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Rapport Année : 2022

Success Prediction in MOOCS based on a transfer learning approach

J Wu
  • Fonction : Auteur
N Ma
  • Fonction : Auteur

Résumé

Massive Open Online Courses (MOOCs) typically present a high rate of non-completing learners. Studying the characteristics of pass and fail learners should help to provide assistance and identify root causes for dropouts. In this work, we propose to improve a success prediction task on a specific course with a solution based on a transfer learning approach. Our experiments are validated on two datasets with different trace properties.
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Dates et versions

hal-04671262 , version 1 (14-08-2024)

Licence

Domaine public

Identifiants

  • HAL Id : hal-04671262 , version 1

Citer

Antoine Pigeau, J Wu, N Ma. Success Prediction in MOOCS based on a transfer learning approach. LS2N, Université de Nantes. 2022. ⟨hal-04671262⟩
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