Exploring the attitude and use of GenAI-image among art and design college students based on TAM and SDT

ABSTRACT

The rapid development of generative artificial intelligence image technology has a tremendous impact on the art and design field and will cause great changes in art and design education. Considering the interrelationships between students’ intentions and motivations, this study combines the technology acceptance model with self-determination theory and also considers the possible risks associated with the new technology to construct an integrated theoretical model, aiming to explore the acceptance of GenAI-image among art and design college students. In this study, 308 questionnaires were collected using the questionnaire method and structural equation modeling. The results showed that art and design college students have distinct professional characteristics, and they are more concerned about the originality and privacy of their work than about the replacement of the future jobs. Additionally, they are more likely to use GenAI-image as an effective tool to enhance their creations, and their acceptance of the technology increases when it is capable of connecting other learners with the same objectives. But the power of the technology may also increase their concerns about job substitution and the privacy of originality.

KEYWORDS:

• Generative artificial intelligence image
• Midjourney
• technology acceptance model
• self-determination theory
• art and design
• college students

Disclosure statement

No potential conflict of interest was reported by the author(s).

Data availability statement

The data presented in this study are available upon request from the corresponding author.

Institutional review board statement

This work has been approved by the Departmental Ethics Committee and the Institutional Review Board of the university where the first author works.

Informed consent

Written informed consent has been obtained from the participants to publish this paper.

Additional information

Funding

This work was supported by National Social Science Foundation of China: [Grant Number 18BYY089], the Humanities and Social Sciences Youth Fund Project of the Ministry of Education (19YJCZH123) and the Education and Teaching reform project (project number: [2022]20) of Guangdong University of Technology.

Notes on contributors

Xiaoqi Shen

Xiaoqi Shen is a graduate student majoring in design at the School of Art and Design, Guangdong University of Technology. She received her bachelor’s degree in Industrial Design from Guangdong University of Technology. Her current research interests include digital technology, mobile learning, information and education technology, educational psychology, user experience and ergonomics.

Xiaohong Mo

Xiaohong Mo is a PhD student of fashion design at the School of Art and Design, Guangdong University of Technology. She is also a senior designer at a fashion design company. Her research direction mainly uses cognitive psychology for clothing cognitive design, including clothing consumer behavior analysis, and consumer visual attention related to clothing design elements. She is good at eye movement physiology experiments and has very rich practical experience in fashion design.

Tiansheng Xia

Tiansheng Xia is an Associate Professor in the School of Art and Design, Guangdong University of Technology, China. He received his Ph.D. in Psychology from South China Normal University, China. His current research interests include mobile learning, educational neuroscience, and multimodal learning analysis. He has published papers in Human Brain Mapping, Journal of neurolinguistics, Current Psychology, International Journal of Psychology and Child Abuse & Neglect.