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Journal articles on the topic 'Concept knowledge'

Author: Grafiati

Published: 25 June 2021

Last updated: 1 February 2022

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1

ZHENG, JEFFREY Z. J., CHRISTIAN H. H. ZHENG, and TOSIYASU L. KUNII. "CONCEPT CELL MODEL FOR KNOWLEDGE REPRESENTATION." International Journal of Information Acquisition 01, no. 02 (June 2004): 149–68. http://dx.doi.org/10.1142/s021987890400015x.

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This paper proposes a unified knowledge model establishing a core structure of knowledge representation in natural and artificial intelligence systems. The Concept Cell Model proposes the use of acyclic lattices to model a concept formed from a knowledge network of simpler concepts. Declarative and procedural knowledge are explicitly defined as the time-invariant and time-variant relationship of concepts. Examples of a Restaurant Servicing Concept Cell and an extended Shopping Complex Concept Cell are used to demonstrate the functionality of this model. Major existing theoretic and engineering Ontology knowledge schools are compared under this framework.

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Ullah, AMM Sharif. "Concept Map and Knowledge." Education Sciences 10, no. 9 (September 15, 2020): 246. http://dx.doi.org/10.3390/educsci10090246.

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3

Oden, G. C. "Concept, Knowledge, and Thought." Annual Review of Psychology 38, no. 1 (January 1987): 203–27. http://dx.doi.org/10.1146/annurev.ps.38.020187.001223.

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4

Bar-On, A. Zvie. "WITTGENSTEIN’S CONCEPT OF KNOWLEDGE." Grazer Philosophische studien 29, no. 1 (August 13, 1987): 63–75. http://dx.doi.org/10.1163/18756735-90000310.

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Messerschmidt, James W. "Engendering Gendered Knowledge." Men and Masculinities 15, no. 1 (January 12, 2012): 56–76. http://dx.doi.org/10.1177/1097184x11428384.

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The appropriation of concepts long established as salient contributions to gender theory and research recently has come under scholarly scrutiny. In this article, the author contributes to this dissection of crucial gender concepts by assessing the recent academic appropriation of the reformulated concept of “hegemonic masculinity” and how this appropriation engenders gendered knowledge. The author first briefly revisits the concept of hegemonic masculinity as reformulated by Connell and Messerschmidt. Following this, the author examines selected studies to illustrate how hegemonic masculinity has been appropriated differently, how this dissimilarity is significant for the production of gendered knowledge, and how several new directions in the appropriations extend gendered knowledge on hegemonic masculinity. Finally, the author discusses the relevance of all his conclusions to the wider debates over the concept of hegemonic masculinity and posits how these conclusions arguably impact future feminist/gender research and theory construction.

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Labouliere, Christa D., Sarah J. Tarquini, Christine M. W. Totura, Krista Kutash, and Marc S. Karver. "Revisiting the Concept of Knowledge." Crisis 36, no. 4 (July 2015): 274–80. http://dx.doi.org/10.1027/0227-5910/a000323.

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Abstract. Background: Although gatekeeper training is effective at increasing knowledge, some question the effectiveness of these programs due to high pretraining knowledge levels. However, knowledge scores may be artificially inflated when students guess answer options correctly but lack information needed to assist suicidal peers. Aims: To use free-recall questions to evaluate suicide prevention knowledge and compare levels of knowledge using this methodology with established assessment methods in the literature. Method: Free-recall knowledge questions were examined before and after participation in a student gatekeeper training program. Focus groups with students enriched interpretation of quantitative results. Results: Unlike in studies using forced-choice assessment, students’ baseline knowledge was markedly low using free-recall questions and, despite making significant improvement from pretraining levels, posttraining knowledge barely approached passable levels. Focus group findings suggest that training sessions may need to be more engaging and interactive in order to improve knowledge transfer. Conclusion: Free-recall questions may provide a less inflated measure of accessible knowledge learned from school-based suicide prevention curricula. Evaluators and programmatic partners should be cognizant of this methodological issue and consider using a mix of assessment methodologies to determine students’ actual levels of knowledge after participation in gatekeeper training.

