In recent years, society's approaches to education and learning have been changing and will continue to do so even more. Advances in technology, underpinned and informed by science, particularly the learning and behavioural sciences, have been a major driver for this change.
In the white paper entitled, “A Future Learning EcoSystem for Pilot Training”, Dr. Richard Kennedy: Head of Learning Science at CAE Civil Aviation Training Solutions, and Dr. Nicklas Dahlstrom, Human Factors Manager at Emirates Airlines, envision the potential benefits of a future Learning EcoSystem for pilot training based-upon Simulation for Experiential Training (SET), embedding training into operations, and leveraging Artificial Intelligence (AI) technology.
Here is a summary of their findings.
Conceptually, the future Learning EcoSystem is represented as a series of matrices mapped upon each other. The bottom matrix is one of regulations, audit requirements, and guidance, which due to the need for regulatory compliance forms the fundament of the Learning EcoSystem. The next layer represents the translation of regulations, requirements, and guidance into KSA (Knowledge, Skills, and Attitudes). These are the competencies that the training needs to address to achieve compliance and respond to the evidence from operations. Finally, the top layer represents the learning material itself including different learning technologies and methods to deliver training.
In the spectrum of training methods – ranging from a text to read by yourself to a session in a Full Flight Simulator – there is still a great need for more methods that meet different types of training needs. Simulation for Experiential Training (SET) is one methodology that can be used to develop both procedural and CRM skills in the context of operational scenarios. Identifying operational situations that are rich in learning potential and putting them in a 'simple simulation' format can allow much more emphasis on different aspects of learning and far more variations of similar (but slightly different) scenarios to be trained. SET therefore offers training capabilities that are not possible, even with more costly high fidelity simulators.
In addition to SET, other concepts will form part of the future Learning EcoSystem. This includes embedded, sometimes referred to as blended, training which at its simplest would incorporate training content into the actual operation itself. In other words, this would mean using time "at work" or operational time when there are no requirements on performance, to train. On a practical level, embedded training simply provides 'bitesize' training modules in operational situations.
AI technology allows us to capture training needs from user behaviour outside of formal learning management systems and the training environment. The ultimate aims of AI in this context are to increase the quality, accessibility, and efficiency of training. The use of AI could also support organisational goals in highlighting to individuals where they may need to focus their attention when their performance is at risk of not reaching required standards. The current manual “trend analysis” could be done by analytic functions and point a pilot to where they need to reinforce their knowledge and skills. In addition, all competencies could be monitored by AI for trends and then linked to training recommendations of interventions from the system.
Combined with the existing training material, new simulation technologies are forming a future 'Learning EcoSystem' that will reshape the training experience from one focused on organisational control to one that supports the trainee's drive to learn. A Learning EcoSystem that simultaneously improves training quality through relevant and interesting material, accessibility, and a focus on trainee drive whilst also reducing cost is a realistic vision that the aviation industry will increasingly move towards in the years ahead.
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