Combating Knowledge Interference (Flashcard Refactoring)

I came across this computer networking Anki flashcard I’ve forgotten over 7 times:

(NW for Sysadmins: Ethernet) Address Resolution Protocol (ARP) – Maps Ethernet addresses to IPv4 addresses and back.

The card uses cloze deletions [] like this:

  • (NW for Sysadmins: Ethernet) [Address Resolution Protocol (ARP)] – [Maps Ethernet addresses to IPv4 addresses and back].
  • (NW for Sysadmins: Ethernet) Address Resolution Protocol (ARP) – Maps [Ethernet addresses] to [IPv4 addresses] and back.

Interestingly, I haven’t forgotten a single review for the right-hand side clozes. Turns out this was the one causing me trouble:

(NW for Sysadmins: Ethernet) […] – Maps Ethernet addresses to IPv4 addresses and back.

Why? The issue seems to be another card in my deck that is very similar, and I’m confusing the two. The other card quizzes a networking concept called “Neighbour Discovery (ND)”, which performs a similar function to ARP except it maps IPv6 addresses to Ethernet and back rather than IPv4 addresses. This is a good example of interference, which refers to the fact that learning similar things can make you confuse them (see Rule 11 of Poitr Wozniak’s classic article on the 20 rules of formulating knowledge).

So the solution I’m opting for is pretty simple, just add a hint:

  • (NW for Sysadmins: Ethernet) ARP (hint: not ND) – Maps Ethernet addresses to IPv4 addresses and back.

One other small improvement is adding another card for the acronym alone:

  • Front: (NW for Sysadmins: Ethernet) ARP (Unpack Acronym)
  • Back: Address Resolution Protocol

These interference issues are tricky because you can’t really anticipate them in advance. You have to discover them as you review your cards.

Another annoyance is I’m not 100% sure that interference was actually the problem. Ideally, I would have discovered this troublesome card during review, so I could know for sure why I’m failing.

So here are some lessons learned from this little exercise:

  • Use hints as an effective tool for reducing interference.
  • Keep an eye out for interference during review of your knowledge. As soon as you encounter it, note it. In the case of Anki, there is a “mark card” feature. I also recommend actually writing text within the card to remind yourself exactly how you failed the card when you fix it later. It would be nice to be able to see basic card statistics, like number of lapses, during review without having to go into card statistics. I inquired on reddit whether there was an addon for this and while there are some good options for desktop, it doesn’t seem like there’s anything that quite meets this need for mobile (where I do all of my reviews).
  • As you get better at knowledge building, interference will become your most common problem. As Poitr Wozniak says, interference is “probably the single greatest cause of forgetting in collections of an experienced user” of spaced repetition systems since it is hard (impossible?) to avoid even if you are really good. You typically discover it during knowledge review time, not knowledge construction time.

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Flashcard Refactoring

I’ve started a weekly habit of flashcard review. I want to share with you my thought process for modifying my cards, because I think this will be valuable to help you improve your own knowledge construction skills.

I also want my flashcard development out in the open so you can call me out when I make mistakes and provide suggestions for further improvements. Please do reach out! I am by no means the ultimate expert in knowledge construction.

So, I will be doing a regular series I call “Flashcard Refactoring” (Refactoring comes from the programming term which basically means revising and improving your code).

To sniff out poor flashcards, I ran prop:lapses>7 in the Anki browser to get all the cards I’ve forgotten over 7 times. Here’s one I came across about a command in the Linux command line to a suspend a job:

  • Side 1: ^Z (Linux Command Line)
  • Side 2: Suspend a job running in the foreground (Linux Command Line)

The card is reversible, so are two cards in total: one with Side 1 as the question, and another with Side 2 as the question.

At first glance, it doesn’t look too bad. It’s fairly concise. But one quick and easy change is reduce words in Side 2, in accordance with the 12th rule of Formulating Knowledge (“Optimize Wording”):

  • Side 2: Suspend foreground job (Linux Command Line)

This is a nice little improvement, but why am I really forgetting this card? I think it’s because ^Z doesn’t really have any meaning – it seems arbitrary and it has no clear connection to suspending foreground jobs.

So, I’ll create a fake connection, i.e. a mnemonic.

The mnemonic that immediately came to mind was the fact that the beginning of “Suspend” kind of sounds like a “Z”, e.g. “Zuspend”. I think this is all that’s required for this to stick in my memory (but only time will tell).

When you come up with a mnemonic, it’s a good idea to create a separate card for it, so I added the following to my deck: 

  • Q: Mnemonic for remembering ^Z suspends foreground job in Linux Command Line.
  • A: Zuspend

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Roam Notes on David Perell Podcast: Tyler Cowen’s Production Function

  • "Author::" [[David Perell]] [[Tyler Cowen]]
  • "Source::" https://www.perell.com/podcast/tyler-cowen-production-function
  • "Recommended By::" [[David Perell]]
  • "Tags:: " #Productivity #podcast #writing
  • Expansion of David Perell’s Show Notes

