rdemiriokbsysa.xlsx

The aim of this study is to reveal in detail the extent to which the variables in The Primary and Secondary Education Institutions Scholarship Examination (İlköğretim ve Ortaöğretim Kurumları Bursluluk Sınavı-IOKBS), predict the scholarship exam success of students with the help of artificial neural networks (ANN). In addition, in the light of the findings obtained as a result of the research, it is aimed to contribute to the improvement of the quality and content of IOKBS and to the revision of the variables in student selection. Descriptive-relational screening model and purposive sampling method were used in the study. The study group of the research included students who were studying in a provincial centre in the Aegean Region of Turkey in the 2023-2024 academic year and who took the IOKBS at the 5th grade level. In the study, the prediction level of these students' 4th and 5th grade written exam scores (independent variable) of Turkish, Mathematics, Science, Social Sciences, Religious Culture and Ethics courses (independent variable) and their IOKBS achievement status (dependent variable) were determined through MATLAB 2023a program classification interface and optimised to achieve the best result.