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Group dynamics as moderators of deep interaction in blended learning: an empirical investigation
Rongling Zhang1,2, Yonghong Wang3, Lifei Wang4
1School of Educational Technology, Northwest Normal University, Lanzhou, 730070, China. zhangrl6@lzcu.edu.cn.
Abstract:
Deep interaction is closely linked to learning quality in blended learning, yet its mechanisms remain unclear. While cognitive interaction has been widely studied, group dynamics are increasingly seen as an important intrinsic factor associated with learners' engagement. Grounded in Moore's Interaction Theory and group dynamics theory, this study examines how group dynamic factors are associated with deep interaction through multiple interaction structures and identifies the configurational conditions underlying this process. Survey data from 357 Chinese college students were analyzed using PLS-SEM and fsQCA. Results indicate that operational interaction has a positive but non-significant association with deep interaction, while learner-content, learner-instructor, and learner-learner interactions show significant positive associations with it. Cohesion negatively moderates learner-instructor interaction but positively moderates learner-learner interaction; driving force shows the opposite pattern. Dissipative force shows no significant linear moderating association, though fsQCA suggests it may serve as a configurational condition contingent on other factors. Deep interaction is thus associated with multiple interaction forms and group dynamic characteristics through equifinal configurational pathways. This study extends Moore's Interaction Theory with a group dynamics perspective and informs group-based interventions for blended learning.
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