of teacher education is to successfully integrate the knowledge students learn in the college classroom with the practical experiences of student teaching. A principal objective of an ideal teacher training situation would be to establish a vertical integration of the various types of exposure to reading both prior to and during contact…

Learning and inference using complex generative models in a spatial localization task.

PubMed

Bejjanki, Vikranth R; Knill, David C; Aslin, Richard N

2016-01-01

A large body of research has established that, under relatively simple task conditions, human observers integrate uncertain sensory information with learned prior knowledge in an approximately Bayes-optimal manner. However, in many natural tasks, observers must perform this sensory-plus-prior integration when the underlying generative model of the environment consists of multiple causes. Here we ask if the Bayes-optimal integration seen with simple tasks also applies to such natural tasks when the generative model is more complex, or whether observers rely instead on a less efficient set of heuristics that approximate ideal performance. Participants localized a "hidden" target whose position on a touch screen was sampled from a location-contingent bimodal generative model with different variances around each mode. Over repeated exposure to this task, participants learned the a priori locations of the target (i.e., the bimodal generative model), and integrated this learned knowledge with uncertain sensory information on a trial-by-trial basis in a manner consistent with the predictions of Bayes-optimal behavior. In particular, participants rapidly learned the locations of the two modes of the generative model, but the relative variances of the modes were learned much more slowly. Taken together, our results suggest that human performance in a more complex localization task, which requires the integration of sensory information with learned knowledge of a bimodal generative model, is consistent with the predictions of Bayes-optimal behavior, but involves a much longer time-course than in simpler tasks.

Accessing and integrating data and knowledge for biomedical research.

PubMed

Burgun, A; Bodenreider, O

2008-01-01

To review the issues that have arisen with the advent of translational research in terms of integration of data and knowledge, and survey current efforts to address these issues. Using examples form the biomedical literature, we identified new trends in biomedical research and their impact on bioinformatics. We analyzed the requirements for effective knowledge repositories and studied issues in the integration of biomedical knowledge. New diagnostic and therapeutic approaches based on gene expression patterns have brought about new issues in the statistical analysis of data, and new workflows are needed are needed to support translational research. Interoperable data repositories based on standard annotations, infrastructures and services are needed to support the pooling and meta-analysis of data, as well as their comparison to earlier experiments. High-quality, integrated ontologies and knowledge bases serve as a source of prior knowledge used in combination with traditional data mining techniques and contribute to the development of more effective data analysis strategies. As biomedical research evolves from traditional clinical and biological investigations towards omics sciences and translational research, specific needs have emerged, including integrating data collected in research studies with patient clinical data, linking omics knowledge with medical knowledge, modeling the molecular basis of diseases, and developing tools that support in-depth analysis of research data. As such, translational research illustrates the need to bridge the gap between bioinformatics and medical informatics, and opens new avenues for biomedical informatics research.

Effectiveness of a perinatal and pediatric End-of-Life Nursing Education Consortium (ELNEC) curricula integration.

PubMed

O'Shea, Eileen R; Campbell, Suzanne Hetzel; Engler, Arthur J; Beauregard, Rachel; Chamberlin, Elizabeth C; Currie, Leanne M

2015-06-01

Educational practices and national guidelines for best practices of providing palliative care to children and their families have been developed and are gaining support; however, the dissemination of those practices lags behind expectations. Incorporating education for pediatric palliative care into nursing pre-licensure programs will provide guidelines for best practices with opportunities to enact them prior to graduation. To evaluate the effect of an integrated curriculum for palliative care on nursing students' knowledge. Matched pretest-posttest. One private and one public university in the northeastern United States. Two groups of baccalaureate nursing students, one exposed to an integrated curriculum for palliative care and one without the same exposure. Pre-testing of the students with a 50-item multiple choice instrument prior to curriculum integration and post-testing with the same instrument at the end of the term. This analysis demonstrated changes in knowledge scores among the experimental (n=40) and control (n=19) groups that were statistically significant by time (Wilks' Lambda=.90, F(1, 57)=6.70, p=.012) and study group (Wilks' Lambda=.83, F(1, 57)=11.79, p=.001). An integrated curriculum for pediatric and perinatal palliative and end-of-life care can demonstrate an increased knowledge in a small convenience sample of pre-licensure baccalaureate nursing students when compared to a control group not exposed to the same curriculum. Future research can examine the effect on graduates' satisfaction with program preparation for this specialty area; the role of the use of the curriculum with practice-partners to strengthen transfer of knowledge to the clinical environment; and the use of this curriculum interprofessionally. Copyright © 2015 Elsevier Ltd. All rights reserved.

Features of Knowledge Building in Biology: Understanding Undergraduate Students’ Ideas about Molecular Mechanisms

PubMed Central

Southard, Katelyn; Wince, Tyler; Meddleton, Shanice; Bolger, Molly S.

2016-01-01

Research has suggested that teaching and learning in molecular and cellular biology (MCB) is difficult. We used a new lens to understand undergraduate reasoning about molecular mechanisms: the knowledge-integration approach to conceptual change. Knowledge integration is the dynamic process by which learners acquire new ideas, develop connections between ideas, and reorganize and restructure prior knowledge. Semistructured, clinical think-aloud interviews were conducted with introductory and upper-division MCB students. Interviews included a written conceptual assessment, a concept-mapping activity, and an opportunity to explain the biomechanisms of DNA replication, transcription, and translation. Student reasoning patterns were explored through mixed-method analyses. Results suggested that students must sort mechanistic entities into appropriate mental categories that reflect the nature of MCB mechanisms and that conflation between these categories is common. We also showed how connections between molecular mechanisms and their biological roles are part of building an integrated knowledge network as students develop expertise. We observed differences in the nature of connections between ideas related to different forms of reasoning. Finally, we provide a tentative model for MCB knowledge integration and suggest its implications for undergraduate learning. PMID:26931398

Integrating Emerging Topics through Online Team Design in a Hybrid Communication Networks Course: Interaction Patterns and Impact of Prior Knowledge

ERIC Educational Resources Information Center

Reisslein, Jana; Seeling, Patrick; Reisslein, Martin

2005-01-01

An important challenge in the introductory communication networks course in electrical and computer engineering curricula is to integrate emerging topics, such as wireless Internet access and network security, into the already content-intensive course. At the same time it is essential to provide students with experiences in online collaboration,…

Integrative Sparse K-Means With Overlapping Group Lasso in Genomic Applications for Disease Subtype Discovery

PubMed Central

Huo, Zhiguang; Tseng, George

2017-01-01

Cancer subtypes discovery is the first step to deliver personalized medicine to cancer patients. With the accumulation of massive multi-level omics datasets and established biological knowledge databases, omics data integration with incorporation of rich existing biological knowledge is essential for deciphering a biological mechanism behind the complex diseases. In this manuscript, we propose an integrative sparse K-means (is-K means) approach to discover disease subtypes with the guidance of prior biological knowledge via sparse overlapping group lasso. An algorithm using an alternating direction method of multiplier (ADMM) will be applied for fast optimization. Simulation and three real applications in breast cancer and leukemia will be used to compare is-K means with existing methods and demonstrate its superior clustering accuracy, feature selection, functional annotation of detected molecular features and computing efficiency. PMID:28959370

Integrative Sparse K-Means With Overlapping Group Lasso in Genomic Applications for Disease Subtype Discovery.

PubMed

Huo, Zhiguang; Tseng, George

2017-06-01

Cancer subtypes discovery is the first step to deliver personalized medicine to cancer patients. With the accumulation of massive multi-level omics datasets and established biological knowledge databases, omics data integration with incorporation of rich existing biological knowledge is essential for deciphering a biological mechanism behind the complex diseases. In this manuscript, we propose an integrative sparse K -means (is- K means) approach to discover disease subtypes with the guidance of prior biological knowledge via sparse overlapping group lasso. An algorithm using an alternating direction method of multiplier (ADMM) will be applied for fast optimization. Simulation and three real applications in breast cancer and leukemia will be used to compare is- K means with existing methods and demonstrate its superior clustering accuracy, feature selection, functional annotation of detected molecular features and computing efficiency.

The influence of prior knowledge on the retrieval-directed function of note taking in prior knowledge activation.

PubMed

Wetzels, Sandra A J; Kester, Liesbeth; van Merriënboer, Jeroen J G; Broers, Nick J

2011-06-01

Prior knowledge activation facilitates learning. Note taking during prior knowledge activation (i.e., note taking directed at retrieving information from memory) might facilitate the activation process by enabling learners to build an external representation of their prior knowledge. However, taking notes might be less effective in supporting prior knowledge activation if available prior knowledge is limited. This study investigates the effects of the retrieval-directed function of note taking depending on learners' level of prior knowledge. It is hypothesized that the effectiveness of note taking is influenced by the amount of prior knowledge learners already possess. Sixty-one high school students participated in this study. A prior knowledge test was used to ascertain differences in level of prior knowledge and assign participants to a low or a high prior knowledge group. A 2×2 factorial design was used to investigate the effects of note taking during prior knowledge activation (yes, no) depending on learners' level of prior knowledge (low, high) on mental effort, performance, and mental efficiency. Note taking during prior knowledge activation lowered mental effort and increased mental efficiency for high prior knowledge learners. For low prior knowledge learners, note taking had the opposite effect on mental effort and mental efficiency. The effects of the retrieval-directed function of note taking are influenced by learners' level of prior knowledge. Learners with high prior knowledge benefit from taking notes while activating prior knowledge, whereas note taking has no beneficial effects for learners with limited prior knowledge. ©2010 The British Psychological Society.

The SwissLipids knowledgebase for lipid biology

PubMed Central

Liechti, Robin; Hyka-Nouspikel, Nevila; Niknejad, Anne; Gleizes, Anne; Götz, Lou; Kuznetsov, Dmitry; David, Fabrice P.A.; van der Goot, F. Gisou; Riezman, Howard; Bougueleret, Lydie; Xenarios, Ioannis; Bridge, Alan

2015-01-01

Motivation: Lipids are a large and diverse group of biological molecules with roles in membrane formation, energy storage and signaling. Cellular lipidomes may contain tens of thousands of structures, a staggering degree of complexity whose significance is not yet fully understood. High-throughput mass spectrometry-based platforms provide a means to study this complexity, but the interpretation of lipidomic data and its integration with prior knowledge of lipid biology suffers from a lack of appropriate tools to manage the data and extract knowledge from it. Results: To facilitate the description and exploration of lipidomic data and its integration with prior biological knowledge, we have developed a knowledge resource for lipids and their biology—SwissLipids. SwissLipids provides curated knowledge of lipid structures and metabolism which is used to generate an in silico library of feasible lipid structures. These are arranged in a hierarchical classification that links mass spectrometry analytical outputs to all possible lipid structures, metabolic reactions and enzymes. SwissLipids provides a reference namespace for lipidomic data publication, data exploration and hypothesis generation. The current version of SwissLipids includes over 244 000 known and theoretically possible lipid structures, over 800 proteins, and curated links to published knowledge from over 620 peer-reviewed publications. We are continually updating the SwissLipids hierarchy with new lipid categories and new expert curated knowledge. Availability: SwissLipids is freely available at http://www.swisslipids.org/. Contact: alan.bridge@isb-sib.ch Supplementary information: Supplementary data are available at Bioinformatics online. PMID:25943471

A schema theory analysis of students' think aloud protocols in an STS biology context

NASA Astrophysics Data System (ADS)

Quinlan, Catherine Louise

This dissertation study is a conglomerate of the fields of Science Education and Applied Cognitive Psychology. The goal of this study is to determine what organizational features and knowledge representation patterns high school students exhibit over time for issues pertinent to science and society. Participants are thirteen tenth grade students in a diverse suburban-urban classroom in a northeastern state. Students' think alouds are recorded, pre-, post-, and late-post treatment. Treatment consists of instruction in three Science, Technology, and Society (STS) biology issues, namely the human genome project, nutrition and health, and stem cell research. Coding and analyses are performed using Marshall's knowledge representations---identification knowledge, elaboration knowledge, planning knowledge, and execution knowledge, as well as qualitative research analysis methods. Schema theory, information processing theory, and other applied cognitive theory provide a framework in which to understand and explain students' schema descriptions and progressions over time. The results show that students display five organizational features in their identification and elaboration knowledge. Students also fall into one of four categories according to if they display prior schema or no prior schema, and their orientation "for" or "against," some of the issues. Students with prior schema and orientation "against" display the most robust schema descriptions and schema progressions. Those with no prior schemas and orientation "against" show very modest schema progressions best characterized by their keyword searches. This study shows the importance in considering not only students' integrated schemas but also their individual schemes. A role for the use of a more schema-based instruction that scaffolds student learning is implicated.

Accessing and Integrating Data and Knowledge for Biomedical Research

PubMed Central

Burgun, A.; Bodenreider, O.

2008-01-01

Summary Objectives To review the issues that have arisen with the advent of translational research in terms of integration of data and knowledge, and survey current efforts to address these issues. Methods Using examples form the biomedical literature, we identified new trends in biomedical research and their impact on bioinformatics. We analyzed the requirements for effective knowledge repositories and studied issues in the integration of biomedical knowledge. Results New diagnostic and therapeutic approaches based on gene expression patterns have brought about new issues in the statistical analysis of data, and new workflows are needed are needed to support translational research. Interoperable data repositories based on standard annotations, infrastructures and services are needed to support the pooling and meta-analysis of data, as well as their comparison to earlier experiments. High-quality, integrated ontologies and knowledge bases serve as a source of prior knowledge used in combination with traditional data mining techniques and contribute to the development of more effective data analysis strategies. Conclusion As biomedical research evolves from traditional clinical and biological investigations towards omics sciences and translational research, specific needs have emerged, including integrating data collected in research studies with patient clinical data, linking omics knowledge with medical knowledge, modeling the molecular basis of diseases, and developing tools that support in-depth analysis of research data. As such, translational research illustrates the need to bridge the gap between bioinformatics and medical informatics, and opens new avenues for biomedical informatics research. PMID:18660883

Integrated Analysis of Pharmacologic, Clinical, and SNP Microarray Data using Projection onto the Most Interesting Statistical Evidence with Adaptive Permutation Testing

PubMed Central

Pounds, Stan; Cao, Xueyuan; Cheng, Cheng; Yang, Jun; Campana, Dario; Evans, William E.; Pui, Ching-Hon; Relling, Mary V.

2010-01-01

Powerful methods for integrated analysis of multiple biological data sets are needed to maximize interpretation capacity and acquire meaningful knowledge. We recently developed Projection Onto the Most Interesting Statistical Evidence (PROMISE). PROMISE is a statistical procedure that incorporates prior knowledge about the biological relationships among endpoint variables into an integrated analysis of microarray gene expression data with multiple biological and clinical endpoints. Here, PROMISE is adapted to the integrated analysis of pharmacologic, clinical, and genome-wide genotype data that incorporating knowledge about the biological relationships among pharmacologic and clinical response data. An efficient permutation-testing algorithm is introduced so that statistical calculations are computationally feasible in this higher-dimension setting. The new method is applied to a pediatric leukemia data set. The results clearly indicate that PROMISE is a powerful statistical tool for identifying genomic features that exhibit a biologically meaningful pattern of association with multiple endpoint variables. PMID:21516175

A bayesian translational framework for knowledge propagation, discovery, and integration under specific contexts.

PubMed

Deng, Michelle; Zollanvari, Amin; Alterovitz, Gil

2012-01-01

The immense corpus of biomedical literature existing today poses challenges in information search and integration. Many links between pieces of knowledge occur or are significant only under certain contexts-rather than under the entire corpus. This study proposes using networks of ontology concepts, linked based on their co-occurrences in annotations of abstracts of biomedical literature and descriptions of experiments, to draw conclusions based on context-specific queries and to better integrate existing knowledge. In particular, a Bayesian network framework is constructed to allow for the linking of related terms from two biomedical ontologies under the queried context concept. Edges in such a Bayesian network allow associations between biomedical concepts to be quantified and inference to be made about the existence of some concepts given prior information about others. This approach could potentially be a powerful inferential tool for context-specific queries, applicable to ontologies in other fields as well.

A Bayesian Translational Framework for Knowledge Propagation, Discovery, and Integration Under Specific Contexts

PubMed Central

Deng, Michelle; Zollanvari, Amin; Alterovitz, Gil

2012-01-01

The immense corpus of biomedical literature existing today poses challenges in information search and integration. Many links between pieces of knowledge occur or are significant only under certain contexts—rather than under the entire corpus. This study proposes using networks of ontology concepts, linked based on their co-occurrences in annotations of abstracts of biomedical literature and descriptions of experiments, to draw conclusions based on context-specific queries and to better integrate existing knowledge. In particular, a Bayesian network framework is constructed to allow for the linking of related terms from two biomedical ontologies under the queried context concept. Edges in such a Bayesian network allow associations between biomedical concepts to be quantified and inference to be made about the existence of some concepts given prior information about others. This approach could potentially be a powerful inferential tool for context-specific queries, applicable to ontologies in other fields as well. PMID:22779044

Prior knowledge-based approach for associating ...

EPA Pesticide Factsheets

Evaluating the potential human health and/or ecological risks associated with exposures to complex chemical mixtures in the ambient environment is one of the central challenges of chemical safety assessment and environmental protection. There is a need for approaches that can help to integrate chemical monitoring and bio-effects data to evaluate risks associated with chemicals present in the environment. We used prior knowledge about chemical-gene interactions to develop a knowledge assembly model for detected chemicals at five locations near two wastewater treatment plants. The assembly model was used to generate hypotheses about the biological impacts of the chemicals at each location. The hypotheses were tested using empirical hepatic gene expression data from fathead minnows exposed for 12 d at each location. Empirical gene expression data was also mapped to the assembly models to statistically evaluate the likelihood of a chemical contributing to the observed biological responses. The prior knowledge approach was able reasonably hypothesize the biological impacts at one site but not the other. Chemicals most likely contributing to the observed biological responses were identified at each location. Despite limitations to the approach, knowledge assembly models have strong potential for associating chemical occurrence with potential biological effects and providing a foundation for hypothesis generation to guide research and/or monitoring efforts relat

Boosting probabilistic graphical model inference by incorporating prior knowledge from multiple sources.

PubMed

Praveen, Paurush; Fröhlich, Holger

2013-01-01

Inferring regulatory networks from experimental data via probabilistic graphical models is a popular framework to gain insights into biological systems. However, the inherent noise in experimental data coupled with a limited sample size reduces the performance of network reverse engineering. Prior knowledge from existing sources of biological information can address this low signal to noise problem by biasing the network inference towards biologically plausible network structures. Although integrating various sources of information is desirable, their heterogeneous nature makes this task challenging. We propose two computational methods to incorporate various information sources into a probabilistic consensus structure prior to be used in graphical model inference. Our first model, called Latent Factor Model (LFM), assumes a high degree of correlation among external information sources and reconstructs a hidden variable as a common source in a Bayesian manner. The second model, a Noisy-OR, picks up the strongest support for an interaction among information sources in a probabilistic fashion. Our extensive computational studies on KEGG signaling pathways as well as on gene expression data from breast cancer and yeast heat shock response reveal that both approaches can significantly enhance the reconstruction accuracy of Bayesian Networks compared to other competing methods as well as to the situation without any prior. Our framework allows for using diverse information sources, like pathway databases, GO terms and protein domain data, etc. and is flexible enough to integrate new sources, if available.

R-Based Software for the Integration of Pathway Data into Bioinformatic Algorithms

PubMed Central

Kramer, Frank; Bayerlová, Michaela; Beißbarth, Tim

2014-01-01

Putting new findings into the context of available literature knowledge is one approach to deal with the surge of high-throughput data results. Furthermore, prior knowledge can increase the performance and stability of bioinformatic algorithms, for example, methods for network reconstruction. In this review, we examine software packages for the statistical computing framework R, which enable the integration of pathway data for further bioinformatic analyses. Different approaches to integrate and visualize pathway data are identified and packages are stratified concerning their features according to a number of different aspects: data import strategies, the extent of available data, dependencies on external tools, integration with further analysis steps and visualization options are considered. A total of 12 packages integrating pathway data are reviewed in this manuscript. These are supplemented by five R-specific packages for visualization and six connector packages, which provide access to external tools. PMID:24833336

HOW SHOULD RESEARCH AND MONITORING BE INTEGRATED

EPA Science Inventory

Scientific knowledge of Chesapeake Bay and tidal tributaries has accumulated over many years beginning mostly with descriptive surveys prior to the 1960's and 1970's and evolving towards a coupling of monitoring and research in recent years. This essay discusses the need to more ...

"Trees Live on Soil and Sunshine!"--Coexistence of Scientific and Alternative Conception of Tree Assimilation.

PubMed

Thorn, Christine Johanna; Bissinger, Kerstin; Thorn, Simon; Bogner, Franz Xaver

2016-01-01

Successful learning is the integration of new knowledge into existing schemes, leading to an integrated and correct scientific conception. By contrast, the co-existence of scientific and alternative conceptions may indicate a fragmented knowledge profile. Every learner is unique and thus carries an individual set of preconceptions before classroom engagement due to prior experiences. Hence, instructors and teachers have to consider the heterogeneous knowledge profiles of their class when teaching. However, determinants of fragmented knowledge profiles are not well understood yet, which may hamper a development of adapted teaching schemes. We used a questionnaire-based approach to assess conceptual knowledge of tree assimilation and wood synthesis surveying 885 students of four educational levels: 6th graders, 10th graders, natural science freshmen and other academic studies freshmen. We analysed the influence of learner's characteristics such as educational level, age and sex on the coexistence of scientific and alternative conceptions. Within all subsamples well-known alternative conceptions regarding tree assimilation and wood synthesis coexisted with correct scientific ones. For example, students describe trees to be living on "soil and sunshine", representing scientific knowledge of photosynthesis mingled with an alternative conception of trees eating like animals. Fragmented knowledge profiles occurred in all subsamples, but our models showed that improved education and age foster knowledge integration. Sex had almost no influence on the existing scientific conceptions and evolution of knowledge integration. Consequently, complex biological issues such as tree assimilation and wood synthesis need specific support e.g. through repeated learning units in class- and seminar-rooms in order to help especially young students to handle and overcome common alternative conceptions and appropriately integrate scientific conceptions into their knowledge profile.

“Trees Live on Soil and Sunshine!”- Coexistence of Scientific and Alternative Conception of Tree Assimilation

PubMed Central

Thorn, Simon; Bogner, Franz Xaver

2016-01-01

Successful learning is the integration of new knowledge into existing schemes, leading to an integrated and correct scientific conception. By contrast, the co-existence of scientific and alternative conceptions may indicate a fragmented knowledge profile. Every learner is unique and thus carries an individual set of preconceptions before classroom engagement due to prior experiences. Hence, instructors and teachers have to consider the heterogeneous knowledge profiles of their class when teaching. However, determinants of fragmented knowledge profiles are not well understood yet, which may hamper a development of adapted teaching schemes. We used a questionnaire-based approach to assess conceptual knowledge of tree assimilation and wood synthesis surveying 885 students of four educational levels: 6th graders, 10th graders, natural science freshmen and other academic studies freshmen. We analysed the influence of learner’s characteristics such as educational level, age and sex on the coexistence of scientific and alternative conceptions. Within all subsamples well-known alternative conceptions regarding tree assimilation and wood synthesis coexisted with correct scientific ones. For example, students describe trees to be living on “soil and sunshine”, representing scientific knowledge of photosynthesis mingled with an alternative conception of trees eating like animals. Fragmented knowledge profiles occurred in all subsamples, but our models showed that improved education and age foster knowledge integration. Sex had almost no influence on the existing scientific conceptions and evolution of knowledge integration. Consequently, complex biological issues such as tree assimilation and wood synthesis need specific support e.g. through repeated learning units in class- and seminar-rooms in order to help especially young students to handle and overcome common alternative conceptions and appropriately integrate scientific conceptions into their knowledge profile. PMID:26807974

A technology training protocol for meeting QSEN goals: Focusing on meaningful learning.

PubMed

Luo, Shuhong; Kalman, Melanie

2018-01-01

The purpose of this paper is to describe and discuss how we designed and developed a 12-step technology training protocol. The protocol is meant to improve meaningful learning in technology education so that nursing students are able to meet the informatics requirements of Quality and Safety Education in Nursing competencies. When designing and developing the training protocol, we used a simplified experiential learning model that addressed the core features of meaningful learning: to connect new knowledge with students' prior knowledge and real-world workflow. Before training, we identified students' prior knowledge and workflow tasks. During training, students learned by doing, reflected on their prior computer skills and workflow, designed individualized procedures for integration into their workflow, and practiced the self-designed procedures in real-world settings. The trainer was a facilitator who provided a meaningful learning environment, asked the right questions to guide reflective conversation, and offered scaffoldings at critical moments. This training protocol could significantly improve nurses' competencies in using technologies and increase their desire to adopt new technologies. © 2017 Wiley Periodicals, Inc.

Stress affects the neural ensemble for integrating new information and prior knowledge.

PubMed

Vogel, Susanne; Kluen, Lisa Marieke; Fernández, Guillén; Schwabe, Lars

2018-06-01

Prior knowledge, represented as a schema, facilitates memory encoding. This schema-related learning is assumed to rely on the medial prefrontal cortex (mPFC) that rapidly integrates new information into the schema, whereas schema-incongruent or novel information is encoded by the hippocampus. Stress is a powerful modulator of prefrontal and hippocampal functioning and first studies suggest a stress-induced deficit of schema-related learning. However, the underlying neural mechanism is currently unknown. To investigate the neural basis of a stress-induced schema-related learning impairment, participants first acquired a schema. One day later, they underwent a stress induction or a control procedure before learning schema-related and novel information in the MRI scanner. In line with previous studies, learning schema-related compared to novel information activated the mPFC, angular gyrus, and precuneus. Stress, however, affected the neural ensemble activated during learning. Whereas the control group distinguished between sets of brain regions for related and novel information, stressed individuals engaged the hippocampus even when a relevant schema was present. Additionally, stressed participants displayed aberrant functional connectivity between brain regions involved in schema processing when encoding novel information. The failure to segregate functional connectivity patterns depending on the presence of prior knowledge was linked to impaired performance after stress. Our results show that stress affects the neural ensemble underlying the efficient use of schemas during learning. These findings may have relevant implications for clinical and educational settings. Copyright © 2018 Elsevier Inc. All rights reserved.

Knowledge-based image processing for on-off type DNA microarray

NASA Astrophysics Data System (ADS)

Kim, Jong D.; Kim, Seo K.; Cho, Jeong S.; Kim, Jongwon

2002-06-01

This paper addresses the image processing technique for discriminating whether the probes are hybrized with target DNA in the Human Papilloma Virus (HPV) DNA Chip designed for genotyping HPV. In addition to the probes, the HPV DNA chip has markers that always react with the sample DNA. The positions of probe-dots in the final scanned image are fixed relative to the marker-dot locations with a small variation according to the accuracy of the dotter and the scanner. The probes are duplicated 4 times for the diagnostic stability. The prior knowledges such as the maker relative distance and the duplication information of probes is integrated into the template matching technique with the normalized correlation measure. Results show that the employment of both of the prior knowledges is to simply average the template matching measures over the positions of the markers and probes. The eventual proposed scheme yields stable marker locating and probe classification.

Planning intensive care unit design using computer simulation modeling: optimizing integration of clinical, operational, and architectural requirements.

PubMed

OʼHara, Susan

2014-01-01

Nurses have increasingly been regarded as critical members of the planning team as architects recognize their knowledge and value. But the nurses' role as knowledge experts can be expanded to leading efforts to integrate the clinical, operational, and architectural expertise through simulation modeling. Simulation modeling allows for the optimal merge of multifactorial data to understand the current state of the intensive care unit and predict future states. Nurses can champion the simulation modeling process and reap the benefits of a cost-effective way to test new designs, processes, staffing models, and future programming trends prior to implementation. Simulation modeling is an evidence-based planning approach, a standard, for integrating the sciences with real client data, to offer solutions for improving patient care.

Sleep Spindle Density Predicts the Effect of Prior Knowledge on Memory Consolidation

PubMed Central

Lambon Ralph, Matthew A.; Kempkes, Marleen; Cousins, James N.; Lewis, Penelope A.

2016-01-01

Information that relates to a prior knowledge schema is remembered better and consolidates more rapidly than information that does not. Another factor that influences memory consolidation is sleep and growing evidence suggests that sleep-related processing is important for integration with existing knowledge. Here, we perform an examination of how sleep-related mechanisms interact with schema-dependent memory advantage. Participants first established a schema over 2 weeks. Next, they encoded new facts, which were either related to the schema or completely unrelated. After a 24 h retention interval, including a night of sleep, which we monitored with polysomnography, participants encoded a second set of facts. Finally, memory for all facts was tested in a functional magnetic resonance imaging scanner. Behaviorally, sleep spindle density predicted an increase of the schema benefit to memory across the retention interval. Higher spindle densities were associated with reduced decay of schema-related memories. Functionally, spindle density predicted increased disengagement of the hippocampus across 24 h for schema-related memories only. Together, these results suggest that sleep spindle activity is associated with the effect of prior knowledge on memory consolidation. SIGNIFICANCE STATEMENT Episodic memories are gradually assimilated into long-term memory and this process is strongly influenced by sleep. The consolidation of new information is also influenced by its relationship to existing knowledge structures, or schemas, but the role of sleep in such schema-related consolidation is unknown. We show that sleep spindle density predicts the extent to which schemas influence the consolidation of related facts. This is the first evidence that sleep is associated with the interaction between prior knowledge and long-term memory formation. PMID:27030764

Word Learning as Bayesian Inference

ERIC Educational Resources Information Center

Xu, Fei; Tenenbaum, Joshua B.

2007-01-01

The authors present a Bayesian framework for understanding how adults and children learn the meanings of words. The theory explains how learners can generalize meaningfully from just one or a few positive examples of a novel word's referents, by making rational inductive inferences that integrate prior knowledge about plausible word meanings with…

Sensor fusion II: Human and machine strategies; Proceedings of the Meeting, Philadelphia, PA, Nov. 6-9, 1989

NASA Technical Reports Server (NTRS)

Schenker, Paul S. (Editor)

1990-01-01

Various papers on human and machine strategies in sensor fusion are presented. The general topics addressed include: active vision, measurement and analysis of visual motion, decision models for sensor fusion, implementation of sensor fusion algorithms, applying sensor fusion to image analysis, perceptual modules and their fusion, perceptual organization and object recognition, planning and the integration of high-level knowledge with perception, using prior knowledge and context in sensor fusion.

Prior Knowledge Facilitates Mutual Gaze Convergence and Head Nodding Synchrony in Face-to-face Communication

PubMed Central

Thepsoonthorn, C.; Yokozuka, T.; Miura, S.; Ogawa, K.; Miyake, Y.

2016-01-01

As prior knowledge is claimed to be an essential key to achieve effective education, we are interested in exploring whether prior knowledge enhances communication effectiveness. To demonstrate the effects of prior knowledge, mutual gaze convergence and head nodding synchrony are observed as indicators of communication effectiveness. We conducted an experiment on lecture task between lecturer and student under 2 conditions: prior knowledge and non-prior knowledge. The students in prior knowledge condition were provided the basic information about the lecture content and were assessed their understanding by the experimenter before starting the lecture while the students in non-prior knowledge had none. The result shows that the interaction in prior knowledge condition establishes significantly higher mutual gaze convergence (t(15.03) = 6.72, p < 0.0001; α = 0.05, n = 20) and head nodding synchrony (t(16.67) = 1.83, p = 0.04; α = 0.05, n = 19) compared to non-prior knowledge condition. This study reveals that prior knowledge facilitates mutual gaze convergence and head nodding synchrony. Furthermore, the interaction with and without prior knowledge can be evaluated by measuring or observing mutual gaze convergence and head nodding synchrony. PMID:27910902

Prior Knowledge Facilitates Mutual Gaze Convergence and Head Nodding Synchrony in Face-to-face Communication.

PubMed

Thepsoonthorn, C; Yokozuka, T; Miura, S; Ogawa, K; Miyake, Y

2016-12-02

As prior knowledge is claimed to be an essential key to achieve effective education, we are interested in exploring whether prior knowledge enhances communication effectiveness. To demonstrate the effects of prior knowledge, mutual gaze convergence and head nodding synchrony are observed as indicators of communication effectiveness. We conducted an experiment on lecture task between lecturer and student under 2 conditions: prior knowledge and non-prior knowledge. The students in prior knowledge condition were provided the basic information about the lecture content and were assessed their understanding by the experimenter before starting the lecture while the students in non-prior knowledge had none. The result shows that the interaction in prior knowledge condition establishes significantly higher mutual gaze convergence (t(15.03) = 6.72, p < 0.0001; α = 0.05, n = 20) and head nodding synchrony (t(16.67) = 1.83, p = 0.04; α = 0.05, n = 19) compared to non-prior knowledge condition. This study reveals that prior knowledge facilitates mutual gaze convergence and head nodding synchrony. Furthermore, the interaction with and without prior knowledge can be evaluated by measuring or observing mutual gaze convergence and head nodding synchrony.

An Integrative Framework for Bayesian Variable Selection with Informative Priors for Identifying Genes and Pathways

PubMed Central

Ander, Bradley P.; Zhang, Xiaoshuai; Xue, Fuzhong; Sharp, Frank R.; Yang, Xiaowei

2013-01-01

The discovery of genetic or genomic markers plays a central role in the development of personalized medicine. A notable challenge exists when dealing with the high dimensionality of the data sets, as thousands of genes or millions of genetic variants are collected on a relatively small number of subjects. Traditional gene-wise selection methods using univariate analyses face difficulty to incorporate correlational, structural, or functional structures amongst the molecular measures. For microarray gene expression data, we first summarize solutions in dealing with ‘large p, small n’ problems, and then propose an integrative Bayesian variable selection (iBVS) framework for simultaneously identifying causal or marker genes and regulatory pathways. A novel partial least squares (PLS) g-prior for iBVS is developed to allow the incorporation of prior knowledge on gene-gene interactions or functional relationships. From the point view of systems biology, iBVS enables user to directly target the joint effects of multiple genes and pathways in a hierarchical modeling diagram to predict disease status or phenotype. The estimated posterior selection probabilities offer probabilitic and biological interpretations. Both simulated data and a set of microarray data in predicting stroke status are used in validating the performance of iBVS in a Probit model with binary outcomes. iBVS offers a general framework for effective discovery of various molecular biomarkers by combining data-based statistics and knowledge-based priors. Guidelines on making posterior inferences, determining Bayesian significance levels, and improving computational efficiencies are also discussed. PMID:23844055

An integrative framework for Bayesian variable selection with informative priors for identifying genes and pathways.

PubMed

Peng, Bin; Zhu, Dianwen; Ander, Bradley P; Zhang, Xiaoshuai; Xue, Fuzhong; Sharp, Frank R; Yang, Xiaowei

2013-01-01

The discovery of genetic or genomic markers plays a central role in the development of personalized medicine. A notable challenge exists when dealing with the high dimensionality of the data sets, as thousands of genes or millions of genetic variants are collected on a relatively small number of subjects. Traditional gene-wise selection methods using univariate analyses face difficulty to incorporate correlational, structural, or functional structures amongst the molecular measures. For microarray gene expression data, we first summarize solutions in dealing with 'large p, small n' problems, and then propose an integrative Bayesian variable selection (iBVS) framework for simultaneously identifying causal or marker genes and regulatory pathways. A novel partial least squares (PLS) g-prior for iBVS is developed to allow the incorporation of prior knowledge on gene-gene interactions or functional relationships. From the point view of systems biology, iBVS enables user to directly target the joint effects of multiple genes and pathways in a hierarchical modeling diagram to predict disease status or phenotype. The estimated posterior selection probabilities offer probabilitic and biological interpretations. Both simulated data and a set of microarray data in predicting stroke status are used in validating the performance of iBVS in a Probit model with binary outcomes. iBVS offers a general framework for effective discovery of various molecular biomarkers by combining data-based statistics and knowledge-based priors. Guidelines on making posterior inferences, determining Bayesian significance levels, and improving computational efficiencies are also discussed.

Boosting Probabilistic Graphical Model Inference by Incorporating Prior Knowledge from Multiple Sources

PubMed Central

Praveen, Paurush; Fröhlich, Holger

2013-01-01

Inferring regulatory networks from experimental data via probabilistic graphical models is a popular framework to gain insights into biological systems. However, the inherent noise in experimental data coupled with a limited sample size reduces the performance of network reverse engineering. Prior knowledge from existing sources of biological information can address this low signal to noise problem by biasing the network inference towards biologically plausible network structures. Although integrating various sources of information is desirable, their heterogeneous nature makes this task challenging. We propose two computational methods to incorporate various information sources into a probabilistic consensus structure prior to be used in graphical model inference. Our first model, called Latent Factor Model (LFM), assumes a high degree of correlation among external information sources and reconstructs a hidden variable as a common source in a Bayesian manner. The second model, a Noisy-OR, picks up the strongest support for an interaction among information sources in a probabilistic fashion. Our extensive computational studies on KEGG signaling pathways as well as on gene expression data from breast cancer and yeast heat shock response reveal that both approaches can significantly enhance the reconstruction accuracy of Bayesian Networks compared to other competing methods as well as to the situation without any prior. Our framework allows for using diverse information sources, like pathway databases, GO terms and protein domain data, etc. and is flexible enough to integrate new sources, if available. PMID:23826291

The effects of activating prior topic and metacognitive knowledge on text comprehension scores.

PubMed

Kostons, Danny; van der Werf, Greetje

2015-09-01

Research on prior knowledge activation has consistently shown that activating learners' prior knowledge has beneficial effects on learning. If learners activate their prior knowledge, this activated knowledge serves as a framework for establishing relationships between the knowledge they already possess and new information provided to them. Thus far, prior knowledge activation has dealt primarily with topic knowledge in specific domains. Students, however, likely also possess at least some metacognitive knowledge useful in those domains, which, when activated, should aid in the deployment of helpful strategies during reading. In this study, we investigated the effects of both prior topic knowledge activation (PTKA) and prior metacognitive knowledge activation (PMKA) on text comprehension scores. Eighty-eight students in primary education were randomly distributed amongst the conditions of the 2 × 2 (PTKA yes/no × PMKA yes/no) designed experiment. Results show that activating prior metacognitive knowledge had a beneficial effect on text comprehension, whereas activating prior topic knowledge, after correcting for the amount of prior knowledge, did not. Most studies deal with explicit instruction of metacognitive knowledge, but our results show that this may not be necessary, specifically in the case of students who already have some metacognitive knowledge. However, existing metacognitive knowledge needs to be activated in order for students to make better use of this knowledge. © 2015 The British Psychological Society.

Finding gene regulatory network candidates using the gene expression knowledge base.

PubMed

Venkatesan, Aravind; Tripathi, Sushil; Sanz de Galdeano, Alejandro; Blondé, Ward; Lægreid, Astrid; Mironov, Vladimir; Kuiper, Martin

2014-12-10

Network-based approaches for the analysis of large-scale genomics data have become well established. Biological networks provide a knowledge scaffold against which the patterns and dynamics of 'omics' data can be interpreted. The background information required for the construction of such networks is often dispersed across a multitude of knowledge bases in a variety of formats. The seamless integration of this information is one of the main challenges in bioinformatics. The Semantic Web offers powerful technologies for the assembly of integrated knowledge bases that are computationally comprehensible, thereby providing a potentially powerful resource for constructing biological networks and network-based analysis. We have developed the Gene eXpression Knowledge Base (GeXKB), a semantic web technology based resource that contains integrated knowledge about gene expression regulation. To affirm the utility of GeXKB we demonstrate how this resource can be exploited for the identification of candidate regulatory network proteins. We present four use cases that were designed from a biological perspective in order to find candidate members relevant for the gastrin hormone signaling network model. We show how a combination of specific query definitions and additional selection criteria derived from gene expression data and prior knowledge concerning candidate proteins can be used to retrieve a set of proteins that constitute valid candidates for regulatory network extensions. Semantic web technologies provide the means for processing and integrating various heterogeneous information sources. The GeXKB offers biologists such an integrated knowledge resource, allowing them to address complex biological questions pertaining to gene expression. This work illustrates how GeXKB can be used in combination with gene expression results and literature information to identify new potential candidates that may be considered for extending a gene regulatory network.

SVS: data and knowledge integration in computational biology.

PubMed

Zycinski, Grzegorz; Barla, Annalisa; Verri, Alessandro

2011-01-01

In this paper we present a framework for structured variable selection (SVS). The main concept of the proposed schema is to take a step towards the integration of two different aspects of data mining: database and machine learning perspective. The framework is flexible enough to use not only microarray data, but other high-throughput data of choice (e.g. from mass spectrometry, microarray, next generation sequencing). Moreover, the feature selection phase incorporates prior biological knowledge in a modular way from various repositories and is ready to host different statistical learning techniques. We present a proof of concept of SVS, illustrating some implementation details and describing current results on high-throughput microarray data.

Delineating the Effect of Semantic Congruency on Episodic Memory: The Role of Integration and Relatedness

PubMed Central

Bein, Oded; Livneh, Neta; Reggev, Niv; Gilead, Michael; Goshen-Gottstein, Yonatan; Maril, Anat

2015-01-01

A fundamental challenge in the study of learning and memory is to understand the role of existing knowledge in the encoding and retrieval of new episodic information. The importance of prior knowledge in memory is demonstrated in the congruency effect—the robust finding wherein participants display better memory for items that are compatible, rather than incompatible, with their pre-existing semantic knowledge. Despite its robustness, the mechanism underlying this effect is not well understood. In four studies, we provide evidence that demonstrates the privileged explanatory power of the elaboration-integration account over alternative hypotheses. Furthermore, we question the implicit assumption that the congruency effect pertains to the truthfulness/sensibility of a subject-predicate proposition, and show that congruency is a function of semantic relatedness between item and context words. PMID:25695759

Delineating the effect of semantic congruency on episodic memory: the role of integration and relatedness.

PubMed

Bein, Oded; Livneh, Neta; Reggev, Niv; Gilead, Michael; Goshen-Gottstein, Yonatan; Maril, Anat

2015-01-01

A fundamental challenge in the study of learning and memory is to understand the role of existing knowledge in the encoding and retrieval of new episodic information. The importance of prior knowledge in memory is demonstrated in the congruency effect-the robust finding wherein participants display better memory for items that are compatible, rather than incompatible, with their pre-existing semantic knowledge. Despite its robustness, the mechanism underlying this effect is not well understood. In four studies, we provide evidence that demonstrates the privileged explanatory power of the elaboration-integration account over alternative hypotheses. Furthermore, we question the implicit assumption that the congruency effect pertains to the truthfulness/sensibility of a subject-predicate proposition, and show that congruency is a function of semantic relatedness between item and context words.

Integrating biological knowledge into variable selection: an empirical Bayes approach with an application in cancer biology

PubMed Central

2012-01-01

Background An important question in the analysis of biochemical data is that of identifying subsets of molecular variables that may jointly influence a biological response. Statistical variable selection methods have been widely used for this purpose. In many settings, it may be important to incorporate ancillary biological information concerning the variables of interest. Pathway and network maps are one example of a source of such information. However, although ancillary information is increasingly available, it is not always clear how it should be used nor how it should be weighted in relation to primary data. Results We put forward an approach in which biological knowledge is incorporated using informative prior distributions over variable subsets, with prior information selected and weighted in an automated, objective manner using an empirical Bayes formulation. We employ continuous, linear models with interaction terms and exploit biochemically-motivated sparsity constraints to permit exact inference. We show an example of priors for pathway- and network-based information and illustrate our proposed method on both synthetic response data and by an application to cancer drug response data. Comparisons are also made to alternative Bayesian and frequentist penalised-likelihood methods for incorporating network-based information. Conclusions The empirical Bayes method proposed here can aid prior elicitation for Bayesian variable selection studies and help to guard against mis-specification of priors. Empirical Bayes, together with the proposed pathway-based priors, results in an approach with a competitive variable selection performance. In addition, the overall procedure is fast, deterministic, and has very few user-set parameters, yet is capable of capturing interplay between molecular players. The approach presented is general and readily applicable in any setting with multiple sources of biological prior knowledge. PMID:22578440

BioGraph: unsupervised biomedical knowledge discovery via automated hypothesis generation

PubMed Central

2011-01-01

We present BioGraph, a data integration and data mining platform for the exploration and discovery of biomedical information. The platform offers prioritizations of putative disease genes, supported by functional hypotheses. We show that BioGraph can retrospectively confirm recently discovered disease genes and identify potential susceptibility genes, outperforming existing technologies, without requiring prior domain knowledge. Additionally, BioGraph allows for generic biomedical applications beyond gene discovery. BioGraph is accessible at http://www.biograph.be. PMID:21696594

Processing and Memory of Information Presented in Narrative or Expository Texts

ERIC Educational Resources Information Center

Wolfe, Michael B. W.; Woodwyk, Joshua M.

2010-01-01

Background: Previous research suggests that narrative and expository texts differ in the extent to which they prompt students to integrate to-be-learned content with relevant prior knowledge during comprehension. Aims: We expand on previous research by examining on-line processing and representation in memory of to-be-learned content that is…

Impact of a 4-H Youth Development Program on At-Risk Urban Teenagers

ERIC Educational Resources Information Center

Cutz, German; Campbell, Benjamin; Filchak, Karen K.; Valiquette, Edith; Welch, Mary Ellen

2015-01-01

Dynamic programs that integrate science literacy and workforce readiness are essential to today's youth. The program reported here combined science literacy (gardening and technology) with workforce readiness to assess the impact of program type, prior program participation, and behavior/punctuality on knowledge gain. Findings show that past…

Visual Representations in Science Education: The Influence of Prior Knowledge and Cognitive Load Theory on Instructional Design Principles

ERIC Educational Resources Information Center

Cook, Michelle Patrick

2006-01-01

Visual representations are essential for communicating ideas in the science classroom; however, the design of such representations is not always beneficial for learners. This paper presents instructional design considerations providing empirical evidence and integrating theoretical concepts related to cognitive load. Learners have a limited…

Pre-Service Teachers' Beliefs about Knowledge, Mathematics, and Science

ERIC Educational Resources Information Center

Cady, Jo Ann; Rearden, Kristin

2007-01-01

This study examines the beliefs of K-8 preservice teachers during a content methods course. The goals of this course included exposing the preservice teachers to student-centered instructional methods for math and science and encouraging the development of lessons that would integrate mathematics and science. Prior research suggested that one must…

The Influence of Prior Knowledge on the Retrieval-Directed Function of Note Taking in Prior Knowledge Activation

ERIC Educational Resources Information Center

Wetzels, Sandra A. J.; Kester, Liesbeth; van Merrienboer, Jeroen J. G.; Broers, Nick J.

2011-01-01

Background: Prior knowledge activation facilitates learning. Note taking during prior knowledge activation (i.e., note taking directed at retrieving information from memory) might facilitate the activation process by enabling learners to build an external representation of their prior knowledge. However, taking notes might be less effective in…

Features of Knowledge Building in Biology: Understanding Undergraduate Students' Ideas about Molecular Mechanisms.

PubMed

Southard, Katelyn; Wince, Tyler; Meddleton, Shanice; Bolger, Molly S

2016-01-01

Research has suggested that teaching and learning in molecular and cellular biology (MCB) is difficult. We used a new lens to understand undergraduate reasoning about molecular mechanisms: the knowledge-integration approach to conceptual change. Knowledge integration is the dynamic process by which learners acquire new ideas, develop connections between ideas, and reorganize and restructure prior knowledge. Semistructured, clinical think-aloud interviews were conducted with introductory and upper-division MCB students. Interviews included a written conceptual assessment, a concept-mapping activity, and an opportunity to explain the biomechanisms of DNA replication, transcription, and translation. Student reasoning patterns were explored through mixed-method analyses. Results suggested that students must sort mechanistic entities into appropriate mental categories that reflect the nature of MCB mechanisms and that conflation between these categories is common. We also showed how connections between molecular mechanisms and their biological roles are part of building an integrated knowledge network as students develop expertise. We observed differences in the nature of connections between ideas related to different forms of reasoning. Finally, we provide a tentative model for MCB knowledge integration and suggest its implications for undergraduate learning. © 2016 K. Southard et al. CBE—Life Sciences Education © 2016 The American Society for Cell Biology. This article is distributed by The American Society for Cell Biology under license from the author(s). It is available to the public under an Attribution–Noncommercial–Share Alike 3.0 Unported Creative Commons License (http://creativecommons.org/licenses/by-nc-sa/3.0).

Strategic Integration of Multiple Bioinformatics Resources for System Level Analysis of Biological Networks.

PubMed

D'Souza, Mark; Sulakhe, Dinanath; Wang, Sheng; Xie, Bing; Hashemifar, Somaye; Taylor, Andrew; Dubchak, Inna; Conrad Gilliam, T; Maltsev, Natalia

2017-01-01

Recent technological advances in genomics allow the production of biological data at unprecedented tera- and petabyte scales. Efficient mining of these vast and complex datasets for the needs of biomedical research critically depends on a seamless integration of the clinical, genomic, and experimental information with prior knowledge about genotype-phenotype relationships. Such experimental data accumulated in publicly available databases should be accessible to a variety of algorithms and analytical pipelines that drive computational analysis and data mining.We present an integrated computational platform Lynx (Sulakhe et al., Nucleic Acids Res 44:D882-D887, 2016) ( http://lynx.cri.uchicago.edu ), a web-based database and knowledge extraction engine. It provides advanced search capabilities and a variety of algorithms for enrichment analysis and network-based gene prioritization. It gives public access to the Lynx integrated knowledge base (LynxKB) and its analytical tools via user-friendly web services and interfaces. The Lynx service-oriented architecture supports annotation and analysis of high-throughput experimental data. Lynx tools assist the user in extracting meaningful knowledge from LynxKB and experimental data, and in the generation of weighted hypotheses regarding the genes and molecular mechanisms contributing to human phenotypes or conditions of interest. The goal of this integrated platform is to support the end-to-end analytical needs of various translational projects.

Computing an optimal time window of audiovisual integration in focused attention tasks: illustrated by studies on effect of age and prior knowledge.

PubMed

Colonius, Hans; Diederich, Adele

2011-07-01

The concept of a "time window of integration" holds that information from different sensory modalities must not be perceived too far apart in time in order to be integrated into a multisensory perceptual event. Empirical estimates of window width differ widely, however, ranging from 40 to 600 ms depending on context and experimental paradigm. Searching for theoretical derivation of window width, Colonius and Diederich (Front Integr Neurosci 2010) developed a decision-theoretic framework using a decision rule that is based on the prior probability of a common source, the likelihood of temporal disparities between the unimodal signals, and the payoff for making right or wrong decisions. Here, this framework is extended to the focused attention task where subjects are asked to respond to signals from a target modality only. Evoking the framework of the time-window-of-integration (TWIN) model, an explicit expression for optimal window width is obtained. The approach is probed on two published focused attention studies. The first is a saccadic reaction time study assessing the efficiency with which multisensory integration varies as a function of aging. Although the window widths for young and older adults differ by nearly 200 ms, presumably due to their different peripheral processing speeds, neither of them deviates significantly from the optimal values. In the second study, head saccadic reactions times to a perfectly aligned audiovisual stimulus pair had been shown to depend on the prior probability of spatial alignment. Intriguingly, they reflected the magnitude of the time-window widths predicted by our decision-theoretic framework, i.e., a larger time window is associated with a higher prior probability.

Conditional reasoning in autism: activation and integration of knowledge and belief.

PubMed

McKenzie, Rebecca; Evans, Jonathan St B T; Handley, Simon J

2010-03-01

Everyday conditional reasoning is typically influenced by prior knowledge and belief in the form of specific exceptions known as counterexamples. This study explored whether adolescents with autism spectrum disorder (ASD; N = 26) were less influenced by background knowledge than typically developing adolescents (N = 38) when engaged in conditional reasoning. Participants were presented with pretested valid and invalid conditional inferences with varying available counterexamples. The group with ASD showed significantly less influence of prior knowledge on valid inferences (p = .01) and invalid inferences (p = .01) compared with the typical group. In a secondary probability judgment task, no significant group differences were found in probabilistic judgments of the believability of the premises. Further experiments found that results could not be explained by differences between the groups in the ability to generate counterexamples or any tendency among adolescents with ASD to exhibit a "yes" response pattern. It was concluded that adolescents with ASD tend not to spontaneously contextualize presented material when engaged in everyday reasoning. These findings are discussed with reference to weak central coherence theory and the conditional reasoning literature.

Unintended Consequences or Testing the Integrity of Teachers and Students.

ERIC Educational Resources Information Center

Kimmel, Ernest W.

Large-scale testing programs are generally based on the assumptions that the test-takers experience standard conditions for taking the test and that everyone will do his or her own work without having prior knowledge of specific questions. These assumptions are not necessarily true. The ways students and educators use to get around standardizing…

Stream Restoration as a Seminar Theme: Opportunities for Synthesis and Integration

ERIC Educational Resources Information Center

Moran, Sharon

2003-01-01

By using stream restoration as a seminar theme, geography faculty can create a topical course that helps provide a shared intellectual agenda for both physical and human geography students, while highlighting the holistic strengths of our discipline. Although it is not necessary that faculty have prior knowledge about the topic, a willingness to…

The critical success factors and impact of prior knowledge to nursing students when transferring nursing knowledge during nursing clinical practise.

PubMed

Tsai, Ming-Tien; Tsai, Ling-Long

2005-11-01

Nursing practise plays an important role in transferring nursing knowledge to nursing students. From the related literature review, prior knowledge will affect how learners gain new knowledge. There has been no direct examination of the prior knowledge interaction effect on students' performance and its influence on nursing students when evaluating the knowledge transfer success factors. This study explores (1) the critical success factors in transferring nursing knowledge, (2) the impact of prior knowledge when evaluating the success factors for transferring nursing knowledge. This research utilizes in-depth interviews to probe the initial success factor phase. A total of 422 valid questionnaires were conducted by the authors. The data were analysed by comparing the mean score and t-test between two groups. Seventeen critical success factors were identified by the two groups of students. Twelve items were selected to examine the diversity in the two groups. Students with prior knowledge were more independent than the other group. They also preferred self-directed learning over students without prior knowledge. Students who did not have prior knowledge were eager to take every opportunity to gain experience and more readily adopted new knowledge.

Balancing the Role of Priors in Multi-Observer Segmentation Evaluation

PubMed Central

Huang, Xiaolei; Wang, Wei; Lopresti, Daniel; Long, Rodney; Antani, Sameer; Xue, Zhiyun; Thoma, George

2009-01-01

Comparison of a group of multiple observer segmentations is known to be a challenging problem. A good segmentation evaluation method would allow different segmentations not only to be compared, but to be combined to generate a “true” segmentation with higher consensus. Numerous multi-observer segmentation evaluation approaches have been proposed in the literature, and STAPLE in particular probabilistically estimates the true segmentation by optimal combination of observed segmentations and a prior model of the truth. An Expectation–Maximization (EM) algorithm, STAPLE’S convergence to the desired local minima depends on good initializations for the truth prior and the observer-performance prior. However, accurate modeling of the initial truth prior is nontrivial. Moreover, among the two priors, the truth prior always dominates so that in certain scenarios when meaningful observer-performance priors are available, STAPLE can not take advantage of that information. In this paper, we propose a Bayesian decision formulation of the problem that permits the two types of prior knowledge to be integrated in a complementary manner in four cases with differing application purposes: (1) with known truth prior; (2) with observer prior; (3) with neither truth prior nor observer prior; and (4) with both truth prior and observer prior. The third and fourth cases are not discussed (or effectively ignored) by STAPLE, and in our research we propose a new method to combine multiple-observer segmentations based on the maximum a posterior (MAP) principle, which respects the observer prior regardless of the availability of the truth prior. Based on the four scenarios, we have developed a web-based software application that implements the flexible segmentation evaluation framework for digitized uterine cervix images. Experiment results show that our framework has flexibility in effectively integrating different priors for multi-observer segmentation evaluation and it also generates results comparing favorably to those by the STAPLE algorithm and the Majority Vote Rule. PMID:20523759

Impaired integration of object knowledge and visual input in a case of ventral simultanagnosia with bilateral damage to area V4.

PubMed

Leek, E Charles; d'Avossa, Giovanni; Tainturier, Marie-Josèphe; Roberts, Daniel J; Yuen, Sung Lai; Hu, Mo; Rafal, Robert

2012-01-01

This study examines how brain damage can affect the cognitive processes that support the integration of sensory input and prior knowledge during shape perception. It is based on the first detailed study of acquired ventral simultanagnosia, which was found in a patient (M.T.) with posterior occipitotemporal lesions encompassing V4 bilaterally. Despite showing normal object recognition for single items in both accuracy and response times (RTs), and intact low-level vision assessed across an extensive battery of tests, M.T. was impaired in object identification with overlapping figures displays. Task performance was modulated by familiarity: Unlike controls, M.T. was faster with overlapping displays of abstract shapes than with overlapping displays of common objects. His performance with overlapping common object displays was also influenced by both the semantic relatedness and visual similarity of the display items. These findings challenge claims that visual perception is driven solely by feedforward mechanisms and show how brain damage can selectively impair high-level perceptual processes supporting the integration of stored knowledge and visual sensory input.

