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.
An rapidly developing outcomes-based culture among policymakers in the higher education sector recognizes the need for measures of value-added to capture the effect of institutions on their students—and the power these measures can have in incentivizing better performance.
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.
Some of the most urgent and contentious debates taking hold in states and school districts around the country revolve around the question of how to accurately measure a teacher's effectiveness. A new RAND Education website provides objective, nonpartisan insights that can help inform the discussion.
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.
Value-added models attempt to measure a teacher's impact on student achievement while controlling for other factors that affect achievement, such as individual ability, family environment, past schooling, and the influence of peers.
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.
The extensive numbers of students with incomplete records and the tendency for those students to be lower-achieving presents a challenge for stakeholders attempting to develop or use value-added models in education.
The authors developed a "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.
To encourage and facilitate data-driven decisionmaking, many states and districts have begun providing staff with information from value-added assessment systems—collections of complex statistical techniques that use multiple years of test-score data to estimate the causal effects of individual schools or teachers on student learning.
Longitudinal data tracking repeated measurements on individuals are highly valued for research because they offer controls for unmeasured individual heterogeneity that might otherwise bias results.
Using longitudinal data from a cohort of middle school students from a large school district, researchers estimate separate “value-added” teacher effects for two subscales of a mathematics assessment under a variety of statistical models varying in form and degree of control for student background characteristics.