Tuesday, April 15, 2014

Freshman Wanderlust

When freshmen students go to college outside their home state, where do they go? It's a question with lots of answers, and the insight is not always easy to figure out, let alone communicate. But I took a stab at it anyway.

There are three views here, using the tabs across the top: If you want to know where students from a particular state enroll out-of-state, you should use the default view: When Freshmen Cross State Lines, Where Do They Go?  Pick any freshman home state (the view shows Michigan to start). You can also limit the colleges displayed by filtering on college region or Carnegie Classification. You can see that 372 freshmen left Michigan to go to The University of Toledo in 2012; 117 went to my institution, DePaul. Note that IPEDS data sometimes has mistakes (choose Arkansas, and you'll see one jump right out at you.** See note below for an update.) But overall, this data looks pretty clean.

If you want to see which colleges enrolled students from specific regions, use the second tab. Again, limit your selections as you wish by using the filters.

Finally, the third tab shows colleges by in-state freshmen, out-of-state freshmen, and percent out-of-state, all colored by the percent out of state. You can sort the institutions by the values in any column, by hovering over the x-axis label and clicking on the little bar icon that pops up. Subsequent clicks resort descending, ascending, and alphabetical. You won't break anything. Click away.

If you're a counselor looking for geographic diversity, this can be helpful. I found lots of interesting stuff that I can use tomorrow as we think about recruiting. What did you see?

**Note: I looked at the data and figured out that Harvard having 226 students from Arkansas was pretty unlikely, as was Harvard having zero students from California, so I took a leap and figured someone typed the data in the wrong box.  It's fixed now.  I also added a map where you can see the number of imports to any college from out of state by choosing the dropdown box on the fourth vis, the map.

** Note Two: I've added two more views, to the right: A bubble chart and a "Percent from out-of-state" chart.

Thursday, April 10, 2014

Is Admissions Fair to Women?

We go through cycles in college admissions, it seems, and the topic of interest in recent days (at least based on my limited view on things) has to do with gender discrimination in college admissions.

Most men readily admit that women are smarter, especially when it comes to high school performance. Others point out that men score higher on standardized tests, which predict far less with regard to college performance than grades do, and probably shouldn't carry as much weight as they do.

The focus on the treatment of young men and women in college admission goes back at least as far as this article in the New York Times in 2006. And the topic has been popping up a lot lately, most recently when Patrick O'Connor sent me this article, and asked for my opinion.  I thought it would be an interesting idea to look at the data.  So I did, using IPEDS data from the Fall of 2012.

The story here is interesting: The thing that jumps out at you, or at least might jump out at you, is that women file far more applications than men, which drives the fact that 55% of college students are now women. (Note: The number of applications from women does not necessarily mean that more women are applying to college, although in this case it does.)

The second thing that might jump out at you is that this is not true at the most selective institutions, where men file about the same number of applications.  Why is this?  Lots of reasons you could speculate about, and almost none of them reflect well on our society.  I'll leave the answers to researchers.

Anyway, have at it.  Use the filters liberally here (you won't break anything); the top three charts show summaries, and the bottom one shows individual institutions.  You can choose by selectivity, state, Carnegie Classification, public or private, in any combination.

And the bottom filter allows you to see the places where men have the greatest advantage in terms of admit rates.  Enjoy.


Wednesday, April 9, 2014

Staffing in Public Schools in the US, 2011

A while ago, I found some interesting NCES data on teacher salaries over time Teacher Salaries; it quickly became the most popular (currently 34,000 views) and the most contentious piece I'd ever posted, and months later, it's still getting hundreds of hits a week.  I simply found the data interesting, and wasn't making any sort of political statement.  I vowed at that time to never post about teachers again, so of course I'm breaking that rule today.

This is from the 2011 Common Core of data, showing all personnel in each state who work in public primary and secondary education.  Click here to see the data table and read all the footnotes, especially if you want to argue.

There are many things that can explain this data: States that have mostly urban areas (like California and New York) are likely to have bigger schools and classrooms, and thus fewer teachers per student.  Different states with similar populations may have more district administrators if they manage schools locally, or fewer if they do it in bigger geographies (by county, for instance.)

