From Technology Acceptance to Human Compute Collaborative Creation: A Conceptual Framework for Enhancing the Creative Practice of Art and Design Faculty in Higher Education

Abstract

Artificial intelligence generated content (AIGC) is increasingly used in art and design education, but existing research often infers the enhancement of creativity from factors such as adoption, efficiency, or positive attitudes, neglecting how technology acceptance translates into creative value. This conceptual study integrates the Technology Acceptance Model (TAM) and the Diffusion of Innovations (DOI) theory to construct an "Acceptance Practice Creativity" (AEC) framework for art and design teachers in higher education. This framework synthesizes four conceptual insights. First, relative advantage and perceived usefulness can foster positive evaluations of innovation, but evaluation alone cannot enhance creativity. Second, perceived usability can reduce interaction friction and promote repeated experimentation. Third, behavioral intentions only promote creativity when translated into sustained human computer collaborative creative practice, a process that requires iterative prompting, comparison, improvement, and critical selection. Fourth, AIGC has a dual effect: it can both expand creativity and, in cases of weak professional judgment and governance, foster dependency, copyright risks, and aesthetic convergence. Therefore, the framework's main contribution lies in pointing out that co creative practices bridge the gap between technology acceptance and teacher creativity, while viewing creativity as novelty, utility, and pedagogical relevance, not just speed. For universities and the creative industries, the framework supports targeted faculty development, process based assessment, copyright management, and human centered AI practices.