AI's integration into education promises to equip teachers with data-driven insights and intervene in student learning. Despite the intended advancements, there is a lack of understanding of interactions and emerging dynamics in classrooms where various stakeholders including teachers, students, and AI, collaborate. This paper aims to understand how students perceive the implications of AI in Education in terms of classroom collaborative dynamics, especially AI used to observe students and notify teachers to provide targeted help. Using the story completion method, we analyzed narratives from 65 participants, highlighting three challenges: AI decontextualizing of the educational context; AI-teacher cooperation with bias concerns and power disparities; and AI's impact on student behavior that further challenges AI's effectiveness. We argue that for effective and ethical AI-facilitated cooperative education, future AIEd design must factor in the situated nature of implementation. Designers must consider the broader nuances of the education context, impacts on multiple stakeholders, dynamics involving these stakeholders, and the interplay among potential consequences for AI systems and stakeholders. It is crucial to understand the values in the situated context, the capacity and limitations of both AI and humans for effective cooperation, and any implications to the relevant ecosystem.

翻译：人工智能与教育的融合有望为教师提供数据驱动的洞察，并介入学生学习过程。尽管预期取得进展，但对于教师、学生和AI等多方利益相关者协作的课堂中的互动与新兴动态，目前仍缺乏深入理解。本文旨在探究学生如何从课堂协作动态的视角看待教育人工智能的影响，特别是AI通过观察学生并通知教师以提供针对性帮助的应用场景。采用故事补全方法，我们分析了65名参与者的叙述，揭示了三大挑战：AI对教育情境的去语境化；存在偏见担忧与权力失衡的AI-教师协作；以及AI对学生行为的影响进一步挑战AI的有效性。我们认为，要实现有效且合乎伦理的AI协同教育，未来教育人工智能设计必须考量实施的情境性特征。设计者需综合考虑教育背景的宏观细微差异、对多方利益相关者的影响、涉及这些利益相关者的动态关系，以及AI系统与利益相关者之间潜在后果的相互作用。理解具体情境中的价值取向、AI与人类有效协作的能力与局限，以及对相关生态系统的潜在影响至关重要。