Can the Paths of Successful Students Help Other Students With Their Course Enrollments?

In this paper, we present an extended evaluation of a course recommendation system to primarily support students who struggle in the first semesters of their studies and are at risk of dropping out. The course recommendation system was developed in earlier work using a student-centered design and is based on the explainable k-Nearest Neighbor algorithm. The system recommends the set of courses that have been passed by the majority of their nearest neighbors who have completed their studies. The present evaluation is based on the data of students from three different study programs. The first result is that the recommendations do lower the dropout risk. A second result is that the set of recommended courses matches quite well the courses taken by students who completed the study program but differs from the courses taken by struggling students. Thus, though the course recommended system targets primarily struggling students, students doing well could use it. A third result is that the number of recommended courses for struggling students is less than the number of courses they actually enrolled in. We state that the recommendations given indicate a different and hopefully feasible path through the study program for students at risk of dropping out.