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Toward sustainable aesthetic education: exploring the impact of GenAl collaboration on students' critical thinking
Huiying Liu1, Tianyue Niu2, Chen Shengyan2
1Jimei University, Xiamen, China.
Introduction:
Artificial intelligence (AI)-enabled tools have increasingly influenced artistic creation processes in aesthetic education. However, empirical evidence regarding their impact on students' critical thinking disposition remains limited. This study examined whether integrating Generative Artificial Intelligence (GenAI) tools into an aesthetic learning workshop could enhance undergraduate students' critical thinking disposition and explored the underlying mechanisms.
Methods:
A mixed-methods design was employed. Sixty-three undergraduate arts and design students were randomly assigned to an experimental group (n = 31) or a control group (n = 32). Both groups participated in a two-week structured landscape sketching workshop, while only the experimental group was permitted to use GenAI tools, including image generation models and large language models, to support idea generation, visual experimentation, and iterative refinement. Critical thinking disposition was measured before and after the intervention using a standardized scale. Quantitative analyses included independent-samples tests and ANCOVA, while qualitative data were analyzed to identify learning mechanisms associated with GenAI use.
Results:
The experimental group demonstrated significantly greater improvement in critical thinking disposition than the control group (p < 0.01, Cohen's d = 0.70). Dimension-level analyses and ANCOVA further confirmed that these gains remained significant across multiple dimensions of critical thinking after controlling for baseline differences. Qualitative findings revealed three interrelated mechanisms contributing to these improvements: perceptual-conceptual alignment, iterative visual experimentation, and AI-mediated reflective structuring.
Discussion:
The findings suggest that GenAI tools can function as cognitive amplifiers in aesthetic learning by promoting more analytical, iterative, and reflective creative practices. This study provides empirical support for the integration of AI tools in design education and offers practical implications for fostering higher-order thinking skills in workshop-based learning environments.
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