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Saeed, F, Bury, A, Bonsall, S and Riahi, R (2018) A proposed Evidential Reasoning (ER) Methodology for Quantitative Assessment of Non-Technical Skills (NTS) Amongst Merchant Navy Deck Officers in a Ship’s Bridge Simulator Environment. TransNav, the International Journal on Marine Navigation and Safety of Sea Transportation, 12 (3). ISSN 2083-6473
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A proposed Evidential Reasoning (ER) Methodology for Quantitative Assessment of Non-Technical Skills (NTS) Amongst Merchant Navy Deck Officers in a Ship's Bridge S.pdf - Published Version Download (610kB) | Preview |
Abstract
Ship’s bridge simulators are very popular in the worldwide training and assessment of merchant navy deck officers. The examiners of simulator courses presently do not have a method to quantitatively assess the performance of a group or an individual. Some examiners use checklists and others use their gut feeling to grade competence. In this paper a novel methodology is established that uses the Evidential Reasoning algorithm to quantitatively assess the Non‐Technical Skills (NTS) of merchant navy officers. To begin with, interviews were conducted with experienced deck officers to develop the taxonomy and behavioural markers that would be used in the assessment process. A random selection of students studying towards their Chief Officer’s Certificate of Competency were recruited to have their NTS to be observed in a ship’s bridge simulator. The participant’s behaviour was rated against five criteria and the subsequent data was entered into the Evidential Reasoning algorithm to produce a crisp number. The results that were generated demonstrate that this approach provides a reliable method to quantitatively assess the NTS performance of merchant navy officers in a simulated bridge environment.
| Item Type: | Article |
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| Subjects: | T Technology > T Technology (General) V Naval Science > V Naval Science (General) |
| Divisions: | Maritime & Mechanical Engineering (merged with Engineering 10 Aug 20) |
| Publisher: | Faculty of Navigation |
| Date Deposited: | 29 Apr 2019 09:06 |
| Last Modified: | 04 Sep 2021 01:50 |
| DOI or ID number: | 10.12716/1001.12.03.20 |
| URI: | https://researchonline.ljmu.ac.uk/id/eprint/10601 |
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