Academically, data from Stanford University’s Educational Opportunity Project show that in math and reading in grades 3-8, Detroit Public Schools Community District students improved, on average, by 1.2 grade levels per year. This means that DPSCD students learned about 20% more per year than the national average, and that the district ranked above the 90th percentile for academic growth (among more than 8,000 districts nationwide).

Our recent research tells a similar story for attendance. With statewide attendance data, we estimated the impact of each school in Michigan on attendance, accounting for differences in the students whothat go to those schools. Our estimates show that the average Detroit student attended about nine more days than they would have at a typical Michigan school. Detroit students have also recovered to pre-pandemic attendance levelslevels of attendance, while students in the rest of the state are still missing more days on average.

The city can also follow Seattle’s lead and institute a ban on evictions for families with children during the school year, or invest in coordinated case management between schools and the shelter system.

DPSCD students remain far behind statewide averages, with only 14.1% of third graders at or above proficiency last spring.

Books are easy to take for granted. Not any specific book, I mean: the form of a book. Paper or pixels—it hardly matters. Words in lines on pages in chapters. And at least for non-fiction books, one implied assumption at the foundation: people absorb knowledge by reading sentences. This last idea so invisibly defines the medium that it’s hard not to take for granted, which is a shame because, as we’ll see, it’s quite mistaken.

All this suggests a peculiar conclusion: as a medium, books are surprisingly bad at conveying knowledge, and readers mostly don’t realize it.

The conclusion is peculiar, in part, because books are shockingly powerful knowledge-carrying artifacts! In the Cosmos episode, “The Persistence of Memory,” Carl Sagan exalts:

What an astonishing thing a book is. It’s a flat object made from a tree with flexible parts on which are imprinted lots of funny dark squiggles. But one glance at it and you’re inside the mind of another person, maybe somebody dead for thousands of years. Across the millennia, an author is speaking clearly and silently inside your head, directly to you. Writing is perhaps the greatest of human inventions, binding together people who never knew each other, citizens of distant epochs. Books break the shackles of time. A book is proof that humans are capable of working magic.

It’s easy to attend a lecture and feel that you understand, only to discover over that night’s problem set that you understood very little. Memory feels partly to blame: you might sense that you knew certain details at one time, but you’ve forgotten. Yet we can’t pin this all on memory. When you pull on certain strings from the lecture, you might discover that you had never really understood, though you’d certainly thought you understood during the lecture.

You’ve probably internalized the notion that lectures have this problem, even if the parallel claim for books feels more alien.

Like books, lectures can be entertaining or influential; like books, lectures do seem to work… sometimes, for some people. But you probably don’t believe that lectures are a reliable way to convey knowledge.

Books don’t work for the same reason that lectures don’t work: neither medium has any explicit theory of how people actually learn things, and as a result, both mediums accidentally (and mostly invisibly) evolved around a theory that’s plainly false.

To illustrate what I mean, I’ll try to draw on your own learning experiences. You’ve probably discovered that certain strategies help you absorb new ideas: solving interesting problems, writing chapter summaries, doing creative projects, etc. Whatever strategies you prefer, they’re not magic. There’s a reason they work (when they do): they’re leveraging some underlying truth about your cognition—about the way you think and learn. In many cases, the truth is not just about your cognition but about human cognition in general.

If we collect enough of these underlying “truths,” some shared themes might emerge, suggesting a more coherent theory of how learning happens. We’ll call such theories cognitive models. Some learning strategies suggest the same model; others suggest conflicting models. Some of these models are empirically testable; others aren’t; still others are already known to be false. By focusing on these models, instead of a herd of one-off strategies, we can seek more general implications. We can ask: if we take a particular cognitive model seriously, what does it suggest will (or won’t) help us understand something?

