Systematic Literature Review on Open Educational Resources Recommender Systems - Sandoussi, Rima; Hnida, Meriem; Daoudi, Najima; Ajhoun, Rachida (International Journal of Interactive Mobile Technologies (iJIM), 2022)
background: In recent years, recommender systems (RS) have grown in popularity among learning and education stakeholders, while open educational resources (OER) have begun to be deployed to improve the education field. The selection of OERs should not be haphazard; rather, it should be based on the learning objectives and (RS) commonly utilized to overcome the abundance of OER. Objective: The aim of this paper is to examine the current advances in OER recommenders and the different commonly used recommendation approaches and technical features, to position our future research alongside the existing. Method: A systematic literature review with a deductive approach using the grounded theory technique, combining quantitative and qualitative analysis by adopting open coding (inductive and deductive) for content analysis. Databases: we employed Google Scholar as a search engine to crawl data. Results: The findings are presented according to the (Bernard, H. Russell .2000) process. We present the results of the analysis using quotes from interviews that illuminate the theory (exemplars). Conclusion: The review reveals an emerging interest in the area; nevertheless, hybrid interactive systems; chatbot-based, dedicated to course creators are lacking. Further and future research is needed