Optimizing Pathways for Cultivating Innovative Digital Arts Talents in Higher Education Empowered by AIGC
Fan Wang, jiechun duan · 2025
With the rapid advancement of computer technology and Artificial Intelligence Generated Content (AIGC), digital arts education is entering a new era—transitioning from digitalization toward intelligence and automation. The rise of AIGC has greatly enriched the methods and forms of digital art creation, profoundly influencing talent cultivation models in higher education. This paper adopts a literature review and case analysis approach to systematically trace the development of AIGC technologies and their representative applications in higher arts education, with a particular focus on innovative practices in curriculum systems, teaching models, and evaluation mechanisms at universities in China and abroad. The research reveals that AIGC enhances creative efficiency and diversifies teaching resources, promotes interdisciplinary integration, and fosters students’ innovative capabilities. Nevertheless, it also presents new challenges regarding faculty adaptation, ethics, and copyright. The paper further proposes a pathway for cultivating innovative digital arts talents centered on multi-level curriculum construction, project-based teaching, university-industry collaboration, and optimization of evaluation mechanisms, supported by case studies and visual models. This provides both theoretical underpinnings and practical references for the high-quality development of digital arts education.