Support Vector Machine and Decision Tree-Based Elective Course Suggestion System: A Case Study

Abstract

Nowadays, online education has become widespread, and the search for new techniques has begun to increase. The high number of quotas in university education in Turkey increases the number of students per instructor. It is not at the desired level for the student to receive a good education in the presence of an advisor and choose the appropriate course for his / her field due to a large number of students. In this study, a suggestion system is proposed by analyzing the previous courses taken by university students in directing the elective course. In this study, which courses would be beneficial to choose and which would be useless are presented with a web interface in which Support Vector Machine and decision trees are used. In the pilot study that the model developed conducted in the Computer Engineering department, an average of 76% success was achieved in test data sets. This success shows that the student can examine the compulsory courses and suggest elective courses suitable for his/her field and that he/she will like.