Predicting Student Performance: A Statistical and Data Mining Approach

Predicting the performance of a student is a great concern to the higher education managements. The scope of this paper is to identify the factors influencing the performance of students in final examinations and find out a suitable data mining algorithm to predict the grade of students so as to a give timely and an appropriate warning to students those who are at risk. In the present investigation, a survey cum experimental methodology was adopted to generate a database and it was constructed from a primary and a secondary source. The obtained results from hypothesis testing reveals that type of school is not influence student performance and parents’ occupation plays a major role in predicting grades. This work will help the educational institutions to identify the students who are at risk and to and provide better additional training for the weak students.