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Relative Efficacy of Teacher Rankings and Curriculum-Based Measures as Predictors of Performance on High-Stakes Tests

机译:教师排名和基于课程措施的相对疗效作为高赌注测试性能的预测因素

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摘要

Data from 403 third graders were analyzed to determine relative and combined efficacy of group-administered Curriculum-Based Measures (CBMs) and Teacher Rankings of student reading and math performance taken early in the school year to predict end-of-year achievement scores. Teacher Rankings added to the power of CBMs to predict reading (R-2 change = .18) and math (R-2 change = .22). Combined CBMs and Teacher Rankings predicted at-risk status in reading (82%) and math (86%), based on logistic regression, and yielded strong area under the curve (AUC) statistics, defining risk status .88 (reading) and .82 (math). Surprisingly, Teacher Rankings yielded higher correlations with end-of-year scores than CBMs. Findings support using rankings as a simple, efficient strategy to add to the predictive power of CBMs readily available within a response to intervention (RTI) context and depicts a methodology school personnel can use to determine the relative/combined predictive power of CBMs and rankings. Of note, predictions based on Teacher Rankings vary across end-of-year performance levels.
机译:分析了403分级学生的数据,以确定小组管理课程措施(CBMS)和学生阅读和数学表现的教师排名的相对和综合疗效,以预测年终成绩得分。教师排名添加到CBM的力量以预测读数(R-2变化= .18)和数学(R-2变化= .22)。基于逻辑回归的读数(82%)和数学(86%)预测CBMS和教师排名,并在曲线(AUC)统计下产生强面积,定义风险状态.88(阅读)和。 82(数学)。令人惊讶的是,教师排名与年末分数比CBM相比产生更高的相关性。调查结果支持使用排名作为一种简单,有效的策略,以便在响应干预(RTI)背景下随时可用的CBMS的预测力量,并描绘了方法学校人员可以用于确定CBMS和排名的相对/组合预测力。注意事项,基于教师排名的预测跨年末性能水平各不相同。

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