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Just Tell Them: The Power of Explanations and Explicit Teaching by Zach Groshell
Erik Jahner, PhD
Erik Jahner, PhD

The sage-on-the-stage is not the enemy. For years, educators have been told that the best teaching happens when students discover knowledge for themselves. Zach Groshell, PhD, turns that assumption on its head. In Just Tell Them: The Power of Explanations and Explicit Teaching, he makes a bold case for something refreshingly straightforward—teachers should teach. Clear, explicit explanations aren’t just helpful; they’re essential. Backed by cognitive science and decades of research, Groshell dismantles the myth that “less teacher talk” means “more learning” and offers a compelling argument for direct instruction done right. His message? Good teaching isn’t about withholding information; it’s about equipping students with the knowledge they need to think critically, problem-solve, and truly understand what they’re learning.

groshell

I’ve seen many teachers, myself included, wrestle with the tension between explicit teaching and discovery learning. The belief that students learn best when they “figure it out” on their own is pervasive, but sometimes we may be asking them to construct knowledge without giving them the raw materials? Groshell’s book is a refreshing reality check, and I found myself nodding along as he unraveled the myth.

The book is structured around key principles of effective explanation, each grounded in research and practical application. Groshell starts with an overview of human cognitive architecture—how working memory and long-term memory shape learning—to explain why clear explanations matter. Students aren’t blank slates; they need structured guidance to process new material without overload.

One of the book’s greatest strengths is its focus on the worked-example effect, a well-documented phenomenon demonstrating that students learn more effectively when they see step-by-step demonstrations before being asked to apply their knowledge. Groshell explores ways to maximize clarity—eliminating vagueness, using visuals effectively, and reinforcing understanding through interaction. His candid reflections on his early teaching missteps make even the more technical discussions feel relatable and engaging.

Beyond simply telling, Groshell lays out a structured approach to explanation, covering interactive techniques like choral response and student self-explanations, alongside the power of visuals, strategic questioning, analogies, and storytelling to make concepts more memorable. His discussion of erroneous examples, where students learn by identifying and correcting mistakes, is particularly compelling.

A particularly valuable section details the Explain and Release model, which follows the ‘I do, We do, You do’ approach—gradually shifting responsibility from the teacher to the student as they gain expertise. This aligns with cognitive load theory, emphasizing that novices require structured support, while experts benefit from increasing independence. Groshell references the expertise reversal effect, illustrating how instructional methods should evolve as students grow more proficient—moving from explicit guidance to independent problem-solving.

Groshell’s writing is refreshingly candid, filled with humor and engaging insights. He reflects on his early preference for student-led discovery and how he came to embrace explicit teaching as a necessity. As I read, I couldn’t help but think of the countless times I’ve watched students breathe a sigh of relief when a difficult concept was finally explained clearly.

Another key focus of the book is creating the right conditions for explanation. Groshell discusses managing student attention by minimizing distractions, reducing classroom clutter, and banning cell phones to improve focus. He argues that classroom seating arrangements and behavior management directly impact how well students absorb explanations.

For educators who have been told to minimize their role as the sage on the stage, this book offers a persuasive counterpoint. It reaffirms the value of direct instruction while advocating for its thoughtful application—explanations should be clear, concise, interactive, and strategically designed to maximize learning. Groshell’s insights are invaluable for teachers, instructional coaches, and education professionals looking to refine their approach.

Ultimately, Just Tell Them is a must-read for educators seeking to optimize their instructional practices through cognitive science. If students could absorb complex concepts without explicit guidance, would we even need teachers? Groshell doesn’t just advocate for explanations—he makes them impossible to ignore. This is a practical, research-driven, and accessible guide that dismantles myths about teacher talk while empowering educators. After reading this book, you’ll never see explanation the same way again.

Attention Must Be Paid
Guest Blogger
Guest Blogger

This guest review of Blake Harvard’s Do I Have Your Attention is written by Justin Cerenzia.


Having followed Blake Harvard’s “The Effortful Educator” blog from its very beginning, it feels especially fitting that his new book – Do I Have Your Attention? Understanding Memory Constraints and Maximizing Learning – poses a question many of us have enthusiastically answered “yes” to for nearly a decade.

Yet this book represents more than an extension of Harvard’s blog—it marks the culmination of his long-standing influence as a leading educator: one who connects cognitive science with classroom practice. Thoughtfully structured into two complementary sections, the book skillfully integrates theoretical perspectives on how memory functions with actionable classroom strategies, offering educators practical tools to foster meaningful and lasting learning.

Book Cover of "Do I Have Your Attention" by Blake Harvard

Harvard deftly navigates the complexities often inherent in cognitive science research. His writing style is both approachable and authoritative, resonating equally with newcomers and seasoned readers alike.

Much of Part I leverages Professor Stephen Chew’s An Advance Organizer for Student Learning: Choke Points and Pitfalls in Studying. Harvard uses this foundational framework to clarify key concepts and common misunderstandings about memory and learning. Crucially, Harvard’s position as a classroom teacher lends him credibility and authenticity, grounding his insights firmly in practical experience rather than mere theory.

