Why books don’t work

Metadata

• Author: Andy Matuschak
• Full Title: Why books don’t work
• Document Note: What is the main argument of the document “Why books don’t work”? The main argument is that books, as a medium, are surprisingly bad at conveying knowledge, and readers mostly don’t realize it. The document argues that neither books nor lectures have a functioning cognitive model at their foundation, and as a result, both mediums evolved around a theory that’s plainly false. What is the purpose of the document “Why books don’t work”? The purpose of the document is to explore why books so often don’t work, and why they succeed when they do. The document provides insights into how we might improve books as a medium, and also how we might weave unfamiliar new forms—not from paper, and not from pixels, but from insights about human cognition. What is the “transmissionism” model of teaching and learning? The “transmissionism” model of teaching and learning is the notion that knowledge can be directly transmitted from teacher to student, like transcribing text from one page onto another. This model is implicitly shared by both lectures and books, and it’s based on a faulty idea about how people learn.
• URL: https://andymatuschak.org/books/

Highlights

• 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. (View Highlight)
• Picture some serious non-fiction tomes. The Selfish Gene; Thinking, Fast and Slow; Guns, Germs, and Steel; etc. Have you ever had a book like this—one you’d read—come up in conversation, only to discover that you’d absorbed what amounts to a few sentences? I’ll be honest: it happens to me regularly. Often things go well at first. I’ll feel I can sketch the basic claims, paint the surface; but when someone asks a basic probing question, the edifice instantly collapses. Sometimes it’s a memory issue: I simply can’t recall the relevant details. But just as often, as I grasp about, I’ll realize I had never really understood the idea in question, though I’d certainly thought I understood when I read the book. Indeed, I’ll realize that I had barely noticed how little I’d absorbed until that very moment. (View Highlight)
• All this suggests a peculiar conclusion: as a medium, books are surprisingly bad at conveying knowledge, and readers mostly don’t realize it. (View Highlight)
• 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. (View Highlight)

