A Study on Generative Design Reasoning and Students' Divergent and Convergent Thinking

Abstract

Computer-aided design (CAD) is a standard design tool used in engineering practice and by students. CAD has become increasingly analytic and inventive in incorporating AI approaches to design with generative design to help expand designers' divergent thinking. However, because generative design technologies are new, we know very little about generative design thinking in students. The purpose of this research is threefold: explore how students engage in the design process when using generative design software, understand the relationship between students' divergent and convergent thinking abilities, and investigate in what ways students' divergent and convergent abilities are related to their generative design understanding. This study was set in an introductory graphics and design course where student designers used Fusion 360. Data collected included a generative design CAD module and both divergent and convergent psychological tests. The results suggest that students approach generative design decision-making similarly to how beginning designers approach standard decision-making and that students' divergent and convergent thinking is not related to their generative design thinking. This study shows that new computational tools might present the same challenges to beginning designers as conventional tools. Instructors should be aware of informed design practices, should continue to encourage students to grow into informed designers by educating them on design practices without technology and, by introducing them to new technology such as AI-driven generative design.