Construction of a faculty competency model for medical simulation education integrated with GenAI: A mixed study based on the perspective of medical students

Background: The rapid advancement of Generative Artificial Intelligence (GenAI) is reshaping the landscape of medical simulation education, necessitating the enhancement of faculty competencies to effectively integrate evolving knowledge systems with GenAI for collaborative decision-making. However, current educational technologies face systemic limitations, including fragmented functionality, a disconnect between conventional and GenAI-driven teaching approaches, and a lack of dynamic capability assessment tools. Constructing a standardized capability scale is crucial to overcoming adaptation bottlenecks. Methods: Grounded in the integrated Technological Pedagogical Content Knowledge (TPACK) framework, this study employed a two-round Delphi method to construct a faculty competency assessment scale, with stratified sampling involving 434 participants from clinical medicine, medical technology, and nursing fields. Exploratory Factor Analysis (EFA) and Confirmatory Factor Analysis (CFA) were used to test model fit (CFI=0.939, RMSEA=0.117). This study was not registered as a clinical trail. Result： The resulting 16-item scale exhibited strong psychometric properties, demonstrating excellent internal consistency (Cronbach’s α = 0.979), sampling adequacy (KMO = 0.961), and significant sphericity (Bartlett’s test, p < 0.001). No factor covariance was detected, and item consensus was high (Kendall’s W = 0.761, p < 0.001). The model showed acceptable fit (χ²/df = 6.893). Conclusion： This validated and standardized assessment model offers a robust empirical tool to support the integration of GenAI into simulation-based medical education. It provides a foundational framework for advancing faculty competency development, thereby fostering adaptive, technology-enhanced teaching practices in the era of intelligent education. Trial registration: This study was approved by the Institutional Ethics Committee of Wenzhou Medical University Second Affiliated Hospital, with Ethical Approval Number: XY-2024-003. Data collection was conducted between February 14 and March 28, 2025.