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Barbara Ericson and I were invited to be discussants at a showing of “Code: Debugging the Gender Gap.” I highly recommend the movie. It was fascinating to watch, made all the more fun by seeing heroes that I know appear, like Nathan Ensmenger, Avis Yates Rivers, Jane Margolis, Ari Schlesinger, Colleen Lewis, and Maria Klawe.
Afterward, I got to make a few comments — expanding on some of the movie’s points, and disagreeing with others.
The movie makes the argument that men and women aren’t wired differently. We are all capable of learning computer science. They didn’t have to make a biological argument. In the Middle East and many other parts of the world, computer science is female-dominated. Clearly, it’s not biology. (Perhaps surprisingly, I recently got asked that question at one of the top institutes of technology in the United States: “Don’t women avoid CS because their brains work differently?” REALLY?!?)
The movie talks about how companies like IBM and RCA started advertising in the 1970’s and 1980’s for “men” with “the right stuff,” and that’s when the field started masculinizing. They don’t say anything about the role that educators played, the story that Nathan Ensmenger has talked about in his book “The Computer Boys Take Over.” When we realized that we couldn’t teach programming well, we instead started to filter out everyone who would not become a great programmer. For example, that’s when calculus was added into computer science degree requirements. Women were less interested in the increasingly competitive computer science programs, especially when there were obvious efforts to weed people out. That was another factor in the masculinization of the field.
Many of those interviewed in the movie talk about the importance of providing “role models” to women in computing. The work of researchers like the late (and great) Joanne Cohoon show that role models aren’t as big a deal as we might think. Here’s a thought experiment to prove the point: There are biology departments where the faculty are even more male than most CS departments, yet those departments are still female-dominant. What we do know is that women and URM students need encouragement to succeed in CS, and that that encouragement can come from male or female teachers.
Finally, several interviewed in the movie say that we have to get girls interested in CS early because high school or university is “way too late.” That’s simply not true. The chair of my School of Interactive Computing, Annie Antón, didn’t meet computing until she was an undergraduate, and now she’s full Professor in a top CS department. Yes, starting earlier would likely attract more women to computing, but it’s never “too late.”
After the movie, an audience member asked me if I really believed that diversity was important to build better products, and how would we prove that. I told him that I didn’t think about it that way. I’m influenced by Joanna Goode and Jane Margolis. Computing jobs are high-paying and numerous. Women and under-represented minority students are not getting to those jobs because they’re not getting access to the opportunites, either because of a lack of access to computing education or because of bias and discrimination that keep them out. It’s not about making better products. This is a social justice issue.
Koli, Finland, 16-19 November 2017
Original submissions are invited in all areas related to the conference theme and should have an explicit connection to computing education. Topics of interest include, but are not limited to:
- Computing education research: theoretical aspects, methodologies and results;
- Development and use of technology to support education in computing and related sciences, e.g., tools for visualisation or concretisation;
- Teaching and assessment approaches, innovations and best practices;
- Distance, online, blended, and informal learning;
- Learning analytics and educational data mining;
- Computing education in all educational levels, e.g., K12, context and teacher training.
Program Chairs, Koli Calling 2017
New research report available at http://services.google.com/fh/files/misc/unconscious-bias-in-the-classroom-report.pdf from with Google and Thomas Dee of Stanford University and Seth Gershenson from American University.
In sum, Unconscious Bias (UB) is a nontrivial problem in education, especially in CS and STEM education, and it is not easily addressed via traditional educational policies and interventions. However, interventions that identify and alter the frequently unconscious psychological processes that harm individuals’ outcomes are currently being developed and piloted. Teacher-facing interventions, which can be administered to both pre- and in-service teachers, are particularly promising. In part, this is because by addressing UB among teachers, we can help shape the entire classroom context in supportive ways. Furthermore, teacher-facing interventions are potentially cost-effective and scalable, because infrastructure for teacher training is already in place.
The ACM Turing China conference will have a SIGCSE track this May. Come see SIGCSE Chair Amber Settle, world-famous CS educator Dan Garcia (recently in NYTimes) from Berkeley, and me in Shanghai in May.
The ACM TURC 2017 (SIGCSE China) conference is a new leading international forum at the intersection of computer science and the learning sciences, seeking to improve practice and theories of CS education. ACM TURC 2017 will be held in Shanghai, China, 12-14 May, 2017. We invite the submission of original rigorous research on methodologies, studies, analyses, tools, or technologies for computing education.
Source: ACM TURC 2017 (SIGCSE China)
Please follow the survey link below to give feedback to Google on what you think is important in CS education research.
We are collecting input to inform the direction of Google’s computer science (CS) education research in order to better support the field. As researchers, educators, and advocates working in the field everyday, your input is extremely valued. Please complete this survey by Sunday, April 23. Feel free to share this survey with others who may be interested in sharing their insights.Thank you,Jennifer, on behalf of Google‘s CS Education Research & Evaluation team
Kate Cunningham is a first year PhD student working with me in computing education research. She just won an NSF graduate research fellowship, and the College of Computing interviewed her. She explains the direction that she’s exploring now, which I think is super exciting.
“I’m interested in examining the kinds of things students draw and sketch when they trace through code,” she said. “Can certain types of sketching help students do better when they learn introductory programming?” She grew interested in this topic while working as a teacher for a program in California. As she watched students there work with code, she found that they worked solely with the numbers and text on their computer screen.“They weren’t really drawing,” she said. “I found that the drawing techniques we encouraged were really useful for those students, so I was inspired to study it at Georgia Tech.”
Essentially, the idea is that by drawing or sketching a visual representation of their work as they code, students may be able to better understand the operations of how the computer works. “It’s a term we call the ‘notional machine,’” Cunningham explained. “It’s this idea of how the computer processes the instructions. I think if students are drawing out the process for how their code is working, that can help them to fully understand how the instructions are working.” That’s one benefit. Another, she said, is better collaboration. If a student is sketching the process, she posits, the teacher can better see and understand what they’re thinking.