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Using a virtual student model for testing intelligent tutoring systems

Using a virtual student model for testing intelligent tutoring systems Education is increasingly using Intelligent Tutoring Systems ITS, both for modelling instructional and teaching strategies and for enhancing educational programs. The first part of the paper introduces the basic structure of an ITS as well as common problems being experienced within the ITS community. The second part describes WITNeSS an original hybrid intelligent system using FuzzyNeuralGA techniques for optimising the presentation of learning material to a student. The original work in this paper is related to the concept of a virtual student. This student model, modelled using fuzzy technologies, will be useful for any ITS, providing it with an optimal learning strategy for fitting the ITS itself to the unique needs of each individual student. In the third part, experiments focus on problems developing a virtual student model, which simulates, in a rudimentary way, human learning behaviour. Part four finishes with concluding remarks. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Interactive Technology and Smart Education Emerald Publishing

Using a virtual student model for testing intelligent tutoring systems

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Publisher
Emerald Publishing
Copyright
Copyright © Emerald Group Publishing Limited
ISSN
1741-5659
DOI
10.1108/17415650480000023
Publisher site
See Article on Publisher Site

Abstract

Education is increasingly using Intelligent Tutoring Systems ITS, both for modelling instructional and teaching strategies and for enhancing educational programs. The first part of the paper introduces the basic structure of an ITS as well as common problems being experienced within the ITS community. The second part describes WITNeSS an original hybrid intelligent system using FuzzyNeuralGA techniques for optimising the presentation of learning material to a student. The original work in this paper is related to the concept of a virtual student. This student model, modelled using fuzzy technologies, will be useful for any ITS, providing it with an optimal learning strategy for fitting the ITS itself to the unique needs of each individual student. In the third part, experiments focus on problems developing a virtual student model, which simulates, in a rudimentary way, human learning behaviour. Part four finishes with concluding remarks.

Journal

Interactive Technology and Smart EducationEmerald Publishing

Published: Aug 31, 2004

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