Review:
Make It Stick, by Peter C. Brown, et al.
| Author: |
Peter C. Brown |
| Author: |
Henry L. Roediger III |
| Author: |
Mark A. McDaniel |
| Publisher: |
Belknap Press |
| Copyright: |
2014 |
| ISBN: |
0-674-72901-3 |
| Format: |
Kindle |
| Pages: |
255 |
Another read for the work book club.
"People generally are going about learning in the wrong ways." This is
the first sentence of the preface of this book by two scientists (Roediger
and McDaniel are both psychology researchers specializing in memory) and a
novelist and former management consultant (Brown). The goal of
Make
It Stick is to apply empirical scientific research to the problem of
learning, specifically retention of information for long-term use. The
authors aim to convince the reader that subjective impressions of the
effectiveness of study habits are highly deceptive, and that scientific
evidence points strongly towards mildly counter-intuitive learning methods
that don't feel like they're producing as good of results.
I have such profound mixed feelings about this book.
Let's start with the good.
Make It Stick is a book containing
actual science. The authors quote the studies, results, and scientific
argument at length. There are copious footnotes and an index, as well as
recommended reading. And the science is concrete and believable, as is
the overlaid interpretation based on cognitive and memory research.
The book's primary argument is that short-term and long-term memory are
very different things, that what we're trying to achieve when we say
"learning" is based heavily on long-term memory and recall of facts for an
extended time after study, and that building this type of recall requires
not letting our short-term memory do all the work. We tend towards study
patterns that show obvious short-term improvement and that produce an
increased feeling of effortless recall of the material, but those study
patterns are training short-term memory and mean the knowledge slips away
quickly. Choosing learning methods that instead make us struggle a little
with what we're learning are significantly better. It's that struggle
that leads to committing the material to long-term memory and building
good recall pathways for it.
On top of this convincingly-presented foundation, the authors walk through
learning methods that feel worse in the moment but have better long-term
effects: mixing practice of different related things (different types of
solids when doing geometry problems, different pitches in batting
practice) and switching types
before you've mastered the one you're
working on, forcing yourself to interpret and analyze material (such as
writing a few paragraphs of summary in your own words) instead of
re-reading it, and practicing material at spaced intervals far enough
apart that you've forgotten some of the material and have to struggle to
recall it. Possibly the most useful insight here (at least for me) was
the role of testing in learning, not as just a way of measuring progress,
but as a learning tool. Frequent, spaced, cumulative testing forces
exactly the type of recall that builds long-term memory. The tests
themselves help improve our retention of what we're learning. It's bad
news for people like me who were delighted to leave school and not have to
take a test again, but viewing tests as a more effective learning tool
than re-reading and review (which they are) does cast them in a far more
positive light.
This is all solid stuff, and I'm very glad the research underlying this
book exists and that I now know about it. But there are some significant
problems with its presentation.
The first is that there just isn't much here. The two long paragraphs
above summarize nearly all of the useful content of this book. The
authors certainly provide more elaboration, and I haven't talked about all
of the study methods they mention or some of the useful examples of their
application. But 80% of it is there, and the book is intentionally
repetitive (because it tries to follow the authors' advice on learning
theory).
Make It Stick therefore becomes tedious and boring,
particularly in the first four chapters. I was saying a lot of "yes, yes,
you said that already" and falling asleep while trying to read it. The
summaries at the end of the book are a bit better, but you will probably
not need most of this book to get the core ideas.
And then there's chapter five, which ends in a train wreck.
Chapter five is on cognitive biases, and I see why the authors wanted to
include it. The Dunning-Kruger effect is directly relevant to their
topic. It undermines our ability to learn, and is yet another thing that
testing helps avoid. Their discussion of Daniel Kahneman's two system
theory (your fast, automatic, subconscious reactions and your slow,
thoughtful, conscious processing) is somewhat less directly relevant, but
it's interesting stuff, and it's at least somewhat related to the
short-term and long-term memory dichotomy. But some of the stories they
choose to use to illustrate this are... deeply unfortunate. Specifically,
the authors decided to use US police work in multiple places as their
example of choice for two-system thinking, and treat it
completely
uncritically.
Some of you are probably already wincing because you can see where this is
going.
They interview a cop who, during scenario training for traffic stops, was
surprised by the car trunk popping open and a man armed with a shotgun
popping out of it. To this day, he still presses down on the trunk of the
car as he walks up; it's become part of his checklist for every traffic
stop. This would be a good example if the authors realized how badly his
training has failed and deconstructed it, but they're apparently
oblivious. I wanted to reach into the book and shake them. People have a
limited number of things they can track and follow as part of a procedure,
and some bad trainer has completely wasted part of this cop's attention in
every traffic stop and thereby made him less safe! Just calculate the
chances that someone would be curled up in an unlocked trunk with a
shotgun and a cop would just happen to stop that car for some random
reason, compared to any other threat the cop could use that same attention
to watch for. This is exactly the type of scenario that's highly
memorable but extremely improbable and therefore badly breaks human risk
analysis. It's what Bruce Schneier calls a movie plot threat. The
correct reaction to movie plot threats is to ignore them; wasting effort
on mitigating them means not having that effort to spend on mitigating
some other less memorable but more likely threat.
