PROFESSOR - OGUNDE, ADEWALE OPEOLUWA (Journal of Computer Science and Information Technology, 2014)
The desire of every organization is to extract hidden but useful knowledge from their data through data mining tools. Also, the recent decline in the standard of education in most developing countries has necessitated researches that will help proffer solutions to some of the problems. From the literature, different analysis has been carried out on university data, which includes student’s university entrance examination and Ordinary level results but the relationship between these entry results and students’ final graduation grades has been in isolation. Therefore, in this work, a new system that will predict students’ graduation grades based on entry results data using the Iterative Dichotomiser 3 (ID3) decision tree algorithm was developed. ID3 decision tree algorithm was used to train the data of the graduated sets. The knowledge represented by decision trees were extracted and presented in form of IF-THEN rules. The trained data were then used to develop a model for making future prediction of students’ graduation grades. The developed system could be very useful in predicting students’ final graduation grades even from the point of entry into the university. This will help management staff, academic planners to properly counsel students in order to improve their overall performance. Keywords: Data mining, Decision trees, Prediction, ID3 algorithm, Knowledge extraction