Data visualization has become a powerful tool for understanding trends in education. Kyle Walker, director of the Center for Urban Studies at Texas Christian University, recently released an interactive visualization titled Educational Attainment in America that maps degree completion across the United States using data from NHGIS and the U.S. Census. Data preparation was completed with R and Python programming languages, and the map itself is hosted by Mapbox.
Educational Attainment in America, Kyle Walker, TCU Center for Urban Studies
In the map, each dot represents between 25 and 500 people, depending on level of zoom. Each color is linked to the highest level of education attained: blue for graduate degrees, green for bachelor’s, yellow for some college, orange for high school, and red for less than high school.
The map draws a sharp contrast between educational attainment in urban areas and more rural areas, which are dotted with red, orange and yellow. “There a lot of conversations around social and political polarization between metro areas and rural areas,” said Walker “One thing that the map does allow us to observe is a clustering of individuals with at least a bachelor’s or graduate degrees in cities as opposed to rural areas.”
Last week, we sat down with Kyle Walker to discuss his project and how it can be used to used to recognize trends in educational attainment and student outcomes. See Q&A below.
Q&A: 2U and Kyle Walker on Educational Attainment in Americadata visualization
2U: Much of your work is in the demography in cities and suburbs, what drew you to look at educational attainment in particular, and how does it relates to some of the other work you have done?
WALKER: Education, over and over again is this stratifying factor in which people with the highest levels of education frequently opt to settle near urban cores rather than in suburbs.
I’m really interested in the idea of how to design interfaces to allow the public to engage with datasets that are publicly available but might require a certain level of technical expertise to really dig into. This project is a fusion of those two things, I was seeing education as an important variable as to where people live within cities, and used that as an input to this interactive interface to allow for exploration of that trend, comparison across cities, and that sort of thing.
2U: One of the things this map does is really paint a picture of the disparity in educational attainment between urban and rural areas. How do you see this potentially relating to brain drain and what regions are doing to attract and retain college graduates?
WALKER: The map reflects a stratification of labor markets between cities and rural areas, you’ll see a clustering of jobs that require higher education or graduate degrees in major cities and as such individuals with that level of education will be attracted to move there.
In areas around major research universities you do see a preponderance of people with graduate degrees, some of those may be affiliated with the universities themselves, but also with industries that have sprung up around that. You can look at examples like Cambridge and Boston, or Silicon Valley around Stanford and Berkeley. An interesting example of this is Pittsburgh, if you look at the area around Carnegie Mellon and University of Pittsburgh you see a preponderance in degrees, and so there is an association there.
Educational Attainment in America, screenshot of Pittsburgh, Kyle Walker, TCU Center for Urban Studies
2U: What conversations do you hope this will spark among individuals and officials at the community level?
WALKER: I think it’s interesting with a map like this, because functionally it’s an interface that reveals patterns in the American community survey in a public dataset, so there are many many ways people can use this information. My goal is by designing an open public interface like this, people can use it to learn more about their communities.
Every city, every community is going to have its own dynamics, its own context that informs those patterns, but I do think there is value in being able to show what the patterns look like and be able to put that into conversation with a local context serve as an illustration of what the outcomes look like within our cities. If there are areas in which people with certain educational backgrounds are residing as opposed to other places, how is that meaningful for all sorts of other initiatives within a city?
There’s research linking educational attainment of adults with that of educational outcomes of children. It’s worth thinking about if you have a neighborhood where everyone, or most of the population, has a graduate degree, how do schools perform as opposed to a neighborhood where educational attainment is less? Hopefully people can take a look at the map and start to think about those issues.
2U: What are some of the ways you think the higher education community can use this data, and the data they’re collecting at their own institutions, to think about educational attainment and outcomes?
WALKER: One thing that people could potentially use this data for is thinking about recruitment of underrepresented groups in higher education. Which I know at my university, like many others, is a priority. Using this type of information, you can look at the communities from which students are coming from. Are they coming from areas in which adults typically have a Bachelor’s degree or higher? Are we doing enough outreach in areas in which there are likely a lot of talented students, but adults don’t typically graduate from college? That could potentially, just by opening up the data, allow for outreach and recruitment in areas underrepresented in higher education.
Higher education institutions have a lot of information about student outcomes, student recruitment, admissions, that kind of thing. That’s not to say these institutions aren’t using it, but I think visualization is a powerful tool to explore trends and reveal things that might be unexpected. Visualization is something that can sometimes surprise you, sometimes it will confirm what you already expected to be there, but at times you’ll see, there is an interesting outlier that the visualization reveals or there is a trend that we hadn’t necessarily picked up on before.