Curriculum-Based Measurement of Reading Progress Monitoring: The Importance of Growth Magnitude and Goal Setting in Decision Making

Author Note. The research reported here was supported by the Institute of Education Sciences, U.S. Department of Education, through Grant R324A130161 to the University of Minnesota. The opinions expressed are those of the authors and do not represent views of the Institute or the U.S. Department of Education.

Theodore J. Christ, PhD, has equity and royalty interests in and will serve on the board of directors for FastBridge Learning (FBL), a company involved in the commercialization of the Formative Assessment System for Teachers (FAST). The University of Minnesota also has equity and royalty interests in FBL. These interests have been reviewed and managed by the University of Minnesota in accordance with its conflict-of-interest policies.

Abstract

Research regarding the technical adequacy of growth estimates from curriculum-based measurement of reading progress monitoring data suggests that current decision-making frameworks are likely to yield inaccurate recommendations unless data are collected for extensive periods of time. Instances where data may not need to be collected for long periods to make defensible decisions are presented. Recommendations to collect data for upwards of 3 months may be appropriate for students whose rate of improvement (ROI) approximates the criterion to which their performance is being compared. A framework is presented to help evaluate whether a student's ROI is substantially discrepant from an expected rate of growth (i.e., goal line). A spreadsheet program was created that used user-specified parameters for goal line magnitude, dataset variability, and data collection duration, in order to identify critical ROIs to determine whether students were making adequate progress with different levels of certainty. Analyses suggest that decisions may be feasible sooner than previously thought, particularly when growth is highly discrepant from the goal line and variability in the data is limited. Implications, limitations, and directions for future research are discussed.

Keywords:

• Curriculum-based measurement
• progress monitoring
• decision rules

Additional information

Notes on contributors

Ethan R. Van Norman

Ethan R. Van Norman, PhD, is an assistant professor in the school psychology program in the Department of Counseling and Psychological Services at Georgia State University. His research primarily focuses on evaluating and improving the technical adequacy of academic and behavioral measures used in schools. In addition, Dr. Van Norman conducts research aimed at building the capacity of educators and school psychologists to use data meaningfully to make sound educational decisions.

Theodore J. Christ

Theodore J. Christ, PhD, is a professor of school psychology in the Department of Educational Psychology and is the director for the Center of Applied Research and Educational Improvement (CAREI) and codirector of the Research Institute for Problem Solving, all at the University of Minnesota. It was his work in those roles that established him as the founder and chief scientific officer of FastBridge Learning (www.fastbridge.org). Dr. Christ is engaged in innovating techniques and technology to serve professional educators who seek to improve educational outcomes. He is interested and engaged with the content, methodology, analytics, technology, software, and people who pursue the same.

Kirsten W. Newell

Kirsten W. Newell, PsyS, NCSP, is a doctoral candidate in the school psychology program at the University of Minnesota. Her years of practice, with a focus on implementation of universal screening, inform her current research. She is interested in how educators understand and use assessment data, particularly for the special population of bilingual students.