NSF Award
2417102
This project aims to serve the national interest by significantly advancing the understanding of the impact of Generative AI on Architectural Engineering students’ ability to generate visual ideas. Architectural Engineering (AE), the application of engineering principles to the design and construction of buildings, relies heavily on visual communication between engineers, architects, and design critics as they work collaboratively on the design of buildings. Practitioners of AE engage in visual ideation as well as visual representation. Emergent technologies such as Generative AI (GenAI) and Augmented Reality (AR) hold great promise to enhance and improve students' visual ideation skills. These technologies permit the use of conversational prompts for quick visual ideation of abstract design ideas. Once designs have been conceptualized, the tools can be used to display immersive 3D models in an engaging manner to all members of the design team. Through these investigations in AE, significant lessons learned will likely inform design in other engineering fields.<br/><br/>The goal of the project is to understand the impact of GenAI-empowered AR (GenAI-AR) combined with multi-user AR on students' collaborative learning in AE design. The PIs plan to develop two GenAI-AR modules for integration into existing AE design studio curricula. Three research questions are posited to guide the investigations designed to enhance understanding of visual thinking and communication during students’ collaborative learning in AE design. An interventional study will be conducted, where the comparison will be between a “control group” as the baseline in one year and two “experimental groups” in the following two years. A mixed method approach involving semi-structured group interviews will be used to elicit answers to questions regarding impact of the intervention on student engagement, self-efficacy and teamwork skills. A qualified evaluator will ensure that impact is assessed in the context of project goals in a way that lays the foundation for scaling up the intervention in future. Robust and comprehensive dissemination plans will exploit an open-source approach, with Unity modules arising from the effort available on GitHub to facilitate easy modification and adaptation for a range of design situations. The NSF IUSE: EHR Program supports research and development projects to improve the effectiveness of STEM education for all students. Through its Engaged Student Learning track, the program supports the creation, exploration, and implementation of promising practices and tools.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
