Predicting Student Participation in Peer Reviews in MOOCs

Abstract

Assessing and providing feedback to thousands of student artefacts in MOOCs is an unfeasible task for instructors. Peer review, a well-known pedagogical approach that offers various learning gains, has been a common approach to address this practical challenge. However, low student participation is a potential barrier to the success of peer reviews. The present study proposes an approach to predict student participation in peer reviews in a MOOC context, which can be utilized to achieve an effective peer-review activity. We attempt to predict the number of different peer works that students will review for each of four assignments based on their past activities in the course. Results show that students’ preceding activities were predictive of their participation in peer reviews starting from the first assignment, and that the prediction accuracy improved considerably with the inclusion of past peer-review activities.