Wang Shuxin, Tao Xin, Ma Hongbo, Li Fanglian, Wu Chuanqi
Changzhou Vocational Institute of Textile and Garment, College of Creative Design, Changzhou, China.
Chizhou University, College of Arts and Education, Chizhou, China.
Front Psychol. 2025 Jul 2;16:1508383. doi: 10.3389/fpsyg.2025.1508383. eCollection 2025.
The purpose of this study has been to evaluate the use of Artificial Intelligence-Generated Content (AIGC) tools in design education, in terms of their effects on creative performance, concentration, and relaxation levels, for university students enrolled in an undergraduate design program.
An experimental design was implemented, using two groups differentiated by their design tool usage (AIGC tools versus traditional software). The sample consisted of 64 third-year undergraduate design students from a public university in Eastern China. Participants completed a three-hour intelligent walking cane design task. The AIGC group used ChatGPT, Midjourney, and Stable Diffusion, while the control group used traditional design software. Neurophysiological states were continuously monitored using BrainLink Pro EEG headband devices. Creative performance was evaluated using standardized design assessment criteria; concentration and relaxation levels were measured through EEG data analysis.
The study's participants demonstrated that use of AIGC tools significantly enhanced creative performance ( = 115.13, SD = 6.44) compared to traditional methods ( = 110.69, SD = 9.37), (62) = 2.208, = 0.031, = 0.55. The AIGC group showed significantly higher concentration levels ( = 51.06, SD = 2.54) than controls ( = 48.31, SD = 2.87), (62) = 4.062, < 0.001, = 1.02. No significant difference was found in relaxation levels between groups ( = 0.191). Correlation analysis revealed a strong positive relationship between concentration level and creative performance ( = 0.67), while relaxation showed weaker associations ( = 0.29).
This study has demonstrated that use of AIGC tools improves creative performance and concentration in design students, with the enhancement primarily driven by improved attentional focus and cognitive resource optimization. The integration of AIGC and EEG technologies provides objective neurophysiological evidence for understanding AI-assisted creativity in design education. It is suggested that AIGC tools should be incorporated into design curricula to enhance student creative outcomes while maintaining appropriate balance with traditional design methods.
本研究旨在评估人工智能生成内容（AIGC）工具在设计教育中的应用，具体考察其对参加本科设计课程的大学生的创意表现、注意力集中程度和放松水平的影响。
采用实验设计，将两组学生根据其使用的设计工具（AIGC工具与传统软件）进行区分。样本包括来自中国东部一所公立大学的64名本科三年级设计专业学生。参与者完成了一项为期三小时的智能手杖设计任务。AIGC组使用ChatGPT、Midjourney和Stable Diffusion，而对照组使用传统设计软件。使用BrainLink Pro EEG头戴式设备持续监测神经生理状态。通过标准化设计评估标准评估创意表现；通过脑电图数据分析测量注意力集中程度和放松水平。
研究参与者表明，与传统方法相比，使用AIGC工具显著提高了创意表现（均值 = 115.13，标准差 = 6.44）（传统方法均值 = 110.69，标准差 = 9.37），t(62) = 2.208，p = 0.031，Cohen's d = 0.55。AIGC组的注意力集中程度显著高于对照组（均值 = 51.06，标准差 = 2.54）（对照组均值 = 48.31，标准差 = 2.87），t(62) = 4.062，p < 0.001，Cohen's d = 1.02。两组之间的放松水平没有显著差异（均值差异 = 0.191）。相关分析显示注意力集中程度与创意表现之间存在强正相关（r = 0.67），而放松水平的相关性较弱（r = 0.29）。
本研究表明，使用AIGC工具可提高设计专业学生的创意表现和注意力集中程度，这种提高主要是由注意力焦点的改善和认知资源的优化驱动的。AIGC与脑电图技术的结合为理解设计教育中的人工智能辅助创造力提供了客观的神经生理证据。建议将AIGC工具纳入设计课程，以提高学生的创意成果，同时与传统设计方法保持适当平衡。
Zotero 插件
