As school districts look for ways to evaluate and improve teacher performance, many turn to statistics to quantify how they’re doing. But those formulas aren’t flawless, says the American Statistical Association, which is urging caution in measuring teacher performance via “value-added” models.
As more schools are turning to statistics-based value-added models (VAMs) to evaluate teachers and schools, the American Statistical Association wants to make sure the method is being used appropriately.
It is our hope that a better understanding of the statistical perspective of VAMs will constructively inform their use in the evaluation of our nation’s teachers and the ongoing discussion.
ASA issued a new position statement [PDF] earlier this month that warns against the limitations of VAMs, which use a series of formulas to measure teacher performance in relation to students’ scores on standardized assessment tests. The use of VAMs has grown over the last several years under the Obama administration’s Race to the Top initiative.
“The ASA is issuing this statement to provide insight to all levels of the education community on what can and cannot be reasonably expected—given current knowledge and experience—from the use of VAMs,” ASA President-elect David Morganstein said in a statement. “It is our hope that a better understanding of the statistical perspective of VAMs will constructively inform their use in the evaluation of our nation’s teachers and the ongoing discussion.”
In particular, ASA noted that the value-added model measures correlations between teacher performance and student achievement, but not causation, so “effects—positive or negative—attributed to a teacher may actually be caused by other factors that are not captured in the model.”
ASA’s statement makes several recommendations for the use of VAMs in “high-stakes” decisions on issues like teacher compensation, awarding tenure, ranking teachers, hiring and dismissing teachers, and closing schools. Among them:
- ASA endorses wise use of data, statistical models, and designed experiments for improving the quality of education.
- VAMs are complex statistical models, and high-level statistical expertise is needed to develop the models and interpret their results.
- Estimates from VAMs should always be accompanied by measures of precision and a discussion of the assumptions and possible limitations of the model. These limitations are particularly relevant if VAMs are used for high-stakes purposes.
In a policy brief on VAMs, the American Education Research Association and the National Academy of Education noted that several factors, in addition to individual teacher performance, can affect student achievement, including class size, peer culture, home environments, and past teachers and schooling.
ASA added that, with their knowledge and expertise, statisticians can help analyze and determine the effectiveness of quality assessment models.
“Statisticians can play an important role in raising the quality of education,” Morganstein said. “The ASA and its members stand ready to help the education community in its efforts to improve the quality of our nation’s educational system.”