Human-AI Collaboration Reconfigures Group Regulation from Socially Shared to Hybrid Co-Regulation
2026-04-09 • Artificial Intelligence
Artificial IntelligenceHuman-Computer Interaction
AI summaryⓘ
The authors studied how using generative AI (GenAI) affects teamwork during learning tasks. They compared groups working together with and without AI to see how they manage their collaboration. They found that when AI was available, groups relied more on mixed forms of managing their work rather than purely shared decisions, with more focus on giving directions and handling problems or emotions. However, the way people focused on different parts of the task stayed mostly the same. This suggests that AI changes how people share responsibility when working together.
Generative AICollaborative learningCo-regulationSocially shared regulationCollaborative regulationHuman-AI interactionRandomised experimentRegulatory processes
Authors
Yujing Zhang, Xianghui Meng, Shihui Feng, Jionghao Lin
Abstract
Generative AI (GenAI) is increasingly used in collaborative learning, yet its effects on how groups regulate collaboration remain unclear. Effective collaboration depends not only on what groups discuss, but on how they jointly manage goals, participation, strategy use, monitoring, and repair through co-regulation and socially shared regulation. We compared collaborative regulation between Human-AI and Human-Human groups in a parallel-group randomised experiment with 71 university students completing the same collaborative tasks with GenAI either available or unavailable. Focusing on human discourse, we used statistical analyses to examine differences in the distribution of collaborative regulation across regulatory modes, regulatory processes, and participatory focuses. Results showed that GenAI availability shifted regulation away from predominantly socially shared forms towards more hybrid co-regulatory forms, with selective increases in directive, obstacle-oriented, and affective regulatory processes. Participatory-focus distributions, however, were broadly similar across conditions. These findings suggest that GenAI reshapes the distribution of regulatory responsibility in collaboration and offer implications for the human-centred design of AI-supported collaborative learning.