A Theoretical Framework for AIGC-Enabled Pedagogy in Digital Media Art and the Transformation of Digital Character Design Education - Wu, Jinlong (Pacific International Journal, 2025)
Artificial Intelligence–Generated Content (AIGC) is rapidly reshaping creative industries and transforming the epistemology, processes, and pedagogies of digital media art. Despite widespread adoption of generative models in concept art, digital illustration, and character design, the theoretical foundations guiding their integration into higher education remain insufficiently developed. This theoretical–framework article examines how AIGC reconfigures creative cognition, studio pedagogy, and ethical discourse within digital character design education. Synthesizing interdisciplinary literature on human–AI co-creativity, constructivist learning, studio-based pedagogy, and AI ethics, the study proposes the TAE Framework as a holistic model for understanding the multidimensional influence of AIGC on curriculum design and creative learning. The framework conceptualizes AIGC as a cognitive collaborator, an artistic catalyst, and an ethical negotiation site. It provides implications for curriculum redesign, human–AI co-creative studio instruction, assessment reform, and responsible AI literacy. This work contributes a foundational theoretical lens for future empirical research and offers practical directions for educators seeking to cultivate creativity, criticality, and ethical discernment in an intelligent learning environment.