Higher Ed Data Stories

Note: If you haven't read my post about the 2016 election results and educational attainment , it might be of interest to read that first.  Or later.  Or not at all. Your choice. This started simply enough: A couple of tables from the Digest of Education Statistics , (tables 302.65 and 302.70) showing the percentage of adults aged 18-24 who were attending a degree-granting college by state and ethnicity in 2005 and 2015.  If you've read this blog enough, you know I have a love/hate relationship with the digest: Great data, but horrible formatting.  The tables are made to be printed on a single 8" x 11" sheet and handed out.  The crucial distinction between data and insight is lost. Regardless, I reformatted the sheets into something workable for Tableau, and started to look at them. I wasn't having much luck: Some of the states didn't have data on African-American students, for instance, in 2005.  The variable for "Asian/Pacific Islander" was rel...

Strategic planning at universities is always an important process, but it's even more crucial to do correctly these days.  And lots of institutions might be missing a really critical element in scanning the external environment: The extent to which federal financial aid programs contribute to the essential revenue streams that run the enterprise. This is a fairly simple, if crowded, visualization, showing about 900 private colleges and universities who have good data in IPEDS.  Each dot is a bubble, colored by region, representing a single institution.  Its position along the horizontal axis shows student loans as percentage of core revenues, from left (low) to right (high).  I've included subsidized undergraduate direct loans, unsubsidized undergraduate direct loans, Parent PLUS loans, graduate subsidized, and Graduate PLUS loans in the calculation.  I did not include private loans. Some of these numbers may seem high, but understand what this says and what...

"You should write something about discount rates." I hear that a lot these days.  Even though NACUBO does its annual discount study , people still want and crave more.  There is no topic, it seems, as much on the minds of people in universities as discount rate. But despite my desire to make you, the loyal readers of this blog, happy, there are a lot of reasons I haven't written about discount rates: First, data are old.  It's a long story, but financial reporting (where you learn about financial aid) is reported about a year after the freshman class enrolls.  So the ability to calculate discount is always behind the most current admissions data.  The viz below is for 2014 freshmen for instance, and it's the most recent publicly available.  It's hard to describe to people how much things have changed between 2014 and 2017. (And even harder to figure out why 2016 admissions data are not out yet.) Second, discount is not as important as accounta...

I was doing some research for our own internal discussions, and decided to take it a few more steps to look at enrollment of undergraduate students by ethnicity at about 2,000 four-year, public and private institutions in the US.  (And when you look at the data and wonder why, rest assured, I checked: Miami Dade does offer Bachelor's degrees via online programs.) It's here, and the first two views are pretty easy to navigate:  Each chart shows a separate ethnicity and lists each institution in descending order.  The first view is by counts, and the second by percentages.  Thus you can see the institution that enrolls either the most Hispanic students, for instance, or the institution with the greatest percentage of Hispanic students, depending on your preference. If you'd like to focus on a single state, just public or private, or colleges of a certain size range, use the filters at the top.  You can always reset the views using the control at the bottom. ...

This post started off simply enough: I found some cool data on changes in educational attainment over time. I was going to take a look at how far we'd come as a nation in the last 40 years (even though I had already published this ), and show where the biggest gains were. It wasn't very compelling, at least at first. Then, I decided to get ambitious (my wife was in her evening class, so I had the night free), and wondered if there were any interesting connections between changes in educational attainment and voting patterns in 2016.  I found a data set with election results  by county, (a handful of counties are missing) and merged it in. And thus, this. Before I start, there are a few points to make about the data.  First, the definitions changed slightly over time.  For instance, in 1970, the field is labeled "College degree," while in 2010, it's labeled "Four or more years of college."  Not the same thing, but we'll have to go with it for n...

Note: I've just discovered that although this data set is labeled 2016, it is for the 2015-2016 data year; thus, this is Fall, 2015 admissions data, not Fall 2016 as I had thought.) This always proves to be a popular post: The 2016 Admissions Data summary. Here you'll find ten views, showing test scores, admit rates, need data, and international student information (which should only be used as a guide, as you'll see.) Use the gray boxes and/or arrows across the top to navigate this information, and the filters to limit the views. Note: This data is "as reported" to Peterson's and is presented as is.  If it's wrong or your college is missing, it's almost certainly a reporting error; most institutions left at least some fields blank. It comes from the Peterson's Undergraduate database and the Peterson's Undergraduate Financial Aid database, both copyright 2016 by Peterson's-Nelnet.  The data here are used with permission of Peterso...

