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Towards Improving Students' Forum Posts Categorization in MOOCs and Impact on Performance Prediction
Author(s) -
Fatima Harrak,
Vanda Luengo,
François Bouchet,
Rémi Bachelet
Publication year - 2019
Publication title -
proceedings of the sixth (2019) acm conference on learning @ scale
Language(s) - English
Resource type - Conference proceedings
DOI - 10.1145/3330430.3333661
Subject(s) - categorization , computer science , annotation , coding (social sciences) , key (lock) , scheme (mathematics) , mathematics education , world wide web , data science , psychology , artificial intelligence , sociology , mathematical analysis , social science , computer security , mathematics
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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