Neurocognitive Predictors of Flight Performance of Successful Solo Flight Students by Emery, Brian, Ph.D., Northcentral University, 2011 , 362 pages; AAT 3489209
AbstractCognitive abilities have been identified as a significant source for determining the potential for individuals to achieve success as pilots. However, while assessments of specific cognitive abilities are considered critical to predicting pilot performance, they do not form part of university admission processes for students applying to flight programs, where attrition rates can be high as 70%. The Cattell-Horn-Carroll (CHC) three-stratum model theory of cognitive abilities links academic and cognitive performance; however, further research could contribute to stratum modifications by expanding understanding of the relationships between CHC theory information processing abilities and specific human performance. In an independent-sample t test research design, this nonexperimental quantitative study examined the relationship between cognitive predictors and successful solo flight performance of student pilots. The CogScreen Aeromedical Edition neurological assessment was used to determine if cognitive factors are valid and reliable of successful solo flight performance. The study participants were 70 student pilots (a convenience sample) between the ages of 18 and 25, 10 female (14%) and 60 male (86%), selected from Embry-Riddle Aeronautical University. The CogScreen-AE measure was administered to the participants prior to their flight instruction. Flight instructors used the FA121 Flight Training Syllabus to evaluate student performance during their training. At the completion of the training, participants were placed in Solo-Completed ( n = 52) and Solo-Not-Completed ( n = 18) groups. Independent-sample t tests were used to compare the mean scores between the Solo-Completed and Solo-Not-Completed groups. The test was significant for the three cognitive measures: divided attention t (68) = 3.77, p < .001, speed-working memory t (68) = 6.81, p < .001, and LRPV t (68) = 17.67, p < .001. The Pearson correlation results revealed that LRPV ( r [52] = .32, p < .05) had the strongest relationship of the three cognitive measures. In addition, regression analyses revealed that the LRPV was the most predictive that explained 81% of the variance ( R ² = .81, F [1, 51] = 213.15, p < .001) in successful solo flight performance. These findings suggest that these cognitive measures are significant of successful solo flight performance and provide further evidence in support of the CHC theory. It is concluded that applying a cognitive performance measure prior to admission to a flight program may reduce attrition rates, support necessary accommodations, and identify flight deficiencies. Further research should compare results among different university flight programs to confirm the findings and to improve the reliability of the CogScreen-AE as a standardized measure for beginning flight students.
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