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The Source of Student Motivation: Deeper than We Know?
Andrew Watson
Andrew Watson

Usually I blog about specific research findings that inform education.

Today — to mix things up — I thought it would be helpful to talk about an under-discussed theory pertinent to education.

This theory helps us at least two ways:

First: it gives useful insights into student motivation. (Teachers want to know everything we can know about motivation.)

Second: it provides useful background for a second up-n-coming theory — as I’ll describe below.

Education and Evolution

Let’s zoom the camera WAY BACK and think about individual human development from an evolutionary perspective.

Certain human interests and abilities can promote our evolutionary fitness.

Tens of thousands of years ago, humans who — say — understood other people and worked with them effectively probably had a survival advantage.

So did humans who took time to make sense of the natural world around them.

Oh, and the physical world as well.

Given those probabilities, humans who learned about people, the natural world, and the physical world would — on average — thrive more than those who did not.

If that’s true, then we probably evolved to learn those things relatively easily. (Obviously, this is a great oversimplification of evolution’s complexities.)

For instance: we rarely teach children to recognize faces — our species evolved to be good at that. We don’t teach them to walk or talk; they do so naturally. (We encourage and celebrate, but we don’t need to teach.)

We don’t have to encourage people to explore the natural or physical world. Throwing rocks, climbing trees, jumping in puddles, chasing small animals: we evolved to be intrinsically interested in those things.

Primary and Secondary

Evolutionary Psychologist David Geary describes these interests as biologically primaryWe evolved to be interested in and learn about what he calls “folk psychology” (people), “folk biology” (the natural world), and “folk physics” (the physical world).

Geary contrasts these several topics with others that we learn because human culture developed them: geometry, grammar, the scientific method, reading. He calls such topics biologically secondary because need for them does not spring from our evolutionary heritage.

We are MUCH less likely to be interested in biologically secondary topics than biologically primary ones. We didn’t evolve to learn them. Our survival — understood on an evolutionary scale — does not depend on them.

Said the other way around: if I don’t explicitly teach my child to walk, she’s highly likely to do so anyway. If I don’t explicitly teach my child calculus, she’s highly unlikely to figure it out on her own. (Newton and Leibnitz did…but that’s about it.)

If you’re keen to understand its nuances, Geary’s 100 page introduction to his theory is here.

Implications: Motivation

If Geary’s correct, his theory helps answer a persistent question in education:

Why don’t students love learning X as much as they loved learning to climb trees/play games/mimic siblings/build stick forts/etc.?

This question usually implies that schools are doing something wrong.

“If only we didn’t get in the way of their natural curiosity,” the question implies, “children would love X as much as those other things.”

Geary’s answer is: playing games is biologically primary, doing X is biologically secondary.

We evolved to be motivated to play games. Our genes, in effect, “want” us to do that.

We did not evolve to learn calculus. Our culture, in effect, “wants” us to do that. But cultural motivations can’t match the power of genetic ones.

In effect, Geary’s argument allows teachers to stop beating ourselves up so much. We shouldn’t feel like terrible people because our students don’t revel in the topics we teach.

Schools focus on biologically secondary topics. Those will always be less intrinsically motivating (on average) than biologically primary ones.

Implications: Cognitive Load

A second theory — cognitive load theory (CLT) — has been getting increasing attention in recent months and years.

CLT helps explain the role of working memory in human cognition. (Frequent readers know: I think working memory is the essential topic for teachers to understand.)

In recent years, CLT’s founders have connected their theory to Geary’s work on biologically primary/secondary learning.

That connection takes too much time to explain here. But, if you’re interested in cognitive load, be aware that Geary’s work might be hovering in the background.

Watch this space.

Reactions

Some scholars just love the analytical power provided by the distinction between biologically primary and secondary learning.

Paul Kirschner (twitter handle: @P_A_Kirschner), for instance, speaks of Geary’s theory with genuine admiration. (In one interview I read, he wished he’d thought of it himself.)

Others: not so much.

Christian Bokhove (twitter handle: @cbokhove), for instance, worries that the theory hasn’t been tested and can’t be tested. (Geary cites research that plausibly aligns with his argument. But, like many evolutionary theories, it’s hard to test directly.)