Using texts in science education: cognitive processes and knowledge representation.

PubMed

van den Broek, Paul

2010-04-23

Texts form a powerful tool in teaching concepts and principles in science. How do readers extract information from a text, and what are the limitations in this process? Central to comprehension of and learning from a text is the construction of a coherent mental representation that integrates the textual information and relevant background knowledge. This representation engenders learning if it expands the reader's existing knowledge base or if it corrects misconceptions in this knowledge base. The Landscape Model captures the reading process and the influences of reader characteristics (such as working-memory capacity, reading goal, prior knowledge, and inferential skills) and text characteristics (such as content/structure of presented information, processing demands, and textual cues). The model suggests factors that can optimize--or jeopardize--learning science from text.

How much to trust the senses: Likelihood learning

PubMed Central

Sato, Yoshiyuki; Kording, Konrad P.

2014-01-01

Our brain often needs to estimate unknown variables from imperfect information. Our knowledge about the statistical distributions of quantities in our environment (called priors) and currently available information from sensory inputs (called likelihood) are the basis of all Bayesian models of perception and action. While we know that priors are learned, most studies of prior-likelihood integration simply assume that subjects know about the likelihood. However, as the quality of sensory inputs change over time, we also need to learn about new likelihoods. Here, we show that human subjects readily learn the distribution of visual cues (likelihood function) in a way that can be predicted by models of statistically optimal learning. Using a likelihood that depended on color context, we found that a learned likelihood generalized to new priors. Thus, we conclude that subjects learn about likelihood. PMID:25398975

The effect of directive tutor guidance on students' conceptual understanding of statistics in problem-based learning.

PubMed

Budé, Luc; van de Wiel, Margaretha W J; Imbos, Tjaart; Berger, Martijn P F

2011-06-01

Education is aimed at students reaching conceptual understanding of the subject matter, because this leads to better performance and application of knowledge. Conceptual understanding depends on coherent and error-free knowledge structures. The construction of such knowledge structures can only be accomplished through active learning and when new knowledge can be integrated into prior knowledge. The intervention in this study was directed at both the activation of students as well as the integration of knowledge. Undergraduate university students from an introductory statistics course, in an authentic problem-based learning (PBL) environment, were randomly assigned to conditions and measurement time points. In the PBL tutorial meetings, half of the tutors guided the discussions of the students in a traditional way. The other half guided the discussions more actively by asking directive and activating questions. To gauge conceptual understanding, the students answered open-ended questions asking them to explain and relate important statistical concepts. Results of the quantitative analysis show that providing directive tutor guidance improved understanding. Qualitative data of students' misconceptions seem to support this finding. Long-term retention of the subject matter seemed to be inadequate. ©2010 The British Psychological Society.

Real-time realizations of the Bayesian Infrasonic Source Localization Method

NASA Astrophysics Data System (ADS)

Pinsky, V.; Arrowsmith, S.; Hofstetter, A.; Nippress, A.

2015-12-01

The Bayesian Infrasonic Source Localization method (BISL), introduced by Mordak et al. (2010) and upgraded by Marcillo et al. (2014) is destined for the accurate estimation of the atmospheric event origin at local, regional and global scales by the seismic and infrasonic networks and arrays. The BISL is based on probabilistic models of the source-station infrasonic signal propagation time, picking time and azimuth estimate merged with a prior knowledge about celerity distribution. It requires at each hypothetical source location, integration of the product of the corresponding source-station likelihood functions multiplied by a prior probability density function of celerity over the multivariate parameter space. The present BISL realization is generally time-consuming procedure based on numerical integration. The computational scheme proposed simplifies the target function so that integrals are taken exactly and are represented via standard functions. This makes the procedure much faster and realizable in real-time without practical loss of accuracy. The procedure executed as PYTHON-FORTRAN code demonstrates high performance on a set of the model and real data.

Effects of Prior Knowledge on Memory: Implications for Education

ERIC Educational Resources Information Center

Shing, Yee Lee; Brod, Garvin

2016-01-01

The encoding, consolidation, and retrieval of events and facts form the basis for acquiring new skills and knowledge. Prior knowledge can enhance those memory processes considerably and thus foster knowledge acquisition. But prior knowledge can also hinder knowledge acquisition, in particular when the to-be-learned information is inconsistent with…

Pre-Service Teachers and Search Engines: Prior Knowledge and Instructional Implications

ERIC Educational Resources Information Center

Colaric, Susan M.; Fine, Bethann; Hofmann, William

2004-01-01

There is a wealth of information available on the World Wide Web that can assist pre-service teachers in their course studies. Yet observation of students in a technology integration class indicated that students were not able to find resources efficiently or reliably. The purpose of this study was to establish a baseline of what undergraduate,…

The Effects of Prior Knowledge Activation on Free Recall and Study Time Allocation.

ERIC Educational Resources Information Center

Machiels-Bongaerts, Maureen; And Others

The effects of mobilizing prior knowledge on information processing were studied. Two hypotheses, the cognitive set-point hypothesis and the selective attention hypothesis, try to account for the facilitation effects of prior knowledge activation. These hypotheses predict different recall patterns as a result of mobilizing prior knowledge. In…

Deepening Understanding of Prior Knowledge: What Diverse First-Generation College Students in the U.S. Can Teach Us

ERIC Educational Resources Information Center

Castillo-Montoya, Milagros

2017-01-01

Educational research indicates that teachers revealing and utilizing students' prior knowledge supports students' academic learning. Yet, the variation in students' prior knowledge is not fully known. To better understand students' prior knowledge, I drew on sociocultural learning theories to examine racially and ethnically diverse college…

A Bayesian Model of the Memory Colour Effect.

PubMed

Witzel, Christoph; Olkkonen, Maria; Gegenfurtner, Karl R

2018-01-01

According to the memory colour effect, the colour of a colour-diagnostic object is not perceived independently of the object itself. Instead, it has been shown through an achromatic adjustment method that colour-diagnostic objects still appear slightly in their typical colour, even when they are colourimetrically grey. Bayesian models provide a promising approach to capture the effect of prior knowledge on colour perception and to link these effects to more general effects of cue integration. Here, we model memory colour effects using prior knowledge about typical colours as priors for the grey adjustments in a Bayesian model. This simple model does not involve any fitting of free parameters. The Bayesian model roughly captured the magnitude of the measured memory colour effect for photographs of objects. To some extent, the model predicted observed differences in memory colour effects across objects. The model could not account for the differences in memory colour effects across different levels of realism in the object images. The Bayesian model provides a particularly simple account of memory colour effects, capturing some of the multiple sources of variation of these effects.

A Bayesian Model of the Memory Colour Effect

PubMed Central

Olkkonen, Maria; Gegenfurtner, Karl R.

2018-01-01

According to the memory colour effect, the colour of a colour-diagnostic object is not perceived independently of the object itself. Instead, it has been shown through an achromatic adjustment method that colour-diagnostic objects still appear slightly in their typical colour, even when they are colourimetrically grey. Bayesian models provide a promising approach to capture the effect of prior knowledge on colour perception and to link these effects to more general effects of cue integration. Here, we model memory colour effects using prior knowledge about typical colours as priors for the grey adjustments in a Bayesian model. This simple model does not involve any fitting of free parameters. The Bayesian model roughly captured the magnitude of the measured memory colour effect for photographs of objects. To some extent, the model predicted observed differences in memory colour effects across objects. The model could not account for the differences in memory colour effects across different levels of realism in the object images. The Bayesian model provides a particularly simple account of memory colour effects, capturing some of the multiple sources of variation of these effects. PMID:29760874

How to achieve synergy between medical education and cognitive neuroscience? An exercise on prior knowledge in understanding.

PubMed

Ruiter, Dirk J; van Kesteren, Marlieke T R; Fernandez, Guillen

2012-05-01

A major challenge in contemporary research is how to connect medical education and cognitive neuroscience and achieve synergy between these domains. Based on this starting point we discuss how this may result in a common language about learning, more educationally focused scientific inquiry, and multidisciplinary research projects. As the topic of prior knowledge in understanding plays a strategic role in both medical education and cognitive neuroscience it is used as a central element in our discussion. A critical condition for the acquisition of new knowledge is the existence of prior knowledge, which can be built in a mental model or schema. Formation of schemas is a central event in student-centered active learning, by which mental models are constructed and reconstructed. These theoretical considerations from cognitive psychology foster scientific discussions that may lead to salient issues and questions for research with cognitive neuroscience. Cognitive neuroscience attempts to understand how knowledge, insight and experience are established in the brain and to clarify their neural correlates. Recently, evidence has been obtained that new information processed by the hippocampus can be consolidated into a stable, neocortical network more rapidly if this new information fits readily into a schema. Opportunities for medical education and medical education research can be created in a fruitful dialogue within an educational multidisciplinary platform. In this synergetic setting many questions can be raised by educational scholars interested in evidence-based education that may be highly relevant for integrative research and the further development of medical education.

Novice and expert teachers' conceptions of learners' prior knowledge

NASA Astrophysics Data System (ADS)

Meyer, Helen

2004-11-01

This study presents comparative case studies of preservice and first-year teachers' and expert teachers' conceptions of the concept of prior knowledge. Kelly's (The Psychology of Personal Construct, New York: W.W. Norton, 1955) theory of personal constructs as discussed by Akerson, Flick, and Lederman (Journal of Research in Science Teaching, 2000, 37, 363-385) in relationship to prior knowledge underpins the study. Six teachers were selected to participate in the case studies based upon their level experience teaching science and their willingness to take part. The comparative case studies of the novice and expert teachers provide insights into (a) how novice and expert teachers understand the concept of prior knowledge and (b) how they use this knowledge to make instructional decisions. Data collection consisted of interviews, classroom observations, and document analysis. Findings suggest that novice teachers hold insufficient conceptions of prior knowledge and its role in instruction to effectively implement constructivist teaching practices. While expert teachers hold a complex conception of prior knowledge and make use of their students' prior knowledge in significant ways during instruction. A second finding was an apparent mismatch between the novice teachers' beliefs about their urban students' life experiences and prior knowledge and the wealth of knowledge the expert teachers found to draw upon.

Use of Elaborative Interrogation to Help Students Acquire Information Consistent with Prior Knowledge and Information Inconsistent with Prior Knowledge.

ERIC Educational Resources Information Center

Woloshyn, Vera E.; And Others

1994-01-01

Thirty-two factual statements, half consistent and half not consistent with subjects' prior knowledge, were processed by 140 sixth and seventh graders. Half were directed to use elaborative interrogation (using prior knowledge) to answer why each statement was true. Across all memory measures, elaborative interrogation subjects performed better…

Brief Report: Teachers' Awareness of the Relationship between Prior Knowledge and New Learning

ERIC Educational Resources Information Center

Journal for Research in Mathematics Education, 2016

2016-01-01

The author examined the degree to which experienced teachers are aware of the relationship between prior knowledge and new learning. Interviews with teachers revealed that they were explicitly aware of when students made connections between prior knowledge and new learning, when they applied their prior knowledge to new contexts, and when they…

"Dare I Ask?": Eliciting Prior Knowledge and Its Implications for Teaching and Learning

ERIC Educational Resources Information Center

Dávila, Liv Thorstensson

2015-01-01

This article examines high school teachers' engagement of newcomer English learner students' prior knowledge. Three central research questions guided this study: 1) To what extent do teachers function as mediators of their students' prior knowledge? 2) What goes into teachers' thinking about how and when to elicit prior knowledge? and 3) How do…

An oral health education programme based on the National Curriculum.

PubMed

Chapman, A; Copestake, S J; Duncan, K

2006-01-01

The aim of this study was to develop and evaluate a teaching programme based on the national curriculum for use in a primary school setting. National Curriculum guidelines were combined with oral health education messages to draw up lesson plans for teachers to deliver. A questionnaire was used to demonstrate children's oral health knowledge prior to the teaching programme, and at 1 and 7 weeks following the programme. The study took place in inner-city, state-run primary schools in Manchester and North London, UK. The subjects were children between the ages of 7 and 8 years from Manchester (n = 58) and North London (n = 30). The main outcome measure was change in knowledge attributable to a newly developed teaching programme. The children in Manchester had a higher level of knowledge prior to the teaching programme. Following the teaching programme, children in both schools showed a significant improvement in dental health knowledge (P < 0.001). Seven weeks later, the Manchester children showed no significant loss of knowledge (P < 0.001). The aims of the National Curriculum were easily integrated with oral health messages. A more widely available teaching resource, such as the one described in this study, would be useful to encourage the teaching profession to take on oral health education without more costly input from dental professionals.

Knowledge discovery about quality of life changes of spinal cord injury patients: clustering based on rules by states.

PubMed

Gibert, Karina; García-Rudolph, Alejandro; Curcoll, Lluïsa; Soler, Dolors; Pla, Laura; Tormos, José María

2009-01-01

In this paper, an integral Knowledge Discovery Methodology, named Clustering based on rules by States, which incorporates artificial intelligence (AI) and statistical methods as well as interpretation-oriented tools, is used for extracting knowledge patterns about the evolution over time of the Quality of Life (QoL) of patients with Spinal Cord Injury. The methodology incorporates the interaction with experts as a crucial element with the clustering methodology to guarantee usefulness of the results. Four typical patterns are discovered by taking into account prior expert knowledge. Several hypotheses are elaborated about the reasons for psychological distress or decreases in QoL of patients over time. The knowledge discovery from data (KDD) approach turns out, once again, to be a suitable formal framework for handling multidimensional complexity of the health domains.

Integrating informative priors from experimental research with Bayesian methods: an example from radiation epidemiology.

PubMed

Hamra, Ghassan; Richardson, David; Maclehose, Richard; Wing, Steve

2013-01-01

Informative priors can be a useful tool for epidemiologists to handle problems of sparse data in regression modeling. It is sometimes the case that an investigator is studying a population exposed to two agents, X and Y, where Y is the agent of primary interest. Previous research may suggest that the exposures have different effects on the health outcome of interest, one being more harmful than the other. Such information may be derived from epidemiologic analyses; however, in the case where such evidence is unavailable, knowledge can be drawn from toxicologic studies or other experimental research. Unfortunately, using toxicologic findings to develop informative priors in epidemiologic analyses requires strong assumptions, with no established method for its utilization. We present a method to help bridge the gap between animal and cellular studies and epidemiologic research by specification of an order-constrained prior. We illustrate this approach using an example from radiation epidemiology.

Integrating Informative Priors from Experimental Research with Bayesian Methods

PubMed Central

Hamra, Ghassan; Richardson, David; MacLehose, Richard; Wing, Steve

2013-01-01

Informative priors can be a useful tool for epidemiologists to handle problems of sparse data in regression modeling. It is sometimes the case that an investigator is studying a population exposed to two agents, X and Y, where Y is the agent of primary interest. Previous research may suggest that the exposures have different effects on the health outcome of interest, one being more harmful than the other. Such information may be derived from epidemiologic analyses; however, in the case where such evidence is unavailable, knowledge can be drawn from toxicologic studies or other experimental research. Unfortunately, using toxicologic findings to develop informative priors in epidemiologic analyses requires strong assumptions, with no established method for its utilization. We present a method to help bridge the gap between animal and cellular studies and epidemiologic research by specification of an order-constrained prior. We illustrate this approach using an example from radiation epidemiology. PMID:23222512

Integrating clinicians, knowledge and data: expert-based cooperative analysis in healthcare decision support

PubMed Central

2010-01-01

Background Decision support in health systems is a highly difficult task, due to the inherent complexity of the process and structures involved. Method This paper introduces a new hybrid methodology Expert-based Cooperative Analysis (EbCA), which incorporates explicit prior expert knowledge in data analysis methods, and elicits implicit or tacit expert knowledge (IK) to improve decision support in healthcare systems. EbCA has been applied to two different case studies, showing its usability and versatility: 1) Bench-marking of small mental health areas based on technical efficiency estimated by EbCA-Data Envelopment Analysis (EbCA-DEA), and 2) Case-mix of schizophrenia based on functional dependency using Clustering Based on Rules (ClBR). In both cases comparisons towards classical procedures using qualitative explicit prior knowledge were made. Bayesian predictive validity measures were used for comparison with expert panels results. Overall agreement was tested by Intraclass Correlation Coefficient in case "1" and kappa in both cases. Results EbCA is a new methodology composed by 6 steps:. 1) Data collection and data preparation; 2) acquisition of "Prior Expert Knowledge" (PEK) and design of the "Prior Knowledge Base" (PKB); 3) PKB-guided analysis; 4) support-interpretation tools to evaluate results and detect inconsistencies (here Implicit Knowledg -IK- might be elicited); 5) incorporation of elicited IK in PKB and repeat till a satisfactory solution; 6) post-processing results for decision support. EbCA has been useful for incorporating PEK in two different analysis methods (DEA and Clustering), applied respectively to assess technical efficiency of small mental health areas and for case-mix of schizophrenia based on functional dependency. Differences in results obtained with classical approaches were mainly related to the IK which could be elicited by using EbCA and had major implications for the decision making in both cases. Discussion This paper presents EbCA and shows the convenience of completing classical data analysis with PEK as a mean to extract relevant knowledge in complex health domains. One of the major benefits of EbCA is iterative elicitation of IK.. Both explicit and tacit or implicit expert knowledge are critical to guide the scientific analysis of very complex decisional problems as those found in health system research. PMID:20920289

Integrating clinicians, knowledge and data: expert-based cooperative analysis in healthcare decision support.

PubMed

Gibert, Karina; García-Alonso, Carlos; Salvador-Carulla, Luis

2010-09-30

Decision support in health systems is a highly difficult task, due to the inherent complexity of the process and structures involved. This paper introduces a new hybrid methodology Expert-based Cooperative Analysis (EbCA), which incorporates explicit prior expert knowledge in data analysis methods, and elicits implicit or tacit expert knowledge (IK) to improve decision support in healthcare systems. EbCA has been applied to two different case studies, showing its usability and versatility: 1) Bench-marking of small mental health areas based on technical efficiency estimated by EbCA-Data Envelopment Analysis (EbCA-DEA), and 2) Case-mix of schizophrenia based on functional dependency using Clustering Based on Rules (ClBR). In both cases comparisons towards classical procedures using qualitative explicit prior knowledge were made. Bayesian predictive validity measures were used for comparison with expert panels results. Overall agreement was tested by Intraclass Correlation Coefficient in case "1" and kappa in both cases. EbCA is a new methodology composed by 6 steps:. 1) Data collection and data preparation; 2) acquisition of "Prior Expert Knowledge" (PEK) and design of the "Prior Knowledge Base" (PKB); 3) PKB-guided analysis; 4) support-interpretation tools to evaluate results and detect inconsistencies (here Implicit Knowledg -IK- might be elicited); 5) incorporation of elicited IK in PKB and repeat till a satisfactory solution; 6) post-processing results for decision support. EbCA has been useful for incorporating PEK in two different analysis methods (DEA and Clustering), applied respectively to assess technical efficiency of small mental health areas and for case-mix of schizophrenia based on functional dependency. Differences in results obtained with classical approaches were mainly related to the IK which could be elicited by using EbCA and had major implications for the decision making in both cases. This paper presents EbCA and shows the convenience of completing classical data analysis with PEK as a mean to extract relevant knowledge in complex health domains. One of the major benefits of EbCA is iterative elicitation of IK.. Both explicit and tacit or implicit expert knowledge are critical to guide the scientific analysis of very complex decisional problems as those found in health system research.

A new multicriteria risk mapping approach based on a multiattribute frontier concept.

PubMed

Yemshanov, Denys; Koch, Frank H; Ben-Haim, Yakov; Downing, Marla; Sapio, Frank; Siltanen, Marty

2013-09-01

Invasive species risk maps provide broad guidance on where to allocate resources for pest monitoring and regulation, but they often present individual risk components (such as climatic suitability, host abundance, or introduction potential) as independent entities. These independent risk components are integrated using various multicriteria analysis techniques that typically require prior knowledge of the risk components' importance. Such information is often nonexistent for many invasive pests. This study proposes a new approach for building integrated risk maps using the principle of a multiattribute efficient frontier and analyzing the partial order of elements of a risk map as distributed in multidimensional criteria space. The integrated risks are estimated as subsequent multiattribute frontiers in dimensions of individual risk criteria. We demonstrate the approach with the example of Agrilus biguttatus Fabricius, a high-risk pest that may threaten North American oak forests in the near future. Drawing on U.S. and Canadian data, we compare the performance of the multiattribute ranking against a multicriteria linear weighted averaging technique in the presence of uncertainties, using the concept of robustness from info-gap decision theory. The results show major geographic hotspots where the consideration of tradeoffs between multiple risk components changes integrated risk rankings. Both methods delineate similar geographical regions of high and low risks. Overall, aggregation based on a delineation of multiattribute efficient frontiers can be a useful tool to prioritize risks for anticipated invasive pests, which usually have an extremely poor prior knowledge base. Published 2013. This article is a U.S. Government work and is in the public domain in the USA.

Perceived knowledge and clinical comfort with genetics among Taiwanese nurses enrolled in a RN-to-BSN program.

PubMed

Hsiao, Chiu-Yueh; Lee, Shu-Hsin; Chen, Suh-Jen; Lin, Shu-Chin

2013-08-01

Advances in genetics have had a profound impact on health care. Yet, many nurses, as well as other health care providers, have limited genetic knowledge and feel uncomfortable integrating genetics into their practice. Very little is known about perceived genetic knowledge and clinical comfort among Taiwanese nurses enrolled in a Registered Nurse to Bachelor of Science in Nursing program. To examine perceived knowledge and clinical comfort with genetics among Taiwanese nurses enrolled in a Registered Nurse to Bachelor of Science in Nursing program and to assess how genetics has been integrated into their past and current nursing programs. The study also sought to examine correlations among perceived knowledge, integration of genetics into the nursing curriculum, and clinical comfort with genetics. A descriptive, cross-sectional study. Taiwanese nurses enrolled in a Registered Nurse to Bachelor of Science in Nursing program were recruited. A total of 190 of 220 nurses returned the completed survey (86.36% response rate). Descriptive statistics and the Pearson product-moment correlation were used for data analysis. Most nurses indicated limited perceived knowledge and clinical comfort with genetics. Curricular hours focused on genetics in a current nursing program were greater than those in past nursing programs. The use of genetic materials, attendance at genetic workshops and conferences, and clinically relevant genetics in nursing practice significantly related with perceived knowledge and clinical comfort with genetics. However, there were no correlations between prior genetic-based health care, perceived knowledge, and clinical comfort with genetics. This study demonstrated the need for emphasizing genetic education and practice to ensure health-related professionals become knowledgeable about genetic information. Given the rapidly developing genetic revolution, nurses and other health care providers need to utilize genetic discoveries to optimize health outcomes. Copyright © 2012 Elsevier Ltd. All rights reserved.

Integrating chronic care with primary care activities: enriching healthcare staff knowledge and skills and improving glycemic control of a cohort of people with diabetes through the First Line Diabetes Care Project in the Philippines

PubMed Central

Ku, Grace Marie V.; Kegels, Guy

2014-01-01

Background This study investigated the effects of integrating primary chronic care with current healthcare activities in two local government health units (LGHU) of the Philippines on knowledge and skills of the LGHU staff and clinical outcomes for people with diabetes. Design Integration was accomplished through health service reorganization, (re)distribution of chronic care tasks, and training of LGHU staff. Levels of the staff's pre- and post-training diabetes knowledge and of their self-assessment of diabetes care-related skills were measured. Primary diabetes care with emphasis on self-care development was provided to a cohort of people with diabetes. Glycosylated hemoglobin (HbA1c) and obesity measures were collected prior to and one year after full project implementation. Results The training workshop improved diabetes knowledge (p<0.001) and self-assessed skills (p<0.001) of the LGHU staff. Significant reductions in HbA1c (p<0.001), waist–hip ratio (p<0.001) and waist circumference (p=0.011) of the cohort were noted. Although the reduction in HbA1c was somewhat greater among those whose community-based care providers showed improvement in knowledge and self-assessed skills, the difference was not statistically significant. Conclusions Primary care for chronic conditions such as diabetes may be integrated with other healthcare activities in health services of low-to-middle-income countries such as the Philippines, utilizing pre-existing human resources for health, and may improve clinical endpoints. PMID:25361726

Integrated learning in practical machine element design course: a case study of V-pulley design

NASA Astrophysics Data System (ADS)

Tantrabandit, Manop

2014-06-01

To achieve an effective integrated learning in Machine Element Design course, it is of importance to bridge the basic knowledge and skills of element designs. The multiple core learning leads the pathway which consists of two main parts. The first part involves teaching documents of which the contents are number of V-groove formulae, standard of V-grooved pulleys, and parallel key dimension's formulae. The second part relates to the subjects that the students have studied prior to participating in this integrated learning course, namely Material Selection, Manufacturing Process, Applied Engineering Drawing, CAD (Computer Aided Design) animation software. Moreover, an intensive cooperation between a lecturer and students is another key factor to fulfill the success of integrated learning. Last but not least, the students need to share their knowledge within the group and among the other groups aiming to gain knowledge of and skills in 1) the application of CAD-software to build up manufacture part drawings, 2) assembly drawing, 3) simulation to verify the strength of loaded pulley by method of Finite Element Analysis (FEA), 4) the software to create animation of mounting and dismounting of a pulley to a shaft, and 5) an instruction manual. The end product of this integrated learning, as a result of the above 1 to 5 knowledge and skills obtained, the participating students can create an assembly derived from manufacture part drawings and a video presentation with bilingual (English-Thai) audio description of Vpulley with datum diameter of 250 mm, 4 grooves, and type of groove: SPA.

Relations among conceptual knowledge, procedural knowledge, and procedural flexibility in two samples differing in prior knowledge.

PubMed

Schneider, Michael; Rittle-Johnson, Bethany; Star, Jon R

2011-11-01

Competence in many domains rests on children developing conceptual and procedural knowledge, as well as procedural flexibility. However, research on the developmental relations between these different types of knowledge has yielded unclear results, in part because little attention has been paid to the validity of the measures or to the effects of prior knowledge on the relations. To overcome these problems, we modeled the three constructs in the domain of equation solving as latent factors and tested (a) whether the predictive relations between conceptual and procedural knowledge were bidirectional, (b) whether these interrelations were moderated by prior knowledge, and (c) how both constructs contributed to procedural flexibility. We analyzed data from 2 measurement points each from two samples (Ns = 228 and 304) of middle school students who differed in prior knowledge. Conceptual and procedural knowledge had stable bidirectional relations that were not moderated by prior knowledge. Both kinds of knowledge contributed independently to procedural flexibility. The results demonstrate how changes in complex knowledge structures contribute to competence development.

The Influence of Prior Knowledge on Memory: A Developmental Cognitive Neuroscience Perspective

PubMed Central

Brod, Garvin; Werkle-Bergner, Markus; Shing, Yee Lee

2013-01-01

Across ontogenetic development, individuals gather manifold experiences during which they detect regularities in their environment and thereby accumulate knowledge. This knowledge is used to guide behavior, make predictions, and acquire further new knowledge. In this review, we discuss the influence of prior knowledge on memory from both the psychology and the emerging cognitive neuroscience literature and provide a developmental perspective on this topic. Recent neuroscience findings point to a prominent role of the medial prefrontal cortex (mPFC) and of the hippocampus (HC) in the emergence of prior knowledge and in its application during the processes of successful memory encoding, consolidation, and retrieval. We take the lateral PFC into consideration as well and discuss changes in both medial and lateral PFC and HC across development and postulate how these may be related to the development of the use of prior knowledge for remembering. For future direction, we argue that, to measure age differential effects of prior knowledge on memory, it is necessary to distinguish the availability of prior knowledge from its accessibility and use. PMID:24115923

When generating answers benefits arithmetic skill: the importance of prior knowledge.

PubMed

Rittle-Johnson, Bethany; Kmicikewycz, Alexander Oleksij

2008-09-01

People remember information better if they generate the information while studying rather than read the information. However, prior research has not investigated whether this generation effect extends to related but unstudied items and has not been conducted in classroom settings. We compared third graders' success on studied and unstudied multiplication problems after they spent a class period generating answers to problems or reading the answers from a calculator. The effect of condition interacted with prior knowledge. Students with low prior knowledge had higher accuracy in the generate condition, but as prior knowledge increased, the advantage of generating answers decreased. The benefits of generating answers may extend to unstudied items and to classroom settings, but only for learners with low prior knowledge.

On-Site Pedagogical Content Knowledge Development

NASA Astrophysics Data System (ADS)

Chan, Kennedy Kam Ho; Yung, Benny Hin Wai

2015-05-01

Experiences and reflection have long been regarded as a foundation for pedagogical content knowledge (PCK) development. However, little is known about how experienced teachers develop their PCK via reflection-in-action during their moment-to-moment classroom instruction. Drawing upon data sources including classroom observations, semi-structured interviews and stimulated recall interviews based on lesson videos, this study examined instances when four experienced teachers were found to invent new instructional strategies/representations on the spot during the lesson (referred to as on-site PCK development) in their first attempts at teaching a new topic. The study documented the moment-to-moment experiences of the teachers, including their reconstructed thought processes associated with these instances of on-site PCK development. An explanatory model of a three-step process comprising a stimulus, an integration process and a response was advanced to account for the on-site PCK development observed among the teachers. Three categories of stimulus that triggered on-site PCK development were identified. Factors influencing the integration process and, hence, the resulting response, included teachers' subject matter knowledge of the new topic, their general pedagogical knowledge and their knowledge of student learning difficulties/prior knowledge related to the new topic. Implications for teacher professional development in terms of how to enhance teachers' on-site PCK development are discussed.

Profiles of inconsistent knowledge in children's pathways of conceptual change.

PubMed

Schneider, Michael; Hardy, Ilonca

2013-09-01

Conceptual change requires learners to restructure parts of their conceptual knowledge base. Prior research has identified the fragmentation and the integration of knowledge as 2 important component processes of knowledge restructuring but remains unclear as to their relative importance and the time of their occurrence during development. Previous studies mostly were based on the categorization of answers in interview studies and led to mixed empirical results, suggesting that methodological improvements might be helpful. We assessed 161 third-graders' knowledge about floating and sinking of objects in liquids at 3 measurement points by means of multiple-choice tests. The tests assessed how strongly the children agreed with commonly found but mutually incompatible statements about floating and sinking. A latent profile transition analysis of the test scores revealed 5 profiles, some of which indicated the coexistence of inconsistent pieces of knowledge in learners. The majority of students (63%) were on 1 of 7 developmental pathways between these profiles. Thus, a child's knowledge profile at a point in time can be used to predict further development. The degree of knowledge integration decreased on some individual developmental paths, increased on others, and remained stable on still others. The study demonstrates the usefulness of explicit quantitative models of conceptual change. The results support a constructivist perspective on conceptual development, in which developmental changes of a learner's knowledge base result from idiosyncratic, yet systematic knowledge-construction processes. PsycINFO Database Record (c) 2013 APA, all rights reserved.

The Effects of the Timing of Isolated FFI on the Explicit Knowledge and Written Accuracy of Learners with Different Prior Knowledge of the Linguistic Target

ERIC Educational Resources Information Center

Shintani, Natsuko

2017-01-01

This study examines the effects of the timing of explicit instruction (EI) on grammatical accuracy. A total of 123 learners were divided into two groups: those with some productive knowledge of past-counterfactual conditionals (+Prior Knowledge) and those without such knowledge (-Prior Knowledge). Each group was divided into four conditions. Two…

In silico model-based inference: a contemporary approach for hypothesis testing in network biology

PubMed Central

Klinke, David J.

2014-01-01

Inductive inference plays a central role in the study of biological systems where one aims to increase their understanding of the system by reasoning backwards from uncertain observations to identify causal relationships among components of the system. These causal relationships are postulated from prior knowledge as a hypothesis or simply a model. Experiments are designed to test the model. Inferential statistics are used to establish a level of confidence in how well our postulated model explains the acquired data. This iterative process, commonly referred to as the scientific method, either improves our confidence in a model or suggests that we revisit our prior knowledge to develop a new model. Advances in technology impact how we use prior knowledge and data to formulate models of biological networks and how we observe cellular behavior. However, the approach for model-based inference has remained largely unchanged since Fisher, Neyman and Pearson developed the ideas in the early 1900’s that gave rise to what is now known as classical statistical hypothesis (model) testing. Here, I will summarize conventional methods for model-based inference and suggest a contemporary approach to aid in our quest to discover how cells dynamically interpret and transmit information for therapeutic aims that integrates ideas drawn from high performance computing, Bayesian statistics, and chemical kinetics. PMID:25139179

In silico model-based inference: a contemporary approach for hypothesis testing in network biology.

PubMed

Klinke, David J

2014-01-01

Inductive inference plays a central role in the study of biological systems where one aims to increase their understanding of the system by reasoning backwards from uncertain observations to identify causal relationships among components of the system. These causal relationships are postulated from prior knowledge as a hypothesis or simply a model. Experiments are designed to test the model. Inferential statistics are used to establish a level of confidence in how well our postulated model explains the acquired data. This iterative process, commonly referred to as the scientific method, either improves our confidence in a model or suggests that we revisit our prior knowledge to develop a new model. Advances in technology impact how we use prior knowledge and data to formulate models of biological networks and how we observe cellular behavior. However, the approach for model-based inference has remained largely unchanged since Fisher, Neyman and Pearson developed the ideas in the early 1900s that gave rise to what is now known as classical statistical hypothesis (model) testing. Here, I will summarize conventional methods for model-based inference and suggest a contemporary approach to aid in our quest to discover how cells dynamically interpret and transmit information for therapeutic aims that integrates ideas drawn from high performance computing, Bayesian statistics, and chemical kinetics. © 2014 American Institute of Chemical Engineers.

Active Prior Tactile Knowledge Transfer for Learning Tactual Properties of New Objects

PubMed Central

Feng, Di

2018-01-01

Reusing the tactile knowledge of some previously-explored objects (prior objects) helps us to easily recognize the tactual properties of new objects. In this paper, we enable a robotic arm equipped with multi-modal artificial skin, like humans, to actively transfer the prior tactile exploratory action experiences when it learns the detailed physical properties of new objects. These experiences, or prior tactile knowledge, are built by the feature observations that the robot perceives from multiple sensory modalities, when it applies the pressing, sliding, and static contact movements on objects with different action parameters. We call our method Active Prior Tactile Knowledge Transfer (APTKT), and systematically evaluated its performance by several experiments. Results show that the robot improved the discrimination accuracy by around 10% when it used only one training sample with the feature observations of prior objects. By further incorporating the predictions from the observation models of prior objects as auxiliary features, our method improved the discrimination accuracy by over 20%. The results also show that the proposed method is robust against transferring irrelevant prior tactile knowledge (negative knowledge transfer). PMID:29466300

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

PubMed

Zeng, Irene Sui Lan; Lumley, Thomas

2018-01-01

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

Epilogue: Reading Comprehension Is Not a Single Ability-Implications for Assessment and Instruction.

PubMed

Kamhi, Alan G; Catts, Hugh W

2017-04-20

In this epilogue, we review the 4 response articles and highlight the implications of a multidimensional view of reading for the assessment and instruction of reading comprehension. We reiterate the problems with standardized tests of reading comprehension and discuss the advantages and disadvantages of recently developed authentic tests of reading comprehension. In the "Instruction" section, we review the benefits and limitations of strategy instruction and highlight suggestions from the response articles to improve content and language knowledge. We argue that the only compelling reason to administer a standardized test of reading comprehension is when these tests are necessary to qualify students for special education services. Instruction should be focused on content knowledge, language knowledge, and specific task and learning requirements. This instruction may entail the use of comprehension strategies, particularly those that are specific to the task and focus on integrating new knowledge with prior knowledge.

Knowledge Structures of Entering Computer Networking Students and Their Instructors

ERIC Educational Resources Information Center

DiCerbo, Kristen E.

2007-01-01

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

Nudging toward Inquiry: Awakening and Building upon Prior Knowledge

ERIC Educational Resources Information Center

Fontichiaro, Kristin, Comp.

2010-01-01

"Prior knowledge" (sometimes called schema or background knowledge) is information one already knows that helps him/her make sense of new information. New learning builds on existing prior knowledge. In traditional reporting-style research projects, students bypass this crucial step and plow right into answer-finding. It's no wonder that many…

Mind wandering during film comprehension: The role of prior knowledge and situational interest.

PubMed

Kopp, Kristopher; Mills, Caitlin; D'Mello, Sidney

2016-06-01

This study assessed the occurrence and factors that influence mind wandering (MW) in the domain of film comprehension. The cascading model of inattention assumes that a stronger mental representation (i.e., a situation model) during comprehension results in less MW. Accordingly, a suppression hypothesis suggests that MW would decrease as a function of having the knowledge of the plot of a film prior to viewing, because the prior-knowledge would help to strengthen the situation model during comprehension. Furthermore, an interest-moderation hypothesis would predict that the suppression effect of prior-knowledge would only emerge when there was interest in viewing the film. In the current experiment, 108 participants either read a short story that depicted the plot (i.e., prior-knowledge condition) or read an unrelated story of equal length (control condition) prior to viewing the short film (32.5 minutes) entitled The Red Balloon. Participants self-reported their interest in viewing the film immediately before the film was presented. MW was tracked using a self-report method targeting instances of MW with metacognitive awareness. Participants in the prior-knowledge condition reported less MW compared with the control condition, thereby supporting the suppression hypothesis. MW also decreased over the duration of the film, but only for those with prior-knowledge of the film. Finally, prior-knowledge effects on MW were only observed when interest was average or high, but not when interest was low.

Structured feedback on students' concept maps: the proverbial path to learning?

PubMed

Joseph, Conran; Conradsson, David; Nilsson Wikmar, Lena; Rowe, Michael

2017-05-25

Good conceptual knowledge is an essential requirement for health professions students, in that they are required to apply concepts learned in the classroom to a variety of different contexts. However, the use of traditional methods of assessment limits the educator's ability to correct students' conceptual knowledge prior to altering the educational context. Concept mapping (CM) is an educational tool for evaluating conceptual knowledge, but little is known about its use in facilitating the development of richer knowledge frameworks. In addition, structured feedback has the potential to develop good conceptual knowledge. The purpose of this study was to use Kinchin's criteria to assess the impact of structured feedback on the graphical complexity of CM's by observing the development of richer knowledge frameworks. Fifty-eight physiotherapy students created CM's targeting the integration of two knowledge domains within a case-based teaching paradigm. Each student received one round of structured feedback that addressed correction, reinforcement, forensic diagnosis, benchmarking, and longitudinal development on their CM's prior to the final submission. The concept maps were categorized according to Kinchin's criteria as either Spoke, Chain or Net representations, and then evaluated against defined traits of meaningful learning. The inter-rater reliability of categorizing CM's was good. Pre-feedback CM's were predominantly Chain structures (57%), with Net structures appearing least often. There was a significant reduction of the basic Spoke- structured CMs (P = 0.002) and a significant increase of Net-structured maps (P < 0.001) at the final evaluation (post-feedback). Changes in structural complexity of CMs appeared to be indicative of broader knowledge frameworks as assessed against the meaningful learning traits. Feedback on CM's seemed to have contributed towards improving conceptual knowledge and correcting naive conceptions of related knowledge. Educators in medical education could therefore consider using CM's to target individual student development.

The Best of Both Worlds

PubMed Central

Ter Wal, Anne L.J.; Alexy, Oliver; Block, Jörn; Sandner, Philipp G.

2016-01-01

Open networks give actors non-redundant information that is diverse, while closed networks offer redundant information that is easier to interpret. Integrating arguments about network structure and the similarity of actors’ knowledge, we propose two types of network configurations that combine diversity and ease of interpretation. Closed-diverse networks offer diversity in actors’ knowledge domains and shared third-party ties to help in interpreting that knowledge. In open-specialized networks, structural holes offer diversity, while shared interpretive schema and overlap between received information and actors’ prior knowledge help in interpreting new information without the help of third parties. In contrast, actors in open-diverse networks suffer from information overload due to the lack of shared schema or overlapping prior knowledge for the interpretation of diverse information, and actors in closed-specialized networks suffer from overembeddedness because they cannot access diverse information. Using CrunchBase data on early-stage venture capital investments in the U.S. information technology sector, we test the effect of investors’ social capital on the success of their portfolio ventures. We find that ventures have the highest chances of success if their syndicating investors have either open-specialized or closed-diverse networks. These effects are manifested beyond the direct effects of ventures’ or investors’ quality and are robust to controlling for the possibility that certain investors could have chosen more promising ventures at the time of first funding. PMID:27499546

Knowledge-guided fuzzy logic modeling to infer cellular signaling networks from proteomic data

PubMed Central

Liu, Hui; Zhang, Fan; Mishra, Shital Kumar; Zhou, Shuigeng; Zheng, Jie

2016-01-01

Modeling of signaling pathways is crucial for understanding and predicting cellular responses to drug treatments. However, canonical signaling pathways curated from literature are seldom context-specific and thus can hardly predict cell type-specific response to external perturbations; purely data-driven methods also have drawbacks such as limited biological interpretability. Therefore, hybrid methods that can integrate prior knowledge and real data for network inference are highly desirable. In this paper, we propose a knowledge-guided fuzzy logic network model to infer signaling pathways by exploiting both prior knowledge and time-series data. In particular, the dynamic time warping algorithm is employed to measure the goodness of fit between experimental and predicted data, so that our method can model temporally-ordered experimental observations. We evaluated the proposed method on a synthetic dataset and two real phosphoproteomic datasets. The experimental results demonstrate that our model can uncover drug-induced alterations in signaling pathways in cancer cells. Compared with existing hybrid models, our method can model feedback loops so that the dynamical mechanisms of signaling networks can be uncovered from time-series data. By calibrating generic models of signaling pathways against real data, our method supports precise predictions of context-specific anticancer drug effects, which is an important step towards precision medicine. PMID:27774993

Assessing the Previous Economic Knowledge of Beginning Students in Germany: Implications for Teaching Economics in Basic Courses

ERIC Educational Resources Information Center

Happ, Roland; Förster, Manuel; Zlatkin-Troitschanskaia, Olga; Carstensen, Vivian

2016-01-01

Study-related prior knowledge plays a decisive role in business and economics degree courses. Prior knowledge has a significant influence on knowledge acquisition in higher education, and teachers need information on it to plan their introductory courses accordingly. Very few studies have been conducted of first-year students' prior economic…

Use of knowledge-sharing web-based portal in gross and microscopic anatomy.

PubMed

Durosaro, Olayemi; Lachman, Nirusha; Pawlina, Wojciech

2008-12-01

Changes in worldwide healthcare delivery require review of current medical school curricula structure to develop learning outcomes that ensures mastery of knowledge and clinical competency. In the last 3 years, Mayo Medical School implemented outcomes-based curriculum to encompass new graduate outcomes. Standard courses were replaced by 6-week clinically-integrated didactic blocks separated by student-self selected academic enrichment activities. Gross and microscopic anatomy was integrated with radiology and genetics respectively. Laboratory components include virtual microscopy and anatomical dissection. Students assigned to teams utilise computer portals to share learning experiences. High-resolution computed tomographic (CT) scans of cadavers prior to dissection were made available for correlative learning between the cadaveric material and radiologic images. Students work in teams on assigned presentations that include histology, cell and molecular biology, genetics and genomic using the Nexus Portal, based on DrupalEd, to share their observations, reflections and dissection findings. New generation of medical students are clearly comfortable utilising web-based programmes that maximise their learning potential of conceptually difficult and labor intensive courses. Team-based learning approach emphasising the use of knowledge-sharing computer portals maximises opportunities for students to master their knowledge and improve cognitive skills to ensure clinical competency.

Cortical Measures of Phoneme-Level Speech Encoding Correlate with the Perceived Clarity of Natural Speech

PubMed Central

2018-01-01

Abstract In real-world environments, humans comprehend speech by actively integrating prior knowledge (P) and expectations with sensory input. Recent studies have revealed effects of prior information in temporal and frontal cortical areas and have suggested that these effects are underpinned by enhanced encoding of speech-specific features, rather than a broad enhancement or suppression of cortical activity. However, in terms of the specific hierarchical stages of processing involved in speech comprehension, the effects of integrating bottom-up sensory responses and top-down predictions are still unclear. In addition, it is unclear whether the predictability that comes with prior information may differentially affect speech encoding relative to the perceptual enhancement that comes with that prediction. One way to investigate these issues is through examining the impact of P on indices of cortical tracking of continuous speech features. Here, we did this by presenting participants with degraded speech sentences that either were or were not preceded by a clear recording of the same sentences while recording non-invasive electroencephalography (EEG). We assessed the impact of prior information on an isolated index of cortical tracking that reflected phoneme-level processing. Our findings suggest the possibility that prior information affects the early encoding of natural speech in a dual manner. Firstly, the availability of prior information, as hypothesized, enhanced the perceived clarity of degraded speech, which was positively correlated with changes in phoneme-level encoding across subjects. In addition, P induced an overall reduction of this cortical measure, which we interpret as resulting from the increase in predictability. PMID:29662947

The Effects of Prior-knowledge and Online Learning Approaches on Students' Inquiry and Argumentation Abilities

NASA Astrophysics Data System (ADS)

Yang, Wen-Tsung; Lin, Yu-Ren; She, Hsiao-Ching; Huang, Kai-Yi

2015-07-01

This study investigated the effects of students' prior science knowledge and online learning approaches (social and individual) on their learning with regard to three topics: science concepts, inquiry, and argumentation. Two science teachers and 118 students from 4 eighth-grade science classes were invited to participate in this research. Students in each class were divided into three groups according to their level of prior science knowledge; they then took either our social- or individual-based online science learning program. The results show that students in the social online argumentation group performed better in argumentation and online argumentation learning. Qualitative analysis indicated that the students' social interactions benefited the co-construction of sound arguments and the accurate understanding of science concepts. In constructing arguments, students in the individual online argumentation group were limited to knowledge recall and self-reflection. High prior-knowledge students significantly outperformed low prior-knowledge students in all three aspects of science learning. However, the difference in inquiry and argumentation performance between low and high prior-knowledge students decreased with the progression of online learning topics.

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

PubMed

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

2012-12-01

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

Explanation and Prior Knowledge Interact to Guide Learning

ERIC Educational Resources Information Center

Williams, Joseph J.; Lombrozo, Tania

2013-01-01

How do explaining and prior knowledge contribute to learning? Four experiments explored the relationship between explanation and prior knowledge in category learning. The experiments independently manipulated whether participants were prompted to explain the category membership of study observations and whether category labels were informative in…

Iterative CT shading correction with no prior information

NASA Astrophysics Data System (ADS)

Wu, Pengwei; Sun, Xiaonan; Hu, Hongjie; Mao, Tingyu; Zhao, Wei; Sheng, Ke; Cheung, Alice A.; Niu, Tianye

2015-11-01

Shading artifacts in CT images are caused by scatter contamination, beam-hardening effect and other non-ideal imaging conditions. The purpose of this study is to propose a novel and general correction framework to eliminate low-frequency shading artifacts in CT images (e.g. cone-beam CT, low-kVp CT) without relying on prior information. The method is based on the general knowledge of the relatively uniform CT number distribution in one tissue component. The CT image is first segmented to construct a template image where each structure is filled with the same CT number of a specific tissue type. Then, by subtracting the ideal template from the CT image, the residual image from various error sources are generated. Since forward projection is an integration process, non-continuous shading artifacts in the image become continuous signals in a line integral. Thus, the residual image is forward projected and its line integral is low-pass filtered in order to estimate the error that causes shading artifacts. A compensation map is reconstructed from the filtered line integral error using a standard FDK algorithm and added back to the original image for shading correction. As the segmented image does not accurately depict a shaded CT image, the proposed scheme is iterated until the variation of the residual image is minimized. The proposed method is evaluated using cone-beam CT images of a Catphan©600 phantom and a pelvis patient, and low-kVp CT angiography images for carotid artery assessment. Compared with the CT image without correction, the proposed method reduces the overall CT number error from over 200 HU to be less than 30 HU and increases the spatial uniformity by a factor of 1.5. Low-contrast object is faithfully retained after the proposed correction. An effective iterative algorithm for shading correction in CT imaging is proposed that is only assisted by general anatomical information without relying on prior knowledge. The proposed method is thus practical and attractive as a general solution to CT shading correction.

Design of CIAO, a research program to support the development of an integrated approach to prevent overweight and obesity in the Netherlands.

PubMed

van Koperen, Marije Tm; van der Kleij, Rianne Mjj; Renders, Carry Cm; Crone, Matty Mr; Hendriks, Anna-Marie Am; Jansen, Maria M; van de Gaar, Vivian Vm; Raat, Hein Jh; Ruiter, Emilie Elm; Molleman, Gerard Grm; Schuit, Jantine Aj; Seidell, Jacob Jc

2014-01-01

The aim of this paper is to describe the research aims, concepts and methods of the research Consortium Integrated Approach of Overweight (CIAO). CIAO is a concerted action of five Academic Collaborative Centres, local collaborations between academic institutions, regional public health services, local authorities and other relevant sectors in the Netherlands. Prior research revealed lacunas in knowledge of and skills related to five elements of the integrated approach of overweight prevention in children (based upon the French EPODE approach), namely political support, parental education, implementation, social marketing and evaluation. CIAO aims to gain theoretical and practical insight of these elements through five sub-studies and to develop, based on these data, a framework for monitoring and evaluation. For this research program, mixed methods are used in all the five sub-studies. First, problem specification through literature research and consultation of stakeholders, experts, health promotion specialists, parents and policy makers will be carried out. Based on this information, models, theoretical frameworks and practical instruments will be developed, tested and evaluated in the communities that implement the integrated approach to prevent overweight in children. Knowledge obtained from these studies and insights from experts and stakeholders will be combined to create an evaluation framework to evaluate the integrated approach at central, local and individual levels that will be applicable to daily practice. This innovative research program stimulates sub-studies to collaborate with local stakeholders and to share and integrate their knowledge, methodology and results. Therefore, the output of this program (both knowledge and practical tools) will be matched and form building blocks of a blueprint for a local evidence- and practice-based integrated approach towards prevention of overweight in children. The output will then support various communities to further optimize the implementation and subsequently the effects of this approach.

Exploring expectation effects in EMDR: does prior treatment knowledge affect the degrading effects of eye movements on memories?

PubMed Central

Littel, Marianne; van Schie, Kevin; van den Hout, Marcel A.

2017-01-01

ABSTRACT Background: Eye movement desensitization and reprocessing (EMDR) is an effective psychological treatment for posttraumatic stress disorder. Recalling a memory while simultaneously making eye movements (EM) decreases a memory’s vividness and/or emotionality. It has been argued that non-specific factors, such as treatment expectancy and experimental demand, may contribute to the EMDR’s effectiveness. Objective: The present study was designed to test whether expectations about the working mechanism of EMDR would alter the memory attenuating effects of EM. Two experiments were conducted. In Experiment 1, we examined the effects of pre-existing (non-manipulated) knowledge of EMDR in participants with and without prior knowledge. In Experiment 2, we experimentally manipulated prior knowledge by providing participants without prior knowledge with correct or incorrect information about EMDR’s working mechanism. Method: Participants in both experiments recalled two aversive, autobiographical memories during brief sets of EM (Recall+EM) or keeping eyes stationary (Recall Only). Before and after the intervention, participants scored their memories on vividness and emotionality. A Bayesian approach was used to compare two competing hypotheses on the effects of (existing/given) prior knowledge: (1) Prior (correct) knowledge increases the effects of Recall+EM vs. Recall Only, vs. (2) prior knowledge does not affect the effects of Recall+EM. Results: Recall+EM caused greater reductions in memory vividness and emotionality than Recall Only in all groups, including the incorrect information group. In Experiment 1, both hypotheses were supported by the data: prior knowledge boosted the effects of EM, but only modestly. In Experiment 2, the second hypothesis was clearly supported over the first: providing knowledge of the underlying mechanism of EMDR did not alter the effects of EM. Conclusions: Recall+EM appears to be quite robust against the effects of prior expectations. As Recall+EM is the core component of EMDR, expectancy effects probably contribute little to the effectiveness of EMDR treatment. PMID:29038685

Self-motion perception in autism is compromised by visual noise but integrated optimally across multiple senses

PubMed Central

Zaidel, Adam; Goin-Kochel, Robin P.; Angelaki, Dora E.

2015-01-01

Perceptual processing in autism spectrum disorder (ASD) is marked by superior low-level task performance and inferior complex-task performance. This observation has led to theories of defective integration in ASD of local parts into a global percept. Despite mixed experimental results, this notion maintains widespread influence and has also motivated recent theories of defective multisensory integration in ASD. Impaired ASD performance in tasks involving classic random dot visual motion stimuli, corrupted by noise as a means to manipulate task difficulty, is frequently interpreted to support this notion of global integration deficits. By manipulating task difficulty independently of visual stimulus noise, here we test the hypothesis that heightened sensitivity to noise, rather than integration deficits, may characterize ASD. We found that although perception of visual motion through a cloud of dots was unimpaired without noise, the addition of stimulus noise significantly affected adolescents with ASD, more than controls. Strikingly, individuals with ASD demonstrated intact multisensory (visual–vestibular) integration, even in the presence of noise. Additionally, when vestibular motion was paired with pure visual noise, individuals with ASD demonstrated a different strategy than controls, marked by reduced flexibility. This result could be simulated by using attenuated (less reliable) and inflexible (not experience-dependent) Bayesian priors in ASD. These findings question widespread theories of impaired global and multisensory integration in ASD. Rather, they implicate increased sensitivity to sensory noise and less use of prior knowledge in ASD, suggesting increased reliance on incoming sensory information. PMID:25941373

Calculus Instructors' Responses to Prior Knowledge Errors

ERIC Educational Resources Information Center

Talley, Jana Renee

2009-01-01

This study investigates the responses to prior knowledge errors that Calculus I instructors make when assessing students. Prior knowledge is operationalized as any skill or understanding that a student needs to successfully navigate through a Calculus I course. A two part qualitative study consisting of student exams and instructor interviews was…

Menarche: Prior Knowledge and Experience.

ERIC Educational Resources Information Center

Skandhan, K. P.; And Others

1988-01-01

Recorded menstruation information among 305 young women in India, assessing the differences between those who did and did not have knowledge of menstruation prior to menarche. Those with prior knowledge considered menarche to be a normal physiological function and had a higher rate of regularity, lower rate of dysmenorrhea, and earlier onset of…

Preparing learners with partly incorrect intuitive prior knowledge for learning

PubMed Central

Ohst, Andrea; Fondu, Béatrice M. E.; Glogger, Inga; Nückles, Matthias; Renkl, Alexander

2014-01-01

Learners sometimes have incoherent and fragmented intuitive prior knowledge that is (partly) “incompatible” with the to-be-learned contents. Such knowledge in pieces can cause conceptual disorientation and cognitive overload while learning. We hypothesized that a pre-training intervention providing a generalized schema as a structuring framework for such knowledge in pieces would support (re)organizing-processes of prior knowledge and thus reduce unnecessary cognitive load during subsequent learning. Fifty-six student teachers participated in the experiment. A framework group underwent a pre-training intervention providing a generalized, categorical schema for categorizing primary learning strategies and related but different strategies as a cognitive framework for (re-)organizing their prior knowledge. Our control group received comparable factual information but no framework. Afterwards, all participants learned about primary learning strategies. The framework group claimed to possess higher levels of interest and self-efficacy, achieved higher learning outcomes, and learned more efficiently. Hence, providing a categorical framework can help overcome the barrier of incorrect prior knowledge in pieces. PMID:25071638

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

Kirby, Carolyn L; Lord, Anna C. Snider

The Bryan Mound caprock was subjected to extens ive sulphur mining prior to the development of the Strategic Petroleum Reserve. Undoubtedl y, the mining has modified the caprock integrity. Cavern wells at Bryan Mound have been subject to a host of well integr ity concerns with many likely compromised by the cavernous capro ck, surrounding corrosive environment (H 2 SO 4 ), and associated elevated residual temperatures al l of which are a product of the mining activities. The intent of this study was to understand the sulphur mining process and how the mining has affected the stability of themore » caprock and how the compromised caprock has influenced the integrity of the cavern wells. After an extensiv e search to collect pert inent information through state agencies, literature sear ches, and the Sandia SPR librar y, a better understanding of the caprock can be inferred from the knowledge gaine d. Specifically, the discovery of the original ore reserve map goes a long way towards modeling caprock stability. In addition the gained knowledge of sulphur mining - subs idence, superheated corrosive wa ters, and caprock collapse - helps to better predict the post mi ning effects on wellbore integrity. This page intentionally left blank« less

The impact of representation format and task instruction on student understanding in science

NASA Astrophysics Data System (ADS)

Stephenson, Susan Raatz

The purpose of this study is to examine how representation format and task instructions impact student learning in a science domain. Learning outcomes were assessed via measures of mental model, declarative knowledge, and knowledge inference. Students were asked to use one of two forms of representation, either drawing or writing, during study of a science text. Further, instructions (summarize vs. explain) were varied to determine if students' intended use of the presentation influenced learning. Thus, this study used a 2 (drawing vs. writing) X 2 (summarize vs. explain) between-subjects design. Drawing was hypothesized to require integration across learning materials regardless of task instructions, because drawings (by definition) require learners to integrate new information into a visual representation. Learning outcomes associated with writing were hypothesized to depend upon task instructions: when asked to summarize, writing should result in reproduction of text; when asked to explain, writing should emphasize integration processes. Because integration processes require connecting and analyzing new and prior information, it also was predicted that drawing (across both conditions of task instructions) and writing (when combined the explain task instructions only) would result in increased metacognitive monitoring. Metacognitive monitoring was assessed indirectly via responses to metacognitive prompts interspersed throughout the study.

