AI 中文总结
本研究通过分析两门爱沙尼亚语编程MOOC的问卷数据，发现课程情境（如时长和内容）比学习者特征更显著地影响GenAI的使用频率和目的，为编程教育设计提供启示。
AI 中文摘要
生成式人工智能（GenAI）工具（如ChatGPT和代码补全助手）的日益普及，引发了关于学习者如何将这些工具整合到学习活动中的问题，尤其是在吸引多样化参与者群体的MOOC中。本研究考察了爱沙尼亚语授课的两门编程MOOC中GenAI的使用情况，这两门课程在时长、工作量、主题复杂性和作业量上有所不同：《关于编程》（4周，预计26小时，n=187）和《编程入门》（8周，预计78小时，n=182）。采用非参数统计方法对课程后问卷数据进行分析，以考察不同课程和学习者背景中自我报告的使用采纳、使用频率和GenAI使用目的。结果显示，GenAI的采纳在两门MOOC中都很普遍，在性别、年龄、教育水平或先前编程经验方面没有统计学显著差异。然而，在较长、更广泛的MOOC中，参与者报告的使用频率显著更高，并且更可能使用GenAI进行调试和想法生成。在较长课程中，代码解释和调试的报告使用频率也更高。探索性分析发现GenAI使用与学习相关结果之间的关系有限。研究结果表明，在塑造GenAI工具的使用方式方面，课程情境可能比学习者特征发挥更大的作用。这些结果为编程教育中的教学设计和指导提供了启示。
英文摘要
The increasing availability of generative artificial intelligence (GenAI) tools, such as ChatGPT and code-completion assistants, raises questions about how learners integrate these tools into learning activities, particularly in MOOCs that attract diverse participant populations. This study examines the use of GenAI in two programming MOOCs taught in Estonian that differ in duration, workload, topic complexity, and assignment volume: About Programming (4 weeks, 26 expected hours, n = 187) and Introduction to Programming (8 weeks, 78 expected hours, n = 182). Post-course questionnaire data were analyzed using non-parametric statistical methods to examine self-reported adoption, usage frequency, and purposes of GenAI use across courses and learner backgrounds. The results show that GenAI adoption was widespread in both MOOCs, with no statistically significant differences by gender, age, education level, or prior programming experience. However, participants in the longer, more extensive MOOC reported significantly higher usage frequency and were more likely to use GenAI for debugging and idea generation. Reported usage frequency for code explanation and debugging was also higher in the longer course. Exploratory analyses found limited relationships between GenAI use and learning-related outcomes. The findings suggest that course context may play a greater role than learner characteristics in shaping how GenAI tools are used. These results provide implications for instructional design and guidance in programming education.
CommentsAccepted to SIGCSE Technical Symposium 2027
