Overview
Throughout this 5-year project, we aim to advance the understanding of persistent gaps in reading achievement across populations disproportionately affected by documented health disparities. We investigate potential sources of individual differences in intervention effects by aggregating data from multiple rigorous studies of supplemental reading interventions that provide intensive, targeted support to students with or at risk for reading disabilities. To date, few studies separate findings by students’ background, making it difficult to know whether reading interventions deemed evidence based are broadly applicable.
Purpose
In this project, we aim to explore variability in the effectiveness of supplemental reading interventions. The project is built on a cross-disciplinary framework that draws on bioecological systems theory to emphasize the role of dynamic interactions within and between our social environments in shaping outcomes. This framework recognizes that interventions may not operate uniformly and that complex systems may differentially influence the effectiveness of these interventions for different subsets of students.
Procedures
The overall goal of this project will be addressed through three specific aims. First, we assemble an integrated dataset with data from rigorous reading intervention studies. Second, we use the integrated data to determine whether there are differential intervention effects for Black students compared to their White peers. And finally, we identify characteristics of students, interventions, and outcomes that explain variation in response to reading interventions. The integrated dataset will be archived and shared on LDbase, a data repository funded by the National Institutes of Health containing decades of knowledge from educational and developmental sciences.
Participants
This project uses deidentified student-level data from existing studies of supplemental reading interventions conducted with kindergarten to 12th-grade students in the United States. The IDARE project website outlines inclusion criteria for a dataset to become part of the IDARE project.