It’s as though we’re invited into Blake’s classroom, watching him expertly guide us through Chew’s graphic.

And this is precisely how he frames the opening of Part II, writing:

“It can be quite overwhelming to know just what is the best bet for optimizing working memory without overloading it while also making the most of moving the content to long-term memory. Compound that with the fact we are tasked with educating, not one brain, but a classroom full of them. That’s a job that only a teacher can understand and appreciate” (65).

Harvard then succinctly-yet-thoroughly guides readers through seven carefully considered strategies to maximize learning. In each case, he showcases a diverse array of tactics that enrich any skilled teacher’s toolkit—all with the ultimate goal of positively influencing student outcomes.

Throughout, he pulls back the curtain even further, transparently revealing how specific shifts in his own teaching practice improved student learning. Clearly, each change has been guided by careful investigation and thoughtful application of research.

That Harvard’s insights—long influential in the educational blogosphere—are now available in book form represents a win for educators everywhere. Rich in research yet highly accessible, this text serves as both an inviting entry point and a resource for deeper exploration.

So too does it underscore the essential role teachers can and should play alongside the research community, brokering knowledge and further bridging the unnecessary divide that sometimes impedes meaningful change. In an era rife with educational theory, Harvard’s concrete examples of classroom success help ensure that even hesitant educators find meaningful, practical guidance.

If Blake Harvard didn’t already have your attention, you’d do well to give it to him now.


If you’d like to learn more, Blake’s webinar on attention and memory will be May 4.


Justin Cerenzia is the Buckley Executive Director of Episcopal Academy’s Center for  Teaching and Learning. A Philadelphia area native, Justin is a veteran of three independent schools over the last two decades, dedicating his career to advancing educational excellence and innovation. A history teacher by trade, Justin nonetheless considers the future of education to be a central focus of his work. At Episcopal Academy, he leads initiatives that blend cognitive science, human connection, and an experimenter’s mindset to enhance teaching and learning. With a passion for fostering curious enthusiasm and pragmatic optimism, Justin strives to make the Center a beacon of learning for educators both within and beyond the school.

Enjoyment or Skill? The Case of Reading
Andrew Watson
Andrew Watson

Do we want our students to ENJOY math, or to BE SKILLED AT math?

At first, this question sounds like a false choice. Obviously, we want BOTH.

As an English teacher, I want my students to have fun analyzing the books we read…and I want their analyses to have heft, merit, and substance.

I suspect that most teachers, no matter the subject  — Math, English, Chemistry, Religion, Pickleball — want our students to revel in core ideas and arrive at correct answers.

At some times, alas, we probably need to prioritize one or the other. Especially at the beginning of a unit, should I focus on …

… ensuring that my students like this stuff (even if they don’t immediately understand it), or on

… ensuring they understand the stuff (even if they don’t immediately like it)?

In teaching as in life: if I try to accomplish both goals simultaneously, I’m likely to accomplish neither.

Reading Research

I’m not surprised to discover in a recent study that students’ enjoyment of reading correlates with their skill at reading.

That is: students who get high scores on various reading tests report enjoying reading more than their low-test-scoring peers.

Of course, correlation (say it with me) isn’t causation.

Does the enjoyment lead to the skill? The skill lead to the enjoyment?

Both?

Neither?

To answer these questions, Elsje van Bergen’s research team looked at twins in Finland — more than 3500 of them.

In theory, if we ask all the right questions, gather the right data, and run the right calculations, we should glean insight into the correlation/causation question.

So: what did Team van Bergen find?

But First…

Before you read the answers to that question, you might pause to make a committment. Try to decide NOW if you’re inclined to trust this methodology.

That is:

a) you think well-done twin studies are likely to be a good way to answer this question. For that reason, you will be inclined to accept this answer even if you initially disagree with it.

or

b) you think twin studies can’t answer questions about skill and enjoyment. Thus, you will not cite this study to support your beliefs even if it aligns with those beliefs.

If we’re going to use research to make decisions about education, we should be scrupulous about doing so even when research contradicts the conclusions we had initially held.

Answers, and Questions

Now, back to this post’s main narrative…

Unlike many studies, this one can be summarized in a few pithy sentences.

A young student looks at a book open on her desk and scratches her head in confusion

Based on the twin data they analyzed, van Bergen’s team concludes that:

  • reading skill increases reading enjoyment,
  • reading enjoyment has no effect on reading skill,
  • genetics influences both positively.

Unsurprisingly, the stats get all stats-y. But the above-the-fold headlines are that simple.

Because I don’t teach reading, I’ve always hesitated to be too opinionated on the topic. Now that this study is in the wild, I do think it adds a useful perspective while the reading wars rage on.

For instance: teachers whom I like and respect have told me that older methods might not have science behind them, but they’re excellent at “making students feel like readers.”

This claim has always puzzled me. How can a student feel like a reader if s/he can’t read?

Van Bergen’s study, I think, gives me permission to address that point directly: “this study suggests that skill at reading will be the more important place to start in reading instruction.”

