Skip to main content


Showing posts from June, 2014

US Post-secondary offerings

If you only read the papers, you'd think US Higher Education consisted of a dozen or so high profile institutions.  But fortunately, there are "more things in heaven and in earth than are dream't of in their philosophy," with all appropriate apologies to Shakespeare. When I started this blog, it was in response to a new Tableau Software feature I had seen pre-viewed last September, called "Story Points."  In fact, the very title of the blog has a lot to do with that: Believing that data can and should be used to tell narratives that provide people with memorable insight. This is my first attempt to use Story Points to tell a story; one I hope sticks with people as we think about a pretty amazing selection of post-secondary options for students.  To navigate the story points, just use the grey boxes along the top, and a new chart or dashboard should point the way to insight. Learn About Tableau

Predicting EFC with One Question

Most everyone who knows anything about our Financial Aid system thinks it needs some improvement.  And almost everyone who actually goes through it, it seems, is astonished by the outcome: They expect me to pay how much for college? And that's just for one year? For those of you who don't know, all federal financial aid begins with the FAFSA , or Free Application for Federal Student Aid.  It's a form that collects information about income, assets, and family size in an attempt to estimate how much a family should be able to contribute to the cost of higher education.  Should being the operative word.  The figure it calculates--EFC, or Expected Family Contribution--is really a misnomer, sort of like the Peacekeeper Missile.  It's really just an index number designed to estimate federal expenditures on financial aid programs.  Many colleges find it so unreliable that they use another form, such as the College Board's Profile , or their own proprietary form to collec

Bachelor's Degrees by Program and Ethnicity, 2010 and 2011

The previous post, about Doctoral Degrees by Program and Ethnicity, generated a followup question from Jennielle Strother at Seminary of the Southwest about similar data for undergraduate enrollment.  While I couldn't find that exact data, I did find this from the Digest of Education Statistics , showing degrees awarded by race and program, so I spent a half hour to pull it into a visualization. Some data visualization experts don't like tree maps because it's hard to make precise comparisons of area across distance, but I do like it for this purpose: You can pretty easily see the data in one view with minimal effort, and since precise comparisons aren't vital, you can get a good sense of the lay of the land. It's also very easy to ask your questions of this chart.  For instance, if you want to see how degrees shook out within a program (like engineering, or English)  you can quickly make those selections and see the results by ethnicity.  If you want to exclu

Doctorates by Discipline and Ethnicity

A recent article in Inside Higher Education touched on a subject I've written a lot about on my other blog (the one with more words than pictures), specifically the role of standardized tests, in this case the GRE in selection of students for graduate programs.  The article cites another article in Nature blaming the dearth of minority and women doctoral graduates in science and engineering, at least in part, on the GRE . For anyone who is at least knee-deep in the debate about the value of standardized tests, the arguments are familiar ones: Too much emphasis on the tests means that too many candidates with strong potential are being overlooked, especially when you consider the predictive validity of the tests.  The authors are pretty blunt: " The GRE is a better indicator of sex and skin colour than of ability and ultimate success." So, in light of that, take a look at this data on 2012 Ph.D. recipients, which was downloaded from the NSF Survey of Earned Doctorat

Yes Education Pays. But maybe not how you think.

You have probably seen the headlines: College graduates make $800,000 more in the course of a lifetime than high school graduates do.  It's statistically correct.  And the conclusion it probably leads many people to is completely wrong. It's true, of course, as you'll see below, that income increases with every increment of education: A high school graduate earns more than someone who didn't graduate from high school; a person with a bachelor's degree earns more than someone with a high school diploma; and someone with a master's degree earns more than someone with just a bachelor's.  (This is not true for every person, of course, just for groups on average; Bill Gates, whom I'm pretty sure earns more than yours truly with a Master's Degree, never finished college.) But it's wrong to say that graduating from college is the cause of the income difference. It's true that earning a degree opens new doors to you, and new opportunities for in

MOOCs: What Harvard and MIT Data Reveal

If you know much about higher education, you know that Massive Open Online Courses (known as MOOCs) are all the rage.  These courses are open to anyone, anywhere, for free, and promise opportunity for students who wish to learn on their own.  They are exciting in concept, and threaten to turn higher education on its head. So the recent release of HarvardX and MITX data on MOOCs is exciting.  The data is scrubbed to protect the privacy of the students who took the courses, but still yields a wealth of interesting stuff.  But you must interact. This dashboard starts with the intro, but has five views you can see by clicking across the tabs at the top. Once on a view, you can limit the data shown by (depending on the dashboard), by gender, education levels of students, home country, or institution, and whether the student registered or completed the course for a grade.  Data are shown by course, age, home country, and institution. Have fun, and let me know what jumps out at you.