Fuzzy Logic in Student Modeling

Abstract

The significant development of the e-learning systems has changed the ways of teaching and learning. In nowadays, everyone can have access to e-learning systems from everywhere. Therefore, the e-learning systems have to adapt the learning material and processes to the needs of each individual learner. However, learning and student’s diagnosis are complex processes, which deal with uncertainty. A solution to this is the use of fuzzy logic, which is able to deal with uncertainty and inaccurate data. This chapter explains how fuzzy logic can be used to automatically model the learning or forgetting process of a student, offering adaptation and increasing the learning effectiveness in Intelligent Tutoring Systems. In particular, it presents a novel rule-based fuzzy logic system, which models the cognitive state transitions of learners, such as forgetting, learning or assimilating. The operation of the presented approach is based on a Fuzzy Network of Related-Concepts (FNR-C), which is a combination of a network of concepts and fuzzy logic. It is used to represent so the organization and structure of the learning material as the knowledge dependencies that exist between the domain concepts of the learning material.