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Murphy, Gregory L., and Thomas L. Spalding. "Knowledge, Similarity, and Concept Formation." Psychologica Belgica 35, no. 2-3 (January 1, 1995): 127. http://dx.doi.org/10.5334/pb.882.

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8

San Segundo, Rosa. "A new concept of knowledge." Online Information Review 26, no. 4 (August 2002): 239–45. http://dx.doi.org/10.1108/14684520210438688.

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Olson, Amy, and Abe Oudshoorn. "Knowledge translation: A concept analysis." Nursing Forum 55, no. 2 (November 13, 2019): 157–64. http://dx.doi.org/10.1111/nuf.12410.

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Rudas, Imre J. "Concept formation and knowledge revision." Engineering Applications of Artificial Intelligence 9, no. 3 (June 1996): 331–32. http://dx.doi.org/10.1016/0952-1976(96)84752-x.

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11

Ji, Lei, Yujing Wang, Botian Shi, Dawei Zhang, Zhongyuan Wang, and Jun Yan. "Microsoft Concept Graph: Mining Semantic Concepts for Short Text Understanding." Data Intelligence 1, no. 3 (June 2019): 238–70. http://dx.doi.org/10.1162/dint_a_00013.

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Knowlege is important for text-related applications. In this paper, we introduce Microsoft Concept Graph, a knowledge graph engine that provides concept tagging APIs to facilitate the understanding of human languages. Microsoft Concept Graph is built upon Probase, a universal probabilistic taxonomy consisting of instances and concepts mined from the Web. We start by introducing the construction of the knowledge graph through iterative semantic extraction and taxonomy construction procedures, which extract 2.7 million concepts from 1.68 billion Web pages. We then use conceptualization models to represent text in the concept space to empower text-related applications, such as topic search, query recommendation, Web table understanding and Ads relevance. Since the release in 2016, Microsoft Concept Graph has received more than 100,000 pageviews, 2 million API calls and 3,000 registered downloads from 50,000 visitors over 64 countries.

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12

Keursten, Paul, and Marcel van der Klink. "Enabling knowledge creation: an emerging concept of knowledge management." Human Resource Development International 6, no. 1 (March 2003): 117–23. http://dx.doi.org/10.1080/13678860210166988.

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13

Ankitha, Arelli. "The Concept of Knowledge Management it’s Impact on Indian Companies." International Journal of Trend in Scientific Research and Development Volume-2, Issue-3 (April 30, 2018): 2623–26. http://dx.doi.org/10.31142/ijtsrd12892.

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14

Machery, Edouard. "The heterogeneity of knowledge representation and the elimination of concept." Behavioral and Brain Sciences 33, no. 2-3 (June 2010): 231–44. http://dx.doi.org/10.1017/s0140525x10000932.

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AbstractIn this response, I begin by defending and clarifying the notion of concept proposed in Doing without Concepts (Machery 2009) against the alternatives proposed by several commentators. I then discuss whether psychologists and philosophers who theorize about concepts are talking about distinct phenomena or about different aspects of the same phenomenon, as argued in some commentaries. Next, I criticize the idea that the cognitive-scientific findings about induction, categorization, concept combination, and so on, could be explained by positing a single kind of concept, and I insist that many categories (substances, types of events, etc.) are represented by distinct coreferential concepts that belong to very different kinds of concept. This is followed by an assessment of the hybrid theories of concepts offered by commentators, according to which categories, substances, and types of events are represented by hybrid concepts made of several parts. Finally, I defend the proposal that it may be useful to eliminate concept from the theoretical vocabulary of psychology.

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Arboit, Aline Ellis. "Knowledge Organization: From Term to Concept, From Concept to Domain." KNOWLEDGE ORGANIZATION 45, no. 2 (2018): 125–36. http://dx.doi.org/10.5771/0943-7444-2018-2-125.

