A friend said to me recently, “my LinkedIn is covered with references to the science of learning, you must feel so proud!”. She was thus surprised to learn that, much like my friend and collaborator Dylan Kane, lately I fall somewhere between ambivalence to concern regarding the increasing use of “SoL” in the education discourse.
Is this just my natural contrarianism? Possibly, possibly. But for reasons we’ll get to, as much as anyone I bear responsibility for popularizing the term “the science of learning,” and nowadays I see it being invoked in ways that bear little to no resemblance of what I intended. It’s become a buzzword. And while I find a small measure of satisfaction that many feel the need to nod in the direction of using scientific insight to inform education practice and policy, we’ve reached the point where SoL can mean just about anything, which is to say, it is verging on meaning nothing.
This irritates me. When my friend Audrey Watters warns us to beware of anything stylized as “Science of ___” in education because it smacks of scientism, I feel nails grating across my mental chalkboard—not because she’s wrong per se, but because I still cling to the belief that there’s value in promoting the science of learning in education…but if and only if we distinguish the useful forms of the idea from the myriad mutations of it floating about.
And so, I hereby present my taxonomy of the science of learning, in similar format to the taxonomy of AI skepticism I published. The same caveats I offered in that essay apply here as well: first, this represents my individual perspective on the science of learning, I am not trying to provide a comprehensive, “objective” summary of the entire landscape. Some of you will no doubt be familiar with versions of SoL and its advocates that aren’t covered here; please share your examples in the comments. Second, there’s a ton of overlap here, and some folks named here may object to where I’ve placed them—I beg your forgiveness in advance, but that’s also the fun of making one’s own taxonomy, I get to be the decider.
All that said, let’s get to it.
1. The Science of Learning comprises a set of cognitive principles about how we think and learn that can be connected to specific teaching practices.
Summary: This version of SoL is deeply grounded in cognitive science, and specifically, a (simple) model of the mind that centers the relationship between information we pay attention to, working memory, and long-term memory. These principles imply that, as a general matter, there are certain teaching practices that can help foster student learning and build durable knowledge.
Layer of nuance deeper: On the science side of things, the cognitive aspect of this cannot be overstated, by which I mean, the emphasis here is on the mind (not the brain) and mental states (not neural or biological activity). On the pedagogical side, supporters of this version of SoL are wary of promoting any specific pedagogical theory to the exclusion of any others; the perspective instead is that there are some favored practices that should be part of every teacher’s pedagogical toolkit.
As the person who founded Deans for Impact and decided to make its very first programmatic activity publishing a document called The Science of Learning—recently updated by the way, check it out here—this is my tribe.
Exemplars: Dan Willingham; Daisy Christodolou; Dylan Kane; Deans for Impact (yes, that’s lot of “Ds”); Blake Harvard
Critiques: Over the years, the most frequent critique I’ve heard directed at this version of SoL is that it only addresses a small sliver of the realities of day-to-day classroom teaching. Fair enough, but make sure to check out version two below.
On the theory side of things, Christian Moore-Anderson has raised interesting questions about whether the simple model of the mind overly fixates on the “mind as computer” metaphor, and thus neglects important concepts such as meaning. (I have an essay in progress on this very topic coming soon.)
2. The Science of Learning is a set of research-supported instructional moves.
Summary: This version of SoL is focused on providing teachers with a detailed set of specific pedagogies to employ across all (or nearly all) aspects of their teaching.
Layer of nuance deeper: A close cousin to the first version of SoL above, the primary difference here is the emphasis on providing educators with more granular guidance on managing their classrooms, from the entry routines when students come into class to the exit tickets collected at the end. The folks in this group typically cite Willingham and other cognitive scientists for general support, but place less emphasis on cognitive processes.
Exemplars: Steplab; Barak Rosenshine (and his principles of instruction); Doug Lemov
Critiques: One challenge to this approach is that teachers may learn specific “moves” without understanding the why behind them, leaving them ill-equipped to adapt specific pedagogies to their unique classroom contexts. Another is that while it may prove useful for initial teacher preparation and the professional development of novice teachers, it can feel reductionist to veteran educators.
