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Does a Peer Recommender Foster Students' Engagement in MOOCs?

Abstract : Overall the social capital of MOOCs is under-exploited. For most students in MOOCs, autonomous learning often means learning alone. Students interested in adding a social dimension to their learning can browse discussion threads, join social medias and may decide to message other students… but usually in a random way. This common isolation might be a contributing factor on student attrition rate and on their general learning experience. To foster learners' persistence in MOOCs, we propose to enhance the MOOC experience with a recommender which provides each student with an individual list of rich-potential contacts, created in real-time on the basis of their own profile and activities. This paper describes a controlled study conducted from Sept. to Nov. 2015 during a MOOC on Project Management. A recommender panel was integrated to the users' interface and allowed to manage contacts, send them an instant message or consult their profile. The population (N = 8,673) was randomly split into 2 parts: a control group, without any recommendations, and an experimental group in which students could choose to activate and use the recommender. After having demonstrated that these populations were similar up to the activation of the recommender, we evaluate the effect of the recommender on the basis of four pillars of learners' persistence: attendance, completion, success and participation. Results suggest that the recommender improved all these four factors: students were much more likely to persist and engage in the MOOC if they received recommendations than if they did not.
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Contributor : François Bouchet <>
Submitted on : Tuesday, October 4, 2016 - 5:47:22 PM
Last modification on : Friday, September 24, 2021 - 2:42:01 PM
Long-term archiving on: : Friday, February 3, 2017 - 4:22:12 PM


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  • HAL Id : hal-01376431, version 1


Hugues Labarthe, François Bouchet, Rémi Bachelet, Kalina Yacef. Does a Peer Recommender Foster Students' Engagement in MOOCs?. 9th International Conference on Educational Data Mining, Jun 2016, Raleigh, United States. pp.418-423. ⟨hal-01376431⟩



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