Bayesian bivariate meta-analysis of diagnostic test studies with interpretable priors.

PubMed

Guo, Jingyi; Riebler, Andrea; Rue, Håvard

2017-08-30

In a bivariate meta-analysis, the number of diagnostic studies involved is often very low so that frequentist methods may result in problems. Using Bayesian inference is particularly attractive as informative priors that add a small amount of information can stabilise the analysis without overwhelming the data. However, Bayesian analysis is often computationally demanding and the selection of the prior for the covariance matrix of the bivariate structure is crucial with little data. The integrated nested Laplace approximations method provides an efficient solution to the computational issues by avoiding any sampling, but the important question of priors remain. We explore the penalised complexity (PC) prior framework for specifying informative priors for the variance parameters and the correlation parameter. PC priors facilitate model interpretation and hyperparameter specification as expert knowledge can be incorporated intuitively. We conduct a simulation study to compare the properties and behaviour of differently defined PC priors to currently used priors in the field. The simulation study shows that the PC prior seems beneficial for the variance parameters. The use of PC priors for the correlation parameter results in more precise estimates when specified in a sensible neighbourhood around the truth. To investigate the usage of PC priors in practice, we reanalyse a meta-analysis using the telomerase marker for the diagnosis of bladder cancer and compare the results with those obtained by other commonly used modelling approaches. Copyright © 2017 John Wiley & Sons, Ltd. Copyright © 2017 John Wiley & Sons, Ltd.

Using Hypermedia: Effects of Prior Knowledge and Goal Strength.

ERIC Educational Resources Information Center

Last, David A.; O'Donnell, Angela M.; Kelly, Anthony E.

The influences of a student's prior knowledge and desired goal on the difficulties and benefits associated with using hypertext were examined in this study. Participants, 12 students from an undergraduate course in educational psychology, were assigned to either the low or high prior knowledge category. Within these two groups, subjects were…

The Role of Prior Knowledge in Learning from Analogies in Science Texts

ERIC Educational Resources Information Center

Braasch, Jason L. G.; Goldman, Susan R.

2010-01-01

Two experiments examined whether inconsistent effects of analogies in promoting new content learning from text are related to prior knowledge of the analogy "per se." In Experiment 1, college students who demonstrated little understanding of weather systems and different levels of prior knowledge (more vs. less) of an analogous everyday…

Promoting knowledge integration of scientific principles and environmental stewardship: Assessing an issue-based approach to teaching evolution and marine conservation

NASA Astrophysics Data System (ADS)

Zimmerman, Timothy David

2005-11-01

Students and citizens need to apply science to important issues every day. Yet the design of science curricula that foster integration of science and everyday decisions is not well understood. For example, can curricula be designed that help learners apply scientific reasons for choosing only environmentally sustainable seafood for dinner? Learners must develop integrated understandings of scientific principles, prior experiences, and current decisions in order to comprehend how everyday decisions impact environmental resources. In order to investigate how such integrated understandings can be promoted within school science classes, research was conducted with an inquiry-oriented curriculum that utilizes technology and a visit to an informal learning environment (aquarium) to promote the integration of scientific principles (adaptation) with environmental stewardship. This research used a knowledge integration approach to teaching and learning that provided a framework for promoting the application of science to environmental issues. Marine biology, often forsaken in classrooms for terrestrial biology, served as the scientific context for the curriculum. The curriculum design incorporated a three-phase pedagogical strategy and new technology tools to help students integrate knowledge and experiences across the classroom and aquarium learning environments. The research design and assessment protocols included comparisons among and within student populations using two versions of the curriculum: an issue-based version and a principle-based version. These inquiry curricula were tested with sophomore biology students attending a marine-focused academy within a coastal California high school. Pretest-posttest outcomes were compared between and within the curricular treatments. Additionally, comparisons were made between the inquiry groups and seniors in an Advanced Placement biology course who attend the same high school. Results indicate that the inquiry curricula enabled students to integrate and apply knowledge of evolutionary biology to real-world environmental stewardship issues. Over the course of the curriculum, students' ideas became more scientifically normative and tended to focus around concepts of natural selection. Students using the inquiry curricula outperformed the Advanced Placement biology students on several measures, including knowledge of evolutionary biology. These results have implications for designing science curricula that seek to promote the application of science to environmental stewardship and integrate formal and informal learning environments.

Integration of preclinical and clinical knowledge to predict intravenous PK in human: bilastine case study.

PubMed

Vozmediano, Valvanera; Ortega, Ignacio; Lukas, John C; Gonzalo, Ana; Rodriguez, Monica; Lucero, Maria Luisa

2014-03-01

Modern pharmacometrics can integrate and leverage all prior proprietary and public knowledge. Such methods can be used to scale across species or comparators, perform clinical trial simulation across alternative designs, confirm hypothesis and potentially reduce development burden, time and costs. Crucial yet typically lacking in integration is the pre-clinical stage. Prediction of PK in man, using in vitro and in vivo studies in different animal species, is increasingly well theorized but could still find wider application in drug development. The aim of the present work was to explore methods for bridging pharmacokinetic knowledge from animal species (i.v. and p.o.) and man (p.o.) into i.v. in man using the antihistamine drug bilastine as example. A model, predictive of i.v. PK in man, was developed on data from two pre-clinical species (rat and dog) and p.o. in man bilastine trials performed earlier. In the knowledge application stage, two different approaches were used to predict human plasma concentration after i.v. of bilastine: allometry (several scaling methods) and a semi-physiological method. Both approaches led to successful predictions of key i.v. PK parameters of bilastine in man. The predictive i.v. PK model was validated using later data from a clinical study of i.v. bilastine. Introduction of such knowledge in development permits proper leveraging of all emergent knowledge as well as quantification-based exploration of PK scenario, e.g. in special populations (pediatrics, renal insufficiency, comedication). In addition, the methods permit reduction or elimination and certainly optimization of learning trials, particularly those concerning alternative off-label administration routes.

Chemistry and Physics of Analyte Identification in Integrated Nanosensors

DTIC Science & Technology

2009-02-05

points," / Differential Geometry 26 (1987), pp. 285-314. 12 [7] S. Haker , G. Sapiro, and A. Tannenbaum, "Knowledge-based segmentation of SAR data with...learned priors," IEEE Trans. Image Processing, vol. 9, pp. 298-302, 2000. [8] S. Haker , L. Zhu, S. Angenent, and A. Tannenbaum, "Optimal mass...transport for registration and warping" Int. Journal Computer Vision, vol. 60, pp. 225-240, 2004. [9] S. Haker , G. Sapiro, A. Tannenbaum, and D. Washburn

The Best of Both Worlds: The Benefits of Open-specialized and Closed-diverse Syndication Networks for New Ventures' Success.

PubMed

Ter Wal, Anne L J; Alexy, Oliver; Block, Jörn; Sandner, Philipp G

2016-09-01

Open networks give actors non-redundant information that is diverse, while closed networks offer redundant information that is easier to interpret. Integrating arguments about network structure and the similarity of actors' knowledge, we propose two types of network configurations that combine diversity and ease of interpretation. Closed-diverse networks offer diversity in actors' knowledge domains and shared third-party ties to help in interpreting that knowledge. In open-specialized networks, structural holes offer diversity, while shared interpretive schema and overlap between received information and actors' prior knowledge help in interpreting new information without the help of third parties. In contrast, actors in open-diverse networks suffer from information overload due to the lack of shared schema or overlapping prior knowledge for the interpretation of diverse information, and actors in closed-specialized networks suffer from overembeddedness because they cannot access diverse information. Using CrunchBase data on early-stage venture capital investments in the U.S. information technology sector, we test the effect of investors' social capital on the success of their portfolio ventures. We find that ventures have the highest chances of success if their syndicating investors have either open-specialized or closed-diverse networks. These effects are manifested beyond the direct effects of ventures' or investors' quality and are robust to controlling for the possibility that certain investors could have chosen more promising ventures at the time of first funding.

Basics of Bayesian methods.

PubMed

Ghosh, Sujit K

2010-01-01

Bayesian methods are rapidly becoming popular tools for making statistical inference in various fields of science including biology, engineering, finance, and genetics. One of the key aspects of Bayesian inferential method is its logical foundation that provides a coherent framework to utilize not only empirical but also scientific information available to a researcher. Prior knowledge arising from scientific background, expert judgment, or previously collected data is used to build a prior distribution which is then combined with current data via the likelihood function to characterize the current state of knowledge using the so-called posterior distribution. Bayesian methods allow the use of models of complex physical phenomena that were previously too difficult to estimate (e.g., using asymptotic approximations). Bayesian methods offer a means of more fully understanding issues that are central to many practical problems by allowing researchers to build integrated models based on hierarchical conditional distributions that can be estimated even with limited amounts of data. Furthermore, advances in numerical integration methods, particularly those based on Monte Carlo methods, have made it possible to compute the optimal Bayes estimators. However, there is a reasonably wide gap between the background of the empirically trained scientists and the full weight of Bayesian statistical inference. Hence, one of the goals of this chapter is to bridge the gap by offering elementary to advanced concepts that emphasize linkages between standard approaches and full probability modeling via Bayesian methods.

New graduate students' baseline knowledge of the responsible conduct of research.

PubMed

Heitman, Elizabeth; Olsen, Cara H; Anestidou, Lida; Bulger, Ruth Ellen

2007-09-01

To assess (1) new biomedical science graduate students' baseline knowledge of core concepts and standards in responsible conduct of research (RCR), (2) differences in graduate students' baseline knowledge overall and across the Office of Research Integrity's nine core areas, and (3) demographic and educational factors in these differences. A 30-question, computer-scored multiple-choice test on core concepts and standards of RCR was developed following content analysis of 20 United States-published RCR texts, and combined with demographic questions on undergraduate experience with RCR developed from graduate student focus groups. Four hundred two new graduate students at three health science universities were recruited for Scantron and online testing before beginning RCR instruction. Two hundred fifty-one of 402 eligible trainees (62%) at three universities completed the test; scores ranged from 26.7% to 83.3%, with a mean of 59.5%. Only seven (3%) participants scored 80% or above. Students who received their undergraduate education outside the United States scored significantly lower (mean 52.0%) than those with U.S. bachelor's degrees (mean 60.5%, P < .001). Participants with prior graduate biomedical or health professions education scored marginally higher than new students, but both groups' mean scores were well below 80%. The mean score of 16 participants who reported previous graduate-level RCR instruction was 67.7%. Participants' specific knowledge varied, but overall scores were universally low. New graduate biomedical sciences students have inadequate and inconsistent knowledge of RCR, irrespective of their prior education or experience. Incoming trainees with previous graduate RCR education may also have gaps in core knowledge.

The Effect of Prior Knowledge Activation on Text Recall: An Investigation of Two Conflicting Hypotheses.

ERIC Educational Resources Information Center

Machiels-Bongaerts, Maureen; And Others

Two hypotheses, the cognitive capacity hypothesis and the selective attention hypothesis, try to account for the facilitation effects of prior knowledge activation. They appear to be mutually exclusive since they predict different recall patterns as a result of prior knowledge activation. This study was designed to determine whether the two…

Understanding the Role of Prior Knowledge in a Multimedia Learning Application

ERIC Educational Resources Information Center

Rias, Riaza Mohd; Zaman, Halimah Badioze

2013-01-01

This study looked at the effects that individual differences in prior knowledge have on student understanding in learning with multimedia in a computer science subject. Students were identified as having either low or high prior knowledge from a series of questions asked in a survey conducted at the Faculty of Computer and Mathematical Sciences at…

A Fuzzy-Based Prior Knowledge Diagnostic Model with Multiple Attribute Evaluation

ERIC Educational Resources Information Center

Lin, Yi-Chun; Huang, Yueh-Min

2013-01-01

Prior knowledge is a very important part of teaching and learning, as it affects how instructors and students interact with the learning materials. In general, tests are used to assess students' prior knowledge. Nevertheless, conventional testing approaches usually assign only an overall score to each student, and this may mean that students are…

Automated sleep stage detection with a classical and a neural learning algorithm--methodological aspects.

PubMed

Schwaibold, M; Schöchlin, J; Bolz, A

2002-01-01

For classification tasks in biosignal processing, several strategies and algorithms can be used. Knowledge-based systems allow prior knowledge about the decision process to be integrated, both by the developer and by self-learning capabilities. For the classification stages in a sleep stage detection framework, three inference strategies were compared regarding their specific strengths: a classical signal processing approach, artificial neural networks and neuro-fuzzy systems. Methodological aspects were assessed to attain optimum performance and maximum transparency for the user. Due to their effective and robust learning behavior, artificial neural networks could be recommended for pattern recognition, while neuro-fuzzy systems performed best for the processing of contextual information.

Reading Time as Evidence for Mental Models in Understanding Physics

NASA Astrophysics Data System (ADS)

Brookes, David T.; Mestre, José; Stine-Morrow, Elizabeth A. L.

2007-11-01

We present results of a reading study that show the usefulness of probing physics students' cognitive processing by measuring reading time. According to contemporary discourse theory, when people read a text, a network of associated inferences is activated to create a mental model. If the reader encounters an idea in the text that conflicts with existing knowledge, the construction of a coherent mental model is disrupted and reading times are prolonged, as measured using a simple self-paced reading paradigm. We used this effect to study how "non-Newtonian" and "Newtonian" students create mental models of conceptual systems in physics as they read texts related to the ideas of Newton's third law, energy, and momentum. We found significant effects of prior knowledge state on patterns of reading time, suggesting that students attempt to actively integrate physics texts with their existing knowledge.

When does prior knowledge disproportionately benefit older adults’ memory?

PubMed Central

Badham, Stephen P.; Hay, Mhairi; Foxon, Natasha; Kaur, Kiran; Maylor, Elizabeth A.

2016-01-01

ABSTRACT Material consistent with knowledge/experience is generally more memorable than material inconsistent with knowledge/experience – an effect that can be more extreme in older adults. Four experiments investigated knowledge effects on memory with young and older adults. Memory for familiar and unfamiliar proverbs (Experiment 1) and for common and uncommon scenes (Experiment 2) showed similar knowledge effects across age groups. Memory for person-consistent and person-neutral actions (Experiment 3) showed a greater benefit of prior knowledge in older adults. For cued recall of related and unrelated word pairs (Experiment 4), older adults benefited more from prior knowledge only when it provided uniquely useful additional information beyond the episodic association itself. The current data and literature suggest that prior knowledge has the age-dissociable mnemonic properties of (1) improving memory for the episodes themselves (age invariant), and (2) providing conceptual information about the tasks/stimuli extrinsically to the actual episodic memory (particularly aiding older adults). PMID:26473767

Is an Illustration Always Worth Ten Thousand Words? Effects of Prior Knowledge, Learning Style and Multimedia Illustrations on Text Comprehension.

ERIC Educational Resources Information Center

Ollerenshaw, Alison; Aidman, Eugene; Kidd, Garry

1997-01-01

This study examined comprehension in four groups of undergraduates under text only, multimedia, and two diagram conditions of text supplementation. Results indicated that effects of text supplementation are mediated by prior knowledge and learning style: multimedia appears more beneficial to surface learners with little prior knowledge and makes…

Effects of Prior Knowledge in Mathematics on Learner-Interface Interactions in a Learning-by-Teaching Intelligent Tutoring System

ERIC Educational Resources Information Center

Bringula, Rex P.; Basa, Roselle S.; Dela Cruz, Cecilio; Rodrigo, Ma. Mercedes T.

2016-01-01

This study attempted to determine the influence of prior knowledge in mathematics of students on learner-interface interactions in a learning-by-teaching intelligent tutoring system. One hundred thirty-nine high school students answered a pretest (i.e., the prior knowledge in mathematics) and a posttest. In between the pretest and posttest, they…

The Effect of the States of Prior Knowledge on Question Answering.

ERIC Educational Resources Information Center

Holmes, Betty C.

A study was conducted to gain insight into the question answering abilities of good and poor readers by comparing how well they answered questions when their prior knowledge was at two different levels (high, low) and in four different states. These states of prior knowledge consisted of the ways in which answers to the questions were stored in…

Learning from Instructional Animations: How Does Prior Knowledge Mediate the Effect of Visual Cues?

ERIC Educational Resources Information Center

Arslan-Ari, I.

2018-01-01

The purpose of this study was to investigate the effects of cueing and prior knowledge on learning and mental effort of students studying an animation with narration. This study employed a 2 (no cueing vs. visual cueing) × 2 (low vs. high prior knowledge) between-subjects factorial design. The results revealed a significant interaction effect…

Integrating quality and safety education into clinical nursing education through a dedicated education unit.

PubMed

Masters, Kelli

2016-03-01

The Institute of Medicine and American Association of Colleges of Nursing are calling for curriculum redesign that prepares nursing students with the requisite knowledge and skills to provide safe, high quality care. The purpose of this project was to improve nursing students' knowledge of quality and safety by integrating Quality and Safety Education for Nurses into clinical nursing education through development of a dedicated education unit. This model, which pairs nursing students with front-line nursing staff for clinical experiences, was implemented on a medical floor in an acute care hospital. Prior to implementation, nurses and students were educated about the dedicated education unit and quality and safety competencies. During each clinical rotation, students collaborated with their nurses on projects related to these competencies. Students' knowledge was assessed using questions related to quality and safety. Students who participated in the dedicated education unit had higher scores than those with traditional clinical rotations. Focus groups were held mid-semester to assess nurses' perceptions of the experience. Five themes emerged from the qualitative data including thirsting for knowledge, building teamwork and collaboration, establishing trust and decreasing anxiety, mirroring organization and time management skills, and evolving confidence in the nursing role. Copyright © 2015 Elsevier Ltd. All rights reserved.

Nurse practitioner and physician assistant students' knowledge, attitudes, and perspectives of chiropractic.

PubMed

Bowden, Briana S; Ball, Lisa

2016-10-01

The purpose of this study was to assess nurse practitioner (NP) and physician assistant (PA) students' views of chiropractic. As the role of these providers progresses in primary care settings, providers' views and knowledge of chiropractic will impact interprofessional collaboration and patient outcomes. Understanding how NP and PA students perceive chiropractic may be beneficial in building integrative health care systems. This descriptive quantitative pilot study utilized a 56-item survey to examine attitudes, knowledge, and perspectives of NP and PA students in their 2nd year of graduate studies. Frequencies and binomial and multinomial logistic regression models were used to examine responses to survey totals. Ninety-two (97%) students completed the survey. There were conflicting results as to whether participants viewed chiropractic as mainstream or alternative. The majority of participants indicated lack of awareness regarding current scientific evidence for chiropractic and indicated a positive interest in learning more about the profession. Students who reported prior experience with chiropractic had higher attitude-positive responses compared to those without experience. Participants were found to have substantial knowledge deficits in relation to chiropractic treatments and scope of practice. The results of this study emphasize the need for increased integrative initiatives and chiropractic exposure in NP and PA education to enhance future interprofessional collaboration in health care.

Dynamic modelling of microRNA regulation during mesenchymal stem cell differentiation.

PubMed

Weber, Michael; Sotoca, Ana M; Kupfer, Peter; Guthke, Reinhard; van Zoelen, Everardus J

2013-11-12

Network inference from gene expression data is a typical approach to reconstruct gene regulatory networks. During chondrogenic differentiation of human mesenchymal stem cells (hMSCs), a complex transcriptional network is active and regulates the temporal differentiation progress. As modulators of transcriptional regulation, microRNAs (miRNAs) play a critical role in stem cell differentiation. Integrated network inference aimes at determining interrelations between miRNAs and mRNAs on the basis of expression data as well as miRNA target predictions. We applied the NetGenerator tool in order to infer an integrated gene regulatory network. Time series experiments were performed to measure mRNA and miRNA abundances of TGF-beta1+BMP2 stimulated hMSCs. Network nodes were identified by analysing temporal expression changes, miRNA target gene predictions, time series correlation and literature knowledge. Network inference was performed using NetGenerator to reconstruct a dynamical regulatory model based on the measured data and prior knowledge. The resulting model is robust against noise and shows an optimal trade-off between fitting precision and inclusion of prior knowledge. It predicts the influence of miRNAs on the expression of chondrogenic marker genes and therefore proposes novel regulatory relations in differentiation control. By analysing the inferred network, we identified a previously unknown regulatory effect of miR-524-5p on the expression of the transcription factor SOX9 and the chondrogenic marker genes COL2A1, ACAN and COL10A1. Genome-wide exploration of miRNA-mRNA regulatory relationships is a reasonable approach to identify miRNAs which have so far not been associated with the investigated differentiation process. The NetGenerator tool is able to identify valid gene regulatory networks on the basis of miRNA and mRNA time series data.

Predicting fifth-grade students' understanding of ecological science concepts with motivational and cognitive variables

NASA Astrophysics Data System (ADS)

Alao, Solomon

The need to identify factors that contribute to students' understanding of ecological concepts has been widely expressed in recent literature. The purpose of this study was to investigate the relationship between fifth grade students' prior knowledge, learning strategies, interest, and learning goals and their conceptual understanding of ecological science concepts. Subject were 72 students from three fifth grade classrooms located in a metropolitan area of the eastern United States. Students completed the goal commitment, interest, and strategy use questionnaire (GISQ), and a knowledge test designed to assess their prior knowledge and conceptual understanding of ecological science concepts. The learning goals scale assessed intentions to try to learn and understand ecological concepts. The interest scale assessed the feeling and value-related valences that students ascribed to science and ecological science concepts. The strategy use scale assessed the use of two cognitive strategies (monitoring and elaboration). The knowledge test assessed students' understanding of ecological concepts (the relationship between living organisms and their environment). Scores on all measures were examined for gender differences; no significant gender differences were observed. The motivational and cognitive variables contributed to students' understanding of ecological concepts. After accounting for interest, learning goals, and strategy use, prior knowledge accounted for 28% of the total variance in conceptual understanding. After accounting for prior knowledge, interest, learning goals, and strategy use explained 7%, 6%, and 4% of the total variance in conceptual understanding, respectively. More importantly, these variables were interrelated to each other and to conceptual understanding. After controlling for prior knowledge, learning goals, and strategy use, interest did not predict the variance in conceptual understanding. After controlling for prior knowledge, interest, and strategy use, learning goals did not predict the variance in conceptual understanding. And, after controlling for prior knowledge, interest, and learning goals, strategy use did not predict the variance in conceptual understanding. Results of this study indicated that prior knowledge, interest, learning goals, and strategy use should be included in theoretical models design to explain and to predict fifth grade students' understanding of ecological concepts. Results of this study further suggested that curriculum developers and science teachers need to take fifth grade students' prior knowledge of ecological concepts, interest in science and ecological concepts; intentions to learn and understand ecological concepts, and use of cognitive strategies into account when designing instructional contexts to support these students' understanding of ecological concepts.

The relation between prior knowledge and students' collaborative discovery learning processes

NASA Astrophysics Data System (ADS)

Gijlers, Hannie; de Jong, Ton

2005-03-01

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 with the environment was logged. Based on students' individual judgments of the truth-value and testability of a series of domain-specific propositions, a detailed description of the knowledge configuration for each dyad was created before they entered the learning environment. Qualitative analyses of two dialogues illustrated that prior knowledge influences the discovery learning processes, and knowledge development in a pair of students. Assessments of student and dyad definitional (domain-specific) knowledge, generic (mathematical and graph) knowledge, and generic (discovery) skills were related to the students' dialogue in different discovery learning processes. Results show that a high level of definitional prior knowledge is positively related to the proportion of communication regarding the interpretation of results. Heterogeneity with respect to generic prior knowledge was positively related to the number of utterances made in the discovery process categories hypotheses generation and experimentation. Results of the qualitative analyses indicated that collaboration between extremely heterogeneous dyads is difficult when the high achiever is not willing to scaffold information and work in the low achiever's zone of proximal development.

Using a numerical model to understand the connection between the ocean and acoustic travel-time measurements.

PubMed

Powell, Brian S; Kerry, Colette G; Cornuelle, Bruce D

2013-10-01

Measurements of acoustic ray travel-times in the ocean provide synoptic integrals of the ocean state between source and receiver. It is known that the ray travel-time is sensitive to variations in the ocean at the transmission time, but the sensitivity of the travel-time to spatial variations in the ocean prior to the acoustic transmission have not been quantified. This study examines the sensitivity of ray travel-time to the temporally and spatially evolving ocean state in the Philippine Sea using the adjoint of a numerical model. A one year series of five day backward integrations of the adjoint model quantify the sensitivity of travel-times to varying dynamics that can alter the travel-time of a 611 km ray by 200 ms. The early evolution of the sensitivities reveals high-mode internal waves that dissipate quickly, leaving the lowest three modes, providing a connection to variations in the internal tide generation prior to the sample time. They are also strongly sensitive to advective effects that alter density along the ray path. These sensitivities reveal how travel-time measurements are affected by both nearby and distant waters. Temporal nonlinearity of the sensitivities suggests that prior knowledge of the ocean state is necessary to exploit the travel-time observations.

The Influence of Self-Regulated Learning and Prior Knowledge on Knowledge Acquisition in Computer-Based Learning Environments

ERIC Educational Resources Information Center

Bernacki, Matthew

2010-01-01

This study examined how learners construct textbase and situation model knowledge in hypertext computer-based learning environments (CBLEs) and documented the influence of specific self-regulated learning (SRL) tactics, prior knowledge, and characteristics of the learner on posttest knowledge scores from exposure to a hypertext. A sample of 160…

Unified approach for extrapolation and bridging of adult information in early-phase dose-finding paediatric studies.

PubMed

Petit, Caroline; Samson, Adeline; Morita, Satoshi; Ursino, Moreno; Guedj, Jérémie; Jullien, Vincent; Comets, Emmanuelle; Zohar, Sarah

2018-06-01

The number of trials conducted and the number of patients per trial are typically small in paediatric clinical studies. This is due to ethical constraints and the complexity of the medical process for treating children. While incorporating prior knowledge from adults may be extremely valuable, this must be done carefully. In this paper, we propose a unified method for designing and analysing dose-finding trials in paediatrics, while bridging information from adults. The dose-range is calculated under three extrapolation options, linear, allometry and maturation adjustment, using adult pharmacokinetic data. To do this, it is assumed that target exposures are the same in both populations. The working model and prior distribution parameters of the dose-toxicity and dose-efficacy relationships are obtained using early-phase adult toxicity and efficacy data at several dose levels. Priors are integrated into the dose-finding process through Bayesian model selection or adaptive priors. This calibrates the model to adjust for misspecification, if the adult and pediatric data are very different. We performed a simulation study which indicates that incorporating prior adult information in this way may improve dose selection in children.

An Ensemble Approach to Building Mercer Kernels with Prior Information

NASA Technical Reports Server (NTRS)

Srivastava, Ashok N.; Schumann, Johann; Fischer, Bernd

2005-01-01

This paper presents a new methodology for automatic knowledge driven data mining based on the theory of Mercer Kernels, which are highly nonlinear symmetric positive definite mappings from the original image space to a very high, possibly dimensional feature space. we describe a new method called Mixture Density Mercer Kernels to learn kernel function directly from data, rather than using pre-defined kernels. These data adaptive kernels can encode prior knowledge in the kernel using a Bayesian formulation, thus allowing for physical information to be encoded in the model. Specifically, we demonstrate the use of the algorithm in situations with extremely small samples of data. We compare the results with existing algorithms on data from the Sloan Digital Sky Survey (SDSS) and demonstrate the method's superior performance against standard methods. The code for these experiments has been generated with the AUTOBAYES tool, which automatically generates efficient and documented C/C++ code from abstract statistical model specifications. The core of the system is a schema library which contains templates for learning and knowledge discovery algorithms like different versions of EM, or numeric optimization methods like conjugate gradient methods. The template instantiation is supported by symbolic-algebraic computations, which allows AUTOBAYES to find closed-form solutions and, where possible, to integrate them into the code.

Chemical-gene interaction networks and causal reasoning for ...

EPA Pesticide Factsheets

Evaluating the potential human health and ecological risks associated with exposures to complex chemical mixtures in the environment is one of the main challenges of chemical safety assessment and environmental protection. There is a need for approaches that can help to integrate chemical monitoring and biological effects data to evaluate risks associated with chemicals present in the environment. Here, we used prior knowledge about chemical-gene interactions to develop a knowledge assembly model for detected chemicals at five locations near the North Branch and Chisago wastewater treatment plants (WWTP) in the St. Croix River Basin, MN and WI. The assembly model was used to generate hypotheses about the biological impacts of the chemicals at each location. The hypotheses were tested using empirical hepatic gene expression data from fathead minnows exposed for 12 d at each location. Empirical gene expression data were also mapped to the assembly models to evaluate the likelihood of a chemical contributing to the observed biological responses using richness and concordance statistics. The prior knowledge approach was able predict the observed biological pathways impacted at one site but not the other. Atrazine was identified as a potential contributor to the observed gene expression responses at a location upstream of the North Branch WTTP. Four chemicals were identified as contributors to the observed biological responses at the effluent and downstream o

Technology-Enhanced Learning in Science (TELS)

NASA Astrophysics Data System (ADS)

Linn, Marcia

2006-12-01

The overall research question addressed by the NSF-funded echnologyEnhanced Learning in Science (TELS) Center is whether interactive scientific visualizations embedded in high quality instructional units can be used to increase pre-college student learning in science. The research draws on the knowledge integration framework to guide the design of instructional modules, professional development activities, and assessment activities. This talk reports on results from the first year where 50 teachers taught one of the 12 TELS modules in over 200 classes in 16 diverse schools. Assessments scored with the knowledge integration rubric showed that students made progress in learning complex physics topics such as electricity, mechanics, and thermodynamics. Teachers encountered primarily technological obstacles that the research team was able to address prior to implementation. Powerful scientific visualizations required extensive instructional supports to communicate to students. Currently, TELS is refining the modules, professional development, and assessments based on evidence from the first year. Preliminary design principles intended to help research teams build on the findings will be presented for audience feedback and discussion.

On the way toward systems biology of Aspergillus fumigatus infection.

PubMed

Albrecht, Daniela; Kniemeyer, Olaf; Mech, Franziska; Gunzer, Matthias; Brakhage, Axel; Guthke, Reinhard

2011-06-01

Pathogenicity of Aspergillus fumigatus is multifactorial. Thus, global studies are essential for the understanding of the infection process. Therefore, a data warehouse was established where genome sequence, transcriptome and proteome data are stored. These data are analyzed for the elucidation of virulence determinants. The data analysis workflow starts with pre-processing including imputing of missing values and normalization. Last step is the identification of differentially expressed genes/proteins as interesting candidates for further analysis, in particular for functional categorization and correlation studies. Sequence data and other prior knowledge extracted from databases are integrated to support the inference of gene regulatory networks associated with pathogenicity. This knowledge-assisted data analysis aims at establishing mathematical models with predictive strength to assist further experimental work. Recently, first steps were done to extend the integrative data analysis and computational modeling by evaluating spatio-temporal data (movies) that monitor interactions of A. fumigatus morphotypes (e.g. conidia) with host immune cells. Copyright © 2011 Elsevier GmbH. All rights reserved.

Software for Probabilistic Risk Reduction

NASA Technical Reports Server (NTRS)

Hensley, Scott; Michel, Thierry; Madsen, Soren; Chapin, Elaine; Rodriguez, Ernesto

2004-01-01

A computer program implements a methodology, denoted probabilistic risk reduction, that is intended to aid in planning the development of complex software and/or hardware systems. This methodology integrates two complementary prior methodologies: (1) that of probabilistic risk assessment and (2) a risk-based planning methodology, implemented in a prior computer program known as Defect Detection and Prevention (DDP), in which multiple requirements and the beneficial effects of risk-mitigation actions are taken into account. The present methodology and the software are able to accommodate both process knowledge (notably of the efficacy of development practices) and product knowledge (notably of the logical structure of a system, the development of which one seeks to plan). Estimates of the costs and benefits of a planned development can be derived. Functional and non-functional aspects of software can be taken into account, and trades made among them. It becomes possible to optimize the planning process in the sense that it becomes possible to select the best suite of process steps and design choices to maximize the expectation of success while remaining within budget.

Using the Biodatamation(TM) strategy to learn introductory college biology: Value-added effects on selected students' conceptual understanding and conceptual integration of the processes of photosynthesis and cellular respiration

NASA Astrophysics Data System (ADS)

Reuter, Jewel Jurovich

The purpose of this exploratory research was to study how students learn photosynthesis and cellular respiration and to determine the value added to the student's learning by each of the three technology-scaffolded learning strategy components (animated concept presentations and WebQuest-style activities, data collection, and student-constructed animations) of the BioDatamation(TM) (BDM) Program. BDM learning strategies utilized the Theory of Interacting Visual Fields(TM) (TIVF) (Reuter & Wandersee, 2002a, 2002b; 2003a, 2003b) which holds that meaningful knowledge is hierarchically constructed using the past, present, and future visual fields, with visual metacognitive components that are derived from the principles of Visual Behavior (Jones, 1995), Human Constructivist Theory (Mintzes & Wandersee, 1998a), and Visual Information Design Theory (Tufte, 1990, 1997, 2001). Student alternative conceptions of photosynthesis and cellular respiration were determined by the item analysis of 263,267 Biology Advanced Placement Examinations and were used to develop the BDM instructional strategy and interview questions. The subjects were 24 undergraduate students of high and low biology prior knowledge enrolled in an introductory-level General Biology course at a major research university in the Deep South. Fifteen participants received BDM instruction which included original and innovative learning materials and laboratories in 6 phases; 8 of the 15 participants were the subject of in depth, extended individual analysis. The other 9 participants received traditional, non-BDM instruction. Interviews which included participants' creation of concept maps and visual field diagrams were conducted after each phase. Various content analyses, including Chi's Verbal Analysis and quantitizing/qualitizing were used for data analysis. The total value added to integrative knowledge during BDM instruction with the three visual fields was an average increase of 56% for cellular respiration and 62% increase for photosynthesis knowledge, improved long-term memory of concepts, and enhanced biological literacy to the multidimensional level, as determined by the BSCS literacy model. WebQuest-style activities and data collection provided for animated prior knowledge in the past visual field, and detailed content knowledge construction in the present visual field. During student construction of animated presentations, layering required participants to think by rearranging words and images for improved hierarchical organization of knowledge with real-life applications.

Does prior domain-specific content knowledge influence students' recall of arguments surrounding interdisciplinary topics?

PubMed

Schmidt, Hiemke K; Rothgangel, Martin; Grube, Dietmar

2017-12-01

Awareness of various arguments can help interactants present opinions, stress points, and build counterarguments during discussions. At school, some topics are taught in a way that students learn to accumulate knowledge and gather arguments, and later employ them during debates. Prior knowledge may facilitate recalling information on well structured, fact-based topics, but does it facilitate recalling arguments during discussions on complex, interdisciplinary topics? We assessed the prior knowledge in domains related to a bioethical topic of 277 students from Germany (approximately 15 years old), their interest in the topic, and their general knowledge. The students read a text with arguments for and against prenatal diagnostics and tried to recall the arguments one week later and again six weeks later. Prior knowledge in various domains related to the topic individually and separately helped students recall the arguments. These relationships were independent of students' interest in the topic and their general knowledge. Copyright © 2017 The Foundation for Professionals in Services for Adolescents. Published by Elsevier Ltd. All rights reserved.

Impact of a low-intensity pedagogical model for integrating MedlinePlus exercises into middle school nutrition lessons.

PubMed

Rankins, Jenice; Kirksey, Otis; Bogan, Yolanda; Brown, Betty

2007-10-01

The research developed and pilot-tested MedlinePlus exercises in a diet-related chronic disease prevention (DCDP) middle school lesson unit called "Live." MedlinePlus exercises were jointly developed by two middle school family and consumer sciences (FCS) teachers and integrated into the "Live" DCDP lesson unit. FCS classes (n = 4) who had participated in a prior "Live" study were chosen to pilot-test the MedlinePlus-supplemented exercises. Evaluation measures included student satisfaction (assessed using an 8-item pre- and posttest questionnaire), knowledge gained, and attitudinal changes (assessed with an abridged version of a previously developed "Live" questionnaire). Statistical analyses were performed using SPSS. Of 62 total study participants, 56 (92.3%) said that they were either "somewhat" or "clearly": (a) more likely to use MedlinePlus as a future source for answering questions about their personal health and (b) more knowledgeable about how eating habits can help prevent disease. Selected parameters were improved for nutrition knowledge (P < 0.01) and attitudes (P < 0.01) related to healthy eating. MedlinePlus has good potential for efficiently communicating trustworthy diet-related disease-prevention behaviors to adolescents in an existing classroom curriculum.

Integration of Temporal and Ordinal Information During Serial Interception Sequence Learning

PubMed Central

Gobel, Eric W.; Sanchez, Daniel J.; Reber, Paul J.

2011-01-01

The expression of expert motor skills typically involves learning to perform a precisely timed sequence of movements (e.g., language production, music performance, athletic skills). Research examining incidental sequence learning has previously relied on a perceptually-cued task that gives participants exposure to repeating motor sequences but does not require timing of responses for accuracy. Using a novel perceptual-motor sequence learning task, learning a precisely timed cued sequence of motor actions is shown to occur without explicit instruction. Participants learned a repeating sequence through practice and showed sequence-specific knowledge via a performance decrement when switched to an unfamiliar sequence. In a second experiment, the integration of representation of action order and timing sequence knowledge was examined. When either action order or timing sequence information was selectively disrupted, performance was reduced to levels similar to completely novel sequences. Unlike prior sequence-learning research that has found timing information to be secondary to learning action sequences, when the task demands require accurate action and timing information, an integrated representation of these types of information is acquired. These results provide the first evidence for incidental learning of fully integrated action and timing sequence information in the absence of an independent representation of action order, and suggest that this integrative mechanism may play a material role in the acquisition of complex motor skills. PMID:21417511

Electrophysiological evidence for Audio-visuo-lingual speech integration.

PubMed

Treille, Avril; Vilain, Coriandre; Schwartz, Jean-Luc; Hueber, Thomas; Sato, Marc

2018-01-31

Recent neurophysiological studies demonstrate that audio-visual speech integration partly operates through temporal expectations and speech-specific predictions. From these results, one common view is that the binding of auditory and visual, lipread, speech cues relies on their joint probability and prior associative audio-visual experience. The present EEG study examined whether visual tongue movements integrate with relevant speech sounds, despite little associative audio-visual experience between the two modalities. A second objective was to determine possible similarities and differences of audio-visual speech integration between unusual audio-visuo-lingual and classical audio-visuo-labial modalities. To this aim, participants were presented with auditory, visual, and audio-visual isolated syllables, with the visual presentation related to either a sagittal view of the tongue movements or a facial view of the lip movements of a speaker, with lingual and facial movements previously recorded by an ultrasound imaging system and a video camera. In line with previous EEG studies, our results revealed an amplitude decrease and a latency facilitation of P2 auditory evoked potentials in both audio-visual-lingual and audio-visuo-labial conditions compared to the sum of unimodal conditions. These results argue against the view that auditory and visual speech cues solely integrate based on prior associative audio-visual perceptual experience. Rather, they suggest that dynamic and phonetic informational cues are sharable across sensory modalities, possibly through a cross-modal transfer of implicit articulatory motor knowledge. Copyright © 2017 Elsevier Ltd. All rights reserved.

The iSCREEN Electronic Diabetes Dashboard: A Tool to Improve Knowledge and Implementation of Pediatric Clinical Practice Guidelines.

PubMed

Zahanova, Stacy; Tsouka, Alexandra; Palmert, Mark R; Mahmud, Farid H

2017-12-01

Clinical practice guidelines (CPG) provide evidence-based recommendations for patient care but may not be optimally applied in clinical settings. As a pilot study, we evaluated the impact of a computerized, point-of-care decision support system (CDSS) on guideline knowledge and adherence in our diabetes clinic. iSCREEN, a CDSS, integrated with a province-wide electronic health record, was designed based on the Canadian Diabetes Association 2013 Clinical Practice Guidelines for the Prevention and Management of Diabetes in Canada. Evaluation data were gathered by retrospective chart review and clinician questionnaire prior to and after implementation of iSCREEN. Records of patients with type 1 diabetes, 14 to 18 years of age, were assessed for appropriate screening for complications and comorbidities. To assess guideline adherence, 50 charts were reviewed at 2 time periods (25 before and 25 after launch of iSCREEN). Results revealed improved frequency of appropriate screening for diabetic nephropathy (p=0.03) and retinopathy (p=0.04), accompanied by a decrease in under- and overscreening for these outcomes. To assess guideline knowledge, 58 surveys were collected (31 prior to and 27 after the launch of iSCREEN) from care providers in the field of pediatric diabetes. There was a trend toward improved guideline knowledge in all team members (p=0.06). Implementation of a de novo CDSS was associated with improved rates of appropriate screening for diabetes-related complications. A trend toward improvement in health professionals' knowledge of the guidelines was also observed. Evaluation of this point-of-care computerized decision support tool suggests that it may facilitate diabetes care by optimizing complication screening and CPG knowledge, with the potential for broader implementation. Copyright © 2017 Diabetes Canada. Published by Elsevier Inc. All rights reserved.

Contribution of prior semantic knowledge to new episodic learning in amnesia.

PubMed

Kan, Irene P; Alexander, Michael P; Verfaellie, Mieke

2009-05-01

We evaluated whether prior semantic knowledge would enhance episodic learning in amnesia. Subjects studied prices that are either congruent or incongruent with prior price knowledge for grocery and household items and then performed a forced-choice recognition test for the studied prices. Consistent with a previous report, healthy controls' performance was enhanced by price knowledge congruency; however, only a subset of amnesic patients experienced the same benefit. Whereas patients with relatively intact semantic systems, as measured by an anatomical measure (i.e., lesion involvement of anterior and lateral temporal lobes), experienced a significant congruency benefit, patients with compromised semantic systems did not experience a congruency benefit. Our findings suggest that when prior knowledge structures are intact, they can support acquisition of new episodic information by providing frameworks into which such information can be incorporated.

Promoting Shifts in Preservice Science Teachers' Thinking through Teaching and Action Research in Informal Science Settings

NASA Astrophysics Data System (ADS)

Wallace, Carolyn S.

2013-08-01

The purpose of this study was to investigate the influence of an integrated experiential learning and action research project on preservice science teachers' developing ideas about science teaching, learning, and action research itself. The qualitative, interpretive study examined the action research of 10 master's degree students who were involved in service learning with children in informal education settings. Results indicated that all of the participants enhanced their knowledge of children as diverse learners and the importance of prior knowledge in science learning. In-depth case studies for three of the participants indicated that two developed deeper understandings of science learners and learning. However, one participant was resistant to learning and gained more limited understandings.

WE-G-207-07: Iterative CT Shading Correction Method with No Prior Information

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

Wu, P; Mao, T; Niu, T

2015-06-15

Purpose: Shading artifacts are caused by scatter contamination, beam hardening effects and other non-ideal imaging condition. Our Purpose is to propose a novel and general correction framework to eliminate low-frequency shading artifacts in CT imaging (e.g., cone-beam CT, low-kVp CT) without relying on prior information. Methods: Our method applies general knowledge of the relatively uniform CT number distribution in one tissue component. Image segmentation is applied to construct template image where each structure is filled with the same CT number of that specific tissue. By subtracting the ideal template from CT image, the residual from various error sources are generated.more » Since the forward projection is an integration process, the non-continuous low-frequency shading artifacts in the image become continuous and low-frequency signals in the line integral. Residual image is thus forward projected and its line integral is filtered using Savitzky-Golay filter to estimate the error. A compensation map is reconstructed on the error using standard FDK algorithm and added to the original image to obtain the shading corrected one. Since the segmentation is not accurate on shaded CT image, the proposed scheme is iterated until the variation of residual image is minimized. Results: The proposed method is evaluated on a Catphan600 phantom, a pelvic patient and a CT angiography scan for carotid artery assessment. Compared to the one without correction, our method reduces the overall CT number error from >200 HU to be <35 HU and increases the spatial uniformity by a factor of 1.4. Conclusion: We propose an effective iterative algorithm for shading correction in CT imaging. Being different from existing algorithms, our method is only assisted by general anatomical and physical information in CT imaging without relying on prior knowledge. Our method is thus practical and attractive as a general solution to CT shading correction. This work is supported by the National Science Foundation of China (NSFC Grant No. 81201091), National High Technology Research and Development Program of China (863 program, Grant No. 2015AA020917), and Fund Project for Excellent Abroad Scholar Personnel in Science and Technology.« less

PANDORA: keyword-based analysis of protein sets by integration of annotation sources.

PubMed

Kaplan, Noam; Vaaknin, Avishay; Linial, Michal

2003-10-01

Recent advances in high-throughput methods and the application of computational tools for automatic classification of proteins have made it possible to carry out large-scale proteomic analyses. Biological analysis and interpretation of sets of proteins is a time-consuming undertaking carried out manually by experts. We have developed PANDORA (Protein ANnotation Diagram ORiented Analysis), a web-based tool that provides an automatic representation of the biological knowledge associated with any set of proteins. PANDORA uses a unique approach of keyword-based graphical analysis that focuses on detecting subsets of proteins that share unique biological properties and the intersections of such sets. PANDORA currently supports SwissProt keywords, NCBI Taxonomy, InterPro entries and the hierarchical classification terms from ENZYME, SCOP and GO databases. The integrated study of several annotation sources simultaneously allows a representation of biological relations of structure, function, cellular location, taxonomy, domains and motifs. PANDORA is also integrated into the ProtoNet system, thus allowing testing thousands of automatically generated clusters. We illustrate how PANDORA enhances the biological understanding of large, non-uniform sets of proteins originating from experimental and computational sources, without the need for prior biological knowledge on individual proteins.

Toward critical spatial thinking in the social sciences and humanities.

PubMed

Goodchild, Michael F; Janelle, Donald G

2010-02-01

The integration of geographically referenced information into the conceptual frameworks and applied uses of the social sciences and humanities has been an ongoing process over the past few centuries. It has gained momentum in recent decades with advances in technologies for computation and visualization and with the arrival of new data sources. This article begins with an overview of this transition, and argues that the spatial integration of information resources and the cross-disciplinary sharing of analysis and representation methodologies are important forces for the integration of scientific and artistic expression, and that they draw on core concepts in spatial (and spatio-temporal) thinking. We do not suggest that this is akin to prior concepts of unified knowledge systems, but we do maintain that the boundaries to knowledge transfer are disintegrating and that our abilities in problem solving for purposes of artistic expression and scientific development are enhanced through spatial perspectives. Moreover, approaches to education at all levels must recognize the need to impart proficiency in the critical and efficient application of these fundamental spatial concepts, if students and researchers are to make use of expanding access to a broadening range of spatialized information and data processing technologies.

Assessment of knowledge transfer in the context of biomechanics

NASA Astrophysics Data System (ADS)

Hutchison, Randolph E.

The dynamic act of knowledge transfer, or the connection of a student's prior knowledge to features of a new problem, could be considered one of the primary goals of education. Yet studies highlight more instances of failure than success. This dissertation focuses on how knowledge transfer takes place during individual problem solving, in classroom settings and during group work. Through the lens of dynamic transfer, or how students connect prior knowledge to problem features, this qualitative study focuses on a methodology to assess transfer in the context of biomechanics. The first phase of this work investigates how a pedagogical technique based on situated cognition theory affects students' ability to transfer knowledge gained in a biomechanics class to later experiences both in and out of the classroom. A post-class focus group examined events the students remembered from the class, what they learned from them, and how they connected them to later relevant experiences inside and outside the classroom. These results were triangulated with conceptual gains evaluated through concept inventories and pre- and post- content tests. Based on these results, the next two phases of the project take a more in-depth look at dynamic knowledge transfer during independent problem-solving and group project interactions, respectively. By categorizing prior knowledge (Source Tools), problem features (Target Tools) and the connections between them, results from the second phase of this study showed that within individual problem solving, source tools were almost exclusively derived from "propagated sources," i.e. those based on an authoritative source. This differs from findings in the third phase of the project, in which a mixture of "propagated" sources and "fabricated" sources, i.e. those based on student experiences, were identified within the group project work. This methodology is effective at assessing knowledge transfer in the context of biomechanics through evidence of the ability to identify differing patterns of how different students apply prior knowledge and make new connections between prior knowledge and current problem features in different learning situations. Implications for the use of this methodology include providing insight into not only students' prior knowledge, but also how they connect this prior knowledge to problem features (i.e. dynamic knowledge transfer). It also allows the identification of instances in which external input from other students or the instructor prompted knowledge transfer to take place. The use of this dynamic knowledge transfer lens allows the addressing of gaps in student understanding, and permits further investigations of techniques that increase instances of successful knowledge transfer.

Scalable Learning for Geostatistics and Speaker Recognition

DTIC Science & Technology

2011-01-01

of prior knowledge of the model or due to improved robustness requirements). Both these methods have their own advantages and disadvantages. The use...application. If the data is well-correlated and low-dimensional, any prior knowledge available on the data can be used to build a parametric model. In the...absence of prior knowledge , non-parametric methods can be used. If the data is high-dimensional, PCA based dimensionality reduction is often the first

Asthma in the community: Designing instruction to help students explore scientific dilemmas that impact their lives

NASA Astrophysics Data System (ADS)

Tate, Erika Dawn

School science instruction that connects to students' diverse home, cultural, or linguistic experiences can encourage lifelong participation in the scientific dilemmas that impact students' lives. This dissertation seeks effective ways to support high school students as they learn complex science topics and use their knowledge to transform their personal and community environments. Applying the knowledge integration perspective, I collaborated with education, science, and community partners to design a technology enhanced science module, Improving Your Community's Asthma Problem. This exemplar community science curriculum afforded students the opportunity to (a) investigate a local community health issue, (b) interact with relevant evidence related to physiology, clinical management, and environmental risks, and (c) construct an integrated understanding of the asthma problem in their community. To identify effective instructional scaffolds that engage students in the knowledge integration process and prepare them to participate in community science, I conducted 2 years of research that included 5 schools, 10 teachers, and over 500 students. This dissertation reports on four studies that analyzed student responses on pre-, post-, and embedded assessments. Researching across four design stages, the iterative design study investigated how to best embed the visualizations of the physiological processes breathing, asthma attack, and the allergic immune response in an inquiry activity and informed evidence-based revisions to the module. The evaluation study investigated the impact of this revised Asthma module across multiple classrooms and differences in students' prior knowledge. Combining evidence of student learning from the iterative and evaluation studies with classroom observations and teacher interviews, the longitudinal study explored the impact of teacher practices on student learning in years 1 and 2. In the final chapter, I studied how the Asthma module and students' local community influenced students as they integrated their ideas related to perspectives, evidence use, the consideration of tradeoffs, and localization to construct explanations and decision justifications regarding their community's asthma problem. In the end, this dissertation offers evidence that informs the future design of community science instruction that successfully engages students in the knowledge integration process and has implications for creating multiple opportunities for students to meaningfully participate in community science.

Learning stoichiometry: A comparison of text and multimedia instructional formats

NASA Astrophysics Data System (ADS)

Evans, Karen L.

Even after multiple instructional opportunities, first year college chemistry students are often unable to apply stoichiometry knowledge in equilibrium and acid-base chemistry problem solving. Cognitive research findings suggest that for learning to be meaningful, learners need to actively construct their own knowledge by integrating new information into, and reorganizing, their prior understandings. Scaffolded inquiry in which facts, procedures, and principles are introduced as needed within the context of authentic problem solving may provide the practice and encoding opportunities necessary for construction of a memorable and usable knowledge base. The dynamic and interactive capabilities of online technology may facilitate stoichiometry instruction that promotes this meaningful learning. Entering college freshmen were randomly assigned to either a technology-rich or text-only set of cognitively informed stoichiometry review materials. Analysis of posttest scores revealed a significant but small difference in the performance of the two treatment groups, with the technology-rich group having the advantage. Both SAT and gender, however, explained more of the variability in the scores. Analysis of the posttest scores from the technology-rich treatment group revealed that the degree of interaction with the Virtual Lab simulation was significantly related to posttest performance and subsumed any effect of prior knowledge as measured by SAT scores. Future users of the online course should be encouraged to engage with the problem-solving opportunities provided by the Virtual Lab simulation through either explicit instruction and/or implementation of some level of program control within the course's navigational features.

SU-E-J-71: Spatially Preserving Prior Knowledge-Based Treatment Planning

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

Wang, H; Xing, L

2015-06-15

Purpose: Prior knowledge-based treatment planning is impeded by the use of a single dose volume histogram (DVH) curve. Critical spatial information is lost from collapsing the dose distribution into a histogram. Even similar patients possess geometric variations that becomes inaccessible in the form of a single DVH. We propose a simple prior knowledge-based planning scheme that extracts features from prior dose distribution while still preserving the spatial information. Methods: A prior patient plan is not used as a mere starting point for a new patient but rather stopping criteria are constructed. Each structure from the prior patient is partitioned intomore » multiple shells. For instance, the PTV is partitioned into an inner, middle, and outer shell. Prior dose statistics are then extracted for each shell and translated into the appropriate Dmin and Dmax parameters for the new patient. Results: The partitioned dose information from a prior case has been applied onto 14 2-D prostate cases. Using prior case yielded final DVHs that was comparable to manual planning, even though the DVH for the prior case was different from the DVH for the 14 cases. Solely using a single DVH for the entire organ was also performed for comparison but showed a much poorer performance. Different ways of translating the prior dose statistics into parameters for the new patient was also tested. Conclusion: Prior knowledge-based treatment planning need to salvage the spatial information without transforming the patients on a voxel to voxel basis. An efficient balance between the anatomy and dose domain is gained through partitioning the organs into multiple shells. The use of prior knowledge not only serves as a starting point for a new case but the information extracted from the partitioned shells are also translated into stopping criteria for the optimization problem at hand.« less

The Practice Integration Profile: Rationale, development, method, and research.

PubMed

Macchi, C R; Kessler, Rodger; Auxier, Andrea; Hitt, Juvena R; Mullin, Daniel; van Eeghen, Constance; Littenberg, Benjamin

2016-12-01

Insufficient knowledge exists regarding how to measure the presence and degree of integrated care. Prior estimates of integration levels are neither grounded in theory nor psychometrically validated. They provide scant guidance to inform improvement activities, compare integration efforts, discriminate among practices by degree of integration, measure the effect of integration on quadruple aim outcomes, or address the needs of clinicians, regulators, and policymakers seeking new models of health care delivery and funding. We describe the development of the Practice Integration Profile (PIP), a novel instrument designed to measure levels of integrated behavioral health care within a primary care clinic. The PIP draws upon the Agency for Health care Research & Quality's (AHRQ) Lexicon of Collaborative Care which provides theoretic justification for a paradigm case of collaborative care. We used the key clauses of the Lexicon to derive domains of integration and generate measures corresponding to those key clauses. After reviewing currently used methods for identifying collaborative care, or integration, and identifying the need to improve on them, we describe a national collaboration to describe and evaluate the PIP. We also describe its potential use in practice improvement, research, responsiveness to multiple stakeholder needs, and other future directions. (PsycINFO Database Record (c) 2016 APA, all rights reserved).

Development of a NASA Integrated Technical Workforce Career Development Model Entitled Requisite Occupation Competencies and Knowledge -- the ROCK

NASA Technical Reports Server (NTRS)

Menrad, Robert J.; Larson, Wiley J.

