Andrew Watson – Page 66 – Education & Teacher Conferences

About Andrew Watson

Andrew began his classroom life as a high-school English teacher in 1988, and has been working in or near schools ever since. In 2008, Andrew began exploring the practical application of psychology and neuroscience in his classroom. In 2011, he earned his M. Ed. from the “Mind, Brain, Education” program at Harvard University. As President of “Translate the Brain,” Andrew now works with teachers, students, administrators, and parents to make learning easier and teaching more effective. He has presented at schools and workshops across the country; he also serves as an adviser to several organizations, including “The People’s Science.” Andrew is the author of "Learning Begins: The Science of Working Memory and Attention for the Classroom Teacher."

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Andrew Watson

November 03, 2017

Meet the Speakers: Dr. Pooja K. Agarwal

Editor’s note: Dr. Agarwal will be speaking at next week’s Learning and the Brain conference. Here’s your chance to get to know her and her work better…

Andrew Watson:

I understand that you worked as a teacher before you started training as a scientist, so I’m curious about that experience. More specifically, how did your classroom experience shape your research interests?

Dr. Pooja K. Agarwal:

I completed Elementary Education Certification in undergrad, and I taught 4^th and 5^th grade. And throughout college I also developed curriculum and taught in summer camps: grades 3 through 12, mostly in science curriculum. So I was majoring in Elementary Education, and—of course—I was also taking Psychology courses.

It was fascinating to be taking my Education classes—where we’re learning pedagogy and teaching methods—simultaneously with taking Psychology classes with my mentor Roddy Roediger on the science of learning and cognitive psychology.

And the two fields just seemed completely disconnected. It was one of those “Aha!” moments for me where I didn’t understand why these two departments, and these two approaches, were so different—because they could really benefit from each other. And that’s what led to my combination of teaching—and my teaching approaches—and being a scientist.

Most of my research in the past 12 years has been in classrooms, as opposed to in laboratory settings. I really enjoy the messiness of doing scientific research in classrooms. The fire alarms, and school assemblies, and kids who are out sick, I really enjoy it because it pushes boundaries. We find all these great things about learning in the psychology laboratory with college students, but do they actually work in the real world?

Watson:

Your research focuses particularly on retrieval practice. Can you define that for us?

And, perhaps you could give an example of something that is retrieval practice, and something that isn’t: “If you do it this way, that’s retrieval practice. If you do it that way, it isn’t retrieval practice.”

Agarwal:

In a laboratory, in one of the comparisons we use most often, students read a passage: let’s say about sea otters.

We might have students read it once, and then have them write down everything they can remember about the passage three times. That would be retrieval practice. They had to bring the material about sea otters back to mind and retrieve what they learned.

On the other hand, after students read the passage, we might have them simply read it three more times. This rereading does not involve any retrieval.

Another example would be a student who re-reads their textbook; or who takes notes, and re-reads their notes; that’s not retrieval practice. As opposed to a student who uses flashcards: that’s retrieval practice.

What I like to say is: it’s the difference between trying to get information INTO your head by re-reading stuff over and over, versus trying to get information OUT of your head by using flashcards or writing down what you can remember.

Watson:

That’s a helpful and a clear way to explain the difference.

Agarwal:

Retrieval practice is actually more intuitive and used more often in K-12 than it is in college. In college, students are very used to sitting down, being talked at in a lecture, and then having to output things only on an exam. In K-12, I think we engage in retrieval much more often. There’s a lot more questioning, or cold calling, or discussion.

In K-12, we should be a little more mindful about, “If I’m going to review something as the teacher, can I change that to a retrieval activity?”

For instance, instead of saying, “Last week we learned about King Tut, and how old he was, and when he died, and what he did as Pharaoh,” a different angle to involve retrieval in a K-12 classroom would be: “All right, write down two things you remember from our discussion about King Tut.” And then have a brief discussion to remind everyone, “Oh, Andrew picked up on something that Pooja did not. And Emily remembered something that Thomas remembered as well. This is cool.”

That sort of retrieval activity could involve “think, pair, share,” where students are thinking, they’re writing down what they learned about King Tut, and then, of course, talking in pairs, and then sharing with the class.

It’s important to know that retrieval practice can take one minute or less, where students think about or write down what they remembered, and then you move on with your lesson – with or without discussion or grading. It’s also important to keep in mind that classroom retrieval activities should be low stakes. Make sure to emphasize retrieval as a learning strategy, not an assessment.

Watson:

You mentioned the difference between doing research in the lab—where most psychology research happens—and doing research in actual schools and classrooms. Can you talk more about that?

