Author Archives: Andrew Watson

I spend most of my professional life talking in front of groups of people. Specifically, I talk about psychology and neuroscience research — and the (careful!) application of those findings to classrooms.

For that reason, I feel quite comfortable writing blog posts about research-based teaching advice: most recently…

… how goals and feedback might motivate students, and

… the relative importance of enjoyment and/or skill in reading instruction, and

… the potential benefits of PBL.

And so forth.

In recent years, I’ve also been getting questions about presenting in public.

While that topic isn’t central to this blog, it might be helpful. After all, I know MANY people who read this blog present at conferences. And I bet many more people would like to.

So: a few quick thoughts.

1: You Do You

No, seriously.

I won’t present well if I’m trying to do (exactly) what you do, and you won’t present well if you try to do (exactly) what I do. We’re different individuals.

While I do think the advice below is broadly helpful, you should also NOT follow this advice if it encourages you to act like someone you’re not.

That is:

• If you try to be funny — because someone somewhere said “funny speakers are good!” — that advice will work only if you’re a funny person. If not, your audience will sense your discomfort (and your unfunniness) right away.
• If I try to get adults up and moving around (“Everybody Conga!”) because John Almarode is GREAT at getting people up and moving, I’ll feel deeply foolish. That’s just not my style. And my audience will know I feel deeply foolish. (They will probably also feel deeply foolish.)

And so forth.

2: You Do What You Say

When I’m giving a talk about avoiding working memory overload, I have to be especially careful to avoid working memory overload. If I don’t, my audience will remember my hypocrisy; they will not remember my content.

If you’re talking about retrieval practice, include retrieval practice. If you don’t, your audience will wonder why you didn’t use the teaching practice that you said was so important.

Ditto if you’re talking about mindfulness, or mini-white-boards, or forming relationships. Speakers who don’t do what they say risk looking like hypocrites.

By the way, this truth creates real problems for presentations on specific pedagogies. If my message is “students best remember ideas they learn through open-ended inquiry,” how can I best make that argument?

• If I give a presentation, then my medium contradicts my message.
• If I let teachers open-endedly explore their own pedagogical interests, they might not explore “open-ended inquiry.” Or, if they do, their inquiry might not arrive at the same conclusion I do.

My point here is not to be snarky, but to note a real challenge for champions of more “student-centered” pedagogical styles. If I give a talk about the inherent futility of giving talks…the paradox probably overwhelms my message.

3: Highlight Structure

Most talks condense LOTS of information into relatively short periods of time. In fact, one reason speakers receive invitations is: their expertise allows them to organize many ideas into a coherent (if complex) package.

Alas, the more info I condense into my talk, the harder my audience has to work to follow my argument. With each passing slide, they think more nervously: “Wait — how does THIS set of ideas connect to ALL THOSE PREVIOUS sets of ideas?”

For that reason, I think speakers should include a clear outline very near the beginning of the talk. And they should return to that outline frequently throughout the talk to indicate progress.

For instance, I’ve got an upcoming talk on the subject of “Rethinking Intrinsic Motivation.” That talk will begin with this outline:

Act I: Here’s what everyone thinks about intrinsic motivation.

Act II: David Geary wants us to RETHINK intrinsic motivation.

Act III: Most people think that this other theory contradicts Geary. But I think it aligns with — and adds to — Geary’s theory.

Act IV: In fact, we need to RETHINK the other theory to convert it from a “to do” list into a “to think” list. Here’s how we do that.

Notice, this initial outline stays fairly abstract. I say that Geary “wants us to rethink motivation,” but I don’t get specific. I don’t even name the other theory. And so forth.

As I make my way through the talk, I explicitly return to that outline and add in all those specifics:

“As you saw in Act II, Geary wants us to rethink intrinsic motivation from an evolutionary angle. For that reason, he argues, school should emphasize topics that we didn’t evolve to learn, not those that we do.

Now, in Act III…”

By starting with an outline, and by returning to it, I clarify my ideas. Even more important: I clarify the relationship among the ideas.

