Expert knowledge maps for knowledge management: a case study in Traditional Chinese Medicine research.

PubMed

Cui, Meng; Yang, Shuo; Yu, Tong; Yang, Ce; Gao, Yonghong; Zhu, Haiyan

2013-10-01

To design a model to capture information on the state and trends of knowledge creation, at both an individual and an organizational level, in order to enhance knowledge management. We designed a graph-theoretic knowledge model, the expert knowledge map (EKM), based on literature-based annotation. A case study in the domain of Traditional Chinese Medicine research was used to illustrate the usefulness of the model. The EKM successfully captured various aspects of knowledge and enhanced knowledge management within the case-study organization through the provision of knowledge graphs, expert graphs, and expert-knowledge biography. Our model could help to reveal the hot topics, trends, and products of the research done by an organization. It can potentially be used to facilitate knowledge learning, sharing and decision-making among researchers, academicians, students, and administrators of organizations.

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

Epistemological Beliefs and Knowledge Sharing in Work Teams: A New Model and Research Questions

ERIC Educational Resources Information Center

Weinberg, Frankie J.

2015-01-01

Purpose: The purpose of this paper is to present a knowledge-sharing model that explains individual members' motivation to share knowledge (knowledge donation and knowledge collection). Design/methodology/approach: The model is based on social-constructivist theories of epistemological beliefs, learning and distributed cognition, and is organized…

Improved knowledge diffusion model based on the collaboration hypernetwork

NASA Astrophysics Data System (ADS)

Wang, Jiang-Pan; Guo, Qiang; Yang, Guang-Yong; Liu, Jian-Guo

2015-06-01

The process for absorbing knowledge becomes an essential element for innovation in firms and in adapting to changes in the competitive environment. In this paper, we present an improved knowledge diffusion hypernetwork (IKDH) model based on the idea that knowledge will spread from the target node to all its neighbors in terms of the hyperedge and knowledge stock. We apply the average knowledge stock V(t) , the variable σ2(t) , and the variance coefficient c(t) to evaluate the performance of knowledge diffusion. By analyzing different knowledge diffusion ways, selection ways of the highly knowledgeable nodes, hypernetwork sizes and hypernetwork structures for the performance of knowledge diffusion, results show that the diffusion speed of IKDH model is 3.64 times faster than that of traditional knowledge diffusion (TKDH) model. Besides, it is three times faster to diffuse knowledge by randomly selecting "expert" nodes than that by selecting large-hyperdegree nodes as "expert" nodes. Furthermore, either the closer network structure or smaller network size results in the faster knowledge diffusion.

A framework for extracting and representing project knowledge contexts using topic models and dynamic knowledge maps

NASA Astrophysics Data System (ADS)

Xu, Jin; Li, Zheng; Li, Shuliang; Zhang, Yanyan

2015-07-01

There is still a lack of effective paradigms and tools for analysing and discovering the contents and relationships of project knowledge contexts in the field of project management. In this paper, a new framework for extracting and representing project knowledge contexts using topic models and dynamic knowledge maps under big data environments is proposed and developed. The conceptual paradigm, theoretical underpinning, extended topic model, and illustration examples of the ontology model for project knowledge maps are presented, with further research work envisaged.

More than Anecdotes: Fishers' Ecological Knowledge Can Fill Gaps for Ecosystem Modeling.

PubMed

Bevilacqua, Ana Helena V; Carvalho, Adriana R; Angelini, Ronaldo; Christensen, Villy

2016-01-01

Ecosystem modeling applied to fisheries remains hampered by a lack of local information. Fishers' knowledge could fill this gap, improving participation in and the management of fisheries. The same fishing area was modeled using two approaches: based on fishers' knowledge and based on scientific information. For the former, the data was collected by interviews through the Delphi methodology, and for the latter, the data was gathered from the literature. Agreement between the attributes generated by the fishers' knowledge model and scientific model is discussed and explored, aiming to improve data availability, the ecosystem model, and fisheries management. The ecosystem attributes produced from the fishers' knowledge model were consistent with the ecosystem attributes produced by the scientific model, and elaborated using only the scientific data from literature. This study provides evidence that fishers' knowledge may suitably complement scientific data, and may improve the modeling tools for the research and management of fisheries.

University Students' Meta-Modelling Knowledge

ERIC Educational Resources Information Center

Krell, Moritz; Krüger, Dirk

2017-01-01

Background: As one part of scientific meta-knowledge, students' meta-modelling knowledge should be promoted on different educational levels such as primary school, secondary school and university. This study focuses on the assessment of university students' meta-modelling knowledge using a paper-pencil questionnaire. Purpose: The general purpose…

A Thematic Analysis of Theoretical Models for Translational Science in Nursing: Mapping the Field

PubMed Central

Mitchell, Sandra A.; Fisher, Cheryl A.; Hastings, Clare E.; Silverman, Leanne B.; Wallen, Gwenyth R.

2010-01-01

Background The quantity and diversity of conceptual models in translational science may complicate rather than advance the use of theory. Purpose This paper offers a comparative thematic analysis of the models available to inform knowledge development, transfer, and utilization. Method Literature searches identified 47 models for knowledge translation. Four thematic areas emerged: (1) evidence-based practice and knowledge transformation processes; (2) strategic change to promote adoption of new knowledge; (3) knowledge exchange and synthesis for application and inquiry; (4) designing and interpreting dissemination research. Discussion This analysis distinguishes the contributions made by leaders and researchers at each phase in the process of discovery, development, and service delivery. It also informs the selection of models to guide activities in knowledge translation. Conclusions A flexible theoretical stance is essential to simultaneously develop new knowledge and accelerate the translation of that knowledge into practice behaviors and programs of care that support optimal patient outcomes. PMID:21074646

Enabling Integrated Decision Making for Electronic-Commerce by Modelling an Enterprise's Sharable Knowledge.

ERIC Educational Resources Information Center

Kim, Henry M.

2000-01-01

An enterprise model, a computational model of knowledge about an enterprise, is a useful tool for integrated decision-making by e-commerce suppliers and customers. Sharable knowledge, once represented in an enterprise model, can be integrated by the modeled enterprise's e-commerce partners. Presents background on enterprise modeling, followed by…

An introduction to the multisystem model of knowledge integration and translation.

PubMed

Palmer, Debra; Kramlich, Debra

2011-01-01

Many nurse researchers have designed strategies to assist health care practitioners to move evidence into practice. While many have been identified as "models," most do not have a conceptual framework. They are unidirectional, complex, and difficult for novice research users to understand. These models have focused on empirical knowledge and ignored the importance of practitioners' tacit knowledge. The Communities of Practice conceptual framework allows for the integration of tacit and explicit knowledge into practice. This article describes the development of a new translation model, the Multisystem Model of Knowledge Integration and Translation, supported by the Communities of Practice conceptual framework.

Detailed clinical models: representing knowledge, data and semantics in healthcare information technology.

PubMed

Goossen, William T F

2014-07-01

This paper will present an overview of the developmental effort in harmonizing clinical knowledge modeling using the Detailed Clinical Models (DCMs), and will explain how it can contribute to the preservation of Electronic Health Records (EHR) data. Clinical knowledge modeling is vital for the management and preservation of EHR and data. Such modeling provides common data elements and terminology binding with the intention of capturing and managing clinical information over time and location independent from technology. Any EHR data exchange without an agreed clinical knowledge modeling will potentially result in loss of information. Many attempts exist from the past to model clinical knowledge for the benefits of semantic interoperability using standardized data representation and common terminologies. The objective of each project is similar with respect to consistent representation of clinical data, using standardized terminologies, and an overall logical approach. However, the conceptual, logical, and the technical expressions are quite different in one clinical knowledge modeling approach versus another. There currently are synergies under the Clinical Information Modeling Initiative (CIMI) in order to create a harmonized reference model for clinical knowledge models. The goal for the CIMI is to create a reference model and formalisms based on for instance the DCM (ISO/TS 13972), among other work. A global repository of DCMs may potentially be established in the future.

More than Anecdotes: Fishers’ Ecological Knowledge Can Fill Gaps for Ecosystem Modeling

PubMed Central

Bevilacqua, Ana Helena V.; Carvalho, Adriana R.; Angelini, Ronaldo; Christensen, Villy

2016-01-01

Background Ecosystem modeling applied to fisheries remains hampered by a lack of local information. Fishers’ knowledge could fill this gap, improving participation in and the management of fisheries. Methodology The same fishing area was modeled using two approaches: based on fishers’ knowledge and based on scientific information. For the former, the data was collected by interviews through the Delphi methodology, and for the latter, the data was gathered from the literature. Agreement between the attributes generated by the fishers’ knowledge model and scientific model is discussed and explored, aiming to improve data availability, the ecosystem model, and fisheries management. Principal Findings The ecosystem attributes produced from the fishers’ knowledge model were consistent with the ecosystem attributes produced by the scientific model, and elaborated using only the scientific data from literature. Conclusions/Significance This study provides evidence that fishers’ knowledge may suitably complement scientific data, and may improve the modeling tools for the research and management of fisheries. PMID:27196131

Knowledge and Opinion on the Nuclear Freeze: A Test of Three Models.

ERIC Educational Resources Information Center

Tankard, James W., Jr.

To explore how knowledge influences opinion in foreign policy, results of a survey on voter familiarity with and attitude toward nuclear policy issues were compared with three theoretical models of the knowledge/opinion relationship: (1) the enlightenment model--as knowledge increases, support for belligerent foreign policy stands decreases; (2)…

The Impact of Secondary School Students' Preconceptions on the Evolution of their Mental Models of the Greenhouse effect and Global Warming

NASA Astrophysics Data System (ADS)

Reinfried, Sibylle; Tempelmann, Sebastian

2014-01-01

This paper provides a video-based learning process study that investigates the kinds of mental models of the atmospheric greenhouse effect 13-year-old learners have and how these mental models change with a learning environment, which is optimised in regard to instructional psychology. The objective of this explorative study was to observe and analyse the learners' learning pathways according to their previous knowledge in detail and to understand the mental model formation processes associated with them more precisely. For the analysis of the learning pathways, drawings, texts, video and interview transcripts from 12 students were studied using qualitative methods. The learning pathways pursued by the learners significantly depend on their domain-specific previous knowledge. The learners' preconceptions could be typified based on specific characteristics, whereby three preconception types could be formed. The 'isolated pieces of knowledge' type of learners, who have very little or no previous knowledge about the greenhouse effect, build new mental models that are close to the target model. 'Reduced heat output' type of learners, who have previous knowledge that indicates compliances with central ideas of the normative model, reconstruct their knowledge by reorganising and interpreting their existing knowledge structures. 'Increasing heat input' type of learners, whose previous knowledge consists of subjective worldly knowledge, which has a greater personal explanatory value than the information from the learning environment, have more difficulties changing their mental models. They have to fundamentally reconstruct their mental models.

Knowledge management in Portuguese healthcare institutions.

PubMed

Cruz, Sofia Gaspar; Ferreira, Maria Manuela Frederico

2016-06-01

Knowledge management imposes itself as a pressing need for the organizations of several sectors of the economy, including healthcare. to evaluate the perception of healthcare institution collaborators in relation to knowledge management in the institution where they operate and analyze the existence of differences in this perception, based on the institution's management model. a study conducted in a sample consisting of 671 collaborators from 10 Portuguese healthcare institutions with different models of management. In order to assess the knowledge management perception, we used a score designed from and based on items from the scores available in the literature. the perception of moderate knowledge management on the healthcare institutions and the statistically significant differences in knowledge management perception were evidenced in each management model. management knowledge takes place in healthcare institutions, and the current management model determines the way staff at these institutions manage their knowledge.

An Ontology-Based Conceptual Model For Accumulating And Reusing Knowledge In A DMAIC Process

NASA Astrophysics Data System (ADS)

Nguyen, ThanhDat; Kifor, Claudiu Vasile

2015-09-01

DMAIC (Define, Measure, Analyze, Improve, and Control) is an important process used to enhance quality of processes basing on knowledge. However, it is difficult to access DMAIC knowledge. Conventional approaches meet a problem arising from structuring and reusing DMAIC knowledge. The main reason is that DMAIC knowledge is not represented and organized systematically. In this article, we overcome the problem basing on a conceptual model that is a combination of DMAIC process, knowledge management, and Ontology engineering. The main idea of our model is to utilizing Ontologies to represent knowledge generated by each of DMAIC phases. We build five different knowledge bases for storing all knowledge of DMAIC phases with the support of necessary tools and appropriate techniques in Information Technology area. Consequently, these knowledge bases provide knowledge available to experts, managers, and web users during or after DMAIC execution in order to share and reuse existing knowledge.

A knowledge base architecture for distributed knowledge agents

NASA Technical Reports Server (NTRS)

Riedesel, Joel; Walls, Bryan

1990-01-01

A tuple space based object oriented model for knowledge base representation and interpretation is presented. An architecture for managing distributed knowledge agents is then implemented within the model. The general model is based upon a database implementation of a tuple space. Objects are then defined as an additional layer upon the database. The tuple space may or may not be distributed depending upon the database implementation. A language for representing knowledge and inference strategy is defined whose implementation takes advantage of the tuple space. The general model may then be instantiated in many different forms, each of which may be a distinct knowledge agent. Knowledge agents may communicate using tuple space mechanisms as in the LINDA model as well as using more well known message passing mechanisms. An implementation of the model is presented describing strategies used to keep inference tractable without giving up expressivity. An example applied to a power management and distribution network for Space Station Freedom is given.

Chemistry Teachers' Knowledge and Application of Models

ERIC Educational Resources Information Center

Wang, Zuhao; Chi, Shaohui; Hu, Kaiyan; Chen, Wenting

2014-01-01

Teachers' knowledge and application of model play an important role in students' development of modeling ability and scientific literacy. In this study, we investigated Chinese chemistry teachers' knowledge and application of models. Data were collected through test questionnaire and analyzed quantitatively and qualitatively. The result indicated…

Implementing a Technology-Supported Model for Cross-Organisational Learning and Knowledge Building for Teachers

ERIC Educational Resources Information Center

Tammets, Kairit; Pata, Kai; Laanpere, Mart

2012-01-01

This study proposed using the elaborated learning and knowledge building model (LKB model) derived from Nonaka and Takeuchi's knowledge management model for supporting cross-organisational teacher development in the temporarily extended organisations composed of universities and schools. It investigated the main LKB model components in the context…

Effects of Working Memory Capacity and Domain Knowledge on Recall for Grocery Prices.

PubMed

Bermingham, Douglas; Gardner, Michael K; Woltz, Dan J

2016-01-01

Hambrick and Engle (2002) proposed 3 models of how domain knowledge and working memory capacity may work together to influence episodic memory: a "rich-get-richer" model, a "building blocks" model, and a "compensatory" model. Their results supported the rich-get-richer model, although later work by Hambrick and Oswald (2005) found support for a building blocks model. We investigated the effects of domain knowledge and working memory on recall of studied grocery prices. Working memory was measured with 3 simple span tasks. A contrast of realistic versus fictitious foods in the episodic memory task served as our manipulation of domain knowledge, because participants could not have domain knowledge of fictitious food prices. There was a strong effect for domain knowledge (realistic food-price pairs were easier to remember) and a moderate effect for working memory capacity (higher working memory capacity produced better recall). Furthermore, the interaction between domain knowledge and working memory produced a small but significant interaction in 1 measure of price recall. This supported the compensatory model and stands in contrast to previous research.

Towards Modeling False Memory With Computational Knowledge Bases.

PubMed

Li, Justin; Kohanyi, Emma

2017-01-01

One challenge to creating realistic cognitive models of memory is the inability to account for the vast common-sense knowledge of human participants. Large computational knowledge bases such as WordNet and DBpedia may offer a solution to this problem but may pose other challenges. This paper explores some of these difficulties through a semantic network spreading activation model of the Deese-Roediger-McDermott false memory task. In three experiments, we show that these knowledge bases only capture a subset of human associations, while irrelevant information introduces noise and makes efficient modeling difficult. We conclude that the contents of these knowledge bases must be augmented and, more important, that the algorithms must be refined and optimized, before large knowledge bases can be widely used for cognitive modeling. Copyright © 2016 Cognitive Science Society, Inc.

The Knowledge Development Model: Responding to the Changing Landscape of Learning in Virtual Environments

ERIC Educational Resources Information Center

Adams, Nan B.

2017-01-01

Society's relationship to knowledge and what is considered to be factual is changing. Effective teaching models focused on leveraging strategic control of the knowledge from teachers to learners in virtual learning environments are critical to insuring a positive path is charted. The Knowledge Development Model serves as the guide for determining…

Problem-Oriented Corporate Knowledge Base Models on the Case-Based Reasoning Approach Basis

NASA Astrophysics Data System (ADS)

Gluhih, I. N.; Akhmadulin, R. K.

2017-07-01

One of the urgent directions of efficiency enhancement of production processes and enterprises activities management is creation and use of corporate knowledge bases. The article suggests a concept of problem-oriented corporate knowledge bases (PO CKB), in which knowledge is arranged around possible problem situations and represents a tool for making and implementing decisions in such situations. For knowledge representation in PO CKB a case-based reasoning approach is encouraged to use. Under this approach, the content of a case as a knowledge base component has been defined; based on the situation tree a PO CKB knowledge model has been developed, in which the knowledge about typical situations as well as specific examples of situations and solutions have been represented. A generalized problem-oriented corporate knowledge base structural chart and possible modes of its operation have been suggested. The obtained models allow creating and using corporate knowledge bases for support of decision making and implementing, training, staff skill upgrading and analysis of the decisions taken. The universal interpretation of terms “situation” and “solution” adopted in the work allows using the suggested models to develop problem-oriented corporate knowledge bases in different subject domains. It has been suggested to use the developed models for making corporate knowledge bases of the enterprises that operate engineer systems and networks at large production facilities.

CmapTools: A Software Environment for Knowledge Modeling and Sharing

NASA Technical Reports Server (NTRS)

Canas, Alberto J.

2004-01-01

In an ongoing collaborative effort between a group of NASA Ames scientists and researchers at the Institute for Human and Machine Cognition (IHMC) of the University of West Florida, a new version of CmapTools has been developed that enable scientists to construct knowledge models of their domain of expertise, share them with other scientists, make them available to anybody on the Internet with access to a Web browser, and peer-review other scientists models. These software tools have been successfully used at NASA to build a large-scale multimedia on Mars and in knowledge model on Habitability Assessment. The new version of the software places emphasis on greater usability for experts constructing their own knowledge models, and support for the creation of large knowledge models with large number of supporting resources in the forms of images, videos, web pages, and other media. Additionally, the software currently allows scientists to cooperate with each other in the construction, sharing and criticizing of knowledge models. Scientists collaborating from remote distances, for example researchers at the Astrobiology Institute, can concurrently manipulate the knowledge models they are viewing without having to do this at a special videoconferencing facility.

A Neural Network Model to Learn Multiple Tasks under Dynamic Environments

NASA Astrophysics Data System (ADS)

Tsumori, Kenji; Ozawa, Seiichi

When environments are dynamically changed for agents, the knowledge acquired in an environment might be useless in future. In such dynamic environments, agents should be able to not only acquire new knowledge but also modify old knowledge in learning. However, modifying all knowledge acquired before is not efficient because the knowledge once acquired may be useful again when similar environment reappears and some knowledge can be shared among different environments. To learn efficiently in such environments, we propose a neural network model that consists of the following modules: resource allocating network, long-term & short-term memory, and environment change detector. We evaluate the model under a class of dynamic environments where multiple function approximation tasks are sequentially given. The experimental results demonstrate that the proposed model possesses stable incremental learning, accurate environmental change detection, proper association and recall of old knowledge, and efficient knowledge transfer.

Mental Models: Knowledge in the Head and Knowledge in the World.

ERIC Educational Resources Information Center

Jonassen, David H.; Henning, Philip

1999-01-01

Explores the utility of mental models as learning outcomes in using complex and situated learning environments. Describes two studies: one aimed at eliciting mental models in the heads of novice refrigeration technicians, and the other an ethnographic study eliciting knowledge and models within the community of experienced refrigeration…

Factors influencing physicians' knowledge sharing on web medical forums.

PubMed

Lin, Tung Cheng; Lai, Ming Cheng; Yang, Shu Wen

2016-09-01

Web medical forums are relatively unique as knowledge-sharing platforms because physicians participate exclusively as knowledge contributors and not as knowledge recipients. Using the perspective of social exchange theory and considering both extrinsic and intrinsic motivations, this study aims to elicit the factors that significantly influence the willingness of physicians to share professional knowledge on web medical forums and develops a research model to explore the motivations that underlie physicians' knowledge-sharing attitudes. This model hypothesizes that constructs, including shared vision, reputation, altruism, and self-efficacy, positively influence these attitudes and, by extension, positively impact knowledge-sharing intention. A conventional sampling method and the direct recruitment of physicians at their outpatient clinic gathered valid data from a total of 164 physicians for analysis in the model. The empirical results support the validity of the proposed model and identified shared vision as the most significant factor of influence on knowledge-sharing attitudes, followed in descending order by knowledge-sharing self-efficacy, reputation, and altruism. © The Author(s) 2015.

A New Perspective on Modeling Groundwater-Driven Health Risk With Subjective Information

NASA Astrophysics Data System (ADS)

Ozbek, M. M.

2003-12-01

Fuzzy rule-based systems provide an efficient environment for the modeling of expert information in the context of risk management for groundwater contamination problems. In general, their use in the form of conditional pieces of knowledge, has been either as a tool for synthesizing control laws from data (i.e., conjunction-based models), or in a knowledge representation and reasoning perspective in Artificial Intelligence (i.e., implication-based models), where only the latter may lead to coherence problems (e.g., input data that leads to logical inconsistency when added to the knowledge base). We implement a two-fold extension to an implication-based groundwater risk model (Ozbek and Pinder, 2002) including: 1) the implementation of sufficient conditions for a coherent knowledge base, and 2) the interpolation of expert statements to supplement gaps in knowledge. The original model assumes statements of public health professionals for the characterization of the exposed individual and the relation of dose and pattern of exposure to its carcinogenic effects. We demonstrate the utility of the extended model in that it: 1)identifies inconsistent statements and establishes coherence in the knowledge base, and 2) minimizes the burden of knowledge elicitation from the experts for utilizing existing knowledge in an optimal fashion.ÿÿ

Online Knowledge-Based Model for Big Data Topic Extraction.

PubMed

Khan, Muhammad Taimoor; Durrani, Mehr; Khalid, Shehzad; Aziz, Furqan

2016-01-01

Lifelong machine learning (LML) models learn with experience maintaining a knowledge-base, without user intervention. Unlike traditional single-domain models they can easily scale up to explore big data. The existing LML models have high data dependency, consume more resources, and do not support streaming data. This paper proposes online LML model (OAMC) to support streaming data with reduced data dependency. With engineering the knowledge-base and introducing new knowledge features the learning pattern of the model is improved for data arriving in pieces. OAMC improves accuracy as topic coherence by 7% for streaming data while reducing the processing cost to half.

How much expert knowledge is it worth to put in conceptual hydrological models?

NASA Astrophysics Data System (ADS)

Antonetti, Manuel; Zappa, Massimiliano

2017-04-01

Both modellers and experimentalists agree on using expert knowledge to improve our conceptual hydrological simulations on ungauged basins. However, they use expert knowledge differently for both hydrologically mapping the landscape and parameterising a given hydrological model. Modellers use generally very simplified (e.g. topography-based) mapping approaches and put most of the knowledge for constraining the model by defining parameter and process relational rules. In contrast, experimentalists tend to invest all their detailed and qualitative knowledge about processes to obtain a spatial distribution of areas with different dominant runoff generation processes (DRPs) as realistic as possible, and for defining plausible narrow value ranges for each model parameter. Since, most of the times, the modelling goal is exclusively to simulate runoff at a specific site, even strongly simplified hydrological classifications can lead to satisfying results due to equifinality of hydrological models, overfitting problems and the numerous uncertainty sources affecting runoff simulations. Therefore, to test to which extent expert knowledge can improve simulation results under uncertainty, we applied a typical modellers' modelling framework relying on parameter and process constraints defined based on expert knowledge to several catchments on the Swiss Plateau. To map the spatial distribution of the DRPs, mapping approaches with increasing involvement of expert knowledge were used. Simulation results highlighted the potential added value of using all the expert knowledge available on a catchment. Also, combinations of event types and landscapes, where even a simplified mapping approach can lead to satisfying results, were identified. Finally, the uncertainty originated by the different mapping approaches was compared with the one linked to meteorological input data and catchment initial conditions.

Developing a framework for transferring knowledge into action: a thematic analysis of the literature

PubMed Central

Ward, Vicky; House, Allan; Hamer, Susan

2010-01-01

Objectives Although there is widespread agreement about the importance of transferring knowledge into action, we still lack high quality information about what works, in which settings and with whom. Whilst there are a large number of models and theories for knowledge transfer interventions, they are untested meaning that their applicability and relevance is largely unknown. This paper describes the development of a conceptual framework of translating knowledge into action and discusses how it can be used for developing a useful model of the knowledge transfer process. Methods A narrative review of the knowledge transfer literature identified 28 different models which explained all or part of the knowledge transfer process. The models were subjected to a thematic analysis to identify individual components and the types of processes used when transferring knowledge into action. The results were used to build a conceptual framework of the process. Results Five common components of the knowledge transfer process were identified: problem identification and communication; knowledge/research development and selection; analysis of context; knowledge transfer activities or interventions; and knowledge/research utilization. We also identified three types of knowledge transfer processes: a linear process; a cyclical process; and a dynamic multidirectional process. From these results a conceptual framework of knowledge transfer was developed. The framework illustrates the five common components of the knowledge transfer process and shows that they are connected via a complex, multidirectional set of interactions. As such the framework allows for the individual components to occur simultaneously or in any given order and to occur more than once during the knowledge transfer process. Conclusion Our framework provides a foundation for gathering evidence from case studies of knowledge transfer interventions. We propose that future empirical work is designed to test and refine the relevant importance and applicability of each of the components in order to build more useful models of knowledge transfer which can serve as a practical checklist for planning or evaluating knowledge transfer activities. PMID:19541874

A network model of knowledge accumulation through diffusion and upgrade

NASA Astrophysics Data System (ADS)

Zhuang, Enyu; Chen, Guanrong; Feng, Gang

2011-07-01

In this paper, we introduce a model to describe knowledge accumulation through knowledge diffusion and knowledge upgrade in a multi-agent network. Here, knowledge diffusion refers to the distribution of existing knowledge in the network, while knowledge upgrade means the discovery of new knowledge. It is found that the population of the network and the number of each agent’s neighbors affect the speed of knowledge accumulation. Four different policies for updating the neighboring agents are thus proposed, and their influence on the speed of knowledge accumulation and the topology evolution of the network are also studied.

Sticky knowledge: A possible model for investigating implementation in healthcare contexts

PubMed Central

Elwyn, Glyn; Taubert, Mark; Kowalczuk, Jenny

2007-01-01

Background In health care, a well recognized gap exists between what we know should be done based on accumulated evidence and what we actually do in practice. A body of empirical literature shows organizations, like individuals, are difficult to change. In the business literature, knowledge management and transfer has become an established area of theory and practice, whilst in healthcare it is only starting to establish a firm footing. Knowledge has become a business resource, and knowledge management theorists and practitioners have examined how knowledge moves in organisations, how it is shared, and how the return on knowledge capital can be maximised to create competitive advantage. New models are being considered, and we wanted to explore the applicability of one of these conceptual models to the implementation of evidence-based practice in healthcare systems. Methods The application of a conceptual model called sticky knowledge, based on an integration of communication theory and knowledge transfer milestones, into a scenario of attempting knowledge transfer in primary care. Results We describe Szulanski's model, the empirical work he conducted, and illustrate its potential applicability with a hypothetical healthcare example based on improving palliative care services. We follow a doctor through two different posts and analyse aspects of knowledge transfer in different primary care settings. The factors included in the sticky knowledge model include: causal ambiguity, unproven knowledge, motivation of source, credibility of source, recipient motivation, recipient absorptive capacity, recipient retentive capacity, barren organisational context, and arduous relationship between source and recipient. We found that we could apply all these factors to the difficulty of implementing new knowledge into practice in primary care settings. Discussion Szulanski argues that knowledge factors play a greater role in the success or failure of a knowledge transfer than has been suspected, and we consider that this conjecture requires further empirical work in healthcare settings. PMID:18096040

An object-relational model for structured representation of medical knowledge.

PubMed

Koch, S; Risch, T; Schneider, W; Wagner, I V

2006-07-01

Domain specific knowledge is often not static but continuously evolving. This is especially true for the medical domain. Furthermore, the lack of standardized structures for presenting knowledge makes it difficult or often impossible to assess new knowledge in the context of existing knowledge. Possibilities to compare knowledge easily and directly are often not given. It is therefore of utmost importance to create a model that allows for comparability, consistency and quality assurance of medical knowledge in specific work situations. For this purpose, we have designed on object-relational model based on structured knowledge elements that are dynamically reusable by different multi-media-based tools for case-based documentation, disease course simulation, and decision support. With this model, high-level components, such as patient case reports or simulations of the course of a disease, and low-level components (e.g., diagnoses, symptoms or treatments) as well as the relationships between these components are modeled. The resulting schema has been implemented in AMOS II, on object-relational multi-database system supporting different views with regard to search and analysis depending on different work situations.

How Structure Shapes Dynamics: Knowledge Development in Wikipedia - A Network Multilevel Modeling Approach

PubMed Central

Halatchliyski, Iassen; Cress, Ulrike

2014-01-01

Using a longitudinal network analysis approach, we investigate the structural development of the knowledge base of Wikipedia in order to explain the appearance of new knowledge. The data consists of the articles in two adjacent knowledge domains: psychology and education. We analyze the development of networks of knowledge consisting of interlinked articles at seven snapshots from 2006 to 2012 with an interval of one year between them. Longitudinal data on the topological position of each article in the networks is used to model the appearance of new knowledge over time. Thus, the structural dimension of knowledge is related to its dynamics. Using multilevel modeling as well as eigenvector and betweenness measures, we explain the significance of pivotal articles that are either central within one of the knowledge domains or boundary-crossing between the two domains at a given point in time for the future development of new knowledge in the knowledge base. PMID:25365319

A Model of the Temporal Dynamics of Knowledge Brokerage in Sustainable Development

ERIC Educational Resources Information Center

Hukkinen, Janne I.

2016-01-01

I develop a conceptual model of the temporal dynamics of knowledge brokerage for sustainable development. Brokerage refers to efforts to make research and policymaking more accessible to each other. The model enables unbiased and systematic consideration of knowledge brokerage as part of policy evolution. The model is theoretically grounded in…

Knowledge modeling of coal mining equipments based on ontology

NASA Astrophysics Data System (ADS)

Zhang, Baolong; Wang, Xiangqian; Li, Huizong; Jiang, Miaomiao

2017-06-01

The problems of information redundancy and sharing are universe in coal mining equipment management. In order to improve the using efficiency of knowledge of coal mining equipments, this paper proposed a new method of knowledge modeling based on ontology. On the basis of analyzing the structures and internal relations of coal mining equipment knowledge, taking OWL as ontology construct language, the ontology model of coal mining equipment knowledge is built with the help of Protégé 4.3 software tools. The knowledge description method will lay the foundation for the high effective knowledge management and sharing, which is very significant for improving the production management level of coal mining enterprises.

The MIKS (Member Integrated Knowledge System) Model: A Visualization of the Individual Organizational Member's Role When a Knowledge Management System Is Utilized in the Learning Organization

ERIC Educational Resources Information Center

Grobmeier, Cynthia

2007-01-01

Relating knowledge management (KM) case studies in various organizational contexts to existing theoretical constructs of learning organizations, a new model, the MIKS (Member Integrated Knowledge System) Model is proposed to include the role of the individual in the process. Their degree of motivation as well as communication and learning…

Knowledge Growth: Applied Models of General and Individual Knowledge Evolution

ERIC Educational Resources Information Center

Silkina, Galina Iu.; Bakanova, Svetlana A.

2016-01-01

The article considers the mathematical models of the growth and accumulation of scientific and applied knowledge since it is seen as the main potential and key competence of modern companies. The problem is examined on two levels--the growth and evolution of objective knowledge and knowledge evolution of a particular individual. Both processes are…

A Theory of the Measurement of Knowledge Content, Access, and Learning.

ERIC Educational Resources Information Center

Pirolli, Peter; Wilson, Mark

1998-01-01

An approach to the measurement of knowledge content, knowledge access, and knowledge learning is developed. First a theoretical view of cognition is described, and then a class of measurement models, based on Rasch modeling, is presented. Knowledge access and content are viewed as determining the observable actions selected by an agent to achieve…

Applying knowledge compilation techniques to model-based reasoning

NASA Technical Reports Server (NTRS)

Keller, Richard M.

1991-01-01

Researchers in the area of knowledge compilation are developing general purpose techniques for improving the efficiency of knowledge-based systems. In this article, an attempt is made to define knowledge compilation, to characterize several classes of knowledge compilation techniques, and to illustrate how some of these techniques can be applied to improve the performance of model-based reasoning systems.

[Study on HIV prevention related knowledge-motivation-psychological model in men who have sex with men, based on a structural equation model].

PubMed

Jiang, Y; Dou, Y L; Cai, A J; Zhang, Z; Tian, T; Dai, J H; Huang, A L

2016-02-01

Knowledge-motivation-psychological model was set up and tested through structural equation model to provide evidence on HIV prevention related strategy in Men who have Sex with Men (MSM). Snowball sampling method was used to recruit a total of 550 MSM volunteers from two MSM Non-Governmental Organizations in Urumqi, Xinjiang province. HIV prevention related information on MSM was collected through a questionnaire survey. A total of 477 volunteers showed with complete information. HIV prevention related Knowledge-motivation-psychological model was built under related experience and literature. Relations between knowledge, motivation and psychological was studied, using a ' structural equation model' with data from the fitting questionnaires and modification of the model. Structural equation model presented good fitting results. After revising the fitting index: RMSEA was 0.035, NFI was 0.965 and RFI was 0.920. Thereafter the exogenous latent variables would include knowledge, motivation and psychological effects. The endogenous latent variable appeared as prevention related behaviors. The standardized total effects of motivation, knowledge, psychological on prevention behavior were 0.44, 0.41 and 0.17 respectively. Correlation coefficient of motivation and psychological effects was 0.16. Correlation coefficient on knowledge and psychological effects was -0.17 (P<0.05). Correlation coefficient of knowledge and motivation did not show statistical significance. Knowledge of HIV and motivation of HIV prevention did not show any accordance in MSM population. It was necessary to increase the awareness and to improve the motivation of HIV prevention in MSM population.

Online Knowledge-Based Model for Big Data Topic Extraction

PubMed Central

Khan, Muhammad Taimoor; Durrani, Mehr; Khalid, Shehzad; Aziz, Furqan

2016-01-01

Lifelong machine learning (LML) models learn with experience maintaining a knowledge-base, without user intervention. Unlike traditional single-domain models they can easily scale up to explore big data. The existing LML models have high data dependency, consume more resources, and do not support streaming data. This paper proposes online LML model (OAMC) to support streaming data with reduced data dependency. With engineering the knowledge-base and introducing new knowledge features the learning pattern of the model is improved for data arriving in pieces. OAMC improves accuracy as topic coherence by 7% for streaming data while reducing the processing cost to half. PMID:27195004

Knowledge management systems success in healthcare: Leadership matters.

PubMed

Ali, Nor'ashikin; Tretiakov, Alexei; Whiddett, Dick; Hunter, Inga

2017-01-01

To deliver high-quality healthcare doctors need to access, interpret, and share appropriate and localised medical knowledge. Information technology is widely used to facilitate the management of this knowledge in healthcare organisations. The purpose of this study is to develop a knowledge management systems success model for healthcare organisations. A model was formulated by extending an existing generic knowledge management systems success model by including organisational and system factors relevant to healthcare. It was tested by using data obtained from 263 doctors working within two district health boards in New Zealand. Of the system factors, knowledge content quality was found to be particularly important for knowledge management systems success. Of the organisational factors, leadership was the most important, and more important than incentives. Leadership promoted knowledge management systems success primarily by positively affecting knowledge content quality. Leadership also promoted knowledge management use for retrieval, which should lead to the use of that better quality knowledge by the doctors, ultimately resulting in better outcomes for patients. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Measuring the ROI on Knowledge Management Systems.

ERIC Educational Resources Information Center

Wickhorst, Vickie

2002-01-01

Defines knowledge management and corporate portals and provides a model that can be applied to assessing return on investment (ROI) for a knowledge management solution. Highlights include leveraging knowledge in an organization; assessing the value of human capital; and the Intellectual Capital Performance Measurement Model. (LRW)

Formalizing nursing knowledge: from theories and models to ontologies.

PubMed

Peace, Jane; Brennan, Patricia Flatley

2009-01-01

Knowledge representation in nursing is poised to address the depth of nursing knowledge about the specific phenomena of importance to nursing. Nursing theories and models may provide a starting point for making this knowledge explicit in representations. We combined knowledge building methods from nursing and ontology design methods from biomedical informatics to create a nursing representation of family health history. Our experience provides an example of how knowledge representations may be created to facilitate electronic support for nursing practice and knowledge development.

The Augmented Cognitive Mediation Model: Examining Antecedents of Factual and Structural Breast Cancer Knowledge Among Singaporean Women.

PubMed

Lee, Edmund W J; Shin, Mincheol; Kawaja, Ariffin; Ho, Shirley S

2016-05-01

As knowledge acquisition is an important component of health communication research, this study examines factors associated with Singaporean women's breast cancer knowledge using an augmented cognitive mediation model. We conducted a nationally representative study that surveyed 802 women between the ages of 30 and 70 using random-digit dialing. The results supported the augmented cognitive mediation model, which proposes the inclusion of risk perception as a motivator of health information seeking and structural knowledge as an additional knowledge dimension. There was adequate support for the hypothesized paths in the model. Risk perception was positively associated with attention to newspaper, television, Internet, and interpersonal communication. Attention to the three media channels was associated with interpersonal communication, but only newspaper and television attention were associated with elaboration. Interpersonal communication was positively associated with structural knowledge, whereas elaboration was associated with both factual and structural knowledge. Differential indirect effects between media attention and knowledge dimensions via interpersonal communication and elaboration were found. Theoretical and practical implications are discussed.

Did you have an impact? A theory-based method for planning and evaluating knowledge-transfer and exchange activities in occupational health and safety.

PubMed

Kramer, Desré M; Wells, Richard P; Carlan, Nicolette; Aversa, Theresa; Bigelow, Philip P; Dixon, Shane M; McMillan, Keith

2013-01-01

Few evaluation tools are available to assess knowledge-transfer and exchange interventions. The objective of this paper is to develop and demonstrate a theory-based knowledge-transfer and exchange method of evaluation (KEME) that synthesizes 3 theoretical frameworks: the promoting action on research implementation of health services (PARiHS) model, the transtheoretical model of change, and a model of knowledge use. It proposes a new term, keme, to mean a unit of evidence-based transferable knowledge. The usefulness of the evaluation method is demonstrated with 4 occupational health and safety knowledge transfer and exchange (KTE) implementation case studies that are based upon the analysis of over 50 pre-existing interviews. The usefulness of the evaluation model has enabled us to better understand stakeholder feedback, frame our interpretation, and perform a more comprehensive evaluation of the knowledge use outcomes of our KTE efforts.

Capturing Knowledge In Order To Optimize The Cutting Process For Polyethylene Pipes Using Knowledge Models

NASA Astrophysics Data System (ADS)

Rotaru, Ionela Magdalena

2015-09-01

Knowledge management is a powerful instrument. Areas where knowledge - based modelling can be applied are different from business, industry, government to education area. Companies engage in efforts to restructure the database held based on knowledge management principles as they recognize in it a guarantee of models characterized by the fact that they consist only from relevant and sustainable knowledge that can bring value to the companies. The proposed paper presents a theoretical model of what it means optimizing polyethylene pipes, thus bringing to attention two important engineering fields, the one of the metal cutting process and gas industry, who meet in order to optimize the butt fusion welding process - the polyethylene cutting part - of the polyethylene pipes. All approach is shaped on the principles of knowledge management. The study was made in collaboration with companies operating in the field.

Learning Gene Expression Through Modelling and Argumentation. A Case Study Exploring the Connections Between the Worlds of Knowledge

NASA Astrophysics Data System (ADS)

Puig, Blanca; Ageitos, Noa; Jiménez-Aleixandre, María Pilar

2017-12-01

There is emerging interest on the interactions between modelling and argumentation in specific contexts, such as genetics learning. It has been suggested that modelling might help students understand and argue on genetics. We propose modelling gene expression as a way to learn molecular genetics and diseases with a genetic component. The study is framed in Tiberghien's (2000) two worlds of knowledge, the world of "theories & models" and the world of "objects & events", adding a third component, the world of representations. We seek to examine how modelling and argumentation interact and connect the three worlds of knowledge while modelling gene expression. It is a case study of 10th graders learning about diseases with a genetic component. The research questions are as follows: (1) What argumentative and modelling operations do students enact in the process of modelling gene expression? Specifically, which operations allow connecting the three worlds of knowledge? (2) What are the interactions between modelling and argumentation in modelling gene expression? To what extent do these interactions help students connect the three worlds of knowledge and modelling gene expression? The argumentative operation of using evidence helps students to relate the three worlds of knowledge, enacted in all the connections. It seems to be a relationship among the number of interactions between modelling and argumentation, the connections between world of knowledge and students' capacity to develop a more sophisticated representation. Despite this is a case study, this approach of analysis reveals potentialities for a deeper understanding of learning genetics though scientific practices.

Evolution of Mathematics Teachers' Pedagogical Knowledge When They Are Teaching through Modeling

ERIC Educational Resources Information Center

Aydogan Yenmez, Arzu; Erbas, Ayhan Kursat; Alacaci, Cengiz; Cakiroglu, Erdinc; Cetinkaya, Bulent

2017-01-01

Use of mathematical modeling in mathematics education has been receiving significant attention as a way to develop students' mathematical knowledge and skills. As effective use of modeling in classes depends on the competencies of teachers we need to know more about the nature of teachers' knowledge to use modeling in mathematics education and how…

High School Students' Meta-Modeling Knowledge

ERIC Educational Resources Information Center

Fortus, David; Shwartz, Yael; Rosenfeld, Sherman

2016-01-01

Modeling is a core scientific practice. This study probed the meta-modeling knowledge (MMK) of high school students who study science but had not had any explicit prior exposure to modeling as part of their formal schooling. Our goals were to (A) evaluate the degree to which MMK is dependent on content knowledge and (B) assess whether the upper…

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

Knowledge into action - supporting the implementation of evidence into practice in Scotland.

PubMed

Davies, Sandra; Herbert, Paul; Wales, Ann; Ritchie, Karen; Wilson, Suzanne; Dobie, Laura; Thain, Annette

2017-03-01

The knowledge into action model for NHS Scotland provides a framework for librarians and health care staff to support getting evidence into practice. Central to this model is the development of a network of knowledge brokers to facilitate identification, use, creation and sharing of knowledge. To translate the concepts described in the model into tangible activities with the intention of supporting better use of evidence in health care and subsequently improving patient outcomes. Four areas of activity were addressed by small working groups comprising knowledge services staff in local and national boards. The areas of activity were as follows: defining existing and required capabilities and developing learning opportunities for the knowledge broker network; establishing national search and summarising services; developing actionable knowledge tools; and supporting person-to-person knowledge sharing. This work presents the development of practical tools and support to translate a conceptual model for getting knowledge into action into a series of activities and outputs to support better use of evidence in health care and subsequently improved patient outcomes. © 2017 Health Libraries Group.

Promoting Knowledge Creation Discourse in an Asian Primary Five Classroom: Results from an inquiry into life cycles

NASA Astrophysics Data System (ADS)

van Aalst, Jan; Sioux Truong, Mya

2011-03-01

The phrase 'knowledge creation' refers to the practices by which a community advances its collective knowledge. Experience with a model of knowledge creation could help students to learn about the nature of science. This research examined how much progress a teacher and 16 Primary Five (Grade 4) students in the International Baccalaureate Primary Years Programme could make towards the discourse needed for Bereiter and Scardamalia's model of knowledge creation. The study consisted of two phases: a five-month period focusing on the development of the classroom ethos and skills needed for this model (Phase 1), followed by a two-month inquiry into life cycles (Phase 2). In Phase 1, we examined the classroom practices that are thought to support knowledge creation and the early experiences of the students with a web-based inquiry environment, Knowledge Forum®. In Phase 2, we conducted a summative evaluation of the students' work in Knowledge Forum in the light of the model. The data sources included classroom video recordings, artefacts of the in-class work, the Knowledge Forum database, a science content test, questionnaires, and interviews. The findings indicate that the students made substantial progress towards the knowledge creation discourse, particularly regarding the social structure of this kind of discourse and, to a lesser extent, its idea-centred nature. They also made acceptable advances in scientific knowledge and appeared to enjoy this way of learning. The study provides one of the first accounts in the literature of how a teacher new to the knowledge creation model enacted it in an Asian primary classroom.

Reducing the Knowledge Tracing Space

ERIC Educational Resources Information Center

Ritter, Steven; Harris, Thomas K.; Nixon, Tristan; Dickison, Daniel; Murray, R. Charles; Towle, Brendon

2009-01-01

In Cognitive Tutors, student skill is represented by estimates of student knowledge on various knowledge components. The estimate for each knowledge component is based on a four-parameter model developed by Corbett and Anderson [Nb]. In this paper, we investigate the nature of the parameter space defined by these four parameters by modeling data…

Knowledge Acquisition in Observational Astronomy.

ERIC Educational Resources Information Center

Vosniadou, Stella

This paper presents findings from research on knowledge acquisition in observational astronomy to demonstrate the kinds of intuitive models children form and to show how these models influence the acquisition of science knowledge. Sixty children of approximate ages 6, 9, and 12 were given a questionnaire to investigate their knowledge of the size,…

Assessing Knowledge of Mathematical Equivalence: A Construct-Modeling Approach

ERIC Educational Resources Information Center

Rittle-Johnson, Bethany; Matthews, Percival G.; Taylor, Roger S.; McEldoon, Katherine L.

2011-01-01

Knowledge of mathematical equivalence, the principle that 2 sides of an equation represent the same value, is a foundational concept in algebra, and this knowledge develops throughout elementary and middle school. Using a construct-modeling approach, we developed an assessment of equivalence knowledge. Second through sixth graders (N = 175)…

Developmental Relations Between Vocabulary Knowledge and Reading Comprehension: A Latent Change Score Modeling Study

PubMed Central

Quinn, Jamie M.; Wagner, Richard K.; Petscher, Yaacov; Lopez, Danielle

2014-01-01

The present study followed a sample of first grade students (N = 316, mean age = 7.05 at first test) through fourth grade to evaluate dynamic developmental relations between vocabulary knowledge and reading comprehension. Using latent change score modeling, competing models were fit to the repeated measurements of vocabulary knowledge and reading comprehension to test for the presence of leading and lagging influences. Univariate models indicated growth in vocabulary knowledge and reading comprehension was determined by two parts: constant yearly change and change proportional to the previous level of the variable. Bivariate models indicated previous levels of vocabulary knowledge acted as leading indicators of reading comprehension growth, but the reverse relation was not found. Implications for theories of developmental relations between vocabulary and reading comprehension are discussed. PMID:25201552

A Knowledge-Modeling Approach to Integrate Multiple Clinical Practice Guidelines to Provide Evidence-Based Clinical Decision Support for Managing Comorbid Conditions.

PubMed

Abidi, Samina

2017-10-26

Clinical management of comorbidities is a challenge, especially in a clinical decision support setting, as it requires the safe and efficient reconciliation of multiple disease-specific clinical procedures to formulate a comorbid therapeutic plan that is both effective and safe for the patient. In this paper we pursue the integration of multiple disease-specific Clinical Practice Guidelines (CPG) in order to manage co-morbidities within a computerized Clinical Decision Support System (CDSS). We present a CPG integration framework-termed as COMET (Comorbidity Ontological Modeling & ExecuTion) that manifests a knowledge management approach to model, computerize and integrate multiple CPG to yield a comorbid CPG knowledge model that upon execution can provide evidence-based recommendations for handling comorbid patients. COMET exploits semantic web technologies to achieve (a) CPG knowledge synthesis to translate a paper-based CPG to disease-specific clinical pathways (CP) that include specialized co-morbidity management procedures based on input from domain experts; (b) CPG knowledge modeling to computerize the disease-specific CP using a Comorbidity CPG ontology; (c) CPG knowledge integration by aligning multiple ontologically-modeled CP to develop a unified comorbid CPG knowledge model; and (e) CPG knowledge execution using reasoning engines to derive CPG-mediated recommendations for managing patients with comorbidities. We present a web-accessible COMET CDSS that provides family physicians with CPG-mediated comorbidity decision support to manage Atrial Fibrillation and Chronic Heart Failure. We present our qualitative and quantitative analysis of the knowledge content and usability of COMET CDSS.

Self organising hypothesis networks: a new approach for representing and structuring SAR knowledge

PubMed Central

2014-01-01

Background Combining different sources of knowledge to build improved structure activity relationship models is not easy owing to the variety of knowledge formats and the absence of a common framework to interoperate between learning techniques. Most of the current approaches address this problem by using consensus models that operate at the prediction level. We explore the possibility to directly combine these sources at the knowledge level, with the aim to harvest potentially increased synergy at an earlier stage. Our goal is to design a general methodology to facilitate knowledge discovery and produce accurate and interpretable models. Results To combine models at the knowledge level, we propose to decouple the learning phase from the knowledge application phase using a pivot representation (lingua franca) based on the concept of hypothesis. A hypothesis is a simple and interpretable knowledge unit. Regardless of its origin, knowledge is broken down into a collection of hypotheses. These hypotheses are subsequently organised into hierarchical network. This unification permits to combine different sources of knowledge into a common formalised framework. The approach allows us to create a synergistic system between different forms of knowledge and new algorithms can be applied to leverage this unified model. This first article focuses on the general principle of the Self Organising Hypothesis Network (SOHN) approach in the context of binary classification problems along with an illustrative application to the prediction of mutagenicity. Conclusion It is possible to represent knowledge in the unified form of a hypothesis network allowing interpretable predictions with performances comparable to mainstream machine learning techniques. This new approach offers the potential to combine knowledge from different sources into a common framework in which high level reasoning and meta-learning can be applied; these latter perspectives will be explored in future work. PMID:24959206

Computational neuroanatomy: ontology-based representation of neural components and connectivity.