I added a couple data pieces to the table: First, the 2010 census data of the population under 18, which is not a perfect proxy for public school enrollment, but it's probably close enough.  I used Data Ferret to extract the data, and used those figures to compute the ratios (students per teacher, for instance.)  Again, a state with a younger population (more in elementary schools) might have fewer students per teacher than one with an older population (more in secondary schools).

Second, I downloaded 2012 election results, to see if data might sort out by Republican and Democrat states.  I'm pleased to say they generally don't, as I suspect that might avoid more colorful "discussion" on the topic.  The colors are applied to all but the top tab; Republicans in red and Democrats in blue.

There are four views, with the tabs across the top.  If you want to sort any of this data by any column, just hover over the x-axis labels at the bottom and click on the little bars icon to the right of the text.


Friday, April 4, 2014

Institutional Grant Aid Changes, 2006-2011

It's no surprise to readers of this blog how much college costs have risen over time.  It's also no secret what's happened to family income over that same period.

How have colleges responded?  By dipping deeper into their own pockets, of course (and if you want to talk about the pain of healing self-inflicted wounds, go right ahead; I won't stop you.)

This shows three things for each of about 1,500 private, four-year universities in the US: What percentage of students received institutional aid in 2006 (fat gray bar); what percentage received institutional aid in 2011 (thin red bar); and the delta over time (orange bar on right).

You can use the filters to narrow down the list: Choose a region and/or a state.  (Note: Those two filters cascade: That is, if you choose "Great Lakes" you won't be able to select "Alabama" in the state section, for instance.) I've begun by limiting the view to colleges and universities of 2,500 full-time undergraduates or more, just because most of the previously-noted problems with IPEDS data occur at smaller institutions, as many of these places have smaller IR staffs. You can change that, using the Enrollment Filter.)

The institutions are sorted by the delta, in the right-hand column.  Go to the label on either axis (at the bottom) and click on the little black icon that appears when you hover to sort in different ways.  Click to your heart's content; it cycles through various views.



Tuesday, April 1, 2014

New Research Just Released

This is an astonishing chart, just released today, April 1, 2014.  Can't get any fresher than that.

The "Get a Life Institute" of Cambridge, Massachusetts has just conducted a one-year, longitudinal study of how much people need to get a life.  I've used a top flight data analysis, tool, Excel, to crunch the data and magically break it into age groups.

13,013 people were asked about their friends and work colleagues: Whether they ever talked about their SAT or ACT scores, their age, and how much the respondent thought that person should "Get a Life."  (That's what the Get a Life Foundation does, duh.)

I think the results speak for themselves.  I have independently verified this data by speaking to a couple guys at Buffalo Wild Wings.  Statistically sound.


Friday, March 28, 2014

Degrees Awarded by Major and Institution

One of the most common questions people in our profession hear has to do with availability of specific--sometimes fairly narrowly focused--degree programs.  Which university offers marine biology? In Kansas?  Who has a program in network security?  Wonder no more.

Please be sure to read the instructions about interacting with this dashboard, to ensure you get the best results.  Then click on the tab at the top to take you to the interactive visualization.


Wednesday, March 26, 2014

The Race Goes On: Who wins?

If you know much about higher education, you know that about 80% of college students enrolled in not-for-profit institutions the US attend public universities and colleges.  Nine percent of all college enrollments, for instance, are in California Community Colleges.

Call me old-fashioned, but I believe public universities--whether they are the state's flagship or a university with two directions in its name--have an obligation at some level to the citizens of the state who support it. And by "citizens of the state" I mean all citizens.

People at the university, of course, are often focused on making the university more prestigious; look at almost any strategic plan, for instance, and you're likely to find something about "improving academic quality as measured by standardized test scores," or something very similar.

One problem: The two goals tend to be in conflict with each other.

So for this visualization, I made it very simple: I took public institutions with a Carnegie Classification of "Research Universities: Very High Research Activity."  They're more often than not considered to be the state flagship institution, or, in some states, one of the flagships.

The charts are identical, except for the x-axis.  On the top chart, it's mean SAT CR+M of the entering freshman class; in the bottom, it's the mean ACT-Composite.  (Because IPEDS reports only 25th and 75th percentiles, I averaged the two, which is not perfect, but close enough for this analysis.)