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Hackenberg, Amy J., and Mi Yeon Lee. "Relationships Between Students' Fractional Knowledge and Equation Writing." Journal for Research in Mathematics Education 46, no. 2 (March 2015): 196–243. http://dx.doi.org/10.5951/jresematheduc.46.2.0196.

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To understand relationships between students' fractional knowledge and algebraic reasoning in the domain of equation writing, an interview study was conducted with 12 secondary school students, 6 students operating with each of 2 different multiplicative concepts. These concepts are based on how students coordinate composite units. Students participated in two 45-minute interviews and completed a written fractions assessment. Students operating with the second multiplicative concept had not constructed fractional numbers, but students operating with the third multiplicative concept had; students operating with the second multiplicative concept represented multiplicatively related unknowns in qualitatively different ways than students operating with the third multiplicative concept. A facilitative link is proposed between the construction of fractional numbers and how students represent multiplicatively related unknowns.

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17

Kim, Hyeon Ju, and Joo Hyun Kim. "Concept Analysis of Tacit Nursing Knowledge." Journal of Korean Academy of Nursing 48, no. 6 (2018): 637. http://dx.doi.org/10.4040/jkan.2018.48.6.637.

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18

Chumakov, A. N., and P. S. Yurchenko. "Coronavirus and Globalization: Knowledge vs Concept." EURASIAN INTEGRATION: economics, law, politics 14, no. 3 (October 18, 2020): 112–22. http://dx.doi.org/10.22394/2073-2929-2020-3-112-122.

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The coronavirus pandemic has generated a lot of talk about the post-coronavirus future of the world community and has drawn close attention to the globalization process. The article notes that something similar in the public consciousness took place after the publication of the first report to the Club of Rome, when the awareness of the danger posed by global problems had quickly come. Now, one of the global problems — the coronavirus pandemic — has changed the usual life rhythm of the entire world community in a matter of weeks. The relevance of the topic is so high that even those who, before that, not only professionally, but even seriously were not interested in either the problems of medicine or global problems, actively joined its discussion. As a result, on the pages of many print and electronic publications, along with serious and verified information, all sorts of guesses and speculations about the nature and correlation of coronavirus and globalization are multiplied. Only knowledge can be opposed to this, according to the authors.

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19

Viju, Jeena Sara. "Concept Interpretation by Semantic Knowledge Harvesting." International Journal for Research in Applied Science and Engineering Technology 6, no. 5 (May 31, 2018): 477–84. http://dx.doi.org/10.22214/ijraset.2018.5081.

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20

Blais, Christine. "Concept Mapping of Movement-Related Knowledge." Perceptual and Motor Skills 76, no. 3 (June 1993): 767–74. http://dx.doi.org/10.2466/pms.1993.76.3.767.

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Concept mapping was developed by Novak and Gowin in 1984 as a technique to examine an individual's knowledge-base in a given domain. In the motor domain, however, with a heavy emphasis on automated and tacit knowledge there may not be a base of information which can be verbally reported. 52 subjects with similar academic backgrounds were asked to explain all they knew about the concept of movement, and these reports were transcribed and assessed by four judges. Subjects also completed a pattern-recognition task related to procedural knowledge for movement. Over-all, the judges were able to identify a clear hierarchy in the levels of movement-related knowledge, suggesting that this technique may be useful in research on movement. However, this declarative knowledge appeared to be distinct from associated procedural knowledge, supporting Anderson's (1982) theory and the need for several tools to provide a more complete reflection of the knowledge base in a particular domain.

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21

Kalfoss, Mary, and Jenny Owe Cand. "Building Knowledge: The Concept of Care." Open Journal of Nursing 06, no. 12 (2016): 995–1011. http://dx.doi.org/10.4236/ojn.2016.612096.

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22

Witten, Ian H., and Bruce A. MacDonald. "Using concept learning for knowledge acquisition." International Journal of Man-Machine Studies 29, no. 2 (August 1988): 171–96. http://dx.doi.org/10.1016/s0020-7373(88)80045-2.

