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

Source

• Source name: arXiv
• Source kind: paper
• Authors / organization: Zhengyuan Liu, Stella Xin Yin, Min-Yen Kan, Nancy F. Chen
• Venue: arXiv: cs.CL
• Published: 2026-06-25
• Collected: 2026-06-26
• URL: http://arxiv.org/abs/2606.27233v1
• PDF: https://arxiv.org/pdf/2606.27233v1
• DOI: UNKNOWN

Plain-Language Brief

The authors present a framework for analyzing dialogue in collaborative problem-solving contexts, particularly focusing on human-AI and multi-agent collaboration. The framework addresses limitations in current analytical approaches by using a hierarchical two-layer coding scheme that integrates cognitive and non-cognitive problem-solving with metacognitive regulatory mechanisms. The effectiveness of the framework is demonstrated across nine datasets from various domains.

What the Document Says

• The authors present a conceptual framework for analyzing dialogue in collaborative problem-solving contexts
• The focus is on human-AI and multi-agent collaboration
• The framework addresses limitations in current analytical approaches
• It uses a hierarchical two-layer coding scheme
• The coding scheme integrates cognitive and non-cognitive problem solving with metacognitive regulatory mechanisms
• The effectiveness of the framework is demonstrated across nine datasets
• The datasets are from multiple domains

Key Concepts Mentioned

• dialogue analysis
• collaborative problem-solving
• human-AI collaboration
• multi-agent collaboration
• cognitive problem solving
• non-cognitive problem solving
• metacognitive regulatory mechanisms

Claims Made by the Document

• The presented framework addresses limitations in current analytical approaches
• Metacognitive regulation can be an essential discriminator of deeper collaboration

Evidence Used

• demonstration of the effectiveness and generalizability across nine datasets

Methods / Approach

• hierarchical two-layer coding scheme for dialogue analysis

Limitations Stated by the Authors

Not stated in source

Limitations Noted by the Agent

Agent interpretation — not from the source.

The text does not provide information about potential limitations of the presented framework beyond those acknowledged by the authors.

Open Questions

• What are these specific limitations in current analytical approaches?
• What is the nature of deeper collaboration as it pertains to metacognitive regulation?

Notes for Future Q&A

May include interpretation. Labeled where it does.

• The text does not elaborate on what the specific limitations in current analytical approaches are.
• Deeper collaboration in this context likely refers to a level of synergy or effectiveness beyond simple cooperation, but the precise definition is unclear.

Raw Abstract / Excerpt

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.