Determining Air Traffic Controller Proficiency: Identifying Objective Measures Using Clustering

Air traffic control (ATC) is a complex and demanding job reserved for highly-trained professionals. Training ATC candidates challenging as trainees are subjectively assessed by instructors who biased their own ways of working. As an effort to determine expertise objectively, this study employed clustering techniques on existing data set in which course professional controllers participated medium-fidelity simulation experiment. Results identified eight measures that formed two distinct stable clusters. A subsequent sensitivity analysis was able reveal how far (or close) each participant positioned from the expert cluster those participants deviated experts. At stage, however, it difficult translate these results into specific advice improve underdeveloped skills. Despite small sample size limited generalizability exploratory study, method appears be promising demonstration determining objective factors describe expertise, warranting further research.