教学生用对话方式与AI协作编程，提升代码思维能力。
Prompt Programming: A Platform for Dialogue-based Computational Problem Solving with Generative AI Models
- 构建对话式编程平台，支持多函数协同与即时执行。
- 900多名学生参与，多数通过多轮对话逐步优化代码。
- 学生谨慎选择测试代码，体现批判性思维提升。
编程学习者越来越多地依赖生成式AI工具获取编程帮助，却缺乏正式指导。这凸显了教授学生如何通过自然语言提示有效与AI互动的重要性，以生成并评估解决计算任务的代码。为此，我们开发了一种新型提示编程平台，支持真实的对话式交互，可处理多个相互依赖函数的问题，并提供生成代码的按需执行功能。对超过900名初学编程课程学生的数据分析显示，平台参与度高，大多数提示来自多轮对话；涉及多函数依赖的问题促使学生进行迭代优化，进度图揭示了多种常见策略。学生在选择测试代码时极为审慎，表明按需执行功能有效促进了批判性思考。鉴于对话式编程教育的重要性日益提升，我们公开发布该工具及配套编程问题语料库，供教学使用。
原文摘要 · Abstract (English)
Computing students increasingly rely on generative AI tools for programming assistance, often without formal instruction or guidance. This highlights a need to teach students how to effectively interact with AI models, particularly through natural language prompts, to generate and critically evaluate code for solving computational tasks. To address this, we developed a novel platform for prompt programming that enables authentic dialogue-based interactions, supports problems involving multiple interdependent functions, and offers on-request execution of generated code. Data analysis from over 900 students in an introductory programming course revealed high engagement, with the majority of prompts occurring within multi-turn dialogues. Problems with multiple interdependent functions encouraged iterative refinement, with progression graphs highlighting several common strategies. Students were highly selective about the code they chose to test, suggesting that on-request execution of generated code promoted critical thinking. Given the growing importance of learning dialogue-based programming with AI, we provide this tool as a publicly accessible resource, accompanied by a corpus of programming problems for educational use.
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