Zooming the Camera Back

While this study and this post have focused on reading instruction, I do think there’s a broader message here as well.

We frequently hear about the importance of intrinsic motivation; that is, a motivation that springs from students’ natural interests, not from external encouragement (or pressure).

This study, to the contrary, finds that the work teachers do to improve students’ skill simultaneously enhances their motivation. That motivation might be — in effect — extrinsic; but, it’s working. (Working = students read better, and want to read more.)

Overall, I believe we need a substantial rethink of the (false) intrinsic/extrinsic dichotomy, and the (unhelpful) criticism of motivational strategies that many teachers currently find themselves using.

If you want to join me for just such a rethink, I’m giving a webinar for Learning and the Brain on April 5th. We’ll be talking about several research-informed approaches to intrinsic motivation, and brainstorming strategies to make those ideas fit in our classrooms.

I hope I’ll persuade you that we have better ways to talk about motivation than “intrinsic/extrinsic,” and those better ways give us useful teacherly guidance.

I hope you’ll join us!


van Bergen, E., Hart, S. A., Latvala, A., Vuoksimaa, E., Tolvanen, A., & Torppa, M. (2023). Literacy skills seem to fuel literacy enjoyment, rather than vice versa. Developmental Science26(3), e13325.

Still Doubting My Doubts: The Case of PBL
Andrew Watson
Andrew Watson

Last week, I described my enduring concerns about “embodied cognition.” I’m not sure I understand the concept clearly: what exactly counts as “embodied cognition” — mindfulness? Direct instruction? (No, seriously, a well-known book on the subject says it does!)

And the “best research” supporting some of the claims doesn’t feel persuasive to me.

Could using gestures help learning? SURE. Have I found enough research for me to advocate for this strategy? Not yet…

This week, I wanted to test my doubts about project-based learning (universally acronymed as PBL). SURPRISE: I end up feeling kinda persuaded — at least in this one case.

Here’s the story…

Another Steelman

If I’m going to critique a teaching method, I want to be sure to avoid straw men. Neither you nor I learn anything if I point out the flaws in an obviously foolish study or approach. I’m going to learn something if and only if I take on the very best case.

Some thoughtful soul — I’m embarrased to say, I can’t remember who — recommended this PBL study to me.

Given the strength of that recommendation, I thought it worth a read — despite my PBL concerns.

What are those PBL concerns?

As is so often the case for me, I worry about working memory overload. If I ask my students to

  • Film a scene from Hamlet, but re-imagine it in a new setting, or
  • Build a model city that enacts 3 core principles of ecological design, or
  • Write a new law that prevents a problem in our school’s community

I’m certainly giving them a rich cognitive task.

However, they almost certainly don’t have enough foundational knowledge to manage any of those tasks. Heck, graduate students in those fields struggle with such problems.

So, while I find the questing adventurousness of such tasks intriguing, my knowledge of working memory limitations tells me: ain’t gonna happen.

I should also confess: my experience assigning project-y work hasn’t gone well.

In brief: although “constructivist” approaches often sound appealing, my focus on basic cognitive capacities makes me extra skeptical.

(Important note: “constructivism” is an ENORMOUSLY broad category, and it’s inaccurate/unfair to lump so many pedagogies together into one ill-defined word.)

The Goals; The Problems

When I look at research, I’ve got a few desiderata:

One: The study should — as much as possible — isolate the variable. I can’t say that (to take a comic example) “chewing gum improves learning” if the participants both chewed gum and tap-danced.

Another one: the study should have a plausible control group. The question isn’t “did X improve learning?” but “did X improve learning compared to the plausible alternative Y?”

Yet another one: the researchers should try hard to measure what they claim. If I say “PBL helps students learn stuff,” I should have some reliable measurement of what they learned. If reseachers make up their own test…well…I worry that they’re (subconsciously) putting a thumb on the scale.

Because I’m a PBL doubter, I read this study with a keen eye on those topics. I’m used to finding such problems. For instance:

Isolate the variable: the study about “using gestures” actually used gestures AND cool tech stuff. I don’t believe claims about X if the students did both X and Y.

Plausible control group: again, the “using gestures” study compared teachers who got something (extra PD; extra curricular materials) with teachers who got nothing (no extra anything).

Measuring the claim: a study claiming that “handwriting helps students learn” didn’t measure learning. (I still can’t get over how many people are citing this study despite this extraordinary flaw.)

So, would this PBL study fall short of these standards?

To be clear — and fair — no study is perfect. Psychology is complicated; teaching is complicated; PEOPLE are complicated. So, I’m not asking that everything be perfect.

But I am asking that the study make a good-faith effort on most of those things.

Envelopes, Please

As a skeptic, I was pleasantly surprised by what I read. Two points stood out in particular:

First: unlike the “gesture” study, the PBL study made an impressive effort to treat teachers in both groups equally.

  • Both groups — not just the PBL group — got extra PD time.
  • Both groups — not just the PBL group — were told that classroom visits were a part of the program.

