Generative models are now capable of producing natural language text that is, in some cases, comparable in quality to the text produced by people. In the computing education context, these models are being used to generate code, code explanations, and programming exercises. The rapid adoption of these models has prompted multiple position papers and workshops which discuss the implications of these models for computing education, both positive and negative. This paper presents results from a series of semi-structured interviews with 12 students and 6 instructors about their awareness, experiences, and preferences regarding the use of tools powered by generative AI in computing classrooms. The results suggest that Generative AI (GAI) tools will play an increasingly significant role in computing education. However, students and instructors also raised numerous concerns about how these models should be integrated to best support the needs and learning goals of students. We also identified interesting tensions and alignments that emerged between how instructors and students prefer to engage with these models. We discuss these results and provide recommendations related to curriculum development, assessment methods, and pedagogical practice. As GAI tools become increasingly prevalent, it's important to understand educational stakeholders' preferences and values to ensure that these tools can be used for good and that potential harms can be mitigated.

翻译：生成模型现已能够生成在某些情况下与人类文本质量相当的自然语言文本。在计算教育领域，这些模型正被用于生成代码、代码解释及编程练习。这类模型的快速普及引发了多篇立场论文与专题研讨会，探讨它们对计算教育的积极与消极影响。本文通过对12名学生和6名教师进行一系列半结构化访谈，呈现了他们在计算课堂中使用生成式人工智能工具的认识、体验与偏好。结果表明，生成式人工智能工具将在计算教育中扮演日益重要的角色。然而，学生与教师也提出了诸多关于如何整合这些模型以最好地支持学生需求与学习目标的关切。我们还发现了教师与学生偏好使用这些模型方式之间值得关注的张力与一致性。我们讨论了这些结果，并就课程开发、评估方法与教学实践提出了建议。随着生成式人工智能工具的日益普及，理解教育相关者的偏好与价值观至关重要，以确保这些工具能被善用，并减轻潜在危害。