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Towards Improving Students’ Forum Posts Categorization in MOOCs and Impact on Performance Prediction

Abstract : Going beyond mere forum posts categorization is key to understand why some students struggle and eventually fail in MOOCs. We propose here an extension of a coding scheme and present the design of the associated automatic annotation tools to tag students’ questions in their forum posts. Working of four sessions of the same MOOC, we cluster students’ questions and show how the obtained clusters are consistent across all sessions and can be sometimes correlated with students’ success in the MOOC. Moreover, it helps us better understand the nature of questions asked by successful vs. unsuccessful students.
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https://hal.archives-ouvertes.fr/hal-02157333
Contributor : Vanda Luengo <>
Submitted on : Friday, June 21, 2019 - 2:09:35 PM
Last modification on : Tuesday, September 17, 2019 - 10:39:07 AM

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Fatima Harrak, Vanda Luengo, François Bouchet, Rémi Bachelet. Towards Improving Students’ Forum Posts Categorization in MOOCs and Impact on Performance Prediction. Learning @ Scale, Jun 2019, Chicago, United States. pp.47:1-47:4, ⟨10.1145/3330430.3333661⟩. ⟨hal-02157333⟩

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