Air Traffic Controller Competence Retention and Retention Modelling: a preliminary study

dc.contributor.authorHove, P.E. ten
dc.contributor.authorTillema, G.H.J.
dc.contributor.authorEaglestone, J.
dc.date.accessioned2026-03-10T13:30:54Z
dc.date.available2026-03-10T13:30:54Z
dc.date.issued2022
dc.description.abstractAir Traffic Controller (ATCO) error can have a huge impact on flight safety, therefore preventing skill decay is essential. Training can be a good remedy, but training is expensive and sometimes unnecessary. Understanding how and when skill decay occurs is essential in personalising retention training. This preliminary study examines methods for measuring (military) ATCO skill decay. Experimental sessions were conducted with five military ATCOs in the MicroNav BEST Training Simulator. During each experiment session a complex approach control task, and a surveillance radar approach, were performed and both subjective- and objective data (i.e. simulator and eye-tracking data) was collected. Although the results showed no significant differences between the sessions, new insights into skill decay indicators were gained, including factors such as change in ATCO scan-patterns and the influence of ATCO experience (i.e. level and exposure) on the task.
dc.identifier.citationPetra ten Hove, Guido Tillema, Jennifer Eaglestone, Air Traffic Controller Competence Retention and Retention Modelling: a preliminary study, Transportation Research Procedia, Volume 66, 2022, Pages 136-147, ISSN 2352-1465, https://doi.org/10.1016/j.trpro.2022.12.015.
dc.identifier.urihttps://hdl.handle.net/10921/1887
dc.language.isoen
dc.publisherElsevier
dc.rights.holder© 2022 NLR
dc.rights.licenseCC BY-NC-ND license
dc.titleAir Traffic Controller Competence Retention and Retention Modelling: a preliminary study
dc.typeArticle

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