TITLE:
AI Large Language Model-Driven Pedagogical Reform and Practice for the Python Programming Course: A Case Study in the Electronic Information Engineering Program
AUTHORS:
Zhengjie Wang
KEYWORDS:
AI, Large Language Models, Pedagogical Reform, Python Programming, Project-Based Learning
JOURNAL NAME:
Journal of Computer and Communications,
Vol.13 No.8,
August
22,
2025
ABSTRACT: This paper explores the integration of Artificial Intelligence (AI) large language models to empower the Python programming course for junior undergraduate students in the electronic information engineering program. We propose a reform framework driven by dual innovations in pedagogical models and curriculum content. In terms of pedagogy, AI large language models serve as intelligent teaching assistants for instructors and personalized tutors for students, significantly enhancing teaching efficiency and learning experiences through human-AI collaboration. Regarding curriculum, the course content is deeply integrated with AI technology, featuring a modular project cluster that progresses from collaborative learning of Python fundamentals to data analysis and web applications, culminating in a typical project on advanced AI applications such as semantic image segmentation and large language model fine-tuning. A semester-long implementation of this model demonstrated a significant improvement in students’ learning interest, engineering practice capabilities, and depth of understanding of cutting-edge AI technologies. Furthermore, it fostered critical thinking, AI ethics awareness in the AI era. This study provides a systematic, feasible implementation plan and a valuable reference for reforming programming courses within the context of New Engineering Education.