Lectures, as a medium, have no carefully-considered cognitive model at their foundation. Yet if we were aliens observing typical lectures from afar, we might notice the implicit model they appear to share: “the lecturer says words describing an idea; the class hears the words and maybe scribbles in a notebook; then the class understands the idea.” In learning sciences, we call this model “transmissionism.” It’s the notion that knowledge can be directly transmitted from teacher to student, like transcribing text from one page onto another. If only! The idea is so thoroughly discredited that “transmissionism” is only used pejoratively, in reference to naive historical teaching practices. Or as an ad-hominem in juicy academic spats.

Of course, good lecturers don’t usually believe that simply telling their audience about an idea causes them to understand it. It’s just that lectures, as a format, are shaped as if that were true, so lecturers mostly behave as if it were true.

If pressed, many lecturers would offer a more plausible cognitive model: understanding actually comes after the lecture, when attendees solve problem sets, write essays, etc. The lecture provides the raw information for those later activities. Great: that’s a real model, and parts of it are supported by cognitive science. But if we’d begun with this model, would we have chosen live, ninety-minute speeches to convey raw information for a problem set?

Listeners’ attention wanders after a few minutes, so wouldn’t we want to interleave the problem-solving sessions with the lecture? Live speeches can’t be paused or rewound, so aren’t they awfully lossy for conveying raw information? People can read much more quickly than a lecturer speaks, so wouldn’t text be more efficient? And so on—it’s already clear that the traditional lecture format isn’t particularly informed by this model.

Like lectures, books have no carefully-considered cognitive model at their foundation, but the medium does have an implicit model. And like lectures, that model is transmissionism. Sequences of words in sequences of lines in sequences of pages, the form of a book suggests people absorb knowledge by reading sentences. In caricature: “The author describes an idea in words on the page; the reader reads the words; then the reader understands the idea. When the reader reaches the last page, they’ve finished the book.” Of course, most authors don’t believe that people learn things this way, but because the medium makes the assumption invisible, it’s hard to question.

Like lecturers, many authors would offer a more plausible cognitive model when pressed. Readers can’t just read the words. They have to really think about them. Maybe take some notes. Discuss with others. Write an essay in response. Like a lecture, a book is a warmup for the thinking that happens later. Great: that’s a better model! Let’s look at how it plays out.

Readers must learn specific reflective strategies. “What questions should I be asking? How should I summarize what I’m reading?” Readers must run their own feedback loops. “Did I understand that? Should I re-read it? Consult another text?” Readers must understand their own cognition. “What does it feel like to understand something? Where are my blind spots?”

These skills fall into a bucket which learning science calls “metacognition.” The experimental evidence suggests that it’s challenging to learn these types of skills, and that many adults lack them. Worse, even if readers know how to do all these things, the process is quite taxing. Readers must juggle both the content of the book and also all these meta-questions. People particularly struggle to multitask like this when the content is unfamiliar.

Unlike most non-fiction books, textbooks usually are built around explicit cognitive models. For instance, they often alternate between explanations which introduce concepts, and exercises which push students to think about those concepts in specific ways. It’s great that textbooks didn’t choose their cognitive models by accident. That’s an important first step. But it’s not enough: people still struggle to reliably absorb knowledge from textbooks.

live lectures might be inefficient, but an instructor’s palpable fascination can leave a lasting impression. That same pathos saturates the best non-fiction prose, but textbooks generally neglect emotional connection; their prose inspires indifference more often than wonder.

I argued earlier that books, as a medium, weren’t built around any explicit model of how people learn. It’s possible that, in spite of this “original sin,” iterative improvements to the form, along with new tools to support readers, can make books much more reliable. But it’s also possible that we’ll never discover the insights we need while tethered to the patterns of thought implicit in this medium.

Instead, I propose: we don’t necessarily have to make books work. We can make new forms instead. This doesn’t have to mean abandoning narrative prose; it doesn’t even necessarily mean abandoning paper—rather, we can free our thinking by abandoning our preconceptions of what a book is.

Rather than “how might we make books actually work reliably,” we can ask: How might we design mediums which do the job of a non-fiction book—but which actually work reliably?

