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Evaluating DAS3H on the EdNet Dataset

Benoît Choffin 1 Fabrice Popineau 1 Yolaine Bourda 1 Jill-Jênn Vie 2
1 LaHDAK - Données et Connaissances Massives et Hétérogènes
LISN - Laboratoire Interdisciplinaire des Sciences du Numérique, SDD - Science des Données
2 Scool - Scool
Inria Lille - Nord Europe, CRIStAL - Centre de Recherche en Informatique, Signal et Automatique de Lille - UMR 9189
Abstract : The EdNet dataset is a massive English language dataset that poses unique challenges for student performance prediction. In this paper, we describe and comment the results of our award-winning model DAS3H in the context of knowledge tracing in EdNet.
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Contributor : Benoît Choffin Connect in order to contact the contributor
Submitted on : Tuesday, March 23, 2021 - 8:09:11 PM
Last modification on : Sunday, August 22, 2021 - 3:26:36 AM
Long-term archiving on: : Thursday, June 24, 2021 - 6:03:59 PM


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  • HAL Id : hal-03175874, version 1


Benoît Choffin, Fabrice Popineau, Yolaine Bourda, Jill-Jênn Vie. Evaluating DAS3H on the EdNet Dataset. AAAI 2021 - The 35th Conference on Artificial Intelligence / Imagining Post-COVID Education with AI, Feb 2021, Virtual, United States. ⟨hal-03175874⟩



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