Adoption Analysis of AIGC Tools by Art Students Using an Extended Technology Acceptance Model

The rapid evolution of computer technology has significantly driven the expansion of generative art, leading to an increased prevalence of generative art tools among art students. This study investigates the widespread acceptance of generative art tools within the art student community by employing an extended model derived from the Technology Acceptance Model (TAM). The objective is to provide practical insights aimed at enhancing the adoption of generative art tools. The research collected data from 434 art students, utilizing quantitative analysis through partial least squares structural equation modeling. In addition to traditional TAM factors such as perceived usefulness and perceived ease of use, this study explores the interplay of computer self-efficacy, professional background, art appreciation, creativity, quality of generated images, level of learning, and acceptance. Ongoing efforts will refine the framework for increased applicability among art students in future research endeavors.