Predict Student Scores Using Bayesian Networks

Selection appropriate courses are one of the main student concerns in the universities which have direct major effects on their educational efficiency. Moreover the correct selections of the courses will decrease the student's educational failure. Prediction scores of the courses is one of the effective approaches which helps the students to select their courses intelligently. One can propose a model for predicting the student course scores based of the student's educational history. In this paper we propose a Bayesian Network model for prediction of student scores. The proposed model predicts the students' scores considering the students attributes and his educational history. To evaluate the efficiency of the proposed model, we use the GeNIe software(korb KB. , Nicholson AE) to run experiments. We have tested our proposed model on 500 different students which has been studied in various Information technology university levels. The results show that applying our proposed method has main effects on the quality of the students and can be used as a helpful tool for them.