@article {Rima202244,
	title = {Systematic Literature Review on Open Educational Resources Recommender Systems},
	journal = {International Journal of Interactive Mobile Technologies},
	volume = {16},
	number = {18},
	year = {2022},
	note = {cited By 0},
	pages = {44-77},
	abstract = {In recent years, open educational resources (OER) gained in popularity among education and learning stakeholders. These resources are widely available on the internet, and recommender systems (RS) are commonly utilized to overcome the abundance of OER. This study aims to evaluate the advances in OER recommenders to identify the frequently used recommendation approaches, explore the technical background, highlight gaps in the existing research, and position our future research alongside the current studies. This paper comprises 413 papers published between 2005 and 2022. It is 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. We employed Google Scholar as a search engine to crawl data, and findings are presented according to the (Bernard, H. Russell.2000) process. The review constitutes a reference for researchers in this field and the future developers of OER recommender systems. It reveals an emerging interest in the area; nevertheless, studies have not yet covered hybrid interactive recommendation systems, Chabot-based, teacher and course creators oriented. Further and future research is needed {\textcopyright} 2022, International Journal of Interactive Mobile Technologies.All Rights Reserved.},
	doi = {10.3991/ijim.v16i18.32197},
	url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85140018978\&doi=10.3991\%2fijim.v16i18.32197\&partnerID=40\&md5=25930ac249e8251c64164a00f3801ad1},
	author = {Rima, S. and Meriem, H. and Najima, D. and Rachida, A.}
}
