Abstract
The integration of artificial intelligence (AI) technology into design education presents both opportunities and challenges. While AItoolscanimprovelearningefficiency, research remains limited in understanding the impact on students’ creative thinking—particularly in relation to the interplay between creative mindset (i.e., growth vs. fixed) and AI self-efficacy. This study adopted a cross- sectional survey design, administering the Creative Mindset Scale and the AISelf-EfficacyScaleto243 design students. Data were analyzed by using structural equation modeling (SEM) with IBM SPSS 23 and AMOS 24. Results indicated that growth mindset served as a significant positive predictor of AI self-efficacy (β = 0.565, p < 0.001), whereas fixed mindset demonstrated insignificant effect on predictive relationship (β = 0.146, p = 0.023). All measurement scales demonstrated high reliability and validity (α = 0.89–0.92). Theoretically, the findings shed light on the psychological mechanisms linking creative cognition and technology adoption. Practically, it is supposed that AI-era design education should prioritize fostering growth mindsets, alongside technical training, to better support creativityinhuman–AIcollaboration.
Keywords
Creative Mindset; AISelf-efficacy; Design Education; Growth Mindset
DOI
https://doi.org/10.21606/iasdr.2025.58
Citation
Shen, Q.H.,and Ma, C.F.(2025) Artificial Intelligence in Higher Education: A Study of the Impact of Creative Mindsets on Design Students' AI Self-efficacy, in Chang, C.-Y., and Hsu, Y. (eds.), IASDR 2025: Design Next, 02-05 December, Taiwan. https://doi.org/10.21606/iasdr.2025.58
Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License
Conference Track
Track 12 - Design Education
Artificial Intelligence in Higher Education: A Study of the Impact of Creative Mindsets on Design Students' AI Self-efficacy
The integration of artificial intelligence (AI) technology into design education presents both opportunities and challenges. While AItoolscanimprovelearningefficiency, research remains limited in understanding the impact on students’ creative thinking—particularly in relation to the interplay between creative mindset (i.e., growth vs. fixed) and AI self-efficacy. This study adopted a cross- sectional survey design, administering the Creative Mindset Scale and the AISelf-EfficacyScaleto243 design students. Data were analyzed by using structural equation modeling (SEM) with IBM SPSS 23 and AMOS 24. Results indicated that growth mindset served as a significant positive predictor of AI self-efficacy (β = 0.565, p < 0.001), whereas fixed mindset demonstrated insignificant effect on predictive relationship (β = 0.146, p = 0.023). All measurement scales demonstrated high reliability and validity (α = 0.89–0.92). Theoretically, the findings shed light on the psychological mechanisms linking creative cognition and technology adoption. Practically, it is supposed that AI-era design education should prioritize fostering growth mindsets, alongside technical training, to better support creativityinhuman–AIcollaboration.