AIGC changes in teaching practice in higher education visual design courses: Curriculum and teaching methods
Kaina Wang, Zhiqiang Yang, Kim Jaehong
Abstract
This paper explores how Artificial Intelligence Generated Content (AIGC) tools can be effectively integrated into visual design courses in higher education. Focusing on the relationship between visual design courses, teaching practices and AIGC, this paper examines the impact of AIGC on traditional visual design courses from three perspectives: the status and impact of integrating AIGC into higher education visual design courses; the opportunities and challenges of integrating AIGC into teaching methods; and the impact of integrating AIGC into teaching activities on the teacher-student relationship. By observing teaching experiments in new visual design courses at universities that have integrated AIGC tools, this paper examines the practical application of AIGC tools in course design and teaching methods, as well as their impact on course design, teaching methods, and teacher-student interaction. The paper emphasises the significant change in educational philosophy and teaching models in university visual design courses brought about by using AIGC.