[00:00:00] Bonni Stachowiak: Today on episode number 346 of the Teaching in Higher Ed podcast, Archana McEligot joins me to talk about filling the equity gap in STEM fields.

[00:00:14] Production Credit: Produced by Innovate Learning, maximizing human potential.

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[00:00:23] Bonni: Welcome to this episode of Teaching in Higher Ed. I’m Bonni Stachowiak, and this is the space where we explore the art and science of being more effective at facilitating learning. We also share ways to improve our productivity approaches, so we can have more peace in our lives and be even more present for our students. Based on my partnership with the California State University, I am so glad to be welcoming Archana McEligot to the Teaching in Higher Ed podcast. She’s an epidemiologist and professor of health science at California State University, Fullerton.

She received her PhD in public health epidemiology from the joint doctoral program between the University of California San Diego, and San Diego State University. Her primary research interests include examination of the association between dietary intakes and chronic disease control and prevention, specifically cancer in at-risk populations. She’s also interested in assessing the relationship between dietary circulating biomarkers such as folate and carotenoids, in conjunction with genetic polymorphisms on disease risk, via population-based large cohort studies.

Dr. McEligot has also received a number of externally-funded grants that allow for developing curricula, guiding students through research, and directing training programs in efforts to support the success of underrepresented students. She serves as the director and principal investigator of BD3-REAP, which you’ll hear about during today’s interview. Archana, welcome to Teaching in Higher Ed.

[00:02:18] Archana McEligot: Thank you so much for having me. It’s my pleasure.

[00:02:21] Bonni: I always get interested in people’s origins stories. I want to hear the story about how you first got into data science, and also if it says anything about what students are experiencing today as they consider pursuing that field.

[00:02:39] Archana: Sure. Data science is a really amazing new field, relatively new field. I like to say, and sometimes I know that depending on which colleagues I talk to, and I was trained in public health epidemiology, that epidemiologists were the first data scientists. In my courses, I talk about John Snow, he was an English physician. He was one of the first to actually do what we call shoe-leather epidemiology. He walked the streets of London to figure out what was the cause of cholera at that time. At that time, in the 1800s, they thought that diseases spread through the air.

Not so different than what we’re experiencing now, but they really did not see it as there’s bacteria and viruses, that there was no awareness of that. He actually went door to door, collected data to see which families were getting ill, what was the source of the water. He actually indeed found that it was through a certain source of water from the Thames River that was causing cholera. As a scientist, especially as an epidemiologist, data is big. We love looking at individual data. We love looking at overall aggregated data. Those are the patterns that tell us what’s going on with health in our community.

To make a long story short, how did I get into data science? I have to say that it was part of my DNA, of my training in terms of looking at data. Really, depending on who you ask, data science is a really interdisciplinary field, it’s not just one area. It really is an amalgamation of several things. One is the statistical know-how, you have to know the stats, you have to know which tests to run, the statistics behind it. You also have to understand the computational capabilities because now with the advent of big data, you have to be able to write algorithms.

You have to write code, certain code, use different software. Actually understand the storage of these massive amounts of data. Then the other very key important factor related to big data or data science is the expertise field. You can’t make sense at all, a computer scientist, a mathematician, a statistician cannot make sense of this data unless you have someone who is knowledgeable in that expertise, whether that be a neuroscientist, whether that be a geneticist. You really do need that interdisciplinary perspective when looking at data.

I really try with my students, for them to understand that, and this has been a long ongoing conversation about working in silos, we can’t work in silos. Some of the greatest innovations and discoveries have happened through a multidisciplinary perspective. I really try to have my students acknowledge and understand that. Also to understand the greater impacts of this public health impact, that if you are just studying one genetic polymorphic variant, what does that really mean in terms of public health? If you’re only looking at one different pathway for a specific disease, what does that confer or add to the literature for that disease?

If they’re interested in data science, honestly, the sky’s the limit, this is the time to do it. It’s an exciting time, it’s a new world, it really is. A student, a middle school student, a high school student, could go online, get data available via Google, many, many other open-source datasets, and solve some of the problems that actually would take decades to solve.

