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First-year student diversity in American colleges and universities, 2018-2022

I started this visualization to show how first-year classes at the highly rejective colleges had changed since COVID-19 forced them all to go to a test-optional approach for the Fall of 2021.  But it sort of took on a life of its own after that, as big, beefy data sets often do. The original point was to help discount the conventional wisdom, which is propped up by a limited, old study of a small set of colleges that showed test-optional policies didn't affect diversity.  I did this post last year , after just one year of data made it fairly clear they did at the institutions that had the luxury of selecting and shaping their class.  This year I took it a little farther.  The views, using the tabs across the top, show the same trends (now going to 2022) for Public Land Grants, Public Flagships, the Ivy and Ivy+ Institutions.  In each case, choose one using the control. Note that I had colored the years by national trends: 2018 and 2019 are pre-test optional, gray is COVID, and blue
Recent posts

Enrollment is complicated, redux

 Enrollment, as I like to say, is complicated.  But that never stopped anyone from asking a question like, "How does enrollment look?" To help answer, I downloaded IPEDS data of enrollment from 2009 to 2022, breaking it out by full-time and part-time, graduate and undergraduate, and gender, and put it into three different views, below, using the tabs across the top.  As always, you need to be a bit careful jumping to any conclusions about this: There is no easy (or even any hard) way I know of to account for the way Penn State has named and renamed itself over time, and changed the way it reported data, for instance, so anomalies will always show up there.  But for the most part, this information is very accurate.  The first view shows summary data.  This is just to get topline information about trends in US higher education enrollments over time.  Choose the type of enrollment at top right, then filter down to the specific categories you'd like to see.  You cannot break

First-year student (freshman) migration, 2022

A new approach to freshman migration, which is always a popular post on Higher Ed Data Stories. If you're a regular reader, you can go right to the visualization and start interacting with it.  And I can't stress enough: You need to use the controls and click away to get the most from these visualizations. If you're new, this post focuses on one of the most interesting data elements in IPEDS: The geographic origins of first-year (freshman) students over time.  My data set includes institutions in the 50 states and DC.  It includes four-year public and four-year, private not-for-profits that participate in Title IV programs; and it includes traditional institutions using the Carnegie classification (Doctoral, Masters, Baccalaureate, and Special Focus Schools in business, engineering, and art/design. Data from other institutions is noisy and often unreliable, or (in the case of colleges in Puerto Rico, American Samoa, and other territories, often shows close to 100% of enroll

Tuition and Fees at Flagship and Land Grant Universities over time

If you believe you can extract strategy from prior activities, I have something for you to try to make sense of here.  This is a long compilation of tuition and fees at America's Flagship and Land Grant institutions.  If you are not quite sure about the distinction between those two types of institutions, you might want to read this first .  TLDR: Land Grants were created by an act of congress, and for this purpose, flagships are whoever I say they are.  There doesn't seem to be a clear definition.   Further, for this visualization, I've only selected the first group of Land Grants, funded by the Morrill Act of 1862.  They tend to be the arch rival of the Flagship, unless, of course, they're the same institution. Anyway, today I'm looking at tuition, something you'd think would be pretty simple.  But there are at least four ways to measure this: Tuition, of course, but also tuition and required fees, and both are different for residents and nonresidents.  Additi

First-year Discount rate at private colleges, 2021

This is always a popular topic, but the subject is misunderstood.  I want to talk about discount rate at private colleges.   IPEDS has the best data on first-year (or freshman) discount, so that's what I visualize.  And the first part of this is going to get a bit into the weeds; if you work in a private college or university, and you use this in your work, or you send it to trustees, you can support my time, effort, software, and hosting costs by buying me a coffee .  If  you don't want the details, and you think you understand this concept, feel free to skip down to the section that breaks down the views, below the line of asterisks. For those who always ask, no, I don't do this for public universities.  It may be helpful to compare institutions within a state, but beyond that, state funding models and the mix of resident and nonresident tuition rates make comparisons across borders mostly meaningless.  And for the more knowledgeable who might wonder, I assume that all in

Yes, your yield rate is STILL falling, version 2022

We finally got the delayed 2022 admissions data from IPEDS yesterday, and I spent the better part of the evening working on pulling this together.  Counselors, parents, students, and admissions/enrollment management officers tell me this is a helpful tool to use while thinking about the state of college admission. There are four views here: All institutions interactive shows admission data for all institutions who report it to IPEDS: The number of applications for the first-year class, the number of students offered admission, and the number who enrolled, shown on the bar charts at top.  Then, below, I've calculated admit rates, yield rates, and draw rates.  Admit rate is total admits/total applications; Yield rate is total enrolls/total admits.  And draw rate is yield/admit rate. Draw rate is intended to show fake, artificially deflated admit rates.  I've written about this a lot, but essentially if you try to look more selective than you are by pumping up soft application

Undergraduate institutions of doctoral recipients

This post is popular every year, and I've just updated it with the most recent NSF data (you can find the link to create your own tables on the visualization if you want.) It shows the undergraduate college of people who received doctorates in 2016, 2018, 2020, and 2022.  As you can see from the top-level view, UC Berkeley produces more graduates who go onto a doctorate than any other institution in the US.  But maybe that's not what you need: You might be working with one of those special high school students who already knows they want to get a doctorate, or you might want to show which college from a group of peers sends the most people to a Ph.D. or Ed.D.  Or you might want bragging rights against your alma mater's bitter academic rival. This visualization, of course is interactive. So use the controls at top to find colleges by region, by religious affiliation, or by broad Carnegie type.  And filter further to find, for instance, the liberal arts college in the Great L