Examining the accuracy of curriculum-based measurement progress monitoring in reading: Alternative methods for evaluating technical adequacy

Date of Award


Degree Type


Degree Name

Doctor of Philosophy (PhD)




Tanya L. Eckert


Curriculum-based measurement, Progress monitoring, Reading, Technical adequacy

Subject Categories

Curriculum and Instruction | Education | Educational Psychology | Psychology | Social and Behavioral Sciences


Before an assessment measure can be considered technically adequate, several factors must be examined including reliability, validity and accuracy. Although several studies have been conducted examining the reliability and validity of Curriculum-Based Measurement (CBM) progress monitoring, few have examined the accuracy. Those that have suggest a large amount of variability within student performance over time, suggesting that trend lines and other outcome measures used to evaluate student performance may not accurately represent student performance from day to day. Currently, CBM progress monitoring is conducted by assessing student's oral reading fluency, or the number of words read correctly in one minute (WRCM). One way to decrease variability in student performance over time, when no instructional changes are made, may be to increase the duration of the oral reading fluency passages. The purpose of the present study was to compare the accuracy of CBM trend lines and the sensitivity of CBM progress monitoring procedures when one-minute and three-minute passages are employed. In addition, this study compared the extent to which trend lines based on data collected between four weeks and nine weeks can be used to predict future student performance when no changes in programming are made. Finally, the present study employed the use of Hierarchical Linear Modeling (HLM) to examine the amount variability in student performance over time. The results of this study suggest, with respect to one-minute and three-minute passages, that three-minute passages may provide a better estimate of student performance when administered over time. Similarly, the three-minute passages were better able to predict student performance. The results of the HLM analyses suggest there is variability between students in performance over time; however, the variability within students suggests a large amount of noise in student performance that may make interpretation of CBM progress monitoring data difficult. Therefore, practitioners should be cautious when using a limited amount of data to make instructional decisions. In addition, it does not appear that trend lines accurately represent student performance over time.