Mixed-methods analysis reveals enhanced academic performance and social-emotional interaction in K–12 students, highlighting the impact of social regulation strategies.
Abstract Social regulation strategies serve as effective means of enhancing students' online collaborative learning by facilitating planning, monitoring, evaluation and reflection throughout their learning process. Additionally, social-emotional interactions occupy a pivotal position within collaborative learning, exerting a significant influence on participants’ overall learning performance. However, the relationships among social regulation, social-emotional interactions, and academic performance in the context of online collaborative learning remain underexplored. Therefore, in this study, based on the online collaboration platform of BoardMix, we constructed a social regulation-based online collaborative learning approach. A total of 80 fifth-grade elementary school students participated in this experiment, the experimental class (43 students) adopting the social regulation-based online collaborative learning (SRBOCL) approach and the control class (37 students) adopting the conventional online collaborative learning (OCL) approach. The results indicated that the SRBOCL approach significantly improved students' academic performance. In addition, the experimental group showed more positive social-emotional interactions and fewer negative social-emotional interactions compared to the control group. This study further elucidates the link between academic performance and social-emotional interactions in the context of online collaborative learning. Simultaneously, it provides deeper insights into how social regulation strategies influence students' social-emotional interactions across different phases. Moreover, this phenomenon is particularly pronounced during the monitoring and reflection phases. In conclusion, the results contribute to the design of the social regulation-based online collaborative learning model, and expand the research on social regulation learning in practice.
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Junqi et al. (2025) studied this question.
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