ESTIMATION OF THE FACTORS AFFECTING THE SUCCESS OF THE UNIVERSITY STUDENTS BY LOGISTIC REGRESSION ANALYSIS

Data mining applications, which provide confidential and useful information from large data stacks, are used to expose important information useful in many fields such as business, finance, medicine, education. In the field of education, hidden useful information that can be obtained from large data piles is also; Increase the quality of education and training, and provide important contributions to the solution of various education and training problems. In this study, data mining techniques using logistic regression analysis and end-of-term course evaluation questionnaires were used to investigate the factors affecting student's course success. Two separate course success variables were defined through questionnaires applied to 5820 university students. The relationship between the answers to the likert scale questions affecting course success variables and the course success was estimated by logistic regression analysis. According to the results of the analysis, it is seen that the student lecture success is more influenced by the number of lesson repetition, as well as the applications which increase the professional development of the students and give new perspective to the students. It was also found that the views of the students who took the course for the first time were generally more positive than those of two or more repeat students. In addition to this, we have reached the opinion that by changing the way the questionnaire is applied, the student will be able to make a more objective assessment of the final derste before the final exam, which will increase both the success of the course and the success of the faculty member