Connecting Dialogue and Thought: Understanding Dialogue Dynamics in Collaborative Problem Solving

Computer Science > Computation and Language

arXiv:2606.27233v1 (cs) [Submitted on 25 Jun 2026]

Title:Bridging Talk and Thought: Understanding Dialogue Dynamics Across Collaborative Problem-Solving Contexts

Authors:Zhengyuan Liu, Stella Xin Yin, Min-Yen Kan, Nancy F. Chen View a PDF of the paper titled Bridging Talk and Thought: Understanding Dialogue Dynamics Across Collaborative Problem-Solving Contexts, by Zhengyuan Liu and 3 other authors View PDF HTML (experimental)

Abstract:We present a conceptual framework for analyzing dialogue in collaborative problem-solving contexts, with an emphasis on the emerging dynamics of human-AI and multi-agent collaboration. As intelligent systems become active agents capable of autonomous reasoning and strategic cooperation, understanding the dialogic interaction during collaborative problem solving is increasingly important for optimizing and evaluating such partnerships. Our framework addresses key limitations in current analytical approaches through a hierarchical two-layer coding scheme that integrates cognitive and non-cognitive problem solving with metacognitive regulatory mechanisms. We demonstrate its effectiveness and generalizability across nine datasets spanning multiple domains, and provide insights into how humans and agents coordinate their knowledge, skills, and efforts to solve complex problems, showing in particular that metacognitive regulation can be an essential discriminator of deeper collaboration.

Subjects:	Computation and Language (cs.CL); Artificial Intelligence (cs.AI)
Cite as:	arXiv:2606.27233 [cs.CL]
	(or arXiv:2606.27233v1 [cs.CL] for this version)
	https://doi.org/10.48550/arXiv.2606.27233 Focus to learn more arXiv-issued DOI via DataCite

Submission history

From: Zhengyuan Liu [view email]
[v1] Thu, 25 Jun 2026 16:20:49 UTC (8,374 KB)
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