A similarity-based generalization of fuzzy orderings preserving the classical axioms
International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems
Formal Concept Analysis: Mathematical Foundations
Formal Concept Analysis: Mathematical Foundations
An Introduction to Systems Science
An Introduction to Systems Science
A knowledge-driven model to personalize e-learning
Journal on Educational Resources in Computing (JERIC)
Digital game-based learning (DGBL) model and development methodology for teaching history
WSEAS Transactions on Computers
Realization of E-University for distance learning
WSEAS Transactions on Computers
Advanced ontology management system for personalised e-Learning
Knowledge-Based Systems
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The main purpose of this study is to provide an integrated method for personal concept structure analysis. Based on the utility of S-P chart (student problem chart) to deal with classification for learning style, students of different learning style display its own features of concept structure. In this study, S-P chart is used to classify learning styles of students. Concept structure analysis (CSA) could display personalized concept structure. CSA algorithm is the major methodology and its foundation is fuzzy logic model of perception (FLMP) and interpretive structural modeling (ISM). CSA could clearly represent hierarchies and linkage among concepts. Therefore, CSA will be effectively to display features of personal concept structures. In this study, an empirical data for concepts of linear algebra from university students is discussed. The results show that students of varied learning styles own distinct knowledge structures. CSA combined with S-P chart could be feasible for cognitive diagnosis. According to the findings and results, some suggestions and recommendations for future research are discussed.