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23

Barrios, Edison. "Knowledge of Grammar and Concept Possession." British Journal for the Philosophy of Science 63, no. 3 (September 1, 2012): 577–606. http://dx.doi.org/10.1093/bjps/axr040.

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24

Leszczynska, Agnieszka. "The concept of knowledge strategy process." International Journal of Management and Enterprise Development 8, no. 4 (2010): 317. http://dx.doi.org/10.1504/ijmed.2010.033618.

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25

Pyöriä, Pasi. "The concept of knowledge work revisited." Journal of Knowledge Management 9, no. 3 (June 2005): 116–27. http://dx.doi.org/10.1108/13673270510602818.

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26

van der Veer, Rene. "From Concept Attainment to Knowledge Formation." Mind, Culture, and Activity 5, no. 2 (January 1, 1998): 89–94. http://dx.doi.org/10.1207/s15327884mca0502_2.

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27

Liu, Chen‐Chung, Shih‐Hsun Fan Chiang, Chih‐Yueh Chou, and Sherry Y. Chen. "Knowledge exploration with concept association techniques." Online Information Review 34, no. 5 (September 28, 2010): 786–805. http://dx.doi.org/10.1108/14684521011084627.

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28

Regan, Elizabeth A. "Knowledge Management: Evolving Concept and Practice." International Journal of Knowledge, Culture, and Change Management: Annual Review 6, no. 9 (2007): 11–24. http://dx.doi.org/10.18848/1447-9524/cgp/v06i09/50280.

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29

Beryl Pilkington, F. "Growing Nursing Knowledge Through Concept Inventing." Nursing Science Quarterly 22, no. 2 (April 2009): 102. http://dx.doi.org/10.1177/0894318409332567.

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30

Schneider, Ursula. "Coping with the Concept of Knowledge." Management Learning 38, no. 5 (November 2007): 613–33. http://dx.doi.org/10.1177/1350507607083396.

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31

Huda, Miftachul, Jibrail Bin Yusuf, Kamarul Azmi Jasmi, and Gamal Nasir Zakaria. "Al-Zarnūjī’s Concept of Knowledge (‘Ilm)." SAGE Open 6, no. 3 (September 2016): 215824401666688. http://dx.doi.org/10.1177/2158244016666885.

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32

Wille, Rudolf. "Concept lattices and conceptual knowledge systems." Computers & Mathematics with Applications 23, no. 6-9 (March 1992): 493–515. http://dx.doi.org/10.1016/0898-1221(92)90120-7.

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33

Rotkin, Vladimir, Roman Yavich, and Sergey Malev. "Concept of A.I. Based Knowledge Generator." Journal of Education and e-Learning Research 5, no. 4 (2018): 235–41. http://dx.doi.org/10.20448/journal.509.2018.54.235.241.

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34

Lethbridge, Timothy C. "Metrics for Concept-Oriented Knowledge Bases." International Journal of Software Engineering and Knowledge Engineering 08, no. 02 (June 1998): 161–88. http://dx.doi.org/10.1142/s021819409800011x.

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Metrics are widely researched and used in software engineering; however there is little analogous work in the field of knowledge engineering. In other words, there are no widely-known metrics that the developers of knowledge bases can use to monitor and improve their work. In this paper we adapt the GQM (Goals-Questions-Metrics) methodology that is used to select and develop software metrics. We use the methodology to develop a series of metrics that measure the size and complexity of concept-oriented knowledge bases. Two of the metrics measure raw size; seven measure various aspects of complexity on scales of 0 to 1, and are shown to be largely independent of each other. The remaining three are compound metrics that combine aspects of the other nine in an attempt to measure the overall 'difficulty' or 'complexity' of a knowledge base. The metrics have been implemented and tested in the context of a knowledge management system called CODE4.

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Shafi Siddiqi, Sameer. "Concept of Knowledge in Quranic Perspective." RESEARCH REVIEW International Journal of Multidisciplinary 5, no. 12 (December 14, 2020): 164–67. http://dx.doi.org/10.31305/rrijm.2020.v05.i12.032.

