With the rising popularity of Computer Science programs and prospects offered by these programs, enrollments are rising. Numerous universities are seeing a significant rise in enrollments, especially in computing programs leading to large classrooms. These large classrooms create pedagogical challenges for the instructors. The size of the classroom restricts the variations and possibilities of instruction design. This especially limits the possibilities of active classroom style and participation activities which have shown vast potential for learning in classroom.
Recommender systems (RS) are an efficient tool to reduce information overload when one has an overwhelming choice of resources. Recommender systems (RS) have applications in various areas, including education, where they can help learners by suggesting learning resources, peers to collaborate with, and more. When RS is used in a learning context, it adds to the issue of lack of trust in the information, source, and intention as one builds knowledge through it. A recommender system can especially be employed in classroom courses to recommend materials there is a variety of resources available for the students to read from.