PubMed

Rubin, Daniel L; Talos, Ion-Florin; Halle, Michael; Musen, Mark A; Kikinis, Ron

2009-02-05

A critical challenge in neuroscience is organizing, managing, and accessing the explosion in neuroscientific knowledge, particularly anatomic knowledge. We believe that explicit knowledge-based approaches to make neuroscientific knowledge computationally accessible will be helpful in tackling this challenge and will enable a variety of applications exploiting this knowledge, such as surgical planning. We developed ontology-based models of neuroanatomy to enable symbolic lookup, logical inference and mathematical modeling of neural systems. We built a prototype model of the motor system that integrates descriptive anatomic and qualitative functional neuroanatomical knowledge. In addition to modeling normal neuroanatomy, our approach provides an explicit representation of abnormal neural connectivity in disease states, such as common movement disorders. The ontology-based representation encodes both structural and functional aspects of neuroanatomy. The ontology-based models can be evaluated computationally, enabling development of automated computer reasoning applications. Neuroanatomical knowledge can be represented in machine-accessible format using ontologies. Computational neuroanatomical approaches such as described in this work could become a key tool in translational informatics, leading to decision support applications that inform and guide surgical planning and personalized care for neurological disease in the future.

A new intrusion prevention model using planning knowledge graph

NASA Astrophysics Data System (ADS)

Cai, Zengyu; Feng, Yuan; Liu, Shuru; Gan, Yong

2013-03-01

Intelligent plan is a very important research in artificial intelligence, which has applied in network security. This paper proposes a new intrusion prevention model base on planning knowledge graph and discuses the system architecture and characteristics of this model. The Intrusion Prevention based on plan knowledge graph is completed by plan recognition based on planning knowledge graph, and the Intrusion response strategies and actions are completed by the hierarchical task network (HTN) planner in this paper. Intrusion prevention system has the advantages of intelligent planning, which has the advantage of the knowledge-sharing, the response focused, learning autonomy and protective ability.

Developing Elementary Teachers' Knowledge about Functions and Rate of Change through Modeling

ERIC Educational Resources Information Center

Weber, Eric; Tallman, Michael A.; Middleton, James A.

2015-01-01

The purpose of this article is to describe the development of elementary school teachers' mathematical knowledge for teaching as they participated in a Modeling Instruction environment that placed heavy emphasis on improving their subject-matter knowledge as a basis for affecting the development of their pedagogical content knowledge. We…

Development of user-centered interfaces to search the knowledge resources of the Virginia Henderson International Nursing Library.

PubMed

Jones, Josette; Harris, Marcelline; Bagley-Thompson, Cheryl; Root, Jane

2003-01-01

This poster describes the development of user-centered interfaces in order to extend the functionality of the Virginia Henderson International Nursing Library (VHINL) from library to web based portal to nursing knowledge resources. The existing knowledge structure and computational models are revised and made complementary. Nurses' search behavior is captured and analyzed, and the resulting search models are mapped to the revised knowledge structure and computational model.

Mapping the Structure of Knowledge for Teaching Nominal Categorical Data Analysis

ERIC Educational Resources Information Center

Groth, Randall E.; Bergner, Jennifer A.

2013-01-01

This report describes a model for mapping cognitive structures related to content knowledge for teaching. The model consists of knowledge elements pertinent to teaching a content domain, the nature of the connections among them, and a means for representing the elements and connections visually. The model is illustrated through empirical data…

Properties of the Bayesian Knowledge Tracing Model

ERIC Educational Resources Information Center

van de Sande, Brett

2013-01-01

Bayesian Knowledge Tracing is used very widely to model student learning. It comes in two different forms: The first form is the Bayesian Knowledge Tracing "hidden Markov model" which predicts the probability of correct application of a skill as a function of the number of previous opportunities to apply that skill and the model…

A Model for Resource Allocation Using Operational Knowledge Assets

ERIC Educational Resources Information Center

Andreou, Andreas N.; Bontis, Nick

2007-01-01

Purpose: The paper seeks to develop a business model that shows the impact of operational knowledge assets on intellectual capital (IC) components and business performance and use the model to show how knowledge assets can be prioritized in driving resource allocation decisions. Design/methodology/approach: Quantitative data were collected from 84…

TPDK, a New Definition of the TPACK Model for a University Setting

ERIC Educational Resources Information Center

Bachy, Sylviane

2014-01-01

In this paper we propose a new Technopedagogical Disciplinary Knowledge model. This model integrates four separate dimensions, which we use to measure a teacher's effectiveness. These are the individual teacher's discipline (D), personal epistemology (E), pedagogical knowledge (P), and knowledge of technology (T). We also acknowledge the…

A Construct Validation of the Mental Models Learning Outcome Using Exploratory Factor Analysis.

ERIC Educational Resources Information Center

Sheehan, Joseph; Tessmer, Martin

A mental model is a knowledge structure composed of concepts and the relations between them. Mental models are distinct from declarative and procedural knowledge--they go beyond semantic relationships and skills acquisition and contain varied intellectual skills and knowledge. This study describes an initial investigation into the construct…

Tacit Beginnings Towards a Model of Scientific Thinking

NASA Astrophysics Data System (ADS)

Glass, Rory J.

2013-10-01

The purpose of this paper is to provide an examination of the role tacit knowledge plays in understanding, and to provide a model to make such knowledge identifiable. To do this I first consider the needs of society, the ubiquity of information in our world and the future demands of the science classroom. I propose the use of more implicit or tacit understandings as foundational elements for the development of student knowledge. To justify this proposition I consider a wide range of philosophical and psychological perspectives on knowledge. Then develop a Model of Scientific Knowledge, based in large part on a similar model created by Paul Ernest (Social constructivism as a philosophy of mathematics, SUNY Press, Albany, NY, 1998a; Situated cognition and the learning of mathematics, University of Oxford Department of Educational Studies, Oxford, 1998b). Finally, I consider the work that has been done by those in fields beyond education and the ways in which tacit knowledge can be used as a starting point for knowledge building.

Conceptualization of an R&D Based Learning-to-Innovate Model for Science Education

NASA Astrophysics Data System (ADS)

Lai, Oiki Sylvia

The purpose of this research was to conceptualize an R & D based learning-to-innovate (LTI) model. The problem to be addressed was the lack of a theoretical L TI model, which would inform science pedagogy. The absorptive capacity (ACAP) lens was adopted to untangle the R & D LTI phenomenon into four learning processes: problem-solving via knowledge acquisition, incremental improvement via knowledge participation, scientific discovery via knowledge creation, and product design via knowledge productivity. The four knowledge factors were the latent factors and each factor had seven manifest elements as measured variables. The key objectives of the non experimental quantitative survey were to measure the relative importance of the identified elements and to explore the underlining structure of the variables. A questionnaire had been prepared, and was administered to more than 155 R & D professionals from four sectors - business, academic, government, and nonprofit. The results showed that every identified element was important to the R & D professionals, in terms of improving the related type of innovation. The most important elements were highlighted to serve as building blocks for elaboration. In search for patterns of the data matrix, exploratory factor analysis (EF A) was performed. Principal component analysis was the first phase of EF A to extract factors; while maximum likelihood estimation (MLE) was used to estimate the model. EF A yielded the finding of two aspects in each kind of knowledge. Logical names were assigned to represent the nature of the subsets: problem and knowledge under knowledge acquisition, planning and participation under knowledge participation, exploration and discovery under knowledge creation, and construction and invention under knowledge productivity. These two constructs, within each kind of knowledge, added structure to the vague R & D based LTI model. The research questions and hypotheses testing were addressed using correlation analysis. The alternative hypotheses that there were positive relationships between knowledge factors and their corresponding types of innovation were accepted. In-depth study of each process is recommended in both research and application. Experimental tests are needed, in order to ultimately present the LTI model to enhance the scientific knowledge absorptive capacity of the learners to facilitate their innovation performance.

Terminological reference of a knowledge-based system: the data dictionary.

PubMed

Stausberg, J; Wormek, A; Kraut, U

1995-01-01

The development of open and integrated knowledge bases makes new demands on the definition of the used terminology. The definition should be realized in a data dictionary separated from the knowledge base. Within the works done at a reference model of medical knowledge, a data dictionary has been developed and used in different applications: a term definition shell, a documentation tool and a knowledge base. The data dictionary includes that part of terminology, which is largely independent of a certain knowledge model. For that reason, the data dictionary can be used as a basis for integrating knowledge bases into information systems, for knowledge sharing and reuse and for modular development of knowledge-based systems.

An Extended Model of Knowledge Governance

NASA Astrophysics Data System (ADS)

Karvalics, Laszlo Z.; Dalal, Nikunj

In current times, we are seeing the emergence of a new paradigm to describe, understand, and analyze the expanding "knowledge domain". This overarching framework - called knowledge governance - draws from and builds upon knowledge management and may be seen as a kind of meta-layer of knowledge management. The emerging knowledge governance approach deals with issues that lie at the intersection of organization and knowledge processes. Knowledge governance has two main interpretation levels in the literature: the company- (micro-) and the national (macro-) level. We propose a three-layer model instead of the previous two-layer version, adding a layer of "global" knowledge governance. Analyzing and separating the main issues in this way, we can re-formulate the focus of knowledge governance research and practice in all layers.

Tacit knowledge: A refinement and empirical test of the Academic Tacit Knowledge Scale.

PubMed

Insch, Gary S; McIntyre, Nancy; Dawley, David

2008-11-01

Researchers have linked tacit knowledge to improved organizational performance, but research on how to measure tacit knowledge is scarce. In the present study, the authors proposed and empirically tested a model of tacit knowledge and an accompanying measurement scale of academic tacit knowledge. They present 6 hypotheses that support the proposed tacit knowledge model regarding the role of cognitive (self-motivation, self-organization); technical (individual task, institutional task); and social (task-related, general) skills. The authors tested these hypotheses with 542 responses to the Academic Tacit Knowledge Scale, which included the respondents' grade point average-the performance variable. All 6 hypotheses were supported.

Structured statistical models of inductive reasoning.

PubMed

Kemp, Charles; Tenenbaum, Joshua B

2009-01-01

Everyday inductive inferences are often guided by rich background knowledge. Formal models of induction should aim to incorporate this knowledge and should explain how different kinds of knowledge lead to the distinctive patterns of reasoning found in different inductive contexts. This article presents a Bayesian framework that attempts to meet both goals and describes [corrected] 4 applications of the framework: a taxonomic model, a spatial model, a threshold model, and a causal model. Each model makes probabilistic inferences about the extensions of novel properties, but the priors for the 4 models are defined over different kinds of structures that capture different relationships between the categories in a domain. The framework therefore shows how statistical inference can operate over structured background knowledge, and the authors argue that this interaction between structure and statistics is critical for explaining the power and flexibility of human reasoning.

The research on construction and application of machining process knowledge base

NASA Astrophysics Data System (ADS)

Zhao, Tan; Qiao, Lihong; Qie, Yifan; Guo, Kai

2018-03-01

In order to realize the application of knowledge in machining process design, from the perspective of knowledge in the application of computer aided process planning(CAPP), a hierarchical structure of knowledge classification is established according to the characteristics of mechanical engineering field. The expression of machining process knowledge is structured by means of production rules and the object-oriented methods. Three kinds of knowledge base models are constructed according to the representation of machining process knowledge. In this paper, the definition and classification of machining process knowledge, knowledge model, and the application flow of the process design based on the knowledge base are given, and the main steps of the design decision of the machine tool are carried out as an application by using the knowledge base.

Structuring and extracting knowledge for the support of hypothesis generation in molecular biology

PubMed Central

Roos, Marco; Marshall, M Scott; Gibson, Andrew P; Schuemie, Martijn; Meij, Edgar; Katrenko, Sophia; van Hage, Willem Robert; Krommydas, Konstantinos; Adriaans, Pieter W

2009-01-01

Background Hypothesis generation in molecular and cellular biology is an empirical process in which knowledge derived from prior experiments is distilled into a comprehensible model. The requirement of automated support is exemplified by the difficulty of considering all relevant facts that are contained in the millions of documents available from PubMed. Semantic Web provides tools for sharing prior knowledge, while information retrieval and information extraction techniques enable its extraction from literature. Their combination makes prior knowledge available for computational analysis and inference. While some tools provide complete solutions that limit the control over the modeling and extraction processes, we seek a methodology that supports control by the experimenter over these critical processes. Results We describe progress towards automated support for the generation of biomolecular hypotheses. Semantic Web technologies are used to structure and store knowledge, while a workflow extracts knowledge from text. We designed minimal proto-ontologies in OWL for capturing different aspects of a text mining experiment: the biological hypothesis, text and documents, text mining, and workflow provenance. The models fit a methodology that allows focus on the requirements of a single experiment while supporting reuse and posterior analysis of extracted knowledge from multiple experiments. Our workflow is composed of services from the 'Adaptive Information Disclosure Application' (AIDA) toolkit as well as a few others. The output is a semantic model with putative biological relations, with each relation linked to the corresponding evidence. Conclusion We demonstrated a 'do-it-yourself' approach for structuring and extracting knowledge in the context of experimental research on biomolecular mechanisms. The methodology can be used to bootstrap the construction of semantically rich biological models using the results of knowledge extraction processes. Models specific to particular experiments can be constructed that, in turn, link with other semantic models, creating a web of knowledge that spans experiments. Mapping mechanisms can link to other knowledge resources such as OBO ontologies or SKOS vocabularies. AIDA Web Services can be used to design personalized knowledge extraction procedures. In our example experiment, we found three proteins (NF-Kappa B, p21, and Bax) potentially playing a role in the interplay between nutrients and epigenetic gene regulation. PMID:19796406

From Whiteboard to Model: A Preliminary Analysis (Preprint)

DTIC Science & Technology

2007-01-01

models built for process control emphasize precision, and so on. One’s available knowledge and data also influence the modeling task. Domains such as...chemical engineering and circuit design are knowledge -rich, which enables a realistic expression of the entities and relationships within the...index into the others so that the modeler can move about freely with ease. And third, no matter the richness of knowledge or data about an

Knowledge representation to support reasoning based on multiple models

NASA Technical Reports Server (NTRS)

Gillam, April; Seidel, Jorge P.; Parker, Alice C.

1990-01-01

Model Based Reasoning is a powerful tool used to design and analyze systems, which are often composed of numerous interactive, interrelated subsystems. Models of the subsystems are written independently and may be used together while they are still under development. Thus the models are not static. They evolve as information becomes obsolete, as improved artifact descriptions are developed, and as system capabilities change. Researchers are using three methods to support knowledge/data base growth, to track the model evolution, and to handle knowledge from diverse domains. First, the representation methodology is based on having pools, or types, of knowledge from which each model is constructed. In addition information is explicit. This includes the interactions between components, the description of the artifact structure, and the constraints and limitations of the models. The third principle we have followed is the separation of the data and knowledge from the inferencing and equation solving mechanisms. This methodology is used in two distinct knowledge-based systems: one for the design of space systems and another for the synthesis of VLSI circuits. It has facilitated the growth and evolution of our models, made accountability of results explicit, and provided credibility for the user community. These capabilities have been implemented and are being used in actual design projects.

Use of metaknowledge in the verification of knowledge-based systems

NASA Technical Reports Server (NTRS)

Morell, Larry J.

1989-01-01

Knowledge-based systems are modeled as deductive systems. The model indicates that the two primary areas of concern in verification are demonstrating consistency and completeness. A system is inconsistent if it asserts something that is not true of the modeled domain. A system is incomplete if it lacks deductive capability. Two forms of consistency are discussed along with appropriate verification methods. Three forms of incompleteness are discussed. The use of metaknowledge, knowledge about knowledge, is explored in connection to each form of incompleteness.

Innovative Extension Models and Smallholders: How ICT platforms can Deliver Timely Information to Farmers in India.

NASA Astrophysics Data System (ADS)

Nagothu, U. S.

2016-12-01

Agricultural extension services, among others, contribute to improving rural livelihoods and enhancing economic development. Knowledge development and transfer from the cognitive science point of view, is about, how farmers use and apply their experiential knowledge as well as acquired new knowledge to solve new problems. This depends on the models adopted, the way knowledge is generated and delivered. New extension models based on ICT platforms and smart phones are promising. Results from a 5-year project (www.climaadapt.org) in India shows that farmer led-on farm validations of technologies and knowledge exchange through ICT based platforms outperformed state operated linear extension programs. Innovation here depends on the connectivity, net-working between stakeholders that are involved in generating, transferring and using the knowledge. Key words: Smallholders, Knowledge, Extension, Innovation, India

Interdisciplinary Characterizations of Models and the Nature of Chemical Knowledge in the Classroom

ERIC Educational Resources Information Center

Erduran, Sibel; Duschl, Richard A.

2004-01-01

In this paper, the authors argue that chemical knowledge in the classroom will be enriched by the application of characterizations of models drawn from a range of disciplinary backgrounds. This discussion highlights two important issues relating to chemical knowledge in the classroom: (1) the status of chemical knowledge in the classroom,…

Using the Knowledge to Action Process Model to Incite Clinical Change

ERIC Educational Resources Information Center

Petzold, Anita; Korner-Bitensky, Nicol; Menon, Anita

2010-01-01

Introduction: Knowledge translation (KT) has only recently emerged in the field of rehabilitation with attention on creating effective KT interventions to increase clinicians' knowledge and use of evidence-based practice (EBP). The uptake of EBP is a complex process that can be facilitated by the use of the Knowledge to Action Process model. This…

Knowledge network model of the energy consumption in discrete manufacturing system

NASA Astrophysics Data System (ADS)

Xu, Binzi; Wang, Yan; Ji, Zhicheng

2017-07-01

Discrete manufacturing system generates a large amount of data and information because of the development of information technology. Hence, a management mechanism is urgently required. In order to incorporate knowledge generated from manufacturing data and production experience, a knowledge network model of the energy consumption in the discrete manufacturing system was put forward based on knowledge network theory and multi-granularity modular ontology technology. This model could provide a standard representation for concepts, terms and their relationships, which could be understood by both human and computer. Besides, the formal description of energy consumption knowledge elements (ECKEs) in the knowledge network was also given. Finally, an application example was used to verify the feasibility of the proposed method.

A Bayesian network approach to knowledge integration and representation of farm irrigation: 1. Model development

NASA Astrophysics Data System (ADS)

Wang, Q. J.; Robertson, D. E.; Haines, C. L.

2009-02-01

Irrigation is important to many agricultural businesses but also has implications for catchment health. A considerable body of knowledge exists on how irrigation management affects farm business and catchment health. However, this knowledge is fragmentary; is available in many forms such as qualitative and quantitative; is dispersed in scientific literature, technical reports, and the minds of individuals; and is of varying degrees of certainty. Bayesian networks allow the integration of dispersed knowledge into quantitative systems models. This study describes the development, validation, and application of a Bayesian network model of farm irrigation in the Shepparton Irrigation Region of northern Victoria, Australia. In this first paper we describe the process used to integrate a range of sources of knowledge to develop a model of farm irrigation. We describe the principal model components and summarize the reaction to the model and its development process by local stakeholders. Subsequent papers in this series describe model validation and the application of the model to assess the regional impact of historical and future management intervention.

Automated extraction of knowledge for model-based diagnostics

NASA Technical Reports Server (NTRS)

Gonzalez, Avelino J.; Myler, Harley R.; Towhidnejad, Massood; Mckenzie, Frederic D.; Kladke, Robin R.

1990-01-01

The concept of accessing computer aided design (CAD) design databases and extracting a process model automatically is investigated as a possible source for the generation of knowledge bases for model-based reasoning systems. The resulting system, referred to as automated knowledge generation (AKG), uses an object-oriented programming structure and constraint techniques as well as internal database of component descriptions to generate a frame-based structure that describes the model. The procedure has been designed to be general enough to be easily coupled to CAD systems that feature a database capable of providing label and connectivity data from the drawn system. The AKG system is capable of defining knowledge bases in formats required by various model-based reasoning tools.

Developing Social Competence and Other Generic Skills in Teacher Education: Applying the Model of Integrative Pedagogy

ERIC Educational Resources Information Center

Tynjälä, Päivi; Virtanen, Anne; Klemola, Ulla; Kostiainen, Emma; Rasku-Puttonen, Helena

2016-01-01

The purpose of the study was to examine how social competence and other generic skills can be developed in teacher education using a pedagogical model called Integrative Pedagogy. This model is based on the idea of integrating the four basic components of expertise: Theoretical knowledge, practical knowledge, self-regulative knowledge, and…

The Importance and Weaknesses of the Productivist Industrial Model of Knowledge Production

ERIC Educational Resources Information Center

Persson, Roland S.

2010-01-01

To view contemporary Science as an industry is a very apt and timely stance. Ghassib's (2010) historical analysis of knowledge production, which he terms "A Productivist Industrial Model of Knowledge Production," is an interesting one. It is important, however, to observe that the outline of this model is based entirely on the production of…

An integrated model of decision-making in health contexts: the role of science education in health education

NASA Astrophysics Data System (ADS)

Arnold, Julia C.

2018-03-01

Health education is to foster health literacy, informed decision-making and to promote health behaviour. To date, there are several models that seek to explain health behaviour (e.g. the Theory of Planned Behaviour or the Health Belief Model). These models include motivational factors (expectancies and values) that play a role in decision-making in health contexts. In this theoretical paper, it is argued that none of these models makes consequent use of expectancy-value pairs. It is further argued that in order to make these models fruitful for science education and for informed decision-making, models should systematically incorporate knowledge as part of the decision-making process. To fill this gap, this theoretical paper introduces The Integrated Model of Decision-Making in Health Contexts. This model includes three types of knowledge (system health knowledge, action-related health knowledge and effectiveness health knowledge) as influencing factors for motivational factors (perceived health threat, attitude towards health action, attitude towards health outcome and subjective norm) that are formed of expectancy-value pairs and lead to decisions. The model's potential for health education in science education as well as research implications is discussed.

A Framework of Operating Models for Interdisciplinary Research Programs in Clinical Service Organizations

ERIC Educational Resources Information Center

King, Gillian; Currie, Melissa; Smith, Linda; Servais, Michelle; McDougall, Janette

2008-01-01

A framework of operating models for interdisciplinary research programs in clinical service organizations is presented, consisting of a "clinician-researcher" skill development model, a program evaluation model, a researcher-led knowledge generation model, and a knowledge conduit model. Together, these models comprise a tailored, collaborative…

Computational neuroanatomy: ontology-based representation of neural components and connectivity

PubMed Central

Rubin, Daniel L; Talos, Ion-Florin; Halle, Michael; Musen, Mark A; Kikinis, Ron

2009-01-01

Background A critical challenge in neuroscience is organizing, managing, and accessing the explosion in neuroscientific knowledge, particularly anatomic knowledge. We believe that explicit knowledge-based approaches to make neuroscientific knowledge computationally accessible will be helpful in tackling this challenge and will enable a variety of applications exploiting this knowledge, such as surgical planning. Results We developed ontology-based models of neuroanatomy to enable symbolic lookup, logical inference and mathematical modeling of neural systems. We built a prototype model of the motor system that integrates descriptive anatomic and qualitative functional neuroanatomical knowledge. In addition to modeling normal neuroanatomy, our approach provides an explicit representation of abnormal neural connectivity in disease states, such as common movement disorders. The ontology-based representation encodes both structural and functional aspects of neuroanatomy. The ontology-based models can be evaluated computationally, enabling development of automated computer reasoning applications. Conclusion Neuroanatomical knowledge can be represented in machine-accessible format using ontologies. Computational neuroanatomical approaches such as described in this work could become a key tool in translational informatics, leading to decision support applications that inform and guide surgical planning and personalized care for neurological disease in the future. PMID:19208191

Relationship between oral health-related knowledge, attitudes and behavior among 15-16-year-old adolescents: a structural equation modeling approach.

PubMed

Tolvanen, Mimmi; Lahti, Satu; Miettunen, Jouko; Hausen, Hannu

2012-03-01

The aim of this study was to confirm the previously observed attitudinal factor structure related to behavioral change and the knowledge-attitude-behavior model on dental health and hygiene among adolescents. The study population consisted of all 8(th) and 9(th) graders (15-16 years) who started the 2004-2005 school year in Rauma, Finland (n = 827). Data on knowledge, attitudes, toothbrushing and using fluoride toothpaste were gathered by questionnaires. Hypothesized structure included four attitudinal factors related to dental health and hygiene: 'importance of toothbrushing when participating in social situations' (F1), 'importance of toothbrushing for health-related reasons and better appearance' (F2), 'being concerned about developing caries lesions' (F3) and 'importance of toothbrushing for feeling accepted' (F4). Structural equation modeling (SEM) was used to test the hypothesized model: pathways lead from knowledge to behavior both directly and via attitudes. The hypothesized model was also modified by removing non-significant pathways and studying the inter-relationships between attitudes. A confirmatory factor analysis revealed that factor F4 had to be removed. In the final model, knowledge influenced behavior directly and via two attitude factors, F1 and F2, which were inter-related. 'Concern about developing caries lesions' was a background factor influencing only knowledge. The final factor structure and SEM model were acceptable-to-good fit. Knowledge had a smaller effect on behavior than on attitudes. Our results support theories about the causal knowledge-attitudes-behavior chain, also for adolescents' oral health-related behaviors.

Using fuzzy rule-based knowledge model for optimum plating conditions search

NASA Astrophysics Data System (ADS)

Solovjev, D. S.; Solovjeva, I. A.; Litovka, Yu V.; Arzamastsev, A. A.; Glazkov, V. P.; L’vov, A. A.

2018-03-01

The paper discusses existing approaches to plating process modeling in order to decrease the distribution thickness of plating surface cover. However, these approaches do not take into account the experience, knowledge, and intuition of the decision-makers when searching the optimal conditions of electroplating technological process. The original approach to optimal conditions search for applying the electroplating coatings, which uses the rule-based model of knowledge and allows one to reduce the uneven product thickness distribution, is proposed. The block diagrams of a conventional control system of a galvanic process as well as the system based on the production model of knowledge are considered. It is shown that the fuzzy production model of knowledge in the control system makes it possible to obtain galvanic coatings of a given thickness unevenness with a high degree of adequacy to the experimental data. The described experimental results confirm the theoretical conclusions.

Dynamic knowledge representation using agent-based modeling: ontology instantiation and verification of conceptual models.

PubMed

An, Gary

2009-01-01

The sheer volume of biomedical research threatens to overwhelm the capacity of individuals to effectively process this information. Adding to this challenge is the multiscale nature of both biological systems and the research community as a whole. Given this volume and rate of generation of biomedical information, the research community must develop methods for robust representation of knowledge in order for individuals, and the community as a whole, to "know what they know." Despite increasing emphasis on "data-driven" research, the fact remains that researchers guide their research using intuitively constructed conceptual models derived from knowledge extracted from publications, knowledge that is generally qualitatively expressed using natural language. Agent-based modeling (ABM) is a computational modeling method that is suited to translating the knowledge expressed in biomedical texts into dynamic representations of the conceptual models generated by researchers. The hierarchical object-class orientation of ABM maps well to biomedical ontological structures, facilitating the translation of ontologies into instantiated models. Furthermore, ABM is suited to producing the nonintuitive behaviors that often "break" conceptual models. Verification in this context is focused at determining the plausibility of a particular conceptual model, and qualitative knowledge representation is often sufficient for this goal. Thus, utilized in this fashion, ABM can provide a powerful adjunct to other computational methods within the research process, as well as providing a metamodeling framework to enhance the evolution of biomedical ontologies.

Knowledge diffusion of dynamical network in terms of interaction frequency.

PubMed

Liu, Jian-Guo; Zhou, Qing; Guo, Qiang; Yang, Zhen-Hua; Xie, Fei; Han, Jing-Ti

2017-09-07

In this paper, we present a knowledge diffusion (SKD) model for dynamic networks by taking into account the interaction frequency which always used to measure the social closeness. A set of agents, which are initially interconnected to form a random network, either exchange knowledge with their neighbors or move toward a new location through an edge-rewiring procedure. The activity of knowledge exchange between agents is determined by a knowledge transfer rule that the target node would preferentially select one neighbor node to transfer knowledge with probability p according to their interaction frequency instead of the knowledge distance, otherwise, the target node would build a new link with its second-order neighbor preferentially or select one node in the system randomly with probability 1 - p. The simulation results show that, comparing with the Null model defined by the random selection mechanism and the traditional knowledge diffusion (TKD) model driven by knowledge distance, the knowledge would spread more fast based on SKD driven by interaction frequency. In particular, the network structure of SKD would evolve as an assortative one, which is a fundamental feature of social networks. This work would be helpful for deeply understanding the coevolution of the knowledge diffusion and network structure.

Knowledge Diffusion on Networks through the Game Strategy

NASA Astrophysics Data System (ADS)

Sun, Shu; Wu, Jiangning; Xuan, Zhaoguo

In this paper, we develop a knowledge diffusion model in which agents determine to give their knowledge to others according to some exchange strategies. The typical network namely small-world network is used for modeling, on which agents with knowledge are viewed as the nodes of the network and the edges are viewed as the social relationships for knowledge transmission. Such agents are permitted to interact with their neighbors repeatedly who have direct connections with them and accordingly change their strategies by choosing the most beneficial neighbors to diffuse knowledge. Two kinds of knowledge transmission strategies are proposed for the theoretical model based on the game theory and thereafter used in different simulations to examine the effect of the network structure on the knowledge diffusion effect. By analyses, two main observations can be found: One is that the simulation results are contrary to our intuition which agents would like to only accept but not share, thus they will maximize their benefit; another one is that the number of the agents acquired knowledge and the corresponding knowledge stock turn out to be independent of the percentage of those agents who choose to contribute their knowledge.

Memory-Based Simple Heuristics as Attribute Substitution: Competitive Tests of Binary Choice Inference Models.

PubMed

Honda, Hidehito; Matsuka, Toshihiko; Ueda, Kazuhiro

2017-05-01

Some researchers on binary choice inference have argued that people make inferences based on simple heuristics, such as recognition, fluency, or familiarity. Others have argued that people make inferences based on available knowledge. To examine the boundary between heuristic and knowledge usage, we examine binary choice inference processes in terms of attribute substitution in heuristic use (Kahneman & Frederick, 2005). In this framework, it is predicted that people will rely on heuristic or knowledge-based inference depending on the subjective difficulty of the inference task. We conducted competitive tests of binary choice inference models representing simple heuristics (fluency and familiarity heuristics) and knowledge-based inference models. We found that a simple heuristic model (especially a familiarity heuristic model) explained inference patterns for subjectively difficult inference tasks, and that a knowledge-based inference model explained subjectively easy inference tasks. These results were consistent with the predictions of the attribute substitution framework. Issues on usage of simple heuristics and psychological processes are discussed. Copyright © 2016 Cognitive Science Society, Inc.

Addressing the translational dilemma: dynamic knowledge representation of inflammation using agent-based modeling.

PubMed

An, Gary; Christley, Scott

2012-01-01

Given the panoply of system-level diseases that result from disordered inflammation, such as sepsis, atherosclerosis, cancer, and autoimmune disorders, understanding and characterizing the inflammatory response is a key target of biomedical research. Untangling the complex behavioral configurations associated with a process as ubiquitous as inflammation represents a prototype of the translational dilemma: the ability to translate mechanistic knowledge into effective therapeutics. A critical failure point in the current research environment is a throughput bottleneck at the level of evaluating hypotheses of mechanistic causality; these hypotheses represent the key step toward the application of knowledge for therapy development and design. Addressing the translational dilemma will require utilizing the ever-increasing power of computers and computational modeling to increase the efficiency of the scientific method in the identification and evaluation of hypotheses of mechanistic causality. More specifically, development needs to focus on facilitating the ability of non-computer trained biomedical researchers to utilize and instantiate their knowledge in dynamic computational models. This is termed "dynamic knowledge representation." Agent-based modeling is an object-oriented, discrete-event, rule-based simulation method that is well suited for biomedical dynamic knowledge representation. Agent-based modeling has been used in the study of inflammation at multiple scales. The ability of agent-based modeling to encompass multiple scales of biological process as well as spatial considerations, coupled with an intuitive modeling paradigm, suggest that this modeling framework is well suited for addressing the translational dilemma. This review describes agent-based modeling, gives examples of its applications in the study of inflammation, and introduces a proposed general expansion of the use of modeling and simulation to augment the generation and evaluation of knowledge by the biomedical research community at large.

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.

Individual nurse and organizational context considerations for better Knowledge Use in Pain Care.

PubMed

Latimer, Margot A; Ritchie, Judith A; Johnston, Celeste C

2010-08-01

Nurses are involved in many of the painful procedures performed on hospitalized children. In collaboration with physicians, nurses have an exceptional responsibility to have knowledge to manage the pain; however, the evidence indicates this is not being done. Issues may be twofold: (a) opportunities to improve knowledge of better pain care practices and/or (b) ability to use knowledge. Empirical evidence is available that if used by health care providers can reduce pain in hospitalized children. Theory-guided interventions are necessary to focus resources designated for learning and knowledge translation initiatives in the area of pain care. This article presents the Knowledge Use in Pain Care (KUPC) conceptual model that blends concepts from the fields of knowledge utilization and work life context, which are believed to influence the translation of knowledge to practice. The four main components in the KUPC model include those related to the organization, the individual nurse, the individual patient, and the sociopolitical context. The KUPC model was conceptualized to account for the complex circumstances surrounding nurse's knowledge uptake and use in the context of pain care. The model provides a framework for health care administrators, clinical leaders, and researchers to consider as they decide how to intervene to increase knowledge use to reduce painful experiences of children in the hospital. Copyright 2010 Elsevier Inc. All rights reserved.

Representing Human Expertise by the OWL Web Ontology Language to Support Knowledge Engineering in Decision Support Systems.

PubMed

Ramzan, Asia; Wang, Hai; Buckingham, Christopher

2014-01-01

Clinical decision support systems (CDSSs) often base their knowledge and advice on human expertise. Knowledge representation needs to be in a format that can be easily understood by human users as well as supporting ongoing knowledge engineering, including evolution and consistency of knowledge. This paper reports on the development of an ontology specification for managing knowledge engineering in a CDSS for assessing and managing risks associated with mental-health problems. The Galatean Risk and Safety Tool, GRiST, represents mental-health expertise in the form of a psychological model of classification. The hierarchical structure was directly represented in the machine using an XML document. Functionality of the model and knowledge management were controlled using attributes in the XML nodes, with an accompanying paper manual for specifying how end-user tools should behave when interfacing with the XML. This paper explains the advantages of using the web-ontology language, OWL, as the specification, details some of the issues and problems encountered in translating the psychological model to OWL, and shows how OWL benefits knowledge engineering. The conclusions are that OWL can have an important role in managing complex knowledge domains for systems based on human expertise without impeding the end-users' understanding of the knowledge base. The generic classification model underpinning GRiST makes it applicable to many decision domains and the accompanying OWL specification facilitates its implementation.

Data Mining and Knowledge Management: A System Analysis for Establishing a Tiered Knowledge Management Model.

ERIC Educational Resources Information Center

Luan, Jing; Willett, Terrence

This paper discusses data mining--an end-to-end (ETE) data analysis tool that is used by researchers in higher education. It also relates data mining and other software programs to a brand new concept called "Knowledge Management." The paper culminates in the Tier Knowledge Management Model (TKMM), which seeks to provide a stable…

M-and-C Domain Map Maker: an environment complimenting MDE with M-and-C knowledge and ensuring solution completeness

NASA Astrophysics Data System (ADS)

Patwari, Puneet; Choudhury, Subhrojyoti R.; Banerjee, Amar; Swaminathan, N.; Pandey, Shreya

2016-07-01

Model Driven Engineering (MDE) as a key driver to reduce development cost of M&C systems is beginning to find acceptance across scientific instruments such as Radio Telescopes and Nuclear Reactors. Such projects are adopting it to reduce time to integrate, test and simulate their individual controllers and increase reusability and traceability in the process. The creation and maintenance of models is still a significant challenge to realizing MDE benefits. Creating domain-specific modelling environments reduces the barriers, and we have been working along these lines, creating a domain-specific language and environment based on an M&C knowledge model. However, large projects involve several such domains, and there is still a need to interconnect the domain models, in order to ensure modelling completeness. This paper presents a knowledge-centric approach to doing that, by creating a generic system model that underlies the individual domain knowledge models. We present our vision for M&C Domain Map Maker, a set of processes and tools that enables explication of domain knowledge in terms of domain models with mutual consistency relationships to aid MDE.

Comparing Multidimensional and Continuum Models of Vocabulary Acquisition: An Empirical Examination of the Vocabulary Knowledge Scale

ERIC Educational Resources Information Center

Stewart, Jeffrey; Batty, Aaron Olaf; Bovee, Nicholas

2012-01-01

Second language vocabulary acquisition has been modeled both as multidimensional in nature and as a continuum wherein the learner's knowledge of a word develops along a cline from recognition through production. In order to empirically examine and compare these models, the authors assess the degree to which the Vocabulary Knowledge Scale (VKS;…

Developmental Relations between Vocabulary Knowledge and Reading Comprehension: A Latent Change Score Modeling Study

ERIC Educational Resources Information Center

Quinn, Jamie M.; Wagner, Richard K.; Petscher, Yaacov; Lopez, Danielle

2015-01-01

The present study followed a sample of first-grade (N = 316, M[subscript age] = 7.05 at first test) through fourth-grade students to evaluate dynamic developmental relations between vocabulary knowledge and reading comprehension. Using latent change score modeling, competing models were fit to the repeated measurements of vocabulary knowledge and…

Modeling Learning in Doubly Multilevel Binary Longitudinal Data Using Generalized Linear Mixed Models: An Application to Measuring and Explaining Word Learning.

PubMed

Cho, Sun-Joo; Goodwin, Amanda P

2016-04-01

When word learning is supported by instruction in experimental studies for adolescents, word knowledge outcomes tend to be collected from complex data structure, such as multiple aspects of word knowledge, multilevel reader data, multilevel item data, longitudinal design, and multiple groups. This study illustrates how generalized linear mixed models can be used to measure and explain word learning for data having such complexity. Results from this application provide deeper understanding of word knowledge than could be attained from simpler models and show that word knowledge is multidimensional and depends on word characteristics and instructional contexts.

Enhancing Users' Participation in Business Process Modeling through Ontology-Based Training

NASA Astrophysics Data System (ADS)

Macris, A.; Malamateniou, F.; Vassilacopoulos, G.

Successful business process design requires active participation of users who are familiar with organizational activities and business process modelling concepts. Hence, there is a need to provide users with reusable, flexible, agile and adaptable training material in order to enable them instil their knowledge and expertise in business process design and automation activities. Knowledge reusability is of paramount importance in designing training material on process modelling since it enables users participate actively in process design/redesign activities stimulated by the changing business environment. This paper presents a prototype approach for the design and use of training material that provides significant advantages to both the designer (knowledge - content reusability and semantic web enabling) and the user (semantic search, knowledge navigation and knowledge dissemination). The approach is based on externalizing domain knowledge in the form of ontology-based knowledge networks (i.e. training scenarios serving specific training needs) so that it is made reusable.

Towards a category theory approach to analogy: Analyzing re-representation and acquisition of numerical knowledge.

PubMed

Navarrete, Jairo A; Dartnell, Pablo

2017-08-01

Category Theory, a branch of mathematics, has shown promise as a modeling framework for higher-level cognition. We introduce an algebraic model for analogy that uses the language of category theory to explore analogy-related cognitive phenomena. To illustrate the potential of this approach, we use this model to explore three objects of study in cognitive literature. First, (a) we use commutative diagrams to analyze an effect of playing particular educational board games on the learning of numbers. Second, (b) we employ a notion called coequalizer as a formal model of re-representation that explains a property of computational models of analogy called "flexibility" whereby non-similar representational elements are considered matches and placed in structural correspondence. Finally, (c) we build a formal learning model which shows that re-representation, language processing and analogy making can explain the acquisition of knowledge of rational numbers. These objects of study provide a picture of acquisition of numerical knowledge that is compatible with empirical evidence and offers insights on possible connections between notions such as relational knowledge, analogy, learning, conceptual knowledge, re-representation and procedural knowledge. This suggests that the approach presented here facilitates mathematical modeling of cognition and provides novel ways to think about analogy-related cognitive phenomena.

Towards a category theory approach to analogy: Analyzing re-representation and acquisition of numerical knowledge

PubMed Central

2017-01-01

Category Theory, a branch of mathematics, has shown promise as a modeling framework for higher-level cognition. We introduce an algebraic model for analogy that uses the language of category theory to explore analogy-related cognitive phenomena. To illustrate the potential of this approach, we use this model to explore three objects of study in cognitive literature. First, (a) we use commutative diagrams to analyze an effect of playing particular educational board games on the learning of numbers. Second, (b) we employ a notion called coequalizer as a formal model of re-representation that explains a property of computational models of analogy called “flexibility” whereby non-similar representational elements are considered matches and placed in structural correspondence. Finally, (c) we build a formal learning model which shows that re-representation, language processing and analogy making can explain the acquisition of knowledge of rational numbers. These objects of study provide a picture of acquisition of numerical knowledge that is compatible with empirical evidence and offers insights on possible connections between notions such as relational knowledge, analogy, learning, conceptual knowledge, re-representation and procedural knowledge. This suggests that the approach presented here facilitates mathematical modeling of cognition and provides novel ways to think about analogy-related cognitive phenomena. PMID:28841643

Pursuing common agendas: a collaborative model for knowledge translation between research and practice in clinical settings.

PubMed

Baumbusch, Jennifer L; Kirkham, Sheryl Reimer; Khan, Koushambhi Basu; McDonald, Heather; Semeniuk, Pat; Tan, Elsie; Anderson, Joan M

2008-04-01

There is an emerging discourse of knowledge translation that advocates a shift away from unidirectional research utilization and evidence-based practice models toward more interactive models of knowledge transfer. In this paper, we describe how our participatory approach to knowledge translation developed during an ongoing program of research concerning equitable care for diverse populations. At the core of our approach is a collaborative relationship between researchers and practitioners, which underpins the knowledge translation cycle, and occurs simultaneously with data collection/analysis/synthesis. We discuss lessons learned including: the complexities of translating knowledge within the political landscape of healthcare delivery, the need to negotiate the agendas of researchers and practitioners in a collaborative approach, and the kinds of resources needed to support this process.

Use of a knowledge-attitude-behaviour education programme for Chinese adults undergoing maintenance haemodialysis: Randomized controlled trial.

PubMed

Liu, Li; Liu, Yue-Ping; Wang, Jing; An, Li-Wei; Jiao, Jian-Mei

2016-06-01

To investigate the effects of a knowledge-attitude-behaviour health education model on acquisition of disease-related knowledge and self-management behaviour by patients undergoing maintenance haemodialysis. Patients recently prescribed MHD were randomly assigned to a control group or an intervention group. Control group patients were treated with usual care and general education models. A specialist knowledge-attitude-behaviour health education model was applied to patients in the intervention group. Eighty-six patients were included (n = 43 per group). Before intervention, there were no significant between-group differences in disease knowledge and self-management behaviour. After 6 months' intervention, a significant between-group difference in acquisition of disease knowledge was observed. Self-management behaviour scores (control of body mass, reasonable diet, correct drug intake, physical activity, correct fistula care, disease condition monitoring, psychological and social behaviours) for the intervention group were also higher than those for the control group. These preliminary findings suggest that the knowledge-attitude-behaviour model appears to be a valuable tool for the health education of MHD patients. © The Author(s) 2016.

Use of a knowledge-attitude-behaviour education programme for Chinese adults undergoing maintenance haemodialysis: Randomized controlled trial

PubMed Central

Liu, Li; Wang, Jing; An, Li-Wei; Jiao, Jian-Mei

2016-01-01

Objective To investigate the effects of a knowledge-attitude-behaviour health education model on acquisition of disease-related knowledge and self-management behaviour by patients undergoing maintenance haemodialysis. Methods Patients recently prescribed MHD were randomly assigned to a control group or an intervention group. Control group patients were treated with usual care and general education models. A specialist knowledge-attitude-behaviour health education model was applied to patients in the intervention group. Results Eighty-six patients were included (n = 43 per group). Before intervention, there were no significant between-group differences in disease knowledge and self-management behaviour. After 6 months’ intervention, a significant between-group difference in acquisition of disease knowledge was observed. Self-management behaviour scores (control of body mass, reasonable diet, correct drug intake, physical activity, correct fistula care, disease condition monitoring, psychological and social behaviours) for the intervention group were also higher than those for the control group. Conclusion These preliminary findings suggest that the knowledge-attitude-behaviour model appears to be a valuable tool for the health education of MHD patients. PMID:26951842

[The discussion of the infiltrative model of chemical knowledge stepping into genetics teaching in agricultural institute or university].

PubMed

Zou, Ping; Luo, Pei-Gao

2010-05-01

Chemistry is an important group of basic courses, while genetics is one of the important major-basic courses in curriculum of many majors in agricultural institutes or universities. In order to establish the linkage between the major course and the basic course, the ability of application of the chemical knowledge previously learned in understanding genetic knowledge in genetics teaching is worthy of discussion for genetics teachers. In this paper, the authors advocate to apply some chemical knowledge previously learned to understand genetic knowledge in genetics teaching with infiltrative model, which could help students learn and understand genetic knowledge more deeply. Analysis of the intrinsic logistic relationship among the knowledge of different courses and construction of the integral knowledge network are useful for students to improve their analytic, comprehensive and logistic abilities. By this way, we could explore a new teaching model to develop the talents with new ideas and comprehensive competence in agricultural fields.

A User-Centric Knowledge Creation Model in a Web of Object-Enabled Internet of Things Environment

PubMed Central

Kibria, Muhammad Golam; Fattah, Sheik Mohammad Mostakim; Jeong, Kwanghyeon; Chong, Ilyoung; Jeong, Youn-Kwae

2015-01-01

User-centric service features in a Web of Object-enabled Internet of Things environment can be provided by using a semantic ontology that classifies and integrates objects on the World Wide Web as well as shares and merges context-aware information and accumulated knowledge. The semantic ontology is applied on a Web of Object platform to virtualize the real world physical devices and information to form virtual objects that represent the features and capabilities of devices in the virtual world. Detailed information and functionalities of multiple virtual objects are combined with service rules to form composite virtual objects that offer context-aware knowledge-based services, where context awareness plays an important role in enabling automatic modification of the system to reconfigure the services based on the context. Converting the raw data into meaningful information and connecting the information to form the knowledge and storing and reusing the objects in the knowledge base can both be expressed by semantic ontology. In this paper, a knowledge creation model that synchronizes a service logistic model and a virtual world knowledge model on a Web of Object platform has been proposed. To realize the context-aware knowledge-based service creation and execution, a conceptual semantic ontology model has been developed and a prototype has been implemented for a use case scenario of emergency service. PMID:26393609

A User-Centric Knowledge Creation Model in a Web of Object-Enabled Internet of Things Environment.

PubMed

Kibria, Muhammad Golam; Fattah, Sheik Mohammad Mostakim; Jeong, Kwanghyeon; Chong, Ilyoung; Jeong, Youn-Kwae

2015-09-18

User-centric service features in a Web of Object-enabled Internet of Things environment can be provided by using a semantic ontology that classifies and integrates objects on the World Wide Web as well as shares and merges context-aware information and accumulated knowledge. The semantic ontology is applied on a Web of Object platform to virtualize the real world physical devices and information to form virtual objects that represent the features and capabilities of devices in the virtual world. Detailed information and functionalities of multiple virtual objects are combined with service rules to form composite virtual objects that offer context-aware knowledge-based services, where context awareness plays an important role in enabling automatic modification of the system to reconfigure the services based on the context. Converting the raw data into meaningful information and connecting the information to form the knowledge and storing and reusing the objects in the knowledge base can both be expressed by semantic ontology. In this paper, a knowledge creation model that synchronizes a service logistic model and a virtual world knowledge model on a Web of Object platform has been proposed. To realize the context-aware knowledge-based service creation and execution, a conceptual semantic ontology model has been developed and a prototype has been implemented for a use case scenario of emergency service.

An empirically based model for knowledge management in health care organizations.

PubMed

Sibbald, Shannon L; Wathen, C Nadine; Kothari, Anita

2016-01-01

Knowledge management (KM) encompasses strategies, processes, and practices that allow an organization to capture, share, store, access, and use knowledge. Ideal KM combines different sources of knowledge to support innovation and improve performance. Despite the importance of KM in health care organizations (HCOs), there has been very little empirical research to describe KM in this context. This study explores KM in HCOs, focusing on the status of current intraorganizational KM. The intention is to provide insight for future studies and model development for effective KM implementation in HCOs. A qualitative methods approach was used to create an empirically based model of KM in HCOs. Methods included (a) qualitative interviews (n = 24) with senior leadership to identify types of knowledge important in these roles plus current information-seeking behaviors/needs and (b) in-depth case study with leaders in new executive positions (n = 2). The data were collected from 10 HCOs. Our empirically based model for KM was assessed for face and content validity. The findings highlight the paucity of formal KM in our sample HCOs. Organizational culture, leadership, and resources are instrumental in supporting KM processes. An executive's knowledge needs are extensive, but knowledge assets are often limited or difficult to acquire as much of the available information is not in a usable format. We propose an empirically based model for KM to highlight the importance of context (internal and external), and knowledge seeking, synthesis, sharing, and organization. Participants who reviewed the model supported its basic components and processes, and potential for incorporating KM into organizational processes. Our results articulate ways to improve KM, increase organizational learning, and support evidence-informed decision-making. This research has implications for how to better integrate evidence and knowledge into organizations while considering context and the role of organizational processes.

Disentangling the Role of Domain-Specific Knowledge in Student Modeling

NASA Astrophysics Data System (ADS)

Ruppert, John; Duncan, Ravit Golan; Chinn, Clark A.

