Nursing, Humber Institute of Technology and Advanced Learning, 205 Humber College Blvd, Etobicoke, ON M9W 5L7, Canada.
University of Missouri, 430 Sinclair School of Nursing, University of Missouri, Columbia, MO 65211, United States of America.
Nurse Educ Today. 2019 Feb;73:65-70. doi: 10.1016/j.nedt.2018.11.016. Epub 2018 Nov 29.
Academic institutions are under pressure to maintain a nearly flawless retention rate, while graduating successful students. The use of standardized admission tests to provide data driven decisions regarding applicant selection is common. The varying reliability and validity of current standardized tests inspired a large Canadian academic institution to use a faculty developed admission test for admission to its practical nursing (PN) program.
The target population for this project was a purposive, convenience sample of graduated PN students from a large publically funded polytechnic institution in southern Ontario, Canada, who had completed the Canadian Practical Nurse Registration Examination (CPNRE) within 2014-2016 (n = 293). Data was obtained retrospectively, and included program entry grade-point average (GPA) and CPNRE result, as well as chemistry, English, biology, and math admission test scores.
The predictors of chemistry, English, math admission test scores, and program entry GPA did not have an effect beyond the effects of the model's predictors. In this model, the R suggests that 9% of the variance can be explained, and 91% not explained. In consideration of all independent variables, findings indicate that mean biology admission test scores (M =74.96) are a predictor of student CPNRE success. Additionally, students who pass the CPNRE have a higher program GPA.
Academic factors including program entry GPA, English, math, biology and chemistry admission scores are a fragment of the characteristics to be considered when determining the predictability of success in PN students. Therefore, it is imperative that program admission processes identify and measure nonacademic program entry criteria, as academic criterion have limited predictability. Furthermore, in isolation, academic admission criteria could be used to identify at-risk-students for appropriate remediation/counselling or as a placement test.
学术机构面临着保持近乎完美的保留率同时培养成功学生的压力。使用标准化入学考试为申请人的选择提供数据驱动的决策是很常见的。当前标准化考试的可靠性和有效性各不相同，这促使加拿大的一所大型学术机构使用教师开发的入学考试来录取其实用护理（PN）专业的学生。
本项目的目标人群是来自加拿大安大略省南部一所大型公立理工学院的实用护理专业的毕业生（n=293），他们在 2014 年至 2016 年间完成了加拿大实用护士注册考试（CPNRE）。数据是回顾性收集的，包括课程入学平均绩点（GPA）和 CPNRE 成绩，以及化学、英语、生物和数学入学考试成绩。
化学、英语、数学入学考试成绩和课程入学 GPA 的预测因素对模型预测因素的影响之外没有影响。在这个模型中，R 表明 9%的方差可以被解释，91%的方差不能被解释。考虑到所有的自变量，研究结果表明，平均生物学入学考试成绩（M=74.96）是学生 CPNRE 成功的预测因素。此外，通过 CPNRE 的学生的课程 GPA 更高。
学术因素包括课程入学 GPA、英语、数学、生物和化学入学成绩是确定实用护理学生成功可预测性的特征之一。因此，在确定课程录取流程时，必须确定和衡量非学术课程入学标准，因为学术标准的预测性有限。此外，孤立地看，学术录取标准可用于识别有风险的学生，以便进行适当的补救/咨询，或作为安置考试。
