研究教师用AI聊天机器人教编程时的互动与情绪，发现三类使用模式。
Exploring Teacher-Chatbot Interaction and Affect in Block-Based Programming
- 通过11组中学教师实测，提炼出探索型、挫败型、混合型三类互动模式。
- 教师认为聊天机器人能提升提问能力和自信心，但也可能削弱批判思维。
- 建议设计应支持教师控制功能，明确使用时机与方式。
基于大语言模型（LLM）的聊天机器人有望加速教学，但若设计不当可能适得其反。本研究通过对11组中学教师在基于积木编程环境中的科学与计算思维活动进行观察，分析音频记录与聊天交互，提出三种教师角色画像：探索型、挫败型和混合型，反映不同的支架需求。研究发现，教师普遍认为聊天机器人有助于提升提问技巧和自信心，但也担忧其可能导致学习深度下降与批判性思维弱化。关键设计建议包括：提供聊天机器人使用引导、赋予教师对功能的控制权，并明确其使用时机与方式。本研究为支持中学编程教学的聊天机器人设计提供了实践依据。
原文摘要 · Abstract (English)
AI-based chatbots have the potential to accelerate learning and teaching, but may also have counterproductive consequences without thoughtful design and scaffolding. To better understand teachers' perspectives on large language model (LLM)-based chatbots, we conducted a study with 11 teams of middle school teachers using chatbots for a science and computational thinking activity within a block-based programming environment. Based on a qualitative analysis of audio transcripts and chatbot interactions, we propose three profiles: explorer, frustrated, and mixed, that reflect diverse scaffolding needs. In their discussions, we found that teachers perceived chatbot benefits such as building prompting skills and self-confidence alongside risks including potential declines in learning and critical thinking. Key design recommendations include scaffolding the introduction to chatbots, facilitating teacher control of chatbot features, and suggesting when and how chatbots should be used. Our contribution informs the design of chatbots to support teachers and learners in middle school coding activities.
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