2017-08-01

This study explores the role of domain-specific knowledge in students' modeling practice and how this knowledge interacts with two domain-general modeling strategies: use of evidence and developing a causal mechanism. We analyzed models made by middle school students who had a year of intensive model-based instruction. These models were made to explain a familiar but unstudied biological phenomenon: late onset muscle pain. Students were provided with three pieces of evidence related to this phenomenon and asked to construct a model to account for this evidence. Findings indicate that domain-specific resources play a significant role in the extent to which the models accounted for provided evidence. On the other hand, familiarity with the situation appeared to contribute to the mechanistic character of models. Our results indicate that modeling strategies alone are insufficient for the development of a mechanistic model that accounts for provided evidence and that, while learners can develop a tentative model with a basic familiarity of the situation, scaffolding certain domain-specific knowledge is necessary to assist students with incorporating evidence in modeling tasks.

A Framework for Understanding Physics Students' Computational Modeling Practices

NASA Astrophysics Data System (ADS)

Lunk, Brandon Robert

With the growing push to include computational modeling in the physics classroom, we are faced with the need to better understand students' computational modeling practices. While existing research on programming comprehension explores how novices and experts generate programming algorithms, little of this discusses how domain content knowledge, and physics knowledge in particular, can influence students' programming practices. In an effort to better understand this issue, I have developed a framework for modeling these practices based on a resource stance towards student knowledge. A resource framework models knowledge as the activation of vast networks of elements called "resources." Much like neurons in the brain, resources that become active can trigger cascading events of activation throughout the broader network. This model emphasizes the connectivity between knowledge elements and provides a description of students' knowledge base. Together with resources resources, the concepts of "epistemic games" and "frames" provide a means for addressing the interaction between content knowledge and practices. Although this framework has generally been limited to describing conceptual and mathematical understanding, it also provides a means for addressing students' programming practices. In this dissertation, I will demonstrate this facet of a resource framework as well as fill in an important missing piece: a set of epistemic games that can describe students' computational modeling strategies. The development of this theoretical framework emerged from the analysis of video data of students generating computational models during the laboratory component of a Matter & Interactions: Modern Mechanics course. Student participants across two semesters were recorded as they worked in groups to fix pre-written computational models that were initially missing key lines of code. Analysis of this video data showed that the students' programming practices were highly influenced by their existing physics content knowledge, particularly their knowledge of analytic procedures. While this existing knowledge was often applied in inappropriate circumstances, the students were still able to display a considerable amount of understanding of the physics content and of analytic solution procedures. These observations could not be adequately accommodated by the existing literature of programming comprehension. In extending the resource framework to the task of computational modeling, I model students' practices in terms of three important elements. First, a knowledge base includes re- sources for understanding physics, math, and programming structures. Second, a mechanism for monitoring and control describes students' expectations as being directed towards numerical, analytic, qualitative or rote solution approaches and which can be influenced by the problem representation. Third, a set of solution approaches---many of which were identified in this study---describe what aspects of the knowledge base students use and how they use that knowledge to enact their expectations. This framework allows us as researchers to track student discussions and pinpoint the source of difficulties. This work opens up many avenues of potential research. First, this framework gives researchers a vocabulary for extending Resource Theory to other domains of instruction, such as modeling how physics students use graphs. Second, this framework can be used as the basis for modeling expert physicists' programming practices. Important instructional implications also follow from this research. Namely, as we broaden the use of computational modeling in the physics classroom, our instructional practices should focus on helping students understand the step-by-step nature of programming in contrast to the already salient analytic procedures.

Sustainability knowledge using “AKASA” model among architecture students from Klang Valley private universities, Malaysia.

NASA Astrophysics Data System (ADS)

Kuppusamy, Sivaraman; Faris Khamidi, Mohd; Sheng, Lee Xia; Salvi Mari, Tamil

2017-12-01

The study intend to investigate sustainability knowledge using “AKASA” model. This model comprises all the literacy level which is the awareness, knowledge, attitude, skills and action. 234 students from 5 selected private universities were surveyed using questionnaires. Students were specifically selected from year 2 and year 3 from private universities in Klang valley, Malaysia. The study intends to investigate the environmental literacy level specifically the knowledge variable. The parametric study was conducted with descriptive analysis and the results shows that the environmental knowledge is at high level compared to other environmental literacy variables among year 2, year 3 and combine year 2 and year 3.

Relations between EFL Teachers' Formal Knowledge of Grammar and Their In-Action Mental Models of Children's Minds and Learning

ERIC Educational Resources Information Center

Haim, O.; Strauss, S.; Ravid, D.

2004-01-01

We studied the relations between English as a foreign language teachers' grammar knowledge and their in-action mental models (MMs) of children's minds and learning. The grammar knowledge we examined was English wh-constructions. A total of 74 teachers completed an assessment task and were classified to have deep, intermediate or shallow knowledge.…

Theoretical and Philosophical Aspects of Knowledge Management (SIG KM).

ERIC Educational Resources Information Center

Day, Ronald E.

2000-01-01

This session abstract discusses the history, philosophy, and theories of knowledge management to better understand its social and organizational potentials and limitations. Topics include determinacy of sense, information retrieval, and the Data Retrieval Model versus the Document Retrieval Model; discussions about knowledge; and surplus…

Knowledge transmission model with differing initial transmission and retransmission process

NASA Astrophysics Data System (ADS)

Wang, Haiying; Wang, Jun; Small, Michael

2018-10-01

Knowledge transmission is a cyclic dynamic diffusion process. The rate of acceptance of knowledge differs upon whether or not the recipient has previously held the knowledge. In this paper, the knowledge transmission process is divided into an initial and a retransmission procedure, each with its own transmission and self-learning parameters. Based on epidemic spreading model, we propose a naive-evangelical-agnostic (VEA) knowledge transmission model and derive mean-field equations to describe the dynamics of knowledge transmission in homogeneous networks. Theoretical analysis identifies a criterion for the persistence of knowledge, i.e., the reproduction number R0 depends on the minor effective parameters between the initial and retransmission process. Moreover, the final size of evangelical individuals is only related to retransmission process parameters. Numerical simulations validate the theoretical analysis. Furthermore, the simulations indicate that increasing the initial transmission parameters, including first transmission and self-learning rates of naive individuals, can accelerate the velocity of knowledge transmission efficiently but have no effect on the final size of evangelical individuals. In contrast, the retransmission parameters, including retransmission and self-learning rates of agnostic individuals, have a significant effect on the rate of knowledge transmission, i.e., the larger parameters the greater final density of evangelical individuals.

Numeric and symbolic knowledge representation of cerebral cortex anatomy: methods and preliminary results.

PubMed

Dameron, O; Gibaud, B; Morandi, X

2004-06-01

The human cerebral cortex anatomy describes the brain organization at the scale of gyri and sulci. It is used as landmarks for neurosurgery as well as localization support for functional data analysis or inter-subject data comparison. Existing models of the cortex anatomy either rely on image labeling but fail to represent variability and structural properties or rely on a conceptual model but miss the inner 3D nature and relations of anatomical structures. This study was therefore conducted to propose a model of sulco-gyral anatomy for the healthy human brain. We hypothesized that both numeric knowledge (i.e., image-based) and symbolic knowledge (i.e., concept-based) have to be represented and coordinated. In addition, the representation of this knowledge should be application-independent in order to be usable in various contexts. Therefore, we devised a symbolic model describing specialization, composition and spatial organization of cortical anatomical structures. We also collected numeric knowledge such as 3D models of shape and shape variation about cortical anatomical structures. For each numeric piece of knowledge, a companion file describes the concept it refers to and the nature of the relationship. Demonstration software performs a mapping between the numeric and the symbolic aspects for browsing the knowledge base.

Distinguishing Knowledge-Sharing, Knowledge-Construction, and Knowledge-Creation Discourses

ERIC Educational Resources Information Center

van Aalst, Jan

2009-01-01

The study reported here sought to obtain the clear articulation of asynchronous computer-mediated discourse needed for Carl Bereiter and Marlene Scardamalia's knowledge-creation model. Distinctions were set up between three modes of discourse: knowledge sharing, knowledge construction, and knowledge creation. These were applied to the asynchronous…

A Conceptual Framework for Examining Knowledge Management in Higher Education Contexts

ERIC Educational Resources Information Center

Lee, Hae-Young; Roth, Gene L.

2009-01-01

Knowledge management is an on-going process that involves varied activities: diagnosis, design, and implementation of knowledge creation, knowledge transfer, and knowledge sharing. The primary goal of knowledge management, like other management theories or models, is to identify and leverage organizational and individual knowledge for the…

A method of computer aided design with self-generative models in NX Siemens environment

NASA Astrophysics Data System (ADS)

Grabowik, C.; Kalinowski, K.; Kempa, W.; Paprocka, I.

2015-11-01

Currently in CAD/CAE/CAM systems it is possible to create 3D design virtual models which are able to capture certain amount of knowledge. These models are especially useful in an automation of routine design tasks. These models are known as self-generative or auto generative and they can behave in an intelligent way. The main difference between the auto generative and fully parametric models consists in the auto generative models ability to self-organizing. In this case design model self-organizing means that aside from the possibility of making of automatic changes of model quantitative features these models possess knowledge how these changes should be made. Moreover they are able to change quality features according to specific knowledge. In spite of undoubted good points of self-generative models they are not so often used in design constructional process which is mainly caused by usually great complexity of these models. This complexity makes the process of self-generative time and labour consuming. It also needs a quite great investment outlays. The creation process of self-generative model consists of the three stages it is knowledge and information acquisition, model type selection and model implementation. In this paper methods of the computer aided design with self-generative models in NX Siemens CAD/CAE/CAM software are presented. There are the five methods of self-generative models preparation in NX with: parametric relations model, part families, GRIP language application, knowledge fusion and OPEN API mechanism. In the paper examples of each type of the self-generative model are presented. These methods make the constructional design process much faster. It is suggested to prepare this kind of self-generative models when there is a need of design variants creation. The conducted research on assessing the usefulness of elaborated models showed that they are highly recommended in case of routine tasks automation. But it is still difficult to distinguish which method of self-generative preparation is most preferred. It always depends on a problem complexity. The easiest way for such a model preparation is this with the parametric relations model whilst the hardest one is this with the OPEN API mechanism. From knowledge processing point of view the best choice is application of the knowledge fusion.

Modelling in Primary School: Constructing Conceptual Models and Making Sense of Fractions

ERIC Educational Resources Information Center

Shahbari, Juhaina Awawdeh; Peled, Irit

2017-01-01

This article describes sixth-grade students' engagement in two model-eliciting activities offering students the opportunity to construct mathematical models. The findings show that students utilized their knowledge of fractions including conceptual and procedural knowledge in constructing mathematical models for the given situations. Some students…

Conceptualising GP teachers' knowledge: a pedagogical content knowledge perspective.

PubMed

Cantillon, Peter; de Grave, Willem

2012-05-01

Most teacher development initiatives focus on enhancing knowledge of teaching (pedagogy), whilst largely ignoring other important features of teacher knowledge such as subject matter knowledge and awareness of the learning context. Furthermore, teachers' ability to learn from faculty development interventions is limited by their existing (often implicit) pedagogical knowledge and beliefs. Pedagogical content knowledge (PCK) represents a model of teacher knowledge incorporating what they know about subject matter, pedagogy and context. PCK can be used to explore teachers' prior knowledge and to structure faculty development programmes so that they take account of a broader range of teachers' knowledge. We set out to examine the application of a PCK model in a general practice education setting. This study is part of a larger study that employed a mixed method approach (concept mapping, phenomenological interviews and video-stimulated recall) to explore features of GP teachers' subject matter knowledge, pedagogical knowledge and knowledge of the learning environment in the context of a general practice tutorial. This paper presents data on GP teachers' pedagogical and context knowledge. There was considerable overlap between different GP teachers' knowledge and beliefs about learners and the clinical learning environment (i.e. knowledge of context). The teachers' beliefs about learners were largely based on assumptions derived from their own student experiences. There were stark differences, however, between teachers in terms of pedagogical knowledge, particularly in terms of their teaching orientations (i.e. transmission or facilitation orientation) and this was manifest in their teaching behaviours. PCK represents a useful model for conceptualising clinical teacher prior knowledge in three domains, namely subject matter, learning context and pedagogy. It can and should be used as a simple guiding framework by faculty developers to inform the design and delivery of their faculty development programmes.

Knowledge service decision making in business incubators based on the supernetwork model

NASA Astrophysics Data System (ADS)

Zhao, Liming; Zhang, Haihong; Wu, Wenqing

2017-08-01

As valuable resources for incubating firms, knowledge resources have received gradually increasing attention from all types of business incubators, and business incubators use a variety of knowledge services to stimulate rapid growth in incubating firms. Based on previous research, we generalize the knowledge transfer and knowledge networking services of two main forms of knowledge services and further divide knowledge transfer services into knowledge depth services and knowledge breadth services. Then, we construct the business incubators' knowledge supernetwork model, describe the evolution mechanism among heterogeneous agents and utilize a simulation to explore the performance variance of different business incubators' knowledge services. The simulation results show that knowledge stock increases faster when business incubators are able to provide knowledge services to more incubating firms and that the degree of discrepancy in the knowledge stock increases during the process of knowledge growth. Further, knowledge transfer services lead to greater differences in the knowledge structure, while knowledge networking services lead to smaller differences. Regarding the two types of knowledge transfer services, knowledge depth services are more conducive to knowledge growth than knowledge breadth services, but knowledge depth services lead to greater gaps in knowledge stocks and greater differences in knowledge structures. Overall, it is optimal for business incubators to select a single knowledge service or portfolio strategy based on the amount of time and energy expended on the two types of knowledge services.

Knowledge Management in healthcare libraries: the current picture.

PubMed

Hopkins, Emily

2017-06-01

Knowledge management has seen something of a resurgence in attention amongst health librarians recently. Of course it has never ceased to exist, but now many library staff are becoming more involved in organisational knowledge management, and positioning themselves as key players in the sphere. No single model of knowledge management is proliferating, but approaches that best fit the organisation's size, structure and culture, and a blending of evidence based practice and knowledge sharing. Whatever it is called and whatever models are used, it's clear that for librarians and information professionals, the importance of putting knowledge and evidence into practice, sharing knowledge well and capturing it effectively, are still what we will continue to do. © 2017 Health Libraries Group.

Rule-based simulation models

NASA Technical Reports Server (NTRS)

Nieten, Joseph L.; Seraphine, Kathleen M.

1991-01-01

Procedural modeling systems, rule based modeling systems, and a method for converting a procedural model to a rule based model are described. Simulation models are used to represent real time engineering systems. A real time system can be represented by a set of equations or functions connected so that they perform in the same manner as the actual system. Most modeling system languages are based on FORTRAN or some other procedural language. Therefore, they must be enhanced with a reaction capability. Rule based systems are reactive by definition. Once the engineering system has been decomposed into a set of calculations using only basic algebraic unary operations, a knowledge network of calculations and functions can be constructed. The knowledge network required by a rule based system can be generated by a knowledge acquisition tool or a source level compiler. The compiler would take an existing model source file, a syntax template, and a symbol table and generate the knowledge network. Thus, existing procedural models can be translated and executed by a rule based system. Neural models can be provide the high capacity data manipulation required by the most complex real time models.

The Joint Venture Model of Knowledge Utilization: a guide for change in nursing.

PubMed

Edgar, Linda; Herbert, Rosemary; Lambert, Sylvie; MacDonald, Jo-Ann; Dubois, Sylvie; Latimer, Margot

2006-05-01

Knowledge utilization (KU) is an essential component of today's nursing practice and healthcare system. Despite advances in knowledge generation, the gap in knowledge transfer from research to practice continues. KU models have moved beyond factors affecting the individual nurse to a broader perspective that includes the practice environment and the socio-political context. This paper proposes one such theoretical model the Joint Venture Model of Knowledge Utilization (JVMKU). Key components of the JVMKU that emerged from an extensive multidisciplinary review of the literature include leadership, emotional intelligence, person, message, empowered workplace and the socio-political environment. The model has a broad and practical application and is not specific to one type of KU or one population. This paper provides a description of the JVMKU, its development and suggested uses at both local and organizational levels. Nurses in both leadership and point-of-care positions will recognize the concepts identified and will be able to apply this model for KU in their own workplace for assessment of areas requiring strengthening and support.

Hybrid forecasting of chaotic processes: Using machine learning in conjunction with a knowledge-based model

NASA Astrophysics Data System (ADS)

Pathak, Jaideep; Wikner, Alexander; Fussell, Rebeckah; Chandra, Sarthak; Hunt, Brian R.; Girvan, Michelle; Ott, Edward

2018-04-01

A model-based approach to forecasting chaotic dynamical systems utilizes knowledge of the mechanistic processes governing the dynamics to build an approximate mathematical model of the system. In contrast, machine learning techniques have demonstrated promising results for forecasting chaotic systems purely from past time series measurements of system state variables (training data), without prior knowledge of the system dynamics. The motivation for this paper is the potential of machine learning for filling in the gaps in our underlying mechanistic knowledge that cause widely-used knowledge-based models to be inaccurate. Thus, we here propose a general method that leverages the advantages of these two approaches by combining a knowledge-based model and a machine learning technique to build a hybrid forecasting scheme. Potential applications for such an approach are numerous (e.g., improving weather forecasting). We demonstrate and test the utility of this approach using a particular illustrative version of a machine learning known as reservoir computing, and we apply the resulting hybrid forecaster to a low-dimensional chaotic system, as well as to a high-dimensional spatiotemporal chaotic system. These tests yield extremely promising results in that our hybrid technique is able to accurately predict for a much longer period of time than either its machine-learning component or its model-based component alone.

Do Knowledge-Component Models Need to Incorporate Representational Competencies?

ERIC Educational Resources Information Center

Rau, Martina Angela

2017-01-01

Traditional knowledge-component models describe students' content knowledge (e.g., their ability to carry out problem-solving procedures or their ability to reason about a concept). In many STEM domains, instruction uses multiple visual representations such as graphs, figures, and diagrams. The use of visual representations implies a…

The Academic Knowledge Management Model of Small Schools in Thailand

ERIC Educational Resources Information Center

Tumtuma, Chamnan; Chantarasombat, Chalard; Yeamsang, Theerawat

2015-01-01

The Academic Knowledge Management Model of Small Schools in Thailand was created by research and development. The quantitative and qualitative data were collected via the following steps: a participatory workshop meeting, the formation of a team according to knowledge base, field study, brainstorming, group discussion, activities carried out…

Rhizomatic Education: Community as Curriculum

ERIC Educational Resources Information Center

Cormier, Dave

2008-01-01

The pace of technological change has challenged historical notions of what counts as knowledge. Dave Cormier describes an alternative to the traditional notion of knowledge. In place of the expert-centered pedagogical planning and publishing cycle, Cormier suggests a rhizomatic model of learning. In the rhizomatic model, knowledge is negotiated,…

Knowledge Management System Model for Learning Organisations

ERIC Educational Resources Information Center

Amin, Yousif; Monamad, Roshayu

2017-01-01

Based on the literature of knowledge management (KM), this paper reports on the progress of developing a new knowledge management system (KMS) model with components architecture that are distributed over the widely-recognised socio-technical system (STS) aspects to guide developers for selecting the most applicable components to support their KM…

Toward a Model of Embodied Environmental Education: Perspectives from Theatre and Indigenous Knowledges

ERIC Educational Resources Information Center

Lane, Julia

2012-01-01

This paper suggests a model of embodied environmental education grounded in participant interviews, fieldwork, scholarly literature, and the author's own embodied relationship with the natural world. In this article, embodiment refers to a process that stems from Indigenous Knowledges and theatre. Although Indigenous Knowledges and theatre…

Structured Statistical Models of Inductive Reasoning

ERIC Educational Resources Information Center

Kemp, Charles; Tenenbaum, Joshua B.

2009-01-01

Everyday inductive inferences are often guided by rich background knowledge. Formal models of induction should aim to incorporate this knowledge and should explain how different kinds of knowledge lead to the distinctive patterns of reasoning found in different inductive contexts. This article presents a Bayesian framework that attempts to meet…

Automation based on knowledge modeling theory and its applications in engine diagnostic systems using Space Shuttle Main Engine vibrational data. M.S. Thesis

NASA Technical Reports Server (NTRS)

Kim, Jonnathan H.

1995-01-01

Humans can perform many complicated tasks without explicit rules. This inherent and advantageous capability becomes a hurdle when a task is to be automated. Modern computers and numerical calculations require explicit rules and discrete numerical values. In order to bridge the gap between human knowledge and automating tools, a knowledge model is proposed. Knowledge modeling techniques are discussed and utilized to automate a labor and time intensive task of detecting anomalous bearing wear patterns in the Space Shuttle Main Engine (SSME) High Pressure Oxygen Turbopump (HPOTP).

A model for indexing medical documents combining statistical and symbolic knowledge.

PubMed

Avillach, Paul; Joubert, Michel; Fieschi, Marius

2007-10-11

To develop and evaluate an information processing method based on terminologies, in order to index medical documents in any given documentary context. We designed a model using both symbolic general knowledge extracted from the Unified Medical Language System (UMLS) and statistical knowledge extracted from a domain of application. Using statistical knowledge allowed us to contextualize the general knowledge for every particular situation. For each document studied, the extracted terms are ranked to highlight the most significant ones. The model was tested on a set of 17,079 French standardized discharge summaries (SDSs). The most important ICD-10 term of each SDS was ranked 1st or 2nd by the method in nearly 90% of the cases. The use of several terminologies leads to more precise indexing. The improvement achieved in the models implementation performances as a result of using semantic relationships is encouraging.

Knowledge Co-production Strategies for Water Resources Modeling and Decision Making

NASA Astrophysics Data System (ADS)

Gober, P.

2016-12-01

The limited impact of scientific information on policy making and climate adaptation in North America has raised awareness of the need for new modeling strategies and knowledge transfer processes. This paper outlines the rationale for a new paradigm in water resources modeling and management, using examples from the USA and Canada. Principles include anticipatory modeling, complex system dynamics, decision making under uncertainty, visualization, capacity to represent and manipulate critical trade-offs, stakeholder engagement, local knowledge, context-specific activities, social learning, vulnerability analysis, iterative and collaborative modeling, and the concept of a boundary organization. In this framework, scientists and stakeholders are partners in the production and dissemination of knowledge for decision making, and local knowledge is fused with scientific observation and methodology. Discussion draws from experience in building long-term collaborative boundary organizations in Phoenix, Arizona in the USA and the Saskatchewan River Basin (SRB) in Canada. Examples of boundary spanning activities include the use of visualization, the concept of a decision theater, infrastructure to support social learning, social networks, and reciprocity, simulation modeling to explore "what if" scenarios of the future, surveys to elicit how water problems are framed by scientists and stakeholders, and humanistic activities (theatrical performances, art exhibitions, etc.) to draw attention to local water issues. The social processes surrounding model development and dissemination are at least as important as modeling assumptions, procedures, and results in determining whether scientific knowledge will be used effectively for water resources decision making.

Does attainment of Piaget's formal operational level of cognitive development predict student understanding of scientific models?

NASA Astrophysics Data System (ADS)

Lahti, Richard Dennis, II

Knowledge of scientific models and their uses is a concept that has become a key benchmark in many of the science standards of the past 30 years, including the proposed Next Generation Science Standards. Knowledge of models is linked to other important nature of science concepts such as theory change which are also rising in prominence in newer standards. Effective methods of instruction will need to be developed to enable students to achieve these standards. The literature reveals an inconsistent history of success with modeling education. These same studies point to a possible cognitive development component which might explain why some students succeeded and others failed. An environmental science course, rich in modeling experiences, was used to test both the extent to which knowledge of models and modeling could be improved over the course of one semester, and more importantly, to identify if cognitive ability was related to this improvement. In addition, nature of science knowledge, particularly related to theories and theory change, was also examined. Pretest and posttest results on modeling (SUMS) and nature of science (SUSSI), as well as data from the modeling activities themselves, was collected. Cognitive ability was measured (CTSR) as a covariate. Students' gain in six of seven categories of modeling knowledge was at least medium (Cohen's d >.5) and moderately correlated to CTSR for two of seven categories. Nature of science gains were smaller, although more strongly correlated with CTSR. Student success at creating a model was related to CTSR, significantly in three of five sub-categories. These results suggest that explicit, reflective experience with models can increase student knowledge of models and modeling (although higher cognitive ability students may have more success), but successfully creating models may depend more heavily on cognitive ability. This finding in particular has implications in the grade placement of modeling standards and curriculum chosen to help these students, particularly those with low cognitive ability, to meet the standards.

Basic self-knowledge and transparency.

PubMed

Borgoni, Cristina

2018-01-01

Cogito -like judgments, a term coined by Burge (1988), comprise thoughts such as, I am now thinking , I [hereby] judge that Los Angeles is at the same latitude as North Africa, or I [hereby] intend to go to the opera tonight. It is widely accepted that we form cogito -like judgments in an authoritative and not merely empirical manner. We have privileged self-knowledge of the mental state that is self-ascribed in a cogito -like judgment. Thus, models of self-knowledge that aim to explain privileged self-knowledge should have the resources to explain the special self-knowledge involved in cogito judgments. My objective in this paper is to examine whether a transparency model of self-knowledge (i.e., models based on Evans ' 1982 remarks) can provide such an explanation: granted that cogito judgments are paradigmatic cases of privileged self-knowledge, does the transparency procedure explain why this is so? The paper advances a negative answer, arguing that the transparency procedure cannot generate the type of thought constitutive of cogito judgments.

Knowledge Engineering as a Component of the Curriculum for Medical Cybernetists.

PubMed

Karas, Sergey; Konev, Arthur

2017-01-01

According to a new state educational standard, students who have chosen medical cybernetics as their major must develop a knowledge engineering competency. Previously, in the course "Clinical cybernetics" while practicing project-based learning students were designing automated workstations for medical personnel using client-server technology. The purpose of the article is to give insight into the project of a new educational module "Knowledge engineering". Students will acquire expert knowledge by holding interviews and conducting surveys, and then they will formalize it. After that, students will form declarative expert knowledge in a network model and analyze the knowledge graph. Expert decision making methods will be applied in software on the basis of a production model of knowledge. Project implementation will result not only in the development of analytical competencies among students, but also creation of a practically useful expert system based on student models to support medical decisions. Nowadays, this module is being tested in the educational process.

[The practice and discussion of the physical knowledge stepping into genetics teaching].

PubMed

Luo, Shen; Luo, Peigao

2014-09-01

Genetics, one of the core courses of biological field, play a key role in biology teaching and research. In fact, there exists high similarity between many genetic knowledge and physical knowledge. Due to strong abstract of genetic contents and the weak basis of genetics, some students lack of interests to study genetics. How to apply the strong physical knowledge which students had been learned in the middle school in genetics teaching is worthwhile for genetics teachers. In this paper, we would like to introduce an infiltrative teaching model on applying physical knowledge into genetic contents by establishing the intrinsic logistic relationship between physical knowledge and genetic knowledge. This teaching model could help students more deeply understand genetic knowledge and enhance students' self-studying ability as well as creating ability.

Arranging ISO 13606 archetypes into a knowledge base.

PubMed

Kopanitsa, Georgy

2014-01-01

To enable the efficient reuse of standard based medical data we propose to develop a higher level information model that will complement the archetype model of ISO 13606. This model will make use of the relationships that are specified in UML to connect medical archetypes into a knowledge base within a repository. UML connectors were analyzed for their ability to be applied in the implementation of a higher level model that will establish relationships between archetypes. An information model was developed using XML Schema notation. The model allows linking different archetypes of one repository into a knowledge base. Presently it supports several relationships and will be advanced in future.

Knowledge-driven genomic interactions: an application in ovarian cancer.

PubMed

Kim, Dokyoon; Li, Ruowang; Dudek, Scott M; Frase, Alex T; Pendergrass, Sarah A; Ritchie, Marylyn D

2014-01-01

Effective cancer clinical outcome prediction for understanding of the mechanism of various types of cancer has been pursued using molecular-based data such as gene expression profiles, an approach that has promise for providing better diagnostics and supporting further therapies. However, clinical outcome prediction based on gene expression profiles varies between independent data sets. Further, single-gene expression outcome prediction is limited for cancer evaluation since genes do not act in isolation, but rather interact with other genes in complex signaling or regulatory networks. In addition, since pathways are more likely to co-operate together, it would be desirable to incorporate expert knowledge to combine pathways in a useful and informative manner. Thus, we propose a novel approach for identifying knowledge-driven genomic interactions and applying it to discover models associated with cancer clinical phenotypes using grammatical evolution neural networks (GENN). In order to demonstrate the utility of the proposed approach, an ovarian cancer data from the Cancer Genome Atlas (TCGA) was used for predicting clinical stage as a pilot project. We identified knowledge-driven genomic interactions associated with cancer stage from single knowledge bases such as sources of pathway-pathway interaction, but also knowledge-driven genomic interactions across different sets of knowledge bases such as pathway-protein family interactions by integrating different types of information. Notably, an integration model from different sources of biological knowledge achieved 78.82% balanced accuracy and outperformed the top models with gene expression or single knowledge-based data types alone. Furthermore, the results from the models are more interpretable because they are framed in the context of specific biological pathways or other expert knowledge. The success of the pilot study we have presented herein will allow us to pursue further identification of models predictive of clinical cancer survival and recurrence. Understanding the underlying tumorigenesis and progression in ovarian cancer through the global view of interactions within/between different biological knowledge sources has the potential for providing more effective screening strategies and therapeutic targets for many types of cancer.

Optimal Financial Knowledge and Wealth Inequality*

PubMed Central

Lusardi, Annamaria; Michaud, Pierre-Carl; Mitchell, Olivia S.

2017-01-01

We show that financial knowledge is a key determinant of wealth inequality in a stochastic lifecycle model with endogenous financial knowledge accumulation, where financial knowledge enables individuals to better allocate lifetime resources in a world of uncertainty and imperfect insurance. Moreover, because of how the U.S. social insurance system works, better-educated individuals have most to gain from investing in financial knowledge. Our parsimonious specification generates substantial wealth inequality relative to a one-asset saving model and one where returns on wealth depend on portfolio composition alone. We estimate that 30–40 percent of retirement wealth inequality is accounted for by financial knowledge. PMID:28555088

A qualitative study of epistemologies and pedagogies of environmental practitioners in Maui, Hawai'i

NASA Astrophysics Data System (ADS)

Buczynski, Sandra C.

This dissertation presents a discussion of the knowledge systems and teaching styles of five environmental practitioners in Maui, Hawaii. The voices of the informants illustrate the beliefs, values, and priorities relevant to local environmental knowledge production and exchange, and are also used to provide a framework for models of epistemological and pedagogical practices. In this qualitative research, several models of local environmental knowledge emerged. The models include local environmental knowledge as a semiotic system, knowledge given and received from narrative sources, experiential based knowledge, and place and plant priorities in seeking and dispensing environmental information. The notion of what constitutes environmental knowledge was expanded through careful interpretation of the informant's voice. Several broad conclusions concerning local environmental knowledge emerged from this research. First, local environmental knowledge is formed through a long-term relationship between the practitioner, the land, and natural resources. Secondly, each of the environmental practitioner's local environmental knowledge is dynamic, plural and hybrid. And finally, transmission of the environmental practitioner's local environmental knowledge is integral to the life of the community as well as a component of their personal identities. Through these local environmental practitioners, endemic knowledge is shared, indigenous species are spared, traditional practices are passed down, customary ways are preserved, and unique ways of knowing and teaching are appreciated. 'A'ohe papu ka 'ike i ka halau ho'okahi. All knowledge is not taught in the same school. One can learn from many sources (Pukui, 1983: 24).

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

Development of a Knowledge Management Model for the Development of a Quality Public Sector Management System for the Office of the Primary Educational Service Area

ERIC Educational Resources Information Center

Khotbancha, Wijitra; Chantarasombat, Chalard; Sriampai, Anan

2015-01-01

The objectives of this research were: 1) to study the current situation and problem of Knowledge Management of the office of the primary education service area, 2) to develop a Knowledge Management model, 3) to study the success of the implementation of the Knowledge Management system. There were 25 persons in the target group. There were 2 kinds…

Early Math Trajectories: Low-Income Children's Mathematics Knowledge From Ages 4 to 11.

PubMed

Rittle-Johnson, Bethany; Fyfe, Emily R; Hofer, Kerry G; Farran, Dale C

2017-09-01

Early mathematics knowledge is a strong predictor of later academic achievement, but children from low-income families enter school with weak mathematics knowledge. An early math trajectories model is proposed and evaluated within a longitudinal study of 517 low-income American children from ages 4 to 11. This model includes a broad range of math topics, as well as potential pathways from preschool to middle grades mathematics achievement. In preschool, nonsymbolic quantity, counting, and patterning knowledge predicted fifth-grade mathematics achievement. By the end of first grade, symbolic mapping, calculation, and patterning knowledge were the important predictors. Furthermore, the first-grade predictors mediated the relation between preschool math knowledge and fifth-grade mathematics achievement. Findings support the early math trajectories model among low-income children. © 2016 The Authors. Child Development © 2016 Society for Research in Child Development, Inc.

Epistemological beliefs of physics undergraduate and graduate students and faculty in the context of a well-structured and an ill-structured problem

NASA Astrophysics Data System (ADS)

Mercan, Fatih C.

This study examines epistemological beliefs of physics undergraduate and graduate students and faculty in the context of solving a well-structured and an ill-structured problem. The data collection consisted of a think aloud problem solving session followed by a semi-structured interview conducted with 50 participants, 10 participants at freshmen, seniors, masters, PhD, and faculty levels. The data analysis involved (a) identification of the range of beliefs about knowledge in the context of the well-structured and the ill-structured problem solving, (b) construction of a framework that unites the individual beliefs identified in each problem context under the same conceptual base, and (c) comparisons of the problem contexts and expertise level groups using the framework. The results of the comparison of the contexts of the well-structured and the ill-structured problem showed that (a) authoritative beliefs about knowledge were expressed in the well-structured problem context, (b) relativistic and religious beliefs about knowledge were expressed in the ill-structured problem context, and (c) rational, empirical, modeling beliefs about knowledge were expressed in both problem contexts. The results of the comparison of the expertise level groups showed that (a) undergraduates expressed authoritative beliefs about knowledge more than graduate students and faculty did not express authoritative beliefs, (b) faculty expressed modeling beliefs about knowledge more than graduate students and undergraduates did not express modeling beliefs, and (c) there were no differences in rational, empirical, experiential, relativistic, and religious beliefs about knowledge among the expertise level groups. As the expertise level increased the number of participants who expressed authoritative beliefs about knowledge decreased and the number of participants who expressed modeling based beliefs about knowledge increased. The results of this study implied that existing developmental and cognitive models of personal epistemology can explain personal epistemology in physics to a limited extent, however, these models cannot adequately account for the variation of epistemological beliefs across problem contexts. Modeling beliefs about knowledge emerged as a part of personal epistemology and an indicator of epistemological sophistication, which do not develop until extensive experience in the field. Based on these findings, the researcher recommended providing opportunities for practicing model construction for students.

Combining patient journey modelling and visual multi-agent computer simulation: a framework to improving knowledge translation in a healthcare environment.

PubMed

Curry, Joanne; Fitzgerald, Anneke; Prodan, Ante; Dadich, Ann; Sloan, Terry

2014-01-01

This article focuses on a framework that will investigate the integration of two disparate methodologies: patient journey modelling and visual multi-agent simulation, and its impact on the speed and quality of knowledge translation to healthcare stakeholders. Literature describes patient journey modelling and visual simulation as discrete activities. This paper suggests that their combination and their impact on translating knowledge to practitioners are greater than the sum of the two technologies. The test-bed is ambulatory care and the goal is to determine if this approach can improve health services delivery, workflow, and patient outcomes and satisfaction. The multidisciplinary research team is comprised of expertise in patient journey modelling, simulation, and knowledge translation.

Examination of Mathematics Teachers' Pedagogical Content Knowledge of Probability

ERIC Educational Resources Information Center

Danisman, Sahin; Tanisli, Dilek

2017-01-01

The aim of this study is to explore the probability-related pedagogical content knowledge (PCK) of secondary school mathematics teachers in terms of content knowledge, curriculum knowledge, student knowledge, and knowledge of teaching methods and strategies. Case study design, a qualitative research model, was used in the study, and the…

Toward a comprehensive areal model of earthquake-induced landslides

USGS Publications Warehouse

Miles, S.B.; Keefer, D.K.

2009-01-01

This paper provides a review of regional-scale modeling of earthquake-induced landslide hazard with respect to the needs for disaster risk reduction and sustainable development. Based on this review, it sets out important research themes and suggests computing with words (CW), a methodology that includes fuzzy logic systems, as a fruitful modeling methodology for addressing many of these research themes. A range of research, reviewed here, has been conducted applying CW to various aspects of earthquake-induced landslide hazard zonation, but none facilitate comprehensive modeling of all types of earthquake-induced landslides. A new comprehensive areal model of earthquake-induced landslides (CAMEL) is introduced here that was developed using fuzzy logic systems. CAMEL provides an integrated framework for modeling all types of earthquake-induced landslides using geographic information systems. CAMEL is designed to facilitate quantitative and qualitative representation of terrain conditions and knowledge about these conditions on the likely areal concentration of each landslide type. CAMEL is highly modifiable and adaptable; new knowledge can be easily added, while existing knowledge can be changed to better match local knowledge and conditions. As such, CAMEL should not be viewed as a complete alternative to other earthquake-induced landslide models. CAMEL provides an open framework for incorporating other models, such as Newmark's displacement method, together with previously incompatible empirical and local knowledge. ?? 2009 ASCE.

Toward a Computational Model of Tutoring.

ERIC Educational Resources Information Center

Woolf, Beverly Park

1992-01-01

Discusses the integration of instructional science and computer science. Topics addressed include motivation for building knowledge-based systems; instructional design issues, including cognitive models, representing student intentions, and student models and error diagnosis; representing tutoring knowledge; building a tutoring system, including…

Knowledge represented using RDF semantic network in the concept of semantic web

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

Lukasova, A., E-mail: alena.lukasova@osu.cz; Vajgl, M., E-mail: marek.vajgl@osu.cz; Zacek, M., E-mail: martin.zacek@osu.cz

The RDF(S) model has been declared as the basic model to capture knowledge of the semantic web. It provides a common and flexible way to decompose composed knowledge to elementary statements, which can be represented by RDF triples or by RDF graph vectors. From the logical point of view, elements of knowledge can be expressed using at most binary predicates, which can be converted to RDF-triples or graph vectors. However, it is not able to capture implicit knowledge representable by logical formulas. This contribution shows how existing approaches (semantic networks and clausal form logic) can be combined together with RDFmore » to obtain RDF-compatible system with ability to represent implicit knowledge and inference over knowledge base.« less

Knowledge Representation and Ontologies

NASA Astrophysics Data System (ADS)

Grimm, Stephan

Knowledge representation and reasoning aims at designing computer systems that reason about a machine-interpretable representation of the world. Knowledge-based systems have a computational model of some domain of interest in which symbols serve as surrogates for real world domain artefacts, such as physical objects, events, relationships, etc. [1]. The domain of interest can cover any part of the real world or any hypothetical system about which one desires to represent knowledge for com-putational purposes. A knowledge-based system maintains a knowledge base, which stores the symbols of the computational model in the form of statements about the domain, and it performs reasoning by manipulating these symbols. Applications can base their decisions on answers to domain-relevant questions posed to a knowledge base.

Interrelationship of Knowledge, Interest, and Recall: Assessing a Model of Domain Learning.

ERIC Educational Resources Information Center

Alexander, Patricia A.; And Others

1995-01-01

Two experiments involving 125 college and graduate students examined the interrelationship of subject-matter knowledge, interest, and recall in the field of human immunology and biology and assessed cross-domain performance in physics. Patterns of knowledge, interest, and performance fit well with the premises of the Model of Domain Learning. (SLD)

A strategic systems perspective of organizational learning theory: models for a case study at the Jet Propulsion Laboratory

NASA Technical Reports Server (NTRS)

Neece, O.

2000-01-01

Organizational learning is an umbrella term that covers a variety of topics including; learning curves, productivity, organizational memory, organizational forgetting, knowledge transfer, knowledge sharing and knowledge creation. This treatise will review some of these theories in concert with a model of how organizations learn.

Knowledge Management in Sustainability Research Projects: Concepts, Effective Models, and Examples in a Multi-Stakeholder Environment

ERIC Educational Resources Information Center

Kaiser, David Brian; Köhler, Thomas; Weith, Thomas

2016-01-01

This article aims to sketch a conceptual design for an information and knowledge management system in sustainability research projects. The suitable frameworks to implement knowledge transfer models constitute social communities, because the mutual exchange and learning processes among all stakeholders promote key sustainable developments through…

Designing and Implementing an Integrated Technological Pedagogical Science Knowledge Framework for Science Teachers Professional Development

ERIC Educational Resources Information Center

Jimoyiannis, Athanassios

2010-01-01

This paper reports on the design and the implementation of the Technological Pedagogical Science Knowledge (TPASK), a new model for science teachers professional development built on an integrated framework determined by the Technological Pedagogical Content Knowledge (TPACK) model and the authentic learning approach. The TPASK curriculum…

Creativity an Ultimate Goal and Challenge for Education: A Response to Ghassib's Article

ERIC Educational Resources Information Center

Sisk, Dorothy A.

2010-01-01

This article presents the author's response to Hisham B. Ghassib's article entitled "Where Does Creativity Fit into a Productivist Industrial Model of Knowledge Production?" Ghassib (2010) outlines a Productivist Industrial Model of Knowledge Production, in which he calls the knowledge enterprise an industry in which creativity and innovation play…

A Conceptual Model for Teaching Critical Thinking in a Knowledge Economy

ERIC Educational Resources Information Center

Chadwick, Clifton

2011-01-01

Critical thinking, viewed as rational and analytic thinking, is crucial for participation in a knowledge economy and society. This article provides a brief presentation of the importance of teaching critical thinking in a knowledge economy; suggests a conceptual model for teaching thinking; examines research on the historical role of teachers in…

A Model to Assess the Behavioral Impacts of Consultative Knowledge Based Systems.

ERIC Educational Resources Information Center

Mak, Brenda; Lyytinen, Kalle

1997-01-01

This research model studies the behavioral impacts of consultative knowledge based systems (KBS). A study of graduate students explored to what extent their decisions were affected by user participation in updating the knowledge base; ambiguity of decision setting; routinization of usage; and source credibility of the expertise embedded in the…

The Result of Developing Secondary School Students' Public Conscience through Process-Knowledge Management in Thailand

ERIC Educational Resources Information Center

Homsin, Nawattakorn; Chantarasombat, Chalard; Yeamsang, Theerawatta

2015-01-01

This research uses Mixed-Methodology applied research and development together with participatory action research. The model is appropriate for the context environment. The participants were able to complete the learning activities in participatory forms of knowledge management, using the following five-step model: 1) Knowledge Identification, 2)…

Models of Lifelong Learning and the "Knowledge Society"

ERIC Educational Resources Information Center

Green, Andy

2006-01-01

Many of the current policy debates in Europe focus on what kind of "knowledge economy" or "knowledge society" would be best in the future if it is to combine both economic competitiveness and social cohesion. Should European economies move increasingly towards the so-called Anglo-Saxon model of flexible labour markets and high…

Knowledge Management in Preserving Ecosystems: The Case of Seoul

ERIC Educational Resources Information Center

Lee, Jeongseok

2009-01-01

This study explores the utility of employing knowledge management as a framework for understanding how public managers perform ecosystem management. It applies the grounded theory method to build a model. The model is generated by applying the concept of knowledge process to an investigation of how the urban ecosystem is publicly managed by civil…

Developing Statistical Knowledge for Teaching during Design-Based Research

ERIC Educational Resources Information Center

Groth, Randall E.

2017-01-01

Statistical knowledge for teaching is not precisely equivalent to statistics subject matter knowledge. Teachers must know how to make statistics understandable to others as well as understand the subject matter themselves. This dual demand on teachers calls for the development of viable teacher education models. This paper offers one such model,…

Knowledge discovery from data and Monte-Carlo DEA to evaluate technical efficiency of mental health care in small health areas

PubMed Central

García-Alonso, Carlos; Pérez-Naranjo, Leonor

2009-01-01

Introduction Knowledge management, based on information transfer between experts and analysts, is crucial for the validity and usability of data envelopment analysis (DEA). Aim To design and develop a methodology: i) to assess technical efficiency of small health areas (SHA) in an uncertainty environment, and ii) to transfer information between experts and operational models, in both directions, for improving expert’s knowledge. Method A procedure derived from knowledge discovery from data (KDD) is used to select, interpret and weigh DEA inputs and outputs. Based on KDD results, an expert-driven Monte-Carlo DEA model has been designed to assess the technical efficiency of SHA in Andalusia. Results In terms of probability, SHA 29 is the most efficient being, on the contrary, SHA 22 very inefficient. 73% of analysed SHA have a probability of being efficient (Pe) >0.9 and 18% <0.5. Conclusions Expert knowledge is necessary to design and validate any operational model. KDD techniques make the transfer of information from experts to any operational model easy and results obtained from the latter improve expert’s knowledge.

Knowledge management model for teleconsulting in telemedicine.

PubMed

Pico, Lilia Edith Aparicio; Cuenca, Orlando Rodriguez; Alvarez, Daniel José Salas; Salgado, Piere Augusto Peña

2008-01-01

The present article shows a study about requirements for teleconsulting in a telemedicine solution in order to create a knowledge management system. Several concepts have been found related to the term teleconsulting in telemedicine which will serve to clear up their corresponding applications, potentialities, and scope. Afterwards, different theories about the art state in knowledge management have been considered by exploring methodologies and architectures to establish the trends of knowledge management and the possibilities of using them in teleconsulting. Furthermore, local and international experiences have been examined to assess knowledge management systems focused on telemedicine. The objective of this study is to obtain a model for developing teleconsulting systems in Colombia because we have many health-information management systems but they don't offer telemedicine services for remote areas. In Colombia there are many people in rural areas with different necessities and they don't have medicine services, teleconsulting will be a good solution to this problem. Lastly, a model of a knowledge system is proposed for teleconsulting in telemedicine. The model has philosophical principles and architecture that shows the fundamental layers for its development.

Knowledge outcomes within rotational models of social work field education.

PubMed

Birkenmaier, Julie; Curley, Jami; Rowan, Noell L

2012-01-01

This study assessed knowledge outcomes among concurrent, concurrent/sequential, and sequential rotation models of field instruction. Posttest knowledge scores of students ( n = 231) in aging-related field education were higher for students who participated in the concurrent rotation model, and for those who completed field education at a long-term care facility. Scores were also higher for students in programs that infused a higher number of geriatric competencies in their curriculum. Recommendations are provided to programs considering rotation models of field education related to older adults.

The atmospheric boundary layer — advances in knowledge and application

NASA Astrophysics Data System (ADS)

Garratt, J. R.; Hess, G. D.; Physick, W. L.; Bougeault, P.

1996-02-01

We summarise major activities and advances in boundary-layer knowledge in the 25 years since 1970, with emphasis on the application of this knowledge to surface and boundary-layer parametrisation schemes in numerical models of the atmosphere. Progress in three areas is discussed: (i) the mesoscale modelling of selected phenomena; (ii) numerical weather prediction; and (iii) climate simulations. Future trends are identified, including the incorporation into models of advanced cloud schemes and interactive canopy schemes, and the nesting of high resolution boundary-layer schemes in global climate models.

Pragmatic User Model Implementation in an Intelligent Help System.

ERIC Educational Resources Information Center

Fernandez-Manjon, Baltasar; Fernandez-Valmayor, Alfredo; Fernandez-Chamizo, Carmen

1998-01-01

Describes Aran, a knowledge-based system designed to help users deal with problems related to Unix operation. Highlights include adaptation to the individual user; user modeling knowledge; stereotypes; content of the individual user model; instantiation, acquisition, and maintenance of the individual model; dynamic acquisition of objective and…

Representing, Running, and Revising Mental Models: A Computational Model

ERIC Educational Resources Information Center

Friedman, Scott; Forbus, Kenneth; Sherin, Bruce

2018-01-01

People use commonsense science knowledge to flexibly explain, predict, and manipulate the world around them, yet we lack computational models of how this commonsense science knowledge is represented, acquired, utilized, and revised. This is an important challenge for cognitive science: Building higher order computational models in this area will…

Supporting Students' Knowledge Transfer in Modeling Activities

ERIC Educational Resources Information Center

Piksööt, Jaanika; Sarapuu, Tago

2014-01-01

This study investigates ways to enhance secondary school students' knowledge transfer in complex science domains by implementing question prompts. Two samples of students applied two web-based models to study molecular genetics--the model of genetic code (n = 258) and translation (n = 245). For each model, the samples were randomly divided into…

Instructional Design Models: What a Revolution!

ERIC Educational Resources Information Center

Faryadi, Qais

2007-01-01

This review examines instructional design models and the construction of knowledge. It further explores to identify the chilling benefits of these models for the inputs and outputs of knowledge transfer. This assessment also attempts to define instructional design models through the eyes and the minds of renowned scholars as well as the most…

Nursing knowledge: hints from the placebo effect.

PubMed

Zanotti, Renzo; Chiffi, Daniele

2017-07-01

Nursing knowledge stems from a dynamic interplay between population-based scientific knowledge (the general) and specific clinical cases (the particular). We compared the 'cascade model of knowledge translation', also known as 'classical biomedical model' in clinical practice (in which knowledge gained at population level may be applied directly to a specific clinical context), with an emergentist model of knowledge translation. The structure and dynamics of nursing knowledge are outlined, adopting the distinction between epistemic and non-epistemic values. Then, a (moderately) emergentist approach to nursing knowledge is proposed, based on the assumption of a two-way flow from the general to the particular and vice versa. The case of the 'placebo effect' is analysed as an example of emergentist knowledge. The placebo effect is usually considered difficult to be explained within the classical biomedical model, and we underscore its importance in shaping nursing knowledge. In fact, nurses are primarily responsible for administering placebo in the clinical setting and have an essential role in promoting the placebo effect and reducing the nocebo effect. The beliefs responsible for the placebo effect are as follows: (1) interactive, because they depend on the relationship between patients and health care professionals; (2) situated, because they occur in a given clinical context related to certain rituals; and (3) grounded on higher order beliefs concerning what an individual thinks about the beliefs of others. It is essential to know the clinical context and to understand other people's beliefs to make sense of the placebo effect. The placebo effect only works when the (higher order) beliefs of doctors, nurses and patients interact in a given setting. Finally, we argue for a close relationship between placebo effect and nursing knowledge. © 2016 John Wiley & Sons Ltd.

