Revisualizing the Labor Market Outcomes of Community College Graduates

Community colleges can be engines of economic mobility, providing students with the skills they need to find meaningful and stable employment. However, research shows that the specific college a student attends is strongly predictive of their resulting labor market outcomes after graduation - and to make matters more complicated, there exists substantial variation in outcomes even within the same college depending on the program of study and student demographic groups. Lastly, graduates of some colleges and programs might find higher wages after graduation, but it seems that higher wages do not always come with other positive outcomes like increased likelihood of employment or higher stability of job. In other words, the overall economic benefit of a community college degree may be a much more complicated thing to understand than we give it credit for.

So how can we communicate this complexity to the public and other stakeholders? And, moreover, how can we empower the public to actually make sense of such complex information when gathering information about what and where to study? The dashboard below is my best attempt at conceptualizing just that. Using "heatmap" visualizations with robust interactive elements, users can explore thousands of datapoints and make meaningful comparisons across colleges, programs, student groups, and outcomes. Reactive options, clear labels, and a "tooltip" that explains the data in plain language all work together to make navigating this rich information more accessible and approachable.

For now, note that all of the following data are fictional and procedurally generated, as this is solely a proof-of-concept for experimentation/discussion/illustration. Any thoughts, feedback, or ideas are greatly appreciated at this stage! See contact info below to get in touch, and thanks for viewing.




Outcome Age Group Sex Group Racial/Ethnic Group Color Scaling






















Visualization by Brian Heseung Kim. Twitter/GitHub/Web: @brhkim
This work is intended only as a proof-of-concept for interactive data visualizations. All opinions expressed are my own. Code heavily modified from work by Yan Holtz here