Reform and Exploration of AIGC in Python Programming Education

DOI: https://doi.org/10.62517/jhet.202515137

Author(s)

Fu Yan, Bao Huricha*

Affiliation(s)

School of Journalism and Communication, Yangzhou University, Yangzhou, China *Corresponding Author

Abstract

Generative Artificial Intelligence Content (AIGC) is gradually becoming an important direction for educational reform. Particularly in Python programming education, the introduction of AIGC has brought significant changes to teaching methods, learning approaches, and educational outcomes. This paper aims to explore the application of AIGC in Python programming education, analyzing through case studies the transformations in both teachers' and students' roles, as well as the existing challenges and future prospects.

Keywords

LLMs, Python Programming Language, Education, Teaching Reform

References

[1]Chen, X., Zhang, Y., & Liu, H. (2023). The potential of generative artificial intelligence content in programming education: A review. Journal of Educational Technology, 45(2), 123-136. [2]Zhao, L., & Wang, Z. (2024). Personalized learning through AI-based content generation in programming education. International Journal of Computer Science Education, 59(1), 78-91. [3]Li, J., & Liu, S. (2022). Challenges in integrating AIGC in programming education: Technological, dependency, and pedagogical perspectives. Educational Innovation Journal, 33(4), 102-115.