From "Ban It Till We Understand It" to "Resistance is Futile": How University Programming Instructors Plan to Adapt as More Students Use AI Code Generation and Explanation Tools such as ChatGPT and GitHub Copilot
From "Ban It Till We Understand It" to "Resistance is Futile": How University Programming Instructors Plan to Adapt as More Students Use AI Code Generation and Explanation Tools such as ChatGPT and GitHub Copilot
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DOI：
10.1145/3568813.3600138
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发表时间：
2023-08
期刊：
影响因子：
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通讯作者：
Sam Lau;Philip J. Guo
中科院分区：
文献类型：
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作者：
Sam Lau;Philip J. Guo
在过去的一年里（2022-2023年），最近发布的人工智能工具（如ChatGPT和GitHub Copilot）得到了计算教育工作者的极大关注。研究人员和实践者都发现，这些工具可以为各种入门编程作业生成正确的解决方案，并准确地解释代码的内容。考虑到他们目前的能力和未来几年可能的进步，大学教师计划如何调整他们的课程，以确保学生仍然学得很好？为了收集不同的观点样本，我们采访了来自9个国家（澳大利亚，博茨瓦纳，加拿大，智利，中国，卢旺达，西班牙，瑞士，美国）的20名入门编程讲师（9名女性+ 11名男性），横跨所有6个人口稠密的大陆。据我们所知，这是第一次收集教师关于他们计划如何适应这些AI编码工具的观点的实证研究，未来更多的学生可能会使用这些工具。我们发现，在短期内，许多人计划立即采取措施阻止人工智能辅助作弊。然后，关于如何长期使用人工智能编码工具的意见出现了分歧，一方希望禁止它们并继续教授编程基础知识，另一方希望将它们整合到课程中，为学生未来的工作做好准备。我们的研究结果在2023年初及时捕捉到了一个罕见的快照，因为计算教师刚刚开始对这种快速增长的现象形成看法，但尚未就最佳实践达成任何共识。利用这些发现作为灵感，我们合成了一组关于如何开发，部署和评估用于计算教育的AI编码工具的开放式研究问题。
Over the past year (2022–2023), recently-released AI tools such as ChatGPT and GitHub Copilot have gained significant attention from computing educators. Both researchers and practitioners have discovered that these tools can generate correct solutions to a variety of introductory programming assignments and accurately explain the contents of code. Given their current capabilities and likely advances in the coming years, how do university instructors plan to adapt their courses to ensure that students still learn well? To gather a diverse sample of perspectives, we interviewed 20 introductory programming instructors (9 women + 11 men) across 9 countries (Australia, Botswana, Canada, Chile, China, Rwanda, Spain, Switzerland, United States) spanning all 6 populated continents. To our knowledge, this is the first empirical study to gather instructor perspectives about how they plan to adapt to these AI coding tools that more students will likely have access to in the future. We found that, in the short-term, many planned to take immediate measures to discourage AI-assisted cheating. Then opinions diverged about how to work with AI coding tools longer-term, with one side wanting to ban them and continue teaching programming fundamentals, and the other side wanting to integrate them into courses to prepare students for future jobs. Our study findings capture a rare snapshot in time in early 2023 as computing instructors are just starting to form opinions about this fast-growing phenomenon but have not yet converged to any consensus about best practices. Using these findings as inspiration, we synthesized a diverse set of open research questions regarding how to develop, deploy, and evaluate AI coding tools for computing education.