2008-01-01

This paper shares the findings of NASA's Integrated Learning and Development Program (ILDP) in its effort to reinvigorate the HANDS-ON practice of space systems engineering and project/program management through focused coursework, training opportunities, on-the job learning and special assignments. Prior to March 2005, NASA responsibility for technical workforce development (the program/project manager, systems engineering, discipline engineering, discipline engineering and associated communities) was executed by two parallel organizations. In March 2005 these organizations merged. The resulting program-ILDP-was chartered to implement an integrated competency-based development model capable of enhancing NASA's technical workforce performance as they face the complex challenges of Earth science, space science, aeronautics and human spaceflight missions. Results developed in collaboration with NASA Field Centers are reported on. This work led to definition of the agency's first integrated technical workforce development model known as the Requisite Occupation Competence and Knowledge (the ROCK). Critical processes and products are presented including: 'validation' techniques to guide model development, the Design-A-CUrriculuM (DACUM) process, and creation of the agency's first systems engineering body-of-knowledge. Findings were validated via nine focus groups from industry and government, validated with over 17 space-related organizations, at an estimated cost exceeding $300,000 (US). Masters-level programs and training programs have evolved to address the needs of these practitioner communities based upon these results. The ROCK reintroduced rigor and depth to the practitioner's development in these critical disciplines enabling their ability to take mission concepts from imagination to reality.

Virtual reality training improves students' knowledge structures of medical concepts.

PubMed

Stevens, Susan M; Goldsmith, Timothy E; Summers, Kenneth L; Sherstyuk, Andrei; Kihmm, Kathleen; Holten, James R; Davis, Christopher; Speitel, Daniel; Maris, Christina; Stewart, Randall; Wilks, David; Saland, Linda; Wax, Diane; Panaiotis; Saiki, Stanley; Alverson, Dale; Caudell, Thomas P

2005-01-01

Virtual environments can provide training that is difficult to achieve under normal circumstances. Medical students can work on high-risk cases in a realistic, time-critical environment, where students practice skills in a cognitively demanding and emotionally compelling situation. Research from cognitive science has shown that as students acquire domain expertise, their semantic organization of core domain concepts become more similar to those of an expert's. In the current study, we hypothesized that students' knowledge structures would become more expert-like as a result of their diagnosing and treating a patient experiencing a hematoma within a virtual environment. Forty-eight medical students diagnosed and treated a hematoma case within a fully immersed virtual environment. Student's semantic organization of 25 case-related concepts was assessed prior to and after training. Students' knowledge structures became more integrated and similar to an expert knowledge structure of the concepts as a result of the learning experience. The methods used here for eliciting, representing, and evaluating knowledge structures offer a sensitive and objective means for evaluating student learning in virtual environments and medical simulations.

Comfort and experience with online learning: trends over nine years and associations with knowledge.

PubMed

Cook, David A; Thompson, Warren G

2014-07-01

Some evidence suggests that attitude toward computer-based instruction is an important determinant of success in online learning. We sought to determine how comfort using computers and perceptions of prior online learning experiences have changed over the past decade, and how these associate with learning outcomes. Each year from 2003-2011 we conducted a prospective trial of online learning. As part of each year's study, we asked medicine residents about their comfort using computers and if their previous experiences with online learning were favorable. We assessed knowledge using a multiple-choice test. We used regression to analyze associations and changes over time. 371 internal medicine and family medicine residents participated. Neither comfort with computers nor perceptions of prior online learning experiences showed a significant change across years (p > 0.61), with mean comfort rating 3.96 (maximum 5 = very comfortable) and mean experience rating 4.42 (maximum 6 = strongly agree [favorable]). Comfort showed no significant association with knowledge scores (p = 0.39) but perceptions of prior experiences did, with a 1.56% rise in knowledge score for a 1-point rise in experience score (p = 0.02). Correlations among comfort, perceptions of prior experiences, and number of prior experiences were all small and not statistically significant. Comfort with computers and perceptions of prior experience with online learning remained stable over nine years. Prior good experiences (but not comfort with computers) demonstrated a modest association with knowledge outcomes, suggesting that prior course satisfaction may influence subsequent learning.

7 CFR 275.2 - State agency responsibilities.

Code of Federal Regulations, 2014 CFR

2014-01-01

...: (i) Data collection through management evaluation (ME) reviews and quality control (QC) reviews; (ii... knowledge of either the household or the decision under review. Where there is prior knowledge, the reviewer must disqualify her/himself. Prior knowledge is defined as having: (1) Taken any part in the decision...

7 CFR 275.2 - State agency responsibilities.

Code of Federal Regulations, 2011 CFR

2011-01-01

...: (i) Data collection through management evaluation (ME) reviews and quality control (QC) reviews; (ii... knowledge of either the household or the decision under review. Where there is prior knowledge, the reviewer must disqualify her/himself. Prior knowledge is defined as having: (1) Taken any part in the decision...

7 CFR 275.2 - State agency responsibilities.

Code of Federal Regulations, 2013 CFR

2013-01-01

...: (i) Data collection through management evaluation (ME) reviews and quality control (QC) reviews; (ii... knowledge of either the household or the decision under review. Where there is prior knowledge, the reviewer must disqualify her/himself. Prior knowledge is defined as having: (1) Taken any part in the decision...

7 CFR 275.2 - State agency responsibilities.

Code of Federal Regulations, 2012 CFR

2012-01-01

...: (i) Data collection through management evaluation (ME) reviews and quality control (QC) reviews; (ii... knowledge of either the household or the decision under review. Where there is prior knowledge, the reviewer must disqualify her/himself. Prior knowledge is defined as having: (1) Taken any part in the decision...

7 CFR 275.2 - State agency responsibilities.

Code of Federal Regulations, 2010 CFR

2010-01-01

...: (i) Data collection through management evaluation (ME) reviews and quality control (QC) reviews; (ii... knowledge of either the household or the decision under review. Where there is prior knowledge, the reviewer must disqualify her/himself. Prior knowledge is defined as having: (1) Taken any part in the decision...

A Knowledge-Based Arrangement of Prototypical Neural Representation Prior to Experience Contributes to Selectivity in Upcoming Knowledge Acquisition.

PubMed

Kurashige, Hiroki; Yamashita, Yuichi; Hanakawa, Takashi; Honda, Manabu

2018-01-01

Knowledge acquisition is a process in which one actively selects a piece of information from the environment and assimilates it with prior knowledge. However, little is known about the neural mechanism underlying selectivity in knowledge acquisition. Here we executed a 2-day human experiment to investigate the involvement of characteristic spontaneous activity resembling a so-called "preplay" in selectivity in sentence comprehension, an instance of knowledge acquisition. On day 1, we presented 10 sentences (prior sentences) that were difficult to understand on their own. On the following day, we first measured the resting-state functional magnetic resonance imaging (fMRI). Then, we administered a sentence comprehension task using 20 new sentences (posterior sentences). The posterior sentences were also difficult to understand on their own, but some could be associated with prior sentences to facilitate their understanding. Next, we measured the posterior sentence-induced fMRI to identify the neural representation. From the resting-state fMRI, we extracted the appearances of activity patterns similar to the neural representations for posterior sentences. Importantly, the resting-state fMRI was measured before giving the posterior sentences, and thus such appearances could be considered as preplay-like or prototypical neural representations. We compared the intensities of such appearances with the understanding of posterior sentences. This gave a positive correlation between these two variables, but only if posterior sentences were associated with prior sentences. Additional analysis showed the contribution of the entorhinal cortex, rather than the hippocampus, to the correlation. The present study suggests that prior knowledge-based arrangement of neural activity before an experience contributes to the active selection of information to be learned. Such arrangement prior to an experience resembles preplay activity observed in the rodent brain. In terms of knowledge acquisition, the present study leads to a new view of the brain (or more precisely of the brain's knowledge) as an autopoietic system in which the brain (or knowledge) selects what it should learn by itself, arranges preplay-like activity as a position for the new information in advance, and actively reorganizes itself.

A Knowledge-Based Arrangement of Prototypical Neural Representation Prior to Experience Contributes to Selectivity in Upcoming Knowledge Acquisition

PubMed Central

Kurashige, Hiroki; Yamashita, Yuichi; Hanakawa, Takashi; Honda, Manabu

2018-01-01

Knowledge acquisition is a process in which one actively selects a piece of information from the environment and assimilates it with prior knowledge. However, little is known about the neural mechanism underlying selectivity in knowledge acquisition. Here we executed a 2-day human experiment to investigate the involvement of characteristic spontaneous activity resembling a so-called “preplay” in selectivity in sentence comprehension, an instance of knowledge acquisition. On day 1, we presented 10 sentences (prior sentences) that were difficult to understand on their own. On the following day, we first measured the resting-state functional magnetic resonance imaging (fMRI). Then, we administered a sentence comprehension task using 20 new sentences (posterior sentences). The posterior sentences were also difficult to understand on their own, but some could be associated with prior sentences to facilitate their understanding. Next, we measured the posterior sentence-induced fMRI to identify the neural representation. From the resting-state fMRI, we extracted the appearances of activity patterns similar to the neural representations for posterior sentences. Importantly, the resting-state fMRI was measured before giving the posterior sentences, and thus such appearances could be considered as preplay-like or prototypical neural representations. We compared the intensities of such appearances with the understanding of posterior sentences. This gave a positive correlation between these two variables, but only if posterior sentences were associated with prior sentences. Additional analysis showed the contribution of the entorhinal cortex, rather than the hippocampus, to the correlation. The present study suggests that prior knowledge-based arrangement of neural activity before an experience contributes to the active selection of information to be learned. Such arrangement prior to an experience resembles preplay activity observed in the rodent brain. In terms of knowledge acquisition, the present study leads to a new view of the brain (or more precisely of the brain’s knowledge) as an autopoietic system in which the brain (or knowledge) selects what it should learn by itself, arranges preplay-like activity as a position for the new information in advance, and actively reorganizes itself. PMID:29662446

Network reconstruction based on proteomic data and prior knowledge of protein connectivity using graph theory.

PubMed

Stavrakas, Vassilis; Melas, Ioannis N; Sakellaropoulos, Theodore; Alexopoulos, Leonidas G

2015-01-01

Modeling of signal transduction pathways is instrumental for understanding cells' function. People have been tackling modeling of signaling pathways in order to accurately represent the signaling events inside cells' biochemical microenvironment in a way meaningful for scientists in a biological field. In this article, we propose a method to interrogate such pathways in order to produce cell-specific signaling models. We integrate available prior knowledge of protein connectivity, in a form of a Prior Knowledge Network (PKN) with phosphoproteomic data to construct predictive models of the protein connectivity of the interrogated cell type. Several computational methodologies focusing on pathways' logic modeling using optimization formulations or machine learning algorithms have been published on this front over the past few years. Here, we introduce a light and fast approach that uses a breadth-first traversal of the graph to identify the shortest pathways and score proteins in the PKN, fitting the dependencies extracted from the experimental design. The pathways are then combined through a heuristic formulation to produce a final topology handling inconsistencies between the PKN and the experimental scenarios. Our results show that the algorithm we developed is efficient and accurate for the construction of medium and large scale signaling networks. We demonstrate the applicability of the proposed approach by interrogating a manually curated interaction graph model of EGF/TNFA stimulation against made up experimental data. To avoid the possibility of erroneous predictions, we performed a cross-validation analysis. Finally, we validate that the introduced approach generates predictive topologies, comparable to the ILP formulation. Overall, an efficient approach based on graph theory is presented herein to interrogate protein-protein interaction networks and to provide meaningful biological insights.

Self-Explanation in the Domain of Statistics: An Expertise Reversal Effect

ERIC Educational Resources Information Center

Leppink, Jimmie; Broers, Nick J.; Imbos, Tjaart; van der Vleuten, Cees P. M.; Berger, Martijn P. F.

2012-01-01

This study investigated the effects of four instructional methods on cognitive load, propositional knowledge, and conceptual understanding of statistics, for low prior knowledge students and for high prior knowledge students. The instructional methods were (1) a reading-only control condition, (2) answering open-ended questions, (3) answering…

Automatic analysis of quantitative NMR data of pharmaceutical compound libraries.

PubMed

Liu, Xuejun; Kolpak, Michael X; Wu, Jiejun; Leo, Gregory C

2012-08-07

In drug discovery, chemical library compounds are usually dissolved in DMSO at a certain concentration and then distributed to biologists for target screening. Quantitative (1)H NMR (qNMR) is the preferred method for the determination of the actual concentrations of compounds because the relative single proton peak areas of two chemical species represent the relative molar concentrations of the two compounds, that is, the compound of interest and a calibrant. Thus, an analyte concentration can be determined using a calibration compound at a known concentration. One particularly time-consuming step in the qNMR analysis of compound libraries is the manual integration of peaks. In this report is presented an automated method for performing this task without prior knowledge of compound structures and by using an external calibration spectrum. The script for automated integration is fast and adaptable to large-scale data sets, eliminating the need for manual integration in ~80% of the cases.

[Educating health workers is key in congenital syphilis elimination in Colombia].

PubMed

Garcés, Juan Pablo; Rubiano, Luisa Consuelo; Orobio, Yenifer; Castaño, Martha; Benavides, Elizabeth; Cruz, Adriana

2017-09-01

Colombia promotes the diagnosis and treatment of gestational syphilis in a single visit using rapid diagnostic tests to prevent mother-to-child transmission. Additionally, integrated health programs pursue the coordinated prevention of mother-to-child transmission of syphilis/HIV. To identify knowledge gaps among health workers in the prevention of mother-to-child transmission of syphilis/HIV and to provide recommendations to support these programs. We conducted a descriptive study based on 306 surveys of health workers in 39 health institutions in the city of Cali. Surveys inquired about planning, management and implementation of services for pregnant women, clinical knowledge of HIV/syphilis rapid diagnostic tests, and prior training. Knowledge deficits in the management of gestational syphilis were detected among the surveyed health workers, including physicians. Rapid tests for syphilis are currently used in clinical laboratories in Cali, however, procedural deficiencies were observed in their use, including quality control assurance. During the two years prior to the survey, training of health workers in the prevention of mother-to-child transmission of syphilis/HIV had been limited. Health workers are interested in identifying and treating gestational syphilis in a single event, in using rapid diagnostic tests and in receiving training. Intensive training targeting health workers, policy/decision makers and academic groups is needed to ensure adequate implementation of new strategies for the prevention of mother-to-child transmission of syphilis/HIV.

Putting Priors in Mixture Density Mercer Kernels

NASA Technical Reports Server (NTRS)

Srivastava, Ashok N.; Schumann, Johann; Fischer, Bernd

2004-01-01

This paper presents a new methodology for automatic knowledge driven data mining based on the theory of Mercer Kernels, which are highly nonlinear symmetric positive definite mappings from the original image space to a very high, possibly infinite dimensional feature space. We describe a new method called Mixture Density Mercer Kernels to learn kernel function directly from data, rather than using predefined kernels. These data adaptive kernels can en- code prior knowledge in the kernel using a Bayesian formulation, thus allowing for physical information to be encoded in the model. We compare the results with existing algorithms on data from the Sloan Digital Sky Survey (SDSS). The code for these experiments has been generated with the AUTOBAYES tool, which automatically generates efficient and documented C/C++ code from abstract statistical model specifications. The core of the system is a schema library which contains template for learning and knowledge discovery algorithms like different versions of EM, or numeric optimization methods like conjugate gradient methods. The template instantiation is supported by symbolic- algebraic computations, which allows AUTOBAYES to find closed-form solutions and, where possible, to integrate them into the code. The results show that the Mixture Density Mercer-Kernel described here outperforms tree-based classification in distinguishing high-redshift galaxies from low- redshift galaxies by approximately 16% on test data, bagged trees by approximately 7%, and bagged trees built on a much larger sample of data by approximately 2%.

A gaze through the lens of decision theory toward knowledge translation science.

PubMed

Bucknall, Tracey

2007-01-01

Research findings become evidence when an individual decides that the information is relevant and useful to a particular circumstance. Prior to that point, they are unrelated facts. For research translation to occur, research evidence needs filtering, interpretation, and application by individuals to the specific situation. For this reason, decision science is complementary to knowledge translation science. Both aim to support the individual in deciding the most appropriate action in a dynamic environment where there are masses of uncensored and nonprioritized information readily available. Decision science employs research theories to study the cognitive processes underpinning the filtering and integration of current scientific information into changing contexts. Two meta-theories, coherence and correspondence theories, have been used to provide alternative views and prompt significant debate to advance the science. The aim of this article is to stimulate debate about the relationship between decision theory and knowledge translation. Discussed is the critical role of cognition in clinical decision making, with a focus on knowledge translation. A critical commentary of the knowledge utilization modeling papers is presented from a decision science perspective. The article concludes with a discussion on the implications for knowledge translation when viewed through the lens of decision science.

Experiential knowledge of expert coaches can help identify informational constraints on performance of dynamic interceptive actions.

PubMed

Greenwood, Daniel; Davids, Keith; Renshaw, Ian

2014-01-01

Coordination of dynamic interceptive movements is predicated on cyclical relations between an individual's actions and information sources from the performance environment. To identify dynamic informational constraints, which are interwoven with individual and task constraints, coaches' experiential knowledge provides a complementary source to support empirical understanding of performance in sport. In this study, 15 expert coaches from 3 sports (track and field, gymnastics and cricket) participated in a semi-structured interview process to identify potential informational constraints which they perceived to regulate action during run-up performance. Expert coaches' experiential knowledge revealed multiple information sources which may constrain performance adaptations in such locomotor pointing tasks. In addition to the locomotor pointing target, coaches' knowledge highlighted two other key informational constraints: vertical reference points located near the locomotor pointing target and a check mark located prior to the locomotor pointing target. This study highlights opportunities for broadening the understanding of perception and action coupling processes, and the identified information sources warrant further empirical investigation as potential constraints on athletic performance. Integration of experiential knowledge of expert coaches with theoretically driven empirical knowledge represents a promising avenue to drive future applied science research and pedagogical practice.

Does physics instruction foster university students' cognitive processes?: A descriptive study of teacher activities

NASA Astrophysics Data System (ADS)

Ferguson-Hessler, Monica G. M.; de Jong, Ton

This study aims at giving a systematic description of the cognitive activities involved in teaching physics. Such a description of instruction in physics requires a basis in two models, that is, the cognitive activities involved in learning physics and the knowledge base that is the foundation of expertise in that subject. These models have been provided by earlier research. The model of instruction distinguishes three main categories of instruction process: presenting new information, integrating (i.e., bringing structure into) new knowledge, and connecting elements of new knowledge to prior knowledge. Each of the main categories has been divided into a number of specific instruction processes. Hereby any limited and specific cognitive teacher activity can be described along the two dimensions of process and type of knowledge. The model was validated by application to lectures and problem-solving classes of first year university courses. These were recorded and analyzed as to instruction process and type of knowledge. Results indicate that teachers are indeed involved in the various types of instruction processes defined. The importance of this study lies in the creation of a terminology that makes it possible to discuss instruction in an explicit and specific way.

Towards a machine learning framework for acquiring and exploiting monitoring and diagnostic knowledge

NASA Technical Reports Server (NTRS)

Manganaris, Stefanos; Fisher, Doug; Kulkarni, Deepak

1993-01-01

In this paper we address the problem of detecting and diagnosing faults in physical systems, for which neither prior expertise for the task nor suitable system models are available. We propose an architecture that integrates the on-line acquisition and exploitation of monitoring and diagnostic knowledge. The focus of the paper is on the component of the architecture that discovers classes of behaviors with similar characteristics by observing a system in operation. We investigate a characterization of behaviors based on best fitting approximation models. An experimental prototype has been implemented to test it. We present preliminary results in diagnosing faults of the Reaction Control System of the Space Shuttle. The merits and limitations of the approach are identified and directions for future work are set.

Comfort and experience with online learning: trends over nine years and associations with knowledge

PubMed Central

2014-01-01

Background Some evidence suggests that attitude toward computer-based instruction is an important determinant of success in online learning. We sought to determine how comfort using computers and perceptions of prior online learning experiences have changed over the past decade, and how these associate with learning outcomes. Methods Each year from 2003–2011 we conducted a prospective trial of online learning. As part of each year’s study, we asked medicine residents about their comfort using computers and if their previous experiences with online learning were favorable. We assessed knowledge using a multiple-choice test. We used regression to analyze associations and changes over time. Results 371 internal medicine and family medicine residents participated. Neither comfort with computers nor perceptions of prior online learning experiences showed a significant change across years (p > 0.61), with mean comfort rating 3.96 (maximum 5 = very comfortable) and mean experience rating 4.42 (maximum 6 = strongly agree [favorable]). Comfort showed no significant association with knowledge scores (p = 0.39) but perceptions of prior experiences did, with a 1.56% rise in knowledge score for a 1-point rise in experience score (p = 0.02). Correlations among comfort, perceptions of prior experiences, and number of prior experiences were all small and not statistically significant. Conclusions Comfort with computers and perceptions of prior experience with online learning remained stable over nine years. Prior good experiences (but not comfort with computers) demonstrated a modest association with knowledge outcomes, suggesting that prior course satisfaction may influence subsequent learning. PMID:24985690

Adaptive integral robust control and application to electromechanical servo systems.

PubMed

Deng, Wenxiang; Yao, Jianyong

2017-03-01

This paper proposes a continuous adaptive integral robust control with robust integral of the sign of the error (RISE) feedback for a class of uncertain nonlinear systems, in which the RISE feedback gain is adapted online to ensure the robustness against disturbances without the prior bound knowledge of the additive disturbances. In addition, an adaptive compensation integrated with the proposed adaptive RISE feedback term is also constructed to further reduce design conservatism when the system also exists parametric uncertainties. Lyapunov analysis reveals the proposed controllers could guarantee the tracking errors are asymptotically converging to zero with continuous control efforts. To illustrate the high performance nature of the developed controllers, numerical simulations are provided. At the end, an application case of an actual electromechanical servo system driven by motor is also studied, with some specific design consideration, and comparative experimental results are obtained to verify the effectiveness of the proposed controllers. Copyright © 2017 ISA. Published by Elsevier Ltd. All rights reserved.

Middle school students' knowledge of autism.

PubMed

Campbell, Jonathan M; Barger, Brian D

2011-06-01

Authors examined 1,015 middle school students' knowledge of autism using a single item of prior awareness and a 10-item Knowledge of Autism (KOA) scale. The KOA scale was designed to assess students' knowledge of the course, etiology, and symptoms associated with autism. Less than half of students (46.1%) reported having heard of autism; however, most students correctly responded that autism was a chronic condition that was not communicable. Students reporting prior awareness of autism scored higher on 9 of 10 KOA scale items when compared to their naïve counterparts. Prior awareness of autism and KOA scores also differed across schools. A more detailed understanding of developmental changes in students' knowledge of autism should improve peer educational interventions.

Relationship of prior knowledge and working engineers' learning preferences: implications for designing effective instruction

NASA Astrophysics Data System (ADS)

Baukal, Charles E.; Ausburn, Lynna J.

2017-05-01

Continuing engineering education (CEE) is important to ensure engineers maintain proficiency over the life of their careers. However, relatively few studies have examined designing effective training for working engineers. Research has indicated that both learner instructional preferences and prior knowledge can impact the learning process, but it has not established if these factors are interrelated. The study reported here considered relationships of prior knowledge and three aspects of learning preferences of working engineers at a manufacturing company: learning strategy choices, verbal-visual cognitive styles, and multimedia preferences. Prior knowledge was not found to be significantly related to engineers' learning preferences, indicating independence of effects of these variables on learning. The study also examined relationships of this finding to the Multimedia Cone of Abstraction and implications for its use as an instructional design tool for CEE.

Exploring the Impact of Prior Knowledge and Appropriate Feedback on Students' Perceived Cognitive Load and Learning Outcomes: Animation-based earthquakes instruction

NASA Astrophysics Data System (ADS)

Yeh, Ting-Kuang; Tseng, Kuan-Yun; Cho, Chung-Wen; Barufaldi, James P.; Lin, Mei-Shin; Chang, Chun-Yen

2012-07-01

The aim of this study was to develop an animation-based curriculum and to evaluate the effectiveness of animation-based instruction; the report involved the assessment of prior knowledge and the appropriate feedback approach, for the purpose of reducing perceived cognitive load and improving learning. The curriculum was comprised of five subunits designed to teach the 'Principles of Earthquakes.' Each subunit consisted of three modules: evaluation of prior knowledge with/without in-time feedback; animation-based instruction; and evaluation of learning outcomes with feedback. The 153 participants consisted of 10th grade high-school students. Seventy-eight students participated in the animation-based instruction, involving assessment of prior knowledge and appropriate feedback mechanism (APA group). A total of 75 students participated in animation-based learning that did not take into account their prior knowledge (ANPA group). The effectiveness of the instruction was then evaluated by using a Science Conception Test (SCT), a self-rating cognitive load questionnaire (CLQ), as well as a structured interview. The results indicated that: (1) Students' perceived cognitive load was reduced effectively through improving their prior knowledge by providing appropriate feedback. (2) When students perceived lower levels of cognitive load, they showed better learning outcome. The result of this study revealed that students of the APA group showed better performance than those of the ANPA group in an open-ended question. Furthermore, students' perceived cognitive load was negatively associated with their learning outcomes.

Investigating the Effectiveness of Inquiry-Based Instruction on Students with Different Prior Knowledge and Reading Abilities

ERIC Educational Resources Information Center

Wang, Jing-Ru; Wang, Yuh-Chao; Tai, Hsin-Jung; Chen, Wen-Ju

2010-01-01

This study examined the differential impacts of an inquiry-based instruction on conceptual changes across levels of prior knowledge and reading ability. The instrument emphasized four simultaneously important components: conceptual knowledge, reading ability, attitude toward science, and learning environment. Although the learning patterns and…

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…

Preparation for College General Chemistry: More than Just a Matter of Content Knowledge Acquisition

ERIC Educational Resources Information Center

Cracolice, Mark S.; Busby, Brittany D.

2015-01-01

This study investigates the potential of five factors that may be predictive of success in college general chemistry courses: prior knowledge of common alternate conceptions, intelligence, scientific reasoning ability, proportional reasoning ability, and attitude toward chemistry. We found that both prior knowledge and scientific reasoning ability…

Third-Grade Students' Mental Models of Energy Expenditure during Exercise

ERIC Educational Resources Information Center

Pasco, Denis; Ennis, Catherine D.

2015-01-01

Background: Students' prior knowledge plays an important role in learning new knowledge. In physical education (PE) and physical activity settings, studies have confirmed the role of students' prior knowledge. According to Placek and Griffin, these studies demonstrate that: "our students are not empty balls waiting to be filled with knowledge…

Learning Multisensory Integration and Coordinate Transformation via Density Estimation

PubMed Central

Sabes, Philip N.

2013-01-01

Sensory processing in the brain includes three key operations: multisensory integration—the task of combining cues into a single estimate of a common underlying stimulus; coordinate transformations—the change of reference frame for a stimulus (e.g., retinotopic to body-centered) effected through knowledge about an intervening variable (e.g., gaze position); and the incorporation of prior information. Statistically optimal sensory processing requires that each of these operations maintains the correct posterior distribution over the stimulus. Elements of this optimality have been demonstrated in many behavioral contexts in humans and other animals, suggesting that the neural computations are indeed optimal. That the relationships between sensory modalities are complex and plastic further suggests that these computations are learned—but how? We provide a principled answer, by treating the acquisition of these mappings as a case of density estimation, a well-studied problem in machine learning and statistics, in which the distribution of observed data is modeled in terms of a set of fixed parameters and a set of latent variables. In our case, the observed data are unisensory-population activities, the fixed parameters are synaptic connections, and the latent variables are multisensory-population activities. In particular, we train a restricted Boltzmann machine with the biologically plausible contrastive-divergence rule to learn a range of neural computations not previously demonstrated under a single approach: optimal integration; encoding of priors; hierarchical integration of cues; learning when not to integrate; and coordinate transformation. The model makes testable predictions about the nature of multisensory representations. PMID:23637588

The Development of Students' Mental Models of Chemical Substances and Processes at the Molecular Level

NASA Astrophysics Data System (ADS)

Dalton, Rebecca Marie

The development of student's mental models of chemical substances and processes at the molecular level was studied in a three-phase project. Animations produced in the VisChem project were used as an integral part of the chemistry instruction to help students develop their mental models. Phase one of the project involved examining the effectiveness of using animations to help first-year university chemistry students develop useful mental models of chemical phenomena. Phase two explored factors affecting the development of student's mental models, analysing results in terms of a proposed model of the perceptual processes involved in interpreting an animation. Phase three involved four case studies that served to confirm and elaborate on the effects of prior knowledge and disembedding ability on student's mental model development, and support the influence of study style on learning outcomes. Recommendations for use of the VisChem animations, based on the above findings, include: considering the prior knowledge of students; focusing attention on relevant features; encouraging a deep approach to learning; using animation to teach visual concepts; presenting ideas visually, verbally and conceptually; establishing 'animation literacy'; minimising cognitive load; using animation as feedback; using student drawings; repeating animations; and discussing 'scientific modelling'.

Integrating knowledge-based multi-criteria evaluation techniques with GIS for landfill site selection: A case study using AHP

NASA Astrophysics Data System (ADS)

Fagbohun, B. J.; Aladejana, O. O.

2016-09-01

A major challenge in most growing urban areas of developing countries, without a pre-existing land use plan is the sustainable and efficient management of solid wastes. Siting a landfill is a complicated task because of several environmental regulations. This challenge gives birth to the need to develop efficient strategies for the selection of proper waste disposal sites in accordance with all existing environmental regulations. This paper presents a knowledge-based multi-criteria decision analysis using GIS for the selection of suitable landfill site in Ado-Ekiti, Nigeria. In order to identify suitable sites for landfill, seven factors - land use/cover, geology, river, soil, slope, lineament and roads - were taken into consideration. Each factor was classified and ranked based on prior knowledge about the area and existing guidelines. Weights for each factor were determined through pair-wise comparison using Saaty's 9 point scale and AHP. The integration of factors according to their weights using weighted index overlay analysis revealed that 39.23 km2 within the area was suitable to site a landfill. The resulting suitable area was classified as high suitability covering 6.47 km2 (16.49%), moderate suitability 25.48 km2 (64.95%) and low suitability 7.28 km2 (18.56%) based on their overall weights.

Impact of a low-intensity pedagogical model for integrating MedlinePlus exercises into middle school nutrition lessons*†

PubMed Central

Rankins, Jenice; Kirksey, Otis; Bogan, Yolanda; Brown, Betty

2007-01-01

Objective: The research developed and pilot-tested MedlinePlus exercises in a diet-related chronic disease prevention (DCDP) middle school lesson unit called “Live.” Methods: MedlinePlus exercises were jointly developed by two middle school family and consumer sciences (FCS) teachers and integrated into the “Live” DCDP lesson unit. FCS classes (n = 4) who had participated in a prior “Live” study were chosen to pilot-test the MedlinePlus-supplemented exercises. Evaluation measures included student satisfaction (assessed using an 8-item pre- and posttest questionnaire), knowledge gained, and attitudinal changes (assessed with an abridged version of a previously developed “Live” questionnaire). Statistical analyses were performed using SPSS. Results: Of 62 total study participants, 56 (92.3%) said that they were either “somewhat” or “clearly”: (a) more likely to use MedlinePlus as a future source for answering questions about their personal health and (b) more knowledgeable about how eating habits can help prevent disease. Selected parameters were improved for nutrition knowledge (P < 0.01) and attitudes (P < 0.01) related to healthy eating. Conclusions: MedlinePlus has good potential for efficiently communicating trustworthy diet-related disease-prevention behaviors to adolescents in an existing classroom curriculum. PMID:17971886

5-years later - have faculty integrated medical genetics into nurse practitioner curriculum?

PubMed

Maradiegue, Ann H; Edwards, Quannetta T; Seibert, Diane

2013-10-31

Abstract Many genetic/genomic educational opportunities are available to assist nursing faculty in their knowledge and understanding of genetic/genomics. This study was conducted to assess advance practice nursing faculty members' current knowledge of medical genetics/genomics, their integration of genetics/genomics content into advance practice nursing curricula, any prior formal training/education in genetics/genomics, and their comfort level in teaching genetics/genomic content. A secondary aim was to conduct a comparative analysis of the 2010 data to a previous study conducted in 2005, to determine changes that have taken place during that time period. During a national nurse practitioner faculty conference, 85 nurse practitioner faculty voluntarily completed surveys. Approximately 70% of the 2010 faculty felt comfortable teaching basic genetic/genomic concepts compared to 50% in 2005. However, there continue to be education gaps in the genetic/genomic content taught to advance practice nursing students. If nurses are going to be a crucial member of the health-care team, they must achieve the requisite competencies to deliver the increasingly complex care patients require.

Mathematics understanding and anxiety in collaborative teaching

NASA Astrophysics Data System (ADS)

Ansari, B. I.; Wahyu, N.

2017-12-01

This study aims to examine students’ mathematical understanding and anxiety using collaborative teaching. The sample consists of 51 students in the 7th-grade of MTs N Jeureula, one of the Islamic public junior high schools in Jeureula, Aceh, Indonesia. A test of mathematics understanding was administered to the students twice during the period of two months. The result suggests that there is a significant increase in mathematical understanding in the pre-test and post-test. We categorized the students into the high, intermediate, and low level of prior mathematics knowledge. In the high-level prior knowledge, there is no difference of mathematical understanding between the experiment and control group. Meanwhile, in the intermediate and low level of prior knowledge, there is a significant difference of mathematical understanding between the experiment and control group. The mathematics anxiety is at an intermediate level in the experiment class and at a high level in the control group. There is no interaction between the learning model and the students’ prior knowledge towards the mathematical understanding, but there are interactions towards the mathematics anxiety. It indicates that the collaborative teaching model and the students’ prior knowledge do not simultaneously impacts on the mathematics understanding but the mathematics anxiety.

Developmental Change in the Influence of Domain-General Abilities and Domain-Specific Knowledge on Mathematics Achievement: An Eight-Year Longitudinal Study

PubMed Central

Geary, David C.; Nicholas, Alan; Li, Yaoran; Sun, Jianguo

2016-01-01

The contributions of domain-general abilities and domain-specific knowledge to subsequent mathematics achievement were longitudinally assessed (n = 167) through 8th grade. First grade intelligence and working memory and prior grade reading achievement indexed domain-general effects and domain-specific effects were indexed by prior grade mathematics achievement and mathematical cognition measures of prior grade number knowledge, addition skills, and fraction knowledge. Use of functional data analysis enabled grade-by-grade estimation of overall domain-general and domain-specific effects on subsequent mathematics achievement, the relative importance of individual domain-general and domain-specific variables on this achievement, and linear and non-linear across-grade estimates of these effects. The overall importance of domain-general abilities for subsequent achievement was stable across grades, with working memory emerging as the most important domain-general ability in later grades. The importance of prior mathematical competencies on subsequent mathematics achievement increased across grades, with number knowledge and arithmetic skills critical in all grades and fraction knowledge in later grades. Overall, domain-general abilities were more important than domain-specific knowledge for mathematics learning in early grades but general abilities and domain-specific knowledge were equally important in later grades. PMID:28781382

Advancing student nurse knowledge of the biomedical sciences: A mixed methods study.

PubMed

Craft, Judy; Christensen, Martin; Bakon, Shannon; Wirihana, Lisa

2017-01-01

Nursing students' ability to learn, integrate and apply bioscience knowledge to their clinical practice remains a concern. To evaluate the implementation, influence, and student perspective of a team-teaching workshop to integrate bioscience theory with clinical nursing practice. The team-teaching workshop was offered prior to commencement of the university semester as a refresher course at an Australian university. This study employed a sequential explanatory mixed methods design incorporating both quantitative and qualitative items. An evaluation survey with quantitative and qualitative items and a focus group were employed. The qualitative data were analysed using a thematic approach. The quantitative data was combined with the emergent themes in the qualitative data. Participants were final year nursing students. Nine students attended the workshop. All students completed the evaluation (N=9) and 44.4% (N=4) attended the focus group. The results revealed six themes: (1) lectures are an inadequate teaching strategy for bioscience; (2) teaching strategies which incorporate active learning engage students; (3) the team-teaching workshop provides an effective learning environment; (4) the workshop content should be expanded; (5) pharmacology should relate to bioscience, and bioscience should relate to nursing; and (6) team-teaching was effective in integrating pharmacology with bioscience, and then translating this into nursing practice. Students had felt there was disjointedness between pharmacology and bioscience, and between bioscience and nursing care within their undergraduate studies. The workshop that was based on team-teaching bridged those gaps, utilised active learning strategies and provided an effective learning environment. Team-teaching that employs active learning strategies is an effective approach to assist nursing students to integrate bioscience knowledge into their nursing practice. Copyright © 2016 Elsevier Ltd. All rights reserved.

Prior schemata transfer as an account for assessing the intuitive use of new technology.

PubMed

Fischer, Sandrine; Itoh, Makoto; Inagaki, Toshiyuki

2015-01-01

New devices are considered intuitive when they allow users to transfer prior knowledge. Drawing upon fundamental psychology experiments that distinguish prior knowledge transfer from new schema induction, a procedure was specified for assessing intuitive use. This procedure was tested with 31 participants who, prior to using an on-board computer prototype, studied its screenshots in reading vs. schema induction conditions. Distinct patterns of transfer or induction resulted for features of the prototype whose functions were familiar or unfamiliar, respectively. Though moderated by participants' cognitive style, these findings demonstrated a means for quantitatively assessing transfer of prior knowledge as the operation that underlies intuitive use. Implications for interface evaluation and design, as well as potential improvements to the procedure, are discussed. Copyright © 2014 Elsevier Ltd and The Ergonomics Society. All rights reserved.

How Prior Knowledge and Colour Contrast Interfere Visual Search Processes in Novice Learners: An Eye Tracking Study

ERIC Educational Resources Information Center

Sonmez, Duygu; Altun, Arif; Mazman, Sacide Guzin

2012-01-01

This study investigates how prior content knowledge and prior exposure to microscope slides on the phases of mitosis effect students' visual search strategies and their ability to differentiate cells that are going through any phases of mitosis. Two different sets of microscope slide views were used for this purpose; with high and low colour…

Identification of Boolean Network Models From Time Series Data Incorporating Prior Knowledge.

PubMed

Leifeld, Thomas; Zhang, Zhihua; Zhang, Ping

2018-01-01

Motivation: Mathematical models take an important place in science and engineering. A model can help scientists to explain dynamic behavior of a system and to understand the functionality of system components. Since length of a time series and number of replicates is limited by the cost of experiments, Boolean networks as a structurally simple and parameter-free logical model for gene regulatory networks have attracted interests of many scientists. In order to fit into the biological contexts and to lower the data requirements, biological prior knowledge is taken into consideration during the inference procedure. In the literature, the existing identification approaches can only deal with a subset of possible types of prior knowledge. Results: We propose a new approach to identify Boolean networks from time series data incorporating prior knowledge, such as partial network structure, canalizing property, positive and negative unateness. Using vector form of Boolean variables and applying a generalized matrix multiplication called the semi-tensor product (STP), each Boolean function can be equivalently converted into a matrix expression. Based on this, the identification problem is reformulated as an integer linear programming problem to reveal the system matrix of Boolean model in a computationally efficient way, whose dynamics are consistent with the important dynamics captured in the data. By using prior knowledge the number of candidate functions can be reduced during the inference. Hence, identification incorporating prior knowledge is especially suitable for the case of small size time series data and data without sufficient stimuli. The proposed approach is illustrated with the help of a biological model of the network of oxidative stress response. Conclusions: The combination of efficient reformulation of the identification problem with the possibility to incorporate various types of prior knowledge enables the application of computational model inference to systems with limited amount of time series data. The general applicability of this methodological approach makes it suitable for a variety of biological systems and of general interest for biological and medical research.

Using discharge data to reduce structural deficits in a hydrological model with a Bayesian inference approach and the implications for the prediction of critical source areas

NASA Astrophysics Data System (ADS)

Frey, M. P.; Stamm, C.; Schneider, M. K.; Reichert, P.

2011-12-01

A distributed hydrological model was used to simulate the distribution of fast runoff formation as a proxy for critical source areas for herbicide pollution in a small agricultural catchment in Switzerland. We tested to what degree predictions based on prior knowledge without local measurements could be improved upon relying on observed discharge. This learning process consisted of five steps: For the prior prediction (step 1), knowledge of the model parameters was coarse and predictions were fairly uncertain. In the second step, discharge data were used to update the prior parameter distribution. Effects of uncertainty in input data and model structure were accounted for by an autoregressive error model. This step decreased the width of the marginal distributions of parameters describing the lower boundary (percolation rates) but hardly affected soil hydraulic parameters. Residual analysis (step 3) revealed model structure deficits. We modified the model, and in the subsequent Bayesian updating (step 4) the widths of the posterior marginal distributions were reduced for most parameters compared to those of the prior. This incremental procedure led to a strong reduction in the uncertainty of the spatial prediction. Thus, despite only using spatially integrated data (discharge), the spatially distributed effect of the improved model structure can be expected to improve the spatially distributed predictions also. The fifth step consisted of a test with independent spatial data on herbicide losses and revealed ambiguous results. The comparison depended critically on the ratio of event to preevent water that was discharged. This ratio cannot be estimated from hydrological data only. The results demonstrate that the value of local data is strongly dependent on a correct model structure. An iterative procedure of Bayesian updating, model testing, and model modification is suggested.

Executive Functions as Moderators of the Worked Example Effect: When Shifting Is More Important than Working Memory Capacity

ERIC Educational Resources Information Center

Schwaighofer, Matthias; Bühner, Markus; Fischer, Frank

2016-01-01

Worked examples have proven to be effective for knowledge acquisition compared with problem solving, particularly when prior knowledge is low (e.g., Kalyuga, 2007). However, in addition to prior knowledge, executive functions and fluid intelligence might be potential moderators of the effectiveness of worked examples. The present study examines…

Can Prior Knowledge Hurt Text Comprehension? An Answer Borrowed from Plato, Aristotle, and Descartes.

ERIC Educational Resources Information Center

Friedman, Lawrence B.

Taking a philosophical approach based on what Plato, Aristotle, and Descartes said about knowledge, this paper addresses some of the murkiness in the conceptual space surrounding the issue of whether prior knowledge does or does not facilitate text comprehension. Specifically, the paper first develops a non-exhaustive typology of cases in which…

Effects of Activation of Prior Knowledge on the Recall of a Clinical Case.

ERIC Educational Resources Information Center

Schmidt, Henk G.; Boshuizen, Henny P. A.

A study investigated the known phenomenon of "intermediate effect" in which medical students with an intermediate amount of knowledge and experience demonstrate higher amounts of recall of the text of a medical case than either experienced clinicians or novices. In this study the amount of activation of prior knowledge was controlled by…

Effect of Altered Prior Knowledge on Passage Recall.

ERIC Educational Resources Information Center

Langer, Judith A.; Nicolich, Mark

A study was conducted to determine: (1) the relationships between prior knowledge and passage recall; (2) the effect of a prereading activity (PReP) on available knowledge; and (3) the effect of the PReP activity on total comprehension scores. The subjects were 161 sixth grade students from a middle class suburban Long Island, New York, public…

Does Teaching Experience Matter? Examining Biology Teachers' Prior Knowledge for Teaching in an Alternative Certification Program

ERIC Educational Resources Information Center

Friedrichsen, Patricia J.; Abell, Sandra K.; Pareja, Enrique M.; Brown, Patrick L.; Lankford, Deanna M.; Volkmann, Mark J.

2009-01-01

Alternative certification programs (ACPs) have been proposed as a viable way to address teacher shortages, yet we know little about how teacher knowledge develops within such programs. The purpose of this study was to investigate prior knowledge for teaching among students entering an ACP, comparing individuals with teaching experience to those…

The Importance of Prior Knowledge when Comparing Examples: Influences on Conceptual and Procedural Knowledge of Equation Solving

ERIC Educational Resources Information Center

Rittle-Johnson, Bethany; Star, Jon R.; Durkin, Kelley

2009-01-01

Comparing multiple examples typically supports learning and transfer in laboratory studies and is considered a key feature of high-quality mathematics instruction. This experimental study investigated the importance of prior knowledge in learning from comparison. Seventh- and 8th-grade students (N = 236) learned to solve equations by comparing…

"Koko et les lunettes magiques": An educational entertainment tool to prevent parasitic worms and diarrheal diseases in Côte d'Ivoire.

PubMed

Essé, Clémence; Koffi, Véronique A; Kouamé, Abel; Dongo, Kouassi; Yapi, Richard B; Moro, Honorine M; Kouakou, Christiane A; Palmeirim, Marta S; Bonfoh, Bassirou; N'Goran, Eliézer K; Utzinger, Jürg; Raso, Giovanna

2017-09-01

Integrated control programs, emphasizing preventive chemotherapy along with health education, can reduce the incidence of soil-transmitted helminthiasis and schistosomiasis. The aim of this study was to develop an educational animated cartoon to improve school children's awareness regarding soil-transmitted helminthiasis, diarrheal diseases, and related hygiene practices in Côte d'Ivoire. The key messages included in the cartoon were identified through prior formative research to specifically address local knowledge gaps. In a first step, preliminary research was conducted to assess the knowledge, attitudes, practices, and beliefs of school-aged children regarding parasitic worm infections and hygiene, to identify key health messages to be included in an animated cartoon. Second, an animated cartoon was produced, which included the drafting of the script and story board, and the production of the cartoon's initial version. Finally, the animated cartoon was pilot tested in eight selected schools and further fine-tuned. According to the questionnaire results, children believed that the consumption of sweet food, eating without washing their hands, sitting on the floor, and eating spoiled food were the main causes of parasitic worm infections. Abdominal pain, diarrhea, lack of appetite, failure to grow, and general fatigue were mentioned as symptoms of parasitic worm infections. Most of the children knew that they should go to the hospital for treatment if they experienced symptoms of parasitic worm diseases. The animated cartoon titled "Koko et les lunettes magiques" was produced by Afrika Toon, in collaboration with a scientific team composed of epidemiologists, civil engineers, and social scientists, and the local school children and teachers. Pilot testing of the animated cartoon revealed that, in the short term, children grasped and kept key messages. Most of the children who were shown the cartoon reported to like it. Acceptance of the animated cartoon was high among children and teachers alike. The messaging was tailored to improve knowledge and practices for prevention of helminthiases and diarrheal diseases through prior identification of knowledge gaps. Integration of such education tools into the school curriculum, along with deworming campaigns, might improve sustainability of control and elimination efforts against helminthiases and diarrheal diseases.

From Data to Knowledge – Promising Analytical Tools and Techniques for Capture and Reuse of Corporate Knowledge and to Aid in the State Evaluation Process

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

Danielson, Gary R.; Augustenborg, Elsa C.; Beck, Andrew E.

2010-10-29

The IAEA is challenged with limited availability of human resources for inspection and data analysis while proliferation threats increase. PNNL has a variety of IT solutions and techniques (at varying levels of maturity and development) that take raw data closer to useful knowledge, thereby assisting with and standardizing the analytical processes. This paper highlights some PNNL tools and techniques which are applicable to the international safeguards community, including: • Intelligent in-situ triage of data prior to reliable transmission to an analysis center resulting in the transmission of smaller and more relevant data sets • Capture of expert knowledge in re-usablemore » search strings tailored to specific mission outcomes • Image based searching fused with text based searching • Use of gaming to discover unexpected proliferation scenarios • Process modeling (e.g. Physical Model) as the basis for an information integration portal, which links to data storage locations along with analyst annotations, categorizations, geographic data, search strings and visualization outputs.« less

What You Know Can Hurt You: Effects of Age and Prior Knowledge on the Accuracy of Judgments of Learning

PubMed Central

Toth, Jeffrey P.; Daniels, Karen A.; Solinger, Lisa A.

2011-01-01

How do aging and prior knowledge affect memory and metamemory? We explored this question in the context of a dual-process approach to Judgments of Learning (JOLs) which require people to predict their ability to remember information at a later time. Young and older adults (n's = 36, mean ages = 20.2 & 73.1) studied the names of actors that were famous in the 1950s or 1990s, providing a JOL for each. Recognition memory for studied and unstudied actors was then assessed using a Recollect/Know/No-Memory (R/K/N) judgment task. Results showed that prior knowledge increased recollection in both age groups such that older adults recollected significantly more 1950s actors than younger adults. Also, for both age groups and both decades, actors judged R at test garnered significantly higher JOLs at study than actors judged K or N. However, while the young showed benefits of prior knowledge on relative JOL accuracy, older adults did not, showing lower levels of JOL accuracy for 1950s actors despite having higher recollection for, and knowledge about, those actors. Overall, the data suggest that prior knowledge can be a double-edged sword, increasing the availability of details that can support later recollection, but also increasing non-diagnostic feelings of familiarity that can reduce the accuracy of memory predictions. PMID:21480715

Effects of Teacher Use of Analogies on Achievement of High School Biology Students with Varying Levels of Cognitive Ability and Prior Knowledge.

ERIC Educational Resources Information Center

Burns, Joseph C.; Okey, James R.

This study investigated the effects of analogy-based and conventional lecture-based instructional strategies on the achievement of four classes of high school biology students (N=123). Prior to treatment, students were assessed for cognitive ability and prior knowledge of the analogy vehicle. The analogy-based treatment consisted of teacher…

The impact of curiosity on learning during a school field trip to the zoo

NASA Astrophysics Data System (ADS)

Carlin, Kerry Ann

1999-11-01

This study was designed to examine (a) differences in cognitive learning as a result of a zoo field trip, (b) if the trip to the zoo had an impact on epistemic curiosity, (c) the role epistemic curiosity plays in learning, (d) the effect of gender, race, prior knowledge and prior visitation to the zoo on learning and epistemic curiosity, (e) participants' affect for the zoo animals, and (f) if prior visitation to the zoo contributes to prior knowledge. Ninety-six fourth and fifth grade children completed curiosity, cognitive, and affective written tests before and after a field trip to the Lowery Park Zoo in Tampa, Florida. The data showed that students were very curious about zoo animals. Dependent T-tests indicated no significant difference between pretest and posttest curiosity levels. The trip did not influence participants' curiosity levels. Multiple regression analysis was used to determine the relationship between the dependent variable, curiosity, and the independent variables, gender, race, prior knowledge, and prior visitation. No significant differences were found. Dependent T-tests indicated no significant difference between pretest and posttest cognitive scores. The field trip to the zoo did not cause an increase in participants' knowledge. However, participants did learn on the trip. After the field trip, participants identified more animals displayed by the zoo than they did before. Also, more animals were identified by species and genus names after the trip than before. These differences were significant (alpha = .05). Multiple regression analysis was used to determine the relationship between the dependent variable, posttest cognitive performance, and the independent variables, curiosity, gender, race, prior knowledge, and prior visitation. A significant difference was found for prior knowledge (alpha = .05). No significant differences were found for the other independent variables. Chi-square tests of significance indicated significant differences (alpha = .05) in preferences for types of animals and preference for animals by gender. Significant differences (alpha = .05) were also found between the reasons why animals were preferred. Differences occurred between animals that were liked and disliked, between genders, and between the pretest and the posttest.

An investigation of multitasking information behavior and the influence of working memory and flow

NASA Astrophysics Data System (ADS)

Alexopoulou, Peggy; Hepworth, Mark; Morris, Anne

2015-02-01

This study explored the multitasking information behaviour of Web users and how this is influenced by working memory, flow and Personal, Artefact and Task characteristics, as described in the PAT model. The research was exploratory using a pragmatic, mixed method approach. Thirty University students participated; 10 psychologists, 10 accountants and 10 mechanical engineers. The data collection tools used were: pre and post questionnaires, a working memory test, a flow state scale test, audio-visual data, web search logs, think aloud data, observation, and the critical decision method. All participants searched information on the Web for four topics: two for which they had prior knowledge and two more without prior knowledge. Perception of task complexity was found to be related to working memory. People with low working memory reported a significant increase in task complexity after they had completed information searching tasks for which they had no prior knowledge, this was not the case for tasks with prior knowledge. Regarding flow and task complexity, the results confirmed the suggestion of the PAT model (Finneran and Zhang, 2003), which proposed that a complex task can lead to anxiety and low flow levels as well as to perceived challenge and high flow levels. However, the results did not confirm the suggestion of the PAT model regarding the characteristics of web search systems and especially perceived vividness. All participants experienced high vividness. According to the PAT model, however, only people with high flow should experience high levels of vividness. Flow affected the degree of change of knowledge of the participants. People with high flow gained more knowledge for tasks without prior knowledge rather than people with low flow. Furthermore, accountants felt that tasks without prior knowledge were less complex at the end of the web seeking procedure than psychologists and mechanical engineers. Finally, the three disciplines appeared to differ regarding the multitasking information behaviour characteristics such as queries, web search sessions and opened tabs/windows.

Hippocampus segmentation using locally weighted prior based level set

NASA Astrophysics Data System (ADS)

Achuthan, Anusha; Rajeswari, Mandava

2015-12-01

Segmentation of hippocampus in the brain is one of a major challenge in medical image segmentation due to its' imaging characteristics, with almost similar intensity between another adjacent gray matter structure, such as amygdala. The intensity similarity has causes the hippocampus to have weak or fuzzy boundaries. With this main challenge being demonstrated by hippocampus, a segmentation method that relies on image information alone may not produce accurate segmentation results. Therefore, it is needed an assimilation of prior information such as shape and spatial information into existing segmentation method to produce the expected segmentation. Previous studies has widely integrated prior information into segmentation methods. However, the prior information has been utilized through a global manner integration, and this does not reflect the real scenario during clinical delineation. Therefore, in this paper, a locally integrated prior information into a level set model is presented. This work utilizes a mean shape model to provide automatic initialization for level set evolution, and has been integrated as prior information into the level set model. The local integration of edge based information and prior information has been implemented through an edge weighting map that decides at voxel level which information need to be observed during a level set evolution. The edge weighting map shows which corresponding voxels having sufficient edge information. Experiments shows that the proposed integration of prior information locally into a conventional edge-based level set model, known as geodesic active contour has shown improvement of 9% in averaged Dice coefficient.

The Emergence of Knowledge and How it Supports the Memory for Novel Related Information.

PubMed

Sommer, Tobias

2017-03-01

Current theories suggest that memories for novel information and events, over time and with repeated retrieval, lose the association to their initial learning context. They are consolidated into a more stable form and transformed into semantic knowledge, that is, semanticized. Novel, related information can then be rapidly integrated into such knowledge, leading to superior memory. We tested these hypotheses in a longitudinal, 302-day, human functional magnetic resonance imaging study in which participants first overlearned and consolidated associative structures. This phase was associated with a shift from hippocampal- to ventrolateral prefrontal cortex (vlPFC)-mediated retrieval, consistent with semanticization. Next, participants encoded novel, related information whose encoding into the already acquired knowledge was orchestrated by the ventromedial prefrontal cortex. Novel related information exhibited reduced forgetting compared with novel control information, which corresponded to a faster shift from hippocampal- to vlPFC-mediated retrieval. In sum, the current results suggest that memory for novel information can be enhanced by anchoring it to prior knowledge via acceleration of the processes observed during semanticization. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Powerful Learning Tools for ELLs: Using Native Language, Familiar Examples, and Concept Mapping to Teach English Language Learners

ERIC Educational Resources Information Center

Dong, Yu Ren

2013-01-01

This article highlights how English language learners' (ELLs) prior knowledge can be used to help learn science vocabulary. The article explains that the concept of prior knowledge needs to encompass the ELL student's native language, previous science learning, native literacy skills, and native cultural knowledge and life experiences.…

Teachers' Beliefs about the Role of Prior Language Knowledge in Learning and How These Influence Teaching Practices

ERIC Educational Resources Information Center

De Angelis, Gessica

2011-01-01

The present study was developed to assess teachers' beliefs on (1) the role of prior language knowledge in language learning; (2) the perceived usefulness of language knowledge in modern society; and (3) the teaching practices to be used with multilingual students. Subjects were 176 secondary schoolteachers working in Italy (N = 103), Austria (N =…

Modifying Cookbook Labs.

ERIC Educational Resources Information Center

Clark, Robert, L.; Clough, Michael P.; Berg, Craig A.

2000-01-01

Modifies an extended lab activity from a cookbook approach for determining the percent mass of water in copper sulfate pentahydrate crystals to one which incorporates students' prior knowledge, engenders active mental struggling with prior knowledge and new experiences, and encourages metacognition. (Contains 12 references.) (ASK)

Posterior Cingulate Cortex: Adapting Behavior to a Changing World

PubMed Central

Pearson, John M.; Heilbronner, Sarah R.; Barack, David L.; Hayden, Benjamin Y.; Platt, Michael L.

