Seven Principles of Learning Better From Cognitive Science

I just finished one of the best books I’ve read on the science of learning. Daniel Willingham is a Harvard educated cognitive scientist who writes books and articles about how to learn and teach better.

The title of his book, Why Don’t Students Like School?, is a tad unfortunate, I think, because the book isn’t really about bored students. Instead, the book is divided into principles of learning. In order to make the cut, these principles needed to fulfill a strict set of scientific criteria:

  1. Robust scientific support. In Willingham’s words, “Each principle is based on a great deal of data, not only one or two studies. If any of these principles is wrong, something close to it is right.”
  2. Doesn’t depend on circumstances. These are facts about how human brains learn, so they don’t change whether you’re learning Spanish or mathematics.
  3. Ignoring it would be costly. Using the principles versus not using them showed a big difference in results. The principles aren’t just theoretical concerns but practically significant.
  4. Suggests non-obvious applications. The final criteria was that the implications of the principle should suggest new ways of teaching and learning.

The book is excellent, and I highly recommend getting a copy for yourself as Willingham explains many of the details and implications of each of these principles. I wanted to discuss each principle briefly, to share the implications it has for learning better.

Side note: The book lists nine principles, but two were more related to teaching, so I omitted them here.

1. Factual knowledge precedes skill.

Einstein was wrong. Knowledge is more important than imagination, because knowledge is what allows us to imagine. There is considerable research showing the importance of background knowledge to how well we learn. Without background knowledge, the kinds of insights Einstein praised are impossible.

Careful studies show that having more background knowledge on a topic means we can read faster, understand more when we do and remember more of it later. This means knowledge is exponential growth, with past knowledge becoming a crucial factor in the speed at which more knowledge is acquired.

This means that you cannot teach someone “how” to think, without first teaching them a considerable amount of “what” to think. Thinking well first requires knowing a lot of stuff, and there’s no way around it.

2. Memory is the residue of thought.

You remember what you think about. Whatever aspect of what you’re learning your mind dwells on, will be the part that it is likely to be retained. If you, inadvertently, spend your studying time thinking about the wrong aspects of your studies you won’t remember much of use.

The problem with this principle is that knowing about it is not enough. We can’t constantly self-monitor our own cognition, noticing what we’re noticing. So even if you try to pay attention to the right things, it can be easy to accidentally focus on less important details which will take precedence in memory.

This is a reason why highlighting is often a lousy tactic. When you highlight, you’re not focusing on underlying meaning, but observing bolded words or particularly emphasized sentences. So you don’t remember much.

I recommend tactics like paraphrasing with sparse notes while reading, the Feynman technique or taking pauses during a reading session to quickly recap what you just read. These are orienting tasks that encourage you to spend more time thinking about underlying meaning, which is almost always what you want to be learning.

This also shows one of the weaknesses I’ve seen in students who misuse analogies. If the analogy you make causes you to think about a surface detail of a concept, and not the underlying structure, you’ll only remember surface details on the test. A metaphor for voltage that uses volcanoes because they both start with “V” won’t help you with problems. The metaphor that voltage is analogous to height is useful because you’re forced to think about what voltage means (in this case the relation between gravitational and electric potential).

Interestingly, this also has implications for languages. The reason the “sounds like” method for memorizing vocabulary words can work is because it forces you to think about how a word sounds more exactly. Having to come up with an image that links to the sound forces you to spend a couple seconds thinking about what the word actually sounds like.

3. We understand new things in the context of what we already know.

Abstract subjects like math, physics, finance or law, can often be hard for people to learn. The reason why is that the we learn things by their relation to other things we already know (sound familiar?). Willingham here suggests using many examples to ground a particular abstraction in concrete terms before moving on.

I would also add that I believe people overestimate their ability to learn abstract things. As such, we tell ourselves we understand an idea without first grounding it in numerous examples or analogies. Smart learners correctly understand the brains weakness for abstraction and build scaffolding to support new ideas before they fully set.

Occasionally when I recommend to students metaphors or analogies for learning a subject, they come up blank. I admit, it can be a tricky technique. But I believe part of the difficulty is that it points out when you don’t really understand a concept. If you understand a concept but can’t put it into a single example or analogy, you don’t really understand it at all (and should first do something like the Feynman technique to get that understanding).

4. Proficiency requires practice.

The only way to become good at skills is to practice them. Additionally, some basic skills require thorough practice in order to be successful at more complicated skills.

Math is an excellent example: you may have a conceptual understanding of calculus, but if you aren’t fully fluent with algebra, it will take you hours to do a simple problem. The only way to make algebra automatic is to practice a lot of problems.

I’ve certainly been guilty of downplaying the importance of repetitive practice in some of my early writing. But there’s no way I could have completed the MIT Challenge or this language project without extensive time spent practicing the basic tools for each subject. Merely understanding isn’t enough.

