Five years ago, I had lunch with a 13-year-old who was thinking about attending my school.
He spent much of the lunch telling me about string theory. As one does, when one is 13, and obsessed with string theory.
I don’t remember much about string theory, but I do remember this part of the conversation: (more…)
The good folks over at TedEd have produced another helpful brain video — this one exploring different brain-scanning techniques.
https://www.youtube.com/watch?v=B10pc0Kizsc
This video does a particularly good job exploring both the strengths and the weaknesses of each technology.
In particular, EEG is very good at measuring timing precisely. Sadly, it can’t pinpoint location very accurately.
On the other hand, fMRI can zoom in on location within a few millimeters. However, its timing measurements are only rough-n-ready: within a few seconds or so.
Surprisingly, the video doesn’t discuss magnetoencephalography (MEG) — which does with magnetic waves what EEG does with electrical waves.
For fun: this video shows the MEG image when the brain reads the single word “dog.”
You’re up before the sun rises, eager for the day’s adventures? Sleep researchers call you a “lark.”
You’re perkiest after midnight, happily contemplating the world while your friends sleep? They call you an “owl.”
If you’re comfortably in the middle, think of yourself as a “finch.”
Sleep researchers know a lot about these three sleep species.
And their insights help teachers and administrators think more carefully about helping our students learn.
Simply put: genes.
Or, to quote a recent article:
Chronotype appears to be largely determined by the genetic composition of an individual’s circadian clock. An individual may be able to choose to change their sleep/meal/activity time due to day-to-day schedule impositions, but they may not be able to shift their internal clocks in the same way, due to its genetic basis.
I want to emphasize the rarity of this explanation. In the worlds of psychology and neuroscience, almost everything results from a combination of nature and nurture.
IQ? Nature and nurture.
Grit? Nature and nurture.
Processing speed? Nature and nurture.
So: don’t let this one instance fool you into thinking that genes routinely determine our fates.
Of course, age has an influence on chronotype as well. Puberty magically transforms more of us into owls. As we age, we might well revert to our initial larkiness — or at least to finchitude.
Note well: students have no control whatsoever over either of these influences. They can’t control their genes, and they can’t control their developmental stage.
In other words: adolescent owls aren’t simply being stubborn when they go to bed late. They’re often simply not tired enough to sleep.
Researchers Smarr and Schirmer looked at the relationship between chronotype and grades in college.
Their finding? In brief: we do best when class time matches our chronotype.
Larks do best in morning classes. Owls catch up in evening classes.
However … and this is a BIG however … owls consistently have lower GPAs than larks and finches.
Even in evening classes, larks and finches have higher GPAs than do owls — although the difference is smaller than in morning classes.
One explanation — favored by morning people everywhere — is that larks are simply smarter than owls.
A better explanation: school schedules benefits larks and make life difficult for owls. After all: when classes begin early in the morning, owls just don’t get enough sleep before class.
And — as you remember — these sleep-deprived owls aren’t being stubborn. They’re just not tired enough to fall asleep in time to get the 8 or 9 hours they need.
In other words: we teach owls, larks, and finches. Our school schedules should work well for all of them. When we favor one sleep species over another, we needlessly disadvantage real students who want to learn.
The seductive allure of neuroscience often blinds us.
In fact, the image on the right shows the part of the brain — the focal geniculative nucleus — that lights up when we’re taken in by false neuroscience information.
Ok, no it doesn’t.
I’ve just grabbed a random picture of a brain with some color highlights.
And: as far as I know, the “focal geniculative nucleus” doesn’t exist. I just made that up.
(By the way: brain regions don’t really “light up.” That’s a way of describing what happens in an fMRI image. You’re really looking at changes in blood flow, indicated by different colors. Brains aren’t Christmas trees or smokers; they don’t light up.)
And yet, for some reason, a picture of a brain with some bits highlighted in color just makes us go wild with credulity.
We’ve known for a while that people believe general psychology research more readily when it includes a picture of a brain.
Is that also true for research in educational psychology? That is, does this problem include research in teaching?
Soo-hyun Im investigated this question with quite a straightforward method. He explained educational research findings to several hundred people.
Some of those findings included extraneous neuroscience information. (“This process takes place in the focal geniculative nucleus.”)
Some also included a meaningless graph.
And some also included an irrelevant brain image (like the one above).
Sure enough: people believed the claims with the irrelevant brain image more than they did the same claim without that image.
In fact, as discussed in this earlier post, even teachers with neuroscience training can be taken in by misleading science claims.
If you’re reading this blog, if you’re attending Learning and the Brain conferences, you are almost certainly really interested in brains.
