The birth of tech groups dedicated to women and underrepresented minorities (URM) is part of a wave of initiatives to support, encourage and mentor underrepresented groups in the tech sector. Simply go to meetup.com and you’ll see groups geared towards URM for almost any software and programming language. In Montreal, I’m one of the co-founders of the R-Ladies Montreal group, which is part of a world-wide organization that aims to support minority genders who are passionate about the R programming language. Every month I get to see a group of people gather for workshops and hands-on sessions in what I can only describe as one of the most welcoming and supportive environments I’ve ever experienced. Our primary goal was to host workshops purely for learning R in a relaxed and inclusive environment. We provide pizza, beer, and soft drinks and dive right into the coding. Once the meetups started, we found that a space to network with other individuals, share information about job opportunities or just chat about all things data scienc-ey developed as a natural consequence of gathering together people interested in R, coding, and data science in general.
As decidedly scientific person (and former academic), I can’t help but ask myself about the empirical evidence around tech groups for URM: Is there scientific evidence that these groups help URM engage more deeply in the tech community? For the purpose of this post, I’ll focus on the experience of people identifying as female.
My first instinct is to head to the scientific literature. I wanted to drill down to the beginning. At their core, segregated tech groups appear to be designed to create a safe environment for URM’s to learn and share. For the moment, I’ll ignore all of the humanistic outcomes that could result in same-gender learning groups (feelings of acceptance, forging of friendships etc.), not because they are not important, but because there isn’t published literature.
My objective: Does gender segregation in learning environments bolster engagement in STEM fields?
I’ll try to start my brief review of the literature by focusing on the studies with rigorous study designs: randomized controlled trials. Randomized controlled trials randomly assign people to an “intervention” arm versus a “control” arm rather than let people choose for themselves. The intervention we’re trying to evaluate here is a same-sex school, and the control arm is a co-ed school. This is an extremely important study feature to bear in mind when we evaluate the influence of gender-segregated schools on engagement in STEM. Randomization will help avoid some of the selection bias that would reflect differences in family characters, rather the impact of the school environment itself. If we looked at students who were opting into same-sex schooling, we could be obscuring the fact that families with parents who are more educated may: 1) send their children to same-sex schools and 2) encourage their children to pursue STEM careers.
A Swedish study found that high school girls randomized to single sex schools performed better in math relative to those randomized to coed schools.
A Swedish study conducted in 2011 showed that single-sex schools improve math scores for girls (something critical for a STEM degree) . More interestingly, better performance in math was also accompanied by an increase in the level of self-reported confidence and greater attribution of success to talent rather than luck. These results, without extrapolating too much, is only scratching the surface of a complex question. But they may highlight the fact that single-sex environments promote a more egalitarian learning atmosphere.
Would you like your views featured on the DSS blog? Apply to DSSe for the chance to write a guest blog post, be featured on our podcast or video interviews, co-moderate a slack chat, or become a mentor to our community of female data scientists.
The next question is: if women in same-sex schools are doing better in math, are they going on to pursue STEM degrees at the college and university level. A large study conducted in Korea examined whether randomization to single sex schools impacted science and math scores in high school, as well as later enrollment in STEM university degrees. Results showed that when kids opt into same-sex schools, there is a positive impact on STEM but not when they are randomized. This suggests that there is likely child- and family-related factors that both predispose kids to attend single-sex schools as well as enroll in STEM programs.
The fact the segregation itself may not have a causal relationship with the pursuit of STEM degrees is not bad news, nor is it evidence that single sex schools have no impact. It may mean that family dynamics are an important way to get women into the STEM field. Closing the gender gap in tech may start in the home.
As previously mentioned, outside of the mere absence of majority group members, we can imagine that same-sex tech groups can serve other purposes: seeking mentorship, connecting with others and self-actualization. Given the difficulty of conducting a randomized trial, we are left with the accounts of people that opt to seek tech groups and we naturally expect these folks to differ from those who don’t. Narrative accounts are an important type of evidence, even if they can’t tell us anything about causation.
Given the sheer number of women in tech groups, many of these groups exist because they are responding to a need and members continue to attend because they provide a sense of fulfilment and enjoyment. Evaluating what elements are the most conducive for the advancement of URM is an important step forward. We can start to think about the features that can help support and engage URM such as size, structure, and content. Some organizations, such as WISE campaign have already started to map out guidelines on how to build successful networking groups for women.
Regardless of causation, correlation, or consequence, women in tech groups have an enduring popularity and provide a welcoming space for URMs to grow, network and learn. They might come for the free pizza and beer and stay for the insights, but in the end these groups may just help URMs go further in their careers.
 Eisenkopf, Gerald et al. Do single-sex schools enhance students’ STEM (science, technology, engineering, and mathematics) outcomes?
 Eisenkopf et al. Academic performance and single-sex schooling: Evidence from a natural experiment in Switzerland. Journal of Economic Behavior & Organization. 2015.
 Park, H. et al. Do single-sex schools enhance students’ STEM (science, technology, engineering, and mathematics) outcomes. PIER Working Paper. 2012.
Add your voice to the movement of female data science practitioners and executives. DSSe connects you with your community on the topics that matter.