3. The Science of Learning is Cognitive Load Theory.
Summary: This version of SoL centers John Sweller’s Cognitive Load Theory as the foundational description of how students learn.
Layer of nuance deeper: As its name would suggest, the focus of CLT is on the severe limitations of our working memory—that is, our inability to handle more than a few small pieces of information at any one time (“cognitive overload”). For more on this, Michael Pershan (him again) recently re-published his comprehensive overview of CLT and its ongoing evolution as a theory of learning.
Exemplars: Well, John Sweller of course; Greg Ashman (maybe?)
Critiques: First, go read that Pershan essay—among other things, he observes that the first wave of CLT largely neglected the role of attention in learning. I also think the name “cognitive load theory” confuses many, because people without a strong background in this area hear the word “cognitive” and therefore think CLT encompasses all of cognitive science (I’ve seen a prominent political advocate for the science of learning make this mistake).
4. The Science of Learning is the justification for traditional teaching aka explicit instruction.
Summary: Supporters of this version of SoL maintain that the most effective way to teach students is through explicit instruction regarding to the content a teacher wants them to learn. Put simply, “just tell them.”
Layer of nuance deeper: Over in England, the pedagogy of teacher-stands-in-front-and-lectures is described as “traditional” teaching, and in contrast with so-called “progressive” or “inquiry” based—more about that in the next section. But the basic idea here is that teachers are in fact “sages on the stage” rather than “guides on the side,” and that therefore they shouldn’t shy away from lessons that involve showing students “what they’re meant to learn, what it is, how to do it, and get everyone to practice it a lot.”
(Explicit instruction is sometimes referred to as direct instruction, which gets confusing because there also is a very specific pedagogy called Direct Instruction (DI). For more on DI, read this by Dylan Kane.)
Exemplars: Zack Groschell (author of the book Just Tell Them); Michaela School (England)
Critiques: Oh there are many. For one thing, any experienced teacher knows that there’s only so much time one can spend lecturing on a subject before kids will tune out. For another, it’s often not clear to me whether or how advocates of explicit instruction think about to ensure students can transfer their knowledge to novel situations. There’s also Dan Meyer’s pointed contention, which I agree with, that the debate on explicit/direct instruction versus inquiry-based teaching is mostly fetishized by the “online commentariat,” and that practicing teachers have little time or interest in hopping into the fray.
5. The Science of Learning is the justification for center-right education policy.
Summary: Originating in England and now with a few outposts around the globe, this version of SoL contains a medley of education policies that have proven enduringly popular with center-right politicians, usually involving at least these three things: phonics instruction, adopting a knowledge-rich curriculum, and explicit instruction.
Layer of nuance deeper: The intellectual godfather of this effort is E.D. Hirsch, who claims to be a political liberal (by US standards) but an “educational conservative” who opposes “progressive educational ideals” because they are ineffective. Nick Gibb, a huge fan of Hirsch who served as Schools Minister in England, describes the “progressive ideology” as including “constructivism, discovery learning, [and] project work,” pedagogies he argues are mistaken because they promote the idea “that the child has agency in the classroom.”
Exemplars: Nick Gibb (England); Erika Stanford (New Zealand); Paul Givan (Northern Ireland); Robert Pondiscio (USA)
Critiques: One glaring problem with this version of SoL is that it sets up an imaginary strawman called “progressive education” that does not resemble any classroom I’ve ever observed in reality. Another is the obvious political challenge of the SoL becoming “right coded,” a problem that has vexed me for over a decade—more on this later. And, uh, good luck with selling parents on the idea that their kids should be deprived of agency in the classroom.
6. The Science of Learning has something to do with neuroscience.
Summary: This version of SoL focuses on features of the brain (rather than the mind) and the underlying biological processes related to brain activity.