Agarwal:

A lot of research on retrieval practice has been in laboratory settings. Typically with lab research, all of the participants are college students. They come in, and we have them look at stuff on the computer: like foreign language word pairs, or brief reading passages: 500 words, maybe 1,000 words.

And then we distract them—we might have them play Tetris. And then, for instance, we ask students: “Okay, write down everything you remember from that passage about sea otters that you just read.”

And then we have students come back, let’s say a week later, and we ask them to do the same thing. “Hey, you read this passage about sea otters. It’s been a week. Your life went on. And now, write down everything you can still remember.”

And so we’ll ask: “How much do students remember a week later [after retrieval practice] compared to if they just re-read that passage over and over again without engaging in retrieval practice?”

And when it comes to classroom research, my colleagues and I have done similar research. We’ve played around with retrieval practice approaches and research questions like

Are multiple-choice quizzes versus short-answer quizzes more beneficial for learning?
Do online websites or retrieval programs like Kahoot! or Quia also boost student learning?
How many times do students have to retrieve in classroom settings to get the “biggest bang for your buck?”
Do pre-quizzes help, or is it better to quiz after a lesson?
Feedback: does it have to explain why students got something wrong, or simply indicate a correct or incorrect answer?

There are definitely advantages to extending lab research into classrooms. Not just to see if lab findings work in the real world, but there are some logistical things that are actually easier.

For instance, it’s hard to get college students to come back into a lab one week later. They forget. Even if we pay them and send email reminders, they don’t show up. They’re college students.

But in K-12, students go to school every day, and so we can look at rich learning in a real environment, and students come back a week later, or three months later, or seven months later. And the vast majority of students are still in school at the end of the school year. Laboratory research looking at learning and forgetting rarely goes beyond one week.

Watson:

Can you think of something in the world of retrieval practice that looked promising when it was researched in a lab, but when you tried it out in a classroom it just didn’t have the same effect there?

Agarwal:

Oh, that’s a good question. There are some lab findings that disappear in a classroom.

Watson:

I’m intrigued. “Disappear” sounds dramatic.

Agarwal:

Let’s look at multiple choice versus short answer retrieval in the form of low-stakes quizzes.

Based on 100 plus years of research, we’ve found that the more challenging the learning strategy, the more robust the learning over the long term. One researcher, Robert Bjork, coined the term “desirable difficulty.”

In line with that theory, from laboratory research it appeared that retrieval practice with short answer questions really boosted long term learning, compared to multiple-choice quizzes. Again, that seems pretty intuitive; there’s more of a desirable difficulty in writing a short answer as opposed to just being able to choose one of four multiple-choice options.

My colleagues (Kathleen McDermott, Roddy Roediger, and Mark McDaniel) and I did pretty much the exact same research in classrooms – 7^th grade science and high school history. Students learned normal materials from their classroom teacher. Then we gave them either multiple-choice or short-answer quizzes. After a few days on a unit exam and even months later at the end of the semester, we saw a large benefit of retrieval practice, but the difference between short-answer quizzes and multiple-choice quizzes disappeared.

It wasn’t as though short-answer quizzes helped students learn more than multiple-choice. That simple act of retrieval improved learning more than not engaging in retrieval at all.

For me that’s an example where findings from the lab don’t appear to apply in classroom settings.

And so I typically recommend to teachers, “You know what? Do what’s logistically easier.” Short-answer quizzes can take more time to grade. Of course, multiple-choice might take more time to develop, because you want to come up with really good alternatives. Either way, retrieval practice boosts long-term student learning, regardless of the low stakes quiz format.

Watson:

Is retrieval practice beneficial for all ages? Is it beneficial for all subjects that are taught?

Agarwal:

Patrice Bain has been a collaborator with me and my colleagues for more than 10 years. She and I like to say that retrieval practice works for all students, all subjects, all the time.

Our research in the Columbia School District outside of St. Louis in Illinois has included special ed. students, gifted students, students in pull-out tutoring programs. We still see the same benefits of retrieval practice.

In terms of all subjects: we’ve seen that retrieval benefits history, science, Spanish, vocabulary learning, a few others.

A subject area that we haven’t done too much research on is math, because—as you can imagine—in math they do retrieval all the time.

Watson:

Right, pretty much all math homework is retrieval practice. Does it work equally well for learning facts and learning skills?

Agarwal:

Good question. There’s more research on fact learning than skill learning, especially in laboratories.

In my dissertation, I focused on fact learning versus higher order learning. In one experiment, in the sixth-grade social studies classroom with my collaborator Patrice Bain, she was teaching chapters on World War II and the Russian Revolution.

