Mining Concepts Relationship Based on Numeric Grades
With vigorous development of the Internet, e-learning system has
become more and more popular and many adaptive learning
systems have been developed. In recent years, researchers have
proposed various approaches for developing adaptive learning
systems based on concept maps. Nevertheless, most of them deal
only with binary grades of each test item, furthermore, the
existing methods that based on fuzzy set theory do not take in
consideration the conceptual weight of concept in each question
that might be cause to construct incorrectly relationships or
exaggerate the degree of relationship. To cope with this problem,
this study proposes an innovative approach to automatically
construct concept maps. Firstly, we use look ahead fuzzy
association rule mining algorithm to mind some information
about the relationships between questions, then we construct the
questions-relationships mapping. After that, we calculate the
relevance degree between concepts in each question to obtain the
final concept maps.
Keywords: Fuzzy Association Rules, Data Mining, Concept Maps, Analysis of Numerical Testing Scores
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