Supporting Self-Regulated Learning in Online Learning Environments and MOOCs: A Systematic Review

Abstract

Massive Open Online Courses (MOOCs) allow learning to take place anytime and anywhere with little external monitoring by teachers. Characteristically, highly diverse groups of learners enrolled in MOOCs are required to make decisions related to their own learning activities to achieve academic success. Therefore, it is considered important to support self-regulated learning (SRL) strategies and adapt to relevant human factors (e.g., gender, cognitive abilities, prior knowledge). SRL supports have been widely investigated in traditional classroom settings, but little is known about how SRL can be supported in MOOCs. Very few experimental studies have been conducted in MOOCs at present. To fill this gap, this paper presents a systematic review of studies on approaches to support SRL in multiple types of online learning environments and how they address human factors. The 35 studies reviewed show that human factors play an important role in the efficacy of SRL supports. Future studies can use learning analytics to understand learners at a fine-grained level to provide support that best fits individual learners. The objective of the paper is twofold: (a) to inform researchers, designers and teachers about the state of the art of SRL support in online learning environments and MOOCs; (b) to provide suggestions for adaptive self-regulated learning support.

The Effects Of Mobile Computer Supported Collaborative Learning to Improve Problem Solving and Achievements

“…Based on the problem of the study and the results of this study can be concluded as follows: (1) The learning strategy of mobile Computer-Supported Collaborative Learning provides better learning achievement than the mobile Computer Supported Individual Learning (Stahl, Koschmann, & Suthers, 2014;Mason & Watts, 2011;Kolloffel et al, 2011;Chen & Law, 2016;Chen & Law, 2016). 2Students with high Self Regulated Learning have better learning achievement than students with low Self Regulated Learning (Sha et al, 2012;Järvelä & Hadwin, 2013;Shi et al, 2013;Wong et al, 2019;Kramarski & Gutman, 2006;Littlejohn et al, 2016). (3) The mobile Computer-Supported Collaborative Learning and mobile Computer-Supported Individual Learning strategies provide equally good learning achievements for students who have high or low Self Regulated Learning.…”

Proposed Self-Regulation Model for Collaborative E-Learning Systems in Kenyan Public Universities

“…Recent studies show that although over 90% of students enroll into elearning courses, only about 35% of them successfully graduate (Maina et al, 2017;Kashorda and Waema, 2014;Makokha and Mutisya, 2016). E-learning students drop out for a variety of reasons; (i) lack of online support as a result of the learner studying in isolation, (ii) poor course interactivity, (iii) lack of motivation from instructors and peers and (iv) poor internet connectivity (Wong et al, 2019;Oboko, 2012;Tarus et al, 2015).…”

“…In contrast, Higher e-learning institutions in sub-Saharan Africa have experienced high drop-out rates due to factors such as (i) Lack of direct interaction between instructors and learners, (ii) the difficulty for instructors to monitor student progress (Lodge et al, 2018), hence e-learners may experience a sense of isolation, (iii) lack of ability to self-regulate (Lee and Choi, 2011), which may in part be due to students not recognizing the effort and organization required to succeed in e-learning courses and (iv) limited self-regulatory skills (Cho and Shen, 2013). Instructors need to carefully consider and purposefully plan and facilitate student learning in support of the development of self-regulation in an e-learning environment (Greene et al, 2011;Wong et al, 2019). In Kenya, e-Learning students have cited lack of support from instructors and peers (Maina et al, 2017), hence need to strengthen their own ability and skills in self-regulation.…”

Learners Self-directing Learning in FutureLearn MOOCs: A Learner-Centered Study

“…As Terras and Ramsay [9] pointed out, researchers also need to understand learners' expectations and how they cope with the specific challenges that are associated with MOOCs. Wong et al [3] emphasized that highly diverse groups of learners enrolled in MOOCs are required to make decisions related to their own learning activities to achieve academic success. Wong et al [3] saw that many studies find positive self-regulated learning and learning outcomes among undergraduates, but there is no evidence or indication that such findings would transfer to a different population or setting.…”

“…Wong et al [3] emphasized that highly diverse groups of learners enrolled in MOOCs are required to make decisions related to their own learning activities to achieve academic success. Wong et al [3] saw that many studies find positive self-regulated learning and learning outcomes among undergraduates, but there is no evidence or indication that such findings would transfer to a different population or setting. Guo and Renicke [10] investigated how learners navigate through MOOCs and they found that most learners engage in non-linear learning trajectories that do not follow a pre-established, sequential progression.…”