{"id":6899,"date":"2017-06-13T01:48:19","date_gmt":"2017-06-13T08:48:19","guid":{"rendered":"https:\/\/www.scotthyoung.com\/blog\/?p=6899"},"modified":"2018-03-29T12:56:55","modified_gmt":"2018-03-29T19:56:55","slug":"how-much-do-you-understand","status":"publish","type":"post","link":"https:\/\/www.scotthyoung.com\/blog\/2017\/06\/13\/how-much-do-you-understand\/","title":{"rendered":"How Much Do You Really Understand?"},"content":{"rendered":"How do you know when you understand something? This is trickier than it seems. Explanations are\r\n\r\nrecursive.<\/a>\r\n
\r\n\r\nrecursive.\r\n
<\/div>\r\nRecursion is the algorithmic equivalent of Matryoshka dolls. The same process nested inside itself again and again. This may sound complicated, but we use\r\n\r\nrecursive processes all the time.<\/a>\r\n
\r\n\r\nrecursive processes all the time.\r\n
<\/div>\r\nConsider trying to clean your house. This is a big task, so you might decide to informally operate with the logic, “If the cleaning task is too big, break it into sections and clean each section.” Following this, you decide to split it up into cleaning the kitchen, living room, bathroom, bedroom and garage. Cleaning the bathroom is still a large task, so you might repeat the recursive procedure and split it into cleaning the bathtub, mirrors, toilet, sink and floors.\r\n
<\/div>\r\nThis is a trivial example, but recursion can go deep. Understanding a difficult idea might have dozens of nested layers of explanation to get it completely from scratch.\r\n\r\n<\/div>\r\n
<\/div>\r\nExplanations are recursive because, in order to explain a big idea, you have to explain the pieces that support that idea. To understand those pieces, you have to explain their pieces, and so on. Nested Russian dolls.\r\n\r\n<\/div>\r\nTo see what I mean,\r\n\r\nclick on any text underlined like this.<\/a>\r\n
\r\n\r\nclick on any underlined text and it will expand the explanation.\r\n
<\/div>\r\nRefreshing the page will re-collapse the article. You can selective collapse any expanded explanation by clicking on the little superscript like this one just to the right of this period.\r\n\r\n<\/div>\r\n
<\/div>\r\nKnowing what you know is called\r\n\r\nmetaknowledge.<\/a>\r\n
\r\n\r\nmetaknowledge. How many times have you showed up to a test, thinking you know the material, only to be baffled by difficult questions? Many students who don’t understand the problem of metaknowledge are quick to cast blame on an unfair exam or teacher. After all, they think they know the material, so how could they possibly fail?\r\n
<\/div>\r\n

The Problem of Metalearning<\/h2>\r\n
<\/div>\r\nMetaknowledge is often one of the hardest parts of learning something new. It isn’t simply that you must acquire new facts, concepts and skills, but it might also be unclear exactly what is missing.\r\n
<\/div>\r\nLeo Tolstoy explained it best:\r\n
<\/div>\r\n
“The most difficult subjects can be explained to the most slow-witted man if he has not formed any idea of them already; but the simplest thing cannot be made clear to the most intelligent man if he is firmly persuaded that he knows already, without a shadow of a doubt, what is laid before him.”<\/blockquote>\r\n
<\/div>\r\nIt’s not what you know, but what you know that just ain’t so,\r\n\r\nthat gets you into trouble.<\/a>\r\n
\r\n\r\nthat gets you into trouble.<\/a>\r\n
that gets you into trouble. (This previous sentence is often attributed as a quote to Mark Twain, but it turns out he never said it. The closest we get is a related quote by another 19th-century humorist, Josh Billings<\/a>.)<\/div>\r\n
<\/div>\r\nInterestingly, confidence in knowing that you know and actual knowledge can often be inversely correlated. The Dunning-Kruger effect is a phenomenon where those with less skill or knowledge, falsely believe themselves to know more than\r\n\r\nthose with greater skill.<\/a>\r\n
\r\n\r\nthose with greater skill.\r\n
<\/div>\r\n

The Dunning-Kruger Effect<\/h2>\r\n
<\/div>\r\nThe original studies for the effect were conducted by David Dunning and Justin Kruger at Cornell. They found that participants would over-estimate confidence for a variety of skills such as reading comprehension, medicine, driving, chess or tennis.\r\n
<\/div>\r\nThe duo suggested that the reason for this overconfidence came down to metaknowledge. When participants lacked skill, they simultaneously lacked the ability to assess their own skill. Only by being exposed to training for the skill, did participants begin to realize their own inadequacies.\r\n
<\/div>\r\nLest the tone of this effect sound accusatory, I believe I’ve also been a victim to this effect before. I’ll often believe I have a reasonable grasp on a topic or skill, until I start learning it more deeply. Then, as I learn more and more, I also become aware of how much I don’t know and the depths of expertise that others possess that I only vaguely understood in the beginning. Every answer itself asks new, previously unseen questions. Knowledge expands, but the space of perceived ignorance expands even faster.\r\n\r\n<\/div>\r\n
<\/div>\r\nAs Bertrand Russell famously stated, “The problem with the world is that the stupid are cocksure, while the intelligent are full of doubt.”\r\n\r\n<\/div>\r\n
<\/div>\r\n

