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In a recent article in The Chronicle of Higher Education, Becky Supiano described the results of an experiment that shed light on the question of why high-achieving, low-income students don’t enroll as often in the selective colleges that high-achieving, wealthier students attend. The great value of the study stems from the fact that it was an experiment – not in the sense we often use the word (“I’m going to try this as an experiment.”), but in the scientific sense, where two similar groups are subjected to different “treatments” of some kind to assess whether they have a differential impact. This is just one example of the sort of questions enrollment managers routinely face when wondering what kinds of policy changes might affect…Read more
data
Conducting an Effective Pilot Study - Monday Musings
Data Sharers and Data Hoarders - Monday Musings
Have you read Robert Fulghum’s “All I Really Need to Know I Learned in Kindergarten”? The first thing on his list is “share everything.” There are many people on college campuses whose professional positions require that they provide reports and data analysis. These professionals can often be categorized into two groups – data sharers and data hoarders. As their “types” would indicate, data sharers are quick to provide charts, tables, and reports to their colleagues to keep them informed about topics of common interest. Many of them are genuinely excited to share data and presentation techniques.
Then there are the data hoarders. At times, they may get hung up on the power of information and tend to hold data close to the vest.…Read more
Ask What Your Data Can Do For You - Monday Musings
Institutions collect all sorts of data... some because they have to (IPEDS reporting, for example), some because they want to (say, for institutional research). They look at financial aid expenditures, socio-economic trends, enrollment behavior… you’ve seen the reports. But not everyone fully appreciates the value of their own data.
With the rapid onset of data warehouses, CRM’s, etc., most institutions aren’t suffering from a shortage of data. But many are having trouble matching the increasing volume of data with the capability to put the data to use in improving institutional policies, decision making, and resource allocation. With the highly competitive marketplace that exists in higher education, institutions can’t afford not…Read more
Adding Web Metrics To Your Key Performance Indicators - Monday Musings
It’s become essential for enrollment managers to use a collection of critical metrics – a dashboard, key performance indicators (KPIs) or some other set of measures – to monitor their institution’s progress throughout the recruitment cycle. These commonly include statistics like the number of inquiries, applicants, admits, deposits, campus visitors and FAFSA filers, as well as ratios like acceptance rate, yield, net tuition revenue per student and discount rate. Back in the days of the horse and buggy (when I got my start in admissions) the original dashboards prevented unpleasant surprises from hitting you in the face and they helped you to clearly see the road ahead – pretty much the same thing we’re using these statistical dashboards…Read more
Update on Student Debt Stats - Monday Musings
In early summer Kathy Kurz wrote a blog about the media frenzy surrounding student loan debt reaching $1 trillion. Now that fall has arrived and new statistics are available, I thought I would share a few.
According to the Project on Student Debt, an initiative of the Institute for College Access & Success (TICAS), here are some interesting statistics on student debt for the Class of 2011, those who graduated from four-year public and not-for-profit colleges and universities:
1 in 3 students graduated with no student loan debt. That’s $0 debt.
For the two-thirds who did borrow, average debt compared to the class of 2010 increased 5.3%, from $25,250 to $26,600.
Unemployment for college graduates, a contributing factor to the concern…Read more
National Trends of Note - Monday Musings
The Chronicle’s annual Almanac came out this year at the same time as NACUBO’s 1962-2012 retrospective. In looking at the trends reported in these two publications, I took note of a few that I wanted to highlight in this week’s blog.
From the Chronicle of Higher Education 2012 Almanac:
For students who started college in fall 2006, the most common transfer destination for students who started at a four-year institution was a two-year institution. Looking specifically at students who started at private non-profit schools, slightly more than 40% of those who transferred went to two-year publics. Slightly less than 40% went to four-year publics and only about 20% went to other four-year private not-for-profits. These statistics surprised…Read more
National Student Clearinghouse - Monday Musings
If you are already using the National Student Clearinghouse’s (NSC) many services, you can stop reading this blog now. However, I continue to be surprised by the number of institutions that are not taking advantage of this valuable source of information.
First, a brief primer about the NSC: They were originally founded in 1993 to serve as a clearinghouse for verifying enrollment, initially primarily for loan deferment purposes – a function that previously was handled by individual registrar’s offices. Since that time, they have expanded to offering many other services including degree verification, the StudentTracker service which is discussed more below, electronic transcript exchange, and now student self-service options. Per the NSC…Read more
Not All Applications Are Created Equal - Monday Musings
Tracking yield rates by various subpopulations is a standard procedure for most admissions offices. In-state and out-of-state; male and female; minority and non-minority; aid filers and non-filers; early action and regular decision; high school GPA levels; SAT/ACT levels. You get the picture. Yields vary by subpopulation, therefore as the application cycle progresses and admissions/enrollment is being asked for projections, it is important to understand how changes in the admit pool in certain categories may affect yield.
