ABSTRACT
Foremost among the recommendation applications in education, however, are course recommender systems that can suggest which courses students should take and in what sequence. CourseRank was built at Stanford University to help students decide what courses to select. As well as providing personal recommendations for courses to take, this chapter presents course descriptions, grade distributions and official evaluation results and enables students anonymously to review the courses they have taken and to rank others' comments. Recommender systems are based on content-based filtering techniques, collaborative filtering or a hybrid approach, which draws from both. Degree Compass is linked to the institution's early alert system and provides data to departmental chairs and advisors, helping to target interventions at students who would benefit from additional support. Course recommender systems can be more complex than the recommendation algorithms used by platforms such as Amazon and Netflix. Future possibilities for recommender systems are discussed by Nam and colleagues.
