Dynamic Decision-Making Of Airline Pilots In Low-Fidelity Simulation

THEORETICAL ISSUES IN ERGONOMICS SCIENCE(2021)

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Abstract
Dynamic decision-making in aviation involves complex problem solving in a dynamic environment characterized by goal conflicts and time constrains. Training mostly focuses on testing domain-specific knowledge and skills that may result in context-specific rather than general problem-solving skills. A low-fidelity decision-making simulation may favour the understanding of the decision process rather than the decision outcome alone. We investigated airline pilots' decision-making strategies and task performance through the use of the low-fidelity computer simulation (microworld) COLDSTORE, a non-linear, opaque, time-delayed task. Almost thirty percent of pilots adapted (Adaptors) to the task's demands, reaching the desired objective. About thirty five percent of pilots approached the task using a cautious strategy (Cautious). However, the success rates in reaching the task's objective revealed that performance was compromised for the cautious group. A changing (Changers) and oscillating (Oscillators) approach was also observed. More experienced pilots differed from least experienced pilots in strategy and performance adopted. We suggest that low-fidelity dynamic decision-making simulations offer an environment for practicing and understanding the decision-making process. That may contribute to pilots' ability to coordinate monitoring, recognition, planning, judgement and choice when acting under flight environment time constraints.
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Key words
Dynamic decision-making, airline pilots, low-fidelity simulations, microworlds, instance-based learning theory
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