Teachers face growing pressure to integrate AI tools into their classrooms, yet are rarely positioned as agentic decision-makers in this process. Understanding the criteria teachers use to evaluate AI tools, and the conditions that support such reasoning, is essential for responsible AI integration. We address this gap through a two-day national summit in which 61 U.S. K-12 mathematics educators developed personal rubrics for evaluating AI classroom tools. The summit was designed to support deliberative sensemaking, a process we conceptualize by integrating Technological Pedagogical Content Knowledge (TPACK) with deliberative agency. Teachers generated over 200 criteria - initial articulations spanning four higher-order themes (Practical, Equitable, Flexible, and Rigorous) - that addressed both AI outputs and the process of using AI. Criteria contained productive tensions (e.g., personalization versus fairness, adaptability versus efficiency), and the vast majority framed AI as an assistant rather than a coaching tool for professional learning. Analysis of surveys, interviews, and summit discussions revealed five mechanisms supporting deliberative sensemaking: time and space for deliberation, artifact-centered sensemaking, collaborative reflection through diverse viewpoints, knowledge-building, and psychological safety. Across these mechanisms, TPACK and agency operated in a mutually reinforcing cycle - knowledge-building enabled more grounded evaluative judgment, while the act of constructing criteria deepened teachers' understanding of tools. We discuss implications for edtech developers seeking practitioner input, school leaders making adoption decisions, educators and professional learning designers, and researchers working to elicit teachers' evaluative reasoning about rapidly evolving technologies.

翻译：教师面临日益增长的压力，需将人工智能工具融入课堂，但在此过程中鲜少被定位为具备自主权的决策者。理解教师评估AI工具所采用的标准，以及支持此类推理的条件，对于负责任地整合AI至关重要。我们通过为期两天的全国峰会填补了这一空白，会上61名美国K-12数学教育者制定了评估课堂AI工具的个人量规。该峰会旨在支持审议性认知，这一过程通过整合技术教学内容知识（TPACK）与审议性主体性得以概念化。教师生成了200余条标准——初步表述涵盖四大高阶主题（实用性、公平性、灵活性与严谨性）——这些标准同时涉及AI输出及使用AI的过程。标准中蕴含生产性张力（如个性化与公平性、适应性与效率之间的张力），且绝大多数标准将AI定位为助手而非专业学习的指导工具。对调查问卷、访谈及峰会讨论的分析揭示了支持审议性认知的五种机制：审议的时空条件、以人工制品为中心的认知、通过多元视角的协作反思、知识建构以及心理安全感。在这些机制中，TPACK与主体性形成了相互强化的循环——知识建构使评估判断更具依据，而建构标准的行为则深化了教师对工具的理解。我们探讨了对寻求从业者反馈的教育科技开发者、进行采纳决策的学校领导、教育工作者与专业学习设计师，以及致力于探究教师对快速演进技术评估推理的研究人员的启示。