@article{ART003135797},
author={Seo Dan Bi and Kim Seung In},
title={A Study on Enhancing the Efficiency of Design Work in Figma using Generative AI},
journal={Industry Promotion Research},
issn={2466-1139},
year={2024},
volume={9},
number={4},
pages={221-226},
doi={10.21186/IPR.2024.9.4.221}
TY - JOUR
AU - Seo Dan Bi
AU - Kim Seung In
TI - A Study on Enhancing the Efficiency of Design Work in Figma using Generative AI
JO - Industry Promotion Research
PY - 2024
VL - 9
IS - 4
PB - Industrial Promotion Institute
SP - 221
EP - 226
SN - 2466-1139
AB - This study investigates ways to enhance the efficiency of design work in Figma through the use of generative AI. By applying Stephen Anderson's Creating Pleasurable Interface Model, the analysis focuses on six key elements: functional, reliable, usable, convenience, pleasure, and meaningful. In-depth interviews and survey results indicate that Figma's generative AI plugins received generally positive evaluations, particularly for their convenience and usability. However, difficulties in prompt creation and the inconvenience of plugin searches were identified as areas needing improvement. This study provides directions for improving Figma's generative AI capabilities and suggests strategies to enhance the efficiency of design work in practical applications. The study outlines how generative AI can boost designers’ creativity and productivity, offering personalized features. These findings serve as a foundation for future design research and practical applications.
KW - Generative AI;Figma;User Experience;Creating Pleasurable Interface Mode;Design Practicel
DO - 10.21186/IPR.2024.9.4.221
ER -
Seo Dan Bi and Kim Seung In. (2024). A Study on Enhancing the Efficiency of Design Work in Figma using Generative AI. Industry Promotion Research, 9(4), 221-226.
Seo Dan Bi and Kim Seung In. 2024, "A Study on Enhancing the Efficiency of Design Work in Figma using Generative AI", Industry Promotion Research, vol.9, no.4 pp.221-226. Available from: doi:10.21186/IPR.2024.9.4.221
Seo Dan Bi, Kim Seung In "A Study on Enhancing the Efficiency of Design Work in Figma using Generative AI" Industry Promotion Research 9.4 pp.221-226 (2024) : 221.
Seo Dan Bi, Kim Seung In. A Study on Enhancing the Efficiency of Design Work in Figma using Generative AI. 2024; 9(4), 221-226. Available from: doi:10.21186/IPR.2024.9.4.221
Seo Dan Bi and Kim Seung In. "A Study on Enhancing the Efficiency of Design Work in Figma using Generative AI" Industry Promotion Research 9, no.4 (2024) : 221-226.doi: 10.21186/IPR.2024.9.4.221
Seo Dan Bi; Kim Seung In. A Study on Enhancing the Efficiency of Design Work in Figma using Generative AI. Industry Promotion Research, 9(4), 221-226. doi: 10.21186/IPR.2024.9.4.221
Seo Dan Bi; Kim Seung In. A Study on Enhancing the Efficiency of Design Work in Figma using Generative AI. Industry Promotion Research. 2024; 9(4) 221-226. doi: 10.21186/IPR.2024.9.4.221
Seo Dan Bi, Kim Seung In. A Study on Enhancing the Efficiency of Design Work in Figma using Generative AI. 2024; 9(4), 221-226. Available from: doi:10.21186/IPR.2024.9.4.221
Seo Dan Bi and Kim Seung In. "A Study on Enhancing the Efficiency of Design Work in Figma using Generative AI" Industry Promotion Research 9, no.4 (2024) : 221-226.doi: 10.21186/IPR.2024.9.4.221
