This study aims to explore the use of large language models (LLM) in analyzing various factors influencing learning behavior among vocational college students. The article identifies key factors such as personal characteristics, learning environment, teaching methods, and technological support through an extensive literature review. Based on these factors, a dynamic model is constructed to quantify and simulate the dynamic changes in students’ learning behavior. The validity of the model is verified through empirical data analysis, and the specific impact of different factors on students’ learning behavior is discussed. The research results provide a scientific basis for personalized teaching strategies and learning support in vocational and technical education, contributing to the optimization of teaching design and the improvement of learning outcomes.
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