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.

翻译：生成式人工智能系统正在重塑学生接触信息及进行认知工作的方式；便利导向的使用可能取代需要付出努力的推理、反思和学习过程，尤其对缺乏领域专长及有效人机交互策略的学习者影响显著。当前AI工具多聚焦于线性、碎片化文本流中的聊天式交互界面，侧重答案生成与效率提升，在协作情境中缺乏对结构化反思、论点构建及意义建构的系统支持。我们提出"引导式意义建构"框架——一种AI增强的多代理话语平台，该平台能围绕核心问题促进深思熟虑观点的形成，为批判性思维提供脚手架支撑，并通过论证结构可视化手段支持批判性思考与协作商讨。系统运用多个交互代理提供情境敏感性提问提示，构建思维脚手架以呈现主题聚类、共识观点与争议焦点，同时避免消解多元视角。本文提出一种概念设计与交互范式，将生成式AI定位为认知研究伙伴而非答案捷径：它外显推理过程、保留用户主体性，并在教育及公民语境中培育结构化、可追溯的意义建构。