为课堂AI助教设计可灵活定制的模块化系统
"Bespoke Bots": Diverse Instructor Needs for Customizing Generative AI Classroom Chatbots
- 按教学需求拆分十类定制功能，支持按需组合
- 不同课程规模与学科差异导致优先级显著不同
- 适合教育开发者构建下一代可配置AI助教
教师正越来越多地尝试在课堂中使用AI聊天机器人。为探究教师如何根据自身教学情境调整聊天机器人，我们首先分析了现有教育用途提示资源，识别出十类常见定制维度，如角色设定、安全约束和个性化等。随后对十位大学理工科教师进行访谈，要求他们对这些类别按优先级排序。结果发现，教师始终优先考虑将聊天机器人行为与课程内容和教学策略对齐，而对角色/语气定制的优先级较低。但其他维度的优先级因课程规模、学科领域和教学风格差异显著变化，甚至同一教师的不同课程间也存在差异，表明单一设计无法满足所有场景。研究建议采用模块化架构的AI聊天机器人是可行方向，并为教育技术开发者提供设计启示。
原文摘要 · Abstract (English)
Instructors are increasingly experimenting with AI chatbots for classroom support. To investigate how instructors adapt chatbots to their own contexts, we first analyzed existing resources that provide prompts for educational purposes. We identified ten common categories of customization, such as persona, guardrails, and personalization. We then conducted interviews with ten university STEM instructors and asked them to card-sort the categories into priorities. We found that instructors consistently prioritized the ability to customize chatbot behavior to align with course materials and pedagogical strategies and de-prioritized customizing persona/tone. However, their prioritization of other categories varied significantly by course size, discipline, and teaching style, even across courses taught by the same individual, highlighting that no single design can meet all contexts. These findings suggest that modular AI chatbots may provide a promising path forward. We offer design implications for educational developers building the next generation of customizable classroom AI systems.
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