Analysis and Evaluation of Factors Influencing Student Success with Explainable Artificial Intelligence Models

Özkurt, Cem

Engineering Science Letter
Vol. 3 No. 03 (2024): Engineering Science Letter

The research aims to explain socio-economic factors affecting student success using interpretable artificial intelligence models and to promote the use of this technology in the development of educational policies. Initially, existing studies on factors determining student success have been examined. The dataset includes socio-economic and personal variables such as parental education, family economic status, student gender, and study duration. Using interpretable artificial intelligence models like InterpretML, analyses have been conducted on this dataset, and the results obtained from examining factors influencing student success have been evaluated. This study aims to contribute to shaping educational policies more effectively through the use of artificial intelligence.