Layer of nuance deeper: Honestly, I can’t give you much here, because I don’t think teachers need to know much of anything about how the brain functions (see critique below). What’s more, many of the actors in this space say or produce things ranging from misleading to incomprehensible.
Exemplars:
Here’s YouCubed suggesting that its favored approach increases “brain activity,” which is true of anything that makes you think:
Here’s a claim by SETA ED that neuroscience reveals that every child is learning every second of every day, which isn’t true, followed by the bizarre conclusion that this mean we need not teach children how to learn.
Here, the Human Potential L.A.B. offers a supposedly scientific “causal chain of capability” that is completely mystifying.
And finally, we arrive at the “Global Brain Economy Initiative” suggesting we need to invest in “brain health” to thereby mobilize “brain capital” in order to build the “brain economy.” All of which makes my brain hurt.
Critiques: Look, my dad was a neuroscientist, I have many friends who are neuroscientists, neuroscience is absolutely fascinating to me (and I’ve written about it), and I think it has next to nothing to do with the realities of classroom teaching. In the same way that you don’t need to know how the internal combustion engine works in order to drive a car, you don’t need to know anything about the cerebellum to effectively teach kids. As Dan Willingham once said, the notion that teachers need to understand neuroscience “strikes me as a colossal waste of teachers’ time.” Beware the many grifters in this space.
7. The Science of Learning is [insert ed-tech product here].
Summary: Impossible, because the range of claims made here are vast.
Layer of nuance deeper: In its best form, the basic idea here is that ed-tech products should be designed and deployed in ways that harmonize with principles of cognitive science. Unfortunately, however, SoL and “learning science” are often invoked by ed-tech vendors and proselytizers as marketing tools.
Exemplars:
(OpenAI)
(Google)
And we’ll get to Alpha School, don’t you worry.
Critiques: Feel free to peruse the back catalog of this newsletter over the past two years. Google has not “infused the science of learning into Gemini,” because you cannot fuse principles of human cognition into a tech product. But you sure can try to hornswoggle people into believing this form of “science” supports what you’re trying to sell.
You’d think after 2,000 words of taxonomizing we might be done here, but there are some important SoL-related things that I couldn’t figure out how to shoehorn into the above format. So here’s a bonus FAQ!
What’s the relationship between the Science of Learning and the Science of Reading?
In its best form, the Science of Reading (SoR) might be thought of as a “subfield” within SoL. Our ability to learn to read and write is one of the most incredible cognitive accomplishments of our species, and we really have developed genuine scientific insight into how this happens. “Ending the Reading Wars: Reading Acquisition from Novice to Expert,” by Anne Castles, Kathleen Rastle, and Kate Nation provides an accessible and comprehensive summary of the relevant science, and has been one of my go-to resources for years.
But then there’s the Science of Reading as the name for a certain camp within the broader and seemingly perpetual “Reading Wars.” A great deal has been written about this already, including by yours truly several years ago, so I’m not going to wade back in now. In my essay, however, I quoted Rachael Gabriel, a reading expert at UConn, with this insightful observation:
There is a wide divide between political debates about the teaching of reading and the actual instruction students receive in classrooms. The sloppy, mudslinging nature of these debates has led to confusion, distrust and a tribe-like affiliation with single approaches among practitioners, researchers and policymakers.
There is resistance to reading mandates in both directions. “Scientific research” — sometimes the very same studies — is used to argue both sides. Philosophical differences are frequently acknowledged, but rarely understood. Like different denominations of a single religion, different approaches to reading instruction often have significant assumptions in common, but some core disagreements that each believes is the fatal flaw of the other and the reason to dismiss it completely.
I’m still nodding. More recently, Michael Pershan—good lord, again?—offered similar observations explaining why Emily Hanford was Basically Wrong. Zing!
Is there a Science of Math? A Science of Behavior? A Science of Every Other Subject?
I don’t think so, at least in the Kuhnian sense of “normal science” with established paradigms across these domains. That may change in the future, of course, and I’m all for continued efforts that help connect education research to teaching practice. But there’s still much work to be done to get basic cognitive principles into the education profession, so perhaps we should focus our attention on that first.