4: Presenting Online

Four quick rules to raise your online game.

a) My eyes should not be at the center line of the screen, but 1/3 of the way down from the top of the screen. Film and TV shows are shot with this “rule of thirds,” so my audience expects it. Eyes at the midline look odd.

b) For heaven’s sake, I must NOT let my laptop camera point up at my face — and therefore up my nostrils. That view is really unpleasant. I should prop the laptop on books so that it’s level with my face.

c) In daily conversation, we don’t typically get very close to the people we’re talking with. If my face is too close to the camera, I’m a “close talker.” The look is unsettling. So, I should move the camera back so that most of my torso is visible.

d) My background matters. If the room behind me is cluttered and unkempt, I look unprofessional. I should find a simple, classy look.

None of those guidelines is complicated; all of them improve online presentations.

In Sum…

Although speakers should be themselves, some guidelines improve almost all talks. I hope the list above proves helpful.

As I wrote last week, thinkers in edu-world often make strong claims at the expense of nuanced ones.

For example:

• “A growth mindset undergirds all learning” vs. “growth mindset is an obvious boondoggle.”
• “AI will transform education for the better” vs. “AI will make people dumber and schools worse.”
• “Be the sage on that stage!” vs “get off the stage to guide from the side!”

The list goes on (and gets angrier).

When researchers start digging into specifics, however, the daily experience of teaching and learning gets mightily complicated, and mighty fast.

All those strong claims start to look…well…too strong for their own good.

One extraordinary example of “digging into the specifics” can be found in Graham Nuthall’s The Hidden Lives of Learners. Nuthall put cameras and mics on students in New Zealand classrooms, and arrived at all sorts of astonishing conclusions.

Another recent study looks quite specifically — no, really specifically — at 4 teachers. The goal: to understand what part of their work helped students learn.

Here’s the story.

Time to Review

A group of scholars, led by Dr. Janet Metcalfe, wondered if students learned more from teachers’ responses to their mistakes than from teachers’ direct instruction. (You can learn more about the study here.)

A few important points merit attention right away.

First: the classroom sessions I’m about to describe are REVIEW sessions. The students have ALREADY learned the math covered in these lessons; the teachers are helping them review in preparation for a high stakes exam.

In other words: this study does not focus on initial instruction. It focuses on subsequent review.

Second: the students involved VOLUNTEERED to take part. They are, presumably, atypically motivated to learn math.

Keep these points in mind as you think about applying the ideas described below.

In this study, 4 teachers helped 175 8th grade students prepare for upcoming state math exams.

For half of the students, the teachers taught 8 lessons (“explicit instruction”) reviewing core math concepts that would be on that exam.

For the other half, the teachers responded to the misakes that students made on practice tests. That is: during 4 sessions, students took 45 minute math tests. And after each of those sessions, the teachers

“were instructed […] to focus on the students’ errors and to do whatever they deemed appropriate to ensure that the issues underlying the errors would not reoccur and that the students would learn from their errors.”

So, which review approach proved more helpful — the explicit instruction, or the learn-from-mistakes instruction? And, why?

An Envelope, and LOTS of Questions…

The answer to that first question — which kind of review proved most helpful? — is easy to answer.

Students in both groups learned math; they did better on the post-test than the pre-test.

The students in the “learn-from-mistakes” group learned more.

This straightforward finding leads to obvious questions. And — alas — those obvious questions are VERY tricky to answer.

For instance, “how much more did the students in the learn-from-mistakes group learn?” That’s a reasonable question. The answer takes some careful parsing.

Roughly speaking, students in the explicit instruction group increased their scores about 2% per hour of instruction.

For those in the learn-from-mistakes group, the answer depended on the teacher.

The least successful teacher helped students in this group improve 2% per hour of instruction. The most successful teacher helped students improve 5% per hour of instruction.

Of course, that last paragraph prompts another reasonable question: what was different about those two teachers? Why did one teacher benefit his/her students more than twice as much as their colleague?

Let the Sleuthing Commence…

The study’s authors spend a great deal of time — and crunch a great many equations — to answer that question.

For instance:

Maybe the teacher whose students learned more (let’s call her Teacher M) is just a better teacher than the one whose students learned less (Teacher L).

As the researchers point out, that explanation doesn’t make much sense. After all, in their explicit instruction sessions, both Teacher M and Teacher L helped their students equally.

