Impact of Inequality on Student Performance

Dataset Overview

  • 4 data sets on pre K-12 public schools in Virginia
    • Standardized test scores from 2012-2017 in English, Math, History, and Science
    • Number of students with free or reduced lunched from 2008-2017
    • Number of students per grade from 2008-2017
    • Coordinates of each school
  • About 2,000 schools, but varies per dataset
  • Published by the University Libraries at Virginia Tech

Project Goals

  • Understanding Virginia’s public school system and potential education inequality throughout the state

Research Questions

  1. How has school performance changed over time?
  2. How do differences in school funding correlate to overall school performance?
  3. How does location impact schools?
  4. How do schools impact their neighboring schools?

Key Insights

The Virginia SOL (Standards of Learning) test is a standardized assessment measuring student mastery of key academic standards. Analyzing its scores over time is necessary because it provides empirical, longitudinal data to track trends in school performance. Some key insights supported by preliminary analysis of the first dataset, Standardized test scores from 2012-2017 in English, Math, History, and Science, include the following:

  • Averaged across all subjects, more affluent areas of VA tend to have higher SOL pass rates.
    • e.g., Northern VA is 2-5% higher than the next highest scoring regions, Central & Eastern VA.
  • Pass rates tend to follow a consistent ranking: History, English, Science, Math (from highest to lowest).
  • Mean SOL pass rates appear to have dipped significantly across all regions & school types between 2012-13 and 2013-14.
    • This may be due to inconsistency in the dataset; data for 2012-13 was sparse and disorganized.

This shows the breakdown of the around 2000 schools that were given in the data sets into elementary, high, and middle school.It’s worth noting that most of the schools in this data set are Elementary schools (preK/K-5). Elementary schools in a given area are often much smaller than neighboring Middle and High schools. The number of high and middle schools in Virginia are extremely similar, both hovering around 300.

It’s worth noting that most of the schools in this data set are Elementary schools (preK/K-5). Elementary schools in a given area are often much smaller than neighboring Middle and High schools.

Accreditation status varies by school level. Middle schools are the least fully accredited overall, even though there are fewer middle schools throughout the state. High schools, despite having the most rigorous curriculum out of the three, maintain high full accreditation levels.

Viewing the accreditation status of schools broken up by level acts as an overview for overall school performance across Virginia. A majority of schools maintain a fully accredited status, hovering around 80% for all levels of schooling. The percentage of partially accredited schools is about 20% across all levels. Finally, the percentage of schools who were denied accreditation is overwhelmingly small, with it being close to only 3%. This chart shows that schools in Virginia have differences in there performance in all levels of schooling.

Visualization 1: How has school performance changed over time?

* Note: The demographic region data used for this visualization was sourced from the UVA Weldon Cooper Center for Public Service.

Visualization 2: How do differences in school funding correlate to overall school performance?

This chart shows that the distribution of free and reduced lunch percentage varies among the different schools in Virginia. Notice that it appears normalized about 50%, which makes sense.

In this graph free/reduced meals and average test scores are used as a proxy for student poverty rates and school performance. Notice that the downward trend of the data is constant even while filtering for school type. Also notice that a majority of schools with less than full accreditation are collected on the right side of the graph, indicating a higher free/reduced meal percentage, and therefore a higher likelihood of the students of that school experiencing poverty.

Visualization 3: How does location impact schools?

This interactive chart allows the user to explore key features of our data set in aggregate. Hovering over the map provides access to location-specific figures, and annotations of major cities makes this hover navigation easier. If the user does not know where a particular county is or is drawn to the accreditation bars, they may select a bar and the corresponding county will be highlighted on the map.

Visualization 4: How do schools impact their neighboring schools?

This visualization shows the major regions of VA, which are composed of several cities and counties.

This visualization shows the similarities and differences between test scores among geographically close schools. Within a similar geographic region, test scores are often separated by county lines and clear clusters of high scores and low scores can be observed. For example, in Central VA, Chesterfield and Henrico County have much higher scores than Richmond City despite being geographically close. A similar county divide can be seen in Hampton Roads between Newport News City and York County.