The article discusses particularly the frequent itemsets concept to determine the interesting rules in the transaction database. We also focus on the analysis of past historical data of the courses enrollments or log data. It aims to discover relationships between student’s activities using association rules method in order to help the student to choose the most appropriate learning materials. In this article, we develop a distributed courses recommender system for the e-learning platform. Furthermore, most of the students in this platform are new graduates who have just come to integrate higher education and who need a system to help them to take the relevant courses that take into account the requirements and needs of each learner. However, this platform faces many challenges, such as the increasing amount of data, the diversity of pedagogical resources and a large number of learners that makes harder to find what the learners are really looking for.

The present work is a part of the ESTenLigne project which is the result of several years of experience for developing e-learning in Sidi Mohamed Ben Abdellah University through the implementation of open, online and adaptive learning environment.

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