عنوان مقاله [English]
To predict academic performance of students and provide useful strategies for increasing the educational effectiveness of universities is of particular importance in the success of educational systems. The purpose of this paper is to identify the effective indicators on academic performance, predict students' academic status using data mining techniques, and finally present a new trend for modifying unit selection and educational strategies to increase the efficiency of the education system. Because, Demographic data and academic records of undergraduate students are entered in database. After data preprocessing, 13 attributes are selected and identified effective with different algorithms, different models were proposed to predict the student's academic status in the next semester. Then, a comparison between the results of 4 different algorithms has done and the Logit Boost algorithm is known as the best model in categorizing in two class and multi-class according to accuracy rate and ROC. So, the proposed model can be used as a decision support tool in educational systems. Finally, due to the results obtained and the opinions of the academic experts, the process of selecting the unit was redesigned.
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