Educational data mining: a review of the state of the art
IEEE Transactions on Systems, Man, and Cybernetics, Part C: Applications and Reviews
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With the rapid development of Internet and Mobile technologies, Web-based Mobile-Learning System has created new ways for educators to communicate with learners. Association rule mining is one of the most important fields in data mining and knowledge discovery in databases. Rules explosion is a serious problem which causes great concerned, as conventional mining algorithms often produce too many rules for decision makers to digest. Since Web-based Mobile-Learning System collects vast amounts of learners profile data, data mining and knowledge discovery techniques can be applied to find interesting relationships between attributes of learners, assessments, the solution strategies adopted by learners and so on. Therefore, this paper concentrates on a new data-mining algorithm, combined with the advantages of improved genetic agorithm, called ARGA (Association rules based on an improved Genetic Algorithm), to mine the association rules from a Web-based Mobile-Learning system. This paper first takes advantage of the genetic algorithm designed specifically for discovering association rules. Moreover, the analysis and experiments are also made to show the proposed method is more efficient and accurate than the Apriori algorithm in Mobile-Learning system.