Willinham suggests an alternative to repetitive practice which can be painfully dull: learn harder subjects that require practicing earlier material. One study showed that those who took an algebra class showed rapid and predictable decline of their skills. The one group that didn’t? Those who learned calculus.

5. Cognition is fundamentally different early and late in training.

Should you learn physics like Newton? For that matter, should you learn science like a scientist, making hypothesis, testing experiments, revising your theory to fit the data? Willingham offers substantial evidence that the answer is no.

I think there’s merit in understanding how scientists perform their work, but it’s also clear that knowledge creation and knowledge acquisition are very different. Because they are different, the learner needs to weigh them against each other. For most disciplines, understanding scientific facts is more important than scientific process, for the simple reason that scientific facts will inform our lives, but few of us will ever do scientific research. The same applies to history, philosophy and nearly any other discipline of knowledge.

Another implication of this is that the ideal method for learning a subject and creating knowledge within a subject will be different. Learning calculus and inventing calculus bear little resemblance, so don’t worry if you can’t learn calculus the way Newton did. You don’t have to.

6. People are more alike than different in how we learn.

Learning styles are bunk. There is no such thing as visual, auditory or kinesthetic learners. This is also true for every serious theory of different cognitive styles for learning.

Defending this conclusion takes a bit of thought, because to most people the idea that people learn differently is obviously true, even though research says otherwise.

Part of the confusion stems from the fact that different abilities can exist while styles do not. Meaning Johnny might be really good at processing visual information and Mary might be good at processing auditory information. Show Johnny a map and he’ll remember where everything is better than Mary. Play Mary a tune, and she can hum it back a week later.

But this isn’t what a theory of learning styles suggests. It suggests that if you taught the same subject to both Johnny and Mary, and played Johnny a slideshow and Mary an audiobook, they would learn better than if Johnny had listened and Mary had watched. The experiments simply don’t find that.

This suggests that the ways we learn are more similar than different. Some people might be better at learning certain types of things than others, but given a particular subject, science hasn’t different ways of learning it that are consistently better for some people but not others.

Side note: Willingham also debunks holistic versus linear thinkers. However the only thing it shares with my idea of “holistic” learning is the name. My version of holistic learning is not a learning style in the sense Willingham debunks here, but a strategy and one that happens to closely correspond with the third cognitive principle listed above. The nomenclature is my mistake, owing to my being unaware of the other learning theory that used the same name at the time. I’ve since used tried to use the word less, preferring “learning by connections” to avoid confusion.

7. Intelligence can be changed through sustained hard work.

This was probably my favorite part of the entire book because it validates much of what I said here. Intelligence is partially genetic and partially environmental. Innate differences do matter and some people are born with more talent than others.

However, Willingham argues that intelligence is malleable. Psychologists used to believe that intelligence was mostly genes. Twin studies and other natural experiments seemed to bear that out. Adopted children turn out more like their biological parents than their adoptive parents in many dimensions.

However, now the consensus has turned far more towards nurture, rather than nature. One of the biggest pieces of evidence is the Flynn Effect, which is the observation that people, over the last century, have gotten smarter (and the effect is too large to be from natural selection). Genes may have an important role in intelligence, but most of that role is played out through the environment, not independent of it.

If you re-read the first principle I listed, that shouldn’t be surprising. Knowledge being exponential growth means that a small initial advantage can quickly compound. If genes gave you a 5% headstart in math in kindergarten, there may not be much difference between you and a similar child. However, expand that small initial advantage over thirty years and you may have someone who has done a PhD in physics and someone who stopped at high-school.

From a population standpoint the difference between these two people may be “explained” by differences in genes. However, genes only created a small headstart. Sustained hard work can help set off your own exponential growth of learning in a domain as well.

Concluding Thoughts

I thoroughly enjoyed this book, and don’t let my brief summary and insights spoil it for you. It’s a fairly easy read while still being smart and insightful. What’s more, the book is based on robust research and science.

In terms of my own, more informal, writing about learning, I was happy that most of the principles discussed in the book reflected my own thinking. It’s comforting to see when the experience I’ve gained from my own learning challenges converges on the serious work scientists are doing to understand the brain and how we learn.

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  • Heather

    I just checked out this book from the library! I was re-reading an article in the NYT which quotes him. Basically the article was about how all these really popular techniques for teaching aren’t based in actual scientific studies of how people learn. The article was Forget What You Know About Good Study Habits By Benedict Carey.

  • Andre

    Thank you for your suggestion; I already ordered it. 🙂
    By the way, the book reminded me of “Make it Stick: The Science of Successful Learning”, which I can absolutely recommend.

  • Sebastian Aiden Daniels

    I am going to check out this book. I found your breakdown of it fascinating. Some of these are common sense, but it is good to be reminded of how to go about learning. It is so true that learning builds upon things and that practice makes perfect. I use to beat myself up when I couldn’t master something right away, but as you start to become more proficient in things, the problems that were once hard are now easy.

    I wish you can a picture on this post so I could post it on pinterest for you.

