Motivation and Creativity in Generative AI-Assisted Architectural Design Education: A 16-Week Mixed-Methods Study

Authors

  • Jieli Feng Japan Advanced Institute of Science and Technology, Nomi, Ishikawa, Japan; Shanghai Urban Construction Drawing Review Consulting Co., Ltd, Shanghai, China; Shanghai Jiguang Polytechnic College, Shanghai, China
  • Weidong Li
  • Song Gao

Keywords:

Generative artificial intelligence, architectural design education, design studio, motivation, creativity, human–AI collaboration, CAAD

Abstract

Generative artificial intelligence (GenAI) is rapidly entering architectural design studios, yet empirical evidence regarding its effects on design students’ learning motivation, design experience, and creativity in authentic course settings remains limited. This paper reports a 16-week mixed-methods study of a GenAI-in tegrated architectural design studio. It examines how text-based and image-based generative tools were embedded in a CAAD-led design workflow and analyzes the relationships among student motivation, process experience, and expert-rated creativity. Forty-three second-year interior architecture students participated in the course; 25 provided valid preand post-test data and complete expert ratings. The study employed the COQ-CR, a survey of attitudes toward the design task, a questionnaire about designing, instructor-rated learning attitude, five external experts’ ratings of final projects on novelty, value, and unexpectedness, and semi-structured interviews with five students. Results showed significant increases in overall COQ-CR, general beliefs, and goal beliefs, and a significant improvement in instructor-rated learning attitude. Task attitudes and process perceptions did not show uniform significant change at the cohort level, but their individual changes were positively correlated with creativity scores. Baseline motivation was positively correlated with the value dimension and composite creativity. Interviews indicated that GenAI supported learning mainly by providing direction, reducing the burden of initiation, expanding the space of possibilities, and accelerating visual externalization, while also generating tensions around reliance, authorship, and tightened process self-assessment. The paper argues that the educational value of GenAI lies not in a uniform “tool effect” but in whether it is organized as a phased, CAAD-anchored, reflective design practice with differentiated scaf folding for students with different baseline motivational profiles.

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Published

2026-11-13

How to Cite

Feng, J., Li, W., & Gao, S. (2026). Motivation and Creativity in Generative AI-Assisted Architectural Design Education: A 16-Week Mixed-Methods Study. Art & Design Research, 7(3), 60–69. Retrieved from https://www.masonpublish.org/index.php/the-art-design-research/article/view/2236

Issue

Section

Articles (2026)

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