Knowledge Evaluation Based on Learner Assessment and Utilizing Fuzzy System to Increase the Accuracy of Evaluation

Learner knowledge evaluation is a process of decision making, personalization and adaptation of learning system. Generally, Traditional methods of knowledge evaluation use few variables in the evaluation process; For instance, the only parameter which is involved in the process is accuracy of answers. While, in case of increasing the accuracy of evaluation in this process, more variables need to be considered. Fuzzy system with ability to accept variety of input variables, inference and output generation, is a good option for the process of evaluation, such that in the recent years there are so much effort in the way of using fuzzy logic and its capabilities in knowledge evaluation that have been done so far. In this paper we will present a method to evaluate the knowledge of learner that by using fuzzy system in three phases which are fuzzification, inference engine, defuzzifaction with considering more variables like accuracy rate, importance and complexity of questions, performs the evaluation process. The prime features of the presented system are clarity, flexibility and simplicity in implementation.