Distributions of Air Traffic Control Students’ Attitudes Towards Workload

Abstract

Mental workload is a well-known concept with a long development history. It can be used to examine students’ attitudes at the end of the educational process and compare them in groups or separately. However, building a continuous workload profile across the range of task complexity increase is still an urgent issue. All four groups of methods used to define mental workload have such flaws for the workload profile construction process as significant time requirements, single value processing and post-processing of the received results. Only one of them can be used without modifications to construct the operator’s attitude chart (profile) regarding the workload range and it doesn’t operate with more reliable absolute values. To resolve this problem, a special workload assessment grid was developed, considering the advantages of a subjective group of methods and seven core characteristics. The reasoning for grid axes choice, threshold values, and question formulation were provided. Statistics were calculated for the full sample, different grades, and educational institutions. Comparison of the received responses with referential values, cross-comparison between institutions and different grades were performed. The results contribute to such important aspects of workload, as redlines, workload profiling, and operator’s comparison.

Development of a Fuzzy Approach for Consistency Determination of ATC Students’ Opinions During Aircraft Flight Norms Violation Hazard Identification

“…It is also worth noting that it would be advisable to establish the opinions consistency levels of ATC students not based on their overall group opinion but by taking into account the opinions of professional ATC controllers. Moreover, as inferred from our research [2,3,4], the ratio of risk-prone and risk-averse ATC students is inversely proportional compared to professional ATC controllers.…”

“…establish a correspondence in mind of the j-th ATC student between a certain flight norm distance L and the i-th score of the linguistic scale variable "hazard level" described in figure 1. Then, considering that this scale is formed by seven terms, it is not difficult, using the research experience [2,7,8], to obtain such an integral indicator of their opinion correspondence regarding the overall group opinion within the q-th flight norm:…”

“…"Forecasting hazards related to flight norms violations by air traffic controllers (ATC) is a challenge that can be addressed using qualimetric methods and means [1]. These tools encompass intricate measurements, tests, and surveys that reflect the ATC's attitude towards risk factors [2,3]. Considered circumstances can be of various types and nature including horizontal distances between aircraft under simultaneous control.…”