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On the Architecture of Intelligent Tutoring Systems and Its Application to a Neural Networks Course

  • J. F. Vega-Riveros
Part of the Studies in Fuzziness and Soft Computing book series (STUDFUZZ, volume 36)

Abstract

This chapter presents the architecture of an Intelligent Tutoring System for a Neural Networks course that consists of four basic modules. The subject knowledge-base stores an object-oriented representation of the theme knowledge. The student modeling module traces the user interaction with the system and assess goal accomplishment and motivation-towards-achievement. The instructional strategy module in this implementation consists of a knowledge navigation tool based on a concept-space metaphor and an automatic multiple choice question generator. The user interface, based on the concept-space metaphor, provides the means for the student to access hypermedia information that includes theory and examples, the question generator and the neural networks simulators. The description of the architecture is followed by a presentation and analysis of a learning model based on which a new Intelligent Tutoring System architecture using collaborating agents is proposed.

Keywords

Intelligent Tutoring System Student Modeling Instructional Model Membership Relation Neural Network Simulator 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2000

Authors and Affiliations

  • J. F. Vega-Riveros
    • 1
  1. 1.Department of Electronic EngineeringJaveriana UniversitySantafé de BogotáColombia

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