I looked at how retrieval practice can improve fact learning—again, we already have lab and classroom research showing that it improves fact learning— sometimes even doubles learning compared to non-retrieval lessons.

But can we use higher order quizzes to improve higher order learning? For instance: questions that go beyond what is explicitly stated in the lesson.

I found that, excitingly, yes, especially with these complex materials, retrieval does improve higher order learning. (I based those materials on Bloom’s taxonomy.)

Watson:

Up to this point our conversation has focused primarily on psychology: which is to say, how minds work. I want to change gears and talk about neuroscience: which is to say how brains work. Do we, as researchers, have any understanding why retrieval practice helps new neural networks form to create long-term memories?

Agarwal:

A bit. That kind of work is recent, and so there’s still a lot more to be done.

The predominant research in neuroscience related to retrieval practice is about a process we call consolidation. The basic idea is that by retrieving, we’re recreating memories, and strengthening neural networks.

Exactly how that happens in terms of synapses or neurotransmitters is something we’re still trying to figure out. There’s not a whole lot known about it.

Watson:

That was my impression.

One of the points we emphasize on the blog is that, in the world of science, skepticism is key for what we do. Scientists know more today than they did yesterday because we’re a skeptical bunch.

I’m hoping that there is skepticism about retrieval practice, and I’m curious to know what you think is the most valid skepticism about it?

Agarwal:

Two things.

One of them is that retrieval practice is just a lot of tests: “Well, this just sounds like a lot of testing, and teaching to the test.”

Retrieval practice used to be referred to as “the testing effect.” Our field has moved away from that, especially because it’s not tests or quizzes that improve learning. It’s the actual process of retrieval. Retrieval is, in many ways, not even related to assessments.

The other main skeptical response is exactly what you asked about with fact learning versus higher-order learning, or more complex skills.

I agree that we should be a bit skeptical. There isn’t much research yet on extending retrieval practice to applied settings, let alone higher-order complex materials. Part of that reason, I think, is that in laboratory settings we like things really controlled so we can make sure A causes B. And when it comes to complex materials it’s very hard to do that.

For instance, it took me a year to develop the higher order complex materials for my dissertation.

I think that skepticism for higher order learning is warranted in that there isn’t yet much research yet. That being said, the research that is there—including my own research—shows that if we engage in complex skills during retrieval, then that will improve complex skills down the road.

Watson:

If I’m hearing you right, it sounds like the concept of retrieval practice itself is pretty well settled, and there aren’t people out there who say, “You did the math wrong. If you studied correctly, the effect goes away.”

Agarwal:

Correct. There is so much reliable research both for labs and in classrooms— especially from the past 15 years—showing that time and time again, huge effect sizes. I don’t think any skeptics still argue that we should be re-reading our textbooks instead of engaging in retrieval.

Watson:

Okay. Are there specific questions I should have asked that I haven’t yet asked you?

Agarwal:

Again, I’ll name two things.

One is: for more research, resources, and a down-loadable retrieval practice guide, go to retrievalpractice.org. We also send out weekly email updates with research summaries and evidence-based recommendations, too.

Second: I like to highlight what someone can do tomorrow. What can a teacher do tomorrow in their classroom to use this powerful strategy?

Depending on the subject area and the grade level, I like to highlight a technique called a “brain dump” which is simply asking students to write down everything they can remember about a class topic, lesson, unit, etc.

And that can take less than a minute. Also, teachers can include a “think, pair, share” after the brain dump or just move on.

So using retrieval practice doesn’t require redoing someone’s teaching approach, or curricula, or anything like that. It can just be as simple as, “Think about this question, or turn and talk to someone about what you learned.”

Watson:

Those are both very helpful.

One last question, which has nothing to do with science. A lot of people who will be attending the conference aren’t from Boston. Do you have any recommendations—restaurants, or museums, or pubs, or parks you think conference goers should see?

Agarwal:

I always recommend one thing that is never mentioned on tourist websites, called the Mapparium. I think it’s fantastic, and I’ve never seen something like it in any other city.

_____________________________

You can listen to an interview with Dr. Agarwal over at Cult of Pedagogy by clicking this link.

_____________________________

Biography:

Pooja K. Agarwal, Ph.D. is an expert in the field of cognitive science. She has conducted learning and memory research in a variety of classroom settings for more than 10 years. Passionate about evidence-based education, Pooja has extensive teaching experience in K-12 and higher education, as well as expertise in education policy at state and national levels. Currently, she is an Assistant Professor at the Berklee College of Music in Boston, teaching psychological science to exceptional undergraduate musicians.

