Does value-added modeling (VAM) demonstrate the importance of teachers to student outcomes? The authors clarify the primary questions raised by VAM for measuring teacher effects, review the most important recent applications of VAM, and discuss a variety of statistical and measurement issues that might affect the validity of VAM inferences. The authors identify numerous possible sources of error and bias in teacher effects and recommend a number of steps for future research into these potential errors.

This text clarifies the primary questions raised by the use of value-added models (VAM) for measuring teacher effects, reviews the most important recent applications of VAM, and discusses statistical and measurement issues associated with VAM.

Since passage of the of No Child Left Behind Act in 2001, academic researchers, econometricians, and statisticians have been exploring various analytical methods of documenting students‘ academic progress over time. Known as value-added models (VAMs), these methods are meant to measure the value a teacher or school adds to student learning from one year to the next. To date, however, there is very little evidence to support the trustworthiness of these models. What is becoming increasingly evident, yet often ignored mainly by policymakers, is that VAMs are 1) unreliable, 2) invalid, 3) nontransparent, 4) unfair, 5) fraught with measurement errors and 6) being inappropriately used to make consequential decisions regarding such things as teacher pay, retention, and termination. Unfortunately, their unintended consequences are not fully recognized at this point either. Given such, the timeliness of this well-researched and thoughtful book cannot be overstated. This book sheds important light on the debate surrounding VAMs and thereby offers states and practitioners a highly important resource from which they can move forward in more research-based ways.

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.

The Strategic Management of Charter Schools addresses the challenges facing such schools by mapping out, in straightforward and highly pragmatic terms, a management framework for them. The first charter school law in the United States was enacted in Minnesota in 1991. In the twenty years since that modest beginning, the movement has burgeoned and spread across the country: there are now more than five thousand charter schools attended by nearly two million students. Yet due to this rapid growth in the number of charter schools and to their generally independent character, the nature and quality of these institutions vary greatly. The promise of charter schools is great, but so are the organizational and educational challenges they face. Organized around three crucial challenges to charter school leaders--managing mission, managing internal operations, and managing the larger stakeholder environment--the book provides charter school leaders with indispensable tools and insights for achieving educational and organizational success. In its elucidation of these managerial challenges, and in its equally helpful and detailed examinations of particular schools, the book offers a clear, credible approach to the efficient and sustainable management of what are still young and experimental educational institutions.--Publisher description.

Value-added models are complex statistical formulas that aim to isolate the effect a teacher has on student learning. States and districts across the nation are adopting laws and policies that will evaluate teachers, in part, using the results provided by value-added models. In many states and districts, these evaluations will be used to inform high-stakes decisions about teacher salary and retention. However, value-added models are imperfect tools for assessing teacher effectiveness, and many scholars have argued that they are not appropriate for use in high-stakes decisions. This Article provides a brief history of the use of value-added models in public education and summarizes the major criticisms of using value-added models. In this context, the Article analyzes and evaluates the extent to which substantive due process claims brought by teachers adversely affected by the results of value-added models will be successful. The Article concludes that while the system as a whole is rationally related to the objective of improving the overall effectiveness of the teaching workforce, in certain cases, individual teachers will be able to successfully claim that the results of their value-added model led to a termination that was arbitrary and capricious. Finally, the paper offers some recommendations to states and school districts on how to implement an evaluation system using value-added models to avoid substantive due process violations.

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.