This kind of care is, in my experience, unusual. I was pleasantly surprised.

Second: the “measurement” sounds (largely) plausible. The researchers did NOT simply make up their own test of the science learning.

Instead, they used the Michigan State standardized test for both the PBL group and the control group. For time reasons, they didn’t use all the questions from that test — so they did have a chance to put that thumb on the scale. But they had less of a chance than if they’d simply created their own test.

Now, don’t get me wrong. I do have some concerns. For instance:

  • Although the teachers in both groups got special treatment, the students didn’t. That is: both groups of teachers got extra PD, but the students in the control group got “same old, same old.” The study would be more persuasive if they too got a new teaching approach.
  • The teachers in both groups got extra stuff, but the teachers in the PBL group got MORE extra stuff. They got more (and more frequent) PD, and more curriculur support, and class visits. (For scheduling reasons, the promised class visits for the control group largely didn’t happen.)
  • As noted above, the research team didn’t exactly use someone else’s measurement — although it seems they made a good-faith effort to do so.

In brief, I can quibble with the study — but I don’t think its flaws merit easy disqualification.

Final Verdict

The research team measured LOTS of variables, and scrupulously tallied scores for MANY important sub-groups and special circumstances.

A student appears to be flying like a superhero in mid-air, but he is actually lying on his side against a dark gray background. He extends one arm forward in a classic "superhero flight" pose, while his legs are bent, creating the illusion of movement. He wears brown pants, a leather belt, and sneakers. The creative perspective and lighting make it look as if he is defying gravity.

If we take the headline number, they found an effect size of 0.277 (technically, “small”) for the amount of additional science knowledge that the students in the PBL group learned compared to the control group.

That is: PBL produced more learning, but not lots-n-lots. We can’t rule out the possibility that all that extra learning resulted from the “shiny new thing,” not from the PBL.

At the same time, my concerns about working memory overload were — at least in this one example — calmed. If this PBL program had overwhelmed WM for these 3rd graders, they wouldn’t have learned much at all; instead, they learned a bit more.

I still have lots of questions and concerns. But I’m heartened to see that — done right — this PBL program offers a potential pathway for further exploration.


Krajcik, J., Schneider, B., Miller, E. A., Chen, I. C., Bradford, L., Baker, Q., … & Peek-Brown, D. (2023). Assessing the effect of project-based learning on science learning in elementary schools. American Educational Research Journal60(1), 70-102.

Doubting My Doubts; The Case of Gesture and Embodied Cognition
Andrew Watson
Andrew Watson

The more time I spend hearing “research-informed educational advice,” the more I worry about the enticing words “research-informed.”

Many MANY people toss around the phrase “research says…”; all too often, even a brief investigation suggests that research really doesn’t say that.

Young girl swinging on a playground swing; a wooden structure behind her

For this reason, I find myself slower to get excited about new “research-based” teaching ideas than many of my colleagues…even colleagues whom I admire, respect, and generally trust.

For instance: lots of scholars are investigating the field of embodied cognition and — more specifically — of using gestures to promote learning.

I’m certainly open to the idea that combining gestures with words and visuals will improve learning. And: I want to know A LOT more about the specifics of this idea:

  • Who is making these gestures? Teachers? Students? Actors in videos?
  • What kind of gestures are they? “Deictic” or”iconic”? Rehearsed or improvised?
  • Does the strategy work well in all disciplines/grades/cultures?

And so forth.

I’d also love to see some straightforwardly convincing research to support the answers to those questions.

So, for instance, I wrote a post about students using gestures to learn about Brownian motion. While the outline of the study made sense to me, it…

… didn’t have a control group,

… chose a topic easily translated into gestures, and

… measured “learning” 2 days later. (Does 2 days count as learning?)

While I’m glad I read the study, and appreciate some of its nuances, I don’t think it’s a slam dunk.

At the same time, I should turn some of my skeptical energy towards myself.

In other words: given all of my doubts, I should also be ready to doubt my own doubtsMaybe the wisdom of the crowd should outweigh my own habitual caution here. Maybe I’m so invested in my skeptic’s persona that I’m subconsciously unwilling to be persuaded…

Enter the Steelman

Because I doubt my doubts, I’m always on the lookout for EXCELLENT research contradicting my outlier point of view. I genuinely WANT to have my errors pointed out to me.

For that reason, I was delighted to find a highly touted study about teaching physics with embodied cognition.

My source here — published by the Educational Endowment Foundation — looks for the very best evidence supporting all sorts of cognitive science-based teaching advice: interleaving, retrieval practice, schemas, and so forth.

Of the 26 studies they found looking at embodied cognition, one stood out for its excellence. (In their rating system, it’s the only only one they rated “high priority.”) If the EEF, and all the wise scholars behind this report, find this study persuasive, it’s likely to be among the best research I can find.

In other words: I’m not analyzing a straw man here. This study is the “steelman.”

Playground Physics

The idea behind this study sounds both sensible and fun. Many of the abstract concepts studied in physics class are acted out quite concretely — that is, they are EMBODIED — when our children get to the playground.