  • [[Modesty]] signals high value.
  • 2:40 – What [[Tyler Cowen]] considers his compounding advantage.
    • Start early and keep going for many years. Many stop learning and self-improvement as they get older.
    • Why do people stop learning and self-improvement? Starting early you give up a normal childhood, which isn’t necessarily bad but many don’t want to do it. Once you reach a certain age (e.g. 45) you can take paths that have high income but low growth / learning (e.g. [[Consulting]])**, so why go the extra mile? **
  • 5:56 – Why being born as an intelligent person is not as important as developing knowledge. #intelligence #knowledge
    • A good lesson is there are many smarter people than you. Figuring out you’re pretty smart, but not that smart is actually a good combination.
  • 8:23 – How [[Tyler Cowen]] maximizes the value of his [[consumption]] and minimizes the drawbacks.
    • A lot of the value of [[consumption]] is [[memory]] or [[anticipation]]. You can cut consumption of bad things by 2/3, but still get most of the benefit (e.g. eating dessert).
  • 9:19 – What draws [[Tyler Cowen]] to the people he likes spending time with, and what he likes best about their friendship.
    • Advantages of people in [[Silicon Valley]]:** super smart but not necessarily highly educated so they don’t just believe what everyone else does. **They think outside the box. They’re thinkers as well as people that have had to do things and pass [[reality]] tests. The only test most academics face is "can I publish this piece?"
  • 12:33 – Why [[Tyler Cowen]] feels that the way he has lived his life has meant has not given anything up.
  • 15:35 – How the fundamentals of productivity came intuitively to [[Tyler Cowen]].
    • He writes every day, with the exception of 10-15 days a year. If you write every day, you don’t have to worry about how much you’ve written, it’s going to add up. The regularity also pushes you along a learning curve so you’ll get more done. #writing
    • One thing he does is lay out arguments of views he disagrees with. You understand them better, sympathize with them more, and sometimes you change your mind. It makes you stupider to repeat views you agree with / are familiar with. #writing #Thinking
  • 17:41 – Why [[Tyler Cowen]] writes in his particular style not by choice, but by necessity.
    • There’s a beauty / clarity choice in [[writing]]. He’s not good at the beautiful prose type of writing. He focuses on clarity.
  • 22:19 – Why the things in [[Tyler Cowen]]’s life that bind his [[output]] aren’t what you think.
    • Big binding factors: [[ideas]], time spent writing / thinking, and time spent talking to people (which helps him come up with ideas).
  • 24:06 – How to develop new [[ideas]] while staying focused on the subject and not getting tangled.
    • Just keep [[writing]] and re-writing. A book will typically be reworked 10 times. Effort and application – there are no tricks.
  • 27:36 – Why [[Tyler Cowen]] sees [[art]] as one of the most important and beneficial things you can spend your [[time]] and [[money]] on.
    • You make your home special, learn other cultures, learn other points of review, develop judgement skills useful in other areas.
  • 32:41 – What writers can learn about inspiration and consistency from [[musicians]] and [[visual artists]].
    • Many [[artists]] tend to work in bursts. That’s not how he writes. Some writers are like that.
    • The half-life of ideas is very short. Be selfish, maximize your personal learning and your impact now. Don’t worry about [[legacy]]. Take [[Gary Becker]] – one of the top [[economics]] Nobel laureates. Nobody reads him now.
  • 37:16 – Why [[Peter Thiel]] has impacted [[Tyler Cowen]] so deeply and why Tyler believes he’s one of the greatest thinkers of our time.
    • He understands the [[humanities]] so well. [[Tyler Cowen]] sees him as a top thinker in this area.
    • He has the best [[bullshit]] detector of anyone he’s ever spoken with. He gets when people are bluffing. He’s probably the best selector of [[talent]], and to do that well you need to have a deep understanding of things that at least correlate with the [[humanities]]. #Hiring
    • He takes the [[humanities]] seriously, and takes a deeply [[moral]] perspective. This is looked down upon and discouraged in a lot of [[academia]]. He takes [[religion]] seriously, takes input from a variety of sources, has real-world experience with companies, fluency in two languages ([[English]] and [[German]]).
  • 40:30 – How [[Tyler Cowen]] is able to extract more from his [[reading]] than other people do.
    • He has [[hyperlexia]]
    • Talks about [[Norway]], some major figures there and why he has read up on major figures in the country.
    • Also talks about prepping for [[Margaret Atwood]]
  • 45:44 – How understanding most other people’s [[intelligence]] is higher than his in most fields gave [[Tyler Cowen]] an edge over other thinkers.
  • 49:00 – Why [[Tyler Cowen]] sees a new visibility of [[talent]] in people and how he is using this visibility.
    • He’s bullish on [[Craig Palsson]], @marketpower on [[Twitter]]. He wants to be out there, determined, focus, and caring about getting things right. The emphasis on [[writing]] is commonly a big plus – it’s a sign of clear thinking.
    • [[David Perell]] sees his advantage as someone that takes action quickly. [[Tyler Cowen]] adds that successful people have an honest "what am I good at" [[metarationality]].
  • 55:24 – How [[Tyler Cowen]] constructs his [[interviews]] to maximize the freedom of his guests to speak freely on what they love.
    • His interview style likely doesn’t apply to most others, unless you read a lot.
    • He doesn’t [[probe]], because people repeat a lot and get defensive.
  • 1:00:03 – How to develop skills as a teacher and where [[Tyler Cowen]] believes the strengths of a good teacher lie. #Teaching
    • Student evaluations aren’t that helpful.
    • He gets better by just teaching a lot.
  • 1:03:34 – Why the novelty and beauty of visiting other cultures excites [[Tyler Cowen]] so much. #travel
  • 1:07:18 – How [[Tyler Cowen]] makes the most out of his travels. #travel
    • It wasn’t until he saw a large number of places did he start to love [[travel]]. The first place he went outside of the US was Oxford, England. He didn’t get much out of it, didn’t really enjoy it that much.
  • As you get older and more successful, it’s harder to get critical [[feedback]] from people. Hang out with critical people and hope you can get benefits. It’s hard to do this. If you are around people that are above you in the hierarchy, you should be critical too. #aging
  • He hasn’t seen anyone better than [[Patrick Collison]] at quickly learning new [[concepts]], by an order of magnitude.
  • 1:13:32 – Why sitting in a suboptimal seat at a concert may give you worse sound but a better understanding of the [[music]]. #concerts #[[live music]]
    • Mentions going to [[The Village Vanguard]] randomly, because you know whatever is there will be good.
  • 1:16:55 – Why knowledge workers are often not motivated to improve their [[skills]]. #[[knowledge work]]
    • Some of it is a fault in the market, because it’s hard to recognize talent. That’s why [[Tyler Cowen]] is writing a new book on spotting talent. You can do things to improve, but there is not always a return because the market doesn’t recognize it. If you’re better at spotting [[talent]], it makes more sense to invest in it.
    • You need a somewhat long [[time-horizon]]
    • You don’t really need [[discipline]]. It can be a form of entertainment or [[procrastination]] to improve your skills. Discipline and [[Conscientiousness]] are more ambiguous than we realize.
  • "The more you know, the more you can order things into coherent thoughts." Learning begets [[learning]]. True of reading, true of travel, true of food. #chunking #Thinking #skills
  • 1:20:48 – Why [[Tyler Cowen]] still responds to every [[Email]] and loves it.
    • He finds time for this because of what he doesn’t do: he hardly watches [[TV]], **his social life is basically the same as his intellectual life **- his social life is geared towards thinking, discussing, exploring ideas. With no TV, you end up with a lot of [[time]]. #[[unproductive internet activities]]
    • Isn’t [[email]] a low leverage use of his time? **He learns a lot from people that email him, and has filtered his audience so it’s mostly smart people. **He does this by being "sufficiently weird". He’s not even sure it’s highly leveraged. He met [[Patrick Collison]] that way. He doesn’t care if it’s highly leveraged if he’s learning from it. #[[Audience Building]]

Anki / Spaced Repetition Tip: Review your Weak Flashcards

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I’ve been a long-time user of spaced repetition tools. I’ll never forget first hearing about SuperMemo from a close friend as I started my undergraduate degree in 2005. I was immediately sold on the value of spaced repetition, and I particularly liked the idea of computers automatically taking care of review scheduling for you. I started using SuperMemo as a central tool for studying, and saw my academic performance skyrocket.