To advance the use of scientifically-based learning strategies, Pooja founded RetrievalPractice.org, a hub of cognitive science research, resources, and tips for educators. Pooja’s research is supported by grants from the National Science Foundation and the U.S. Department of Education. In addition, her work has been featured in the New York Times, Education Week, and Scientific American, as well as academic journals, books, and podcasts. For more information, visit poojaagarwal.com and retrievalpractice.org.

Contact Information

Pooja K. Agarwal, Ph.D.

Assistant Professor

Berklee College of Music

[email protected]

@PoojaAgarwal

poojaagarwal.com

@RetrieveLearn

retrievalpractice.org

Multiple-Choice Tests Are A) Good or B) Bad

Andrew Watson

November 02, 2017

Multiple-Choice Tests Are A) Good or B) Bad

Teachers hate (and love) multiple-choice tests. On the one hand, they seem dreadfully reductive. On the other, they’re blissfully easy to grade — and easy grading is never to be belittled.

In our recent conversation, Pooja Agarwal recommended multiple-choice tests as one kind of retrieval practice. Inspired by her guidance, you might be asking yourself: “what can researchers tell me about the best kind of multiple-choice test to give?”

If you’re asking yourself that question, look no further: the estimable Andrew Butler is on the case.

(For example: if you want to know how many distractors to include on your test, you should see what Butler has to say…)

Andrew Watson

October 31, 2017

The Pro-Homework Argument

The Effortful Educator, an 11th and 12th grade psychology teacher, outlines the research-based case…

Andrew Watson

October 29, 2017

Bright Screens and Sleep

Here’s a handy review of the effects that bright computer and tablet screens have on sleep. (Hint: they’re not helping.)

Author Viatcheslav Wlassoff concludes with a few simple hints on how to reduce the detrimental effects of screens on melatonin.

Andrew Watson

October 27, 2017

5 Praises a Day

Back in May, a brief flurry of articles rose up (here, here, and here) around the “Five Praises a Day Campaign,” which encourages parents of 2- to 4-year-olds to praise their children more often.

(The authors don’t claim that the number five is magic; they picked it to align with the well-known advice about “five fruits and vegetables a day.” They’re more interested in being sure that there’s enough praise; and “enough” will vary from child to child.)

I’m frankly surprised to read this advice, given all the recent concern about the self-esteem movement.

As you know, especially in the 1970s, researchers noticed a correlation between self-esteem and academic success (and lots of other good things). They concluded that we can help students learn by helping them feel good about themselves.

Voila: the Self-Esteem Movement.

Sadly, this advice confused correlation with causation. It turns out that academic success raises self-esteem (obvi), but high self-esteem doesn’t prompt academic success.

(Check out Baumeister and Tierney’s book Willpower — especially Chapter 9, “Raising Strong Children: Self-Esteem versus Self-Control — for the history and the research.)

While Baumeister argues that too much praise saps self-control, Carol Dweck has shown that the wrong kind of praise fosters a fixed mindset and imperils a growth mindset.

For instance, Mueller and Dweck’s 1998 study shows that praising a student’s ability or intelligence leads to all sorts of unfortunate consequences. It even encourages them to lie to demonstrate their success!

Rejoinders, and Re-Rejoinders

While championing the 5 Praises campaign, Carole Sutton does acknowledge these concerns. First:

Dweck (2007) has highlighted the pitfalls of allowing children to expect unwavering approval, especially when this is directed towards their intelligence rather than their effort. She is right: these pitfalls exist. However, we are concerned here with very young children, those below the age of five and primarily with their behaviour, rather than their intelligence or physical attributes.

And second:

Other critics, such as Baumeister, Hutton and Cairns (1990), have demonstrated that giving praise to skilled practitioners has the effect of undermining those skills, not enhancing them. However, we are concerned here with very unskilled practitioners indeed, namely, toddlers learning to walk, to feed themselves, to toilet themselves, to dress themselves and to develop a sense of competence and self worth.

My first concern with these explanations is that they’re actually quite hard to find. Neither the Time article nor the ScienceDaily.com post — which I linked to above — nor even the press release touting a 5 Praises lecture, mentions them.

I found them on the last page of a document that’s downloadable at the very end of a university web page.

My second concern is that they’re not very persuasive.

Sutton, for example, says that the 5 Praises advice focuses on behavior — not intellect or ability — for young children. However, Dweck’s research makes clear that fixed and growth mindsets influence all ages, and a great many human attributes.

For example, I might say to a 3-year-old: “That was very good–you remembered to say “excuse me” before you asked a question!”

Or, I might say: “That was very good–you’re such a polite boy!”

Both of those compliments focus on behavior. The first compliment, however, fosters a growth mindset by emphasizing what the child is doing; the second promotes a fixed mindset by emphasizing what kind of person the child is.

