Advisor(s) - Committee Chair
Xiaowen Chen, Jacob Byl, Lance Han, Elizabeth Shoenfelt
Department of Psychological Sciences
Master of Science
Debates on commercial airline pilot job requirements have arisen in the United States and caught more public attention during the Covid-19 pandemic. Review and re-analysis of the job requirements are ways to de-escalate the heated dispute. The purposes of the current study are to systematically review the commercial pilot qualifications required in the current job market, and to identify the knowledge, skills, abilities, and other attributes (KSAOs) required to perform commercial pilot work in the American airline industry. To realize these purposes, I used Machine Learning (ML) techniques to analyze the commercial airline pilot job advertisements (N = 611). I was able to identify KSAOs and job activities with a Latent Dirichlet Allocation (LDA) topic model. The ML analysis results were validated by a survey with twenty Subject Matter Experts (SMEs) participation. No significant changes were found between commercial airline pilot job requirements reported by federal agencies and the requirements identified in the current study. ML can be used to identify the general information of KSAOs and job activities but its function to identify specific information is quite limited. The implications, future research directions, and limitations were discussed.
Arts and Humanities | Business | Performance Management | Social and Behavioral Sciences | Training and Development
Fults, Adam, "Exploring Commercial Airline Pilot Job Requirements with the Support of Machine Learning Techniques" (2023). Masters Theses & Specialist Projects. Paper 3635.
Available for download on Friday, March 26, 2123