If we could connect abstract classroom physics with embodied playground phyics, that approach could be really helpful.

This study begins with a good idea…and an ENORMOUS sample size. Over 3400 (!) students were in the initial sample; after (unusually high) attrition, that number dropped to about 1300 — roughly 800 in the “playground physics” group, and 500 in the control group.

The researchers wanted to see if the students in the playground group would a) learn more physics, b) feel more engaged, and c) feel more motivated — all compared to the control group.

The special “playground physics” program begins with a training session for the teachers, and includes curricular materials.

Crucially, playground physics also includes a phone app that students use to analyze their own motion:

“Using the app, users record videos of themselves and their friends engaging in physical play, and the app generates graphs of distance traveled, speed, direction, and kinetic and potential energy. As users watch the video, they see graphs of their movement unfolding. Users can pause to examine where they are moving fastest or slowest, where a force is pushing or pulling, and where their kinetic and potential energies are at their highest and lowest points. This is intended to support conversations grounded in the children’s physical experience”

Honestly, the whole experience sound really interesting!

Persistent Doubts

Although I tried to find a Steelman Study to support the case for Team Embodied Cognition, I’m still not persuaded.

I have two substantial concerns:

First:

This study does not measure the benefits of embodied cognition for learning physics.

Instead, it measures the benefits of embodied cognition PLUS cool tech gadgetry for learning physics. In fact, the study is published in a journal that focuses on technology in education.

Yes, the students learned more — but the extra learning could have come from the app (so much fun with video!) or from the embodied cognition (moving is so cool!) or both. We just don’t know.

I am not the only person pointing out this concern. The study’s authors say several times that they don’t know what the “mechanism” is that created additional learning. In other words: they do not claim that the embodiment matter more than the tech — or that it mattered at all. They don’t know.

To be persuaded by research into the use of gestures, I want to see a study that singles out the gestures; it should — in the lingo of research — “isolate the variable.” This one doesn’t.

Second:

When we compare two groups, we want them to be close enough to each other to be good proxies for each other. I’m not sure we can say that for this study.

A) The teachers of Playground Physics received extra PD; the teachers in the control group didn’t. Did the PD itself make the difference? We don’t know.

B) The study used a “business-as-usual control group.” That is: control group teachers just did what they always did. Teachers and students in the Playground Physics group got a Shiny New Thing. Was it the novelty that made the difference? We don’t know.

C) The Playground Physics group spent 15.5 hours studying physics; the control group spent 13.2 hours. The study’s authors write that this difference isn’t “statistically significant.” But — as a classroom teacher — I’m thinking two hours and fifteen minutes of additional practice would be significant, even if it isn’t “significant.” *

Because the study doesn’t isolate the variable (that’s the first concern) and the two groups don’t sufficiently resemble each other (that’s the second concern), I’m still stuck thinking: “this study doesn’t persuade me that embodied cognition is a thing.”

And — as you recall — I looked at this study because a respected group said it’s the best one they found.

TL;DR

I’m still looking for the study that makes the Embodied Cognition approach to teaching persuasive enough for me to recommend it to others.

I haven’t found it yet…but I haven’t given up hope.

By the way: if you know of such a study, please send it my way!


* I spoke with a stats-whisperer friend, who agrees with me that this simply isn’t a reasonable claim.


Margolin, J., Ba, H., Friedman, L. B., Swanlund, A., Dhillon, S., & Liu, F. (2021). Examining the impact of a play-based middle school physics program. Journal of Research on Technology in Education53(2), 125-139.

Teaching & Learning Illuminated by Bradley Busch, Edward Watson, & Ludmila Bogatchek
Erik Jahner, PhD
Erik Jahner, PhD

Teaching and Learning Illuminated_FAW.inddFrom The Science of Learning, Bradley Busch, Edward Watson, and Ludmila Bogatchek have kicked it up a notch in this fresh innovative presentation of Teaching & Learning Illuminated: the Big Ideas Illustrated.

While revamping my college course, I was given this book, and suddenly, prepping felt less like a chore and more like rediscovering the excitement of teaching—like stepping into a bookstore where every title holds the promise of a new perspective. But this isn’t a collection of gimmicks; it’s a book designed to challenge and refine your thinking, helping you sharpen your teaching practice with the most well-supported research. If The Science of Learning is the blueprint, this follow-up book is the user-friendly manual, packed with visuals that make big ideas click. Teaching is a constant process of adapting, and Teaching & Learning Illuminated acts as both a guide and a catalyst, helping you build on your knowledge while freeing your mind to think in new and innovative ways.

What makes this book unique is how it presents information. The graphics aren’t just illustrations; they are well-designed thinking tools that clarify teaching principles backed by decades of research. Each topic is covered in a two-page spread, pairing a full-page visual with a clear, concise explanation. This format simplifies complex ideas while easing the cognitive load, allowing us to imagine how these concepts playout in the classroom. The graphics encourage deeper thinking, serving as both inspiration and a framework for instructional design.

