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.

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Research on expository text has shown that the accuracy of students' judgments of learning (JOLs) can be improved by instructional interventions that allow students to test their knowledge of the text. The present study extends this research, investigating whether allowing students to test the knowledge they acquired from studying a worked example by means of solving an identical problem, either immediately or delayed, would enhance JOL accuracy. Fifth grade children (i) gave an immediate JOL, (ii) a delayed JOL, (iii) solved a problem immediately and then gave a JOL, (iv) solved a problem immediately and gave a delayed JOL, or (v) solved a problem at a delay and then gave a JOL. Results show that problem solving after example study improved children's JOL accuracy (i.e., overestimation decreased). However, no differences in the accuracy of restudy indications were found. Results are discussed in relation to cue utilization when making JOLs.

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