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

Cem Özkurt

doi:10.56741/esl.v3i03.556

Authors

Cem Özkurt
cemozkurt@subu.edu.tr
Sakarya University of Applied Sciences https://orcid.org/0000-0002-1251-7715

Keywords:

explainable artificial intelligence, InterpretML, machine learning, data preprocessing

Abstract

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.

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Author Biography

Cem Özkurt, Sakarya University of Applied Sciences

is a dedicated researcher and lecturer affiliated with both the AI and Data Science Research and Application Center and the Department of Computer Engineering at Sakarya University of Applied Sciences in Sakarya, Turkey. He is actively involved in advancing the field of artificial intelligence and data science through both teaching and research. His work primarily focuses on the development and application of AI technologies to solve complex problems. (emai: cemozkurt@subu.edu.tr).

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