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September 29, 2025 - GTU Office of Press and Public Relations Researchers at the Faculty of Business Administration, Gebze Technical University (GTU), develop a powerful system capable of predicting students’ academic performance in advance using artificial intelligence. The study is published in the journal "Information Development", bringing it to the attention of the international scientific community.
One of the most important goals at universities is ensuring that students successfully complete their education. However, some students may struggle in courses or face the risk of failure.
Assoc. Prof. Yavuz Selim Balcıoğlu and Melike Artar (PhD) from GTU’s Departments of Management Information Systems and Management, Faculty of Business Administration, have developed a model using machine learning and deep learning algorithms to predict students’ academic performance and address this challenge.
The study utilized the Open University Learning Analytics (OULA) dataset, representing a large-scale educational data pool with international validity. Students were categorized into three groups: Successful, At Risk of Failure, and Near Success.
The methods tested on this dataset included Decision Trees, Support Vector Machines, Artificial Neural Networks, and an Ensemble Model (combined method).
The results showed that the Ensemble Model achieved the highest accuracy rate, outperforming all other methods.
Why the Study Matters Early warning system: Students at risk may be identified at the beginning of the academic year. Targeted support: Universities could provide counseling, supplementary courses, or learning assistance to students at risk of failure. Personalized learning: Predictions enable the design of tailored educational strategies and learning pathways for each student.
These findings demonstrate that AI-based systems not only enhance student success but also strongly contribute to universities’ goals of academic quality and excellence.
Authors: Assoc. Prof. Yavuz Selim Balcıoğlu, Research Assistant Melike Artar, PhD (2025), GTU Faculty of Business Administration 👉DOI: 10.1177/02666669231213023 |
