Keywords
AIGC
Teaching reform
Practical teaching
Performance analysis
Submitted : 2026-04-18
Accepted : 2026-05-03
Published : 2026-05-18
Abstract
Aiming at the prominent problems in the traditional teaching of “Object-Oriented Programming (Java)” such as low student learning interest, weak practical ability, and disconnection between theory and practice, this paper takes the teaching practices of the spring semester of 2024 (traditional teaching mode) and the spring semester of 2025 (Generative Artificial Intelligence [AIGC]-assisted teaching mode) as the research objects. The comparative study is carried out by the same teacher with consistent textbooks, syllabuses, and assessment methods. Through a combination of quantitative and qualitative analysis methods, this paper systematically explores the impact mechanism of integrating AIGC technology into curriculum teaching on teaching effects. The research results show that by accurately meeting students’ learning needs, providing real-time Q&A and programming guidance, and reducing the threshold for understanding abstract concepts, AIGC has effectively stimulated students’ learning initiative and improved their academic performance (the final average score increased by 9 points, P < 0.01). This paper provides a replicable practical path and effect evidence for the intelligent teaching reform of computer-related courses.
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