To Sum Up

To be clear: I’m in favor of praise. At the same time, we’ve got lots of research showing that the kind of praise and the reasons for praise matter a lot–more than simply the amount of praise. Praising children more won’t necessarily lead to good results, even if they eat all five of their fruits and vegetables.

Andrew Watson

October 26, 2017

Working Memory Cheat Sheet

I write a lot about working memory on this blog. If you’d like a quick overview of its characteristics and development, here’s a handy link.

Technology in Schools: Beyond Anecdotes…

Andrew Watson

October 25, 2017

Technology in Schools: Beyond Anecdotes…

Because technology is everywhere, anecdotes about technology abound. Almost everyone in your school has opinions — strong opinions! — about the effect that technology has on learning.

If we move past anecdotes, what does the research show?

For all sorts of reasons, researching technology in education is tricky to do. (For one thing: by the time a particular innovation has been researched, it’s most likely out of date.)

The National Bureau of Education Research has done a heroic job of surveying quality research, and they’ve reached four conclusions:

First: especially in K-12 classrooms, simply adding technology doesn’t consistently increase learning. Unsurprisingly, students get better at learning the technology. Whether they get better at learning the academic content, however, is much less clear.

Second: “computer-assisted learning” has shown real promise. When students solve math problems on a computer, and find out right away whether or not they got the right answer — and why — their learning clearly benefits.

Third: “behavioral nudges” by text reminders (for example) do have a measurable effect. And, they’re really inexpensive.

Fourth: “relative to courses with some degree of face-to-face teaching, students taking online-only courses may experience negative learning outcomes” (88-89). That’s research speak for online courses don’t (yet) help students learn as well as physically-present-and-breathing teachers do.

If your school is pursuing technology zealously, it might be worth your while to contribute the $5 at the link above to get the full report.

Andrew Watson

October 20, 2017

Consider the Squirrel…

If you have a chance, I highly recommend reading The Distracted Mind — especially if you’ll be attending the upcoming conference.

Authors Adam Gazzaley (a neuroscientist) and Larry D. Rosen (a psychologist) explain our current difficulties with attention by looking at — hold on to your hat — foraging theory. If that sounds crazy, let me explain…

Imagine you’re a squirrel foraging for nuts in a particular tree. How long should you spend in this tree, and when should you head out for a neighboring tree?

The answer depends, in brief, on two variables: the richness of the tree you’re in, and the distance to the next tree. If you’re in a particularly nutty tree, you’re likely to stay longer. If another tree is quite nearby, you’re tempted to make the leap sooner than if it were far away.

Gazzaley and Rosen argue that humans are information foragers. We are a curious bunch, and we constantly want to know more: information relevant to our survival, information about people who are close to us, information topics that pique our interest. (Deflate-gate anyone?)

In this framework, technology distracts us so much because it makes information available to us constantly. The cell phone in your pocket is like an oak tree moving closer and closer to a squirrel.

(Gazzaley and Rosen joke that a text message ping is like a tree throwing a nut at a squirrel to say, “Hey! Come forage over here!”)

They support this argument with several chapters detailing the psychological and neurobiological functions behind our attentional systems; they also map the practical effects that these distractions have on learning and on life.

G&R conclude with two chapters of solutions. While their ideas here aren’t revolutionary, the foraging framework they offer helps clarify how and why each of these strategies might improve our concentration and cognition.

By the way: The Distracted Mind is written with admirable clarity. It doesn’t dumb down the science, and it remains lively, clear, and well-organized.

Action Video Games Harm the Hippocampus, Right?

Andrew Watson

October 18, 2017

Action Video Games Harm the Hippocampus, Right?

Here’s a headline to get your attention: Action video games decrease gray matter, study finds.

The article opens with this alarming sentence:

“A new study suggests that playing action video games can be detrimental to the brain, reducing the amount of gray matter in the hippocampus.” [emphasis mine, ACW]

We have a number of reasons to be curious about this claim.

Primarily, researchers have debated one another with vehemence–and occasional vitriol–on the benefits and detriments of action video games–such as Call of Duty. This article seems to be an interesting addition to that debate.

The article itself is behind a paywall, but you can read the abstract here. Let me quote the first and last sentence of the abstract:

“The hippocampus is critical to healthy cognition, yet results in the current study show that action video game players have reduced grey matter within the hippocampus. [… ]
These results show that video games can be beneficial or detrimental to the hippocampal system depending on the navigation strategy that a person employs and the genre of the game.” [emphasis mine, ACW]

So, does this research show that video games can be detrimental to the hippocampus, as the article’s first sentence claims? Yes, it does.

