<p>Technical and Vocational Education and Training (TVET) programs require reliable methods to teach and assess performance-based skills in authentic contexts. Immersive platforms such as the metaverse offer promising environments for simulating real-world tasks and providing scalable training opportunities. In these technology-rich settings, stealth assessment is recognized as a psychometrically sound and theoretically grounded approach. However, its application has been largely confined to video games and primarily in contexts emphasizing creativity and collaboration. This study broadens that scope by embedding stealth assessment within a metaverse environment to develop and evaluate technical competencies in PC building. Guided by evidence-centered design, a two-part investigation examined (1) the suitability of stealth assessment in a metaverse context and (2) the effectiveness of metaverse-based training in improving learning outcomes and facilitating skill transfer. Undergraduate students from computing and engineering programs engaged in structured PC-building scenarios within the metaverse, where their performance was tracked through automated event logs, validated against expert evaluations, and analyzed using inferential statistical methods. Results indicate that embedding stealth assessment in the metaverse enabled reliable and unobtrusive evaluation of learners’ technical competencies. Metaverse-based PC-building training yielded higher learning gains than traditional methods, and learners demonstrated the ability to transfer skills from virtual tasks to physical PC-building. Overall, these findings offer evidence-informed insights for educators, researchers, and policymakers on integrating immersive technologies and embedded assessments in technical education and vocational training.</p>