Ship collision is a form of maritime accident that possess great threats to transportation safety, economy, and human lives. Deck watchkeeping officers who oversee the safe navigation of the ships are responsible for preventing these collision accidents. Yet, most of the collisions are directly linked to the human errors onboard. One way to reduce these human errors is to train competent navigation officers for collision avoidance situations. However, training maritime students for complex collision situations is a challenging task. This study aims to examine if game-based learning (GBL) can help students to perform better in collision avoidance situations by providing them the necessary skills to properly identify risks, goals, and cues in collision situations. With this purpose, we developed a digital game-based decision-making training containing eight collisions at sea scenarios. The developed tool was then presented to maritime engineering students as supplementary training.Thirty undergraduate maritime transportation engineering students participated in the study. A pretest/posttest control group design was adopted to investigate the effects of GBL. Tests are conducted with the use of a full mission bridge simulator. Observed changes in situational awareness, decision making, navigation, and collision avoidance performance of the participants were analyzed. The results showed that the intervention group had small but significant improvements in all dimensions compared to the control group. Overall, the game-based decision-making training helped students to reach a better understanding of the related course material. Required efforts and challenges to develop and incorporate such training into the existing maritime curriculum are discussed.
Seafarers should be educated and trained according the conditions they face on board. An improved training method should be adopted. This way, the future officers will be qualified to intervene in emergency situations.
Marine mucilage or sea snot is one of the intensely seen environmental problems that increase with the global warming and pollution. In recent years, marine mucilage that especially occurs in inland seas and gulfs has increased both in incidence and intensity in Turkish seas. In this context, this study aims to provide benefits to researchers who will work in this field by analyzing the literature on marine mucilage. A total of 108 academic publications indexed on "Web of Science" database on marine mucilage were analyzed by text mining and bibliometric analyzes using the Vosviewer 1.6.17 program. Analysis results about authors, institutions, and countries of the authors, keywords, citations, abstracts, and regions of the research are presented with descriptive statistics and visual graphics. Findings show that most studies on marine mucilage are published by Italian researchers and researchers at the Rudjer Boskovic Institute (Croatia). When the keywords were analyzed, it was seen that the most frequently used words were "mucilage" and "Adriatic Sea". Text mining conducted on the abstracts of the publications showed the most striking and interacting words as "species", "production" and "summer". As a comprehensive literature review on this subject, this study could act as a starting point for researchers who will work in this field.
It has widely been an undeniable fact that oil spill has a destructive impact on the health of all inhabitants both on land and in sea. Significantly, oil spill that directly affects the residents exposed to plenty of hazards is likely to cause certain social upheavals and prevalent concerns. This study aims to analyze the socio-economic effects of oil spill on the residents of the region caused by M/V Lady Tuna, as a result of an accident encountered in Cesme/İzmir on Dec.18.2016. The analysis covers the perceptions of the residents in Cesme. The Turkish version of a scale developed by Safford et. al. (2012) has been used for data collection instrument. The sample of the study (n=326) has been determined by a quota sampling method in Cesme. The data collected from the residents have been evaluated by means of frequency and logistics regression analyses. Findings show that the residents of Cesme have an overall view/idea about the pollution, and they are aware of the responsibilities of different related parties of oil spill disaster and possible effects of it.
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