提示优先，终成现实
Prompts First, Finally
AI总结：
针对生成式AI对计算机科学教育的冲击争议，本文梳理计算机学科抽象层次发展脉络，提出编程抽象本就朝向自然语言发展，主张在计算机科学教育中采用“Prompts First”方法。
摘要：
生成式人工智能（GenAI），尤其是大语言模型，正在颠覆计算机科学教育。事实证明，它们在应对越来越多的挑战方面能力日益增强。一些教育工作者认为，它们对计算教育构成了严重威胁，我们应该禁止在课堂上使用它们。尽管GenAI仍存在一些尚未解决的严重问题，但当下退一步审视整个计算机科学的整体发展轨迹或许是有益的。从一开始，我们的学科就致力于在每一种新的表示形式中提升抽象层次。我们从硬件拨码开关起步，历经专用语言和流程图等可视化表示形式，一路发展到如今的“自然语言”。随着GenAI的出现，学生们终于可以将问题的抽象层次转换为他们毕生都在用来“解决问题”的“语言”。在本文中，我们提出，我们的编程抽象一直都在朝着这个方向发展——即走向自然语言。现在是时候在计算机科学教育中采用“Prompts First（提示优先）”方法了。
英文摘要：
Generative AI (GenAI) and large language models in particular, are disrupting Computer Science Education. They are proving increasingly capable at more and more challenges. Some educators argue that they pose a serious threat to computing education, and that we should ban their use in the classroom. While there are serious GenAI issues that remain unsolved, it may be useful in the present moment to step back and examine the overall trajectory of Computer Science writ large. Since the very beginning, our discipline has sought to increase the level of abstraction in each new representation. We have progressed from hardware dip switches, through special purpose languages and visual representations like flow charts, all the way now to ``natural language.'' With the advent of GenAI, students can finally change the abstraction level of a problem to the ``language'' they've been ``problem solving'' with all their lives. In this paper, we argue that our programming abstractions were always headed here -- to natural language. Now is the time to adopt a ``Prompts First'' approach to Computer Science Education.
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。