I myself am drawn to this framework — in part because evolutionary arguments make lots of sense to me. I do however worry about the lack of more evidence.

And: I’m puzzled that so little work has been done with the theory since it was first published in 2007. If it makes so much sense to me (a non-specialist), why haven’t other specialists picked up the topic and run with it?

For the time being, I think teachers should at least know about this theory.

You might start considering your students’ interests and motivations in this light — perhaps Geary’s distinction will offer a helpful perspective.

And, I don’t doubt that — as cognitive load theory gets more attention — the distinction between biologically primary and secondary learning will be more and more a part of teacherly conversations.

“But How Do We Know If It Works in the Classroom?”: The Latest on Retrieval Practice
Andrew Watson
Andrew Watson

We’ve heard so much about retrieval practice in the last two years that it seems like we’ve ALWAYS known about its merits.

But no: this research pool hasn’t been widely known among teachers until recently.

We can thank Agarwal and Bain’s wonderful Powerful Teaching for giving it a broad public audience. (If you had been attending Learning and the Brain conferences, of course, you would have heard about it a few years before that.)

Of course, we should stop every now and then to ask ourselves: how do we know this works?

In this case, we’ve got several answers.

In addition to Agarwal and Bain’s book, both Make it Stick (by Brown, Roediger, and McDaniel) and How We Learn (by Benedict Carey) offer helpful surveys of the research.

You could also check out current research. Ayanna Kim Thomas recently published a helpful study about frequent quizzing in college classrooms. (It helps!)

All these ways of knowing help. Other ways of knowing would be equally helpful.

For instance: I might want to know if retrieval practice helps in actual classrooms, not just in some psychology lab somewhere.

Yes, yes: Agarwal and Bain’s research mostly happened in classrooms. But if you’ve met them you know: it might work because they’re such engaging teachers! What about teachers like me — who don’t quite live up to their energy and verve?

Today’s News

A recent meta-analysis looked at the effect on retrieval practice in actual classrooms with actual students. (How many students? Almost 8000 of them…)

Turns out: retrieval practice helps when its studied in psychology labs.

And, it helps when vivacious teachers (like Agarwal and Bain) use it.

And, it helps when everyday teachers (like me) use it.

It really just helps. As in: it helps students learn.

A few interesting specifics from this analysis:

First: retrieval practice quizzes helped students learn more when they were counted for a final grade than when they weren’t. (Although: they did help when not counted toward the grade.)

Second: they helped more when students got feedback right away than when feedback was delayed. (This finding contradicts the research I wrote about last week.)

Third: short answer quizzes helped learning more than multiple choice (but: multiple choice quizzes did produce modest benefits).

Fourth: announced quizzes helped more than unannounced quizzes.

and, by the way

Fifth: retrieval practice helped middle-school and high-school students more than college students. (Admittedly: based on only a few MS and HS studies.)

In brief: all that good news about retrieval practice has not been over sold. It really is among the most robustly researched and beneficial teaching strategies we can use.

And: it’s EASY and FREE.

A Final Note

Because psychology research can be — ahem — written for other psychology researchers (and not for teachers), these meta-analyses can be quite daunting. I don’t often encourage people to read them.

In this case, however, authors Sotola and Crede have a straightforward, uncomplicated prose style.

They don’t hold back on the technical parts — this is, after all, a highly technical kind of writing.

But the explanatory paragraphs are unusually easy to read. If you can get a copy — ask your school’s librarian, or see if it shows up on Google Scholar — you might enjoy giving it a savvy skim.

“Sooner or Later”: What’s the Best Timing for Feedback?
Andrew Watson
Andrew Watson

Given the importance of feedback for learning, it seems obvious teachers should have well-established routines around its timing.

In an optimal world, would we give feedback right away? 24 hours later? As late as possible?

Which option promotes learning?

In the past, I’ve seen research distinguishing between feedback given right this second and that given once students are done with the exercise: a difference of several seconds, perhaps a minute or two.

It would, of course, be interesting to see research into longer periods of time.

Sure enough, Dan Willingham recently tweeted a link to this study, which explores exactly that question.

The Study Plan

In this research, a team led by Dr. Hillary Mullet gave feedback to college students after they finished a set of math problems. Some got that feedback when they submitted the assignment; others got it a week later.

