Virtual reality (VR) has emerged as a transformative technology for training and education, providing immersive environments that simulate real-world scenarios for workforce training in high-stakes domains such as healthcare, aviation, and manufacturing. Effective VR training requires effective management of cognitive load and situation awareness (SA), which supports decision-making. The interplay between cognitive load and SA is particularly notable in VR training environments. Despite significant research on VR-based training, a comprehensive understanding of their bidirectional relationship remains limited. This study aims to address this gap by analyzing prior research on SA and cognitive load in VR training environments, identifying design principles that optimize both constructs, and providing actionable recommendations for adaptive VR training systems. Studies demonstrate that SA and cognitive load have a reciprocal relationship. Findings also reveal that task complexity and multimodal cues substantially influence both constructs. Proper task design and adaptive VR systems informed by real-time physiological measurements are necessary to optimize training outcomes. This study identifies design principles to minimize extraneous cognitive load, balance intrinsic demands, and strengthen SA, offering recommendations for creating VR training systems that align with human cognitive and perceptual capacities. The findings aim to guide the development of more effective, user-centered VR training environments.
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