2011-01-01

When has the world changed enough to warrant a new approach? The answer depends upon current needs, behavioral flexibility, and prior knowledge about the environment. Formal approaches solve the problem by integrating the recent history of rewards, errors, uncertainty, and context via Bayesian inference to detect changes in the world and alter behavioral policy. Neuronal activity in posterior cingulate cortex (CGp)—a key node in the default network—is known to vary with learning, memory, reward, and task engagement. We propose that these modulations reflect the underlying process of change detection and motivate subsequent shifts in behavior. PMID:21420893

The angular difference function and its application to image registration.

PubMed

Keller, Yosi; Shkolnisky, Yoel; Averbuch, Amir

2005-06-01

The estimation of large motions without prior knowledge is an important problem in image registration. In this paper, we present the angular difference function (ADF) and demonstrate its applicability to rotation estimation. The ADF of two functions is defined as the integral of their spectral difference along the radial direction. It is efficiently computed using the pseudopolar Fourier transform, which computes the discrete Fourier transform of an image on a near spherical grid. Unlike other Fourier-based registration schemes, the suggested approach does not require any interpolation. Thus, it is more accurate and significantly faster.

Metadynamic metainference: Enhanced sampling of the metainference ensemble using metadynamics

PubMed Central

Bonomi, Massimiliano; Camilloni, Carlo; Vendruscolo, Michele

2016-01-01

Accurate and precise structural ensembles of proteins and macromolecular complexes can be obtained with metainference, a recently proposed Bayesian inference method that integrates experimental information with prior knowledge and deals with all sources of errors in the data as well as with sample heterogeneity. The study of complex macromolecular systems, however, requires an extensive conformational sampling, which represents a separate challenge. To address such challenge and to exhaustively and efficiently generate structural ensembles we combine metainference with metadynamics and illustrate its application to the calculation of the free energy landscape of the alanine dipeptide. PMID:27561930

Teaching the Anatomy of Oncology: Evaluating the Impact of a Dedicated Oncoanatomy Course

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

Chino, Junzo P., E-mail: junzo.chino@duke.ed; Lee, W. Robert; Madden, Richard

Purpose: Anatomic considerations are often critical in multidisciplinary cancer care. We developed an anatomy-focused educational program for radiation oncology residents integrating cadaver dissection into the didactic review of diagnostic, surgical, radiologic, and treatment planning, and herein assess its efficacy. Methods and Materials: Monthly, anatomic-site based educational modules were designed and implemented during the 2008-2009 academic year at Duke University Medical Center. Ten radiation oncology residents participated in these modules consisting of a 1-hour didactic introduction followed by a 1-hour session in the gross anatomy lab with cadavers prepared by trained anatomists. Pretests and posttests were given for six modules, andmore » post-module feedback surveys were distributed. Additional review questions testing knowledge from prior sessions were integrated into the later testing to evaluate knowledge retention. Paired analyses of pretests and postests were performed by Wilcoxon signed-rank test. Results: Ninety tests were collected and scored with 35 evaluable pretest and posttest pairs for six site-specific sessions. Posttests had significantly higher scores (median percentage correct 66% vs. 85%, p < 0.001). Of 47 evaluable paired pretest and review questions given 1-3 months after the intervention, correct responses rates were significantly higher for the later (59% vs. 86%, p = 0.008). Resident course satisfaction was high, with a median rating of 9 of 10 (IQR 8-9); with 1 being 'less effective than most educational interventions' and 10 being 'more effective than most educational interventions.' Conclusions: An integrated oncoanatomy course is associated with improved scores on post-intervention tests, sustained knowledge retention, and high resident satisfaction.« less

Polyenergetic known-component reconstruction without prior shape models

NASA Astrophysics Data System (ADS)

Zhang, C.; Zbijewski, W.; Zhang, X.; Xu, S.; Stayman, J. W.

2017-03-01

Purpose: Previous work has demonstrated that structural models of surgical tools and implants can be integrated into model-based CT reconstruction to greatly reduce metal artifacts and improve image quality. This work extends a polyenergetic formulation of known-component reconstruction (Poly-KCR) by removing the requirement that a physical model (e.g. CAD drawing) be known a priori, permitting much more widespread application. Methods: We adopt a single-threshold segmentation technique with the help of morphological structuring elements to build a shape model of metal components in a patient scan based on initial filtered-backprojection (FBP) reconstruction. This shape model is used as an input to Poly-KCR, a formulation of known-component reconstruction that does not require a prior knowledge of beam quality or component material composition. An investigation of performance as a function of segmentation thresholds is performed in simulation studies, and qualitative comparisons to Poly-KCR with an a priori shape model are made using physical CBCT data of an implanted cadaver and in patient data from a prototype extremities scanner. Results: We find that model-free Poly-KCR (MF-Poly-KCR) provides much better image quality compared to conventional reconstruction techniques (e.g. FBP). Moreover, the performance closely approximates that of Poly- KCR with an a prior shape model. In simulation studies, we find that imaging performance generally follows segmentation accuracy with slight under- or over-estimation based on the shape of the implant. In both simulation and physical data studies we find that the proposed approach can remove most of the blooming and streak artifacts around the component permitting visualization of the surrounding soft-tissues. Conclusion: This work shows that it is possible to perform known-component reconstruction without prior knowledge of the known component. In conjunction with the Poly-KCR technique that does not require knowledge of beam quality or material composition, very little needs to be known about the metal implant and system beforehand. These generalizations will allow more widespread application of KCR techniques in real patient studies where the information of surgical tools and implants is limited or not available.

Effects of Prior Economic Education, Native Language, and Gender on Economic Knowledge of First-Year Students in Higher Education. A Comparative Study between Germany and the USA

ERIC Educational Resources Information Center

Brückner, Sebastian; Förster, Manuel; Zlatkin-Troitschanskaia, Olga; Walstad, William B.

2015-01-01

The assessment of university students' economic knowledge has become an increasingly important research area within and across countries. Particularly, the different influences of prior education, native language, and gender as some of the main prerequisites on students' economic knowledge have been highlighted since long. However, the findings…

Fuzzy-based propagation of prior knowledge to improve large-scale image analysis pipelines

PubMed Central

Mikut, Ralf

2017-01-01

Many automatically analyzable scientific questions are well-posed and a variety of information about expected outcomes is available a priori. Although often neglected, this prior knowledge can be systematically exploited to make automated analysis operations sensitive to a desired phenomenon or to evaluate extracted content with respect to this prior knowledge. For instance, the performance of processing operators can be greatly enhanced by a more focused detection strategy and by direct information about the ambiguity inherent in the extracted data. We present a new concept that increases the result quality awareness of image analysis operators by estimating and distributing the degree of uncertainty involved in their output based on prior knowledge. This allows the use of simple processing operators that are suitable for analyzing large-scale spatiotemporal (3D+t) microscopy images without compromising result quality. On the foundation of fuzzy set theory, we transform available prior knowledge into a mathematical representation and extensively use it to enhance the result quality of various processing operators. These concepts are illustrated on a typical bioimage analysis pipeline comprised of seed point detection, segmentation, multiview fusion and tracking. The functionality of the proposed approach is further validated on a comprehensive simulated 3D+t benchmark data set that mimics embryonic development and on large-scale light-sheet microscopy data of a zebrafish embryo. The general concept introduced in this contribution represents a new approach to efficiently exploit prior knowledge to improve the result quality of image analysis pipelines. The generality of the concept makes it applicable to practically any field with processing strategies that are arranged as linear pipelines. The automated analysis of terabyte-scale microscopy data will especially benefit from sophisticated and efficient algorithms that enable a quantitative and fast readout. PMID:29095927

Language knowledge and event knowledge in language use.

PubMed

Willits, Jon A; Amato, Michael S; MacDonald, Maryellen C

2015-05-01

This paper examines how semantic knowledge is used in language comprehension and in making judgments about events in the world. We contrast knowledge gleaned from prior language experience ("language knowledge") and knowledge coming from prior experience with the world ("world knowledge"). In two corpus analyses, we show that previous research linking verb aspect and event representations have confounded language and world knowledge. Then, using carefully chosen stimuli that remove this confound, we performed four experiments that manipulated the degree to which language knowledge or world knowledge should be salient and relevant to performing a task, finding in each case that participants use the type of knowledge most appropriate to the task. These results provide evidence for a highly context-sensitive and interactionist perspective on how semantic knowledge is represented and used during language processing. Copyright © 2015. Published by Elsevier Inc.

Incorporating linguistic knowledge for learning distributed word representations.

PubMed

Wang, Yan; Liu, Zhiyuan; Sun, Maosong

2015-01-01

Combined with neural language models, distributed word representations achieve significant advantages in computational linguistics and text mining. Most existing models estimate distributed word vectors from large-scale data in an unsupervised fashion, which, however, do not take rich linguistic knowledge into consideration. Linguistic knowledge can be represented as either link-based knowledge or preference-based knowledge, and we propose knowledge regularized word representation models (KRWR) to incorporate these prior knowledge for learning distributed word representations. Experiment results demonstrate that our estimated word representation achieves better performance in task of semantic relatedness ranking. This indicates that our methods can efficiently encode both prior knowledge from knowledge bases and statistical knowledge from large-scale text corpora into a unified word representation model, which will benefit many tasks in text mining.

Incorporating Linguistic Knowledge for Learning Distributed Word Representations

PubMed Central

Wang, Yan; Liu, Zhiyuan; Sun, Maosong

2015-01-01

Combined with neural language models, distributed word representations achieve significant advantages in computational linguistics and text mining. Most existing models estimate distributed word vectors from large-scale data in an unsupervised fashion, which, however, do not take rich linguistic knowledge into consideration. Linguistic knowledge can be represented as either link-based knowledge or preference-based knowledge, and we propose knowledge regularized word representation models (KRWR) to incorporate these prior knowledge for learning distributed word representations. Experiment results demonstrate that our estimated word representation achieves better performance in task of semantic relatedness ranking. This indicates that our methods can efficiently encode both prior knowledge from knowledge bases and statistical knowledge from large-scale text corpora into a unified word representation model, which will benefit many tasks in text mining. PMID:25874581

Knowledge about complementary, alternative and integrative medicine (CAM) among registered health care providers in Swedish surgical care: a national survey among university hospitals

PubMed Central

2012-01-01

Background Previous studies show an increased interest and usage of complementary and alternative medicine (CAM) in the general population and among health care workers both internationally and nationally. CAM usage is also reported to be common among surgical patients. Earlier international studies have reported that a large amount of surgical patients use it prior to and after surgery. Recent publications indicate a weak knowledge about CAM among health care workers. However the current situation in Sweden is unknown. The aim of this study was therefore to explore perceived knowledge about CAM among registered healthcare professions in surgical departments at Swedish university hospitals. Method A questionnaire was distributed to 1757 registered physicians, nurses and physiotherapists in surgical wards at the seven university hospitals in Sweden from spring 2010 to spring 2011. The questionnaire included classification of 21 therapies into conventional, complementary, alternative and integrative, and whether patients were recommended these therapies. Questions concerning knowledge, research, and patient communication about CAM were also included. Result A total of 737 (42.0%) questionnaires were returned. Therapies classified as complementary; were massage, manual therapies, yoga and acupuncture. Alternative therapies; were herbal medicine, dietary supplements, homeopathy and healing. Classification to integrative therapy was low, and unfamiliar therapies were Bowen therapy, iridology and Rosen method. Therapies recommended by > 40% off the participants were massage and acupuncture. Knowledge and research about CAM was valued as minor or none at all by 95.7% respectively 99.2%. Importance of possessing knowledge about it was valued as important by 80.9%. It was believed by 61.2% that more research funding should be addressed to CAM research, 72.8% were interested in reading CAM-research results, and 27.8% would consider taking part in such research. Half of the participants (55.8%) were positive to learning such therapy. Communication about CAM between patients and the health care professions was found to be rare. Conclusion There is a lack of knowledge about CAM and research about it among registered health care professions in Swedish surgical care. However, in contrast to previous studies the results revealed that the majority perceived it as important to gain knowledge in this field. PMID:22498305

Knowledge about complementary, alternative and integrative medicine (CAM) among registered health care providers in Swedish surgical care: a national survey among university hospitals.

PubMed

Bjerså, Kristofer; Stener Victorin, Elisabet; Fagevik Olsén, Monika

2012-04-12

Previous studies show an increased interest and usage of complementary and alternative medicine (CAM) in the general population and among health care workers both internationally and nationally. CAM usage is also reported to be common among surgical patients. Earlier international studies have reported that a large amount of surgical patients use it prior to and after surgery. Recent publications indicate a weak knowledge about CAM among health care workers. However the current situation in Sweden is unknown. The aim of this study was therefore to explore perceived knowledge about CAM among registered healthcare professions in surgical departments at Swedish university hospitals. A questionnaire was distributed to 1757 registered physicians, nurses and physiotherapists in surgical wards at the seven university hospitals in Sweden from spring 2010 to spring 2011. The questionnaire included classification of 21 therapies into conventional, complementary, alternative and integrative, and whether patients were recommended these therapies. Questions concerning knowledge, research, and patient communication about CAM were also included. A total of 737 (42.0%) questionnaires were returned. Therapies classified as complementary; were massage, manual therapies, yoga and acupuncture. Alternative therapies; were herbal medicine, dietary supplements, homeopathy and healing. Classification to integrative therapy was low, and unfamiliar therapies were Bowen therapy, iridology and Rosen method. Therapies recommended by > 40% off the participants were massage and acupuncture. Knowledge and research about CAM was valued as minor or none at all by 95.7% respectively 99.2%. Importance of possessing knowledge about it was valued as important by 80.9%. It was believed by 61.2% that more research funding should be addressed to CAM research, 72.8% were interested in reading CAM-research results, and 27.8% would consider taking part in such research. Half of the participants (55.8%) were positive to learning such therapy. Communication about CAM between patients and the health care professions was found to be rare. There is a lack of knowledge about CAM and research about it among registered health care professions in Swedish surgical care. However, in contrast to previous studies the results revealed that the majority perceived it as important to gain knowledge in this field.

Estimating the effect of lay knowledge and prior contact with pulmonary TB patients, on health-belief model in a high-risk pulmonary TB transmission population.

PubMed

Zein, Rizqy Amelia; Suhariadi, Fendy; Hendriani, Wiwin

2017-01-01

The research aimed to investigate the effect of lay knowledge of pulmonary tuberculosis (TB) and prior contact with pulmonary TB patients on a health-belief model (HBM) as well as to identify the social determinants that affect lay knowledge. Survey research design was conducted, where participants were required to fill in a questionnaire, which measured HBM and lay knowledge of pulmonary TB. Research participants were 500 residents of Semampir, Asemrowo, Bubutan, Pabean Cantian, and Simokerto districts, where the risk of pulmonary TB transmission is higher than other districts in Surabaya. Being a female, older in age, and having prior contact with pulmonary TB patients significantly increase the likelihood of having a higher level of lay knowledge. Lay knowledge is a substantial determinant to estimate belief in the effectiveness of health behavior and personal health threat. Prior contact with pulmonary TB patients is able to explain the belief in the effectiveness of a health behavior, yet fails to estimate participants' belief in the personal health threat. Health authorities should prioritize males and young people as their main target groups in a pulmonary TB awareness campaign. The campaign should be able to reconstruct people's misconception about pulmonary TB, thereby bringing around the health-risk perception so that it is not solely focused on improving lay knowledge.

The positive and negative consequences of multiple-choice testing.

PubMed

Roediger, Henry L; Marsh, Elizabeth J

2005-09-01

Multiple-choice tests are commonly used in educational settings but with unknown effects on students' knowledge. The authors examined the consequences of taking a multiple-choice test on a later general knowledge test in which students were warned not to guess. A large positive testing effect was obtained: Prior testing of facts aided final cued-recall performance. However, prior testing also had negative consequences. Prior reading of a greater number of multiple-choice lures decreased the positive testing effect and increased production of multiple-choice lures as incorrect answers on the final test. Multiple-choice testing may inadvertently lead to the creation of false knowledge.

A novel approach for data integration and disease subtyping

PubMed Central

Tagett, Rebecca; Diaz, Diana

2017-01-01

Advances in high-throughput technologies allow for measurements of many types of omics data, yet the meaningful integration of several different data types remains a significant challenge. Another important and difficult problem is the discovery of molecular disease subtypes characterized by relevant clinical differences, such as survival. Here we present a novel approach, called perturbation clustering for data integration and disease subtyping (PINS), which is able to address both challenges. The framework has been validated on thousands of cancer samples, using gene expression, DNA methylation, noncoding microRNA, and copy number variation data available from the Gene Expression Omnibus, the Broad Institute, The Cancer Genome Atlas (TCGA), and the European Genome-Phenome Archive. This simultaneous subtyping approach accurately identifies known cancer subtypes and novel subgroups of patients with significantly different survival profiles. The results were obtained from genome-scale molecular data without any other type of prior knowledge. The approach is sufficiently general to replace existing unsupervised clustering approaches outside the scope of bio-medical research, with the additional ability to integrate multiple types of data. PMID:29066617

Integrated rare variant-based risk gene prioritization in disease case-control sequencing studies.

PubMed

Lin, Jhih-Rong; Zhang, Quanwei; Cai, Ying; Morrow, Bernice E; Zhang, Zhengdong D

2017-12-01

Rare variants of major effect play an important role in human complex diseases and can be discovered by sequencing-based genome-wide association studies. Here, we introduce an integrated approach that combines the rare variant association test with gene network and phenotype information to identify risk genes implicated by rare variants for human complex diseases. Our data integration method follows a 'discovery-driven' strategy without relying on prior knowledge about the disease and thus maintains the unbiased character of genome-wide association studies. Simulations reveal that our method can outperform a widely-used rare variant association test method by 2 to 3 times. In a case study of a small disease cohort, we uncovered putative risk genes and the corresponding rare variants that may act as genetic modifiers of congenital heart disease in 22q11.2 deletion syndrome patients. These variants were missed by a conventional approach that relied on the rare variant association test alone.

Whatever the cost? Information integration in memory-based inferences depends on cognitive effort.

PubMed

Hilbig, Benjamin E; Michalkiewicz, Martha; Castela, Marta; Pohl, Rüdiger F; Erdfelder, Edgar

2015-05-01

One of the most prominent models of probabilistic inferences from memory is the simple recognition heuristic (RH). The RH theory assumes that judgments are based on recognition in isolation, such that other information is ignored. However, some prior research has shown that available knowledge is not generally ignored. In line with the notion of adaptive strategy selection--and, thus, a trade-off between accuracy and effort--we hypothesized that information integration crucially depends on how easily accessible information beyond recognition is, how much confidence decision makers have in this information, and how (cognitively) costly it is to acquire it. In three experiments, we thus manipulated (a) the availability of information beyond recognition, (b) the subjective usefulness of this information, and (c) the cognitive costs associated with acquiring this information. In line with the predictions, we found that RH use decreased substantially, the more easily and confidently information beyond recognition could be integrated, and increased substantially with increasing cognitive costs.

Utopia documents: linking scholarly literature with research data

PubMed Central

Attwood, T. K.; Kell, D. B.; McDermott, P.; Marsh, J.; Pettifer, S. R.; Thorne, D.

2010-01-01

Motivation: In recent years, the gulf between the mass of accumulating-research data and the massive literature describing and analyzing those data has widened. The need for intelligent tools to bridge this gap, to rescue the knowledge being systematically isolated in literature and data silos, is now widely acknowledged. Results: To this end, we have developed Utopia Documents, a novel PDF reader that semantically integrates visualization and data-analysis tools with published research articles. In a successful pilot with editors of the Biochemical Journal (BJ), the system has been used to transform static document features into objects that can be linked, annotated, visualized and analyzed interactively (http://www.biochemj.org/bj/424/3/). Utopia Documents is now used routinely by BJ editors to mark up article content prior to publication. Recent additions include integration of various text-mining and biodatabase plugins, demonstrating the system's ability to seamlessly integrate on-line content with PDF articles. Availability: http://getutopia.com Contact: teresa.k.attwood@manchester.ac.uk PMID:20823323

A linear programming computational framework integrates phosphor-proteomics and prior knowledge to predict drug efficacy.

PubMed

Ji, Zhiwei; Wang, Bing; Yan, Ke; Dong, Ligang; Meng, Guanmin; Shi, Lei

2017-12-21

In recent years, the integration of 'omics' technologies, high performance computation, and mathematical modeling of biological processes marks that the systems biology has started to fundamentally impact the way of approaching drug discovery. The LINCS public data warehouse provides detailed information about cell responses with various genetic and environmental stressors. It can be greatly helpful in developing new drugs and therapeutics, as well as improving the situations of lacking effective drugs, drug resistance and relapse in cancer therapies, etc. In this study, we developed a Ternary status based Integer Linear Programming (TILP) method to infer cell-specific signaling pathway network and predict compounds' treatment efficacy. The novelty of our study is that phosphor-proteomic data and prior knowledge are combined for modeling and optimizing the signaling network. To test the power of our approach, a generic pathway network was constructed for a human breast cancer cell line MCF7; and the TILP model was used to infer MCF7-specific pathways with a set of phosphor-proteomic data collected from ten representative small molecule chemical compounds (most of them were studied in breast cancer treatment). Cross-validation indicated that the MCF7-specific pathway network inferred by TILP were reliable predicting a compound's efficacy. Finally, we applied TILP to re-optimize the inferred cell-specific pathways and predict the outcomes of five small compounds (carmustine, doxorubicin, GW-8510, daunorubicin, and verapamil), which were rarely used in clinic for breast cancer. In the simulation, the proposed approach facilitates us to identify a compound's treatment efficacy qualitatively and quantitatively, and the cross validation analysis indicated good accuracy in predicting effects of five compounds. In summary, the TILP model is useful for discovering new drugs for clinic use, and also elucidating the potential mechanisms of a compound to targets.

A biological network-based regularized artificial neural network model for robust phenotype prediction from gene expression data.

PubMed

Kang, Tianyu; Ding, Wei; Zhang, Luoyan; Ziemek, Daniel; Zarringhalam, Kourosh

2017-12-19

Stratification of patient subpopulations that respond favorably to treatment or experience and adverse reaction is an essential step toward development of new personalized therapies and diagnostics. It is currently feasible to generate omic-scale biological measurements for all patients in a study, providing an opportunity for machine learning models to identify molecular markers for disease diagnosis and progression. However, the high variability of genetic background in human populations hampers the reproducibility of omic-scale markers. In this paper, we develop a biological network-based regularized artificial neural network model for prediction of phenotype from transcriptomic measurements in clinical trials. To improve model sparsity and the overall reproducibility of the model, we incorporate regularization for simultaneous shrinkage of gene sets based on active upstream regulatory mechanisms into the model. We benchmark our method against various regression, support vector machines and artificial neural network models and demonstrate the ability of our method in predicting the clinical outcomes using clinical trial data on acute rejection in kidney transplantation and response to Infliximab in ulcerative colitis. We show that integration of prior biological knowledge into the classification as developed in this paper, significantly improves the robustness and generalizability of predictions to independent datasets. We provide a Java code of our algorithm along with a parsed version of the STRING DB database. In summary, we present a method for prediction of clinical phenotypes using baseline genome-wide expression data that makes use of prior biological knowledge on gene-regulatory interactions in order to increase robustness and reproducibility of omic-scale markers. The integrated group-wise regularization methods increases the interpretability of biological signatures and gives stable performance estimates across independent test sets.

A constrained regularization method for inverting data represented by linear algebraic or integral equations

NASA Astrophysics Data System (ADS)

Provencher, Stephen W.

1982-09-01

CONTIN is a portable Fortran IV package for inverting noisy linear operator equations. These problems occur in the analysis of data from a wide variety experiments. They are generally ill-posed problems, which means that errors in an unregularized inversion are unbounded. Instead, CONTIN seeks the optimal solution by incorporating parsimony and any statistical prior knowledge into the regularizor and absolute prior knowledge into equallity and inequality constraints. This can be greatly increase the resolution and accuracyh of the solution. CONTIN is very flexible, consisting of a core of about 50 subprograms plus 13 small "USER" subprograms, which the user can easily modify to specify special-purpose constraints, regularizors, operator equations, simulations, statistical weighting, etc. Specjial collections of USER subprograms are available for photon correlation spectroscopy, multicomponent spectra, and Fourier-Bessel, Fourier and Laplace transforms. Numerically stable algorithms are used throughout CONTIN. A fairly precise definition of information content in terms of degrees of freedom is given. The regularization parameter can be automatically chosen on the basis of an F-test and confidence region. The interpretation of the latter and of error estimates based on the covariance matrix of the constrained regularized solution are discussed. The strategies, methods and options in CONTIN are outlined. The program itself is described in the following paper.

Knowledge Integration in Global R&D Networks

NASA Astrophysics Data System (ADS)

Erkelens, Rose; van den Hooff, Bart; Vlaar, Paul; Huysman, Marleen

This paper reports a qualitative study conducted at multinational organizations' R&D departments about their process of knowledge integration. Taking into account the knowledge based view (KBV) of the firm and the practice-based view of knowledge, and building on the literatures concerning specialization and integration of knowledge in organizations, we explore which factors may have a significant influence on the integration process of knowledge between R&D units. The findings indicated (1) the contribution of relevant factors influencing knowledge integration processes and (2) a thoughtful balance between engineering and emergent approaches to be helpful in understanding and overcoming knowledge integration issues.

Language knowledge and event knowledge in language use

PubMed Central

Willits, Jon A.; Amato, Michael S.; MacDonald, Maryellen C.

2018-01-01

This paper examines how semantic knowledge is used in language comprehension and in making judgments about events in the world. We contrast knowledge gleaned from prior language experience (“language knowledge”) and knowledge coming from prior experience with the world (“world knowledge”). In two corpus analyses, we show that previous research linking verb aspect and event representations have confounded language and world knowledge. Then, using carefully chosen stimuli that remove this confound, we performed four experiments that manipulated the degree to which language knowledge or world knowledge should be salient and relevant to performing a task, finding in each case that participants use the type of knowledge most appropriate to the task. These results provide evidence for a highly context-sensitive and interactionist perspective on how semantic knowledge is represented and used during language processing. PMID:25791750

An empirical Bayes approach to network recovery using external knowledge.

PubMed

Kpogbezan, Gino B; van der Vaart, Aad W; van Wieringen, Wessel N; Leday, Gwenaël G R; van de Wiel, Mark A

2017-09-01

Reconstruction of a high-dimensional network may benefit substantially from the inclusion of prior knowledge on the network topology. In the case of gene interaction networks such knowledge may come for instance from pathway repositories like KEGG, or be inferred from data of a pilot study. The Bayesian framework provides a natural means of including such prior knowledge. Based on a Bayesian Simultaneous Equation Model, we develop an appealing Empirical Bayes (EB) procedure that automatically assesses the agreement of the used prior knowledge with the data at hand. We use variational Bayes method for posterior densities approximation and compare its accuracy with that of Gibbs sampling strategy. Our method is computationally fast, and can outperform known competitors. In a simulation study, we show that accurate prior data can greatly improve the reconstruction of the network, but need not harm the reconstruction if wrong. We demonstrate the benefits of the method in an analysis of gene expression data from GEO. In particular, the edges of the recovered network have superior reproducibility (compared to that of competitors) over resampled versions of the data. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

78 FR 29071 - Assessment of Mediation and Arbitration Procedures

Federal Register 2010, 2011, 2012, 2013, 2014

2013-05-17

... proceeding. Program participants in the new arbitration program will have prior knowledge of the issues to be... final rules, all parties opting into the arbitration program will have full prior knowledge that these... including discovery, the submission of evidence, and the treatment of confidential information, and the...

Teaching Practice: A Perspective on Inter-Text and Prior Knowledge

ERIC Educational Resources Information Center

Costley, Kevin C.; West, Howard G.

2012-01-01

The use of teaching practices that involve intertextual relationship discovery in today's elementary classrooms is increasingly essential to the success of young learners of reading. Teachers must constantly strive to expand their perspective of how to incorporate the dialogue included in prior knowledge assessment. Teachers must also consider how…

Elaborative-Interrogation and Prior-Knowledge Effects on Learning of Facts.

ERIC Educational Resources Information Center

Woloshyn, Vera E.; And Others

1992-01-01

The differences among elaborative-interrogation, reading-to-understand, and no-exposure control conditions with familiar domain material in contrast to unfamiliar domain material were studied for 50 Canadian and 50 west German undergraduates. Results provide evidence of effects of both elaborative interrogation and prior knowledge on learning.…

Effects of Example Variability and Prior Knowledge in How Students Learn to Solve Equations

ERIC Educational Resources Information Center

Guo, Jian-Peng; Yang, Ling-Yan; Ding, Yi

2014-01-01

Researchers have consistently demonstrated that multiple examples are better than one example in facilitating learning because the comparison evoked by multiple examples supports learning and transfer. However, research outcomes are unclear regarding the effects of example variability and prior knowledge on learning from comparing multiple…

Relationship of Students' Prior Knowledge and Order of Questions on Tests to Students' Test Scores.

ERIC Educational Resources Information Center

Papp, Klara K.; And Others

1987-01-01

A study examined whether students beginning a cell biology course with prior knowledge of its three areas (genetics, histology, and biochemistry) would retain that advantage throughout the course and whether achievement was influenced by the order of questions in a test. (MSE)

The Impact of Prior Programming Knowledge on Lecture Attendance and Final Exam

ERIC Educational Resources Information Center

Veerasamy, Ashok Kumar; D'Souza, Daryl; Lindén, Rolf; Laakso, Mikko-Jussi

2018-01-01

In this article, we report the results of the impact of prior programming knowledge (PPK) on lecture attendance (LA) and on subsequent final programming exam performance in a university level introductory programming course. This study used Spearman's rank correlation coefficient, multiple regression, Kruskal-Wallis, and Bonferroni correction…

Composing Knowledge: Writing, Rhetoric, and Reflection in Prior Learning Assessment

ERIC Educational Resources Information Center

Leaker, Cathy; Ostman, Heather

2010-01-01

In this article, we argue that prior learning assessment (PLA) essays manifest a series of issues central to composition research and practice: they foreground the "contact zone" between the unauthorized writer, institutional power, and the articulation of knowledge claims; they reinforce the central role of a multifaceted approach to…

Using Analogies to Facilitate Conceptual Change in Mathematics Learning

ERIC Educational Resources Information Center

Vamvakoussi, Xenia

2017-01-01

The problem of adverse effects of prior knowledge in mathematics learning has been amply documented and theorized by mathematics educators as well as cognitive/developmental psychologists. This problem emerges when students' prior knowledge about a mathematical notion comes in contrast with new information coming from instruction, giving rise to…

Specific Previous Experience Affects Perception of Harmony and Meter

ERIC Educational Resources Information Center

Creel, Sarah C.

2011-01-01

Prior knowledge shapes our experiences, but which prior knowledge shapes which experiences? This question is addressed in the domain of music perception. Three experiments were used to determine whether listeners activate specific musical memories during music listening. Each experiment provided listeners with one of two musical contexts that was…

Pre-Test Assessment

ERIC Educational Resources Information Center

Berry, Thomas

2008-01-01

Pre-tests are a non-graded assessment tool used to determine pre-existing subject knowledge. Typically pre-tests are administered prior to a course to determine knowledge baseline, but here they are used to test students prior to topical material coverage throughout the course. While counterintuitive, the pre-tests cover material the student is…

COMPUTING THERAPY FOR PRECISION MEDICINE: COLLABORATIVE FILTERING INTEGRATES AND PREDICTS MULTI-ENTITY INTERACTIONS.

PubMed

Regenbogen, Sam; Wilkins, Angela D; Lichtarge, Olivier

2016-01-01

Biomedicine produces copious information it cannot fully exploit. Specifically, there is considerable need to integrate knowledge from disparate studies to discover connections across domains. Here, we used a Collaborative Filtering approach, inspired by online recommendation algorithms, in which non-negative matrix factorization (NMF) predicts interactions among chemicals, genes, and diseases only from pairwise information about their interactions. Our approach, applied to matrices derived from the Comparative Toxicogenomics Database, successfully recovered Chemical-Disease, Chemical-Gene, and Disease-Gene networks in 10-fold cross-validation experiments. Additionally, we could predict each of these interaction matrices from the other two. Integrating all three CTD interaction matrices with NMF led to good predictions of STRING, an independent, external network of protein-protein interactions. Finally, this approach could integrate the CTD and STRING interaction data to improve Chemical-Gene cross-validation performance significantly, and, in a time-stamped study, it predicted information added to CTD after a given date, using only data prior to that date. We conclude that collaborative filtering can integrate information across multiple types of biological entities, and that as a first step towards precision medicine it can compute drug repurposing hypotheses.

COMPUTING THERAPY FOR PRECISION MEDICINE: COLLABORATIVE FILTERING INTEGRATES AND PREDICTS MULTI-ENTITY INTERACTIONS

PubMed Central

REGENBOGEN, SAM; WILKINS, ANGELA D.; LICHTARGE, OLIVIER

2015-01-01

Biomedicine produces copious information it cannot fully exploit. Specifically, there is considerable need to integrate knowledge from disparate studies to discover connections across domains. Here, we used a Collaborative Filtering approach, inspired by online recommendation algorithms, in which non-negative matrix factorization (NMF) predicts interactions among chemicals, genes, and diseases only from pairwise information about their interactions. Our approach, applied to matrices derived from the Comparative Toxicogenomics Database, successfully recovered Chemical-Disease, Chemical-Gene, and Disease-Gene networks in 10-fold cross-validation experiments. Additionally, we could predict each of these interaction matrices from the other two. Integrating all three CTD interaction matrices with NMF led to good predictions of STRING, an independent, external network of protein-protein interactions. Finally, this approach could integrate the CTD and STRING interaction data to improve Chemical-Gene cross-validation performance significantly, and, in a time-stamped study, it predicted information added to CTD after a given date, using only data prior to that date. We conclude that collaborative filtering can integrate information across multiple types of biological entities, and that as a first step towards precision medicine it can compute drug repurposing hypotheses. PMID:26776170

The Interpretation of a Knowledge Claim in the Recognition of Prior Learning (RPL) and the Impact of This on RPL Practice

ERIC Educational Resources Information Center

de Graaff, Frederika

2014-01-01

The question addressed in this paper is: what does a knowledge claim consist of in the context of the Recognition of Prior Learning (RPL)? The research comprises a case study of RPL applicants' entry into a postgraduate diploma (a fourth-year programme) in project management. The focus is on the knowledge claims made as part of the RPL application…

Transfer Learning of Classification Rules for Biomarker Discovery and Verification from Molecular Profiling Studies

PubMed Central

Ganchev, Philip; Malehorn, David; Bigbee, William L.; Gopalakrishnan, Vanathi

2013-01-01

We present a novel framework for integrative biomarker discovery from related but separate data sets created in biomarker profiling studies. The framework takes prior knowledge in the form of interpretable, modular rules, and uses them during the learning of rules on a new data set. The framework consists of two methods of transfer of knowledge from source to target data: transfer of whole rules and transfer of rule structures. We evaluated the methods on three pairs of data sets: one genomic and two proteomic. We used standard measures of classification performance and three novel measures of amount of transfer. Preliminary evaluation shows that whole-rule transfer improves classification performance over using the target data alone, especially when there is more source data than target data. It also improves performance over using the union of the data sets. PMID:21571094

The impact of group membership on collaborative learning with wikis.

PubMed

Matschke, Christina; Moskaliuk, Johannes; Kimmerle, Joachim

2013-02-01

The social web stimulates learning through collaboration. However, information in the social web is often associated with information about its author. Based on previous evidence that ingroup information is preferred to outgroup information, the current research investigates whether group memberships of wiki authors affect learning. In an experimental study, we manipulated the group memberships (ingroup vs. outgroup) of wiki authors by using nicknames. The designated group memberships (being fans of a soccer team or not) were completely irrelevant for the domain of the wiki (the medical disorder fibromyalgia). Nevertheless, wiki information from the ingroup led to more integration of information into prior knowledge as well as more increase of factual knowledge than information from the outgroup. The results demonstrate that individuals apply social selection strategies when considering information from wikis, which may foster, but also hinder, learning and collaboration. Practical implications for collaborative learning in the social web are discussed.

Process analytical technology in the pharmaceutical industry: a toolkit for continuous improvement.

PubMed

Scott, Bradley; Wilcock, Anne

2006-01-01

Process analytical technology (PAT) refers to a series of tools used to ensure that quality is built into products while at the same time improving the understanding of processes, increasing efficiency, and decreasing costs. It has not been widely adopted by the pharmaceutical industry. As the setting for this paper, the current pharmaceutical manufacturing paradigm and PAT guidance to date are discussed prior to the review of PAT principles and tools, benefits, and challenges. The PAT toolkit contains process analyzers, multivariate analysis tools, process control tools, and continuous improvement/knowledge management/information technology systems. The integration and implementation of these tools is complex, and has resulted in uncertainty with respect to both regulation and validation. The paucity of staff knowledgeable in this area may complicate adoption. Studies to quantitate the benefits resulting from the adoption of PAT within the pharmaceutical industry would be a valuable addition to the qualitative studies that are currently available.

International Dengue Vaccine Communication and Advocacy: Challenges and Way Forward.

PubMed

Carvalho, Ana; Van Roy, Rebecca; Andrus, Jon

2016-01-01

Dengue vaccine introduction will likely occur soon. However, little has been published on international dengue vaccine communication and advocacy. More effort at the international level is required to review, unify and strategically disseminate dengue vaccine knowledge to endemic countries' decision makers and potential donors. Waiting to plan for the introduction of new vaccines until licensure may delay access in developing countries. Concerted efforts to communicate and advocate for vaccines prior to licensure are likely challenged by unknowns of the use of dengue vaccines and the disease, including uncertainties of vaccine impact, vaccine access and dengue's complex pathogenesis and epidemiology. Nevertheless, the international community has the opportunity to apply previous best practices for vaccine communication and advocacy. The following key strategies will strengthen international dengue vaccine communication and advocacy: consolidating existing coalitions under one strategic umbrella, urgently convening stakeholders to formulate the roadmap for integrated dengue prevention and control, and improving the dissemination of dengue scientific knowledge.

The Impact of Group Membership on Collaborative Learning with Wikis

PubMed Central

Matschke, Christina; Moskaliuk, Johannes

2013-01-01

Abstract The social web stimulates learning through collaboration. However, information in the social web is often associated with information about its author. Based on previous evidence that ingroup information is preferred to outgroup information, the current research investigates whether group memberships of wiki authors affect learning. In an experimental study, we manipulated the group memberships (ingroup vs. outgroup) of wiki authors by using nicknames. The designated group memberships (being fans of a soccer team or not) were completely irrelevant for the domain of the wiki (the medical disorder fibromyalgia). Nevertheless, wiki information from the ingroup led to more integration of information into prior knowledge as well as more increase of factual knowledge than information from the outgroup. The results demonstrate that individuals apply social selection strategies when considering information from wikis, which may foster, but also hinder, learning and collaboration. Practical implications for collaborative learning in the social web are discussed. PMID:23113690

Global-constrained hidden Markov model applied on wireless capsule endoscopy video segmentation

NASA Astrophysics Data System (ADS)

Wan, Yiwen; Duraisamy, Prakash; Alam, Mohammad S.; Buckles, Bill

2012-06-01

Accurate analysis of wireless capsule endoscopy (WCE) videos is vital but tedious. Automatic image analysis can expedite this task. Video segmentation of WCE into the four parts of the gastrointestinal tract is one way to assist a physician. The segmentation approach described in this paper integrates pattern recognition with statiscal analysis. Iniatially, a support vector machine is applied to classify video frames into four classes using a combination of multiple color and texture features as the feature vector. A Poisson cumulative distribution, for which the parameter depends on the length of segments, models a prior knowledge. A priori knowledge together with inter-frame difference serves as the global constraints driven by the underlying observation of each WCE video, which is fitted by Gaussian distribution to constrain the transition probability of hidden Markov model.Experimental results demonstrated effectiveness of the approach.

Creating illusions of knowledge: learning errors that contradict prior knowledge.

PubMed

Fazio, Lisa K; Barber, Sarah J; Rajaram, Suparna; Ornstein, Peter A; Marsh, Elizabeth J

2013-02-01

Most people know that the Pacific is the largest ocean on Earth and that Edison invented the light bulb. Our question is whether this knowledge is stable, or if people will incorporate errors into their knowledge bases, even if they have the correct knowledge stored in memory. To test this, we asked participants general-knowledge questions 2 weeks before they read stories that contained errors (e.g., "Franklin invented the light bulb"). On a later general-knowledge test, participants reproduced story errors despite previously answering the questions correctly. This misinformation effect was found even for questions that were answered correctly on the initial test with the highest level of confidence. Furthermore, prior knowledge offered no protection against errors entering the knowledge base; the misinformation effect was equivalent for previously known and unknown facts. Errors can enter the knowledge base even when learners have the knowledge necessary to catch the errors. 2013 APA, all rights reserved

Age differences in suggestibility to contradictions of demonstrated knowledge: the influence of prior knowledge.

PubMed

Umanath, Sharda

2016-11-01

People maintain intact general knowledge into very old age and use it to support remembering. Interestingly, when older and younger adults encounter errors that contradict general knowledge, older adults suffer fewer memorial consequences: Older adults use fewer recently-encountered errors as answers for later knowledge questions. Why do older adults show this reduced suggestibility, and what role does their intact knowledge play? In three experiments, I examined suggestibility following exposure to errors in fictional stories that contradict general knowledge. Older adults consistently demonstrated more prior knowledge than younger adults but also gained access to even more across time. Additionally, they did not show a reduction in new learning from the stories, indicating lesser involvement of episodic memory failures. Critically, when knowledge was stably accessible, older adults relied more heavily on that knowledge compared to younger adults, resulting in reduced suggestibility. Implications for the broader role of knowledge in aging are discussed.

Cognitive patterns of neuroanatomy concepts: Knowledge organizations that emerge from problem solving versus information gathering

NASA Astrophysics Data System (ADS)

Weidner, Jeanne Margaret O'malley

2000-10-01

This study was motivated by some of the claims that are found in the literature on Problem-Based Learning (PBL). This instructional technique, which uses case studies as its primary instructional tool, has been advanced as an alternative to traditional instruction in order to foster more meaningful, integrative learning of scientific concepts. Several of the advantages attributed to Problem-Based Learning are that it (1) is generally preferred by students because it appears to foster a more nurturing and enjoyable learning experience, (2) fosters greater retention of knowledge and concepts acquired, and (3) results in increased ability to apply this knowledge toward solving new problems. This study examines the differences that result when students learn neuroanatomy concepts under two instructional contexts: problem solving vs. information gathering. The technological resource provided to students to support learning under each of these contexts was the multimedia program BrainStorm: An Interactive Neuroanatomy Atlas (Coppa & Tancred, 1995). The study explores the influence of context with regard to subjects' performance on objective post-tests, organization of knowledge as measured by Pathfinder Networks, differential use of the multimedia software and discourse differences emerging from the transcripts. The findings support previous research in the literature that problem-solving results in less knowledge acquisition in the short term, greater retention of material over time, and a subjects' preference for the method. However, both the degree of retention and preference were influenced by subjects' prior knowledge of the material in the exercises, as there was a significant difference in performance between the two exercises: for the exercise about which subjects appeared to have greater background information, memory decay was less, and subject attitude toward the problem solving instructional format was more favorable, than for the exercise for which subjects had less prior knowledge. Subjects also used the software differently under each format with regard to modules accessed, time spent in modules, and types of information sought. In addition, analyses of the transcripts showed more numerous occurrences of explanations and summarizations in the problem-solving context, compared to the information gathering context. The attempts to show significant differences between the contexts by means of Pathfinder analyses were less than successful.

Using children's literature to enhance views of nature of science and scientific attitude in fourth graders

NASA Astrophysics Data System (ADS)

Hampton, Kathryn Walker

This project was an effort to study the effect of integrating children's trade books into the fourth grade science curriculum on the students' views of the nature of science and their scientific attitude. The effect on the students' reading and language achievement, and science content knowledge was also analyzed. This was done by comparing the nature of science views and scientific attitudes, reading and language achievement scores, and the science grades of the treatment group, prior to and immediately following the intervention period, with the control group which did not participate in the integration of children's books. The science teacher's views on the nature of science and her attitude towards teaching science were also evaluated prior to and after the intervention. The selected trade books were evaluated for their coverage of nature of science aspects. Three intact classes of fourth grade students from a local elementary school were involved in the study along with their science and reading teacher. Two of the classes made up the experimental group and the remaining class served as the control group. All students were assessed prior to the intervention phase on their views of the nature of science and scientific attitudes. The experimental group was engaged in reading selected science trade books during their science class and study hall over a semester period. The results of the study showed a significant difference in the groups' initial reading and language achievement, which may have affected the lack of an effect from the intervention. The instrument selected to assess the student's views on the nature of science and scientific attitude (SAI II) was not reliable with this group. There was no significant difference on the students' science content knowledge as measured by their semester grade averages. The results from the teacher's response on the STAS II did indicate slight changes on her views on the nature of science. Sixty-nine of the eighty-three children's trade books selected had one or more aspects of the nature of science included.

MRAC Control with Prior Model Knowledge for Asymmetric Damaged Aircraft

PubMed Central

Zhang, Jing

2015-01-01

This paper develops a novel state-tracking multivariable model reference adaptive control (MRAC) technique utilizing prior knowledge of plant models to recover control performance of an asymmetric structural damaged aircraft. A modification of linear model representation is given. With prior knowledge on structural damage, a polytope linear parameter varying (LPV) model is derived to cover all concerned damage conditions. An MRAC method is developed for the polytope model, of which the stability and asymptotic error convergence are theoretically proved. The proposed technique reduces the number of parameters to be adapted and thus decreases computational cost and requires less input information. The method is validated by simulations on NASA generic transport model (GTM) with damage. PMID:26180839

Pilot Study Evaluating a Practice-Based Learning and Improvement Curriculum Focusing on the Development of System-Level Quality Improvement Skills

PubMed Central

Tomolo, Anne M; Lawrence, Renée H; Watts, Brook; Augustine, Sarah; Aron, David C; Singh, Mamta K

2011-01-01

Background We developed a practice-based learning and improvement (PBLI) curriculum to address important gaps in components of content and experiential learning activities through didactics and participation in systems-level quality improvement projects that focus on making changes in health care processes. Methods We evaluated the impact of our curriculum on resident PBLI knowledge, self-efficacy, and application skills. A quasi-experimental design assessed the impact of a curriculum (PBLI quality improvement systems compared with non-PBLI) on internal medicine residents' learning during a 4-week ambulatory block. We measured application skills, self-efficacy, and knowledge by using the Systems Quality Improvement Training and Assessment Tool. Exit evaluations assessed time invested and experiences related to the team projects and suggestions for improving the curriculum. Results The 2 groups showed differences in change scores. Relative to the comparison group, residents in the PBLI curriculum demonstrated a significant increase in the belief about their ability to implement a continuous quality improvement project (P  =  .020), comfort level in developing data collection plans (P  =  .010), and total knowledge scores (P < .001), after adjusting for prior PBLI experience. Participants in the PBLI curriculum also demonstrated significant improvement in providing a more complete aim statement for a proposed project after adjusting for prior PBLI experience (P  =  .001). Exit evaluations were completed by 96% of PBLI curriculum participants who reported high satisfaction with team performance. Conclusion Residents in our curriculum showed gains in areas fundamental for PBLI competency. The observed improvements were related to fundamental quality improvement knowledge, with limited gain in application skills. This suggests that while heading in the right direction, we need to conceptualize and structure PBLI training in a way that integrates it throughout the residency program and fosters the application of this knowledge and these skills. PMID:22379523

Pilot study evaluating a practice-based learning and improvement curriculum focusing on the development of system-level quality improvement skills.

PubMed

Tomolo, Anne M; Lawrence, Renée H; Watts, Brook; Augustine, Sarah; Aron, David C; Singh, Mamta K

2011-03-01

We developed a practice-based learning and improvement (PBLI) curriculum to address important gaps in components of content and experiential learning activities through didactics and participation in systems-level quality improvement projects that focus on making changes in health care processes. We evaluated the impact of our curriculum on resident PBLI knowledge, self-efficacy, and application skills. A quasi-experimental design assessed the impact of a curriculum (PBLI quality improvement systems compared with non-PBLI) on internal medicine residents' learning during a 4-week ambulatory block. We measured application skills, self-efficacy, and knowledge by using the Systems Quality Improvement Training and Assessment Tool. Exit evaluations assessed time invested and experiences related to the team projects and suggestions for improving the curriculum. The 2 groups showed differences in change scores. Relative to the comparison group, residents in the PBLI curriculum demonstrated a significant increase in the belief about their ability to implement a continuous quality improvement project (P  =  .020), comfort level in developing data collection plans (P  =  .010), and total knowledge scores (P < .001), after adjusting for prior PBLI experience. Participants in the PBLI curriculum also demonstrated significant improvement in providing a more complete aim statement for a proposed project after adjusting for prior PBLI experience (P  =  .001). Exit evaluations were completed by 96% of PBLI curriculum participants who reported high satisfaction with team performance. Residents in our curriculum showed gains in areas fundamental for PBLI competency. The observed improvements were related to fundamental quality improvement knowledge, with limited gain in application skills. This suggests that while heading in the right direction, we need to conceptualize and structure PBLI training in a way that integrates it throughout the residency program and fosters the application of this knowledge and these skills.

Resident physician's knowledge and attitudes toward biostatistics and research methods concepts.

PubMed

Alzahrani, Sami H; Aba Al-Khail, Bahaa A

2015-10-01

To assess the knowledge and attitudes of resident physicians toward biostatistics and research methodology concepts. We conducted a cross-sectional study between November 2014 and October 2014 at King Abdulaziz University Hospital, Jeddah, Kingdom of Saudi Arabia. A self-administered questionnaire was distributed to all participants. The response rate was 90%. One hundred sixty-two resident completed the questionnaire. Most residents were well-informed in basic concepts, such as, "P" values, study power, and case control studies; more than half had confidence in interpreting the results of scientific papers. Conversely, more than 67% of the residents were not knowledgeable on more sophisticated terms in biostatistics. Residents with previous training in evidence-based medicine (EBM) (p=0.05) and non-specialist residents (p=0.003) were more likely to have better knowledge scores. Females (p=0.003), and those with previous training in biostatistics and epidemiology had positive attitude toward biostatistics (p less than 0.001 in both cases). Residents who read medical journals scored lower than those who never read journals (p=0.001). Prior courses in EBM, as well as male gender were associated with knowledge scores. Reinforcing training after graduation from medical school with special focus on integrating biostatistics with epidemiology and research methods is needed.

The influence of text cohesion and picture detail on young readers' knowledge of science topics.

PubMed

Désiron, Juliette C; de Vries, Erica; Bartel, Anna N; Varahamurti, Nalini

2017-10-16

The effects of text cohesion and added pictures on acquired knowledge have been heavily studied each in isolation. Furthermore, studies on the effects of specific characteristics of pictures, whether facilitating or hindering, are scarce. Schnotz's ITCP Model (2014) allows to formulate hypotheses regarding the combined effect of text cohesion and presence and level of detail of a picture. This study investigates these hypotheses in the case of children reading scientific texts. One hundred and one-second-, third-, and fourth-grade pupils with a mean age of 9 years, in the western United States. Data were collected over three sessions to encompass an understanding of each pupil's knowledge based on prior sessions. Results showed a significant increase in pupils' knowledge between pre-test and immediate post-test, but as hypothesized, no significant difference between levels of cohesion. No significant difference between types of pictures was detected. After 1 week, knowledge built with a high cohesive text significantly dropped with low-detail picture, whereas, with high detail, or no picture, there was no significant difference. Results suggested that when participants were given a low-detail picture with a low cohesive text, the integration process of the material was more restricted than with a high cohesive text. © 2017 The British Psychological Society.

Outside-In Systems Pharmacology Combines Innovative Computational Methods With High-Throughput Whole Vertebrate Studies.

PubMed

Schulthess, Pascal; van Wijk, Rob C; Krekels, Elke H J; Yates, James W T; Spaink, Herman P; van der Graaf, Piet H

2018-04-25

To advance the systems approach in pharmacology, experimental models and computational methods need to be integrated from early drug discovery onward. Here, we propose outside-in model development, a model identification technique to understand and predict the dynamics of a system without requiring prior biological and/or pharmacological knowledge. The advanced data required could be obtained by whole vertebrate, high-throughput, low-resource dose-exposure-effect experimentation with the zebrafish larva. Combinations of these innovative techniques could improve early drug discovery. © 2018 The Authors CPT: Pharmacometrics & Systems Pharmacology published by Wiley Periodicals, Inc. on behalf of American Society for Clinical Pharmacology and Therapeutics.

Potentiation in young infants: The origin of the prior knowledge effect?

PubMed Central

Barr, Rachel; Rovee-Collier, Carolyn; Learmonth, Amy

2011-01-01

In two experiments with 6-month-old infants, we found that prior learning of an operant task (remembered for 2 weeks) mediated new learning of a modeling event (remembered for only 1 day) and increased its recall. Infants first learned to associate lever pressing with moving a toy train housed in a large box. One or 2 weeks later, three target actions were modeled on a hand puppet while the train box (a retrieval cue) was in view. Merely retrieving the train memory strengthened it, and simultaneously pairing its retrieved memory with the modeled actions potentiated their learning and recall. When paired 1 week later, deferred imitation increased from 1 day to 4 weeks; when paired 2 weeks later, it increased from 1 day to 6 weeks. The striking parallels between potentiated learning in infants and the prior knowledge effect in adults suggests that the prior knowledge effect originates in early infancy. PMID:21264602

When Relationships Depicted Diagrammatically Conflict with Prior Knowledge: An Investigation of Students' Interpretations of Evolutionary Trees

ERIC Educational Resources Information Center

Novick, Laura R.; Catley, Kefyn M.

2014-01-01

Science is an important domain for investigating students' responses to information that contradicts their prior knowledge. In previous studies of this topic, this information was communicated verbally. The present research used diagrams, specifically trees (cladograms) depicting evolutionary relationships among taxa. Effects of college…

Building Knowledge through Portfolio Learning in Prior Learning Assessment and Recognition

ERIC Educational Resources Information Center

Conrad, Dianne

2008-01-01

It is important for academic credibility that the process of prior learning assessment and recognition (PLAR) keeps learning and knowledge as its foundational tenets. Doing so ensures PLAR's recognition as a fertile ground for learners' cognitive and personal growth. In many postsecondary venues, PLAR is often misunderstood and confused with…

Temporal Learning in 4 1/2- and 6-Year-Old Children: Role of Instructions and Prior Knowledge.

ERIC Educational Resources Information Center

Droit, Sylvie; And Others

1990-01-01

Examined the role of prior temporal knowledge of 4 1/2- and 6-year-olds through the use of high-rate, interval, and minimal instructions in a fixed-interval training schedule. Determined that the subjects' learning depended on their verbal self-control skills. (BC)

Understanding the Complexities of Prior Knowledge

ERIC Educational Resources Information Center

Soiferman, L. Karen

2014-01-01

The purpose of the study was to gain an understanding of the kinds of prior knowledge students bring with them from high school as it relates to the conventions of writing that they are expected to follow in ARTS 1110 Introduction to University. The research questions were "Can first-year students taking the Arts 1110 Introduction to…

An Effectiveness Index and Profile for Instructional Media.

ERIC Educational Resources Information Center

Bond, Jack H.

A scale was developed for judging the relative value of various media in teaching children. Posttest scores were partitioned into several components: error, prior knowledge, guessing, and gain from the learning exercise. By estimating the amounts of prior knowledge, guessing, and error, and then subtracting these from the total score, an index of…

Making Connections in Math: Activating a Prior Knowledge Analogue Matters for Learning

ERIC Educational Resources Information Center

Sidney, Pooja G.; Alibali, Martha W.

2015-01-01

This study investigated analogical transfer of conceptual structure from a prior-knowledge domain to support learning in a new domain of mathematics: division by fractions. Before a procedural lesson on division by fractions, fifth and sixth graders practiced with a surface analogue (other operations on fractions) or a structural analogue (whole…

An Investigation of the Relationships between Prior Knowledge and Vocabulary Development with Culturally Diverse Students.

ERIC Educational Resources Information Center

Karbon, Jacqueline C.

Using a semantic mapping technique for vocabulary instruction, a study explored how children of diverse groups bring different cultural backgrounds and prior knowledge to tasks involved in learning new words. The study was conducted in three sixth-grade classrooms--one containing rural Native American (especially Menominee) children, another…

The Influence of Prior Knowledge on Perception and Action: Relationships to Autistic Traits

ERIC Educational Resources Information Center

Buckingham, Gavin; Michelakakis, Elizabeth Evgenia; Rajendran, Gnanathusharan

2016-01-01

Autism is characterised by a range of perceptual and sensorimotor deficits, which might be related to abnormalities in how autistic individuals use prior knowledge. We investigated this proposition in a large non-clinical population in the context of the size-weight illusion, where individual's expectations about object weight influence their…

Interplay of Prior Knowledge, Self-Regulation and Motivation in Complex Multimedia Learning Environments

ERIC Educational Resources Information Center

Song, H. S.; Kalet, A. L.; Plass, J. L.

