NeuroTracker Multiple Object Tracking Ability Predicts Novice Performance on a Simulated Air Traffic Control Task

Abstract

ABSTRACT Objective To explore the utility of multiple object tracking (MOT) ability, measured using NeuroTracker, as a predictor of air traffic control (ATC) task performance. Background The perceptual-cognitive abilities required for MOT are also important for ATC performance. The current study provides a novel examination of NeuroTracker’s utility to predict novice performance on a simulated ATC task, relative to two discrete measures of working memory (WM). Method Forty-six participants completed computer-based assessments of MOT ability (NeuroTracker) and WM (Corsi Block Tapping, Automated Operation Span) followed by the simulated ATC task. Regression analyses were performed to determine the associations between ATC task performance and the MOT and WM measures. Results After controlling for age and video game playing, MOT ability significantly predicted more correct detections of conflicts between aircraft, fewer false alarm responses to conflicts, and faster aircraft acceptance and hand-off. When WM measures were included in regressions, MOT was a stronger predictor of performance than WM on those outcomes, and remained a statistically significant predictor of better conflict detection, false alarm response, and hand-off performance. Conclusion The findings demonstrate the relevance of MOT ability to ATC task performance and support the potential utility of NeuroTracker for controller applicant screening and selection. Research is required to validate the findings in larger and more representative samples under more realistic conditions.