Abstract: This article focuses on the physiology questions from the National Medical Licensing Examination between 2014 and 2023, systematically analyzing their distribution patterns and core knowledge points. Based on this analysis, we reflect on current teaching methodologies to provide guidance for subsequent instructional optimization. Specific measures include: aligning the teaching syllabus and content coverage with the updated licensing exam outline, deeply integrating actual exam questions into fundamental theory instruction, and implementing high-quality question banks to meet examination requirements. Furthermore, we propose constructing intelligent learning resources such as knowledge graphs to help students establish a systematic and comprehensive understanding of physiological knowledge networks. This research provides data-driven support for precision reform in medical education, ultimately aiming to enhance the pass rates of the licensing examination.

Key words: Physiology, National medical licensing examination, Teaching application, Case teaching, Basic theory, Smart course