A Classification and Prediction Model for Student's Performance in University Level
Ashraf Abazeed and Moaiad Khder
DOI : 10.3844/jcssp.2017.228.233
Journal of Computer Science
Volume 13, Issue 7
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.
© 2017 Ashraf Abazeed and Moaiad Khder. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.