Flying the Needles: Flight Deck Automation Erodes Fine-Motor Flying Skills Among Airline Pilots
Open accessAbstract
Objective: The aim of this study was to evaluate the influence of practice and training on fine-motor flying skills during a manual instrument landing system (ILS) approach. Background: There is an ongoing debate that manual flying skills of long-haul crews suffer from a lack of flight practice due to conducting only a few flights per month and the intensive use of automation. However, objective evidence is rare. Method: One hundred twenty-six randomly selected airline pilots had to perform a manual flight scenario with a raw data precision approach. Pilots were assigned to four equal groups according to their level of practice and training by fleet (short-haul, long-haul) and rank (first officer, captain). Results: Average ILS deviation scores differed significantly in relation to the group assignments. The strongest predictor variable was fleet, indicating degraded performance among long-haul pilots. Conclusion: Manual flying skills are subject to erosion due to a lack of practice on long-haul fleets: All results support the conclusion that recent flight practice is a significantly stronger predictor for fine-motor flying performance than the time period since flight school or even the total or type-specific flight experience. Application: Long-haul crews have to be supported in a timely manner by adequate training tailored to address manual skills or by operational provisions like mixed-fleet flying or more frequent transitions between short-haul and long-haul operation.
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In aviation, manual flying skills can degrade from lack of practice when aircraft are highly automated, reducing pilots' opportunity to meet their competence need.
“For example, in the aviation industry, manual flying skills can become degraded due to a lack of opportunity to practice when aircraft are highly automated99, decreasing the opportunity for pilots to meet their need for competence.”
From Understanding and shaping the future of work with self-determination theory (2022) · cites this paper as [99]
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- Authors
- Haslbeck, A., & Hoermann, H.-J.
- Affiliations
- Technical University of Munich (DE)
- Deutsches Zentrum für Luft- und Raumfahrt e. V. (DLR) (DE)
- Corresponding author
- Haslbeck, Andreas
- Venue
- Human Factors: The Journal of the Human Factors and Ergonomics Society
- Publisher
- SAGE Publications
- Published
- 2016-04-13
- Volume
- 58
- Issue
- 4
- Pages
- 533-545
- ISSN
- 0018-7208 (ISSN-L)
- 1547-8181
- OpenAlex
- W2338427307
- Cited by
- 70
- References
- 22
- Citations by year
- 2026: 6 · 2025: 12 · 2024: 7 · 2023: 6 · 2022: 8 · 2021: 7 · 2020: 7 · 2019: 5 · 2018: 6 · 2017: 5 · 2016: 1
- FWCI
- 8.90
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Locations
- Human Factors The Journal of the Human Factors and Ergonomics Society (publishedVersion)
- PubMed (publishedVersion)
- elib (German Aerospace Center) (acceptedVersion)
- Funders
- Bundesministerium für Wirtschaft und Technologie
- Topics
- Social Sciences › Psychology › Social Psychology › Human-Automation Interaction and Safety
- Physical Sciences › Engineering › Aerospace Engineering › Aerospace and Aviation Technology
- Life Sciences › Neuroscience › Cognitive Neuroscience › Motor Control and Adaptation
- Keywords
- flight automation, airline pilots, pilot training
- MeSH terms
- Work Performance, Pilots, Adult, Aircraft, Automation, Humans, Male, Middle Aged, Motor Skills, Practice, Psychological
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