Importantly, both groups got the same feedback.

Mullet’s team then looked at students’ scores on the final exams. More specifically, if the students got delayed feedback on “Fourier Transforms” — whatever those are — Mullet checked to see how they did on the exam questions covering Fourier.

And: they also surveyed the students to see which timing they preferred — right now vs. one week later.

The Results

I’m not surprised to learn that students strongly preferred immediate feedback. Students who got delayed feedback said they didn’t like it. And: some worried that it interfered with their learning.

Were those students’ worries correct?

Nope. In fact, just the opposite.

To pick one set of scores: students who got immediate feedback scored 83% on that section of an exam. Students who got delayed feedback scored a 94%.

Technically speaking, that’s HUGE.

Explanations and Implications

I suspect that delayed feedback benefitted these students because it effectively spread out the students’ practice.

We have shed loads of research showing that spacing practice out enhances learning more than doing it all at once.

So, if students got feedback right away, they did all their Fourier thinking at the same time.  They did that mental work all at once.

However, if the feedback arrived a week later, they had to think about it an additional, distinct time. They spread that mental work out more.

If that explanation is true, what should teachers do with this information? How should we apply it to our teaching?

As always: boundary conditions matter. That is, Mullet worked with college students studying — I suspect — quite distinct topics. If they got delayed feedback on Fourier Transforms, that delay didn’t interfere with their ability to practice “convolution.”

In K-12 classrooms, however, students often need feedback on yesterday’s work before they can undertake tonight’s assignment.

In that case, it seems obvious that we should get feedback to them ASAP. As a rule: we shouldn’t require new work on a topic until we’ve given them feedback on relevant prior work.

With that caveat, Mullet’s research suggests that delaying feedback as much as reasonably possible might help students learn. The definition of “reasonably” will depend on all sorts of factors: the topic we’re studying, the age of my students, the trajectory of the curriculum, and so forth.

But: if we do this right, feedback helps a) because feedback is vital, and b) because it creates the spacing effect. That double-whammy might help our students in the way it helped Mullet’s. That would be GREAT.

 

Have I Been Spectacularly Wrong for Years? New Research on Handwriting and Learning
Andrew Watson
Andrew Watson

Long-timer readers know my weakness.

I’m usually an easy-going guy. But if you want to see me frantic with frustration, tell me about the superiority of handwriting for taking notes.

Here’s the story.

Back in 2014, two Princeton researchers did a study which concluded that handwritten notes lead to better learning than notes taken on laptops.

That’s a helpful question to have answered, and so I read their study with a mixture of curiosity and gratitude.

Imagine my surprise when I found that their conclusion rests on the assumption that students can’t learn to do new things. (That’s a VERY weird belief for a teacher to have.)

If you believe a student CAN learn new to do things, then the researchers’ data strongly suggest that laptop notes will be better.

Oh, and, by the way, their study does not replicate.

Despite these glaring flaws, people still cite this study — and look at me with pity (contempt?) when I try to convince them otherwise. “But research says so,” they say wearily. I seethe, but try to do so politely.

Today’s Exciting News

When I try to explain my argument, my interlocutor often says something like “handwriting engages more neural processing through kinesthetic yada yada,” and therefore boosts learning.

In the first place, that’s NOT the argument that the Princeton researchers make. It might be true, but that’s changing the subject — never a good way to prove a point.

In the second place, where is the evidence of that claim? I’d love to review it.

To date, no one has taken me up on that offer.

But — [sound of trumpets blaring] — I recently found a post at Neuroscience News with this splendid headline: “Why Writing by Hand Makes Kids Smarter.”

Here’s the first sentence of the article:

Children learn more and remember better when writing by hand, a new study reports. The brains of children are more active when handwriting than typing on a computer keyboard.

“Learn more.” “Remember better.” That’s impressive. At last: the research I’ve been asking for all these years!

Believe it or not, I rather enjoy finding research that encourages me to change my mind. That process reminds me of the power of the scientific method. I believe one thing until I see better evidence on the other side of the argument. Then I believe the other thing.

So, AT LAST, I got to read the research showing that handwriting helps students learn more and remember better.

Want to know what I found?

The Study

The researchers did not test anyone’s learning or memory.

