Progress Monitoring of Reading Comprehension: Comparing Content-Specific and Maze Curriculum-Based Measurement

Abstract

A substantial body of research supports the use of data-based decision making (DBDM) to support student reading progress, particularly in the areas of foundational skills such as word reading and oral reading fluency; less is known about DBDM in the context of reading comprehension. In this study, we compared a researcher-developed content-specific curriculum-based measurement (CS-CBM) with a standardized Maze CBM to determine the ways in which these sources of data may mediate student reading comprehension outcomes. Students’ progress was monitored using the CS-CBM and the Maze CBM during a reading comprehension intervention (Strategies for Reading Information and Vocabulary Effectively; STRIVE) paired with data-based decision making (DBDM). Findings reveal that both measures have potential utility in the decision-making process; the CS-CBM may be more predictive of outcomes as well as more sensitive to student growth over time, specifically for students receiving content-area reading comprehension intervention.