The Federal Aviation Administration (FAA) has experienced decreased return on investment caused by hiring too many air traffic controller specialists (ATCSs) who performed poorly in field training, thus failing to become certified professional controllers (CPCs). Based on Schmidt and Hunter's theory of job performance and biodata theory, this quantitative, archival study examined whether factors of cognitive ability and biodata could predict job performance status of 2 generations of ATCSs, poststrike (PS) and next generation (NG) controllers. For each generation of controllers, binary logistic regression analysis was conducted to determine if any of the independent variables---transmuted composite (TMC) score for PS controllers, Air Traffic and Selection and Training (AT-SAT) test score for NG controllers, average of high school arithmetic/math letter grade, overall high school average letter grade, self-estimation of time to become fully effective in the ATCS role, self-estimation of percentile ranking in the FAA program relative to the class, size of neighborhood raised, or socioeconomic status---are significant predictors of job performance status for controllers as measured by whether they pass the field OJT (i.e., certified or still in training, or failed certification or left training). The regression results for the PS and NG controllers were found to be statistically significant (chi2 (23) = 68.377, p < .001) and (chi 2 (17) = 99.496, p < .001), respectively. Findings that overall high school grade point average and socioeconomic status significantly predicted ATCS job performance for both PS and NG controllers could influence the FAA's use of revised biodata to better predict ATCS job performance. Further research should include studies of socioeconomic status, gender, and race to address new evidence that the AT-SAT has adverse impact.
| Identifer | oai:union.ndltd.org:waldenu.edu/oai:scholarworks.waldenu.edu:dissertations-2119 |
| Date | 01 January 2011 |
| Creators | Fox, Karen D. |
| Publisher | ScholarWorks |
| Source Sets | Walden University |
| Language | English |
| Detected Language | English |
| Type | text |
| Format | application/pdf |
| Source | Walden Dissertations and Doctoral Studies |
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