[00:06:32] Bonni: I want to go back to John Snow, I’m going to make an assumption about John Snow. I think I’ve heard of him before, but I could also be imagining it, but I’m going to make an assumption about him. He sounds to me like he might be a man. He also sounds like he might be white, is that correct?

[00:06:50] Archana: Absolutely.

[00:06:52] Bonni: We know that John Snow has been multiplied and really has persisted in STEM fields more broadly. Also, of course, within data science specifically. Would you speak a bit about what we know in terms of representation of historically marginalized populations and also of women?

[00:07:14] Archana: Yes, thank you for asking that question. This is an important critical, continued area. It’s not even an area, it’s almost something that is inherent in education that we have to address, is the underrepresentedness, the inequality. I can just be very blatant about it, we have less than 10%, about 7% of the BIPOC community, African Americans, Latinx communities that are entering the STEM fields, the data science-related fields. There’s gender inequality as well. It’s critical for us to address it. There’s less than 10%, whereas the BIPOC communities, the black, indigenous people of color make up, really, 30% to 40% of certain areas and certain populations, and in the United States as a whole.

When you look to see, that’s called not having equal representation, just by the numbers alone. I really feel that when you don’t have the voices, this gets us back into what we’re facing today in our society, the continued inequities. Until we really address that through education, we’re just going to continue to have health disparities. I think people just can’t close their eyes and say, “Well, it’s not affecting me.” It is affecting you, and it will affect you. I think that many people, individuals, adults, students, kids, they get into this mindset that it is only that, “Well, if it’s not affecting me, then there’s really nothing that I need to do about it.”

In reality, as you can see, during this entire pandemic that we’ve gone through, it affects all of us. That unless we’re able to address disparities, health inequities, educational inequities, it will impact all of our lives. We could see that if we’re not addressing these, then it’s going to impact our healthcare system. That’s what’s going on right now. It’s impacting our healthcare system. Unless we give people appropriate access to care, appropriate and equitable access to education, in many other areas, we’re going to continue to see an onslaught of disparities that will impact all of us.

[00:09:45] Bonni: When we start to look at some of the biases that exist that prevent the kind of inclusion that you describe, I so often hear conversations which are important. That look at how to change those perceptions, but I also have found it very compelling, the evidence that would say, perhaps, not instead of, but in addition to, to place an emphasis on systems that could interrupt the bias. The example could come from resumes. Perhaps we don’t see the names before we evaluate the resume on whether or not this would be an individual we’d like to speak to. Are there things that come to your mind that you’re seeing, that can interrupt the systems that allow these inequities to persist?

[00:10:38] Archana: Definitely. There is this inherent, I think stereotype that goes on in our minds. That in itself is critical. I think through our program, which we’ve had the BD3-REAP program at Cal State University Fullerton, along with my incredible colleagues that I’ve worked with in the math and the biology department, systemically, we have to provide small steps for all to engage in these types of experiences. I think what’s been really successful for our program, where many underrepresented students, they experience this imposter syndrome, so we have to ourselves move past our own innate biases that we bring into our teachings, into what we’re doing. That’s one thing.

I think it’s also within the cultures too that that’s there, that this is what we like to set. What I’m saying is that, yes, moving past the negative stereotypes, moving past feelings of imposter syndrome. I think the other issue is that there’s a lot of feeling of isolation for BIPOC communities, for people of color on campuses. What our program has done, we’ve had several evaluations that we’ve done with our students. What we’ve found is that really having that experience, that research-based experience, they have this extraordinary experience at USC. This research inquiry-based experience and where they gained skills.

I really contribute their success to two things. One is through not just building self-efficacy, but what some of the students have said is that knowing the belief of others, other faculty in them was really important. I think it was a combination of both. That was really derived through four or five things that we did, and that was through intensive research experiences, so they built that efficacy. They knew how to code, they knew how to program, programming or they had experiences in Python, and many more when they went to USC, so they built their skills. The other really critical thing was that they built one-on-one relationships with faculty.

We didn’t seem so mysterious, unapproachable. We really had this program where they interacted individually with each faculty, especially at Cal State University, at CSUF. Then the other thing we did I think was really important, and the evaluation actually demonstrated this, is that they were a tight-knit group. We created this mass, this critical mass of students where they had each other’s support. I think what’s also important in this fostering this exploration, this desire, this love of science, and wanting to continue, is to actually be part and present in the broader scientific community.