  • John

    Hi Scott!

    I have great news. A new book on science of learning has been released. This books is a comprehensive summary of the last 20 years of cognitive science as it relates to learning. It builds on the work of Daniel Willingham and other top cognitive scientists. Daniel actually wrote a blurb for the book complementing it.

    Book: Make it Stick by Peter C. Brown (Harvard University Press, 2014)

  • Sam

    This summary has made me reinforce my belief that, every body can actually learn despite all seeming odds. – practice & understanding. Thanks Scott for this pointer

  • Becca Britten

    I have just purchased this book, your article sold me. I can’t wait to delve right into it and reap the rewards. Learning should never be a difficult process, sometimes all that needs to change are our perceptions.

  • Chantal

    Well written! I think it’s true that genes are the base and everybody can decide what they will build on it. If we focus on it and practice a lot, we can become intelligent. I must confess, I use analogies a lot in my life and I think it helps me a lot. It makes things easier for me. On the other hand, I find it really interesting that the imagination depends on our knowledge. I haven’t realized that. You made some strong true points here. Thank you!

  • Nate Glenn

    I’ve always felt that learning was related more to enjoyment than some sort of natural ability. I interesting to hear that learning styles don’t exist, but I think you might still find the effects. Teaching someone via an activity that they enjoy will likely get them to participate a lot better than teaching them through something they do not enjoy.

  • Faiq

    Happy birthday

  • Allen Edwards

    Excellent, excellent post Scott! Helpful, inspiring and uplifting. Thank you!

  • Eric-Wubbo

    Hmm… I think that Willingham is actually an excellent cognitive scientist who does very useful work – I’ve read at least one of his papers on evidence on the relative efficiency of learning methods.

    But I am really not enthusiastic about this particular book of his. I have the feeling that Willingham is continuously ‘pulling punches’, trying to sell the book to traditionalist schoolteachers by telling them that they are basically doing everything fine, and that educational reforms are mostly hogwash. Teachers may breathe a sigh of relief: finally, a real scientist is supporting them instead of attacking them! (An excellent question is why so many scientists seem to be attacking traditional teaching methods… a question Willingham does not really answer) When reading this book, I had to wince every few pages as Willingham posited a ‘pleasing’ but rather misleading or simply erroneous ‘truth’. Yes, many ‘expert’ teachers (read: teachers who have had their job for many years) don’t write out lessons in advance. By saying this, Willingham suggests they don’t need to deal with this ‘low level of abstraction’ anymore. But the research on direct instruction strongly suggest they should, in fact, deal with such ‘details’. Similarly, it is true that students don’t necessarily think like scientists in the sense that scientists automatically ask themselves certain questions or pay much more attention to certain details than a layperson would (the particular questions and details depending strongly on the specific branch of science). But the idea that if you spend long-enough time in boring classrooms learing science from teachers you will automatically gather the knowledge that provides mastery is nonsense; being a scientist, meaning a person who asks the right questions, is not produced by teachers cramming facts into the students’ heads; and even a four-year old can learn to think like a scientist by a mentor who focuses on teaching the right questions to ask, more than the average 16-year old learns to think ‘scientifically’ by following classes and learning a number of simple tricks to solve standardized problems. That most teachers don’t seem to educate scientists, and that scientists like Newton, Darwin and Einstein were far from jubilant about their official school curriculum, simply highlights the gap between teachers and scientists: a teacher who does not think like a scientist cannot teach scientific thinking to students, and any claim that the students simply ‘need more knowledge’ to become like experts is misleading at least. There are definitely teacher-scientists and scientist-teachers, but a teacher who is not in the least part a scientist him- or herself will not teach scientific thinking [of course, this may not be necessarily bad, as many schools strive to let students score high on standardized tests, and thinking like a scientist is not necessary for that]

    Some of Willingham’s points are valid, sure. But as a scientist who has read more than one book on learning, psychology and the brain, I vastly prefer John Hattie’s “Visible Learning” and Ruth Colvin Clark’s “Building expertise”, or even Willingham’s scientific papers over this book.

  • anon

    Other evidence-based reading on optimizing learning practices:

    Bjork RA, J Dunlosky, N Kornell (2013). Self-Regulated Learning: Beliefs, techniques, and illusions. Annu Rev Psychol.2013. 64:16.1–16.28.

    Dunlosky J, KA Rawson, EJ Marsh, MJ Nathan, DT Willingham (2013). Improving Student’s Learning with Effective Learning Techniques: Promising directions from cognitive and educational psychology. Psych Sci in the Public Interest 14(1):4-58.

    Ericsson, KA (2008). Deliberate Practice and Acquisition of Expert Performance: A general overview. Acad Emerg Med 15:988-994.

    Thalheimer W (2013). The Decisive Dozen: Research background abridged

  • Yoori

    I fucking love this book. Thanks for an excellent recommendation.

  • Yoori

    I fucking love this book. Thanks for an excellent recommendation.