Every illustration invites reflection—from the key takeaways of retrieval, interleaving, and cognitive load theory to Rosenshine’s principles, thinking biases, and fostering motivation and resilience. These visuals do more than convey information; they prompt us to reconsider our approaches and apply insights in new ways.

One of the most practical aspects of this book is how versatile the visuals are. I’ve used them not just for lesson planning but also as quick reference points throughout the day. Even better, the book includes access to high-resolution downloadable posters, which I’ve printed and placed in my workspace. These serve as constant reminders of strategies I want to implement, keeping important ideas at the forefront of my practice.

One of the challenges of learning effective teaching practices is the sheer volume of ways to improve, which can easily lead to analysis paralysis. This book strikes the perfect balance, providing just enough challenge to keep you engaged while offering the right support to help you apply new strategies and explore with confidence.

This book doesn’t just present research-backed insights—it makes them actionable and memorable. The visuals don’t just explain concepts; they stick with you in a way that words alone often can’t. They leave a lasting impression, nudging your thinking in new directions and helping your mind wander constructively.

What stands out most about Teaching & Learning Illuminated is how it refreshes the way we think about teaching. It’s not just another book—it’s a resource that makes cognitive science visible, tangible, and usable. Whether you’re a seasoned educator or just starting to integrate research-based strategies, this book makes it easier to turn theory into practice. It’s insightful, engaging, and a must-have for any educator eager to turn research into real classroom impact and illuminate their practice.

Revisiting the “Handwriting vs. Laptops” Debate: More Moving Goalposts
Andrew Watson
Andrew Watson

I don’t often repost articles, but I think this one deserves another look — for at least two reasons:

First: The study described below has been cited FREQUENTLY in recent weeks, although it really does not merit the confidence that it inspires, and

Second: The study has in fact drawn a strong rebuttal from other researchers in the field.

For both these reasons, I think you’ll find this post worth another look. (I have, by the way, updated  this post to reflect the newly published rebuttal.)


Imagine this conversation that you and I might have:

ANDREW: The fastest way to drive from here to the school is via South Street.

YOU: It is? That seems like a long detour. Why would I go that way?

ANDREW: I didn’t say it was the fastest; I said it was the best because it’s the prettiest.

YOU: You DID say it was fastest…wait, the prettiest? It’s basically junk yards and construction sites.

ANDREW: Yes, but because of all the bakeries, it smells really nice.

YOU: What does that have to do with fastest/prettiest?

ANDREW: Why are you being so unpleasant and difficult? South Street is the best route…

I suspect you would think: “this conversation is very frustrating and unhelpful because the goal posts keep moving.”

That is: I initially claimed that South Street is the fastest…but keep moving my claims as soon as you object. (And, oddly, I’m mad at you for being unreasonable.)

I routinely notice this pattern when I ask questions about the claim that “handwriting is better than laptops for note taking.”

Watch the goalposts move:

CLAIM: Handwriting is better than laptops for note taking. This study says so.

ANDREW: That study starts with the BIZARRE assumption that students can’t learn how to do new things — like, how to take notes correctly. And, research since then has routinely complicated or contradicted it.

CLAIM: I didn’t say handwriting is better because of this study. It’s because writing by hand changes neural networks. This research says so.

ANDREW: You DID make that claim because of that study…wait, that other research says that writing by hand helps students learn to write by hand. Of course it does.

But that doesn’t mean that writing by hand helps students learn other things — like, say, history or chemistry or German. Can you show me research supporting that claim?

CLAIM: I can’t, but when students write on laptops they distract students around them.

ANDREW: Yes, but that’s a completely different claim than the one you started with.

CLAIM: Why are you being so unpleasant and difficult? Writing by hand is better than taking notes on laptops!

Once again, I find this conversation frustrating and unhelpful. SO MANY MOVING GOALPOSTS.

I am entirely open to the idea that handwriting is better. But if someone makes that claim, and says it’s “research-based,” I’d like them to provide research that actually supports the claim.

A bright yellow American football goalpost, above a bright green field and against dark stadium

So far, that turns out to be a big ask.

This idea that “handwriting is better than keyboarding” keeps popping (I suspect because of a recent study), so I want to re-investigate this claim — with a keen eye on those goalposts.

Reasonable Start

If you see a headline that says, “Why Writing by Hand Is Better for Memory and Learning,” you might interpret that claim roughly this way:

Students who take handwritten notes — in their 6th grade history class, say, or their 10th grade science class — remember more of that material after 2 weeks than students who took notes on laptops.

Yes, I conjured up some of those specifics: “6th grade history,” “two weeks later.” But those seem like reasonable extrapolations. What else could the claim substantively mean?

Briefly: plausible goalpost = “students remember more history 2 weeks later.”

So, let’s look at the recent research being used to support this claim.

Here’s a very basic question: “how did the researchers measure how much the students learned and remembered?”

Did the students take a quiz two weeks later? Did they undertake a “brain dump” the following day? How, precisely, do we know what they learned?

The answer is:

The researchers did not measure how much the students learned/remembered.

Honestly. No quiz. No brain dump. Nothing.

