Adaptive MOOC - An Approach to Identify Learners' Preferences to Enhance Their Engagement

Massive Open Online Courses have completely revolutionized the delivery of education, affording new levels of access to learners of all walks of life around the world. However, one of the greatest challenges facing educators and the providers of platforms on which these courses are delivered is how to keep learners engaged in the courses and motivate them to complete the courses they are registered into. This paper proposes a novel method of improving learner engagement in a course by determining and appealing to individual preferences in content delivery. The proposed framework draws on learner log data from the LMS (Moodle) to cluster students according to their interactions with different types of course material. Based on the preferred content types for each cluster, we will be able to recommend the most suitable materials to the individual learners and enhance overall engagement and motivation towards active participation in the course. It also includes the results of a questionnaire circulated to these students, in order to cross-check the results of the clustering analysis and provide important insights with respect to the effectiveness of the proposed approach.