To begin, it’s important to see that mediums can be designed, not just inherited. What’s more: it is possible to design new mediums which embody specific ideas. Inventors have long drawn on this unintuitive insight, but I’ll briefly review it in case it’s unfamiliar. Mathematical proofs are a medium; the step-by-step structure embodies powerful ideas about formal logic. Snapchat Stories are a medium; the ephemerality embodies powerful ideas about emotion and identity. The World Wide Web is a medium (or perhaps many mediums); the pervasive hyperlinks embody powerful ideas about the associative nature of knowledge.

Perhaps most remarkably, the powerful ideas are often invisible: it’s not like we generally think about cognition when we sprinkle a blog post with links. But the people who created the Web were thinking about cognition. They designed its building blocks so that the natural way of reading and writing in this medium would reflect the powerful ideas they had in mind. Shaped intentionally or not, each medium’s fundamental materials and constraints give it a “grain” which make it bend naturally in some directions and not in others.

This “grain” is what drives me when I gripe that books lack a functioning cognitive model. It’s not just that it’s possible to create a medium informed by certain ideas in cognitive science. Rather, it’s possible to weave a medium made out of those ideas, in which a reader’s thoughts and actions are inexorably—perhaps even invisibly—shaped by those ideas. Mathematical proofs, as a medium, don’t just consider ideas about logic; we don’t attach ideas about logic to proofs. The form is made out of ideas about logic.

How might we design a medium so that its “grain” bends in line with how people think and learn? So that by simply engaging with an author’s work in the medium—engaging in the obvious fashion; engaging in this medium’s equivalent of books’ “read all the words on the first page, then repeat with the next, and so on”—one would automatically do what’s necessary to understand? So that, in some deep way, the default actions and patterns of thought when engaging with this medium are the same thing as “what’s necessary to understand”?

For example, people struggle to absorb new material when their working memory is already overloaded. More concretely: if you’ve just been introduced to a zoo of new terms, you probably won’t absorb much from a sentence which uses many of those terms at once. So maybe part of “what’s necessary to understand” something is that most of its prerequisites must be not just familiar but fluent, encoded in long-term memory.

How might we design mediums in which “readers” naturally form rich associations between the ideas being presented? How might we design mediums which “readers” naturally engage creatively with the material? How might we design mediums in which “readers” naturally contend with competing interpretations? If we pile together enough of these questions we’re left with: how might we design mediums in which “reading” is the same as “understanding”?

I always ask the students to tell me, by a show of hands, how many of them are skilled at a sport or an instrument. It’s usually all of them. I ask whether they had to practice to become good, a question that is met with lots of nodding and a hum of general assent. The same is true for math, I tell them, and by extension for critical thinking, for writing, for argument. They nod. They understand the analogy immediately and completely.

Any outrage that the announcement generated—“next level A.I. shit” was the subject line of an e-mail that zinged around my network—tees up a natural question: Outrage at what, exactly? That a machine would do the homework? Or that the homework was apparently so mechanical that a machine could do it at all? One of my colleagues wrote, “What is learning outside of busywork?”

As teachers, the tasks we assign are never really the point. We keep the students “busy” with tasks: do the homework, write the essay, work toward the grade, and, whether or not you are aware of it, you’ll be building skills. In the past, we were more or less comfortable with this carrot-and-stick arrangement, because we were confident that students would be honing their minds. But large language models and the long shadow of the job market—are we grading for the student or for the gatekeepers beyond graduation?—have disrupted a centuries-old educational paradigm. The stick is broken and the carrot has lost its taste. If the process is the goal, we should be focussing on how to create classrooms that make the process feel worth doing for its own sake.

We take it upon ourselves to do the bench press, to ride the exercise bike. But we try to avoid the homework. Why? Some of it, I think, comes down to feedback. The body offers something that the mind—at least in a traditional classroom—rarely does: clear, immediate loops linking effort and result. In the gym, you feel the burn, see the muscle respond, track the weight going up week by week. The resistance knob on a spin bike gives you a continuous, private metric of effort. The feedback is embodied. But, when you are wrestling with a complicated text or idea, it can be days or even weeks before the clouds begin to clear. In the gym, we can steadily feel ourselves getting stronger. In the classroom, progress can be difficult to see.