It needs to be the right broader scientific community at times, where I think they see people of color, they see faculty of color. Not always, but I think it’s important they see women in that particular field. For many students, they’ve never even gotten on a plane, they haven’t been out of the state, so that really does change a lot of things in their mind, and see that, “Oh, okay.” They see all these other students doing it, other peers, and say, they themselves, “If they can do it, I can certainly do it.” I think that those were really critical steps in helping our students succeed and to apply to graduate school, and continue their education in the STEM fields.

[00:14:23] Bonni: When we talk about John Snow, the way that you told that story felt to me like you just invited me into the conversation, because you didn’t start to define your terms and say, “These are the different kinds of data scientists, and this year–” I don’t even think you mentioned the year, I wouldn’t even have remembered it if you had said it, but you started really posing some questions. We got immediately into John Snow’s head, and some of the challenges in the day, and then some of the ways in which they were missing information. They didn’t have the imagination for the kinds of ways that diseases were spreading in that time.

It’s reminding me a little bit, as you talk about some of your students’ experiences, that I even think for myself, and I consider myself to be very privileged in this world, but I didn’t know what it meant, I didn’t know what degrees were. I didn’t even know the degree I was earning, let alone somebody else, that I wouldn’t have been able to tell you what a master’s degree was versus a PhD, versus other types of doctoral. Absolutely no idea.

There’s both the, “I can’t picture this world,” but then there’s also the, “I don’t even think I would belong in there, even if I could imagine it.” Even if we try to expand students’ imagination, if all we show them are white men, we’ve actually made the problem worse of like, “Well, now that I see what the world looks like, I for sure couldn’t fit in.” We have to have that, “I could see myself there,” but also, “Someone else could see me there too. Someone else believes in me that I could do this.”

[00:16:14] Archana: I think that is still critical, what you just said, that I think them seeing someone that looks like them is so important. I remember the first time I saw– I’m Indian, I saw an Indian girl on a TV show. I remembered that moment when I was 12. I don’t remember many things in my childhood, but I remember that moment. I think that continues to go back to the having representation of mentors that look like them. That really when they see that, they say, “Hey, if this person could do it, I can do it, too.” It is really important.

I think also, in addition to that, that we’re really discussing this– I don’t think it’s a new concept, but I’m glad we’re talking about it, is allyship. That how do we support people of color, even if you’re not that particular ethnicity. I also tell my students, it’s okay to have others as allies. They don’t need to look exactly like you, be you, but if they’re there in expanding some knowledge, information to help you become that independent scientist, that independent researcher eventually, and their styles may be different, just don’t get offended. You can’t get offended in science, you just have to keep going.

Like you said, sometimes a lot of students just don’t know about a master’s degree, what degree. I think a lot of them and many of us get caught up in that question of, “What question should I ask? What research questions should I ask?” If you go from the broader umbrella of just not knowing at all what it is and then finally answering that question, what I tell them is to just continue, and there’s all types of responses in science. If it’s something that feels offensive to you, that’s fine, that’s something that happened, but you have to get not used to it, I don’t want to say that, but I think you have to work your way around it.

Then just know that you won’t get an immediate response from someone if they’re busy, you have to go ahead and continue with it. It goes back to if you’re passionate about your work. If that is what you want to do, you’re passionate about that question, that will actually take you a long way in moving forward. You’re right, not everyone can say that to themselves. That’s why I think having programs like this, having other faculty at institutions maybe that may not have such exposure to diversity– At Cal State, Fullerton, it’s incredible, we have such a diverse campus.

When I am at graduations, I’ve been at nearly 15 graduations, when I’m there, I look out into the audience and I think, “This is the world.” We have people from all over the world, and it’s such a unique place, but then I have to remind myself that many institutions are not like that. I can see where students get that feeling of isolation and have that feeling that there’s these negative stereotypes about them and the microaggressions that they must feel when interacting with faculty. I think for those institutions, they do need to take a really good look at themselves.

