An ontology-based model for student representation in intelligent tutoring systems for distance learning

Abstract

An Intelligent Tutoring System (ITS) offers personalized education to each student in accordance with his/her learning preferences and his/her background. One of the most fundamental components of an ITS is the student model, that contains all the information about a student such as demographic information, learning style and academic performance. This information enables the system to be fully adapted to the student. Our research work intends to propose a student model and enhance it with semantics by developing (or via) an ontology in order to be exploitable effectively within an ITS, for example as a domain-independent vocabulary for the communication between intelligent agents. The ontology schema consists of two main taxonomies: (a) student's academic information and (b) student's personal information. The characteristics of the student that have been included in the student model ontology were derived from an empirical study on a sample of students. © 2012 IFIP International Federation for Information Processing.