You want to know more about synapses and neurotransmitters and the occipital cortex. You probably wish that the focal geniculative nucleus really did exist. (Sorry, it doesn’t.)
On the one hand, this fascination offers teachers real benefits. For a number of reasons, I think it helps (some) teachers to know more about the process of synapse formation, or to recognize parts of the brain that participate in error detection.
At the same time, this interest confers upon us special responsibilities.
If we’re going to rely on brain explanations to support our teaching methods, then we should get in the habit of asking tough-minded questions.
Why are you showing me this brain image? Is the claim credible without the image?
What does that highlighted brain region have to do with learning?
Who says so? Can you cite some articles?
If the person presenting the information can’t — or won’t — answer these questions, then put down the fMRI image and step away from the research.
The teaching method itself might be sound, but the brain claims behind it are simply relying on the seductive allure of neuroscience.
Like Odysseus, you might be tempted — but do not give in to these neuro-Sirens.
“Flipping the classroom” has been around long enough now to have its own Wikipedia page.
Proponents suggest that this strategy allows teachers to focus less on direct instruction and more on collaboration, problem solving, and application.
Critics respond that direct instruction offers many benefits. They also wonder if we are fooling ourselves by claiming that students learn deeply by watching videos at home.
Most discussion of flipped classrooms focuses on younger grades: its potential for teaching mitosis or long-division or the basics of circuitry.
What about adult learners? Can flipped classrooms help them learn?
A just-published study looks at a Principles of Epidemiology course for grad students at Columbia University.
In 2015, instructors taught in the “traditional” way: 90 minutes of lecture, followed by 90 minutes of discussion.
In 2016, they flipped the classroom: “pre-recorded lectures [were] viewed outside the classroom setting (at home), and in-person classroom time [was] devoted to interactive exercises, discussion, or group projects.”
So: who learned more?
By practically every measure, it just didn’t make much difference.
For instance: at the midterm, the median grade in the traditional class was 94.0. In the flipped class, it was … 94.4.
On the final exam, the median traditional grade was — again — 94.0. The flipped class median was 92.5.
(If you look at mean grades instead of median, there is a slight — and statistically trivial — advantage for the flipped classroom.)
Although these grad students didn’t learn any more epidemiology, they did prefer the flipped-classroom format. Why? Because it gave them greater flexibility in their otherwise over-scheduled and hectic lives.
If schools can promote the same amount of learning more conveniently, then that strategy feels like a real win.
At the same time, it’s not clear that this benefit transfers to younger learners.
In other words: flipped classrooms simplified schedules for these graduate students — even though they didn’t improve learning.
Whether or not that benefit transfers to K-12 students, however, depends a great deal on the specific circumstances that those students face.
Over at his blog Filling the Pail, Greg Ashman likes challenging popular ideas. In a recent post, he takes issue with meta-analysis as a way of analyzing educational research.
In the first place, Ashman argues — in effect — “garbage in, garbage out.” Combining badly-designed studies with well-designed studies still gives some weight to the badly-designed ones.
Of course, Ashman has some thoughtful suggestions as well.
Why should we care about such an obscure and complicated statistical technique?
Meta-analysis matters because we pay so much attention to it.
For instance: just a month ago, a pair of meta-analyses about Mindset Theory set off another round of anxiety. Edu-twitter lit right up with thoughtful scholars wondering if we should stop focusing so much on the right kind of praise.
Or: I frequently rebut claims about working memory training by citing this well-known meta-analysis by Melby-Lervag and Hulme.
If we’re going to rely so much on this technique, we should be clear-minded about its strengths and its weaknesses.
Teachers have a love/hate relationship with technology.
In some cases, technology provides exciting opportunities to enhance teaching. (Here‘s a recent post about virtual reality technology, and another about classroom clickers.)
In other cases, however, it distracts our students, muddles their thinking, and interferes with their healthy relationships.
Action video games and cell phones take most of the heat in these discussions. Who’s got anything good to say about either?
We’ve got lots of evidence to suggest that action video games improve visual attention. All that virtual racing around, all that shooting at monsters and aliens seems to heighten our visual systems.
A recent study in China wondered how quickly video games might might produce this effect. They reached two conclusions.
First: expert video game players do better on tests of visual attention than beginners. Basically, their peripheral vision is more acute.
And, EEG data show that specific brain regions process visual information more efficiently for these experts. The details aren’t important — EEG data are very difficult to summarize — but the results are clear. Playing action video games trains up visual attention.
Second: the beginning video-game players improved their visual attention after only one hour of play.
Their peripheral vision improved from before to after. And, the EEG data showed more expert-like processing of visual information.
Yup. After JUST ONE HOUR.
Now, the study doesn’t show that this improvement will last. Presumably it takes more than an hour to create enduring changes in such sophisticated cognitive systems.
