2026 ASEE Annual Conference & Exposition

Virtualizing the Cleanroom: An Investigation into Learner Outcomes, Usability, and Technology Acceptance in Immersive Semiconductor Training

Presented at Computers in Education (CoED): Computing Pedagogy & Methods (5 of 8) -- T408B

Semiconductor manufacturing training is often constrained by high equipment costs, hazardous materials, and limited access to cleanroom facilities. To address these challenges, this study investigates the efficacy of a standalone immersive Virtual Reality (VR) training system designed to support photolithography instruction. Using a single-group pre- and post-test experimental design with 10 electrical engineering students, the study evaluated within-subject changes in conceptual knowledge and self-efficacy while examining technology acceptance and usability. Results indicated that the VR intervention yielded significant improvements in both knowledge (p < .001, d = 1.86) and self-efficacy (p < .05, d = 0.77), positioning the system as a valid environment for procedural skill acquisition. Furthermore, regression analysis supported the Technology Acceptance Model (TAM), revealing that Perceived Ease of Use significantly predicted Perceived Usefulness (R2 = .895). However, findings also highlighted a significant negative correlation between cognitive load and system usability (r = -.85), suggesting that high mental workload can diminish user acceptance and sense of agency. These findings suggest that while VR is a powerful tool for specialized engineering education, instructional designers must prioritize interaction simplicity and cognitive load management to ensure technology acceptance and learning effectiveness.

Authors
  1. Yuanyuan Gu University of Missouri - Columbia
  2. Xinhao Xu Orcid 16x16http://orcid.org/0000-0002-4981-4641 University of Missouri - Columbia
  3. Shangman Li University of Missouri - Columbia
  4. YUPEI DUAN Orcid 16x16http://orcid.org/0009-0008-8268-8107 University of Missouri - Columbia
  5. Olivia Kaye Franken University of Missouri - Columbia
  6. Donghan Fu University of Missouri - Columbia
  7. Mohammed Almalaysha University of Missouri - Columbia
  8. Mahmoud Almasri University of Missouri - Columbia
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