Student performance reflects many factors beyond their teacher's effectiveness, yet teacher evaluations often reflect how well their students do on standardized tests. RAND researchers are nationally recognized for their work using value-added modeling to distinguish a teacher's impact from factors such as individual ability, family environment, past schooling, and peer influence.
Value-added models, or VAMs, attempt to measure a teacher's impact on student achievement apart from other factors, such as individual ability, family environment, past schooling, and the influence of peers. Value-added estimates enable relative judgments but are not absolute indicators of effectiveness.
Structured observation protocols for assessing how teachers provide lessons to their students offer the opportunity to provide teachers with valuable feedback on how their practices could be improved, writes Terrance Dean Savitsky.
Judging teachers' performance by that of their students is fraught with the potential for error and unintended consequences, but several states and districts have been striving to incorporate student performance data in ways that are accurate and fair.
An accurate combined measure of teacher effectiveness would be the gold standard to capture and communicate information about the quality of educators. While the challenges to building such a measure are significant, research can help guide the way.
A new RAND Education website provides objective, nonpartisan insights that can help inform the discussion on how to measure teacher effectiveness.
Many factors contribute to a student's academic performance, but research suggests that, among school-related factors, teachers matter most. What's less clear is how to measure an individual teacher's effectiveness. A new RAND Education website features fact sheets, blog posts, research briefs, and more on this important issue.
This fact sheet describes value-added modeling and its limitations in measuring teaching effectiveness.
In this paper, we outline a practical guide for policymakers interested in developing institutional performance measures for the higher education sector.
This article develops a validity argument approach for use on observation protocols currently used to assess teacher quality for high-stakes personnel and professional development decisions.
In this article, we discuss controlling simultaneous errors in classification of teachers or schools by a decision-theoretic approach.
Assesses the effect that missing data in student achievement records, and the assumption that such data are missing at random, have on value-added modeling approaches to using student achievement data to assess school and teacher performance.
Researchers develop the "generalized persistence" (GP) model, a Bayesian multivariate model for estimating teacher effects that accommodates longitudinal data that are not vertically scaled by allowing less than perfect correlation of a teacher's effects across test administrations.
The authors analyze the systems of three districts and two states that have begun or are planning to incorporate measures of student performance into teacher evaluations.
The Los Angeles Times has published a series of articles and developed a database that include value-added statistical estimates of the effectiveness of individual teachers in the Los Angeles Unified School District based on analyses of student test scores. Although the Times has sought to be clear on this point, some readers of the coverage have inferred that the RAND Corporation did these analyses. That inference is wrong; RAND was not involved in the Times' analysis or reporting.
Addresses complex issues related to teacher assessment and teacher quality.
This article studies the year-to-year variability in value-added measures for elementary and middle school mathematics teachers from five large Florida school districts.
This article develops a model for longitudinal student achievement data designed to estimate heterogeneity in teacher effects across students of different achievement levels.
Examines how Pennsylvania's value-added assessment program has been implemented at the district, school, and classroom levels and its effects on student achievement.
Demonstrates through analysis and simulation that the mixed model approach to tracking repeated measurements can mitigate bias due to uncontrolled differences among individuals, and applies it to student achievement measures.
Interest in value-added models relying on longitudinal student-level test score data to isolate teachers' contributions to student achievement.