Over the years, I’ve slowly improved my skill in designing flashcards. It is by no means a trivial skill: it took me years to get pretty good at it, and to this day I still often make flashcards that are complete failures.

I believe there will eventually be an open collaborative platform for flashcard development and sharing, where experts can contribute and refine perfectly crafted cards. Users contribute their deck statistics, revealing poorly formed cards and contributing to our understanding of optimal flashcards.

But until that day, it pays to develop your flashcard creation skills.

Flashcard quality is top of mind for me since I’ve revisited the classic article by Peter Wozniak (of SuperMemo fame), “Effective Learning: Twenty Rules of Formulating Knowledge)”. It is a must-read for anyone that creates flashcards for learning (i.e. almost everyone at some point in their life). I’ve published my summary notes on this article (aside: my notetaking tool of choice is Roam my notes are easy to copy-paste into your own Roam database if you happen to use it as well).

One great way to improve your flashcard development skills, while simultaneously improving the quality of your deck, is to review your old cards regularly. Review your top 10-20 most problematic cards weekly, and for each one you encounter, do one of the following things:

  • Revise: With the Twenty Rules of Formulating Knowledge by your side, refine your card or break it down into a larger number of small, easy to digest cards.
  • Suspend: If you don’t think you need to have a card in spaced repetition anymore, but don’t want to delete it entirely, suspending is a good option.
  • Delete: If you know the knowledge is completely useless to you, trash the card entirely.

But what cards should you review? If you’re like me, you have a pretty big collection, and it’s just not feasible to review all your cards every week to find the weak ones.

Anki makes it quite easy to find these problematic cards. Two main search commands in the Anki Browser are useful here:

  • tag:leech – this finds all of the “leeches” in your Anki deck, which are cards that you keep forgetting. By default, Anki tags your card as “leech” when you fail a card 8 times.
  • prop:lapses>n – this reveals all of the cards you have failed (“lapsed“) over n times. You can set n to whatever number you like. Start with high-n cards and work your way down.

In addition to using these search techniques, I try to make a habit of “marking” cards that are problematic or poorly formed in some way, during review. If it’s an easy correction (e.g. obvious suspension, or small text changes), I’ll make the change right away in the mobile app. Otherwise, I will simply mark the card and filter it out during weekly review to make improvements.

When you do revise your cards, I recommend “resetting” the card so it’s like a “do-over” – the card should be reviewed again as if you just created it. This serves two purposes: it ensures that the card will no longer show up in your “problem cards” lists when you do the above queries. It also provides you with more opportunities to review your new formulation of the knowledge.

Unfortunately, it seems the only way to do this in Anki is do create new card(s) with the information you want and delete the old one. There is an option for “rescheduling” the card, but this only restarts the review process and doesn’t delete your review history. As a result, the card will still appear as one of your problem cards if you do a query like prop:lapses>n. Luckily, it’s not much extra effort to do this.

I have to admit that I do not entirely practice what I preach here. Weekly review of my cards is something I haven’t fully incorporated yet, but I’m resolving to start doing it today. In the next weeks, I’m going to experiment with a Flashcard Refactoring series to illustrate the card refinement process. Stay tuned!

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Roam Notes on Poitr Wozniak (Supermemo) Twenty Rules of Formulating Knowledge

  • "Author::" [[Poitr Wozniak]]
  • "Source::" https://www.supermemo.com/en/archives1990-2015/articles/20rules
  • "Recommended By::"
  • "Tags:: " #Flashcards #[[Spaced Repetition]] #[[flashcard design]] #Learning
  • Summary

