Video-Based Learning Recommender Systems: A Systematic Literature Review
Houssam El Aouifi, Mohamed El Hajji, Youssef Es-Saady, Hassan Douzi
Abstract
Recently, using videos as a learning resource has received a lot of attention and turned widely exploited as an effective learning tool. With the rapid spread of instructional videos, the number of these tools in all disciplines is becoming very high. It is fractious for learners to find video courses adapted to their needs. Recommender system is an important tool; it can help learners for better navigation and better guidance to access and reach information and interesting videos content and restrict the number of choices provided. This article presents results of a systematic literature review on video-based learning recommender systems. This systematic literature review included the papers indexed in five scientific digital libraries and published between 2009 and 2023. Our review focuses on examining both the technical and pedagogical aspects of video-based learning recommender systems. In terms of technical aspects, we analyze the most commonly used recommendation approaches in video-based learning, as well as additional methods and techniques employed to enhance the effectiveness of video-based learning recommendations. We also explore the variables and data sources that have been investigated in the process of recommending videos for learning purposes, along with the evaluation metrics used to assess the performance of these systems. Regarding the pedagogical aspects, we investigate the learning environments where these systems have been implemented, the subjects and educational programs that hold primary importance in video-based learning recommendations, and the overall learning process.