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Make It Stick: The Science of Successful Learning

Peter C. Brown, Henry L. Roediger III, Mark A. McDaniel · 13 HN comments
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Amazon Summary
To most of us, learning something "the hard way" implies wasted time and effort. Good teaching, we believe, should be creatively tailored to the different learning styles of students and should use strategies that make learning easier. Make It Stick turns fashionable ideas like these on their head. Drawing on recent discoveries in cognitive psychology and other disciplines, the authors offer concrete techniques for becoming more productive learners. Memory plays a central role in our ability to carry out complex cognitive tasks, such as applying knowledge to problems never before encountered and drawing inferences from facts already known. New insights into how memory is encoded, consolidated, and later retrieved have led to a better understanding of how we learn. Grappling with the impediments that make learning challenging leads both to more complex mastery and better retention of what was learned. Many common study habits and practice routines turn out to be counterproductive. Underlining and highlighting, rereading, cramming, and single-minded repetition of new skills create the illusion of mastery, but gains fade quickly. More complex and durable learning come from self-testing, introducing certain difficulties in practice, waiting to re-study new material until a little forgetting has set in, and interleaving the practice of one skill or topic with another. Speaking most urgently to students, teachers, trainers, and athletes, Make It Stick will appeal to all those interested in the challenge of lifelong learning and self-improvement.
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Jul 15, 2020 · mikece on Ask HN: How to take notes?
It's a truth that teaching is the best way to learn; even if you never "teach" the course you're learning it's useful write down key points as questions (along with their answers in your notes) and compose an exam from the material you just learned as though you're going to use it to test someone else's knowledge. Then take the exam you created, first right after you're done with your learning session and then again the next day before you start with your next session. The act of recalling from memory what you've learned is key to locking in information for long-term retrieval. (And your collection of practice exams make for a great way to cumulatively test that you're recalling everything you've learned.)

This and many more tricks were learned by reading "Make it Stick: The Science of Successful Learning" --

I've heard of Serge Lang [0] that, when he wanted to learn something, he would write a book about it.


> On a more meta level, it feels like we’ve barely touched the margins of how humans learn best. That’s always struck me as odd.

It's very well studied. I'd start by reading a cognitive science textbook and go from there. I have Cognition by Reisberg[0], it was well-written and well-structured.

Alternatively, an entertaining and informative popular account is Make It Stick by Brown, Roediger and McDaniel[1].

I do agree that the research findings are greatly underapplied, though.



I enjoyed the second book recommendation. Looks promising.

Thank you.

Creating a quiz of the material covered and then taking that quiz a few days later. The act of memory recall reinforces learning... one of the many "tricks" picked up from the book "Make It Stick" --
> Should I be re-reading/re-listening to certain chapters? Keep notes and refer back to them often?

No - simply re-reading your notes or the original text is not optimal and can give you a false sense of progress.

It's important that your repetition involves active recall - that is, you must close the textbook/notebook and try to recall the key definitions and ideas. Only then should you open your notebook and compare your current knowledge with the original information. If there are large gaps in your knowledge, schedule the next review soon otherwise leave it longer.

I've found it's quite painful to sit and force my mind to grasp onto ideas which are just out of reach, especially when the information is just a click away, but it leads to much better retention of important knowledge.

A great book on this subject is Making It Stick:

This article is untethered from the mammoth amounts of research that's been done specifically on how people learn. The answer to this question doesn't lie in anecdotes about various professors' "philosophy", in fact that kind of approach is a huge barrier to actually improving the learning that occurs on college campuses. This is an opinion article, so I understand it's not thorough reporting, but the author should familiarize herself with the literature.

A book like is accessible and provides a good survey of what we know about how the brain learns and remembers things, and how it relates to existing practices.

I don't disagree, but to add some additional complexity: cog-sci-y "learning science" literature mostly just captures one (very significant!) part of what goes on in a college course...learning things in the sense of being able to then recall facts (WWI started from an assassination!), perform new tasks (implement a linked list!), develop specific useful habits (cite your sources!), and so forth.

I know the headline says the word "retention" and the content deals with this above stuff to some degree, but there's also different goals stated like inspiring students to want to learn, getting students to reflect on their inherited values, and becoming sensitive to experiencing themes in literature. For purposes like these, there's simply no point to covering a lot of material, and it may often be counterproductive.