  • The rules are listed in order from most important / common to least.
  • Rule 1: Do not learn if you do not understand. Trying to memorize things you don’t understand increase the time to learn and more importantly, reduces the value of the knowledge to nothing (e.g. memorizing a German history book when you don’t know German – you won’t know any of its history). #[[Flashcard Tip: Don’t add Things you Don’t Understand]]
  • Rule 2: Learn before you memorize. He recommends building an overall picture of the learned knowledge before memorizing. You’ll reduce learning time when the individual pieces fit a single coherent structure. So, read the chapter first, then add the cards. #[[Flashcard Tip: Learn Before you Memorize]]
    • Notes: Why can’t you learn with [[Flashcards]] alone? Perhaps this is efficient if presented in the proper order. Also, perhaps the cards need to change when first learning when compared to committing to long-term memory. If so, how do they change? In other words, how are "questions for learning" different than "questions for retention"? #[[Personal Ideas]]
  • Rule 3: Build upon the basics. Start simple, and build from there. Don’t hesitate to memorize basic, obvious things. The cost of memorizing them is small, because they’re easy to answer. "usually you spend 50% of your time repeating just 3-5% of the learned material" source #[[Flashcard Tip: Build Upon the Basics]]
    • Notes: The basics provide [[scaffolding]] that you can build upon. This reminds me of the [[80-20 rule]], where a big chunk of your time is spent on a small number of [[flashcards]]. #[[Flashcard Tip: Track Down and Eliminate Your Problem Cards]].
  • Rule 4: Stick to the minimum information principle. Formulate knowledge as simply as possible. Simple is easy to remember, and having a complex answer means there is more to remember – a larger number of simpler cards covering the same knowledge lets you review each sub-component at its own appropriate pace. #[[Minimum Information Principle]] #[[Flashcard Tip: Follow the Minimum Information Principle]]
  • Rule 5: Cloze deletion is easy and effective. #[[Flashcard Tip: Use Cloze Deletion]]
  • Rule 6: Use imagery. Our brains are wired for them. They usually take more time to create though compared to a basic verbal card, so weigh the benefits. #[[Flashcard Tip: Use Images]]
  • Rule 7: Use mnemonic techniques. He makes an interesting point that these do not solve the problem of forgetting, since the bottleneck is long-lasting and useful memory, not quickly memorizing knowledge. For that, you need #[[Spaced Repetition]]. "Experience shows that with a dose of training you will need to consciously apply mnemonic techniques in only 1-5% of your items". #[[Flashcard Tip: Save Mnemonics for Difficult Cards]] #mnemonics
  • Rule 8: Graphic deletion is as good as cloze deletion. #[[Flashcard Tip: Use Image Occlusion]]
  • Rule 9: Avoid sets. Sets are unordered collections of objects. Very difficult to memorize. If you must, use [[enumerations]] instead, which are ordered in some way. #sets #[[Flashcard Tip: Avoid sets]]
  • Rule 10: Avoid enumerations #enumerations #[[Flashcard Tip: Avoid Enumerations]]
    • He includes a nice method for [[memorizing text]] such as [[poems]] or [[prayers]], without using [[cloze deletion]]
  • Rule 11: Combat interference: #[[memory interference]] #[[Flashcard Tip: Combat Interference]]
    • Learning similar things tends to make you confuse them. [[memory interference]] – "knowledge of one item tends to make it harder to remember another item".
    • "**Interference is probably the single greatest cause of forgetting in collections of an experienced user of **[[SuperMemo]]."
    • The only strategy to work against this is detect and eliminate. It’s hard to know you’ll face interference at card creation time.
  • Rule 12: Optimize wording #[[Flashcard Tip: Optimize Wording]]
    • Shave down the number of words you use. Make your cards as clear and concise as possible. Focus on the piece of information that is important.
  • Rule 13: Refer to other memories #[[Flashcard Tip: Refer to Other Memories]]
    • When you add a new card, try incorporating things you’ve learned from other cards.
  • Rule 14: Personalize and provide examples: #[[Flashcard Tip: Personalize and Provide Examples]]
    • Link your cards to your personal life.
  • Rule 15: Rely on emotional states: #[[Flashcard Tip: Rely on Emotional States]]
    • We remember things better that are vivid or shocking.
  • Rule 16: Context cues simplify wording: #[[Flashcard Tip: Use Context Cues]]
    • They often reduce the number of words you need
  • Rule 17: Redundancy does not contradict minimum information principle #[[Flashcard Tip: Use Redundancy]]
    • Redundancy – more information than needed or duplicate information.
    • It can be good, and minimum information principle does not mean minimum number of characters in your deck.
  • Rule 18: Provide source: #[[Flashcard Tip: Provide Sources]]
  • Rule 19: Provide date stamping: #[[Flashcard Tip: Use Date Stamps]]
    • Particularly for knowledge that changes over time and can become obsolete.
  • Rule 20: Prioritize: #[[Flashcard Tip: Prioritize]]
    • There is way more knowledge in the world than you’ll be able to absorb and remember long-term.
    • Focus on adding knowledge that is most relevant and important to you.

Excerpts from “The Use of Flashcards in an Introduction to Psychology Class”

Excerpts

  • Abstract: Four hundred fifteen undergraduate students in an Introduction to Psychology course voluntarily reported their use of [[Flashcards]] on three exams as well as answered other questions dealing with flashcard use (e.g., when did a student first use flashcards). Almost 70% of the class used flashcards to study for one or more exams. Students who used flashcards for all three exams had significantly higher exam scores overall than those students who did not use flashcards at all or only used flashcards on one or two exams. These results are discussed in terms of [[retrieval]] practice, a specific component of using flashcards.
  • Despite their apparent prevalence and impressive claims regarding their effectiveness, there appear to be no published studies examining whether flashcard use increases students’ exam performance in a naturalistic context.
    • Researchers have investigated flashcard effectiveness in laboratory settings.
  • A [[crib sheet]] (or cheat sheet) is an index card that contains ‘‘brief written notes’’ for a class and that a student can use during an exam (Dickson & Miller, 2005).
    • some research on crib sheets may pertain to how [[Flashcards]] influence exam performance. Studies have shown that merely creating crib sheets does not aid in student learning because students depend on being able to use the crib sheets during an exam and may not actually learn the exam material (Dickson & Bauer, 2008; Funk & Dickson, 2011). Yet, Funk and Dickson (2011) found that when students created crib sheets but did not expect to use them during an exam, they performed better on that exam than on another exam for which they expected to use their crib sheets. The former condition may be similar to creating flashcards in that students generate and use flashcards with the clear understanding that these cards will not be used during the exam. #[[How Much Does Flashcard Creation Aid Learning?]] #[[Blog Post: How Much Does Flashcard Creation Aid Learning?]]
  • [[Descriptive Statistics About Flashcard Use]]
    • Overall, 69.9% of the class used flashcards for at least one of the three exams; 65.5% used written flashcards, 3.9% used computer flashcards, and 0.5% used both self-generated and [[computer flashcards]]. Also, 55.2% of the class used flashcards (either written or computer) to study for two of the three exams and 34.9% used flashcards to study for all exams.
    • The results showed that flashcards were also used in other classes: 48% used only written flashcards in other classes, 2% used only [[computer flashcards]] in other classes, and 6.5% used written and computer flashcards in other classes. About half of students (49%) who used flashcards in the present Psychology course used them in other courses. Only about a quarter of students (23%) did not use flashcards in any class. Finally, only a small percentage of students (7%) did not use flashcards in Introduction to Psychology, but used flashcards in other courses
  • In our study, students primarily used self-generated [[Flashcards]]. In fact, so few students used [[computer flashcards]] that analyses could not be conducted comparing the two types of flashcards.
  • it is likely that the proliferation of smaller computers and electronic devices (e.g., iPads) will lead to an increase in [[computer flashcard]] use in the years ahead.
  • Flashcard use should be examined in greater detail by investigating the composition of the flashcards that are generated (i.e., what is on each card), how students actually use the cards (e.g., how often do the students test themselves, how long do students spend generating and using flashcards), whether other study techniques are used in conjunction with flashcards, and how the nature of the materials to be studied impacts flashcard use. #[[Gaps in Flashcard Research]]
  • three important [[methodological limitations]] that should be noted
    • there is the possibility that students may have exaggerated or misremembered information about flashcard use
    • the survey was only conducted with a single Psychology class
    • the present study did not include information that might differentiate flashcard users and nonusers #[[selection bias]]

How to Deal with Lists in Anki

Photo by Glenn Carstens-Peters on Unsplash

When adding cards to Anki (or any other spaced repetition system), you’ll find you often need to deal with lists. In the spaced repetition community, these are sometimes called “Sets” (see Anki Essentials, Chapter 7, “The 20 Rules”).