(By the way: to simplify this blog post, I’m leaving out the two other teachers for now.)

Okay, maybe Teacher M did a better job of focusing on students’ mistakes, whereas Teacher L spent too much time focusing on questions that students got right.

Nope. This study includes quite an eye-watering graph to show that they both focused about the same on students’ mistakes.

As the researchers write: “all of the teachers taught to the errors of their students, and … the extent to which they did so did not predict student learning.”

So, what was the secret sauce?

The Perfect Combination

After a few more false leads, the study focuses on two moment-by-moment variables: the teachers’ focus, and the kind of interaction with the student.

Focus: did the teachers

“[dwell] upon how to solve the problem correctly,” or

“[delve] into the nature of the errors – why the students had made them, what the difficulty in the logic was, and/or how to recognize and circumvent such mistakes in the future”?

Kind of interaction: did the teachers explain/lecture, or did they discuss/interact?

With this pair of questions, at last, the study struck gold.

Teacher L — whose students learned relatively little — focused almost all her time on “how to solve the problem correctly.” While pursuing that goal, she divided her time equally between lecture and discussion.

Teacher M — whose students improved more quickly — spent almost all her time in discussion, with almost no time in lecture. While in this interactive mode, she divided her time more-or-less equally between solving problems and understanding the nature of the mistake.

This final insight allows us to make this claim:

Highly motivated 8th grade math students,

reviewing in preparation for a high-stakes exam,

learn less from explicit instruction and more from making and reviewing their mistakes,

as long as the teacher keeps those review sessions interactive,

and equally focused on “getting the answer right” and “understanding the nature of the mistake.’

Notice, by the way, all the nuance in this statement.

To emphasize just one point here: this study does NOT argue that “learning from mistakes” is better than “direct instruction” in all circumstances.

It argues that students learn more from mistakes when reviewing, as long as the teacher follows a very particular formula.

A Final Note

Heated battles in this field often get hung up on specific labels.

As I’ve written before, we do a LOT of arguing about benefits of “desirable difficulty” vs. “productive struggle” — an odd set of arguments, given that both phrases seem to mean the same thing.

This study was co-authored by (among other scholars) Robert Bjork — who helped coin the phrase “desirable difficulty.” For that reason, you might be surprised to learn that this study touts the benefits of “productive struggle.”

That is: the students took a test, they made mistakes, they wrestled with those mistakes, and they learned more. Their struggle (trying to understand what they did wrong) was productive (they improved on their test scores — and probably their understanding of math).

Of course, I could just as easily describe that process as “desirable difficulty.” The difficulties these students faced here — the test, the mistakes, the analysis — turned out to be beneficial — that is, “desirable.”

My own view is: don’t get hung up on the label. The question is: are the students both thinking harder and ultimately succeeding? If “yes” and “yes,” then this teaching approach will benefit students.

Metcalfe, J., Xu, J., Vuorre, M., Siegler, R., Wiliam, D., & Bjork, R. A. (2024). Learning from errors versus explicit instruction in preparation for a test that counts. British Journal of Educational Psychology.

Over on eX/Twitter, a debate has been raging — with all the subtlety and nuance of your typical Twitter debate. The opening salvo was something like:

“Despite what you’ve heard, all people learn the same way.”

You can imagine what happened next. (Free advice: look away.)

Despite all the Twitter mishegas, the underlying question is useful and important — so I’ll do my best to find the greys among the black-vs-white thinking.

Here goes.

Useful…

I suspect that this claim — “all people learn the same way” — got started as a rebuttal to various myths about “meaningful sub-categories of learners.” Alas, most of those proposed sub-categories turn out not to be true or useful.

• No, learning styles theory has not held up well.
• No, the theory of “multiple intelligences” has no useful teaching implications. (And Howard Gardner didn’t claim that it did.)
• No, “left-brain, right-brain” dichotomies don’t give us insights into teaching and learning.
• No, the Myers-Briggs Type Indicator doesn’t tell us how to manage classrooms or lesson plans. *
• My British friends tell me about some system to sort students according to different colored hats. (I do not think I’m making this up.)
• (I’ve written about these claims so many times that I’m not going to rehash the evidence here.)

