Large Language Models (LLMs) have gained traction in educational settings, often framed as virtual tutors or teaching assistants. Following early skepticism and bans, many schools and universities have begun integrating these systems into curricula. Yet decisions about whether and how to deploy LLM-based tools are frequently made without systematic engagement with the full range of stakeholders they affect. In this paper, we argue that understanding stakeholder perceptions of LLM-based systems in the classroom is not a matter of measuring approval or acceptance, but of identifying whose concerns are surfaced, in which contexts, and with what implications for responsible design and governance. We introduce Contextualized Perceptions for the Adoption of LLMs in Education (Co-PALE), a stakeholder-first framework that connects educational context, responsible AI principles, and categories of perception to support more deliberate decision-making about the adoption of LLM-based tools. We ground Co-PALE through a targeted analysis of prior work to diagnose recurring gaps in how stakeholder perceptions are studied, and through contextually distinct educational scenarios that illustrate how the same technology raises different concerns for different stakeholders. We further examine how university faculty and K--12 parents make sense of the framework through focus groups, using their reflections to surface tensions and uncertainties. Co-PALE supports more systematic reasoning about whether, where, and for whom LLM-based tools should be deployed in education.

翻译：大语言模型在教育场景中日益受到关注，常被定位为虚拟导师或教学助理。在经历早期质疑与禁令后，众多学校与大学已开始将这些系统整合至课程体系。然而，关于是否部署及如何部署大语言模型工具的决策，往往未能系统性地征询其影响所涉及的全部利益相关方。本文主张，理解课堂中基于大语言模型系统的利益相关方看法，并非衡量支持度或接受度的问题，而关键在于识别：在哪些情境下、哪些相关方的关切被呈现，以及这对负责任的设计与治理有何启示。我们提出“教育中大语言模型采用的情境化认知框架”，这是一个以利益相关方优先的框架，通过联结教育情境、负责任AI原则与认知类别，以支持更审慎的关于采用大语言模型工具的决策。我们通过对既有研究的靶向分析来验证Co-PALE框架，诊断相关方认知研究中反复出现的空白，并通过情境各异的教育场景示例，说明同一技术如何对不同利益相关方引发不同关切。我们进一步通过焦点小组方式，考察大学教师与K-12家长如何理解该框架，并利用他们的反馈揭示潜在的紧张因素与不确定性。Co-PALE框架支持对以下问题开展更系统的推理：在何处、针对谁部署基于大语言模型的教育工具，以及是否应当部署。