For example, here’s a section from a book I’m working through called The Art of Doing Science and Engineering by Richard Hamming, where he summarizes the main advantages of computers over humans:

“People are sure the machine can never compete, ignoring all the advantages the machines have…These are: economics, speed, accuracy, reliability, rapidity of control, freedom from boredom, bandwidth in and out, ease of retraining, hostile environments, and personnel problems.”

This is a frustrating passage, because it’s packed with valuable information but tough to turn it into flashcards.

One easy approach is to cloze delete each individual option, and then cloze delete the entire list to make sure you can recall the whole thing. While this makes the cards easy to create, you’ll run into these issues when reviewing them:

  • It’s a lot to read, and you have to read every option to know what the missing one is.
  • It’s hard to remember. Even if you do individual cloze deletions for each point, you will still be very likely to fail on the question where you are asked to recall the entire list. Also, many lists (including the example above), are open ended and not necessarily exhaustive. So, when it comes time to review, you’re not quite sure what’s on the list, and you may list things that are “correct” but just not included on that particular list.
  • It violates a fundamental rule of flashcard creation. The “Minimum Information Principle” states that your questions and answers should be as simple as possible. A large number of simple cards is far more efficient to remember than a small number of big, demanding, awkward cards.
  • It’s hard to rate yourself. How do you rate your performance when you get 9 out of the 10 answers in the list correct? Do you fail yourself if you only got one wrong?

So, what are our options for dealing with these annoying lists?

Break it Down

First, ask yourself: do I really need to memorize the list? Do you really need to be able to spout off the list of advantages of computers over humans, and not miss any of points? Probably not.

Then ask yourself, what do I really want to get out of this list? In my example, I want advantages of computers over humans to pop up in my mind when the time is right. For example, when I’m working on a process at work that is repetitive, rote, and requires accuracy, I want to recognize computer scripts as a good solution.

So, I would not Ankify this specific list at all. Instead, I would look in the source to Ankify material focused on each individual point. For example, I could add specific questions on the relative costs of computing compared to manual effort, or details about the speed of computing compared to hand calculations. Doing this will give a deeper understanding of the advantages of computers over humans. It will probably also increase the likelihood of being able to recall the entire list at once (even though it’s unlikely I’ll need to do that).

You can also lists into sub-categories and then add those smaller lists to spaced repetition. Aim for each sub-category to have 1-2 items.

Take Advantage of Special List Structure

Sometimes you can take advantage of the inherent structure of a list to break the flashcard down. For example, your list can take a special form of a “1-n relationship”, as discussed in this thread .

A 1-n relationship is best understood by example. Suppose you want to memorize the Provinces in Canada. This list has the special property where each province in the list is associated with one and only one country (i.e. 1 country – n provinces). With lists like this, you can add questions like “what country does the province of Manitoba belong to?”, “What country does the province of Alberta belong to?”, etc. Of course, this fails if there is a province in another country with the same name, (that would mean it’s not a 1-n relationship), but you get the point.

Turn the List into an Enumeration

One of the problems with the example list of computer advantages is the order of the items has no meaning. There is no reason why “personnel problems” should be last rather than first. This makes it far more difficult to memorize because it’s just a bunch of seemingly random points.

Enumerations are ordered lists. Although they can still be difficult to memorize, they at least have some structure that your mind can latch on to. You should always try to convert your list into an enumeration if it’s not one already.

Ideally, your ordering will contain useful knowledge itself. For example, you could list the advantages of computers over humans, from most important to least important according to the author.

There are many other possibilities for turning lists into enumerations, depending on what you are trying to memorize, such as chronological order, area of the body, size, popularity, population, etc. If you can’t find a meaningful ordering, you can always list items alphabetically.

Enumerations are a free lunch, because they make list easier to memorize and provide bonus knowledge about the material. For example, wouldn’t it be much better to know the order of the planets in the solar system from closest to the sun to furthest, rather than just knowing the individual planets?

Use Cloze Overlapper

After you have turned something into an enumeration. How should you design your repetitions?

One option is to do one cloze deletion per item in the list. For example, take the list (a, b, c, d, e, f). Your cloze deletions are then ([…], b, c, d, e, f), (a, […], c, d, e, f), (a, b, […], d, e, f), etc.

I have done this many times in the past, and while I can usually answer the questions quickly and accurately, I find it hard to retain the information. When asked to reproduce the whole list, I fail. This is because the questions are too easy – removing only one item provides way too much context.

Until recently, I thought this was the best option. Then I came across the “overlapping cloze”: close deletions on individual items in the list, but with only a small amount of context given. For example, something like this: ([…], …, …, …, …), (a, […], …, …, …), (…, b, […], …, …), etc.

It’s actually quite painful to create overlapping clozes in vanilla Anki. Luckily, there is an add-on for this: Cloze Overlapper. This video by Glutanimate, the author of the add-on, provides an overview of issues with lists in and illustrates how how to use the add-on (aside: the author is the developer of another great add-on, image occlusion enhanced). I haven’t tried out Cloze Overlapper yet, so I can’t fully vouch for the technique or the add-on, but it seems to be highly regarded in the spaced repetition community.

Use Mnemonic Techniques

With a bit of practice, mnemonic techniques can help you achieve incredible feats of memory. Many are easy to learn. Even doing a little bit of studying on these techniques can produce big payoffs for your memory.

The technique I probably use most is the link method. For example, one flashcard I have on computer networking asks me to recall the main types of datalink layer errors. I added it as an unordered list: frame errors, drops, collisions, and overruns.

It’s actually a pretty poor card, but I haven’t had much trouble memorizing it because of the mnemonic I used:

  • I think of Link (from Zelda) with a shirt that says ERROR on it (dataLINK layer ERRORS).
  • Then I imagine him putting on some glasses (frame errors)
  • Link throws the glasses down to the ground (drops)
  • A giant truck hits Link (collisions)
  • Finally, the truck runs over the glasses that are on the ground (overruns)

Sounds silly, but it works. Our minds are extremely good at retaining images.