They need to say, “Okay, how can we train our faculty? How can we work with them?” and just actually recognizing it. I think it goes so much into why is it important to having scientists of people of color? One, I really do think they bring different ideas. When we get more perspective, we will get better representation, not just in the academic field but in participation. There’s a lot of fear in communities to participate in science. Once we can bring that understanding of a legitimate fear of where historically this comes from, for participation in science, I think that they can really help address that. As I said, subsequently, improve health equity, reduce health disparities.

[00:20:35] Bonni: It’s another both/and. There is helping people recognize that they are going to be operating in a world in which bias exists. Let’s not try to pretend that it’s not. You said very clearly that we need to be able to name these things, and they’re not okay, but they’re also not a reason that you should feel like you don’t belong here. You’ve talked about finding a way around can they bring you any strength? We have to be very careful how we say these things, and more in a question form to see that student, their own experiences, their own personality that they may be able to draw on in these things.

I was thinking back. Early on in the MeToo movement, there was a meme that went everywhere. It was asking, “Have you ever carried your keys in between your fingers on the way to the car? Have you ever waited for the next elevator? Have you ever walked to the other side of the street? Waited until multiple people were going out into the parking lot?” You get the idea. It was 20 things or whatever. I talked about that with a lot of women. We were all like, “Yes, yes, yes, yes.” Again, that’s not okay that that ever happened. When we think about common microaggressions, it can be so healthy to talk about them because they’re not okay.

Yes, they’re so representative of bias, but then you go, “Oh, but there’s strength in numbers. Look at how many of us have experienced this.” The only way we’re going to have more representation is if we can come together collectively and find ways. I just loved what you said about, it can be helpful for people to know that it’s a choice whether or not we want to take something so personally that it’s going to affect every aspect of our life. There is a choice we could make to not take it in. Again, it’s so easy to oversimplify that. This is something that we really wrestle with.

[00:22:48] Archana: No, I agree. I agree about that. Definitely, I say that. It’s not that it’s the individual, but it is in some instances. We know that the barriers that are in front of African Americans, Latinx communities, underrepresented communities, it does come down to the structural racism that we have set into place. It starts from the Jim Crow laws. It continues with the massive incarceration that we see. We know that’s there. We even know that in these communities, there’s a huge block for them to even get to the university. The enormous block is, if we look, there’s still segregation.

There’s still opportunity-grabbing. There’s still educational inequities that are going on at that level before they get to the university. When the students do get to that university, what I try to say is, in that that you were saying, that, yes, it’s not that choice but it’s to recognize that this will happen in science. That everyone will have to strive for it, everyone, because everyone wants to get there. They want their research question addressed. They want to contribute to the field. I just ask them what I ask my students, is just to continue to put one footstep in front of the other. If they can be there, then you deserve to be there as well. Part of it is, it is that self-efficacy building.

That once they get that skill and say, “Hey, I do know what this is. I do know what a variable is. I can look at a codebook and understand the codebook or a data dictionary,” that goes a long way into them feeling, “I belong here, no matter where I came from.” Then also, as I said, preparing a poster, preparing an oral presentation, actually doing it, that builds a lot of confidence in saying, “I’m able to be part of this community.” Yes, it’s a combination of the two things. It is understanding that structural piece, and then understanding how they can navigate that, and they have navigated it to get there as an undergraduate. Then to continue as a graduate student.

[00:25:09] Bonni: Before we get to the recommendations segment, I wanted to just go a little bit more on self-efficacy. Well, actually, other efficacy. I don’t know what the name for it would be. You stressed that as important. I would love to hear a story from you of a student that you’ve worked with that you feel you actually were able to utilize that. It’s both knowledge and skill to be able to recognize the importance of building another up and letting them know that you have confidence in them. Does any story come to mind for you?

[00:25:43] Archana: I have to say, there is one story that comes to mind, but I think that I’m so impressed with all our students. I really have to say that. When you give them an opportunity, and that’s where our inherent bias comes in because many of them come in quiet and shy and not really able to talk about what they’re interested in, but once you expose them to all these opportunities and actually tell them, “Okay, find the research question you’re interested in. Here’s the data set that you can look at. These are the tests you can run,” and actually have them do it, have them sit down, download the data set, take a look at it, the transformation is undeniable.

