Value-added methods refer to efforts to estimate the relative contributions of specific teachers, schools, or programs to student test performance. In recent years, these methods have attracted considerable attention because of their potential applicability for educational accountability, teacher pay-for-performance systems, school and teacher improvement, program evaluation, and research. Value-added methods involve complex statistical models applied to test data of varying quality. Accordingly, there are many technical challenges to ascertaining the degree to which the output of these models provides the desired estimates. Despite a substantial amount of research over the last decade and a half, overcoming these challenges has proven to be very difficult, and many questions remain unanswered--at a time when there is strong interest in implementing value-added models in a variety of settings.
The National Research Council and the National Academy of Education held a workshop, summarized in this volume, to help identify areas of emerging consensus and areas of disagreement regarding appropriate uses of value-added methods, in an effort to provide research-based guidance to policy makers who are facing decisions about whether to proceed in this direction.
Table of Contents
|1 Introduction to Value-Added Modeling||1-14|
|2 Uses and Consequences of Value-Added Models||15-26|
|3 Measurement Issues||27-40|
|4 Analytic Issues||41-54|
|5 Considerations for Policy Makers||55-68|
|Appendix A: Workshop Agenda and Participants||73-78|
|Appendix B: Biographical Sketches of Committee Members and Staff||79-82|
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