Generative AI in Higher Art Education
Xi Chen, Yuebin Liao, Wei Yu
Abstract
This research delves into the perspectives of Chinese university art teachers on the integration of Artificial Intelligence in Generative Content. Collaboratively initiated by art teachers from Chinese universities through the AI Art Education Alliance in Wuhan, the study aims to comprehend their attitudes, concerns, and preparations regarding the infusion of generative AI tools into art and design curricula. The research employs a comprehensive approach, incorporating group interviews during the inaugural session of the AI Art Education Alliance. Additionally, questionnaire research is utilized as supplementary evidence. Participants include middle-level administrators and teachers from diverse colleges, offering a nuanced understanding of viewpoints across various educational institutions. Key findings reveal nuanced perspectives on AI in higher art education. Notably, there exists a spectrum of AI anxiety, with comprehensive universities showing readiness, while caution prevails in art colleges. The study underscores the potential benefits of AI in art education but highlights concerns about its impact on traditional pedagogy. The research emphasizes the urgency of addressing equity issues related to resource disparities, academic integrity, and cultural resistance within the education community. Recommendations include standardized AI tool usage, adaptations in professional structures, and fostering collaborative alliances to harness AI's potential effectively.