Large Language Models (LLMs) like GPT and Bard are capable of producing code based on textual descriptions, with remarkable efficacy. Such technology will have profound implications for computing education, raising concerns about cheating, excessive dependence, and a decline in computational thinking skills, among others. There has been extensive research on how teachers should handle this challenge but it is also important to understand how students feel about this paradigm shift. In this research, 52 first-year CS students were surveyed in order to assess their views on technologies with code-generation capabilities, both from academic and professional perspectives. Our findings indicate that while students generally favor the academic use of GPT, they don't over rely on it, only mildly asking for its help. Although most students benefit from GPT, some struggle to use it effectively, urging the need for specific GPT training. Opinions on GPT's impact on their professional lives vary, but there is a consensus on its importance in academic practice.

翻译：像 GPT 和 Bard 这样的大型语言模型（LLMs）能够根据文本描述生成代码，效果显著。此类技术将对计算机教育产生深远影响，引发对作弊、过度依赖以及计算思维技能下降等问题的担忧。已有大量研究探讨教师应如何应对这一挑战，但了解学生对这一范式转变的看法同样重要。本研究对 52 名计算机科学（CS）专业一年级学生进行了调查，旨在从学术和职业两个维度评估他们对具备代码生成能力技术的看法。我们的研究结果表明：尽管学生总体上倾向于在学术中使用 GPT，但他们并未过度依赖，仅适度寻求其帮助。虽然大多数学生从 GPT 中获益，但部分学生难以有效使用它，这表明有必要开展专门的 GPT 使用培训。关于 GPT 对其职业生活影响的看法存在差异，但在其学术实践中的重要性上达成了共识。