Whenever anyone says “we can usefully divide students into THIS kind of learner and THAT kind of learner,” we should be highly suspicious and ask to see lots of research. (If you want to evaluate that research critically, I can recommend a good book.)

Well, the shortest rebuttal to this sort of claim is: “Those sub-categories don’t exist. ALL PEOPLE LEARN THE SAME WAY.”

Now, any time someone makes an absolute claim about teaching and learning in six words and seven syllables, you know that claim is oversimplified.

But you can understand the temptation to cut off all those untrue claims with a brusque rejoinder. That temptation pulses all the stronger because those untrue claims persist so stubbornly. (In 2025, schools of education are STILL teaching learning styles.)

…and (substantially) True

This claim (“all people…”) isn’t simply useful; it’s also largely accurate.

For example:

At the neuro-biological level — neurons, neurotransmitters, synapses, myelin, etc. — long-term memories form the same way for everyone.

As far as we know…

• men and women
• tall people and short people
• introverts and extroverts
• people who think cilantro tastes like soap, and the rest of us

… everyone forms new neural networks (that is: “learns”) the same way. (I should emphasize that our understanding of this neural process is still VERY basic. We’ve still got SO MUCH to learn.)

When we switch our analysis from neuroscience to psychology, the claim still holds up well.

For instance:

• Everyone uses working memory to combine new information from the environment with concepts and facts stored in long-term memory.
• Everyone depends on a complex of systems that we call “attention” to control the flow of all that information.
• Everyone responds simultaneously with emotion and cognition to any given set of circumstances. (These two systems overlap so much that distinguishing between them creates lots o’ challenges.)

And so forth.

Given all these similarities, cognitive science research really can offer up advice that applies to almost everyone in almost all circumstances.

Yes: we really must manage working memory load so that students can build concepts effectively.

Yes: retrieval practice helps almost all learners consolidate and transfer almost all school learning. (Yes, “retrieval-induced forgetting” is a concern, but can be managed if we strategize effecively.)

Yes: spacing and interleaving enhance learning in most circumstances.

And so on…

Given the broad usefulness and truth of the “we-all-learn-the-same” claim, I certainly understand why it’s tempting to make it — and to defend it.

Exceptions Matter

I’ve written that the claim is “broadly” useful and true; but I don’t think it’s ALWAYS true.

For example:

Students with diagnoseable learning differences really might learn differently.

For instance: dyslexic readers combine distinctive neural networks to get their reading done. Those readers almost certainly benefit from distinct teaching strategies. In other words: by any reasonable definition, they “learn differently.”

Another example:

All learning depends on prior knowledge.

That claim — which sounds like “all people learn the same way” — also suggests that people learn differently.

Let’s imagine that you know A LOT more about opera than I do. (This assumption is almost certainly true.) If you and I both attend an advanced lecture about an obscure opera — “Der Häusliche Krieg” —  your learning will function quite differently from mine. Because you’re an expert and I’m a novice, we will learn differently.

Lots of individual differences will bring teachers to this same point.

Because I teach English, I teach grammar — and MANY of my students simply hate grammar. Their prior experience tells them it’s boring, useless, and impossible to understand.

On the one hand, those enduring cognitive principles listed above (working memory, retrieval practice, etc.) do apply to them. But their emotional response to the content will in fact shape the way they go about learning it.

Core principles of learning apply, and my students’ prior experience means that their learning process might well be different.

Beyond Twitter Rage

Twitter generates lots of extreme debates because complex ideas can’t be boiled down into its trivializing format.

So it’s not surprising that a nuanced understanding of “individual differences within important, broad, and meaningful similarities” doesn’t work in Twitter-ville.

At the same time, I do think our discussions of learning should be able to manage — and to focus on — that nuance.

Our students will learn more when we recognize BOTH the broad cognitive principles that shape instruction, AND the individual variation that will be essential within those principles.

Back in 2019, Paul Kirschner wrote a blog post on this same point. His “digestive system” analogy is VERY helpful.

* A few years back, I emailed the MBTI people to ask for research supporting their claims. They did not send me any. They did, however, sign me up for their newsletter.