Fuzzy Logic Representation for Student Modelling
- Cite this paper as:
- Goel G., Lallé S., Luengo V. (2012) Fuzzy Logic Representation for Student Modelling. In: Cerri S.A., Clancey W.J., Papadourakis G., Panourgia K. (eds) Intelligent Tutoring Systems. ITS 2012. Lecture Notes in Computer Science, vol 7315. Springer, Berlin, Heidelberg
Our aim is to develop a Fuzzy Logic based student model which removes the arbitrary specification of precise numbers and facilitates the modelling at a higher level of abstraction. Fuzzy Logic involves the use of natural language in the form of If-Then statements to demonstrate knowledge of domain experts and hence generates decisions and facilitates human reasoning based on imprecise information coming from the student-computer interaction. Our case study is in geometry. In this paper, we propose a fuzzy logic representation for student modelling and compare it with the Additive Factor Model (AFM) algorithm implemented on DataShop. Two rule-based fuzzy inference systems have been developed that ultimately predict the degree of error a student makes in the next attempt to the problem. Results indicate the rule-based systems achieve levels of accuracy matching that of the AFM algorithm.
KeywordsStudent model fuzzy inference system rule-base
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