Data mining: Prediction for performance improvement of graduate students using classification

Student performance in university courses is of great concern to the higher education where several factors may affect the performance. This paper is an attempt to apply the data mining processes, particularly classification, to help in enhancing the quality of the higher educational system by evaluating student data to study the main attributes that may affect the student performance in courses. For this purpose, we have used data obtained from Vikram University, Ujjain of course B.A. first year student. The classification rule generation process is based on the decision tree as a classification method where the generated rules are studied and evaluated. A system that facilitates the use of the generated rules is built which allows students to predict the final grade in a course under study.