Grade prediction improved by regular and maximal association rules

Abstract

In this paper we propose a method of predicting student scholar performance using the power of regular and maximal association rules. Due to the large number of generated rules, traditional data mining algorithms can become difficult and inappropriate to educational systems. Thus, we use some methods to overcome this problem, discovering rules useful in educational process. These methods are applied to the e-learning system Moodle, for “Database” course.

Keywords

• Education data mining, Regular association rule, Maximal association rule, Learning management system

References

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