Knowledge management for efficient quantitative analyses during regulatory reviews.

PubMed

Krudys, Kevin; Li, Fang; Florian, Jeffry; Tornoe, Christoffer; Chen, Ying; Bhattaram, Atul; Jadhav, Pravin; Neal, Lauren; Wang, Yaning; Gobburu, Joga; Lee, Peter I D

2011-11-01

Knowledge management comprises the strategies and methods employed to generate and leverage knowledge within an organization. This report outlines the activities within the Division of Pharmacometrics at the US FDA to effectively manage knowledge with the ultimate goal of improving drug development and advancing public health. The infrastructure required for pharmacometric knowledge management includes provisions for data standards, queryable databases, libraries of modeling tools, archiving of analysis results and reporting templates for effective communication. Two examples of knowledge management systems developed within the Division of Pharmacometrics are used to illustrate these principles. The benefits of sound knowledge management include increased productivity, allowing reviewers to focus on research questions spanning new drug applications, such as improved trial design and biomarker development. The future of knowledge management depends on the collaboration between the FDA and industry to implement data and model standards to enhance sharing and dissemination of knowledge.

Number-Knower Levels in Young Children: Insights from Bayesian Modeling

ERIC Educational Resources Information Center

Lee, Michael D.; Sarnecka, Barbara W.

2011-01-01

Lee and Sarnecka (2010) developed a Bayesian model of young children's behavior on the Give-N test of number knowledge. This paper presents two new extensions of the model, and applies the model to new data. In the first extension, the model is used to evaluate competing theories about the conceptual knowledge underlying children's behavior. One,…

Combining Modeling and Gaming for Predictive Analytics

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

Riensche, Roderick M.; Whitney, Paul D.

2012-08-22

Many of our most significant challenges involve people. While human behavior has long been studied, there are recent advances in computational modeling of human behavior. With advances in computational capabilities come increases in the volume and complexity of data that humans must understand in order to make sense of and capitalize on these modeling advances. Ultimately, models represent an encapsulation of human knowledge. One inherent challenge in modeling is efficient and accurate transfer of knowledge from humans to models, and subsequent retrieval. The simulated real-world environment of games presents one avenue for these knowledge transfers. In this paper we describemore » our approach of combining modeling and gaming disciplines to develop predictive capabilities, using formal models to inform game development, and using games to provide data for modeling.« less

Trust from the past: Bayesian Personalized Ranking based Link Prediction in Knowledge Graphs

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

Zhang, Baichuan; Choudhury, Sutanay; Al-Hasan, Mohammad

2016-02-01

Estimating the confidence for a link is a critical task for Knowledge Graph construction. Link prediction, or predicting the likelihood of a link in a knowledge graph based on prior state is a key research direction within this area. We propose a Latent Feature Embedding based link recommendation model for prediction task and utilize Bayesian Personalized Ranking based optimization technique for learning models for each predicate. Experimental results on large-scale knowledge bases such as YAGO2 show that our approach achieves substantially higher performance than several state-of-art approaches. Furthermore, we also study the performance of the link prediction algorithm in termsmore » of topological properties of the Knowledge Graph and present a linear regression model to reason about its expected level of accuracy.« less

A Biological Conception of Knowledge: One Problematic Consequence.

ERIC Educational Resources Information Center

Haroutunian, Sophie

1980-01-01

Piaget's use of the equilibrium model to define knowledge results in a cybernetic conception of knowledge that cannot explain how knowledge becomes possible. The knowledge that behaviors apply discriminately must be acquired, and cannot be programed, and therefore cannot be learned. (FG)

Pappas and Tepe's Pathways to Knowledge Model.

ERIC Educational Resources Information Center

Zimmerman, Nancy P.; Pappas, Marjorie L.; Tepe, Ann E.

2002-01-01

Describes the Pathways to Knowledge model for helping students achieve information literacy in library media programs. Discusses the searcher's thinking, information search or seeking, and instructional strategies; information skills; the six stages in the model, including appreciation, presearch, search, interpretation, communication, and…

Identifying and prioritizing the tools/techniques of knowledge management based on the Asian Productivity Organization Model (APO) to use in hospitals.

PubMed

Khajouei, Hamid; Khajouei, Reza

2017-12-01

Appropriate knowledge, correct information, and relevant data are vital in medical diagnosis and treatment systems. Knowledge Management (KM) through its tools/techniques provides a pertinent framework for decision-making in healthcare systems. The objective of this study was to identify and prioritize the KM tools/techniques that apply to hospital setting. This is a descriptive-survey study. Data were collected using a -researcher-made questionnaire that was developed based on experts' opinions to select the appropriate tools/techniques from 26 tools/techniques of the Asian Productivity Organization (APO) model. Questions were categorized into five steps of KM (identifying, creating, storing, sharing, and applying the knowledge) according to this model. The study population consisted of middle and senior managers of hospitals and managing directors of Vice-Chancellor for Curative Affairs in Kerman University of Medical Sciences in Kerman, Iran. The data were analyzed in SPSS v.19 using one-sample t-test. Twelve out of 26 tools/techniques of the APO model were identified as the tools applicable in hospitals. "Knowledge café" and "APO knowledge management assessment tool" with respective means of 4.23 and 3.7 were the most and the least applicable tools in the knowledge identification step. "Mentor-mentee scheme", as well as "voice and Voice over Internet Protocol (VOIP)" with respective means of 4.20 and 3.52 were the most and the least applicable tools/techniques in the knowledge creation step. "Knowledge café" and "voice and VOIP" with respective means of 3.85 and 3.42 were the most and the least applicable tools/techniques in the knowledge storage step. "Peer assist and 'voice and VOIP' with respective means of 4.14 and 3.38 were the most and the least applicable tools/techniques in the knowledge sharing step. Finally, "knowledge worker competency plan" and "knowledge portal" with respective means of 4.38 and 3.85 were the most and the least applicable tools/techniques in the knowledge application step. The results showed that 12 out of 26 tools in the APO model are appropriate for hospitals of which 11 are significantly applicable, and "storytelling" is marginally applicable. In this study, the preferred tools/techniques for implementation of each of the five KM steps in hospitals are introduced. Copyright © 2017 Elsevier B.V. All rights reserved.

Harnessing expert knowledge: Defining a Bayesian network decision model with limited data-Model structure for the vibration qualification problem

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

Rizzo, Davinia B.; Blackburn, Mark R.

As systems become more complex, systems engineers rely on experts to inform decisions. There are few experts and limited data in many complex new technologies. This challenges systems engineers as they strive to plan activities such as qualification in an environment where technical constraints are coupled with the traditional cost, risk, and schedule constraints. Bayesian network (BN) models provide a framework to aid systems engineers in planning qualification efforts with complex constraints by harnessing expert knowledge and incorporating technical factors. By quantifying causal factors, a BN model can provide data about the risk of implementing a decision supplemented with informationmore » on driving factors. This allows a systems engineer to make informed decisions and examine “what-if” scenarios. This paper discusses a novel process developed to define a BN model structure based primarily on expert knowledge supplemented with extremely limited data (25 data sets or less). The model was developed to aid qualification decisions—specifically to predict the suitability of six degrees of freedom (6DOF) vibration testing for qualification. The process defined the model structure with expert knowledge in an unbiased manner. Finally, validation during the process execution and of the model provided evidence the process may be an effective tool in harnessing expert knowledge for a BN model.« less

Harnessing expert knowledge: Defining a Bayesian network decision model with limited data-Model structure for the vibration qualification problem

DOE PAGES

Rizzo, Davinia B.; Blackburn, Mark R.

2018-03-30

As systems become more complex, systems engineers rely on experts to inform decisions. There are few experts and limited data in many complex new technologies. This challenges systems engineers as they strive to plan activities such as qualification in an environment where technical constraints are coupled with the traditional cost, risk, and schedule constraints. Bayesian network (BN) models provide a framework to aid systems engineers in planning qualification efforts with complex constraints by harnessing expert knowledge and incorporating technical factors. By quantifying causal factors, a BN model can provide data about the risk of implementing a decision supplemented with informationmore » on driving factors. This allows a systems engineer to make informed decisions and examine “what-if” scenarios. This paper discusses a novel process developed to define a BN model structure based primarily on expert knowledge supplemented with extremely limited data (25 data sets or less). The model was developed to aid qualification decisions—specifically to predict the suitability of six degrees of freedom (6DOF) vibration testing for qualification. The process defined the model structure with expert knowledge in an unbiased manner. Finally, validation during the process execution and of the model provided evidence the process may be an effective tool in harnessing expert knowledge for a BN model.« less

Knowledge Integration to Make Decisions About Complex Systems: Sustainability of Energy Production from Agriculture

ScienceCinema

Danuso, Francesco

2017-12-22

A major bottleneck for improving the governance of complex systems, rely on our ability to integrate different forms of knowledge into a decision support system (DSS). Preliminary aspects are the classification of different types of knowledge (a priori or general, a posteriori or specific, with uncertainty, numerical, textual, algorithmic, complete/incomplete, etc.), the definition of ontologies for knowledge management and the availability of proper tools like continuous simulation models, event driven models, statistical approaches, computational methods (neural networks, evolutionary optimization, rule based systems etc.) and procedure for textual documentation. Following these views at University of Udine, a computer language (SEMoLa, Simple, Easy Modelling Language) for knowledge integration has been developed.  SEMoLa can handle models, data, metadata and textual knowledge; it implements and extends the system dynamics ontology (Forrester, 1968; Jørgensen, 1994) in which systems are modelled by the concepts of material, group, state, rate, parameter, internal and external events and driving variables. As an example, a SEMoLa model to improve management and sustainability (economical, energetic, environmental) of the agricultural farms is presented. The model (X-Farm) simulates a farm in which cereal and forage yield, oil seeds, milk, calves and wastes can be sold or reused. X-Farm is composed by integrated modules describing fields (crop and soil), feeds and materials storage, machinery management, manpower  management, animal husbandry, economic and energetic balances, seed oil extraction, manure and wastes management, biogas production from animal wastes and biomasses.

Integrating local pastoral knowledge, participatory mapping, and species distribution modeling for risk assessment of invasive rubber vine (Cryptostegia grandiflora) in Ethiopia’s Afar region

USGS Publications Warehouse

Luizza, Matthew; Wakie, Tewodros; Evangelista, Paul; Jarnevich, Catherine S.

2016-01-01

The threats posed by invasive plants span ecosystems and economies worldwide. Local knowledge of biological invasions has proven beneficial for invasive species research, but to date no work has integrated this knowledge with species distribution modeling for invasion risk assessments. In this study, we integrated pastoral knowledge with Maxent modeling to assess the suitable habitat and potential impacts of invasive Cryptostegia grandiflora Robx. Ex R.Br. (rubber vine) in Ethiopia’s Afar region. We conducted focus groups with seven villages across the Amibara and Awash-Fentale districts. Pastoral knowledge revealed the growing threat of rubber vine, which to date has received limited attention in Ethiopia, and whose presence in Afar was previously unknown to our team. Rubber vine occurrence points were collected in the field with pastoralists and processed in Maxent with MODIS-derived vegetation indices, topographic data, and anthropogenic variables. We tested model fit using a jackknife procedure and validated the final model with an independent occurrence data set collected through participatory mapping activities with pastoralists. A Multivariate Environmental Similarity Surface analysis revealed areas with novel environmental conditions for future targeted surveys. Model performance was evaluated using area under the receiver-operating characteristic curve (AUC) and showed good fit across the jackknife models (average AUC = 0.80) and the final model (test AUC = 0.96). Our results reveal the growing threat rubber vine poses to Afar, with suitable habitat extending downstream of its current known location in the middle Awash River basin. Local pastoral knowledge provided important context for its rapid expansion due to acute changes in seasonality and habitat alteration, in addition to threats posed to numerous endemic tree species that provide critical provisioning ecosystem services. This work demonstrates the utility of integrating local ecological knowledge with species distribution modeling for early detection and targeted surveying of recently established invasive species.

Reusing Design Knowledge Based on Design Cases and Knowledge Map

ERIC Educational Resources Information Center

Yang, Cheng; Liu, Zheng; Wang, Haobai; Shen, Jiaoqi

2013-01-01

Design knowledge was reused for innovative design work to support designers with product design knowledge and help designers who lack rich experiences to improve their design capacity and efficiency. First, based on the ontological model of product design knowledge constructed by taxonomy, implicit and explicit knowledge was extracted from some…

Content-Related Knowledge of Biology Teachers from Secondary Schools: Structure and Learning Opportunities

ERIC Educational Resources Information Center

Großschedl, Jörg; Mahler, Daniela; Kleickmann, Thilo; Harms, Ute

2014-01-01

Teachers' content-related knowledge is a key factor influencing the learning progress of students. Different models of content-related knowledge have been proposed by educational researchers; most of them take into account three categories: content knowledge, pedagogical content knowledge, and curricular knowledge. As there is no consensus about…

Arranging ISO 13606 archetypes into a knowledge base using UML connectors.

PubMed

Kopanitsa, Georgy

2014-01-01

To enable the efficient reuse of standard based medical data we propose to develop a higher-level information model that will complement the archetype model of ISO 13606. This model will make use of the relationships that are specified in UML to connect medical archetypes into a knowledge base within a repository. UML connectors were analysed for their ability to be applied in the implementation of a higher-level model that will establish relationships between archetypes. An information model was developed using XML Schema notation. The model allows linking different archetypes of one repository into a knowledge base. Presently it supports several relationships and will be advanced in future.

System and method for knowledge based matching of users in a network

DOEpatents

Verspoor, Cornelia Maria [Santa Fe, NM; Sims, Benjamin Hayden [Los Alamos, NM; Ambrosiano, John Joseph [Los Alamos, NM; Cleland, Timothy James [Los Alamos, NM

2011-04-26

A knowledge-based system and methods to matchmaking and social network extension are disclosed. The system is configured to allow users to specify knowledge profiles, which are collections of concepts that indicate a certain topic or area of interest selected from an. The system utilizes the knowledge model as the semantic space within which to compare similarities in user interests. The knowledge model is hierarchical so that indications of interest in specific concepts automatically imply interest in more general concept. Similarity measures between profiles may then be calculated based on suitable distance formulas within this space.

Consulting as a Strategy for Knowledge Transfer

PubMed Central

Jacobson, Nora; Butterill, Dale; Goering, Paula

2005-01-01

Academic researchers who work on health policy and health services are expected to transfer knowledge to decision makers. Decision makers often do not, however, regard academics’ traditional ways of doing research and disseminating their findings as relevant or useful. This article argues that consulting can be a strategy for transferring knowledge between researchers and decision makers and is effective at promoting the “enlightenment” and “interactive” models of knowledge use. Based on three case studies, it develops a model of knowledge transfer–focused consulting that consists of six stages and four types of work. Finally, the article explores how knowledge is generated in consulting and identifies several classes of factors facilitating its use by decision makers. PMID:15960773

Diagnosis by integrating model-based reasoning with knowledge-based reasoning

NASA Technical Reports Server (NTRS)

Bylander, Tom

1988-01-01

Our research investigates how observations can be categorized by integrating a qualitative physical model with experiential knowledge. Our domain is diagnosis of pathologic gait in humans, in which the observations are the gait motions, muscle activity during gait, and physical exam data, and the diagnostic hypotheses are the potential muscle weaknesses, muscle mistimings, and joint restrictions. Patients with underlying neurological disorders typically have several malfunctions. Among the problems that need to be faced are: the ambiguity of the observations, the ambiguity of the qualitative physical model, correspondence of the observations and hypotheses to the qualitative physical model, the inherent uncertainty of experiential knowledge, and the combinatorics involved in forming composite hypotheses. Our system divides the work so that the knowledge-based reasoning suggests which hypotheses appear more likely than others, the qualitative physical model is used to determine which hypotheses explain which observations, and another process combines these functionalities to construct a composite hypothesis based on explanatory power and plausibility. We speculate that the reasoning architecture of our system is generally applicable to complex domains in which a less-than-perfect physical model and less-than-perfect experiential knowledge need to be combined to perform diagnosis.

Data and Model Integration Promoting Interdisciplinarity

NASA Astrophysics Data System (ADS)

Koike, T.

2014-12-01

It is very difficult to reflect accumulated subsystem knowledge into holistic knowledge. Knowledge about a whole system can rarely be introduced into a targeted subsystem. In many cases, knowledge in one discipline is inapplicable to other disciplines. We are far from resolving cross-disciplinary issues. It is critically important to establish interdisciplinarity so that scientific knowledge can transcend disciplines. We need to share information and develop knowledge interlinkages by building models and exchanging tools. We need to tackle a large increase in the volume and diversity of data from observing the Earth. The volume of data stored has exponentially increased. Previously, almost all of the large-volume data came from satellites, but model outputs occupy the largest volume in general. To address the large diversity of data, we should develop an ontology system for technical and geographical terms in coupling with a metadata design according to international standards. In collaboration between Earth environment scientists and IT group, we should accelerate data archiving by including data loading, quality checking and metadata registration, and enrich data-searching capability. DIAS also enables us to perform integrated research and realize interdisciplinarity. For example, climate change should be addressed in collaboration between the climate models, integrated assessment models including energy, economy, agriculture, health, and the models of adaptation, vulnerability, and human settlement and infrastructure. These models identify water as central to these systems. If a water expert can develop an interrelated system including each component, the integrated crisis can be addressed by collaboration with various disciplines. To realize this purpose, we are developing a water-related data- and model-integration system called a water cycle integrator (WCI).

Active vision and image/video understanding with decision structures based on the network-symbolic models

NASA Astrophysics Data System (ADS)

Kuvich, Gary

2003-08-01

Vision is a part of a larger information system that converts visual information into knowledge structures. These structures drive vision process, resolve ambiguity and uncertainty via feedback projections, and provide image understanding that is an interpretation of visual information in terms of such knowledge models. The ability of human brain to emulate knowledge structures in the form of networks-symbolic models is found. And that means an important shift of paradigm in our knowledge about brain from neural networks to "cortical software". Symbols, predicates and grammars naturally emerge in such active multilevel hierarchical networks, and logic is simply a way of restructuring such models. Brain analyzes an image as a graph-type decision structure created via multilevel hierarchical compression of visual information. Mid-level vision processes like clustering, perceptual grouping, separation of figure from ground, are special kinds of graph/network transformations. They convert low-level image structure into the set of more abstract ones, which represent objects and visual scene, making them easy for analysis by higher-level knowledge structures. Higher-level vision phenomena are results of such analysis. Composition of network-symbolic models works similar to frames and agents, combines learning, classification, analogy together with higher-level model-based reasoning into a single framework. Such models do not require supercomputers. Based on such principles, and using methods of Computational intelligence, an Image Understanding system can convert images into the network-symbolic knowledge models, and effectively resolve uncertainty and ambiguity, providing unifying representation for perception and cognition. That allows creating new intelligent computer vision systems for robotic and defense industries.

The Misidentified Identifiability Problem of Bayesian Knowledge Tracing

ERIC Educational Resources Information Center

Doroudi, Shayan; Brunskill, Emma

2017-01-01

In this paper, we investigate two purported problems with Bayesian Knowledge Tracing (BKT), a popular statistical model of student learning: "identifiability" and "semantic model degeneracy." In 2007, Beck and Chang stated that BKT is susceptible to an "identifiability problem"--various models with different…

National Models for Continuing Professional Development: The Challenges of Twenty-First-Century Knowledge Management

ERIC Educational Resources Information Center

Leask, Marilyn; Younie, Sarah

2013-01-01

If teacher quality is the most critical factor in improving educational outcomes, then why is so little attention drawn to the knowledge and evidence base available to support teachers in improving the quality of their professional knowledge? This paper draws together findings from a range of sources to propose national models for continuing…

A Model of Knowledge Based Information Retrieval with Hierarchical Concept Graph.

ERIC Educational Resources Information Center

Kim, Young Whan; Kim, Jin H.

1990-01-01

Proposes a model of knowledge-based information retrieval (KBIR) that is based on a hierarchical concept graph (HCG) which shows relationships between index terms and constitutes a hierarchical thesaurus as a knowledge base. Conceptual distance between a query and an object is discussed and the use of Boolean operators is described. (25…

Effective Tutorial Ontology Modeling on Organic Rice Farming for Non-Science & Technology Educated Farmers Using Knowledge Engineering

ERIC Educational Resources Information Center

Yanchinda, Jirawit; Chakpitak, Nopasit; Yodmongkol, Pitipong

2015-01-01

Knowledge of the appropriate technologies for sustainable development projects has encouraged grass roots development, which has in turn promoted sustainable and successful community development, which a requirement is to share and reuse this knowledge effectively. This research aims to propose a tutorial ontology effectiveness modeling on organic…

Momentum Concept in the Process of Knowledge Construction

ERIC Educational Resources Information Center

Ergul, N. Remziye

2013-01-01

Abstraction is one of the methods for learning knowledge with using mental processes that cannot be obtained through experiment and observation. RBC model that is based on abstraction in the process of creating knowledge is directly related to mental processes. In this study, the RBC model is used for the high school students' processes of…

The Application of SECI Model as a Framework of Knowledge Creation in Virtual Learning: Case Study of IUST Virtual Classes

ERIC Educational Resources Information Center

Hosseini, Seyede Mehrnoush

2011-01-01

The research aims to define SECI model of knowledge creation (socialization, externalization, combination, and internalization) as a framework of Virtual class management which can lead to better online teaching-learning mechanisms as well as knowledge creation. It has used qualitative research methodology including researcher's close observation…

The Development Model of Knowledge Management via Web-Based Learning to Enhance Pre-Service Teacher's Competency

ERIC Educational Resources Information Center

Rampai, Nattaphon; Sopeerak, Saroch

2011-01-01

This research explores that the model of knowledge management and web technology for teachers' professional development as well as its impact in the classroom on learning and teaching, especially in pre-service teacher's competency and practices that refer to knowledge creating, analyzing, nurturing, disseminating, and optimizing process as part…

Challenges in Mentoring Software Development Projects in the High School: Analysis According to Shulman's Teacher Knowledge Base Model

ERIC Educational Resources Information Center

Meerbaum-Salant, Orni; Hazzan, Orit

2009-01-01

This paper focuses on challenges in mentoring software development projects in the high school and analyzes difficulties encountered by Computer Science teachers in the mentoring process according to Shulman's Teacher Knowledge Base Model. The main difficulties that emerged from the data analysis belong to the following knowledge sources of…

The Transfer of Content Knowledge in a Cascade Model of Professional Development

ERIC Educational Resources Information Center

Turner, Fay; Brownhill, Simon; Wilson, Elaine

2017-01-01

A cascade model of professional development presents a particular risk that "knowledge" promoted in a programme will be diluted or distorted as it passes from originators of the programme to local trainers and then to the target teachers. Careful monitoring of trainers' and teachers' knowledge as it is transferred through the system is…

Domain and Specification Models for Software Engineering

NASA Technical Reports Server (NTRS)

Iscoe, Neil; Liu, Zheng-Yang; Feng, Guohui

1992-01-01

This paper discusses our approach to representing application domain knowledge for specific software engineering tasks. Application domain knowledge is embodied in a domain model. Domain models are used to assist in the creation of specification models. Although many different specification models can be created from any particular domain model, each specification model is consistent and correct with respect to the domain model. One aspect of the system-hierarchical organization is described in detail.

Interactive knowledge discovery with the doctor-in-the-loop: a practical example of cerebral aneurysms research.

PubMed

Girardi, Dominic; Küng, Josef; Kleiser, Raimund; Sonnberger, Michael; Csillag, Doris; Trenkler, Johannes; Holzinger, Andreas

2016-09-01

Established process models for knowledge discovery find the domain-expert in a customer-like and supervising role. In the field of biomedical research, it is necessary to move the domain-experts into the center of this process with far-reaching consequences for both their research output and the process itself. In this paper, we revise the established process models for knowledge discovery and propose a new process model for domain-expert-driven interactive knowledge discovery. Furthermore, we present a research infrastructure which is adapted to this new process model and demonstrate how the domain-expert can be deeply integrated even into the highly complex data-mining process and data-exploration tasks. We evaluated this approach in the medical domain for the case of cerebral aneurysms research.

Computer-Assisted Simulation Methods of Learning Process

ERIC Educational Resources Information Center

Mayer, Robert V.

2015-01-01

In this article we analyse: 1) one-component models of training; 2) the multi-component models considering transition of weak knowledge in strong and vice versa; and 3) the models considering change of working efficiency of the pupil during the day. The results of imitating modeling are presented, graphs of dependences of the pupil's knowledge on…

Elementary Preservice Teachers' and Elementary Inservice Teachers' Knowledge of Mathematical Modeling

ERIC Educational Resources Information Center

Schwerdtfeger, Sara

2017-01-01

This study examined the differences in knowledge of mathematical modeling between a group of elementary preservice teachers and a group of elementary inservice teachers. Mathematical modeling has recently come to the forefront of elementary mathematics classrooms because of the call to add mathematical modeling tasks in mathematics classes through…

The DAB model of drawing processes

NASA Technical Reports Server (NTRS)

Hochhaus, Larry W.

1989-01-01

The problem of automatic drawing was investigated in two ways. First, a DAB model of drawing processes was introduced. DAB stands for three types of knowledge hypothesized to support drawing abilities, namely, Drawing Knowledge, Assimilated Knowledge, and Base Knowledge. Speculation concerning the content and character of each of these subsystems of the drawing process is introduced and the overall adequacy of the model is evaluated. Second, eight experts were each asked to understand six engineering drawings and to think aloud while doing so. It is anticipated that a concurrent protocol analysis of these interviews can be carried out in the future. Meanwhile, a general description of the videotape database is provided. In conclusion, the DAB model was praised as a worthwhile first step toward solution of a difficult problem, but was considered by and large inadequate to the challenge of automatic drawing. Suggestions for improvements on the model were made.

When one model is not enough: combining epistemic tools in systems biology.

PubMed

Green, Sara

2013-06-01

In recent years, the philosophical focus of the modeling literature has shifted from descriptions of general properties of models to an interest in different model functions. It has been argued that the diversity of models and their correspondingly different epistemic goals are important for developing intelligible scientific theories (Leonelli, 2007; Levins, 2006). However, more knowledge is needed on how a combination of different epistemic means can generate and stabilize new entities in science. This paper will draw on Rheinberger's practice-oriented account of knowledge production. The conceptual repertoire of Rheinberger's historical epistemology offers important insights for an analysis of the modelling practice. I illustrate this with a case study on network modeling in systems biology where engineering approaches are applied to the study of biological systems. I shall argue that the use of multiple representational means is an essential part of the dynamic of knowledge generation. It is because of-rather than in spite of-the diversity of constraints of different models that the interlocking use of different epistemic means creates a potential for knowledge production. Copyright © 2013 Elsevier Ltd. All rights reserved.

Learning a Health Knowledge Graph from Electronic Medical Records.

PubMed

Rotmensch, Maya; Halpern, Yoni; Tlimat, Abdulhakim; Horng, Steven; Sontag, David

2017-07-20

Demand for clinical decision support systems in medicine and self-diagnostic symptom checkers has substantially increased in recent years. Existing platforms rely on knowledge bases manually compiled through a labor-intensive process or automatically derived using simple pairwise statistics. This study explored an automated process to learn high quality knowledge bases linking diseases and symptoms directly from electronic medical records. Medical concepts were extracted from 273,174 de-identified patient records and maximum likelihood estimation of three probabilistic models was used to automatically construct knowledge graphs: logistic regression, naive Bayes classifier and a Bayesian network using noisy OR gates. A graph of disease-symptom relationships was elicited from the learned parameters and the constructed knowledge graphs were evaluated and validated, with permission, against Google's manually-constructed knowledge graph and against expert physician opinions. Our study shows that direct and automated construction of high quality health knowledge graphs from medical records using rudimentary concept extraction is feasible. The noisy OR model produces a high quality knowledge graph reaching precision of 0.85 for a recall of 0.6 in the clinical evaluation. Noisy OR significantly outperforms all tested models across evaluation frameworks (p < 0.01).

Knowledge diffusion in complex networks by considering time-varying information channels

NASA Astrophysics Data System (ADS)

Zhu, He; Ma, Jing

2018-03-01

In this article, based on a model of epidemic spreading, we explore the knowledge diffusion process with an innovative mechanism for complex networks by considering time-varying information channels. To cover the knowledge diffusion process in homogeneous and heterogeneous networks, two types of networks (the BA network and the ER network) are investigated. The mean-field theory is used to theoretically draw the knowledge diffusion threshold. Numerical simulation demonstrates that the knowledge diffusion threshold is almost linearly correlated with the mean of the activity rate. In addition, under the influence of the activity rate and distinct from the classic Susceptible-Infected-Susceptible (SIS) model, the density of knowers almost linearly grows with the spreading rate. Finally, in consideration of the ubiquitous mechanism of innovation, we further study the evolution of knowledge in our proposed model. The results suggest that compared with the effect of the spreading rate, the average knowledge version of the population is affected more by the innovation parameter and the mean of the activity rate. Furthermore, in the BA network, the average knowledge version of individuals with higher degree is always newer than those with lower degree.

Distinguishing Models of Professional Development: The Case of an Adaptive Model's Impact on Teachers' Knowledge, Instruction, and Student Achievement

ERIC Educational Resources Information Center

Koellner, Karen; Jacobs, Jennifer

2015-01-01

We posit that professional development (PD) models fall on a continuum from highly adaptive to highly specified, and that these constructs provide a productive way to characterize and distinguish among models. The study reported here examines the impact of an adaptive mathematics PD model on teachers' knowledge and instructional practices as well…

Government, industry, and university partnerships: A model for the knowledge age

NASA Astrophysics Data System (ADS)

Varner, Michael O.

1996-03-01

New technologies are transforming the industrial economy into a marketplace driven by information and knowledge. The depth, breadth, and rate of technology development, however, overwhelms our ability to absorb, process, and recall new information. Moreover, the bright future enabled by the knowledge age cannot be realized without the development of new organizational models and philosophies. This paper discusses the necessity for business, government, and universities to create inter-institutional partnerships in order to accommodate change and flourish in the knowledge age.

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.

A Methodology for Multiple Rule System Integration and Resolution Within a Singular Knowledge Base

NASA Technical Reports Server (NTRS)

Kautzmann, Frank N., III

1988-01-01

Expert Systems which support knowledge representation by qualitative modeling techniques experience problems, when called upon to support integrated views embodying description and explanation, especially when other factors such as multiple causality, competing rule model resolution, and multiple uses of knowledge representation are included. A series of prototypes are being developed to demonstrate the feasibility of automating the process of systems engineering, design and configuration, and diagnosis and fault management. A study involves not only a generic knowledge representation; it must also support multiple views at varying levels of description and interaction between physical elements, systems, and subsystems. Moreover, it will involve models of description and explanation for each level. This multiple model feature requires the development of control methods between rule systems and heuristics on a meta-level for each expert system involved in an integrated and larger class of expert system. The broadest possible category of interacting expert systems is described along with a general methodology for the knowledge representation and control of mutually exclusive rule systems.

Pharmacy Educator Motives to Pursue Pedagogical Knowledge.

PubMed

Baia, Patricia; Strang, Aimee F

2016-10-25

Objective. To investigate motives of pharmacy educators who pursue pedagogical knowledge through professional development programs and to develop a model of motivation to inform future development. Methods. A mixed-methods approach was used to study both qualitative and quantitative data. Written narratives, postmodule quizzes, and survey data were collected during a 5-year period (2010-2014) from pharmacy educators who participated in an online professional development program titled Helping Educators Learn Pedagogy (HELP). Grounded theory was used to create a model of motivation for why pharmacy educators might pursue pedagogical knowledge. Results. Participants reported being driven intrinsically by a passion for their own learning (self-centered motivation) and by the need to improve student learning (student-centered motivation) and extrinsically by program design, funding, and administrator encouragement. Conclusion. A new model of pharmacy educator motivation to pursue pedagogy knowledge, Pedagogical Knowledge Acquisition Theory (PKAT), emerged as a blended intrinsic and extrinsic model, which may have value in developing future professional development programs.

Pharmacy Educator Motives to Pursue Pedagogical Knowledge

PubMed Central

Strang, Aimee F.

2016-01-01

Objective. To investigate motives of pharmacy educators who pursue pedagogical knowledge through professional development programs and to develop a model of motivation to inform future development. Methods. A mixed-methods approach was used to study both qualitative and quantitative data. Written narratives, postmodule quizzes, and survey data were collected during a 5-year period (2010-2014) from pharmacy educators who participated in an online professional development program titled Helping Educators Learn Pedagogy (HELP). Grounded theory was used to create a model of motivation for why pharmacy educators might pursue pedagogical knowledge. Results. Participants reported being driven intrinsically by a passion for their own learning (self-centered motivation) and by the need to improve student learning (student-centered motivation) and extrinsically by program design, funding, and administrator encouragement. Conclusion. A new model of pharmacy educator motivation to pursue pedagogy knowledge, Pedagogical Knowledge Acquisition Theory (PKAT), emerged as a blended intrinsic and extrinsic model, which may have value in developing future professional development programs. PMID:27899828

Conceptual Model-Based Systems Biology: Mapping Knowledge and Discovering Gaps in the mRNA Transcription Cycle

PubMed Central

Somekh, Judith; Choder, Mordechai; Dori, Dov

2012-01-01

We propose a Conceptual Model-based Systems Biology framework for qualitative modeling, executing, and eliciting knowledge gaps in molecular biology systems. The framework is an adaptation of Object-Process Methodology (OPM), a graphical and textual executable modeling language. OPM enables concurrent representation of the system's structure—the objects that comprise the system, and behavior—how processes transform objects over time. Applying a top-down approach of recursively zooming into processes, we model a case in point—the mRNA transcription cycle. Starting with this high level cell function, we model increasingly detailed processes along with participating objects. Our modeling approach is capable of modeling molecular processes such as complex formation, localization and trafficking, molecular binding, enzymatic stimulation, and environmental intervention. At the lowest level, similar to the Gene Ontology, all biological processes boil down to three basic molecular functions: catalysis, binding/dissociation, and transporting. During modeling and execution of the mRNA transcription model, we discovered knowledge gaps, which we present and classify into various types. We also show how model execution enhances a coherent model construction. Identification and pinpointing knowledge gaps is an important feature of the framework, as it suggests where research should focus and whether conjectures about uncertain mechanisms fit into the already verified model. PMID:23308089

Distributed, cooperating knowledge-based systems

NASA Technical Reports Server (NTRS)

Truszkowski, Walt

1991-01-01

Some current research in the development and application of distributed, cooperating knowledge-based systems technology is addressed. The focus of the current research is the spacecraft ground operations environment. The underlying hypothesis is that, because of the increasing size, complexity, and cost of planned systems, conventional procedural approaches to the architecture of automated systems will give way to a more comprehensive knowledge-based approach. A hallmark of these future systems will be the integration of multiple knowledge-based agents which understand the operational goals of the system and cooperate with each other and the humans in the loop to attain the goals. The current work includes the development of a reference model for knowledge-base management, the development of a formal model of cooperating knowledge-based agents, the use of testbed for prototyping and evaluating various knowledge-based concepts, and beginning work on the establishment of an object-oriented model of an intelligent end-to-end (spacecraft to user) system. An introductory discussion of these activities is presented, the major concepts and principles being investigated are highlighted, and their potential use in other application domains is indicated.

Energy literacy of Indiana high school practical arts and vocational teachers

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

Emshousen, F.W. Jr.

The purpose of the study was to develop an energy knowledge examination, investigate the extent high school teachers of home economics, agriculture, and industrial arts differ in their knowledge of energy, and to ascertain the extent their knowledge of energy differs with personal, educational, and geographic characteristics. Based upon literature review, a subject model was structured according to Bloom's (1956) taxonomy category of Knowledge and Hauenstein's (1972) procedure for classifying knowledges. Energy experts critically evaluated this model, which after refinement, was used to develop an Energy Knowledge Examination. The model consisted of six primary elements: sources, uses, costs, conservation, conversion,more » and policy issues. Energy experts reviewed items for accuracy, relevance, reading level, and clarity. The final instrument (65 multiple choice questions), was administered to a stratified random sample of Indiana public high school (IPHS) teachers from selected disciplines. Findings revealed significant biases among energy experts regarding relevance of specific subject content to the needs of teachers and students. Significant differences in the energy knowledge of IPHS teachers existed only in specific areas of the subject.« less

Knowledge work productivity effect on quality of knowledge work in software development process in SME

NASA Astrophysics Data System (ADS)

Yusoff, Mohd Zairol; Mahmuddin, Massudi; Ahmad, Mazida

2016-08-01

Knowledge and skill are necessary to develop the capability of knowledge workers. However, there is very little understanding of what the necessary knowledge work (KW) is, and how they influence the quality of knowledge work or knowledge work productivity (KWP) in software development process, including that in small and medium-sized (SME) enterprise. The SME constitutes a major part of the economy and it has been relatively unsuccessful in developing KWP. Accordingly, this paper seeks to explore the influencing dimensions of KWP that effect on the quality of KW in SME environment. First, based on the analysis of the existing literatures, the key characteristics of KW productivity are defined. Second, the conceptual model is proposed, which explores the dimensions of the KWP and its quality. This study analyses data collected from 150 respondents (based on [1], who involve in SME in Malaysia and validates the models by using structural equation modeling (SEM). The results provide an analysis of the effect of KWP on the quality of KW and business success, and have a significant relevance for both research and practice in the SME

Event-related potentials in response to violations of content and temporal event knowledge.

PubMed

Drummer, Janna; van der Meer, Elke; Schaadt, Gesa

2016-01-08

Scripts that store knowledge of everyday events are fundamentally important for managing daily routines. Content event knowledge (i.e., knowledge about which events belong to a script) and temporal event knowledge (i.e., knowledge about the chronological order of events in a script) constitute qualitatively different forms of knowledge. However, there is limited information about each distinct process and the time course involved in accessing content and temporal event knowledge. Therefore, we analyzed event-related potentials (ERPs) in response to either correctly presented event sequences or event sequences that contained a content or temporal error. We found an N400, which was followed by a posteriorly distributed P600 in response to content errors in event sequences. By contrast, we did not find an N400 but an anteriorly distributed P600 in response to temporal errors in event sequences. Thus, the N400 seems to be elicited as a response to a general mismatch between an event and the established event model. We assume that the expectancy violation of content event knowledge, as indicated by the N400, induces the collapse of the established event model, a process indicated by the posterior P600. The expectancy violation of temporal event knowledge is assumed to induce an attempt to reorganize the event model in working memory, a process indicated by the frontal P600. Copyright © 2015 Elsevier Ltd. All rights reserved.

Getting Mental Models and Computer Models to Cooperate

NASA Technical Reports Server (NTRS)

Sheridan, T. B.; Roseborough, J.; Charney, L.; Mendel, M.

1984-01-01

A qualitative theory of supervisory control is outlined wherein the mental models of one or more human operators are related to the knowledge representations within automatic controllers (observers, estimators) and operator decision aids (expert systems, advice-givers). Methods of quantifying knowledge and the calibration of one knowledge representation to another (human, computer, or objective truth) are discussed. Ongoing experiments in the use of decision aids for exploring one's own objective function or exploring system constraints and control strategies are described.

Knowledge-Based Planning Model for Courses of Action Generation,

DTIC Science & Technology

1986-04-07

AO-AIS 608 KNOWLEDGE-BASED PLANNING MODEL FOR COURSES OF ACTION mJI OENERATION(U) ARMY MAR COLL CARLISLE BARRACKS PA USI FE D R COLLINS ET AL. 97APR...agencies. This document may not be released for open publication until it has been cleared by the appropriate military service or government agency. 00 DTIC...I ELECTE KNOWLEDGE-BASED PLANNING MODEL C AUG 5~ FOR COURSES OF ACTION GENERATION DD BY COLONEL D. R. COLLINS LIEUTENANT COLONEL(P) T. A. BAUCUM

Origins of Knowledge: Insights from Precocial Species.

PubMed

Versace, Elisabetta; Vallortigara, Giorgio

2015-01-01

Behavioral responses are influenced by knowledge acquired during the lifetime of an individual and by predispositions transmitted across generations. Establishing the origin of knowledge and the role of the unlearned component is a challenging task, given that both learned and unlearned knowledge can orient perception, learning, and the encoding of environmental features since the first stages of life. Ethical and practical issues constrain the investigation of unlearned knowledge in altricial species, including human beings. On the contrary, precocial animals can be tested on a wide range of tasks and capabilities immediately after birth and in controlled rearing conditions. Insects and precocial avian species are very convenient models to dissect the knowledge systems that enable young individuals to cope with their environment in the absence of specific previous experience. We present the state of the art of research on the origins of knowledge that comes from different models and disciplines. Insects have been mainly used to investigate unlearned sensory preferences and prepared learning mechanisms. The relative simplicity of the neural system and fast life cycle of insects make them ideal models to investigate the neural circuitry and evolutionary dynamics of unlearned traits. Among avian species, chicks of the domestic fowl have been the focus of many studies, and showed to possess unlearned knowledge in the sensory, physical, spatial, numerical and social domains. Solid evidence shows the existence of unlearned knowledge in different domains in several species, from sensory and social preferences to the left-right representation of the mental number line. We show how non-mammalian models of cognition, and in particular precocial species, can shed light into the adaptive value and evolutionary history of unlearned knowledge.

Model-based software design

NASA Technical Reports Server (NTRS)

Iscoe, Neil; Liu, Zheng-Yang; Feng, Guohui; Yenne, Britt; Vansickle, Larry; Ballantyne, Michael

1992-01-01

Domain-specific knowledge is required to create specifications, generate code, and understand existing systems. Our approach to automating software design is based on instantiating an application domain model with industry-specific knowledge and then using that model to achieve the operational goals of specification elicitation and verification, reverse engineering, and code generation. Although many different specification models can be created from any particular domain model, each specification model is consistent and correct with respect to the domain model.

For Performance through Learning, Knowledge Management Is Critical Practice

ERIC Educational Resources Information Center

Gorelick, Carol; Tantawy-Monsou, Brigitte

2005-01-01

Purpose: This paper proposes that knowledge management is a system that integrates people, process and technology for sustainable results by increasing performance through learning. Definitions of knowledge, knowledge management and performance serve as a foundation. Design/methodology/approach: The model for the knowledge era proposed in this…

Structural and Informal Knowledge Acquisition and Dissemination in Organizational Learning: An Exploratory Analysis

ERIC Educational Resources Information Center

Hoe, Siu Loon; McShane, Steven

2010-01-01

Purpose: The topic of organizational learning is populated with many theories and models; many relate to the enduring organizational learning framework consisting of knowledge acquisition, knowledge dissemination, and knowledge use. However, most of the research either emphasizes structural knowledge acquisition and dissemination as a composite…

A Portal of Educational Resources: Providing Evidence for Matching Pedagogy with Technology

ERIC Educational Resources Information Center

Di Blas, Nicoletta; Fiore, Alessandro; Mainetti, Luca; Vergallo, Roberto; Paolini, Paolo

2014-01-01

The TPACK (Technology, Pedagogy and Content Knowledge) model presents the three types of knowledge that are necessary to implement a successful technology-based educational activity. It highlights how the intersections between TPK (Technological Pedagogical Knowledge), PCK (Pedagogical Content Knowledge) and TCK (Technological Content Knowledge)…

Relationships between Organizational Trust, Knowledge Transfer, Knowledge Creation, and Firm's Innovativeness

ERIC Educational Resources Information Center

Sankowska, Anna

2013-01-01

Purpose: This study seeks to provide empirical evidence of relationships between organizational trust, knowledge transfer, creation and innovativeness at the firm level. It aims to hypothesize a mediational model implying that organizational trust is related to knowledge transfer, which will, in turn, enhance knowledge creation, thereby…

Analysing Teacher Knowledge for Technology Education in Primary Schools

ERIC Educational Resources Information Center

Rohaan, Ellen J.; Taconis, Ruurd; Jochems, Wim M. G.

2012-01-01

Teacher knowledge guides a teacher's behaviour in the classroom. Teacher knowledge for technology education is generally assumed to play an important role in affecting pupils' learning in technology. There are an abundant number of teacher knowledge models that visualise different domains of teacher knowledge, but clear empirical evidence on how…

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.

PSYCHE: An Object-Oriented Approach to Simulating Medical Education

PubMed Central

Mullen, Jamie A.

1990-01-01

Traditional approaches to computer-assisted instruction (CAI) do not provide realistic simulations of medical education, in part because they do not utilize heterogeneous knowledge bases for their source of domain knowledge. PSYCHE, a CAI program designed to teach hypothetico-deductive psychiatric decision-making to medical students, uses an object-oriented implementation of an intelligent tutoring system (ITS) to model the student, domain expert, and tutor. It models the transactions between the participants in complex transaction chains, and uses heterogeneous knowledge bases to represent both domain and procedural knowledge in clinical medicine. This object-oriented approach is a flexible and dynamic approach to modeling, and represents a potentially valuable tool for the investigation of medical education and decision-making.

Middle-School Science Students' Scientific Modelling Performances Across Content Areas and Within a Learning Progression

NASA Astrophysics Data System (ADS)

Bamberger, Yael M.; Davis, Elizabeth A.

2013-01-01

This paper focuses on students' ability to transfer modelling performances across content areas, taking into consideration their improvement of content knowledge as a result of a model-based instruction. Sixty-five sixth grade students of one science teacher in an urban public school in the Midwestern USA engaged in scientific modelling practices that were incorporated into a curriculum focused on the nature of matter. Concept-process models were embedded in the curriculum, as well as emphasis on meta-modelling knowledge and modelling practices. Pre-post test items that required drawing scientific models of smell, evaporation, and friction were analysed. The level of content understanding was coded and scored, as were the following elements of modelling performance: explanation, comparativeness, abstraction, and labelling. Paired t-tests were conducted to analyse differences in students' pre-post tests scores on content knowledge and on each element of the modelling performances. These are described in terms of the amount of transfer. Students significantly improved in their content knowledge for the smell and the evaporation models, but not for the friction model, which was expected as that topic was not taught during the instruction. However, students significantly improved in some of their modelling performances for all the three models. This improvement serves as evidence that the model-based instruction can help students acquire modelling practices that they can apply in a new content area.

Should students design or interact with models? Using the Bifocal Modelling Framework to investigate model construction in high school science

NASA Astrophysics Data System (ADS)

Fuhrmann, Tamar; Schneider, Bertrand; Blikstein, Paulo

2018-05-01

The Bifocal Modelling Framework (BMF) is an approach for science learning which links students' physical experimentation with computer modelling in real time, focusing on the comparison of the two media. In this paper, we explore how a Bifocal Modelling implementation supported learning outcomes related to both content and metamodeling knowledge, focusing on the role of designing models. Our study consisted of three conditions implemented with a total of 69 9th grade high-school students. The first and second classes were assigned two implementation modes of BMF: with and without a model design module. The third condition, employed as a control, consisted of a class that received instruction in the school's traditional approach. Our results indicate that students participating in both BMF implementations demonstrated improved content knowledge and a better understanding of metamodeling. However, only the 'BMF-with-design' group improved significantly in both content and metamodeling knowledge. Our qualitative analyses indicate that both BMF groups designed detailed models that included scientific explanations. However only students who engaged in the model design component: (1) completed a detailed model displaying molecular interaction; and (2) developed a critical perspective about models. We discuss the implications of those results for teaching scientific science concepts and metamodeling knowledge.

Where Does Creativity Fit into a Productivist Industrial Model of Knowledge Production?

ERIC Educational Resources Information Center

Ghassib, Hisham B.

2010-01-01

The basic premise of this paper is the fact that science has become a major industry: the knowledge industry. The paper throws some light on the reasons for the transformation of science from a limited, constrained and marginal craft into a major industry. It, then, presents a productivist industrial model of knowledge production, which shows its…

Promoting Conceptual Change of Learning Sorting Algorithm through the Diagnosis of Mental Models: The Effects of Gender and Learning Styles

ERIC Educational Resources Information Center

Lau, Wilfred W. F.; Yuen, Allan H. K.

2010-01-01

It has been advocated that pedagogical content knowledge as well as subject matter knowledge are important for improving classroom instructions. To develop pedagogical content knowledge, it is argued that understanding of students' mental representations of concepts is deemed necessary. Yet assessing and comparing mental model of each individual…

Discovering and Articulating What Is Not yet Known: Using Action Learning and Grounded Theory as a Knowledge Management Strategy

ERIC Educational Resources Information Center

Pauleen, David J.; Corbitt, Brian; Yoong, Pak

2007-01-01

Purpose: To provide a conceptual model for the discovery and articulation of emergent organizational knowledge, particularly knowledge that develops when people work with new technologies. Design/methodology/approach: The model is based on two widely accepted research methods--action learning and grounded theory--and is illustrated using a case…

Putting TPACK on the Radar: A Visual Quantitative Model for Tracking Growth of Essential Teacher Knowledge

ERIC Educational Resources Information Center

Colvin, Julien C.; Tomayko, Ming C.

2015-01-01

Since Mishra and Koehler's (2006) description of technological pedagogical content knowledge (also known as TPACK), scholars have analyzed the various paths preservice and in-service teachers can take to develop their knowledge in each of the subdomains. However, the model of the overall framework can be confusing to teachers, as Venn diagrams are…

The Influence of Content Knowledge on Teaching and Learning in Traditional and Sport Education Contexts: An Exploratory Study

ERIC Educational Resources Information Center

Iserbyt, Peter; Ward, Phillip; Martens, Jonas

2016-01-01

Background: Our understanding of the role in which content knowledge (CK) can strengthen instructional models and how that knowledge matters for professional development is limited. It is contended that mere use of an instructional model is insufficient to impact psychomotor learning in meaningful ways. Purpose: This study was conducted to…

Early Math Trajectories: Low-Income Children's Mathematics Knowledge from Ages 4 to 11

ERIC Educational Resources Information Center

Rittle-Johnson, Bethany; Fyfe, Emily R.; Hofer, Kerry G.; Farran, Dale C.