The y-axis shows percentage of freshmen who receive a Pell Grant.  Of course, to be fair, it's not the percentage of admitted freshmen who are eligible for a Pell Grant, so there are several possible explanations for this number that is a residual of a complicated process.

Right away, of course, you notice the trend: As test scores go up, low-income students go down.  Add to it diversity, as indicated by the color of the point, and you see another pattern: The bluer dots are more heavily Asian and Caucasian; note also that they're below the line (presumably under-performing on enrolling kids with Pell), and more likely to be on the right side (high test scores) of the chart.

It's a fair criticism, of course, to point out that not every state has similar levels of wealth and poverty.  But I doubt that many of these places would be unable to find more poor students in their state, were they to simply understand that the thing they think is propelling them--test scores--may be the very thing that is holding them back.



Tuesday, March 25, 2014

Endowment Data from 847 Colleges and Universities

The 2014 NACUBO report on college and university endowments is hot off the presses.  Unfortunately, it's in a table in a pdf on the organization's website.  So, after considerable frustration to get the data into useable format, it's now visualized here for you.

Note that there are three different views, and you can change them by clicking the tabs across the top:

  1. Endowment Value Dashboard is a heat map, which is sort of like a pie chart, except it's like a sheet cake cut into pieces the size of the listed university endowment. The 847 institutions in the study collectively hold about $455B in endowment funds.  You can see the pieces of the cake: Harvard's for instance, is about $32B, or 7% of all the endowments of all the colleges and universities in the country. The pieces are colored by the percentage gain in one year.  For instance, Stanford gained $1.6B between 2012 and 2013, but the 10% increase only ranked it 483rd.  When you have a lot, you don't need a big increase to grow a lot.
  2. The Endowment Change Dashboard shows four variables: The rank of the percentage change along the x-axis and the rank of the value gained along the y-axis; the color shows the raw amount of the one-year change; and the size shows the relative value of the endowment at the end of 2013.
  3. The Value and Change Dashboard shows the 2013 value in the gray bar; the amount of change on the red, both on the top chart; and then the values and changes arrayed on the bottom.  Each of the two dot charts is colored by the rank of the other variable.
Confused? Good.  This is really intended to show a couple of things:
  • The (some might say) ridiculous range of endowment at institutions of higher learning in the US and Canada.  Note that even with relatively modest growth at the wealthiest institutions, six of them increased endowment by more than $1B in a year.  Only 83 institutions even have an endowment of $1B or more.
  • The absolute futility of trying to catch up, unless you're already in striking distance.
  • Never put your data in a table if you want it to be interesting
There's a lot of stuff here. And way more that could be done.  What do you see?



Friday, March 21, 2014

Origins of International Students in the US, 2012

Good data on international students enrolled in the US is really hard to find.  There is this awful table of data from NCES, in which it's almost impossible to discern which groups are discreet and which are rolled up into other groups, for instance.  Other things on the web are very high-level with almost no granularity, and thus, almost no insight to be had.

This from the Institute of International Education is only slightly better, showing just the top ten countries of origins, but breaking enrollment out into four levels.  The top ten countries account for about 67% of all enrollments of international students, so it's robust, especially when you see the relative contribution of Turkey (#10) compared to China (#1).

Use the two filters to limit the all three views, but be sure to understand that the bottom two (showing different percents of total) start with just 67% of all international students, and the base decreases as you filter countries or levels out.


Monday, March 17, 2014

Education and Inflation

The cost of (almost) everything keeps going up, so it can be hard to tell whether inflation is to blame, or something else.  Let's ask FRED.

FRED is the data service of the St. Louis Federal Reserve, and it provides a wealth of consumer and economic data for you to download and work with, including CPI and Chained CPI data.  For this visualization, I simply downloaded Chained CPI data for several consumer goods, like Housing, Fuel and Utilities, and Medical Expenses. Given the name of this blog, you can probably figure out where this is going.

Use the filters to show only the series or group of series you're interested in comparing. Hover over a point for details.

Many people and economists (not that those are necessarily discreet) argue with the idea of Chained CPI, but the nuances are beside the point for this purpose, I think.  It's interesting to see the comparisons between and among different categories of consumer goods; it's even more interesting to think economists boil much of this down to a single number in explaining what's happening in the economy.

