Generative Mechanisms of Individual Self-Regulation to Group Shared Regulation in Collaborative Learning: A Qualitative Study Based on Social Shared Regulation Theory

Abstract

This study, grounded in the theory of social shared regulation, employed qualitative research methods to explore the transformation from individual self-regulation to group shared regulation within collaborative learning. Through systematic coding and analysis of reports from 30 college students on their perception and application of self-regulation strategies, as well as transcripts of audio recordings and in-depth interview data from eight collaborative learning groups, the research identified three primary types of self-regulation strategies utilized by college students during collaborative learning: cognitive strategies emphasizing organization and fine processing, resource management strategies primarily focused on time management and teamwork. However, the application of these strategies was found to be uneven. The study also uncovered three core mechanisms for the shift from self-regulation to shared regulation: the sharing of goal clarification strategies, the synergistic application of time management strategies, and the evolution from individual knowledge integration to common knowledge construction. Additionally, individual strategy failure, increased task complexity, and external resource support were identified as critical conditions that trigger a leap in the regulatory hierarchy. Comparative analysis revealed that high-transformation groups exhibited “structured collaboration,” efficiently transformed through mechanisms such as goal structuring, democratic decision-making, and resource integration, whereas low-transformation groups were characterized by “loose dependency,” with the transformation process impeded by unclear goals, passive responses, and superficial interactions. These findings have enhanced our understanding of the generative mechanisms of regulatory levels within the theory of social shared regulation and offer empirical support for the training of regulatory strategies and the design of support systems in collaborative learning.