Research Explores Ways To Overcome STEM Fields' Gender Gap

Why do so few women sign up for careers in science, technology, engineering and math? Research suggests having few women in college in these fields and in technology companies creates a vicious cycle.

DAVID GREENE, HOST:

When you look at fields such as engineering and technology - fields that have a lot of well-paying jobs - women are significantly outnumbered by men. And the problem is not just recruitment; it's retention. There's new research now into why it is often hard to retain women at tech companies and engineering schools. And here to talk about it is NPR social science correspondent Shankar Vedantam. Hey, Shankar.

SHANKAR VEDANTAM, BYLINE: Hi, David.

GREENE: So what is the problem you're looking at here?

VEDANTAM: Well, you know, people used to say that women were not as good at math. But as women have started to do as well as men at science and math, the narrative has shifted, David. And now people say, look, women really aren't as interested in these fields as men. And there's some evidence to back up this theory. Only 18 percent of engineering majors in college are female. Lots of female students show up in college saying they're interested in science, technology, engineering and math, but a couple of years later, they've switch their majors.

At the University of Massachusetts at Amherst, the psychologist Nilanjana Dasgupta told me that she had a different theory on why women might drop out of math and tech careers.

NILANJANA DASGUPTA: The prototype of success in tech is very male, so I think those stereotypes get in the way of women feeling that this is the field for them. They feel good at multiple subjects, and you feel like you don't really belong in a place. Over time, you start to de-identify or move away from fields and hang out more in other fields where your friends are.

GREENE: So women feeling like they don't necessarily belong in a place - how did she actually test this?

VEDANTAM: Well, she invited female engineering students to join workgroups that were trying to solve various kinds of problems, David. Each of these workgroups had four members. What the volunteers didn't know is that three people on each of these teams were actually researchers. So only one person on each of these teams was actually a volunteer.

Dasgupta and her colleagues manipulated the team so sometimes the volunteer was the only woman on the team. Sometimes, she was 1 of 2 women. Sometimes, she was 1 of 3 women on the team. Now, by making sure the other three people did exactly the same things every time, Dasgupta was now able to tell what happened when the female students found themselves in a minority, in a group with gender parity and in the majority.

DASGUPTA: In teams where there's 50 percent women or where women are in the majority, these female engineering students feel much more confident in their ability in engineering. And at the end of the team activity, they feel much more interested in pursuing careers in engineering, whereas if they are the only woman on the team, all of that sort of drops significantly.

VEDANTAM: But here's the thing that's interesting - there was not a single volunteer in the study who reported that the group had any affect on her behavior. Every woman who was a volunteer said their participation was shaped only by their own knowledge and by their own interest. In reality, we know this is not the case. The behavior of the volunteers was shaped significantly by their groups.

GREENE: This really feels like it's looking at sexism and bias in a very different way, looking at much more - at the thinking of the person who is being negatively affected by this in some way.

VEDANTAM: I think that's right, David. One of the implications of this work is that tech companies or engineering schools might want to ensure that when you have groups that have been historically underrepresented in certain areas - fields like engineering or fields like math - it might make sense to have a critical mass of women in work groups rather than spreading the women very thinly across, you know, your whole campus.

GREENE: Shankar, thanks for coming in to chat, as always.

VEDANTAM: Thank you, David.

GREENE: That's NPR Shankar Vedantam, who regularly joins us to talk about social science research. And you can follow him on Twitter. He is @HiddenBrain. You can follow this program - @nprgreene and @MorningEdition.

Copyright © 2016 NPR. All rights reserved. Visit our website terms of use and permissions pages at www.npr.org for further information.

NPR transcripts are created on a rush deadline by Verb8tm, Inc., an NPR contractor, and produced using a proprietary transcription process developed with NPR. This text may not be in its final form and may be updated or revised in the future. Accuracy and availability may vary. The authoritative record of NPR’s programming is the audio record.