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Communication Dans Un Congrès Année : 2012

Fuzzy Logic Representation for Student Modelling

Résumé

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.
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Dates et versions

hal-00873888 , version 1 (08-09-2021)

Identifiants

Citer

Goel Gagan, Sébastien Lalle, Vanda Luengo. Fuzzy Logic Representation for Student Modelling: Case Study on Geometry. ITS 2012 - 11th International Conference on Intelligent Tutoring Systems - Co-adaptation in Learning, Jun 2012, Chania, Crête, Greece. pp.428-433, ⟨10.1007/978-3-642-30950-2_55⟩. ⟨hal-00873888⟩
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