用AI教学生正确使用AI，提升提问能力与责任感。
Learning to Use AI for Learning: Teaching Responsible Use of AI Chatbot to K-12 Students Through an AI Literacy Module
- 设计基于大模型的提示教学模块，通过真实场景练习提升学生能力。
- 学生提问技巧显著提升，对AI辅助学习信心增强。
- 开放题和判断题比选择题更有效评估提示素养，适合中小学教学。
随着人工智能日益融入日常生活，亟需培养下一代负责任地应用、交互、评估和协作使用AI系统的能力。现有研究指出，中小学教育者迫切需要教授学生在学习中伦理且高效地使用AI。为此，我们设计了一个基于大语言模型（LLM）的提示素养教学模块，包含与智能LLM代理直接互动的情境化刻意练习活动，旨在促进中学生负责任地使用AI聊天机器人。我们在11个真实的中学课堂中进行了两轮教学部署，评估了：1）基于AI的自动评分系统的表现；2）学生在使用AI学习时的提示表现与信心变化；3）学习与评估材料的质量。结果表明，基于AI的自动评分系统可实现令人满意的评分质量。教学材料有效支持学生通过练习提升提示技能，并促使学生对使用AI学习的认知产生积极转变。此外，第一轮研究数据用于优化第二轮评估设计。第二轮分析显示，判断题和开放题比选择题更能有效衡量目标学习者的提示素养。这些成果凸显该模块具有广泛推广潜力，也表明需开展更多研究以评估学习效果与测评设计的有效性。
原文摘要 · Abstract (English)
As Artificial Intelligence (AI) becomes increasingly integrated into daily life, there is a growing need to equip the next generation with the ability to apply, interact with, evaluate, and collaborate with AI systems responsibly. Prior research highlights the urgent demand from K-12 educators to teach students the ethical and effective use of AI for learning. To address this need, we designed an Large-Language Model (LLM)-based module to teach prompting literacy. This includes scenario-based deliberate practice activities with direct interaction with intelligent LLM agents, aiming to foster secondary school students' responsible engagement with AI chatbots. We conducted two iterations of classroom deployment in 11 authentic secondary education classrooms, and evaluated 1) AI-based auto-grader's capability; 2) students' prompting performance and confidence changes towards using AI for learning; and 3) the quality of learning and assessment materials. Results indicated that the AI-based auto-grader could grade student-written prompts with satisfactory quality. In addition, the instructional materials supported students in improving their prompting skills through practice and led to positive shifts in their perceptions of using AI for learning. Furthermore, data from Study 1 informed assessment revisions in Study 2. Analyses of item difficulty and discrimination in Study 2 showed that True/False and open-ended questions could measure prompting literacy more effectively than multiple-choice questions for our target learners. These promising outcomes highlight the potential for broader deployment and highlight the need for broader studies to assess learning effectiveness and assessment design.
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