You read that right. This article claims that handwriting improves learning and memory, but they didn’t test those claims.

This research team asked 24 participants — twelve adults and twelve 12-year-olds — to write by hand, or write on a laptop. They then observed the neural regions involved in those tasks.

Based on what they saw, they inferred that handwriting ought to result in better learning.

But they did not test that hypothesis.

So, based on a tiny sample size and a huge leap of neuro-faith, they have concluded that handwriting is better. (And, astonishingly, some big names in the field have echoed this claim.)

The Bigger Picture

Believe it or not, I’m entirely open to the possibility that handwritten notes enhance learning more than laptop notes do.

I’m even open to the possibility that kinesthetic yada yada is the reason.

To take one example, Jeffrey Wammes has done some splendid research showing that — in specific circumstances — drawing pictures helps students remember words and concepts.

If drawing boosts learning, maybe handwriting does too. That’s plausible.

But here’s the thing: before Wammes made his claim, he tested the actual claim he made.

He did not — as the Princeton researchers did — start from the assumption that students can’t learn to do new things.

He did not — as this current research does — extrapolate from neural patterns (of 24 people!) to predict how much learning might happen later on.

Wammes designed a plausible study to measure his hypothesis. In fact, he worked hard to disprove his interpretation of the data. Only when he couldn’t did he admit that — indeed — drawing can boost learning.

Before I believe in the superiority of either handwritten notes or laptop notes, I want to see the study that works hard to disprove its own claims. At present, the best known research on the topic conspicuously fails to meet that test.

Do you know of research that meets this standard? If yes, please let me know!

Meet the Keynotes: Stuart Shanker
Andrew Watson
Andrew Watson

What’s the difference between self-control and self-regulation?

Dr. Stuart Shanker has written and thought about this topic for years.

Here’s his two-minute answer.

https://www.youtube.com/watch?v=FZFIB2AxSM0

To dig more deeply into this topic, come meet Dr. Shanker at our online fall conference. You can learn more and sign up here.

Meet the Keynotes: Chloé Valdary
Andrew Watson
Andrew Watson

“The Theory of Enchantment is a social-emotional learning program that teaches individuals how to develop character, develop tools for resiliency…but more importantly, to learn how to love oneself.”

Intrigued?

Meet Chloé Valdary in this TedTalk, at at our conference, November 7-8.

https://www.youtube.com/watch?v=dB7gsp_zDZc

“Rich” or “Bland”: Which Diagrams Helps Students Learn Deeply?
Andrew Watson
Andrew Watson

Here’s a practical question: should the diagrams we use with students be detailed, colorful, bright, and specific?

Or, should they be simple, black and white, somewhat abstract?

We might reasonably assume that DETAILS and COLORS attract students’ attention. If so, they could help students learn.

We might, instead, worry that DETAILS and COLORS focus students’ attention on surface features, not deep structures. If so, students might learn a specific idea, but not transfer their learning to a new context.

In other words: richly-decorated diagrams might offer short-term benefits (attention!), but result in long-term limitations (difficulties with transfer). If so, blandly-decorated diagrams might be the better pedagogical choice.

Today’s Research

Scholars in Wisconsin — led by David Menendez — have explored this question.

Specifically, they asked college students to watch a brief video about metamorphosis. (They explained that the video was meant for younger students, so that the cool college kids wouldn’t be insulted by the simplicity of the topic.)

For half the students, that video showed only the black-and-white diagram to the left; for the other half, the video showed the colors and dots.

Did the different diagrams shape the students’ learning? Did it shape their ability to transfer that learning?

Results, Please…

No, and yes. Well, mostly yes.

In other words: students who watched both videos learned about ladybug metamorphosis equally well.

But — and this is a BIG but — students who watched the video with the “rich” diagram did not transfer their learning to other species as well as students who saw the “bland” diagram.

In other words: the bright colors and specifics of the rich diagram seem to limit metamorphosis to this specific species right here. An abstract representation allowed for more successful transfer of these concepts to other species.

In sum: to encourage transfer, we should use “bland,” abstract diagrams.

By the way: Team Menendez tested this hypothesis with both in-person learners and online learners. They got (largely) the same result.

So: if you’re teaching face-to-face or remotely, this research can guide your thinking.

