Guided Sensemaking: Agents in Collaborative Deliberation

2026-06-01

AI Summary

This work addresses the limitations of current generative AI tools, which prioritize rapid question-answering at the expense of structured reflection, argument construction, and collaborative meaning-making—often undermining deep thinking. To counter this, we propose a multi-agent collaborative platform that positions AI as a research partner rather than an answer provider. Through context-aware prompting and cognitive scaffolding, the system guides users to develop well-reasoned perspectives around core questions. Integrating multi-agent interaction, thematic clustering, and visualized argument structures, the platform externalizes reasoning processes while preserving user agency and enabling traceable representation of diverse viewpoints. This design effectively supports structured collaborative reasoning and in-depth dialogue in both educational and civic contexts.

Abstract

Generative AI systems are aggressively reshaping how students engage with information and perform cognitive work; convenience-oriented use has the potential to displace effortful reasoning, reflection, and learning, especially for those who lack domain expertise and effective human-AI interaction strategies. Current AI tools are heavily focused on chat-style interfaces geared towards answer generation and efficiency in a linear and fragmented stream of text, offering limited support for structured reflection, argument construction, and sensemaking in collaborative contexts. We introduce Guided Sensemaking, an AI-augmented multiagent discourse platform that facilitates composition of well-thought-out ideas around a central question, provides scaffolding for critical thinking, and enables visualization of argumentative structure to support critical thinking and collaborative deliberation. The system uses several interactive agents to provide context-sensitive questioning prompts and a scaffolding for thought that exposes thematic clusters, agreements, and points of contention without collapsing diverse perspectives. This paper proposes a conceptual design and interaction paradigm that positions generative AI not as a shortcut to answers but as a research partner that externalizes reasoning, preserves user agency, and fosters structured, traceable sensemaking in educational and civic contexts.

Problem

• sensemaking
• collaborative deliberation
• generative AI
• critical thinking
• argument construction

Innovation

• Guided Sensemaking
• multiagent discourse
• argument visualization
• scaffolded critical thinking
• human-AI collaboration