The focus on teacher quality has prompted an abundance of research and development on how to gauge educator effectiveness. The most controversial of the new evaluation approaches is value-added modeling or VAM.
VAM is being used by a growing number of districts due to recent statistical advances that make it possible to look at student achievement gains after adjusting for some student and school characteristics. As more experience is gained with VAM, new research indicates that it is not the panacea hoped for by policymakers. A recent report from the Economic Policy Institute (EPI) titled Problems with the Use of Student Test Scores to Evaluate Teachers 
points out the good, the bad, and the ugly about these new VAM methods.
Value-added measures are considered to be fairer comparisons of teachers than judgments based on their students’ test scores at a single point in time or comparisons of cohorts that involve different students at two points in time. Indeed, VAM methods have contributed to stronger analyses of school progress, program influences, and the validity of evaluation methods than were previously possible. Used with caution, value-added modeling can add useful information to a comprehensive analysis of student progress.
Broad agreement is emerging among statistical researchers that student test scores alone are not sufficiently reliable and valid indicators of teacher effectiveness to be used in high stakes personnel decisions. VAM estimates have proven to be unstable across statistical models, years, and classes that teachers teach. One study found that across five large urban districts, among teachers who were ranked in the top 20 percent of effectiveness in the first year, fewer than a third were in that top group the next year, and another third moved all the way down to the bottom 40 percent. The instability can be the result of:
Aside from an individual teacher’s influence, student learning is also strongly influenced by other teachers, school conditions, scheduling practices, summer learning loss, and other variables that cannot be isolated for effect.
Despite the problem with instability, many policymakers have encouraged the use of VAM methods to make decisions about teacher quality, teacher compensation, and teacher removal. Aside from inaccurate personnel decisions, other negative consequences have resulted from overreliance on VAM in teacher evaluation. Research shows that an excessive focus on basic math and reading scores can lead to narrowing and oversimplifying the curriculum and discourage teachers from wanting to work in schools with the neediest students.
Do these findings mean that value-added modeling should be scrapped? Researchers say no. Used with caution, along with other evaluation approaches, VAM can be useful. VAM proponents say that a minimum of three years of data is needed to infer a teacher’s effect and most advocate the use of multiple measures of evaluation. EPI researchers concluded that changes in test scores should be used only as a modest part of a broader set of evidence about teacher practice.
Some other approaches to teacher evaluation, with less reliance on test scores, have been found to improve teachers’ practice while identifying differences in teacher effectiveness. These approaches use systematic, research-based protocols to examine teaching, including observations or videotapes of classroom practice, teacher interviews, and artifacts such as lesson plans, assignments, and student work samples. Student learning gains supplement these observations of teacher practice through multiple measures that include test scores.
Researchers acknowledge that there is no perfect way to evaluate teachers. However, progress has been made in developing standards-based evaluations of teaching practice and research finds that the use of these methods by some districts has provided both useful and valid evidence about teaching practice and improvements in student achievement.