This isn't the worst, though. The worst is the very next paragraph, also
from police training, of showing up at a domestic call, seeing an armed
person on the porch who stands up and walks away when ordered to drop
their weapon, and not being sure how to react, resulting in that person
(in the simulated exercise) killing the cop before they did anything. The
authors actually use this as an example of how the cop was using system
two and needed to train to use system one in that situation to react
faster, and that this is part of the point of the training.
Those of us who have been paying attention to the real world know what
using system one here means: the person on the porch gets shot if they're
black and doesn't get shot if they're white. The authors studiously
refuse to even hint at this problem.
I would have been perfectly happy if this book avoided the unconscious
bias aspect of system one thinking. It's a bit far afield of the point of
the book, and the authors are doubtless trying to stay apolitical. But
that's why you pick some other example. You cannot just drop this kind of
thing on the page and then refuse to even comment on it! It's like
writing a chapter about the effect of mass transit on economic
development, choosing Atlanta as one of your case studies, and then never
mentioning race.
Also, some editor seriously should have taken an ax to the sentence where
the authors (for no justified reason) elaborate a story to describe a cop
maiming a person, solely to make a cliched joke about how masculinity is
defined by testicles and how people who lose body parts are less human.
Thanks, book.
This was bad enough that it dominated my memory of this chapter, but,
reviewing the book for this review, I see it was just a few badly chosen
examples at the end of the chapter and one pointless story at the start.
The rest of the chapter is okay, although it largely summarizes things
covered better in other books. The most useful part that's relevant to
the topic of the book is probably the discussion of peer instruction.
Just skip over all the police bits; you won't be missing anything.
Thankfully, the rest of the book mostly avoids failing quite this hard.
Chapter six does open with the authors obliviously falling for a string of
textbook examples of survivorship bias (immediately after the chapter on
cognitive biases!), but they shortly thereafter settle down to the
accurate and satisfying work of critiquing theories of learning methods
and types of intelligence. And by critiquing, I mean pointing out that
they're mostly unscientific bullshit, which is fighting the good fight as
far as I'm concerned.
So, mixed feelings. The science seems solid, and is practical and
directly applicable to my life.
Make It Stick does an okay job at
presenting it, but gets tedious and boring in places, particularly near
the beginning. And there are a few train-wreck examples that had me
yelling at the book and scribbling notes, which wasn't really the cure for
boredom I was looking for. I recommend being aware of this research, and
I'm glad the authors wrote this book, but I can't really recommend the
book itself as a reading experience.
Rating: 6 out of 10
This morning I remembered I had a beefy virtual-server setup to run some kernel builds upon (when I was playing with Linux security moduels), and I figured before I shut it down I should use the power to run some fuzzing.
As I was writing some code in Emacs at the time I figured "why not fuzz emacs?"
After a few hours this was the result:
My monthly report covers a large part of what I have been doing in the free software world. I write it for 
To be able to get in sync with Kali, I introduced an hashcat-meta source package (in contrib) providing hashcat-nvidia to make it easy to install hashcat for owners of NVidia hardware.
Misc stuff
Distro Tracker. I merged a small CSS fix from Aur lien Couderc (
Two scenarios are tested:
It seems to be becoming popular to send a mail each month detailing your free
software work for that month. I have been slowly ramping my F/LOSS activity
back up, after years away where I worked on completing my degree. My final
exam for that was in June 2017 and as such I am now in a position to try and
get on with more F/LOSS work.
My focus, as you might expect, has been on 
DRM leasing part three (vblank)
The last couple of weeks have been consumed by getting frame sequence
numbers and events handled within the leasing environment (and Vulkan)
correctly.
Vulkan EXT_display_control extension
This little extension provides the bits necessary for applications to
track the display of frames to the user.
Here is my monthly update covering what I have been doing in the free software world (
It's great to see people finding ways to share the principles of technological freedoms far and wide and it will be interesting to see how this relationship with their town hall grows in the future.
The news media deliberately over-rates social media
News media outlets, including TV, radio and print, gain a significant benefit crowd-sourcing live information, free of charge, from the public on social media. It is only logical that they will cheer on social media sites and give them regular attention. Have you noticed that whenever Facebook's publicity department makes an announcement, the media are quick to publish it ahead of more significant stories about social or economic issues that impact our lives? Why do you think the media puts Facebook up on a podium like this, ahead of all other industries, if the media aren't getting something out of it too?
The tail doesn't wag the dog
One particular example is the news media's fascination with Donald Trump's Twitter account. Some people have gone as far as suggesting that this billionaire could have simply parked his jet and spent the whole of 2016 at one of his golf courses sending tweets and he would have won the presidency anyway. Suggesting that Trump's campaign revolved entirely around Twitter is like suggesting the tail wags the dog.
The reality is different: Trump has been a prominent public figure for decades, both in the business and entertainment world. During his presidential campaign, he