## 8 Conclusions  
This study proposed a method for designing AR/MR interfaces that effectively enable SA to support decision-making in construction environments. The method organizesknowledge, techniques, and design considerations from the SA and IA frameworks to assist designers in presenting information to increase practitioners' perception and comprehension of the situation, enhancing the projection of its future status, thereby supporting more informed decision-making. The method was applied and evaluated in a practical case. Participants achieved high SA levels with both AR and MR interfaces: 100% vs. 93% for level 2 SA (comprehension of the current situation) and 71% vs. 86% for level 3 SA (projection of future status). [PERSON]'s exact tests confirmed no statistically significant differences between AR and MR environments (all \(p\)-values > 0.05). These results demonstrate that interfaces designed using the proposed method effectively support high SA in both immersive environments. Regarding practical implications, the proposed method provides a structured approach for designing immersive interfaces. It enables designers to create AR/MR interfaces that increase SA in complex decision-making environments, where cognitive overload and timely decisions are critical. The method addresses this complexity by first formalizing the information required for decision-making and then systematically translating these user needs into intuitive, traceable, and actionable design specifications for developers. Moreover, the method is useful in scenarios where formal design guidance is lacking by providing designers and researchers with a replicable workflow that can be applied across diverse projects. Likewise, developers can use the design matrix to understand the rationale behind the interface designs, thereby guiding development efforts. Although the method was focused on construction, it is readily applicable across various disciplines. The structured nature of the method allows construction practitioners and general users to explore its different phases, including requirement analysis, technology analysis, design conceptualization, and practical applications and outcomes, to critically evaluate the capacity of AR/MR solutions to support SA. It is important to recognize the limitations of the study. The practical application focused on a single goal/task. Therefore, it is possible that more complex goals could lead to significant differences in the SA achieved between AR and MR designs, as well as between students and practitioners. Future research can apply the proposed method to develop AR and MR solutions for a broader range of goals to confirm or complement the results of this study. Likewise, this study used only SAGAT to evaluate the interface effectiveness. Measures such as usability heuristics or workload assessment are also valuable for that purpose; however, this study primarily focused on presenting a novel AR/MR interface design method for supporting SA. Moreover, the developed interfaces were proof-of-concept prototypes aimed to demonstrate the potential of the method. In this regard, other assessments beyond SA fall outside the scope of the study and may not provide meaningful insights due to the preliminary nature of the prototypes. Future work could include complementary assessment methods to provide a more comprehensive evaluation and obtain additional insights into interface effectiveness. Finally, the study did not compare the developed interface prototypes against a control condition. At the time of the study, there was no widely accepted baseline method specifically tailored for promoting SA in AR/MR environments, making it difficult to establish an adequate comparison. Moreover, this study aimed to demonstrate the feasibility and theoretical foundation of the method, rather than conduct a broad comparative analysis. Implementing meaningful control conditions would require significant additional resources and development, falling outside the scope and purpose of the study.