Applying computational science techniques to support adaptive learning

Authors:
Juan M. Santos;Luis Anido;Martín Llamas;Luis M. Álvarez;Fernando A. Mikic
Affiliations:
E.T.S.E. Telecomunicacións, Vigo, Pontevedra, Spain;E.T.S.E. Telecomunicacións, Vigo, Pontevedra, Spain;E.T.S.E. Telecomunicacións, Vigo, Pontevedra, Spain;E.T.S.E. Telecomunicacións, Vigo, Pontevedra, Spain;E.T.S.E. Telecomunicacións, Vigo, Pontevedra, Spain
Venue:
ICCS'03 Proceedings of the 2003 international conference on Computational science: PartII
Year:
2003

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Abstract

Adaptive Learning Systems offer customized learning experiences according to the actual student needs and capabilities. Effective student modelling, adequate representation of the knowledge domain and proper characterization of learning tools are key issues to provide high quality Adaptive Learning Systems. Most current systems are based on Artificial Intelligence techniques (e.g. fuzzy logic, neural networks, Bayesian networks, etc.) trying to reproduce human teaching behaviours by using a computational representation of expertise. This paper offers a survey on Adaptive Learning showing how Computational Science techniques are applied to instructional systems and identifying forthcoming trends for the future.