Supporting Learner´s Needs with an Ontology-Based Bayesian Network

This paper presents a study of MENTOR, a web adaptive educational environment (WBES), where the learnerpsilas needs and preferences are diagnosed using an ontology-based Bayesian network approach during the learning process. Firstly, the proposed method uses an OWL ontology to store the affective knowledge regarding the learner. Then, this ontology is extended appropriately to deal with uncertainty so that a Bayesian network (BN) can be constructed from it. Finally, using the derived BN we can make inferences and reasoning on the learnerpsilas individual needs. In this way we form a schema where the uncertain affective information (AfI) can be represented efficiently and exploited properly in order to maintain the efforts of a learner. Therefore, based on this model we can detect the learnerpsilas affective model and to support his efforts during the learning process by suggesting the proper pedagogical guidance.