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<p>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.</p>

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Group dynamics as moderators of deep interaction in blended learning: an empirical investigation

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2026年7月21日

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  • Rongling Zhang,
  • Yonghong Wang,
  • Lifei Wang

摘要

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.