This study examines the effectiveness of game-based learning in enhancing hazard identification skills. The research employed a mixed-methods approach, combining quantitative analysis of participants’ hazard identification performance and eye-tracking data with qualitative insights from participant feedback. In a simulated study, participants were asked to identify hazards following the game-based training intervention. The Hazard Identification Index (HII) scores increased significantly (p < 0.0001) in the post-training trials, indicating enhanced hazard recognition abilities. The analysis of eye-tracking data revealed changes in participants’ attention allocation patterns in the post-training trials. Furthermore, the study highlights the importance of minimizing task interruptions during hazard identification activities, as interruptions negatively impacted participants’ performance. The findings of this study have significant implications for training programs focused on workplace safety. Integrating game-based learning in safety training programs can help employers enhance hazard identification skills among their employees, ultimately contributing to safer work environments and reducing incidents of accidents and injuries.

Mixed-reality (MR) technology has been widely used to simulate high-risk workplaces in order to minimize safety concerns. However, its use in understanding worker attentional allocation during interactions with drones in future construction environments remains underexplored. This study developed a futuristic bricklaying MR environment, where human-drone interaction was mandatory, to capture participants’ naturalistic behaviors (i.e., attention, productivity, and distraction) across different interaction levels (i.e., no interaction, coexistence, and collaboration). The core research question explored whether workers maintained situational awareness of the drones or were distracted by them. The results confirmed that participants experienced a high sense of presence in the MR environment, driven by the use of environmental modalities, passive haptics, and drones’ sounds and spinning blades. Moreover, the findings demonstrated that participants were distracted by the drones during coexistence, as evidenced by lower productivity and reflections indicating they felt they were over-allocating attention to the drones. Conversely, participants exhibited situational awareness of the drones during collaboration, deliberately allocating attention to ensure safety, despite a reduction in productivity. These findings highlight the value of immersive technology in investigating workers’ naturalistic behaviors in future construction scenarios where workers and robots must function as teammates.

Drawing on social influence and behavioral intention theories, coworkers' risk-taking serves as an "extra motive" -an exogenous factor-for risk-taking behaviors among workers in the workplace. Social influence theories have shown that social factors, such as social pressure and coworker risk-taking, may predict risk-taking behaviors and significantly affect decision-making. While immersive technologies have been widely used to create close-to-real simulations for construction safety-related studies, there is a paucity of research considering the impact of social presence in evaluating workers' risk decision-making within immersive environments. To bridge this gap, this study developed a state-of-the-art Augmented Virtuality (AV) environment to investigate roofers' risk-taking behaviors when exposed to social stressors (working alongside a safe/unsafe peer). In this augmented virtuality environment, a virtual peer with safe and unsafe behaviors was simulated in order to impose peer pressure and increase participants' sense of social presence. Participants were asked to install asphalt shingles on a physical section of a roof (passive haptics) while the rest of the environment was projected virtually. During shingle installation, participants' cognitive and behavioral responses were captured using psychophysiological wearable technologies and self-report measures. The results demonstrated that the developed AV model could successfully enhance participants' sense of presence and social presence while serving as an appropriate platform for assessing individuals' decision-making orientations and behavioral changes in the presence of social stressors. Such information shows the value of immersive technologies to examine the naturalistic responses of individuals without exposing them to actual risks.

Immersive environments have been successfully applied to a broad range of safety training in high-risk domains. However, very little research has used these systems to evaluate the risk-taking behavior of construction workers. In this study, we investigated the feasibility and usefulness of providing passive haptics in a mixed-reality environment to capture the risk-taking behavior of workers, identify at-risk workers, and propose injury-prevention interventions to counteract excessive risk-taking and risk-compensatory behavior. Within a mixed-reality environment in a CAVE-like display system, our subjects installed shingles on a (physical) sloped roof of a (virtual) two-story residential building on a morning in a suburban area. Through this controlled, within-subject experimental design, we exposed each subject to three experimental conditions by manipulating the level of safety intervention. Workers' subjective reports, physiological signals, psychophysical responses, and reactionary behaviors were then considered as promising measures of Presence. The results showed that our mixed-reality environment was a suitable platform for triggering behavioral changes under different experimental conditions and for evaluating the risk perception and risk-taking behavior of workers in a risk-free setting. These results demonstrated the value of immersive technology to investigate natural human factors.