How design ability anxiety leads to design students' dependence on artificial intelligence? Internship and professional identity, feedback and evaluation mechanisms, and the role of innovative mindset

AI-Generated Design (AIGD) is a technique that uses deep learning algorithms to generate realistic images. It can create new images from scratch or generate images of a specific style, style or theme based on a given input. The emergence of this technology has disrupted not only traditional design work but also the field of design education. The use of AI-Generated Design (AIGD) by design students to cope with their academic work has been prevalent since its emergence. However, the intervention of AI technology in the field of pedagogy has a double-sided effect; the growing popularity of this technology increases the learning efficiency of students to a certain extent, but it may also increase the likelihood of undue dependence on this new technology. Drawing upon theoretical models of technology dependence, this study investigates the factors that contribute to students' anxiety regarding their design skills and the reasons behind the tool dependency on AI that leads to design students. Mediation analyses were conducted by collecting data from 432 design school students using AI-Generated Design (AIGD), and the results showed that Design Ability Anxiety was positively associated with Students Rely on AIGD and that Internship and Professional The results show that Design Ability Anxiety is positively related to Students Rely on AIGD and that design education factors such as Internship and Professional Identity, Feedback and Evaluation Mechanisms, and Innovative Mindset all show mediating effects, and that students' reliance on technology is influenced by a combination of design education factors.