Prerequisite Structure Discovery in Intelligent Tutoring Systems - Inria - Institut national de recherche en sciences et technologies du numérique Access content directly
Conference Papers Year : 2023

Prerequisite Structure Discovery in Intelligent Tutoring Systems

Abstract

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
Origin : Files produced by the author(s)

Dates and versions

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

Licence

Attribution

Identifiers

Cite

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 View
16 Download

Altmetric

Share

Gmail Facebook X LinkedIn More