Analysis of students' performance evaluation using classification techniques

Educational Data Mining is one of the emerging disciplines which includes the process of analyzing the students' details using different attributes. The attributes such as students' name, roll number, previous semester marks, attendance, assignment, seminar performance, lab work and gender are used to evaluate the students' performance (Pass / Reappear). In this paper, classification techniques are described and used for educational data mining. The classification process is based on C5.0 algorithm with good classification accuracy. The system is helpful to the learners as well as to the teachers for the academic performance evaluation. It is a warning system for the students' to improve their study performance.