For your reference, CPI (inflation) over the years 2000--2013 has been about 35%, so if you're paying for college, the good news is that alcoholic beverages are cheaper today than they were then.

And as always, this is mostly for interest, and to show general trends. Consult your economist to see if higher education is affordable for you.



Wednesday, March 5, 2014

Nominal Income Expectations

We'd like to think that higher education operates in a vacuum, and that the demand for what we offer is mostly inelastic.  But if you've been to other posts on this blog, you know that family income adjusted for inflation has fallen since 2000.  You know that the number of high school graduates is changing demographically and shrinking in many parts of the country.  And you know that colleges continue to raise price irrationally.

Here's something else: The University of Michigan and Thompson Reuters have been asking people since at least 1976 what they expect to happen to their income in the next twelve months.  This chart is very intimidating at first, but use the filters to look at certain groups: Try, for instance, to see what percentage of people over time think their income will decrease.  Then add "stay the same" to see recent trends most adults haven't seen or don't remember.  (Note: Be sure to click "apply" to make the chart update; hover over a point to see a popup with details.) Things are not as gloomy as they were in 2009, of course, but they're still bad.

Is this a "Dead cat bounce" or an honest rebound in consumer confidence? And regardless, have universities learned their lesson?  Do we collectively understand that college is a four-year commitment on the part of families, and that making a commitment requires confidence?



Tuesday, March 4, 2014

Changes in College Costs Over Time

Fresh from the 2013 Digest of Education Statistics comes one of the most popular tables: Average College Costs over Time, showing lots of stuff, including what I've visualized here: Average Tuition, Room, Board, and Required Fees for four-year, public and private colleges and universities in the US since 1969.

But before I begin, a caveat: Don't use this data to try to figure out how much you or your student is going to pay at any particular college.  Don't tell me the averages are too low.  This is NCES Data, and it's not always exactly what it's made out to be.  For instance, it seems that the growth in for-profit institutions has skewed the private costs low; I'd prefer to show only four-year, not-for-profit private universities, but that data does not go back quite as far, and I thought the longer trend was more interesting.  For reference, using just not-for-profits in 2012 would bump the average shown from $35,074 to $39,302.  Adjust accordingly.

Still, there is some interesting stuff, not the least of which is the trends from 1969 to about 1981 for private institutions.  Up until then, tuition increases largely followed inflation.  Note the rapid split after that date; the same thing happens at public institutions about ten years later.

Also, notice that the rate of increase at publics has increased in recent years, having caught up to privates and surpassed them (of course, a larger increase on a smaller base is still, in this case, a smaller number.)

What else do you see?



Thursday, February 27, 2014

A Deeper Dive on Financial Health

Federal Student Aid, a division of the Department of Education, releases its list of colleges and universities based on Financial Responsibility (sometimes called Financial Health, which I think is more accurate.)  In general, to continue to be eligible to award your students federal financial aid, you need a score of 1.5 or above (on a three-point scale.)  The scores go down to -1.

Most presentations of the data are pretty static: A table with the data, for instance.  But I think there is a bigger story here: Where are colleges in trouble located? How many are not-for-profit? How many students do they enroll? What about Pell grant recipients and students of color? Do are they more likely to enroll in colleges with failing financial health?

So I merged some 2011 IPEDS data into the mix.  Some of the results surprise me; neither Harvard nor MIT are a 3, for instance; the Franciscan School of Theology in California, however, is.  Results like this have caused some consternation among accountants, CFOs and their professional organizations, causing them to question whether there is any value at all to these rankings.

What do you think?  There are several views of the data here, including one that allows you to look at individual institutions.  For viewing, I've rolled all the scores into 1/2 point bands, and color-coded them. Enjoy.



Monday, February 24, 2014

Are Graduation Rates an Input or an Output?

It seems obvious: Students come in, and students go out. The type of students who enter your university are measured on lots of things, like test scores, GPA, ethnicity, and parental income, to name just a few. Universities are measured too, on lots of those same things, as well as others, including the graduation rate. Lots of people think the graduation rate is a function of what the university does or does not do, and in some sense, of course, they are correct: If you don't care about your students, or their progress, or you're not challenging their minds, they may leave.

