This study aims to develop a teaching–learning model that alleviates design fixation and fosters creative outcomes in the pattern design development process. In particular, Generative Artificial Intelligence was integrated into the instructional pro...
This study aims to develop a teaching–learning model that alleviates design fixation and fosters creative outcomes in the pattern design development process. In particular, Generative Artificial Intelligence was integrated into the instructional process to verify differences before and after AI utilization, using emotional satisfaction as the main variable, and to identify directions for model improvement through in-depth learner interviews. The findings are as follows. First, the literature review revealed that previous studies on design fixation can be largely categorized into two types, while prior research on teaching methods utilizing generative AI can be divided into three main approaches. Second, the teaching–learning model designed in this study consists of six stages: exploration/understanding, ideation, concretization, critique, execution, and sharing. Third, when the model was applied to 23 learners and emotional satisfaction was analyzed for 10 randomly selected design outputs, statistically significant differences were found in motif, expression technique, and arrangement method between pre- and post-AI utilization. The level of emotional satisfaction was higher after employing AI in the design process.
Finally, in-depth interview analysis showed that learners used various strategies to overcome design fixation. They also reported common difficulties in prompt formulation when using generative AI, suggesting the need for detailed prompt-writing instruction and terminology guides for style and visual expression. At the same time, learners demonstrated a critical and reflective attitude toward AI-generated outputs rather than relying on them unconditionally.