But, as my highlighting makes clear, it also shows that video games can be beneficial to the hippocampal system.

In other words: the article’s scary headline — and several of its subsequent statements — mischaracterize the underlying article.

After all, if I wrote an article claiming that Leonardo diCaprio is the best and the worst actor of his generation, and you summarized my article with the headline “Watson calls DiCaprio This Generation’s Worst Actor,” you’d be technically correct, but substantively misleading.

You can’t just leave out half of the argument.

To be fair: the study itself is quite complex. It distinguishes, first, between action video games — like Call of Duty — and 3D video games — like SuperMario. It further distinguishes between two strategies that players use to navigate those games.

SuperMario-like games are beneficial to hippocampal gray matter whichever navigation strategy players use. For Call-of-Duty-like games, the benefit or detriment depends on the navigational strategy.

The Lesson for Teachers to Learn

I believe that we, as teachers, must increasingly inform our classroom practice with research from neuroscience and psychology. We should know, for instance, whether or not action video games do bad things to the brain.

(When I spoke with parents at a school in New York just two weeks ago, I got that very question.)

If we’re going to rely on scientific research, however, we need to hone our scientific skepticism skills.

For me, here’s rule number one: ALWAYS READ THE ABSTRACT.

If a book or a speaker or an article make a research-based claim, get the primary source and read the abstract–that’s the first paragraph that summarizes the key points of the study.

(It’s usually very easy to find the abstract: use Google Scholar.)

When you read the abstract, you can see right away whether or not the speaker, article, or book summarized the research correctly–or at least plausibly.

In this case, you can easily see that the article mischaracterized half of the the researchers’ conclusions. So, as a newly-minted skeptic, you know what to do: look elsewhere. This source isn’t strong enough to use as a resource for making school decisions.

(BTW: I have reached out to the website that published this summary. As of today–October 4–they’re sticking to their claims. If they make changes, I’ll update this post.)

Next Steps

If you’d like to hone your skepticism skills, you might check out the TILT curriculum at The People’s Science–developed by Stephanie Sasse (former editor of this blog) and Maya Bialik (former writer for this blog; speaker at the upcoming LatB Conference).

Andrew Watson

October 15, 2017

Meet the Speakers: Dr. Sapna Cheryan

This article is the first in an occasional series where I’ll introduce people who will be speaking at an upcoming Learning and the Brain conference.

Dr. Sapna Cheryan, Associate Professor of Psychology at the University of Washington, has been researching the ways that physical classroom environments reduce or increase students’ academic interests.

Specifically, she looks at decorations in Computer Science classrooms, and asks if they create a stereotyped atmosphere that might discourage students from taking those classes.

I spoke with Dr. Cheryan by phone to learn more about her research. (This interview has been lightly edited for clarity and condensed for brevity.)

Andrew Watson:

Dr. Cheryan, your research focuses on stereotypes and the power that they have to shape the decisions that we make—for instance, the major we might choose in school. How did you first get interested in that topic?

Sapna Cheryan:

I grew up a second generation Indian American in the Midwest, and I think that caused me to be interested in race, stereotypes, and diversity. On top of that, I went to a STEM focused high school, so gender was relevant there—for example, noticing who was taking what classes.

I just enjoyed thinking about diversity and how broader societal forces shape attitudes and behaviors.

I got interested in studying gender disparities in Computer Science, which is my main focus, because of an experience I had as a graduate student.

It was the early 2000’s. I was in Silicon Valley because I was a student at Stanford. I had just come from two years at a consulting job on the East Coast, so I had the business background and I thought, “Okay, I’ll get a summer internship.”

I remember going to one of the interviews and it was a really good job at a good company. I got an offer, but I ended up leaving that interview feeling like, “Oh, I don’t really think I would really fit in here with these people. I don’t think I really belong here.” And I drew that conclusion based on the way that the company looked: the physical space.

I remember seeing conference rooms that were named after Star Trek ships, and I drew the conclusion that I probably just won’t fit in with people who work at this company.

Then I went to a different interview. I interviewed at Adobe and Adobe has a much different environment. It was really open and colorful, and there was a cafeteria and a gym.

I only met men in both interviews. I would have had a male boss in both cases. But, for me, I really thought the type of people who work [at Adobe]—men and women—are probably going to be people that I fit in with better. I thought I’d have a better summer.

I ended up choosing Adobe, even though they were offering me a lower salary. But that was less important to me than the social fit (though I did end up negotiating my salary because I knew the research on how women get paid less).

