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Designer-AI co-creation in product design is rapidly growing, but research on the systematic evaluation of human-AI collaboration remains limited. This paper proposes a hybrid evaluation framework that combines fuzzy Kansei assessment with Bloom’s taxonomy to analyze the affective and cognitive dimensions of designer-AI interaction across 16 design touchpoints. The four-step Kansei engineering method built a Kansei image database and identified key indicators. Fuzzy comprehensive evaluation quantified indicator weights across 16 touchpoints to produce scores. Combined with qualitative analysis based on Bloom’s taxonomy, revealing cognitive differences between designers at different expertise stages in AI collaboration. The research clarifies relationships between Kansei perception and cognitive strategies, providing a systematic perspective for evaluating human-AI co-creation. It offers a validated framework, connects perception and cognition, advancing mixed-method evaluation. In practice, it guides AI-collaborative education, AI tool development, and designer professional development, promoting both theoretical innovations and practical guidelines grounded in human-centered AI design.
Xue et al. (Wed,) studied this question.