Pivots: Immersive Experiential Training for Robotic Additive Manufacturing in Construction

This project aims to serve the national interest by developing a skilled workforce capable of deploying robotic additive manufacturing in the construction industry—an emerging technology that is critical for increasing productivity and addressing persistent labor shortages in infrastructure development. Additive manufacturing in construction, commonly known as 3D printing, utilizes robotics and advanced materials to fabricate building components and, in some cases, entire structures. Despite its growing relevance, current construction professionals and tradespeople rarely have opportunities to gain hands-on experience with these advanced technologies. To bridge this gap, the project will implement an immersive experiential training program that enables experienced workers to pivot into careers in construction automation and advanced manufacturing. Participants will gain practical knowledge in robotic 3D printing technology, including equipment operation, safety procedures, design for additive manufacturing, and quality control of printed construction elements. Through partnerships with construction firms, robotic printer manufacturers, labor unions, and workforce development agencies, the project will support national efforts to modernize the construction workforce, broaden participation in STEM fields, and accelerate the adoption of emerging technologies in the built environment. The project will develop and evaluate the Robotic Additive Manufacturing Experiential Immersive Learning (RAMEIL) platform, a web-based immersive training environment enhanced with artificial intelligence to support personalized learning. A nationwide needs assessment will identify the critical competencies required for robotic 3D printing in construction, including calibration, material handling, and jobsite safety. These findings will inform the development of interactive, immersive modules grounded in experiential learning and cognitive apprenticeship frameworks. The platform will feature real-time performance tracking and adaptive feedback to support individualized progression. Upon completing the immersive component, participants will engage in a two-week, hands-on lab training using educational 3D printing equipment, followed by a four-week micro-internship with partnering industry firms. By integrating classroom instruction, immersive virtual training, laboratory practice, and real-world industry experience, the project offers a comprehensive pathway for upskilling the construction workforce in advanced manufacturing techniques. The research team will employ a mixed-methods evaluation strategy—combining pre- and post-assessments, usability testing, and field performance metrics—to evaluate learning outcomes and job readiness. Through the integration of theoretical instruction and applied practice, the project aims to advance scalable, data-driven training strategies for reskilling professionals in automation-intensive sectors. Close collaboration with major construction companies (including general contractors and technology suppliers) and local trade organizations will ensure the training remains responsive to industry needs and that successful participants have clear pathways to employment in emerging roles such as robotic construction machine operators and additive manufacturing specialists. Ultimately, the project will contribute to evidence-based training models that support career transitions into emerging technology fields and enhance the nation’s capacity for innovation in construction. The ExLENT Program, supported by the NSF TIP and EDU Directorates, seeks to support experiential learning opportunities for individuals to increase their interest in and access to career pathways in emerging technology fields. 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.