Styles of Excellence

with Stephon Alexander

My friend Stephon Alexander—theoretical physicist, author, Brown University professor, and jazz saxophonist—says we need more Michael Jordans among our science students. At first, that sounds like a fanciful wish. Michael Jordan is arguably the greatest basketball player who ever lived. If there is an equivalent to Michael Jordan in physics, of course we’d want as many of them as we could get. Unfortunately, they don’t come along every day or every year or every 50 years.

But sitting around and waiting for prodigies to arrive is not what Steph has in mind. He’s referring not to Jordan’s astonishing natural ability but to his equally astonishing work ethic. Steph thinks the problem of lagging performance in underrepresented minorities in quantitative fields is fixable through the right kind of mentorship and through the cultivation of the kind of practice and hard work that transforms potential into excellence.

In the following excerpt from my recent conversation with Steph, he affirms that we should not abandon testing for the basic competencies required in any quantitative field. If you want study physics or economics, you’ve got to show that you can do the math. But Steph also thinks that we may sometimes be too narrow-minded in the way we teach and test math skills. Students who perform poorly on traditional tests may show themselves to be dynamos when talking through the same equations on a blackboard. And it may be that minority students who are underperforming need the help of mentors they can relate to before they’ll be able to put in the long, hard hours necessary to learn real math and science. As a brilliant, black theoretical physicist who came up through public schools in the Bronx, Steph has been that mentor for many students.

Maybe Steph’s personal experience has broader applicability. I certainly hope that’s the case. I have to believe that black students have as much potential as anybody to succeed in the most intellectually demanding fields. But seeing that potential come to fruition sometimes feels like a rarer experience than it should be.

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GLENN LOURY: What do you think about this idea? You're in a technical field, theoretical physics. It's heavily mathematical. I mean, that's the language of the field. It's very technical and specialized, and they are relatively few black people who excel at that craft or at least have been accepted within the fraternity. And there's a huge gap in the test scores. When you do GRE quantitative or whatever it is and you look at the population statistics, the overlapping bell curves and whatnot. What do you think?

So there's two different claims. One of them is, well, if the field is technical, it requires mathematical abilities and accomplishments, and if there's racial differences, well, you'd expect racial differences in the representation. Versus the theory that says those tests don't really measure very well who's going to be a good physicist and who's gonna be a good economist or not. And if you are getting exclusionary results from the test, you probably need to think about different ways of selecting people for your program of study.

To which many conservatives—and I don't mean Trump-voting conservatives, I mean people who want to keep doing science the same way it's always been done—would say, “Come on, man. I know the difference between somebody who's in the 99th percentile of the distribution of math ability and somebody who's in the 90th percentile. I know the difference in terms of how their minds work and how quickly they're able to assimilate and process and extend, calculate, conceive, generalize. I know the difference. And I'm sorry, but it's those people, the people who are at the 99th percentile not at the 90th percentile, who are gonna be the ones, by and large, with very few exceptions, who are gonna be making scientific advances.” Where would you situate yourself in that debate?

STEPHON ALEXANDER: I think I would situate myself with a little of both, actually. So let me expound on how I would situate, because it is how I actually approach my own evaluation of students. I mentor PhD students, I have to train students to get their PhD. And as far as I'm concerned, I make it really clear to those students, look, it is my job, before you're granted a PhD [and] I find that you have what it takes, to say I sign off on a PhD, along with the committee, is that you're ready. You are ready to go off, and actually you have the skill sets, you have the tools to succeed as a physicist.

And so I do believe that there are basic competencies. Like, you know, if you want to learn how to fly an airplane, would you go into an airplane with somebody that's kind of shaky on a certain tool or skill set to learn how to land an airplane? You wouldn't. I wouldn't. So I think that, likewise in physics, or I can just say in general, there are things, some basic competencies.

How those competencies are evaluated, how we screen for that, may differ. So some people may shine if they're sitting facing a piece of paper with a pen. Some people may shine, may be able to reveal that on a blackboard, showing and telling. I've been in situations where students who are really good test takers in this mode, a sort of sitting and writing mode ... There have been semesters where I would give both a midterm that was a written midterm, but then the final would be an oral. You get on the blackboard and you calculate.

And I found, interestingly, that there are some students that performed really well in this mode, in the writing mode. But when I ask them to get on the blackboard and show me a calculation, they freeze up. There's cognitive dissonance, for lack of a better word. So again, I believe it's important that there are basic competencies that we should agree on for a given field at the different levels that we are testing or we're looking to evaluate. We can debate and agree on what those things are. And I think once we do, then I believe that there are different modes, different ways of evaluating and screening for that. So that's where I stand on that.

Therefore, I think that now there's a question of how you regulate that and whether it's doable. At a large university, it's much harder to do that. At a small college, like the one I went to with 1200 students, it may be more realistic to evaluate in a more multidimensional manner.

