Designing a Fuzzy Learning Style Identifier in E-learning Environment

in an e-learning environment, learners have different previous knowledge, age, experience, motivation, and goals. Without adaptive approaches, effective learning doesn’t occur; therefore, the final goal in adaptive learning is offering courses and learning contents based on the specific characteristics of each learner. The most important step in adaptive learning is to select the appropriate index which based on educational adaptation is made. Researchers have used a variety of indexes, and because learning style is one of the most important characteristics to recognize any individual differences in the learning process to adapt in e-learning environment, in this study, the selective index is Kolb s learning style , which is very complex due to its uncertainty and cannot be exactly described and defined. The fuzzy sets theory was used to model the uncertainty and ambiguity by creating a set of rules to identify of learning style dimensions. For this purpose, a fuzzy system was designed that can identify learners learning style using network behaviors. The accuracy of this system in measuring the learning style of learners, compared with the results of a questionnaire previously completed by learners, was obtained 89.07%. The accuracy of this method is increased compared to other methods.