Managing the Learner Model With Multi-Entity Bayesian Networks in Adaptive Hypermedia Systems-Reference-Cited by-同舟云学术

Managing the Learner Model With Multi-Entity Bayesian Networks in Adaptive Hypermedia Systems

Published:2019 Issue: Volume: Page:89-108
ISSN:2326-8905
Container-title:Cognitive Computing in Technology-Enhanced Learning
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Author:

Tadlaoui Mouenis Anouar¹^ORCID,Carvalho Rommel Novaes²,Khaldi Mohamed¹^ORCID

Affiliation:

1. Abdelmalek Essaâdi University, Morocco

2. University of Brasília, Brazil

Abstract

Modeling the learner in adaptive systems involves different information. There are several methods to manage the learner model. They do not handle the uncertainty in the dynamic modeling of the learner. The main hypothesis of this chapter is the management of the learner model based on multi-entity Bayesian networks. This chapter focuses on modeling the learner model in a dynamic and probabilistic way. The authors propose in this work the use of the notion of fragments and m-theory to lead to a Bayesian multi-entity network. The use of this Bayesian method can handle the whole course of a learner as well as all of its shares in an adaptive educational hypermedia.

Publisher

IGI Global

Reference20 articles.

1. Anouar Tadlaoui, M. (2016). Gestion d’un modèle d’apprenant dans un système éducatif adaptatif basée sur les réseaux bayésiens. Academic Press.

2. Learner Modeling in Adaptive Educational Systems: A Comparative Study

3. The initialization of the learner model combining the Bayesian networks and the stereotypes methods

4. A learner model based on multi-entity Bayesian networks and artificial intelligence in adaptive hypermedia educational systems

5. Anouar Tadlaoui, M., Carvalho, R. N., & Khaldi, M. (2018). Combining the Overlay Model and Bayesian Networks to determine Learning styles in AHES. In Handbook of Research on E-Assessment in Higher Education. IGI Global.