Towards Improving Students’ Forum Posts Categorization in MOOCs and Impact on Performance Prediction - Archive ouverte HAL Accéder directement au contenu
Communication Dans Un Congrès Année : 2019

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

Résumé

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.
Fichier principal
Vignette du fichier
LS final.pdf (114.64 Ko) Télécharger le fichier
Poster_LaS_v4.pdf (493.88 Ko) Télécharger le fichier
Origine : Fichiers produits par l'(les) auteur(s)
Format : Poster
Origine : Fichiers produits par l'(les) auteur(s)
Loading...

Dates et versions

hal-02157333 , version 1 (21-06-2019)

Identifiants

Citer

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⟩
142 Consultations
147 Téléchargements

Altmetric

Partager

Gmail Facebook X LinkedIn More