The Effortful Educator, an 11th and 12th grade psychology teacher, outlines the research-based case…
Category Archives: L&B Blog
October-29-2017
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.
October-27-2017
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.
October-26-2017
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.
October-25-2017
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.
October-21-2017
When we walk into a classroom, especially an early learning or elementary school one, manipulatives are almost always within reach. Look to your left, and notice the group of children spinning the hands on a pretend clock, trying to figure out what 6:30 should look like. Glance to you right, and watch the students sort pretend money into the dollar slots of a dinging cash register. And peer over your shoulder, as students use square, circle, and triangle magnets to create geometric worlds on a magnetic easel.
In a previous article, I discussed some of the cognitive research on problem-solving and decision-making. And while that piece focuses primarily on how conscious and unconscious thoughts make sense of questions and choices, this article turns to another important aspect of problem-solving: classroom manipulatives.
How do physical objects help us make sense of questions and concepts?
Manipulatives in Mathematics
Manipulatives are a type of symbol that can take nearly any form. One of the most common types of manipulatives that we may come across are base-10 blocks; small foam squares that can be combined and separated to help students understand basic math concepts (e.g., addition). Other common manipulatives in the classroom include pretend money, model buildings, and modeling clay.
Now, fiddling with manipulatives can be pretty enjoyable; but, as a learning tool, they come with a fair amount of controversy. This is especially so with mathematics manipulatives.
The more traditional school of thought tends to suggest that manipulatives help children learn math by reducing the abstractness of math problems. [1] They do this by substituting mathematical symbols with concrete objects. For example, the symbolic character “3” can be represented with three blocks. And if you toss in another three blocks, you’ve represented both the concept of addition and “6”.
But, more recent arguments have asserted that manipulatives can only really promote mathematics learning when teachers assist children in understanding the symbolic relation between physical objects and the math concepts they represent. The dual-representation hypothesis posits that when children perceive manipulatives as only being objects (e.g., a single base-10 block as just a squishy square), it is challenging to understand their relation to the mathematical expression they represent (e.g., the number one).
Style vs. Substance
One study that demonstrated just how tricky manipulatives can be investigated the ways in which elementary school students used pretend money when solving math word problems. [2]
First, fourth, and sixth grade students were asked to complete ten world problems that involved money. Half of the participating students received manipulatives: realistic bills and coins along with the suggestion that these materials could be used to help solve the problems. The other half of the students did not receive any manipulatives.
At all grades, the students who did not have access to the manipulatives performed better on the word problems than the students who did. Access to the pretend money actually appeared to interfere with students’ accuracy.
But why?
In a second experiment, fifth grade students were asked to complete ten more word problems. This time, the students were assigned to one of three manipulatives conditions:
- realistic, perceptually rich bills and coins
- bland bills and coins
- no physical manipulatives
The students were also asked to show their work on their answer sheets. This allowed the researchers to analyze students’ incorrect answers to determine whether they made conceptual or computational errors.
The researchers found that the students who used the perceptually rich pretend money made more errors than both the children who used the bland money and the children who did not use manipulatives.
The students who used the bland money performed at the same level as the students who had no access to the manipulatives.
Further, when analyzing the pattern of errors made by students in each condition, it appeared that strategy selection was influenced by the students’ access to the perceptually rich money. Compared to the students in the other two conditions, students in the perceptually rich condition were more likely to select a particular strategy (such as multiplication or division) that often resulted in an incorrect answer.
However, even though these students made more errors overall, their written work indicated that their conceptual understanding of the word problems was the strongest of the three groups.
Thus, there appears to be somewhat of a trade-off when using manipulatives. While these materials can help students relate their learning to real-world experiences, as well as promote conceptual understandings, perceptually rich manipulatives may distract children–and that distraction ultimately results in computational errors.
Two Sides to Every Coin
Interestingly, although research suggests that physical manipulatives can be distracting in a not-so-good way, it also seems that symbols can sometimes distract in a not-so-bad way.
This finding has been shown in preschoolers who participate in the Less is More task. In this tricky game, children must point to a small tray holding two candies in order to receive a larger tray with five candies. To succeed, children must inhibit their urge to point to the tray with more candies on it when asked which one they would like.
