Are We Training for Competence or for Compliance?
Rethinking Simulator Training Through Neuroscience and Evidence-Based Practice
An Article by Capt. Y. Franciosa
During a recent simulator session, I watched two experienced pilots handle every manoeuvre flawlessly: steep turns, engine failures, approaches and go-arounds. All performed with precision. Yet, when a simple, unexpected rerouting with a minor system degradation emerged, their performance deteriorated. Their techniques were solid. Their competence in managing the scenario proved fragile.
It was not a matter of skill. It was a matter of how they had been trained.
For decades, simulator sessions have been shaped by regulatory lists of manoeuvres. This approach has served aviation well, but its limits are becoming increasingly visible. While training in aviation has evolved over the years, its rate of progress seems to have reached a plateau.
If we are honest, the last structural change in airline training arrived many years ago, with the global push for Upset Prevention and Recovery Training after accidents like Air France 447 over the Atlantic. UPRT was an important step, supported by ICAO and regulators worldwide, and it addressed a clear pattern of loss-of-control accidents.
Since then, our industry has become very good at proving compliance with new requirements, but much slower at rethinking how we design training itself. Too often I hear some version of: “It has worked so far, why change it?” The problem is that “it has worked so far” does not mean we are safe. It only means we have been safe up to now. Sometimes we are safe only until the next accident reveals the holes in our mental models.
We have been taught that we want pilots to be resilient and able to deal with unforeseen circumstances. Therefore, the question for the industry is simple:
Do we really train competence, or do we train compliance?
The Brain Does Not Learn in Checklists, It Learns in Patterns
Working memory has limits. When we attempt to fill a 5-hour session with as many items as possible, we create overload. Pilots leave the simulator tired, saturated with tasks, but not transformed.
Neuroscience offers a clear explanation for why fragmented, high-reposition, manoeuvre-driven training often fails to build real competence.
1. The prefrontal cortex needs coherent context
The prefrontal cortex (PFC) is the brain’s flight director for thinking. It integrates information, weighs options, and supports judgment. When a simulator session becomes a sequence of disconnected activities, the PFC is forced into constant task switching. This overload reduces the quality of decision-making and situational awareness.
2. The basal ganglia require repetition inside meaningful scenarios
The basal ganglia support habit formation and automaticity. They learn patterns, not isolated events. When we practice a circling approach here, a windshear there, and a stall recovery somewhere else, we train movement but not the conditions that make those movements relevant. The brain encodes actions, not the situational patterns behind them.
3. The hippocampus builds mental maps, not isolated memories
The hippocampus encodes context and links cause and effect. Frequent repositioning breaks this narrative structure. Pilots leave the simulator remembering what they did, but not when, why, or how the situation developed. This prevents the formation of robust mental models.
Therefore, neuroscience tells us that deep learning requires consolidation, pattern recognition, and time for reflection. What matters is not how many manoeuvres we fit into the slot, but how deliberately and meaningfully we practice the competencies that matter.
In other words, manoeuvre-based training feeds the brain checklist items. Competence-based training feeds the brain patterns. And safety depends on patterns.
EBT and ATQP: A Strong Foundation, Not the Final Step
The industry has already made important progress. Evidence-Based Training (EBT) and ATQP programmes have shifted the focus from manoeuvres to competencies, such as:
- Problem Solving and Decision Making
- Situational Awareness
- Leadership and Teamwork
- Workload Management
These frameworks recognise that safety emerges from how pilots think, not only how they fly.
However, many training programmes still apply EBT principles on paper while retaining manoeuvre-based structures in practice, mostly due to legacy syllabi, regulatory pressure, or operational convenience.
Designing a Five-Hour Session for Competence
True competence is the ability to recognise a developing situation, predict what may come next, and adapt procedures intelligently. Compliance, instead, is the ability to execute a manoeuvre when prompted in ideal conditions. The latter is useful for standardisation, but the former is what saves lives.
So, the real question should be:
What two or three core competencies do we want to shape in this crew today?
Once that is clear, the simulator profile should be designed around those competencies, not around a shopping list of unrelated tasks.
A structured session in these terms might include:
- A single overarching scenario with evolving conditions.
- Manoeuvres integrated naturally into the scenario.
- Minimal repositioning to maintain situational coherence.
- Error-based learning, allowing crews to make and analyse mistakes.
- A structured, competency-based debrief centred on behaviours, not tasks.
This is aligned with the philosophy of Evidence-Based Training and ATQP, which have already laid strong foundations. The next step is to fully embrace the neuroscience of how pilots actually learn.
From Box-Ticking to Adaptive, Scenario-Based Training
Here is an idea I believe we need to take seriously. When I play a video game, I can change the level of difficulty and the way I use my character, even if the background story is the same for everyone. We start from the same mission, but each player can become something different and explore different paths.
Why should simulators be less intelligent than a game console?
Imagine a training programme where the simulator has a common background storyline for all crews, but the scenario adapts from pilot to pilot. The same departure, the same destination, the same general frame. Yet the weather evolution, failures, traffic, or ATC constraints change dynamically based on what the crew does and on their current level of competence.
- A crew that is coping well might face a more complex chain of minor threats that tests their capacity to prioritise and anticipate.
- A crew that is struggling might have the scenario quietly simplified, so they can still practise the target competencies without being overwhelmed.
In this model, the instructor becomes a real resource, not a “script runner.” Their experience is used to debrief patterns, decision points, and mental strategies, while an AI-driven engine can inject unforeseen events that are not limited to the personal history or imagination of that instructor or that operator. Instead of every scenario being shaped by our biases, we deliberately introduce controlled unpredictability, which is exactly what the brain needs to build robust mental models.
Standardisation is not lost. We can still maintain it through clear checks where pilots must demonstrate that they can perform a defined set of manoeuvres to specific parameters. But around those check events, training time is used to build competence: judgment, adaptability, crew coordination, and resilience under pressure.
That is a very different philosophy from “wasting” simulator time on ticking as many boxes as possible.
Conclusion
Aviation has long been at the forefront of training innovation. With EBT and ATQP, the foundation is already there. The next step is aligning our simulator practices with how the brain actually learns.
The question is no longer whether pilots can perform a sequence of manoeuvres. The question is:
Can they manage the unexpected when the scenario does not follow the script?
That is competence.
And competence is what keeps people safe.
Capt. Y. A. Franciosa
References
Dekker, S. (2014). The field guide to understanding human error. CRC Press.
Endsley, M. R. (1995). Toward a theory of situation awareness in dynamic systems. Human Factors, 37(1), 32–64.
Ericsson, K. A. (2008). Deliberate practice and the acquisition of expert performance. Psychological Review, 113(3), 486–512.
Hancock, P. A., & Scerbo, M. W. (2011). Performance under stress. Human Factors, 53(2), 75–86.
Miller, E. K., & Cohen, J. D. (2001). An integrative theory of prefrontal cortex function. Annual Review of Neuroscience, 24, 167–202.
Parasuraman, R., & Rizzo, M. (2008). Neuroergonomics: The brain at work. Oxford University Press.
Schmidt, R. A., & Bjork, R. A. (1992). New conceptualizations of practice, common principles in three paradigms suggest new concepts for training. Psychological Science, 3(4), 207–217.
Wiggins, M. W., & O’Hare, D. (2020). Aviation decision making and cognitive skill. The International Journal of Aviation Psychology, 30(1–2), 1–20.
