探索EFL学生如何与AI交流以发展文本
Exploring how EFL students talk to and through AI to develop texts
AI总结：
本文研究EFL学生通过提示工程和协商作者身份与AI互动，探讨其对写作表现的影响，发现不同的人机对话责任模式对写作表现无显著影响。
摘要：
生成式人工智能（AI）为英语作为外语（EFL）写作教学提出了新挑战。本研究探讨学生如何通过提示工程和协商作者身份与AI互动，并检查后者是否与学生的写作表现有关。采用探索性混合方法设计，分析了44名香港中学生在AI聊天机器人上完成课程写作任务的屏幕记录。内容分析识别出学生使用的十种提示策略，包括问题、搜索和详细指示。通过聚类这些策略，出现了三种不同的人机修辞负载责任模式：AI主导（52%的学生）、人类主导（25%）和协作人机（14%）。方差分析表明，修辞负载责任对写作表现的三个维度（内容、语言和组织）无显著影响。学生的提示策略和修辞负载责任模式对EFL写作教学中的参与和自主性具有启示意义。
英文摘要：
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.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