When an institution embarks on a new application-generating approach, such as a pre-populated application from the search pool, membership in the Common Application, or other methods, it is with the expectation that the number…Read more
Auto-packaging vs. Predictive Modeling: A Tale of Two Approaches - Monday Musings
Financial aid offices experience very tangible benefits from automated award packaging. Staff members spend less time manually calculating and entering award amounts and have more time to spend counseling students. Improving students’ (and parents’) understanding of their financial aid packages improves their ability to make informed decisions about college. There is also the benefit to the financial aid operation of reducing the errors that inevitably result from manual processes. These are significant tactical improvements in a critical enrollment function.
In addition, many institutions use auto-packaging as a test exercise to estimate the impact of changes in awarding policies on the aid budget, or to understand potential losses in…Read more
Elastic or Inelastic, That is the Question - Monday Musings
If you work in the Admissions or Financial Aid office of your institution you’ve probably heard a hundred different students say, “If you could just find a way to give me a couple thousand extra dollars in scholarships, then I’d enroll.” Or perhaps something like this, “University X is offering me $16,000 in grants and you’re only offering me $15,000? Isn’t there anything you can do to match their offer?” Students and their families have become savvy consumers. Some are facing financial hardships, others are just looking to get the best deal possible, and most aren’t afraid to ask for more money. The big questions for college administrators are, “Should we offer these students a little more money?” “Will it increase our…Read more
Limits of Modeling - Monday Musings
When I was part of an admissions office, every day in April at 10:00 AM, you could have mistaken the tension and excitement in the office for an episode of Discovery Channel’s Deadliest Catch, brought on by the arrival of the mail bin. Enrollment deposits that arrived via phone were harkened by the ringing of a bell, and we each took guesses at what the final tally for the day would be once the web payments were counted. If we had a particularly good day, the news traveled like wildfire across campus. Wherever I went, on campus or off, if I ran into someone I knew, I would invariably be asked how the numbers looked. Anticipation was in the air, even with sophisticated data tracking and aid strategies developed through predictive modeling in…Read more
Measuring, Moving, & Markets - Monday Musings
Last week was office moving day for a few folks at S&K. We are hiring another research analyst, the second time in three years that the research team has expanded in order keep up with the demand for our core services, which require significant data analysis and predictive modeling.
The move into “new territory” for some S&K staffers made me think of what should happen when an admissions office decides to expand into new markets/geographic territories. In preparation for our office move, there was measuring, measuring, and more measuring, all in an effort to make the move very efficient once the professional movers arrived to begin the heavy lifting. There was none of the “how does this look here?” or “do you think this will fit there?”…Read more
Thoughts on Reading the 2011 NACUBO Tuition Discounting Study Report - Monday Musings
The recently released NACUBO Tuition Discounting Study for 2011 starts off with the following quote: "Many four‐year private nonprofit (independent) colleges and universities use tuition discounting strategies in order to increase their undergraduate enrollments. Unfortunately, data from the 2011 NACUBO Tuition Discounting Study (TDS) suggests that this strategy is no longer working effectively at a large number of colleges and universities."
From our perspective, this view of the data gathered in the study is overly simplistic, and points out limitations in the analysis. For many institutions across the country, discount rates have increased over the last few years NOT because those institutions have introduced more generous packaging policies…Read more
Cleaning Up Data Messes - Monday Musings
Have you ever been responsible for cleaning up a big mess? I’m talking about a mess so big that you don’t even know where to begin. Maybe some of your attics, garages, or basements fit that description. I know my garage does for certain: tools piling up all over the place, boxes full of various things, rakes, shovels, a chipper/shredder, and a wheelbarrow round out the mess. Most of the items in my garage are actually useful for my home improvements projects; however in their current state of disorganization, it’s a challenge to find the item I need in a timely manner.
Looking at my messy garage or maybe your messy attic we can all have a bit of a laugh; when it comes to your data at work though, no one is laughing. So what do you do?…Read more
Is Distorted Data Driving You Down? - Monday Musings
A couple of weeks ago, my colleague Don Gray discussed how to get the most value out of your data. He stressed the importance of preserving both enrolled and non-enrolled data to facilitate future data analysis. But there is more to it than just storing your data to perform meaningful analysis. Data needs to be captured, transferred, and recorded accurately; otherwise you will quickly be looking at a "garbage in, garbage out" situation. In order to avoid putting yourself in this "trashy" state, I have listed several common data errors that I have found in my experiences as a researcher:
Deleting non-enrolled aid: The only way to do proper analysis on how financial aid impacts enrollment is to look at the money offered to all admitted students,…Read more
Getting the Most Value Out of Your Data - Monday Musings
I’ve spent the past six and a half years analyzing higher education data for more than sixty institutions, from large public universities to small private liberal arts colleges. The most common data challenge I find is institutions deleting data on students who were admitted, but ultimately decided not to enroll. I’ve found many institutions do well at recording any data they can get their hands on, but then preserve only the data for enrolled students. One common example is need-based aid, which often gets cancelled, without being archived, for non-enrolled students.
In the aggregate, your final enrollment, discount rate, diversity and SAT/ACT numbers don’t tell the whole story. It’s often important to dig deeper, analyzing results…Read more