Having just spent a year being trained as a graduate student of Social Psychology, I remember thinking: “I wonder if this is something more broad. If there’s something about this geeky stereotype that might be a deterrent to more women than men.” Perhaps that could help explain gender disparities in the field.

Andrew Watson:

Of course, both stereotypes and decision-making processes operate very subtly. Can you explain how to research something that happens so quietly and subtly deep in the psyche?

Sapna Cheryan:

Stereotypes sometimes operate subtly, and sometimes they’re not so subtle. If you ask people to list stereotypes, especially with something like Computer Science—where there’s no real fear of being seen as racist or sexist—people are pretty willing to tell you what their stereotypes of certain majors are.

We just simply ask people, “Describe computer scientists.”

Even when we’re asking for an accurate description, undergrads will still give us highly stereotypical phrases. They’ll say things like, “Don’t take showers.” “Socially awkward.” “Interested in Sci Fi.” They have all these stereotypes and they’ll tell them to you even if you don’t use the word “stereotypes.”

In our studies, we set up an environment where the stereotype is salient in some way, but participants don’t know that we’re studying that stereotype.

For example, the very first study that I did with gender disparities was trying to replicate my own experience of going to those different [summer internship] interviews.

We took over a small classroom at the Computer Science building in Stanford. We decorated it to look like the first company that I interviewed at. We put up Star Trek posters. We had soda cans that were stacked in a pyramid. We had science fiction books and stray electronic parts lying around.

Students would either come into a room that looked like that, or into the same room but redecorated. Instead of Star Wars and Star Trek, we had nature posters and art posters and water bottles instead of soda cans. General interest books and magazines.

We told the students, “We’re sharing this room with another group. That’s why there’s all this stuff in the room. You can just ignore it. Please sit here at this table and fill out this questionnaire.” We told them we were doing a study on career interests. They thought they were just filling out a career interest inventory.

We asked them how interested they were in majoring in Computer Science as part of that questionnaire. What we found is that the stereotypical room, the one with the Star Trek stuff, caused women to express lower interest in Computer Science than the women who were in the non-stereotypical room.

For men, we didn’t see a difference in that study.

That was one way that we can get at the effect of the stereotypes without the students knowing that we’re studying those specific stereotypes.

[Editor’s note: here’s a link to that study.]

Andrew Watson:

In describing the effect that stereotypical objects have on people, you’ve used the phrase “ambient belonging.” Can you talk a little bit more about what that means?

Sapna Cheryan:

We came up with that phrase to describe the sense that people get when they walk into an environment, look around and get a feel for whether they fit with the environment and with the people that they imagine to be in that environment.

We investigated it with Computer Science, but we think that the term can be thought of more broadly.

The example I like to give is when you visit a new city for the first time and you’re driving or walking around. I think a lot of people can get a sense of whether they fit with that city—even without talking to the people, or looking up facts about the city.

They’re doing it by looking at the stores and the restaurants and the cars, and getting a sense of whether this city feels like somewhere they would want to live or whether they feel similar to the people in that city.

It’s the idea that you can walk into a space and get an immediate impression of whether you would fit there and with the people you imagine would be there.

Andrew Watson:

Got it. A lot of your writing is actually quite specific and practical about ways to improve ambient belonging for groups who are typically left out. Can you give a suggestion or two?

Sapna Cheryan:

Our focus has really been on changing the stereotypes and broadening the image of Computer Science so that students don’t think they have to fit this narrow, geeky image to be successful in the field. We targeted three ways to change this image.

One is by changing environments, as we talked about. Companies and departments [should] look around and see what their spaces are communicating. If you are trying to recruit a broader group of people, you should make sure that the physical environment actually fits with the image you want to be communicating.

We’ve also talked about the media. One of the most common ways students learn about different careers, sadly, is from the media. They get more exposure to what a scientist is because of TV shows than they do from any other source. Media depictions of computer scientists and engineers include Big Bang Theory and Revenge of the Nerds. The archetypal Computer Science image has not changed much since the 1980’s.

I’d like to get a new image out there, to give Computer Science a TV show like what ER did for medicine or LA Law did for law. Those two shows actually helped diversify the fields because they presented an image that was diverse: women and men, and people of all races. That helped make the image of those fields more welcoming to more, different kinds of people.

The third [way to change stereotypes] is role modeling. That can mean portraying yourself as more than just the stereotypes. Not only talking about the ways you fit the stereotype, but also talking about your other interests.

Andrew Watson:

Certainly, the first and third of your suggestions are the sorts of things that schools can do to promote social change.

Sapna Cheryan:

Schools do have a lot of power to influence the way their students think about majors. I think mandatory Computer Science classes could help. But, we also have to be very careful how that Computer Science is taught.

