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预测入门级物理治疗师教育计划毕业生首次全国物理治疗考试成绩
Ryan Dombkowski1,2,3,4,5, Steven Sullivan1,2,3,4,5, Tricia Widenhoefer1,2,3,4,5
1Ryan Dombkowski Doctor of Physical Therapy Program at the Trine University.
Journal, physical therapy education
|March 13, 2024
概括
学术变量可以预测物理治疗考试的成功. 结合本科GPA,基础科学GPA和综合考试成绩的模型可以识别需要国家物理治疗考试 (NPTE) 支持的学生.
科学领域:
- 物理治疗教育教育 物理治疗教育
- 学术成绩预测预测
- 许可证审查 许可证审查
背景情况:
- 国家物理治疗考试 (NPTE) 评估入门级物理治疗师的能力.
- 之前的研究发现了影响NPTE成绩的申请人和学生变量.
- 很少有研究将这些变量结合起来来预测NPTE结果.
研究的目的:
- 开发和评估模型来预测首次NPTE成绩.
- 使用学术变量预测NPTE通过/失败的结果.
- 为物理治疗计划提供一个框架.
主要方法:
- 利用了来自185名物理治疗师毕业生的入院前后数据.
- 使用多重线性回归来预测NPTE得分.
- 使用二进制物流回归来预测NPTE结果.
主要成果:
- 一个结合本科预先条件GPA,课程基础科学GPA和综合考试成绩的模型解释了30.9%的NPTE分数差异.
- 这个模型准确地预测了NPTE结果 (通过/失败) 81.1%的时间.
结论:
- 通过结合申请人和学生的学术变量来增强NPTE绩效预测.
- 识别出面临NPTE斗争风险的学生可以获得有针对性的支持.
- 该研究为学术课程干预提供了实际框架.
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