Evaluating School Success with Tableau

Imagine being tasked with making decisions that impacted one-seventh of your state's population. Sounds pretty important right? Well, that is exactly where the state of Massachusetts Secretary of Education found themselves with a school system made up of approximately 953,748 high school students (almost a million kids!). This means that decisions regarding high school education are especially important to get right. That's where my analysis came in!

Background

The state of Massachusetts wanted its education data analyzed as the Secretary of Education explored ways to increase college attendance. One proposed solution included investing in building more schools to lower the average class size. By doing so, they hoped to see a boost in the percentage of students attending college. Using Tableau, I have taken a deep dive into the data.

All the data is available to look at on this Tableau Dashboard

The original dataset can be found here 👉 Dataset

Analysis

In 2018, the average class size for the entire state was 18. When comparing the average class size to the % of students attending college, there was a slight indication that as the class size went up, so did the % of people pursuing higher education after college.

Based on the data, the sweet spot for class sizes was between 12 and 20 students.I also looked at how the % of economically disadvantaged student affected how many students attended college after graduation.

The schools with a higher percentage of economically disadvantaged students showed a lower tendency to attend college. Identifying barriers and blockers would be important to improve these percentages. Let's look at more data!

Then I looked at the schools with the lowest percentage of students graduating. I identified Springfield Public, Boston Charter, Whaling City Junior, Springfield High, and Phoenix Academy as the lowest performing schools. Starting with these schools to understand the causes of the current state and blockers toward improvement would be a great place to start.

Conclusion

I recommend creating a program that pairs high-performing schools with low-performing schools to share strategies and tips on what is leading to their success.

Before investing in building more schools, the state needs to partner with schools containing a higher number of economically disadvantaged students to identify the areas of opportunity to improve their graduation rates.

If you enjoyed reading this, I'd love to connect with you on LinkedIn! I'll be sharing more of my data analytics projects and always welcome feedback.

This project was done as part of the DAA Boot Camp Projects. Educational purpose.