by Faris Matraji
Last updated on December 6th, 2022
for Data Visualization for Allwith Prof. Jack DoughertyTrinity College, Hartford CT, USA
In the following work, I will be seeking to address the question of “In each town, how do student enrollment rates vary between school types and how have they changed over time?” This question is important for many reasons, and the findings that come from addressing this question can help guide decisions made by the people in charge on some very important aspects regarding schools in Connecticut. For starters, it is important to understand the total number of students enrolled in each type of school because this can dictate how much funding certain schools get, how much resources they require, how many staff members they require, and many more key aspects of running a school. If the enrollment numbers of a certain type of school are very low, policy makers know they don’t have to divert quite as much resources or money to that certain school compared to a type of school with much larger enrollment numbers. Another reason this question is important is because it allows people to locate trends within the schooling districts that potentially may need addressing. For example, if it is noticed that a certain type of school in a certain town is losing kids drastically year over year, it may point to a systematic issue in that school type or in that town as a whole. On the other end of the spectrum, if it is noticed that a certain type of school was able to grow their enrollment steadily over the years, other school types or districts could learn from what they are doing and implement it in their own schools or towns. To address this question, I originally planned on focusing on the four largest types of schools in Connecticut, those being traditional public schools, Sheff magnet schools, open choice schools, and technical schools. While there are other types of schools in Connecticut,I decided focusing on the four largest would be most relevant because there would be the most data available for these schools, and they would be more representative when discussing larger overall trends due to the larger sample size. Before breaking it down by individual school type, I decided to look at the total change in student enrollment across all four school types combined, in order to see if there were any initial trends about student enrollment that jumped out. The map below displays the percentage point change in student enrollment across the four school types from 2016 to 2022.
As displayed in the map, a majority of the 33 towns that were focused on experienced an overall increase in total student enrollment from 2016. While this increase in student enrollment over time makes sense as the general human population naturally increases over time, there were a couple of data points that stuck out in particular. For starters, the massive decrease in student enrollment that South Windsor experienced is a very interesting piece of data. Seeing as no other town faced nearly as sharp of a decrease, it leads me to wonder if there were specific things that the town did that led to such a decrease. This finding also led me to wonder whether South Windsor faced a decrease in student enrollment across each type of school, or if there was a certain type of school that caused this decrease. Another interesting piece of data was the significant increase in the Hartford total student enrollment. Seeing this increase compared with the decrease in South Windsor led me to wonder whether a possibility was people moving from South Windsor to Hartford and enrolling in the school systems there.
After exploring the overall changes in student enrollment, I decided to further analyze these changes by exploring the shifts in student enrollment by school type. To do this, I decided to create a chart showing the percent point change in traditional public schools, Sheff magnet schools, and then I grouped the other school types together and showed their percent point change. The reason I decided to break it up into these categories was because traditional public schools and Sheff magnet schools were the two largest school types with the most data available for them. The other school types didn’t necessarily have data for every town, which made creating an individual bar for each individual school type unfeasible.
Using the official Connecticut State website, I used data from as far back as they had available, which was the year 2016. My data shows the change from 2016 to the current day in each type of school across the 33 different towns. Across these different towns, there were some findings in particular that stood out to me. Firstly, the drastic increase in program school enrollment in the towns Glastonbury and Enfield jumped out to me. Seeing such big increases in these towns makes me wonder what these towns were doing that could have led to such an increase. Did they perhaps focus on building more program schools? Did they make a concerted effort to attract more kids to these schools? Another finding that stood out to me was the pretty significant decrease in Portland in sheff magnet schools. It leads me to wonder if there is a correlation between this decrease and a certain factor that occurred in these towns during these years. A broad trend I noticed throughout my data was that no singular town had a positive increase across all different school types. Despite population increasing across these towns, their school enrollments didn’t necessarily increase which I found to be interesting. A possible explanation for this is that the COVID-19 epidemic could have delayed or in some cases even decreased school enrollment. Another possibility is that although population increased, it may not have been the population of students in the age range that would enroll in these schools that increased.
While finding and organizing my data for this question, I encountered a couple of situations where it caused some uncertainty in my overall findings.Firstly, the state of Connecticut only has data going back to 2016 regarding student enrollment in each town for these specific types of schools. Because of this, I was only able to create visualizations covering a 6 year period. I would have preferred to look at a longer period of time because I believe that would have been more indicative of larger trends in the Connecticut schooling system. Another instance that added uncertainty to my findings was the lack of data in certain categories. Many towns did not have any data recorded for student enrollment in certain school types, mostly technical schools and open choice schools. This made it difficult in creating comparable data for those towns, which is why I combined the remaining school types into one category.
“EdSight Home Page.” CT.gov. Accessed November 30, 2022. https://public-edsight.ct.gov/?language=en_US.