An open-access curriculum for teaching generative design methodologies and thinking

Generative artificial intelligence (AI) algorithms are increasingly used during engineering design in academic and industrial settings. The Generative Design (GD) paradigm is characterized by the use of these algorithms to drive design exploration, after a user defines objectives and constraints. However, few undergraduate engineering curricula currently introduce GD. Furthermore, GD represents a paradigm shift from Traditional Design (TD) and Parametric Design (PD), in which human designers drive design exploration. To master GD, students must learn novel methodologies and ways of design thinking. Simply learning to operate GD tools is insufficient. To address this gap, we present the Educating Designers for Generative Engineering (EDGE) curriculum, which introduces methodologies and ways of design thinking associated with TD, PD, and GD. Our curriculum includes an open-ended design problem (OEDP), which students solve once within each paradigm and once more using any paradigm(s) of their choice. In this study, four undergraduate engineering students completed the curriculum and the four OEDPs. Analysis of their design process data suggests that students (1) used distinct solution methodologies when solving the TD/PD/GD OEDPs, (2) employed methodologies from multiple paradigms when solving the final OEDP, and (3) developed differing strategies for interacting with the GD algorithm.