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

Abstract

The technological landscape of the modern e-learning is dominated by learning management systems.Learning management systems are powerful, integrated systems that support a number of activities carried out by teachers and students during the elearning process.Teachers use e-learning systems to develop course notes and quizzes on the web, to communicate with students and to monitor and classify student progress.Students use it for learning, communication and collaboration [1-2].There are various attempts to model the learner in different adaptive educational hypermedia; these are the static representations of this model, representations that are generally based on information given by the learner himself when he enters the system.This gives a static view of the learner model.