Jerry Falwell, Jr., President of Liberty University, has just indicated that he will head a new task force to examine the Department of Education's policies on colleges and universities: Things like, " overreaching regulation” and micromanagement by the department in areas like accreditation and policies that affect colleges’ student-recruiting behavior, like the new  “borrower defense to repayment” regulations," according to this report in the Chronicle of Higher Education (subscription required, but if you're in higher ed and you're not subscribing, you should. I've not been paid to endorse the Chronicle. Or anything, for that matter.) Thousands of people on Twitter and in other social media have already pointed out why this is a bad idea, especially coming on what appears to be the approval of Besty De Vos as Secretary of Education.  But if you want to see how far Liberty has taken recruitment, even under the current regulations that attempt to make adm...

What kind of jobs can I get if I major in English? (Lots) Do I have to major in science to go to medical school? (No) Do actors have to go to a Theater program? (No). All these sound like conventional wisdom, but now, thanks to my friends at Human Capital Research Corporation , we have some better answers.  The data set they put together is based on The American Community Survey (ACS) of the Census Bureau, a small but statistically significant sample of the US Population.  It asks questions that include occupation and college major (for those who are working, and for those who have a bachelor's degree).  The data below contains over 3 million individual responses to these questions (for people in the labor force between the ages of 25 and 60 with a bachelor's degree). One the first dashboard (using the tabs across the top), you see two views.  On the blue chart on the left, choose a major (cluster) at the top.  The chart below will show you the professions...

Recently, I received a message from Akil Bello who pointed out a data visualization he had seen.  It was originally posted to Reddit , but later was edited to eliminate the red-green barrier that people with color-blindness face.  The story was here , using a more suitable blue-red scheme. There's nothing really wrong with visualizing test scores, of course.  I do it all the time.  But many of the comments on Reddit suggest that somehow the tests have real meaning, as a single variable devoid of any context.  I don't think that's a good way to analyze data. So I went to the NY City Department of Education to see what I can find.  There is a lot of good stuff there, so I pulled some of it down and began taking a look at it.  Here's what I found. On the first chart, I wanted to see if the SAT could be described as an outcome of other variables, so I put the average SAT score on the y-axis, and began with a simple measure: Eighth grade math and En...

Much of what I post here is slightly modified from what I use at work, and this is no exception.  Here at DePaul (like most universities) the biggest single slice of enrollment comes from our own state, and it's important to know what's going to be happening to the student markets in the future. So I downloaded data from The Illinois State Board of Education showing enrollments for two years: 2010--2011 and 2015-2016 to see how things have changed over time, and to get a glimpse of the future.  This is a more granular look than the WICHE data I visualized recently , but it's also not actual projections going forward, but rather just numbers; projections require a lot of time and mathematics skills, neither of which I have.  I would have liked to gone deeper and farther with this, but the data are messy , and even things like School District IDs have changed over time. There are four views using the tabs across the top: First by region, then county-by-county, and then ...

You can look at a lot of places on this blog to find the story of women and the increases in educational attainment over time, but perhaps none is so compelling as this one.  It was very rare for women to have college degrees in the 1940's and 1950's , but even rarer to find doctors, lawyers, and dentists who were women. As you'll see below, that all changed in the late 1960's and early 1970's.  What happened? It's probably a lot of things, but you could probably do worse than to point to birth control as a major contributing factor. There are four views of the data from the Digest of Educational Statistics : View 1 shows all degrees over time to men and women; the top via stacked bars, and the bottom using line charts.  The top chart shows the dramatic increase in degrees to women; the bottom shows that in 1955-56, almost all degrees (blue line) were awarded to men (purple line.) View 2 shows the same data, presented a different way.  On the top chart, ...

Note: You should view this on a tablet or desktop. The Western Interstate Commission for Higher Education (WICHE) has just published the 9th version of " Knocking on the Door ," a look at demographic projections of high school graduates in the US.  And several organizations have already published interesting views of the data, like this one on the WICHE site and this one on Hechinger Report . As I make my case for more self-service BI, these are great examples of what I call the 80/80 rule: Eighty percent of what an analyst will give you is not what you need as a practitioner; and 80% of your questions won't be answered when someone else does the analysis for you.  So I took the data ( and allow me to complain a little bit about putting data for 50 states and DC in 51 worksheets in an Excel workbook, WICHE ) and spent a lot of time restructuring it for analysis.  Then I started asking my questions, and came up with 6 views, in an attempt to provide practitioners maxi...