I am by no means an expert in these techniques, but I’ve found that learning a little bit helps a lot. If you go deeper, I’m sure you’ll see even bigger benefits. Other useful memory systems include peg and Method of Loci.

If you use a mnemonic technique for a list in your spaced repetition system, be sure to add flashcards to remember mnemonic itself.

Conclusion

Avoid lists if you can, but if you must, try to break them down into sub-categories, make sure they’re ordered (preferably with some relevant meaning to the ordering), use cloze overlapping to implement the reviews and limit context, and use mnemonic techniques. Together, this will give you a solid arsenal for committing lists to memory without much pain.

Resources

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Why Learning By Teaching Works and How to Use It

Insights from Learning by Teaching Human Pupils and Teachable Agents: The Importance of Recursive Feedback by Sandra Okita and Daniel Schwartz.

Want to commit key points from this blog post to long-term memory? You can access an Anki Deck here.

Special thank-you to Andy Matuschak for pointing me to this paper.

Brief Overview of the Okita and Schwartz Paper

You have probably heard the advice that you should teach something if you really want to understand it. But does it really work, and if so, how?

Okita and Schwartz provide an extremely readable primer on the research behind Learning by Teaching and why it is so effective as a learning strategy.

They also explore a little-known benefit of learning by teaching called “recursive feedback” – feedback from watching your pupils use what you taught them. Using two separate experiments, Okita and Schwartz find that this special kind of feedback significantly improves teacher learning.

In this post, I summarize key insights from the paper on why learning by teaching works, and conclude with some thoughts on specific strategies for learning by teaching to improve your learning.

Why Learning by Teaching Works

Okita and Schwartz divide the learning by teaching process into three distinct phases: preparation (the teacher’s preparations to teach), teaching (the actual act of teaching), and observation (when the teacher receives recursive feedback by seeing the student apply what they learned from the teacher). It turns out that each of these phases contribute to the teacher’s learning.

Preparing

Preparing to teach students helps teachers learn due to three main forces:

  • Motivation: Preparation introduces strong emotions and motivation to truly understand the material and do it justice. This includes a sense of responsibility, the anticipation of a public performance, and a desire to avoid embarrassment or “looking stupid”.
  • Generation: Preparing to teach involves a “generation effect“. The generation effect means that you remember information better when you generate it from your mind rather than passively reading it. Preparing to teach is generative because you have to frequently retrieve and elaborate on information from your memory as you think about how you are going to teach your students.
  • Meta-cognitive vigilance: Meta-cognition refers to an awareness of your own thoughts. It turns out that preparing to teach generates this kind of awareness through the teacher’s self-explaining and self-generated questions as they anticipate the needs and questions of their pupils. This, in turn, helps teachers identify areas where they have conflicting knowledge or incomplete understanding.

Teaching

Three main aspects of this phase helps teachers learn:

  • Explanation. The act of teaching involves explaining ideas to others. This leads to “explanation effects” that occur from explaining ideas rather than just receiving them.
  • Question answering. Students often have questions of their teachers, which can reveal gaps in the teachers understanding or encourage the teacher to extend their understanding. In fact, Okita and Schwartz cite a study by Roscoe and Chi (2007) that found “tutees’ questions were responsible for about two-thirds of tutors’ reflective knowledge-building activity”.
  • Physiological arousal. Anyone that has experienced public speaking knows that it is a very stimulating activity that focuses your mind. As you might expect, this kind of arousal and attention improves learning.

Observing

In this phase, the teacher receives recursive feedback by watching the student apply what they learned. You might think it’s obvious that feedback improves learning, but it turns out that’s not always the case.

For example, direct feedback, where a student tells a teacher directly how well they did, can be counterproductive because people often take this kind of feedback personally, leading to “self-handicapping, learned hopelessness, or social comparison”. When this happens, the recipient of the feedback tends to adopt attitudes like, “well, I guess I’m not the kind of person who’s good at math“. As a result, they give up or opt for an easier subject. As much as we all like to believe we would receive feedback objectively and use it to our advantage, our egos often get involved, whether we like it or not.

Thankfully, recursive feedback side-steps this issue. Since the teacher is not directly receiving feedback from the student, their egos are uninvolved. Instead, they see for themselves what worked and what didn’t. No one explicitly tells them, “this is where you need to improve, this is what you did wrong”. Okita and Schwartz note that this “creates an ego-protective buffer, because the pupil rather than the tutor takes the immediate responsibility for being wrong”.

I also believe recursive feedback helps build empathy skills. A lack of empathy, in my opinion, is often a major barrier to learning and self-improvement. Think of how many people you have encountered in schools or workplaces that have tried to explain something to you, but assume an unreasonable amount of knowledge, leave out critical bits of information, or explain things in ways that are otherwise unhelpful (e.g. using tons of jargon you’re unfamiliar with)? Often these people are very intelligent, and would be far more effective if they gained some empathy.

How can we use these lessons about Learning by Teaching to improve our own learning?

The main lesson I took away from the Okita and Schwartz paper is that Learning by Teaching is not just folk wisdom. It works. So, as learners, we should try to use it wherever we can. Here are some ideas:

  • Develop a course or become a tutor. If there is a topic you really want to master, and you have enough time and resources, you can run an online or in-person course. In addition to the learning benefits, you can make some side income.
  • Observe your students. To take advantage of recursive feedback, you need to be able to see your students apply their knowledge. Use tests, presentations, or projects to see what your students learned.
  • Keep it interactive. Interaction with your students means more questions from them and, as a result, more learning for you. Okita and Schwartz note “Tutoring sessions should be arranged to limit the natural tendency of tutors to slip into didactics, which can eliminate opportunities for pupils to ask questions“. Students will often ask useful questions that help you better understand the material.
  • Write online. Writing online is a form of teaching, whether it’s blog posts, twitter, email newsletters, or something else. It also provides ample opportunity to receive valuable feedback about your work.
  • Develop a smart and interesting following. The quality of pupil questions impacts teacher learning. This means that, if you have an email list or a blog, or some other kind of online following, you learning would benefit from attracting high-quality people. Check out David Perell’s work on writing online, where he emphasizes the importance of writing for intelligent readers and leveraging their feedback to improve yourself.
  • Encourage your students to keep in touch about the projects they work on and how they applied the knowledge you taught them. Your students will appreciate this, and you’ll also get valuable recursive feedback.
  • Build things and watch people use what you’ve built. Okita and Schwartz point out that recursive feedback applies to areas other than Learning by Teaching. For example, producing products, tools, crafts, art, and then getting recursive feedback by observing how your “customer” uses it. One application of this idea that comes to mind is Agile software methodology, which relies on building software quickly, getting feedback on it as soon as possible, and constantly iterating and improving based on that feedback. If you produce something that others consume, you’ll gain by watching them use it.