But, it’s impressive to see how quickly those changes start taking place.
Although “visual attention” sounds like a good thing to have, we might nonetheless worry that action video games have other bad effects.
For example, they might interfere with our students’ ability to make friends. We’ve all seen enough lonely nerdy gamers in movies to wonder about their real-life counterparts.
Well, according to two recent studies from Sweden, we needn’t worry. Gamers are just as likely to befriend their peers as non-gamers: “high-use did not make game users socially isolated or less popular in school.” In fact, gamers often make friends with other gamers in the real world.
Perhaps Swedish and American cultural contexts are so different that these results don’t apply to our students. However, that objection seems a bit of a stretch to me.
Of course, we might still be concerned about video games. One of my grad-school professors forbade his children from playing Grand Theft Auto because its messages struck him as so deeply anti-social. He nonetheless showed us lots of research suggesting that video games really don’t have all the bad effects that people worry about.
I got a question about “cell phone addiction” from a teacher just last week. As a society — and as teachers within that society — we’re deeply concerned about children’s relationships with this portable slice of technology.
A recently-published think piece offers a fresh perspective on the dangers of cell phones. Its authors don’t discount those dangers; the specifically note correlations of cell-phone use with anxiety and loneliness.
Instead, they reframe them within an evolutionary perspective. Humans have evolved to be highly social beings, and practically everything we do with cell phones — texts, chats, conversations, schedules, even games — is ultimately largely social.
In other words: we’re not addicted to cell phones. We’re addicted to the social possibilities they allow us.
If we rethink cell-phone use, and strategies to manage cell-phone use, within this perspective, we might be considerably more effective in helping curb addictive impulses.
We might also be quicker to see the healthy benefits of technology: when used best, it helps us develop cognitive function and connect with the broader social world.
These findings strike me as good news indeed.
Over the last ten years, I’ve found many articles and studies that I return to frequently. Some summarize lots of research suggestions. Others explore particular questions with verve and clarity.
I hope you enjoy these as much as I do.
Our students often confuse PERFORMANCE (a high score on a test) with LEARNING (enduring knowledge and skill). Nick Soderstrom sorts through all kinds of evidence to help teachers distinguish between the two. Helpfully, he includes evidence for both physical and cognitive learning.
Learning versus Performance: An Integrative Review, by Nick Soderstrom and Robert Bjork
This comprehensive (!) article examines research behind ten well-known teaching practices: from underlining to retrieval practice. In each case, it looks at the quality of evidence. It then helps you choose those that fit your subject and your students best. (Danger: several sacred oxen gored here.)
Improving Students’ Learning with Effective Learning Techniques, by John Dunlosky (and many others)
Deans for Impact have boiled their suggestions to a list of six. You’ve got everything here from motivation to transfer. It also offers a solid list of sources when you want to check out the primary research.
The Science of Learning, by Deans for Impact
Regular readers of this blog know that “retrieval practice” helps students learn MUCH more effectively than simple review does. In brief: don’t have students reread a chapter. Have them quiz each other on the chapter. This kind of active recall fosters new learning. In this splendid study, a researcher, a teacher, and a principal move this finding out of the psychology lab and into the classroom.
The Value of Applied Research: Retrieval Practice Improves Classroom Learning and Recommendations from a Teacher, a Principal, and a Scientist, by Agarwal, Bain, and Chamberlain
In this marvelous study, researchers wonder if testing students on material before they’ve even seen it might help them ultimately learn it better. Here’s the fun part: when their first study suggests the answer is “yes,” they then repeat the study four more times in an attempt to prove themselves wrong. Only when they can’t come up with any other explanations for their findings do they finally persuade themselves.
The Pretesting Effect: Do Unsuccessful Retrieval Attempts Enhance Learning?, by Richland, Kornell, and Kau
Today’s post is a bit more informal and personal than usual.
When I 
first started attending Learning and the Brain conferences in 2008, I looked at the presenters as Speakers of Truth from a Platform of Verity.
They KNEW THINGS. They had DONE RESEARCH.
I wasn’t there to ask questions. I was there to write down what they told me.
Over the last ten years, I’ve learned to think differently about the relationship between research and understanding. Research always begins as a cheerfully contentious conversation among competing theories.
Can people pay attention for more than 10 minutes? Researchers argue about that.
Does retrieval practice have limits? Researchers argue about that.
Is Mindset a thing? Researchers argue about that A LOT.
I’m also gradually learning to think differently about researchers themselves.
In the past, they struck me as distant, awe-inspiring figures. They were busy, out questing for truth.
I would no sooner have interrupted a researcher to ask a question than I would have interrupted a surgeon mid-slice. They’ve got better things to do.