Some Caveats

First: as is often the case, this effect depended on the students’ prior knowledge. Students who knew a lot about metamorphosis weren’t as distracted by the “rich” details.

Second: like much psychology research, this study worked with college students. Will its core concepts work with younger students?

As it turns out, Team Menendez has others studies underway to answer that very question. Watch This Space!

Third: Like much psychology research, this study looked at STEM materials. Will it work in the humanities?

What, after all, is the detail-free version of a poem? How do you study a presidency without specifics and details?

When I asked Menendez that question, he referred me to a study about reader illustrations. I’ll be writing about this soon.

In Sum

Like seductive details, “rich” diagrams might seem like a good teaching idea to increase interest and attention.

Alas, that perceptual richness seems to help in the short term but interfere with transfer over time.

To promote transfer, teach with “bland” diagrams — and use a different strategy to grab the students’ interest.

Meet the Keynotes: Mary Helen Immordino-Yang
Andrew Watson
Andrew Watson

If you’re as excited for our November conference as I am, you might want to know more about our speakers.

Mary Helen Immordino-Yang is an affective neuroscientist and an educational psychologist.

That means: she studies how “children’s emotional and social relationships shape their LEARING, and also shape the BRAIN DEVELOPMENT that undergirds their learning.”

Yes: her work is that interesting.

https://www.youtube.com/watch?v=DEeo350WQrs

I got to interview Dr. Immordino-Yang back in 2018; she’s practical and funny and insightful. And she KNOWS SO MUCH.

You can read more here.

If you want to learn more about Rebuilding SEL Skills in the Age of COVID-19, we hope you’ll join us, and Dr. Immordino-Yang.

“If I Want My Students to Learn Math, Should I Teach Them More Math?”
Andrew Watson
Andrew Watson

We all agree, I suspect, that students should learn math. And reading. They should learn history. And science. SO MANY other topics.

What’s the best way to meet these goals?

If I want my students to learn math, is math teaching the best way to go? If I want them to understand history, should I teach more history?

Or, instead, is there a handy shortcut?

If I could help students improve their reading by teaching something other than reading, that alternate approach just might be more efficient and motivating.

In fact, two candidates get lots of attention as “alternative approaches.”  If either or both pan out, they would offer us more choices. Maybe even a higher chance of success.

Music and Math

I don’t remember where I first heard that music education improves math learning. Specifically: learning to play the violin ultimately makes students better at learning calculus.

The explanation focused on “strengthened neural circuits” “repurposed” for “higher cognitive function.” Something like that. That string of words sounded quite impressive, and inclined me to believe.

Given the complexity of calculus, that would be really helpful!

But: is it true?

A recent meta-analysis looked at 54 relevant studies, including just under 7,000 participants.

Their findings? Let me quote key points from their summary:

Music training has repeatedly been claimed to positively impact children’s cognitive skills and academic achievement (literacy and mathematics).

This claim relies on the assumption that engaging in intellectually demanding activities fosters particular domain-general cognitive skills, or even general intelligence.

The present meta-analytic review shows that this belief is incorrect.

Once the quality of study design is controlled for, the overall effect of music training programs is null.

It gets worse:

Small statistically significant overall effects are obtained only in those studies implementing no random allocation of participants and employing non-active controls.

In other words: you get this result only if the study isn’t correctly designed.

And worse:

Interestingly, music training is ineffective regardless of the type of outcome measure (e.g., verbal, non-verbal, speed-related, etc.), participants’ age, and duration of training.

That is: no matter what you measure, the answer is still “no.”

Violin training sure strengthened some neural circuits. But that additional strength doesn’t get “repurposed for ‘higher’ cognitive function.”

If I want my students to learn math, I should teach them math.

Chess and Intelligence

If you watch The West Wing, you know that President Bartlet is smarter than everyone else because he won a Nobel Prize, and he plays chess frequently. He says things like “rook takes queen in five.” And then Leo nods appreciatively.

So smart.

It might be true that being smart makes you better at chess. (Although, Anders Ericsson says “no.”)

Is it true that playing chess makes you smarter? If we want our students to learn math and reading and science, should we teach them more chess? Would some neural circuitry get repurposed?

Let’s go to the tape:

In contrast to much of the existing literature, we find no evidence of an effect of chess instruction upon children’s mathematics, reading or science test scores.

