A Web-Based Intelligent Tutoring System Using Hybrid Rules as Its Representational Basis

Authors:
Jim Prentzas;Ioannis Hatzilygeroudis;John D. Garofalakis
Affiliations:
-;-;-
Venue:
ITS '02 Proceedings of the 6th International Conference on Intelligent Tutoring Systems
Year:
2002

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Abstract

In this paper, we present the architecture and describe the functionality of a Web-based Intelligent Tutoring System (ITS), which uses neurules for knowledge representation. Neurules are a type of hybrid rules integrating symbolic rules with neurocomputing. The use of neurules as the knowledge representation basis of the ITS results in a number of advantages. Part of the functionality of the ITS is controlled by a neurule-based inference engine. Apart from that, the system consists of four other components: the domain knowledge, containing the structure of the domain and the educational content, the user modeling component, which records information concerning the user, the pedagogical model, which encompasses knowledge regarding the various pedagogical decisions, and the supervisor unit that controls the functionality of the whole system. The system focuses on teaching Internet technologies.