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Mechanism Models of the Conventional and Advanced Methods of Construction Safety Training. Is the Traditional Method of Safety Training Sufficient?

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  • Aminu Darda’u Rafindadi

    (Department of Civil & Environmental Engineering, Universiti Teknologi PETRONAS, Seri Iskandar 32610, Malaysia
    Department of Civil Engineering, Faculty of Engineering, Bayero University, Kano P.M.B 3011, Nigeria)

  • Nasir Shafiq

    (Department of Civil & Environmental Engineering, Universiti Teknologi PETRONAS, Seri Iskandar 32610, Malaysia)

  • Idris Othman

    (Department of Civil & Environmental Engineering, Universiti Teknologi PETRONAS, Seri Iskandar 32610, Malaysia)

  • Miljan Mikić

    (Department of Engineering Management, Faculty of Engineering, University of Leeds, Leeds LS2 9JT, UK)

Abstract

Cognitive failures at the information acquiring (safety training), comprehension, or application stages led to near-miss or accidents on-site. The previous studies rarely considered the cognitive processes of two different kinds of construction safety training. Cognitive processes are a series of chemical and electrical brain impulses that allow you to perceive your surroundings and acquire knowledge. Additionally, their attention was more inclined toward the worker’s behavior during hazard identification on-site while on duty. A study is proposed to fill the knowledge gap by developing the mechanism models of the two safety training approaches. The mechanism models were developed based on cognitive psychology and Bloom’s taxonomy and six steps of cognitive learning theory. A worker’s safety training is vital in acquiring, storing, retrieving, and utilizing the appropriate information for hazard identification on-site. It is assumed that those trained by advanced techniques may quickly identify and avoid hazards on construction sites because of the fundamental nature of the training, and when they come across threats, they may promptly use their working memory and prevent them, especially for more complex projects. The main benefit of making such a model, from a cognitive point of view, is that it can help us learn more about the mental processes of two different types of construction safety training, and it can also help us come up with specific management suggestions to make up for the approaches’ flaws. Future research will concentrate on the organizational aspects and other cognitive failures that could lead to accidents.

Suggested Citation

  • Aminu Darda’u Rafindadi & Nasir Shafiq & Idris Othman & Miljan Mikić, 2023. "Mechanism Models of the Conventional and Advanced Methods of Construction Safety Training. Is the Traditional Method of Safety Training Sufficient?," IJERPH, MDPI, vol. 20(2), pages 1-19, January.
    • Handle: RePEc:gam:jijerp:v:20:y:2023:i:2:p:1466-:d:1034697
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    References listed on IDEAS

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    1. Chang, Y.H.J. & Mosleh, A., 2007. "Cognitive modeling and dynamic probabilistic simulation of operating crew response to complex system accidents," Reliability Engineering and System Safety, Elsevier, vol. 92(8), pages 1041-1060.
    2. Gui Ye & Hongzhe Yue & Jingjing Yang & Hongyang Li & Qingting Xiang & Yuan Fu & Can Cui, 2020. "Understanding the Sociocognitive Process of Construction Workers’ Unsafe Behaviors: An Agent-Based Modeling Approach," IJERPH, MDPI, vol. 17(5), pages 1-33, March.
    3. Mengchun Zhang & Dongping Fang, 2013. "A cognitive analysis of why Chinese scaffolders do not use safety harnesses in construction," Construction Management and Economics, Taylor & Francis Journals, vol. 31(3), pages 207-222, March.
    4. Bougie, J.R.G. & Pieters, R. & Zeelenberg, M., 2003. "Angry customers don't come back, they get back : The experience and behavioral implications of anger and dissatisfaction in services," Other publications TiSEM 1708fb71-fd68-41d9-b870-e, Tilburg University, School of Economics and Management.
    5. S M Jamil Uddin & Alex Albert & Abdullah Alsharef & Bhavana Pandit & Yashwardhan Patil & Chukwuma Nnaji, 2020. "Hazard Recognition Patterns Demonstrated by Construction Workers," IJERPH, MDPI, vol. 17(21), pages 1-14, October.
    6. Chang, Y.H.J. & Mosleh, A., 2007. "Cognitive modeling and dynamic probabilistic simulation of operating crew response to complex system accidents. Part 2: IDAC performance influencing factors model," Reliability Engineering and System Safety, Elsevier, vol. 92(8), pages 1014-1040.
    7. Chang, Y.H.J. & Mosleh, A., 2007. "Cognitive modeling and dynamic probabilistic simulation of operating crew response to complex system accidents. Part 4: IDAC causal model of operator problem-solving response," Reliability Engineering and System Safety, Elsevier, vol. 92(8), pages 1061-1075.
    8. Chang, Y.H.J. & Mosleh, A., 2007. "Cognitive modeling and dynamic probabilistic simulation of operating crew response to complex system accidents," Reliability Engineering and System Safety, Elsevier, vol. 92(8), pages 997-1013.
    9. Aminu Darda’u Rafindadi & Nasir Shafiq & Idris Othman, 2022. "A Conceptual Framework for BIM Process Flow to Mitigate the Causes of Fall-Related Accidents at the Design Stage," Sustainability, MDPI, vol. 14(20), pages 1-37, October.
    10. Chang, Y.H.J. & Mosleh, A., 2007. "Cognitive modeling and dynamic probabilistic simulation of operating crew response to complex system accidents," Reliability Engineering and System Safety, Elsevier, vol. 92(8), pages 1076-1101.
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