The purpose of the present study was to examine the predictive ability of oral reading fluency (R-CBM) on a sixth grade high-stakes assessment with ELL and non-ELL students, as well as determine the average rate of growth on R-CBM and how that relates to level of English Proficiency. The participants in the current study included 350 sixth grade students from a middle school located in west Phoenix, AZ. Ninety of the 350 students were English Language Learners at varying levels of language proficiency in English. Archival data was used for the study. Each participant completed R-CBM three times throughout the 2006–2007 school year (fall, winter, and spring benchmarks), the Maze assessment (administered once in early spring), and the state accountability exam (AIMS) given in the spring. Of the 350 total students in the sample, 90 also were administered a Language proficiency exam (Arizona English Language Learner Assessment), due to their ELL status. In an attempt to avoid statistical and interpretive problems with the data analysis, HLM, multiple regression, and data visualization was used. This study was conducted for the purpose of examining the typical rate of growth on R-CBM over one school year for ELL and non-ELL students. It also assisted in determining whether reading screening measures (R-CBM, Maze) are effective in predicting future reading success or failure.

Results indicated that the average initial status as measured by the Fall R-CBM was 103.51 words read correctly per minute with an average growth rate (slope) of 10.36 words read correct from Fall to Winter, and from Winter to Spring. Thus, the overall growth was about 20.72 words over one school year. The results indicated that there was significant variation between ELL and non-ELL students in their initial status as measured by the Fall R-CBM score. However, while ELL students score significantly lower in the Fall on R-CBM, they did not vary in their growth trajectories from non-ELL students throughout the school year. Students varied significantly based on their AIMS level in their initial status as measured by the fall R-CBM score, but did not vary significantly on their growth rates relative to their performance level on AIMS. The regression analysis for the overall student population showed that Fall RCBM (initial status), percentage of growth on RCB from Fall to Spring, and ELL status were all significant predictors of student performance on AIMS. The Maze assessment was not a significant predictor. A student’s initial status, as measured by the Fall R-CBM measure, was the most important factor in predicting whether that student will meet the state standards on the AIMS assessment in the spring for both the ELL and non-ELL populations. Implications for instruction and suggestions for future research are discussed.