Association for Public Policy Analysis & Management

Policymakers are increasingly looking to the public education system to close the achievement gaps that exist between advantaged and disadvantaged students when they start kindergarten, but research on the extent to which schools are able to level the playing field has been disheartening. While there is evidence that schooling interventions—and the impact of teachers in particular—could help close these gaps, they often don’t because teacher quality itself is inequitably distributed across students.

In response to mounting evidence of “teacher quality gaps” (TQGs) between advantaged and disadvantaged schools, the federal government has recently directed states to develop plans to reduce inequity in the distribution of teacher quality across public schools. Unfortunately, states are forced to develop these plans in what is close to an empirical vacuum about the history of these TQGs. That is, existing studies of TQGs represent snapshots in time and provide virtually no information about how these gaps have changed over time or how these gaps were formed in the first place.

In this paper, we use comprehensive, longitudinal data on public school students, teachers, and schools from three “focus states”—Florida, North Carolina, and Washington—to document the evolution of TQGs in these states. Most importantly, our data covers a minimum of 15 years (in Florida) and up to 30 years (in Washington), allowing us to examine the evolution of TQGs over the past several decades. These states also differ from one another in several ways that may influence the extent and evolution of TQGs; e.g., terms of collective bargaining rights, teacher salaries, average district size, charter school history, and student diversity. We can therefore assess the extent to which these patterns may be generalizable to different settings.

Data from these states include many different measures of teacher quality and student disadvantage that we can use to calculate TQGs. Specifically, we can measure teacher quality in terms of experience, credential test scores, and value-added estimates of effectiveness. Likewise, we can categorize students as disadvantaged if they are eligible for free/reduced lunch or are from an underrepresented minority group. For each combination of teacher quality measure and student disadvantage measure, we can calculate the corresponding TQG in each state and year as the average difference in teacher quality between teachers of advantaged and disadvantaged students. We can then paint a complete picture of the evolution of TQGs along a number of different dimensions.

We will also investigate the extent to which TQGs are due to differences across districts, across schools within a district, and across classrooms within a school. This is important because it helps to inform the level that policymakers looking to close TQGs should focus on. For example, policymakers may wish to focus on statewide interventions, such as revisions to state funding formulas, if most inequity is at the district level. On the other hand, if the majority of state-level TQGs are explained by within-district disparities, it might be more efficacious to focus on within-district salary incentives or differences in school working conditions.