But in another sense, it's also possible to think of outputs as a function of inputs. It's been suggested before by Malcolm Gladwell, for instance, that we often confuse selection effects with treatment effects:

Social scientists distinguish between what are known as treatment effects and selection effects. The Marine Corps, for instance, is largely a treatment-effect institution. It doesn’t have an enormous admissions office grading applicants along four separate dimensions of toughness and intelligence. It’s confident that the experience of undergoing Marine Corps basic training will turn you into a formidable soldier. A modelling agency, by contrast, is a selection-effect institution. You don’t become beautiful by signing up with an agency. You get signed up by an agency because you’re beautiful.
At the heart of the American obsession with the Ivy League is the belief that schools like Harvard provide the social and intellectual equivalent of Marine Corps basic training—that being taught by all those brilliant professors and meeting all those other motivated students and getting a degree with that powerful name on it will confer advantages that no local state university can provide. Fuelling the treatment-effect idea are studies showing that if you take two students with the same S.A.T. scores and grades, one of whom goes to a school like Harvard and one of whom goes to a less selective college, the Ivy Leaguer will make far more money ten or twenty years down the road.
The extraordinary emphasis the Ivy League places on admissions policies, though, makes it seem more like a modelling agency than like the Marine Corps, and, sure enough, the studies based on those two apparently equivalent students turn out to be flawed. How do we know that two students who have the same S.A.T. scores and grades really are equivalent? It’s quite possible that the student who goes to Harvard is more ambitious and energetic and personable than the student who wasn’t let in, and that those same intangibles are what account for his better career success. To assess the effect of the Ivies, it makes more sense to compare the student who got into a top school with the student who got into that same school but chose to go to a less selective one. Three years ago, the economists Alan Krueger and Stacy Dale published just such a study. And they found that when you compare apples and apples the income bonus from selective schools disappears.
Take a look at the interactive graph below, and see how strongly certain input characteristics are associated with graduation outputs.  What do you think?  You might also want to look at research from HERI at UCLA, especially the table on the bottom of page 23 in this publication.





Sunday, February 9, 2014

Trends in Federal Student Loans to Undergraduates

Since I was at the College Board Midwestern Regional Forum today doing a presentation, I thought I'd show some of their data in a visualization.  It's one I've been working on for a while, because it's trickier than it looks.

This shows loan volume for undergraduates borrowing Subsidized Stafford, Unsubsidized Stafford, and PLUS Loans.  In case you're not familiar with the parlance, you can read about it here.

Up until 2010-2011, colleges and universities could particpate in either The Direct Loan Program (FDSLP on these charts) or Federal Family Education Loan Program (FFELP) which was administered through financial institutions.

I think the trends are interesting, but you decide: I recommend when looking at volume you use constant (inflation-adjusted) dollars to see the trends unless you really want to see the growth in nominal dollars.

In order to stack the bars to show total volume, I had to do this on two charts, as it doesn't make sense to stack two averages for different types of programs.  Note that when you choose "Number of Borrrowers" and "Number of Loans" the numbers are not the same because some students do either Unsubsidized or Subsidized or both; a student is counted only once.  And the bottom chart only shows the average per type of loan; it's possible a student/family could take out all three types of loans, so it does not show student indebtedness.  That's a viz for another day.


Tuesday, February 4, 2014

Where did Doctoral Recipients go to College?

Don't get freaked by how busy this looks. It's starting off showing all the data, but you'll want to filter it down to make it easier to view.

This shows the college or university that awarded the bachelor's degree to doctoral recipients in 2011. I'd recommend you start by choosing just one of the large academic rollups, or even specific programs.

It's no surprise, of course, that larger institutions with more students produce more students who go on to a doctorate, so you can choose "Highest Degree Awarded" to look at different types of colleges. If you want to look at your specific favorite college, you can use the text box, or the state filter to narrow it down.

On all dropdown filters, make your selections and click "apply" to activate the filter.

The data came without the IPEDS ID number attached to it, so I can't (yet) merge this data with enrollment; but at some point I'd like to be able to convert the display to show percentage of graduates earning doctorates.  Obviously, it would be more meaningful, but I can't get to it yet.

