A classification and prediction model for student's performance in university level

Abstract

Educational Data Mining is a new discipline, focusing on studying the methods and creating models to utilize educational data, using those methods to better understand students and their performance. We implemented two different techniques on our dataset; classification used to build a prediction model and association rules were used to find interesting hidden information in the student's records. This study will help the student's to determine their direction and improve when necessary to cope up with their studies. It also provide a great tool to predict and evaluate those students who need attention and correction actions and find out any deviation before it happen and become a decrease in performance and reduce failure rate.