大数据工程实践与生成式AI——学生在编程中的使用及其对学习的影响

Big Data Engineering Practices and Generative AI—Students’ Usage in Programming and Its Impact on Learning

摘要: 生成式AI技术能力的迅速提升显著提升了高校学生学习与高校教师备课的效率。然而，AI辅助工具与高等教育的融合过程仍存在诸多问题，例如学生知识掌握情况不理想和AI辅助工具使用方法不合理等。为优化生成式AI技术背景下的高等教育教学模式，本研究以大数据方向工程实践的教学过程为例，研究学生使用AI进行大数据编程实践的过程，探讨生成式AI对工科专业学生学习造成的影响。调研目标为某高校计算机学院三年内参与过大数据方向工程实践的学生，统计结果显示，在高等教育的大数据方向工程实践开发中，学生主要借助生成式AI进行开发代码错误检查、辅助环境部署、帮助理解工程开发概念、生成并优化脚本代码及对辅助进行代码注释。

Abstract: The swift progress of generative AI capabilities has substantially improved the learning efficiency of university students and the effectiveness of teaching preparation for educators. Nevertheless, challenges remain in the integration of AI-assisted tools with higher education systems, such as subpar knowledge retention among students and inappropriate usage methods of AI tools. To optimize teaching models under generative AI technology, this study explores the application of AI in big data programming practices via engineering practice courses in the computer science department of a university. The research probes into how generative AI influences the learning outcomes of engineering students. Focusing on third-year students participating in big data engineering practices in the computer science school of a university, statistical analysis indicates that students mainly employ generative AI for code error detection, environment deployment support, conceptual understanding facilitation, script generation and optimization, as well as code annotation assistance during the development of big data engineering practices.