Augmented Reality (AR) tools have demonstrated considerable promise to enhance creative architectural design and support the retrofitting problem-solving processes through on-site daylighting visualization. AR’s capacity to integrate embodied motion enhances the non-expert’s understanding of the spatial characteristics and design ramifications within the built environment for complex facade design. Motion provides insights and increases the accessibility of retrofitting, encouraging more energy-efficient rework as opposed to complete building reconstruction. This study investigates the decision-making outcomes and cognitive-physical load implications of integrating a Building Information Modeling-driven AR system into the retrofitting design process and how movement is best leveraged to understand daylighting impacts. We conducted a study with 128 non-expert participants, who were asked to choose a window facade retrofit to improve an interior space. We analyze the effects of head movement, head rotations, and eye movements to understand how embodied motion improves overall objective performance across several daylighting and energy design metrics. We found no significant difference in the overall decision-making outcome between those who used an AR tool or a conventional desktop approach and that greater eye movement in AR was related to non-experts better balancing the complicated impacts facades have on daylight, aesthetics, and energy. This study indicates future expansion of AR retrofitting tools should encourage more eye movement.

Augmented Reality (AR) tools have shown significant potential in providing on-site visualization of Building Information Modeling (BIM) data and models for supporting construction evaluation, inspection, and guidance. Retrofitting existing buildings, however, remains a challenging task requiring more innovative solutions to successfully integrate AR and BIM. This study aims to investigate the impact of AR+BIM technology on the retrofitting training process and assess the potential for future on-site usage. We conducted a study with 64 non-expert participants, who were asked to perform a common retrofitting procedure of an electrical outlet installation using either an AR+BIM system or a standard printed blueprint documentation set. Our findings indicate that AR+BIM reduced task time significantly and improved performance consistency across participants, while also decreasing the physical and cognitive demands of the training. This study provides a foundation for augmenting future retrofitting construction research that can extend the use of [Formula: see text] technology, thus facilitating more efficient retrofitting of existing buildings. A video presentation of this article and all supplemental materials are available at https://github.com/DesignLabUCF/SENSEable_RetrofittingTraining.