Using a hybrid rule-based approach in developing an intelligent tutoring system with knowledge acquisition and update capabilities

  • Authors:

  • Ioannis Hatzilygeroudis;Jim Prentzas

  • Affiliations:

  • Department of Computer Engineering and Informatics, School of Engineering, University of Patras, 26500 Patras, Hellas, Greece and Research Academic Computer Technology Institute, P.O. Box 1122, 26 ...;Department of Computer Engineering and Informatics, School of Engineering, University of Patras, 26500 Patras, Hellas, Greece and Research Academic Computer Technology Institute, P.O. Box 1122, 26 ...

  • Venue:
  • Expert Systems with Applications: An International Journal
  • Year:
  • 2004

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Abstract

In this paper, we present the architecture and describe the functionality of an Intelligent Tutoring System (ITS), which uses an expert system to make decisions during the teaching process. The expert system uses neurules for knowledge representation of the pedagogical knowledge. Neurules are a type of hybrid rules integrating symbolic rules with neurocomputing. The expert system consists of three components: the user modelling unit, the pedagogical unit and the inference system. The pedagogical knowledge is distributed in a number of neurule bases within the user modelling and the pedagogical unit. Another important component of the ITS, for both its development and maintenance, is its knowledge management unit, which provides knowledge acquisition and knowledge update capabilities to the system, that is, offers expert knowledge authoring capabilities to the system.