Abstract

In the context of e-Learning systems, we can distinguish between two different types of settings. First, we have adaptable systems, which refer to the property of changing the system settings. The learner can change the behavior of the system. Then, the learner is able to customize the system in a specified way to fit the needs of users. The learner model is the key element to generate the adaptation of the system to each specific user. It’s a representation of the learner information through which the system is based in to make it adaptable. We will present in this paper the implementation of a probabilistic learner model developed based on multi entities Bayesian networks and artificial intelligence, into a Course Creation Application Compatible with LMS-LD. The results presented in this work favor the implementation of a learner model to endorse the adaptation into some learning situations that the learners have followed during a year of testing.

Keyword

Learner model, Learner profile, Adaptive hypermedia, LMS-LD, Multi entity Bayesian networks, Artificial intelligence, Collaborative learning, E-learning personalization, Learning styles.

Cite this article

Tadlaoui MA, El Moudden F, Khaldi M

Refference

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