• We’ve been discussing books so far, but have you ever had the same type of experience with a lecture? 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. (View Highlight)
• 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. (View Highlight)
• 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. (View Highlight)
• That’s an important question because it’s hard to convey knowledge. Most lecture attendees don’t absorb the intended knowledge; most book readers don’t absorb the intended knowledge. Failure is the default here. So if you hope to help others understand things, you had better draw on some great ideas about how people learn. It would be nice if this weren’t true. It would be nice if one could simply explain an idea clearly to someone, then trust that they’ve understood it. Unfortunately, as you’ve likely seen in classrooms and in your own life, complex ideas are rarely understood so automatically. (View Highlight)
• 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. (View Highlight)
• 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? (View Highlight)
• The lectures-as-warmup model is a post-hoc rationalization, but it does gesture at a deep theory about cognition: to understand something, you must actively engage with it. That notion, taken seriously, would utterly transform classrooms. We’d prioritize activities like interactive discussions and projects; we’d deploy direct instruction only when it’s the best way to enable those activities. I’m not idly speculating: for the last few decades, this has been one of the central evolutionary forces in US K–12 policy and practice. (View Highlight)
• In summary: lectures don’t work because the medium lacks a functioning cognitive model. It’s (implicitly) built on a faulty idea about how people learn—transmissionism—which we can caricaturize as “lecturer says words describing an idea; students hear words; then they understand.” When lectures do work, it’s generally as part of a broader learning context (e.g. projects, problem sets) with a better cognitive model. But the lectures aren’t pulling their weight. If we really wanted to adopt the better model, we’d ditch the lectures, and indeed, that’s what’s been happening in US K–12 education. (View Highlight)
• 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. (View Highlight)
• I acknowledged earlier that of course, some people do absorb knowledge from books. Indeed, those are the people who really do think about what they’re reading. The process is often invisible. These readers’ inner monologues have sounds like: “This idea reminds me of…,” “This point conflicts with…,” “I don’t really understand how…,” etc. If they take some notes, they’re not simply transcribing the author’s words: they’re summarizing, synthesizing, analyzing. (View Highlight)
• Unfortunately, these tactics don’t come easily. 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?” (View Highlight)
• 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. (View Highlight)
• If lecturers believe that lectures are a warm-up for the understanding developed through problem sets and essays, then at least the lecturers design those activities and offer feedback on students’ work. By comparison, if authors believe that understanding comes only when readers really think about their words, then they’re largely leaving readers to design their own “problem sets” and to generate their own feedback. All this effortful “thinking about thinking” competes with actually thinking about the book’s ideas. (View Highlight)
• We saw earlier how non-fiction books’ accidental cognitive model left readers doing all the metacognitive work to plan, execute, and monitor their engagement with the book’s ideas. By contrast, textbooks do have explicit cognitive models: they support engagement with their concepts through things like exercises and discussion questions. Yet much of the metacognitive burden still remains with the reader. (View Highlight)
• Readers must decide which exercises to do and when. Readers must run their own feedback loops: did they clearly understand the ideas involved in the exercise? If not, what should they do next? What should students do if they’re completely stuck? Some issues are subtler. For example, textbook exercises are often designed to yield both a solution to that specific problem and also broader insights about the subject. Will readers notice if they solved a problem but missed the insights it was supposed to reveal? (View Highlight)
• By contrast, courses handle much of this metacognitive burden. Their syllabi offer a scheduled scope and sequence, so students need do less planning of their own. Students generally receive feedback on exercises, both individually and through class-wide discussion. If students are stuck, they can attend office hours to receive finer-grained help. Instructors can discuss the implications of the previous week’s exercises in class. Certainly, courses do none of this perfectly. Plenty of students still absorb nothing from a class. But by shouldering some of the metacognition, courses preserve more of students’ attention for the material itself. (View Highlight)
• At this point, a typical narrative in educational technology would observe how AI-based learning systems could offer automated feedback and task planning outside of the classroom. There’s been intriguing progress here, and these methods can indeed improve on textbooks, but these systems generally fixate on a narrow, task-oriented view of what’s happening in classrooms. Academic courses offer more than just metacognitive support for textbooks; their cognitive model is also social and emotional. (View Highlight)
• For instance, class discussions support social learning: students understand topics more deeply by grappling with their peers’ understandings of the same ideas. Courses can provide a personal relationship with a disciplinary expert, a rich conduit for accessing the discipline’s culture—much of which may be tacit. For many students, courses offer a helpful accountability structure, playing an important role in supporting their willpower. (View Highlight)
• 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. (View Highlight)
• To help people encode more into long-term memory, we can draw on another powerful idea from cognitive science: spaced repetition. By re-testing yourself on material you’ve learned over expanding intervals, you can cheaply and reliably commit huge volumes of information to long-term memory. Of course, memory is only a small slice of “understanding,” but to illustrate how one might begin to address understanding as a whole, let’s explore how we might weave a medium out of these two ideas about memory. (View Highlight)
• My collaborator Michael Nielsen and I made an initial attempt with Quantum Country, a “book” on quantum computation. But reading this “book” doesn’t look like reading any other book. The explanatory text is tightly woven with brief interactive review sessions, meant to exploit the ideas we just introduced. Reading Quantum Country means reading a few minutes of text, then quickly testing your memory about everything you’ve just read, then reading for a few more minutes, or perhaps scrolling back to reread certain details, and so on. Reading Quantum Country also means repeating those quick memory tests in expanding intervals over the following days, weeks, and months. If you read the first chapter, then engage with the memory tests in your inbox over the following days, we expect your working memory will be substantially less taxed when reading the second chapter. What’s more, the interleaved review sessions lighten the metacognitive burden normally foisted onto the reader: they help readers see where they’re absorbing the material and where they’re not. (View Highlight)