by Anna Tran
Last updated on December 6, 2022
for Data Visualization for Allwith Prof. Jack DoughertyTrinity College, Hartford CT, USA
Introduction
Although in Connecticut, over $12 billion is spent on K-12 public education, this spending is not distributed equitably across school districts and towns (School State Finance). The Education Cost Sharing (ECS) formula is used to take into consideration student learning needs when calculating costs of funding in order to more equitably fund students with learning needs.
Despite this, schools across the state are still not funded equitably (School State Finance). This results in marginalized students (BIPOC students, students with disabilities, low-income students, etc) being disproportionately affected.
According to Lauren Ruth, a research and policy director of Connecticut Voices, “We’ve seen a decline in the performance of special education students, which suggests our funding doesn’t provide an appropriate education” (Bamberger 2021). In particular, students with disabilities lack not only the funding, but the resources across Connecticut that would adequately fund their education.
In order to begin addressing these funding inequities, it is important to ask the following questions: How do enrollment rates by school type vary by students with (and without) disabilities and how does district-level per-student spending vary by percent of students with disabilities?
Funding is not adequately distributed across school districts for SWD. Even though East Hartford and New Britain school districts have the highest percentage of SWD enrolled in their schools, they also have a much lower Per Pupil Expenditure (PPE). Program school types were not included in these data sets because they are schools meant for SWD to begin with, so the main focus will be on other school types in East Hartford and New Britain.
In the following sections, I will discuss three key findings and how this shows that there are funding disparities across districts and why it matters.
When looking at what districts SWD are enrolled in, we find that there is a high percentage of SWD enrolled in East Hartford and New Britain school districts compared to other school districts in Figure 1.
East Hartford and New Britain were chosen as examples because these towns have high percentages of students with disabilities enrolled in their schools. Because of these high enrollment numbers, these were important towns to look at when taking into account funding disparities for students with learning needs.
It is also important to note that East Hartford and New Britain school districts (seen in blue in Figure 1) have three times the enrollment of SWD compared to the bottom three schools, which happen to be charter schools (seen in red in Figure 1).
Figure 1 | Link to Chart
It is necessary to note that the concentration of SWD in East Hartford and New Britain may allude to a bigger problem about funding with charter schools since these schools have the least percentage of SWD enrolled. This may be because charter schools are discouraging SWD to enroll or they simply do not have enough funding to host these students. As a result, other districts may find a higher enrollment rate of SWD instead.
There is a high percentage of SWD enrolled in neighborhood public schools compared to other school types as seen in Figure 2. Here, the term “neighborhood public schools” is used instead of “public schools” because it is not an adequate label for these types of schools. All of these school types are publicly funded, so the term neighborhood public school is used to describe schools that do not require an application process.
Figure 2 shows that both East Hartford and New Britain have higher enrollments of SWD in neighborhood public schools than other school types. This means that if students with disabilities are not enrolled in Program schools, which are designed for SWD, they are then funneled into neighborhood public schools that may not have the funding to support these students.
Figure 2 | Link to Chart
In both charts, there is no data for other magnet or open choice schools because there are five or less students with disabilities enrolled in these schools. When there are less than five students with disabilities enrolled in a school, the data is suppressed and will not show up in order to protect the student(s)’s information.
As seen in the Figures, the other school types have a considerable percentage of students with disabilities, but more of these students are concentrated in neighborhood public schools schools.
The fact that more SWD are enrolled in neighborhood public schools is significant. This means that these schools need more equitable funding in order to foster a strong learning environment for students with disabilities. However, neighborhood public schools do not always get the necessary funding that they need for students with disabilities. This is important to take into consideration as neighborhood public schools will need special attention and funding to create an equitable learning environment.
Although East Hartford and New Britain Have varying enrollments of students with disabilities, there are similarities in which school types that these students tend to enroll in. Given the information from these two charts, it is also necessary to look at per pupil expenditure (PPE) by districts and percentage of students with disabilities by district in order to get a better picture of how funding is being distributed across districts to schools with significant percentages of enrolled students with disabilities.
By looking at Figure 3 and figuring out the correlation coefficient (the r in the chart), there is a moderate positive pattern between percentage of students with disabilities enrolled by district and per-pupil expenditure for district schools. Although there are a few outliers, these school districts are generally close together with a moderate positive correlation.
This moderate positive correlation should be expected because if the percentage of enrolled SWD is higher, so should the district’s PPE. A correlation coefficient of 0.43 is a moderate positive correlation in statistics, so this means that a trend like this should be expected if schools are truly working towards equity and fair funding across districts. Although there is a moderate positive correlation, this does not necessarily mean that these schools are equitably funded since there should be a stronger correlation.