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Huang, Sue-Fen. "Cognitive diagnostic assessment based on knowledge structure." MATEC Web of Conferences 169 (2018): 01020. http://dx.doi.org/10.1051/matecconf/201816901020.

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The purpose of this study is to provide an integrated method of fuzzy theory basis for individualized concept structure analysis. In order to insight the misconception of learning basic mathematics and progress teaching. This method integrates Fuzzy Logic Model of Perception (FLMP) and Interpretive Structural Modelling (ISM). The combined algorithm could analyze individualized concepts structure based on the comparisons with concept structure of expert. In this paper, some well-known knowledge structure assessment methods will be discussed. For item connection, Bart et al ordering theory and Takeya’s item relational structure provided ordering coefficient to construct item relationships and hierarchies. For concepts or skills connection, Warfield’s ISM and Lin et al Concept Advanced Interpretive Structural Modelling (CAISM) provided to construct graphic relationship among elements and display the individualized concept hierarchy structure by numeric and picture. Samples contain 427 which come from Min-Hwei Junior College. Subjects were analyzed by CAISM. It shows the traditional assessment is not the only criteria; it must be combined with other assessment tools. The result shows that CAISM gives meaningful learning and lacks of learners.

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37

Wang, Xu Yang. "A Knowledge Reduction Method Based on Concept Lattice." Advanced Materials Research 219-220 (March 2011): 604–7. http://dx.doi.org/10.4028/www.scientific.net/amr.219-220.604.

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Formal concept analysis and rough set theory provide two different methods for data analysis and knowledge processing. Knowledge reduct in this paper combines the two models. For an initial data sets described by formal context, look for absolute necessary attribute sets by applying rough set theory. The sets can image the concepts and hiberarchy structure completely. Then calculate the value cores of attributes values for all objects and delete redundant attributes. At last, delete repeated instances and get the minimum formal context. Construct the concept lattice of the minimum formal context can diminish the size of concept lattice of the initial table at a certain extent.

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Friedman, Alon, and Richard P. Smiraglia. "Nodes and arcs: concept map, semiotics, and knowledge organization." Journal of Documentation 69, no. 1 (January 11, 2013): 27–48. http://dx.doi.org/10.1108/00220411311295315.

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PurposeThe purpose of the research reported here is to improve comprehension of the socially‐negotiated identity of concepts in the domain of knowledge organization. Because knowledge organization as a domain has as its focus the order of concepts, both from a theoretical perspective and from an applied perspective, it is important to understand how the domain itself understands the meaning of a concept.Design/methodology/approachThe paper provides an empirical demonstration of how the domain itself understands the meaning of a concept. The paper employs content analysis to demonstrate the ways in which concepts are portrayed in KO concept maps as signs, and they are subjected to evaluative semiotic analysis as a way to understand their meaning. The frame was the entire population of formal proceedings in knowledge organization – all proceedings of the International Society for Knowledge Organization's international conferences (1990‐2010) and those of the annual classification workshops of the Special Interest Group for Classification Research of the American Society for Information Science and Technology (SIG/CR).FindingsA total of 344 concept maps were analyzed. There was no discernible chronological pattern. Most concept maps were created by authors who were professors from the USA, Germany, France, or Canada. Roughly half were judged to contain semiotic content. Peirceian semiotics predominated, and tended to convey greater granularity and complexity in conceptual terminology. Nodes could be identified as anchors of conceptual clusters in the domain; the arcs were identifiable as verbal relationship indicators. Saussurian concept maps were more applied than theoretical; Peirceian concept maps had more theoretical content.Originality/valueThe paper demonstrates important empirical evidence about the coherence of the domain of knowledge organization. Core values are conveyed across time through the concept maps in this population of conference papers.

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Mittelstrass, Jürgen. "The Order of Knowledge: From Disciplinarity to Transdisciplinarity and Back." European Review 26, S2 (August 20, 2018): S68—S75. http://dx.doi.org/10.1017/s1062798718000273.