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Notes on Developing Transformative Tools for Thought

Occasionally, special tools come along that amplify our minds, enabling new kinds of thought not otherwise possible. Computers, writing, speaking, and the printing press are all examples of these “Tools for Thought” that surge human potential. 

This essay from Andy Matuschak and Michael Nielsen explores whether we can accelerate the development of these kind of tools. They also provide a taste of potential tools for thought with their prototype “mnemonic medium”, an interactive post on quantum mechanics called “Quantum Country” with embedded flashcards combined with a spaced repetition system delivered through email follow-ups. 

Their essay is a must-read for anyone interested in spaced-repetition or productive learning. There are several points I found thought-provoking. I believe each of these insights indicate a need for a new Tool for Thought for flashcard development and sharing.

Spaced repetition creates exponential returns to studying

Based on Quantum Country user data, Matuschak and Nielsen estimate that devoting only 50% more time to spaced repetition after reading the essay resulted in users recalling the key points for months or years. 

In other words, relatively small investments in spaced repetition after reading an article produces outsized results – more evidence to place on top of the mountain of research suggesting spaced repetition works. 

Good flashcard development is difficult

Matuschak and Nielsen note that it takes a surprising amount of skill and time to build quality flashcards, especially for abstract concepts. This is probably a big reason why most people fail to adopt spaced-repetition tools like Anki. Since flashcard development is a skill that you develop over much time and effort, new users tend to add cards in a way that inevitably leads to frustration and failure. 

This may partially explain the efficacy of Quantum Country: the authors are experts in both quantum mechanics and flashcard development – a rare but essential combination of skills for their essay to work. 

Flashcards written by others can be useable

Some people the spaced repetition community don’t believe in using flashcards created by others, and with good reason. They’re often poorly written. They’re idiosyncratic. They’re missing crucial contextual information that you lack as someone who hasn’t read the original source material. I used to be one of these non-believers.

But the effectiveness of the Quantum Country essay suggests that shared flashcards can work well. This has benefits of saving users of the burden of flash card creation, as well as preventing new user frustration from poor flashcard building skills and poor domain knowledge.

Matuschak and Nielsen hypothesize that the quality of their flashcards is what makes this work. I agree, but I have a few more hypotheses: 

  • Their flashcards are introduced in a logical progression as users read the essay. In contrast, shared decks in Anki shuffle cards randomly and are not encoded with dependency information.
  • Their flashcards are clearly connected to a source (i.e. the essay), providing important context for the user.
  • Users learn the material before they review flashcards. This is in line with the common wisdom that flashcards don’t work if you don’t already understand the material – they are a tool for retention, not learning. Aside: is this common wisdom true? I’m not so sure. Socrates taught using Q and A, so why can’t you teach a subject entirely with flashcards? If it is possible, what are the prerequisites to making it work? 

Elaborative encoding

Matuschak and Nielsen note elaborative encoding as another learning tool shown to be extremely powerful in promoting memory. Essentially, it means connecting new ideas you want to remember with old ideas you know well, providing a fast path in your brain to new information. 

Remember this concept while developing your flashcards. Whenever you add a new card, think about what you already know well and how you can connect this to the new knowledge.

A New Tool for Thought?

Matuschak and Nielsen’s article has renewed my interest in a tool for thought idea I’ve been pondering for quite a while: a platform for collaborative flashcards development and sharing. I believe such a tool, if properly developed, can address the issues that limit the use of spaced repetition:

  • Spaced repetition practitioners currently need to develop their own flashcards, which requires a significant amount of time, domain expertise, and flashcard-building skill. There needs to be a place where experts can create shared flashcards, and there should be a proper incentive structure encouraging creators to improve these flashcards over time.
  • Flashcards are not clearly connected to original sources. Spaced repetition practitioners should be able to pull up pre-built flashcards for a source document they are working through. 
  • Current tools do not provide information that link flashcards together (other than knowing two flashcards are part of the same deck, or have the same tag). At the very least, flashcards should have a notion of “depends on” or “prerequisite to”. This would make shared decks more useful by showing the intended progression of knowledge. It would also aid elaborative encoding (e.g. examining cards you’ve reviewed and linking them up to cards “nearby” in a knowledge graph)

I strongly believe a tool like this needs to exist, as you may have guessed if you noticed the Download my Brain feature I built for this site that provides a platform for sharing my personal Anki decks. I have started work on a more generic tool for collaborative flashcard construction and sharing and will keep you posted once I have something ready for production. 

Thanks to Andy Matuschak and Michael Nielsen for the inspiration to follow this path.

If you’re interested in space repetition and techniques for productive learning, subscribe to my Spaced Repetition Newsletter. Check out my shared data science Anki decks here: Download my Brain.

The Hidden Power of Compounding (and 4 Ideas for Harnessing it)

Ways to take advantage of this powerful and often-overlooked force for improvement 

Ever wonder how successful people reach such heights? Think of a wildly successful person you admire. How did they get there? 

The typical answers are hard work, innate gifts (personality, natural ability) and luck. These factors play a role, but the most important factor is left out: they leverage the power of compounding.

What is Compounding?

For compounding to occur, only two things are required:

  • Growth: Something must be growing by some percentage each year
  • Time: The growth process happens over multiple years

You’ve probably heard of a specific type of compounding: compound interest. In this context, compounding means that growing your money by some percentage every year eventually snowballs into huge results if you give it enough time. 

For example, say you are able to earn 7% per year on your money. That doesn’t sound like a lot: if you invest $1000, that’s $70 in a year. Seems pretty modest.

Yes, you’ll earn $70 in year one, but in year 2 you earn $70 (7% of $1000) plus 7% on the $70 of additional money in your account that grew from year 1. As time passes, that 7% per year pumps out bigger and bigger piles of cash:

  • In Year 10: You’ve doubled the size of your account ($1,967)
  • In Year 20: You’ve quadrupled the size of your account ($3,870)
  • In Year 30: Your account is now almost 8 times your original investment of $1,000 ($7,612)

One lesson from this exercise is to save and invest some of your money. Your future self will thank you. 