Note: Large numbers of doctoral recipients came from foreign or unknown institutions; I've excluded them in the first view, but you can use the filter on the bottom right to add them if you wish.



Thursday, January 30, 2014

Educational Attainment in the US, 1940--2013

The last half of the previous century was an astounding time for increasing educational attainment in the United States.  In 1940, for instance, the majority of adults had an 8th grade education or less; 13% of the adult population never made it to fifth grade.  And in 1940, if you had a college degree, you were special indeed: Only 5% of all adults were so privileged. The first interesting point is the effect of compulsory education through high school.

Many people believe the rise in family incomes and quality of life is related to educational attainment, although which is the cause, and which is the effect is subject to interesting debate.  It's pretty clear, however, that the end of World War II was the turning point.

This visualization started out very complex, but I decided to make it simpler in the end: Choose an age category and, if you like, a smaller subset of years.  Compare men to women in educational attainment, and see how that changes over time.

I'm drawn to the 55+ age group: The baby boomers and older.  Notice how college degrees exploded over time for both men and women, but how men in this group are still more likely to have a college degree or more.  Now look at the other age groups: In the younger categories, women have surged ahead, or, depending on your perspective, men have fallen behind.: That's the real story here.  And with enrollment rates of women continuing to be much higher than for men, it's likely to stay that way for a long time.


Tuesday, January 28, 2014

No Graduate Students Need Apply

Often, the data I use on this blog is a fairly comprehensive set of colleges and universities in the United States. But very many very good smaller colleges can get lost in the array of data.

So I thought about colleges that don't award any graduate degrees, and selected the 511 from the list of over 7,000 in IPEDS. These institutions are both public and private, not for profit, and they are in almost every state. Beyond that, though, you get an interesting look at the wide range of diversity in the group via Box and Whisker Charts. If you don't know how to read a box plot, take a quick look at this article, or just know that each dot represents an institution, placed higher or lower on the chart based on the value shown; 50% of the points on the chart are contained within the gray box, 25% are above the top of it, and 25% are below the bottom of it.

Use the filters to include other types of colleges (but be warned, many have not-so-great data) or regions or control.



Monday, January 27, 2014

Colleges and the Weather

A brief aside:

When colleges across the country close for several days in a row, the weather becomes a subject of Higher Ed Data Stories. Using Wikipedia, I drew down data on the all-time high and low temperatures by state. (As an aside, it is really hard to get good data on weather records. Are you listening, NOAO?)

You can choose high temperatures or low temperatures (either Fahrenheit or Celsius; or the range between the state's all time high and low. Although this is a diversion, of course, it's interesting to me because you get surprised when you look at the data, and you find things in a visualization you'd probably not notice in a static table.

Monday, January 20, 2014

The President's Agenda for College Completion and One Little Problem

Many of you know about President Obama's call for the US to lead the world by 2020 in the percentage of citizens with college degrees.  It's a noble challenge to the country: We were first as recently as 1990, but we currently rank 12th.

And of course, it's not just a challenge to students: It's one to colleges and universities to improve access and to improve college completion among enrolled students via a wide ranging series of measures.

I had earlier tweeted that there was one small problem with this: That if we want to improve that rate by 2020, we're going to have to invent a time machine, go back 10 years, and spend more on pre-K and elementary education, which have frequently (but admittedly not definitively, for those who want to argue everything) to be the best investment in education.  Kids who don't do well in school early have greater struggles farther on, and the dream of college is even less likely. (Of course, doing well in early grade school does not ensure college readiness, either.)

And then we have the issue of paying for college, once a student qualifies for admission.  We know that Pell Grants have not kept pace with college costs, and we also know that college costs have risen too fast.  (Note: I include this Pell Grant chart for its information only; the visual suggests just the opposite of reality, in what can only be called one of the worst charts ever.)

One problem: We're pretty much going backwards on something as simple as free and reduced lunches. Take a look at the map below, and pull the slider from 2000 to 2011.  If we have more students from families who can't afford school lunch; rising college costs; and decreased federal support, it's going to be tough to get more kids to college.

Note: The qualifications for reduced for free lunches are not perfectly static, of course.  Here is the data over time.