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This study investigates how generative AI functions as an epistemic arbiter in educational settings, revealing that it shifts student collaboration from traditional planning sequences to pathways mediated by conflict resolution and social engagement. While the model reduces direct cognitive behaviors like task planning during interactions, it successfully facilitates constructive disagreement management using AI-generated facts and visualizations. The research highlights a fundamental transformation in collaborative problem-solving dynamics where generative tools actively mediate the transition between social friction and joint reasoning processes.
Beyond Information Retrieval: Generative AI as an Epistemic Arbiter to Enhance Collaborative Problem-Solving
arXiv:2608.05171v1 Announce Type: cross Abstract: Generative AI (GAI) creates new opportunities for collaborative problem-solving (CPS), yet its role in shaping student interaction remains unclear. To address this gap, we conducted a six-week quasi-experimental study with 201 fifth-grade students in two conditions: with and without GAI. Chi-square analysis showed significant differences in CPS behavior distributions between groups. Compared with the control group, the GAI-supported group demonstrated more social behaviors, particularly engagement and conflict management, but less frequent cognitive behaviors such as task planning and solution reasoning. Lag sequential analysis further revealed distinct interaction patterns: while the control group followed a more conventional transition from listening to planning, the GAI group showed a robust pathway from task planning to conflict management to solution reasoning. Thematic analysis of AI interaction logs suggested that students used GAI as an epistemic arbiter, drawing on AI-generated facts and visualizations to resolve disagreements constructively. These findings suggest that GAI reshapes CPS by mediating the transition from social conflict to collaborative reasoning.
Abstract:Generative AI (GAI) creates new opportunities for collaborative problem-solving (CPS), yet its role in shaping student interaction remains unclear. To address this gap, we conducted a six-week quasi-experimental study with 201 fifth-grade students in two conditions: with and without GAI. Chi-square analysis showed significant differences in CPS behavior distributions between groups. Compared with the control group, the GAI-supported group demonstrated more social behaviors, particularly engagement and conflict management, but less frequent cognitive behaviors such as task planning and solution reasoning. Lag sequential analysis further revealed distinct interaction patterns: while the control group followed a more conventional transition from listening to planning, the GAI group showed a robust pathway from task planning to conflict management to solution reasoning. Thematic analysis of AI interaction logs suggested that students used GAI as an epistemic arbiter, drawing on AI-generated facts and visualizations to resolve disagreements constructively. These findings suggest that GAI reshapes CPS by mediating the transition from social conflict to collaborative reasoning.
Computers and Society (cs.CY); Artificial Intelligence (cs.AI)
arXiv:2608.05171 [cs.CY]
(or arXiv:2608.05171v1 [cs.CY] for this version)
https://doi.org/10.48550/arXiv.2608.05171 Focus to learn more arXiv-issued DOI via DataCite
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