A review on Recommender Systems for Course Selection in Higher Education
Ninyikiriza Deborah Lynn ,Andi wahju Rahardjo Emanuel

Universitas Atma Jaya Yogyakarta
Universitas Atma Jaya Yogyakarta

Abstract

Recommender systems are widely used in several fields. These systems work by recommending a personalized list of items to users based on their interests and thus helping users to overcome excessive information offered to them. Choosing the right courses is a very challenging task for students while joining a new academic level. It is very essential for students to choose courses or majors of their ability. Choosing the wrong course may affect a student’s whole career life. Although universities have tried to use several methods to help students to choose right majors, such as providing counselors to help students on decision making, the system is not that much efficient because a lot of time is wasted in meeting the counselors and still, the students end up making wrong choices. This is primarily due to the myriad courses available in different faculties of universities every year. The fact that some of these courses are almost the same, new students tend to be confused. The existing researches about recommendation in the education field are limited to recommending articles, research papers, and books to students and research scholars. This paper aims at exploring the use of recommender systems to assist students in selecting courses that correspond to their abilities and interests. The results from this review showed that Hybrid recommendation approach/system can be the best method to help students to choose the right courses in preparation for their future careers.

Keywords: Recommender Systems, Students, Course Selection, Higher Education.

Topic: Computer Science