Division of Teaching and Outcomes of Education, Faculty of Health Science, Medical University of Warsaw, Zwirki i Wigury 61, 02-091, Warsaw, Poland.
Department of Public Health, Faculty of Health Sciences, Medical University of Warsaw, Warsaw, Poland.
BMC Med Educ. 2017 Sep 11;17(1):157. doi: 10.1186/s12909-017-1007-z.
Evaluation of the predictive validity of selected sociodemographic factors and admission criteria for Master's studies in Public Health at the Faculty of Health Sciences, Medical University of Warsaw (MUW).
For the evaluation purposes recruitment data and learning results of students enrolled between 2008 and 2012 were used (N = 605, average age 22.9 ± 3.01). The predictive analysis was performed using the multiple linear regression method. In the proposed regression model 12 predictors were selected, including: sex, age, professional degree (BA), the Bachelor's studies grade point average (GPA), total score of the preliminary examination broken down into five thematic areas. Depending on the tested model, one of two dependent variables was used: first-year GPA or cumulative GPA in the Master program.
The regression model based on the result variable of Master's GPA program was better matched to data in comparison to the model based on the first year GPA (adjusted R 0.413 versus 0.476 respectively). The Bachelor's studies GPA and each of the five subtests comprising the test entrance exam were significant predictors of success achieved by a student both after the first year and at the end of the course of studies.
Criteria of admissions with total score of MCQs exam and Bachelor's studies GPA can be successfully used for selection of the candidates for Master's degree studies in Public Health. The high predictive validity of the recruitment system confirms the validity of the adopted admission policy at MUW.
评估华沙医科大学(MUW)健康科学学院公共卫生硕士课程中选择的社会人口因素和入学标准的预测有效性。
为了评估目的,使用了 2008 年至 2012 年期间入学的学生的招生数据和学习成绩(N=605,平均年龄 22.9±3.01)。使用多元线性回归方法进行预测分析。在所提出的回归模型中,选择了 12 个预测因子,包括:性别、年龄、专业学位(BA)、学士学位成绩平均绩点(GPA)、初步考试的总分分为五个专题领域。根据测试模型,使用两个因变量之一:第一年的 GPA 或硕士课程的累积 GPA。
基于硕士 GPA 程序的因变量的回归模型与数据的匹配程度优于基于第一年 GPA 的模型(分别为调整后的 R 0.413 和 0.476)。学士学位 GPA 和构成入学考试的五个分测验中的每一个都是学生在第一年和课程结束时取得成功的重要预测因素。
采用 MCQs 考试总分和学士学位 GPA 的入学标准可以成功地用于选择公共卫生硕士学位课程的候选人。招生系统的高预测有效性证实了 MUW 采用的招生政策的有效性。