In this case, by the way, the “tape” is a randomized control trial with more than 4,000 students in it. So: that result seems impressively well established.

So far, it seems that if I want my students to be better at X, I should teach them X. Teaching them Y and hoping that Y makes them better at X hasn’t panned out well…

Social Studies and Reading

Reading might be an interesting exception to this rule. On the one hand, reading is a skill that students must acquire.

And, at the same time, they have to apply the skill of reading to the content being read. The more that students know about the content, maybe the better they’ll do at reading.

In any case, that’s a plausible hypothesis.

A recently released report from the Thomas Fordham Institute crunches the numbers, and finds that additional time devoted to social studies instruction ultimately improves reading scores.

Two key sentences from the executive summary:

Instead of devoting more class time to English language arts, we should be teaching elementary school children more social studies — as in, rich content about history, geography, and civics.

Literacy gains are more likely to materialize when students spend more time learning social studies.

In fact, they find that social studies instruction most benefits students from lower-income households, and from non-English speaking homes.

For a variety of reasons, this study looks at correlation, and so can’t demonstrate causation.

However, the underlying theory makes sense. If students can decode the sounds of the words “Berlin” and “Wall,” but don’t know the geography of Germany or cold-war history, they’re unlikely to make much sense of a reading passage about that in/famous border.

In Sum

Students improve at the skills they practice. Those skills — alas —  rarely transfer to distantly unrelated disciplines.

To help students learn math, teach them math. To help them read, teach them to read — and also about the scientific, historical, geographic, and philosophical concepts that make reading so important and so worthwhile.

How Psychologists and Teachers Can Talk about Research Most Wisely
Andrew Watson
Andrew Watson

Dr. Neil Lewis thinks a lot about science communication: in fact, his appointment at Cornell is in both the Psychology AND the Communications departments. (For a complete bio, click here.)

He and Dr. Jonathan Wai recently posted an article focusing on a troubling communication paradox:

Researchers are encouraged to “give science away”; however, because of the “replication crisis,” it’s hard to know what science is worth being given.

Here at Learning and the Brain, we think about that question frequently — so I was delighted that Dr. Lewis agreed to chat with me about his article.

In this conversation, we talk about…

… how teachers can ask psychologists good questions

… the dangers of “eminence”

… what we should think about growth mindset research

… the research “hype cycle.”

I hope you enjoy this conversation as much as I did.


Andrew Watson:

Thank you, Dr. Lewis, for sharing your ideas with our readers.

In your recent article, you and Dr. Wai write about tensions between two imperatives in the field of psychology.

First, psychologists are being asked to “give research away.” And second, our field worries about the “replication crisis.”

Both of those phrases mean more or less what they say. Could you define them a little more precisely, and talk about the tensions that these imperatives are creating?

Dr. Lewis:

There has been a long-standing call in psychology—going back, really, to the 60’s when George Miller first issued this call—to “give psychology away.”

As scholars, we spend our time doing all this research: we should try to communicate it with the world so that people can use it and improve lives.

Professional psychology societies and organizations really encourage researchers to “get our work out there.”

But at the same time, over the past decade or so, there has been a movement to reflect on what we really know in psychology.

A “replication crisis” has occurred—not only in psychology, it’s been happening in many areas.

We are having a hard time replicating many research findings. And that [failure] is making us, the scientists, wrestle with: what do we know? How do we know it? How robust are some of our findings?

And so there’s a tension here. We’re supposed to be “giving our findings away,” but at the same time we’re not sure which ones are robust enough to be worth giving away.

Andrew Watson:

That does sound like a problem. In that tension, do you see any special concerns about the field of education?

Dr. Lewis:

One of the things I’ve been thinking about for education researchers is: how do we know what we know? We have to look very closely at the details of the paper to figure those things out.

Which students are being studied in the papers you’re reading?

What kinds of schools?

What kind of teachers?

At least in the US, there’s so much segregation in our school systems that schools look very different.

If studies are run—let’s say—with kids in the Ithaca school district where I live in upstate New York: those kids, those parents, those schools are very different than studies run—let’s say—in the Detroit public school district, which is the district I thought a lot about during my graduate training when I lived in Michigan.

