Understanding Participant’s Behaviour in Massively Open Online Courses

As the offer of Massive Open Online Courses (MOOCs) continues to grow around the world, a great deal of MOOC research has focused on their low success rates and used indicators that might be more appropriate for traditional degree-seeking students than for MOOC learners, who, because of the openness of MOOCs, represent a more diverse clientele who exhibit different characteristics and behaviours. In this study, conducted in a French MOOC that is part of the EDUlib initiative, we systematically classified MOOC user profiles based on their behaviour in the open-source learning management system (LMS) — in this case, Sakai — and studied their survival in the MOOC. After formatting the logs in ordinal variables in order to reflect a continuum of participation central to the behavioural engagement concept (Fredricks, Blumenfeld, & Paris, 2004), we incrementally executed a two-step cluster analysis procedure that led us to identify five different user profiles, after having manually excluded Ghots : Browser, Self-Assessor, Serious Reader, Active-Independent, and Active-Social. These five profiles differed both qualitatively and quantitatively on the continuum of engagement, and a significant proportion of the less active profiles did not drop out of the MOOC. Our results confirm the importance of social behaviours, as in recent typologies, but also point out a new Self-Assessor category. The implications of these profiles for MOOC design are discussed.

International Review of Research in Open and Distributed Learning