ETA-ESW DCL: Enhancing Hands-On Cleanroom Semiconductor Fabrication Education with AI-Assisted Extended Reality

This IUSE Level 1 Engaged Student Learning project aims to serve the national interest by addressing the significant demand for a semiconductor workforce. The project intends to leverage the emerging technology of extended reality (XR) and generative artificial intelligence (GAI) to develop innovative microfabrication cleanroom training. A planned outcome of this training is a supply of talent possessing specialized skills necessary to address technological advancements and supply chain challenges of the semiconductor industry.

The goal is to elevate and streamline the learning experience for undergraduates enrolled in semiconductor-related courses, equipping them with the essential skills for successful careers in the semiconductor industry, and to increase awareness and interest in the semiconductor field for more students at large. The cost-effective and immersive XR and GAI-enabled lab training will be accessible to a broad audience, including undergraduate and graduate students, post-doctoral fellows, adult learners, and cleanroom users.

Additional plans include training for local middle and high schools, and a partner HBCU to foster interest in semiconductor science and engineering. Efforts will focus on encouraging students from underrepresented groups to enroll and participate in the training activities.

The project will approach the following objectives: (1) create and refine an immersive learner-centered hands-on educational program that integrates cleanroom fabrication experiences using XR and GAI technology, (2) investigate the effectiveness and advance understanding of the education innovation through a comprehensive examination and multifaceted analysis, taking into account the knowledge and skills transfer, retention, and overall learning experiences of the target students; and (3) apply the research outcomes to form effective instructional principles and develop an instructional system, including participatory learning experience, multiple scaffolding levels, and triangulated assessment, for enhancing the semiconductor education curriculum as well as workforce and career pathway development. The project is designed to align with undergraduate course instruction on key semiconductor processes such as photolithography, etching, and deposition.

Goals will include introduction of innovative lab training incorporating virtual reality (VR) on portable headsets for immersive and flexible learning without relying on a cleanroom facility, while building a mixed reality (MR) program providing real-time guidance to reduce errors, shorten training time, and promote skill transfer in the cleanroom. The plan will involve use of VR and MR which utilize the latest XR technologies with eye tracking to enhance engagement and sensory experiences.

Project plans also include integration of generative AI for contextual learning, combining XR, GAI, and learner-centered activities into a comprehensive instructional design. Using constructionist approaches and design-based research, the project aims to bridge the skills gap in semiconductor education, preparing undergraduates for the semiconductor industry’s evolving challenges.

The NSF IUSE: EDU Program supports research and development projects to improve the effectiveness of STEM education for all students. Through the Engaged Student Learning track, the program supports the creation, exploration, and implementation of promising practices and tools.

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.