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

dc.contributor.author Hove, P.E. ten
dc.contributor.author Tillema, G.H.J.
dc.contributor.author Eaglestone, J.
dc.date.accessioned 2026-03-10T13:30:54Z
dc.date.available 2026-03-10T13:30:54Z
dc.date.issued 2022
dc.description.abstract Air 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.citation Petra 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.uri https://hdl.handle.net/10921/1887
dc.language.iso en
dc.publisher Elsevier
dc.rights.holder © 2022 NLR
dc.rights.license CC BY-NC-ND license
dc.title Air Traffic Controller Competence Retention and Retention Modelling: a preliminary study
dc.type Article
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