Abstract—Educational data mining is the process of applying
data mining tools and techniques to analyze data at educational
institutions. In this paper, we used educational data mining to
predict students' final GPA based on their grades in previous
courses. In our case study, we collected students' transcript data
that included their final GPA and their grades in all courses.
After pre-processing the data, we applied the J48 decision tree
algorithm to discover classification rules. We extracted useful
knowledge for final GPA, and identify the most important
courses in the students' study plan based on their grades in the
mandatory courses.
Index Terms—Educational data mining, classification,
decision tree, analysis.
The authors are with King Saud University, Saudi Arabia (e-mail:
mbarrak@ksu.edu.sa).
Cite: Mashael A. Al-Barrak and Muna Al-Razgan, "Predicting Students Final GPA Using Decision Trees: A Case Study," International Journal of Information and Education Technology vol. 6, no. 7, pp. 528-533, 2016.