分析大一学生用GPT写代码的提示行为，发现多数人能有效使用但需引导批判性思维。
"Give me the code" -- Log Analysis of First-Year CS Students' Interactions With GPT
- 观察69名大一学生在无训练情况下使用GPT解决编程题的提示方式。
- 超半数学生成功整合GPT生成代码，近半数能甄别并选择最优解。
- 揭示学生已具备初步评估AI代码的能力，适合教学设计参考。
大型语言模型（如GPT-3、GPT-4和Bard）对计算机科学教育的影响预计深远。如今，学生可利用这些模型生成各类编程作业的代码解决方案。对于大一学生而言，这可能尤为危险——基础技能尚在形成阶段，过度依赖生成式AI会阻碍其掌握核心编程概念。本研究分析了69名本科生在项目任务中为解决特定编程问题所使用的提示内容，且未提供事先的提示训练。我们还介绍了促使这些提示产生的任务规则，旨在培养互动过程中的批判性思维。尽管提示技巧普遍简单，但研究发现，多数学生成功利用GPT将建议方案融入项目。此外，约一半学生展现出从多个生成结果中进行选择的判断力，体现了其在评估AI生成代码方面批判性思维能力的发展。
原文摘要 · Abstract (English)
The impact of Large Language Models (LLMs) like GPT-3, GPT-4, and Bard in computer science (CS) education is expected to be profound. Students now have the power to generate code solutions for a wide array of programming assignments. For first-year students, this may be particularly problematic since the foundational skills are still in development and an over-reliance on generative AI tools can hinder their ability to grasp essential programming concepts. This paper analyzes the prompts used by 69 freshmen undergraduate students to solve a certain programming problem within a project assignment, without giving them prior prompt training. We also present the rules of the exercise that motivated the prompts, designed to foster critical thinking skills during the interaction. Despite using unsophisticated prompting techniques, our findings suggest that the majority of students successfully leveraged GPT, incorporating the suggested solutions into their projects. Additionally, half of the students demonstrated the ability to exercise judgment in selecting from multiple GPT-generated solutions, showcasing the development of their critical thinking skills in evaluating AI-generated code.
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