Using Rules Discovery for the Continuous Improvement of e-Learning Courses

This paper presents a cyclical methodology for the continuous improvement of e-learning courses using data mining techniques applied to education. For this purpose, a specific data mining tool has been developed, which discovers relevant relationships between data about how students use a course. Unlike others data mining approaches applied to education, which focus on the student, this method is aimed professors and how to help them improve the structure and contents of an e-learning course by making recommendations. We also use a rule discovery algorithm without parameters in order to be easily used by non-expert users in data mining. The results of experimental tests performed on an online course are also presented, demonstrating the usefulness of the proposed methodology and algorithm.

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