Predicting academic performance of students
Academic performance of students in schools and colleges is an important factor in determining their overall success and sustainability. Traditionally, schools and colleges have measured this after the fact i.e. after students go through tests, exams, etc and are assigned grades based on their performance. With data mining tools, schools and colleges could predict academic performance of students before the fact. By mining data about historical performance of students, their demographics, etc educational institutions could create predictive models to determine whether a specific student (with a unique profile) is likely to pass or fail an exam. Universities offering admissions to prospective students could determine before hand whether a student will likely succeed or not in the program that they propose to enroll in. This could be used by Admissions Committees to improve the quality of students that they offer admissions to and therefore improve the standi...