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Replication data for: "Which simulator to use for maritime education and training? - An assessment using multi-criteria decision-making methods"

posted on 2022-12-01, 00:10 authored by Hasan Mahbub TusherHasan Mahbub Tusher

Description of data:

The data files include preliminary survey responses from simulator experts to be used in combination with data scripts from MATLAB using JAGS for Best-Worst Method (Mohammadi & Rezaei, 2020). In this study, we investigated different types of maritime simulators and assessed their suitability of use based on 13 identified criteria.


Simulators have been an integral part of maritime education and training (MET). It has been implemented in different levels of seafarer training as mandated by both local and international regulations. State-of-the-art simulator technologies have evolved over the years making it possible to train in different modalities, i.e., in full-mission, desktop-based, cloud-based and virtual reality (VR) simulators. However, selecting an ideal type of simulator for the varying maritime training needs is a daunting task for the instructors, decision-makers in the institutions. This study adopts a hybrid multi-criteria decision-making approach to identify the most appropriate type of simulator based on training needs. The Bayesian Best-Worst Method is utilized to rank the 13 identified criteria that influence use of simulators in MET. The criteria weights from the ranking are then used to rank and assess the four types of simulators using the Preference Ranking Organization Method for Enrichment Evaluation (PROMETHEE). The results reveal that the full-mission simulators are the most preferable solution followed by VR simulators, cloud-based and desktop simulators considering the aggregated weight of identified criteria. In addition, regulatory compliance was identified as the most significant criterion while the cost of simulators remains the least significant consideration in the context of maritime simulator training. 


The Directorate for Internationalisation and Quality Development in Higher Education (HK-dir). Project code: SFU/10021-COAST