Exploring the Effectiveness of Self-Regulated Learning in Massive Open Online Courses on Non-Native English Speakers

2015 ◽  
Vol 13 (3) ◽  
pp. 61-73 ◽  
Author(s):  
Liang-Yi Chung

Massive Open Online Courses (MOOCs) are expanding the scope of online distance learning in the creation of a cross-country global learning environment. For learners worldwide, MOOCs offer a wealth of online learning resources. However, such a diversified environment makes the learning process complicated and challenging. To achieve their objectives, learners need to adapt regulation strategies based on different situations in the process, which is called self-regulated learning. Previous research findings emphasize that self-efficacy is one of the key factors that influences self-regulated learning. Currently MOOCs are primarily offered in English, but many students are non-native English speakers. For these learners, English serves as a cross-language and cross-cultural communication medium, and English self-efficacy is a defining element affecting this language application. To further examine the impact of English self-efficacy on self-regulated learning, this study uses non-native English learners in MOOCs as test subjects. It is evident that there is a positive and significant correlation between non-English learners' self-efficacy and self-regulated learning in MOOCs; the higher the English self-efficacy, the better use of self-regulated learning strategies. This study aims to offer some insight into self-regulated learning strategies of non-native English speakers taking MOOCs, so relevant instructors can subsequently provide more suitable and effective learning methods.

2018 ◽  
Vol 80 ◽  
pp. 179-196 ◽  
Author(s):  
Jorge Maldonado-Mahauad ◽  
Mar Pérez-Sanagustín ◽  
René F. Kizilcec ◽  
Nicolás Morales ◽  
Jorge Munoz-Gama

Author(s):  
M. Elena Alonso-Mencía ◽  
Carlos Alario-Hoyos ◽  
Iria Estévez-Ayres ◽  
Carlos Delgado Kloos

Massive open online courses (MOOCs) require registered learners to be autonomous in their learning. Nevertheless, prior research studies showed that many learners lack the necessary self-regulated learning (SRL) skills to succeed in MOOCs. This research study aimed to gain insights into the relationships that exist between SRL and background information from MOOC learners. To this end, a series of three MOOCs on computer programming offered through edX were used to collect self-reported data from learners using an adaptation of the Motivated Strategies for Learning Questionnaire. Results show significant differences in general learning strategies and motivation by continent, prior computing experience and percentage of completed MOOCs. Men reported higher motivation than women, whereas pre-university learners needed further guidance to improve their learning strategies.


2020 ◽  
Vol 146 ◽  
pp. 103771 ◽  
Author(s):  
Renée S. Jansen ◽  
Anouschka van Leeuwen ◽  
Jeroen Janssen ◽  
Rianne Conijn ◽  
Liesbeth Kester

Author(s):  
Daeyeoul Lee ◽  
Sunnie Lee Watson ◽  
William R Watson

This study examines the relationships between self-efficacy, task value, and the use of self-regulated learning strategies by massive open online course (MOOC) learners from a social cognitive perspective. A total of 184 participants who enrolled in two MOOCs completed surveys. The results of Pearson’s correlation analysis show a positive correlation between self-efficacy and the use of self-regulated learning strategies, as well as a positive correlation between task value and the use of self-regulated learning strategies. The results of hierarchical multiple regression analysis show that self-efficacy and task value are significant predictors of the use of self-regulated learning strategies. There was a statistically significant difference in the use of self-regulated learning strategies between learners who possessed high self-efficacy and those who possessed low self-efficacy. In addition, learners who had high task value showed statistically significant higher average self-regulated learning scores than those who had low task value. Implications and future research directions are discussed based on the findings.


Author(s):  
Daeyeoul Lee ◽  
Sunnie Lee Watson ◽  
William R Watson

Despite arguments about the importance of self-regulated learning (SRL) in massive open online courses (MOOCs) (Terras & Ramsay, 2015), understanding of the topic is limited. This study offers a systematic review of empirical research on SRL in MOOCs. It revealed that the body of literature on SRL in MOOCs has grown from 2014 to 2016. The content analysis findings show that SRL was a factor positively influencing learning in MOOCs. SRL strategies were identified, including motivational regulation strategies, specifically self-efficacy, task value, and goal setting. Particular cognitive regulation strategies were not identified, and goal setting was found as a metacognitive regulation strategy. Regarding behavioural and contextual regulation strategies, help seeking, time management, and effort regulation were identified. In addition, several MOOC designs and SRL interventions that consider unique characteristics of MOOCs were proposed to promote SRL. Implications of these findings and future research are discussed.


Author(s):  
Daeyeoul Lee ◽  
Sunnie Lee Watson ◽  
William R. Watson

High dropout rates have been an unsolved issue in massive open online courses (MOOCs). As perceived effectiveness predicts learner retention in MOOCs, instructional design factors that affect it have been increasingly examined. However, self-regulated learning, self-efficacy, and task value have been underestimated from the perspective of instructors even though they are important instructional design considerations for MOOCs. This study investigated the influence of self-regulated learning strategies, self-efficacy, and task value on perceived effectiveness of successful MOOC learners. Three hundred fifty-three learners who successfully completed the Mountain 101 MOOC participated in this study by completing a survey through e-mail. The results of stepwise multiple regression analysis showed that perceived effectiveness was significantly predicted by both self-regulated learning strategies and task value. In addition, the results of another stepwise multiple regression analysis showed that meta-cognitive activities after learning, environmental structuring, and time management significantly predicted perceived effectiveness.


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