Given that young children generally have difficulty inhibiting themselves under such conditions, one study asked whether variations of the Less is More task might reduce the affective component of the game through symbolic distancing. [3] That is, would three year olds’ performance on the task improve if the large and small quantities of candy were represented by something else?
Children were randomly assigned to one of four conditions:
- the traditional representation of smaller and larger quantities of candies (real treats)
- rocks representing the candies, with children shown one-to-one correspondence between the rocks and candies (i.e., if children chose the tray with two rocks, they got five candies)
- arrays of dots to represent the candies without one-to-one correspondence (i.e., one set of dots was larger than the other, but the number of dots was not the same as the number of candies)
- one picture of mice and one picture of an elephant to represent small and large rewards, respectively
It turned out that the preschoolers’ performance on the mouse/elephant condition was significantly better than on the real treat condition. In other words, children more often pointed to the mice (small symbol) in order to get the elephant (large reward) than they did the two candies (small quantity) in order to get the five candies (large quantity).
Performance on both the mouse/elephant condition and the dots condition were significantly better than the real-treat and rock conditions. It appears, then, that the use of symbols can also distract in a helpful way. In particular, symbols with greater psychological distance from their referent (i.e., the mouse and elephant seem less related to the candies than the one-to-one corresponding rocks do) can reduce the emotional component of the Less is More task.
With this buffer from the emotional temptation of the larger tray of candies, children seem better able to inhibit their instinct to point to it.
Use ‘Em or Lose ‘Em
Despite the controversy that surrounds manipulatives and symbolic reasoning, most researchers seem to agree that there is a time and a place for each. And, most certainly, each has its own learning curve.
In order for manipulatives to be beneficial, researchers generally suggest that teachers:
a) should strive to explicitly connect the manipulatives to the concepts they represent; and
b) should select objects that easily allow children to understand their relation to concepts.
For example, the best math manipulatives tend to be objects that are only used for math learning (e.g., base-10 blocks); are not particularly interesting or familiar; and possess an internal structure that explicitly represents the relevant math concept.
But, when aiming to distract from emotionally-charged situations, symbols that seem unrelated to the emotionally charged object or event generally set students (especially young children) up for success.
References:
[1] Uttal, D. H., Scudder, K. V., & DeLoache, J. S. (1997). Manipulatives as symbols: A new perspective on the use of concrete objects to teach mathematics. Journal of Applied Developmental Psychology, 18, 37-54.
[2] McNeil, N. M., Uttal, D. H., Jarvin, L., & Sternberg, R. J. (2009). Should you show me the money? Concrete objects both hurt and help performance on math problems. Learning and Instruction, 19, 171-184.
[3] Carlson, S. M., Davis, A. C., Leach, J. G. (2005). Less is more: Executive function and symbolic representation in preschool children. Psychological Science, 16, 609-616.
October-20-2017
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.
October-18-2017
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).
October-15-2017
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.
October-13-2017
Because working memory is so important for learning, and because human working memory capacity isn’t as large as we wish it were, we would LOVE to be able to increase it.
If we could make working memory bigger, then all sorts of complex cognitive tasks–comparing historical figures, multiplying multi-digit numbers, parsing complex sentences, coding useful programs–would just be easier.
Various researchers and companies have touted exercises and games to embiggen working memory. However, many scholars are quite skeptical about such activities.
Except in unusual circumstances (say, a particular kind of brain injury, or a very long gap in schooling), we simply haven’t had much luck in artificially boosting WM.
Recently I’ve been reading more and more about an alternate approach to cognitive enhancement: transcranial direct-current stimulation. That’s a fancy way of saying: applying electricity to the brain through the skull. (Safely.)
Although the ideas sounds really cool in a sci-fi kind of way, this recent study dampens the hype. The details of the study, and the statistical analysis, are quite complex.
The short version is: don’t sign up to get zapped any time soon.
Given that working memory training programs tend to be VERY expensive and VERY time consuming, I advise skeptical caution before going that route.
When he first sees Jaws, Roy Scheider tells Robert Shaw that they’ll need a bigger boat. If we want to enhance working memory, we’re going to need a better technology.
For the time being, the best working-memory enhancer is what it’s always been: school.