Generative Artificial Intelligence (GenAI) offers numerous opportunities to revolutionise teaching and learning in Computing Education (CE). However, educators have expressed concerns that students may over-rely on GenAI and use these tools to generate solutions without engaging in the learning process. While substantial research has explored GenAI use in CE, and many Computer Science (CS) educators have expressed their opinions and suggestions on the subject, there remains little consensus on implementing curricula and assessment changes. In this paper, we describe our experiences with using GenAI in CS-focused educational settings and the changes we have implemented accordingly in our teaching in recent years since the popularisation of GenAI. From our experiences, we propose two primary actions for the CE community: 1) redesign take-home assignments to incorporate GenAI use and assess students on their process of using GenAI to solve a task rather than simply on the final product; 2) redefine the role of educators to emphasise metacognitive aspects of learning, such as critical thinking and self-evaluation. This paper presents and discusses these stances and outlines several practical methods to implement these strategies in CS classrooms. Then, we advocate for more research addressing the concrete impacts of GenAI on CE, especially those evaluating the validity and effectiveness of new teaching practices.

翻译：生成式人工智能（GenAI）为计算教育（CE）的教学与学习革新提供了诸多机遇。然而，教育工作者担忧学生可能过度依赖GenAI，并利用这些工具生成解决方案而未能真正参与学习过程。尽管已有大量研究探讨了GenAI在CE中的应用，且许多计算机科学（CS）教育工作者就该主题表达了观点与建议，但在课程实施与评估改革方面仍缺乏共识。本文阐述了自GenAI普及以来，我们在以CS为重点的教育环境中使用GenAI的经验，以及近年来相应实施的教学变革。基于这些经验，我们为CE领域提出两项核心行动：1）重新设计课后作业以纳入GenAI的使用，并评估学生运用GenAI解决问题的过程而非仅关注最终成果；2）重新定义教育者的角色，强调学习中的元认知维度，如批判性思维与自我评估。本文阐述并讨论了这些立场，概述了在CS课堂中实施这些策略的若干实用方法。最后，我们呼吁开展更多研究以探讨GenAI对CE的具体影响，特别是评估新教学实践有效性与实效性的研究。