A meta-analysis on air traffic controllers selection: cognitive and non-cognitive predictors

This psychometric meta-analysis investigated the relation of cognitive and non-cognitive factors to the training success of Air Traffic Controllers by synthesizing 51 studies (N = 65,839). Cognitive factors were classified by Cattel-Horn-Carrol theory. Cognitive composite scores and work samples were also included. Non-cognitive factors consisted of Big Five personality traits, biodata, motivation and non-cognitive composite scores. Medium effect was measured for cognitive factors (k = 45, p = .37). Quantitative knowledge, processing speed, work sample, short-term working memory, cognitive composite and visuo-spatial processing predictors showed large effects (p > .30). Significant moderating effects of criterion nature and period of publication were observed. Initial training (k = 30, p = .50) was generally better predicted than on-the-job training (k = 25, p = .18). Better predictive validity was measured from the 60's to nowadays. For non-cognitive factors, only a small effect was measured (k = 24, p = .15). Non-cognitive composites and education showed large effects (p > .30). No significant relation was measured between Big Five personality traits and success criteria. The present findings suggest that selection processes used for Air Traffic Controllers should focus on cognitive predictors or other methods of assessments. Data and scripts can be found at https://osf.io/mkyw7/.