研究学生如何与AI对话写作，发现三种人机协作模式。
Exploring how EFL students talk to and through AI to develop texts
- 分析44名学生用AI写作文时的提问策略和责任分工模式。
- 52%学生依赖AI主导，但不同模式对写作表现无显著影响。
- 适合关注AI辅助英语写作教学的教师与研究者参考。
生成式人工智能为英语作为外语（EFL）写作教学带来新挑战。本研究探索学生通过提示工程（prompt engineering）与作者权协商与AI互动的方式，并考察后者是否与写作表现相关。采用探索性混合方法设计，分析了44名香港中学生在课程写作任务中使用AI聊天机器人的屏幕录制。内容分析识别出十类提示策略，包括提问、搜索和详细指令。基于这些策略聚类，提炼出三种人机修辞责任模式：AI主导型（52%）、人类主导型（25%）和协作型（14%）。多变量方差分析显示，修辞责任模式在内容、语言和组织三个维度上对写作表现无显著影响。学生的提示策略与责任模式对EFL写作教学中的参与度与自主性具有启示意义。
原文摘要 · Abstract (English)
Generative Artificial Intelligence (AI) introduces new considerations for English as a foreign language (EFL) writing pedagogy. This study explores how students talk to and through AI by prompt engineering and negotiating authorship, respectively, and whether any patterns in the latter relate to students' writing performance. Using an exploratory mixed methods design, we analyzed screen recordings of 44 Hong Kong secondary students completing a Curricular Writing Task with AI Chatbots. Content analysis identified ten types of prompting strategies students employed, including questions, searches, and detailed instructions. From clustering these strategies, three distinct profiles of human-AI rhetorical load responsibility emerged: AI-dominant (52% of students), Human-dominant (25%) and Collaborative human-AI (14%). A MANOVA analysis indicated no significant multivariate effect of rhetorical load responsibility on three dimensions of students' writing performance: content, language, and organization. Students' prompting strategies and rhetorical load responsibility patterns have implications for their engagement and autonomy in EFL writing pedagogy.
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