Why did the Science of Learning get such good traction in England?
Good news, Greg Toppo at The 74 already wrote the definitive story about this. Basically, there was an interesting confluence of grass-roots teacher interest in cognitive science (fueled in part by Twitter and a recurring series of in-person conferences called ResearchED), as well as policymakers with real power driving change to frameworks and the like. For more, Nick Gibb’s book Reforming Lessons goes deep into the weeds, though as noted above he continually attacks a strawman “progressivist ideology” that I find counterproductive to building a movement beyond the center-right.
Are there policymaking advocates for the Science of Learning on the political left?
Sigh. If there are, I’ve struggled to find them—and believe me, I’ve looked. For some, this is reason alone to dismiss the science of learning, which I understand but find tragic.
There are glimmers of hope. My friend and former colleague Callie Lowenstein invokes terms such as “cognitive justice” and “the science and social justice of reading” that make me swoon. I’ve never met Eric Liu, but his 2015 essay on building a common cultural literacy in the US (per Hirsch) but one that reflects our true diversity is another example of left-coded science of learning. More recently, my good friend and collaborator Pip Sanderson invoked the term Cognitive Solidarity, a concept that Dylan Kane and I have been batting around too, to hint at a future where we focus more on how our cognition develops socially through the little social experiments we call classrooms.
If education philanthropy wasn’t such a broken mess right now, with an ongoing collective myopia on how to build sustainable social change, this would be a good thing for it to be funding.
What’s the deal with Alpha School hiring a bunch of science of learning advocates?
Ugh. Ugh ugh ugh ugh ugh ugh.
So, to start, I’m not sure what more can be done at this point to derail the Alpha School hype train. We’ve got 404 Media’s expose of Alpha School “treating students like guinea pigs” and using AI to generate incoherent lessons. We’ve got the Wired story of families abandoning its Brownsville, Texas campus in droves, while expelling other kids for failing to make sufficient academic progress, oh and also getting kicked off IXL for violating its terms of service. And, as of last week, we now have Dan Meyer’s expose of Alpha School’s charter school in Arizona, which is completely and utterly failing to meet its stated goals for student learning.
Because I love irony, I used AI to help me create these complex graphic representations of the data that Meyer uncovered:
Against this backdrop of incompetence, over the last year or so Alpha School started to contract with prominent learning science advocates, including Carl Hendrick, Becky Allen, and Zach Groshell. Here is how Hendrick describes what they’re up to:
I am currently working with an amazing group of learning scientists and developers at Alpha School…to solve the problem of designing adaptive learning systems that honour rather than violate the instructional invariants, that treat cognitive constraints as design specifications rather than obstacles to user experience. The challenge is considerable, but so is the opportunity. I am cautiously optimistic. The invariants do not care whether instruction comes from a teacher or an algorithm; they care only that the conditions for learning are met. A set of apps that meets them could be potentially transformative.
Could be, could be. The problem, however, is that actual human children—as opposed to whatever “instructional invariants” are supposed to describe—very much do care whether their instruction comes from a human teacher or an algorithm. Deep down, even folks at Alpha School know this, given that they literally pay students in cash money to get them to go through their two hours of digital device usage learning every day.
Which just goes to show that you can get both adults and kids alike to say or do just about anything if you give them enough money.
My thanks to those who helped me compile this taxonomy—and thanks to all of you for subscribing and reading. If you made it all the way here, you deserve a prize—and hey, Cognitive Resonance the Newsletter just passed 5,000 subscribers. Time for another mailbag! If you have questions about AI, human cognition, education, or life, the universe, everything, please send ‘em my way at info@cognitiveresonance.net.
I appreciate your sharing these concerns and clarifications, because I think there is a very big risk that we could see a policy push to mandate "SoL Approved Methods™" similar to what we've seen with the "science of reading." You mentioned what happened with England under the previous Tory government, but it's also happening right now in Australia in an even more intensified form.
