A proposed quantitative methodology for the evaluation of the effectiveness of Human Element, Leadership and Management (HELM) training in the UK

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• 作者：F. Saeed ; A. Wall ; C. Roberts ; R. Riahi ; A. Bury
• 关键词：Non ; technical skills ; Human element ; Leadership ; Management ; Evidential reasoning ; Analytical hierarchy process
• 刊名：WMU Journal of Maritime Affairs
• 出版年：2017
• 出版时间：January 2017
• 年：2017
• 卷：16
• 期：1
• 页码：115-138
• 全文大小：514KB
• 刊物主题：Public International Law; Environmental Law/Policy/Ecojustice; Marine & Freshwater Sciences; Offshore Engineering;
• 出版者：Springer Berlin Heidelberg
• ISSN：1654-1642
• 卷排序：16

文摘

In 2006, a review of maritime accidents found that non-technical skills (NTSs) are the single largest contributing factor towards such incidents. NTSs are composed of both interpersonal and cognitive elements. These include things such as situational awareness, teamwork, decision making, leadership, management and communication skills. In a crisis situation, good NTSs allow a deck officer to quickly recognise that a problem exists and then harness the resources that are at their disposal to safely and efficiently bring the situation back under control. This paper has two aims. The first is to develop a methodology which will enable educators to quantitatively assess the impact of Maritime and Coastguard Agency (MCA)-approved Human Element, Leadership and Management (HELM) training on deck officer’s NTSs with a view to identifying further training requirements. The second is to determine whether the HELM training provided to develop the NTSs of trainee deck officers is fit for purpose. To achieve these aims, a three-phase approach was adopted. Initially, a taxonomy for deck officer’s NTSs is established, behavioural markers are identified and the relative importance of each attribute is calculated using the analytical hierarchy process (AHP). Subsequently, a set of scenarios were identified for the assessment of deck officer’s NTSs in a ship bridge simulator environment. A random selection of students that have completed the Chief Mate (CM) programme was performed, and data regarding their NTS-related performance in the scenarios was collected. Finally, the collected data was fed into the evidential reasoning (ER) algorithm, utility values were produced and, having established these values, the effectiveness of the HELM training that the students have received was then evaluated.