Publikationsdatum:
2024-05-09
Beschreibung:
The diffusion of Building Information Modeling (BIM) and advanced visualization technologies in the increasingly digitalised construction sector is fostering the development and implementation of disruptive approaches for workforce Health and Safety (H&S) training. Project-specific risks, safety procedures and information can be administered through immersive Virtual Reality (VR) experiences where construction site environments and activities are reproduced without exposing the trainees to real hazards. However, despite numerous research and industry applications demonstrating the potential benefits of these technologies, a standardized framework and methodology for the evaluation of VR safety training effectiveness for construction workers is still lacking hence hindering its large scale-adoption and recognition from policymakers. Within the scope of previous authors contributions on the development and implementation of BIM-based VR experiences for construction workers’ safety training, this paper aims to address the evaluation of their effectiveness proposing a novel semi-qualitative approach based on the integration of trainees’ subjective and objective data. A post-experience evaluation questionnaire is developed to collect trainees’ direct and qualitative feedback about the experience immersivity and perceived safety content transfer. Furthermore, the integration with trainees’ spatial tracking data is proposed to complement the qualitative feedback with the quantitative evaluation of their use of the virtual space for safety training purposes. The application of the presented approach in case study is currently undergoing and the related results will be subject of future contributions
Schlagwort(e):
Virtual Reality (VR)
;
Construction worker
;
Safety training
;
Evaluation
;
Spatial tracking
;
Heatmap visualization
;
Survey
;
thema EDItEUR::U Computing and Information Technology::UT Computer networking and communications::UTV Virtualization
Sprache:
Englisch
Format:
image/jpeg
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