Using rules discovery for the continuous improvement of e-learning courses

Authors:
Enrique García;Cristóbal Romero;Sebastián Ventura;Carlos de Castro
Affiliations:
Escuela Politécnica Superior, Universidad de Córdoba, Córdoba, Spain;Escuela Politécnica Superior, Universidad de Córdoba, Córdoba, Spain;Escuela Politécnica Superior, Universidad de Córdoba, Córdoba, Spain;Escuela Politécnica Superior, Universidad de Córdoba, Córdoba, Spain
Venue:
IDEAL'06 Proceedings of the 7th international conference on Intelligent Data Engineering and Automated Learning
Year:
2006

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Abstract

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.