Although massive open online courses (MOOCs) increase the number of choices in higher education and enhance learning, their low completion rate remains problematic. Previous studies have shown that learning engagement is a crucial factor influencing learning success and learner retention. However, few literature reviews on learning engagement in MOOCs have been conducted, and specific data analysis methods are lacking. Moreover, the internal and external factors that affect learning engagement have not been fully elucidated. Therefore, this systematic literature review summarized articles pertaining to learning engagement in MOOCs published from 2015 to 2022. Thirty articles met the inclusion and quality assurance criteria. We found that (1) learning engagement can be measured through analysis of log, text, image, interview, and survey data; (2) measures that have been used to analyze learning engagement include self-report (e.g., the Online Learning Engagement Scale, Online Student Engagement Questionnaire, and MOOC Engagement Scale) and automatic analysis methods [e.g., convolutional neural network (CNN), bidirectional encoder representations from transformers-CNN, K-means clustering, and semantic network analysis]; and (3) factors affecting learning engagement can be classified as internal (learning satisfaction, etc.) or external (curriculum design, etc.). Future research should obtain more diverse, multimodal data pertaining to social engagement. Second, researchers should employ automatic analysis methods to improve measurement accuracy. Finally, course instructors should provide technical support (“scaffolding”) for self-regulated learning to enhance student engagement with MOOCs.

Education research is increasingly focused on fostering self-regulated learning (SRL) and socially shared regulation of learning (SSRL) among students. However, previous meta-analyses have rarely focused on the specific types of regulated learning scaffolding. Therefore, this meta-analysis examines the effects of different types of regulated learning scaffolding on regulation strategies and academic performance. A total of 46 articles met the inclusion criteria and were included in the final analysis. The findings showed that overall, regulated learning scaffolding had a moderate effect (g = 0.587). In addition, moderation analyses were performed using a random effects model that focused on four types of scaffolding. The results showed that overall, composite tools had the greatest effect, while the most useful scaffolding for SRL and SSRL were group awareness tools (g = 0.61) and composite tools (g = 0.53), respectively. In terms of learning outcomes, composite tools had the greatest effect on regulation strategies, while intelligent pedagogical agents had the greatest effect on academic performance. We also performed a meta-regression analysis to identify the moderators that had the greatest influence on the effects of regulated learning scaffolding. The results showed that grade level, academic subject, and cooperation all had a significant impact. In conclusion, these findings provide evidence for validating the effectiveness of four regulated learning scaffolding and for discovering their function for SSRL, and presented some practical implications of our findings.

In recent years, there has been an increasing interest among language educators in implementing and researching collaborative learning in wiki-based learning environments. However, little empirical evidence has been reported about the role of EFL learners’ online self-regulating capacity in their collaborative learning. This study used wiki-based literature circles as an instructional method to engage EFL learners in collaborative learning. Using a mixed research method, this study examined the under-researched relationship between learners’ online self-regulation and their attitude toward learning through wiki-based literature circles activities. Quantitative data were collected from two surveys, the online self-regulated English learning (OSEL) and the attitude toward wiki-based literature circles (AWLC), among 228 university students in China. Qualitative data were collected from a follow-up interview of 13 participants to explore further the interplay between the students’ online self-regulation and their attitude. The results indicated that students hold positive attitude toward learning through wiki-based literature circles in terms of perceived usefulness, self-efficacy, affection, and behavior. The findings partially confirmed the positive correlations between students’ self-regulated learning strategies and their attitudes. More interestingly, stepwise regression analysis revealed that students’ goal setting acted as a significant predicator of their perceived usefulness of and self-efficacy in completing wiki-based literature circles activities. Self-evaluation was found to be the variable to predict the learners’ affection for and behavior in doing this task. This study highlighted the positive role of students’ goal setting and self-evaluation for explaining their attitude toward wiki-based collaborative learning. Pedagogical implications and future work are also addressed.