DISTRIBUTIONS OF AIR TRAFFIC CONTROL STUDENTS’ ATTITUDES TOWARDS WORKLOAD

Borsuk, Serhii; Reva, Oleksii · 2021 · Crossref

DOI: 10.3846/aviation.2021.15954

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Summary

This study addresses the challenge of constructing continuous mental workload (MWL) profiles for air traffic control (ATC) students, a critical factor in aviation safety and performance. Existing MWL assessment methods—categorized as performance, subjective, physiological, or analytical—often fail to provide continuous data across varying task complexities due to high time requirements, single-value processing limitations, or reliance on relative rather than absolute values. To resolve this, the authors developed a specialized subjective assessment grid that allows operators to self-estimate their utility and satisfaction across a range of simultaneous aircraft controls. The method is grounded in the Yerkes-Dodson law, which posits an inverted-U relationship between workload and performance, where both underload (boredom) and overload (panic) result in negative utility, while optimal workload yields peak performance. The research involved 124 ATC students from two Ukrainian institutions (NAU and KFA), comprising fourth- and fifth-grade students with at least 150 hours of simulation training. Participants were asked to plot their self-assessed utility on a grid ranging from -100 (maximum discomfort/uselessness) to +100 (maximum satisfaction/utility) against the number of aircraft under control (0 to 30). They identified five key points: minimum workload ($n_{min}$), the transition from minimum to optimal ($n_{min\to opt}$), optimal workload ($n_{opt}$), the transition from optimal to maximum ($n_{opt\to max}$), and maximum workload ($n_{max}$). This approach avoided the intrusiveness of real-time monitoring methods and the processing complexity of traditional questionnaires like NASA-TLX. The results revealed distinct distributions for the key workload points. The peak for $n_{min}$ was 6 aircraft, aligning with Miller’s “magic number” for operational memory capacity. The optimal workload ($n_{opt}$) exhibited a bimodal distribution with peaks at 10 and 15 aircraft. Approximately 20% of respondents indicated plateaus of optimal performance rather than single points, with 56% of these citing two specific aircraft counts as equally optimal. Statistical analysis showed significant differences between grade levels; fifth-grade students demonstrated wider peaks and higher maximum workload thresholds compared to fourth-grade students. Additionally, 13.7% of respondents, all from one institution, deviated from the expected inverted-U utility pattern, suggesting individual variations in workload perception. The study concludes that the proposed grid method effectively captures continuous MWL profiles, offering a practical alternative to existing analytical and physiological methods. It provides absolute referential values for workload redlines and optimal performance zones, facilitating better comparison between operators and educational institutions. The findings support the application of subjective self-assessment in ATC training to identify individual capacity limits and optimize training scenarios, thereby enhancing safety by mitigating risks associated with both underload and overload.

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• workload measurement
• mental demand

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• Empirical Findings: self report data
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• Theoretical Contribution: theory or model