Xiaofei Sun, Zhenzhen Wang, Bin Yang, Lei Wu, Jie Huang, Zeng Li, Wenwen Pan

Wenwen Pan

Novermber 20, 2025

Large language models, Experimental pedagogy, Learning behavior analysis, Personalized learning.

Data structure is a core course in computer related majors, and its experimental teaching is crucial for students to deeply understand and master algorithms and programming skills. However, traditional experimental teaching methods have shortcomings in terms of personalization, learning feedback, and the cultivation of self-directed learning abilities. In recent years, the gradual popularization of big model technology has provided new development ideas for experimental teaching in data structure courses. This article takes the transformation of students' learning habits under the background of big models as the starting point, proposes an experimental teaching mode based on big models, integrates intelligent question answering, code diagnosis, and evolutionary learning, and uses big models to analyze students' learning behavior, dynamically adjust experimental tasks and learning resources that are suitable for learning situations. The research results indicate that the experimental teaching mode based on large models effectively enhances students' learning interest, learning efficiency, and innovation ability.

This is an open access article distributed under the CC BY-NC license