A neuro-fuzzy approach to detect student's motivation

Stathacopoulou, R. and Samarakou, M. and Grigoriadou, M. and Magoulas, George (2004) A neuro-fuzzy approach to detect student's motivation. In: Kinshuk and Looi, C.-K. and Sutinen, E. and Sampson, D.G. and Aedo, I. and Uden, L. and Kahkonen, E. (eds.) Proceedings of the IEEE International Conference on Advanced Learning Technologies. IEEE Computer Society.

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Official URL: https://doi.org/10.1109/ICALT.2004.1357377

Abstract

In this paper the fuzzy knowledge representation of a neural network-based fuzzy model is presented. The model is used to assess student's motivational state in a discovery learning environment. Student's observable behavior and motivational factors are described with linguistic variables. The inputs of the model are tailored from real students' data, with the assistance of a group of expert teachers. Results of our preliminary study were encouraging, since data obtained from real students' log files, have been successfully used to form the membership functions that assign membership degrees to the linguistic values of the linguistic variables.

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:	22 Jun 2021 12:45
Last Modified:	09 Aug 2023 12:51
URI:	https://eprints.bbk.ac.uk/id/eprint/44851

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