混合效应位置尺度模型用于联合建模学校增值效应对学生成绩的平均值和差异的影响
George Leckie1, Richard Parker1, Harvey Goldstein1
1University of Bristol.
概括
新的学校附加值模型分析了成绩变化,而不仅仅是平均分数. 这有助于识别异常高或低学生学习传播的学校,提高问责制.
科学领域:
- 教育测量和统计学
- 量化教育研究 量化教育研究
背景情况:
- 学校附加值模型 (VAM) 是基于学生学习收益评估学校绩效的标准.
- 传统的VAM使用混合效应模型来估计学生的平均成绩,控制先前的成绩和背景因素.
- 这些模型提供了"学校附加值得分",代表了学生成绩差异的平均值.
研究的目的:
- 通过分析学校内学生成绩的差异来扩展传统的学校附加值模型.
- 为了确定在学生成绩中异常高或低的变化,超出平均成绩的学校.
- 为学校问责制系统和教育研究提供新的见解.
主要方法:
- 配合混合效果的位置尺度模型.
- 扩展传统的混合效应线性回归VAM以同时建模学生成绩的平均值和差异.
- 分析学生成绩数据,以估计学校一级的中心趋势和分散.
主要成果:
- 提出的方法允许估计和研究学校特定的成绩差异.
- 确定了在学生成绩上具有统计学意义的高或低变化,独立于VAM平均分数的学校.
- 证明了将位置规模模型应用于VAMs的可行性,以进行更丰富的学校绩效分析.
结论:
- 除了平均值之外,分析成绩差异还可以更全面地了解学校的有效性.
- 这种方法可以识别出具有明显成就模式的学校 (例如,高一致性与高可变性).
- 这些发现对改进学校问责制指标和指导教育干预措施有重大影响.
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