Using Curriculum-Based Measurement to Predict Eighth-Grade Student Performance on a Statewide Reading Assessment
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The purpose of this study was to analyze the relationship between oral reading fluency (ORF) and Maze, two common Curriculum-Based Measures (CBMs), and the statewide large-scale assessment of reading in Oregon, the Oregon Assessment of Knowledge and Skills- Reading (OAKS-R). A sample of three cohorts of eighth-grade students in an Oregon school district was used to examine concurrent validity, predictive validity, and the relation between demographic characteristics, disability status, and socio-economic status and the ability to predict performance on the OAKS-R. Findings of the concurrent validity analysis revealed a moderately strong positive correlation between the OAKS-R and both ORF and Maze measures, with ORF demonstrating a slightly stronger correlation with the OAKS-R. Multiple regression analyses were used to analyze the predictive relationship between ORF and Maze and scores on the eighth-grade OAKS-R. Both ORF and Maze were statistically significant predictors of OAKS-R, demonstrating moderately positive relationships with scores on the state reading test. Although no interaction effect was found between disability classification or eligibility for free or reduced-price meals and the different CBMs, in relation to the OAKS-R, student disability status was negatively related to performance on the OAKS-R. The relationship between OAKS-R performance and low socio-economic status, as measured by eligibility for free or reduced-price lunch status, was not consistent across the cohorts. This finding is promising, as it indicates that there may be factors that schools can take advantage of to ameliorate the relationship between poverty and reading outcome measures for eighth-grade students. In light of study results, suggestions for future research, as well as implications for the field, are discussed. This study adds to the research literature documenting that ORF and Maze assessments provide schools with valuable information to predict student performance on statewide large-scale assessments of reading. With CBM data available early in the school year, schools can provide additional intervention as needed, potentially leading to improved end-of-year student performance on the OAKS-R.