And yet, even though the study doesn’t measure memory or learning, it is being used to argue that handwriting enhances memory and learning.

I find this astonishing.

Imagine that I claimed “research shows that this drug will lower your blood pressure!” but I never actually measured anyone’s blood pressure. This study takes a similar logical shortcut.

That is: the study measures activity “in brain regions associated with memory and learning.”

Did you notice something?

Goalpost plausibly was: “students remember more history 2 weeks later.”

Goalpost now is: “more activity in important brain regions.”

Grrr.

Getting Specific

When evaluating “research-based” claims, it’s helpful to know exactly what the participants in the research did.

So, these 36 participants wrote the same fifteen words multiple times. Sometimes they wrote with a stylus on a tablet; sometimes they typed using only their right index finger. (BTW: all the participants were right handed.)

Now, this insistance on “right index finger” makes sense from a neuro-research perspective. If both “handwriters” and “keyboarders” are using one hand, then the researchers reduce lots of confounding variables.

At the same time, this emphasis also leads to highly artificial circumstances.

Presumably some people type with one finger. But, I’m guessing that most people who want to take laptop notes don’t. I suspect they want to take laptop notes because they have some degree of facility on a keyboard.

So:

Goalpost initially was: “students remember more history 2 weeks later.”

Goalpost then was: “more activity in important brain regions.”

Goalpost now is: “more activity in important brain regions when participants write as they usually do than when they type in a really, really unnatural way.”

Double grrr.

It is, of course, helpful to know about these differences in neural responses. But I don’t think they plausibly add up to “students remember more.” Because — remember — no one measured learning.

I Am Not Alone

Since I published the original version of this article almost a year ago, it has been sharply questioned by other scholars in the very same journal.

These scholars describe the original study’s conclusions as “a logical shortcut.” They share my alarm that research which never measured any learning is being used to make strong claims about learning.

They also note we shouldn’t reach an emphatic verdict about grade-school learners based on college-age students:

“Drawing conclusions on learning processes in children in a classroom from a lab study carried out on a group of university students that did not include any type of learning seems slippery at best.” (Exasperated emphasis added)

This rebuttal also expresses technical concerns about the original study’s neuro-conclusions:

While theta and alpha oscillations have been functionally related to a variety of cognitive processes it has not been clearly established that increased theta/alpha connectivity creates appropriate conditions for learning.

I don’t know enough about theta and alpha oscillations to have a strong opinion here — but I think it’s helpful to know that other neuro-experts express reasons to doubt the original study’s confidence.

Lest I Be Misunderstood

In such conversations, I’m often misunderstood to be confident about the right answer. That is: I might seem to be saying “I’m confident that laptops are better than handwriting for learning.”

I am NOT saying that.

Instead, I’m asking for research that directly measures the claim being made.

If I say to you: “research shows that handwriting is better for learning than laptops,” I should be able to show you research that directly measures that claim.

If, instead, I have research showing that handwriting develops neural networks that might be beneficial for learning, I should say that.

My frustration about this point stems from a broader concern.

Over and over, I find that non-teachers cite research — especially neuroscience research — to boss teachers around. While I certainly do believe that teachers should know about pertinent research findings (that’s why I write this blog!), I also believe that we need to acknowledge the limits of our research-based knowledge.

I just don’t think that research (yet) demonstrates that handwritten notes generate more learning than laptop notes.

Overall, I’m inclined to believe:

Practicing fine motor skills (by, say, handwriting) is really important for young learners.

Practicing handwriting makes us better at handwriting — and other word-related skills.

As students get older and more facile with a keyboard, the benefits of handwriting vs. keyboarding will probably depend on the student, the subject, the kind of notes being taken, etc.

And if I see more than one study directly testing the claim that handwriting helps people learn better, I’m entirely open to that possibility.

But at least so far, that claim is not — by any definition that seems reasonable to me– “research-based.”


Van der Weel, F. R., & Van der Meer, A. L. (2024). Handwriting but not typewriting leads to widespread brain connectivity: a high-density EEG study with implications for the classroom. Frontiers in Psychology14, 1219945.

Pinet, S., & Longcamp, M. (2025). Commentary: Handwriting but not typewriting leads to widespread brain connectivity: a high-density EEG study with implications for the classroom. Frontiers in Psychology15, 1517235.

Goals, Failure, and Emotions: a Conceptual Framework
Andrew Watson
Andrew Watson

Researchers can provide guidance to teachers by looking at specific teaching practices.

In last week’s post, for instance, I looked at a study about learning from mistakes. TL;DR: students learned more from review sessions where they explored their own mistakes than those where teachers reviewed ideas.

Or,

Back in December, I looked at a study about using “pre-questions” to reduce mind-wandering. Sure enough, students who answered pre-questions about a topic spent less time mind-wandering than those who didn’t.

Obviously, these studies might provide us with lots of useful guidance.

At the same time, this “one-study-at-a-time” approach has its drawbacks. For instance:

What if my students (or class) don’t really resemble the students (or class) in the study?

What if THIS study says that pre-questions reduce mind-wandering, but THAT study says they don’t?

