A Literature Review on MOOCs Integrated With Learning Analytics

A Literature Review on MOOCs Integrated With Learning Analytics

Zhonggen Yu
Copyright: © 2021 |Pages: 18
DOI: 10.4018/JITR.2021040104
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Although there have been numerous studies committed to MOOCs integrated with learning analytics, fewer of them have systematically reviewed the related literature. Using clustering techniques, bibliographic network visualization, content analysis, and STARLITE method, this study systematically reviews the literature in terms of learning analytics models, platforms of MOOCs, effect of learning analytics, effect of engagement, self-regulation, motivation, and online interactions, as well as other influencing factors of the effectiveness of MOOCs integrated with learning analytics. It provides constructive suggestions for designers, researchers, learners, and instructors of MOOCs so as to lower down learner dropout rates, increase completion rates, enhance learner engagement, and better learning outcomes. Future research into MOOCs could focus on the improvements on learning analytics because learning analytics could exert an essential influence on the effectiveness of MOOCs.
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MOOCs Integrated with Learning Analytics

With swift development of information technology, the new decade has been witnessing growing interest in international massive open online courses (MOOCs), e.g. edX, Coursera, FutureLearn (Ruiperez-Valiente et al., 2020), and ahMOOC (García-Peñalvo, Fidalgo-Blanco, & Sein-Echaluce, 2018). MOOCs have aroused unprecedented interest and stimulated much public debate. General public debates on MOOCs were considered important in that they could provide deeper insight into social and learning issues, and could solve many educational problems and involve a wide range of users (Kovanović et al., 2015). MOOCs could also develop entrepreneurship competencies in energy sustainability (Beltrán Hernández de Galindo, & Ramírez-Montoya, 2019).

Recent studies have shed light on both advantages and disadvantages of MOOCs in education. MOOCs bridge the gap between courses and learners and make them have easy access to knowledge whenever and wherever they feel convenient by providing informal learning (Martínez-Núñez, Borrás-Gene, & Fidalgo-Blanco, 2016). MOOCs promoted learning convenience to a large extent, where any learner with any background could learn the courses provided via MOOC platforms free of charge. The interactive forum in MOOCs could also provide feedback for teachers and learners so that learners could be encouraged to participate in learning activities and teachers could design or modify the pedagogical approach.

The main disadvantages of MOOCs are lower completion and higher dropout rates of users than traditional courses. While various kinds of MOOCs could provide individualized services via various videos, lower engagements were still prevalent, which could not compare with traditional courses where higher engagement and completion rate could produce much more satisfactory learning outcomes (Klemke et al., 2018). Learner retention and learning outcomes were quite low although some MOOCs were instructed by distinguished professors and were of high quality (Shukor & Abdullah, 2019). Completion rates of MOOCs also appeared quite low possibly because the free delivery approach was different from the traditional fee-based courses (Pursel et al., 2016). Learning process of MOOCs could be facilitated through learning analytics (LA), which is considered a breakthrough in educational improvement (García-Peñalvo, 2020).

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