基于生成式人工智能的大学生编程学习行为分析研究

A Study on Analysis of College Students'Programming Learning Behavior Based on Generative Artificial Intelligence

生成式人工智能可以为教育提供高效且个性化的智能化服务和技术支持。作为典型的生成式人工智能语言模型,ChatGPT在编程中的应用已然获得业界的广泛关注。然而,鲜有学者从实证研究的层面探究学习者如何利用ChatGPT来进行编程学习。研究通过细粒度地采集学习者的编程行为和知识探究问题,对36位学习者的编程过程进行分析。研究结果表明:(1)学习者将ChatGPT视为有用的编程学习资源,依赖其指导学习过程,并倾向于将代码或调试错误信息拷贝至ChatGPT,进而复制其反馈信息;(2)高绩效组主要在前期使用ChatGPT辅助编程,低绩效组在整个编程过程中更频繁地使用ChatGPT进行编程;(3)学习者在使用ChatGPT时主要关注浅层和中层知识的探究,其中,高绩效组通过自主提问获得ChatGPT的反馈,中低绩效组则依赖对ChatGPT反馈内容的追问获得问题解决方案。研究针对如何利用ChatGPT辅助大学生开展编程学习提出了相关的建议,以期为提高编程学习效率提供参考。

Generative artificial intelligence can provide efficient and personalized intelligent services and technical support for education.As a typical generative artificial intelligence language model,the application of ChatGPT in programming has been widely concerned by the industry.However,few scholars have explored how learners use ChatGPT to learn programming from the level of empirical research.Through fine-grained analysis of learners'programming behaviors and knowledge inquiry coding methods,this study has analyzed the programming process of 36 learners.The results show that:(1)learners view ChatGPT as a useful programming learning resource,rely on it to guide the learning process,and tend to copy code or debug errors to ChatGPT,and then copy its feedback;(2)the high-performance group mainly use ChatGPT to assist programming in the early stages,while the low-performance group use ChatGPT more frequently throughout the programming process;(3)learners mainly focus on exploring shallow and middle-level knowledge when using ChatGPT.The high-performance group obtain feedback from ChatGPT by asking questions independently,while the medium-and low-performance group obtain problem solutions by asking questions about feedback from ChatGPT.The study puts forward some suggestions on how to use ChatGPT to assist college students in programming learning,with a view to providing references for improving the efficiency of programming learning.