Evaluation of the Academic Achievement of Vocational School of Higher Education Students Through Artificial Neural Networks

Abstract

This study aimed to determine the importance levels of mathematics lecture achievement, Turkish lecture achievement, Higher Education Admission Exam score, academic self-efficacy, attitude towards vocational education, academic motivation and mother and father education on the academic achievement of vocational schools of higher education students using the artificial neural network method. The data was obtained through 468 students from vocational schools of higher education at two different universities in Turkey. According to the quantitative research methodology, the correlational research design was used. The artificial neural network analysis results revealed that mathematics lecture achievement, Turkish lecture achievement and academic self-efficacy were the most critical variables that predicted the academic achievement of vocational schools of higher education students. These variables were followed by mother education level, father education level, attitude towards vocational education, Higher Education Admission Exam score and academic motivation. The results suggest that the effectiveness of the Higher Education Admission Exam score, which contributes very little to predict the academic achievement of vocational education students, need to be more questioned.