Abstract
An ongoing concern for researchers, policy makers, and educators is the contribution to student achievement of educational inputs such as individual schools and teachers, interventions, teaching practices, and school policies. Value-added modeling estimates such effects from longitudinal student achievement data. This article provides an overview of Value-Added Models (VAMs) by describing representative examples of econometric, statistical, and alternative approaches and their essential features. It also discusses the concerns that value-added modeling estimates may be biased or lack sufficient stability and precision to support desired inferences.
| Original language | English (US) |
|---|---|
| Title of host publication | International Encyclopedia of Education |
| Subtitle of host publication | Fourth Edition |
| Publisher | Elsevier |
| Pages | 390-396 |
| Number of pages | 7 |
| ISBN (Electronic) | 9780128186299 |
| DOIs | |
| State | Published - Jan 1 2022 |
Keywords
- Bias
- Cross-classified models
- Fixed effects models
- Hierarchical linear models
- Layered model
- Longitudinal data
- Precision
- School effects
- Teacher effects
- Teacher evaluation systems
- Variable persistence model
ASJC Scopus subject areas
- Social Sciences(all)