A Collaborative Filtering Based Approach for Recommending Elective Courses
This addresses course choice difficulties for students in management education, but it is incremental as it applies an existing method to a new domain.
The paper tackles the problem of elective course selection for management students by extending collaborative filtering to predict grades, showing the system is effective in terms of accuracy.
In management education programmes today, students face a difficult time in choosing electives as the number of electives available are many. As the range and diversity of different elective courses available for selection have increased, course recommendation systems that help students in making choices about courses have become more relevant. In this paper we extend the concept of collaborative filtering approach to develop a course recommendation system. The proposed approach provides student an accurate prediction of the grade they may get if they choose a particular course, which will be helpful when they decide on selecting elective courses, as grade is an important parameter for a student while deciding on an elective course. We experimentally evaluate the collaborative filtering approach on a real life data set and show that the proposed system is effective in terms of accuracy.