Estimating Model-Based Oral Reading Fluency: A Bayesian Approach

Abstract

Oral reading fluency (ORF), used by teachers and school districts across the country to screen and progress monitor at-risk readers, has been documented as a good indicator of reading comprehension and overall reading competence. In traditional ORF administration, students are given one minute to read a grade-level passage, after which the assessor calculates the words correct per minute (WCPM) fluency score by subtracting the number of incorrectly read words from the total number of words read aloud. As part of a larger effort to develop an improved ORF assessment system, this study expands on and demonstrates the performance of a new model-based estimate of WCPM based on a recently developed latent-variable psychometric model of speed and accuracy for ORF data. The proposed method was applied to a data set collected from 58 fourth-grade students who read four passages (a total of 260 words). The proposed model-based WCPM scores were also evaluated through a simulation study with respect to sample size and number of passages read.