MineL: A Framework for Mining E-Learning Logs

A. Bellaachia, E. Vommina (USA), and B. Berrada (Morocco)


E-learning, Data Mining, Graph Theory, and Personalization.


In this paper, we present a framework for personalizing the learning content in an adaptive learning environment by analyzing the navigational behavior and the performance of the learner in order to make the learner reach his learning objective. The overall effectiveness of an E-learning system can be made equal to that of a traditional classroom approach with efficient use of available technologies and analysis techniques. In this paper, we use weblog-based framework to analyze the navigational behavior in the E-learners. By personalizing the content, we mean the learning material provided to the learner would meet his or her interests. Our main objective is to achieve the above by focusing on the weblogs of the E-learning site to obtain the learning paths and the learner behavior. We discuss how mining techniques can be applied on the weblogs.

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