Of course, they make it as difficult as they possibly can to use that data, but where there's a will there's a way.

All this week I want to take a look at the performance of economically disadvantaged students and see what the data tells us. Let's see if the various bromides and theories we've been debating for the last few weeks find some support in the data.

I'm going to use the dataset for Pennsylvania 2005. It's not the most recent dataset (that would be 2007), but it is the latest dataset that includes financial and demographic data. I found data for 446 of Pennsylvania's 501 school districts.

Today let's focus on the relationship between school expenditures and low-SES student performance. Hardly a day goes by in which some edupundit will claim that we need more school funding to improve test scores. It's become a kneejerk reaction, especially by those slightly-left-of-center edupundits who still cling to the notion that more money can solve anything. Let's put this theory to the test.

**Theory One:**Low-SES students perform better in schools with lots of resources. Stated differently, low-SES student achievement can be improved by providing schools with more resources. To test this theory, let's compare the performance of low-SES students on PA's state test to the total expenditures in each school district.

I also calculated:**R **- The coefficient of the correlation between the score/actual data and the score predicted by the regression. For R values close to 1, there is a strong association between the variables. For R values close to zero, there is a weak association between the variables. Generally, we don't get to excited until the R values are greater than about 0.5.**R ^{2}** - the percentage of the variability in the predicted score explained by the variability in the actual data. In other words, how well does the actual data fit the predicted score. For R

^{2}values close to one, there is a good fit. For R

^{2}values, close to zero, there is a poor fit.

**P value**- If the P value is less than 0.05 we reject the null hypothesis,

*i.e.*, it is safe to assume tht the results are statistically significant.

For this regression the results are:

**R = 0.06**(there is a very weak association between total school expenditures and the performance of low-SES students)

**R**(there is a very poor fit between the data)

^{2}= 0.0036**P = 0.20**(the results are not statistically significant)

I put the trend line in the graph, but there is such a poor fit between the data and the predicted score (the trend line) that the slight downward slope of the trendline is misleading.

**Interpretation**: I calculated the average score for all PA students on a per school district basis to be 60.7 in 2005 with a standard deviation of

13.1. I also calculated the average score for low-SES students to be 43.0. this represents a large achievement gap of 1.36 standard deviation. As you can see from the graph, it didn't matter whether the school district was spending $8,000 or $19,000 per student, the performance of low-SES remained unchanged with a large amount of variation between high performing districts and low-performing districts across the board. At today's funding levels, I'd say that resources are not an issue. Especially, when you consider that, at least in PA, school districts with lots of (>50%) low-SES students are funded just as well as school districts with few (<10%)

School expenditures are weakly correlated with the number of low-SES students in a district.

In case you were wondering, I also ran the regression with instructional expenditures instead of total expenditures to see if perhaps these districts with lots of low-SES students were squandering their resources on non-instructional expenses. Apparently, they aren't. The correlation between instructional expenditures and low-SES student achievement was even weaker than that for total expenditures (

**R**= 0.03,

**R**

^{2}= 0.0012, and

**P**= 0.47).

The data does not support the theory that spending more money on schools will led to improved low-SES student achievement at today's funding levels. the data suggests that even if we doubled the funding to the typical school district, we should not expect to see improved low-SES student achievement.

## 5 comments:

Nice analysis. I don't necessarily reject your entire premise, but the data isn't really adequate to address your question.

Spending varies greatly WITHIN districts, between schools. Money follows teacher salaries, and the highest paid teachers tend to be in the schools with the highest SES students.

Paul Hill and the Education Trust West have done some great work on these types of resource inequities.

You may find that your analysis would get you similar results or you may not. But there is not a lot of good data out there because most schools don't break out real spending per school.

A second problem may be that the relationship between resources (expressed in teacher salaries) and student achievement between schools may not be linear. One hypothesis, for example, is that the relationship is curvilinear (an inverted "U"). This would reflect that teachers with some experience (but not so senior as have to become complacent, perhaps 5-10 years) who are in the middle of the salary range would provide the most effective instruction. Correlation coefficients would not find a significant relationship between resources (in this case, teacher salaries) if this were true.

Hi Charles

Spending varies greatly WITHIN districts, between schools.I'm not so sure this is the case in PA. We have 501 school districts and generally each district has 1 or 2 high school, 1 or 2 middle schools, and up to a half dozen or so elementary schools with all schools at each level getting funded similarly unless one school is a title I school in which case the school gets additional funding. I think the only two exceptions are the mega school districts of philly and pittsburgh.

Money follows teacher salaries, and the highest paid teachers tend to be in the schools with the highest SES students.

There is data for teacher resources in the dataset, so I should be able to run that comparison.

While I don't think more money may necessarily solve all the problems, I do believe that students and teachers should have the right to be in facilities that are comparable to surrounding districts.

Furthermore, in California, our governor is proposing massive cuts in education. In years past when this has happened, it has had very little impact on affluent Districts. This is because parents in these districts are often very willing to close any of the funding gaps through massive fundraisers/donations.

In my district, this is not possible. We are faced with another round of cuts to staff and the possibility of reduction to programs, such as the intervention programs we have implemented to help close the achievement gap.

We have still not recovered the last time huge cuts took place to our budget. It just gets a little disheartening.

"

...I do believe that students and teachers should have the right to be in facilities that are comparable to surrounding districts.

"Furthermore, in California, our governor is proposing massive cuts in education. In years past when this has happened, it has had very little impact on affluent Districts. This is because parents in these districts are often very willing to close any of the funding gaps through massive fundraisers/donations.

Do you have any suggestions on how to level the spending other than simply prohibiting the wealthy parents from giving money to their local school districts?

[Also in California ...]

-Mark Roulo

Anonymous,

I haven't a clue. However, I am seriously contemplating leaving my current district, due to this and other issues. While I might have to deal with other issues, it would be nice to teach in a room that doesn't have a leaky roof or one in which the janitors actually have adequate time to clean.

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