Keywords
AIGC
High-level language programming
Intelligence programming
Efficiency improvement
Submitted : 2025-05-06
Accepted : 2025-05-21
Published : 2025-06-05
Abstract
With the rapid development of artificial intelligence technology, AIGC (Artificial Intelligence-Generated Content) has triggered profound changes in the field of high-level language programming courses. This paper deeply explored the application principles, advantages, and limitations of AIGC in intelligent code generation, analyzed the new mode of human-computer collaboration in high-level language programming courses driven by AIGC, discussed the impact of human-computer collaboration on programming efficiency and code quality through practical case studies, and looks forward to future development trends. This research aims to provide theoretical and practical guidance for high-level language programming courses and promote innovative development of high-level language programming courses under the human-computer collaboration paradigm.
References
Zhao X, Zhang X, Han Z, et al., 2017, Practice of Cultivating Problem-Solving and Innovation Abilities in Python Language Teaching. Computer Education, 2017(9): 1672–5913.
Zhang X, Li H, Chen M, et al., 2021, Teaching Design and Practice of Big Data Technology Development Course Based on OBE Concept. Computer Education, 2021(8): 5.
Zhao D, Zhang X, Wu J, 2024, Financial Data Analysis and Software Course Teaching Aimed at Cultivating the Ability to Solve Complex Engineering Problems. Computer Education, 2024(2): 159–163.
Li X, Hu Y, Wang M, et al., 2024, A Review of Research on Artificial Intelligence Generated Content: Applications, Risks, and Governance. Library and Information Work, 68(17): 136–149.
China Academy of Information and Communications Technology, JD Exploration Research Institute, 2022, Artificial Intelligence Generated Content (AIGC) White Paper, viewed April 18, 2025, http://www.caict.ac.cn/english/research/whitepapers/202211/P020221111501862950279.pdf
Chen L, Chen P, Lin Z, 2020, Artificial Intelligence in Education: A Review. IEEE Access, 8: 75264–75278.
Chen L, 2024, Design and Research of an Intelligent Learning System for University Physics. Journal of Contemporary Educational Research, 8(7): 95–99.
Luo C, 2025, Research on Improving the Quality of Employment Guidance in Local Universities through Artificial Intelligence. Journal of Contemporary Educational Research, 9(3): 1–8.