An Examination Of Students’ Perceptions Of The Efficacy Of Using Generative Artificial Intelligence In Structural Engineering Education

Abstract

With the rapid advancement of Generative Artificial Intelligence (GenAI) tools like ChatGPT, their integration into education introduces both opportunities and challenges for students and educators. This study examines Gen Z students’ perceptions of the efficacy of GenAI in structural engineering education. The integration of GenAI tools has the potential to transform how students approach complex engineering problems, yet understanding their perceived value and limitations remains underexplored. The research adopts a mixed-methods approach, centred on a targeted exercise where students complete a series of structural analysis problems using both traditional hand calculations and GenAI. Data collected through pre- and post-exercise surveys, alongside reflective critiques, provided insights into how students' perceptions evolved throughout the exercise. Students reported GenAI to be effective in solving questions related to basic stability and determinacy but, while they found GenAI helpful in explaining procedures, it generally was unable to accurately solve more complicated deflected shape and beam analysis questions. There was a statistically significant increase in students’ perceptions of the efficacy of GenAI to solve stability and determinacy questions following the completion of the exercise, but not in relation deflected shape or beam analysis questions. These findings highlight the importance for students to have a strong foundational structural analysis understanding to effectively evaluate and validate GenAI outputs.