And yet, I’m learning how eager many researchers are to connect with teachers.
In the last two weeks, I have sent emails to six different researchers, asking them questions about the classroom implications of their work.
To be clear: I’ve never met any of these researchers. I’ve certainly never had the chance to do anything for them. I was, in other words, a total stranger asking a question out of the blue.
You know what? Five of those six have responded; three of them responded in about 2 hours. (I’m still hoping to hear from #6.)
In fact, they all responded substantively and enthusiastically. They liked my questions, had specific suggestions, and pointed me to other articles to check out.
They didn’t see my question as an intrusion, but as an invitation to a teaching conversation they were glad to join.
I’m not naming these researchers here because I don’t want them to be swamped with email. But I do hope you feel as encouraged as I do. If you’ve got a question about the study you just read — for example, how best to make it work in your classroom — you just might reach out to the study’s author.
You might very well start a fascinating conversation.
Regular readers of this blog know that I’m very skeptical about training working memory. Despite all the promises, most studies show that WM training just doesn’t do very much.
Better said: working memory training helps people do better on other, similar working memory tests. But it doesn’t help students learn to read or calculate or analyze any better.
(Earlier posts on this topic here and here.)
But here’s a tantalizing possibility: what if we could find an even better shortcut to cognitive success?
Researchers at Abo Akademi University in Turku wondered why WM training works in psychology labs, but not in classrooms.
(One of the champions of WM training — Dr. Susanne Jaeggi — has spoken at Learning and the Brain conferences. If you’ve seen her, you know she’s an incredibly impressive researcher. You too might reasonably wonder why that research isn’t panning out.)
These Finnish researchers wondered if the WM training simply gave students the chance to figure out a particular WM strategy.
That is: they didn’t have more working memory. But, they were using the WM they already had more strategically.
This strategy applied to the specific working memory task (which is why their WM scores seemed to get better), but doesn’t apply to other cognitive work (like math and reading).
If that hypothesis is true, then we could simply tell our students that strategy. We would then see the same pattern of WM development that comes from the training — only much faster.
Specifically, we would expect to see improvement in similar WM tasks — where students could apply the same strategy — but not on unrelated tasks — where that strategy doesn’t help.
If their hypothesis is correct, then the results that take 6 WEEKS of training might be available in 30 MINUTES. Rather than have students figure out the strategy on their own (the slow, 6 week version), we can simply tell them the strategy and let them practice (the 30 minute version).
The Finnish researchers worked with three groups of adults.
Control group #1 did a WM test on Monday and a WM test on Friday. They got no practice; they got no training.
Control group #2 also did WM tests on Monday and Friday. In between, they got to practice a WM task for 30 minutes. This is a mini-version of the WM training model. (If they had gotten the full six weeks, they might have figured out the strategy on their own.)
The study group — lucky devils — were TOLD a strategy to use during their practice session. (More on this strategy below.)
What did the researchers find?
First: As they predicted, the group that was told the strategy made rapid progress, but the other two groups didn’t.
Control group #1 didn’t make progress because they didn’t even get to practice. Control group #2 did practice…but they didn’t have enough time to figure out the strategy.
Only the study group made progress because only they knew the strategy.
Second: As researchers predicted, the group that learned the strategy didn’t get better at WM tasks unrelated to the strategy they learned.
In other words: the group given a strategy behaved just like earlier groups who had discovered that strategy for themselves during 6 weeks of practice. They did better at related WM tasks, but not at unrelated tasks.
We don’t need 6 weeks to get those results. We can get them in 30 minutes.
The precise strategy depends on the working memory exercise being tested.
In general, the answer is: visualize the data in patterns. If you’ve visualized the pattern correctly, you can more easily perform the assigned WM task.
You can check out page 10 of this PDF; you’ll see right away what the strategy is, and why it helps solve some WM problems. You’ll also see why it doesn’t particularly help with other WM tasks — like, for example, understanding similes or multiplying exponents.
This research suggests that we shouldn’t train students’ general WM capacity, because we can’t. Instead, we should find specific WM strategies that most resemble the cognitive activity we want our students to do.
Those strategies allow students to use the WM they have more effectively. With the same WM capacity, they can accomplish more WM work.
The key question is: what WM strategies are most like school tasks?
We don’t yet know the answer to that question. (I’ve reached out to the lead author to see if she has thoughts on the matter.)
I do have a suspicion, and here it is: perhaps the practice that we’re already doing is the best kind. That is: maybe the working memory exercise that’s most like subtraction is subtraction. The working memory exercise most like reading is reading.
If I’m right, then we don’t need to devise fancy new WM exercises. The great news just might be: the very best WM exercise already exists, and it’s called “school.”