That’s what I really love to see in all of these students. I think that partially does go into them understanding that we believe in them, that I believe in them, I believe that they can do it, and not to let that go wasted. That’s the nice thing about our program. It is multidisciplinary. I work with Dr. Cuajungco in the biology department, Dr. Behseta in the mathematics department, Dr. Mitra in the business department, and of course, Dr. Toga and Braskie from USC. You could see it was this collaborative work.

I think when students are exposed to that and when they’re able to explain pathways that I don’t understand– that’s what I wanted to say, that they’re able to do it in such detail and understanding, the clarity that they present to me, I just think, “Why can’t you do this? Why wouldn’t you do this? Why wouldn’t you pursue this? You are a natural scientist.” Yes, I definitely think there’s a couple of students where I could say they had a lot of life challenges but we stuck with them. I stuck with them, and that there’s no rationale– “I don’t see any reason why you shouldn’t pursue this. You are a scientist. You ask the right questions. You want to pursue this.”

I’m proud to say that those couple of students are in their master’s program, one of them fully funded, but I think they’re all capable. They just blow me away every time they present their work, that how much time they take into understanding, into relaying, into practicing. I was going to use the Harry Potter analogy. Anyone can be Harry Potter. [laughs] Meaning that if we have the correct philosophy-mentored training that is needed, that any student can really get there and reach that potential.

[00:28:38] Bonni: I’m hearing something that feels so new. It’s probably just because I’ve had to hear it multiple times just to be able to understand it. You aren’t saying that you’re just encouraging them, “I believe in you.” You’re giving them evidence for them to believe in themselves. Because the way that you shared that story wasn’t that you patted them on the head and said, “You’re great.” You gave them opportunities to do things that scientists do. You’ve said, “Hey, here’s the evidence. What evidence do you have that you can’t do this? Because I just saw you do it.”

[00:29:16] Archana: Exactly.

[00:29:16] Bonni: That is so powerful. I love that. Of course, you would approach it like a scientist. You gave them data that would support the hypothesis that they can do this, instead of just trite words.

[00:29:28] Archana: Definitely. It’s in the inquiry-based learning, that’s really for me where it begins. I definitely agree with that. Exactly, it’s evidence for themselves. It’s data for themselves.

[00:29:42] Bonni: That’s really powerful. Well, this is the time in the show that we each get to share our recommendations. I hadn’t really known, of course, where our conversation was going to go. I’m realizing it does fit in with your story. I watched a movie called Queen of Katwe. It is a biographical drama and it depicts the real life story of Phiona Mutesi. She’s a girl who lived in Katwe, which is a slum in Uganda, and she’s supposed to sell maize for her mom and her other family members, they have been in poverty for generations.

It’s one of those stories where it just feels like there’s no escape. She ends up seeing there’s a community group, that the man who leads it, both teaches them how to play soccer, he also teaches them how to play chess. You can tell just even if you looked at the movie poster, so I’m not giving too much away, that she ends up being pretty darn good at it. I won’t give the ending away, but it definitely is a feel-good movie for what’s possible when people have access. The thing that comes out in the movie is not that this man taught this young woman everything about chess.

He was a decent player at chess, but that wasn’t his area of expertise, but that there was so much potential within her, so it really does tie back to the story that you’ve just told, and he provided encouragement. Again, it was really encouragement based on the evidence that she demonstrated of being uniquely good at this, and then he was able to advocate for her and become an ally for her, and it’s just wonderful. Of course, that man who’s in the story, also was a member of the community there and had risen from poverty.

Again, I don’t want to give too much of the story away other than to say, some of the problems I know with movies like this in the past is that there’s the white savior that comes in to save the day. It’s not one of those stories at least, because he is from that community and he’s able to be a part of healing and making possibilities available, but because this is such an extraordinary woman, it’s really fun. At the end of the movie, they share what some of the characters in the movie and what their actual lives are like now, and that’s, of course, always fun to see. Yes, it’s a great movie. I’ll pass it over to you now for whatever you’d like to recommend.

