A LEARNING STYLE INFERENCE SYSTEM BASED ON FUZZY LOGIC TECHNIQUE

Abstract

There are many reasons why education is very important in daily life and business. Such that learning will continue every time parallel to the rapid developments and changes in innovation and the technology. In this study, fuzzy logic based dunn learning style inference system is developed to measure student’s success in learning. Dunn learning style identifies five important factors on which student learning style differs; namely environmental, emotional, sociological, physiological, and psychological. In this study, a software system is developed and an interface which includes some questions in relation with Dunn learning style is designed.  Answers of the students are rated and given as an input to the proposed fuzzy logic engine. The proposed software system inferences Education Style, Learning Status and the Level of Learning Style of the student. By this way, the instructor will be able to match his teaching style with student's learning style which contributes to student’s success in education field.