A Review of literature on Recommender Models for career pathway selection in Competency-Based Education

Abstract

In Competency-based Education (CBE), learners acquire skills and knowledge through a personalized and flexible learning path, based on their prior knowledge and skills. To support learners in selecting career pathways that match their interests and competencies, recommender models are widely used. Recommender models (RM) analyze learners' competencies, interests and goals to suggest career pathways suited for them. This paper reviews literature by analyzing recommender models used for career pathway selection in CBE through desk study. First, it explains the concepts of CBE. Secondly, it discusses the types of recommender models used for career pathway selection in CBE. Lastly, it discusses various recommender models developed for career pathway selection highlighting their strengths and weaknesses. Findings from the review reveals that hybrid recommender model is popularly employed for career pathway selection compared to content-based, knowledge-based, and collaborative filtering recommender models as it gives a higher level of accuracy in the recommendation. Overall, this review paper contributes to the growing body of literature on recommender models for career pathway selection in CBE. In addition, it provides valuable insights for practitioners, researchers and emphasizes the need for future research to address the challenges associated with recommender models for career pathway selection in CBE.