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Lookup NU author(s): Dr Jevon Chan, Dr Kayvan PazoukiORCiD, Dr Rosemary NormanORCiD, Dr David GolightlyORCiD
This work is licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0).
The maritime industry is rapidly advancing toward the initial stages of the digitised era of shipping, characterised by considerable advances in maritime autonomous technology in recent times. This study examines the effectiveness of training packages and the impact of rank during the failure of a sophisticated autopilot control system. For this study, the fault recognition and diagnostic skills of 60 navigational seafarers conducting a navigational watch in a full mission bridge watchkeeping simulator were analysed. Participants had either significant experience as qualified navigational officers of the watch or were navigational officers of the watch cadets with 12 months’ watchkeeping experience. These groups were subdivided into those who were given a training package focused on behavioural aspects of managing automation, such as maintaining situational awareness, and those given a technical training package. The findings were analysed using an Event Tree Analysis method to assess the participants’ performance in diagnosing a navigation fault. Additionally, the fault recognition skills were assessed between groups of training and rank. The study found that participants who received the behavioural training were more successful in both recognising and diagnosing the fault during the exercise. Behavioural training groups outperformed technical training groups, even when technical training participants were experienced seafarers. This difference in performance occurred without any apparent differences in workload or secondary task performance. Understanding the data gathered from the study could lead to the development of future training regimes for navigational officers of the watch and help to optimise the evolution of the seafaring role.
Author(s): Chan JP, Pazouki K, Norman R, Golightly D
Publication type: Article
Publication status: Published
Journal: Journal of Marine Science and Engineering
Year: 2025
Volume: 13
Issue: 4
Print publication date: 20/04/2025
Online publication date: 20/04/2025
Acceptance date: 18/04/2025
Date deposited: 22/04/2025
ISSN (electronic): 2077-1312
Publisher: MDPI
URL: https://doi.org/10.3390/jmse13040818
DOI: 10.3390/jmse13040818
Data Access Statement: The original contributions presented in this study are included in the article. Further inquiries can be directed to the corresponding author
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