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

Autor:	Mouenis Anouar Tadlaoui, Rommel N. Carvalho, Mohamed Khaldi
Rok vydání:	2019
Předmět:	Computer science business.industry Multi entity bayesian networks ComputingMilieux_COMPUTERSANDEDUCATION Artificial intelligence Adaptive hypermedia business
DOI:	10.4018/978-1-5225-9031-6.ch005
Popis:	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.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_________::137fc3aefd373a3952106acf5ea09d23 https://doi.org/10.4018/978-1-5225-9031-6.ch005 Zobrazit plný text záznamu