I think one key point is stated in the article: no one thinks "slow teaching" should be the only method. But (anecdotally lol) I personally am glad I had a few seminars with a glacial pace, as those were the ones where I really learned how to write, plus how to think when facts aren't available or directly relevant.

Personally I think stepping back and asking what a course is trying to do is the first step. If it's to expose students to as much evo bio as possible, a slow teaching "philosophy" wouldn't be appropriate. If it's to get a group of people who might be hostile to the idea of evolution to consider the possibility ("reflecting on values"), I don't know what other approach could work.

It seems like you might enjoy the article Stupid Tutoring Systems, Intelligent Humans! It talks about some less commonly thought of factors (e.g.emotional) that are important for teaching processes.

Thank you for the link! I was actually wanting to read a survey on this topic. I'm obviously sympathetic with the general approach of focusing on augmenting rather than replacing humans in teaching.

I confess I'm more skeptical of "data, data, and more data" than the author (from whence it comes? an A/B test of the video widget we wrote last week? the "anecdotes" of a skilled teacher with decades of experience can surely be more informative sometimes!), but I'm certainly eager to incorporate what good data is available!


For instance, we all probably had to go through math classes where the professor writes so fast that it's a hand cramping race just to even scribble together enough notes to follow each gigantic derivation later for learning purposes. Nobody in that class is retaining any of that.

The kid who aces that class, is almost invariably someone who likes to to play with the equations in their free time at their own pace, so they get a feel for what process they need to employ toward a solution rather than brute forcing it. (When applicable, sometimes brute force is the only tactic.)

Math classes in general really, desperately need to slow down and let students grasp higher-order concepts. The number crunching method is stressful, and all it does is massively discourage bright people who may be geniuses in their field but flee University because the school made Calculus their "breakout" class.

Anecdote. When I went to University, I had a professor who graduated MIT tell the class that he'd realized how much pressure we were under in our Calculus class trying to keep up, that this was deeply unfair, and that he was erasing our last test score because they were unreflective of the performance that he knew we were capable of if we had any time for his class. Calculus was a core requirement, his class was elective, so almost every student had been forced to ignore his class, and we were amazingly lucky that he was good enough to sympathize.

This man used to work at Bell Labs and swam 200 laps a day to keep fit. And he was telling us we had it rough. I saw people cry out of gratitude.

What a hero. In my opinion academics often take their role quite a bit too seriously. They are not aware that their role outside of the actually practice related subjects is mostly to be a brain teaser.
It's heroic to give someone a passing grade in a college level class when they can't keep up with a college level workload?

I think that its just fraud.

It is sacrificing his academic creditably for the good of his student's gpa.
In a perfect world, neither group would care about either of those things.
I can see how GPA imperfectly measures a student's knowledge/intelligence. However credibility and honesty should be valued in a perfect world.
It's not a perfect world.
A hero for realizing being just another minor data point for most of his students lifes.
Anecdata: I didn't grasp any of algebra until 10th grade. From about 7th to 10th grade chemistry class, I was just winging it. Sure, 10x=30, I could get x. But any of the trig or the parabolas, not a chance. It wasn't until chemistry, when I actually had to use algebra to get the molarity, moles, grams, etc, that I was able to grasp it. I remember sitting in class after the bell let out, on my desk, just doing the molarity equations over and over. It was one of the largest smiles of my life. I finally got it.

So, math happens when it happens. Maybe, yeah, I was a little retarded from the rest of my peers in grasping this idea of algebra. But I did get it eventually, when I needed to use it, finally. Saying that math is 'hard' isn't the best way of going about it. Everyone is different and learns differently and at different times. Some may not be able to get 3rd year Calc until they are 30, some get it at 15.

I tapped out of formal math classes at number-theory at ~22. Diff-eqs, Lagrangians, General Relativity, all fine with me, but number theory was a whole different level of pedantry I was not about to dive into.

It wasn't until chemistry, when I actually had to use algebra to get the molarity, moles, grams, etc, that I was able to grasp it.

There was this study that found this kind of difference in application. People were given a logic problem phrased abstractly. Then other people were given the same logic problem, but phrased in terms of catching someone cheating at something. It was like people's IQ's suddenly greatly increased.

I also remember an anecdote about this father coaching his kid through the multiplication tables, which the kid didn't like and had trouble with. They were riding in the car quizzing the kid, who was not doing well, but then the kid asked to do the 7's, which he rattled off with aplomb. Turns out, the kid really liked football. (US football)

I think your first reference is to the Wason selection task:

Nice ones!

