There exists an imbalance between the number of pilots trained to practice in the field of aviation and the amount of those individuals who are qualified to fly airplanes. By putting a systematic selection system in place, it helps to ensure that the best possible candidates fill open positions in the field. Specifically developing a selection system to train and acclimate future pilots while they are in a university setting will not only help select top-tier candidates into the aviation program, but also prepare them for what to expect when they enter the job market. This research study built upon two iterations of a pilot selection battery for a Midwestern university aviation program. Participants completed a battery that was then used for research purposes to obtain information about the potential predictors of pilot performance. The measures include the IPIP Five Factor Scale, Assertive Interpersonal Schema Questionnaire, Cockpit Management Attitudes Questionnaire, Proactive Personality Scale - Short Version, Block Counting Measure, and Rotated Blocks Measure. Additionally, flight instructors evaluated their students based on several aspects of effective performance. Data from 30 student pilots were examined with bivariate correlations and linear regression and the results from the current sample indicated that a pilot personality profile, assertiveness, proactivity, cockpit management skills, and spatial reasoning did not consistently predict flight performance. Further research is warranted to accumulate a larger sample size in order to determine if these characteristics do, indeed, predict performance in the field.
Date of Degree
Master of Arts (MA)
Social and Behavioral Sciences
Hanna, R. T. (2014). Development and Enhancement to a Pilot Selection Battery for a University Aviation Program [Master’s thesis, Minnesota State University, Mankato]. Cornerstone: A Collection of Scholarly and Creative Works for Minnesota State University, Mankato. https://cornerstone.lib.mnsu.edu/etds/297/
Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License