Douglas R. Keskula is Assistant Professor in the Physical Therapy Program at Medical College of Georgia, Augusta, GA 30912-3209.
J Athl Train. 1995 Mar;30(1):55-6.
The Purpose of this investigation was to determine which information used in the applicant selection process would best predict the final grade point average of students in a National Athletic Trainers Association (NATA) graduate athletic training education program. The criterion variable used was the graduate grade-point average (GPAg) calculated at the completion of the program of study. The predictor variables included: 1) Graduate Record Examination-Quantitative (GRE-Q) scores; and 2) Graduate Record Examination-Verbal (GRE-V) scores, 3) preadmission grade point average (GPAp), 4) total athletic training hours (hours), and 5) curriculum or internship undergraduate athletic training education (program). Data from 55 graduate athletic training students during a 5-year period were evaluated. Stepwise multiple regression analysis indicated that GPAp was a significant predictor of GPAg, accounting for 34% of the variance. GRE-Q, GRE-V, hours, and program did not significantly contribute individually or in combination to the prediction of GPAg. The results of this investigation suggest that, of the variables examined, GPAp is the best predictor of academic success in an NATA-approved graduate athletic training education program.
本研究旨在确定在国家运动训练协会（NATA）认可的运动训练教育项目的申请人选拔过程中使用的哪些信息最能预测学生的最终平均绩点。使用的因变量为在课程结束时计算的研究生平均绩点（GPAg）。预测变量包括：1）研究生入学考试-定量（GRE-Q）分数；2）研究生入学考试-语文（GRE-V）分数；3）入学前平均绩点（GPAP）；4）运动训练总时间（小时）；5）课程或实习本科生运动训练教育（项目）。在 5 年期间对 55 名研究生运动训练学生的数据进行了评估。逐步多元回归分析表明，GPAP 是 GPAg 的重要预测指标，占方差的 34%。GRE-Q、GRE-V、小时和项目单独或组合对 GPAg 的预测均无显著贡献。这项研究的结果表明，在所检查的变量中，GPAP 是 NATA 认可的研究生运动训练教育项目学业成功的最佳预测指标。
