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Self-regulated learning in MOOCs: lessons learned from a literature review

, ORCID Icon, , ORCID Icon, & ORCID Icon
Pages 319-345 | Received 17 Jul 2018, Accepted 20 Dec 2018, Published online: 25 Mar 2019
 

ABSTRACT

Learners in massive open online courses (MOOCs) are required to be autonomous during their learning process, and thus they need to self-regulate their learning to achieve their goals. According to existing literature, self-regulated learning (SRL) research in MOOCs is still scarce. More studies which build on past works regarding SRL in MOOCs are required, as well as literature reviews that help to identify the main challenges and future research directions in relation to this area. In this paper, the authors present the results of a systematic literature review on SRL in MOOCs, covering all the related papers published until the end of 2017. The papers considered in this review include real experiences with at least a MOOC (other learning scenarios sometimes claimed as MOOCs, such as blended courses, or online courses with access restrictions, are out of the scope of this analysis). Most studies on SRL in MOOCs share some common features: they are generally exploratory, based on one single MOOC and tend not to specify in which SRL model they are grounded. The results reveal that high self-regulators engage in non-linear navigation and approach MOOCs as an informal learning opportunity. In general, they prefer setting specific goals based on knowledge development and control their learning through assignments.

Disclosure statement

No potential conflict of interest was reported by the authors.

Additional information

Funding

This work was supported by the CONICYT/DOCTORADO NACIONAL 2016 [Grant Number 21160081]; European Commission [Grant Numbers 561533-EPP-1-2015-1-ES-EPPKA2-CBHE-JP and 574212-EPP-1-2016-1-NL-EPPKA2-CBHE-JP]; Fondo Nacional de Desarrollo Científico y Tecnológico [Grant Number 11150231]; Madrid Regional Government [Grant Number S2013/ICE-2715]; Spanish Ministry of Economy and Competitiveness [Grant Number TIN2017-85179-C3-1-R].

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