Synergising Computational and Design Thinking in Design Education: A Dual‐Process Framework to Enhancing Creativity and Appropriateness

Abstract This study addressed the critical challenge of integrating computational thinking (CT) and design thinking (DT) in design education, a necessity further amplified by the rapid proliferation of generative artificial intelligence (AI) to enhance both creativity and appropriateness in design outcomes. Grounded in cognitive theory, a novel dual‐process framework is proposed and validated, synergising CT's algorithmic rigour with DT's iterative empathy within a structured two‐dimensional ontology space. In an experiment on fashion pattern design, AI style transfer extended human‐originated concepts. Using a mixed‐methods approach—combining eye‐tracking, subjective ratings and expert evaluation—results demonstrate that CT‐extended designs significantly outperformed human‐originated counterparts in creativity (originality, usefulness) and appropriateness (thematic relevance, aesthetic satisfaction). The findings support the framework's efficacy in expanding the solution space while ensuring contextual coherence, balancing divergent and convergent processes. Theoretically, it contributes a validated dual‐process model; methodologically, a replicable multimodal protocol; and practically, it provides design educators actionable, evidence‐based guidance for integrating AI, including structured cognitive bridging prompts.