Bachelor'S Degree Student Dropouts: Who Tend To Stay And Who Tend To Leave?

Factors of students' dropout can be studied either by surveys among students or by analyzing data the university collects. In the work reported in this paper, we analyzed data known about students at the time of admission as well as data about the students' study achievements collected on a semester basis. Using data about students who enrolled in the academic year 2013/14, we created several data mining models to predict who will finish their studies successfully and who will not. Our results show that the key factor is the percentage of lost credit vouchers in the most recent semester. The pre-entry attributes have only a very small impact. We also created association rules of different types to find characteristics of students who did not successfully complete the first semester of study. Here, the factor that mainly increases the probability of a failure is the time gap between secondary and tertiary education.