LMOOC research 2014 to 2021: What have we done and where are we going next?

IF 4.6 1区 文学 Q1 EDUCATION & EDUCATIONAL RESEARCH Recall Pub Date : 2023-01-04 DOI:10.1017/S0958344022000246
Yining Zhang, Ruoxi Sun
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Abstract

Abstract This 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.
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2014年至2021年LMOOC研究:我们做了什么,下一步要去哪里?
摘要本研究回顾了从语言开放在线课程成立到2021年发表的71项关于语言开放在线在线课程的高质量研究。本研究的目的是更深入地了解研究现状,并为未来LMOOC研究确定富有成效的方向。首先,我们回顾了这些研究的三组基本特征:(1)研究趋势——例如,发表类型和年份;(2) 研究背景——例如,进行研究的国家、受试者的目标语言、语言能力水平、技能,以及重点课程是否有特定目的;以及(3)研究设计,包括数据收集、数据分析和理论框架。然后,我们使用了一种称为潜在狄利克雷分配的文本挖掘方法,该方法使用机器学习技术来识别所收集研究的研究主题共性。通过这种方式,总共确定了九个主题。它们是:(1)LMOOCs的核心要素;(2) LMOOC中的互动和交流;(3) 创新LMOOC教学实践;(4) LMOOC标准和质量保证;(5) LMOOC的实施、参与和完成;(6) LMOOC教学计划;(7) LMOOC学习有效性及其驱动因素/障碍;(8) 学习者和LMOOC学习;以及(9)LMOOC的包容性。然后将其绘制为主题河流,显示了九个已确定主题的进化趋势。具体而言,对主题5、7和9的学术兴趣随着时间的推移而增加,而对主题1和6的兴趣则有所下降。根据我们的研究结果,我们强调了未来LMOOC研究的具体方向。
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来源期刊
Recall
Recall Multiple-
CiteScore
8.50
自引率
4.40%
发文量
17
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