Skip to main content

Watch Out, Guys

Women have made tremendous strides in educational attainment of bachelor's degrees in the last half of 20th century and the first decade of the 21st.  And even though doctoral degrees have lagged behind, we can see dramatic changes there as well.

Take a look at this visualization using National Science Foundation Data (this link downloads the data for you in Excel as Table 14).  What you see over time is a dramatic increase in the number of women who earned doctorates since 1983, but also a shift in the percentage distributions. Women are now the majority in Life Sciences, Education, and Social Sciences, and close to dead even with men in all fields except Physical Sciences and Engineering.

The second view (using the tabs across the top) shows doctorate by broad discipline over time.  Use the filter at the top to compare men and women, or to see the totals.  Note the tremendous percentage growth in women in engineering since 1983: From 124 to 2,051, an increase of over 1,500%.

While it's not necessarily true that most doctoral recipients work in higher education, it's true that higher education gets most of its instructional faculty from doctoral recipients; the long, slow trend (assuming it will continue, or even just stabilize) means there are some interesting changes in store in the higher education labor force in the coming decades.  It's possible college faculty will look very different 20 years from now

What do you think?

P.S. You might also be interested in this, showing bachelor's attainment over time.



Comments

Popular posts from this blog

The Highly Rejective Colleges

If you're not following Akil Bello on Twitter, you should be.  His timeline is filled with great insights about standardized testing, and he takes great effort to point out racism (both subtle and not-so-subtle) in higher education, all while throwing in references to the Knicks and his daughter Enid, making the experience interesting, compelling, and sometimes, fun. Recently, he created the term " highly rejective colleges " as a more apt description for what are otherwise called "highly selective colleges."  As I've said before, a college that admits 15% of applicants really has a rejections office, not an admissions office.  The term appears to have taken off on Twitter, and I hope it will stick. So I took a look at the highly rejectives (really, that's all I'm going to call them from now on) and found some interesting patterns in the data. Take a look:  The 1,132 four-year, private colleges and universities with admissions data in IPEDS are incl

Yes, your yield rate is still falling, redux (2021)

I've been creating this data visualization, or some form of it, for several years now .  I think it's most useful for higher education enrollment professionals who have to explain to people at their university why their yield rate is falling.  The short answer is that applications and admits are increasing faster than student populations: If a student today applies to an average of seven colleges, compared to four colleges twenty years ago, yield rate almost has to go down.  I'm sure AI will fix this, and all our problems, very soon. But I've spoken to others who use this other ways: To work with students to talk about chances for admission; to show parents how things have changed in the past twenty years; or to help journalists understand the lay of the land.  Whatever you use this for, I hope it's instructive, and I hope you feel free to share it widely. And if you work in a college or university and save yourself some time by using this, or if you work with clien

Freshman Migration, 1986 to 2020

(Note: I discovered that in IPEDS, Penn State Main Campus now reports with "The Pennsylvania State University" as one system.  So when you'd look at things over time, Penn State would have data until 2018, and then The Penn....etc would show up in 2020.  I found out Penn State main campus still reports its own data on the website, so I went there, and edited the IPEDS data by hand.  So if you noticed that error, it should be corrected now, but I'm not sure what I'll do in years going forward.) Freshman migration to and from the states is always a favorite visualization of mine, both because I find it a compelling and interesting topic, and because I had a few breakthroughs with calculated variables the first time I tried to do it. If you're a loyal reader, you know what this shows: The number of freshman and their movement between the states.  And if you're a loyal viewer and you use this for your work in your business, please consider supporting the costs