Classification accuracy of oral reading fluency and maze in predicting performance on large-scale reading assessments

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.