[00:32:17] Archana: Thank you. I’ll have to watch it. I think I did see it, but I didn’t watch it, so I will have to do that.

[00:32:23] Bonni: It’s so good, it’s really great.

[00:32:25] Archana: I’ve been thinking about this. There’s a couple of things I wanted to add. One is one book that really stayed with me, and it’s a flip in some ways to what you were saying. I don’t know if you are aware of the book, The Short and Tragic Life of Robert Peace, it’s written by Jeff Hobbs. It’s a true story. It’s about a young man. As I was reading through this, I just kept thinking about, okay, where could have we intervened in the education system, where could have we advocated or supported for a better outcome, but actually, it’s a great book.

I have to say that it is a sad book in many ways when you’re reading through it, but it’s very telling of our systems and our communities that that’s going on. It’s about a young African American man. He grew up in the worst socio-economic areas in New York, New Jersey, but he was brilliant. At a young age, he had this memory where he could remember many facts that most people can’t remember. He just had this innate intellectual ability that most people don’t. His mom, once again, single mother, father was incarcerated, where you can see the mass incarceration, the systemic racism, but he actually did make it into an Ivy League eventually.

Even after that, I kept thinking what are the points where we could have intervened. I don’t want to give away the entire story in the entire book, but sadly, yes, it doesn’t end– it’s not a happy note, unlike what you were mentioning about the movie, which seems uplifting. I think it does give such a good insight on where are the points, and I kept thinking that it could have been this point. Could it have been that point? Should we have done this here? Because even in his classes at school, he barely studied and was able to just do extremely well.

It was such a tragic loss that it shouldn’t have happened, and it probably is for all the things that we talked about, but it’s very impressionable, really good book to read. The other thing I wanted to mention is just now it’s been a tough time for many people. We’ve gone through an incredible experience, incredible difficult time, and I think many of us have felt that obviously we’ve had to stay home. We’ve talked about being in isolation. Sometimes many people feel that way. I think it’s just really important to move, to get up, to move, to get that energy going in our bodies.

Really, for me, when I step outside, I look at the sunset, I look at the birds, the leaves, that to me, it really is revitalizing, because we forget that. I think part of our brain shuts off if we don’t do that, and just having that movement really helps get us going. A short walk, even a brisk walk for a little bit amount of time and increasing your heart rate level, just increases the heat in our body and makes us feel different. I think we’re missing that right now, so it’s really important to do that for us.

[00:36:02] Bonni: Oh, I love both of these recommendations. Of course we didn’t plan this. We didn’t know what each other would be recommending, but I almost hesitated to recommend the Queen of Katwe, just because it does feel a little bit too neat and tidy, and life doesn’t work that way and it’s certainly not. I liked that you were able to parallel that. It’s still an enjoyable piece of entertainment, but there are real systemic issues, and so I think they actually go together, even though we didn’t plan it, and boy, what a difference moving can make. Thank you for that reminder to us as well.

[00:36:37] Archana: Yes, definitely, so important.

[00:36:40] Bonni: I’m so glad to have been connected with you today, and from even just when we hopped on the line together, you have brought me a lot of ideas. It’s really fun to hear you talk about your work and the ways in which you’re able to help to fill that equity gap in STEM fields. I’m so appreciative for your work, and then you also mentioned so many colleagues, because I know this is something that is done definitely as a team. It’s not something that people can do alone.

I just love your work and collaboration like that. I’m going to encourage people to go visit some of the links on the show notes for the episode too, because I want them to be able to go see specifically about the work that your center’s doing and some of your collaborative efforts there as well. Such a joy to be connected with you.

[00:37:23] Archana: Yes. Thank you so much. It was my pleasure and it was great speaking with you today.

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[00:37:31] Bonni: I’m so thankful to Dr. Archana McEligot for joining me for today’s episode, and to the Cal State University for connecting us. Thanks to all of you for listening to the episode as well. If you would like to receive the updates from Teaching in Higher Ed with recent show notes, as well as a blog post written by me, you can head on over to TeachinginHigherEd.com/subscribe. If you’d like to see the show notes for today’s episode, head on over to TeachinginHigherEd.com/346. Thanks so much for listening and we’ll see you next time on Teaching in Higher Ed.

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