Last Saturday I gave a presentation at the National Association for College Admission Counseling Conference titled “Matching the Under-Matched Student: Small Colleges and Big Data Offer Strategies for Success.” The presentation used a statistical analysis and case studies from two small liberal arts colleges to identify ways in which colleges may respond to the finding of Hoxby and Avery (2012) that the vast majority of very high-achieving students who are low-income do not apply to any selective college or university.
You can access the presentation here.
The presentation was created entirely in R Markdown. If you want to learn how to create presentations like this stop by my office (ETC 223). You can navigate the presentation using the arrow keys on your keyboard.
There are several data visualizations of interest packed into this presentation. For example, on slide 6 there is a motion chart that displays the graduation rate, acceptance rate and percent of Pell Eligible students at every four-year college in America. You can change nearly everything on this graph (i.e. x-axis, y-axis, color of points, size of points, etc.) simply by clicking on the drop-down menus. Additionally, you can track certain institutions more closely over time by selecting them from the list of colleges to the right of the graph. Pressing the ‘play’ button in the bottom left corner will ‘run’ the graph and show changes in metrics over time.
You will notice that almost all of the points representing schools with acceptance rates below 30% and graduation rates above 60% are represented with a dark blue color. This indicates that these schools also have a relatively low percentage of Pell eligible students. Additionally, once you set the graph in motion, you will notice that these institutions do not change much over time. However, the color of the points representing less selective institutions with lower graduation rates become noticeably warmer over time. This indicates that these institutions are enrolling an increasing number of Pell eligible students.
Other visualizations of note in the presentation include Sankey diagrams on slides 12, 15 and 18. These diagrams show the reasons that students did not continue their education after high school, delayed their education, and enrolled at a particular college by income quartiles. Hovering over any line in one of these Sankey diagrams will display the percentage of students represented by the line. Additionally, you can drag and drop any of the nodes in the graphs to change the way the information is displayed.
If you have questions about how to create interactive data visualizations like the graphics included in this presentation please contact me (majerus@reed.edu) or stop by my office (ETC 223).