Prerequisite structure discovery for an intelligent tutoring system based on intrinsic motivation - Inria - Institut national de recherche en sciences et technologies du numérique Access content directly
Poster Communications Year : 2023

Prerequisite structure discovery for an intelligent tutoring system based on intrinsic motivation

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
Prerequisite_structure_discovery_in_intelligent_tutoring_systems___IMOL2.pdf (332.36 Ko) Télécharger le fichier
Origin : Files produced by the author(s)

Dates and versions

hal-04201624 , version 1 (11-09-2023)

Licence

Attribution

Identifiers

  • HAL Id : hal-04201624 , version 1

Cite

Louis Annabi, Sao Mai Nguyen. Prerequisite structure discovery for an intelligent tutoring system based on intrinsic motivation. IMOL 2023 - The 6th Internatinal Workshop on Intrinsically Motivated Open-ended Learning, Sep 2023, Paris, France. ⟨hal-04201624⟩
88 View
22 Download

Share

Gmail Facebook X LinkedIn More