Treatment Fidelity in Studies of Educational Intervention is a detailed guide to the increasing emphasis on methodological rigor and implementation fidelity in educational research. A timely contribution to the field, this book offers practical guidance and systematic research on the nature of implementation fidelity in experimental settings, and provides strategies for combining fidelity-related data with other data types to evaluate a program’s impact in schools and other educational settings. With contributions from leading scholars in the area of research methods in education, Treatment Fidelity synthesizes recommendations for current measurement practices, case studies of recent or ongoing research programs, and technical evaluation reports on studies that measure and model fidelity as part of estimating a treatment’s impact. Intended for scholars, professionals, and graduate students interested in school-based intervention, this volume presents information on how to address implementation in applied research.
Implementation Fidelity in Randomized Educational Trials: An Applied Perspective. Greg Roberts, Sharon Vaughn, Tasha Beretvas & Vivian Wong. Measuring Fidelity in Educational Settings. Willliam M. Murrah, Jeff J. Kosovich & Chris S. Hulleman. Features of Fidelity in Schools and Classrooms: Constructs and Measurement. Frank Gresham. Integrating Fidelity Data into the Analysis of Outcomes: Statistical Methods for Reducing Bias. Lynne Stokes, Jill H. Allor & Long Luo. Propensity Scores and Instrumental Variables as a Basis of Modeling Fidelity: Within-Study Comparisons. Greg Roberts & Nancy Scammacca. Intent-to-Treat and Treatment Take-Up Effects of Parent Training on Adolescent Developmental Outcomes. Keith Zvoch & Charles Martinez. Causal Inference and Using Implementation Fidelity Data in RCT Evaluations: The Break Through to Literacy Evaluation as Example. Fatih Unlu, et al. Concluding Remarks and Recommendations for Ongoing Programs of Research. Greg Roberts, Sharon Vaughn, Tasha Beretvas & Vivian Wong.