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General Information
    • ISSN: 2010-3689 (online)
    • Abbreviated Title: Int. J. Inf. Educ. Technol.
    • Frequency: Monthly
    • DOI: 10.18178/IJIET
    • Editor-in-Chief: Prof. Dr. Steve Thatcher
    • Executive Editor: Ms. Nancy Y. Liu
    • Abstracting/ Indexing: Scopus (Since 2019), EI(INSPEC, IET), EBSCO, Electronic Journals Library, Google Scholar, Crossref, etc.
    • E-mail: ijiet@ejournal.net
Prof. Dr. Steve Thatcher
QUniversity, Australia
It is my honor to be the editor-in-chief of IJIET. The journal publishes good-quality papers which focous on the advanced researches in the field of information and education technology. Hopefully, IJIET will become a recognized journal among the scholars in the related fields.

IJIET 2016 Vol.6(7): 528-533 ISSN: 2010-3689
DOI: 10.7763/IJIET.2016.V6.745

Predicting Students Final GPA Using Decision Trees: A Case Study

Mashael A. Al-Barrak and Muna Al-Razgan
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.

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E-mail: ijiet@ejournal.net