Prerequisite Structure Discovery in Intelligent Tutoring Systems - Inria - Institut national de recherche en sciences et technologies du numérique Accéder directement au contenu
Communication Dans Un Congrès Année : 2023

Prerequisite Structure Discovery in Intelligent Tutoring Systems

Résumé

This paper addresses the importance of Knowledge Structure (KS) and Knowledge Tracing (KT) in improving the recommendation of educational content in intelligent tutoring systems. The KS represents the relations between different Knowledge Components (KCs), while KT predicts a learner's success based on her past history. The contribution of this research includes proposing a KT model that incorporates the KS as a learnable parameter, enabling the discovery of the underlying KS from learner trajectories. The quality of the uncovered KS is assessed by using it to recommend content and evaluating the recommendation algorithm with simulated students.
Fichier principal
Vignette du fichier
Annabi20232IICDLI.pdf (637.35 Ko) Télécharger le fichier
Origine : Fichiers produits par l'(les) auteur(s)

Dates et versions

hal-04401880 , version 1 (18-01-2024)

Licence

Paternité

Identifiants

Citer

Louis Annabi, Sao Mai Nguyen. Prerequisite Structure Discovery in Intelligent Tutoring Systems. ICDL 2023 - IEEE International Conference on Development and Learning, Nov 2023, Macau, China. pp.176-181, ⟨10.1109/icdl55364.2023.10364416⟩. ⟨hal-04401880⟩
26 Consultations
19 Téléchargements

Altmetric

Partager

Gmail Facebook X LinkedIn More