There are big differences between these districts. We have to figure out: are the schools that we’re trying to intervene in, similar to the studies that were run? Or are they different?

Andrew Watson:

I have a question about that process.

Here’s a problem: to know what questions teachers ought to be asking, we need expert knowledge. Because we’re teachers not psychologists, it’s hard to know the right questions.

So: what’s the best question that a nonspecialist teacher can ask of a researcher, in order to get an answer that we can genuinely understand?

Dr. Lewis:

I think there are some basic things that teachers can ask of researchers.

The teachers can ask what kinds of schools were these studies run in. Are they urban schools, rural schools?

What percentage of the students are on free lunch? (That’s an indicator of poverty levels of the school. Research findings are often influenced by background characteristics about the students.)

What do we know about the kinds of students that were involved in studies?

What do we know about the teachers?

Those are basic things that the researchers should be able to tell you. And then you can figure out whether those are similar to:

the students that you’re working with,

the kinds of schools that you have,

the kind of leadership in your school district, and the like.

Those basic characteristics about how the study was done will help you figure out whether or not you can use it.

Andrew Watson:

I spend a lot of time talking with teachers about this concern. Most psychology research is done with college undergraduates. That research is obviously important. But if you’re teaching reading to third graders, maybe that research translates to your context and maybe it doesn’t.

Dr. Lewis:

Right.

Andrew Watson:

One of the more intriguing points you made in the article has to do with the idea of eminence.

In the world of education, we’re often drawn to Big Names. You argue that the things scholars do to achieve eminence don’t necessarily help them produce high quality research.

As teachers, how do we sort through this paradox? How can we be wise when we think about that?

Dr. Lewis:

We brought up eminence to reinforce what I just noted. Look at the details of the study and don’t rely on the “cue” of eminence as your signal that research must be good.

Researchers are judged by many metrics. Once you put those metrics in place, people do what they can to… I hesitate to use the word “game,” but to optimize their standing in those metrics.

Andrew Watson:

Which is a lot like “gaming,” isn’t it?

Dr. Lewis:

Yes. In the research world, there are a few metrics that don’t necessarily help [produce meaningful results]. One of them, for instance, is that researchers are incentivized to publish as much as we can.

Unfortunately, publishing fast is the way to rise up the ranks. But sometimes figuring out these differences that I have been talking about—like, between contexts and samples—it takes some time. It slows you down from churning out papers; and unfortunately, researchers often aren’t incentivized to take that slower, more careful approach.

And so there’s that tension again too. I don’t want to leave the impression that we just shouldn’t trust eminent people. That’s not the point I want to make.

The point is: eminence in and of itself is not a useful signal of quality. You have to look very closely at the details of the studies in front of you. Then compare those details to your own situation and judge the work on that. Judge the work, don’t judge based on how famous the person is.

Andrew Watson:

It occurs to me as you’re explaining this, there’s a real problem with the emphasis on rapid publication. One of the consistent findings in education research is that short-term performance isn’t a good indicator of long-term learning.

But if scholars are incentivized to publish quickly, they’re incentivized to the study short-term, which doesn’t tell us much about what we really want to know: learning that lasts.

Dr. Lewis:

Absolutely right. As I’ve written in other articles, we don’t have enough longitudinal studies for the very reasons we’re talking about: longitudinal studies take forever—and, again, the incentive is to publish fast, publish often.

The outcomes that are often measured in psychology studies are these shorter term things. You have the student do something, and you measure at the end of the session. Maybe you look again at the end of the semester.

But [we should] look next year, two years, three years, because we know some of these effects take time to accumulate.

Some older studies have looked at long-term outcomes. I’ve seen a few fascinating studies showing, initially, no significant findings. But if you look far enough down the road, you start to see meaningful effects. It just takes time for the benefits to accumulate.

In education, we shouldn’t assume that research results “generalize.” [Editor: That is, we shouldn’t assume that research with 1st graders applies to 10th graders; or that short term findings will also be true in the long term.]

Now, until I see more evidence, I assume findings are context-specific. [Editor: That is, research with 1st graders applies to 1st graders—but not much beyond that age/grade. Research from the United States applies to the US cultural context, but not—perhaps—to Korea.]

