A Review of Recommender Systems Based on Video Learning Resources in Online Education

Compared to texts, videos can better stimulate learners’ learning motivation and keep their attention. Recommender systems based on video learning resources can aid learners in discovering relevant resources by considering the video’s attributes and learners’ preferences. This study follows PRISMA to conduct a literature review of the recommender system based on video learning resources in online education, and retains 27 articles. The analysis concentrated on the primary recommendation methods, data types utilized, evaluation metrics, application effects, and the influence of these systems on learners’ educational experiences. The findings indicate that the design and implementation of video learning resource-based recommender systems are advanced, yielding highly precise recommendations. However, the potential of the video learning resource recommender system to significantly enhance learners’ educational outcomes and its precise operational mechanisms warrant further investigation. Future research are suggested in the end of this study.