Practical Effects of Classwide Mathematics Intervention

Abstract.

The current article presents additional analyses of a classwide mathematics intervention, from a previously reported randomized controlled trial, to offer new information about the treatment and to demonstrate the utility of different types of effect sizes. Multilevel modeling was used to examine treatment effects by race, sex, socioeconomic status, special education status, and achievement risk status and did not indicate differences in intervention effects on year-end state test scores by subgroup. Multilevel modeling analyses found score differences on spring curriculum-based measurements by race, treatment assignment, and prior educational risk, but only treatment assignment predicted differences in gains over time, favoring the intervention group for two of the three measures. Race and treatment assignment predicted differences in gains for one measure. Nonproficient scorers were proportionate by all demographic categories in the intervention group, but in the control group, there were disproportionately higher numbers of African American students, students receiving special education services, and students with an initial achievement risk who scored in the nonproficient range on the year-end test. Risk reduction analyses, including absolute risk reduction, relative risk reduction, and number-needed-to-treat (NNT) estimates, were computed overall and by subgroup. Overall, the data suggested stronger intervention effects for students who began the intervention at greater risk, including students of minority ethnicity (NNT = 4), students receiving special education (NNT = 3), and students with initial achievement risk (NNT = 3), in this sample.

Additional information

Notes on contributors

Amanda M. VanDerHeyden

Amanda M. VanDerHeyden, PhD, is a private consultant and researcher living in Fairhope, Alabama. She is a frequent contributor to the literature in mathematics, with a particular focus on data-based decision making and systemic intervention. She serves as senior adviser to Edspring (www.edspring.com) and Technology and Information Educational Services (TIES) and is the developer of Intervention Adviser, a web-based assessment and intervention system for mathematics for students in Grades K–8. She is coauthor of the Evidence-Based Mathematics Innovation Configuration for the National Comprehensive Center for Teacher Quality at Vanderbilt University and now the Collaboration for Effective Education Development, Accountability, and Reform at the University of Florida. Her most recent book is The RTI Approach to Evaluating Learning Disabilities (Kovaleski, VanDerHeyden, & Shapiro, 2013). Dr. VanDerHeyden is active on a number of boards focused on improving learning outcomes for children.

Robin S. Codding

Robin S. Codding is an associate professor of school psychology at the University of Massachusetts Boston. She earned her PhD from Syracuse University. Dr. Codding completed her predoctoral internship and postdoctoral fellowship at the May Institute, where she served as an educational and behavioral consultant. Dr. Codding has served in the role of Associate Editor for the Journal of Behavioral Education and the Journal of School Psychology. Dr. Codding's research interests focus on the intersection of intervention and implementation by developing and exploring the effectiveness of school-based interventions, the factors that contribute to student responsiveness of those interventions, and strategies to support intervention implementation. Dr. Codding's work has emphasized academic interventions and associated assessment for data-based decision making, particularly in the area of mathematics.