For instance: “growth mindset.” In recent studies, authors have been looking at how much the effect varies by context and by population. Those details matter in thinking about mindset studies.

Andrew Watson:

Yes, I think mindset is a really interesting case study for the topic we’re talking about. My impression is that teachers got super excited about growth mindset. We went to a highly simplistic “poster-on-the-wall” version of the theory.

And in the last 18 months or so, there has been a real backlash. Now we hear: “growth mindset means nothing whatsoever! Why are you wasting your time?”

We need to find our way to a nuanced middle ground. No, growth mindset is not a panacea. But nothing is a panacea. At the same time, in a specific set of circumstances, mindset can help certain students in specific ways.

That balanced conclusion can be a hard place to get the conversation to go.

Dr. Lewis

Yes, issues like that motivated us to write our paper.

If we [researchers] are able to communicate those nuances clearly, then I think we avoid these misunderstandings. It’s not that mindset is useless; instead, mindset will have a small effect under certain conditions. We should just say that.

We have a problem with the “hype cycle.”

If something is over-hyped one day, then you’re really setting people’s expectations unreasonably high. Later, when the research doesn’t meet those expectations, teachers are disappointed.

And so researchers should set expectations appropriately. Mindset is not a panacea. We shouldn’t expect enormous impacts. And that’s fine. Let’s just say that.

Andrew Watson:

I think this “hype cycle” is part of the challenge that we’re facing.

For instance, with learning styles, teachers thought that it had a lot of scientific backing. We embraced it because it was “research based.”

Now the message is: “no, research got that wrong; learning styles aren’t a thing. But here’s another research-based thing instead.”

And teachers are saying: “wait, if I shouldn’t have followed research about learning styles, why should I believe new research about new teaching suggestions?”

Dr. Lewis:

That’s a tricky problem.

One way to think about science is: science is a way of reducing uncertainty.

We had this idea about learning styles. We gathered some initial evidence about it. It seemed like a good idea for a while.

But as we continued studying it, we realized, well, maybe there is not as much good evidence as we thought.

And that’s part of the scientific process. I think it’s important to explain that.

But: that shift without an explanation naturally leads teachers to be suspicious.

Teachers think: “why are you telling me, just make this change. You have to explain to me what is going on and why should I make that change.”

This explanation does take more time. But that’s what is necessary to get people to update their understanding of the world.

Something that we all have to keep in mind: just as every year teachers are learning new ways to teach the new generations of students, scientists are doing the same thing too. We’re constantly trying to update our knowledge.

So there will be changes in the recommendations over time. If there weren’t changes, none of us would be doing our best. So we’re learning and improving constantly.

But we have to have that conversation. How are we updating our knowledge? And what are ways that we can implement that new knowledge into curriculum?

And, the conversation has to go both ways. Researchers communicate things to teachers, but teachers also need to be telling things to researchers. So we can keep that real classroom context in mind as we’re developing research advice.

Andrew Watson:

In your article, you and Dr. Wai remind researchers that they’re not communicating with one undifferentiated public. They are talking with many distinct, smaller audiences—audiences which have different interests and needs.

Are there difficulties that make it especially hard to communicate with teachers about psychology research? Is there some way that we’re an extra challenging audience? Or maybe, an especially easy audience?

Dr. Lewis:

I think what’s hard for presenters is not knowing details about the audience, where they’re coming from. That section of the paper is about is really getting to know your audience, and tailoring your message from there.

If I’m going to go explain psychology findings to a group of STEM teachers, that talk might be different than if the audience is a broader cross-section of teachers.

In the university setting, it’s easier to figure out those distinctions because you know which department invited you to speak.

In broader K-12 settings you don’t always know. A school district invites you. You can do some Googling to try to figure something out about the district. But you don’t know who’s going to be in the room, and what is happening [in that district]. So you might end up giving too broad a talk, that might be less informative than if you did get some more information.

Andrew Watson:

Are there questions I haven’t asked that I ought to have asked?

Dr. Lewis:

The key point for me is: when we communicate about science in the world, we really have to look at key research details and have serious conversations about them. Nuances matter, and we just can’t gloss over them.

Andrew Watson:

Dr. Lewis, I very much appreciate your taking the time to talk with me today.

Dr. Lewis:

Thank you.