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The concept of transdisciplinarity has found a foothold in science. It is increasingly taking the place of the concept of interdisciplinarity and is making the concept of disciplinarity look pale. However, the concept of transdisciplinarity is not self-explanatory – as it is often understood – and the concept of disciplinarity is not at all outdated – as it seems. This becomes clear in the conceptual analysis of the concepts of disciplinarity, interdisciplinarity and transdisciplinarity.

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DONG, ANDY. "Concept formation as knowledge accumulation: A computational linguistics study." Artificial Intelligence for Engineering Design, Analysis and Manufacturing 20, no. 1 (February 2006): 35–53. http://dx.doi.org/10.1017/s0890060406060033.

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Language plays at least two roles in design. First, language serves as representations of ideas and concepts through linguistic behaviors that represent the structure of thought during the design process. Second, language also performs actions and creates states of affairs. Based on these two perspectives on language use in design, we apply the computational linguistics tools of latent semantic analysis and lexical chain analysis to characterize how design teams engage in concept formation as the accumulation of knowledge represented by lexicalized concepts. The accumulation is described in a data structure comprised by a set of links between elemental lexicalized concepts. The folding together of these two perspectives on language use in design with the information processing theories of the mind afforded by the computational linguistics tools applied creates a new means to evaluate concept formation in design teams. The method suggests that analysis at a linguistic level can characterize concept formation even where process-oriented critiques were limited in their ability to uncover a formal design method that could explain the phenomenon.

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41

TODOROV, KONSTANTIN, CELINE HUDELOT, ADRIAN POPESCU, and PETER GEIBEL. "FUZZY ONTOLOGY ALIGNMENT USING BACKGROUND KNOWLEDGE." International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems 22, no. 01 (February 2014): 75–112. http://dx.doi.org/10.1142/s0218488514500044.

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We propose an ontology alignment framework with two core features: the use of background knowledge and the ability to handle vagueness in the matching process and the resulting concept alignments. The procedure is based on the use of a generic reference vocabulary, which is used for fuzzifying the ontologies to be matched. The choice of this vocabulary is problem-dependent in general, although Wikipedia represents a general-purpose source of knowledge that can be used in many cases, and even allows cross language matchings. In the first step of our approach, each domain concept is represented as a fuzzy set of reference concepts. In the next step, the fuzzified domain concepts are matched to one another, resulting in fuzzy descriptions of the matches of the original concepts. Based on these concept matches, we propose an algorithm that produces a merged fuzzy ontology that captures what is common to the source ontologies. The paper describes experiments in the domain of multimedia by using ontologies containing tagged images, as well as an evaluation of the approach in an information retrieval setting. The undertaken fuzzy approach has been compared to a classical crisp alignment by the help of a ground truth that was created based on human judgment.

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Sinclair, Rebekah. "Un-Settling Species Concepts through Indigenous Knowledge." Environmental Ethics 42, no. 4 (2020): 313–34. http://dx.doi.org/10.5840/enviroethics202042431.

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The voices of Native American philosophers, scientists, and storytellers need to be amplified to problematize and decolonize the often taken-for-granted concept of species in environmental ethics. Especially in the context of climate change, concepts such as cross-species native,invasive, and endangered species have become cornerstones for understanding and evaluating moral obligations to other lives.Yet, even as the species concept does ethical work, it has not itself been subject to critical ethical evaluation. Instead, uncritical treatment of the species concept can naturalize Western metaphysical conceptual habits in ways that both support settler colonial organization of the world and conflict with Indigenous ontological and ethico-epistemological understandings of species. This can be especially problematic as scientists and environmentalists increasingly seek to engage Indigenous knowledge of particular species (for the purposes of conservation, for example) while assuming the sovereignty and objectivity of Western scientific taxonomies and species concepts. Yet, far from being objective and neutral with respect to culture, Western species concepts and taxonomies were first universalized and naturalized in part through the cooption and dismissal of Indigenous species knowledges.

