Using Regression-Adjusted Graduation Rates to Benchmark Demographically Similar Schools

Using Regression-Adjusted Graduation Rates to Benchmark Demographically Similar Schools

March 19, 2020

In EducationNext, Erica Blom and Theresa Anderson make a case for the use of regression-adjusted graduation rates to compare schools “against other schools with similar demographics, allowing for fairer comparisons.” This, they argue, “allows the performance of entire schools to be meaningfully compared without having to compare each subgroup separately.” The subgroups refer to the “four different dimensions” that the Every Student Succeeds Act requires schools to break out graduation rates into: economic disadvantage, race or ethnicity, English learner, and disability status. While implementation questions remain, adjusting graduation rates for student disadvantage would allow for a more direct comparison of schools with similar demographics, which would be “a good first step to make quality measurement more accurate and fair.”