CLASSIFYING THE STUDENTS AT RISK THROUGH THE PERFORMANCE REFLECTED IN PRE-REQUISITE AND NATURE OF MODULE IN HIGHER EDUCATIONAL SYSTEM

Educational institutions are growing diametrically to stand internationally in providing honorable merit employable graduates. Future prediction should be essential factor in an institute to take additional effort in fallout spaces. The existing student’s performance data and the present nature of the module from the institutions are used to analysis and predict the earlier performance for a module. Data mining techniques like feature selection, clustering and predicting methods are been used in evaluating future prediction. The prediction are categories the features in three groups like conquer group, modest group and letdown group. Based on this groups, the institutions can have an appropriate indication on the upcoming results and to help the students in right time. Institutions can focus on the modest and letdown groups more than the conquer group students who are at risk.