Utilize este identificador para referenciar este registo: http://hdl.handle.net/10362/184580
Título: Analyzing the drivers of pilots' individual performance in simulation training
Autor: Lopes, Nuno Moura
Aparicio, Manuela
Neves, Fátima Trindade
Palavras-chave: Pilot training
Simulation
Situation awareness
Individual performance
Musical intelligence
Technostress
Neuroscience (miscellaneous)
Applied Psychology
Human-Computer Interaction
Computer Science Applications
Cognitive Neuroscience
Artificial Intelligence
SDG 4 - Quality Education
SDG 5 - Gender Equality
SDG 9 - Industry, Innovation, and Infrastructure
Data: 1-Ago-2025
Resumo: Simulation is a cornerstone of pilot training and safety in aviation. This study investigates the determinants of pilots' individual performance in simulation environments through a novel theoretical model grounded in the Information Systems Success Model, Cognitive Fit Theory, and Situation Awareness (SA). Using survey data from 233 pilots and structural equation modeling (SEM-PLS), we find that SA, perceived task technological fit, and musical intelligence significantly and directly influence performance. Our model explains 40 % of the variance in individual performance. Notably, technostress does not significantly impact SA, but trust in technology influences both technostress and perceived fit. These findings highlight the critical roles of digital tools, cognitive alignment, and musical intelligence in enhancing simulation training outcomes.
Descrição: Lopes, N. M., Aparicio, M., & Neves, F. T. (2025). Analyzing the drivers of pilots' individual performance in simulation training. Computers in Human Behavior Reports, 19, Article 100731. https://doi.org/10.1016/j.chbr.2025.100731 --- This work was supported by national funds through FCT (Fundação para a Ciência e a Tecnologia), under the project - UIDB/04152/2020 - Centro de Investigação em Gestão de Informação (MagIC)/NOVA IMS) (https://doi.org/10.54499/UIDB/04152/2020).
Peer review: yes
URI: http://hdl.handle.net/10362/184580
DOI: https://doi.org/10.1016/j.chbr.2025.100731
ISSN: 2451-9588
Aparece nas colecções:NIMS: MagIC - Artigos em revista internacional com arbitragem científica (Peer-Review articles in international journals)

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