AI-powered education technologies can support students and teachers in computer science education. However, with the recent developments in generative AI, and especially the increasingly emerging popularity of ChatGPT, the effectiveness of using large language models for solving programming tasks has been underexplored. The present study examines ChatGPT's ability to generate code solutions at different difficulty levels for introductory programming courses. We conducted an experiment where ChatGPT was tested on 127 randomly selected programming problems provided by Kattis, an automatic software grading tool for computer science programs, often used in higher education. The results showed that ChatGPT independently could solve 19 out of 127 programming tasks generated and assessed by Kattis. Further, ChatGPT was found to be able to generate accurate code solutions for simple problems but encountered difficulties with more complex programming tasks. The results contribute to the ongoing debate on the utility of AI-powered tools in programming education.

翻译：人工智能驱动的教育技术能够支持计算机科学教育中的学生和教师。然而，随着生成式人工智能的最新发展，特别是ChatGPT日益普及，利用大型语言模型解决编程任务的有效性仍未得到充分探索。本研究考察了ChatGPT在初级编程课程中生成不同难度代码解决方案的能力。我们进行了一项实验，测试了ChatGPT在Kattis（一种常用于高等教育的计算机科学项目自动评分工具）提供的127个随机选取的编程问题上的表现。结果显示，ChatGPT能够独立解决Kattis生成并评估的127个编程任务中的19个。此外，ChatGPT能够为简单问题生成准确的代码解决方案，但在处理更复杂的编程任务时遇到困难。这些结果对关于人工智能驱动工具在编程教育中实用性的持续讨论做出了贡献。