Main Subcommittee Category: Training

How would you label your submission?: Industry

Abstract:

Understanding the cognitive processes of trainees is crucial for effective training, especially in high-risk professions such as air traffic control (ATCO), where complex cognitive skills and extensive workload management are required. While tooling exists to measure technical competencies such as adherence to separation protocols and clearance procedures, obtaining insight into non-technical competencies and the cognitive processes underlying the ATCO’s performance has remained more challenging.

In this work, a technology demonstrator is developed with the aim of supporting instructors with coaching of air traffic controllers on non-technical competencies, whilst providing insight into the cognitive processes of the trainee. Specifically, we explore the use of objective and physiological data to gain insight into the cognitive processes underlying three key competencies: situational assessment; workload management; and problem solving and decision-making.

Employing eye-tracking and simulator data, a demonstrator is developed that facilitates real-time visualization of scanning patterns while the ATCO manages traffic, offering a comprehensive live view of the collected data to the instructor during training sessions.

Moreover, to assist the instructor and trainee post-training, a standalone debrief application is developed to display a variety of performance metrics related to perception of information, mental workload, task load and decision-making.

Overall, this research contributes to the enhancement of ATCO training methodologies by bridging the gap in understanding and assessing the intricate cognitive processes involved.

Keywords: ANALYTICS

Additional Keywords not in the list above: Performance-based training, ATC, eye tracking

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Daniela Pistone