Brewer’s “Performance Funding” plan: How to make it more equitable

by David Safier

The Performance Funding plan proposed in Brewer's budget is inherently inequitable, rewarding every school with high income students with significant extra funding while making it far more difficult for schools with low income students to receive a similar cash award. I described the inequities in two earlier posts — the first going over the theory and the second using three different schools as examples demonstrating the basic inequity of Brewer's Performance Funding system.

Personally, I don't like the concept of Performance Funding. It punishes schools with low achievement scores by lowering their funding instead of helping them to be more successful by offering expert help coupled with extra funding. (In most industrialized nations, lower performing schools are given extra resources to help them improve.) But if Arizona decides to go with some form of Performance Funding, Brewer's model needs to be changed to eliminate its inherent bias against schools with low income students.

Here's one possible Performance Funding model that would minimize or eliminate the inequities:

  1. Set an equalized base funding for all schools that will meet the educational needs of their students. Performance Funding should not be a "rob Peter to pay Paul" system where necessary funding is taken away from one school and given to another.
  2. Give extra funding to schools that exceed the reasonable expectations for student achievement, factoring in the family income of the students.
  3. Give extra funding to schools that show improvement over their previous years' student achievement.

Part 1 — giving all schools a reasonable base funding — makes sense to anyone who isn't a punish-the-poor, end-public-schooling-as-we-know-it conservative, so it needs no further explanation. Part 3 is essentially a continuation of the improvement component of Brewer's proposed formula, so it's not really a change. Part 2, however, is significantly different from Brewer's proposed formula and needs to be defined and explained.

Part 2 is an acknowlegement of the well established fact that the most accurate predictor of student achievement is family income. Every serious analysis of national and international test scores confirms that students from high income families outperform students from low income families by a significant margin. So it makes no sense to reward schools with high income students simply for performing at an expected level while schools with students at lower income levels are punished for the same reason.

I took a random sample of 100 Arizona elementary schools and looked at their A-F state grades as well as the percentage of students on free/reduced lunch. I found you could predict the grade a school would get by knowing the percentage of students on free/reduced lunch with a 50% to 70% rate of accuracy.

  • A (70% likelihood): 35% or fewer students on free/reduced lunch.
  • B (50% likelihood): 35-70% of students on free/reduced lunch.
  • C (60% likelihood): 70-85% of students on free/reduced lunch.
  • D (60% likelihood): 85% or more students on free/reduced lunch.

(The state gave very few F grades this first year, so I didn't consider F schools in my calculations.)

If a school with 85% or more students on free/reduced lunch is going to receive a D grade 60% of the time, it makes sense for a Performance Funding model to reward the 40% of schools that get a C or higher, increasing the amount they receive the more they exceed expectations. The same is true with schools likely to get a C or a B. If they exceed expectations, they should get extra funding.

However, the system breaks down for schools with 35% or fewer students on free/reduced lunch, since they are expected to get an A, which is currently the highest possible grade. Using the A-F grading system, you can't get higher than an A, so those schools can't exceed expectations, meaning they have no way of earning extra funding. But that problem can be solved by creating a new grade: A+.

The score needed to pass the AIMS test is purposely set low so 60% of Arizona students pass. (Lots of states set similarly low bars for passing their standardized tests so their passing rates don't look bad on national No Child Left Behind comparisons.) The percent of students passing AIMS is the single largest component of a school's grade. Because the bar is set so low, the passing rate for schools with high income students is between 85% and 95%, which virtually guarantees them a state grade of A or, at worst, a high B. But if schools at the high end are graded on their students' raw AIMS scores rather than their passing rate, you can create an A+ grade that will indicate which of the high income schools exceed expectations. Here's how it would work.

The state calculates every school's mean (average) score on the AIMS Reading and Math tests, the only two tests the state uses to determine a school's grade. Combining those scores gives you a figure that has a greater range than the AIMS passing score.

Statewide, the lowest combined mean AIMS scores are about 700, and the highest are about 1300. Among the schools in my sample with 35% or fewer students on free/reduced lunch, there was a 60% likelihood they would get combined mean scores ranging from 880 to 920. So any high income school with a score above 920 would be exceeding expectations and be as deserving of extra funding as schools at other income levels that perform above expectations.

By factoring the family income of students into the Performance Funding equation (using free or reduced lunch as a proxy for income), the economic playing field is leveled. All schools have an equal chance of receiving the extra Performance Funding based on their success with their students as measured by the AIMS test, not based on parental income.

NOTE: The numbers I've used here are based on a small sample and are meant to be reasonable approximations, not absolutely accurate figures. If a system like this were put into place, someone would need to perform a more sophisticated statistical analysis of the data, then decide how to scale the extra funding based on the degree to which a given school exceeds expectations. The ways to reward improvement would also need to be changed somewhat using this system.