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Kiv, Arnold, Vladimir Soloviev, Elena Tarasova, Tetyana Koycheva, and Katrina Kolesnykova. "Semantic knowledge networks in education." E3S Web of Conferences 166 (2020): 10022. http://dx.doi.org/10.1051/e3sconf/202016610022.

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The article is devoted to the modeling a semantic knowledge networks. The knowledge network is the basic concept of the problem of knowledge management. This is a new discipline that implements the principles of sustainable development of education. The method of constructing a semantic knowledge network allows us to analyze the connections between educational disciplines: “Economic Cybernetics”, “Algorithms and Programming” and “Calculus”. The paper compares the topological characteristics of the concept graphs related to various disciplines. We develop the algorithm to implement the subject area model in the form of a semantic knowledge network. 125 concepts are analyzed that provide optimal mastering disciplines and establish the connection between them.

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44

Sisson, Philip, and Julie J. C. H. Ryan. "A Knowledge Concept Map: Structured Concept Analysis from Systematic Literature Review." Journal of Entrepreneurship, Management and Innovation 13, no. 3 (2017): 29–69. http://dx.doi.org/10.7341/20171332.

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45

Abdurakhmanova, Kh T. "COGNITIVE CONCEPT «KNOWLEDGE» IN THE ENGLISH LINGUISTIC WORLD PICTURE." Международный журнал экспериментального образования (International Journal of Experimental Education), no. 1 2021 (2021): 5–9. http://dx.doi.org/10.17513/mjeo.12004.

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46

Burrows, Nikita L., and Suazette Reid Mooring. "Using concept mapping to uncover students' knowledge structures of chemical bonding concepts." Chemistry Education Research and Practice 16, no. 1 (2015): 53–66. http://dx.doi.org/10.1039/c4rp00180j.

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General chemistry is the first undergraduate course in which students further develop their understanding of fundamental chemical concepts. Many of these fundamental topics highlight the numerous conceptual interconnections present in chemistry. However, many students possess incoherent knowledge structures regarding these topics. Therefore, effective assessments are needed to identify these interconnections. The use of concept-mapping and think-aloud interviews to investigate the knowledge structures of undergraduate organic chemistry students' regarding bonding concepts is the focus of this research study. Herein, we spotlight the bonding concepts of electronegativity and polar covalent bonds. In essence, the study found that understanding of electronegativity was weak among students with low concept map scores (LS students) compared to students with high concept map scores (HS students). Additionally, several common misconceptions of electronegativity were revealed through student interviews. An examination of LS student interviews further revealed that a lack of understanding of electronegativity led to a misunderstanding of polar covalent bonding. The think-aloud interviews were a reflection of the connections students made with the concepts of electronegativity and polar covalent bonding in their concept maps. Implications for the chemistry curriculum are also presented.

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Kinchin, Ian M., Aet Möllits, and Priit Reiska. "Uncovering Types of Knowledge in Concept Maps." Education Sciences 9, no. 2 (June 13, 2019): 131. http://dx.doi.org/10.3390/educsci9020131.

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Concept maps have been shown to have a positive impact on the quality of student learning in a variety of disciplinary contexts and educational levels from primary school to university by helping students to connect ideas and develop a productive knowledge structure to support future learning. However, the evaluation of concept maps has always been a contentious issue. Some authors focus on the quantitative assessment of maps, while others prefer a more descriptive determination of map quality. To our knowledge, no previous consideration of concept maps has evaluated the different types of knowledge (e.g., procedural and conceptual) embedded within a concept map, or the ways in which they may interact. In this paper we consider maps using the lens provided by the Legitimation Code Theory (LCT) to analyze concept maps in terms of semantic gravity and semantic density. Weaving between these qualitatively, different knowledges are considered necessary to achieve professional knowledge or expert understanding. Exemplar maps are used as illustrations of the way in which students may navigate their learning towards expertise and how this is manifested in their concept maps. Implications for curriculum design and teaching evaluation are included.

