An Ontological Approach to Infer Student’s Emotions
This paper presents a method which is based on an Ontological Approach in combination with the Bayesian Network (BN) model in order to elicit student’s emotion during the learning process. The produced Ontology serves as a basis for the formal representation of emotions and it is stored in the Learner Affective Model (LAM). The use of BNs contributes to the identification of student’s affective state and deals with affective information (emotions, personality) which involves uncertainty. The proposed method is exploited by an Affective Module of a Web-Based Adaptive Educational System, which is called MENTOR, to support personalized distance learning.