2017-01-01

Early mathematics knowledge is a strong predictor of later academic achievement, but children from low-income families enter school with weak mathematics knowledge. An early math trajectories model is proposed and evaluated within a longitudinal study of 517 low-income American children from ages 4 to 11. This model includes a broad range of math…

Early Math Trajectories: Low-Income Children's Mathematics Knowledge from Age 4 to 11

ERIC Educational Resources Information Center

Rittle-Johnson, Bethany; Fyfe, Emily R.; Hofer, Kerry G.; Farran, Dale C.

2016-01-01

Early mathematics knowledge is a strong predictor of later academic achievement, but children from low-income families enter school with weak mathematics knowledge. An Early Math Trajectories model is proposed and evaluated within a longitudinal study of 517 low-income American children from age 4 to 11. This model includes a broad range of math…

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.

Dynamic Bayesian Networks for Student Modeling

ERIC Educational Resources Information Center

Kaser, Tanja; Klingler, Severin; Schwing, Alexander G.; Gross, Markus

2017-01-01

Intelligent tutoring systems adapt the curriculum to the needs of the individual student. Therefore, an accurate representation and prediction of student knowledge is essential. Bayesian Knowledge Tracing (BKT) is a popular approach for student modeling. The structure of BKT models, however, makes it impossible to represent the hierarchy and…

A Multidisciplinary Model for Development of Intelligent Computer-Assisted Instruction.

ERIC Educational Resources Information Center

Park, Ok-choon; Seidel, Robert J.

1989-01-01

Proposes a schematic multidisciplinary model to help developers of intelligent computer-assisted instruction (ICAI) identify the types of required expertise and integrate them into a system. Highlights include domain types and expertise; knowledge acquisition; task analysis; knowledge representation; student modeling; diagnosis of learning needs;…

Viewing Knowledge Bases as Qualitative Models.

ERIC Educational Resources Information Center

Clancey, William J.

The concept of a qualitative model provides a unifying perspective for understanding how expert systems differ from conventional programs. Knowledge bases contain qualitative models of systems in the world, that is, primarily non-numeric descriptions that provide a basis for explaining and predicting behavior and formulating action plans. The…

The Gain-Loss Model: A Probabilistic Skill Multimap Model for Assessing Learning Processes

ERIC Educational Resources Information Center

Robusto, Egidio; Stefanutti, Luca; Anselmi, Pasquale

2010-01-01

Within the theoretical framework of knowledge space theory, a probabilistic skill multimap model for assessing learning processes is proposed. The learning process of a student is modeled as a function of the student's knowledge and of an educational intervention on the attainment of specific skills required to solve problems in a knowledge…

Pre-Service Physics Teachers' Knowledge of Models and Perceptions of Modelling

ERIC Educational Resources Information Center

Ogan-Bekiroglu, Feral

2006-01-01

One of the purposes of this study was to examine the differences between knowledge of pre-service physics teachers who experienced model-based teaching in pre-service education and those who did not. Moreover, it was aimed to determine pre-service physics teachers' perceptions of modelling. Posttest-only control group experimental design was used…

Multidisciplinary Modelling of Symptoms and Signs with Archetypes and SNOMED-CT for Clinical Decision Support.

PubMed

Marco-Ruiz, Luis; Maldonado, J Alberto; Karlsen, Randi; Bellika, Johan G

2015-01-01

Clinical Decision Support Systems (CDSS) help to improve health care and reduce costs. However, the lack of knowledge management and modelling hampers their maintenance and reuse. Current EHR standards and terminologies can allow the semantic representation of the data and knowledge of CDSS systems boosting their interoperability, reuse and maintenance. This paper presents the modelling process of respiratory conditions' symptoms and signs by a multidisciplinary team of clinicians and information architects with the help of openEHR, SNOMED and clinical information modelling tools for a CDSS. The information model of the CDSS was defined by means of an archetype and the knowledge model was implemented by means of an SNOMED-CT based ontology.

Dimensional reduction for a SIR type model

NASA Astrophysics Data System (ADS)

Cahyono, Edi; Soeharyadi, Yudi; Mukhsar

2018-03-01

Epidemic phenomena are often modeled in the form of dynamical systems. Such model has also been used to model spread of rumor, spread of extreme ideology, and dissemination of knowledge. Among the simplest is SIR (susceptible, infected and recovered) model, a model that consists of three compartments, and hence three variables. The variables are functions of time which represent the number of subpopulations, namely suspect, infected and recovery. The sum of the three is assumed to be constant. Hence, the model is actually two dimensional which sits in three-dimensional ambient space. This paper deals with the reduction of a SIR type model into two variables in two-dimensional ambient space to understand the geometry and dynamics better. The dynamics is studied, and the phase portrait is presented. The two dimensional model preserves the equilibrium and the stability. The model has been applied for knowledge dissemination, which has been the interest of knowledge management.

Towards a New Generation of Agricultural System Data, Models and Knowledge Products: Design and Improvement

NASA Technical Reports Server (NTRS)

Antle, John M.; Basso, Bruno; Conant, Richard T.; Godfray, H. Charles J.; Jones, James W.; Herrero, Mario; Howitt, Richard E.; Keating, Brian A.; Munoz-Carpena, Rafael; Rosenzweig, Cynthia

2016-01-01

This paper presents ideas for a new generation of agricultural system models that could meet the needs of a growing community of end-users exemplified by a set of Use Cases. We envision new data, models and knowledge products that could accelerate the innovation process that is needed to achieve the goal of achieving sustainable local, regional and global food security. We identify desirable features for models, and describe some of the potential advances that we envisage for model components and their integration. We propose an implementation strategy that would link a "pre-competitive" space for model development to a "competitive space" for knowledge product development and through private-public partnerships for new data infrastructure. Specific model improvements would be based on further testing and evaluation of existing models, the development and testing of modular model components and integration, and linkages of model integration platforms to new data management and visualization tools.

Towards a new generation of agricultural system data, models and knowledge products: Design and improvement.

PubMed

Antle, John M; Basso, Bruno; Conant, Richard T; Godfray, H Charles J; Jones, James W; Herrero, Mario; Howitt, Richard E; Keating, Brian A; Munoz-Carpena, Rafael; Rosenzweig, Cynthia; Tittonell, Pablo; Wheeler, Tim R

2017-07-01

This paper presents ideas for a new generation of agricultural system models that could meet the needs of a growing community of end-users exemplified by a set of Use Cases. We envision new data, models and knowledge products that could accelerate the innovation process that is needed to achieve the goal of achieving sustainable local, regional and global food security. We identify desirable features for models, and describe some of the potential advances that we envisage for model components and their integration. We propose an implementation strategy that would link a "pre-competitive" space for model development to a "competitive space" for knowledge product development and through private-public partnerships for new data infrastructure. Specific model improvements would be based on further testing and evaluation of existing models, the development and testing of modular model components and integration, and linkages of model integration platforms to new data management and visualization tools.

Applying Service-Oriented Architecture on The Development of Groundwater Modeling Support System

NASA Astrophysics Data System (ADS)

Li, C. Y.; WANG, Y.; Chang, L. C.; Tsai, J. P.; Hsiao, C. T.

2016-12-01

Groundwater simulation has become an essential step on the groundwater resources management and assessment. There are many stand-alone pre- and post-processing software packages to alleviate the model simulation loading, but the stand-alone software do not consider centralized management of data and simulation results neither do they provide network sharing functions. Hence, it is difficult to share and reuse the data and knowledge (simulation cases) systematically within or across companies. Therefore, this study develops a centralized and network based groundwater modeling support system to assist model construction. The system is based on service-oriented architecture and allows remote user to develop their modeling cases on internet. The data and cases (knowledge) are thus easy to manage centralized. MODFLOW is the modeling engine of the system, which is the most popular groundwater model in the world. The system provides a data warehouse to restore groundwater observations, MODFLOW Support Service, MODFLOW Input File & Shapefile Convert Service, MODFLOW Service, and Expert System Service to assist researchers to build models. Since the system architecture is service-oriented, it is scalable and flexible. The system can be easily extended to include the scenarios analysis and knowledge management to facilitate the reuse of groundwater modeling knowledge.

Knowledge mobilisation for policy development: implementing systems approaches through participatory dynamic simulation modelling.

PubMed

Freebairn, Louise; Rychetnik, Lucie; Atkinson, Jo-An; Kelly, Paul; McDonnell, Geoff; Roberts, Nick; Whittall, Christine; Redman, Sally

2017-10-02

Evidence-based decision-making is an important foundation for health policy and service planning decisions, yet there remain challenges in ensuring that the many forms of available evidence are considered when decisions are being made. Mobilising knowledge for policy and practice is an emergent process, and one that is highly relational, often messy and profoundly context dependent. Systems approaches, such as dynamic simulation modelling can be used to examine both complex health issues and the context in which they are embedded, and to develop decision support tools. This paper reports on the novel use of participatory simulation modelling as a knowledge mobilisation tool in Australian real-world policy settings. We describe how this approach combined systems science methodology and some of the core elements of knowledge mobilisation best practice. We describe the strategies adopted in three case studies to address both technical and socio-political issues, and compile the experiential lessons derived. Finally, we consider the implications of these knowledge mobilisation case studies and provide evidence for the feasibility of this approach in policy development settings. Participatory dynamic simulation modelling builds on contemporary knowledge mobilisation approaches for health stakeholders to collaborate and explore policy and health service scenarios for priority public health topics. The participatory methods place the decision-maker at the centre of the process and embed deliberative methods and co-production of knowledge. The simulation models function as health policy and programme dynamic decision support tools that integrate diverse forms of evidence, including research evidence, expert knowledge and localised contextual information. Further research is underway to determine the impact of these methods on health service decision-making.

A Design Thinking Approach to Teaching Knowledge Management

ERIC Educational Resources Information Center

Wang, Shouhong; Wang, Hai

2008-01-01

Pedagogies for knowledge management courses are still undeveloped. This Teaching Tip introduces a design thinking approach to teaching knowledge management. An induction model used to guide students' real-life projects for knowledge management is presented. (Contains 1 figure.)

PSOLA: A Heuristic Land-Use Allocation Model Using Patch-Level Operations and Knowledge-Informed Rules.

PubMed

Liu, Yaolin; Peng, Jinjin; Jiao, Limin; Liu, Yanfang

2016-01-01

Optimizing land-use allocation is important to regional sustainable development, as it promotes the social equality of public services, increases the economic benefits of land-use activities, and reduces the ecological risk of land-use planning. Most land-use optimization models allocate land-use using cell-level operations that fragment land-use patches. These models do not cooperate well with land-use planning knowledge, leading to irrational land-use patterns. This study focuses on building a heuristic land-use allocation model (PSOLA) using particle swarm optimization. The model allocates land-use with patch-level operations to avoid fragmentation. The patch-level operations include a patch-edge operator, a patch-size operator, and a patch-compactness operator that constrain the size and shape of land-use patches. The model is also integrated with knowledge-informed rules to provide auxiliary knowledge of land-use planning during optimization. The knowledge-informed rules consist of suitability, accessibility, land use policy, and stakeholders' preference. To validate the PSOLA model, a case study was performed in Gaoqiao Town in Zhejiang Province, China. The results demonstrate that the PSOLA model outperforms a basic PSO (Particle Swarm Optimization) in the terms of the social, economic, ecological, and overall benefits by 3.60%, 7.10%, 1.53% and 4.06%, respectively, which confirms the effectiveness of our improvements. Furthermore, the model has an open architecture, enabling its extension as a generic tool to support decision making in land-use planning.

PSOLA: A Heuristic Land-Use Allocation Model Using Patch-Level Operations and Knowledge-Informed Rules

PubMed Central

Liu, Yaolin; Peng, Jinjin; Jiao, Limin; Liu, Yanfang

2016-01-01

Optimizing land-use allocation is important to regional sustainable development, as it promotes the social equality of public services, increases the economic benefits of land-use activities, and reduces the ecological risk of land-use planning. Most land-use optimization models allocate land-use using cell-level operations that fragment land-use patches. These models do not cooperate well with land-use planning knowledge, leading to irrational land-use patterns. This study focuses on building a heuristic land-use allocation model (PSOLA) using particle swarm optimization. The model allocates land-use with patch-level operations to avoid fragmentation. The patch-level operations include a patch-edge operator, a patch-size operator, and a patch-compactness operator that constrain the size and shape of land-use patches. The model is also integrated with knowledge-informed rules to provide auxiliary knowledge of land-use planning during optimization. The knowledge-informed rules consist of suitability, accessibility, land use policy, and stakeholders’ preference. To validate the PSOLA model, a case study was performed in Gaoqiao Town in Zhejiang Province, China. The results demonstrate that the PSOLA model outperforms a basic PSO (Particle Swarm Optimization) in the terms of the social, economic, ecological, and overall benefits by 3.60%, 7.10%, 1.53% and 4.06%, respectively, which confirms the effectiveness of our improvements. Furthermore, the model has an open architecture, enabling its extension as a generic tool to support decision making in land-use planning. PMID:27322619

The lure of rationality: Why does the deficit model persist in science communication?

PubMed

Simis, Molly J; Madden, Haley; Cacciatore, Michael A; Yeo, Sara K

2016-05-01

Science communication has been historically predicated on the knowledge deficit model. Yet, empirical research has shown that public communication of science is more complex than what the knowledge deficit model suggests. In this essay, we pose four lines of reasoning and present empirical data for why we believe the deficit model still persists in public communication of science. First, we posit that scientists' training results in the belief that public audiences can and do process information in a rational manner. Second, the persistence of this model may be a product of current institutional structures. Many graduate education programs in science, technology, engineering, and math (STEM) fields generally lack formal training in public communication. We offer empirical evidence that demonstrates that scientists who have less positive attitudes toward the social sciences are more likely to adhere to the knowledge deficit model of science communication. Third, we present empirical evidence of how scientists conceptualize "the public" and link this to attitudes toward the deficit model. We find that perceiving a knowledge deficit in the public is closely tied to scientists' perceptions of the individuals who comprise the public. Finally, we argue that the knowledge deficit model is perpetuated because it can easily influence public policy for science issues. We propose some ways to uproot the deficit model and move toward more effective science communication efforts, which include training scientists in communication methods grounded in social science research and using approaches that engage community members around scientific issues. © The Author(s) 2016.

Knowledge Representation Of CT Scans Of The Head

NASA Astrophysics Data System (ADS)

Ackerman, Laurens V.; Burke, M. W.; Rada, Roy

1984-06-01

We have been investigating diagnostic knowledge models which assist in the automatic classification of medical images by combining information extracted from each image with knowledge specific to that class of images. In a more general sense we are trying to integrate verbal and pictorial descriptions of disease via representations of knowledge, study automatic hypothesis generation as related to clinical medicine, evolve new mathematical image measures while integrating them into the total diagnostic process, and investigate ways to augment the knowledge of the physician. Specifically, we have constructed an artificial intelligence knowledge model using the technique of a production system blending pictorial and verbal knowledge about the respective CT scan and patient history. It is an attempt to tie together different sources of knowledge representation, picture feature extraction and hypothesis generation. Our knowledge reasoning and representation system (KRRS) works with data at the conscious reasoning level of the practicing physician while at the visual perceptional level we are building another production system, the picture parameter extractor (PPE). This paper describes KRRS and its relationship to PPE.

How to reduce the latent social risk of disease: the determinants of vaccination against rabies in Taiwan.

PubMed

Ku-Yuan, Lee; Li-Chi, Lan; Jiun-Hao, Wang; Chen-Ling, Fang; Kun-Sun, Shiao

2014-06-04

To control the latent social risk of disease, the government usually spreads accurate information and attempts to improve the public's attitude toward adopting prevention. However, these methods with the Knowledge, Attitudes, and Practices (KAP) model do not always work. Therefore, we used the theory of planned behavior (TPB) to understand dog owners' behavior and distinguished the knowledge effect as objective knowledge (OK) and subjective knowledge (SK). A total of 310 dog owners completed a questionnaire based on our model. We employed structural equation modeling to verify the structural relationships and found three main results. First, our model was fit, and each path was significant. People with better attitudes, stronger subjective norms, and more perceptive behavioral control have stronger behavioral intention. Second, perceived behavioral control, not attitude, was the best predictive index in this model. Finally, on perceived behavioral control, subjective knowledge showed more influence than objective knowledge. We successfully extended TPB to explain the behavioral intention of dog owners and presented more workable recommendations. To reduce the latent social risk of disease, the government should not only address dog owners' attitudes, but also their subjective norms and perceptive behavioral control. Indeed, perceptive behavioral control and SK showed the most influence in this model. It is implied that the self-efficacy of dog owners is the most important factor in such a behavior. Therefore, the government should focus on enhancing dog owners' self-efficacy first while devoted to prevention activities.

How to Reduce the Latent Social Risk of Disease: The Determinants of Vaccination against Rabies in Taiwan

PubMed Central

Ku-Yuan, Lee; Li-Chi, Lan; Jiun-Hao, Wang; Chen-Ling, Fang; Kun-Sun, Shiao

2014-01-01

To control the latent social risk of disease, the government usually spreads accurate information and attempts to improve the public’s attitude toward adopting prevention. However, these methods with the Knowledge, Attitudes, and Practices (KAP) model do not always work. Therefore, we used the theory of planned behavior (TPB) to understand dog owners’ behavior and distinguished the knowledge effect as objective knowledge (OK) and subjective knowledge (SK). A total of 310 dog owners completed a questionnaire based on our model. We employed structural equation modeling to verify the structural relationships and found three main results. First, our model was fit, and each path was significant. People with better attitudes, stronger subjective norms, and more perceptive behavioral control have stronger behavioral intention. Second, perceived behavioral control, not attitude, was the best predictive index in this model. Finally, on perceived behavioral control, subjective knowledge showed more influence than objective knowledge. We successfully extended TPB to explain the behavioral intention of dog owners and presented more workable recommendations. To reduce the latent social risk of disease, the government should not only address dog owners’ attitudes, but also their subjective norms and perceptive behavioral control. Indeed, perceptive behavioral control and SK showed the most influence in this model. It is implied that the self-efficacy of dog owners is the most important factor in such a behavior. Therefore, the government should focus on enhancing dog owners’ self-efficacy first while devoted to prevention activities. PMID:24901413

Web-video-mining-supported workflow modeling for laparoscopic surgeries.

PubMed

Liu, Rui; Zhang, Xiaoli; Zhang, Hao

2016-11-01

As quality assurance is of strong concern in advanced surgeries, intelligent surgical systems are expected to have knowledge such as the knowledge of the surgical workflow model (SWM) to support their intuitive cooperation with surgeons. For generating a robust and reliable SWM, a large amount of training data is required. However, training data collected by physically recording surgery operations is often limited and data collection is time-consuming and labor-intensive, severely influencing knowledge scalability of the surgical systems. The objective of this research is to solve the knowledge scalability problem in surgical workflow modeling with a low cost and labor efficient way. A novel web-video-mining-supported surgical workflow modeling (webSWM) method is developed. A novel video quality analysis method based on topic analysis and sentiment analysis techniques is developed to select high-quality videos from abundant and noisy web videos. A statistical learning method is then used to build the workflow model based on the selected videos. To test the effectiveness of the webSWM method, 250 web videos were mined to generate a surgical workflow for the robotic cholecystectomy surgery. The generated workflow was evaluated by 4 web-retrieved videos and 4 operation-room-recorded videos, respectively. The evaluation results (video selection consistency n-index ≥0.60; surgical workflow matching degree ≥0.84) proved the effectiveness of the webSWM method in generating robust and reliable SWM knowledge by mining web videos. With the webSWM method, abundant web videos were selected and a reliable SWM was modeled in a short time with low labor cost. Satisfied performances in mining web videos and learning surgery-related knowledge show that the webSWM method is promising in scaling knowledge for intelligent surgical systems. Copyright © 2016 Elsevier B.V. All rights reserved.

Artificial intelligence in process control: Knowledge base for the shuttle ECS model

NASA Technical Reports Server (NTRS)

Stiffler, A. Kent

1989-01-01

The general operation of KATE, an artificial intelligence controller, is outlined. A shuttle environmental control system (ECS) demonstration system for KATE is explained. The knowledge base model for this system is derived. An experimental test procedure is given to verify parameters in the model.

Designing Informal Learning Experiences for Early Career Academics Using a Knowledge Ecosystem Model

ERIC Educational Resources Information Center

Miller, Faye; Partridge, Helen; Bruce, Christine; Hemmings, Brian

2017-01-01

This article presents a "knowledge ecosystem" model of how early career academics experience using information to learn while building their social networks for developmental purposes. Developed using grounded theory methodology, the model offers a way of conceptualising how to empower early career academics through (1) agency…

The Inferential Structure of Actionable Science in Climatological and Hydrological Co-Productions

NASA Astrophysics Data System (ADS)

Brumble, K. C.

2016-12-01

Across the geophysical sciences, and in hydrology in particular, there is a growing emphasis on and desire to produce "actionable science" and "user-inspired" science. Fueled by the need to make research approachable, intelligible, and useful for decision-makers, policy-makers, and across disciplinary boundaries, actionable science endeavors seek to replace the traditional downward flow of information model for knowledge in the sciences. Instead the focus is on more dynamical knowledge flow between the local and contingent and the vast and complex. New methodologies which allow for the co-production of knowledge between modelers, model users, and decision-makers will be surveyed for the structure of knowledge flow present, and for innovations in communicating and handling uncertainties across traditional disciplinary boundaries. Current and possible future methods for handling sources of uncertainty and cascades of uncertainty will be addressed. Examples will be drawn from recent projects involving the interactions between climate modeling groups, hydrological modelers, and decision makers at the local and regional level in water security to try and identify key methodologies for the co-production of actionable knowledge exportable to other applications in the boundary between systems impacted by climate change.

Public attention to science and political news and support for climate change mitigation

NASA Astrophysics Data System (ADS)

Hart, P. Sol; Nisbet, Erik C.; Myers, Teresa A.

2015-06-01

We examine how attention to science and political news may influence public knowledge, perceived harm, and support for climate mitigation policies. Previous research examining these relationships has not fully accounted for how political ideology shapes the mental processes through which the public interprets media discourses about climate change. We incorporate political ideology and the concept of motivated cognition into our analysis to compare and contrast two prominent models of opinion formation, the scientific literacy model, which posits that disseminating scientific information will move public opinion towards the scientific consensus, and the motivated reasoning model, which posits that individuals will interpret information in a biased manner. Our analysis finds support for both models of opinion formation with key differences across ideological groups. Attention to science news was associated with greater perceptions of harm and knowledge for conservatives, but only additional knowledge for liberals. Supporting the literacy model, greater knowledge was associated with more support for climate mitigation for liberals. In contrast, consistent with motivated reasoning, more knowledgeable conservatives were less supportive of mitigation policy. In addition, attention to political news had a negative association with perceived harm for conservatives but not for liberals.

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…

Knowledge Building: Reinventing Education for the Knowledge Age

ERIC Educational Resources Information Center

Philip, Donald N.

2011-01-01

This paper examines the Knowledge Age and how economic factors are causing educators to rethink and reinvent education. Two key factors in education in the Knowledge Age will be education for an economy of innovation, and the increasing virtualization of education. We present knowledge building pedagogy as a model for education in the Knowledge…

Can Moral Hazard Be Resolved by Common-Knowledge in S4n-Knowledge?

NASA Astrophysics Data System (ADS)

Matsuhisa, Takashi

This article investigates the relationship between common-knowledge and agreement in multi-agent system, and to apply the agreement result by common-knowledge to the principal-agent model under non-partition information. We treat the two problems: (1) how we capture the fact that the agents agree on an event or they get consensus on it from epistemic point of view, and (2) how the agreement theorem will be able to make progress to settle a moral hazard problem in the principal-agents model under non-partition information. We shall propose a solution program for the moral hazard in the principal-agents model under non-partition information by common-knowledge. Let us start that the agents have the knowledge structure induced from a reflexive and transitive relation associated with the multi-modal logic S4n. Each agent obtains the membership value of an event under his/her private information, so he/she considers the event as fuzzy set. Specifically consider the situation that the agents commonly know all membership values of the other agents. In this circumstance we shall show the agreement theorem that consensus on the membership values among all agents can still be guaranteed. Furthermore, under certain assumptions we shall show that the moral hazard can be resolved in the principal-agent model when all the expected marginal costs are common-knowledge among the principal and agents.

Effect of the science teaching advancement through modeling physical science professional development workshop on teachers' attitudes, beliefs and content knowledge and students' content knowledge

NASA Astrophysics Data System (ADS)

Dietz, Laura

The Science Teaching Advancement through Modeling Physical Science (STAMPS) professional development workshop was evaluated for effectiveness in improving teachers' and students' content knowledge. Previous research has shown modeling to be an effective method of instruction for improving student and teacher content knowledge, evidenced by assessment scores. Data includes teacher scores on the Force Concept Inventory (FCI; Hestenes, Wells, & Swackhamer, 1992) and the Chemistry Concept Inventory (CCI; Jenkins, Birk, Bauer, Krause, & Pavelich, 2004), as well as student scores on a physics and chemistry assessment. Quantitative data is supported by teacher responses to a post workshop survey and classroom observations. Evaluation of the data shows that the STAMPS professional development workshop was successful in improving both student and teacher content knowledge. Conclusions and suggestions for future study are also included.

A Model for Indexing Medical Documents Combining Statistical and Symbolic Knowledge.

PubMed Central

Avillach, Paul; Joubert, Michel; Fieschi, Marius

2007-01-01

OBJECTIVES: To develop and evaluate an information processing method based on terminologies, in order to index medical documents in any given documentary context. METHODS: We designed a model using both symbolic general knowledge extracted from the Unified Medical Language System (UMLS) and statistical knowledge extracted from a domain of application. Using statistical knowledge allowed us to contextualize the general knowledge for every particular situation. For each document studied, the extracted terms are ranked to highlight the most significant ones. The model was tested on a set of 17,079 French standardized discharge summaries (SDSs). RESULTS: The most important ICD-10 term of each SDS was ranked 1st or 2nd by the method in nearly 90% of the cases. CONCLUSIONS: The use of several terminologies leads to more precise indexing. The improvement achieved in the model’s implementation performances as a result of using semantic relationships is encouraging. PMID:18693792

Process consistency in models: The importance of system signatures, expert knowledge, and process complexity

NASA Astrophysics Data System (ADS)

Hrachowitz, M.; Fovet, O.; Ruiz, L.; Euser, T.; Gharari, S.; Nijzink, R.; Freer, J.; Savenije, H. H. G.; Gascuel-Odoux, C.

2014-09-01

Hydrological models frequently suffer from limited predictive power despite adequate calibration performances. This can indicate insufficient representations of the underlying processes. Thus, ways are sought to increase model consistency while satisfying the contrasting priorities of increased model complexity and limited equifinality. In this study, the value of a systematic use of hydrological signatures and expert knowledge for increasing model consistency was tested. It was found that a simple conceptual model, constrained by four calibration objective functions, was able to adequately reproduce the hydrograph in the calibration period. The model, however, could not reproduce a suite of hydrological signatures, indicating a lack of model consistency. Subsequently, testing 11 models, model complexity was increased in a stepwise way and counter-balanced by "prior constraints," inferred from expert knowledge to ensure a model which behaves well with respect to the modeler's perception of the system. We showed that, in spite of unchanged calibration performance, the most complex model setup exhibited increased performance in the independent test period and skill to better reproduce all tested signatures, indicating a better system representation. The results suggest that a model may be inadequate despite good performance with respect to multiple calibration objectives and that increasing model complexity, if counter-balanced by prior constraints, can significantly increase predictive performance of a model and its skill to reproduce hydrological signatures. The results strongly illustrate the need to balance automated model calibration with a more expert-knowledge-driven strategy of constraining models.

Treating Depression in Staff-Model Versus Network-Model Managed Care Organizations

PubMed Central

Meredith, Lisa S; Rubenstein, Lisa V; Rost, Kathryn; Ford, Daniel E; Gordon, Nancy; Nutting, Paul; Camp, Patti; Wells, Kenneth B

1999-01-01

OBJECTIVE To compare primary care providers’ depression-related knowledge, attitudes, and practices and to understand how these reports vary for providers in staff or group-model managed care organizations (MCOs) compared with network-model MCOs including independent practice associations and preferred provider organizations. DESIGN Survey of primary care providers’ depression-related practices in 1996. SETTING AND PARTICIPANTS We surveyed 410 providers, from 80 outpatient clinics, in 11 MCOs participating in four studies designed to improve the quality of depression care in primary care. MEASUREMENTS AND MAIN RESULTS We measured knowledge based on depression guidelines, attitudes (beliefs about burden, skill, and barriers) related to depression, and reported behavior. Providers in both types of MCO are equally knowledgeable about treating depression (better knowledge of pharmacologic than psychotherapeutic treatments) and perceive equivalent skills in treating depression. However, compared with network-model providers, staff/group-model providers have stronger beliefs that treating depression is burdensome to their practice. While more staff/group-model providers reported time limitations as a barrier to optimal depression treatment, more network-model providers reported limited access to mental health specialty referral as a barrier. Accordingly, these staff/group-model providers are more likely to treat patients with major depression through referral (51% vs 38%) or to assess but not treat (17% vs 7%), and network-model providers are more likely to prescribe antidepressants (57% vs 6%) as first-line treatment. CONCLUSIONS Whereas the providers from staff/group-model MCOs had greater access to and relied more on referral, the providers from network-model organizations were more likely to treat depression themselves. Given varying attitudes and behaviors, improving primary care for the treatment of depression will require unique strategies beyond enhancing technical knowledge for the two types of MCOs. PMID:9893090

Models for open innovation in the pharmaceutical industry.

PubMed

Schuhmacher, Alexander; Germann, Paul-Georg; Trill, Henning; Gassmann, Oliver

2013-12-01

The nature of the pharmaceutical industry is such that the main driver for its growth is innovation. In view of the vast challenges that the industry has been facing for several years and, in particular, how to manage stagnating research and development (R&D) productivity, pharmaceutical companies have opened their R&D organizations to external innovation. Here, we identify and characterize four new types of open innovator, which we call 'knowledge creator', 'knowledge integrator', 'knowledge translator' and 'knowledge leverager', and which describe current open R&D models. Copyright © 2013 Elsevier Ltd. All rights reserved.

Evaluation of the Processes and Outcomes of Implementing a Competency Model to Foster Research Knowledge Utilization in Education

ERIC Educational Resources Information Center

Briand-Lamarche, Mélodie; Pinard, Renée; Thériault, Pascale; Dagenais, Christian

2016-01-01

To encourage the use of research-based information (RBI) in education in Quebec, the "Centre de transfert pour la réussite educative du Québec" CTREQ and the RENARD team, a knowledge transfer research team, developed the Competency Model for Knowledge Translation to Support Educational Achievement among Quebec Youth. They then developed…

Using expert knowledge to incorporate uncertainty in cause-of-death assignments for modeling of cause-specific mortality

USGS Publications Warehouse

Walsh, Daniel P.; Norton, Andrew S.; Storm, Daniel J.; Van Deelen, Timothy R.; Heisy, Dennis M.

2018-01-01

Implicit and explicit use of expert knowledge to inform ecological analyses is becoming increasingly common because it often represents the sole source of information in many circumstances. Thus, there is a need to develop statistical methods that explicitly incorporate expert knowledge, and can successfully leverage this information while properly accounting for associated uncertainty during analysis. Studies of cause-specific mortality provide an example of implicit use of expert knowledge when causes-of-death are uncertain and assigned based on the observer's knowledge of the most likely cause. To explicitly incorporate this use of expert knowledge and the associated uncertainty, we developed a statistical model for estimating cause-specific mortality using a data augmentation approach within a Bayesian hierarchical framework. Specifically, for each mortality event, we elicited the observer's belief of cause-of-death by having them specify the probability that the death was due to each potential cause. These probabilities were then used as prior predictive values within our framework. This hierarchical framework permitted a simple and rigorous estimation method that was easily modified to include covariate effects and regularizing terms. Although applied to survival analysis, this method can be extended to any event-time analysis with multiple event types, for which there is uncertainty regarding the true outcome. We conducted simulations to determine how our framework compared to traditional approaches that use expert knowledge implicitly and assume that cause-of-death is specified accurately. Simulation results supported the inclusion of observer uncertainty in cause-of-death assignment in modeling of cause-specific mortality to improve model performance and inference. Finally, we applied the statistical model we developed and a traditional method to cause-specific survival data for white-tailed deer, and compared results. We demonstrate that model selection results changed between the two approaches, and incorporating observer knowledge in cause-of-death increased the variability associated with parameter estimates when compared to the traditional approach. These differences between the two approaches can impact reported results, and therefore, it is critical to explicitly incorporate expert knowledge in statistical methods to ensure rigorous inference.

How to Construct More Accurate Student Models: Comparing and Optimizing Knowledge Tracing and Performance Factor Analysis

ERIC Educational Resources Information Center

Gong, Yue; Beck, Joseph E.; Heffernan, Neil T.

2011-01-01

Student modeling is a fundamental concept applicable to a variety of intelligent tutoring systems (ITS). However, there is not a lot of practical guidance on how to construct and train such models. This paper compares two approaches for student modeling, Knowledge Tracing (KT) and Performance Factors Analysis (PFA), by evaluating their predictive…

Inductive reasoning.

PubMed

Hayes, Brett K; Heit, Evan; Swendsen, Haruka

2010-03-01

Inductive reasoning entails using existing knowledge or observations to make predictions about novel cases. We review recent findings in research on category-based induction as well as theoretical models of these results, including similarity-based models, connectionist networks, an account based on relevance theory, Bayesian models, and other mathematical models. A number of touchstone empirical phenomena that involve taxonomic similarity are described. We also examine phenomena involving more complex background knowledge about premises and conclusions of inductive arguments and the properties referenced. Earlier models are shown to give a good account of similarity-based phenomena but not knowledge-based phenomena. Recent models that aim to account for both similarity-based and knowledge-based phenomena are reviewed and evaluated. Among the most important new directions in induction research are a focus on induction with uncertain premise categories, the modeling of the relationship between inductive and deductive reasoning, and examination of the neural substrates of induction. A common theme in both the well-established and emerging lines of induction research is the need to develop well-articulated and empirically testable formal models of induction. Copyright © 2010 John Wiley & Sons, Ltd. For further resources related to this article, please visit the WIREs website. Copyright © 2010 John Wiley & Sons, Ltd.

Knowledge modeling tool for evidence-based design.

PubMed

Durmisevic, Sanja; Ciftcioglu, Ozer

2010-01-01

The aim of this study is to take evidence-based design (EBD) to the next level by activating available knowledge, integrating new knowledge, and combining them for more efficient use by the planning and design community. This article outlines a framework for a performance-based measurement tool that can provide the necessary decision support during the design or evaluation of a healthcare environment by estimating the overall design performance of multiple variables. New knowledge in EBD adds continuously to complexity (the "information explosion"), and it becomes impossible to consider all aspects (design features) at the same time, much less their impact on final building performance. How can existing knowledge and the information explosion in healthcare-specifically the domain of EBD-be rendered manageable? Is it feasible to create a computational model that considers many design features and deals with them in an integrated way, rather than one at a time? The found evidence is structured and readied for computation through a "fuzzification" process. The weights are calculated using an analytical hierarchy process. Actual knowledge modeling is accomplished through a fuzzy neural tree structure. The impact of all inputs on the outcome-in this case, patient recovery-is calculated using sensitivity analysis. Finally, the added value of the model is discussed using a hypothetical case study of a patient room. The proposed model can deal with the complexities of various aspects and the relationships among variables in a coordinated way, allowing existing and new pieces of evidence to be integrated in a knowledge tree structure that facilitates understanding of the effects of various design interventions on overall design performance.

WE-A-BRD-01: Innovation in Radiation Therapy Planning I: Knowledge Guided Treatment Planning

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

Wu, Q; Olsen, L

2014-06-15

Intensity modulated radiation therapy (IMRT) and Volumetric Modulated Arc Therapy (VMAT) offer the capability of normal tissues and organs sparing. However, the exact amount of sparing is often unknown until the plan is complete. This lack of prior guidance has led to the iterative, trial and-error approach in current planning practice. Even with this effort the search for patient-specific optimal organ sparing is still strongly influenced by planner's experience. While experience generally helps in maximizing the dosimetric advantages of IMRT/VMAT, there have been several reports showing unnecessarily high degree of plan quality variability at individual institutions and amongst different institutions,more » even with a large amount of experience and the best available tools. Further, when physician and physicist evaluate a plan, the dosimetric quality of the plan is often compared with a standard protocol that ignores individual patient anatomy and tumor characteristic variations. In recent years, developments of knowledge models for clinical IMRT/VMAT planning guidance have shown promising clinical potentials. These knowledge models extract past expert clinical experience into mathematical models that predict dose sparing references at patient-specific level. For physicians and planners, these references provide objective values that reflect best achievable dosimetric constraints. For quality assurance, applying patient-specific dosimetry requirements will enable more quantitative and objective assessment of protocol compliance for complex IMRT planning. Learning Objectives: Modeling and representation of knowledge for knowledge-guided treatment planning. Demonstrations of knowledge-guided treatment planning with a few clinical caanatomical sites. Validation and evaluation of knowledge models for cost and quality effective standardization of plan optimization.« less

Validation Workshop of the DRDC Concept Map Knowledge Model: Issues in Intelligence Analysis

DTIC Science & Technology

2010-06-29

group noted problems with grammar , and a more standard approach to the grammar of the linking term (e.g. use only active tense ) would certainly have...Knowledge Model is distinct from a Concept Map. A Concept Map is a single map, probably presented in one view, while a Knowledge Model is a set of...Agenda The workshop followed the agenda presented in Table 2-3. Table 2-3: Workshop Agenda Time Title 13:00 – 13:15 Registration 13:15 – 13:45

Comprehensible knowledge model creation for cancer treatment decision making.

PubMed

Afzal, Muhammad; Hussain, Maqbool; Ali Khan, Wajahat; Ali, Taqdir; Lee, Sungyoung; Huh, Eui-Nam; Farooq Ahmad, Hafiz; Jamshed, Arif; Iqbal, Hassan; Irfan, Muhammad; Abbas Hydari, Manzar

2017-03-01

A wealth of clinical data exists in clinical documents in the form of electronic health records (EHRs). This data can be used for developing knowledge-based recommendation systems that can assist clinicians in clinical decision making and education. One of the big hurdles in developing such systems is the lack of automated mechanisms for knowledge acquisition to enable and educate clinicians in informed decision making. An automated knowledge acquisition methodology with a comprehensible knowledge model for cancer treatment (CKM-CT) is proposed. With the CKM-CT, clinical data are acquired automatically from documents. Quality of data is ensured by correcting errors and transforming various formats into a standard data format. Data preprocessing involves dimensionality reduction and missing value imputation. Predictive algorithm selection is performed on the basis of the ranking score of the weighted sum model. The knowledge builder prepares knowledge for knowledge-based services: clinical decisions and education support. Data is acquired from 13,788 head and neck cancer (HNC) documents for 3447 patients, including 1526 patients of the oral cavity site. In the data quality task, 160 staging values are corrected. In the preprocessing task, 20 attributes and 106 records are eliminated from the dataset. The Classification and Regression Trees (CRT) algorithm is selected and provides 69.0% classification accuracy in predicting HNC treatment plans, consisting of 11 decision paths that yield 11 decision rules. Our proposed methodology, CKM-CT, is helpful to find hidden knowledge in clinical documents. In CKM-CT, the prediction models are developed to assist and educate clinicians for informed decision making. The proposed methodology is generalizable to apply to data of other domains such as breast cancer with a similar objective to assist clinicians in decision making and education. Copyright © 2017 Elsevier Ltd. All rights reserved.

Investigation of prospective teachers' knowledge and understanding of models and modeling and their attitudes towards the use of models in science education

NASA Astrophysics Data System (ADS)

Aktan, Mustafa B.

The purpose of this study was to investigate prospective science teachers' knowledge and understanding of models and modeling, and their attitudes towards the use of models in science teaching through the following research questions: What knowledge do prospective science teachers have about models and modeling in science? What understandings about the nature of models do these teachers hold as a result of their educational training? What perceptions and attitudes do these teachers hold about the use of models in their teaching? Two main instruments, semi-structured in-depth interviewing and an open-item questionnaire, were used to obtain data from the participants. The data were analyzed from an interpretative phenomenological perspective and grounded theory methods. Earlier studies on in-service science teachers' understanding about the nature of models and modeling revealed that variations exist among teachers' limited yet diverse understanding of scientific models. The results of this study indicated that variations also existed among prospective science teachers' understanding of the concept of model and the nature of models. Apparently the participants' knowledge of models and modeling was limited and they viewed models as materialistic examples and representations. I found that the teachers believed the purpose of a model is to make phenomena more accessible and more understandable. They defined models by referring to an example, a representation, or a simplified version of the real thing. I found no evidence of negative attitudes towards use of models among the participants. Although the teachers valued the idea that scientific models are important aspects of science teaching and learning, and showed positive attitudes towards the use of models in their teaching, certain factors like level of learner, time, lack of modeling experience, and limited knowledge of models appeared to be affecting their perceptions negatively. Implications for the development of science teaching and teacher education programs are discussed. Directions for future research are suggested. Overall, based on the results, I suggest that prospective science teachers should engage in more modeling activities through their preparation programs, gain more modeling experience, and collaborate with their colleagues to better understand and implement scientific models in science teaching.

Knowledge diffusion in the collaboration hypernetwork

NASA Astrophysics Data System (ADS)

Yang, Guang-Yong; Hu, Zhao-Long; Liu, Jian-Guo

2015-02-01

As knowledge constitutes a primary productive force, it is important to understand the performance of knowledge diffusion. In this paper, we present a knowledge diffusion model based on the local-world non-uniform hypernetwork, which introduces the preferential diffusion mechanism and the knowledge absorptive capability αj, where αj is correlated with the hyperdegree dH(j) of node j. At each time step, we randomly select a node i as the sender; a receiver node is selected from the set of nodes that the sender i has published with previously, with probability proportional to the number of papers they have published together. Applying the average knowledge stock V bar(t) , the variance σ2(t) and the variance coefficient c(t) of knowledge stock to measure the growth and diffusion of knowledge and the adequacy of knowledge diffusion, we have made 3 groups of comparative experiments to investigate how different network structures, hypernetwork sizes and knowledge evolution mechanisms affect the knowledge diffusion, respectively. As the diffusion mechanisms based on the hypernetwork combine with the hyperdegree of node, the hypernetwork is more suitable for investigating the performance of knowledge diffusion. Therefore, the proposed model could be helpful for deeply understanding the process of the knowledge diffusion in the collaboration hypernetwork.

Knowledge Acquisition of Generic Queries for Information Retrieval

PubMed Central

Seol, Yoon-Ho; Johnson, Stephen B.; Cimino, James J.

2002-01-01

Several studies have identified clinical questions posed by health care professionals to understand the nature of information needs during clinical practice. To support access to digital information sources, it is necessary to integrate the information needs with a computer system. We have developed a conceptual guidance approach in information retrieval, based on a knowledge base that contains the patterns of information needs. The knowledge base uses a formal representation of clinical questions based on the UMLS knowledge sources, called the Generic Query model. To improve the coverage of the knowledge base, we investigated a method for extracting plausible clinical questions from the medical literature. This poster presents the Generic Query model, shows how it is used to represent the patterns of clinical questions, and describes the framework used to extract knowledge from the medical literature.

Knowledge-acquisition tools for medical knowledge-based systems.

PubMed

Lanzola, G; Quaglini, S; Stefanelli, M

1995-03-01

Knowledge-based systems (KBS) have been proposed to solve a large variety of medical problems. A strategic issue for KBS development and maintenance are the efforts required for both knowledge engineers and domain experts. The proposed solution is building efficient knowledge acquisition (KA) tools. This paper presents a set of KA tools we are developing within a European Project called GAMES II. They have been designed after the formulation of an epistemological model of medical reasoning. The main goal is that of developing a computational framework which allows knowledge engineers and domain experts to interact cooperatively in developing a medical KBS. To this aim, a set of reusable software components is highly recommended. Their design was facilitated by the development of a methodology for KBS construction. It views this process as comprising two activities: the tailoring of the epistemological model to the specific medical task to be executed and the subsequent translation of this model into a computational architecture so that the connections between computational structures and their knowledge level counterparts are maintained. The KA tools we developed are illustrated taking examples from the behavior of a KBS we are building for the management of children with acute myeloid leukemia.

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.

Knowledge Management through the Equilibrium Pattern Model for Learning

NASA Astrophysics Data System (ADS)

Sarirete, Akila; Noble, Elizabeth; Chikh, Azeddine

Contemporary students are characterized by having very applied learning styles and methods of acquiring knowledge. This behavior is consistent with the constructivist models where students are co-partners in the learning process. In the present work the authors developed a new model of learning based on the constructivist theory coupled with the cognitive development theory of Piaget. The model considers the level of learning based on several stages and the move from one stage to another requires learners' challenge. At each time a new concept is introduced creates a disequilibrium that needs to be worked out to return back to its equilibrium stage. This process of "disequilibrium/equilibrium" has been analyzed and validated using a course in computer networking as part of Cisco Networking Academy Program at Effat College, a women college in Saudi Arabia. The model provides a theoretical foundation for teaching especially in a complex knowledge domain such as engineering and can be used in a knowledge economy.

A Knowledge Navigation Method for the Domain of Customers' Services of Mobile Communication Corporations in China

NASA Astrophysics Data System (ADS)

Wu, Jiangning; Wang, Xiaohuan

Rapidly increasing amount of mobile phone users and types of services leads to a great accumulation of complaining information. How to use this information to enhance the quality of customers' services is a big issue at present. To handle this kind of problem, the paper presents an approach to construct a domain knowledge map for navigating the explicit and tacit knowledge in two ways: building the Topic Map-based explicit knowledge navigation model, which includes domain TM construction, a semantic topic expansion algorithm and VSM-based similarity calculation; building Social Network Analysis-based tacit knowledge navigation model, which includes a multi-relational expert navigation algorithm and the criterions to evaluate the performance of expert networks. In doing so, both the customer managers and operators in call centers can find the appropriate knowledge and experts quickly and exactly. The experimental results show that the above method is very powerful for knowledge navigation.

Formal Representations of Eligibility Criteria: A Literature Review

PubMed Central

Weng, Chunhua; Tu, Samson W.; Sim, Ida; Richesson, Rachel

2010-01-01

Standards-based, computable knowledge representations for eligibility criteria are increasingly needed to provide computer-based decision support for automated research participant screening, clinical evidence application, and clinical research knowledge management. We surveyed the literature and identified five aspects of eligibility criteria knowledge representations that contribute to the various research and clinical applications: the intended use of computable eligibility criteria, the classification of eligibility criteria, the expression language for representing eligibility rules, the encoding of eligibility concepts, and the modeling of patient data. We consider three of them (expression language, codification of eligibility concepts, and patient data modeling), to be essential constructs of a formal knowledge representation for eligibility criteria. The requirements for each of the three knowledge constructs vary for different use cases, which therefore should inform the development and choice of the constructs toward cost-effective knowledge representation efforts. We discuss the implications of our findings for standardization efforts toward sharable knowledge representation of eligibility criteria. PMID:20034594

The use of tacit knowledge in occupational safety and health management systems.

PubMed

Podgórski, Daniel

2010-01-01

A systematic approach to occupational safety and health (OSH) management and concepts of knowledge management (KM) have developed independently since the 1990s. Most KM models assume a division of knowledge into explicit and tacit. The role of tacit knowledge is stressed as necessary for higher performance in an enterprise. This article reviews literature on KM applications in OSH. Next, 10 sections of an OSH management system (OSH MS) are identified, in which creating and transferring tacit knowledge contributes significantly to prevention of occupational injuries and diseases. The roles of tacit knowledge in OSH MS are contrasted with those of explicit knowledge, but a lack of a model that would describe this process holistically is pointed out. Finally, examples of methods and tools supporting the use of KM in OSH MS are presented and topics of future research aimed at enhancing KM applications in OSH MS are proposed.

The cognitive mediation model: factors influencing public knowledge of the H1N1 pandemic and intention to take precautionary behaviors.

PubMed

Ho, Shirley S; Peh, Xianghong; Soh, Veronica W L

2013-01-01

This study uses the cognitive mediation model as the theoretical framework to examine the influence of motivations, communication, and news elaboration on public knowledge of the H1N1 pandemic and the intention to take precautionary behaviors in Singapore. Using a nationally representative random digit dialing telephone survey of 1,055 adult Singaporeans, the authors' results show that the cognitive mediation model can be applied to health contexts, in which motivations (surveillance gratification, guidance, and need for cognition) were positively associated with news attention, elaboration, and interpersonal communication. News attention, elaboration, and interpersonal communication in turn positively influence public knowledge about the H1N1 influenza. In addition, results show that the motivations have significant indirect effects on behavioral intentions, as partially mediated by communication (media attention and interpersonal communication), elaboration, and knowledge. The authors conclude that the cognitive mediation model can be extended to behavioral outcomes, above and beyond knowledge. Implications for theory and practice for health communication were discussed.

Modelling students' knowledge organisation: Genealogical conceptual networks

NASA Astrophysics Data System (ADS)

Koponen, Ismo T.; Nousiainen, Maija

2018-04-01

Learning scientific knowledge is largely based on understanding what are its key concepts and how they are related. The relational structure of concepts also affects how concepts are introduced in teaching scientific knowledge. We model here how students organise their knowledge when they represent their understanding of how physics concepts are related. The model is based on assumptions that students use simple basic linking-motifs in introducing new concepts and mostly relate them to concepts that were introduced a few steps earlier, i.e. following a genealogical ordering. The resulting genealogical networks have relatively high local clustering coefficients of nodes but otherwise resemble networks obtained with an identical degree distribution of nodes but with random linking between them (i.e. the configuration-model). However, a few key nodes having a special structural role emerge and these nodes have a higher than average communicability betweenness centralities. These features agree with the empirically found properties of students' concept networks.