I have a personal example. My high school had mandatory Computer Science. I went to a small high school. It was 53 students. In our class of 53, one girl ended up going into Computer Science. Even though we were all very well trained for a field like Computer Science and we were graduating at a time when there was a huge need [in the tech field].

40% of our boys ended up being Computer Scientists. Our class was taught in a way that really reinforced that Computer Science was something that the boys were good at. We went in with stereotypes that the role-playing-game boys were going to do well in the class.

My suspicion now is that the girls probably got higher grades than the boys. The boys were talking a lot in class, using all these buzz words that we had never heard of. We had this impression that they were really, really smart.

Now that I know the research, my guess is that we were probably doing just as well or better in the class than the boys. But nobody ever told us. Nobody ever said, “You’re getting an A. You should consider pursing this.” The class just reinforced our stereotypes going in.

Andrew Watson:

Are there misunderstandings about your research that you’d like to correct?

Sapna Cheryan:

That’s a good question.

First, when I listed three ways to change stereotypes, I want to be clear that you can’t just change one thing. You can’t just go change the posters in your lobby or just add one TV show. If it was that simple, then gender disparities would be decreasing, and they’re not. They’re stagnant in Computer Science. It’s going to require a sort of cultural revolution: some big social movement in Computer Science and other fields, like Engineering and Physics, to really make this change.

Second, I think a bigger misunderstanding is that talking about stereotypes promotes them. Sometimes people say, “Just by researching these stereotypes you are making them real. Students now think that this is how Computer Science is. We should just not talk about it.”

I think that’s a misconception, because students already have these stereotypes in their head. I’m not putting them there. If we don’t talk about it, then there’s nothing to interrupt that or get students to question whether they should have those stereotypes or not.

The [third misunderstanding] is when I talk about “men and women,” I never mean all men and all women.

Every time I give a talk, I mention that it’s not all men like this stereotype and all women don’t. We always get a core group of women in our studies who choose the stereotypical room over the non-stereotypical room.

The first time I gave a talk at Google, first question I got was from a woman who said, “I love Star Trek. It’s why I’m a programmer. Star Trek got me into this field.” It’s a reminder that when I talk about disparities, I’m talking about in aggregate and not talking about any individual.

I’m not trying to kick the geeks out of Computer Science, or say that we should completely change the image to a feminine one. What I’m trying to do is broaden the umbrella. You can identify as a geek, or somebody who likes Star Trek, and get into the field.

But, that shouldn’t be the only type of person who thinks that they can be in the field. We should also welcome people who didn’t start coding when they were four years old. We have to have a broader umbrella.

I think again, medicine is a good example. When I say, “Imagine a doctor,” you might have an image of a doctor and maybe it’s a male doctor. Then I say, “Think of another doctor.” It’s not too hard to think of a doctor who looks different from that first doctor.

But with Computer Scientists, you think of one, and a second one, you think of a third one, they all seem similar to each other. That’s what I want to change. I want to make it so that we think of different types of successful people in the field.

[Editor’s note: Here‘s a TedX talk where Dr. Cheryan elaborates on this point.]

Andrew Watson:

On the blog, we emphasize that in the sciences, whenever people publish new or important ideas, there is always disagreement and push-back. In fact, the criticism and the tussle really improve our understanding of those ideas.

So, my next question is: because you’ve published new and important ideas, I’m sure that people are pushing back. What do you think are the most valid critiques of the work you’re doing? Where do you think skepticism is most justified?

Sapna Cheryan:

Sometimes people say to me, “classrooms don’t really look like this. You don’t see geeky, stereotypical classrooms.” I think that’s fair; a lot of classrooms don’t look like this.

(Although, people have come to me and told me stories about classrooms that do look that: maybe not as extreme, but they do have elements of the stereotypical things.)

I am trying to show that these stereotypes matter. It would be great to go through and catalog what real classrooms look like. How extreme are they on these variables, and how much [stereotypical] stuff do you need in the classroom to have people start drawing conclusions? Can you just have one poster or a few action figures? Is that enough for people to draw conclusions? If not, does that mean we should only focus on the small percentage of classrooms that have an extreme version?

Andrew Watson:

A non-science question for you. Some of the people at the conference haven’t been to Boston before. Are there places you’d recommend?

Sapna Cheryan:

I live really far from Boston, but my best friend lives in Boston, so I visit her on occasion. My favorite place to go is called Sofra. It’s this cool Middle Eastern restaurant and the food is really, really good. I think it might be in Cambridge. We try to go there every time I visit.

Andrew Watson:

I’ll pass that along. Thanks so much for taking this time.

Sapna Cheryan:

You’re welcome.

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