Okay, that's interesting. Do you think there is a racial, black-white, Asian, Latino difference relevant of the sort that you just got through calling attention to, that your point is relevant to how different groups of people are being assessed?

Yeah, that's another good point. I mean, it's interesting. I've been a college professor since 2005. So it's close to 17 years, right? From my own personal experience, I would say I've seen some black students walk on water. I just had a student a couple of years ago at Brown. He was a freshman, a first year student, African American fellow, who was sitting in my graduate-level general relativity class. And this guy was already taking graduate-level math courses and acing them, getting As. He'll be graduating this next year having completed half of the PhD curriculum for pure mathematics. But if you look at this kid, he has tatts around his body. He's one of those guys. You definitely would not wanna read that book too much.

Let me see, I want to get your question correctly. You're saying, in terms of how students are being evaluated differently ... ?

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You made the point that kids might have a mastery of skill [or] a skill set, but be able to demonstrate it in different ways. And that one kid might sit with a paper and pencil and answer questions, get a high score, but not be able to perform at the blackboard. And another kid might not do so well with a paper and pencil, but when you ask him to show you how to solve the problem, they reveal that they have a deep understanding. And that makes sense to me. Therefore you would want to have a variety of different ways of assessing and not just rely on one narrow way of assessing. If the hypothesis is true, that people are different in that respect, then it follows from that that you'd want to be different in how you assess.

And then I ask, okay, the predicate going into this part of the conversation was there are racial differences in the representation amongst people doing science, doing theoretical physics or doing quantitative economics. Blacks are whatever percent, 12% of the population and we're like 2% or even less in some of these fields of people doing this stuff. And other groups are overrepresented. Jews are overrepresented, Asians are overrepresented. And when you look at the test scores, the test scores kind of line up with the representation numbers in terms of who's in the very highest rank of the people performing on the test, which does not necessarily proxy their ability. I don't know about this young man who's taking math. My guess is he's gonna ace any tests that you give him, but I could be wrong about that.

But anyway, my point was, do you see a relevance between this kind of diversity of assessment and the racial representation? Do you think blacks, underrepresented minorities, historically excluded marginalized groups ought in some sense be looked upon as different with respect to how they show their excellence and that their underrepresentation is partly a result of institutions not adopting a more heterogeneous, more diverse way of assessing talent?

I say, again, from my observation of all different sorts of students, I fundamentally believe—it is my fundamental hypothesis because it's just a belief system—but it's based on some education, my own interacting with thousands of students over the last 17 years, is that I see no difference in terms of the phenotypical representations of race and performance and the potential to perform in these exams or ability to do compared to other other races, and also across across gender. I see those different forms of intelligence are randomly distributed across those populations. That's my hypothesis. That's how I approach my students.

Now, having said that, I think that there are other factors I found to account for the gap, the performance gap. One factor that I found and I've played on was just like this program I founded at Dartmouth called the E.E Just Program. When I started with that program, during that time—this was in 2008, I believe—there were four students in that program. This program was designed for students from economically disadvantaged backgrounds, and it was named the E.E. Just Scholars Program, named after the pioneer and black biologist Ernest Everett Just, the father of epigenetics, who went to Dartmouth.

But in a nutshell, the program was designed, or I guess the goal of the program was to fix the retention problem. You know, the fact that 90% or some large number of students that came into that school to pursue a science field didn't, dropped out of that and went into something else. Well, I can say that, four years later, that 20% number or whatever that number was—I don't want to quote a definite number—that number went to 90%.

And the other thing that was interesting was that the performance wasn't just students getting by. Students were excelling. Students were applying to get into PhD program. I just found out one of my students from that program, Jared—I'm gonna big him up—Jared Boyce, just got into an MD/PhD program in neuroscience at the University of Wisconsin. And you know, he's a black kid from New York City who went to Dartmouth.

And I think one of the main things also was a lot of these kids, for them, just simply seeing a black science professor—I mean, I'm actually now talking about myself—who came to them and said, “Listen, this C is not good enough, buddy. I need to see some As here. I expect you to do this, because I think you're brilliant, but you know what? I'm up till three in the morning calculating. What are you doing?” Like, I think that if we want to a culture within the academy of really having them see future versions of themselves and see those examples …

I think Michael Jordan was like, “Yo, you guys think I have all this talent? Maybe I do. But I practice my left hand for hours every day, over and over and over again.” Oh wait, if Michael Jordan can do that, I should do that, too. I think that these things go overlooked. I'll be honest, Glenn, as a young faculty person, a younger person, I used to look at your work and go get your papers and try to understand the equations. And as a younger person in a quantitative field, I was like, okay, I need to do this. I need to rise to this high occasion. And this is gonna take some blood, sweat, and tears. So anyway, that's kind of an example of what I think is possible. Simply put, having more Michael Jordans out there in physics.

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