Recommender Systems for MOOCs: A Systematic Literature Survey (January 1, 2012 – July 12, 2019)

In recent years, massive open online courses (MOOCs) have gained popularity with learners and providers, and thus MOOC providers have started to further enhance the use of MOOCs through recommender systems. This paper is a systematic literature review on the use of recommender systems for MOOCs, ex...

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Autores principales:	Asra Khalid, Karsten Lundqvist, Anne Yates
Formato:	article
Lenguaje:	EN
Publicado:	Athabasca University Press 2020
Materias:	recommender system massive open online course MOOC systematic review implemented recommender system Special aspects of education LC8-6691
Acceso en línea:	https://doaj.org/article/36bcf1b547824dd3b13f407b21395106
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spelling	oai:doaj.org-article:36bcf1b547824dd3b13f407b213951062021-12-02T18:02:58ZRecommender Systems for MOOCs: A Systematic Literature Survey (January 1, 2012 – July 12, 2019)10.19173/irrodl.v21i4.46431492-3831https://doaj.org/article/36bcf1b547824dd3b13f407b213951062020-06-01T00:00:00Zhttp://www.irrodl.org/index.php/irrodl/article/view/4643https://doaj.org/toc/1492-3831 In recent years, massive open online courses (MOOCs) have gained popularity with learners and providers, and thus MOOC providers have started to further enhance the use of MOOCs through recommender systems. This paper is a systematic literature review on the use of recommender systems for MOOCs, examining works published between January 1, 2012 and July 12, 2019 and, to the best of our knowledge, it is the first of its kind. We used Google Scholar, five academic databases (IEEE, ACM, Springer, ScienceDirect, and ERIC) and a reference chaining technique for this research. Through quantitative analysis, we identified the types and trends of research carried out in this field. The research falls into three major categories: (a) the need for recommender systems, (b) proposed recommender systems, and (c) implemented recommender systems. From the literature, we found that research has been conducted in seven areas of MOOCs: courses, threads, peers, learning elements, MOOC provider/teacher recommender, student performance recommender, and others. To date, the research has mostly focused on the implementation of recommender systems, particularly course recommender systems. Areas for future research and implementation include design of practical and scalable online recommender systems, design of a recommender system for MOOC provider and teacher, and usefulness of recommender systems. Asra KhalidKarsten LundqvistAnne YatesAthabasca University Pressarticlerecommender systemmassive open online courseMOOCsystematic reviewimplemented recommender systemSpecial aspects of educationLC8-6691ENInternational Review of Research in Open and Distributed Learning, Vol 21, Iss 4 (2020)
institution	DOAJ
collection	DOAJ
language	EN
topic	recommender system massive open online course MOOC systematic review implemented recommender system Special aspects of education LC8-6691
spellingShingle	recommender system massive open online course MOOC systematic review implemented recommender system Special aspects of education LC8-6691 Asra Khalid Karsten Lundqvist Anne Yates Recommender Systems for MOOCs: A Systematic Literature Survey (January 1, 2012 – July 12, 2019)
description	In recent years, massive open online courses (MOOCs) have gained popularity with learners and providers, and thus MOOC providers have started to further enhance the use of MOOCs through recommender systems. This paper is a systematic literature review on the use of recommender systems for MOOCs, examining works published between January 1, 2012 and July 12, 2019 and, to the best of our knowledge, it is the first of its kind. We used Google Scholar, five academic databases (IEEE, ACM, Springer, ScienceDirect, and ERIC) and a reference chaining technique for this research. Through quantitative analysis, we identified the types and trends of research carried out in this field. The research falls into three major categories: (a) the need for recommender systems, (b) proposed recommender systems, and (c) implemented recommender systems. From the literature, we found that research has been conducted in seven areas of MOOCs: courses, threads, peers, learning elements, MOOC provider/teacher recommender, student performance recommender, and others. To date, the research has mostly focused on the implementation of recommender systems, particularly course recommender systems. Areas for future research and implementation include design of practical and scalable online recommender systems, design of a recommender system for MOOC provider and teacher, and usefulness of recommender systems.
format	article
author	Asra Khalid Karsten Lundqvist Anne Yates
author_facet	Asra Khalid Karsten Lundqvist Anne Yates
author_sort	Asra Khalid
title	Recommender Systems for MOOCs: A Systematic Literature Survey (January 1, 2012 – July 12, 2019)
title_short	Recommender Systems for MOOCs: A Systematic Literature Survey (January 1, 2012 – July 12, 2019)
title_full	Recommender Systems for MOOCs: A Systematic Literature Survey (January 1, 2012 – July 12, 2019)
title_fullStr	Recommender Systems for MOOCs: A Systematic Literature Survey (January 1, 2012 – July 12, 2019)
title_full_unstemmed	Recommender Systems for MOOCs: A Systematic Literature Survey (January 1, 2012 – July 12, 2019)
title_sort	recommender systems for moocs: a systematic literature survey (january 1, 2012 – july 12, 2019)
publisher	Athabasca University Press
publishDate	2020
url	https://doaj.org/article/36bcf1b547824dd3b13f407b21395106
work_keys_str_mv	AT asrakhalid recommendersystemsformoocsasystematicliteraturesurveyjanuary12012july122019 AT karstenlundqvist recommendersystemsformoocsasystematicliteraturesurveyjanuary12012july122019 AT anneyates recommendersystemsformoocsasystematicliteraturesurveyjanuary12012july122019
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Recommender Systems for MOOCs: A Systematic Literature Survey (January 1, 2012 – July 12, 2019)

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