Data Analysis for the Future of Education
Overview
The Superintendent of the state of Massachusetts education department requested an analysis on the performance of all schools, specifically related to graduation percentage. In breaking down the performance data, key questions arose that were necessary to answer to provide the superintendent with their desired results.
Questions
Analysis
This data analysis was conducted mainly using Tableau by importing an Excel file containing the necessary data from Kaggle. The data set can be found here. The public Tableau dashboard can be also be found at this link.
To find the 10 high schools with the lowest graduation rate, the data was organized first by filtering out all schools that were not high schools. This is because only high schools have graduate rates. Once the null values were removed, the data was formatted by comparing "School Name" and "% Graduated" using a Bar Chart. To identify the lower graduation rates, the data was then organized using the “field” tab to display in ascending order (Schools with the lowest Graduation rates at the top).
To emphasize the numerical graduation rates so they stand out, labels were added showing the graduation percentages using the “label” card on the panel. I adjusted the coloring to emphasize the schools that have the lowest graduation rates in red to take the data visualization a step further.
Based on the bar chart, the 10 schools with the lowest graduation percentages are:
1. Curtis-Tufts 0.0%
2. Springfield Public Day High School 8.7%
3. Boston Day and Evening Academy Charter School 9.8%
4. Whaling City Junior/Senior High School 11.4 %
5. Springfield High School 11.6%
6. Phoenix Academy Lawrence 13.0%
7. Chicopee Academy 15.8%
8. Dorchester Academy 16.4%
9. Gateway to College at Springfield Technical Community College 16.7%
10. Haverhill Alternative School 18.2%
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At this point in the analysis, the first question has been answered. This analysis will now focus on answering the second and third question.
The superintendent is considering investing in building more schools to lower class size for better instruction. A scatterplot was made to see if smaller class sizes had a positive effect on graduation percentage.
The percent of students attending college per high school was plotted over the average class size and filtered by economic advantage/disadvantage. The circles fade from red to green with red representing a higher percent of being economically disadvantaged.
The scatter plot gives the following results:
To answer the fourth question, the schools were grouped by district to analyze the average test score results for the 4th grade MCAS math assessment. The reason for this is because the superintendent believes that 4th grade math is the key to a student’s success in the future. According to the data, a passing score was 50%. The goal of the superintendent is to take some of the teachers from the districts performing above the passing level and having them train other teachers in the state who are underperforming.
A bar chart was made comparing “% MCAS 4th grade Math P+A” and the District Name using a horizontal view. It is important to note that “P” stands for Proficient, and “A” stands for Advanced. Since not all schools have elementary MCAS scores, the null data was filtered out. Since the superintendent wants to know the top schools, the data was sorted in descending order of math percentage. Since the desired score for the districts average math passing score is 50%, a reference line was added to the data. All districts at or above the 50% reference line were grouped together for better data visualization.
The school districts in green represent districts performing at or above the 50% threshold (75 schools) whereas the districts in red represent performing below the 50% threshold (25 schools).
According to the data, the top 5 performing schools on the 4th grade MCAS are as follows:
Findings
Recommendations
Based on the data, the superintendent should not invest in building new schools. Decreasing class size will not lead to increased college attendance based on the current data. Instead, the superintendent should use funding to support the economically disadvantaged schools that have low college attendance.
The superintendent should also use funding to support underperforming schools with low 4th grade math test scores.
The superintendent could have a conference with teachers from successful economically disadvantaged school districts to see what resources have helped aid students to success.
after reading the article, i can easily say that you have very good analytical skills
Great work Rachel! I loved that you answered the questions thoroughly and provided recommendations for the superintendent. Your visuals are clear and easy to read with meaningful coloring. Thanks for sharing 🙂
Processing and Converting data into quality information and visualization adds great value toward effective decision making . Great work!!!
I love how you used green and red in your scatter plot, made it very easy to understand!
Fantastic, well done Rachel 👏💪👏