Human-AI Collaboration Reconfigures Group Regulation from Socially Shared to Hybrid Co-Regulation

2026-04-09

AI Summary

This study investigates how generative artificial intelligence (GenAI) reshapes group regulation mechanisms in collaborative learning, encompassing processes such as goal setting, participation, strategy use, and monitoring-repair. Through a parallel-group randomized controlled experiment, the research systematically codes and statistically analyzes human dialogue to compare regulatory behaviors between human–AI hybrid groups and all-human groups. The findings reveal, for the first time, that GenAI shifts group regulation from socially shared regulation toward a hybrid human–AI co-regulation model, selectively enhancing directive, obstacle-oriented, and affective regulatory processes. While GenAI significantly reconfigures the distribution of regulatory responsibilities, the focus of participation remains stable. These results provide empirical grounding for designing human-centered AI systems that support collaborative learning.

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.

Problem

• Human-AI collaboration
• collaborative regulation
• generative AI
• socially shared regulation
• co-regulation

Innovation

• human-AI collaboration
• generative AI
• co-regulation
• socially shared regulation
• collaborative learning