I tend to be more critical of many of the SoL folks, not because cognitive load theory and direct instruction are bad, wrong, etc. but because many of their proponents act as though they are the definitive, settled science about how humans learn instead of a collection of useful theories from cognitive psychology. I think a much healthier term would be the "learning sciences" to account for the fact that there are a lot of fields that offer insight into how people learn beyond the incredibly narrow slice of cognitive science these folks are drawing on. Rather ironically, I've spoke to several cognitive scientists who were completely gobsmacked (and quite annoyed!) that folks like Ashman, Groschell, etc. are framing their work as supported by cognitive science.
You might find my conversation with Christian Moore-Anderson interesting, as both of us had a similar experience with the movement; initially, we were excited at the prospect of promoting research informed teaching, but quickly realized that there was more interest in brand loyalty and canonizing a handful of researchers/theories, than actually pursuing a rich understanding of all the worthwhile scholarship on teaching and learning.
https://trevoraleo.substack.com/p/christian-moore-anderson-talks-teaching
Good post. I have lots of thoughts and agree with most of this - first off, I think it's true that teachers do not need to completely understand the neuroscience of the brain in order to teach well. Despite this, over my 30+ year career we have had more than one PD day devoted to folks who have claimed to "crack the code" on applying neuroscientific principles to teaching - just in the past few years, we had the guy who wrote Neuro Teach - Brain Science and the Future of Education - which is probably a perfect example of this trend. I liked the guy, he gave some helpful tips (happy to share the stuff he gave us) and most veteran teachers nodded along - most of this stuff we were doing anyway but there were some interesting and helpful suggestions. I can't say though they remained top of mind as I went about designing my lessons over the years since his visit. But on the larger point, the "Science of Learning" has changed so much over the course of my career that's its easy to dismiss some of it as flavor of the month (remember Learning Styles? - completely debunked as far as I am aware). On direct instruction, as a content guy, I think kids need to "know stuff" in order to both read well and do activities. Asking students to write on a topic in which they know nothing about, unless it's for a baseline sense of where kids are, is pretty pointless. Having kids "teach each" in paired or group activities when they know next to nothing or haven't been assigned material, is also a waste of time. I've had parents (and kids) say to me why do I want my class mates to peer edit my work if they a) don't know how to write to begin with and b) don't know how to edit. This is where I do think AI has some potential but it's challenging. And, on Alpha school, my take is they are trying to game a system they did not create but dictates almost every metric by which outside forces evaluate school effectiveness - test scores. What do test scores primarily measure? Reading comprehension and math fluency. That's pretty much it - they design activities that boost kids abilities in those areas, push for mastery (essentially through bribes), and you can tout superior results. My major take on Alpha is they either don't buy into or think it's important to emphasize a lot of the rhetoric around learning that the average teacher expresses about the importance of their subject matter. If a kid goes from 2nd grade to 3rd grade and has not mastered the basics of the curriculum - whether that's reading or math - does it matter if they "love learning" or "work well with others"? Most teachers would say "of course it does!" - Alpha would say (despite their marking materials on "loving school") not if they can't do the basics. As a parent, I want both, but candidly, I want them to know how to do the skills, right? Anyway, longer than I intended, but the post hit a nerve - in a good way! - because we constantly get introduced with "the SoL" and then, as a veteran teacher, we mostly go back to teaching either a) the way we were taught or b) pick up on the tips and suggestions that resonate and actually work once we try them in the classroom. The two best PDs I've ever done is one on the social-emotional reality of MS students by Michael Thompson (nothing to do with the SoL per se, but everything to do with how MS kids actually experience the world) and my two separate 2-week stints at HGSE on Project Zero. Those were deep dives with some really lasting frameworks, including (TfU) - teaching for understanding - which is basically their version of UbD, the Wiggins and McTighe framework. Last - on reading, I wrote about this a few weeks ago - hardly an expert, but having taught, watched, and been a reader all my life, it's such an essential skill that we ignore it at our peril. Nice work, Ben! More to come ...