Predictors of aviation service selection among U.S. Naval Academy graduates
Gonzalez, James Mario
Mallory, Linda D.
Mehay, Stephen L.
MetadataShow full item record
The purpose of this study is to investigate U.S. Naval Academy student predictors of aviation selection for graduates between 1995 and 2002. The main hypothesis is that the background characteristics that predict aviation selectees will differ from the characteristics that predict non-aviation selectees. Although prior research suggests that several characteristics (academic, cognitive, athletic, and personality traits) play an important role in predicting success in aviation, other research suggests that many of those characteristics have not been included in the service selection process at the Naval Academy. Two empirical models were estimated to investigate this hypothesis. The models were used to determine whether the significance of predictive factors differ between all aviation selectees and non-aviation selectees, and likewise between pilot aviation selectees and non-pilot aviation selectees. The results show that of all of the variables in both models PFAR (an ASTB score) was the most important factor in predicting aviation selection. Both PFAR and academic grade point average at USNA had a large impact on aviation selection and separately on pilot selection. These results were representative of both aviation and pilot selection. It is also important to note that some variables were strong negative predictors in the models, although prior research suggested they would be positive predictors of aviation success. Apparently, the factors that predict success in aviation flight training are not the same that predict selection of the aviation community.
RightsThis publication is a work of the U.S. Government as defined in Title 17, United States Code, Section 101. Copyright protection is not available for this work in the United States.
Showing items related by title, author, creator and subject.
Kamel, Magdi N. (Monterey, California. Naval Postgraduate School, 2020-10); NPS-IS-20-002Machine learning analysis of student aviator training performance data offers novel and more accurate methodologies for performance assessment that includes identifying students for attrition or remediation as well as ...
Aviation selection test battery component predictiveness of primary flight training outcomes among diverse groups Lopez, Ramon A.; Denton, Tremain L. (Monterey, California. Naval Postgraduate School, 2011-03);The Aviation Selection Test Battery (ASTB) has been the qualifying benchmark for the Naval Aviation since World War II. While it is necessary that test scores effectively select the candidates with the greatest chance for ...
Selection to Naval Special Warfare and the retention of Naval Special Warfare Officers commissioned from the United States Naval Academy Rehak, Joseph G. (Monterey, California: Naval Postgraduate School, 1999);This research analyzes United States Naval Academy's admissions and midshipman performance variables and their impact on the career development of graduates in the Special Warfare (SEAL) community. Non-linear LOGIT regression ...