Digital Transformation and Efficiency Optimization of Art Education Management: An Empirical Study on Resource Allocation and Teacher Training Systems Based on Multi-Campus Surveys

Abstract

With the advent of the Industry 4.0 era and the pervasive integration of educational informatization, digital transformation has emerged as a pivotal catalyst for optimizing the operational efficiency of art education management. Traditional art education paradigms, characterized by subjective assessment metrics and decentralized resource architectures, encounter significant bottlenecks in resource allocation and standardized faculty development—particularly within the complex ecosystem of multi-campus educational conglomerates. This paper presents a data-driven framework for the efficiency optimization of art education management. Drawing upon a comprehensive dataset comprising 2,500 valid questionnaires and institutional records collected from 12 art colleges across 4 multi-campus educational groups, this study employs Data Envelopment Analysis (DEA) to quantitatively evaluate the technical efficiency of resource allocation and utilizes Structural Equation Modeling (SEM) to elucidate the causal mechanisms linking digital training to pedagogical performance. The empirical findings demonstrate that digital transformation yields a significant improvement in the technical efficiency of art institutions, with an average increase of 35.2\%. Specifically, the implementation of intelligent scheduling algorithms significantly enhances studio utilization rates and curriculum precision. Furthermore, the study validates that a hybrid training system integrating VR/AR (Virtual/Augmented Reality) technologies with traditional seminars achieves the highest efficacy in elevating teacher satisfaction and innovation capabilities. This research contributes a theoretical framework and practical roadmap for the intelligent governance of art education in the digital age.