A conceptual map model for developing intelligent tutoring systems
Computers & Education
Evaluating students' learning achievement using fuzzy membership functions and fuzzy rules
Expert Systems with Applications: An International Journal
Automatically constructing concept maps based on fuzzy rules for adapting learning systems
Expert Systems with Applications: An International Journal
Automatically constructing grade membership functions of fuzzy rules for students' evaluation
Expert Systems with Applications: An International Journal
Solving Non-Uniqueness in Agglomerative Hierarchical Clustering Using Multidendrograms
Journal of Classification
Learning barriers diagnosis based on fuzzy rules for adaptive learning systems
Expert Systems with Applications: An International Journal
Extracting learning concepts from educational texts in intelligent tutoring systems automatically
Expert Systems with Applications: An International Journal
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Recently, testing and diagnostic learning systems have been considered as a useful tool for analyzing students' learning problems and giving helpful learning suggestions to them to improve their learning performance. Among the existing methods, a multi-expert approach has introduced a set of rules to integrate test item-concept relationship opinions given by multiple experts. However, when integrating the opinions from multiple experts, there are some problems that might effect on the quality of learning suggestions for students. Furthermore, it is time consuming to reconsidering their opinion when the conflict opinion exists. Therefore, a novel majority density approach is proposed to solve the mentioned problems. The experimental results show that this method can yield more reasonable integrated opinions than the previous approach and also reduce the number of reconsidering opinions.