2016-01-01

This study examined the direct and indirect effects of medical clerkship students' prior knowledge, self-regulation and motivation on learning performance in complex multimedia learning environments. The data from 386 medical clerkship students from six medical schools were analysed using structural equation modeling. The structural model revealed…

Effects of Students' Prior Knowledge on Scientific Reasoning in Density.

ERIC Educational Resources Information Center

Yang, Il-Ho; Kwon, Yong-Ju; Kim, Young-Shin; Jang, Myoung-Duk; Jeong, Jin-Woo; Park, Kuk-Tae

2002-01-01

Investigates the effects of students' prior knowledge on the scientific reasoning processes of performing the task of controlling variables with computer simulation and identifies a number of problems that students encounter in scientific discovery. Involves (n=27) 5th grade students and (n=33) 7th grade students. Indicates that students' prior…

Relationship of Prior Knowledge and Working Engineers' Learning Preferences: Implications for Designing Effective Instruction

ERIC Educational Resources Information Center

Baukal, Charles E.; Ausburn, Lynna J.

2017-01-01

Continuing engineering education (CEE) is important to ensure engineers maintain proficiency over the life of their careers. However, relatively few studies have examined designing effective training for working engineers. Research has indicated that both learner instructional preferences and prior knowledge can impact the learning process, but it…

The Influence of Prior Knowledge and Viewing Repertoire on Learning from Video

ERIC Educational Resources Information Center

de Boer, Jelle; Kommers, Piet A. M.; de Brock, Bert; Tolboom, Jos

2016-01-01

Video is increasingly used as an instructional tool. It is therefore becoming more important to improve learning of students from video. We investigated whether student learning effects are influenced through an instruction about other viewing behaviours, and whether these learning effects depend on their prior knowledge. In a controlled…

Prior Knowledge and Online Inquiry-Based Science Reading: Evidence from Eye Tracking

ERIC Educational Resources Information Center

Ho, Hsin Ning Jessie; Tsai, Meng-Jung; Wang, Ching-Yeh; Tsai, Chin-Chung

2014-01-01

This study employed eye-tracking technology to examine how students with different levels of prior knowledge process text and data diagrams when reading a web-based scientific report. Students' visual behaviors were tracked and recorded when they read a report demonstrating the relationship between the greenhouse effect and global climate…

Students' Achievement in Relation to Reasoning Ability, Prior Knowledge and Gender

ERIC Educational Resources Information Center

Yenilmez, Ayse; Sungur, Semra; Tekkaya, Ceren

2006-01-01

This study investigated students' achievement regarding photosynthesis and respiration in plants in relation to reasoning ability, prior knowledge and gender. A total of 117 eighth-grade students participated in the study. Test of logical thinking and the two-tier multiple choice tests were administered to determine students' reasoning ability and…

The Effectiveness of Using Incorrect Examples to Support Learning about Decimal Magnitude

ERIC Educational Resources Information Center

Durkin, Kelley; Rittle-Johnson, Bethany

2012-01-01

Comparing common mathematical errors to correct examples may facilitate learning, even for students with limited prior domain knowledge. We examined whether studying incorrect and correct examples was more effective than studying two correct examples across prior knowledge levels. Fourth- and fifth-grade students (N = 74) learned about decimal…

Students' inductive reasoning skills and the relevance of prior knowledge: an exploratory study with a computer-based training course on the topic of acne vulgaris.

PubMed

Horn-Ritzinger, Sabine; Bernhardt, Johannes; Horn, Michael; Smolle, Josef

2011-04-01

The importance of inductive instruction in medical education is increasingly growing. Little is known about the relevance of prior knowledge regarding students' inductive reasoning abilities. The purpose is to evaluate this inductive teaching method as a means of fostering higher levels of learning and to explore how individual differences in prior knowledge (high [HPK] vs. low [LPK]) contribute to students' inductive reasoning skills. Twenty-six LPK and 18 HPK students could train twice with an interactive computer-based training object to discover the underlying concept before doing the final comprehension check. Students had a median of 76.9% of correct answers in the first, 90.9% in the second training, and answered 92% of the final assessment questions correctly. More important, 86% of all students succeeded with inductive learning, among them 83% of the HPK students and 89% of the LPK students. Prior knowledge did not predict performance on overall comprehension. This inductive instructional strategy fostered students' deep approaches to learning in a time-effective way.

Relationship of resident characteristics, attitudes, prior training and clinical knowledge to communication skills performance.

PubMed

Laidlaw, Toni Suzuki; Kaufman, David M; MacLeod, Heather; van Zanten, Sander; Simpson, David; Wrixon, William

2006-01-01

A substantial body of literature demonstrates that communication skills in medicine can be taught and retained through teaching and practice. Considerable evidence also reveals that characteristics such as gender, age, language and attitudes affect communication skills performance. Our study examined the characteristics, attitudes and prior communication skills training of residents to determine the relationship of each to patient-doctor communication. The relationship between communication skills proficiency and clinical knowledge application (biomedical and ethical) was also examined through the use of doctor-developed clinical content checklists, as very little research has been conducted in this area. A total of 78 first- and second-year residents across all departments at Dalhousie Medical School participated in a videotaped 4-station objective structured clinical examination presenting a range of communication and clinical knowledge challenges. A variety of instruments were used to gather information and assess performance. Two expert raters evaluated the videotapes. Significant relationships were observed between resident characteristics, prior communication skills training, clinical knowledge and communication skills performance. Females, younger residents and residents with English as first language scored significantly higher, as did residents with prior communication skills training. A significant positive relationship was found between the clinical content checklist and communication performance. Gender was the only characteristic related significantly to attitudes. Gender, age, language and prior communication skills training are related to communication skills performance and have implications for resident education. The positive relationship between communication skills proficiency and clinical knowledge application is important and should be explored further.

“Koko et les lunettes magiques”: An educational entertainment tool to prevent parasitic worms and diarrheal diseases in Côte d’Ivoire

PubMed Central

Kouamé, Abel; Dongo, Kouassi; Yapi, Richard B.; Moro, Honorine M.; Kouakou, Christiane A.; Palmeirim, Marta S.; Bonfoh, Bassirou; N’Goran, Eliézer K.; Utzinger, Jürg

2017-01-01

Background Integrated control programs, emphasizing preventive chemotherapy along with health education, can reduce the incidence of soil-transmitted helminthiasis and schistosomiasis. The aim of this study was to develop an educational animated cartoon to improve school children’s awareness regarding soil-transmitted helminthiasis, diarrheal diseases, and related hygiene practices in Côte d’Ivoire. The key messages included in the cartoon were identified through prior formative research to specifically address local knowledge gaps. Methodology In a first step, preliminary research was conducted to assess the knowledge, attitudes, practices, and beliefs of school-aged children regarding parasitic worm infections and hygiene, to identify key health messages to be included in an animated cartoon. Second, an animated cartoon was produced, which included the drafting of the script and story board, and the production of the cartoon’s initial version. Finally, the animated cartoon was pilot tested in eight selected schools and further fine-tuned. Principal findings According to the questionnaire results, children believed that the consumption of sweet food, eating without washing their hands, sitting on the floor, and eating spoiled food were the main causes of parasitic worm infections. Abdominal pain, diarrhea, lack of appetite, failure to grow, and general fatigue were mentioned as symptoms of parasitic worm infections. Most of the children knew that they should go to the hospital for treatment if they experienced symptoms of parasitic worm diseases. The animated cartoon titled “Koko et les lunettes magiques” was produced by Afrika Toon, in collaboration with a scientific team composed of epidemiologists, civil engineers, and social scientists, and the local school children and teachers. Pilot testing of the animated cartoon revealed that, in the short term, children grasped and kept key messages. Most of the children who were shown the cartoon reported to like it. Acceptance of the animated cartoon was high among children and teachers alike. The messaging was tailored to improve knowledge and practices for prevention of helminthiases and diarrheal diseases through prior identification of knowledge gaps. Integration of such education tools into the school curriculum, along with deworming campaigns, might improve sustainability of control and elimination efforts against helminthiases and diarrheal diseases. PMID:28934198

Human body segmentation via data-driven graph cut.

PubMed

Li, Shifeng; Lu, Huchuan; Shao, Xingqing

2014-11-01

Human body segmentation is a challenging and important problem in computer vision. Existing methods usually entail a time-consuming training phase for prior knowledge learning with complex shape matching for body segmentation. In this paper, we propose a data-driven method that integrates top-down body pose information and bottom-up low-level visual cues for segmenting humans in static images within the graph cut framework. The key idea of our approach is first to exploit human kinematics to search for body part candidates via dynamic programming for high-level evidence. Then, by using the body parts classifiers, obtaining bottom-up cues of human body distribution for low-level evidence. All the evidence collected from top-down and bottom-up procedures are integrated in a graph cut framework for human body segmentation. Qualitative and quantitative experiment results demonstrate the merits of the proposed method in segmenting human bodies with arbitrary poses from cluttered backgrounds.

Optimal Appearance Model for Visual Tracking

PubMed Central

Wang, Yuru; Jiang, Longkui; Liu, Qiaoyuan; Yin, Minghao

2016-01-01

Many studies argue that integrating multiple cues in an adaptive way increases tracking performance. However, what is the definition of adaptiveness and how to realize it remains an open issue. On the premise that the model with optimal discriminative ability is also optimal for tracking the target, this work realizes adaptiveness and robustness through the optimization of multi-cue integration models. Specifically, based on prior knowledge and current observation, a set of discrete samples are generated to approximate the foreground and background distribution. With the goal of optimizing the classification margin, an objective function is defined, and the appearance model is optimized by introducing optimization algorithms. The proposed optimized appearance model framework is embedded into a particle filter for a field test, and it is demonstrated to be robust against various kinds of complex tracking conditions. This model is general and can be easily extended to other parameterized multi-cue models. PMID:26789639

The Neuroscience Information Framework: A Data and Knowledge Environment for Neuroscience

PubMed Central

Akil, Huda; Ascoli, Giorgio A.; Bowden, Douglas M.; Bug, William; Donohue, Duncan E.; Goldberg, David H.; Grafstein, Bernice; Grethe, Jeffrey S.; Gupta, Amarnath; Halavi, Maryam; Kennedy, David N.; Marenco, Luis; Martone, Maryann E.; Miller, Perry L.; Müller, Hans-Michael; Robert, Adrian; Shepherd, Gordon M.; Sternberg, Paul W.; Van Essen, David C.; Williams, Robert W.

2009-01-01

With support from the Institutes and Centers forming the NIH Blueprint for Neuroscience Research, we have designed and implemented a new initiative for integrating access to and use of Web-based neuroscience resources: the Neuroscience Information Framework. The Framework arises from the expressed need of the neuroscience community for neuroinformatic tools and resources to aid scientific inquiry, builds upon prior development of neuroinformatics by the Human Brain Project and others, and directly derives from the Society for Neuroscience’s Neuroscience Database Gateway. Partnered with the Society, its Neuroinformatics Committee, and volunteer consultant-collaborators, our multi-site consortium has developed: (1) a comprehensive, dynamic, inventory of Web-accessible neuroscience resources, (2) an extended and integrated terminology describing resources and contents, and (3) a framework accepting and aiding concept-based queries. Evolving instantiations of the Framework may be viewed at http://nif.nih.gov, http://neurogateway.org, and other sites as they come on line. PMID:18946742

Mutual information, neural networks and the renormalization group

NASA Astrophysics Data System (ADS)

Koch-Janusz, Maciej; Ringel, Zohar

2018-06-01

Physical systems differing in their microscopic details often display strikingly similar behaviour when probed at macroscopic scales. Those universal properties, largely determining their physical characteristics, are revealed by the powerful renormalization group (RG) procedure, which systematically retains `slow' degrees of freedom and integrates out the rest. However, the important degrees of freedom may be difficult to identify. Here we demonstrate a machine-learning algorithm capable of identifying the relevant degrees of freedom and executing RG steps iteratively without any prior knowledge about the system. We introduce an artificial neural network based on a model-independent, information-theoretic characterization of a real-space RG procedure, which performs this task. We apply the algorithm to classical statistical physics problems in one and two dimensions. We demonstrate RG flow and extract the Ising critical exponent. Our results demonstrate that machine-learning techniques can extract abstract physical concepts and consequently become an integral part of theory- and model-building.

The neuroscience information framework: a data and knowledge environment for neuroscience.

PubMed

Gardner, Daniel; Akil, Huda; Ascoli, Giorgio A; Bowden, Douglas M; Bug, William; Donohue, Duncan E; Goldberg, David H; Grafstein, Bernice; Grethe, Jeffrey S; Gupta, Amarnath; Halavi, Maryam; Kennedy, David N; Marenco, Luis; Martone, Maryann E; Miller, Perry L; Müller, Hans-Michael; Robert, Adrian; Shepherd, Gordon M; Sternberg, Paul W; Van Essen, David C; Williams, Robert W

2008-09-01

With support from the Institutes and Centers forming the NIH Blueprint for Neuroscience Research, we have designed and implemented a new initiative for integrating access to and use of Web-based neuroscience resources: the Neuroscience Information Framework. The Framework arises from the expressed need of the neuroscience community for neuroinformatic tools and resources to aid scientific inquiry, builds upon prior development of neuroinformatics by the Human Brain Project and others, and directly derives from the Society for Neuroscience's Neuroscience Database Gateway. Partnered with the Society, its Neuroinformatics Committee, and volunteer consultant-collaborators, our multi-site consortium has developed: (1) a comprehensive, dynamic, inventory of Web-accessible neuroscience resources, (2) an extended and integrated terminology describing resources and contents, and (3) a framework accepting and aiding concept-based queries. Evolving instantiations of the Framework may be viewed at http://nif.nih.gov , http://neurogateway.org , and other sites as they come on line.

The application of SSADM to modelling the logical structure of proteins.

PubMed

Saldanha, J; Eccles, J

1991-10-01

A logical design that describes the overall structure of proteins, together with a more detailed design describing secondary and some supersecondary structures, has been constructed using the computer-aided software engineering (CASE) tool, Auto-mate. Auto-mate embodies the philosophy of the Structured Systems Analysis and Design Method (SSADM) which enables the logical design of computer systems. Our design will facilitate the building of large information systems, such as databases and knowledgebases in the field of protein structure, by the derivation of system requirements from our logical model prior to producing the final physical system. In addition, the study has highlighted the ease of employing SSADM as a formalism in which to conduct the transferral of concepts from an expert into a design for a knowledge-based system that can be implemented on a computer (the knowledge-engineering exercise). It has been demonstrated how SSADM techniques may be extended for the purpose of modelling the constituent Prolog rules. This facilitates the integration of the logical system design model with the derived knowledge-based system.

RegNetwork: an integrated database of transcriptional and post-transcriptional regulatory networks in human and mouse

PubMed Central

Liu, Zhi-Ping; Wu, Canglin; Miao, Hongyu; Wu, Hulin

2015-01-01

Transcriptional and post-transcriptional regulation of gene expression is of fundamental importance to numerous biological processes. Nowadays, an increasing amount of gene regulatory relationships have been documented in various databases and literature. However, to more efficiently exploit such knowledge for biomedical research and applications, it is necessary to construct a genome-wide regulatory network database to integrate the information on gene regulatory relationships that are widely scattered in many different places. Therefore, in this work, we build a knowledge-based database, named ‘RegNetwork’, of gene regulatory networks for human and mouse by collecting and integrating the documented regulatory interactions among transcription factors (TFs), microRNAs (miRNAs) and target genes from 25 selected databases. Moreover, we also inferred and incorporated potential regulatory relationships based on transcription factor binding site (TFBS) motifs into RegNetwork. As a result, RegNetwork contains a comprehensive set of experimentally observed or predicted transcriptional and post-transcriptional regulatory relationships, and the database framework is flexibly designed for potential extensions to include gene regulatory networks for other organisms in the future. Based on RegNetwork, we characterized the statistical and topological properties of genome-wide regulatory networks for human and mouse, we also extracted and interpreted simple yet important network motifs that involve the interplays between TF-miRNA and their targets. In summary, RegNetwork provides an integrated resource on the prior information for gene regulatory relationships, and it enables us to further investigate context-specific transcriptional and post-transcriptional regulatory interactions based on domain-specific experimental data. Database URL: http://www.regnetworkweb.org PMID:26424082

Kinematics Card Sort Activity: Insight into Students' Thinking

NASA Astrophysics Data System (ADS)

Berryhill, Erin; Herrington, Deborah; Oliver, Keith

2016-12-01

Kinematics is a topic students are unknowingly aware of well before entering the physics classroom. Students observe motion on a daily basis. They are constantly interpreting and making sense of their observations, unintentionally building their own understanding of kinematics before receiving any formal instruction. Unfortunately, when students take their prior conceptions to understand a new situation, they often do so in a way that inaccurately connects their learning. We were motivated to identify strategies to help our students make accurate connections to their prior knowledge and understand kinematics at a deeper level. To do this, we integrated a formative assessment card sort into a kinematic graphing unit within an introductory high school physics course. Throughout the activities, we required students to document and reflect upon their thinking. This allowed their learning to build upon their own previously held conceptual understanding, which provided an avenue for cognitive growth. By taking a more direct approach to eliciting student reasoning, we hoped to improve student learning and guide our assessment of their learning.

Prior Knowledge Activation: How Different Concept Mapping Tasks Lead to Substantial Differences in Cognitive Processes, Learning Outcomes, and Perceived Self-Efficacy

ERIC Educational Resources Information Center

Gurlitt, Johannes; Renkl, Alexander

2010-01-01

Two experiments investigated the effects of characteristic features of concept mapping used for prior knowledge activation. Characteristic demands of concept mapping include connecting lines representing the relationships between concepts and labeling these lines, specifying the type of the semantic relationships. In the first experiment,…

Concept Development and Meaningful Learning among Electrical Engineering Students Engaged in a Problem-Based Laboratory Experience

ERIC Educational Resources Information Center

Bledsoe, Karen E.; Flick, Lawrence

2012-01-01

This phenomenographic study documented changes in student-held electrical concepts the development of meaningful learning among students with both low and high prior knowledge within a problem-based learning (PBL) undergraduate electrical engineering course. This paper reports on four subjects: two with high prior knowledge and two with low prior…

Formative Assessment Pre-Test to Identify College Students' Prior Knowledge, Misconceptions and Learning Difficulties in Biology

ERIC Educational Resources Information Center

Lazarowitz, Reuven; Lieb, Carl

2006-01-01

A formative assessment pretest was administered to undergraduate students at the beginning of a science course in order to find out their prior knowledge, misconceptions and learning difficulties on the topic of the human respiratory system and energy issues. Those findings could provide their instructors with the valuable information required in…

The Influence of Prior Knowledge, Peer Review, Age, and Gender in Online Philosophy Discussions

ERIC Educational Resources Information Center

Cuddy, Lucas Stebbins

2016-01-01

Using a primarily experimental design, this study investigated whether discussion boards in online community college philosophy classes can be designed in the Blackboard course management system to lead to higher order thinking. Discussions were designed using one of two teaching techniques: the activation of prior knowledge or the use of peer…

Thai University Students' Prior Knowledge about P-Waves Generated during Particle Motion

ERIC Educational Resources Information Center

Rakkapao, Suttida; Arayathanikul, Kwan; Pananont, Passakorn

2009-01-01

The goal of this study is to identify Thai students' prior knowledge about particle motion when P-waves arrive. This existing idea significantly influences what and how students learn in the classroom. The data were collected via conceptual open-ended questions designed by the researchers and through explanatory follow-up interviews. Participants…

The Interpretation of Cellular Transport Graphics by Students with Low and High Prior Knowledge

ERIC Educational Resources Information Center

Cook, Michelle; Carter, Glenda; Wiebe, Eric N.

2008-01-01

The purpose of this study was to examine how prior knowledge of cellular transport influenced how high school students in the USA viewed and interpreted graphic representations of this topic. The participants were Advanced Placement Biology students (n = 65); each participant had previously taken a biology course in high school. After assessing…

The Effects of Prior-Knowledge and Online Learning Approaches on Students' Inquiry and Argumentation Abilities

ERIC Educational Resources Information Center

Yang, Wen-Tsung; Lin, Yu-Ren; She, Hsiao-Ching; Huang, Kai-Yi

2015-01-01

This study investigated the effects of students' prior science knowledge and online learning approaches (social and individual) on their learning with regard to three topics: science concepts, inquiry, and argumentation. Two science teachers and 118 students from 4 eighth-grade science classes were invited to participate in this research. Students…

Python Environment for Bayesian Learning: Inferring the Structure of Bayesian Networks from Knowledge and Data

PubMed Central

Shah, Abhik; Woolf, Peter

2009-01-01

Summary In this paper, we introduce pebl, a Python library and application for learning Bayesian network structure from data and prior knowledge that provides features unmatched by alternative software packages: the ability to use interventional data, flexible specification of structural priors, modeling with hidden variables and exploitation of parallel processing. PMID:20161541

The Instructional Effectiveness of Animated Signaling among Learners with High and Low Prior Knowledge

ERIC Educational Resources Information Center

Li, Shanshan

2012-01-01

The purpose of this study was to investigate the instructional effectiveness of animated signals among learners with high and low prior knowledge. Each of the two treatments was presented with animated instruction either with signals or without signals on the content of how an airplane achieves lift. Subjects were eighty-seven undergraduate…

A Fair and Balanced Look at the News: What Affects Memory for Controversial Arguments?

ERIC Educational Resources Information Center

Wiley, J.

2005-01-01

This research demonstrates how prior knowledge may allow for qualitative differences in representation of texts about controversial issues. People often experience a memory bias in favor of information with which they agree. In several experiments it was found that individuals with high prior knowledge about the topic were better able to recall…

Prior Knowledge Influence on Self-Explanation Effectiveness when Solving Problems: An Exploratory Study in Science Learning

ERIC Educational Resources Information Center

Ionas, Ioan Gelu; Cernusca, Dan; Collier, Harvest L.

2012-01-01

This exploratory study presents the outcomes of using self-explanation to improve learners' performance in solving basic chemistry problems. The results of the randomized experiment show the existence of a moderation effect between prior knowledge and the level of support self-explanation provides to learners, suggestive of a synergistic effect…

The Impact of Learner's Prior Knowledge on Their Use of Chemistry Computer Simulations: A Case Study

ERIC Educational Resources Information Center

Liu, Han-Chin; Andre, Thomas; Greenbowe, Thomas

2008-01-01

It is complicated to design a computer simulation that adapts to students with different characteristics. This study documented cases that show how college students' prior chemistry knowledge level affected their interaction with peers and their approach to solving problems with the use of computer simulations that were designed to learn…

Feedback Both Helps and Hinders Learning: The Causal Role of Prior Knowledge

ERIC Educational Resources Information Center

Fyfe, Emily R.; Rittle-Johnson, Bethany

2016-01-01

Feedback can be a powerful learning tool, but its effects vary widely. Research has suggested that learners' prior knowledge may moderate the effects of feedback; however, no causal link has been established. In Experiment 1, we randomly assigned elementary school children (N = 108) to a condition based on a crossing of 2 factors: induced strategy…

The Effect of Prior Knowledge and Feedback Type Design on Student Achievement and Satisfaction in Introductory Accounting

ERIC Educational Resources Information Center

Campbell, Donald P.

2013-01-01

This study investigated the effect of student prior knowledge and feedback type on student achievement and satisfaction in an introductory managerial accounting course using computer-based formative assessment tools. The study involved a redesign of the existing Job Order Costing unit using the ADDIE model of instructional design. The…

Activating Junior Secondary School Students' Prior Knowledge for the Development of Vocabulary, Concepts and Mathematics through Instructional Strategies

ERIC Educational Resources Information Center

Oyinloye, Olu; Popoola, Abiodun A.

2013-01-01

This paper investigates the activation of students' prior knowledge for the development of vocabulary, concepts and mathematics. It has been observed that many secondary school students are not performing well in the examination conducted by the West African Examinations Council and National Examinations Council of Nigeria. The situation became…

How the prior information shapes couplings in neural fields performing optimal multisensory integration

NASA Astrophysics Data System (ADS)

Wang, He; Zhang, Wen-Hao; Wong, K. Y. Michael; Wu, Si

Extensive studies suggest that the brain integrates multisensory signals in a Bayesian optimal way. However, it remains largely unknown how the sensory reliability and the prior information shape the neural architecture. In this work, we propose a biologically plausible neural field model, which can perform optimal multisensory integration and encode the whole profile of the posterior. Our model is composed of two modules, each for one modality. The crosstalks between the two modules can be carried out through feedforwad cross-links and reciprocal connections. We found that the reciprocal couplings are crucial to optimal multisensory integration in that the reciprocal coupling pattern is shaped by the correlation in the joint prior distribution of the sensory stimuli. A perturbative approach is developed to illustrate the relation between the prior information and features in coupling patterns quantitatively. Our results show that a decentralized architecture based on reciprocal connections is able to accommodate complex correlation structures across modalities and utilize this prior information in optimal multisensory integration. This work is supported by the Research Grants Council of Hong Kong (N_HKUST606/12 and 605813) and National Basic Research Program of China (2014CB846101) and the Natural Science Foundation of China (31261160495).

Using Bayesian statistics for modeling PTSD through Latent Growth Mixture Modeling: implementation and discussion.

PubMed

Depaoli, Sarah; van de Schoot, Rens; van Loey, Nancy; Sijbrandij, Marit

2015-01-01

After traumatic events, such as disaster, war trauma, and injuries including burns (which is the focus here), the risk to develop posttraumatic stress disorder (PTSD) is approximately 10% (Breslau & Davis, 1992). Latent Growth Mixture Modeling can be used to classify individuals into distinct groups exhibiting different patterns of PTSD (Galatzer-Levy, 2015). Currently, empirical evidence points to four distinct trajectories of PTSD patterns in those who have experienced burn trauma. These trajectories are labeled as: resilient, recovery, chronic, and delayed onset trajectories (e.g., Bonanno, 2004; Bonanno, Brewin, Kaniasty, & Greca, 2010; Maercker, Gäbler, O'Neil, Schützwohl, & Müller, 2013; Pietrzak et al., 2013). The delayed onset trajectory affects only a small group of individuals, that is, about 4-5% (O'Donnell, Elliott, Lau, & Creamer, 2007). In addition to its low frequency, the later onset of this trajectory may contribute to the fact that these individuals can be easily overlooked by professionals. In this special symposium on Estimating PTSD trajectories (Van de Schoot, 2015a), we illustrate how to properly identify this small group of individuals through the Bayesian estimation framework using previous knowledge through priors (see, e.g., Depaoli & Boyajian, 2014; Van de Schoot, Broere, Perryck, Zondervan-Zwijnenburg, & Van Loey, 2015). We used latent growth mixture modeling (LGMM) (Van de Schoot, 2015b) to estimate PTSD trajectories across 4 years that followed a traumatic burn. We demonstrate and compare results from traditional (maximum likelihood) and Bayesian estimation using priors (see, Depaoli, 2012, 2013). Further, we discuss where priors come from and how to define them in the estimation process. We demonstrate that only the Bayesian approach results in the desired theory-driven solution of PTSD trajectories. Since the priors are chosen subjectively, we also present a sensitivity analysis of the Bayesian results to illustrate how to check the impact of the prior knowledge integrated into the model. We conclude with recommendations and guidelines for researchers looking to implement theory-driven LGMM, and we tailor this discussion to the context of PTSD research.

Knowledge integration, teamwork and performance in health care.

PubMed

Körner, Mirjam; Lippenberger, Corinna; Becker, Sonja; Reichler, Lars; Müller, Christian; Zimmermann, Linda; Rundel, Manfred; Baumeister, Harald

2016-01-01

Knowledge integration is the process of building shared mental models. The integration of the diverse knowledge of the health professions in shared mental models is a precondition for effective teamwork and team performance. As it is known that different groups of health care professionals often tend to work in isolation, the authors compared the perceptions of knowledge integration. It can be expected that based on this isolation, knowledge integration is assessed differently. The purpose of this paper is to test these differences in the perception of knowledge integration between the professional groups and to identify to what extent knowledge integration predicts perceptions of teamwork and team performance and to determine if teamwork has a mediating effect. The study is a multi-center cross-sectional study with a descriptive-explorative design. Data were collected by means of a staff questionnaire for all health care professionals working in the rehabilitation clinics. The results showed that there are significant differences in knowledge integration within interprofessional health care teams. Furthermore, it could be shown that knowledge integration is significantly related to patient-centered teamwork as well as to team performance. Mediation analysis revealed partial mediation of the effect of knowledge integration on team performance through teamwork. PRACTICAL/IMPLICATIONS: In practice, the results of the study provide a valuable starting point for team development interventions. This is the first study that explored knowledge integration in medical rehabilitation teams and its relation to patient-centered teamwork and team performance.

Applying knowledge translation tools to inform policy: the case of mental health in Lebanon.

PubMed

Yehia, Farah; El Jardali, Fadi

2015-06-06

Many reform efforts in health systems fall short because the use of research evidence to inform policy remains scarce. In Lebanon, one in four adults suffers from a mental illness, yet access to mental healthcare services in primary healthcare (PHC) settings is limited. Using an "integrated" knowledge framework to link research to action, this study examines the process of influencing the mental health agenda in Lebanon through the application of Knowledge Translation (KT) tools and the use of a KT Platform (KTP) as an intermediary between researchers and policymakers. This study employed the following KT tools: 1) development of a policy brief to address the lack of access to mental health services in PHC centres, 2) semi-structured interviews with 10 policymakers and key informants, 3) convening of a national policy dialogue, 4) evaluation of the policy brief and dialogue, and 5) a post-dialogue survey. Findings from the key informant interviews and a comprehensive synthesis of evidence were used to develop a policy brief which defined the problem and presented three elements of a policy approach to address it. This policy brief was circulated to 24 participants prior to the dialogue to inform the discussion. The policy dialogue validated the evidence synthesized in the brief, whereby integrating mental health into PHC services was the element most supported by evidence as well as participants. The post-dialogue survey showed that, in the following 6 months, several implementation steps were taken by stakeholders, including establishing national taskforce, training PHC staff, and updating the national essential drug list to include psychiatric medications. Relationships among policymakers, researchers, and stakeholders were strengthened as they conducted their own workshops and meetings after the dialogue to further discuss implementation, and their awareness about and demand for KT tools increased. This case study showed that the use of KT tools in Lebanon to help generate evidence-informed programs is promising. This experience provided insights into the most helpful features of the tools. The role of the KTP in engaging stakeholders, particularly policymakers, prior to the dialogue and linking them with researchers was vital in securing their support for the KT process and uptake of the research evidence.

Knowledge exchange and integrated services: experiences from an integrated community intellectual (learning) disability service for adults.

PubMed

Farrington, C; Clare, I C H; Holland, A J; Barrett, M; Oborn, E

2015-03-01

This paper examines knowledge exchange dynamics in a specialist integrated intellectual (learning) disability service, comprising specialist healthcare provision with social care commissioning and management, and considers their significance in terms of integrated service delivery. A qualitative study focusing on knowledge exchange and integrated services. Semi-structured interviews (n = 25) were conducted with members of an integrated intellectual disability service in England regarding their perceptions of knowledge exchange within the service and the way in which knowledge exchange impinges on the operation of the integrated service. Exchange of 'explicit' (codifiable) knowledge between health and care management components of the service is problematic because of a lack of integrated clinical governance and related factors such as IT and care record systems and office arrangements. Team meetings and workplace interactions allowed for informal exchange of explicit and 'tacit' (non-codifiable) knowledge, but presented challenges in terms of knowledge exchange completeness and sustainability. Knowledge exchange processes play an important role in the functioning of integrated services incorporating health and care management components. Managers need to ensure that knowledge exchange processes facilitate both explicit and tacit knowledge exchange and do not rely excessively on informal, 'ad hoc' interactions. Research on integrated services should take account of micro-scale knowledge exchange dynamics and relationships between social dynamics and physical factors. © 2014 MENCAP and International Association of the Scientific Study of Intellectual and Developmental Disabilities and John Wiley & Sons Ltd.

Perceptual learning of degraded speech by minimizing prediction error.

PubMed

Sohoglu, Ediz; Davis, Matthew H

2016-03-22

Human perception is shaped by past experience on multiple timescales. Sudden and dramatic changes in perception occur when prior knowledge or expectations match stimulus content. These immediate effects contrast with the longer-term, more gradual improvements that are characteristic of perceptual learning. Despite extensive investigation of these two experience-dependent phenomena, there is considerable debate about whether they result from common or dissociable neural mechanisms. Here we test single- and dual-mechanism accounts of experience-dependent changes in perception using concurrent magnetoencephalographic and EEG recordings of neural responses evoked by degraded speech. When speech clarity was enhanced by prior knowledge obtained from matching text, we observed reduced neural activity in a peri-auditory region of the superior temporal gyrus (STG). Critically, longer-term improvements in the accuracy of speech recognition following perceptual learning resulted in reduced activity in a nearly identical STG region. Moreover, short-term neural changes caused by prior knowledge and longer-term neural changes arising from perceptual learning were correlated across subjects with the magnitude of learning-induced changes in recognition accuracy. These experience-dependent effects on neural processing could be dissociated from the neural effect of hearing physically clearer speech, which similarly enhanced perception but increased rather than decreased STG responses. Hence, the observed neural effects of prior knowledge and perceptual learning cannot be attributed to epiphenomenal changes in listening effort that accompany enhanced perception. Instead, our results support a predictive coding account of speech perception; computational simulations show how a single mechanism, minimization of prediction error, can drive immediate perceptual effects of prior knowledge and longer-term perceptual learning of degraded speech.

Perceptual learning of degraded speech by minimizing prediction error

PubMed Central

Sohoglu, Ediz

2016-01-01

Human perception is shaped by past experience on multiple timescales. Sudden and dramatic changes in perception occur when prior knowledge or expectations match stimulus content. These immediate effects contrast with the longer-term, more gradual improvements that are characteristic of perceptual learning. Despite extensive investigation of these two experience-dependent phenomena, there is considerable debate about whether they result from common or dissociable neural mechanisms. Here we test single- and dual-mechanism accounts of experience-dependent changes in perception using concurrent magnetoencephalographic and EEG recordings of neural responses evoked by degraded speech. When speech clarity was enhanced by prior knowledge obtained from matching text, we observed reduced neural activity in a peri-auditory region of the superior temporal gyrus (STG). Critically, longer-term improvements in the accuracy of speech recognition following perceptual learning resulted in reduced activity in a nearly identical STG region. Moreover, short-term neural changes caused by prior knowledge and longer-term neural changes arising from perceptual learning were correlated across subjects with the magnitude of learning-induced changes in recognition accuracy. These experience-dependent effects on neural processing could be dissociated from the neural effect of hearing physically clearer speech, which similarly enhanced perception but increased rather than decreased STG responses. Hence, the observed neural effects of prior knowledge and perceptual learning cannot be attributed to epiphenomenal changes in listening effort that accompany enhanced perception. Instead, our results support a predictive coding account of speech perception; computational simulations show how a single mechanism, minimization of prediction error, can drive immediate perceptual effects of prior knowledge and longer-term perceptual learning of degraded speech. PMID:26957596

Attitudes and perceptions of Australian pharmacy students towards Complementary and Alternative Medicine – a pilot study

PubMed Central

Tiralongo, Evelin; Wallis, Marianne

2008-01-01

Background With the increased usage of CAM worldwide comes the demand for its integration into health professional education. However, the incorporation of CAM into health professional curricula is handled quite differently by different institutions and countries. Furthermore, the evaluation of CAM curricula is complicated because students' ability to learn about CAM may be influenced by factors such as student's prior knowledge and motivation, together with the perceptions and attitudes of clinical preceptors. The study aimed to describe the attitudes, perceptions and beliefs of second, third and fourth year pharmacy students towards complementary and alternative medicine (CAM) and to explore factors that might affect attitudes such as learning, preceptors and placements. Methods Pharmacy students from a University in South East Queensland, Australia participated in the study. The study consisted of a cross-sectional survey (n = 110) and semi-structured interviews (n = 9). Results The overall response rate for the survey was 75%, namely 50% (36/72) for second year, 77.3% (34/44) for third year and 97.6% (40/41) for fourth year students. Overall, 95.5% of pharmacy students believe that pharmacists should be able to advise patients about CAM and most (93.7%) have used CAM prior to course enrolment. Students' attitudes to CAM are influenced by the use of CAM by family, friends and self, CAM training, lecturers and to a lesser degree by preceptors. The majority of pharmacy students (89.2%) perceive education about CAM as a core and integral part of their professional degree and favour it over an additional postgraduate degree. However, they see a greater need for education in complementary medicines (such as herbal medicines, vitamins and minerals) than for education in complementary therapies (such as acupuncture, meditation and bio-magnetism). Knowledge and educational input rationalised rather than marginalised students' attitudes towards CAM. Conclusion Pharmacy students perceive education about CAM as a core and integral part of their professional degree. Students' attitudes towards CAM can be influenced by learning, lecturers, preceptors and practice experience. The content and focus of CAM education has to be further investigated and tailored to meet the professional needs of our future health professionals. PMID:18221569

Trust-based learning and behaviors for convoy obstacle avoidance

NASA Astrophysics Data System (ADS)

Mikulski, Dariusz G.; Karlsen, Robert E.

2015-05-01

In many multi-agent systems, robots within the same team are regarded as being fully trustworthy for cooperative tasks. However, the assumption of trustworthiness is not always justified, which may not only increase the risk of mission failure, but also endanger the lives of friendly forces. In prior work, we addressed this issue by using RoboTrust to dynamically adjust to observed behaviors or recommendations in order to mitigate the risks of illegitimate behaviors. However, in the simulations in prior work, all members of the convoy had knowledge of the convoy goal. In this paper, only the lead vehicle has knowledge of the convoy goals and the follow vehicles must infer trustworthiness strictly from lead vehicle performance. In addition, RoboTrust could only respond to observed performance and did not dynamically learn agent behavior. In this paper, we incorporate an adaptive agent-specific bias into the RoboTrust algorithm that modifies its trust dynamics. This bias is learned incrementally from agent interactions, allowing good agents to benefit from faster trust growth and slower trust decay and bad agents to be penalized with slower trust growth and faster trust decay. We then integrate this new trust model into a trust-based controller for decentralized autonomous convoy operations. We evaluate its performance in an obstacle avoidance mission, where the convoy attempts to learn the best speed and following distances combinations for an acceptable obstacle avoidance probability.

The Role of Specificity, Targeted Learning Activities, and Prior Knowledge for the Effects of Relevance Instructions

ERIC Educational Resources Information Center

Roelle, Julian; Lehmkuhl, Nina; Beyer, Martin-Uwe; Berthold, Kirsten

2015-01-01

In 2 experiments we examined the role of (a) specificity, (b) the type of targeted learning activities, and (c) learners' prior knowledge for the effects of relevance instructions on learning from instructional explanations. In Experiment 1, we recruited novices regarding the topic of atomic structure (N = 80) and found that "specific"…

Effects of Prior Knowledge of Topics and the Instructional Objectives on Students' Achievement in Literature-in-English

ERIC Educational Resources Information Center

Mbah, Blessing Akaraka

2015-01-01

This study investigated the effects of prior knowledge of topics with their instructional objectives on senior secondary school class two (SS II) students. The study was carried out in Abakaliki Education Zone of Ebonyi State, Nigeria. The design of the study is quasi experimental of pretest-posttest of non-equivalent control group. Two research…

Polite Web-Based Intelligent Tutors: Can They Improve Learning in Classrooms?

ERIC Educational Resources Information Center

McLaren, Bruce M.; DeLeeuw, Krista E.; Mayer, Richard E.

2011-01-01

Should an intelligent software tutor be polite, in an effort to motivate and cajole students to learn, or should it use more direct language? If it should be polite, under what conditions? In a series of studies in different contexts (e.g., lab versus classroom) with a variety of students (e.g., low prior knowledge versus high prior knowledge),…

"She Has to Drink Blood of the Snake": Culture and Prior Knowledge in Science|Health Education

ERIC Educational Resources Information Center

Bricker, Leah A.; Reeve, Suzanne; Bell, Philip

2014-01-01

In this analysis, we argue that science education should attend more deeply to youths' cultural resources and practices (e.g. material, social, and intellectual). Inherent in our argument is a call for revisiting conceptions of "prior knowledge" to theorize how people make sense of the complex ecologies of experience, ideas, and cultural…

Effects of Different Types of True-False Questions on Memory Awareness and Long-Term Retention

ERIC Educational Resources Information Center

Schaap, Lydia; Verkoeijen, Peter; Schmidt, Henk

2014-01-01

This study investigated the effects of two different true-false questions on memory awareness and long-term retention of knowledge. Participants took four subsequent knowledge tests on curriculum learning material that they studied at different retention intervals prior to the start of this study (i.e. prior to the first test). At the first and…

Effects of Prior Knowledge and Concept-Map Structure on Disorientation, Cognitive Load, and Learning

ERIC Educational Resources Information Center

Amadieu, Franck; van Gog, Tamara; Paas, Fred; Tricot, Andre; Marine, Claudette

2009-01-01

This study explored the effects of prior knowledge (high vs. low; HPK and LPK) and concept-map structure (hierarchical vs. network; HS and NS) on disorientation, cognitive load, and learning from non-linear documents on "the infection process of a retrograde virus (HIV)". Participants in the study were 24 adults. Overall subjective ratings of…

Relevant Prior Knowledge Moderates the Effect of Elaboration during Small Group Discussion on Academic Achievement

ERIC Educational Resources Information Center

Van Blankenstein, Floris M.; Dolmans, Diana H. J. M.; Van der Vleuten, Cees P. M.; Schmidt, Henk G.

2013-01-01

This study set out to test whether relevant prior knowledge would moderate a positive effect on academic achievement of elaboration during small-group discussion. In a 2 × 2 experimental design, 66 undergraduate students observed a video showing a small-group problem-based discussion about thunder and lightning. In the video, a teacher asked…

The Mediation Effect of In-Game Performance between Prior Knowledge and Posttest Score. CRESST Report 819

ERIC Educational Resources Information Center

Kerr, Deirdre; Chung, Gregory K. W. K.

2012-01-01

Though video games are commonly considered to hold great potential as learning environments, their effectiveness as a teaching tool has yet to be determined. One reason for this is that researchers often run into the problem of multicollinearity between prior knowledge, in-game performance, and posttest scores, thereby making the determination of…

Developmental Change in the Influence of Domain-General Abilities and Domain-Specific Knowledge on Mathematics Achievement: An Eight-Year Longitudinal Study

ERIC Educational Resources Information Center

Geary, David C.; Nicholas, Alan; Li, Yaoran; Sun, Jianguo

2017-01-01

The contributions of domain-general abilities and domain-specific knowledge to subsequent mathematics achievement were longitudinally assessed (n = 167) through 8th grade. First grade intelligence and working memory and prior grade reading achievement indexed domain-general effects, and domain-specific effects were indexed by prior grade…

Blended Learning Based on Schoology: Effort of Improvement Learning Outcome and Practicum Chance in Vocational High School

ERIC Educational Resources Information Center

Irawan, Vincentius Tjandra; Sutadji, Eddy; Widiyanti

2017-01-01

The aims of this study were to determine: (1) the differences in learning outcome between Blended Learning based on Schoology and Problem-Based Learning, (2) the differences in learning outcome between students with prior knowledge of high, medium, and low, and (3) the interaction between Blended Learning based on Schoology and prior knowledge to…

Why is a Pomegranate an Apple? The Role of Shape, Taxonomic Relatedness, and Prior Lexical Knowledge in Children's Overextensions of "Apple" and "Dog."

ERIC Educational Resources Information Center

Gelman, Susan A.; Croft, William; Fu, Panfang; Clausner, Timothy; Gottfried, Gail

1998-01-01

Examined how object shape, taxonomic relatedness, and prior lexical knowledge influenced children's overextensions (e.g., referring to pomegranates as apples). Researchers presented items that disentangled the three factors and used a novel comprehension task where children could indicate negative exemplars. Error patterns differed by task and by…

Building dynamical models from data and prior knowledge: the case of the first period-doubling bifurcation.

PubMed

Aguirre, Luis Antonio; Furtado, Edgar Campos

2007-10-01

This paper reviews some aspects of nonlinear model building from data with (gray box) and without (black box) prior knowledge. The model class is very important because it determines two aspects of the final model, namely (i) the type of nonlinearity that can be accurately approximated and (ii) the type of prior knowledge that can be taken into account. Such features are usually in conflict when it comes to choosing the model class. The problem of model structure selection is also reviewed. It is argued that such a problem is philosophically different depending on the model class and it is suggested that the choice of model class should be performed based on the type of a priori available. A procedure is proposed to build polynomial models from data on a Poincaré section and prior knowledge about the first period-doubling bifurcation, for which the normal form is also polynomial. The final models approximate dynamical data in a least-squares sense and, by design, present the first period-doubling bifurcation at a specified value of parameters. The procedure is illustrated by means of simulated examples.

Mixture class recovery in GMM under varying degrees of class separation: frequentist versus Bayesian estimation.

PubMed

Depaoli, Sarah

2013-06-01

Growth mixture modeling (GMM) represents a technique that is designed to capture change over time for unobserved subgroups (or latent classes) that exhibit qualitatively different patterns of growth. The aim of the current article was to explore the impact of latent class separation (i.e., how similar growth trajectories are across latent classes) on GMM performance. Several estimation conditions were compared: maximum likelihood via the expectation maximization (EM) algorithm and the Bayesian framework implementing diffuse priors, "accurate" informative priors, weakly informative priors, data-driven informative priors, priors reflecting partial-knowledge of parameters, and "inaccurate" (but informative) priors. The main goal was to provide insight about the optimal estimation condition under different degrees of latent class separation for GMM. Results indicated that optimal parameter recovery was obtained though the Bayesian approach using "accurate" informative priors, and partial-knowledge priors showed promise for the recovery of the growth trajectory parameters. Maximum likelihood and the remaining Bayesian estimation conditions yielded poor parameter recovery for the latent class proportions and the growth trajectories. (PsycINFO Database Record (c) 2013 APA, all rights reserved).

Prompted Journal Writing Supports Preservice History Teachers in Drawing on Multiple Knowledge Domains for Designing Learning Tasks

ERIC Educational Resources Information Center

Wäschle, Kristin; Lehmann, Thomas; Brauch, Nicola; Nückles, Matthias

2015-01-01

Becoming a history teacher requires the integration of pedagogical knowledge, pedagogical content knowledge, and content knowledge. Because the integration of knowledge from different disciplines is a complex task, we investigated prompted learning journals as a method to support teacher students' knowledge integration. Fifty-two preservice…

Using Genetic Programming with Prior Formula Knowledge to Solve Symbolic Regression Problem.

PubMed

Lu, Qiang; Ren, Jun; Wang, Zhiguang

2016-01-01

A researcher can infer mathematical expressions of functions quickly by using his professional knowledge (called Prior Knowledge). But the results he finds may be biased and restricted to his research field due to limitation of his knowledge. In contrast, Genetic Programming method can discover fitted mathematical expressions from the huge search space through running evolutionary algorithms. And its results can be generalized to accommodate different fields of knowledge. However, since GP has to search a huge space, its speed of finding the results is rather slow. Therefore, in this paper, a framework of connection between Prior Formula Knowledge and GP (PFK-GP) is proposed to reduce the space of GP searching. The PFK is built based on the Deep Belief Network (DBN) which can identify candidate formulas that are consistent with the features of experimental data. By using these candidate formulas as the seed of a randomly generated population, PFK-GP finds the right formulas quickly by exploring the search space of data features. We have compared PFK-GP with Pareto GP on regression of eight benchmark problems. The experimental results confirm that the PFK-GP can reduce the search space and obtain the significant improvement in the quality of SR.

XGR software for enhanced interpretation of genomic summary data, illustrated by application to immunological traits.

PubMed

Fang, Hai; Knezevic, Bogdan; Burnham, Katie L; Knight, Julian C

2016-12-13

Biological interpretation of genomic summary data such as those resulting from genome-wide association studies (GWAS) and expression quantitative trait loci (eQTL) studies is one of the major bottlenecks in medical genomics research, calling for efficient and integrative tools to resolve this problem. We introduce eXploring Genomic Relations (XGR), an open source tool designed for enhanced interpretation of genomic summary data enabling downstream knowledge discovery. Targeting users of varying computational skills, XGR utilises prior biological knowledge and relationships in a highly integrated but easily accessible way to make user-input genomic summary datasets more interpretable. We show how by incorporating ontology, annotation, and systems biology network-driven approaches, XGR generates more informative results than conventional analyses. We apply XGR to GWAS and eQTL summary data to explore the genomic landscape of the activated innate immune response and common immunological diseases. We provide genomic evidence for a disease taxonomy supporting the concept of a disease spectrum from autoimmune to autoinflammatory disorders. We also show how XGR can define SNP-modulated gene networks and pathways that are shared and distinct between diseases, how it achieves functional, phenotypic and epigenomic annotations of genes and variants, and how it enables exploring annotation-based relationships between genetic variants. XGR provides a single integrated solution to enhance interpretation of genomic summary data for downstream biological discovery. XGR is released as both an R package and a web-app, freely available at http://galahad.well.ox.ac.uk/XGR .

Integration of oncology and palliative care: setting a benchmark.

PubMed

Vayne-Bossert, P; Richard, E; Good, P; Sullivan, K; Hardy, J R

2017-10-01

Integration of oncology and palliative care (PC) should be the standard model of care for patients with advanced cancer. An expert panel developed criteria that constitute integration. This study determined whether the PC service within this Health Service, which is considered to be fully "integrated", could be benchmarked against these criteria. A survey was undertaken to determine the perceived level of integration of oncology and palliative care by all health care professionals (HCPs) within our cancer centre. An objective determination of integration was obtained from chart reviews of deceased patients. Integration was defined as >70% of all respondents answered "agree" or "strongly agree" to each indicator and >70% of patient charts supported each criteria. Thirty-four HCPs participated in the survey (response rate 69%). Over 90% were aware of the outpatient PC clinic, interdisciplinary and consultation team, PC senior leadership, and the acceptance of concurrent anticancer therapy. None of the other criteria met the 70% agreement mark but many respondents lacked the necessary knowledge to respond. The chart review included 67 patients, 92% of whom were seen by the PC team prior to death. The median time from referral to death was 103 days (range 0-1347). The level of agreement across all criteria was below our predefined definition of integration. The integration criteria relating to service delivery are medically focused and do not lend themselves to interdisciplinary review. The objective criteria can be audited and serve both as a benchmark and a basis for improvement activities.

A Curriculum Experiment in Climate Change Education Using and Integrated Approach of Content Knowledge Instruction and Student-Driven Research to Promote Civic Engagement

NASA Astrophysics Data System (ADS)

Adams, P. E.; Heinrichs, J. F.

2009-12-01

One of the greatest challenges facing the world is climate change. Coupled with this challenge is an under-informed population that has not received a rigorous education about climate change other than what is available through the media. Fort Hays State University is piloting a course on climate change targeted to students early in their academic careers. The course is modeled after our past work (NSF DUE-0088818) of integrating content knowledge instruction and student-driven research where there was a positive correlation between student research engagement and student knowledge gains. The current course, based on prior findings, utilizes a mix of inquiry-based instruction, problem-based learning, and student-driven research to educate and engage the students in understanding climate change. The course was collaboratively developed by a geoscientist and science educator both of whom are active in citizen science programs. The emphasis on civic engagement by students is reflected in the course structure. The course model is unique in that 50% of the course is dedicated to developing core knowledge and technical skills (e.g. critical analysis, writing, data acquisition, data representation, and research design), and 50% to conducting a research project using available data sets from federal agencies and research groups. A key element of the course is a focus on local and regional data sets to make climate change relevant to the students. The research serves as a means of civic engagement by the students as they are tasked to understand their role in communicating their research findings to the community and coping with the local and regional changes they find through their research.

Integration of prior CT into CBCT reconstruction for improved image quality via reconstruction of difference: first patient studies

NASA Astrophysics Data System (ADS)

Zhang, Hao; Gang, Grace J.; Lee, Junghoon; Wong, John; Stayman, J. Webster

2017-03-01

Purpose: There are many clinical situations where diagnostic CT is used for an initial diagnosis or treatment planning, followed by one or more CBCT scans that are part of an image-guided intervention. Because the high-quality diagnostic CT scan is a rich source of patient-specific anatomical knowledge, this provides an opportunity to incorporate the prior CT image into subsequent CBCT reconstruction for improved image quality. We propose a penalized-likelihood method called reconstruction of difference (RoD), to directly reconstruct differences between the CBCT scan and the CT prior. In this work, we demonstrate the efficacy of RoD with clinical patient datasets. Methods: We introduce a data processing workflow using the RoD framework to reconstruct anatomical changes between the prior CT and current CBCT. This workflow includes processing steps to account for non-anatomical differences between the two scans including 1) scatter correction for CBCT datasets due to increased scatter fractions in CBCT data; 2) histogram matching for attenuation variations between CT and CBCT; and 3) registration for different patient positioning. CBCT projection data and CT planning volumes for two radiotherapy patients - one abdominal study and one head-and-neck study - were investigated. Results: In comparisons between the proposed RoD framework and more traditional FDK and penalized-likelihood reconstructions, we find a significant improvement in image quality when prior CT information is incorporated into the reconstruction. RoD is able to provide additional low-contrast details while correctly incorporating actual physical changes in patient anatomy. Conclusions: The proposed framework provides an opportunity to either improve image quality or relax data fidelity constraints for CBCT imaging when prior CT studies of the same patient are available. Possible clinical targets include CBCT image-guided radiotherapy and CBCT image-guided surgeries.

PRIOR-WK&E: Social Software for Policy Making in the Knowledge Society

NASA Astrophysics Data System (ADS)

Turón, Alberto; Aguarón, Juan; Escobar, María Teresa; Gallardo, Carolina; Moreno-Jiménez, José María; Salazar, José Luis

This paper presents a social software application denominated as PRIOR-WK&E. It has been developed by the Zaragoza Multicriteria Decision Making Group (GDMZ) with the aim of responding to the challenges of policy making in the Knowledge Society. Three specific modules have been added to PRIOR, the collaborative tool used by the research group (GDMZ) for considering the multicriteria selection of a discrete set of alternatives. The first module (W), that deals with multiactor decision making through the Web, and the second (K), that concerns the extraction and diffusion of knowledge related to the scientific resolution of the problem, were explained in [1]. The new application strengthens securitization and includes a third module (E) that evaluates the effectiveness of public administrations policy making.

Developing Dental Students' Awareness of Health Care Disparities and Desire to Serve Vulnerable Populations Through Service-Learning.

PubMed

Behar-Horenstein, Linda S; Feng, Xiaoying; Roberts, Kellie W; Gibbs, Micaela; Catalanotto, Frank A; Hudson-Vassell, Charisse M

2015-10-01

Service-learning in dental education helps students integrate knowledge with practice in an underserved community setting. The aim of this study was to explore how a service-learning experience affected a small group of dental students' beliefs about cultural competence, professionalism, career development, desire to practice in a community service setting, and perceptions about access and disparities issues. Prior to beginning their first year of dental school, five first-year dental students at one U.S. dental school participated in a six-week service-learning program in which they interned at one of three at-risk settings in order to experience health care delivery there. After the program, 60 reflective writing assignments completed by the participants were analyzed using grounded theory methods; interviews with the students were used to corroborate the findings from that analysis. Seven themes identified in the journal reflections and interview findings showed enhanced awareness of social health care issues and patient differences, as well as a social justice orientation and desire to address disparities. Building on this study, future research should explore the curricular components of service-learning programs to ensure students receive ample opportunity to reflect upon their experiences in order to integrate previously held assumptions with their newfound knowledge.

Understanding the Role of Representation in Interorganizational Knowledge Integration: A Case Study of an IT Outsourcing Project

ERIC Educational Resources Information Center

Werr, Andreas; Runsten, Philip

2013-01-01

Purpose: The current paper aims at contributing to the understanding of interorganizational knowledge integration by highlighting the role of individuals' understandings of the task and how they shape knowledge integrating behaviours. Design/methodology/approach: The paper presents a framework of knowledge integration as heedful interrelating.…

Induction as Knowledge Integration

NASA Technical Reports Server (NTRS)

Smith, Benjamin D.; Rosenbloom, Paul S.

