生成式人工智能时代的计算机科学教育
Computer Science Education in the Age of Generative AI
AI总结：
本文探讨生成式AI（如ChatGPT、Codex）对计算机科学教育的机遇与挑战，并提出课程整合、学习评估及政策建议，以在发挥AI潜力的同时保持教育诚信与严谨。
摘要：
生成式人工智能工具——尤其是像 ChatGPT 和 Codex 这样的大语言模型（LLMs）——正在迅速变革计算机科学教育。这些工具能够生成、调试和解释代码，从而改变编程教学的格局。本文考察了人工智能在总体上为提升计算机科学教育所提供的重大机遇，从编码辅助到培养创新性教学实践以及简化评估流程。与此同时，本文也强调了其中的挑战，包括学术诚信问题、过度依赖人工智能的风险，以及验证原创性的困难。我们讨论了在人工智能时代计算机科学教育者应当教授什么内容，如何以最佳方式将这些技术整合到课程中，以及在一个由人工智能能够生成代码、原型和用户反馈的环境中评估学生学习的最佳实践。最后，我们提出了一套政策建议，旨在发挥生成式人工智能的潜力，同时保持计算机科学教育的诚信与严谨。全文使用实证数据和新兴研究来支持我们的论点。
英文摘要：
Generative AI tools - most notably large language models (LLMs) like ChatGPT and Codex - are rapidly revolutionizing computer science education. These tools can generate, debug, and explain code, thereby transforming the landscape of programming instruction. This paper examines the profound opportunities that AI offers for enhancing computer science education in general, from coding assistance to fostering innovative pedagogical practices and streamlining assessments. At the same time, it highlights challenges including academic integrity concerns, the risk of over-reliance on AI, and difficulties in verifying originality. We discuss what computer science educators should teach in the AI era, how to best integrate these technologies into curricula, and the best practices for assessing student learning in an environment where AI can generate code, prototypes and user feedback. Finally, we propose a set of policy recommendations designed to harness the potential of generative AI while preserving the integrity and rigour of computer science education. Empirical data and emerging studies are used throughout to support our arguments.
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。
