Abstract
AbstractThis study reviews 71 high-quality studies of massive open online courses focused on languages (LMOOCs) that were published from the inception of LMOOCs to 2021. The purpose of this study is to gain a deeper understanding of the current state of research and identify fruitful directions for future LMOOC research. First, we reviewed three basic sets of characteristics of these studies: (1) research trends – for example, publication types and years; (2) research contexts – for example, countries in which the studies were conducted, the subjects’ target languages, language-ability levels, skills, and whether the focal courses are for specific purposes; and (3) research design, including data collection, data analysis, and theoretical frameworks. We then utilized a text-mining approach called Latent Dirichlet Allocation that uses machine-learning techniques to identify research-topic commonalities underlying the collected studies. In this way, a total of nine topics were identified. They were: (1) core elements of LMOOCs; (2) interaction and communication in LMOOCs; (3) innovative LMOOC teaching practices; (4) LMOOC standards and quality assurance; (5) LMOOC implementation, participation, and completion; (6) LMOOC teaching plans; (7) LMOOC learning effectiveness and its drivers/obstacles; (8) learners and learning in LMOOCs; and (9) inclusiveness in LMOOCs. These were then diagrammed as a ThemeRiver, which showed the evolutionary trend of the nine identified topics. Specifically, scholarly interest in Topics 5, 7, and 9 increased over time, whereas for Topics 1 and 6, it decreased. Based on our results, we highlighted specific directions for future LMOOC research on each of the identified research topics.
Publisher
Cambridge University Press (CUP)
Subject
Computer Science Applications,Linguistics and Language,Language and Linguistics,Education
Cited by
3 articles.
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