Exploring the Teaching Mode of University Physics Experiments from the Perspective of Big Data Technology

With the rapid development of big data technology, the "big data +" model has permeated various fields, including education. In the context of university physics experiment teaching, the integration of "big data +" not only transforms traditional teaching methods but also holds significant potential for improving educational outcomes. This paper analyzes the impact of the "big data +" model on university physics experiment teaching in the science and engineering majors of Hubei Second Normal University over one academic year. The study focuses on key aspects such as pre-class self-study, in-class teaching effectiveness, post-class experiment summaries, and review effectiveness. Additionally, the research proposes practical strategies, including big data-driven teaching design, the construction of an experimental teaching platform under big data technology, and the evaluation and optimization of teaching effectiveness, to effectively integrate big data technology into university physics experiment teaching. Through the "big data technology" model, not only is the quality of physics experiment teaching enhanced, but innovative educational practices are also explored, providing students with a superior learning experience and guiding future teaching reforms in this course.