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Enhancing Safety Training Performance Using Extended Reality: A Hybrid Delphi–AHP Multi-Attribute Analysis in a Type-2 Fuzzy Environment

Author(s): ORCID
ORCID



Medium: journal article
Language(s): English
Published in: Buildings, , n. 3, v. 13
Page(s): 625
DOI: 10.3390/buildings13030625
Abstract:

Safety training effectively addresses the inexperience of and lack of knowledge among construction workers, which are some of the most significant contributors to workplace accidents on construction sites. This paper aims to understand the effectiveness of different extended reality (XR) technologies in imparting important construction safety training to construction workers in a virtual environment compared to conventional classroom training sessions. A group of experts were engaged to understand the most effective learning criteria and the impact of XR visualizations, and their responses were analysed using the interval type-2 fuzzy Delphi (IT2FD) method. Following this, a cohort of engineering students were subjected to construction safety training in traditional, augmented reality (AR) and virtual reality (VR) environments. Their feedback was collected using an online questionnaire and the responses were analysed using the interval type-2 fuzzy analytic hierarchy process (IT2F–AHP). The results revealed that addressing the virtual interface design of the training to maintain the attention of trainees and ensuring the virtual environment’s resemblance to the actual site and task were the most important factors in ensuring effective knowledge retention by the trainees. AR visualizations were most effective at imparting knowledge, and their interactive nature allowed trainees to retain the learned knowledge.

Copyright: © 2023 by the authors; licensee MDPI, Basel, Switzerland.
License:

This creative work has been published under the Creative Commons Attribution 4.0 International (CC-BY 4.0) license which allows copying, and redistribution as well as adaptation of the original work provided appropriate credit is given to the original author and the conditions of the license are met.

  • About this
    data sheet
  • Reference-ID
    10712490
  • Published on:
    21/03/2023
  • Last updated on:
    10/05/2023
 
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