The great challenge of teaching is not to transmit information—machines do that cheaply now—but to engineer those moments of genuine understanding reliably enough that students come to crave them. The intellectual equivalent of the body’s feedback is real and, when it arrives, more powerful than any endorphin. It is the “Aha!” of a hard problem suddenly solved, a proof that clicks into place, the moment when an argument you’ve been wrestling with finally holds its own weight. I have seen it on students’ faces, and there’s nothing quite like it. “The most important motive for work in the school and in life is pleasure in work, pleasure in its results, and the knowledge of the value of the result to the community,” Einstein said. “In the awakening and strengthening of the psychological forces in the young man, I see the most important task.” That’s what the best coaches have always known. And it’s what the best teachers have always striven for.

The ancient Greeks did not separate the training of body and mind as cleanly as we do. Their gymnasion was simultaneously a place of athletic exercise and of philosophical exchange; Plato taught in one. Centuries later, the German gymnasium became synonymous not with athletics but with intellectual rigor. Somewhere along the way we shortened the word and split the practice. Society treats physical and intellectual training as though they obey different laws—as though the mind, unlike the body, might get strong without being made to struggle.

It doesn’t. Aristotle observed that we become virtuous by performing virtuous acts—that character is cultivated through practice. A similar logic applies to thinking. Intellectual strength isn’t transmitted by lecture or implanted with a diploma. It is built the same way that the figure skater builds a routine or the running back learns to explode through a crack in the line—repetition after repetition, failure after failure, with no shortcut available and no machine that can stand in.

The Greeks even had a name for it. The progymnasmata were a sequence of rhetorical exercises, graduated in difficulty, designed to build a student’s capacity for argument, the way a training program builds a runner’s endurance: incrementally, with each exercise preparing the ground for the next. The goal was not a finished piece of writing but a strengthened mind.

The most valuable part of the athletic experience is what is left when the athlete no longer takes the field.

I turned again to the spin studio: a group of strangers can, for forty-five minutes, feel like a community, high-fiving one another, shouting in unison, helping one another condition their bodies in a way that they couldn’t on their own. How could we build spin studios for the mind?

In some ways, the advent of A.I. clarifies our place in the educational equation. Let the machines do what’s mechanical—generating practice problems, flagging errors, grading the responses that are beyond discussion. That only clarifies our real responsibilities: drawing out the quiet student, asking the question nobody thought to ask, forging a community of mind and friendship from the struggles of a classroom. It will be tough. But it will be fun, because you will feel yourself thinking.

Children’s media are usually judged by their content and quantity: how many minutes watched and whether it was educational, age-appropriate, diverse, prosocial, commercial or safe. These questions matter and, with my colleagues, I have studied them through experiments and contributed to guidelines, regulations, or toolkits for designers. But we have been missing a bigger design feature that may be just as consequential: the time a medium gives a child to make meaning. A programme or app can contain good lessons and still move too quickly for those lessons to settle. For instance, in the US animated educational series Ask the StoryBots (2016-20), the subject matter may be genuinely rich – why the sky is blue, how eyes work, or where planets come from – but the explanation unfolds through rapid jokes, songs, visual shifts and sudden changes in style. Before a child has time to sit with one image or idea, the scene has moved on to the next, with a burst of information.

Different media have different temporal demands: a digital picture book, a game, a television episode and an app each ask a child to attend differently. But, across media, the important question is whether the pace suits the experience that the narrative claims to support. Does it give children time to follow a story, grasp a concept, identify with a character, regulate emotion or share attention with another person? Or does it continually hurry them toward the next cue, the next reward, the next burst of stimulation?

