Review on Predicting Student Academic Performance using Data Mining Classification Algorithm
Wasyihun Sema Admass
Faculty of informatics and Department of information technology, University of Gondar, Ethiopia
: J Comput Eng Inf Technol
Abstract
This paper has reviewed previous studies on predicting students’ performance with various analytical methods. Most of the researchers have used cumulative grade point average (CGPA) and internal assessment as data sets. While for prediction techniques, the classification method is frequently used in educational data mining area. Under the classification techniques, Neural Network and Decision Tree are the two methods highly used by the researchers for predicting students’ performance. In conclusion, the meta-analysis on predicting students’ performance has motivated us to carry out further research to be applied in our environment. It will help the educational system to monitor the students’ performance in a systematic way.
Biography
Wasyihun Sema Admass is working as a Faculty of informatics and Department of information technology in the University of Gondar, Ethiopia