Theoretical model to explain the problem-solving process in physics

NASA Astrophysics Data System (ADS)

Lopez, Carlos

2011-03-01

This work reports a theoretical model developed with the aim to explain the mental mechanisms of knowledge building during the problem-solving process in physics using a hybrid approach of assimilation- formation of concepts. The model has been termed conceptual chains and represents graphic diagrams of conceptual dependency, which have yielded information about the background knowledge required during the learning process, as well as about the formation of diverse structures that correspond to distinct forms of networking concepts Additionally, the conceptual constructs of the model have been classified according to five types of knowledge. Evidence was found about the influence of these structures, as well as of the distinct types of knowledge about the degree of difficulty of the problems. I want to be grateful to Laureate International Universities, Baltimore M.D., USA, for the financing granted for the accomplishment of this work.

A biological compression model and its applications.

PubMed

Cao, Minh Duc; Dix, Trevor I; Allison, Lloyd

2011-01-01

A biological compression model, expert model, is presented which is superior to existing compression algorithms in both compression performance and speed. The model is able to compress whole eukaryotic genomes. Most importantly, the model provides a framework for knowledge discovery from biological data. It can be used for repeat element discovery, sequence alignment and phylogenetic analysis. We demonstrate that the model can handle statistically biased sequences and distantly related sequences where conventional knowledge discovery tools often fail.

A Model for Collaborative Working to Facilitate Knowledge Mobilisation in Public Health

ERIC Educational Resources Information Center

McCabe, Karen Elizabeth; Wallace, Annie; Crosland, Ann

2015-01-01

This paper introduces a model for collaborative working to facilitate knowledge mobilisation in public health. The model has been developed by university researchers who worked collaboratively with public health commissioners and strategic partners to evaluate a portfolio of short-term funded interventions to inform re-commissioning. Within this…

A Generative Approach to the Development of Hidden-Figure Items.

ERIC Educational Resources Information Center

Bejar, Issac I.; Yocom, Peter

This report explores an approach to item development and psychometric modeling which explicitly incorporates knowledge about the mental models used by examinees in the solution of items into a psychometric model that characterize performances on a test, as well as incorporating that knowledge into the item development process. The paper focuses on…

The Abstraction Process of Limit Knowledge

ERIC Educational Resources Information Center

Sezgin Memnun, Dilek; Aydin, Bünyamin; Özbilen, Ömer; Erdogan, Günes

2017-01-01

The RBC+C abstraction model is an effective model in mathematics education because it gives the opportunity to analyze research data through cognitive actions. For this reason, we aim to examine the abstraction process of the limit knowledge of two volunteer participant students using the RBC+C abstraction model. With this aim, the students'…

Mathematical Learning Models that Depend on Prior Knowledge and Instructional Strategies

ERIC Educational Resources Information Center

Pritchard, David E.; Lee, Young-Jin; Bao, Lei

2008-01-01

We present mathematical learning models--predictions of student's knowledge vs amount of instruction--that are based on assumptions motivated by various theories of learning: tabula rasa, constructivist, and tutoring. These models predict the improvement (on the post-test) as a function of the pretest score due to intervening instruction and also…

Adaptive Search through Constraint Violations

DTIC Science & Technology

1990-01-01

procedural) knowledge? Different methodologies are used to investigate these questions: Psychological experiments, computer simulations, historical studies...learns control knowledge through adaptive search. Unlike most other psychological models of skill acquisition, HS is a model of analytical, or...Newzll, 1986; VanLehn, in press). Psychological models of skill acquisition employ different problem solving mechanisms (forward search, backward

Knowledge Management Model: Practical Application for Competency Development

ERIC Educational Resources Information Center

Lustri, Denise; Miura, Irene; Takahashi, Sergio

2007-01-01

Purpose: This paper seeks to present a knowledge management (KM) conceptual model for competency development and a case study in a law service firm, which implemented the KM model in a competencies development program. Design/methodology/approach: The case study method was applied according to Yin (2003) concepts, focusing a six-professional group…

An optoelectric professional's training model based on Unity of Knowing and Doing theory

NASA Astrophysics Data System (ADS)

Qin, Shiqiao; Wu, Wei; Zheng, Jiaxing; Wang, Xingshu; Zhao, Yingwei

2017-08-01

The "Unity of Knowing and Doing" (UKD) theory is proposed by an ancient Chinese philosopher, Wang Shouren, in 1508, which explains how to unify knowledge and practice. Different from the Chinese traditional UKD theory, the international higher education usually treats knowledge and practice as independent, and puts more emphasis on knowledge. Oriented from the UKD theory, the College of Opto-electric Science and Engineering (COESE) at National University of Defense Technology (NUDT) explores a novel training model in cultivating opto-electric professionals from the aspects of classroom teaching, practice experiment, system experiment, design experiment, research experiment and innovation experiment (CPSDRI). This model aims at promoting the unity of knowledge and practice, takes how to improve the students' capability as the main concern and tries to enhance the progress from cognition to professional action competence. It contains two hierarchies: cognition (CPS) and action competence (DRI). In the cognition hierarchy, students will focus on learning and mastering the professional knowledge of optics, opto-electric technology, laser, computer, electronics and machine through classroom teaching, practice experiment and system experiment (CPS). Great attention will be paid to case teaching, which links knowledge with practice. In the action competence hierarchy, emphasis will be placed on promoting students' capability of using knowledge to solve practical problems through design experiment, research experiment and innovation experiment (DRI). In this model, knowledge is divided into different modules and capability is cultivated on different levels. It combines classroom teaching and experimental teaching in a synergetic way and unifies cognition and practice, which is a valuable reference to the opto-electric undergraduate professionals' cultivation.

Goal oriented soil mapping: applying modern methods supported by local knowledge: A review

NASA Astrophysics Data System (ADS)

Pereira, Paulo; Brevik, Eric; Oliva, Marc; Estebaranz, Ferran; Depellegrin, Daniel; Novara, Agata; Cerda, Artemi; Menshov, Oleksandr

2017-04-01

In the recent years the amount of soil data available increased importantly. This facilitated the production of better and accurate maps, important for sustainable land management (Pereira et al., 2017). Despite these advances, the human knowledge is extremely important to understand the natural characteristics of the landscape. The knowledge accumulated and transmitted generation after generation is priceless, and should be considered as a valuable data source for soil mapping and modelling. The local knowledge and wisdom can complement the new advances in soil analysis. In addition, farmers are the most interested in the participation and incorporation of their knowledge in the models, since they are the end-users of the study that soil scientists produce. Integration of local community's vision and understanding about nature is assumed to be an important step to the implementation of decision maker's policies. Despite this, many challenges appear regarding the integration of local and scientific knowledge, since in some cases there is no spatial correlation between folk and scientific classifications, which may be attributed to the different cultural variables that influence local soil classification. The objective of this work is to review how modern soil methods incorporated local knowledge in their models. References Pereira, P., Brevik, E., Oliva, M., Estebaranz, F., Depellegrin, D., Novara, A., Cerda, A., Menshov, O. (2017) Goal Oriented soil mapping: applying modern methods supported by local knowledge. In: Pereira, P., Brevik, E., Munoz-Rojas, M., Miller, B. (Eds.) Soil mapping and process modelling for sustainable land use management (Elsevier Publishing House) ISBN: 9780128052006

To ontologise or not to ontologise: An information model for a geospatial knowledge infrastructure

NASA Astrophysics Data System (ADS)

Stock, Kristin; Stojanovic, Tim; Reitsma, Femke; Ou, Yang; Bishr, Mohamed; Ortmann, Jens; Robertson, Anne

2012-08-01

A geospatial knowledge infrastructure consists of a set of interoperable components, including software, information, hardware, procedures and standards, that work together to support advanced discovery and creation of geoscientific resources, including publications, data sets and web services. The focus of the work presented is the development of such an infrastructure for resource discovery. Advanced resource discovery is intended to support scientists in finding resources that meet their needs, and focuses on representing the semantic details of the scientific resources, including the detailed aspects of the science that led to the resource being created. This paper describes an information model for a geospatial knowledge infrastructure that uses ontologies to represent these semantic details, including knowledge about domain concepts, the scientific elements of the resource (analysis methods, theories and scientific processes) and web services. This semantic information can be used to enable more intelligent search over scientific resources, and to support new ways to infer and visualise scientific knowledge. The work describes the requirements for semantic support of a knowledge infrastructure, and analyses the different options for information storage based on the twin goals of semantic richness and syntactic interoperability to allow communication between different infrastructures. Such interoperability is achieved by the use of open standards, and the architecture of the knowledge infrastructure adopts such standards, particularly from the geospatial community. The paper then describes an information model that uses a range of different types of ontologies, explaining those ontologies and their content. The information model was successfully implemented in a working geospatial knowledge infrastructure, but the evaluation identified some issues in creating the ontologies.

Knowledge assistant for robotic environmental characterization

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

Feddema, J.; Rivera, J.; Tucker, S.

1996-08-01

A prototype sensor fusion framework called the {open_quotes}Knowledge Assistant{close_quotes} has been developed and tested on a gantry robot at Sandia National Laboratories. This Knowledge Assistant guides the robot operator during the planning, execution, and post analysis stages of the characterization process. During the planning stage, the Knowledge Assistant suggests robot paths and speeds based on knowledge of sensors available and their physical characteristics. During execution, the Knowledge Assistant coordinates the collection of data through a data acquisition {open_quotes}specialist.{close_quotes} During execution and postanalysis, the Knowledge Assistant sends raw data to other {open_quotes}specialists,{close_quotes} which include statistical pattern recognition software, a neural network,more » and model-based search software. After the specialists return their results, the Knowledge Assistant consolidates the information and returns a report to the robot control system where the sensed objects and their attributes (e.g., estimated dimensions, weight, material composition, etc.) are displayed in the world model. This report highlights the major components of this system.« less

New Proposals for Generating and Exploiting Solution-Oriented Knowledge

ERIC Educational Resources Information Center

Gredig, Daniel; Sommerfeld, Peter

2008-01-01

The claim that professional social work should be based on scientific knowledge is many decades old with knowledge transfer usually moving in the direction from science to practice. The authors critique this model of knowledge transfer and support a hybrid one that places more of an emphasis on professional knowledge and action occurring in the…

The Relationship between Agriculture Knowledge Bases for Teaching and Sources of Knowledge

ERIC Educational Resources Information Center

Rice, Amber H.; Kitchel, Tracy

2015-01-01

The purpose of this study was to describe the agriculture knowledge bases for teaching of agriculture teachers and to see if a relationship existed between years of teaching experience, sources of knowledge, and development of pedagogical content knowledge (PCK), using quantitative methods. A model of PCK from mathematics was utilized as a…

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…

Word sense disambiguation in the clinical domain: a comparison of knowledge-rich and knowledge-poor unsupervised methods

PubMed Central

Chasin, Rachel; Rumshisky, Anna; Uzuner, Ozlem; Szolovits, Peter

2014-01-01

Objective To evaluate state-of-the-art unsupervised methods on the word sense disambiguation (WSD) task in the clinical domain. In particular, to compare graph-based approaches relying on a clinical knowledge base with bottom-up topic-modeling-based approaches. We investigate several enhancements to the topic-modeling techniques that use domain-specific knowledge sources. Materials and methods The graph-based methods use variations of PageRank and distance-based similarity metrics, operating over the Unified Medical Language System (UMLS). Topic-modeling methods use unlabeled data from the Multiparameter Intelligent Monitoring in Intensive Care (MIMIC II) database to derive models for each ambiguous word. We investigate the impact of using different linguistic features for topic models, including UMLS-based and syntactic features. We use a sense-tagged clinical dataset from the Mayo Clinic for evaluation. Results The topic-modeling methods achieve 66.9% accuracy on a subset of the Mayo Clinic's data, while the graph-based methods only reach the 40–50% range, with a most-frequent-sense baseline of 56.5%. Features derived from the UMLS semantic type and concept hierarchies do not produce a gain over bag-of-words features in the topic models, but identifying phrases from UMLS and using syntax does help. Discussion Although topic models outperform graph-based methods, semantic features derived from the UMLS prove too noisy to improve performance beyond bag-of-words. Conclusions Topic modeling for WSD provides superior results in the clinical domain; however, integration of knowledge remains to be effectively exploited. PMID:24441986

Image/video understanding systems based on network-symbolic models

NASA Astrophysics Data System (ADS)

Kuvich, Gary

2004-03-01

Vision is a part of a larger information system that converts visual information into knowledge structures. These structures drive vision process, resolve ambiguity and uncertainty via feedback projections, and provide image understanding that is an interpretation of visual information in terms of such knowledge models. Computer simulation models are built on the basis of graphs/networks. The ability of human brain to emulate similar graph/network models is found. Symbols, predicates and grammars naturally emerge in such networks, and logic is simply a way of restructuring such models. Brain analyzes an image as a graph-type relational structure created via multilevel hierarchical compression of visual information. Primary areas provide active fusion of image features on a spatial grid-like structure, where nodes are cortical columns. Spatial logic and topology naturally present in such structures. Mid-level vision processes like perceptual grouping, separation of figure from ground, are special kinds of network transformations. They convert primary image structure into the set of more abstract ones, which represent objects and visual scene, making them easy for analysis by higher-level knowledge structures. Higher-level vision phenomena are results of such analysis. Composition of network-symbolic models combines learning, classification, and analogy together with higher-level model-based reasoning into a single framework, and it works similar to frames and agents. Computational intelligence methods transform images into model-based knowledge representation. Based on such principles, an Image/Video Understanding system can convert images into the knowledge models, and resolve uncertainty and ambiguity. This allows creating intelligent computer vision systems for design and manufacturing.

Knowledge-Production-and Utilization: A General Model. Third Approximation. Iowa Agricultural and Home Economics Experiment Station Project No. 2218. Sociology Report No. 138.

ERIC Educational Resources Information Center

Meehan, Peter M.; Beal, George M.

The objective of this monograph is to contribute to the further understanding of the knowledge-production-and-utilization process. Its primary focus is on a model both general and detailed enough to provide a comprehensive overview of the diverse functions, roles, and processes required to understand the flow of knowledge from its point of origin…

Leveraging the Affordances of YouTube: The Role of Pedagogical Knowledge and Mental Models of Technology Functions for Lesson Planning with Technology

ERIC Educational Resources Information Center

Krauskopf, Karsten; Zahn, Carmen; Hesse, Friedrich W.

2012-01-01

Web-based digital video tools enable learners to access video sources in constructive ways. To leverage these affordances teachers need to integrate their knowledge of a technology with their professional knowledge about teaching. We suggest that this is a cognitive process, which is strongly connected to a teacher's mental model of the tool's…

Knowledge repositories for multiple uses

NASA Technical Reports Server (NTRS)

Williamson, Keith; Riddle, Patricia

1991-01-01

In the life cycle of a complex physical device or part, for example, the docking bay door of the Space Station, there are many uses for knowledge about the device or part. The same piece of knowledge might serve several uses. Given the quantity and complexity of the knowledge that must be stored, it is critical to maintain the knowledge in one repository, in one form. At the same time, because of quantity and complexity of knowledge that must be used in life cycle applications such as cost estimation, re-design, and diagnosis, it is critical to automate such knowledge uses. For each specific use, a knowledge base must be available and must be in a from that promotes the efficient performance of that knowledge base. However, without a single source knowledge repository, the cost of maintaining consistent knowledge between multiple knowledge bases increases dramatically; as facts and descriptions change, they must be updated in each individual knowledge base. A use-neutral representation of a hydraulic system for the F-111 aircraft was developed. The ability to derive portions of four different knowledge bases is demonstrated from this use-neutral representation: one knowledge base is for re-design of the device using a model-based reasoning problem solver; two knowledge bases, at different levels of abstraction, are for diagnosis using a model-based reasoning solver; and one knowledge base is for diagnosis using an associational reasoning problem solver. It was shown how updates issued against the single source use-neutral knowledge repository can be propagated to the underlying knowledge bases.

Perspectives to performance of environment and health assessments and models--from outputs to outcomes?

PubMed

Pohjola, Mikko V; Pohjola, Pasi; Tainio, Marko; Tuomisto, Jouni T

2013-06-26

The calls for knowledge-based policy and policy-relevant research invoke a need to evaluate and manage environment and health assessments and models according to their societal outcomes. This review explores how well the existing approaches to assessment and model performance serve this need. The perspectives to assessment and model performance in the scientific literature can be called: (1) quality assurance/control, (2) uncertainty analysis, (3) technical assessment of models, (4) effectiveness and (5) other perspectives, according to what is primarily seen to constitute the goodness of assessments and models. The categorization is not strict and methods, tools and frameworks in different perspectives may overlap. However, altogether it seems that most approaches to assessment and model performance are relatively narrow in their scope. The focus in most approaches is on the outputs and making of assessments and models. Practical application of the outputs and the consequential outcomes are often left unaddressed. It appears that more comprehensive approaches that combine the essential characteristics of different perspectives are needed. This necessitates a better account of the mechanisms of collective knowledge creation and the relations between knowledge and practical action. Some new approaches to assessment, modeling and their evaluation and management span the chain from knowledge creation to societal outcomes, but the complexity of evaluating societal outcomes remains a challenge.

Population dynamics of minimally cognitive individuals. Part I: Introducing knowledge into the dynamics

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

Schmieder, R.W.

The author presents a new approach for modeling the dynamics of collections of objects with internal structure. Based on the fact that the behavior of an individual in a population is modified by its knowledge of other individuals, a procedure for accounting for knowledge in a population of interacting objects is presented. It is assumed that each object has partial (or complete) knowledge of some (or all) other objects in the population. The dynamical equations for the objects are then modified to include the effects of this pairwise knowledge. This procedure has the effect of projecting out what the populationmore » will do from the much larger space of what it could do, i.e., filtering or smoothing the dynamics by replacing the complex detailed physical model with an effective model that produces the behavior of interest. The procedure therefore provides a minimalist approach for obtaining emergent collective behavior. The use of knowledge as a dynamical quantity, and its relationship to statistical mechanics, thermodynamics, information theory, and cognition microstructure are discussed.« less

The Use of Problem-Solving Techniques to Develop Semiotic Declarative Knowledge Models about Magnetism and Their Role in Learning for Prospective Science Teachers

ERIC Educational Resources Information Center

Ismail, Yilmaz

2016-01-01

This study aims to develop a semiotic declarative knowledge model, which is a positive constructive behavior model that systematically facilitates understanding in order to ensure that learners think accurately and ask the right questions about a topic. The data used to develop the experimental model were obtained using four measurement tools…

Generic domain models in software engineering

NASA Technical Reports Server (NTRS)

Maiden, Neil

1992-01-01

This paper outlines three research directions related to domain-specific software development: (1) reuse of generic models for domain-specific software development; (2) empirical evidence to determine these generic models, namely elicitation of mental knowledge schema possessed by expert software developers; and (3) exploitation of generic domain models to assist modelling of specific applications. It focuses on knowledge acquisition for domain-specific software development, with emphasis on tool support for the most important phases of software development.

A knowledge representation of local pandemic influenza planning models.

PubMed

Islam, Runa; Brandeau, Margaret L; Das, Amar K

2007-10-11

Planning for pandemic flu outbreak at the small-government level can be aided through the use of mathematical policy models. Formulating and analyzing policy models, however, can be a time- and expertise-expensive process. We believe that a knowledge-based system for facilitating the instantiation of locale- and problem-specific policy models can reduce some of these costs. In this work, we present the ontology we have developed for pandemic influenza policy models.

A Technological Teacher Education Program Planning Model.

ERIC Educational Resources Information Center

Hansen, Ronald E.

1993-01-01

A model for technology teacher education curriculum has three facets: (1) purpose (experiential learning, personal development, technological enlightenment, economic well-being); (2) content (professional knowledge, curriculum development competence, pedagogical knowledge and skill, technological foundations); and (3) process (planned reflection,…

Modeling technology innovation: how science, engineering, and industry methods can combine to generate beneficial socioeconomic impacts.

PubMed

Stone, Vathsala I; Lane, Joseph P

2012-05-16

Government-sponsored science, technology, and innovation (STI) programs support the socioeconomic aspects of public policies, in addition to expanding the knowledge base. For example, beneficial healthcare services and devices are expected to result from investments in research and development (R&D) programs, which assume a causal link to commercial innovation. Such programs are increasingly held accountable for evidence of impact-that is, innovative goods and services resulting from R&D activity. However, the absence of comprehensive models and metrics skews evidence gathering toward bibliometrics about research outputs (published discoveries), with less focus on transfer metrics about development outputs (patented prototypes) and almost none on econometrics related to production outputs (commercial innovations). This disparity is particularly problematic for the expressed intent of such programs, as most measurable socioeconomic benefits result from the last category of outputs. This paper proposes a conceptual framework integrating all three knowledge-generating methods into a logic model, useful for planning, obtaining, and measuring the intended beneficial impacts through the implementation of knowledge in practice. Additionally, the integration of the Context-Input-Process-Product (CIPP) model of evaluation proactively builds relevance into STI policies and programs while sustaining rigor. The resulting logic model framework explicitly traces the progress of knowledge from inputs, following it through the three knowledge-generating processes and their respective knowledge outputs (discovery, invention, innovation), as it generates the intended socio-beneficial impacts. It is a hybrid model for generating technology-based innovations, where best practices in new product development merge with a widely accepted knowledge-translation approach. Given the emphasis on evidence-based practice in the medical and health fields and "bench to bedside" expectations for knowledge transfer, sponsors and grantees alike should find the model useful for planning, implementing, and evaluating innovation processes. High-cost/high-risk industries like healthcare require the market deployment of technology-based innovations to improve domestic society in a global economy. An appropriate balance of relevance and rigor in research, development, and production is crucial to optimize the return on public investment in such programs. The technology-innovation process needs a comprehensive operational model to effectively allocate public funds and thereby deliberately and systematically accomplish socioeconomic benefits.

Modeling technology innovation: How science, engineering, and industry methods can combine to generate beneficial socioeconomic impacts

PubMed Central

2012-01-01

Background Government-sponsored science, technology, and innovation (STI) programs support the socioeconomic aspects of public policies, in addition to expanding the knowledge base. For example, beneficial healthcare services and devices are expected to result from investments in research and development (R&D) programs, which assume a causal link to commercial innovation. Such programs are increasingly held accountable for evidence of impact—that is, innovative goods and services resulting from R&D activity. However, the absence of comprehensive models and metrics skews evidence gathering toward bibliometrics about research outputs (published discoveries), with less focus on transfer metrics about development outputs (patented prototypes) and almost none on econometrics related to production outputs (commercial innovations). This disparity is particularly problematic for the expressed intent of such programs, as most measurable socioeconomic benefits result from the last category of outputs. Methods This paper proposes a conceptual framework integrating all three knowledge-generating methods into a logic model, useful for planning, obtaining, and measuring the intended beneficial impacts through the implementation of knowledge in practice. Additionally, the integration of the Context-Input-Process-Product (CIPP) model of evaluation proactively builds relevance into STI policies and programs while sustaining rigor. Results The resulting logic model framework explicitly traces the progress of knowledge from inputs, following it through the three knowledge-generating processes and their respective knowledge outputs (discovery, invention, innovation), as it generates the intended socio-beneficial impacts. It is a hybrid model for generating technology-based innovations, where best practices in new product development merge with a widely accepted knowledge-translation approach. Given the emphasis on evidence-based practice in the medical and health fields and “bench to bedside” expectations for knowledge transfer, sponsors and grantees alike should find the model useful for planning, implementing, and evaluating innovation processes. Conclusions High-cost/high-risk industries like healthcare require the market deployment of technology-based innovations to improve domestic society in a global economy. An appropriate balance of relevance and rigor in research, development, and production is crucial to optimize the return on public investment in such programs. The technology-innovation process needs a comprehensive operational model to effectively allocate public funds and thereby deliberately and systematically accomplish socioeconomic benefits. PMID:22591638

A model to capture and manage tacit knowledge using a multiagent system

NASA Astrophysics Data System (ADS)

Paolino, Lilyam; Paggi, Horacio; Alonso, Fernando; López, Genoveva

2014-10-01

This article presents a model to capture and register business tacit knowledge belonging to different sources, using an expert multiagent system which enables the entry of incidences and captures the tacit knowledge which could fix them. This knowledge and their sources are evaluated through the application of trustworthy algorithms that lead to the registration of the data base and the best of each of them. Through its intelligent software agents, this system interacts with the administrator, users, with the knowledge sources and with all the practice communities which might exist in the business world. The sources as well as the knowledge are constantly evaluated, before being registered and also after that, in order to decide the staying or modification of its original weighting. If there is the possibility of better, new knowledge are registered through the old ones. This is also part of an investigation being carried out which refers to knowledge management methodologies in order to manage tacit business knowledge so as to make the business competitiveness easier and leading to innovation learning.

Knowledge engineering for adverse drug event prevention: on the design and development of a uniform, contextualized and sustainable knowledge-based framework.

PubMed

Koutkias, Vassilis; Kilintzis, Vassilis; Stalidis, George; Lazou, Katerina; Niès, Julie; Durand-Texte, Ludovic; McNair, Peter; Beuscart, Régis; Maglaveras, Nicos

2012-06-01

The primary aim of this work was the development of a uniform, contextualized and sustainable knowledge-based framework to support adverse drug event (ADE) prevention via Clinical Decision Support Systems (CDSSs). In this regard, the employed methodology involved first the systematic analysis and formalization of the knowledge sources elaborated in the scope of this work, through which an application-specific knowledge model has been defined. The entire framework architecture has been then specified and implemented by adopting Computer Interpretable Guidelines (CIGs) as the knowledge engineering formalism for its construction. The framework integrates diverse and dynamic knowledge sources in the form of rule-based ADE signals, all under a uniform Knowledge Base (KB) structure, according to the defined knowledge model. Equally important, it employs the means to contextualize the encapsulated knowledge, in order to provide appropriate support considering the specific local environment (hospital, medical department, language, etc.), as well as the mechanisms for knowledge querying, inference, sharing, and management. In this paper, we present thoroughly the establishment of the proposed knowledge framework by presenting the employed methodology and the results obtained as regards implementation, performance and validation aspects that highlight its applicability and virtue in medication safety. Copyright © 2012 Elsevier Inc. All rights reserved.

Corporate knowledge repository: Adopting academic LMS into corporate environment

NASA Astrophysics Data System (ADS)

Bakar, Muhamad Shahbani Abu; Jalil, Dzulkafli

2017-10-01

The growth of Knowledge Economy has transformed human capital to be the vital asset in business organization of the 21st century. Arguably, due to its white-collar nature, knowledge-based industry is more favorable than traditional manufacturing business. However, over dependency on human capital can also be a major challenge as any workers will inevitably leave the company or retire. This situation will possibly create knowledge gap that may impact business continuity of the enterprise. Knowledge retention in the corporate environment has been of many research interests. Learning Management System (LMS) refers to the system that provides the delivery, assessment and management tools for an organization to handle its knowledge repository. By using the aspirations of a proven LMS implemented in an academic environment, this paper proposes LMS model that can be used to enable peer-to-peer knowledge capture and sharing in the knowledge-based organization. Cloud Enterprise Resource Planning (ERP), referred to an ERP solution in the internet cloud environment was chosen as the domain knowledge. The complexity of the Cloud ERP business and its knowledge make it very vulnerable to the knowledge retention problem. This paper discusses how the company's essential knowledge can be retained using the LMS system derived from academic environment into the corporate model.

The Shrinkage Model And Expert System Of Plastic Lens Formation

NASA Astrophysics Data System (ADS)

Chang, Rong-Seng

1988-06-01

Shrinkage causes both the appearance & dimension defects of the injected plastic lens. We have built up a model of state equations with the help of finite element analysis program to estimate the volume change (shrinkage and swelling) under the combinations of injection variables such as pressure and temperature etc., then the personal computer expert system has been build up to make that knowledge conveniently available to the user in the model design, process planning, process operation and some other work. The domain knowledge is represented by a R-graph (Relationship-graph) model which states the relationships of variables & equations. This model could be compare with other models in the expert system. If the user has better model to solve the shrinkage problem, the program will evaluate it automatically and a learning file will be trigger by the expert system to teach the user to update their knowledge base and modify the old model by this better model. The Rubin's model and Gilmore's model have been input to the expert system. The conflict has been solved both from the user and the deeper knowledge base. A cube prism and the convex lens examples have been shown in this paper. This program is written by MULISP language in IBM PC-AT. The natural language provides English Explaination of know why and know how and the automatic English translation for the equation rules and the production rules.

Information and knowledge management for sustainable forestry

Treesearch

Alan J. Thomson; Michael Rauscher; Daniel L. Schmoldt; Harald Vacik

2007-01-01

Institutional information and knowledge management often involves a range of systems and technologies to aid decisions and produce reports. Construction of a knowledge system organizing hierarchy facilitates exploration of the interrelationships among knowledge management, inventory and monitoring, statistics and modeling, and policy. Two case studies illustrate these...

Background Knowledge in Learning-Based Relation Extraction

ERIC Educational Resources Information Center

Do, Quang Xuan

2012-01-01

In this thesis, we study the importance of background knowledge in relation extraction systems. We not only demonstrate the benefits of leveraging background knowledge to improve the systems' performance but also propose a principled framework that allows one to effectively incorporate knowledge into statistical machine learning models for…

Models as Relational Categories

NASA Astrophysics Data System (ADS)

Kokkonen, Tommi

2017-11-01

Model-based learning (MBL) has an established position within science education. It has been found to enhance conceptual understanding and provide a way for engaging students in authentic scientific activity. Despite ample research, few studies have examined the cognitive processes regarding learning scientific concepts within MBL. On the other hand, recent research within cognitive science has examined the learning of so-called relational categories. Relational categories are categories whose membership is determined on the basis of the common relational structure. In this theoretical paper, I argue that viewing models as relational categories provides a well-motivated cognitive basis for MBL. I discuss the different roles of models and modeling within MBL (using ready-made models, constructive modeling, and generative modeling) and discern the related cognitive aspects brought forward by the reinterpretation of models as relational categories. I will argue that relational knowledge is vital in learning novel models and in the transfer of learning. Moreover, relational knowledge underlies the coherent, hierarchical knowledge of experts. Lastly, I will examine how the format of external representations may affect the learning of models and the relevant relations. The nature of the learning mechanisms underlying students' mental representations of models is an interesting open question to be examined. Furthermore, the ways in which the expert-like knowledge develops and how to best support it is in need of more research. The discussion and conceptualization of models as relational categories allows discerning students' mental representations of models in terms of evolving relational structures in greater detail than previously done.

Pesticide risk perceptions and the differences between farmers and extensionists: Towards a knowledge-in-context model

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

Ríos-González, Adriana, E-mail: adrianariosg@hotmail.com; The Africa and Latin America Research Groups Network; Jansen, Kees, E-mail: Kees.Jansen@wur.nl

A growing body of literature analyzes farmer perceptions of pesticide risk, but much less attention has been given to differences in risk perception between farmers and technical experts. Furthermore, inconsistencies in knowledge have too easily been explained in terms of lack of knowledge rather than exploring the underlying reasons for particular forms of thinking about pesticide risks. By doing this, the division between expert and lay knowledge has been deepened rather than transcended. Objective: This study aims to understand differences and similarities among the perceptions of pesticide risks of farmers, farm workers, and technical experts such as extensionists, by applyingmore » a social science approach towards knowledge and risk attitudes. Methods: Semi-structured interviews and field observations were conducted to smallholders, farm workers, extensionists, health professionals and scientists involved in the use and handling of pesticides. Subsequently, a survey was carried out to quantify the farmers and extensionists' acceptance or rejection of typical assertions expressed previously in the semi-structured interviews. Results: Smallholders showed to gain knowledge from their own experiences and to adapt pesticides practices, which is a potential basis for transforming notions of pesticide safety and risk reduction strategies. Though extensionists have received formal education, they sometimes develop ideas deviating from the technical perspective. The risk perception of the studied actors appeared to vary according to their role in the agricultural labor process; they varied much less than expected according to their schooling level. Conclusions: Commitment to the technical perspective is not dramatically different for extensionists on the one hand and farmers as well as farm workers on the other hand. Ideas about a supposed lack of knowledge by farmers and the need of formal training are too much driven by a deficit model of knowledge. Further research on risk perceptions of pesticides and training of rural people will benefit from the development of a knowledge-in-context model. -- Highlights: • Researching perceptions of farmers' extensionists and other professionals. • Experts as well as farmers deviate from the technical perspective. • Blaming who is responsible for pesticide problems creates expert-lay division. • Qualitative and quantitative methods, not as complementary but integrated. • Knowledge-in-context model as an alternative to the knowledge-deficit model.« less

Models versus theories as a primary carrier of nursing knowledge: A philosophical argument.

PubMed

Bender, Miriam

2018-01-01

Theories and models are not equivalent. I argue that an orientation towards models as a primary carrier of nursing knowledge overcomes many ongoing challenges in philosophy of nursing science, including the theory-practice divide and the paradoxical pursuit of predictive theories in a discipline that is defined by process and a commitment to the non-reducibility of the health/care experience. Scientific models describe and explain the dynamics of specific phenomenon. This is distinct from theory, which is traditionally defined as propositions that explain and/or predict the world. The philosophical case has been made against theoretical universalism, showing that a theory can be true in its domain, but that no domain is universal. Subsequently, philosophers focused on scientific models argued that they do the work of defining the boundary conditions-the domain(s)-of a theory. Further analysis has shown the ways models can be constructed and function independent of theory, meaning models can comprise distinct, autonomous "carriers of scientific knowledge." Models are viewed as representations of the active dynamics, or mechanisms, of a phenomenon. Mechanisms are entities and activities organized such that they are productive of regular changes. Importantly, mechanisms are by definition not static: change may alter the mechanism and thereby alter or create entirely new phenomena. Orienting away from theory, and towards models, focuses scholarly activity on dynamics and change. This makes models arguably critical to nursing science, enabling the production of actionable knowledge about the dynamics of process and change in health/care. I briefly explore the implications for nursing-and health/care-knowledge and practice. © 2017 John Wiley & Sons Ltd.

Situation Model for Situation-Aware Assistance of Dementia Patients in Outdoor Mobility

PubMed Central

Yordanova, Kristina; Koldrack, Philipp; Heine, Christina; Henkel, Ron; Martin, Mike; Teipel, Stefan; Kirste, Thomas

2017-01-01

Background: Dementia impairs spatial orientation and route planning, thus often affecting the patient’s ability to move outdoors and maintain social activities. Situation-aware deliberative assistive technology devices (ATD) can substitute impaired cognitive function in order to maintain one’s level of social activity. To build such a system, one needs domain knowledge about the patient’s situation and needs. We call this collection of knowledge situation model. Objective: To construct a situation model for the outdoor mobility of people with dementia (PwD). The model serves two purposes: 1) as a knowledge base from which to build an ATD describing the mobility of PwD; and 2) as a codebook for the annotation of the recorded behavior. Methods: We perform systematic knowledge elicitation to obtain the relevant knowledge. The OBO Edit tool is used for implementing and validating the situation model. The model is evaluated by using it as a codebook for annotating the behavior of PwD during a mobility study and interrater agreement is computed. In addition, clinical experts perform manual evaluation and curation of the model. Results: The situation model consists of 101 concepts with 11 relation types between them. The results from the annotation showed substantial overlapping between two annotators (Cohen’s kappa of 0.61). Conclusion: The situation model is a first attempt to systematically collect and organize information related to the outdoor mobility of PwD for the purposes of situation-aware assistance. The model is the base for building an ATD able to provide situation-aware assistance and to potentially improve the quality of life of PwD. PMID:29060937

The effectiveness of physical models in teaching anatomy: a meta-analysis of comparative studies.

PubMed

Yammine, Kaissar; Violato, Claudio

2016-10-01

There are various educational methods used in anatomy teaching. While three dimensional (3D) visualization technologies are gaining ground due to their ever-increasing realism, reports investigating physical models as a low-cost 3D traditional method are still the subject of considerable interest. The aim of this meta-analysis is to quantitatively assess the effectiveness of such models based on comparative studies. Eight studies (7 randomized trials; 1 quasi-experimental) including 16 comparison arms and 820 learners met the inclusion criteria. Primary outcomes were defined as factual, spatial and overall percentage scores. The meta-analytical results are: educational methods using physical models yielded significantly better results when compared to all other educational methods for the overall knowledge outcome (p < 0.001) and for spatial knowledge acquisition (p < 0.001). Significantly better results were also found with regard to the long-retention knowledge outcome (p < 0.01). No significance was found for the factual knowledge acquisition outcome. The evidence in the present systematic review was found to have high internal validity and at least an acceptable strength. In conclusion, physical anatomical models offer a promising tool for teaching gross anatomy in 3D representation due to their easy accessibility and educational effectiveness. Such models could be a practical tool to bring up the learners' level of gross anatomy knowledge at low cost.

Data to knowledge: how to get meaning from your result.

PubMed

Berman, Helen M; Gabanyi, Margaret J; Groom, Colin R; Johnson, John E; Murshudov, Garib N; Nicholls, Robert A; Reddy, Vijay; Schwede, Torsten; Zimmerman, Matthew D; Westbrook, John; Minor, Wladek

2015-01-01

Structural and functional studies require the development of sophisticated 'Big Data' technologies and software to increase the knowledge derived and ensure reproducibility of the data. This paper presents summaries of the Structural Biology Knowledge Base, the VIPERdb Virus Structure Database, evaluation of homology modeling by the Protein Model Portal, the ProSMART tool for conformation-independent structure comparison, the LabDB 'super' laboratory information management system and the Cambridge Structural Database. These techniques and technologies represent important tools for the transformation of crystallographic data into knowledge and information, in an effort to address the problem of non-reproducibility of experimental results.

Knowledgeable Neighbors: a mobile clinic model for disease prevention and screening in underserved communities.

PubMed

Hill, Caterina; Zurakowski, David; Bennet, Jennifer; Walker-White, Rainelle; Osman, Jamie L; Quarles, Aaron; Oriol, Nancy

2012-03-01

The Family Van mobile health clinic uses a "Knowledgeable Neighbor" model to deliver cost-effective screening and prevention activities in underserved neighborhoods in Boston, MA. We have described the Knowledgeable Neighbor model and used operational data collected from 2006 to 2009 to evaluate the service. The Family Van successfully reached mainly minority low-income men and women. Of the clients screened, 60% had previously undetected elevated blood pressure, 14% had previously undetected elevated blood glucose, and 38% had previously undetected elevated total cholesterol. This represents an important model for reaching underserved communities to deliver proven cost-effective prevention activities, both to help control health care costs and to reduce health disparities.

A research-based didactic model for education to promote culturally competent nursing care in Sweden.

PubMed

Gebru, Kerstin; Willman, Ania

2003-01-01

As Sweden changes toward a multicultural society, scientific knowledge of transcultural nursing care becomes increasingly important. Earlier studies in Swedish nursing education have demonstrated a lack of knowledge base in transcultural nursing. Through an extensive review of the literature, a didactic model was developed to help facilitate the establishment of this body of knowledge in transcultural nursing. The article demonstrates how the model applies the content and structure of Leininger's theory of culture care diversity and universality and ethnonursing method in a 3-year nursing program in theory as well as clinical education. The model includes a written guide for faculty members, with references to scientific articles and documents to be used.

Children's knowledge of the earth: a new methodological and statistical approach.

PubMed

Straatemeier, Marthe; van der Maas, Han L J; Jansen, Brenda R J

2008-08-01

In the field of children's knowledge of the earth, much debate has concerned the question of whether children's naive knowledge-that is, their knowledge before they acquire the standard scientific theory-is coherent (i.e., theory-like) or fragmented. We conducted two studies with large samples (N=328 and N=381) using a new paper-and-pencil test, denoted the EARTH (EArth Representation Test for cHildren), to discriminate between these two alternatives. We performed latent class analyses on the responses to the EARTH to test mental models associated with these alternatives. The naive mental models, as formulated by Vosniadou and Brewer, were not supported by the results. The results indicated that children's knowledge of the earth becomes more consistent as children grow older. These findings support the view that children's naive knowledge is fragmented.

Integrating HL7 RIM and ontology for unified knowledge and data representation in clinical decision support systems.

PubMed

Zhang, Yi-Fan; Tian, Yu; Zhou, Tian-Shu; Araki, Kenji; Li, Jing-Song

2016-01-01

The broad adoption of clinical decision support systems within clinical practice has been hampered mainly by the difficulty in expressing domain knowledge and patient data in a unified formalism. This paper presents a semantic-based approach to the unified representation of healthcare domain knowledge and patient data for practical clinical decision making applications. A four-phase knowledge engineering cycle is implemented to develop a semantic healthcare knowledge base based on an HL7 reference information model, including an ontology to model domain knowledge and patient data and an expression repository to encode clinical decision making rules and queries. A semantic clinical decision support system is designed to provide patient-specific healthcare recommendations based on the knowledge base and patient data. The proposed solution is evaluated in the case study of type 2 diabetes mellitus inpatient management. The knowledge base is successfully instantiated with relevant domain knowledge and testing patient data. Ontology-level evaluation confirms model validity. Application-level evaluation of diagnostic accuracy reaches a sensitivity of 97.5%, a specificity of 100%, and a precision of 98%; an acceptance rate of 97.3% is given by domain experts for the recommended care plan orders. The proposed solution has been successfully validated in the case study as providing clinical decision support at a high accuracy and acceptance rate. The evaluation results demonstrate the technical feasibility and application prospect of our approach. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

A Developmental Model of Financial Capability: A Framework for Promoting a Successful Transition to Adulthood

ERIC Educational Resources Information Center

Serido, Joyce; Shim, Soyeon; Tang, Chuanyi

2013-01-01

This study proposes a developmental model of financial capability to understand the process by which young adults acquire the financial knowledge and behaviors needed to manage full-time adult social roles and responsibilities. The model integrates financial knowledge, financial self-beliefs, financial behavior, and well-being into a single…

Problem-Based Learning--Buginese Cultural Knowledge Model--Case Study: Teaching Mathematics at Junior High School

ERIC Educational Resources Information Center

Cheriani, Cheriani; Mahmud, Alimuddin; Tahmir, Suradi; Manda, Darman; Dirawan, Gufran Darma

2015-01-01

This study aims to determine the differences in learning output by using Problem Based Model combines with the "Buginese" Local Cultural Knowledge (PBL-Culture). It is also explores the students activities in learning mathematics subject by using PBL-Culture Models. This research is using Mixed Methods approach that combined quantitative…

The Knowledge Building Paradigm: A Model of Learning for Net Generation Students

ERIC Educational Resources Information Center

Philip, Donald

2005-01-01

In this article Donald Philip describes Knowledge Building, a pedagogy based on the way research organizations function. The global economy, Philip argues, is driving a shift from older, industrial models to the model of the business as a learning organization. The cognitive patterns of today's Net Generation students, formed by lifetime exposure…

Person-Fit and the Rasch Model, with an Application to Knowledge of Logical Quantors.

ERIC Educational Resources Information Center

Molenaar, Ivo W.; Hoijtink, Herbert

1996-01-01

Some specific person-fit results for the Rasch model are presented, followed by an application to a test measuring knowledge of reasoning with logical quantors. Some issues are relevant to all attempts to use person-fit statistics in research, but the special role of the Rasch model is highlighted. (SLD)

Acquiring, Representing, and Evaluating a Competence Model of Diagnostic Strategy.

ERIC Educational Resources Information Center

Clancey, William J.

This paper describes NEOMYCIN, a computer program that models one physician's diagnostic reasoning within a limited area of medicine. NEOMYCIN's knowledge base and reasoning procedure constitute a model of how human knowledge is organized and how it is used in diagnosis. The hypothesis is tested that such a procedure can be used to simulate both…

A Short Commentary on "Where Does Creativity Fit into a Productivist Industrial Model of Knowledge Production?"

ERIC Educational Resources Information Center

Gentry, Marcia

2010-01-01

This article presents the author's brief comment on Hisham B. Ghassib's "Where Does Creativity Fit into a Productivist Industrial Model of Knowledge Production?" Ghassib (2010) takes the reader through an interesting history of human innovation and processes and situates his theory within a productivist model. The deliberate attention to…

Mental Models and Creative Problem-Solving: The Relationship of Objective and Subjective Model Attributes

ERIC Educational Resources Information Center

Mumford, Michael D.; Hester, Kimberly S.; Robledo, Issac C.; Peterson, David R.; Day, Eric A.; Hougen, Dean F.; Barrett, Jamie D.

2012-01-01

Knowledge, or expertise, has been held to contribute to creative problem-solving. In this effort, the relationship of one form of knowledge, mental models, to creative problem-solving was assessed. Undergraduates were asked to solve either a marketing or an education problem calling for creative thought. Prior to generating solutions to these…

Designing Cognitively Diagnostic Assessment for Algebraic Content Knowledge and Thinking Skills

ERIC Educational Resources Information Center

Zhang, Zhidong

2018-01-01

This study explored a diagnostic assessment method that emphasized the cognitive process of algebra learning. The study utilized a design and a theory-driven model to examine the content knowledge. Using the theory driven model, the thinking skills of algebra learning was also examined. A Bayesian network model was applied to represent the theory…

Integrating Social Activity Theory and Critical Discourse Analysis: A Multilayered Methodological Model for Examining Knowledge Mediation in Mentoring

ERIC Educational Resources Information Center

Becher, Ayelet; Orland-Barak, Lily

2016-01-01

This study suggests an integrative qualitative methodological framework for capturing complexity in mentoring activity. Specifically, the model examines how historical developments of a discipline direct mentors' mediation of professional knowledge through the language that they use. The model integrates social activity theory and a framework of…

Identifying and Applying the Communicative and the Constructivist Approaches To Facilitate Transfer of Knowledge in the Bilingual Classroom.

ERIC Educational Resources Information Center

Olivares, Rafael A.; Lemberger, Nancy

2002-01-01

Provides recommendations for the implementation of the communication, constructivism, and transference of knowledge (CCT) model in the education of English language learners (ELLS). Describes how the CCT model is identified in research studies and suggests specific recommendations to facilitate the implementation of the model in the education of…

Literature-Based Scientific Learning: A Collaboration Model

ERIC Educational Resources Information Center

Elrod, Susan L.; Somerville, Mary M.

2007-01-01

Amidst exponential growth of knowledge, student insights into the knowledge creation practices of the scientific community can be furthered by science faculty collaborations with university librarians. The Literature-Based Scientific Learning model advances undergraduates' disciplinary mastery and information literacy through experience with…

Evaluation, Use, and Refinement of Knowledge Representations through Acquisition Modeling

ERIC Educational Resources Information Center

Pearl, Lisa

2017-01-01

Generative approaches to language have long recognized the natural link between theories of knowledge representation and theories of knowledge acquisition. The basic idea is that the knowledge representations provided by Universal Grammar enable children to acquire language as reliably as they do because these representations highlight the…

A Nudge Is Best: Helping Students through the Perry Scheme of Intellectual Development.

ERIC Educational Resources Information Center

Kloss, Robert J.

1994-01-01

This article discusses William G. Perry's model of intellectual development, which posits that college students move through four phases of understanding their relationship to knowledge: dualism (knowledge as received truth), multiplicity (knowledge as opinion), relativism (knowledge as relativistic), and commitment in relativism. Specific…

Knowledge Productivity for Sustainable Innovation: Social Capital as HRD Target

ERIC Educational Resources Information Center

Ehlen, Corry; van der Klink, Marcel; Roentgen, Uta; Curfs, Emile; Boshuizen, Henny

2014-01-01

Purpose: The purpose of this paper is to test the feasibility of a conceptual model on relations between organisational innovation, knowledge productivity and social capital. It explores processes of knowledge productivity for sustainable innovation and associated HRD implications in knowledge intensive organisations, taking the perspective that…

Teacher Education: Considerations for a Knowledge Base Framework.

ERIC Educational Resources Information Center

Tumposky, Nancy

Traditionally, the knowledge base has been defined more as product than process and has encompassed definitions, principles, values, and facts. Recent reforms in teaching and teacher education have brought about efforts to redefine the knowledge base. The reconceptualized knowledge base builds upon the earlier model but gives higher priority to…

Knowledge Management, Human Resource Management, and Higher Education: A Theoretical Model

ERIC Educational Resources Information Center

Brewer, Peggy D.; Brewer, Kristen L.

2010-01-01

Much has been written on the importance of knowledge management, the challenges facing organizations, and the important human resource management activities involved in assuring the acquisition and transfer of knowledge. Higher business education plays an important role in preparing students to assume the knowledge management and human resource…

XML-Based SHINE Knowledge Base Interchange Language

NASA Technical Reports Server (NTRS)

James, Mark; Mackey, Ryan; Tikidjian, Raffi

2008-01-01

The SHINE Knowledge Base Interchange Language software has been designed to more efficiently send new knowledge bases to spacecraft that have been embedded with the Spacecraft Health Inference Engine (SHINE) tool. The intention of the behavioral model is to capture most of the information generally associated with a spacecraft functional model, while specifically addressing the needs of execution within SHINE and Livingstone. As such, it has some constructs that are based on one or the other.

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

Application of artificial intelligence (AI) concepts to the development of space flight parts approval model

NASA Technical Reports Server (NTRS)

Krishnan, G. S.

1997-01-01

A cost effective model which uses the artificial intelligence techniques in the selection and approval of parts is presented. The knowledge which is acquired from the specialists for different part types are represented in a knowledge base in the form of rules and objects. The parts information is stored separately in a data base and is isolated from the knowledge base. Validation, verification and performance issues are highlighted.

The knowledge-value chain: A conceptual framework for knowledge translation in health.