What if THIS study (again) says that pre-questions reduce mind wandering, but THAT study says that mindful meditation reduces mind-wandering? Which strategy should I use?

And so forth.

Because of these complexities, we can — and should — rely on researchers in another way. In addition to all that research, they might also provide conceptual frameworks that help us think through a teaching situation.

These conceptual frameworks don’t necessarily say “do this.” Instead, they say “consider these factors as you decide what to do.”

Because such guidance is both less specific and more flexible, it might be either especially frustrating or especially useful.

Here’s a recent example…

Setting Goals, and Failing…

We spend a lot of time — I mean, a LOT of time — talking about the benefits of short-term failure. Whether the focus is “desirable difficulty” or “productive struggle” or “a culture of error,” we talk as if failure were the best idea since banning smoking on airplanes.

Of course, ask any student about “failure” and you’ll get a different answer. Heck: they might prefer smoking on airplanes.

After all: failure feels really unpleasent — neither desirable nor productive, nor cultured.

In a recent paper, scholars Ryan Carlson and Ayelet Fishbach explore the complexity of “learning from failure”: specifically, how failure interefers with students’ goals.

To create a conceptual framework around this question, Carlson and Fishbach create two concept pairs.

First: they consider the important distinction between goal setting and goal striving.

Happily, those terms mean just what they say.

When I decide that I want to learn Spanish, or strengthen my friendships, or stop drinking caffein, I am setting a goal.

When I decide to enroll in a Spanish class, schedule more frequent dinners with pals, or purge my kitchen of all my coffee clutter, now I’m goal striving.

This pair helps us think through the big category “goals” in smaller steps.

Second: Carlson and Fishbach consider that both emotional barriers and cognitive barriers can interfere with goal setting and goal striving.

The resulting conceptual possibilities look like this:

A 2x2 grid: with "goal setting" and "goal striving" as two columens, and "emotional barriers" and "cognitive barriers" as two rows.

The grid created by these conceptual pairs allows us to THINK differently about failure: both about the problems that students face, and the solutions that we might use to address them.

Troubling Examples

Having proposed this grid, Carlson and Fishbach explore research into its four quadrants. I’ll be honest, resulting research and insights frequently alarmed me.

For instance, let’s look at the top-left quadrant: “emotional barriers during goal setting.”

Imagine that one of my students contemplates an upcoming capstone project. She wants to set an ambitious goal, but fears that this ambitious target will lead to failure.

Her emotional response during  goal setting might prompt her to settle for an easier project instead.

In this case, her emotional response shuts down her thinking before it even started. As Carlson and Fishbach pithily summarize this situation: “people do not need to fail for failure to undermine learning.”

YIKES. (Suddenly, the whole “desirable difficulties” project sounds much less plausible…)

Or, top right (emotional barriers/goal striving): it turns out that “information avoidance” is a thing.

People often don’t want to learn results of medical tests — their emotions keep them from getting to work solving a potential health problem.

So, too, I can tell you from painful experience that students often don’t read the comments on their papers. When they’re disappointed with a grade, they don’t consistently react by considering the very feedback that would help them improve — that is, “strive to meet the goal of higher grades.”

Or, lower right (cognitive barriers/goal striving). Carlson and Fishbach describe a study — intriguingly called “The Mystery Box Game.”

Long-story short: in this game, learning how to fail is more beneficial than learning about one path to success. Yet about 1/3 of participants regularly choose the less beneficial path — presumably because “learning how to fail” feels too alarming.

Problems Beget Solutions?

So far, this blog post might feel rather glum: so much focus on failure!

Yet Carlson and Fishbach conclude their essay by contemplating solutions. Specifically, they use a version of that grid above to consider solutions to the cognitive and emotional barriers during goal setting and goal striving.

For example:

  • “Vicarious learning”: people learn more from negative feedback when it’s directed at someone else.
  • “Giving advice”: counter-intuitively, people who give advice benefit from it at least as much as those who receive it. So, students struggling with the phases above (say: cognitive barriers during goal striving) might be asked for advice on how to help another student in a similar situation. The advice they give will help them.
  • “Counter-factual thinking”: students who ask “what if” questions (“what if I had studied with a partner? what if I had done more practice problems”) bounce back from negative feedback more quickly and process it more productively.

Because I’ve only recently come across this article, I’m still pondering its helpfulness in  thinking about all these questions.

Given the optimism of “desirable difficulty/productive struggle” in our Learning and the Brain conversations, I think it offers a helpful balance to understand and manage these extra levels of realism.


Carlson, R. W., & Fishbach, A. (2024). Learning from failure. Motivation Science.

“Learning from Mistakes” vs. “Learning from Explanations”
Andrew Watson
Andrew Watson

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).

A closeup of a young student leaning his face up against a chalkboard, his eyes closed in frustration.

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.

“All People Learn the Same Way”: Exploring a Debate
Andrew Watson
Andrew Watson

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.)

A graphic of two heads facing each other in conversation: one with a lightbulb inside, the other with a question mark.

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.