Systematic Literature Review on Open Educational Resources Recommender Systems

Systematic Literature Review on Open Educational Resources Recommender Systems

Recommender Systems

Open Educational Resources

Systematic literature review

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

Sandoussi, Rima

Hnida, Meriem

Daoudi, Najima

Ajhoun, Rachida

International Journal of Interactive Mobile Technologies (iJIM); Vol. 16 No. 18 (2022); pp. 44-77

1865-7923

International Association of Online Engineering (IAOE), Vienna, Austria

2022-10-03

Copyright (c) 2022 rima sandoussi

https://creativecommons.org/licenses/by/4.0

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eng

info:eu-repo/semantics/article

info:eu-repo/semantics/publishedVersion

Peer-reviewed Article