HRMARS - Against the backdrop of the deepening advancement of educational digital transformation, the professional development of university music teachers faces the dual challenges of digital intelligence technology innovation and the unique characteristics of arts education. From the perspective of digital intelligence technology empowerment, and grounded in the TPACK framework, self-efficacy theory, and professional learning community theory, this study constructs a theoretical framework for a professional development support system for university music teachers encompassing four dimensions: Digital Infrastructure Support (DIS), Professional Learning Community Support (PLCS), Administrative Policy Support (APS), and Technical Skills Training Support (TSTS). Using Digital Teaching Efficacy (DTE) as a mediating variable and Professional Development Outcomes (PDO) as the dependent variable, a large-scale questionnaire survey was conducted among 487 in-service music teachers across 52 universities in 15 provinces. Quantitative analysis was performed using Structural Equation Modeling (SEM) and Bootstrap mediation testing. The results indicate that: (1) all four dimensions of support factors have significant positive predictive effects on professional development outcomes; (2) digital teaching efficacy plays a significant partial mediating role between the support system and professional development outcomes, with a mediation proportion of approximately 35%; (3) technical skills training support exhibits the strongest predictive power, followed by professional learning community support; and (4) institution type significantly moderates the path from technical skills training support to digital teaching efficacy. Based on these empirical findings, this study proposes a “three-level, four-dimension, dual-drive” framework for constructing a professional development support system for university music teachers, and outlines specific practical pathways across the four dimensions of infrastructure construction, community cultivation, policy optimization, and full-chain training, aiming to provide a reference for promoting the high-quality development of university music education in the digital intelligence era.
Wei Wang (Wed,) studied this question.