At Columbia University, women make up 37% of computer science majors. With the national average slightly below 20%, Columbia’s relatively high percentage ranks it among the top universities in attracting women to computer science. It wasn’t always so. In 2008, the percentage of women majoring in computer science at Columbia was 8%, mirroring a nation-wide, generation-long decline that began in 1984 when women nationally made up 37% of computer science majors. Columbia’s success in reversing the trend is due to efforts by the Computer Science Department to directly address the gender imbalance, both by dispelling popular stereotypes and misconceptions about who is good at computer science, and by exposing students sooner to the wide range of problems that can be solved computationally.
Why do so few women major in computer science?
Cultural stereotypes may have a lot to do with it. The popular image of a computer programmer—a male sitting alone in front of a computer screen for hours on end either coding or gaming while consuming fast food in situ with Star Wars posters on the wall—isn’t attractive to many people. It’s not just women; many men don’t see themselves in this picture either.
It’s an unfortunate stereotype and an untrue one. Much more than programming, computer science is an approach to problem solving, entailing critical, abstract, and creative thinking that has application across disciplines, from biology and medicine, the social and natural sciences, to music, art, and the liberal arts.
Nor is programming solitary. In the real world, programming and software development are collaborative activities, with people working to build something together.
The whole notion of purposeful creation is lacking from the popular stereotype, which equates programming with computer science. It is a high school concept of computer science, and it’s in high school that the stereotype takes hold for many students, perhaps in part because the original AP exam—introduced in 1984, the beginning of the decline of women in computer science—requires students to know details of programming syntax. (Changes are in place with the introduction this fall of a new AP exam, Computer Science Principles, which focuses on algorithms, variables, and other general computing concepts.)
The jumpstart in programming that male students get in high school carries over to the college level, leading to what Julia Hirschberg, chair of Columbia’s Computer Science Department, sees as a confidence gap. “Because men typically enter college with more computer programming than female classmates, men often have higher confidence levels about computing and are more eager to speak up in class. For students just starting out, not yet fluent in the vocabulary or syntax of computer science, it’s easy to feel far behind. It can be discouraging.”
Unfortunately, introductory computer science classes, necessarily focused on teaching basic programming and computational skills, often do little initially to dispel the popular thinking. And the packed, auditorium-sized lecture classes may make it harder for students to become acquainted with peers and form study groups to help one another.
Much more than programming
In 2008, the year the number of women computer science majors hit rock bottom at Columbia, Adam Cannon, Chris Murphy, and Kristen Parton introduced the Emerging Scholars Program (ESP) to directly address the gender imbalance. ESP takes its name and model from workshops started in the 1970s by Uri Treisman at the University of California, Berkeley to improve the performance of underrepresented minority students in math classes by encouraging students to form small study groups.
With seed funding from the National Center for Women and Information Technology, Cannon, Murphy, and Parton adapted the ESP model for a computer science setting. Combining ESP with the Peer-Led Team Learning (following the example of Susan Rodger), they created a one-point, once-a-week seminar to expose students to the non-programming and collaborative aspects of computer science that typically are not a big part of introductory classes.
There is no coding and no grading or homework in ESP; the focus is entirely on high-level concepts in computer science, particularly on algorithmic thinking, the logical, step-by-step decomposing of a problem into component parts that can be solved by computer; it’s a type of critical thinking with application beyond computer science. In ESP, students learn algorithmic thinking by discussing together algorithmic solutions to a set of problems taken from natural language processing, artificial intelligence, cryptography, and social networking.
When it’s easy for a beginner to get stuck on trivial things—for loops, syntax—Emerging Scholars serves as a sort of preview of the interesting problems students will encounter in later classes.
The approach has proven successful. Students taking ESP are much more likely (as much as three times more likely) to major in computer science than the students who don’t take ESP. Over the first four years of ESP being offered (2008-2012), women went from 9% to 23% of Columbia computer science majors.
What the women are doing about it
Women themselves have not been sitting around waiting for others to fix the problem. In 1998, when women made up 10% of computer science majors (but fully half of the top 10% of students), a number of undergraduate women approached Kathy McKeown, then chair of the Computer Science Department, about forming a woman’s support group that would provide an informal, friendly environment for women in the department to connect with one another, get help on problems and projects, and share their experiences in a heavily male-dominated field. Women in Computer Science (WiCS) has grown over the years and broadened its charter to organizing networking events and arranging site visits to employers in the city.
Though funded by the department and some corporate sponsors, WiCS works outside the department to make computer science more inclusive to women. But Cherie Luo, president of WiCS, see signs that the department itself is becoming more responsive to the increasing diversity of students who want to develop computational skills. “I think a way to make computer science more appealing to women and those who yet not exposed to it is to show how computer science can apply and relate to students in all fields of study. Computing in Context does that in an approachable, interdisciplinary setting outside the ‘hyper-competitive’ intro classes.”
“Little things can help a lot. Example problems sets shouldn’t always use just men; include women also or use the plural to include everyone.”
“Role models are important. It would be nice to see more women professors and more women TAs.”
“It’s always inspiring to talk to women who have gone through the academic channel and what’s it’s been like for them.”
Changes in course curriculum
Started by Cannon in Spring 2015 to teach computing to liberal arts students, Computing in Context is a rigorous introductory computer science course that is half computer science and half applications of computer science. The course is taught by a team of professors; a computer science professor lectures to all students on basic computer and programming skills, and professors in the humanities, social sciences, and other departments show through projects and lectures (some live, some recorded) how those skills and methods apply to a specific liberal arts discipline.
Computing in Context thus engages students on their own ground, teaching computer science not as a separate field of study but as a way for students to better understand their own fields. In doing so, Computing in Context is the rare case of an introductory computer science class that naturally achieves gender balance.
The course is a unique collaboration between the Computer Science Department and other departments across campus that want to give their students the computational skills increasingly necessary in all fields and disciplines. Currently, Computing in Context has tracks for digital humanities, social science, economics and finance, and international and public affairs, with plans to add computational biology starting next year.
As new tracks are added, more students are exposed to computer science, including many students who would not otherwise take a computer science class or who still harbor misconceptions about what computer science entails. Often students coming to Computing in Context to learn how to better study their own fields surprise themselves by becoming passionate about computer science, even switching their major. It might not be the most direct route to a computer science major but it is a route nonetheless, and one that may be more inviting to many women.
By shifting the emphasis from coding to the tremendous potential of computer science to solve problems in the real world—and doing so in a context that makes sense to students—both ESP and Computing in Context more fully define the field of computer science, erasing for once and all the simplistic stereotypes that students might once have held. And this may be key to making computer science accessible not just to women but to all students, especially those who don’t see themselves as stereotypical programmers.