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Assessing Lifeboat Coxswain Training Alternatives Using a Simulator

Published online by Cambridge University Press:  19 September 2019

Randy Billard ,
Jennifer Smith  and
Brian Veitch
Randy Billard*
Affiliation:
(Engineering, Virtual Marine Technology, St. John's, Newfoundland and Labrador, Canada)
Jennifer Smith
Affiliation:
(Faculty of Engineering and Applied Sciences, Memorial University of Newfoundland, St. John's, Newfoundland and Labrador, Canada)
Brian Veitch
Affiliation:
(Faculty of Engineering and Applied Sciences, Memorial University of Newfoundland, St. John's, Newfoundland and Labrador, Canada)
*
(E-mail: [email protected])
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Abstract

Lifeboats are essential life-saving equipment for all types of water-going vessels and offshore platforms. Lifeboat simulators have been created specifically for offshore personnel to practice in conditions that are normally too risky for live training. As simulation training is a relatively new alternative, there is a need to assess how training performed with a simulator compares with conventional training. This study was performed to evaluate how skills acquired with different training approaches transferred to an emergency scenario. Over a period of one year, participants received quarterly training in one of three ways: using live boats, computer-based training or a simulator. Following training, participants were evaluated on their ability to launch and manoeuvre a lifeboat in a plausible emergency. The study results suggest a benefit to performing training with realistic lifeboat controls and practicing using representative emergency scenarios. Insights are provided on how training can be modified to increase competence.

Keywords

SimulationLifeboatEmergencyTraining
Type
Research Article
Information
The Journal of Navigation , Volume 73 , Issue 2 , March 2020 , pp. 455 - 470
Copyright
Copyright © The Royal Institute of Navigation 2019

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References

REFERENCES

Arthur, W. Jr., Bennett, W. Jr., Stanush, P. L. and McNelly, T. L. (1998). Factors that influence skill decay and retention: a quantitative review and analysis. Human Performance, 11(1), 57–101.CrossRefGoogle Scholar
Baumann, M. R., Gohm, C. L., & Bonner, B. L. (2011). Phased training for high-reliability occupations live-fire exercises for civilian firefighters. Human Factors: The Journal of the Human Factors and Ergonomics Society, 53(5), 548–557.CrossRefGoogle ScholarPubMed
Billard, R., Smith, J., Magee, L., Veitch, B. (2018). Simulator training for offshore oil and gas emergency preparedness. ITEC Proceedings, Stuttgart.Google Scholar
C-Core (2015). Metocean climate study offshore Newfoundland and Labrador, Nalcor Energy Report. http://exploration.nalcorenergy.com/wp-content/uploads/2016/09/Nalcor-Metocean-Study-Final-Report-Volume-2-27-May-2015.pdf.Google Scholar
Driskell, J. E., Willis, R. P. and Copper, C. (1992). Effect of overlearning on retention. Journal of Applied Psychology, 77(5), 615–622.CrossRefGoogle Scholar
International Maritime Organization (2014). International Convention for the Safety of Life at Sea (SOLAS), Consolidated Edition. International Maritime Organization, London.Google Scholar
International Maritime Organization and International Conference on Training and Certification of Seafarers (2010). STCW including 2010 Manila Amendments, 2017 Edition. 4 Albert Embankment, London SE1 7SR United Kingdom: IMO Publishing.Google Scholar
Klein, G. (2008). Naturalistic decision making. Human Factors: The Journal of Human Factors and Ergonomic Society, 50(3), 456–460.CrossRefGoogle ScholarPubMed
Lim, J., Reiser, R. and Olina, Z. (2009). The effects of part-task and whole-task instructional approaches on acquisition and transfer of a cognitive skill. Educational Technology Research and Development, 57, 61–77.CrossRefGoogle Scholar
Magee, L. E., Smith, J. J. E., Billard, R. and Patterson, A. (2016). Simulator training for lifeboat maneuvers. Proceedings of the Inteservice/Industry Training, Simulation, and Education Conference (I/ITSEC). Orlando, Florida, USA. p. 16030.Google Scholar
McClernon, C. K., McCauley, M. E., O'Connor, P. E. and Warm, J. S. (2011). Stress training improves performance during a stressful flight. Human Factors: The Journal of the Human Factors and Ergonomics Society, 53(3), 207–218.CrossRefGoogle ScholarPubMed
Sellberg, C. (2017). Simulators in bridge operations training and assessment: a systematic review and qualitative synthesis. WMU Journal of Maritime Affairs, 16(2), 247–263.CrossRefGoogle Scholar
Stefanidis, D., Korndorffer, J. R., Markley, S., Sierra, R., Heniford, B. T. and Scott, D. J. (2007). Closing the gap in operative performance between novices and experts: does harder mean better for laparoscopic simulator training? Journal of the American College of Surgeons, 205(2), 307–313.CrossRefGoogle ScholarPubMed
Stewart, J., Johnson, D. and Howse, W. (2008). Fidelity requirements for army aviation training devices, Army Research Institute for the Behavioral and Social Sciences, Research. Report 1887, Arlington, Virginia, USA: Army Research Institute.Google Scholar
van Merriënboer, J. J. G., Clark, R. E. and de Croock, M. B. M. (2002). Blueprints for complex learning: The 4C/ID-model. Educational Technology Research and Development, 50(2), 39–64.CrossRefGoogle Scholar
Van Rossum, J. H. (1990). Schmidt's schema theory: The empirical base of the variability of practice hypothesis: a critical analysis. Human Movement Science, 9(3), 387–435.CrossRefGoogle Scholar
Wickens, C., Hollands, J., Banbury, S., Parasuraman, R., (2013). Engineering Psychology and Human Performance, 4th Edition, New York, NY, USA: Pearson.Google Scholar