A study on predictive validity of psychological selection for student pilots
10.3760/cma.j.cn113854-20230724-00074
- VernacularTitle:飞行学员心理选拔预测效度研究
- Author:
Xuefeng WANG
1
;
Yan ZHANG
;
Bingjie FAN
;
Shengli LI
;
Xueqian DENG
;
Yishuang ZHANG
;
Liu YANG
Author Information
1. 空军招飞局，北京 100195
- Publication Type:Journal Article
- Keywords:
Psychology;
Eligibility determination;
Forecasting;
Regression analysis;
Student pilots
- From:
Chinese Journal of Aerospace Medicine
2024;35(1):1-5
- CountryChina
- Language:Chinese
-
Abstract:
Objective:To provide data references for psychological selection of student pilots by verifying the predictive validity of the total score of psychological selection (TSPS) in primary training stage.Methods:A systematic evaluation study was conducted. A cluster sampling of student pilots graduated from an academy in recent years was performed. The total scores that represented the comprehensive level of the students in primary training stage and their scores of college entrance examination in recruitment stage were collected and converted (standard deviation standardization) into flight performance (FP) and standardized scores of college entrance examination (SSCEE). TSPS was extracted and its 3 sub-scores, such as basic cognitive ability scores (BCAS), flight special ability scores (FSAS) and interview performance scores (IPS), were processed to 9-point scale. According to standard deviation, SSCEE was divided into high score group (≥1.0 point), medium score group (-1.0-1.0 point) and low score group (≤-1.0 point). TSPS was divided into high score group (≥6.5 points), medium score group (4.5-6.5 points) and low score group (≤4.5 points) according to the classification method of enrollment stage. The FP differences were compared among different student pools, SSCEE and TSPS. The correlation between FP and SSCEE, TSPS, BCAS, FSAS and IPS was analyzed respectively. By taking BCAS, FSAS, IPS and SSCEE as the independent variables and FP as the dependent variable, the regression equation was constructed. According to the prediction results of correlation analysis and regression analysis, the optimal weights of BCAS, FSAS and IPS composed in TSPS model were calculated.Results:A total of 267 student pilots were selected, and TSPS, BCAS, FSAS and IPS all showed positive correlations with FP ( r=0.440, 0.160, 0.303, 0.380, all P<0.001). There was a significant difference in FP among different TSPS group ( H=55.37, P<0.001). There were significant differences in FP and TSPS among different student pool groups ( H=7.26 , F=7.43, P=0.039,<0.001). There was no significant difference in FP and TSPS among different SSCEE groups ( P>0.05). TSPS calculated based on correlation coefficient and regression coefficient was positively correlated with FP ( r=0.450, 0.452, both P<0.001). The prediction validity of each model was better than that of the existing model (0.440). Conclusions:In psychological selection, IPS and FSAS positively contribute to the predictions of the training efficiency of student pilots. Among which, IPS and FSAS take relative higher weights in TSPS model. It is suggested that the psychological selection should be managed upon scientific scheduling, as well as the dynamic optimization and effective evaluation mechanism.
