发表机构
North Carolina State University; Kennesaw State University; University of Virginia; Georgia Institute of Technology（北卡罗来纳州立大学; 肯尼索州立大学; 弗吉尼亚大学; 佐治亚理工学院）
机构由 AI 辅助整理，请以论文原文为准。AI 中文总结
本研究通过27名中学教师的专业发展工作坊，分析配置与交互日志，发现教师意图与聊天机器人配置及行为存在偏差，强调创作工具需支持教师表达、测试和完善预期行为。
AI 中文摘要
教师越来越多地使用生成式AI来支持教学，然而，教学意图如何转化为聊天机器人配置并反映在聊天机器人行为中，仍不清楚。我们在专业发展工作坊中，对27名中学教师使用的一款面向教师的聊天机器人创作工具进行了研究，分析了焦点小组访谈以及配置和交互日志。教师设想聊天机器人作为教学支架，能够提供差异化支持、扩展获取帮助的途径，并在教师设定的边界内保留学生思维。配置分析显示，“目的”主要捕获教学目标与内容焦点，而“规则”则更常规定教学行为、护栏和针对学习者的调整。基于日志的评估显示，响应性（88.9%）和角色（81.5%）的一致性高于规则（70.4%）和目的（59.3%）。这些发现表明，仅靠可配置控件并不能确保教学保真度，并凸显了创作工具需要帮助教师表达、测试和完善预期聊天机器人行为的必要性。
英文摘要
Teachers are increasingly using generative AI to support instruction, yet it remains unclear how pedagogical intentions are translated into chatbot configurations and reflected in chatbot behavior. We studied a teacher-facing chatbot authoring tool in professional development workshops with 27 middle school teachers, analyzing focus-group interviews alongside configuration and interaction logs. Teachers envisioned chatbots as instructional scaffolds that could provide differentiated support, extend access to assistance, and preserve student thinking within teacher-defined boundaries. Configuration analysis showed that Purpose primarily captured instructional goals and content focus, whereas Rules more often specified pedagogical behavior, guardrails, and learner-specific adaptations. Log-based evaluation showed stronger alignment for responsiveness (88.9%) and persona (81.5%) than for rules (70.4%) and purpose (59.3%). These findings show that configurable controls alone do not ensure pedagogical fidelity and highlight the need for authoring tools that help teachers express, test, and refine intended chatbot behavior.
Comments17 pages, 5 figures
