Capturing multi-layered regulated learning in collaboration.

Previous studies have reported the importance of regulation in collaborative learning. To understand and support students' learning, researchers have identified that regulation in collaboration emerges as a series of contingent activities at individual and social levels, addressing various learning foci in cognitive, motivational, emotional, and behavioural aspects. However, explanations on how different levels and foci of regulation together influence learning performance have not been made clear. To capture the complexity of regulated learning and the linkage to learning performance, this study examined the temporal sequences of regulated learning, including types (levels), sub-processes, and foci of regulation. Video and interview data were collected from undergraduate students working on a collaborative learning task. These multi-channel data were analysed by content analysis and triangulated to identify the dynamic emergence of regulation events. Process mining was employed to analyse and visualise the temporality and sequences of regulatory processes. The results showed that co-regulated content monitoring was critical in facilitating regulation and task execution at a group level. High-performing groups demonstrated different patterns in developing shared content monitoring and co-regulation of motivation and emotion in the overall learning task. Meanwhile, the variances in how the groups regulated content development and task progress across learning phases were identified. This research extends the conceptualisation of regulated learning to a dynamic multi-layered system. The methods and findings from this study have implications for developing timely and systemic support to improve group performance. [ABSTRACT FROM AUTHOR]