## 7 Discussion
This feature reduced the advantage that seasoned practitioners might have in handling large quantities of information compared to inexperienced participants [60], thereby equalizing the conditions for both types of participants in completing the task. Notably, construction sites introduce additional challenges beyond those addressed in the conducted task, such as increased task complexity, time pressure, and other factors that may increase practitioners' cognitive load and could compromise the level of SA achieved through AR/MR systems. However, the proposed method is designed to adapt to more complex tasks than the one employed in the practical case, as it uses SA-oriented design principles specifically intended for complex and dynamic environments such as construction. These principles aim to reduce perceptual overload and increase SA in such scenarios. Moreover, the proposed method adjusts the interface design based on the goal/task to address. In this regard, more complex tasks would require more tailored design concepts, a process that is systematically supported by the method. Additionally, in real on-site scenarios, practitioners are typically familiar with the project context, which can lead to more internalized information requirements and potentially higher SA. In this context, it is expected that system interfaces designed through the proposed method can achieve SA levels comparable to, or even exceeding, those reported in this study, even under complex field conditions. Overall, the practical case provided valuable evidence of the applicability and utility of the method in effectively enabling SA within AR and MR environments. The results not only validate the method's approach, but also provide insights for improving the immersive interface design to better support cognitive performance in complex and dynamic decision-making contexts. This study contributes to a body of knowledge where the AR/MR interface design advanced along two complementary yet often disconnected research areas: SA and IA. SA research addresses the user's cognitive needs (what information is required) for designing system interfaces. For instance, [PERSON] et al. [61] proposed a dynamic spatial information design framework that combines SA theory with the skill, rule, knowledge taxonomy, and a cognitive-centric guide for interface and system design, to develop an AR head-up display that improved drivers' SA and hazard response. On the other hand, IA research focuses on how to present information in immersive environments, as exemplified by the study of [PERSON] et al. [62], which identified ten common design patterns for situated visualization in AR and provided design guidelines for implementation. In contrast to these approaches, the present study introduces a unified structured method that integrates both SA and IA. The method aligns what information to present with how to present it to ensure that interface design is grounded in the user's cognitive needs, leading to more effective AR/MR decision support systems for complex and dynamic environments, such as construction. Moreover, the method incorporates key human-computer interaction (HCI) principles, including designing interfaces that are intuitive to use, responsive to user interaction, and iteratively improved through user feedback [63]. In this regard, the proposed method advances not only SA and IA research, but also represents a contribution to HCI practice in immersive contexts.