Study Architecture 
ProPEL 
Author(s): Eric Peterson, Shahin Vassigh & Biayna Bogosian
Technological advancements in robotics and automation are poised to disrupt the Architecture, Engineering, and Construction (AEC) industry sector but robotics training within these fields has historically faced issues of high cost, limited accessibility, and narrow demographic representation. Architecture students are typically at a disadvantage compared to their peers in engineering disciplines due to a historic and ongoing lack of access to robotic tools and established training opportunities tailored to their educational needs. Women and minority students often face even greater obstacles to access due to the scarcity of robotics training options in a male-dominated field that tends to lack diversity. This paper examines how emerging artificial intelligence (AI) and immersive technologies can help to transform robotics education to be more equitable, adaptive, and scaable. It begins by outlining current limitations in traditional training methods, which rely on in-person workshops with proprietary systems. Next, it explores the educational affordances and ethical risks of incorporating AI for personalized learning. The paper then discusses how virtual reality (VR) and augmented reality (AR) can be employed to create more accessible and engaging robotics curricula, underscoring that these same advanced technologies may also introduce potential biases if training data is not sufficiently diverse. The paper describes ongoing initiatives by an interdisciplinary research team led by architecture faculty at a coalition of public majority-minority research universities to help improve access to training and representation in the field of robotics. It describes three projects funded by the National Science Foundation that leverage VR, AR, and AI to create a more inclusive robotics training tailored for learners from multicultural and minoritized backgrounds. These projects collect learner data and real-time performance metrics to support the design of adaptive learning systems that can enhance learning outcomes for a diverse pool of learners. The paper addresses the pressing imperative to re-envision existing technical training models by leveraging AI and immersive technologies to foster enhanced representation and improve access to robotics education.
https://doi.org/10.35483/ACSA.AM.113.65
Volume Editors
Sara Jensen Carr & Rubén García Rubio
ISBN
978-1-944214-48-7
