Journals Proceedings

International Journal of Artificial Intelligence and Neural Networks

Ontology based approach to Fuzzy student model design



The integration of Information and Communication Technology (ICT) in the teaching and learning process in our today’s educational environments gave birth to what is known as elearning technology. Correct implementation of these e-learning technologies can brings about a number of potential benefits to the educational systems that can ultimately leads to achieving the desired objectives through the use of these modern and qualitative innovations. When these technologies and innovations are effectively used in the instructional process not only they will reduced the cost effectiveness of the pedagogical and other relative constrains, but can also create a conducive atmosphere for exploring effective designed components from different perspectives. An important component of these elearning systems in use today is called the intelligent tutoring system (ITS). ITS is a software system designed using artificial intelligent techniques (comprising of Fuzzy Logic, Neural-Networks, Bayesian networks, Ontology, Genetic Algorithms and Software Agents) to provide a personalized tutoring adaptable to each student based on his/her profile or characteristics. In this paper we intend to employ the use of Fuzzy logic and Ontology techniques to model the student’s learning behaviour with the aim of improving the learning path and increase the system’s adaptability. The use of fuzzy logic in this context is to enable the computational analysis of the student’s characteristics and learning behaviours in order to handle the uncertainty issues related to the student model design. Ontology approach on the other hand is one of the recent techniques used to design the representation of student’s cognitive state. Moreover, Ontology is considered as a key component for managing knowledge in a particular domain, and we intend to use its methodology as a tool to examine and manage the student’s knowledge state, competency and skills.

No fo Author(s) : 2
Page(s) : 13 - 17
Electronic ISSN : 2250-3749
Volume 4 : Issue 2
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