Selection in Air Traffic Control: Is Nonradar Training a Predictor of Radar Performance?

Abstract

Objective: The purpose of the current research was to investigate whether performance in nonradar training would predict performance in radar training. Background: There is a discussion in the Federal Aviation Administration about the necessity of keeping nonradar training as part of the required selection criteria for radar controllers. In nonradar training, controllers separate traffic by relying on the estimated time over navigational fixes printed on flight progress strips, rather than monitoring the perceptually available positional information on a radar screen. The two ways of controlling traffic—nonradar and radar—are different along a number of dimensions. Method: Sixteen participants were taught to control simulated air traffic using nonradar and radar procedures. Performance on final radar scenarios was predicted from cognitive variables; performance on earlier, simpler radar scenarios; and performance on nonradar scenarios. Results: Performance during nonradar trials predicted final radar performance (i.e., collisions and landed aircraft count) independent of the predictive power of cognitive variables and above and beyond earlier radar training. Conclusion: Performance in nonradar training enhanced users' ability to predict radar performance, even in addition to the predictive power of simpler, earlier radar performance variables. Good nonradar performers had higher situation awareness in the radar environment. Application: Performance in a nonradar environment may serve as an important selection tool in assessing the performance of student controllers in radar environments. The results indicate the need for future research with field controllers.