{"title":"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","authors":"Joseph F. T. Nese, Akihito Kamata","doi":"10.1177/1534508420937801","DOIUrl":null,"url":null,"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.","PeriodicalId":1,"journal":{"name":"Accounts of Chemical Research","volume":null,"pages":null},"PeriodicalIF":16.4000,"publicationDate":"2020-07-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1177/1534508420937801","citationCount":"2","resultStr":"{\"title\":\"Addressing the Large Standard Error of Traditional CBM-R: Estimating the Conditional Standard Error of a Model-Based Estimate of CBM-R\",\"authors\":\"Joseph F. T. Nese, Akihito Kamata\",\"doi\":\"10.1177/1534508420937801\",\"DOIUrl\":null,\"url\":null,\"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.\",\"PeriodicalId\":1,\"journal\":{\"name\":\"Accounts of Chemical Research\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":16.4000,\"publicationDate\":\"2020-07-02\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://sci-hub-pdf.com/10.1177/1534508420937801\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Accounts of Chemical Research\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1177/1534508420937801\",\"RegionNum\":1,\"RegionCategory\":\"化学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"CHEMISTRY, MULTIDISCIPLINARY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Accounts of Chemical Research","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1177/1534508420937801","RegionNum":1,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"CHEMISTRY, MULTIDISCIPLINARY","Score":null,"Total":0}
Addressing the Large Standard Error of Traditional CBM-R: Estimating the Conditional Standard Error of a Model-Based Estimate of CBM-R
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.
期刊介绍:
Accounts of Chemical Research presents short, concise and critical articles offering easy-to-read overviews of basic research and applications in all areas of chemistry and biochemistry. These short reviews focus on research from the author’s own laboratory and are designed to teach the reader about a research project. In addition, Accounts of Chemical Research publishes commentaries that give an informed opinion on a current research problem. Special Issues online are devoted to a single topic of unusual activity and significance.
Accounts of Chemical Research replaces the traditional article abstract with an article "Conspectus." These entries synopsize the research affording the reader a closer look at the content and significance of an article. Through this provision of a more detailed description of the article contents, the Conspectus enhances the article's discoverability by search engines and the exposure for the research.