Pilot training of the future will look very different than it does today. This White Paper builds upon the ideas presented in the previous four White Papers from CAE-Emirates on the future learning ecosystem for pilot training framework which outlined the main ideas and concepts to enable the pilot training of tomorrow.
Specifically, this paper provides ideas for the evolution and expansion of Simulation for Experiential Training (SET) and how to scale SET so that it becomes a training tool that is used widely in the industry. This expansion will have to be focused on building a collection of scenarios that represent the set of different situations for which SET can provide the best possible training value. Developing scenarios is challenging and too often underestimated in the industry. While training technology in the form of simulation has seen great development, the understanding of scenario design seems to be at best incoherent across the industry.
One way to expedite the expansion of available SET scenarios would be establish a Simulation for Experiential Training (SET) Collaborative. Partner airlines would commit to developing a small number of scenarios, for example, three to five. This would allow the “SET Collaborative” to build-up a large scenario simulation bank in a relatively short period of time. Such a solution could also lead to a “developer’s community” with selected partner airlines. Properly managed SET training data would also provide a broader view on operational challenges that confront the whole business as an additional source of information for the collective Safety Management System.
One great benefit with developing SET to scale would be the amount of data produced by trainees. This would provide insights to pilot performance that in turn generates new training needs and thus new scenarios. The argument could then be made that this type of data identifies specific focus for improvements (e.g., monitoring and workload management for pilots with less than 3000 hours) and existing scenarios could be recommended for those pilots or new ones could be developed.
With SET, there is great potential to capture data that reflects actual pilot performance, and this would be combined with the use of analytics on that data. This would be a low-cost version of data collection, similar to what is known as SOQA (Simulator Operational Quality Assurance), but more basic, given the limitation of the amount of data and the design option to focus on certain competencies in scenarios.
Fully implemented at scale, SET would be integrated into the training system so that the full range of pilots from cadet to senior captain, would have practical and simple training available to them covering diverse scenarios at varying levels of difficulty. Since SET is a “safe to fail” activity, pilots would be more willing to experiment with alternative management strategies.
This paper has considered how Simulation for Experiential Training (SET) can be further evolved and expanded within the future learning ecosystem for pilot training.
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