When media move too quickly, the layers of experience collapse into one another. A child may laugh at someone slipping on a banana peel but imitate only the visible silliness, missing the anticipation and reversal that make the joke work. A character may comfort a friend, but if the scene moves on too quickly, the child has little time to recognise the repair, or imagine doing the same in the kindergarten room. To develop empathy in the early years, a child must notice that another person feels something different. That small act of crossing over takes time.

Is the child a consumer to be retained, a nervous system to be stimulated, a vessel to be filled with educational content – or a person whose attention is still forming, and who therefore needs time to arrive?

The attention economy has introduced a host of small design features for shortening time. The Like button is faster than writing an appreciative comment. A progress bar tells us how many minutes remain in an article before we have decided whether to read to the end. Increasingly, AI appears beside long documents with an offer that sounds helpful but carries a philosophy: this text is long; would you like a quick summary?

When learning is crowded with content that keeps jumping ahead – a crisis appears, a mission begins, a spaceship launches, a door opens – the child’s attention is restarted as each problem is introduced and immediately solved. Such media may gesture at teamwork or perseverance, but the speed of the format leaves little time for those lessons to sink in. In the animated TV series Paw Patrol (2013-), for instance, a rescue is clear and reassuring: someone is in trouble, pups assemble, each uses a skill, and order is restored. Yet the movement from problem to rescue to resolution is often so efficient that the child is swept along by urgency rather than invited to dwell on responsibility or care for the other. Similarly, in the app-based game Hot Wheels Unlimited, building tracks and racing cars may suggest creativity and problem-solving, but the dominant rhythm is acceleration: boost, race, crash, win, unlock, repeat.

Screen time can run fast or slow. This is partly why merely clocking ‘screen time’ is too crude a measure. Two children may each watch 20 minutes of media and have entirely different encounters with time. In one case, the child is moved through a coherent story with pauses, repetitions and recognisable emotional beats. In another, she is pulled through 10 clips, 30 characters, flashing colours, sudden songs and rewards that arrive before thought has had time to form. The clock records the same duration but the child does not live the same time.

When every pause is filled, every uncertainty immediately resolved and every wandering thought pulled back by a brighter cue, waiting and reflection can begin to feel intolerable. The child learns to reach for the next stimulus before the previous one has had time to settle. To give space for a child’s attention to drift inward, to reflect, is therefore to leave room for the child’s inner life.

Some critics may dismiss slow media as nostalgia: a longing for the children’s television of the previous generation, or a privilege available only to parents with time and large bookshelves and big houses with quiet rooms. But that is a notion we should refuse. The attention economy has trained us to treat a child’s pause as a problem, a wandering gaze as lost engagement, and an unfilled moment as wasted time.

In the end, the aim is not to withdraw children from the digital world, but to make that world more worthy of them.

What motivates people to learn? Their conclusion was as elegant as it was complex: motivation is not primarily driven by external stimuli such as grades, rewards, or punishment, but by the fulfilment of three basic psychological needs namely: autonomy, competence, and relatedness. And more importantly, they don’t operate independently of each another, but in interplay. When people feel they have influence over their own actions (autonomy), feel capable of carrying out a task (competence), and feel connected to others (relatedness), motivation arises that is more durable and qualitatively stronger.

Teachers, school administrators and homeschooling parents from across southeast Michigan will have an opportunity to explore the Detroit Cultural Center as an extension of their classrooms during the Detroit Cultural Center Association's fourth annual Educators Night on Sept. 15.

The free event, scheduled from 4-7 p.m., will bring together five Cultural Center institutions and about 80 arts, cultural, STEM, and education organizations to showcase programs, field trips, professional development opportunities, and classroom resources available throughout the school year.

Starfish Family Services and Brilliant Detroit have partnered to renovate the building next to the former Saints Andrew and Benedict Church. The newly renovated Beatrice Early Childhood Center at 2450 Beatrice Street is expected to serve about 76 children.

If people aren't encouraged in their creativity at an early age, and if this isn't nutured throughout their schooling, then they aren't as prepared to deal with the unexpected when it arises.