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. IntroductionA massive open online course (MOOC) generally refers to "a model for delivering learning content online to virtually any person-with no limit on attendance-who wants to take the course" (Educause Learning Initiative, 2011, ¶ 4). MOOCs have changed traditional online learning by putting hundreds of thousands of learners from different geographical locations into an online space where they study at their preferred pace and according to their own learning style (Johnson, Becker, Estrada, & Freeman, 2014). Traditional online courses and MOOCs are distinguished by the fact that MOOCs are open to all applicants with freely accessible information and resources and do not typically require registration fees except for those learners seeking more formal certifications (Schulze, 2014). There is also a difference in goals and structures between regular online courses and MOOCs (Perna et al., 2014).In MOOCs, "learners are expected to be autonomous and manage their own learning by making their own social and conceptual connections to suit their own needs" (Tschofen & Mackness, 2012, p. 126). Glance, Forsey, and Riley (2013) and Barnes (2013) explained that most MOOCs usually include short lecture videos with embedded questions, auto-graded quizzes, peer reviewing or assessment, and online discussion forums. As MOOCs place "control of learning at the discretion of the learner" (Terras & Ramsay, 2015, p. 1), it is essential to understand the learner behaviours required for autonomous learning in MOOCs (Terras & Ramsay, 2015). While little has been discovered about learner behaviours in MOOCs, self-regulated learning (SRL) has recently gotten attention as a crucial factor related to learner behaviours in MOOCs (deWaard, 2011;Terras & Ramsay, 2015). SRL has been identified as one of the vital factors positively affecting students' success in traditional online learning environments (Cho & Shen, 2013;Dabbagh & Kitsantas, 2005). In addition, how to support online learners' SRL has been widely examined (e...

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.

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Qualitative research is inherently critical, interpretive, and multimethod in function, and Denzin and Lincoln (2005) argue that the current status of qualitative research sees the social sciences as a place for critical conversation. This highlights the task at hand for qualitative educational researchers, and their responsibility in bringing a critical view to methodology, promoting social justice, and engaging with systems of education by seeking to identify and address the problems within them. While the problems in education are complex, the application of systems thinking for identifying and solving complex problems has largely been absent. Critical Systems Theory (CST) brings a systemsthinking lens to help educational researchers understand the complex nature of educational systems and problems, while incorporating critical perspectives in both methodology and broader research objectives such as emancipation and social justice. CST is derived from both systems theory and critical social theory. In the mid-twentieth century, systems theory was established by a multidisciplinary group of researchers who believed that studies of science had become increasingly reductionist and the various disciplines isolated. The term system has been defined in various ways, but the core concept is one of relations between components, which together comprise a whole. Among the first to establish systems theory, Bertalanffy (1968) noted the existence of principles and laws that could be generalized across systems and their components regardless of the type of system or its relations to other systems. Ultimately, systems thinking entails identifying the

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