A Neuro-Fuzzy Approach to Detect Student's Motivation

Authors:
Regina Stathacopoulou;Maria Samarakou;Maria Grigoriadou;George D. Magoulas
Affiliations:
University of Athens;Technological Education Institute of Athens;University of Athens;University of London
Venue:
ICALT '04 Proceedings of the IEEE International Conference on Advanced Learning Technologies
Year:
2004

Citing 0
Cited 2

Monitoring students' actions and using teachers' expertise in implementing and evaluating the neural network-based fuzzy diagnostic model

Expert Systems with Applications: An International Journal
Review Article: Applications of neuro fuzzy systems: A brief review and future outline

Applied Soft Computing

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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. Studentýs observable behavior and motivational factors are described with linguistic variables. The inputs of the model are tailored from real studentsý data, with the assistance of a group of expert teachers. Results of our preliminary study were encouraging, since data obtained from real studentsý log files, have been successfully used to form the membership functions that assign membership degrees to the linguistic values of the linguistic variables.