The Power of Education Data

If policymakers (see Brown, Jerry) still aren’t convinced that education data matters, two reports released this week demonstrate that high quality, actionable information about schools and students is vital in efforts to improve education and student outcomes.

Bill summarized the important work of the Data Quality Campaign yesterday. More states than ever are collecting the information educators and policymakers need to make informed decisions about what’s working and what isn’t in schools. But just because the data can be collected, it doesn’t mean that states’ work is complete. Data for Action 2011 identifies four challenges – turf, trust, technical issues, and time – that continue to hinder states’ efforts to utilize the full potential of their data (shameless plug: you should read my report, Data That Matters, for another set of 4 Ts that all states should follow to make their data user-friendly and actionable for school leaders).

In another example of the power of data, the Department of Education released a landmark study this week examining comparability in state and local funding of schools. Educators, researchers, and policy wonks have known – anecdotally or through small pockets of data – that high-poverty schools get shortchanged when it comes to state and local funding because of teacher salaries. Basically, high-poverty schools tend to be staffed by less experienced teachers who are paid entry-level salaries. But as they gain experience –and see their salaries increase accordingly – teachers often transfer to schools with fewer minorities and poor children. The Department’s report provides the first nationwide data confirming this phenomenon. In the over 13,000 districts examined, almost half of all high-poverty, Title I schools received state and local funding that was at least 10% below the average level of school spending in their district.

When the federal government first began funding high-poverty schools through Title I, a provision in the law required states and districts to demonstrate that state and local funding was comparable between Title I and non-Title I schools before federal funds were distributed. There were concerns that the new federal funding would be used to replace state and local funds, rather than enhance them. But lawmakers created a loophole in the comparability provision. Instead of requiring states and districts to include real teacher salaries in their calculation of school-level spending, a uniform salary schedule could be used instead. So long as the salaries of all teachers in the district were determined in the same manner, it didn’t matter if the highest paid, most experienced teachers were in low-poverty schools. Because actual personnel costs weren’t included, state and local per pupil expenditure data on a school-by-school basis was virtually non-existent.

Until now. How did this happen? As part of the agreement to use federal money from the stimulus package for education, states and school districts were required to report all sorts of new data to the Department, including actual school-level per pupil spending based on real teacher salaries. Thanks to the new data, we finally know the extent of the comparability loophole problem. More importantly, we have an estimate for what it might cost to fix it: according to the Department, “providing low-income schools with comparable spending would cost as little as 1 percent of the average district’s total spending.” The move could also have an outsized impact for high-poverty schools “by adding between 4 percent and 15 percent to the budget” of these schools.

This report is a powerful tool advocacy groups and legislators can use to push Congress to close the comparability loophole, like the proposal in the Harkin-Enzi ESEA Reauthorization bill. The stimulus reporting requirements were a one-time deal. It is now up to policymakers to ensure that the reporting of this data continues and to finally enforce one of the basic tenets of Title I: supplement not supplant.

See what a little data can get you?