@proceedings{67,
title = {An Ontology-Based Model for Student Representation in Intelligent Tutoring Systems for Distance Learning},
author = {Ioannis Panagiotopoulos and Aikaterini Kalou and Christos Pierrakeas and Achilles Kameas},
url = {http://link.springer.com/chapter/10.1007/978-3-642-33409-2_31},
year = {2012},
date = {2012-01-01},
journal = {8th Artificial Intelligence Applications and Innovations (AIAI 2012).},
volume = {IFIP AICT 381},
publisher = {Springer Berlin Heidelberg},
address = {Halkidiki, Greece},
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) studenttextquoterights academic information and (b) studenttextquoterights 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.
<p style="text-align: justify;">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) studenttextquoterights academic information and (b) studenttextquoterights 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.</p>
