| Title |
Educational Applications of Generative AI in Design Studio Education through Analysis of Learners’ Cognitive Processes |
| Authors |
김영호(Kim, Young-Ho) ; 박찬일(Park, Chan-Il) |
| DOI |
https://doi.org/10.14774/JKIID.2026.35.4.029 |
| Keywords |
Generative Artificial Intelligence; Chicago Design Process; Bloom’s Taxonomy; Cognitive Processes; Design Studio Education |
| Abstract |
This study comparatively analyzes how generative AI use relates to learners’ cognitive activity patterns across the design process in a lighting design studio course. To this end, an analytical framework?the CDP?Bloom matrix? was developed by integrating the Chicago Design Process (CDP) with Bloom’s cognitive taxonomy. Over one semester, case observation was conducted with the 54 students enrolled in the course, and the analysis of the post-project survey focused on 51 valid respondents (45 in the generative AI user group and 6 in the non-user group). The results show that the AI user group reported relatively higher perceptions in the Define?Collect and Present?Improve stages?particularly in information search, idea visualization, concept communication, and feedback reflection?and tended to engage earlier and more iteratively in higher-order cognition such as analysis, evaluation, and creation. In contrast, in the Brainstorm?Develop stage, the non-user group showed relatively higher mean scores in items related to circulation planning, drawing accuracy, and sense of scale. These findings suggest that generative AI can support visualization and communication in the design process, while drawing- and model-based design reasoning remains important for spatial scale, circulation, and functional logic. Therefore, lighting design education should not treat AI-generated outputs as final results, but should guide learners to re-examine them through plans, sections, models, and diagrams and to connect them with their own design logic. |