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Crampes, Michel, Sylvie Ranwez, Jean Villerd, Filip Velickovski, Chris Mooney, Andrew Emery, and Nicholas Mille. "Concept Maps for Designing Adaptive Knowledge Maps." Information Visualization 5, no. 3 (June 22, 2006): 211–24. http://dx.doi.org/10.1057/palgrave.ivs.9500127.

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Concept Maps (CMaps) are an excellent method to visually represent and interact with a knowledge domain. A Knowledge Map (KMap) is a further complicated instance of a CMap, containing many instances of concepts and concept relations that add to the complexity of a visual representation. Adaptivity is also a key requirement for KMaps that we will demonstrate through practical example. This paper presents both a method, called ‘Domain-View-Controller’ (DVC) and a software environment specifically designed to create adaptive KMaps from CMaps. These tools give professional knowledge designers the means for specifying the domain knowledge of end users, allowing them to build well-organized adaptive KMaps with partial automated assistance. This paper also presents a scheme for the fully automated process of creating KMaps from domain specifications, giving end users the ability to display complex knowledge without having the expertise of knowledge engineers. The paper focuses on a real-world example from the domain of music to illustrate the underlying principles.

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Tangaraja, Gangeswari, Roziah Mohd Rasdi, Bahaman Abu Samah, and Maimunah Ismail. "Knowledge sharing is knowledge transfer: a misconception in the literature." Journal of Knowledge Management 20, no. 4 (July 11, 2016): 653–70. http://dx.doi.org/10.1108/jkm-11-2015-0427.

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Purpose The paper aims to clearly differentiate knowledge sharing (KS) and knowledge transfer (KT) besides exemplifying their interconnections to minimize the current confusions in the knowledge management (KM) literature. Design/methodology/approach An extensive literature review method was used to analyse relevant literature on both KS and KT to clearly delineate their differences and their interconnections. Findings The paper found that KS is a subset of KT (using personalization strategy), whereas KT as a whole is a broader concept, if compared with KS. However, KS is not one of the immediate processes involved in KT (using codification strategy). The processes involved in KS and KT differ according to the strategy used (in KT) and perspective chosen (in KS). Other findings include KS (unidirectional) as reflective concept (viewed so far), whereas KS (bidirectional), KT (personalization) and KT (codification) as formative concepts. Research limitations/implications The findings of this paper were based on the review of selected relevant articles only. Practical Implications The paper will minimize the current confusions in the KM literature and will assist future researches on both KS and KT to ensure what these concepts entail to avoid construct underrepresentation. Originality/value As compared to previous attempts, the present paper has shown the interconnections between KS and KT, as well as the differences based on the two perspectives of KS (unidirectional/bidirectional) and the two strategies of KT (personalization/codification), and such effort is new in the literature.

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TAN, AH-HWEE, and HUI-SHIN VIVIEN SOON. "CONCEPT HIERARCHY MEMORY MODEL: A NEURAL ARCHITECTURE FOR CONCEPTUAL KNOWLEDGE REPRESENTATION, LEARNING, AND COMMONSENSE REASONING." International Journal of Neural Systems 07, no. 03 (July 1996): 305–19. http://dx.doi.org/10.1142/s0129065796000270.

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This article introduces a neural network based cognitive architecture termed Concept Hierarchy Memory Model (CHMM) for conceptual knowledge representation and commonsense reasoning. CHMM is composed of two subnetworks: a Concept Formation Network (CFN), that acquires concepts based on their sensory representations; and a Concept Hierarchy Network (CHN), that encodes hierarchical relationships between concepts. Based on Adaptive Resonance Associative Map (ARAM), a supervised Adaptive Resonance Theory (ART) model, CHMM provides a systematic treatment for concept formation and organization of a concept hierarchy. Specifically, a concept can be learned by sampling activities across multiple sensory fields. By chunking relations between concepts as cognitive codes, a concept hierarchy can be learned/modified through experience. Also, fuzzy relations between concepts can now be represented in terms of the weights on the links connecting them. Using a unified inferencing mechanism based on code firing, CHMM performs an important class of commonsense reasoning, including concept recognition and property inheritance.

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