The Effects of Aeronautical Decision-Making Models on Student Pilots’ Situational Awareness and Cognitive Workload in Simulated Non-Normal Flight Deck Environment

Objective: This paper investigates the effects of using different decision-making models on pilots’ performance while facing non-normal flight circumstances. Background: The captain must quickly make appropriate decisions once an aircraft faces emergency. Usually, human error is one primary cause of accidents, which inevitably affects the captain’s decision progress. Method: Ten participants carried out a standard non-normal scenario (cargo smoke). Each participant is equipped with simulation experience and executed three sessions using three different decision models: the DOGAM, DECIDE, and CLEAR. After each session, the situation awareness (SA) and perceived workload were assessed using the Situational Awareness Rating Technology (SART) and NASA-TLX. An in-depth interview was also completed to comprehend their subjective perception of decision-making. Results: Although the CLEAR outperformed the other models in SART and NASA-TLX scores, their performance regarding workload and SA was comparable. The fixing time of DOGAM was the longest, and the other two models were no significant difference. Subjectively, the DECIDE may require a high mental demand by simultaneously processing lots of information and measuring significant changes, whilst the DOGAM may encourage participants follow their own idea, promoting aggressive decisions. Conclusion: This paper clarifies the importance of incorporating decision models into the cockpit and investigates the relatively feasible decision-making model. Variation across our results illustrated applying different decision models to train pilots and solve problems is suggested, thereby improving flight safety.