Race Tracking

Ashley Thorne

Anna Garcia’s grip tightens on the mouse. Her forehead furrows in frustration. She’s doing math problems on the computer and can’t remember how to find the area of a circle. Just as she’s beginning to feel defeated, the mouse sensor registers her vice hold and the camera attached to the computer identifies her facial expressions. “You can do it!” says a smiling digital Hispanic woman on the screen. “Remember, πr2!” 

University of Massachusetts at Amherst researchers in the Computer Science department, led by Beverly Woolf and Ivon Arroyo, are developing software to help elementary and middle school girls with math by reading and responding to their emotions. Why girls and not boys? Woolf and Arroyo say they want to find ways to keep girls interested in math once they reach high school, when many girls begin to struggle in the subject. 

The software provides each student with a customized “learning companion,” an electronic tutor matched to the student by race. The idea is to “enhance attractiveness” of the tutor to the student. Supposedly if the teacher looks like you, you’ll be more motivated to learn.  

My first computer game, circa 1995, was a 2-D program called Math Blaster. For hours I would practice addition, subtraction, multiplication, and division via outer-space-themed games. The astronaut and alien characters weren’t tailored to look like me, but that didn’t matter much. Nor did appearance matter when I took typing lessons from the fictional character, Mavis Beacon, depicted in the software as an elegant African-American woman. Her presence on the side of the screen didn’t alter the abundance of my mis-typed letters splatting as bugs on my virtual windshield. Come to think of it, I played on another typing program taught by a lovable nasal-voiced cartoon ghost. He didn’t look like me either.  

Virtual tutors may really help children who struggle in math. According to the UMass report, students who use the software see their math test scores improve by 10 percent. Most of these students are girls, who respond well to the emotional support from the mood- and race-matched computer characters. Apparently “boys mute or turn off the learning companion character twice as often as girls when working through the mathematics tutorials.”  

But in addition to the ostensible discrimination against boys and the impulse to dismiss girls’ diminished capability in math as a socially constructed gender stereotype, what’s problematic about this software is its message to students that they are defined mainly by race. The program’s effort to match students with e-tutors by race and ethnicity teaches that you can’t learn from someone who doesn’t look like you, and that it’s “more attractive,” or even safer to associate only with people of your own skin color. The researchers at U Mass—a university which NAS has long observed to possess a troubled understanding of race and “justice”—buy into the logic that minority students learn better when they receive special treatment that takes their race into account.  

The Chronicle of Higher Education (subscription required) this week highlights another emerging trend in this vein, in an interview with James Ellenson, adjunct associate chemistry professor at North Carolina Central University, a historically black institution. Professor Ellenson’s premise is that minority students are more engaged in the classroom when they are asked to respond anonymously to questions throughout the class time using “clickers.” 

Teaching with clickers is growing in popularity as pedagogy to determine whether students are “getting it,” understanding the course material, and paying attention. Systematic surveying of a roomful of students could be useful in a large lecture hall where discussion is limited, personal attention is rare, and the course content is largely objective, as in math or science. In that case, it might serve the professor well to know, based on a poll, that only 36% of the class knows what the reading was about. Such assessments may have a place in online courses as well.  

The NAS blog recently hosted an informal debate on clickers, prompted by Professor David Clemens’ post satirizing them. Dr. Clemens, a professor of Great Books, wanted to show that clickers cannot measure many of the most important aspects of learning, such as whether students understand complex themes in literature. Relying on these assessment tools also encourages professors to aim low and require students to have only surface-level familiarity with a subject. This is similar to the student learning outcomes (SLO) movement, which impels professors to set low goals in order to easily attain them, since meeting the goal is more important than what the goal actually is. 

Professor Clemens’ post elicited a response from Derek Bruff, a senior lecturer of mathematics at Vanderbilt University and author of the book Teaching with Classroom Response Systems: Creating Active Learning Environments. Bruff argued that clickers help engage students, because “Instead of hearing from just a handful of students in response to a question, each and every student can be expected to respond. This means more students are thinking about the question and more are prepared to contribute to the discussion that follows.”  

These purported benefits of clicker-use, however, are not race-specific. Neither are the advantages of which Professor Ellenson speaks in his Chronicle interview. There he says that anonymous polls eliminate social pressure from classmates who resent the know-it-all who speaks up in class. Ellenson alludes to a student who stopped talking in class because “I’ve lost all my friends,” friends who said, “Quit acting so smart.” 

Ellenson describes typical benefits of using interactive technology—individual participation uninfluenced by the opinions of peers, increased alertness in the classroom, and directed study. The only time he mentions race is to say that in their homes most minority students aren’t getting support for their studies. This is true, but it can be the case for non-minority students as well. Bottom line: regardless of whether using clickers is a good teaching method, there simply isn’t a good argument for treating students differently based on their skin color.  

In a recent Inside Higher Ed article, Roger Clegg showed how the “role model” rationale for racial preferences in hiring faculty members is illegal and bad policy. Creating digital “role models” in the UMass math software seems to be a way to get around the illegality. But the message to students is the same: your role models should be people who look like you; you will learn better from people who share your cultural background. It teaches students to stick with their own kind and to regard members of other races with suspicion. It counteracts the very diversity doctrine in whose name it is declared. Rather than “celebrating” how we are all different and can learn from one another (ostensibly the lesson of “diversity”), the message is to retreat into segregated identity groups.  

Yet perhaps NAS can learn from this approach. Our computer scientists are getting to work to design a program that can read the faces and register the mouse grips of our readers. Our learning coaches will offer handy hints and encouraging clichés to help you plow through our articles.  

We’ll even design matching avatars to look like you. Bald? You got it. Bearded? We’ll add whiskers. Bespectacled? Your digital coach will rock the glasses look. Two-headed?  Our bi-cephalous avatar is the perfect match.  And we’ll interrupt your reading at each paragraph to make sure you’re tracking. 

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