Another lesson is the earlier you start, the better. More years means more opportunity for exponential growth. 

But there’s an interesting corollary to this exercise that is less obvious, and much more exciting: compounding isn’t just something that happens to your bank account – it applies to many other areas of life. 

“We’re all sort of blundering fools, but if you just get some rate of improvement and let it keep compounding, you can do pretty well…You always want to be on some sort of curve where you’re compounding.”

– Tyler Cowen, on David Perell’s Podcast

All you need for compounding is growth and time – there is nothing about dollars or bank accounts mentioned in that definition. If you can get some percentage growth rate in some area of interest every year, you’ll eventually reach heights you never dreamed possible.

Think about some area where you want to excel. As an example, let’s say you’re in sales. If you improved at sales 10% every year, you would be twice as good in 7 years, four times as good in 15 years ten times as good in 25 years, and seventeen times as good in 30 years. In any given year, you’re not making tremendous improvements, but over time persistence leads to tremendous outcomes.

Also, keep in mind that although 10% growth is a great rate for a bank account, who’s to say this is a good rate of growth for your sales career? Maybe a reasonable growth rate is much higher. If that’s the case, you can expect much more dramatic results. 

I believe this is how extraordinary people like Elon Musk reach rarefied heights: achieving a high growth rate in an area (e.g. managing a private space company) through intense focus and then relentlessly persisting to maintain that high growth rate over many years.

4 Ideas for Better Compounding

There are lots of ways you can compound in an area you want to improve. Look for anything that 1) gives you growth by some percentage or 2) helps you maintain that growth over multiple years. Some of the obvious ideas here include reading, taking lessons, attending talks, working with a mentor, and just simply doing work in the area you want to compound.

That being said, I have a few other tips that can both increase your percentage growth rate (ideas #2 and #3) and ensure you stick to it over the years (ideas #1 and #4). 

Idea #1 – Have a plan

The key to compounding is consistent, focused effort over multiple years. It’s hard to do that without being clear about where you want to improve. If you don’t have clear goals, you’ll forget them or lose discipline, stifling your compounding efforts.

So, I recommend writing down the areas you would like to compound over time. Check back on this list regularly (I check weekly) and make sure that every year you’re making some effort to improve your abilities by some percentage.

For example, here’s a list of areas I’m personally focused on compounding over time:

  • Data science
    • Statistics / math
    • Programming
  • Communication
    • Writing
    • Speaking
    • Sales / persuasion
  • Managing teams / project management
  • Personal brand / developing followers on my blog and email list
  • Health
  • Relationships
  • Cooking
  • Drumming

I keep a Google document of this list and keep track of specific things that I am doing within each category to propel myself forward. 

Idea #2 – Use spaced repetition

You’ve probably had this experience: you read a book or take a course and you want to retain it and apply as much as you can. Inevitably, the precious knowledge slowly exits your mind and 6 months later it feels like you didn’t learn anything in the first place.

Spaced repetition is a solution to this problem.

Spaced repetition is quizzing yourself on knowledge in increasing intervals of time. It’s extremely effective and time efficient. I have flashcards in my spaced repetition system that I just answered that I will not be quizzed on again in 2 years. This spacing allows you to hold tens of thousands of flashcards in your mind while only reviewing tens of flashcards a day. 

For more information about the science behind spaced repetition, check out this great summary by Gwern Branwen.

I have been a long-time user of spaced-repetition tools for committing things to long-term memory. During my university years, I wrote cards in Supermemo for all of my courses, and it was the secret weapon to my performance. Today, I use Anki, and it continues to be a key tool for compounding my knowledge in data science and retaining the vast amount of information required for success in the field.

I’m so excited about spaced repetition, I even have a feature on my website that I built to share my data science Anki decks with the world, organized by source: Download my Brain! I’m also running a Spaced Repetition Newsletter that will provide the latest news and links related to Anki, tips on using Anki, and ideas related to spaced repetition and productive learning.

Idea #3 – Keep a commonplace book

A commonplace book is a place where you store wisdom or interesting things you’ve read or heard from others, or have thought about yourself.  I’ve written previously about the benefits of keeping a commonplace book and a summary of my personal commonplace book system that involves a spaced-repetition-esque component (I wrote code to email myself 5 randomly selected commonplace book notes from my collection). Lots of others have written about them as well (here is a good article from Ryan Holiday, which is where I first heard about this idea). 

A commonplace book is similar to spaced repetition in that it’s a tool to help you retain more of the important things that you learn. It also provides you with a body of material you can draw from, which is particularly valuable if you are a writer. 

I personally use my commonplace book system to hold long-form wisdom that doesn’t lend itself well to flash card quizzing.

Idea #4 – Use commitment contracts

Once you have a plan for compounding in your improvement areas, you need to follow-through with that plan. Over the years I’ve tried many strategies to help deal with this issue of staying motivated and sticking to a plan, and the most effective tool I’ve found are commitment contracts. I’ve used commitment contracts to read and write more than I ever have in the past, despite being busier than ever with a full time job and a 3-year-old at home.

Commitment contracts are agreements where you commit to doing something, and failing leads to actual consequences. For example, I have a commitment contract to spend a minimum number of hours each week on various areas of interest. I track my time during the week, report back each week, and if I’m below my target I’m penalized $5. 

I have found this surprisingly effective, especially considering the low stakes. It doesn’t take much of a penalty to provide enough motivation to follow through with your targets. I think this may be tapping into our inherent loss-aversion: we are irrationally repulsed by a loss, much more than the size of the loss would indicate. Of course, you can make your failure penalties higher if you want, but I personally don’t find it necessary. 

The specific tool that I use for commitment contracts is StickK. I highly recommend it. 

Conclusion

I think these tips will help you out, but the most important point to remember is compounding only requires two things: growth and time. Growth ensures you make progress, and time is what allows you to reach heights you never thought possible. In any given year, you may not be making huge improvements, but over time your persistence leads to huge outcomes.

If you want to commit this article to long-term memory, download the Anki deck I put together for it here. If you are a user of Anki or other spaced repetition tools, you can subscribe to my Spaced Repetition Newsletter for the latest news, tips, and ideas about spaced repetition, using Anki, and improving your learning speed.

I made a speech based on this blog post that you can find here:

This is a speech version of this post from my local Toastmasters group