Comparing Student Model Accuracy with Bayesian Network and Fuzzy Logic in Predicting Student Knowledge Level
نویسنده
چکیده
The use of computer has widely used as a tool to help student in learning, one of the computer application to help student in learning is in the form of Intelligent Tutoring System. Intelligent Tutoring System used to diagnose student knowledge state and provide adaptive assistance to student. However, diagnosing student knowledge level is a difficult task due to rife with uncertainty. Student Model is the key component in Intelligent Tutoring System to deal with uncertainty. Bayesian Network and Fuzzy Logic is the most widely used to develop student model. In this paper we will compare the accuracy of student model developed with Bayesian Network and Fuzzy Logic in predicting student knowledge level.
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