1996-01-01

Two key issues for induction algorithms are the accuracy of the learned hypothesis and the computational resources consumed in inducing that hypothesis. One of the most promising ways to improve performance along both dimensions is to make use of additional knowledge. Multi-strategy learning algorithms tackle this problem by employing several strategies for handling different kinds of knowledge in different ways. However, integrating knowledge into an induction algorithm can be difficult when the new knowledge differs significantly from the knowledge the algorithm already uses. In many cases the algorithm must be rewritten. This paper presents Knowledge Integration framework for Induction (KII), a KII, that provides a uniform mechanism for integrating knowledge into induction. In theory, arbitrary knowledge can be integrated with this mechanism, but in practice the knowledge representation language determines both the knowledge that can be integrated, and the costs of integration and induction. By instantiating KII with various set representations, algorithms can be generated at different trade-off points along these dimensions. One instantiation of KII, called RS-KII, is presented that can implement hybrid induction algorithms, depending on which knowledge it utilizes. RS-KII is demonstrated to implement AQ-11, as well as a hybrid algorithm that utilizes a domain theory and noisy examples. Other algorithms are also possible.

Healthcare providers' knowledge and attitudes about rapid tissue donation (RTD): phase one of establishing a rapid tissue donation programme in thoracic oncology.

PubMed

Schabath, Matthew B; McIntyre, Jessica; Pratt, Christie; Gonzalez, Luis E; Munoz-Antonia, Teresita; Haura, Eric B; Quinn, Gwendolyn P

2014-02-01

In preparation for the development of a rapid tissue donation (RTD) programme, we surveyed healthcare providers (HCPs) in our institution about knowledge and attitudes related to RTD with lung cancer patients. A 31-item web based survey was developed collecting data on demographics, knowledge and attitudes about RTD. The survey contained three items measuring participants' knowledge about RTD, five items assessing attitudes towards RTD recruitment and six items assessing HCPs' level of agreement with factors influencing decisions to discuss RTD. Response options were presented on a 5-point Likert scale. Ninety-one HCPs participated in the study. 66% indicated they had never heard of RTD prior to the survey, 78% rated knowledge of RTD as none or limited and 95.6% reported not having ethical or religious concerns about discussing RTD with patients. The majority were either not comfortable (17.8%) or not sure if they felt comfortable discussing RTD with cancer patients (42.2%). 56.1% indicated their knowledge of RTD would play an integral role in their decision to discuss RTD with patients. 71.4% reported concerns with RTD discussion and the emotional state of the patient. Physicians and nurses play an important role in initiating conversations about recruitment and donation to research that can ultimately influence uptake. Increasing HCP knowledge about RTD is a necessary step towards building an RTD programme. Our study provides important information about characteristics associated with low levels of knowledge and practice related to RTD where additional education and training may be warranted.

Translating three states of knowledge--discovery, invention, and innovation

PubMed Central

2010-01-01

Background Knowledge Translation (KT) has historically focused on the proper use of knowledge in healthcare delivery. A knowledge base has been created through empirical research and resides in scholarly literature. Some knowledge is amenable to direct application by stakeholders who are engaged during or after the research process, as shown by the Knowledge to Action (KTA) model. Other knowledge requires multiple transformations before achieving utility for end users. For example, conceptual knowledge generated through science or engineering may become embodied as a technology-based invention through development methods. The invention may then be integrated within an innovative device or service through production methods. To what extent is KT relevant to these transformations? How might the KTA model accommodate these additional development and production activities while preserving the KT concepts? Discussion Stakeholders adopt and use knowledge that has perceived utility, such as a solution to a problem. Achieving a technology-based solution involves three methods that generate knowledge in three states, analogous to the three classic states of matter. Research activity generates discoveries that are intangible and highly malleable like a gas; development activity transforms discoveries into inventions that are moderately tangible yet still malleable like a liquid; and production activity transforms inventions into innovations that are tangible and immutable like a solid. The paper demonstrates how the KTA model can accommodate all three types of activity and address all three states of knowledge. Linking the three activities in one model also illustrates the importance of engaging the relevant stakeholders prior to initiating any knowledge-related activities. Summary Science and engineering focused on technology-based devices or services change the state of knowledge through three successive activities. Achieving knowledge implementation requires methods that accommodate these three activities and knowledge states. Accomplishing beneficial societal impacts from technology-based knowledge involves the successful progression through all three activities, and the effective communication of each successive knowledge state to the relevant stakeholders. The KTA model appears suitable for structuring and linking these processes. PMID:20205873

Measuring Knowledge Elaboration Based on a Computer-Assisted Knowledge Map Analytical Approach to Collaborative Learning

ERIC Educational Resources Information Center

Zheng, Lanqin; Huang, Ronghuai; Hwang, Gwo-Jen; Yang, Kaicheng

2015-01-01

The purpose of this study is to quantitatively measure the level of knowledge elaboration and explore the relationships between prior knowledge of a group, group performance, and knowledge elaboration in collaborative learning. Two experiments were conducted to investigate the level of knowledge elaboration. The collaborative learning objective in…

Mi-STAR: Designing Integrated Science Curriculum to Address the Next Generation Science Standards and Their Foundations

NASA Astrophysics Data System (ADS)

Gochis, E. E.; Huntoon, J. E.

2015-12-01

Mi-STAR (Michigan Science Teaching and Assessment Reform, http://mi-star.mtu.edu/) was funded by the Herbert H. and Grace A. Dow Foundation to reform K-12 science education to present science as an integrated body of knowledge that is applied to address societal issues. To achieve this goal, Mi-STAR is developing an integrated science curriculum for the middle grades that will be aligned with the Next Generation Science Standards (NGSS). Similar to the geosciences, the curriculum requires the integration of science, engineering and math content to explore 21st-century issues and demonstrates how these concepts can be used in service of society. The curriculum is based on the Mi-STAR Unit Specification Chart which pairs interdisciplinary themes with bundled NGSS Performance Expectations. Each unit is developed by a collaborative team of K-12 teachers, university STEM content experts and science education experts. Prior to developing a unit, each member on the team attends the on-line Mi-STAR Academy, completing 18+ hours of professional development (PD). This on-line PD program familiarizes teachers and experts with necessary pedagogical and content background knowledge, including NGSS and three-dimensional learning. With this background, teams use a staged, backwards design process to craft a multi-week unit based on a series of performance based tasks, or 'challenges' that engage students in actively doing science and engineering. Each unit includes Disciplinary Core Ideas from multiple disciplines, which focus on local and familiar examples that demonstrate the relevance of science in student's lives. Performance-based assessments are interwoven throughout the unit. Mi-STAR units will go through extensive pilot testing in several school districts across the state of Michigan. Additionally, the Mi-STAR program will develop teacher professional development programs to support implementation of the curriculum and design a pre-service teacher program in integrated science. We will share preliminary results on the collaborative Mi-STAR process of designing integrated science curriculum to address NGSS.

Design and development of a severe storm research UAS

NASA Astrophysics Data System (ADS)

Avery, Alyssa Shearon

A small unmanned aircraft system (SUAS) was designed and developed to be utilized for meteorological data collection, specifically information useful for severe storm and tornado prediction. The system will operate prior to and during severe weather in order to minimize current knowledge gaps with respect to severe storms. This aircraft was developed to maximize the useful data collection while retaining the operational simplicity required of a tool used in an unpredictable environment. The aircraft design is capable of collecting in-situ atmospheric and IR thermodynamic data continuously in flight and deploying sensor packages, dropsondes, at vital locations. The airframe was built, has undergone initial testing, and will be integrated into an operational system in future work.

Superposing pure quantum states with partial prior information

NASA Astrophysics Data System (ADS)

Dogra, Shruti; Thomas, George; Ghosh, Sibasish; Suter, Dieter

2018-05-01

The principle of superposition is an intriguing feature of quantum mechanics, which is regularly exploited in many different circumstances. A recent work [M. Oszmaniec et al., Phys. Rev. Lett. 116, 110403 (2016), 10.1103/PhysRevLett.116.110403] shows that the fundamentals of quantum mechanics restrict the process of superimposing two unknown pure states, even though it is possible to superimpose two quantum states with partial prior knowledge. The prior knowledge imposes geometrical constraints on the choice of input states. We discuss an experimentally feasible protocol to superimpose multiple pure states of a d -dimensional quantum system and carry out an explicit experimental realization for two single-qubit pure states with partial prior information on a two-qubit NMR quantum information processor.

The Impacts of Virtual Manipulatives and Prior Knowledge on Geometry Learning Performance in Junior High School

ERIC Educational Resources Information Center

Lee, Chun-Yi; Chen, Ming-Jang

2014-01-01

Previous studies on the effects of virtual and physical manipulatives have failed to consider the impact of prior knowledge on the efficacy of manipulatives. This study focuses on the learning of plane geometry in junior high schools, including the sum of interior angles in polygons, the sum of exterior angles in polygons, and the properties of…

Exploring the Impact of Prior Knowledge and Appropriate Feedback on Students' Perceived Cognitive Load and Learning Outcomes: Animation-Based Earthquakes Instruction

ERIC Educational Resources Information Center

Yeh, Ting-Kuang; Tseng, Kuan-Yun; Cho, Chung-Wen; Barufaldi, James P.; Lin, Mei-Shin; Chang, Chun-Yen

2012-01-01

The aim of this study was to develop an animation-based curriculum and to evaluate the effectiveness of animation-based instruction; the report involved the assessment of prior knowledge and the appropriate feedback approach, for the purpose of reducing perceived cognitive load and improving learning. The curriculum was comprised of five subunits…

How Word Decoding, Vocabulary and Prior Topic Knowledge Predict Reading Comprehension. A Study of Language-Minority Students in Norwegian Fifth Grade Classrooms

ERIC Educational Resources Information Center

Rydland, Veslemoy; Aukrust, Vibeke Grover; Fulland, Helene

2012-01-01

This study examined the contribution of word decoding, first-language (L1) and second-language (L2) vocabulary and prior topic knowledge to L2 reading comprehension. For measuring reading comprehension we employed two different reading tasks: Woodcock Passage Comprehension and a researcher-developed content-area reading assignment (the Global…

The Effectiveness of Worked Examples Associated with Presentation Format and Prior Knowledge: A Web-Based Experiment

ERIC Educational Resources Information Center

Hsiao, E-Ling

2010-01-01

The aim of this study is to explore whether presentation format and prior knowledge affect the effectiveness of worked examples. The experiment was conducted through a specially designed online instrument. A 2X2X3 factorial before-and-after design was conducted. Three-way ANOVA was employed for data analysis. The result showed first, that prior…

Case-based reasoning for space applications: Utilization of prior experience in knowledge-based systems

NASA Technical Reports Server (NTRS)

King, James A.

1987-01-01

The goal is to explain Case-Based Reasoning as a vehicle to establish knowledge-based systems based on experimental reasoning for possible space applications. This goal will be accomplished through an examination of reasoning based on prior experience in a sample domain, and also through a presentation of proposed space applications which could utilize Case-Based Reasoning techniques.

Effects of Reading Ability, Prior Knowledge, Topic Interest, and Locus of Control on At-Risk College Students' Use of Graphic Organizers and Summarizing.

ERIC Educational Resources Information Center

Balajthy, Ernest; Weisberg, Renee

A study investigated the influence of key factors (general comprehension ability, prior knowledge of passage topic, interest in passage topic, and locus of control) on training at-risk college students in the use of graphic organizers as a cognitive learning strategy. Subjects, 60 college freshmen required to take a developmental reading/study…

Lending a Helping Hand: Voluntary Engagement in Knowledge Sharing

ERIC Educational Resources Information Center

Mergel, Ines; Lazer, David; Binz-Scharf, Maria Christina

2008-01-01

Knowledge is essential for the functioning of every social system, especially for professionals in knowledge-intensive organisations. Since individuals do not possess all the work-related knowledge that they require, they turn to others in search for that knowledge. While prior research has mainly focused on antecedents and consequences of…

Science Literacy and Prior Knowledge of Astronomy MOOC Students

NASA Astrophysics Data System (ADS)

Impey, Chris David; Buxner, Sanlyn; Wenger, Matthew; Formanek, Martin

2018-01-01

Many of science classes offered on Coursera fall into fall into the category of general education or general interest classes for lifelong learners, including our own, Astronomy: Exploring Time and Space. Very little is known about the backgrounds and prior knowledge of these students. In this talk we present the results of a survey of our Astronomy MOOC students. We also compare these results to our previous work on undergraduate students in introductory astronomy courses. Survey questions examined student demographics and motivations as well as their science and information literacy (including basic science knowledge, interest, attitudes and beliefs, and where they get their information about science). We found that our MOOC students are different than the undergraduate students in more ways than demographics. Many MOOC students demonstrated high levels of science and information literacy. With a more comprehensive understanding of our students’ motivations and prior knowledge about science and how they get their information about science, we will be able to develop more tailored learning experiences for these lifelong learners.

49 CFR 192.915 - What knowledge and training must personnel have to carry out an integrity management program?

Code of Federal Regulations, 2013 CFR

2013-10-01

...: MINIMUM FEDERAL SAFETY STANDARDS Gas Transmission Pipeline Integrity Management § 192.915 What knowledge... to the integrity management program possesses and maintains a thorough knowledge of the integrity... 49 Transportation 3 2013-10-01 2013-10-01 false What knowledge and training must personnel have to...

49 CFR 192.915 - What knowledge and training must personnel have to carry out an integrity management program?

Code of Federal Regulations, 2014 CFR

2014-10-01

...: MINIMUM FEDERAL SAFETY STANDARDS Gas Transmission Pipeline Integrity Management § 192.915 What knowledge... to the integrity management program possesses and maintains a thorough knowledge of the integrity... 49 Transportation 3 2014-10-01 2014-10-01 false What knowledge and training must personnel have to...

49 CFR 192.915 - What knowledge and training must personnel have to carry out an integrity management program?

Code of Federal Regulations, 2011 CFR

2011-10-01

...: MINIMUM FEDERAL SAFETY STANDARDS Gas Transmission Pipeline Integrity Management § 192.915 What knowledge... to the integrity management program possesses and maintains a thorough knowledge of the integrity... 49 Transportation 3 2011-10-01 2011-10-01 false What knowledge and training must personnel have to...

49 CFR 192.915 - What knowledge and training must personnel have to carry out an integrity management program?

Code of Federal Regulations, 2012 CFR

2012-10-01

...: MINIMUM FEDERAL SAFETY STANDARDS Gas Transmission Pipeline Integrity Management § 192.915 What knowledge... to the integrity management program possesses and maintains a thorough knowledge of the integrity... 49 Transportation 3 2012-10-01 2012-10-01 false What knowledge and training must personnel have to...

Transition to life--a sendoff to the real world for graduating medical students.

PubMed

Coates, Wendy C; Spector, Tahlia S; Uijtdehaage, Sebastian

2012-01-01

Graduating medical students will enter the workforce, often for the first time. Many have spent the past 20 years as students, receiving financial support from parents, and have not managed real-life issues such as financial planning, real estate, balancing well-being with employment, and integrating into a new community with stressful working conditions. To address a perceived need, we designed an intervention to introduce graduating medical students to financial planning, real estate choices, physician wellness during relocation/internship, and traits of efficient interns. The objectives of this study are to (a) assess baseline experience, knowledge, and comfort of seniors about "real-life" experiences, and (b) assess the efficacy of a 4-hr educational intervention on perceptions of understanding financial planning, real estate choices, intern preparedness, and physician wellness. Acute Care College seniors (classes of 2009 and 2010) attended the intervention after match day and completed a survey to gather demographic data and assess preexisting knowledge and a postintervention survey (1-7 Likert scale). Forty-nine students (45% male; M age = 25.5 years) participated. Prior experiences: 43% no break in education, 51% no full-time job, 38% never signed a rental lease and 94% had not purchased real estate, 90% did not have (or were not aware of having) disability insurance, and 82% had educational debt exceeding $50,000. Following the workshop, students felt more confident in their understanding of life skills topics (real estate, 83%; financial planning, 94%; well-being, 86%). Our workshop assisted in preparing for life after medical school for 98% of the participants. Graduating medical students can gain knowledge about real-life responsibilities and confidence during an educational session prior to starting residency.

Mission Engineering of a Rapid Cycle Spacecraft Logistics Fleet

NASA Technical Reports Server (NTRS)

Holladay, Jon; McClendon, Randy (Technical Monitor)

2002-01-01

The requirement for logistics re-supply of the International Space Station has provided a unique opportunity for engineering the implementation of NASA's first dedicated pressurized logistics carrier fleet. The NASA fleet is comprised of three Multi-Purpose Logistics Modules (MPLM) provided to NASA by the Italian Space Agency in return for operations time aboard the International Space Station. Marshall Space Flight Center was responsible for oversight of the hardware development from preliminary design through acceptance of the third flight unit, and currently manages the flight hardware sustaining engineering and mission engineering activities. The actual MPLM Mission began prior to NASA acceptance of the first flight unit in 1999 and will continue until the de-commission of the International Space Station that is planned for 20xx. Mission engineering of the MPLM program requires a broad focus on three distinct yet inter-related operations processes: pre-flight, flight operations, and post-flight turn-around. Within each primary area exist several complex subsets of distinct and inter-related activities. Pre-flight processing includes the evaluation of carrier hardware readiness for space flight. This includes integration of payload into the carrier, integration of the carrier into the launch vehicle, and integration of the carrier onto the orbital platform. Flight operations include the actual carrier operations during flight and any required real-time ground support. Post-flight processing includes de-integration of the carrier hardware from the launch vehicle, de-integration of the payload, and preparation for returning the carrier to pre-flight staging. Typical space operations are engineered around the requirements and objectives of a dedicated mission on a dedicated operational platform (i.e. Launch or Orbiting Vehicle). The MPLM, however, has expanded this envelope by requiring operations with both vehicles during flight as well as pre-launch and post-landing operations. These unique requirements combined with a success-oriented schedule of four flights within a ten-month period have provided numerous opportunities for understanding and improving operations processes. Furthermore, it has increased the knowledge base of future Payload Carrier and Launch Vehicle hardware and requirement developments. Discussion of the process flows and target areas for process improvement are provided in the subject paper. Special emphasis is also placed on supplying guidelines for hardware development. The combination of process knowledge and hardware development knowledge will provide a comprehensive overview for future vehicle developments as related to integration and transportation of payloads.

An Integrated Model of Knowledge Acquisition and Innovation: Examining the Mediation Effects of Knowledge Integration and Knowledge Application

ERIC Educational Resources Information Center

Dahiyat, Samer E.

2015-01-01

The aim of this research is to empirically investigate the relationships among the three vital knowledge management processes of acquisition, integration and application, and their effects on organisational innovation in the pharmaceutical manufacturing industry in Jordan; a knowledge-intensive business service (KIBS) sector. Structural equation…

Characterizing Middle Grade Students' Integrated Alternative Science Knowledge about the Effects of Climate Change

ERIC Educational Resources Information Center

Fick, Sarah J.; Songer, Nancy Butler

2017-01-01

Recent reforms emphasize a shift in how students should learn and demonstrate knowledge of science. These reforms call for students to learn content knowledge using science and engineering practices, creating integrated science knowledge. While there is existing literature about the development of integrated science knowledge assessments, few…

Crossing borders: High school science teachers learning to teach the specialized language of science

NASA Astrophysics Data System (ADS)

Patrick, Jennifer Drake

The highly specialized language of science is both challenging and alienating to adolescent readers. This study investigated how secondary science teachers learn to teach the specialized language of science in their classrooms. Three research questions guided this study: (a) what do science teachers know about teaching reading in science? (b) what understanding about the unique language demands of science reading do they construct through professional development? and (c) how do they integrate what they have learned about these specialized features of science language into their teaching practices? This study investigated the experience of seven secondary science teachers as they participated in a professional development program designed to teach them about the specialized language of science. Data sources included participant interviews, audio-taped professional development sessions, field notes from classroom observations, and a prior knowledge survey. Results from this study suggest that science teachers (a) were excited to learn about disciplinary reading practices, (b) developed an emergent awareness of the specialized features of science language and the various genres of science writing, and (c) recognized that the challenges of science reading goes beyond vocabulary. These teachers' efforts to understand and address the language of science in their teaching practices were undermined by their lack of basic knowledge of grammar, availability of time and resources, their prior knowledge and experiences, existing curriculum, and school structure. This study contributes to our understanding of how secondary science teachers learn about disciplinary literacy and apply that knowledge in their classroom instruction. It has important implications for literacy educators and science educators who are interested in using language and literacy practices in the service of science teaching and learning. (Full text of this dissertation may be available via the University of Florida Libraries web site. Please check http://www.uflib.ufl.edu/etd.html)

Atypical combinations and scientific impact.

PubMed

Uzzi, Brian; Mukherjee, Satyam; Stringer, Michael; Jones, Ben

2013-10-25

Novelty is an essential feature of creative ideas, yet the building blocks of new ideas are often embodied in existing knowledge. From this perspective, balancing atypical knowledge with conventional knowledge may be critical to the link between innovativeness and impact. Our analysis of 17.9 million papers spanning all scientific fields suggests that science follows a nearly universal pattern: The highest-impact science is primarily grounded in exceptionally conventional combinations of prior work yet simultaneously features an intrusion of unusual combinations. Papers of this type were twice as likely to be highly cited works. Novel combinations of prior work are rare, yet teams are 37.7% more likely than solo authors to insert novel combinations into familiar knowledge domains.

From science to action: Principles for undertaking environmental research that enables knowledge exchange and evidence-based decision-making.

PubMed

Cvitanovic, C; McDonald, J; Hobday, A J

2016-12-01

Effective conservation requires knowledge exchange among scientists and decision-makers to enable learning and support evidence-based decision-making. Efforts to improve knowledge exchange have been hindered by a paucity of empirically-grounded guidance to help scientists and practitioners design and implement research programs that actively facilitate knowledge exchange. To address this, we evaluated the Ningaloo Research Program (NRP), which was designed to generate new scientific knowledge to support evidence-based decisions about the management of the Ningaloo Marine Park in north-western Australia. Specifically, we evaluated (1) outcomes of the NRP, including the extent to which new knowledge informed management decisions; (2) the barriers that prevented knowledge exchange among scientists and managers; (3) the key requirements for improving knowledge exchange processes in the future; and (4) the core capacities that are required to support knowledge exchange processes. While the NRP generated expansive and multidisciplinary science outputs directly relevant to the management of the Ningaloo Marine Park, decision-makers are largely unaware of this knowledge and little has been integrated into decision-making processes. A range of barriers prevented efficient and effective knowledge exchange among scientists and decision-makers including cultural differences among the groups, institutional barriers within decision-making agencies, scientific outputs that were not translated for decision-makers and poor alignment between research design and actual knowledge needs. We identify a set of principles to be implemented routinely as part of any applied research program, including; (i) stakeholder mapping prior to the commencement of research programs to identify all stakeholders, (ii) research questions to be co-developed with stakeholders, (iii) implementation of participatory research approaches, (iv) use of a knowledge broker, and (v) tailored knowledge management systems. Finally, we articulate the individual, institutional and financial capacities that must be developed to underpin successful knowledge exchange strategies. Copyright © 2016 The Authors. Published by Elsevier Ltd.. All rights reserved.

Automatized spleen segmentation in non-contrast-enhanced MR volume data using subject-specific shape priors

NASA Astrophysics Data System (ADS)

Gloger, Oliver; Tönnies, Klaus; Bülow, Robin; Völzke, Henry

2017-07-01

To develop the first fully automated 3D spleen segmentation framework derived from T1-weighted magnetic resonance (MR) imaging data and to verify its performance for spleen delineation and volumetry. This approach considers the issue of low contrast between spleen and adjacent tissue in non-contrast-enhanced MR images. Native T1-weighted MR volume data was performed on a 1.5 T MR system in an epidemiological study. We analyzed random subsamples of MR examinations without pathologies to develop and verify the spleen segmentation framework. The framework is modularized to include different kinds of prior knowledge into the segmentation pipeline. Classification by support vector machines differentiates between five different shape types in computed foreground probability maps and recognizes characteristic spleen regions in axial slices of MR volume data. A spleen-shape space generated by training produces subject-specific prior shape knowledge that is then incorporated into a final 3D level set segmentation method. Individually adapted shape-driven forces as well as image-driven forces resulting from refined foreground probability maps steer the level set successfully to the segment the spleen. The framework achieves promising segmentation results with mean Dice coefficients of nearly 0.91 and low volumetric mean errors of 6.3%. The presented spleen segmentation approach can delineate spleen tissue in native MR volume data. Several kinds of prior shape knowledge including subject-specific 3D prior shape knowledge can be used to guide segmentation processes achieving promising results.

The concept verification testing of materials science payloads

NASA Technical Reports Server (NTRS)

Griner, C. S.; Johnston, M. H.; Whitaker, A.

1976-01-01

The concept Verification Testing (CVT) project at the Marshall Space Flight Center, Alabama, is a developmental activity that supports Shuttle Payload Projects such as Spacelab. It provides an operational 1-g environment for testing NASA and other agency experiment and support systems concepts that may be used in shuttle. A dedicated Materials Science Payload was tested in the General Purpose Laboratory to assess the requirements of a space processing payload on a Spacelab type facility. Physical and functional integration of the experiments into the facility was studied, and the impact of the experiments on the facility (and vice versa) was evaluated. A follow-up test designated CVT Test IVA was also held. The purpose of this test was to repeat Test IV experiments with a crew composed of selected and trained scientists. These personnel were not required to have prior knowledge of the materials science disciplines, but were required to have a basic knowledge of science and the scientific method.

The Role of "Creative Transfer" in Professional Transitions

ERIC Educational Resources Information Center

Triantafyllaki, Angeliki

2016-01-01

This paper discusses the concept of "knowledge transfer" in terms of expansion of prior knowledge, creativity and approaches to generating new knowledge. It explores professional transitions in which knowledge restructuring and identity reformation are pathways into greater work flexibility and adjustment. Two studies, exploring…

Medical student knowledge regarding radiology before and after a radiological anatomy module: implications for vertical integration and self-directed learning.

PubMed

Murphy, Kevin P; Crush, Lee; O'Malley, Eoin; Daly, Fergus E; O'Tuathaigh, Colm M P; O'Connor, Owen J; Cryan, John F; Maher, Michael M

2014-10-01

To examine the impact that anatomy-focused radiology teaching has on non-examined knowledge regarding radiation safety and radiology as a specialty. First-year undergraduate medical students completed surveys prior to and after undertaking the first-year anatomy programme that incorporates radiological anatomy. Students were asked opinions on preferred learning methodology and tested on understanding of radiology as a specialty and radiation safety. Pre-module and post-module response rates were 93 % (157/168) and 85 % (136/160), respectively. Pre-module and post-module, self-directed learning (SDL) ranked eighth (of 11) for preferred gross-anatomy teaching formats. Correct responses regarding radiologist/radiographer roles varied from 28-94 % on 16 questions with 4/16 significantly improving post-module. Identification of modalities that utilise radiation significantly improved for five of eight modalities post-module but knowledge regarding relative amount of modality-specific radiation use was variable pre-module and post-module. SDL is not favoured as an anatomy teaching method. Exposure of students to a radiological anatomy module delivered by senior clinical radiologists improved basic knowledge regarding ionising radiation use, but there was no improvement in knowledge regarding radiation exposure relative per modality. A possible explanation is that students recall knowledge imparted in didactic lectures but do little reading around the subject when the content is not examined. • Self-directed learning is not favoured as a gross anatomy teaching format amongst medical students. • An imaging anatomy-focused module improved basic knowledge regarding ionising radiation use. • Detailed knowledge of modality-specific radiation exposure remained suboptimal post-module. • Knowledge of roles within a clinical radiology department showed little change post-module.

Effects of Process-Oriented and Product-Oriented Worked Examples and Prior Knowledge on Learner Problem Solving and Attitude: A Study in the Domain of Microeconomics

ERIC Educational Resources Information Center

Brooks, Christopher Darren

2009-01-01

The purpose of this study was to investigate the effectiveness of process-oriented and product-oriented worked example strategies and the mediating effect of prior knowledge (high versus low) on problem solving and learner attitude in the domain of microeconomics. In addition, the effect of these variables on learning efficiency as well as the…

Influence of Prior Knowledge and Interest on Fourth- and Fifth-Grade Passage Comprehension on the Qualitative Reading Inventory-4

ERIC Educational Resources Information Center

Clark, Mary Kristen; Kamhi, Alan G.

2014-01-01

Purpose: In 2 experiments, we examined the influence of prior knowledge and interest on 4th- and 5th-grade students' passage comprehension scores on the Qualitative Reading Inventory-4 (QRI-4) and 2 experimenter constructed passages. Method: In Experiment 1, 4th- and 5th-grade students were administered 4 Level 4 passages or 4 Level 5…

Effects of Type of Exploratory Strategy and Prior Knowledge on Middle School Students' Learning of Chemical Formulas from a 3D Role-Playing Game

ERIC Educational Resources Information Center

Chen, Ming-Puu; Wong, Yu-Ting; Wang, Li-Chun

2014-01-01

The purpose of this study was to examine the effects of the type of exploratory strategy and level of prior knowledge on middle school students' performance and motivation in learning chemical formulas via a 3D role-playing game (RPG). Two types of exploratory strategies-RPG exploratory with worked-example and RPG exploratory without…

Counting-On, Trading and Partitioning: Effects of Training and Prior Knowledge on Performance on Base-10 Tasks

ERIC Educational Resources Information Center

Saxton, Matthew; Cakir, Kadir

2006-01-01

Factors affecting performance on base-10 tasks were investigated in a series of four studies with a total of 453 children aged 5-7 years. Training in counting-on was found to enhance child performance on base-10 tasks (Studies 2, 3, and 4), while prior knowledge of counting-on (Study 1), trading (Studies 1 and 3), and partitioning (Studies 1 and…

Track Everything: Limiting Prior Knowledge in Online Multi-Object Recognition.

PubMed

Wong, Sebastien C; Stamatescu, Victor; Gatt, Adam; Kearney, David; Lee, Ivan; McDonnell, Mark D

2017-10-01

This paper addresses the problem of online tracking and classification of multiple objects in an image sequence. Our proposed solution is to first track all objects in the scene without relying on object-specific prior knowledge, which in other systems can take the form of hand-crafted features or user-based track initialization. We then classify the tracked objects with a fast-learning image classifier, that is based on a shallow convolutional neural network architecture and demonstrate that object recognition improves when this is combined with object state information from the tracking algorithm. We argue that by transferring the use of prior knowledge from the detection and tracking stages to the classification stage, we can design a robust, general purpose object recognition system with the ability to detect and track a variety of object types. We describe our biologically inspired implementation, which adaptively learns the shape and motion of tracked objects, and apply it to the Neovision2 Tower benchmark data set, which contains multiple object types. An experimental evaluation demonstrates that our approach is competitive with the state-of-the-art video object recognition systems that do make use of object-specific prior knowledge in detection and tracking, while providing additional practical advantages by virtue of its generality.

Filtering genetic variants and placing informative priors based on putative biological function.

PubMed

Friedrichs, Stefanie; Malzahn, Dörthe; Pugh, Elizabeth W; Almeida, Marcio; Liu, Xiao Qing; Bailey, Julia N

2016-02-03

High-density genetic marker data, especially sequence data, imply an immense multiple testing burden. This can be ameliorated by filtering genetic variants, exploiting or accounting for correlations between variants, jointly testing variants, and by incorporating informative priors. Priors can be based on biological knowledge or predicted variant function, or even be used to integrate gene expression or other omics data. Based on Genetic Analysis Workshop (GAW) 19 data, this article discusses diversity and usefulness of functional variant scores provided, for example, by PolyPhen2, SIFT, or RegulomeDB annotations. Incorporating functional scores into variant filters or weights and adjusting the significance level for correlations between variants yielded significant associations with blood pressure traits in a large family study of Mexican Americans (GAW19 data set). Marker rs218966 in gene PHF14 and rs9836027 in MAP4 significantly associated with hypertension; additionally, rare variants in SNUPN significantly associated with systolic blood pressure. Variant weights strongly influenced the power of kernel methods and burden tests. Apart from variant weights in test statistics, prior weights may also be used when combining test statistics or to informatively weight p values while controlling false discovery rate (FDR). Indeed, power improved when gene expression data for FDR-controlled informative weighting of association test p values of genes was used. Finally, approaches exploiting variant correlations included identity-by-descent mapping and the optimal strategy for joint testing rare and common variants, which was observed to depend on linkage disequilibrium structure.

3D spatially encoded and accelerated TE-averaged echo planar spectroscopic imaging in healthy human brain.

PubMed

Iqbal, Zohaib; Wilson, Neil E; Thomas, M Albert

2016-03-01

Several different pathologies, including many neurodegenerative disorders, affect the energy metabolism of the brain. Glutamate, a neurotransmitter in the brain, can be used as a biomarker to monitor these metabolic processes. One method that is capable of quantifying glutamate concentration reliably in several regions of the brain is TE-averaged (1) H spectroscopic imaging. However, this type of method requires the acquisition of multiple TE lines, resulting in long scan durations. The goal of this experiment was to use non-uniform sampling, compressed sensing reconstruction and an echo planar readout gradient to reduce the scan time by a factor of eight to acquire TE-averaged spectra in three spatial dimensions. Simulation of glutamate and glutamine showed that the 2.2-2.4 ppm spectral region contained 95% glutamate signal using the TE-averaged method. Peak integration of this spectral range and home-developed, prior-knowledge-based fitting were used for quantitation. Gray matter brain phantom measurements were acquired on a Siemens 3 T Trio scanner. Non-uniform sampling was applied retrospectively to these phantom measurements and quantitative results of glutamate with respect to creatine 3.0 (Glu/Cr) ratios showed a coefficient of variance of 16% for peak integration and 9% for peak fitting using eight-fold acceleration. In vivo scans of the human brain were acquired as well and five different brain regions were quantified using the prior-knowledge-based algorithm. Glu/Cr ratios from these regions agreed with previously reported results in the literature. The method described here, called accelerated TE-averaged echo planar spectroscopic imaging (TEA-EPSI), is a significant methodological advancement and may be a useful tool for categorizing glutamate changes in pathologies where affected brain regions are not known a priori. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.

42 CFR § 414.1460 - Monitoring and program integrity.

Code of Federal Regulations, 2010 CFR

2017-10-01

... SERVICES (CONTINUED) MEDICARE PROGRAM (CONTINUED) PAYMENT FOR PART B MEDICAL AND OTHER HEALTH SERVICES Merit-Based Incentive Payment System and Alternative Payment Model Incentive § 414.1460 Monitoring and program integrity. (a) Vetting eligible clinicians prior to payment of the APM Incentive Payment. Prior to...

The Extension-Reduction Strategy: Activating Prior Knowledge

ERIC Educational Resources Information Center

Sloyer, Cliff W.

2004-01-01

A mathematical problem is solved using the extension-reduction or build it up-tear it down tactic. This technique is implemented in reviving students' earlier knowledge to enable them to apply this knowledge to solving new problems.

Interactive web-based learning modules prior to general medicine advanced pharmacy practice experiences.

PubMed

Isaacs, Alex N; Walton, Alison M; Nisly, Sarah A

2015-04-25

To implement and evaluate interactive web-based learning modules prior to advanced pharmacy practice experiences (APPEs) on inpatient general medicine. Three clinical web-based learning modules were developed for use prior to APPEs in 4 health care systems. The aim of the interactive modules was to strengthen baseline clinical knowledge before the APPE to enable the application of learned material through the delivery of patient care. For the primary endpoint, postassessment scores increased overall and for each individual module compared to preassessment scores. Postassessment scores were similar among the health care systems. The survey demonstrated positive student perceptions of this learning experience. Prior to inpatient general medicine APPEs, web-based learning enabled the standardization and assessment of baseline student knowledge across 4 health care systems.

Interplay between Content Knowledge and Scientific Argumentation

ERIC Educational Resources Information Center

Hakyolu, Hanife; Ogan-Bekiroglu, Feral

2016-01-01

This research study aimed to analyze the relationship between content knowledge and argumentation by examining students' prior subject matter knowledge and their production of arguments as well as by comparing students' arguments with their knowledge-in-use during scientific argumentation sessions. A correlational research design was carried out…

Creating Illusions of Knowledge: Learning Errors that Contradict Prior Knowledge

ERIC Educational Resources Information Center

Fazio, Lisa K.; Barber, Sarah J.; Rajaram, Suparna; Ornstein, Peter A.; Marsh, Elizabeth J.

2013-01-01

Most people know that the Pacific is the largest ocean on Earth and that Edison invented the light bulb. Our question is whether this knowledge is stable, or if people will incorporate errors into their knowledge bases, even if they have the correct knowledge stored in memory. To test this, we asked participants general-knowledge questions 2 weeks…

49 CFR 240.209 - Procedures for making the determination on knowledge.

Code of Federal Regulations, 2010 CFR

2010-10-01

... knowledge. 240.209 Section 240.209 Transportation Other Regulations Relating to Transportation (Continued... determination on knowledge. (a) Each railroad, prior to initially certifying or recertifying any person as an... with the requirements of § 240.125 of this part, demonstrated sufficient knowledge of the railroad's...

Activation of Background Knowledge for Inference Making: Effects on Reading Comprehension

ERIC Educational Resources Information Center

Elbro, Carsten; Buch-Iversen, Ida

2013-01-01

Failure to "activate" relevant, existing background knowledge may be a cause of poor reading comprehension. This failure may cause particular problems with inferences that depend heavily on prior knowledge. Conversely, teaching how to use background knowledge in the context of gap-filling inferences could improve reading comprehension in…

Building on prior knowledge without building it in.

PubMed

Hansen, Steven S; Lampinen, Andrew K; Suri, Gaurav; McClelland, James L

2017-01-01

Lake et al. propose that people rely on "start-up software," "causal models," and "intuitive theories" built using compositional representations to learn new tasks more efficiently than some deep neural network models. We highlight the many drawbacks of a commitment to compositional representations and describe our continuing effort to explore how the ability to build on prior knowledge and to learn new tasks efficiently could arise through learning in deep neural networks.

Smoothing Spline ANOVA Decomposition of Arbitrary Splines: An Application to Eye Movements in Reading

PubMed Central

Matuschek, Hannes; Kliegl, Reinhold; Holschneider, Matthias

2015-01-01

The Smoothing Spline ANOVA (SS-ANOVA) requires a specialized construction of basis and penalty terms in order to incorporate prior knowledge about the data to be fitted. Typically, one resorts to the most general approach using tensor product splines. This implies severe constraints on the correlation structure, i.e. the assumption of isotropy of smoothness can not be incorporated in general. This may increase the variance of the spline fit, especially if only a relatively small set of observations are given. In this article, we propose an alternative method that allows to incorporate prior knowledge without the need to construct specialized bases and penalties, allowing the researcher to choose the spline basis and penalty according to the prior knowledge of the observations rather than choosing them according to the analysis to be done. The two approaches are compared with an artificial example and with analyses of fixation durations during reading. PMID:25816246

Use of prior knowledge for the analysis of high-throughput transcriptomics and metabolomics data

PubMed Central

2014-01-01

Background High-throughput omics technologies have enabled the measurement of many genes or metabolites simultaneously. The resulting high dimensional experimental data poses significant challenges to transcriptomics and metabolomics data analysis methods, which may lead to spurious instead of biologically relevant results. One strategy to improve the results is the incorporation of prior biological knowledge in the analysis. This strategy is used to reduce the solution space and/or to focus the analysis on biological meaningful regions. In this article, we review a selection of these methods used in transcriptomics and metabolomics. We combine the reviewed methods in three groups based on the underlying mathematical model: exploratory methods, supervised methods and estimation of the covariance matrix. We discuss which prior knowledge has been used, how it is incorporated and how it modifies the mathematical properties of the underlying methods. PMID:25033193

Using knowledge translation as a framework for the design of a research protocol.

PubMed

Fredericks, Suzanne; Martorella, Géraldine; Catallo, Cristina

2015-05-01

Knowledge translation has been defined as the synthesis, dissemination, exchange and ethically sound application of knowledge to improve health, resulting in a stronger health-care system. Using KT activities to aid in the adoption of evidence into practice can address current health-care challenges such as increasing organizational practice standards, alleviating the risk for adverse events and meeting practitioner needs for evidence at the bedside. Two general forms of KT have been identified. These being integrated KT and end-of-grant KT. Integrated KT involves the knowledge users in the research team and in the majority of stages of the research process. End-of-grant KT relates to the translation of findings through a well-developed dissemination plan. This paper describes the process of using an integrated knowledge translation approach to design a research protocol that will examine the effectiveness of a web-based patient educational intervention. It begins with a description of integrated knowledge translation, followed by the presentation of a specific case example in which integrated knowledge translation is used to develop a nursing intervention. The major elements of integrated knowledge translation pertain to need for a knowledge user who represents the broad target user group, and who is knowledgeable in the area under investigation and who as authority to enact changes to practice. Use of knowledge users as equal partners within the research team; exploring all feasible opportunities for knowledge exchange; and working with knowledge users to identify all outcomes related to knowledge translation are the other major elements of integrated knowledge translation that are addressed throughout this paper. Furthermore, the relevance of psychosocial or educational interventions to knowledge translation is also discussed as a source of knowledge. In summary, integrated knowledge translation is an important tool for the development of new interventions, as it helps to apply science to practice accurately. It supports the elaboration of the design while enhancing the relevance of the intervention through the validation of feasibility and acceptability with clinicians and patients. © 2015 Wiley Publishing Asia Pty Ltd.

Intelligent Integrated Health Management for a System of Systems

NASA Technical Reports Server (NTRS)

Smith, Harvey; Schmalzel, John; Figueroa, Fernando

2008-01-01

An intelligent integrated health management system (IIHMS) incorporates major improvements over prior such systems. The particular IIHMS is implemented for any system defined as a hierarchical distributed network of intelligent elements (HDNIE), comprising primarily: (1) an architecture (Figure 1), (2) intelligent elements, (3) a conceptual framework and taxonomy (Figure 2), and (4) and ontology that defines standards and protocols. Some definitions of terms are prerequisite to a further brief description of this innovation: A system-of-systems (SoS) is an engineering system that comprises multiple subsystems (e.g., a system of multiple possibly interacting flow subsystems that include pumps, valves, tanks, ducts, sensors, and the like); 'Intelligent' is used here in the sense of artificial intelligence. An intelligent element may be physical or virtual, it is network enabled, and it is able to manage data, information, and knowledge (DIaK) focused on determining its condition in the context of the entire SoS; As used here, 'health' signifies the functionality and/or structural integrity of an engineering system, subsystem, or process (leading to determination of the health of components); 'Process' can signify either a physical process in the usual sense of the word or an element into which functionally related sensors are grouped; 'Element' can signify a component (e.g., an actuator, a valve), a process, a controller, an actuator, a subsystem, or a system; The term Integrated System Health Management (ISHM) is used to describe a capability that focuses on determining the condition (health) of every element in a complex system (detect anomalies, diagnose causes, prognosis of future anomalies), and provide data, information, and knowledge (DIaK) not just data to control systems for safe and effective operation. A major novel aspect of the present development is the concept of intelligent integration. The purpose of intelligent integration, as defined and implemented in the present IIHMS, is to enable automated analysis of physical phenomena in imitation of human reasoning, including the use of qualitative methods. Intelligent integration is said to occur in a system in which all elements are intelligent and can acquire, maintain, and share knowledge and information. In the HDNIE of the present IIHMS, an SoS is represented as being operationally organized in a hierarchical-distributed format. The elements of the SoS are considered to be intelligent in that they determine their own conditions within an integrated scheme that involves consideration of data, information, knowledge bases, and methods that reside in all elements of the system. The conceptual framework of the HDNIE and the methodologies of implementing it enable the flow of information and knowledge among the elements so as to make possible the determination of the condition of each element. The necessary information and knowledge is made available to each affected element at the desired time, satisfying a need to prevent information overload while providing context-sensitive information at the proper level of detail. Provision of high-quality data is a central goal in designing this or any IIHMS. In pursuit of this goal, functionally related sensors are logically assigned to groups denoted processes. An aggregate of processes is considered to form a system. Alternatively or in addition to what has been said thus far, the HDNIE of this IIHMS can be regarded as consisting of a framework containing object models that encapsulate all elements of the system, their individual and relational knowledge bases, generic methods and procedures based on models of the applicable physics, and communication processes (Figure 2). The framework enables implementation of a paradigm inspired by how expert operators monitor the health of systems with the help of (1) DIaK from various sources, (2) software tools that assist in rapid visualization of the condition of the system, (3) analical software tools that assist in reasoning about the condition, (4) sharing of information via network communication hardware and software, and (5) software tools that aid in making decisions to remedy unacceptable conditions or improve performance.

45 CFR 1616.3 - Qualifications.

Code of Federal Regulations, 2010 CFR

2010-10-01

...) Academic training and performance; (b) The nature and extent of prior legal experience; (c) Knowledge and understanding of the legal problems and needs of the poor; (d) Prior working experience in the client community...

Integration of genome-wide association studies with biological knowledge identifies six novel genes related to kidney function.

PubMed

Chasman, Daniel I; Fuchsberger, Christian; Pattaro, Cristian; Teumer, Alexander; Böger, Carsten A; Endlich, Karlhans; Olden, Matthias; Chen, Ming-Huei; Tin, Adrienne; Taliun, Daniel; Li, Man; Gao, Xiaoyi; Gorski, Mathias; Yang, Qiong; Hundertmark, Claudia; Foster, Meredith C; O'Seaghdha, Conall M; Glazer, Nicole; Isaacs, Aaron; Liu, Ching-Ti; Smith, Albert V; O'Connell, Jeffrey R; Struchalin, Maksim; Tanaka, Toshiko; Li, Guo; Johnson, Andrew D; Gierman, Hinco J; Feitosa, Mary F; Hwang, Shih-Jen; Atkinson, Elizabeth J; Lohman, Kurt; Cornelis, Marilyn C; Johansson, Asa; Tönjes, Anke; Dehghan, Abbas; Lambert, Jean-Charles; Holliday, Elizabeth G; Sorice, Rossella; Kutalik, Zoltan; Lehtimäki, Terho; Esko, Tõnu; Deshmukh, Harshal; Ulivi, Sheila; Chu, Audrey Y; Murgia, Federico; Trompet, Stella; Imboden, Medea; Coassin, Stefan; Pistis, Giorgio; Harris, Tamara B; Launer, Lenore J; Aspelund, Thor; Eiriksdottir, Gudny; Mitchell, Braxton D; Boerwinkle, Eric; Schmidt, Helena; Cavalieri, Margherita; Rao, Madhumathi; Hu, Frank; Demirkan, Ayse; Oostra, Ben A; de Andrade, Mariza; Turner, Stephen T; Ding, Jingzhong; Andrews, Jeanette S; Freedman, Barry I; Giulianini, Franco; Koenig, Wolfgang; Illig, Thomas; Meisinger, Christa; Gieger, Christian; Zgaga, Lina; Zemunik, Tatijana; Boban, Mladen; Minelli, Cosetta; Wheeler, Heather E; Igl, Wilmar; Zaboli, Ghazal; Wild, Sarah H; Wright, Alan F; Campbell, Harry; Ellinghaus, David; Nöthlings, Ute; Jacobs, Gunnar; Biffar, Reiner; Ernst, Florian; Homuth, Georg; Kroemer, Heyo K; Nauck, Matthias; Stracke, Sylvia; Völker, Uwe; Völzke, Henry; Kovacs, Peter; Stumvoll, Michael; Mägi, Reedik; Hofman, Albert; Uitterlinden, Andre G; Rivadeneira, Fernando; Aulchenko, Yurii S; Polasek, Ozren; Hastie, Nick; Vitart, Veronique; Helmer, Catherine; Wang, Jie Jin; Stengel, Bénédicte; Ruggiero, Daniela; Bergmann, Sven; Kähönen, Mika; Viikari, Jorma; Nikopensius, Tiit; Province, Michael; Ketkar, Shamika; Colhoun, Helen; Doney, Alex; Robino, Antonietta; Krämer, Bernhard K; Portas, Laura; Ford, Ian; Buckley, Brendan M; Adam, Martin; Thun, Gian-Andri; Paulweber, Bernhard; Haun, Margot; Sala, Cinzia; Mitchell, Paul; Ciullo, Marina; Kim, Stuart K; Vollenweider, Peter; Raitakari, Olli; Metspalu, Andres; Palmer, Colin; Gasparini, Paolo; Pirastu, Mario; Jukema, J Wouter; Probst-Hensch, Nicole M; Kronenberg, Florian; Toniolo, Daniela; Gudnason, Vilmundur; Shuldiner, Alan R; Coresh, Josef; Schmidt, Reinhold; Ferrucci, Luigi; Siscovick, David S; van Duijn, Cornelia M; Borecki, Ingrid B; Kardia, Sharon L R; Liu, Yongmei; Curhan, Gary C; Rudan, Igor; Gyllensten, Ulf; Wilson, James F; Franke, Andre; Pramstaller, Peter P; Rettig, Rainer; Prokopenko, Inga; Witteman, Jacqueline; Hayward, Caroline; Ridker, Paul M; Parsa, Afshin; Bochud, Murielle; Heid, Iris M; Kao, W H Linda; Fox, Caroline S; Köttgen, Anna

2012-12-15

In conducting genome-wide association studies (GWAS), analytical approaches leveraging biological information may further understanding of the pathophysiology of clinical traits. To discover novel associations with estimated glomerular filtration rate (eGFR), a measure of kidney function, we developed a strategy for integrating prior biological knowledge into the existing GWAS data for eGFR from the CKDGen Consortium. Our strategy focuses on single nucleotide polymorphism (SNPs) in genes that are connected by functional evidence, determined by literature mining and gene ontology (GO) hierarchies, to genes near previously validated eGFR associations. It then requires association thresholds consistent with multiple testing, and finally evaluates novel candidates by independent replication. Among the samples of European ancestry, we identified a genome-wide significant SNP in FBXL20 (P = 5.6 × 10(-9)) in meta-analysis of all available data, and additional SNPs at the INHBC, LRP2, PLEKHA1, SLC3A2 and SLC7A6 genes meeting multiple-testing corrected significance for replication and overall P-values of 4.5 × 10(-4)-2.2 × 10(-7). Neither the novel PLEKHA1 nor FBXL20 associations, both further supported by association with eGFR among African Americans and with transcript abundance, would have been implicated by eGFR candidate gene approaches. LRP2, encoding the megalin receptor, was identified through connection with the previously known eGFR gene DAB2 and extends understanding of the megalin system in kidney function. These findings highlight integration of existing genome-wide association data with independent biological knowledge to uncover novel candidate eGFR associations, including candidates lacking known connections to kidney-specific pathways. The strategy may also be applicable to other clinical phenotypes, although more testing will be needed to assess its potential for discovery in general.

Integration of genome-wide association studies with biological knowledge identifies six novel genes related to kidney function

PubMed Central

Chasman, Daniel I.; Fuchsberger, Christian; Pattaro, Cristian; Teumer, Alexander; Böger, Carsten A.; Endlich, Karlhans; Olden, Matthias; Chen, Ming-Huei; Tin, Adrienne; Taliun, Daniel; Li, Man; Gao, Xiaoyi; Gorski, Mathias; Yang, Qiong; Hundertmark, Claudia; Foster, Meredith C.; O'Seaghdha, Conall M.; Glazer, Nicole; Isaacs, Aaron; Liu, Ching-Ti; Smith, Albert V.; O'Connell, Jeffrey R.; Struchalin, Maksim; Tanaka, Toshiko; Li, Guo; Johnson, Andrew D.; Gierman, Hinco J.; Feitosa, Mary F.; Hwang, Shih-Jen; Atkinson, Elizabeth J.; Lohman, Kurt; Cornelis, Marilyn C.; Johansson, Åsa; Tönjes, Anke; Dehghan, Abbas; Lambert, Jean-Charles; Holliday, Elizabeth G.; Sorice, Rossella; Kutalik, Zoltan; Lehtimäki, Terho; Esko, Tõnu; Deshmukh, Harshal; Ulivi, Sheila; Chu, Audrey Y.; Murgia, Federico; Trompet, Stella; Imboden, Medea; Coassin, Stefan; Pistis, Giorgio; Harris, Tamara B.; Launer, Lenore J.; Aspelund, Thor; Eiriksdottir, Gudny; Mitchell, Braxton D.; Boerwinkle, Eric; Schmidt, Helena; Cavalieri, Margherita; Rao, Madhumathi; Hu, Frank; Demirkan, Ayse; Oostra, Ben A.; de Andrade, Mariza; Turner, Stephen T.; Ding, Jingzhong; Andrews, Jeanette S.; Freedman, Barry I.; Giulianini, Franco; Koenig, Wolfgang; Illig, Thomas; Meisinger, Christa; Gieger, Christian; Zgaga, Lina; Zemunik, Tatijana; Boban, Mladen; Minelli, Cosetta; Wheeler, Heather E.; Igl, Wilmar; Zaboli, Ghazal; Wild, Sarah H.; Wright, Alan F.; Campbell, Harry; Ellinghaus, David; Nöthlings, Ute; Jacobs, Gunnar; Biffar, Reiner; Ernst, Florian; Homuth, Georg; Kroemer, Heyo K.; Nauck, Matthias; Stracke, Sylvia; Völker, Uwe; Völzke, Henry; Kovacs, Peter; Stumvoll, Michael; Mägi, Reedik; Hofman, Albert; Uitterlinden, Andre G.; Rivadeneira, Fernando; Aulchenko, Yurii S.; Polasek, Ozren; Hastie, Nick; Vitart, Veronique; Helmer, Catherine; Wang, Jie Jin; Stengel, Bénédicte; Ruggiero, Daniela; Bergmann, Sven; Kähönen, Mika; Viikari, Jorma; Nikopensius, Tiit; Province, Michael; Ketkar, Shamika; Colhoun, Helen; Doney, Alex; Robino, Antonietta; Krämer, Bernhard K.; Portas, Laura; Ford, Ian; Buckley, Brendan M.; Adam, Martin; Thun, Gian-Andri; Paulweber, Bernhard; Haun, Margot; Sala, Cinzia; Mitchell, Paul; Ciullo, Marina; Kim, Stuart K.; Vollenweider, Peter; Raitakari, Olli; Metspalu, Andres; Palmer, Colin; Gasparini, Paolo; Pirastu, Mario; Jukema, J. Wouter; Probst-Hensch, Nicole M.; Kronenberg, Florian; Toniolo, Daniela; Gudnason, Vilmundur; Shuldiner, Alan R.; Coresh, Josef; Schmidt, Reinhold; Ferrucci, Luigi; Siscovick, David S.; van Duijn, Cornelia M.; Borecki, Ingrid B.; Kardia, Sharon L.R.; Liu, Yongmei; Curhan, Gary C.; Rudan, Igor; Gyllensten, Ulf; Wilson, James F.; Franke, Andre; Pramstaller, Peter P.; Rettig, Rainer; Prokopenko, Inga; Witteman, Jacqueline; Hayward, Caroline; Ridker, Paul M; Parsa, Afshin; Bochud, Murielle; Heid, Iris M.; Kao, W.H. Linda; Fox, Caroline S.; Köttgen, Anna

2012-01-01

In conducting genome-wide association studies (GWAS), analytical approaches leveraging biological information may further understanding of the pathophysiology of clinical traits. To discover novel associations with estimated glomerular filtration rate (eGFR), a measure of kidney function, we developed a strategy for integrating prior biological knowledge into the existing GWAS data for eGFR from the CKDGen Consortium. Our strategy focuses on single nucleotide polymorphism (SNPs) in genes that are connected by functional evidence, determined by literature mining and gene ontology (GO) hierarchies, to genes near previously validated eGFR associations. It then requires association thresholds consistent with multiple testing, and finally evaluates novel candidates by independent replication. Among the samples of European ancestry, we identified a genome-wide significant SNP in FBXL20 (P = 5.6 × 10−9) in meta-analysis of all available data, and additional SNPs at the INHBC, LRP2, PLEKHA1, SLC3A2 and SLC7A6 genes meeting multiple-testing corrected significance for replication and overall P-values of 4.5 × 10−4–2.2 × 10−7. Neither the novel PLEKHA1 nor FBXL20 associations, both further supported by association with eGFR among African Americans and with transcript abundance, would have been implicated by eGFR candidate gene approaches. LRP2, encoding the megalin receptor, was identified through connection with the previously known eGFR gene DAB2 and extends understanding of the megalin system in kidney function. These findings highlight integration of existing genome-wide association data with independent biological knowledge to uncover novel candidate eGFR associations, including candidates lacking known connections to kidney-specific pathways. The strategy may also be applicable to other clinical phenotypes, although more testing will be needed to assess its potential for discovery in general. PMID:22962313

Integrating pedagogical content knowledge and pedagogical/psychological knowledge in mathematics.

