Computational intelligence in adaptive educational hypermedia

Papanikolaou, K.A. and Magoulas, George and Grigoriadou, M. (2000) Computational intelligence in adaptive educational hypermedia. In: UNSPECIFIED (ed.) Proceedings of the IEEE-INNS-ENNS International Joint Conference on Neural Networks, IJCNN 2000, Neural Computing: New Challenges and Perspectives for the New Millennium. IEEE Computer Society, pp. 629-636. ISBN 0769506194.

Full text not available from this repository.

Official URL: https://doi.org/10.1109/IJCNN.2000.859466

Abstract

In this paper neuro-fuzzy synergism is applied to implement content sequencing in adaptive hypermedia systems. The level of understanding of the learner is used to construct lessons adapted to the learner's knowledge goals and level of expertise on the domain concepts s/he has already studied. The learner's evaluation is based on defining appropriate fuzzy sets and relate learner's response with appropriate knowledge and cognitive characterizations. A connectionist-based structure of the domain knowledge is adopted for representing knowledge and inferring the planning strategy for generating the hypermedia page from pieces of educational material. The fuzziness associated with the evaluation of the learner is handled well by the proposed connectionist architecture.

Metadata

Item Type:	Book Section
School:	Birkbeck Faculties and Schools > Faculty of Science > School of Computing and Mathematical Sciences
Depositing User:	Sarah Hall
Date Deposited:	06 Jul 2021 11:03
Last Modified:	09 Aug 2023 12:51
URI:	https://eprints.bbk.ac.uk/id/eprint/44998

Statistics

Archive Staff Only (login required)

Edit/View Item