Üniversite Yerleşme Başarısını Etkileyen Faktörlerin Yapay Zekâ Yöntemleriyle Araştırılması.

Doğan, Ayhan; Ünal, Cihan

There are several factors affecting students' success. This study investigates the factors that affect university placement success. A forty-question questionnaire, prepared with the opinions of experts, was applied to university students from various fields. The data obtained from the questionnaire was analyzed using artificial intelligence methods to predict the most important factors affecting success. The study evaluated the success of the prediction models with performance measurement metrics using four different machine learning methods. It is important to note that the most successful method varied depending on the performance metrics used for evaluation. The Random Forest method had the best results with 4.95 MSE and 2.22 RMSE values, followed by the Extreme Gradient Boosting method with a 1.60 MAE value and the Linear Regression method with a 0.36 MAPE value. Based on all metrics, the success rate of the Support Vector Machines method was relatively lower than that of other methods. The study suggests that by considering the factors affecting university placement success in order of importance, it can be possible to increase the students' success. Therefore, educators, families, counselors, and students can make improvements, conduct studies in the relevant areas, and take necessary measures to account for this order of importance.

SUPPORT vector machines; ARTIFICIAL intelligence; RANDOM forest algorithms; MACHINE learning; ACADEMIC achievement

Journal of Turkish Educational Sciences, 2024, Vol 22, Issue 3, p1678

1303-8451

Academic Journal

10.37217/tebd.1438947