Can learner characteristics predict their behaviour on MOOCs?

Abstract

The full-text may be used and/or reproduced, and given to third parties in any format or medium, without prior permission or charge, for personal research or study, educational, or not-for-prot purposes provided that:• a full bibliographic reference is made to the original source • a link is made to the metadata record in DRO • the full-text is not changed in any way The full-text must not be sold in any format or medium without the formal permission of the copyright holders.Please consult the full DRO policy for further details. ABSTRACTStereotyping is the first type of adaptation in education ever proposed. However, the early systems have never dealt with the numbers of learners that current MOOCs provide. Thus, the umbrella question that this work tackles is if learner characteristics can predict their overall, but also fine-grain behaviour. Earlier results point at differences related to gender or to age. However, our finer-grain analysis shows that the result may further depend on the course topic, or even week. Surprisingly, for instance, women chat less in a Psychology-related course, but more (or similar) on a Computer Science course. These results are analysed in this paper in details, including different methods of averaging comments, leading to surprisingly different results. The outcomes can help in informing future runs, in terms of potential personalised feedback for teachers and students.

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