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Updated: May 26, 2025
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Using Learning Outcome Measures to assess Doctoral Nursing Education
Published on: June 21, 2010
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使用数据驱动程序变化:重新计算NCLEX-RN成功率
Lucy Graham1, Mary Jo Stanley1, Erin C Donovan1
1Moss School of Nursing, Department of Health Sciences, Colorado Mesa University, United States of America.
概括
护理课程课程失败强烈预测较低的第一次NCLEX-RN通过率. 招生前的GPA和卡普兰分数也与NCLEX-RN考试的成功相关.
科学领域:
- 护理教育 护理教育
- 高等教育 高等教育
- 健康 专业 教育 卫生 专业 教育
背景情况:
- 护理课程使用不同的入学标准来选择合格的学生.
- 高学业成绩并不能保证在注册护士国家委员会执照考试 (NCLEX-RN) 中取得成功.
- 许多护理课程采用过时或未经验证的入学流程,突出显示了数据驱动改进的必要性.
研究的目的:
- 为了识别与首次NCLEX-RN通过率相关并预测的易于获得的变量.
- 通过数据分析改进护理课程录取和学生支持策略.
主要方法:
- 使用了追溯的定量描述性设计.
- 分析了四组传统护理学士 (BSN) 学生的数据.
- 预录取标准,人口统计学变量,卡普兰考试成绩和护理课程失败率与NCLEX-RN第一次尝试通过率进行了比较.
主要成果:
- 护理学校课程失败成为第一个尝试失败NCLEX-RN的最重要的预测因素.
- 护理学前学业平均成绩 (GPA) 和入学前卡普兰成绩是NCLEX-RN成功的统计学上显著的预测指标.
- 与其他变量相比,预护理学校GPA解释了NCLEX-RN第一次失败率变异的比例较大.
结论:
- 对护理课程数据的全面审查对于实施有意义的,持久的变化至关重要.
- 基于数据的决策可以帮助护理课程超越表面的改进,在学生的成绩上取得实质性的进步.
- 根据预测数据修订录取标准可能会提高NCLEX-RN通过率.
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