PubMed

Landry, Réjean; Amara, Nabil; Pablos-Mendes, Ariel; Shademani, Ramesh; Gold, Irving

2006-08-01

This article briefly discusses knowledge translation and lists the problems associated with it. Then it uses knowledge-management literature to develop and propose a knowledge-value chain framework in order to provide an integrated conceptual model of knowledge management and application in public health organizations. The knowledge-value chain is a non-linear concept and is based on the management of five dyadic capabilities: mapping and acquisition, creation and destruction, integration and sharing/transfer, replication and protection, and performance and innovation.

The knowledge-value chain: A conceptual framework for knowledge translation in health.

PubMed Central

Landry, Réjean; Amara, Nabil; Pablos-Mendes, Ariel; Shademani, Ramesh; Gold, Irving

2006-01-01

This article briefly discusses knowledge translation and lists the problems associated with it. Then it uses knowledge-management literature to develop and propose a knowledge-value chain framework in order to provide an integrated conceptual model of knowledge management and application in public health organizations. The knowledge-value chain is a non-linear concept and is based on the management of five dyadic capabilities: mapping and acquisition, creation and destruction, integration and sharing/transfer, replication and protection, and performance and innovation. PMID:16917645

Evaluating Environmental Knowledge Dimension Convergence to Assess Educational Programme Effectiveness

NASA Astrophysics Data System (ADS)

Liefländer, Anne K.; Bogner, Franz X.; Kibbe, Alexandra; Kaiser, Florian G.

2015-03-01

One aim of environmental education is fostering sustainable environmental action. Some environmental behaviour models suggest that this can be accomplished in part by improving people's knowledge. Recent studies have identified a distinct, psychometrically supported environmental knowledge structure consisting of system, action-related and effectiveness knowledge. Besides system knowledge, which is most often the focus of such studies, incorporating the other knowledge dimensions into these dimensions was suggested to enhance effectiveness. Our study is among the first to implement these dimensions together in an educational campaign and to use these dimensions to evaluate the effectiveness of a programme on water issues. We designed a four-day environmental education programme on water issues for students at an educational field centre. We applied a newly developed multiple-choice instrument using a pre-, post-, retention test design. The knowledge scales were calibrated with the Rasch model. In addition to the commonly assessed individual change in knowledge level, we also measured the change in knowledge convergence, the extent to which the knowledge dimensions merge as a person's environmental knowledge increases, as an innovative indicator of educational success. Following programme participation, students significantly improved in terms of amount learned in each knowledge dimension and in terms of integration of the knowledge dimensions. The effectiveness knowledge shows the least gain, persistence and convergence, which we explain by considering the dependence of the knowledge dimensions on each other. Finally, we discuss emerging challenges for educational researchers and practical implications for environmental educators.

Design Specifications for the Advanced Instructional Design Advisor (AIDA). Volume 1

DTIC Science & Technology

1992-01-01

research; (3) Describe the knowledge base sufficient to support the varieties of knowledge to be represented in the AIDA model ; (4) Document the...feasibility of continuing the development of the AIDA model . 2.3 Background In Phase I of the AIDA project (Task 0006), (1) the AIDA concept was defined...the AIDA Model A paper-based demonstration of the AIDA instructional design model was performed by using the model to develop a minimal application

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…

Modeling of knowledge transmission by considering the level of forgetfulness in complex networks

NASA Astrophysics Data System (ADS)

Cao, Bin; Han, Shui-hua; Jin, Zhen

2016-06-01

In this study, we establish a general model by considering the level of forgetfulness during knowledge transmission in complex networks, where the level of forgetfulness depends mainly on the number in a crowd who possess knowledge, while the saturated incidence is also considered. In theory, we analyze the stability of the equilibrium points and the transmission threshold R0 is also given. If R0 > 1, then knowledge can ​be transmitted, but if not, it will become completely extinct. In addition, we performed some numerical simulations to verify the reasonability of the theoretical analysis. The results of the simulations also suggest ​that the proportion of the crowd with knowledge will be increased under a better cultural atmosphere.

Rethinking historical and cultural source of spontaneous mental models of water cycle: in the perspective of South Korea

NASA Astrophysics Data System (ADS)

Nam, Younkyeong

2012-06-01

This review explores Ben-Zvi Assaraf, Eshach, Orion, and Alamour's paper titled "Cultural Differences and Students' Spontaneous Models of the Water Cycle: A Case Study of Jewish and Bedouin Children in Israel" by examining how the authors use the concept of spontaneous mental models to explain cultural knowledge source of Bedouin children's mental model of water compared to Jewish children's mental model of water in nature. My response to Ben-Zvi Assaraf et al.'s work expands upon their explanations of the Bedouin children's cultural knowledge source. Bedouin children's mental model is based on their culture, religion, place of living and everyday life practices related to water. I suggest a different knowledge source for spontaneous mental model of water in nature based on unique history and traditions of South Korea where people think of water in nature in different ways. This forum also addresses how western science dominates South Korean science curriculum and ways of assessing students' conceptual understanding of scientific concepts. Additionally I argue that western science curriculum models could diminish Korean students' understanding of natural world which are based on Korean cultural ways of thinking about the natural world. Finally, I also suggest two different ways of considering this unique knowledge source for a more culturally relevant teaching Earth system education.

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

Narrative review of frameworks for translating research evidence into policy and practice.

PubMed

Milat, Andrew J; Li, Ben

2017-02-15

A significant challenge in research translation is that interested parties interpret and apply the associated terms and conceptual frameworks in different ways. The purpose of this review was to: a) examine different research translation frameworks; b) examine the similarities and differences between the frameworks; and c) identify key strengths and weaknesses of the models when they are applied in practice. The review involved a keyword search of PubMed. The search string was (translational research OR knowledge translation OR evidence to practice) AND (framework OR model OR theory) AND (public health OR health promotion OR medicine). Included studies were published in English between January 1990 and December 2014, and described frameworks, models or theories associated with research translation. The final review included 98 papers, and 41 different frameworks and models were identified. The most frequently applied knowledge translation framework in the literature was RE-AIM, followed by the knowledge translation continuum or 'T' models, the Knowledge to Action framework, the PARiHS framework, evidence based public health models, and the stages of research and evaluation model. The models identified in this review stem from different fields, including implementation science, basic and medical sciences, health services research and public health, and propose different but related pathways to closing the research-practice gap.

Critical review of membrane bioreactor models--part 1: biokinetic and filtration models.

PubMed

Naessens, W; Maere, T; Nopens, I

2012-10-01

Membrane bioreactor technology exists for a couple of decades, but has not yet overwhelmed the market due to some serious drawbacks of which operational cost due to fouling is the major contributor. Knowledge buildup and optimisation for such complex systems can significantly benefit from mathematical modelling. In this paper, the vast literature on modelling MBR biokinetics and filtration is critically reviewed. It was found that models cover the wide range of empirical to detailed mechanistic descriptions and have mainly been used for knowledge development and to a lesser extent for system optimisation/control. Moreover, studies are still predominantly performed at lab or pilot scale. Trends are discussed, knowledge gaps identified and interesting routes for further research suggested. Copyright © 2012 Elsevier Ltd. All rights reserved.

Local versus global knowledge in the Barabási-Albert scale-free network model.

PubMed

Gómez-Gardeñes, Jesús; Moreno, Yamir

2004-03-01

The scale-free model of Barabási and Albert (BA) gave rise to a burst of activity in the field of complex networks. In this paper, we revisit one of the main assumptions of the model, the preferential attachment (PA) rule. We study a model in which the PA rule is applied to a neighborhood of newly created nodes and thus no global knowledge of the network is assumed. We numerically show that global properties of the BA model such as the connectivity distribution and the average shortest path length are quite robust when there is some degree of local knowledge. In contrast, other properties such as the clustering coefficient and degree-degree correlations differ and approach the values measured for real-world networks.

Automation of energy demand forecasting

NASA Astrophysics Data System (ADS)

Siddique, Sanzad

Automation of energy demand forecasting saves time and effort by searching automatically for an appropriate model in a candidate model space without manual intervention. This thesis introduces a search-based approach that improves the performance of the model searching process for econometrics models. Further improvements in the accuracy of the energy demand forecasting are achieved by integrating nonlinear transformations within the models. This thesis introduces machine learning techniques that are capable of modeling such nonlinearity. Algorithms for learning domain knowledge from time series data using the machine learning methods are also presented. The novel search based approach and the machine learning models are tested with synthetic data as well as with natural gas and electricity demand signals. Experimental results show that the model searching technique is capable of finding an appropriate forecasting model. Further experimental results demonstrate an improved forecasting accuracy achieved by using the novel machine learning techniques introduced in this thesis. This thesis presents an analysis of how the machine learning techniques learn domain knowledge. The learned domain knowledge is used to improve the forecast accuracy.

Computational Modeling for Language Acquisition: A Tutorial With Syntactic Islands.

PubMed

Pearl, Lisa S; Sprouse, Jon

2015-06-01

Given the growing prominence of computational modeling in the acquisition research community, we present a tutorial on how to use computational modeling to investigate learning strategies that underlie the acquisition process. This is useful for understanding both typical and atypical linguistic development. We provide a general overview of why modeling can be a particularly informative tool and some general considerations when creating a computational acquisition model. We then review a concrete example of a computational acquisition model for complex structural knowledge referred to as syntactic islands. This includes an overview of syntactic islands knowledge, a precise definition of the acquisition task being modeled, the modeling results, and how to meaningfully interpret those results in a way that is relevant for questions about knowledge representation and the learning process. Computational modeling is a powerful tool that can be used to understand linguistic development. The general approach presented here can be used to investigate any acquisition task and any learning strategy, provided both are precisely defined.

Multi-model-based interactive authoring environment for creating shareable medical knowledge.

PubMed

Ali, Taqdir; Hussain, Maqbool; Ali Khan, Wajahat; Afzal, Muhammad; Hussain, Jamil; Ali, Rahman; Hassan, Waseem; Jamshed, Arif; Kang, Byeong Ho; Lee, Sungyoung

2017-10-01

Technologically integrated healthcare environments can be realized if physicians are encouraged to use smart systems for the creation and sharing of knowledge used in clinical decision support systems (CDSS). While CDSSs are heading toward smart environments, they lack support for abstraction of technology-oriented knowledge from physicians. Therefore, abstraction in the form of a user-friendly and flexible authoring environment is required in order for physicians to create shareable and interoperable knowledge for CDSS workflows. Our proposed system provides a user-friendly authoring environment to create Arden Syntax MLM (Medical Logic Module) as shareable knowledge rules for intelligent decision-making by CDSS. Existing systems are not physician friendly and lack interoperability and shareability of knowledge. In this paper, we proposed Intelligent-Knowledge Authoring Tool (I-KAT), a knowledge authoring environment that overcomes the above mentioned limitations. Shareability is achieved by creating a knowledge base from MLMs using Arden Syntax. Interoperability is enhanced using standard data models and terminologies. However, creation of shareable and interoperable knowledge using Arden Syntax without abstraction increases complexity, which ultimately makes it difficult for physicians to use the authoring environment. Therefore, physician friendliness is provided by abstraction at the application layer to reduce complexity. This abstraction is regulated by mappings created between legacy system concepts, which are modeled as domain clinical model (DCM) and decision support standards such as virtual medical record (vMR) and Systematized Nomenclature of Medicine - Clinical Terms (SNOMED CT). We represent these mappings with a semantic reconciliation model (SRM). The objective of the study is the creation of shareable and interoperable knowledge using a user-friendly and flexible I-KAT. Therefore we evaluated our system using completeness and user satisfaction criteria, which we assessed through the system- and user-centric evaluation processes. For system-centric evaluation, we compared the implementation of clinical information modelling system requirements in our proposed system and in existing systems. The results suggested that 82.05% of the requirements were fully supported, 7.69% were partially supported, and 10.25% were not supported by our system. In the existing systems, 35.89% of requirements were fully supported, 28.20% were partially supported, and 35.89% were not supported. For user-centric evaluation, the assessment criterion was 'ease of use'. Our proposed system showed 15 times better results with respect to MLM creation time than the existing systems. Moreover, on average, the participants made only one error in MLM creation using our proposed system, but 13 errors per MLM using the existing systems. We provide a user-friendly authoring environment for creation of shareable and interoperable knowledge for CDSS to overcome knowledge acquisition complexity. The authoring environment uses state-of-the-art decision support-related clinical standards with increased ease of use. Copyright © 2017 Elsevier B.V. All rights reserved.

VIP: A knowledge-based design aid for the engineering of space systems

NASA Technical Reports Server (NTRS)

Lewis, Steven M.; Bellman, Kirstie L.

1990-01-01

The Vehicles Implementation Project (VIP), a knowledge-based design aid for the engineering of space systems is described. VIP combines qualitative knowledge in the form of rules, quantitative knowledge in the form of equations, and other mathematical modeling tools. The system allows users rapidly to develop and experiment with models of spacecraft system designs. As information becomes available to the system, appropriate equations are solved symbolically and the results are displayed. Users may browse through the system, observing dependencies and the effects of altering specific parameters. The system can also suggest approaches to the derivation of specific parameter values. In addition to providing a tool for the development of specific designs, VIP aims at increasing the user's understanding of the design process. Users may rapidly examine the sensitivity of a given parameter to others in the system and perform tradeoffs or optimizations of specific parameters. A second major goal of VIP is to integrate the existing corporate knowledge base of models and rules into a central, symbolic form.

The process-knowledge model of health literacy: evidence from a componential analysis of two commonly used measures.

PubMed

Chin, Jessie; Morrow, Daniel G; Stine-Morrow, Elizabeth A L; Conner-Garcia, Thembi; Graumlich, James F; Murray, Michael D

2011-01-01

We investigated the effects of domain-general processing capacity (fluid ability such as working memory), domain-general knowledge (crystallized ability such as vocabulary), and domain-specific health knowledge for two of the most commonly used measures of health literacy (S-TOFHLA and REALM). One hundred forty six community-dwelling older adults participated; 103 had been diagnosed with hypertension. The results showed that older adults who had higher levels of processing capacity or knowledge (domain-general or health) performed better on both of the health literacy measures. Processing capacity interacted with knowledge: Processing capacity had a lower level of association with health literacy for participants with more knowledge than for those with lower levels of knowledge, suggesting that knowledge may offset the effects of processing capacity limitations on health literacy. Furthermore, performance on the two health literacy measures appeared to reflect a different weighting for the three types of abilities. S-TOFHLA performance reflected processing capacity as well as general knowledge, whereas performance on the REALM depended more on general and health knowledge than on processing capacity. The findings support a process-knowledge model of health literacy among older adults, and have implications for selecting health literacy measures in various health care contexts.

Translational systems biology using an agent-based approach for dynamic knowledge representation: An evolutionary paradigm for biomedical research.

PubMed

An, Gary C

2010-01-01

The greatest challenge facing the biomedical research community is the effective translation of basic mechanistic knowledge into clinically effective therapeutics. This challenge is most evident in attempts to understand and modulate "systems" processes/disorders, such as sepsis, cancer, and wound healing. Formulating an investigatory strategy for these issues requires the recognition that these are dynamic processes. Representation of the dynamic behavior of biological systems can aid in the investigation of complex pathophysiological processes by augmenting existing discovery procedures by integrating disparate information sources and knowledge. This approach is termed Translational Systems Biology. Focusing on the development of computational models capturing the behavior of mechanistic hypotheses provides a tool that bridges gaps in the understanding of a disease process by visualizing "thought experiments" to fill those gaps. Agent-based modeling is a computational method particularly well suited to the translation of mechanistic knowledge into a computational framework. Utilizing agent-based models as a means of dynamic hypothesis representation will be a vital means of describing, communicating, and integrating community-wide knowledge. The transparent representation of hypotheses in this dynamic fashion can form the basis of "knowledge ecologies," where selection between competing hypotheses will apply an evolutionary paradigm to the development of community knowledge.

Linking Earth Observations and Models to Societal Information Needs: The Case of Coastal Flooding

NASA Astrophysics Data System (ADS)

Buzzanga, B. A.; Plag, H. P.

2016-12-01

Coastal flooding is expected to increase in many areas due to sea level rise (SLR). Many societal applications such as emergency planning and designing public services depend on information on how the flooding spectrum may change as a result of SLR. To identify the societal information needs a conceptual model is needed that identifies the key stakeholders, applications, and information and observation needs. In the context of the development of the Global Earth Observation System of Systems (GEOSS), which is implemented by the Group on Earth Observations (GEO), the Socio-Economic and Environmental Information Needs Knowledge Base (SEE-IN KB) is developed as part of the GEOSS Knowledge Base. A core function of the SEE-IN KB is to facilitate the linkage of societal information needs to observations, models, information and knowledge. To achieve this, the SEE-IN KB collects information on objects such as user types, observational requirements, societal goals, models, and datasets. Comprehensive information concerning the interconnections between instances of these objects is used to capture the connectivity and to establish a conceptual model as a network of networks. The captured connectivity can be used in searches to allow users to discover products and services for their information needs, and providers to search for users and applications benefiting from their products. It also allows to answer "What if?" questions and supports knowledge creation. We have used the SEE-IN KB to develop a conceptual model capturing the stakeholders in coastal flooding and their information needs, and to link these elements to objects. We show how the knowledge base enables the transition of scientific data to useable information by connecting individuals such as city managers to flood maps. Within the knowledge base, these same users can request information that improves their ability to make specific planning decisions. These needs are linked to entities within research institutions that have the capabilities to meet them. Further, current research such as that investigating precipitation-induced flooding under different SLR scenarios is linked to the users who benefit from the knowledge, effectively creating a bi-directional channel between science and society that increases knowledge and improves foresight.

How students learn to coordinate knowledge of physical and mathematical models in cellular physiology

NASA Astrophysics Data System (ADS)

Lira, Matthew

This dissertation explores the Knowledge in Pieces (KiP) theory to account for how students learn to coordinate knowledge of mathematical and physical models in biology education. The KiP approach characterizes student knowledge as a fragmented collection of knowledge elements as opposed to stable and theory-like knowledge. This dissertation sought to use this theoretical lens to account for how students understand and learn with mathematical models and representations, such as equations. Cellular physiology provides a quantified discipline that leverages concepts from mathematics, physics, and chemistry to understand cellular functioning. Therefore, this discipline provides an exemplary context for assessing how biology students think and learn with mathematical models. In particular, the resting membrane potential provides an exemplary concept well defined by models of dynamic equilibrium borrowed from physics and chemistry. In brief, membrane potentials, or voltages, "rest" when the electrical and chemical driving forces for permeable ionic species are equal in magnitude but opposite in direction. To assess students' understandings of this concept, this dissertation employed three studies: the first study employed the cognitive clinical interview to assess student thinking in the absence and presence of equations. The second study employed an intervention to assess student learning and the affordances of an innovative assessment. The third student employed a human-computer-interaction paradigm to assess how students learn with a novel multi-representational technology. Study 1 revealed that students saw only one influence--the chemical gradient--and that students coordinated knowledge of only this gradient with the related equations. Study 2 revealed that students benefited from learning with the multi-representational technology and that the assessment detected performance gains across both calculation and explanation tasks. Last, Study 3 revealed how students shift from recognizing one influence to recognizing both the chemical and the electrical gradients as responsible for a cell's membrane potential reaching dynamic equilibrium. Together, the studies illustrate that to coordinate knowledge, students need opportunities to reflect upon relations between representations of mathematical and physical models as well as distinguish between physical quantities such as molarities for ions and transmembrane voltages.

Modelling Teaching Strategies.

ERIC Educational Resources Information Center

Major, Nigel

1995-01-01

Describes a modelling language for representing teaching strategies, based in the context of the COCA intelligent tutoring system. Examines work on meta-reasoning in knowledge-based systems and describes COCA's architecture, giving details of the language used for representing teaching knowledge. Discusses implications for future work. (AEF)

Chemical leasing business models: a contribution to the effective risk management of chemical substances.

PubMed

Ohl, Cornelia; Moser, Frank

2007-08-01

Chemicals indisputably contribute greatly to the well-being of modern societies. Apart from such benefits, however, chemicals often pose serious threats to human health and the environment when improperly handled. Therefore, the European Commission has proposed a regulatory framework for the Registration, Evaluation and Authorization of Chemicals (REACH) that requires companies using chemicals to gather pertinent information on the properties of these substances. In this article, we argue that the crucial aspect of this information management may be the honesty and accuracy of the transfer of relevant knowledge from the producer of a chemical to its user. This may be particularly true if the application of potentially hazardous chemicals is not part of the user's core competency. Against this background, we maintain that the traditional sales concept provides no incentives for transferring this knowledge. The reason is that increased user knowledge of a chemical's properties may raise the efficiency of its application. That is, excessive and unnecessary usage will be eliminated. This, in turn, would lower the amount of chemicals sold and in competitive markets directly decrease profits of the producer. Through the introduction of chemical leasing business models, we attempt to present a strategy to overcome the incentive structure of classical sales models, which is counterproductive for the transfer of knowledge. By introducing two models (a Model A that differs least and a Model B that differs most from traditional sales concepts), we demonstrate that chemical leasing business models are capable of accomplishing the goal of Registration, Evaluation and Authorization of Chemicals: to effectively manage the risk of chemicals by reducing the total quantity of chemicals used, either by a transfer of applicable knowledge from the lessor to the lessee (Model A) or by efficient application of the chemical by the lessor him/herself (Model B).

SISL and SIRL: Two knowledge dissemination models with leader nodes on cooperative learning networks

NASA Astrophysics Data System (ADS)

Li, Jingjing; Zhang, Yumei; Man, Jiayu; Zhou, Yun; Wu, Xiaojun

2017-02-01

Cooperative learning is one of the most effective teaching methods, which has been widely used. Students' mutual contact forms a cooperative learning network in this process. Our previous research demonstrated that the cooperative learning network has complex characteristics. This study aims to investigating the dynamic spreading process of the knowledge in the cooperative learning network and the inspiration of leaders in this process. To this end, complex network transmission dynamics theory is utilized to construct the knowledge dissemination model of a cooperative learning network. Based on the existing epidemic models, we propose a new susceptible-infected-susceptible-leader (SISL) model that considers both students' forgetting and leaders' inspiration, and a susceptible-infected-removed-leader (SIRL) model that considers students' interest in spreading and leaders' inspiration. The spreading threshold λcand its impact factors are analyzed. Then, numerical simulation and analysis are delivered to reveal the dynamic transmission mechanism of knowledge and leaders' role. This work is of great significance to cooperative learning theory and teaching practice. It also enriches the theory of complex network transmission dynamics.

Realtime Knowledge Management (RKM): From an International Space Station (ISS) Point of View

NASA Technical Reports Server (NTRS)

Robinson, Peter I.; McDermott, William; Alena, Richard L.

2004-01-01

We are developing automated methods to provide realtime access to spacecraft domain knowledge relevant a spacecraft's current operational state. The method is based upon analyzing state-transition signatures in the telemetry stream. A key insight is that documentation relevant to a specific failure mode or operational state is related to the structure and function of spacecraft systems. This means that diagnostic dependency and state models can provide a roadmap for effective documentation navigation and presentation. Diagnostic models consume the telemetry and derive a high-level state description of the spacecraft. Each potential spacecraft state description is matched against the predictions of models that were developed from information found in the pages and sections in the relevant International Space Station (ISS) documentation and reference materials. By annotating each model fragment with the domain knowledge sources from which it was derived we can develop a system that automatically selects those documents representing the domain knowledge encapsulated by the models that compute the current spacecraft state. In this manner, when the spacecraft state changes, the relevant documentation context and presentation will also change.

Effective behavioral modeling and prediction even when few exemplars are available

NASA Astrophysics Data System (ADS)

Goan, Terrance; Kartha, Neelakantan; Kaneshiro, Ryan

2006-05-01

While great progress has been made in the lowest levels of data fusion, practical advances in behavior modeling and prediction remain elusive. The most critical limitation of existing approaches is their inability to support the required knowledge modeling and continuing refinement under realistic constraints (e.g., few historic exemplars, the lack of knowledge engineering support, and the need for rapid system deployment). This paper reports on our ongoing efforts to develop Propheteer, a system which will address these shortcomings through two primary techniques. First, with Propheteer we abandon the typical consensus-driven modeling approaches that involve infrequent group decision making sessions in favor of an approach that solicits asynchronous knowledge contributions (in the form of alternative future scenarios and indicators) without burdening the user with endless certainty or probability estimates. Second, we enable knowledge contributions by personnel beyond the typical core decision making group, thereby casting light on blind spots, mitigating human biases, and helping maintain the currency of the developed behavior models. We conclude with a discussion of the many lessons learned in the development of our prototype Propheteer system.

Mental representation of normal subjects about the sources of knowledge in different semantic categories and unique entities.

PubMed

Gainotti, Guido; Ciaraffa, Francesca; Silveri, Maria Caterina; Marra, Camillo

2009-11-01

According to the "sensory-motor model of semantic knowledge," different categories of knowledge differ for the weight that different "sources of knowledge" have in their representation. Our study aimed to evaluate this model, checking if subjective evaluations given by normal subjects confirm the different weight that various sources of knowledge have in the representation of different biological and artifact categories and of unique entities, such as famous people or monuments. Results showed that the visual properties are considered as the main source of knowledge for all the living and nonliving categories (as well as for unique entities), but that the clustering of these "sources of knowledge" is different for biological and artifacts categories. Visual data are, indeed, mainly associated with other perceptual (auditory, olfactory, gustatory, and tactual) attributes in the mental representation of living beings and unique entities, whereas they are associated with action-related properties and tactile information in the case of artifacts.

Knowledge workers and knowledge-intense organizations, Part 2: Designing and managing for productivity.

PubMed

Weaver, D; Sorrells-Jones, J

1999-09-01

Our economy is shifting from a hard goods and material products base to one in which knowledge is the primary mode of production. Organizations are experimenting with designs that support knowledge work by clustering individuals with different but complementary skills in focused teams. The goal is to increase applied knowledge that furthers the organization's strategic intent. The team-based knowledge work model holds promise for healthcare organizations that are under pressure to use knowledge to improve clinical care, integrate care across disciplines and settings, and accept accountability for costs. However, the shift from the traditional bureaucratic model to the flexible team-based design mandates changes in the design of the organization, the role of leadership, and the attributes of the teams and team members. In Part 2 of this three-part series, the authors explore the necessary design changes and the new roles for leadership, teams, and their members. Additionally, implications for healthcare clinicians, particularly nurses, are discussed.

The Exploration-Exploitation Dilemma: A Multidisciplinary Framework

PubMed Central

Berger-Tal, Oded; Meron, Ehud; Saltz, David

2014-01-01

The trade-off between the need to obtain new knowledge and the need to use that knowledge to improve performance is one of the most basic trade-offs in nature, and optimal performance usually requires some balance between exploratory and exploitative behaviors. Researchers in many disciplines have been searching for the optimal solution to this dilemma. Here we present a novel model in which the exploration strategy itself is dynamic and varies with time in order to optimize a definite goal, such as the acquisition of energy, money, or prestige. Our model produced four very distinct phases: Knowledge establishment, Knowledge accumulation, Knowledge maintenance, and Knowledge exploitation, giving rise to a multidisciplinary framework that applies equally to humans, animals, and organizations. The framework can be used to explain a multitude of phenomena in various disciplines, such as the movement of animals in novel landscapes, the most efficient resource allocation for a start-up company, or the effects of old age on knowledge acquisition in humans. PMID:24756026

Mississippi State University Center for Air Sea Technology. FY93 and FY 94 Research Program in Navy Ocean Modeling and Prediction

DTIC Science & Technology

1994-09-30

relational versus object oriented DBMS, knowledge discovery, data models, rnetadata, data filtering, clustering techniques, and synthetic data. A secondary...The first was the investigation of Al/ES Lapplications (knowledge discovery, data mining, and clustering ). Here CAST collabo.rated with Dr. Fred Petry...knowledge discovery system based on clustering techniques; implemented an on-line data browser to the DBMS; completed preliminary efforts to apply object

A prototype knowledge-based simulation support system

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

Hill, T.R.; Roberts, S.D.

1987-04-01

As a preliminary step toward the goal of an intelligent automated system for simulation modeling support, we explore the feasibility of the overall concept by generating and testing a prototypical framework. A prototype knowledge-based computer system was developed to support a senior level course in industrial engineering so that the overall feasibility of an expert simulation support system could be studied in a controlled and observable setting. The system behavior mimics the diagnostic (intelligent) process performed by the course instructor and teaching assistants, finding logical errors in INSIGHT simulation models and recommending appropriate corrective measures. The system was programmed inmore » a non-procedural language (PROLOG) and designed to run interactively with students working on course homework and projects. The knowledge-based structure supports intelligent behavior, providing its users with access to an evolving accumulation of expert diagnostic knowledge. The non-procedural approach facilitates the maintenance of the system and helps merge the roles of expert and knowledge engineer by allowing new knowledge to be easily incorporated without regard to the existing flow of control. The background, features and design of the system are describe and preliminary results are reported. Initial success is judged to demonstrate the utility of the reported approach and support the ultimate goal of an intelligent modeling system which can support simulation modelers outside the classroom environment. Finally, future extensions are suggested.« less

Team Knowledge Sharing Intervention Effects on Team Shared Mental Models and Student Performance in an Undergraduate Science Course

ERIC Educational Resources Information Center

Sikorski, Eric G.; Johnson, Tristan E.; Ruscher, Paul H.

2012-01-01

The purpose of this study was to examine the effects of a shared mental model (SMM) based intervention on student team mental model similarity and ultimately team performance in an undergraduate meteorology course. The team knowledge sharing (TKS) intervention was designed to promote team reflection, communication, and improvement planning.…

Teachers' Perceptions of the Teaching of Acids and Bases in Swedish Upper Secondary Schools

ERIC Educational Resources Information Center

Drechsler, Michal; Van Driel, Jan

2009-01-01

We report in this paper on a study of chemistry teachers' perceptions of their teaching in upper secondary schools in Sweden, regarding models of acids and bases, especially the Bronsted and the Arrhenius model. A questionnaire consisting of a Likert-type scale was developed, which focused on teachers' knowledge of different models, knowledge of…

Effects of Three Comprehensive Models of Vocabulary Instruction during Shared Storybook Read Alouds on Kindergartener's Tier Two Target Word Knowledge

ERIC Educational Resources Information Center

Steuber, Julie Ann

2013-01-01

The purpose of this study was to determine the effectiveness of three researcher-designed experimental models of vocabulary instruction during shared storybook read alouds on kindergarten children's Tier Two target word learning and maintenance of word knowledge. The Integrated Model consisted of two readings of the same storybook, direct…

Sales Training for Army Recruiter Success: Modeling the Sales Strategies and Skills of Excellent Recruiters

DTIC Science & Technology

1987-11-01

strategies used by excellent Army recruiters. Neurolinguistic programming (NLP) was used as the protocol for modeling performance and acquiring...Behavioral and Social Sciences 3001 Eisenhower Avenue, Alexandria, VA 22333-5600 10. PROGRAM ELEMENT. PROJECT. TASK ARE* 4 WORK UNIT...Modeling ’Expert knowledge,, Neurolinguistics Knowledge engineering; Recruiting Sales, &’ Sales cycle Sales skills Sales strategies 20

Computer Model of the Empirical Knowledge of Physics Formation: Coordination with Testing Results

ERIC Educational Resources Information Center

Mayer, Robert V.

2016-01-01

The use of method of imitational modeling to study forming the empirical knowledge in pupil's consciousness is discussed. The offered model is based on division of the physical facts into three categories: 1) the facts established in everyday life; 2) the facts, which the pupil can experimentally establish at a physics lesson; 3) the facts which…

Imaging, Imagining Knowledge in Higher Education Curricula: New Visions and Troubled Thresholds

ERIC Educational Resources Information Center

Parker, Jan

2013-01-01

It is urgent that we re-examine models of knowledge and knowledge-making within the university, at this time of open learning and deregulated multi-million dollar and euro open science hubs and portals. For otherwise, we are bound into "crude" instrumentalism, "delivering" "knowledge packets" rather than seeing our…

A Unified Model of Knowledge Sharing Behaviours: Theoretical Development and Empirical Test

ERIC Educational Resources Information Center

Chennamaneni, Anitha; Teng, James T. C.; Raja, M. K.

2012-01-01

Research and practice on knowledge management (KM) have shown that information technology alone cannot guarantee that employees will volunteer and share knowledge. While previous studies have linked motivational factors to knowledge sharing (KS), we took a further step to thoroughly examine this theoretically and empirically. We developed a…

The Co-Evolution of Knowledge and Event Memory

ERIC Educational Resources Information Center

Nelson, Angela B.; Shiffrin, Richard M.

2013-01-01

We present a theoretical framework and a simplified simulation model for the co-evolution of knowledge and event memory, both termed SARKAE (Storing and Retrieving Knowledge and Events). Knowledge is formed through the accrual of individual events, a process that operates in tandem with the storage of individual event memories. In 2 studies, new…

Japan InK: Distributing the Information Networked Knowledge (InK) Base to the Japanese Research Community.

ERIC Educational Resources Information Center

Naito, Eisuke

This paper discusses knowledge management (KM) in relation to a shared cataloging system in Japanese university libraries. The first section describes the Japanese scene related to knowledge management and the working environment, including the SECI (Socialization, Externalization, Combination, Internalization) model, the context of knowledge, and…

Transformation of Topic-Specific Professional Knowledge into Personal Pedagogical Content Knowledge through Lesson Planning

ERIC Educational Resources Information Center

Stender, Anita; Brückmann, Maja; Neumann, Knut

2017-01-01

This study investigates the relationship between two different types of pedagogical content knowledge (PCK): the topic-specific professional knowledge (TSPK) and practical routines, so-called teaching scripts. Based on the Transformation Model of Lesson Planning, we assume that teaching scripts originate from a transformation of TSPK during lesson…

Introducing the Intellectual Capital Interplay Model: Advancing Knowledge Frameworks in the Not-for-Profit Environment of Higher Education

ERIC Educational Resources Information Center

Helm-Stevens, Roxanne; Brown, Kneeland C.; Russell, Julia K.

2011-01-01

Knowledge management has the potential to develop strategic advantage and enhance the performance of an organization in terms of productivity and business process efficiency. For this reason, organizations are contributing significant resources to knowledge management; investing in information location and implementing knowledge management…

A Process-Based Knowledge Management System for Schools: A Case Study in Taiwan

ERIC Educational Resources Information Center

Lee, Chi-Lung; Lu, Hsi-Peng; Yang, Chyan; Hou, Huei-Tse

2010-01-01

Knowledge management systems, or KMSs, have been widely adopted in business organizations, yet little research exists on the actual integration of the knowledge management model and the application of KMSs in secondary schools. In the present study, the common difficulties and limitations regarding the implementation of knowledge management into…

Relationships between Teachers' Metacognitive Knowledge and Students' Metacognitive Knowledge and Reading Achievement

ERIC Educational Resources Information Center

Soodla, Piret; Jõgi, Anna-Liisa; Kikas, Eve

2017-01-01

The study examined the relationships between teachers' metacognitive knowledge of reading strategies and their students' metacognitive knowledge and reading comprehension. The study was carried out among language art teachers (N = 34) and their students (N = 534) in the last year of primary school (ninth grade) in Estonia. Multilevel modeling was…

Knowledge, Understanding, and Behavior

DTIC Science & Technology

2003-10-04

UNCLASSIFIED Defense Technical Information Center Compilation Part Notice ADP021346 TITLE: Knowledge , Understanding , and Behavior DISTRIBUTION... Knowledge , Understanding , and Behavior James Albus Intelligent Systems Division , National Institute of Standards and Technology, Gaithersburg, MD 20899 301... understanding ? How does understanding the world works, and knowledge of procedures for using influence behavior? These are philosophical questions models to

Analysis of Knowledge-Sharing Evolutionary Game in University Teacher Team

ERIC Educational Resources Information Center

Huo, Mingkui

2013-01-01

The knowledge-sharing activity is a major drive force behind the progress and innovation of university teacher team. Based on the evolutionary game theory, this article analyzes the knowledge-sharing process model of this team, studies the influencing mechanism of various factors such as knowledge aggregate gap, incentive coefficient and risk…

Vision, knowledge, and assertion.

PubMed

Turri, John

2016-04-01

I report two experiments studying the relationship among explicit judgments about what people see, know, and should assert. When an object of interest was surrounded by visibly similar items, it diminished people's willingness to judge that an agent sees, knows, and should tell others that it is present. This supports the claim, made by many philosophers, that inhabiting a misleading environment intuitively decreases our willingness to attribute perception and knowledge. However, contrary to stronger claims made by some philosophers, inhabiting a misleading environment does not lead to the opposite pattern whereby people deny perception and knowledge. Causal modeling suggests a specific psychological model of how explicit judgments about perception, knowledge, and assertability are made: knowledge attributions cause perception attributions, which in turn cause assertability attributions. These findings advance understanding of how these three important judgments are made, provide new evidence that knowledge is the norm of assertion, and highlight some important subtleties in folk epistemology. Copyright © 2016 Elsevier Inc. All rights reserved.

Young children's acquisition of knowledge about the Earth: A longitudinal study.

PubMed

Hannust, Triin; Kikas, Eve

2010-10-01

This longitudinal study examined the acquisition of early knowledge of astronomy to determine whether children's knowledge at any point in time is consistent with a naive "mental model." Children were first assessed by means of open questions and drawing tasks at 2 and 3 years of age (N=143). The knowledge was reassessed over the course of the following 3 years. The results showed that although a few indications of naive mental models were found, in most cases young children's knowledge was fragmented and accurate knowledge was often expressed alongside inaccurate/synthetic ideas. Furthermore, it was shown that children need to know scientific facts before they start taking the global perspective when describing the world and, when faced with ambiguous open questions, children often experience difficulties that can induce them to change the types of answers they provide. Copyright 2010 Elsevier Inc. All rights reserved.

The dynamics of meaningful social interactions and the emergence of collective knowledge

PubMed Central

Dankulov, Marija Mitrović; Melnik, Roderick; Tadić, Bosiljka

2015-01-01

Collective knowledge as a social value may arise in cooperation among actors whose individual expertise is limited. The process of knowledge creation requires meaningful, logically coordinated interactions, which represents a challenging problem to physics and social dynamics modeling. By combining two-scale dynamics model with empirical data analysis from a well-known Questions & Answers system Mathematics, we show that this process occurs as a collective phenomenon in an enlarged network (of actors and their artifacts) where the cognitive recognition interactions are properly encoded. The emergent behavior is quantified by the information divergence and innovation advancing of knowledge over time and the signatures of self-organization and knowledge sharing communities. These measures elucidate the impact of each cognitive element and the individual actor’s expertise in the collective dynamics. The results are relevant to stochastic processes involving smart components and to collaborative social endeavors, for instance, crowdsourcing scientific knowledge production with online games. PMID:26174482

Conceptual model of knowledge base system

NASA Astrophysics Data System (ADS)

Naykhanova, L. V.; Naykhanova, I. V.

2018-05-01

In the article, the conceptual model of the knowledge based system by the type of the production system is provided. The production system is intended for automation of problems, which solution is rigidly conditioned by the legislation. A core component of the system is a knowledge base. The knowledge base consists of a facts set, a rules set, the cognitive map and ontology. The cognitive map is developed for implementation of a control strategy, ontology - the explanation mechanism. Knowledge representation about recognition of a situation in the form of rules allows describing knowledge of the pension legislation. This approach provides the flexibility, originality and scalability of the system. In the case of changing legislation, it is necessary to change the rules set. This means that the change of the legislation would not be a big problem. The main advantage of the system is that there is an opportunity to be adapted easily to changes of the legislation.

The dynamics of meaningful social interactions and the emergence of collective knowledge

NASA Astrophysics Data System (ADS)

Dankulov, Marija Mitrović; Melnik, Roderick; Tadić, Bosiljka

2015-07-01

Collective knowledge as a social value may arise in cooperation among actors whose individual expertise is limited. The process of knowledge creation requires meaningful, logically coordinated interactions, which represents a challenging problem to physics and social dynamics modeling. By combining two-scale dynamics model with empirical data analysis from a well-known Questions & Answers system Mathematics, we show that this process occurs as a collective phenomenon in an enlarged network (of actors and their artifacts) where the cognitive recognition interactions are properly encoded. The emergent behavior is quantified by the information divergence and innovation advancing of knowledge over time and the signatures of self-organization and knowledge sharing communities. These measures elucidate the impact of each cognitive element and the individual actor’s expertise in the collective dynamics. The results are relevant to stochastic processes involving smart components and to collaborative social endeavors, for instance, crowdsourcing scientific knowledge production with online games.

The dynamics of meaningful social interactions and the emergence of collective knowledge.

PubMed

Dankulov, Marija Mitrović; Melnik, Roderick; Tadić, Bosiljka

2015-07-15

Collective knowledge as a social value may arise in cooperation among actors whose individual expertise is limited. The process of knowledge creation requires meaningful, logically coordinated interactions, which represents a challenging problem to physics and social dynamics modeling. By combining two-scale dynamics model with empirical data analysis from a well-known Questions &Answers system Mathematics, we show that this process occurs as a collective phenomenon in an enlarged network (of actors and their artifacts) where the cognitive recognition interactions are properly encoded. The emergent behavior is quantified by the information divergence and innovation advancing of knowledge over time and the signatures of self-organization and knowledge sharing communities. These measures elucidate the impact of each cognitive element and the individual actor's expertise in the collective dynamics. The results are relevant to stochastic processes involving smart components and to collaborative social endeavors, for instance, crowdsourcing scientific knowledge production with online games.

The structural approach to shared knowledge: an application to engineering design teams.

PubMed

Avnet, Mark S; Weigel, Annalisa L

2013-06-01

We propose a methodology for analyzing shared knowledge in engineering design teams. Whereas prior work has focused on shared knowledge in small teams at a specific point in time, the model presented here is both scalable and dynamic. By quantifying team members' common views of design drivers, we build a network of shared mental models to reveal the structure of shared knowledge at a snapshot in time. Based on a structural comparison of networks at different points in time, a metric of change in shared knowledge is computed. Analysis of survey data from 12 conceptual space mission design sessions reveals a correlation between change in shared knowledge and each of several system attributes, including system development time, system mass, and technological maturity. From these results, we conclude that an early period of learning and consensus building could be beneficial to the design of engineered systems. Although we do not examine team performance directly, we demonstrate that shared knowledge is related to the technical design and thus provide a foundation for improving design products by incorporating the knowledge and thoughts of the engineering design team into the process.

'I remember therefore I am, and I am therefore I remember': exploring the contributions of episodic and semantic self-knowledge to strength of identity.

PubMed

Haslam, Catherine; Jetten, Jolanda; Haslam, S Alexander; Pugliese, Cara; Tonks, James

2011-05-01

The present research explores the relationship between the two components of autobiographical memory--episodic and semantic self-knowledge--and identity strength in older adults living in the community and residential care. Participants (N= 32) completed the autobiographical memory interview and measures of personal identity strength and multiple group memberships. Contrary to previous research, autobiographical memory for all time periods (childhood, early adulthood, and recent life) in the semantic domain was associated with greater strength in personal identity. Further, we obtained support for the hypothesis that the relationship between episodic self-knowledge and identity strength would be mediated by knowledge of personal semantic facts. However, there was also support for a reverse mediation model indicating that a strong sense of identity is associated with semantic self-knowledge and through this may enhance self-relevant recollection. The discussion elaborates on these findings and we propose a self-knowledge and identity model (SKIM) whereby semantic self-knowledge mediates a bidirectional relationship between episodic self-knowledge and identity. ©2010 The British Psychological Society.

Knowledge assistant: A sensor fusion framework for robotic environmental characterization

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

Feddema, J.T.; Rivera, J.J.; Tucker, S.D.

1996-12-01

A prototype sensor fusion framework called the {open_quotes}Knowledge Assistant{close_quotes} has been developed and tested on a gantry robot at Sandia National Laboratories. This Knowledge Assistant guides the robot operator during the planning, execution, and post analysis stages of the characterization process. During the planning stage, the Knowledge Assistant suggests robot paths and speeds based on knowledge of sensors available and their physical characteristics. During execution, the Knowledge Assistant coordinates the collection of data through a data acquisition {open_quotes}specialist.{close_quotes} During execution and post analysis, the Knowledge Assistant sends raw data to other {open_quotes}specialists,{close_quotes} which include statistical pattern recognition software, a neuralmore » network, and model-based search software. After the specialists return their results, the Knowledge Assistant consolidates the information and returns a report to the robot control system where the sensed objects and their attributes (e.g. estimated dimensions, weight, material composition, etc.) are displayed in the world model. This paper highlights the major components of this system.« less

The Genome-based Knowledge Management in Cycles model: a complex adaptive systems framework for implementation of genomic applications.

PubMed

Arar, Nedal; Knight, Sara J; Modell, Stephen M; Issa, Amalia M

2011-03-01

The main mission of the Genomic Applications in Practice and Prevention Network™ is to advance collaborative efforts involving partners from across the public health sector to realize the promise of genomics in healthcare and disease prevention. We introduce a new framework that supports the Genomic Applications in Practice and Prevention Network mission and leverages the characteristics of the complex adaptive systems approach. We call this framework the Genome-based Knowledge Management in Cycles model (G-KNOMIC). G-KNOMIC proposes that the collaborative work of multidisciplinary teams utilizing genome-based applications will enhance translating evidence-based genomic findings by creating ongoing knowledge management cycles. Each cycle consists of knowledge synthesis, knowledge evaluation, knowledge implementation and knowledge utilization. Our framework acknowledges that all the elements in the knowledge translation process are interconnected and continuously changing. It also recognizes the importance of feedback loops, and the ability of teams to self-organize within a dynamic system. We demonstrate how this framework can be used to improve the adoption of genomic technologies into practice using two case studies of genomic uptake.

The effect of the PROSPER partnership model on cultivating local stakeholder knowledge of evidence-based programs: a five-year longitudinal study of 28 communities.

PubMed

Crowley, D Max; Greenberg, Mark T; Feinberg, Mark E; Spoth, Richard L; Redmond, Cleve R

2012-02-01

A substantial challenge in improving public health is how to facilitate the local adoption of evidence-based interventions (EBIs). To do so, an important step is to build local stakeholders' knowledge and decision-making skills regarding the adoption and implementation of EBIs. One EBI delivery system, called PROSPER (PROmoting School-community-university Partnerships to Enhance Resilience), has effectively mobilized community prevention efforts, implemented prevention programming with quality, and consequently decreased youth substance abuse. While these results are encouraging, another objective is to increase local stakeholder knowledge of best practices for adoption, implementation and evaluation of EBIs. Using a mixed methods approach, we assessed local stakeholder knowledge of these best practices over 5 years, in 28 intervention and control communities. Results indicated that the PROSPER partnership model led to significant increases in expert knowledge regarding the selection, implementation, and evaluation of evidence-based interventions. Findings illustrate the limited programming knowledge possessed by members of local prevention efforts, the difficulty of complete knowledge transfer, and highlight one method for cultivating that knowledge.

Website Quality, Expectation, Confirmation, and End User Satisfaction: The Knowledge-Intensive Website of the Korean National Cancer Information Center

PubMed Central

Koo, Chulmo; Wati, Yulia; Park, Keeho

2011-01-01

Background The fact that patient satisfaction with primary care clinical practices and physician-patient communications has decreased gradually has brought a new opportunity to the online channel as a supplementary service to provide additional information. Objective In this study, our objectives were to examine the process of cognitive knowledge expectation-confirmation from eHealth users and to recommend the attributes of a “knowledge-intensive website.”. Knowledge expectation can be defined as users’ existing attitudes or beliefs regarding expected levels of knowledge they may gain by accessing the website. Knowledge confirmation is the extent to which user’s knowledge expectation of information systems use is realized during actual use. In our hypothesized research model, perceived information quality, presentation and attractiveness as well as knowledge expectation influence knowledge confirmation, which in turn influences perceived usefulness and end user satisfaction, which feeds back to knowledge expectation. Methods An empirical study was conducted at the National Cancer Center (NCC), Republic of Korea (South Korea), by evaluating its official website. A user survey was administered containing items to measure subjectively perceived website quality and expectation-confirmation attributes. A study sample of 198 usable responses was used for further analysis. We used the structural equation model to test the proposed research model. Results Knowledge expectation exhibited a positive effect on knowledge confirmation (beta = .27, P < .001). The paths from information quality, information presentation, and website attractiveness to knowledge confirmation were also positive and significant (beta = .24, P < .001; beta = .29, P < .001; beta = .18, P < .001, respectively). Moreover, the effect of knowledge confirmation on perceived usefulness was also positively significant (beta = .64, P < .001). Knowledge expectation together with knowledge confirmation and perceived usefulness also significantly affected end user satisfaction (beta = .22 P < .001; beta = .39, P < .001; beta = .25, P < .001, respectively). Conclusions Theoretically, this study has (1) identified knowledge-intensive website attributes, (2) enhanced the theoretical foundation of eHealth from the information systems (IS) perspective by adopting the expectation-confirmation theory (ECT), and (3) examined the importance of information and knowledge attributes and explained their impact on user satisfaction. Practically, our empirical results suggest that perceived website quality (ie, information quality, information presentation, and website attractiveness) is a core requirement for knowledge building. In addition, our study has also shown that knowledge confirmation has a greater effect on satisfaction than both knowledge expectation and perceived usefulness. PMID:22047810

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

Computational Models of Relational Processes in Cognitive Development

ERIC Educational Resources Information Center

Halford, Graeme S.; Andrews, Glenda; Wilson, William H.; Phillips, Steven

2012-01-01

Acquisition of relational knowledge is a core process in cognitive development. Relational knowledge is dynamic and flexible, entails structure-consistent mappings between representations, has properties of compositionality and systematicity, and depends on binding in working memory. We review three types of computational models relevant to…

Rubber airplane: Constraint-based component-modeling for knowledge representation in computer-aided conceptual design

NASA Technical Reports Server (NTRS)

Kolb, Mark A.

1990-01-01

Viewgraphs on Rubber Airplane: Constraint-based Component-Modeling for Knowledge Representation in Computer Aided Conceptual Design are presented. Topics covered include: computer aided design; object oriented programming; airfoil design; surveillance aircraft; commercial aircraft; aircraft design; and launch vehicles.

Instruction for Web Searching: An Empirical Study.

ERIC Educational Resources Information Center

Colaric, Susan M.