Figure 3 | Link to Chart
A moderate positive correlation does not mean schools are equitably funded because these districts still may not be getting the full funding that they need in order to host students with disabilities and students with other learning needs. Equal funding would mean that each district gets the exact same amount of funding in schools for every student. However, equitable funding takes into consideration the systemic barriers that certain students face and allocates more money towards schools where these students are enrolled in.
Although this moderate positive correlation may show that there is equal funding, equitable funding is more important in order to work towards a more fair and just school system for all students– regardless of race, socio-economic background, or dis/abilities. This positive correlation shows that these districts are on the right track, but may not paint the full picture about funding for students with disabilities.
There may be a pattern based on school type because it may be easier for students with disabilities to enroll in neighborhood public schools because there is no application requirement. Additionally, there is no pattern across districts because the Per Pupil Expenditure does not correlate with the percentage of SWD enrolled.
Using data from EdSight, the raw data was pulled from two different tables. One raw data set shows the PPE by district and the other shows the number of students with disabilities enrolled by district. The enrollment of students with disabilities by district was converted into a percentage. This data was processed this way in order to show a comparison between the PPE and percentage of students with disabilities enrolled by district.
These charts were created using data from EdSight. In order to create this data story, the raw data had to be filtered and processed by the 33 towns and 38 districts that were relevant to the class’s community partner, Center for Leadership and Justice. When figuring out the percentage of students with disabilities enrolled in New Britain and East Hartford, the raw number of students with disabilities was divided by the total number of students and sorted by school type. The same thing was done to get the percentage enrolled of students of disabilities by district in Figures 1 and 3.
However, in those Figures, I extracted the PPE data from the raw data and sorted by the relevant districts using VLOOKUP in my Google Sheets. After using VLOOKUP to narrow down the data to the relevant districts, the processed data was organized using Datawrapper to create a scatter chart to show the comparisons between the PPE and enrollment of students with disabilities.
Some things to consider is that if the number of students enrolled is five or less, then the data will be suppressed and not show up for calculations– which is why there is no data for school types such as other magnet and open choice in Figure 2. As a result, Open Choice and Other Magnet schools were not included because there was no data (0% enrollment). When processing the raw data, Program School data was not included in Figure 2 because these schools have a high enrollment of SWD to begin with because they are designed for students with disabilities.
CT Technical Education and Career Schools was also shortened to CT Technical Schools. Public Schools was changed to “Neighborhood Public Schools” because Public Schools does not adequately describe the kind of school it is because all of the school types from the data are publicly funded.
In Figure 3, Goodwin University Educational Services (GUES) is not included because this data was not available in the data set found on EdSight. This may be because GUES has changed its name over the years and this updated name was not updated for the 2020-21 data sets.
It is also important to note that this is data taken from the school year ending (SYE) in 2021, and data from before the pandemic in 2020 may show different trends that might not correlate with the most recent data.
Additionally, in Figure 2, the state does not clearly define College Affiliated Schools and the other school labels when I checked the documents available on EdSight. Given these limitations, definitions of these school types may vary across different websites or resources.
In conclusion, based on all three charts and previous background information, students with disabilities are in school districts that do not have adequate funding based on the ECS formula since the percentage of enrolled SWD should have a stronger correlation with the PPE by district. This data shows that among the two school districts, East Hartford and New Britain, with the highest enrollment of students with disabilities, many of these students are concentrated in neighborhood public schools. This could be due to the fact that it is easier to enroll in neighborhood public schools because they do not have an application process like the other school types mentioned in Figure 1, which explains why they have a higher percentage of enrollment.
For school districts like East Hartford and New Britain that have a higher enrollment of students with disabilities in their neighborhood public schools, it matters how and where funding is distributed. Given that SWD are concentrated in neighborhood public schools, the fact that there is only a moderate positive correlation with per pupil expenditure and enrollment of students with disabilities across districts is a problem. A moderate positive correlation of 0.43 may show equal funding, but equitable funding is needed in order to address systemic barriers that show up in the education system because it does not cater towards students with disabilities or other learning needs.
This is important to note because in order to work towards a more equitable future where all students receive the funding that they need, current funding disparities need to be taken into account and talked about with school boards and other community organizations and members.
Bamberger, Cayla. “Report: CT's Funding, Delivery of Special Education 'Insufficient, Ineffective and Inequitable'.” CT Voices, 6 Dec. 2021, https://ctvoices.org/in_the_news/ report-cts-funding-delivery-of-special-education-insufficient-ineffective-and-inequitable/.
“How Connecticut Funds Education.” School+State Finance Project, https://schoolstatefinance.org/issues/how-ct-funds-education.
“Per Pupil Expenditures by Object (District).” CT.gov, https://public-edsight.ct.gov/Overview/ Per-Pupil-Expenditures-by-Function---District/Per-Pupil-Expenditures-by-Object— District?language=en_US.
“Resident Town Export.” CT.gov, https://public-edsight.ct.gov/Overview/Resident-Town- Dashboard/Resident-Town-Export?language=en_US.