Tableau: Massachusetts Public Schools
This data set is a compilation of data from the Massachusetts Department of Education including various characteristics of K-12 public and charter schools. Original data set can be found here.
1) My first dashboard focuses on graduation rates and the factors that drive them. The bar graph below shows the graduation rates of high schools in Massachusetts.
2) One factor that seems to correlate with graduation rates is the percentage of students in high schools that are considered High Needs. The R2 value is about 0.57, meaning that about 57% of the variation in graduation rates among high schools can be attributed to the percentage of students in those schools that are considered High Needs.
3) Another factor that seems to correlate with graduation rates is the percentage of students in high schools that are considered Economically Disadvantaged. The R2 value is about 0.58, meaning that about 58% of the variation in graduation rates among high schools can be attributed to the percentage of students in those schools that are considered Economically Disadvantaged.
While these visualizations highlight correlations between student demographics and graduation rates, correlation does not imply causation. These graphs can not explain why some schools have higher or lower graduation rates. It’s also likely that there is significant overlap between the effects of economically disadvantaged and high need student populations on graduation rates. A multiple regression analysis would be required to determine their combined impact on graduation rates in high schools.
4) My second dashboard for this project focuses on the performance of elementary, middle, and high school students on the Math portion of the MCAS exam. The Massachusetts Comprehensive Assessment System (MCAS) is a state standardized exam that is designed to assess what students should know at their grade level according to the Massachusetts Curriculum Frameworks. Students in grades 3-8 and 10 take the Math and English portions of the exam.
The dashboard above shows the average scores of each district for 4th grade, 8th grade, and 10th grade. The data points represent the percentage of students in each district that received either a proficient or advanced score on the MCAS Math exam. The dotted line marks 50%, meaning 50% of students scored either proficient or advanced on the Math exam. If a district falls to the right of the line, then over half of their students are proficient in Math, likewise if a district falls to the left of the line, less than half of the students from that district are proficient in Math.
5) My third dashboard for this project focuses on the percentage of students going on to college after high school, as well as the factors that correlate with that percentage. The graph below shows the relationship between the percentage of high school students considered economically disadvantaged and the percentage of high school students attending college. As you can see there is a tight grouping of schools with a small percentage of economically disadvantaged students that send a very high percentage of their students on to college, and as you move down the x axis the graph becomes more scattered.
The R2 value is about 0.37 meaning that about 37% of the variance in the percentage of students attending college is caused by how many students are considered economically disadvantaged.
6) The second graph in my third dashboard is shown below. This graph shows the relationship between high school class size and college attendance. Initially I suspected that larger class sizes would correlate with poorer educational outcomes and therefore less students going on to college after high school. To my surprise it seems the opposite is true, at least to a small degree.
Perhaps a larger class size better simulates the actual college learning environment and plays a role in preparing students for the lecture hall style of education common at the college level. Regardless, the actual relationship between these two variables is not strong, the R2 value is only about 0.19.
You will notice that there is a color gradation in this scatter plot, this range of color saturation represents the percentage of students at each school considered economically disadvantaged, data points with a darker color have more economically disadvantaged students while data points with lighter colors have less. As you can see from the graph, there is a relatively tight cluster of schools near the top with low numbers of economically disadvantaged students that send a high percentage of their students on to college.
7) The last graph in my third dashboard for this project is shown below. This graph shows the relationship between the percentage of students that are considered high needs and the percentage of students that move on to college after high school. This graph also shows the color gradation representing the percentage of students at a school considered economically disadvantaged.
The R2 value is about 0.41 meaning that about 41% of the variance in college attendance after high school is caused by the percentage of students considered high needs at a particular school.
