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Talking about Race in CS Education

By Mark Guzdial

Communications of the ACM, Vol. 64 No. 1, Pages 10-11

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https://bit.ly/3ggVGIm June 5, 2020

The horrific death of George Floyd and the social unrest in the U.S. have raised awareness of race that has been too long left out of the mainstream conversations. I am explicitly thinking about how to incorporate an understanding of race (and culture and other identity characteristics) when we teach computer science (CS). I am just as guilty of not considering the issues of race in CS education in my everyday practice. I am in a position of privilege. I have not had to face the same life experiences that my students and colleagues have.

Back in March, when the pandemic hit the U.S. and shut down our campuses, I wrote a blog post about how much I was learning about emergency remote teaching from the ACM SIGCSE-Members email list (see https://bit.ly/3l51pE1). Now, as I am realizing I have been negligent in incorporating an awareness of race issues in my CS teaching, I am again finding terrific resources in that email list, started by a note from Monica McGill (one of the leads on the terrific CSEdResearch.org website; https://csedresearch.org/). Two crises in just a few months, and SIGCSE is the community offering important resources for both of them.

Broadening Participation in Computing (https://www.nsf.gov/cise/bpc/) was the main focus of my research and service agenda for over a dozen years. I thought the goal was to get more women and underrepresented minorities into CS. CS is obviously valuable and important for students. I thought we just had to help students with diverse backgrounds to realize that. Instead, the lack of diversity is the canary in the coal mine.

I am learning our goal should be to change CS Education so that everyone is welcome and supported. CS is not a welcoming place. We CS teachers have structured our systems to keep people out, to limit access to that valuable and important knowledge. We spend so much time and energy on detecting cheating and on finding ways to limit access to our major, which sends the message that most people don't belong. A better use of that time and energy might be to provide tutoring and change our curriculum so that more diverse students succeed. We need to send the message that we are willing to change in order to address historic and systemic inequities.

We have to change CS so it serves the needs of our students and society. Using methods like Peer Instruction and curricula like Media Computation are steps in the right direction, since they are measurably better for women and underserved populations, but those are results from the few diverse students who even walk in our door—and too few CS teachers are even willing to adopt these small measures.

We do not have a meritocracy. Our CS education systems are structured to disadvantage students who are not like us and the students currently in CS. Frankly, the game is rigged. We used to think that we were about helping students "How to Think Like a Computer Scientist" (https://bit.ly/3jSEtGk). But that's just telling all these students that they have to be like us to succeed. Now we have to change how computer scientists think. We all have to change CS.

Get started educating yourself by reading Nicki Washington's paper in SIGCSE 2020, "When twice as good isn't enough: The case for cultural competence in computing" (https://bit.ly/3244eO8). Her paper is a great starting point because she directly addresses issues of undergraduate CS education. It's not just about race, but today, race is the elephant in the room that we (speaking as a white and as a male CS professor, which describes most U.S. CS professors) have ignored for too long. My student Amber Solomon made me aware of intersectionality in her paper "Not just Black and not just a woman: Black women belonging in computing" (https://bit.ly/34QJriP). Efforts to attract more Black students to CS often assume Black men. Her experience as a Black woman in computing is different. As you add other identities (like transgender), you realize that when we design our classes for the majority of our students, we are making explicit and implicit choices that make it harder for other groups.

Manuel Perez Quinones gave the most concrete example that made me question how I teach:

I will say that sometimes the problem is not in the lecture, tool, academic intervention, etc. In my experience with underrepresented students the problem is more of a personal nature rather than academic nature. For example, it should not be a surprise to anyone that students from low socioeconomic status tend to be ones that have multiple jobs, sometimes are attending to family members at home, maybe even picking up younger siblings from school, etc. And unfortunately, low socioeconomic status can be a proxy for minorities. In situations like that, having flexible deadlines makes a difference. If students work on weekends, then making a programming assignment on Sunday night (assuming you are giving them more time) is not helping and might actually put those that work at a disadvantage. Similar issues come up with office hours, labs, etc.

Do not assume that if they miss class they are lazy, irresponsible, or don't care. No, they might have other things that are more pressing than 5 points in an assignment.

"We do not have a meritocracy. Our CS education systems are structured to disadvantage students who are not like us and the students currently in CS. Frankly, the game is rigged."

Liz Johnson shared the book Grading for Equity by Joe Feldman (https://amzn.to/3jMNiS1) and the (easier to get started) article "How Teachers are Changing Grade Practices with an Eye on Equity" (https://bit.ly/2JwibOk). The key idea here is standards-based grading. You set out the standards for what students have to achieve, and you give grades based on that. No pre-allocating or rationing grades. No grades for interacting with you. If your class requires attendance at office hours just to get by, your class is inequitable. You are demanding more from the students than they signed up for when registered.

Leigh Ann DeLyser, executive director of CSforAll (https://www.cs-forall.org/), made the comment that forced me to realize that I have to change for my majority students, too:

Nikki Washington and Owen Astrachan both teach courses where examples are critically examined alongside the examples we so often assume are "colorblind." Look for those examples, be explicit, not so that your black students feel welcome, but so your white students understand the minefield they are walking into.

Some of the other books now on my reading list from these discussions:

If you read nothing else from this essay, please read these two short posts from my former colleagues at Georgia Tech, Dean Charles Isbell of the College of Computing (https://b.gatech.edu/360TukH) and Kamau Bobb, Senior Director of the Center of the Constellations Center for Equity in Computing (https://bit.ly/2TJTaku). The life experience of our students and colleagues who are BIPOC (Black, Indigenous, and People of Color) is significantly different than that of the majority of people in CS today. If we ignore that, we do them a disservice.

We have ignored that. We have to correct our mistakes.

My enormous thanks to Melissa Perez, Leigh Ann DeLyser, Betsy DiSalvo, Leo Porter, Chad Jenkins, Wes Weimer, Barbara Ericson, Matthew Guzdial, Katie Guzdial, and Manuel Perez Quinones, who all gave me valuable feedback on this.

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You might be interested in our book Culturally Responsive Strategies for Reforming STEM Higher Education: Turning the TIDES on Inequity.

The TIDES project had teams from quite a diverse population of studies and groups. One of the most useful activities that I participated in during my years as a professor. I learned so much.

The book isn't focused on CS, but rather STEM, but there are lessons for all of us in each chapter. We were led by the amazing Kelly Mack, with assistance from Kate Winter and a team of advisors.


Douglas Blank

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Mark Guzdial is professor of electrical engineering and computer science in the College of Engineering, and professor of information in the School of Information, the University of Michigan.

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