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Evolutionary algorithms for subgroup discovery in e-learning: A practical application using Moodle data
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DOI：10.1016/j.eswa.2007.11.026.png)
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Abstract
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This work describes the application of subgroup discovery using evolutionary algorithms to the usage data of the Moodle Course management system, a case study of the University of Cordoba, Spain. The objective is to obtain rules which describe relationships between the student's usage of the different activities and modules provided by this c-learning system and the final marks obtained in the courses. We use an evolutionary algorithm for the induction of fuzzy rules in canonical form and disjunctive normal form. The results obtained by different algorithms for subgroup discovery are compared, showing the suitability of the evolutionary subgroup discovery to this problem. (c) 2007 Elsevier Ltd. All rights reserved.
Keywords:
Web-based education
Subgroup discovery
Evolutionary algorithms
Fuzzy rules
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