2003-01-01

Discussion of problems that users have with Web searching focuses on a study of undergraduates that investigated three instructional methods (instruction by example, conceptual models without illustrations, and conceptual models with illustrations) to determine differences in knowledge acquisition related to three types of knowledge (declarative,…

Integration into Big Data: First Steps to Support Reuse of Comprehensive Toxicity Model Modules (SOT)

EPA Science Inventory

Data surrounding the needs of human disease and toxicity modeling are largely siloed limiting the ability to extend and reuse modules across knowledge domains. Using an infrastructure that supports integration across knowledge domains (animal toxicology, high-throughput screening...

Mental model mapping as a new tool to analyse the use of information in decision-making in integrated water management

NASA Astrophysics Data System (ADS)

Kolkman, M. J.; Kok, M.; van der Veen, A.

The solution of complex, unstructured problems is faced with policy controversy and dispute, unused and misused knowledge, project delay and failure, and decline of public trust in governmental decisions. Mental model mapping (also called concept mapping) is a technique to analyse these difficulties on a fundamental cognitive level, which can reveal experiences, perceptions, assumptions, knowledge and subjective beliefs of stakeholders, experts and other actors, and can stimulate communication and learning. This article presents the theoretical framework from which the use of mental model mapping techniques to analyse this type of problems emerges as a promising technique. The framework consists of the problem solving or policy design cycle, the knowledge production or modelling cycle, and the (computer) model as interface between the cycles. Literature attributes difficulties in the decision-making process to communication gaps between decision makers, stakeholders and scientists, and to the construction of knowledge within different paradigm groups that leads to different interpretation of the problem situation. Analysis of the decision-making process literature indicates that choices, which are made in all steps of the problem solving cycle, are based on an individual decision maker’s frame of perception. This frame, in turn, depends on the mental model residing in the mind of the individual. Thus we identify three levels of awareness on which the decision process can be analysed. This research focuses on the third level. Mental models can be elicited using mapping techniques. In this way, analysing an individual’s mental model can shed light on decision-making problems. The steps of the knowledge production cycle are, in the same manner, ultimately driven by the mental models of the scientist in a specific discipline. Remnants of this mental model can be found in the resulting computer model. The characteristics of unstructured problems (complexity, uncertainty and disagreement) can be positioned in the framework, as can the communities of knowledge construction and valuation involved in the solution of these problems (core science, applied science, and professional consultancy, and “post-normal” science). Mental model maps, this research hypothesises, are suitable to analyse the above aspects of the problem. This hypothesis is tested for the case of the Zwolle storm surch barrier. Analysis can aid integration between disciplines, participation of public stakeholders, and can stimulate learning processes. Mental model mapping is recommended to visualise the use of knowledge, to analyse difficulties in problem solving process, and to aid information transfer and communication. Mental model mapping help scientists to shape their new, post-normal responsibilities in a manner that complies with integrity when dealing with unstructured problems in complex, multifunctional systems.

Modeling Guru: Knowledge Base for NASA Modelers

NASA Astrophysics Data System (ADS)

Seablom, M. S.; Wojcik, G. S.; van Aartsen, B. H.

2009-05-01

Modeling Guru is an on-line knowledge-sharing resource for anyone involved with or interested in NASA's scientific models or High End Computing (HEC) systems. Developed and maintained by the NASA's Software Integration and Visualization Office (SIVO) and the NASA Center for Computational Sciences (NCCS), Modeling Guru's combined forums and knowledge base for research and collaboration is becoming a repository for the accumulated expertise of NASA's scientific modeling and HEC communities. All NASA modelers and associates are encouraged to participate and provide knowledge about the models and systems so that other users may benefit from their experience. Modeling Guru is divided into a hierarchy of communities, each with its own set forums and knowledge base documents. Current modeling communities include those for space science, land and atmospheric dynamics, atmospheric chemistry, and oceanography. In addition, there are communities focused on NCCS systems, HEC tools and libraries, and programming and scripting languages. Anyone may view most of the content on Modeling Guru (available at http://modelingguru.nasa.gov/), but you must log in to post messages and subscribe to community postings. The site offers a full range of "Web 2.0" features, including discussion forums, "wiki" document generation, document uploading, RSS feeds, search tools, blogs, email notification, and "breadcrumb" links. A discussion (a.k.a. forum "thread") is used to post comments, solicit feedback, or ask questions. If marked as a question, SIVO will monitor the thread, and normally respond within a day. Discussions can include embedded images, tables, and formatting through the use of the Rich Text Editor. Also, the user can add "Tags" to their thread to facilitate later searches. The "knowledge base" is comprised of documents that are used to capture and share expertise with others. The default "wiki" document lets users edit within the browser so others can easily collaborate on the same document, even allowing the author to select those who may edit and approve the document. To maintain knowledge integrity, all documents are moderated before they are visible to the public. Modeling Guru, running on Clearspace by Jive Software, has been an active resource to the NASA modeling and HEC communities for more than a year and currently has more than 100 active users. SIVO will soon install live instant messaging support, as well as a user-customizable homepage with social-networking features. In addition, SIVO plans to implement a large dataset/file storage capability so that users can quickly and easily exchange datasets and files with one another. Continued active community participation combined with periodic software updates and improved features will ensure that Modeling Guru remains a vibrant, effective, easy-to-use tool for the NASA scientific community.

Knowledge acquisition and learning process description in context of e-learning

NASA Astrophysics Data System (ADS)

Kiselev, B. G.; Yakutenko, V. A.; Yuriev, M. A.

2017-01-01

This paper investigates the problem of design of e-learning and MOOC systems. It describes instructional design-based approaches to e-learning systems design: IMS Learning Design, MISA and TELOS. To solve this problem we present Knowledge Field of Educational Environment with Competence boundary conditions - instructional engineering method for self-learning systems design. It is based on the simplified TELOS approach and enables a user to create their individual learning path by choosing prerequisite and target competencies. The paper provides the ontology model for the described instructional engineering method, real life use cases and the classification of the presented model. Ontology model consists of 13 classes and 15 properties. Some of them are inherited from Knowledge Field of Educational Environment and some are new and describe competence boundary conditions and knowledge validation objects. Ontology model uses logical constraints and is described using OWL 2 standard. To give TELOS users better understanding of our approach we list mapping between TELOS and KFEEC.

Applying Self-Determination Theory to Adolescent Sexual-Risk Behavior and Knowledge: A Structural Equation Model [Formula: see text].

PubMed

Riley, Bettina H; McDermott, Ryon C

2018-05-01

National health priorities identify adolescent sexual-risk behavior outcomes as research and intervention targets for mental health. Reduce sexual-risk behavioral outcomes by applying self-determination theory to focus on decision-making autonomy. This study examined late adolescents' recollections of parental autonomy support/sexual-risk communication experiences and autonomy motivation as predictors of sexual-risk behaviors/knowledge. A convenience sample ( N = 249) of 19- and 20-year-old university students completed self-report questionnaires. Structural equation modeling with latent variables examined direct/indirect effects in the hypothesized model. Parents contributed uniquely through sexual-risk communication and/or autonomy support to late adolescents' autonomous motivation. The final model evidenced acceptable fit and explained 12% of the variation in adolescent sexual-risk behavior, 7% in adolescent autonomous motivation, and 2% in adolescent sexual-risk knowledge. Psychiatric mental health nurses should conduct further research and design interventions promoting parent autonomy support and adolescent autonomous motivation to reduce sexual risk-behavior and increase sexual-risk knowledge.

A Very Large Area Network (VLAN) knowledge-base applied to space communication problems

NASA Technical Reports Server (NTRS)

Zander, Carol S.

1988-01-01

This paper first describes a hierarchical model for very large area networks (VLAN). Space communication problems whose solution could profit by the model are discussed and then an enhanced version of this model incorporating the knowledge needed for the missile detection-destruction problem is presented. A satellite network or VLAN is a network which includes at least one satellite. Due to the complexity, a compromise between fully centralized and fully distributed network management has been adopted. Network nodes are assigned to a physically localized group, called a partition. Partitions consist of groups of cell nodes with one cell node acting as the organizer or master, called the Group Master (GM). Coordinating the group masters is a Partition Master (PM). Knowledge is also distributed hierarchically existing in at least two nodes. Each satellite node has a back-up earth node. Knowledge must be distributed in such a way so as to minimize information loss when a node fails. Thus the model is hierarchical both physically and informationally.

Modeling the Relations Among Morphological Awareness Dimensions, Vocabulary Knowledge, and Reading Comprehension in Adult Basic Education Students

PubMed Central

Tighe, Elizabeth L.; Schatschneider, Christopher

2016-01-01

This study extended the findings of Tighe and Schatschneider (2015) by investigating the predictive utility of separate dimensions of morphological awareness as well as vocabulary knowledge to reading comprehension in adult basic education (ABE) students. We competed two- and three-factor structural equation models of reading comprehension. A three-factor model of real word morphological awareness, pseudoword morphological awareness, and vocabulary knowledge emerged as the best fit and accounted for 79% of the reading comprehension variance. The results indicated that the constructs contributed jointly to reading comprehension; however, vocabulary knowledge was the only potentially unique predictor (p = 0.052), accounting for an additional 5.6% of the variance. This study demonstrates the feasibility of applying a latent variable modeling approach to examine individual differences in the reading comprehension skills of ABE students. Further, this study replicates the findings of Tighe and Schatschneider (2015) on the importance of differentiating among dimensions of morphological awareness in this population. PMID:26869981

Modeling the Relations Among Morphological Awareness Dimensions, Vocabulary Knowledge, and Reading Comprehension in Adult Basic Education Students.

PubMed

Tighe, Elizabeth L; Schatschneider, Christopher

2016-01-01

This study extended the findings of Tighe and Schatschneider (2015) by investigating the predictive utility of separate dimensions of morphological awareness as well as vocabulary knowledge to reading comprehension in adult basic education (ABE) students. We competed two- and three-factor structural equation models of reading comprehension. A three-factor model of real word morphological awareness, pseudoword morphological awareness, and vocabulary knowledge emerged as the best fit and accounted for 79% of the reading comprehension variance. The results indicated that the constructs contributed jointly to reading comprehension; however, vocabulary knowledge was the only potentially unique predictor (p = 0.052), accounting for an additional 5.6% of the variance. This study demonstrates the feasibility of applying a latent variable modeling approach to examine individual differences in the reading comprehension skills of ABE students. Further, this study replicates the findings of Tighe and Schatschneider (2015) on the importance of differentiating among dimensions of morphological awareness in this population.

Linking knowledge and action through mental models of sustainable agriculture.

PubMed

Hoffman, Matthew; Lubell, Mark; Hillis, Vicken

2014-09-09

Linking knowledge to action requires understanding how decision-makers conceptualize sustainability. This paper empirically analyzes farmer "mental models" of sustainability from three winegrape-growing regions of California where local extension programs have focused on sustainable agriculture. The mental models are represented as networks where sustainability concepts are nodes, and links are established when a farmer mentions two concepts in their stated definition of sustainability. The results suggest that winegrape grower mental models of sustainability are hierarchically structured, relatively similar across regions, and strongly linked to participation in extension programs and adoption of sustainable farm practices. We discuss the implications of our findings for the debate over the meaning of sustainability, and the role of local extension programs in managing knowledge systems.

Knowledgeable Neighbors:A Mobile Clinic Model for Disease Prevention and Screening in Underserved Communities

PubMed Central

Zurakowski, David; Bennet, Jennifer; Walker-White, Rainelle; Osman, Jamie L.; Quarles, Aaron; Oriol, Nancy

2012-01-01

The Family Van mobile health clinic uses a “Knowledgeable Neighbor” model to deliver cost-effective screening and prevention activities in underserved neighborhoods in Boston, MA. We have described the Knowledgeable Neighbor model and used operational data collected from 2006 to 2009 to evaluate the service. The Family Van successfully reached mainly minority low-income men and women. Of the clients screened, 60% had previously undetected elevated blood pressure, 14% had previously undetected elevated blood glucose, and 38% had previously undetected elevated total cholesterol. This represents an important model for reaching underserved communities to deliver proven cost-effective prevention activities, both to help control health care costs and to reduce health disparities. PMID:22390503

Data to knowledge: how to get meaning from your result

PubMed Central

Berman, Helen M.; Gabanyi, Margaret J.; Groom, Colin R.; Johnson, John E.; Murshudov, Garib N.; Nicholls, Robert A.; Reddy, Vijay; Schwede, Torsten; Zimmerman, Matthew D.; Westbrook, John; Minor, Wladek

2015-01-01

Structural and functional studies require the development of sophisticated ‘Big Data’ technologies and software to increase the knowledge derived and ensure reproducibility of the data. This paper presents summaries of the Structural Biology Knowledge Base, the VIPERdb Virus Structure Database, evaluation of homology modeling by the Protein Model Portal, the ProSMART tool for conformation-independent structure comparison, the LabDB ‘super’ laboratory information management system and the Cambridge Structural Database. These techniques and technologies represent important tools for the transformation of crystallographic data into knowledge and information, in an effort to address the problem of non-reproducibility of experimental results. PMID:25610627

Cognitive algorithms: dynamic logic, working of the mind, evolution of consciousness and cultures

NASA Astrophysics Data System (ADS)

Perlovsky, Leonid I.

2007-04-01

The paper discusses evolution of consciousness driven by the knowledge instinct, a fundamental mechanism of the mind which determines its higher cognitive functions. Dynamic logic mathematically describes the knowledge instinct. It overcomes past mathematical difficulties encountered in modeling intelligence and relates it to mechanisms of concepts, emotions, instincts, consciousness and unconscious. The two main aspects of the knowledge instinct are differentiation and synthesis. Differentiation is driven by dynamic logic and proceeds from vague and unconscious states to more crisp and conscious states, from less knowledge to more knowledge at each hierarchical level of the mind. Synthesis is driven by dynamic logic operating in a hierarchical organization of the mind; it strives to achieve unity and meaning of knowledge: every concept finds its deeper and more general meaning at a higher level. These mechanisms are in complex relationship of symbiosis and opposition, which leads to complex dynamics of evolution of consciousness and cultures. Modeling this dynamics in a population leads to predictions for the evolution of consciousness, and cultures. Cultural predictive models can be compared to experimental data and used for improvement of human conditions. We discuss existing evidence and future research directions.

A comprehensive model for executing knowledge management audits in organizations: a systematic review.

PubMed

Shahmoradi, Leila; Ahmadi, Maryam; Sadoughi, Farahnaz; Piri, Zakieh; Gohari, Mahmood Reza

2015-01-01

A knowledge management audit (KMA) is the first phase in knowledge management implementation. Incomplete or incomprehensive execution of the KMA has caused many knowledge management programs to fail. A study was undertaken to investigate how KMAs are performed systematically in organizations and present a comprehensive model for performing KMAs based on a systematic review. Studies were identified by searching electronic databases such as Emerald, LISA, and the Cochrane library and e-journals such as the Oxford Journal and hand searching of printed journals, theses, and books in the Tehran University of Medical Sciences digital library. The sources used in this study consisted of studies available through the digital library of the Tehran University of Medical Sciences that were published between 2000 and 2013, including both Persian- and English-language sources, as well as articles explaining the steps involved in performing a KMA. A comprehensive model for KMAs is presented in this study. To successfully execute a KMA, it is necessary to perform the appropriate preliminary activities in relation to the knowledge management infrastructure, determine the knowledge management situation, and analyze and use the available data on this situation.

A study of EMR-based medical knowledge network and its applications.

PubMed

Zhao, Chao; Jiang, Jingchi; Xu, Zhiming; Guan, Yi

2017-05-01

Electronic medical records (EMRs) contain an amount of medical knowledge which can be used for clinical decision support. We attempt to integrate this medical knowledge into a complex network, and then implement a diagnosis model based on this network. The dataset of our study contains 992 records which are uniformly sampled from different departments of the hospital. In order to integrate the knowledge of these records, an EMR-based medical knowledge network (EMKN) is constructed. This network takes medical entities as nodes, and co-occurrence relationships between the two entities as edges. Selected properties of this network are analyzed. To make use of this network, a basic diagnosis model is implemented. Seven hundred records are randomly selected to re-construct the network, and the remaining 292 records are used as test records. The vector space model is applied to illustrate the relationships between diseases and symptoms. Because there may exist more than one actual disease in a record, the recall rate of the first ten results, and the average precision are adopted as evaluation measures. Compared with a random network of the same size, this network has a similar average length but a much higher clustering coefficient. Additionally, it can be observed that there are direct correlations between the community structure and the real department classes in the hospital. For the diagnosis model, the vector space model using disease as a base obtains the best result. At least one accurate disease can be obtained in 73.27% of the records in the first ten results. We constructed an EMR-based medical knowledge network by extracting the medical entities. This network has the small-world and scale-free properties. Moreover, the community structure showed that entities in the same department have a tendency to be self-aggregated. Based on this network, a diagnosis model was proposed. This model uses only the symptoms as inputs and is not restricted to a specific disease. The experiments conducted demonstrated that EMKN is a simple and universal technique to integrate different medical knowledge from EMRs, and can be used for clinical decision support. Copyright © 2017 Elsevier B.V. All rights reserved.

Knowledge of Dengue Among Students Exposed to Various Awareness Campaigns in Model Schools of Islamabad: A Cross-Sectional Study.

PubMed

Javed, Nismat; Ghazanfar, Haider; Naseem, Sajida

2018-04-10

Objective To determine the knowledge of dengue among school students exposed to various awareness campaigns in model schools of Islamabad. Methods We conducted a cross-sectional study of students who were studying in Islamabad Model School for Girls F-7/2 and Islamabad Model College for Boys F-7/3 from September 2017 to October 2017. Students in the ninth and tenth grades who were willing to participate in the study and who were studying in the school for more than six months were included in the study. The data was collected through a self-constructed questionnaire. Cronbach's alpha was used to assess the internal consistency of the questionnaire, and it was found to be 0.83. The data obtained was analyzed on IBM's statistical package for the social sciences (SPSS) version 21 (IBM, Armonk, NY). Results Out of 601 participants, 345 (57.4%) were males and 256 (42.6%) were females. The mean age of the participants was 14.72±1.09. About 380 participants (63.2%) were studying in the ninth grade and 221 participants (36.8%) were studying in the tenth grade. A majority of the participants (67.2%) had poor knowledge of dengue. The participants scored highest in knowledge of prevention of the dengue domain and scored the lowest in knowledge of transmission of dengue. A majority of the participants (72.9%) reported that they acquire knowledge about dengue fever through television and radio. About 44.60% of the participants reported that they acquired knowledge about dengue fever through awareness campaigns in school. Conclusions The knowledge of the students was found to be insufficient despite several awareness campaigns. There is a need to re-evaluate the structure of the awareness campaigns as they fail to reach their target. Electronic media was identified as the most useful source of knowledge, and its incorporation can help increase the effectiveness of awareness campaigns.

Adaptive Modeling of the International Space Station Electrical Power System

NASA Technical Reports Server (NTRS)

Thomas, Justin Ray

2007-01-01

Software simulations provide NASA engineers the ability to experiment with spacecraft systems in a computer-imitated environment. Engineers currently develop software models that encapsulate spacecraft system behavior. These models can be inaccurate due to invalid assumptions, erroneous operation, or system evolution. Increasing accuracy requires manual calibration and domain-specific knowledge. This thesis presents a method for automatically learning system models without any assumptions regarding system behavior. Data stream mining techniques are applied to learn models for critical portions of the International Space Station (ISS) Electrical Power System (EPS). We also explore a knowledge fusion approach that uses traditional engineered EPS models to supplement the learned models. We observed that these engineered EPS models provide useful background knowledge to reduce predictive error spikes when confronted with making predictions in situations that are quite different from the training scenarios used when learning the model. Evaluations using ISS sensor data and existing EPS models demonstrate the success of the adaptive approach. Our experimental results show that adaptive modeling provides reductions in model error anywhere from 80% to 96% over these existing models. Final discussions include impending use of adaptive modeling technology for ISS mission operations and the need for adaptive modeling in future NASA lunar and Martian exploration.

Thinking Outside the Box: Agile Business Models for CNOs

NASA Astrophysics Data System (ADS)

Loss, Leandro; Crave, Servane

This paper introduces the idea of an agile Business Model for CNOs grounded on a new model of innovation based on the effects of globalization and of Knowledge Economy. The agile Business Model considers the resources that are spread out and available worldwide as well as the need for each customer to receive a unique customer experience. It aims at reinforcing in the context of the Knowledge Economy the different business models approaches developed so far. The paper also identifies the levers and the barriers of Agile Business Models Innovation in CNOs.

A Rapid Approach to Modeling Species-Habitat Relationships

NASA Technical Reports Server (NTRS)

Carter, Geoffrey M.; Breinger, David R.; Stolen, Eric D.

2005-01-01

A growing number of species require conservation or management efforts. Success of these activities requires knowledge of the species' occurrence pattern. Species-habitat models developed from GIS data sources are commonly used to predict species occurrence but commonly used data sources are often developed for purposes other than predicting species occurrence and are of inappropriate scale and the techniques used to extract predictor variables are often time consuming and cannot be repeated easily and thus cannot efficiently reflect changing conditions. We used digital orthophotographs and a grid cell classification scheme to develop an efficient technique to extract predictor variables. We combined our classification scheme with a priori hypothesis development using expert knowledge and a previously published habitat suitability index and used an objective model selection procedure to choose candidate models. We were able to classify a large area (57,000 ha) in a fraction of the time that would be required to map vegetation and were able to test models at varying scales using a windowing process. Interpretation of the selected models confirmed existing knowledge of factors important to Florida scrub-jay habitat occupancy. The potential uses and advantages of using a grid cell classification scheme in conjunction with expert knowledge or an habitat suitability index (HSI) and an objective model selection procedure are discussed.

Use of cccupancy models to evaluate expert knowledge-based species-habitat relationships

USGS Publications Warehouse

Iglecia, Monica N.; Collazo, Jaime A.; McKerrow, Alexa

2012-01-01

Expert knowledge-based species-habitat relationships are used extensively to guide conservation planning, particularly when data are scarce. Purported relationships describe the initial state of knowledge, but are rarely tested. We assessed support in the data for suitability rankings of vegetation types based on expert knowledge for three terrestrial avian species in the South Atlantic Coastal Plain of the United States. Experts used published studies, natural history, survey data, and field experience to rank vegetation types as optimal, suitable, and marginal. We used single-season occupancy models, coupled with land cover and Breeding Bird Survey data, to examine the hypothesis that patterns of occupancy conformed to species-habitat suitability rankings purported by experts. Purported habitat suitability was validated for two of three species. As predicted for the Eastern Wood-Pewee (Contopus virens) and Brown-headed Nuthatch (Sitta pusilla), occupancy was strongly influenced by vegetation types classified as “optimal habitat” by the species suitability rankings for nuthatches and wood-pewees. Contrary to predictions, Red-headed Woodpecker (Melanerpes erythrocephalus) models that included vegetation types as covariates received similar support by the data as models without vegetation types. For all three species, occupancy was also related to sampling latitude. Our results suggest that covariates representing other habitat requirements might be necessary to model occurrence of generalist species like the woodpecker. The modeling approach described herein provides a means to test expert knowledge-based species-habitat relationships, and hence, help guide conservation planning.

Eliciting and Representing High-Level Knowledge Requirements to Discover Ecological Knowledge in Flower-Visiting Data

PubMed Central

2016-01-01

Observations of individual organisms (data) can be combined with expert ecological knowledge of species, especially causal knowledge, to model and extract from flower–visiting data useful information about behavioral interactions between insect and plant organisms, such as nectar foraging and pollen transfer. We describe and evaluate a method to elicit and represent such expert causal knowledge of behavioral ecology, and discuss the potential for wider application of this method to the design of knowledge-based systems for knowledge discovery in biodiversity and ecosystem informatics. PMID:27851814

Bridging the gap: simulations meet knowledge bases

NASA Astrophysics Data System (ADS)

King, Gary W.; Morrison, Clayton T.; Westbrook, David L.; Cohen, Paul R.

2003-09-01

Tapir and Krill are declarative languages for specifying actions and agents, respectively, that can be executed in simulation. As such, they bridge the gap between strictly declarative knowledge bases and strictly executable code. Tapir and Krill components can be combined to produce models of activity which can answer questions about mechanisms and processes using conventional inference methods and simulation. Tapir was used in DARPA's Rapid Knowledge Formation (RKF) project to construct models of military tactics from the Army Field Manual FM3-90. These were then used to build Courses of Actions (COAs) which could be critiqued by declarative reasoning or via Monte Carlo simulation. Tapir and Krill can be read and written by non-knowledge engineers making it an excellent vehicle for Subject Matter Experts to build and critique knowledge bases.

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.

Modelling robot's behaviour using finite automata

NASA Astrophysics Data System (ADS)

Janošek, Michal; Žáček, Jaroslav

2017-07-01

This paper proposes a model of a robot's behaviour described by finite automata. We split robot's knowledge into several knowledge bases which are used by the inference mechanism of the robot's expert system to make a logic deduction. Each knowledgebase is dedicated to the particular behaviour domain and the finite automaton helps us switching among these knowledge bases with the respect of actual situation. Our goal is to simplify and reduce complexity of one big knowledgebase splitting it into several pieces. The advantage of this model is that we can easily add new behaviour by adding new knowledgebase and add this behaviour into the finite automaton and define necessary states and transitions.

Research and application of knowledge resources network for product innovation.

PubMed

Li, Chuan; Li, Wen-qiang; Li, Yan; Na, Hui-zhen; Shi, Qian

2015-01-01

In order to enhance the capabilities of knowledge service in product innovation design service platform, a method of acquiring knowledge resources supporting for product innovation from the Internet and providing knowledge active push is proposed. Through knowledge modeling for product innovation based on ontology, the integrated architecture of knowledge resources network is put forward. The technology for the acquisition of network knowledge resources based on focused crawler and web services is studied. Knowledge active push is provided for users by user behavior analysis and knowledge evaluation in order to improve users' enthusiasm for participation in platform. Finally, an application example is illustrated to prove the effectiveness of the method.

Merging curriculum design with chemical epistemology: A case of teaching and learning chemistry through modeling

NASA Astrophysics Data System (ADS)

Erduran, Sibel

The central problem underlying this dissertation is the design of learning environments that enable the teaching and learning of chemistry through modeling. Significant role of models in chemistry knowledge is highlighted with a shift in emphasis from conceptual to epistemological accounts of models. Research context is the design and implementation of student centered Acids & Bases Curriculum, developed as part of Project SEPIA. Qualitative study focused on 3 curriculum activities conducted in one 7th grade class of 19 students in an urban, public middle school in eastern United States. Questions guiding the study were: (a) How can learning environments be designed to promote growth of chemistry knowledge through modeling? (b) What epistemological criteria facilitate learning of growth of chemistry knowledge through modeling? Curriculum materials, and verbal data from whole class conversations and student group interviews were analyzed. Group interviews consisted of same 4 students, selected randomly before curriculum implementation, and were conducted following each activity to investigate students' developing understandings of models. Theoretical categories concerning definition, properties and kinds of models as well as educational and chemical models informed curriculum design, and were redefined as codes in the analysis of verbal data. Results indicate more diversity of codes in student than teacher talk across all activities. Teacher concentrated on educational and chemical models. A significant finding is that model properties such as 'compositionality' and 'projectability' were not present in teacher talk as expected by curriculum design. Students did make reference to model properties. Another finding is that students demonstrate an understanding of models characterized by the seventeenth century Lemery model of acids and bases. Two students' developing understandings of models across curriculum implementation suggest that curriculum bears some change in students' understanding of models. The tension between students' everyday knowledge and teacher's scientific knowledge is highlighted relative to the patterns in codes observed in data. Implications for theory of learning, curriculum design and teacher education are discussed. It is argued that future educational research should acknowledge and incorporate perspectives from chemical epistemology.

Total Quality Management in a Knowledge Management Perspective.

ERIC Educational Resources Information Center

Johannsen, Carl Gustav

2000-01-01

Presents theoretical considerations on both similarities and differences between information management and knowledge management and presents a conceptual model of basic knowledge management processes. Discusses total quality management and quality control in the context of information management. (Author/LRW)

Developing and evaluating a paper-and-pencil test to assess components of physics teachers' pedagogical content knowledge

NASA Astrophysics Data System (ADS)

Kirschner, Sophie; Borowski, Andreas; Fischer, Hans E.; Gess-Newsome, Julie; von Aufschnaiter, Claudia

2016-05-01

Teachers' professional knowledge is assumed to be a key variable for effective teaching. As teacher education has the goal to enhance professional knowledge of current and future teachers, this knowledge should be described and assessed. Nevertheless, only a limited number of studies quantitatively measures physics teachers' professional knowledge. The study reported in this paper was part of a bigger project with the broader goal of understanding teacher professional knowledge. We designed a test instrument to assess the professional knowledge of physics teachers (N = 186) in the dimensions of content knowledge (CK), pedagogical content knowledge (PCK), and pedagogical knowledge (PK). A model describing the relationships between these three dimensions of professional knowledge was created to inform the design of the tests used to measure CK, PCK, and PK. In this paper, we describe the model with particular emphasis on the PCK part, and the subsequent PCK test development and its implementation in detail. We report different approaches to evaluate the PCK test, including the description of content validity, the examination of the internal structure of professional knowledge, and the analysis of construct validity by testing teachers across different school subjects, teachers from different school types, pre-service teachers, and physicists. Our findings demonstrate that our PCK test results could distinguish physics teachers from the other groups tested. The PCK test results could not be explained by teachers' CK or PK, cognitive abilities, computational skills, or science knowledge.

Use of the Rasch Measurement Model to Explore the Relationship between Content Knowledge and Topic-Specific Pedagogical Content Knowledge for Organic Chemistry

ERIC Educational Resources Information Center

Davidowitz, Bette; Potgieter, Marietjie

2016-01-01

Research has shown that a high level of content knowledge (CK) is necessary but not sufficient to develop the special knowledge base of expert teachers known as pedagogical content knowledge (PCK). This study contributes towards research to quantify the relationship between CK and PCK in science. In order to determine the proportion of the…

Intrusion Detection Systems with Live Knowledge System

DTIC Science & Technology

2016-05-31

Ripple -down Rule (RDR) to maintain the knowledge from human experts with knowledge base generated by the Induct RDR, which is a machine-learning based RDR...propose novel approach that uses Ripple -down Rule (RDR) to maintain the knowledge from human experts with knowledge base generated by the Induct RDR...detection model by applying Induct RDR approach. The proposed induct RDR ( Ripple Down Rules) approach allows to acquire the phishing detection

Inter-firm Networks, Organizational Learning and Knowledge Updating: An Empirical Study

NASA Astrophysics Data System (ADS)

Zhang, Su-rong; Wang, Wen-ping

In the era of knowledge-based economy which information technology develops rapidly, the rate of knowledge updating has become a critical factor for enterprises to gaining competitive advantage .We build an interactional theoretical model among inter-firm networks, organizational learning and knowledge updating thereby and demonstrate it with empirical study at last. The result shows that inter-firm networks and organizational learning is the source of knowledge updating.

BiGG Models: A platform for integrating, standardizing and sharing genome-scale models

DOE PAGES

King, Zachary A.; Lu, Justin; Drager, Andreas; ...

2015-10-17

In this study, genome-scale metabolic models are mathematically structured knowledge bases that can be used to predict metabolic pathway usage and growth phenotypes. Furthermore, they can generate and test hypotheses when integrated with experimental data. To maximize the value of these models, centralized repositories of high-quality models must be established, models must adhere to established standards and model components must be linked to relevant databases. Tools for model visualization further enhance their utility. To meet these needs, we present BiGG Models (http://bigg.ucsd.edu), a completely redesigned Biochemical, Genetic and Genomic knowledge base. BiGG Models contains more than 75 high-quality, manually-curated genome-scalemore » metabolic models. On the website, users can browse, search and visualize models. BiGG Models connects genome-scale models to genome annotations and external databases. Reaction and metabolite identifiers have been standardized across models to conform to community standards and enable rapid comparison across models. Furthermore, BiGG Models provides a comprehensive application programming interface for accessing BiGG Models with modeling and analysis tools. As a resource for highly curated, standardized and accessible models of metabolism, BiGG Models will facilitate diverse systems biology studies and support knowledge-based analysis of diverse experimental data.« less

BiGG Models: A platform for integrating, standardizing and sharing genome-scale models

PubMed Central

King, Zachary A.; Lu, Justin; Dräger, Andreas; Miller, Philip; Federowicz, Stephen; Lerman, Joshua A.; Ebrahim, Ali; Palsson, Bernhard O.; Lewis, Nathan E.

2016-01-01

Genome-scale metabolic models are mathematically-structured knowledge bases that can be used to predict metabolic pathway usage and growth phenotypes. Furthermore, they can generate and test hypotheses when integrated with experimental data. To maximize the value of these models, centralized repositories of high-quality models must be established, models must adhere to established standards and model components must be linked to relevant databases. Tools for model visualization further enhance their utility. To meet these needs, we present BiGG Models (http://bigg.ucsd.edu), a completely redesigned Biochemical, Genetic and Genomic knowledge base. BiGG Models contains more than 75 high-quality, manually-curated genome-scale metabolic models. On the website, users can browse, search and visualize models. BiGG Models connects genome-scale models to genome annotations and external databases. Reaction and metabolite identifiers have been standardized across models to conform to community standards and enable rapid comparison across models. Furthermore, BiGG Models provides a comprehensive application programming interface for accessing BiGG Models with modeling and analysis tools. As a resource for highly curated, standardized and accessible models of metabolism, BiGG Models will facilitate diverse systems biology studies and support knowledge-based analysis of diverse experimental data. PMID:26476456

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.

Lowering the barriers to computational modeling of Earth's surface: coupling Jupyter Notebooks with Landlab, HydroShare, and CyberGIS for research and education.

NASA Astrophysics Data System (ADS)

Bandaragoda, C.; Castronova, A. M.; Phuong, J.; Istanbulluoglu, E.; Strauch, R. L.; Nudurupati, S. S.; Tarboton, D. G.; Wang, S. W.; Yin, D.; Barnhart, K. R.; Tucker, G. E.; Hutton, E.; Hobley, D. E. J.; Gasparini, N. M.; Adams, J. M.

2017-12-01

The ability to test hypotheses about hydrology, geomorphology and atmospheric processes is invaluable to research in the era of big data. Although community resources are available, there remain significant educational, logistical and time investment barriers to their use. Knowledge infrastructure is an emerging intellectual framework to understand how people are creating, sharing and distributing knowledge - which has been dramatically transformed by Internet technologies. In addition to the technical and social components in a cyberinfrastructure system, knowledge infrastructure considers educational, institutional, and open source governance components required to advance knowledge. We are designing an infrastructure environment that lowers common barriers to reproducing modeling experiments for earth surface investigation. Landlab is an open-source modeling toolkit for building, coupling, and exploring two-dimensional numerical models. HydroShare is an online collaborative environment for sharing hydrologic data and models. CyberGIS-Jupyter is an innovative cyberGIS framework for achieving data-intensive, reproducible, and scalable geospatial analytics using the Jupyter Notebook based on ROGER - the first cyberGIS supercomputer, so that models that can be elastically reproduced through cloud computing approaches. Our team of geomorphologists, hydrologists, and computer geoscientists has created a new infrastructure environment that combines these three pieces of software to enable knowledge discovery. Through this novel integration, any user can interactively execute and explore their shared data and model resources. Landlab on HydroShare with CyberGIS-Jupyter supports the modeling continuum from fully developed modelling applications, prototyping new science tools, hands on research demonstrations for training workshops, and classroom applications. Computational geospatial models based on big data and high performance computing can now be more efficiently developed, improved, scaled, and seamlessly reproduced among multidisciplinary users, thereby expanding the active learning curriculum and research opportunities for students in earth surface modeling and informatics.

Learning multisensory representations for auditory-visual transfer of sequence category knowledge: a probabilistic language of thought approach.

PubMed

Yildirim, Ilker; Jacobs, Robert A

2015-06-01

If a person is trained to recognize or categorize objects or events using one sensory modality, the person can often recognize or categorize those same (or similar) objects and events via a novel modality. This phenomenon is an instance of cross-modal transfer of knowledge. Here, we study the Multisensory Hypothesis which states that people extract the intrinsic, modality-independent properties of objects and events, and represent these properties in multisensory representations. These representations underlie cross-modal transfer of knowledge. We conducted an experiment evaluating whether people transfer sequence category knowledge across auditory and visual domains. Our experimental data clearly indicate that we do. We also developed a computational model accounting for our experimental results. Consistent with the probabilistic language of thought approach to cognitive modeling, our model formalizes multisensory representations as symbolic "computer programs" and uses Bayesian inference to learn these representations. Because the model demonstrates how the acquisition and use of amodal, multisensory representations can underlie cross-modal transfer of knowledge, and because the model accounts for subjects' experimental performances, our work lends credence to the Multisensory Hypothesis. Overall, our work suggests that people automatically extract and represent objects' and events' intrinsic properties, and use these properties to process and understand the same (and similar) objects and events when they are perceived through novel sensory modalities.

Exploring knowledge exchange: a useful framework for practice and policy.

PubMed

Ward, Vicky; Smith, Simon; House, Allan; Hamer, Susan

2012-02-01

Knowledge translation is underpinned by a dynamic and social knowledge exchange process but there are few descriptions of how this unfolds in practice settings. This has hampered attempts to produce realistic and useful models to help policymakers and researchers understand how knowledge exchange works. This paper reports the results of research which investigated the nature of knowledge exchange. We aimed to understand whether dynamic and fluid definitions of knowledge exchange are valid and to produce a realistic, descriptive framework of knowledge exchange. Our research was informed by a realist approach. We embedded a knowledge broker within three service delivery teams across a mental health organisation in the UK, each of whom was grappling with specific challenges. The knowledge broker participated in the team's problem-solving process and collected observational fieldnotes. We also interviewed the team members. Observational and interview data were analysed quantitatively and qualitatively in order to determine and describe the nature of the knowledge exchange process in more detail. This enabled us to refine our conceptual framework of knowledge exchange. We found that knowledge exchange can be understood as a dynamic and fluid process which incorporates distinct forms of knowledge from multiple sources. Quantitative analysis illustrated that five broadly-defined components of knowledge exchange (problem, context, knowledge, activities, use) can all be in play at any one time and do not occur in a set order. Qualitative analysis revealed a number of distinct themes which better described the nature of knowledge exchange. By shedding light on the nature of knowledge exchange, our findings problematise some of the linear, technicist approaches to knowledge translation. The revised model of knowledge exchange which we propose here could therefore help to reorient thinking about knowledge exchange and act as a starting point for further exploration and evaluation of the knowledge exchange process. Copyright © 2011 Elsevier Ltd. All rights reserved.

Comparing Curriculum Types: 'Powerful Knowledge' and '21st Century Learning'

ERIC Educational Resources Information Center

McPhail, Graham; Rata, Elizabeth

2016-01-01

This paper theorises a curriculum model containing four features. We use these features as criteria to analyse and evaluate two distinctive curriculum design types: '21st Century Learning' and 'Powerful Knowledge'. The four features are: (i) the underpinning theory of knowledge in each curriculum design type; (ii) the knowledge structures used to…

Characterizing the Development of Specialized Mathematical Content Knowledge for Teaching in Algebraic Reasoning and Number Theory

ERIC Educational Resources Information Center

Bair, Sherry L.; Rich, Beverly S.

2011-01-01

This article characterizes the development of a deep and connected body of mathematical knowledge categorized by Ball and Bass' (2003b) model of Mathematical Knowledge for Teaching (MKT), as Specialized Content Knowledge for Teaching (SCK) in algebraic reasoning and number sense. The research employed multiple cases across three years from two…

Adoption by Policy Makers of Knowledge from Educational Research: An Alternative Perspective

ERIC Educational Resources Information Center

Brown, Chris

2012-01-01

The phrase knowledge adoption refers to the ways in which policymakers take up and use evidence. Whilst frameworks and models have been put forward to explain knowledge adoption activity, this paper argues that current approaches are flawed and do not address the complexities affecting the successful realisation of knowledge-adoption efforts.…

The Visual Representation and Acquisition of Driving Knowledge for Autonomous Vehicle

NASA Astrophysics Data System (ADS)

Zhang, Zhaoxia; Jiang, Qing; Li, Ping; Song, LiangTu; Wang, Rujing; Yu, Biao; Mei, Tao

2017-09-01

In this paper, the driving knowledge base of autonomous vehicle is designed. Based on the driving knowledge modeling system, the driving knowledge of autonomous vehicle is visually acquired, managed, stored, and maintenanced, which has vital significance for creating the development platform of intelligent decision-making systems of automatic driving expert systems for autonomous vehicle.

Knowledge Navigation for Virtual Vehicles

NASA Technical Reports Server (NTRS)

Gomez, Julian E.

2004-01-01

A virtual vehicle is a digital model of the knowledge surrounding a potentially real vehicle. Knowledge consists not only of the tangible information, such as CAD, but also what is known about the knowledge - its metadata. This paper is an overview of technologies relevant to building a virtual vehicle, and an assessment of how to bring those technologies together.

Design Knowledge Management System (DKMS) Beta Test Report

DTIC Science & Technology

1992-11-01

design process. These problems, which include knowledge representation, constraint propagation, model design, and information integration, are...effective delivery of life-cycle engineering knowledge assistance and information to the design/engineering activities. It does not matter whether these...platfomi. 4. Reuse - existing data, information , and knowledge can be reused. 5. Remote Execution -- automatically handles remote execution without

Culture as a Tool: Facilitating Knowledge Construction in the Context of a Learning Community

ERIC Educational Resources Information Center

Chang, Bo

2010-01-01

Knowledge construction is regarded as an effective learning model in practice. When more and more learning communities are organized to promote knowledge construction, it is necessary to know how to use different tools to support knowledge construction in the learning community context. In the literature, few researchers discuss how to construct…

The assessment of knowledge and learning in competence spaces: The gain-loss model for dependent skills.

PubMed

Anselmi, Pasquale; Stefanutti, Luca; de Chiusole, Debora; Robusto, Egidio

2017-11-01

The gain-loss model (GaLoM) is a formal model for assessing knowledge and learning. In its original formulation, the GaLoM assumes independence among the skills. Such an assumption is not reasonable in several domains, in which some preliminary knowledge is the foundation for other knowledge. This paper presents an extension of the GaLoM to the case in which the skills are not independent, and the dependence relation among them is described by a well-graded competence space. The probability of mastering skill s at the pretest is conditional on the presence of all skills on which s depends. The probabilities of gaining or losing skill s when moving from pretest to posttest are conditional on the mastery of s at the pretest, and on the presence at the posttest of all skills on which s depends. Two formulations of the model are presented, in which the learning path is allowed to change from pretest to posttest or not. A simulation study shows that models based on the true competence space obtain a better fit than models based on false competence spaces, and are also characterized by a higher assessment accuracy. An empirical application shows that models based on pedagogically sound assumptions about the dependencies among the skills obtain a better fit than models assuming independence among the skills. © 2017 The British Psychological Society.

Perspectives to Performance of Environment and Health Assessments and Models—From Outputs to Outcomes?

PubMed Central

Pohjola, Mikko V.; Pohjola, Pasi; Tainio, Marko; Tuomisto, Jouni T.

2013-01-01

The calls for knowledge-based policy and policy-relevant research invoke a need to evaluate and manage environment and health assessments and models according to their societal outcomes. This review explores how well the existing approaches to assessment and model performance serve this need. The perspectives to assessment and model performance in the scientific literature can be called: (1) quality assurance/control, (2) uncertainty analysis, (3) technical assessment of models, (4) effectiveness and (5) other perspectives, according to what is primarily seen to constitute the goodness of assessments and models. The categorization is not strict and methods, tools and frameworks in different perspectives may overlap. However, altogether it seems that most approaches to assessment and model performance are relatively narrow in their scope. The focus in most approaches is on the outputs and making of assessments and models. Practical application of the outputs and the consequential outcomes are often left unaddressed. It appears that more comprehensive approaches that combine the essential characteristics of different perspectives are needed. This necessitates a better account of the mechanisms of collective knowledge creation and the relations between knowledge and practical action. Some new approaches to assessment, modeling and their evaluation and management span the chain from knowledge creation to societal outcomes, but the complexity of evaluating societal outcomes remains a challenge. PMID:23803642

XML-based data model and architecture for a knowledge-based grid-enabled problem-solving environment for high-throughput biological imaging.

PubMed

Ahmed, Wamiq M; Lenz, Dominik; Liu, Jia; Paul Robinson, J; Ghafoor, Arif

2008-03-01

High-throughput biological imaging uses automated imaging devices to collect a large number of microscopic images for analysis of biological systems and validation of scientific hypotheses. Efficient manipulation of these datasets for knowledge discovery requires high-performance computational resources, efficient storage, and automated tools for extracting and sharing such knowledge among different research sites. Newly emerging grid technologies provide powerful means for exploiting the full potential of these imaging techniques. Efficient utilization of grid resources requires the development of knowledge-based tools and services that combine domain knowledge with analysis algorithms. In this paper, we first investigate how grid infrastructure can facilitate high-throughput biological imaging research, and present an architecture for providing knowledge-based grid services for this field. We identify two levels of knowledge-based services. The first level provides tools for extracting spatiotemporal knowledge from image sets and the second level provides high-level knowledge management and reasoning services. We then present cellular imaging markup language, an extensible markup language-based language for modeling of biological images and representation of spatiotemporal knowledge. This scheme can be used for spatiotemporal event composition, matching, and automated knowledge extraction and representation for large biological imaging datasets. We demonstrate the expressive power of this formalism by means of different examples and extensive experimental results.

Multi-dimensional knowledge translation: enabling health informatics capacity audits using patient journey models.

PubMed

Catley, Christina; McGregor, Carolyn; Percival, Jennifer; Curry, Joanne; James, Andrew

2008-01-01

This paper presents a multi-dimensional approach to knowledge translation, enabling results obtained from a survey evaluating the uptake of Information Technology within Neonatal Intensive Care Units to be translated into knowledge, in the form of health informatics capacity audits. Survey data, having multiple roles, patient care scenarios, levels, and hospitals, is translated using a structured data modeling approach, into patient journey models. The data model is defined such that users can develop queries to generate patient journey models based on a pre-defined Patient Journey Model architecture (PaJMa). PaJMa models are then analyzed to build capacity audits. Capacity audits offer a sophisticated view of health informatics usage, providing not only details of what IT solutions a hospital utilizes, but also answering the questions: when, how and why, by determining when the IT solutions are integrated into the patient journey, how they support the patient information flow, and why they improve the patient journey.

Towards a reference plant trait ontology for modeling knowledge of plant traits and phenotypes

USDA-ARS?s Scientific Manuscript database

Ontology engineering and knowledge modeling for the plant sciences is expected to contribute to the understanding of the basis of plant traits that determine phenotypic expression in a given environment. Several crop- or clade-specific plant trait ontologies have been developed to describe plant tr...

Design as Knowledge Construction: Constructing Knowledge of Design

ERIC Educational Resources Information Center

Cennamo, Katherine C.

2004-01-01

In this article, I present a model of instructional design that has evolved from analysis and reflection on the process of designing materials for constructivist learning environments. I observed how we addressed the critical questions for instructional design, comparing the process to traditional instructional design models and to my emerging…

Upper Secondary Teachers' Knowledge for Teaching Chemical Bonding Models

ERIC Educational Resources Information Center

Bergqvist, Anna; Drechsler, Michal; Chang Rundgren, Shu-Nu

2016-01-01

Researchers have shown a growing interest in science teachers' professional knowledge in recent decades. The article focuses on how chemistry teachers impart chemical bonding, one of the most important topics covered in upper secondary school chemistry courses. Chemical bonding is primarily taught using models, which are key for understanding…

The University in the Knowledge Economy: The Triple Helix Model and Its Implications

ERIC Educational Resources Information Center

Zheng, Peijun; Harris, Michael

2007-01-01

In the context of the global knowledge economy, the three major players--university, industry, and government--are becoming increasingly interdependent. As more intensified interactions and relationships of increasing complexity among the institutions evolve, the Triple Helix model attempts to describe not only interactions among university,…

Educational Impact on the Relationship of Environmental Knowledge and Attitudes

ERIC Educational Resources Information Center

Liefländer, A. K.; Bogner, F. X.

2018-01-01

This study examines the relationships between the environmental attitudes and environmental knowledge of school children within the framework of an environmental intervention. We employed questions from the 2-MEV model to monitor students' environmental attitudes in terms of the model factors Preservation and Utilisation while concurrently…

Teaching Competencies Efficiently through the Internet--A Practical Example

ERIC Educational Resources Information Center

Caniels, Marjolein C. J.

2005-01-01

Universities increasingly adopt innovative teaching models, which focus on the development of skills instead of the reproduction of knowledge. These new teaching models emphasise the importance of knowledge application and the development of competencies. Yet, using these teaching methods usually implies a high assessment burden for lecturers.…

Understanding the Codevelopment of Modeling Practice and Ecological Knowledge

ERIC Educational Resources Information Center

Manz, Eve

2012-01-01

Despite a recent focus on engaging students in epistemic practices, there is relatively little research on how learning environments can support the simultaneous, coordinated development of both practice and the knowledge that emerges from and supports scientific activity. This study reports on the co-construction of modeling practice and…

Learning to Teach: Pedagogical Content Knowledge in Adventure-Based Learning

ERIC Educational Resources Information Center

Sutherland, Sue; Stuhr, Paul T.; Ayvazo, Shiri

2016-01-01

Background: Many alternative curricular models exist in physical education to better meet the needs of students than the multi-activity team sports curriculum that dominates in the USA. These alternative curricular models typically require different content knowledge (CK) and pedagogical CK (PCK) to implement successfully. One of the complexities…

Implicit Trust in a Data Model

DTIC Science & Technology

2011-10-01

model, interfacing will be easier 8. This aspect is usually not a concern for operators. 8. Interfacing can account for between 25-70% of the cost of...32 6.7.3 Flexibility . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 33 6.7.4 Cost of Knowledge Acquisition...51 8.5.4 Cost of Knowledge Acquisition . . . . . . . . . . . . . . . . . . 52 8.6 Reputation