PubMed

Harr, Nora; Eichler, Andreas; Renkl, Alexander

2014-01-01

In teacher education at universities, general pedagogical and psychological principles are often treated separately from subject matter knowledge and therefore run the risk of not being applied in the teaching subject. In an experimental study (N = 60 mathematics student teachers) we investigated the effects of providing aspects of general pedagogical/psychological knowledge (PPK) and pedagogical content knowledge (PCK) in an integrated or separated way. In both conditions ("integrated" vs. "separated"), participants individually worked on computer-based learning environments addressing the same topic: use and handling of multiple external representations, a central issue in mathematics. We experimentally varied whether PPK aspects and PCK aspects were treated integrated or apart from one another. As expected, the integrated condition led to greater application of pedagogical/psychological aspects and an increase in applying both knowledge types simultaneously compared to the separated condition. Overall, our findings indicate beneficial effects of an integrated design in teacher education.

Ontological modelling of knowledge management for human-machine integrated design of ultra-precision grinding machine

NASA Astrophysics Data System (ADS)

Hong, Haibo; Yin, Yuehong; Chen, Xing

2016-11-01

Despite the rapid development of computer science and information technology, an efficient human-machine integrated enterprise information system for designing complex mechatronic products is still not fully accomplished, partly because of the inharmonious communication among collaborators. Therefore, one challenge in human-machine integration is how to establish an appropriate knowledge management (KM) model to support integration and sharing of heterogeneous product knowledge. Aiming at the diversity of design knowledge, this article proposes an ontology-based model to reach an unambiguous and normative representation of knowledge. First, an ontology-based human-machine integrated design framework is described, then corresponding ontologies and sub-ontologies are established according to different purposes and scopes. Second, a similarity calculation-based ontology integration method composed of ontology mapping and ontology merging is introduced. The ontology searching-based knowledge sharing method is then developed. Finally, a case of human-machine integrated design of a large ultra-precision grinding machine is used to demonstrate the effectiveness of the method.

Hyperspectral Feature Detection Onboard the Earth Observing One Spacecraft using Superpixel Segmentation and Endmember Extraction

NASA Technical Reports Server (NTRS)

Thompson, David R.; Bornstein, Benjamin; Bue, Brian D.; Tran, Daniel Q.; Chien, Steve A.; Castano, Rebecca

2012-01-01

We present a demonstration of onboard hyperspectral image processing with the potential to reduce mission downlink requirements. The system detects spectral endmembers and then uses them to map units of surface material. This summarizes the content of the scene, reveals spectral anomalies warranting fast response, and reduces data volume by two orders of magnitude. We have integrated this system into the Autonomous Science craft Experiment for operational use onboard the Earth Observing One (EO-1) Spacecraft. The system does not require prior knowledge about spectra of interest. We report on a series of trial overflights in which identical spacecraft commands are effective for autonomous spectral discovery and mapping for varied target features, scenes and imaging conditions.

Human trafficking education for nurse practitioners: Integration into standard curriculum.

PubMed

Lutz, Rebecca M

2018-02-01

Human trafficking is a crime resulting in serious negative health outcomes for the victims. To provide optimal care, thus improving health outcomes, healthcare providers must be able to identify victims as they seek care for acute and chronic physical illness, communicable diseases, sexually transmitted infections, and mental health disorders (Lederer and Wetzel, 2014; Oram et al., 2012). Unfortunately, healthcare providers lack appropriate knowledge of clues that would lead to victim identification. This may result in a failure to identify victims (Beck et al., 2015; Ross et al., 2015; Konstantopoulos et al., 2013; Chisolm-Straker et al., 2012). Increasing the number of healthcare providers able to identify, treat, and refer victims of trafficking for further care is imperative. The study evaluated the knowledge level of student nurse practitioners enrolled in an adult, family, or pediatric clinical course. Knowledge domains included the definitions, laws, prevalence, identification, treatment, and community and social service resources. The study was designed as a non-probability sampling of adult, family, and pediatric nurse practitioner students (n=73). Participants included students enrolled in the Adult & Older Adult I or the Primary Care of the Child & Adolescent I course at a large public university. The study was designed as a one hour educational intervention intended for presentation in a lecture-style format. The educational intervention included a PowerPoint lecture and embedded videos. The pre-survey, designed as a paper survey, contained a demographic section followed by six survey questions covering the six domains of interest. Following the intervention, participants completed the post-survey prior to leaving the classroom. Pre-survey results pinpointed knowledge gaps across all six domains under investigation. Post-survey results revealed an increase in knowledge across all six domains of interest. The educational intervention increased knowledge of human trafficking among students enrolled in a nurse practitioner program. Informed nurse practitioners have the ability to identify, treat, and refer victims of trafficking. As an integral part of the health care team, nurse practitioners should receive trafficking education as part of the standard course curricula. Copyright © 2017 Elsevier Ltd. All rights reserved.

A Study about Placement Support Using Semantic Similarity

ERIC Educational Resources Information Center

Katz, Marco; van Bruggen, Jan; Giesbers, Bas; Waterink, Wim; Eshuis, Jannes; Koper, Rob

2014-01-01

This paper discusses Latent Semantic Analysis (LSA) as a method for the assessment of prior learning. The Accreditation of Prior Learning (APL) is a procedure to offer learners an individualized curriculum based on their prior experiences and knowledge. The placement decisions in this process are based on the analysis of student material by domain…

The Effects of Feedback during Exploratory Mathematics Problem Solving: Prior Knowledge Matters

ERIC Educational Resources Information Center

Fyfe, Emily R.; Rittle-Johnson, Bethany; DeCaro, Marci S.

2012-01-01

Providing exploratory activities prior to explicit instruction can facilitate learning. However, the level of guidance provided during the exploration has largely gone unstudied. In this study, we examined the effects of 1 form of guidance, feedback, during exploratory mathematics problem solving for children with varying levels of prior domain…

Learners' strategies for reconstructing cognitive frameworks and navigating conceptual change from prior conception to consensual genetics knowledge

NASA Astrophysics Data System (ADS)

Parrott, Annette M.

Problem. Science teachers are charged with preparing students to become scientifically literate individuals. Teachers are given curriculum that specifies the knowledge that students should come away with; however, they are not necessarily aware of the knowledge with which the student arrives or how best to help them navigate between the two knowledge states. Educators must be aware, not only of where their students are conceptually, but how their students move from their prior knowledge and naive theories, to scientifically acceptable theories. The understanding of how students navigate this course has the potential to revolutionize educational practices. Methods. This study explored how five 9th grade biology students reconstructed their cognitive frameworks and navigated conceptual change from prior conception to consensual genetics knowledge. The research questions investigated were: (1) how do students in the process of changing their naive science theories to accepted science theories describe their journey from prior knowledge to current conception, and (2) what are the methods that students utilize to bridge the gap between alternate and consensual science conceptions to effect conceptual change. Qualitative and quantitative methods were employed to gather and analyze the data. In depth, semi-structured interviews formed the primary data for probing the context and details of students' conceptual change experience. Primary interview data was coded by thematic analysis. Results and discussion. This study revealed information about students' perceived roles in learning, the role of articulation in the conceptual change process, and ways in which a community of learners aids conceptual change. It was ascertained that students see their role in learning primarily as repeating information until they could add that information to their knowledge. Students are more likely to consider challenges to their conceptual frameworks and be more motivated to become active participants in constructing their knowledge when they are working collaboratively with peers instead of receiving instruction from their teacher. Articulation was found to be instrumental in aiding learners in identifying their alternate conceptions as well as in revisiting, investigating and reconstructing their conceptual frameworks. Based on the assumptions generated, suggestions were offered to inform pedagogical practice in support of the conceptual change process.

Temporal dynamics of the knowledge-mediated visual disambiguation process in humans: a magnetoencephalography study.

PubMed

Urakawa, Tomokazu; Ogata, Katsuya; Kimura, Takahiro; Kume, Yuko; Tobimatsu, Shozo

2015-01-01

Disambiguation of a noisy visual scene with prior knowledge is an indispensable task of the visual system. To adequately adapt to a dynamically changing visual environment full of noisy visual scenes, the implementation of knowledge-mediated disambiguation in the brain is imperative and essential for proceeding as fast as possible under the limited capacity of visual image processing. However, the temporal profile of the disambiguation process has not yet been fully elucidated in the brain. The present study attempted to determine how quickly knowledge-mediated disambiguation began to proceed along visual areas after the onset of a two-tone ambiguous image using magnetoencephalography with high temporal resolution. Using the predictive coding framework, we focused on activity reduction for the two-tone ambiguous image as an index of the implementation of disambiguation. Source analysis revealed that a significant activity reduction was observed in the lateral occipital area at approximately 120 ms after the onset of the ambiguous image, but not in preceding activity (about 115 ms) in the cuneus when participants perceptually disambiguated the ambiguous image with prior knowledge. These results suggested that knowledge-mediated disambiguation may be implemented as early as approximately 120 ms following an ambiguous visual scene, at least in the lateral occipital area, and provided an insight into the temporal profile of the disambiguation process of a noisy visual scene with prior knowledge. © 2014 Federation of European Neuroscience Societies and John Wiley & Sons Ltd.

The dynamics of fidelity over the time course of long-term memory.

PubMed

Persaud, Kimele; Hemmer, Pernille

2016-08-01

Bayesian models of cognition assume that prior knowledge about the world influences judgments. Recent approaches have suggested that the loss of fidelity from working to long-term (LT) memory is simply due to an increased rate of guessing (e.g. Brady, Konkle, Gill, Oliva, & Alvarez, 2013). That is, recall is the result of either remembering (with some noise) or guessing. This stands in contrast to Bayesian models of cognition while assume that prior knowledge about the world influences judgments, and that recall is a combination of expectations learned from the environment and noisy memory representations. Here, we evaluate the time course of fidelity in LT episodic memory, and the relative contribution of prior category knowledge and guessing, using a continuous recall paradigm. At an aggregate level, performance reflects a high rate of guessing. However, when aggregate data is partitioned by lag (i.e., the number of presentations from study to test), or is un-aggregated, performance appears to be more complex than just remembering with some noise and guessing. We implemented three models: the standard remember-guess model, a three-component remember-guess model, and a Bayesian mixture model and evaluated these models against the data. The results emphasize the importance of taking into account the influence of prior category knowledge on memory. Copyright © 2016 Elsevier Inc. All rights reserved.

Assessment of Knowledge Transfer in the Context of Biomechanics

ERIC Educational Resources Information Center

Hutchison, Randolph E.

2011-01-01

The dynamic act of knowledge transfer, or the connection of a student's prior knowledge to features of a new problem, could be considered one of the primary goals of education. Yet studies highlight more instances of failure than success. This dissertation focuses on how knowledge transfer takes place during individual problem solving, in…

New Knowledge Derived from Learned Knowledge: Functional-Anatomic Correlates of Stimulus Equivalence

ERIC Educational Resources Information Center

Schlund, Michael W.; Hoehn-Saric, Rudolf; Cataldo, Michael F.

2007-01-01

Forming new knowledge based on knowledge established through prior learning is a central feature of higher cognition that is captured in research on stimulus equivalence (SE). Numerous SE investigations show that reinforcing behavior under control of distinct sets of arbitrary conditional relations gives rise to stimulus control by new, "derived"…

They're Lovin' It: How Preschool Children Mediated Their Funds of Knowledge into Dramatic Play

ERIC Educational Resources Information Center

Karabon, Anne

2017-01-01

The funds of knowledge framework promotes connecting community contexts with curriculum aimed to activate children's prior knowledge. Typically, teachers determine what knowledge sources harmonise best with their existing programming, potentially omitting particular resources that may not align. Young children, on the other hand, can act as agents…

Is knowledge important? Empirical research on nuclear risk communication in two countries.

PubMed

Perko, Tanja; Zeleznik, Nadja; Turcanu, Catrinel; Thijssen, Peter

2012-06-01

Increasing audience knowledge is often set as a primary objective of risk communication efforts. But is it worthwhile focusing risk communication strategies solely on enhancing specific knowledge? The main research questions tackled in this paper were: (1) if prior audience knowledge related to specific radiation risks is influential for the perception of these risks and the acceptance of communicated messages and (2) if gender, attitudes, risk perception of other radiation risks, confidence in authorities, and living in the vicinity of nuclear/radiological installations may also play an important role in this matter. The goal of this study was to test empirically the mentioned predictors in two independent case studies in different countries. The first case study was an information campaign for iodine pre-distribution in Belgium (N = 1035). The second was the information campaign on long-term radioactive waste disposal in Slovenia (N = 1,200). In both cases, recurrent and intensive communication campaigns were carried out by the authorities aiming, among other things, at increasing specific audience knowledge. Results show that higher prior audience knowledge leads to more willingness to accept communicated messages, but it does not affect people’s perception of the specific risk communicated. In addition, the influence of prior audience knowledge on the acceptance of communicated messages is shown to be no stronger than that of general radiation risk perception. The results in both case studies suggest that effective risk communication has to focus not only on knowledge but also on other more heuristic predictors, such as risk perception or attitudes toward communicated risks.

A pilot educational intervention for headache and concussion: The headache and arts program.

PubMed

Minen, Mia T; Boubour, Alexandra

2018-05-15

Using a science, technology, engineering, arts, and mathematics (STEAM) curriculum, we developed, piloted, and tested the Headache and Arts Program. This program seeks to increase knowledge and awareness of migraine and concussion among high school students through a visual arts-based curriculum. We developed a 2-week Headache and Arts Program with lesson plans and art assignments for high school visual arts classes and an age-appropriate assessment to assess students' knowledge of migraine and concussion. We assessed students' knowledge through (1) the creation of artwork that depicted the experience of a migraine or concussion, (2) the conception and implementation of methods to transfer knowledge gained through the program, and (3) preassessment and postassessment results. The assessment was distributed to all students prior to the Headache and Arts Program. In a smaller sample, we distributed the assessment 3 months after the program to assess longitudinal effects. Descriptive analyses and p values were calculated using SPSS V.24 and Microsoft Excel. Forty-eight students participated in the research program. Students created artwork that integrated STEAM knowledge learned through the program and applied creative methods to teach others about migraine and concussion. At baseline, students' total scores averaged 67.6% correct. Total scores for the longitudinal preassessment, immediate postassessment, and delayed 3-month postassessment averaged 69.4%, 72.8%, and 80.0% correct, respectively. The use of a visual arts-based curriculum may be effective for migraine and concussion education among high school students. © 2018 American Academy of Neurology.

Relations among Conceptual Knowledge, Procedural Knowledge, and Procedural Flexibility in Two Samples Differing in Prior Knowledge

ERIC Educational Resources Information Center

Schneider, Michael; Rittle-Johnson, Bethany; Star, Jon R.

2011-01-01

Competence in many domains rests on children developing conceptual and procedural knowledge, as well as procedural flexibility. However, research on the developmental relations between these different types of knowledge has yielded unclear results, in part because little attention has been paid to the validity of the measures or to the effects of…

Toward automated interpretation of integrated information: Managing "big data" for NDE

NASA Astrophysics Data System (ADS)

Gregory, Elizabeth; Lesthaeghe, Tyler; Holland, Stephen

2015-03-01

Large scale automation of NDE processes is rapidly maturing, thanks to recent improvements in robotics and the rapid growth of computer power over the last twenty years. It is fairly straightforward to automate NDE data collection itself, but the process of NDE remains largely manual. We will discuss three threads of technological needs that must be addressed before we are able to perform automated NDE. Spatial context, the first thread, means that each NDE measurement taken is accompanied by metadata that locates the measurement with respect to the 3D physical geometry of the specimen. In this way, the geometry of the specimen acts as a database key. Data context, the second thread, means that we record why the data was taken and how it was measured in addition to the NDE data itself. We will present our software tool that helps users interact with data in context, Databrowse. Condition estimation, the third thread, is maintaining the best possible knowledge of the condition (serviceability, degradation, etc.) of an object or part. In the NDE context, we can prospectively use Bayes' Theorem to integrate the data from each new NDE measurement with prior knowledge. These tools, combined with robotic measurements and automated defect analysis, will provide the information needed to make high-level life predictions and focus NDE measurements where they are needed most.

Integrating across Episodes: Investigating the Long-term Accessibility of Self-derived Knowledge in 4-Year-Old Children

PubMed Central

Varga, Nicole L.; Stewart, Rebekah A.; Bauer, Patricia J.

2016-01-01

Semantic memory, defined as our store of knowledge about the world, provides representational support for all of our higher order cognitive functions. As such, it is crucial that the contents of semantic memory remain accessible over time. Although memory for knowledge learned through direct observation has been previously investigated, we know very little about the retention of knowledge derived through integration of information acquired across separate learning episodes. The present research investigated cross-episode integration in 4-year-old children. Participants were presented with novel facts via distinct story episodes and tested for knowledge extension through cross-episode integration, as well as for retention of the information over a 1-week delay. In Experiment 1, children retained the self-derived knowledge over the delay, though performance was primarily evidenced in a forced-choice format. In Experiment 2, we sought to facilitate the accessibility and robustness of self-derived knowledge by providing a verbal reminder after the delay. The accessibility of self-derived knowledge increased, irrespective of whether participants successfully demonstrated knowledge of the integration facts during the first visit. The results suggest knowledge extended through integration remains accessible after delays, even in a population in which this learning process is less robust. The findings also demonstrate the facilitative effect of reminders on the accessibility and further extension of knowledge over extended time periods. PMID:26774259

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

PedAM: a database for Pediatric Disease Annotation and Medicine.

PubMed

Jia, Jinmeng; An, Zhongxin; Ming, Yue; Guo, Yongli; Li, Wei; Li, Xin; Liang, Yunxiang; Guo, Dongming; Tai, Jun; Chen, Geng; Jin, Yaqiong; Liu, Zhimei; Ni, Xin; Shi, Tieliu

2018-01-04

There is a significant number of children around the world suffering from the consequence of the misdiagnosis and ineffective treatment for various diseases. To facilitate the precision medicine in pediatrics, a database namely the Pediatric Disease Annotations & Medicines (PedAM) has been built to standardize and classify pediatric diseases. The PedAM integrates both biomedical resources and clinical data from Electronic Medical Records to support the development of computational tools, by which enables robust data analysis and integration. It also uses disease-manifestation (D-M) integrated from existing biomedical ontologies as prior knowledge to automatically recognize text-mined, D-M-specific syntactic patterns from 774 514 full-text articles and 8 848 796 abstracts in MEDLINE. Additionally, disease connections based on phenotypes or genes can be visualized on the web page of PedAM. Currently, the PedAM contains standardized 8528 pediatric disease terms (4542 unique disease concepts and 3986 synonyms) with eight annotation fields for each disease, including definition synonyms, gene, symptom, cross-reference (Xref), human phenotypes and its corresponding phenotypes in the mouse. The database PedAM is freely accessible at http://www.unimd.org/pedam/. © The Author(s) 2017. Published by Oxford University Press on behalf of Nucleic Acids Research.

An investigation of prior knowledge in Automatic Music Transcription systems.

PubMed

Cazau, Dorian; Revillon, Guillaume; Krywyk, Julien; Adam, Olivier

2015-10-01

Automatic transcription of music is a long-studied research field with many operational systems available commercially. In this paper, a generic transcription system able to host various prior knowledge parameters has been developed, followed by an in-depth investigation of their impact on music transcription. Explicit links between musical knowledge and algorithmic formalism have been made. Musical knowledge covers classes of timbre, musicology, and playing style of an instrument repertoire. An evaluation sound corpus gathering musical pieces played by human performers from three different instrument repertoires, namely, classical piano, steel-string acoustic guitar, and the marovany zither from Madagascar, has been developed. The different components of musical knowledge have been successively incorporated in a complete transcription system, consisting mainly of a Probabilistic Latent Component Analysis algorithm post-processed with a Hidden Markov Model, and their impact on transcription results have been comparatively evaluated.

Weighted integration of short-term memory and sensory signals in the oculomotor system.

PubMed

Deravet, Nicolas; Blohm, Gunnar; de Xivry, Jean-Jacques Orban; Lefèvre, Philippe

2018-05-01

Oculomotor behaviors integrate sensory and prior information to overcome sensory-motor delays and noise. After much debate about this process, reliability-based integration has recently been proposed and several models of smooth pursuit now include recurrent Bayesian integration or Kalman filtering. However, there is a lack of behavioral evidence in humans supporting these theoretical predictions. Here, we independently manipulated the reliability of visual and prior information in a smooth pursuit task. Our results show that both smooth pursuit eye velocity and catch-up saccade amplitude were modulated by visual and prior information reliability. We interpret these findings as the continuous reliability-based integration of a short-term memory of target motion with visual information, which support modeling work. Furthermore, we suggest that saccadic and pursuit systems share this short-term memory. We propose that this short-term memory of target motion is quickly built and continuously updated, and constitutes a general building block present in all sensorimotor systems.

Pesticide use knowledge and practices: A gender differences in Nepal

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

Atreya, Kishor

It is important to understand gender difference on pesticide use knowledge, attitude and practices for identifying pesticide risks by gender and to recommend more gender-sensitive programs. However, very few studies have been conducted so far in Nepal. This study, thus, interviewed a total of 325 males and 109 females during 2005 to assess gender differences on pesticide use knowledge, attitude and practices. More than 50% females had never been to school and only <8% individuals were found trained in Integrated Pest Management (IPM). Almost all males and females did not smoke, drink and eat during pesticides application and also believedmore » that pesticides are harmful to human health, livestock, plant diversity and their environment. However, there were gender differences on household decision on pesticides to be used (p<0.001), care of wind direction during spraying (p=0.032), prior knowledge on safety measures (p=0.016), reading and understanding of pesticides labels (p<0.001), awareness of the labels (p<0.001) and protective covers. Almost all respondents were aware of negative impacts of pesticide use on human health and environment irrespective of gender; however, females were at higher risk due to lower level of pesticide use safety and awareness. It is strongly recommended to initiate gender-sensitive educational and awareness activities, especially on pesticide use practices and safety precautions.« less

Development of an Integrative Program of Nanosafety: Promote the Coordination Between Industries and Risk Assessor

NASA Astrophysics Data System (ADS)

Emond, Claude; Kouassi, Serge; Schuster, Frédéric

2013-04-01

Nanomaterials are widely present in many industrial sectors (e.g., chemical, biomedical, environment), and their application is expected to significantly expand in the coming years. However, nanomaterial use raises many questions about the potential risks to human health and the environment and, more specifically, to occupational health. The available literature supports the ability of the lung, gastrointestinal tract, and skin to act as significant barriers against systemic exposure to many nanomaterials. However, because a potential risk issue exists about the toxicity of nanomaterials to the biological material, tools need to be developed for improving the risk management of the regulators. The goal is to develop a tool that examines the current knowledge base regarding the health risks posed by engineered nanoparticles to improve nanotechnology safety prior to the marketing phase. The approach proposed during this work was to establish a safety assessment constructed on a decision-control pathway regarding nanomaterial production and consumer's product to integrate different aspects. These aspects include: (1) primarily research and identification of the nanomaterial base of physicochemical properties, toxicity, and application; (2) the occupational exposure risk during the manufacturing process; (3) and the engineered nanomaterial upon the consumer product. This approach provides important parameters to reduce the uncertainty related to the production of nanomaterials prior their commercialization, reduce the reluctance from the industry, and provide a certification tool of sanitary control for the regulators. This work provides a better understanding of a critical issue of nanomaterials and consumer safety.

What are they up to? The role of sensory evidence and prior knowledge in action understanding.

PubMed

Chambon, Valerian; Domenech, Philippe; Pacherie, Elisabeth; Koechlin, Etienne; Baraduc, Pierre; Farrer, Chlöé

2011-02-18

Explaining or predicting the behaviour of our conspecifics requires the ability to infer the intentions that motivate it. Such inferences are assumed to rely on two types of information: (1) the sensory information conveyed by movement kinematics and (2) the observer's prior expectations--acquired from past experience or derived from prior knowledge. However, the respective contribution of these two sources of information is still controversial. This controversy stems in part from the fact that "intention" is an umbrella term that may embrace various sub-types each being assigned different scopes and targets. We hypothesized that variations in the scope and target of intentions may account for variations in the contribution of visual kinematics and prior knowledge to the intention inference process. To test this hypothesis, we conducted four behavioural experiments in which participants were instructed to identify different types of intention: basic intentions (i.e. simple goal of a motor act), superordinate intentions (i.e. general goal of a sequence of motor acts), or social intentions (i.e. intentions accomplished in a context of reciprocal interaction). For each of the above-mentioned intentions, we varied (1) the amount of visual information available from the action scene and (2) participant's prior expectations concerning the intention that was more likely to be accomplished. First, we showed that intentional judgments depend on a consistent interaction between visual information and participant's prior expectations. Moreover, we demonstrated that this interaction varied according to the type of intention to be inferred, with participant's priors rather than perceptual evidence exerting a greater effect on the inference of social and superordinate intentions. The results are discussed by appealing to the specific properties of each type of intention considered and further interpreted in the light of a hierarchical model of action representation.

Dialogical Argumentation Instruction as a Catalytic Agent for the Integration of School Science with Indigenous Knowledge Systems

ERIC Educational Resources Information Center

Diwu, Christopher T.; Ogunniyi, Meshach B.

2012-01-01

In South Africa and elsewhere, the integration of science and Indigenous Knowledge Systems (IKS) is a contentious issue. This is due to both knowledge systems being underpinned by diverse epistemic authorities. This paper explores the possibilities and challenges associated with the integration of the two knowledge corpuses and how a Dialogical…

Cone beam CT imaging with limited angle of projections and prior knowledge for volumetric verification of non-coplanar beam radiation therapy: a proof of concept study

NASA Astrophysics Data System (ADS)

Meng, Bowen; Xing, Lei; Han, Bin; Koong, Albert; Chang, Daniel; Cheng, Jason; Li, Ruijiang

2013-11-01

Non-coplanar beams are important for treatment of both cranial and noncranial tumors. Treatment verification of such beams with couch rotation/kicks, however, is challenging, particularly for the application of cone beam CT (CBCT). In this situation, only limited and unconventional imaging angles are feasible to avoid collision between the gantry, couch, patient, and on-board imaging system. The purpose of this work is to develop a CBCT verification strategy for patients undergoing non-coplanar radiation therapy. We propose an image reconstruction scheme that integrates a prior image constrained compressed sensing (PICCS) technique with image registration. Planning CT or CBCT acquired at the neutral position is rotated and translated according to the nominal couch rotation/translation to serve as the initial prior image. Here, the nominal couch movement is chosen to have a rotational error of 5° and translational error of 8 mm from the ground truth in one or more axes or directions. The proposed reconstruction scheme alternates between two major steps. First, an image is reconstructed using the PICCS technique implemented with total-variation minimization and simultaneous algebraic reconstruction. Second, the rotational/translational setup errors are corrected and the prior image is updated by applying rigid image registration between the reconstructed image and the previous prior image. The PICCS algorithm and rigid image registration are alternated iteratively until the registration results fall below a predetermined threshold. The proposed reconstruction algorithm is evaluated with an anthropomorphic digital phantom and physical head phantom. The proposed algorithm provides useful volumetric images for patient setup using projections with an angular range as small as 60°. It reduced the translational setup errors from 8 mm to generally <1 mm and the rotational setup errors from 5° to <1°. Compared with the PICCS algorithm alone, the integration of rigid registration significantly improved the reconstructed image quality, with a reduction of mostly 2-3 folds (up to 100) in root mean square image error. The proposed algorithm provides a remedy for solving the problem of non-coplanar CBCT reconstruction from limited angle of projections by combining the PICCS technique and rigid image registration in an iterative framework. In this proof of concept study, non-coplanar beams with couch rotations of 45° can be effectively verified with the CBCT technique.

Collaborative Knowledge Building with Wikis: The Impact of Redundancy and Polarity

ERIC Educational Resources Information Center

Moskaliuk, Johannes; Kimmerle, Joachim; Cress, Ulrike

2012-01-01

Wikis as shared digital artifacts may enable users to participate in processes of knowledge building. To what extent and with which quality knowledge building can take place is assumed to depend on the interrelation between people's prior knowledge and the information available in a wiki. In two experimental studies we examined the impact on…

The Effects of Prior Knowledge on Children's Memory and Suggestibility

ERIC Educational Resources Information Center

Elischberger, Holger B.

2005-01-01

In this study, 5- and 6-year-olds were read a story and asked to recall its details. Two independent factors-prestory knowledge and poststory suggestions-were crossed to examine the effects on children's story recall. The results indicated that prestory social knowledge about the story protagonist as well as academic knowledge relating to the…

Topic-Specific Pedagogical Content Knowledge (TSPCK) in Redox and Electrochemistry of Experienced Teachers

ERIC Educational Resources Information Center

O'Brien, Stephanie

2017-01-01

Topic specific pedagogical content knowledge (TSPCK) is the basis by which knowledge of subject matter of a particular topic is conveyed to students. This includes students' prior knowledge, curricular saliency, what makes a topic easy or difficult to teach, representations, and teaching strategies. The goal of this study is to assess the…

Creating Connections: Using the Internet to Support Struggling Readers' Background Knowledge. Issues in Technology

ERIC Educational Resources Information Center

Karchmer, Rachel A.

2004-01-01

Background knowledge plays an important role in one?s ability to learn. We learn new knowledge by relating it to our prior knowledge, which in turn provides concrete understanding (Piaget, 1969). Rosenblatt (1996) explained, "The reader brings to the work personality traits, memories of past events, present needs and preoccupations, a…

Interplay of Secondary Pre-Service Teacher Content Knowledge (CK), Pedagogical Content Knowledge (PCK) and Attitudes Regarding Scientific Inquiry Teaching within Teacher Training

ERIC Educational Resources Information Center

Smit, Robbert; Weitzel, Holger; Blank, Robert; Rietz, Florian; Tardent, Josiane; Robin, Nicolas

2017-01-01

Background: Beginning teachers encounter several constraints with respect to scientific inquiry. Depending on their prior beliefs, knowledge and understanding, these constraints affect their teaching of inquiry. Purpose: To investigate quantitatively the longitudinal relationship between pre-service teachers' knowledge and attitudes on scientific…

77 FR 5580 - Notice of Intent To Seek Approval To Extend an Information Collection

Federal Register 2010, 2011, 2012, 2013, 2014

2012-02-03

... Program supports innovation in the integrative conduct of research, education and knowledge transfer... disciplines, weaving together knowledge creation, knowledge integration, and knowledge transfer. STCs conduct... organizations, and/or other public/private entities. New knowledge thus created is meaningfully linked to...

Prior Conceptual Knowledge and Textbook Search.

ERIC Educational Resources Information Center

Byrnes, James P.; Guthrie, John T.

1992-01-01

The role of a subject's conceptual knowledge in the procedural task of searching a text for information was studied for 51 college undergraduates in 2 experiments involving knowledge of anatomy. Students with more anatomical information were able to search a text more quickly. Educational implications are discussed. (SLD)

How Knowledge Powers Reading

ERIC Educational Resources Information Center

Lemov, Doug

2017-01-01

Recent research shows that reading comprehension relies heavily on prior knowledge. Far more than generic "reading skills" like drawing inferences, making predictions, and knowing the function of subheads, how well students learn from a nonfiction text depends on their background knowledge of the text's subject matter. And in a cyclical…

Employees and Creativity: Social Ties and Access to Heterogeneous Knowledge

ERIC Educational Resources Information Center

Huang, Chiung-En; Liu, Chih-Hsing Sam

2015-01-01

This study dealt with employee social ties, knowledge heterogeneity contacts, and the generation of creativity. Although prior studies demonstrated a relationship between network position and creativity, inadequate attention has been paid to network ties and heterogeneity knowledge contacts. This study considered the social interaction processes…

Computer Experiences, Self-Efficacy and Knowledge of Students Enrolled in Introductory University Agriculture Courses.

ERIC Educational Resources Information Center

Johnson, Donald M.; Ferguson, James A.; Lester, Melissa L.

1999-01-01

Of 175 freshmen agriculture students, 74% had prior computer courses, 62% owned computers. The number of computer topics studied predicted both computer self-efficacy and computer knowledge. A substantial positive correlation was found between self-efficacy and computer knowledge. (SK)

Designing Computer Learning Environments for Engineering and Computer Science: The Scaffolded Knowledge Integration Framework.

ERIC Educational Resources Information Center

Linn, Marcia C.

1995-01-01

Describes a framework called scaffolded knowledge integration and illustrates how it guided the design of two successful course enhancements in the field of computer science and engineering: the LISP Knowledge Integration Environment and the spatial reasoning environment. (101 references) (Author/MKR)

Integrating pedagogical content knowledge and pedagogical/psychological knowledge in mathematics

PubMed Central

Harr, Nora; Eichler, Andreas; Renkl, Alexander

2014-01-01

In teacher education at universities, general pedagogical and psychological principles are often treated separately from subject matter knowledge and therefore run the risk of not being applied in the teaching subject. In an experimental study (N = 60 mathematics student teachers) we investigated the effects of providing aspects of general pedagogical/psychological knowledge (PPK) and pedagogical content knowledge (PCK) in an integrated or separated way. In both conditions (“integrated” vs. “separated”), participants individually worked on computer-based learning environments addressing the same topic: use and handling of multiple external representations, a central issue in mathematics. We experimentally varied whether PPK aspects and PCK aspects were treated integrated or apart from one another. As expected, the integrated condition led to greater application of pedagogical/psychological aspects and an increase in applying both knowledge types simultaneously compared to the separated condition. Overall, our findings indicate beneficial effects of an integrated design in teacher education. PMID:25191300

Semantically-based priors and nuanced knowledge core for Big Data, Social AI, and language understanding.

PubMed

Olsher, Daniel

2014-10-01

Noise-resistant and nuanced, COGBASE makes 10 million pieces of commonsense data and a host of novel reasoning algorithms available via a family of semantically-driven prior probability distributions. Machine learning, Big Data, natural language understanding/processing, and social AI can draw on COGBASE to determine lexical semantics, infer goals and interests, simulate emotion and affect, calculate document gists and topic models, and link commonsense knowledge to domain models and social, spatial, cultural, and psychological data. COGBASE is especially ideal for social Big Data, which tends to involve highly implicit contexts, cognitive artifacts, difficult-to-parse texts, and deep domain knowledge dependencies. Copyright © 2014 Elsevier Ltd. All rights reserved.

Advancing affective attributes and empowering undergraduate students--lessons learned from the Bali bombing.

PubMed

Hanson, Julie

2011-11-01

Caring as an integral component in the nursing curriculum is enjoying a resurgence in the literature of late. The argument is that nursing education has tended to overemphasise the cognitive domain and under emphasise the affective. An alternative is to use the combined effect of cognition, imagination, intuition and emotion. This is supported by the theory of transformational learning, whereby students clarify their personal and professional purpose in life and are empowered to become informed, self-efficacious practitioners and autonomous thinkers as they negotiate personal values and meaning. In order to integrate these important theoretical concepts into everyday practice, educators need practical examples and case studies that show how caring is taught. This paper continues the conversation on narrative and transformational learning pedagogies and illustrates how affective attributes are developed through a single lecture. The aim of the lecture was to sensitise students to the human impact of terrorism and violence and the effects on both health care workers and the survivors of trauma. The rationale was that by allowing students to critically reflect on their own core knowledge and skills, they could question prior perceptions of their role, resulting in a revised or new perspective of those experiences and strengthen their belief in their abilities to cope in crisis situations. This transformative approach involved the delivery of knowledge and theory underpinning disaster response, personal narratives about a critical learning event that embodied clinically relevant lessons, activities that promoted critical self-reflection to strengthen students' beliefs in their own ability to cope by converting core knowledge into action and, finally student evaluation of the lesson (see Table 1). Copyright © 2011 Elsevier Ltd. All rights reserved.

The altitudinal temperature lapse rates applied to high elevation rockfalls studies in the Western European Alps

NASA Astrophysics Data System (ADS)

Nigrelli, Guido; Fratianni, Simona; Zampollo, Arianna; Turconi, Laura; Chiarle, Marta

2018-02-01

Temperature is one of the most important aspects of mountain climates. The relationships between air temperature and rockfalls at high-elevation sites are very important to know, but are also very difficult to study. In relation to this, a reliable method to estimate air temperatures at high-elevation sites is to apply the altitudinal temperature lapse rates (ATLR). The aims of this work are to quantify the values and the variability of the hourly ATLR and to apply this to estimated temperatures at high-elevation sites for rockfalls studies. To calculate ATLR prior the rockfalls, we used data acquired from two automatic weather stations that are located at an elevation above 2500 m. The sensors/instruments of these two stations are reliable because subjected to an accurate control and calibration once for year and the raw data have passed two automatic quality controls. Our study has yielded the following main results: (i) hourly ATLR increases slightly with increasing altitude, (ii) it is possible to estimate temperature at high-elevation sites with a good level of accuracy using ATLR, and (iii) temperature plays an important role on slope failures that occur at high-elevation sites and its importance is much more evident if the values oscillate around 0 °C with an amplitude of ±5 °C during the previous time-period. For these studies, it is not enough to improve the knowledge on air temperature, but it is necessary to develop an integrated knowledge of the thermal conditions of different materials involved in these processes (rock, debris, ice, water). Moreover, this integrated knowledge must be acquired by means of sensors and acquisition chains with known metrological traceability and uncertainty of measurements.

Exploring the Associations Among Nutrition, Science, and Mathematics Knowledge for an Integrative, Food-Based Curriculum.

PubMed

Stage, Virginia C; Kolasa, Kathryn M; Díaz, Sebastián R; Duffrin, Melani W

2018-01-01

Explore associations between nutrition, science, and mathematics knowledge to provide evidence that integrating food/nutrition education in the fourth-grade curriculum may support gains in academic knowledge. Secondary analysis of a quasi-experimental study. Sample included 438 students in 34 fourth-grade classrooms across North Carolina and Ohio; mean age 10 years old; gender (I = 53.2% female; C = 51.6% female). Dependent variable = post-test-nutrition knowledge; independent variables = baseline-nutrition knowledge, and post-test science and mathematics knowledge. Analyses included descriptive statistics and multiple linear regression. The hypothesized model predicted post-nutrition knowledge (F(437) = 149.4, p < .001; Adjusted R = .51). All independent variables were significant predictors with positive association. Science and mathematics knowledge were predictive of nutrition knowledge indicating use of an integrative science and mathematics curriculum to improve academic knowledge may also simultaneously improve nutrition knowledge among fourth-grade students. Teachers can benefit from integration by meeting multiple academic standards, efficiently using limited classroom time, and increasing nutrition education provided in the classroom. © 2018, American School Health Association.

Enhancing Knowledge Integration: An Information System Capstone Project

ERIC Educational Resources Information Center

Steiger, David M.

2009-01-01

This database project focuses on learning through knowledge integration; i.e., sharing and applying specialized (database) knowledge within a group, and combining it with other business knowledge to create new knowledge. Specifically, the Tiny Tots, Inc. project described below requires students to design, build, and instantiate a database system…

Mapping out the Integration of the Components of Pedagogical Content Knowledge (PCK): Examples from High School Biology Classrooms

ERIC Educational Resources Information Center

Park, Soonhye; Chen, Ying-Chih

2012-01-01

This study explored the nature of the integration of the five components of pedagogical content knowledge (PCK): (a) Orientations toward Teaching Science, (b) Knowledge of Student Understanding, (c) Knowledge of Instructional Strategies and Representations, (d) Knowledge of Science Curriculum, and (e) Knowledge of Assessment of Science Learning.…

Sociotechnical Walkthrough: A Means for Knowledge Integration

ERIC Educational Resources Information Center

Herrmann, Thomas; Loser, Kai-Uwe; Jahnke, Isa

2007-01-01

Purpose: The purpose of this research is to show that for the successful development of socio-technical systems it is essential that various stakeholders are able to integrate their different knowledge and perspectives. A method that supports knowledge integration in the course of introduction and development of socio-technical systems is the…

Integrating Knowledge, Skills and Attitudes: Conceptualising Learning Processes towards Vocational Competence

ERIC Educational Resources Information Center

Baartman, Liesbeth K. J.; de Bruijn, Elly

2011-01-01

Current research focuses on competence development and complex professional tasks. However, "learning processes" towards the integration of knowledge, skills and attitudes largely remain a black box. This article conceptualises three integration processes, in analogy to theories on transfer. Knowledge, skills and attitudes are defined, reconciling…

Lateral orbitofrontal cortex anticipates choices and integrates prior with current information

PubMed Central

Nogueira, Ramon; Abolafia, Juan M.; Drugowitsch, Jan; Balaguer-Ballester, Emili; Sanchez-Vives, Maria V.; Moreno-Bote, Rubén

2017-01-01

Adaptive behavior requires integrating prior with current information to anticipate upcoming events. Brain structures related to this computation should bring relevant signals from the recent past into the present. Here we report that rats can integrate the most recent prior information with sensory information, thereby improving behavior on a perceptual decision-making task with outcome-dependent past trial history. We find that anticipatory signals in the orbitofrontal cortex about upcoming choice increase over time and are even present before stimulus onset. These neuronal signals also represent the stimulus and relevant second-order combinations of past state variables. The encoding of choice, stimulus and second-order past state variables resides, up to movement onset, in overlapping populations. The neuronal representation of choice before stimulus onset and its build-up once the stimulus is presented suggest that orbitofrontal cortex plays a role in transforming immediate prior and stimulus information into choices using a compact state-space representation. PMID:28337990

Do Runner Beans Really Make You Run Fast? Young Children Learning About Science-Related Food Concepts in Informal Settings

NASA Astrophysics Data System (ADS)

Cumming, Jenny

2003-08-01

Early years practitioners acknowledge that much learning takes place in a family context. Science educators, in particular, recognise the importance of children's prior knowledge, both as a foundation on which to build and as a possible source of misconceptions. However, little work has been done to discover what young children learn outside school. This study utilised parent diaries and questionnaires to elucidate the experiences of children aged four to seven which might contribute to their knowledge about the origin of food and its destiny after being eaten. The findings indicate that children learn more scientifically correct information with friends and family than teachers might realise. Awareness of children's informal knowledge can assist teachers when planning activities. As well as this, children's prior knowledge can be utilised in classroom discourse to promote understanding.

Prediction of Slot Shape and Slot Size for Improving the Performance of Microstrip Antennas Using Knowledge-Based Neural Networks.

PubMed

Khan, Taimoor; De, Asok

2014-01-01

In the last decade, artificial neural networks have become very popular techniques for computing different performance parameters of microstrip antennas. The proposed work illustrates a knowledge-based neural networks model for predicting the appropriate shape and accurate size of the slot introduced on the radiating patch for achieving desired level of resonance, gain, directivity, antenna efficiency, and radiation efficiency for dual-frequency operation. By incorporating prior knowledge in neural model, the number of required training patterns is drastically reduced. Further, the neural model incorporated with prior knowledge can be used for predicting response in extrapolation region beyond the training patterns region. For validation, a prototype is also fabricated and its performance parameters are measured. A very good agreement is attained between measured, simulated, and predicted results.

Prediction of Slot Shape and Slot Size for Improving the Performance of Microstrip Antennas Using Knowledge-Based Neural Networks

PubMed Central

De, Asok

2014-01-01

In the last decade, artificial neural networks have become very popular techniques for computing different performance parameters of microstrip antennas. The proposed work illustrates a knowledge-based neural networks model for predicting the appropriate shape and accurate size of the slot introduced on the radiating patch for achieving desired level of resonance, gain, directivity, antenna efficiency, and radiation efficiency for dual-frequency operation. By incorporating prior knowledge in neural model, the number of required training patterns is drastically reduced. Further, the neural model incorporated with prior knowledge can be used for predicting response in extrapolation region beyond the training patterns region. For validation, a prototype is also fabricated and its performance parameters are measured. A very good agreement is attained between measured, simulated, and predicted results. PMID:27382616

Tacit knowledge.

PubMed

Walker, Alexander Muir

2017-04-01

Information that is not made explicit is nonetheless embedded in most of our standard procedures. In its simplest form, embedded information may take the form of prior knowledge held by the researcher and presumed to be agreed to by consumers of the research product. More interesting are the settings in which the prior information is held unconsciously by both researcher and reader, or when the very form of an "effective procedure" incorporates its creator's (unspoken) understanding of a problem. While it may not be productive to exhaustively detail the embedded or tacit knowledge that manifests itself in creative scientific work, at least at the beginning, we may want to routinize methods for extracting and documenting the ways of thinking that make "experts" expert. We should not back away from both expecting and respecting the tacit knowledge the pervades our work and the work of others.

Preservice Agricultural Education Teachers' Experiences in and Anticipation of Content Knowledge Preparation

ERIC Educational Resources Information Center

Rice, Amber H.; Kitchel, Tracy

2015-01-01

This study explored the experiences of preservice agriculture teachers in content knowledge preparation for pedagogical content knowledge (PCK) development. The researchers employed a phenomenological approach in which six preservice teachers were interviewed the semester prior to student teaching. The researchers found there was general…

The Effects of Prior Knowledge and Instruction on Understanding Image Formation.

ERIC Educational Resources Information Center

Galili, Igal; And Others

1993-01-01

Reports a study (n=27) concerning the knowledge about image formation exhibited by students following instruction in geometrical optics in an activity-based college physics course for prospective elementary teachers. Student diagrams and verbal comments indicate their knowledge can be described as an intermediate state: a hybridization of…

Designing Knowledge Scaffolds to Support Mathematical Problem Solving

ERIC Educational Resources Information Center

Rittle-Johnson, Bethany; Koedinger, Kenneth R.

2005-01-01

We present a methodology for designing better learning environments. In Phase 1, 6th-grade students' (n = 223) prior knowledge was assessed using a difficulty factors assessment (DFA). The assessment revealed that scaffolds designed to elicit contextual, conceptual, or procedural knowledge each improved students' ability to add and subtract…

Uncovering and Informing Preservice Teachers' Prior Knowledge about Poverty

ERIC Educational Resources Information Center

Mundy, Charlotte Anne; Leko, Melinda Marie

2015-01-01

This study explored 30 preservice teachers' knowledge on issues related to poverty. In an open-ended questionnaire, preservice teachers' perceptions of poverty and how teachers should respond to students from poverty were explored. Results indicated that preservice teachers' knowledge was nonspecific and lacked focus on the relationship among…

Toward cognitive robotics

NASA Astrophysics Data System (ADS)

Laird, John E.

2009-05-01

Our long-term goal is to develop autonomous robotic systems that have the cognitive abilities of humans, including communication, coordination, adapting to novel situations, and learning through experience. Our approach rests on the recent integration of the Soar cognitive architecture with both virtual and physical robotic systems. Soar has been used to develop a wide variety of knowledge-rich agents for complex virtual environments, including distributed training environments and interactive computer games. For development and testing in robotic virtual environments, Soar interfaces to a variety of robotic simulators and a simple mobile robot. We have recently made significant extensions to Soar that add new memories and new non-symbolic reasoning to Soar's original symbolic processing, which should significantly improve Soar abilities for control of robots. These extensions include episodic memory, semantic memory, reinforcement learning, and mental imagery. Episodic memory and semantic memory support the learning and recalling of prior events and situations as well as facts about the world. Reinforcement learning provides the ability of the system to tune its procedural knowledge - knowledge about how to do things. Mental imagery supports the use of diagrammatic and visual representations that are critical to support spatial reasoning. We speculate on the future of unmanned systems and the need for cognitive robotics to support dynamic instruction and taskability.

Learning Robotics in a Science Museum Theatre Play: Investigation of Learning Outcomes, Contexts and Experiences

NASA Astrophysics Data System (ADS)

Peleg, Ran; Baram-Tsabari, Ayelet

2017-12-01

Theatre is often introduced into science museums to enhance visitor experience. While learning in museums exhibitions received considerable research attention, learning from museum theatre has not. The goal of this exploratory study was to investigate the potential educational role of a science museum theatre play. The study aimed to investigate (1) cognitive learning outcomes of the play, (2) how these outcomes interact with different viewing contexts and (3) experiential learning outcomes through the theatrical experience. The play `Robot and I', addressing principles in robotics, was commissioned by a science museum. Data consisted of 391 questionnaires and interviews with 47 children and 20 parents. Findings indicate that explicit but not implicit learning goals were decoded successfully. There was little synergy between learning outcomes of the play and an exhibition on robotics, demonstrating the effect of two different physical contexts. Interview data revealed that prior knowledge, experience and interest played a major role in children's understanding of the play. Analysis of the theatrical experience showed that despite strong identification with the child protagonist, children often doubted the protagonist's knowledge jeopardizing integration of scientific content. The study extends the empirical knowledge and theoretical thinking on museum theatre to better support claims of its virtues and respond to their criticism.

Medical education and information and communication technology.

PubMed

Houshyari, Asefeh Badiey; Bahadorani, Mahnaz; Tootoonchi, Mina; Gardiner, John Jacob Zucker; Peña, Roberto A; Adibi, Peyman

2012-01-01

Information and communication technology (ICT) has brought many changes in medical education and practice in the last couple of decades. Teaching and learning medicine particularly has gone under profound changes due to computer technologies, and medical schools around the world have invested heavily either in new computer technologies or in the process of adapting to this technological revolution. In order to catch up with the rest of the world, developing countries need to research their options in adapting to new computer technologies. This descriptive survey study was designed to assess medical students' computer and Internet skills and their attitude toward ICT. Research findings showed that the mean score of self-perceived computer knowledge for male students in general was greater than for female students. Also, students who had participated in various prior computer workshops, had access to computer, Internet, and e-mail, and frequently checked their e-mail had higher mean of self-perceived knowledge and skill score. Finally, students with positive attitude toward ICT scored their computer knowledge higher than those who had no opinion. The results have confirmed that the medical schools, particularly in developing countries, need to bring fundamental changes such as curriculum modification in order to integrate ICT into medical education, creating essential infrastructure for ICT use in medical education and practice, and structured computer training for faculty and students.

Analogical and category-based inference: a theoretical integration with Bayesian causal models.

PubMed

Holyoak, Keith J; Lee, Hee Seung; Lu, Hongjing

2010-11-01

A fundamental issue for theories of human induction is to specify constraints on potential inferences. For inferences based on shared category membership, an analogy, and/or a relational schema, it appears that the basic goal of induction is to make accurate and goal-relevant inferences that are sensitive to uncertainty. People can use source information at various levels of abstraction (including both specific instances and more general categories), coupled with prior causal knowledge, to build a causal model for a target situation, which in turn constrains inferences about the target. We propose a computational theory in the framework of Bayesian inference and test its predictions (parameter-free for the cases we consider) in a series of experiments in which people were asked to assess the probabilities of various causal predictions and attributions about a target on the basis of source knowledge about generative and preventive causes. The theory proved successful in accounting for systematic patterns of judgments about interrelated types of causal inferences, including evidence that analogical inferences are partially dissociable from overall mapping quality.

Harnessing opportunities for good governance of health impacts of mining projects in Mongolia: results of a global partnership.

PubMed

Pfeiffer, Michaela; Vanya, Delgermaa; Davison, Colleen; Lkhagvasuren, Oyunaa; Johnston, Lesley; Janes, Craig R

2017-06-27

The Sustainable Development Goals call for the effective governance of shared natural resources in ways that support inclusive growth, safeguard the integrity of the natural and physical environment, and promote health and well-being for all. For large-scale resource extraction projects -- e.g. in the mining sector -- environmental regulations and in particular environmental impact assessments (EIA) provide an important but insufficiently developed avenue to ensure that wider sustainable development issues, such as health, have been considered prior to the permitting of projects. In recognition of the opportunity provided in EIA to influence the extent to which health issues would be addressed in the design and delivery of mining projects, an international and intersectoral partnership, with the support of WHO and public funds from Canadian sources, engaged over a period of six years in a series of capacity development activities and knowledge translation/dissemination events aimed at influencing policy change in the extractives sector so as to include consideration of human health impacts. Early efforts significantly increased awareness of the need to include health considerations in EIAs. Coupling effective knowledge translation about health in EIA with the development of networks that fostered good intersectoral partnerships, this awareness supported the development and implementation of key pieces of legislation. These results show that intersectoral collaboration is essential, and must be supported by an effective conceptual understanding about which methods and models of impact assessment, particularly for health, lend themselves to integration within EIA. The results of our partnership demonstrate that when specific conditions are met, integrating health into the EIA system represents a promising avenue to ensure that mining activities contribute to wider sustainable development goals and objectives.

Applying a Data Stewardship Maturity Matrix to the NOAA Observing System Portfolio Integrated Assessment Process

NASA Astrophysics Data System (ADS)

Peng, G.; Austin, M.

2017-12-01

Identification and prioritization of targeted user community needs are not always considered until after data has been created and archived. Gaps in data curation and documentation in the data production and delivery phases limit data's broad utility specifically for decision makers. Expert understanding and knowledge of a particular dataset is often required as a part of the data and metadata curation process to establish the credibility of the data and support informed decision-making. To enhance curation practices, content from NOAA's Observing System Integrated Assessment (NOSIA) Value Tree, NOAA's Data Catalog/Digital Object Identifier (DOI) projects (collection-level metadata) have been integrated with Data/Stewardship Maturity Matrices (data and stewardship quality information) focused on assessment of user community needs. This results in user focused evidence based decision making tools created by NOAA's National Environmental Satellite, Data, and Information Service (NESDIS) through identification and assessment of data content gaps related to scientific knowledge and application to key areas of societal benefit. Through enabling user need feedback from the beginning of data creation through archive allows users to determine the quality and value of data that is fit for purpose. Data gap assessment and prioritization are presented in a user-friendly way using the data stewardship maturity matrices as measurement of data management quality. These decision maker tools encourages data producers and data providers/stewards to consider users' needs prior to data creation and dissemination resulting in user driven data requirements increasing return on investment. A use case focused on need for NOAA observations linked societal benefit will be used to demonstrate the value of these tools.

Rectification of elemental image set and extraction of lens lattice by projective image transformation in integral imaging.

PubMed

Hong, Keehoon; Hong, Jisoo; Jung, Jae-Hyun; Park, Jae-Hyeung; Lee, Byoungho

2010-05-24

We propose a new method for rectifying a geometrical distortion in the elemental image set and extracting an accurate lens lattice lines by projective image transformation. The information of distortion in the acquired elemental image set is found by Hough transform algorithm. With this initial information of distortions, the acquired elemental image set is rectified automatically without the prior knowledge on the characteristics of pickup system by stratified image transformation procedure. Computer-generated elemental image sets with distortion on purpose are used for verifying the proposed rectification method. Experimentally-captured elemental image sets are optically reconstructed before and after the rectification by the proposed method. The experimental results support the validity of the proposed method with high accuracy of image rectification and lattice extraction.

Using expert knowledge for test linking.

PubMed

Bolsinova, Maria; Hoijtink, Herbert; Vermeulen, Jorine Adinda; Béguin, Anton

2017-12-01

Linking and equating procedures are used to make the results of different test forms comparable. In the cases where no assumption of random equivalent groups can be made some form of linking design is used. In practice the amount of data available to link the two tests is often very limited due to logistic and security reasons, which affects the precision of linking procedures. This study proposes to enhance the quality of linking procedures based on sparse data by using Bayesian methods which combine the information in the linking data with background information captured in informative prior distributions. We propose two methods for the elicitation of prior knowledge about the difference in difficulty of two tests from subject-matter experts and explain how these results can be used in the specification of priors. To illustrate the proposed methods and evaluate the quality of linking with and without informative priors, an empirical example of linking primary school mathematics tests is presented. The results suggest that informative priors can increase the precision of linking without decreasing the accuracy. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

Indigenous Knowledge for Development: Opportunities and Challenges.

ERIC Educational Resources Information Center

Gorjestani, Nicolas

Indigenous knowledge is a critical factor for sustainable development. Empowerment of local communities is a prerequisite for the integration of indigenous knowledge in the development process. The integration of appropriate indigenous knowledge systems into development programs has already contributed to efficiency, effectiveness, and sustainable…

Validating Measurement of Knowledge Integration in Science Using Multiple-Choice and Explanation Items

ERIC Educational Resources Information Center

Lee, Hee-Sun; Liu, Ou Lydia; Linn, Marcia C.

2011-01-01

This study explores measurement of a construct called knowledge integration in science using multiple-choice and explanation items. We use construct and instructional validity evidence to examine the role multiple-choice and explanation items plays in measuring students' knowledge integration ability. For construct validity, we analyze item…

Integrating Individual Learning Processes and Organizational Knowledge Formation: Foundational Determinants for Organizational Performance

ERIC Educational Resources Information Center

Song, Ji Hoon; Chermack, Thomas J.; Kim, Hong Min

2008-01-01

This research examined the link between learning processes and knowledge formation through an integrated literature review from both academic and practical viewpoints. Individuals' learning processes and organizational knowledge creation were reviewed by means of theoretical and integrative analysis based on a lack of empirical research on the…