I think application is important, but the diversity of what a child will care about is crazy large. You can't reach them all. My SO is a teacher (of chemistry, ironically) and some kids get the material and some just don't. It's not a lack of trying, it's just that they don't get it. As such, the frustration of the child comes out and makes things worse. Good family lives are very important throughout their lives and help, but some kids just aren't going to get certain subjects. We're all different people.

Aside from the fact that pedagogical research is 95% focused on youth and not learning across the lifespan, there is a massive divide between pedagogical research and practice that doesn't look to improve, and the problem is as much political as it is historical.
A reviewer of the book mentions this magazine article:

("What Works, What Doesn't: Some study techniques accelerate learning, whereas others are just a waste of time—but which ones are which? An unprecedented review maps out the best pathways to follow.")

Behind paywall, but mirrored at

A short summary for the article is:

Any books or other resources you recommend to learn these things? On learning to learn I have enjoyed A Mind for Numbers[1] by Barbra Oakley with Coursera course[2], Make it Stick[3] by Peter C. Brown, and How We Learn[4] by Benedict Carey.





There's a great book called 'Making It Stick' which details effective, proven methods to improve memorisation and learning. Spaced repition (or more generally active recall) is one of those major methods.


The science underpinning the idea of learning, memory, recall and is based/described in neuroscience at at cellular level. So you can read papers. The coursework is really at a more abstracted level describing the processes as a model based on cited research. This is a high level course to improve learning, not STEM as such. Still very useful.

Chunking is described in more detail at Week2 and books:

If somebody prefer a book instead, one of the recommended books for this course is book [1] Make it stick: The science of successful learning. The book is written by several cognitive scientist and it contains many useful tricks about learning. Here you can find a short summary containing main ideas of the book [2].



I read this (similar) book recently and using the techniques in it I passed the AWS exams in a short space of time:
I just read the audiobook version of this:

It's pretty good.

The main idea is that learning is supposed to feel hard. That sense of frustration and confusion is what building new neural connections feels like.

I think this is called varied practice and that the idea has been around for awhile. The book Make It Stick[1] discusses a study that had 8 year olds toss beanbags at a target. For one group, the distance to the target was varied. For another, the distance to the target was fixed. At a later time, both groups were tested and the group that practiced with a variable distance performed better than the fixed distance group.


Don't be depressed. This is normal. All memories are subject to gradual decay. The best way to prevent this decay is by reviewing and testing yourself on the material you want to remember. Unless one reviews or uses specific knowledge regularly, corresponding memories will fade on courses taken, books read, bugs fixed, technologies or languages learned, code that's been understood (read) or written, etc.

If you only spent a few weeks working on that new project, then you probably didn't spend near the amount of time Bill Gates spent writing, thinking about, and reviewing his Altair BASIC code. Even though he whipped up his code in less than a month or two prior to the first MITS demo, he likely spent weeks or months after that demo modifying and polishing the BASIC interpreter for subsequent releases. You didn't mention your experience level, but Gates' years of prior programming experience likely benefited him as well, providing him with a nice cognitive framework to which lots of these facts could "stick."

One additional thing: when Gates says he still knows the source code for Altair BASIC by heart, it probably doesn't mean "completely, line-by-line" by heart. I'm guessing it means he still remembers some snippets by heart, or that he believes he could re-write it from scratch from memory (which would still be exceedingly impressive).

Some useful resources on memory and learning:

Memory and Learning: Myths and Facts (

Want to Remember Everything You'll Ever Learn? Surrender to This Algorithm (

Make It Stick: The Science of Successful Learning (

Very interesting. Thank you for posting this.
A more up-to-date and complete treatment of these exact topics can be found in the recently-published book, _Make it Stick: The Science of Successful Learning_ ( For those that have already immersed themselves in spaced repetition techniques via Anki, SuperMemo, Mnemosyne, etc., some of the material in the book will be review. But there is a wealth of useful information for both students and lifelong learners. In addition to that, the intertwined, real-life case studies and anecdotes drive home the points. And lest my comments come off like a back-cover endorsement, I will say that I was a bit disappointed that the authors seemed to have little awareness of SRS' momentum on the Internet with the aforementioned programs. For example, even though the book spends quite a bit of time discussing spaced repetition and flashcards, it never once mentions Anki, SuperMemo, or other popular SRS software. Aside from that, it's still an excellent book.
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