Addressing the Large Standard Error of Traditional CBM-R: Estimating the Conditional Standard Error of a Model-Based Estimate of CBM-R

IF 1.2 Q2 EDUCATION & EDUCATIONAL RESEARCH
Joseph F. T. Nese, Akihito Kamata
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引用次数: 2

Abstract

Curriculum-based measurement of oral reading fluency (CBM-R) is widely used across the country as a quick measure of reading proficiency that also serves as a good predictor of comprehension and overall reading achievement, but it has several practical and technical inadequacies, including a large standard error of measurement (SEM). Reducing the SEM of CBM-R scores has positive implications for educators using these measures to screen or monitor student growth. The purpose of this study was to compare the SEM of traditional CBM-R words correct per minute (WCPM) fluency scores and the conditional SEM (CSEM) of model-based WCPM estimates, particularly for students with or at risk of poor reading outcomes. We found (a) the average CSEM for the model-based WCPM estimates was substantially smaller than the reported SEMs of traditional CBM-R systems, especially for scores at/below the 25th percentile, and (b) a large proportion (84%) of sample scores, and an even larger proportion of scores at/below the 25th percentile (about 99%) had a smaller CSEM than the reported SEMs of traditional CBM-R systems.
解决传统CBM-R的大标准误差:估计基于模型的CBM-R估计的条件标准误差
基于课程的口语阅读流利度测量(CBM-R)在全国范围内广泛使用,作为阅读熟练程度的快速测量,也可以作为理解和整体阅读成绩的良好预测指标,但它存在一些实际和技术上的不足,包括测量的大标准误差(SEM)。降低CBM-R分数的SEM对教育者使用这些措施来筛选或监测学生的成长具有积极意义。本研究的目的是比较传统的CBM-R每分钟字数正确(WCPM)流畅性分数的SEM和基于模型的WCPM估计的条件SEM (CSEM),特别是对于阅读结果较差或有阅读结果风险的学生。我们发现(a)基于模型的WCPM估计的平均CSEM比传统CBM-R系统报告的ssem小得多,特别是在25百分位/以下的分数上;(b)大部分(84%)样本分数,甚至更大比例的25百分位/以下分数(约99%)的CSEM比传统CBM-R系统报告的ssem小。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
ASSESSMENT FOR EFFECTIVE INTERVENTION
ASSESSMENT FOR EFFECTIVE INTERVENTION EDUCATION & EDUCATIONAL RESEARCH-
CiteScore
3.10
自引率
0.00%
发文量
16
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