Classification Accuracy Of Oral Reading Fluency And Maze In Predicting Performance On Large‐Scale Reading Assessments
Published online on May 06, 2014
Abstract
The purpose of this study was to examine whether using a multiple‐measure framework yielded better classification accuracy than oral reading fluency (ORF) or maze alone in predicting pass/fail rates for middle‐school students on a large‐scale reading assessment. Participants were 178 students in Grades 7 and 8 from a Midwestern school district. The multiple‐measure framework yielded classification accuracy rates that were either similar to, or better than, the individual predictors. Specificity was improved using a combined measure of ORF and maze versus individual predictors alone. Educational implications for identifying students in need of reading intervention are discussed.