Learning through the experts' eyes: an eye-movement modelling example based training intervention in an air traffic control decision making task

This study explored the effectiveness of Eye Movement Modeling Examples (EMME) as a training intervention for novices performing an air traffic control (ATC) decision-making task. Nineteen participants were randomly assigned to either an implicit (visual-only) or explicit (visual-audio) training group. Participants completed a pre-test and post-test, with eye-tracking technology capturing gaze behaviour (fixations, saccades) alongside performance measures (accuracy, response time). Linear and negative binomial mixed models assessed changes over time and between groups. Results showed no significant interaction effects for accuracy or gaze behaviour between training modalities. However, response time, number of fixations, and number of saccades significantly decreased from pre- to post-test in both groups, suggesting improved visual processing efficiency. The implicit group demonstrated significantly longer fixation durations, indicating greater cognitive effort. While explicit verbal instruction did not enhance performance, overall reductions in gaze metrics suggest EMME may foster perceptual-cognitive refinement even in brief interventions. These findings support early-stage learning effects showing improved visual search patterns and faster response time. The study underscores EMMEs promise in training visual decision making in complex environments and highlights the need for longitudinal, mixed-methods, and area-ofinterest focused future research.