Advancement in technology has increased access to education, most notably, through Massive Open Online Courses (MOOCs). Given the low completion rates in MOOCs, it appears that opening access to education is insufficient for learning when learners do not have the necessary skills to successfully learn. The lack of external regulation in MOOCs due to the physical distance between learners and instructors means that learners have to rely a lot more on themselves to regulate their learning in order to successfully complete the course. However, most learners have difficulties with self-regulated learning (SRL). Therefore, it is crucial to examine how SRL can be supported in MOOCs. To our knowledge, the current study is the first to examine the use of videos to prompt SRL in MOOCs. When learners interact with any of the course items, the studied MOOC provider logs these interactions as clickstream data. By analyzing the clickstream data, we aim to understand how learners learn and self-regulate their learning when provided with videos to prompt SRL. Data presented in the current paper form part of a larger study in which data are being collected from multiple MOOCs. Results from the MOOC where data have been collected show that learners who viewed the SRL-prompt videos completed more course activities compared to learners who did not view the SRL-prompt videos. In addition, the analysis of sequential pattern of transition shows that learners who viewed the SRL-prompt videos made more progress in the MOOC and the SRL-prompt video is featured in most of the sequences. However, further analysis and development of the algorithm used to analyze clickstream data in this study is needed to better understand how learners learn and model the SRL process in MOOCs. Nonetheless, this paper adds to the field by using clickstream data to examine SRL in MOOCs.