Do You Know Your Facts?<\/h2>\r\n<\/div>\r\n
<\/div>\r\nWith facts, metaknowledge is relatively easy. If you want to convince yourself you know the capital of France, you think Paris, and\r\n\r\nconvince yourself you have the right answer.<\/a>\r\n
\r\n\r\nconvince yourself you have the right answer.\r\n
<\/div>\r\nFactual knowledge is easier because the procedure of self-testing gives a fairly reliable cue for whether you possess the knowledge. However, even here, metaknowledge can be incorrect if a different, less reliable procedure is used.\r\n
<\/div>\r\nMany students, for instance, don’t check their factual knowledge with self-testing. Instead, they use activities like re-reading notes to convince themselves they understand the material. This creates a cue that the knowledge was effectively recognized, but not\r\n\r\neffectively recalled.<\/a>\r\n
\r\n\r\neffectively recalled.\r\n
<\/div>\r\n

Recall vs Recognition<\/h2>\r\n
<\/div>\r\nRecall and recognition are\r\n\r\ndifferent cognitive processes.<\/a>\r\n
\r\n\r\ndifferent cognitive processes, but there is debate about whether they are different aspects of the same mechanism (e.g. recognition is just weaker recall, or recognition is a type of recall) or whether they are different mechanisms (e.g. recall involves cognitive processes which aren’t used in recognition).\r\n
<\/div>\r\n

What is the Relationship Between Recognition and Recall in the Brain?<\/h2>\r\n
<\/div>\r\nResearch in cognitive science typically proceeds in the following fashion: someone suggests a model of a system trying to capture some important aspects of how humans think and learn. This model is then compared against experimental evidence which either implies or refutes the model.\r\n
<\/div>\r\nThe state of cognitive science is nascent enough that many fundamental questions of how the brain does what it does are still open to competing interpretations. The difference between recall and recognition is a great example of this.\r\n
<\/div>\r\nIn the research on the relationship between recall and recognition two important models are generate-recognize models, proposed by Anderson, Bower, Kintsch and others; and Tulving’s synergistic ecphory.\r\n
<\/div>\r\nThe generate-recognize model states that recall is a more elaborate process that itself includes recognition. You first generate candidate information (generate) and then you recognize whether or not it is correct. Experiments seem to offer empirical support that recall can, in fact, be estimated by separately\r\n\r\nmeasuring these two different mechanisms.<\/a>\r\n
\r\n\r\nmeasuring these two different mechanisms.\r\n
<\/div>\r\n

Generate-Recognize Models<\/h2>\r\n
<\/div>\r\nBahrick (1970) investigated the two-stage approach by having an experiment with three different groups. One group was asked, after reading a list of words, to generate as many words related to a given category as possible. This gave a rough percentage of successful generation for words. A second group was asked to recognize those words from a larger bank of words of the same category. This gave a percentage of successfully recognized words. Finally, a third group was asked to freely recall the words from the original list in that category. This experiment showed that the free-recall condition was related to the multiplied probabilities of the two stages independently.\r\n
<\/div>\r\n

Tulving’s Critique of the Two-Stage Approach<\/h2>\r\n<\/div>\r\n
<\/div>\r\nTulving and Thompson, however, have a rather strong critique of this. They contend that if recall itself includes recognition, then it would be impossible to recall an item that you couldn’t recognize. Their experiments, however, show that, under special circumstances, you can do exactly that–have subjects be able to\r\n\r\nrecall an item without being able to recognize it.<\/a>\r\n
\r\n\r\nrecall an item without being able to recognize it.\r\n
<\/div>\r\nTo establish this effect, they used an ingenious experimental design. Like most memory experiments, this involved subjects learning a list of words paired with cues (e.g. COLD-ground, KNIFE-pen). However all of the to-be-remembered words also happened to have a strongly-associated word (e.g. COLD-HOT, KNIFE-FORK). The experiment then proceeded in three stages:\r\n
<\/div>\r\n
    \r\n \t
  1. Subjects first learned the words with their cues (COLD-ground).<\/li>\r\n \t
  2. Subjects were presented a list of the words which included the strongly-associated words (HOT, FORK). These were not words given earlier, but, in many cases the subjects nonetheless produced many of the words from the original list. Subjects were asked to tick next to words that were from the original list<\/em>. Invariably, recognition that some of the words produced were from the original list was poor.<\/li>\r\n \t
  3. After, subjects were given their original cues and asked to recall the words (e.g. ______-ground, _______-pen). Recall, here, was actually better than recognition, with subjects recalling more words than they recognized in the previous step.<\/li>\r\n<\/ol>\r\n
    <\/div>\r\nTulving’s explanation here makes some intuitive sense. Because the generated words in the second step were cued by words unrelated to the original learning task, many readers did not recognize them.\r\n\r\n<\/div>\r\nTheir alternative model is that recall and recognition are not actually separate processes, but different variations of the same underlying process, which they call\r\n\r\nsynergistic ecphory.<\/a>\r\n
    \r\n\r\nsynergistic ecphory.\r\n
    <\/div>\r\n

    Synergistic Ecphory<\/h2>\r\n
    <\/div>\r\nThe term “ecphory” comes from a Greek word which roughly means “to be made known.” In Tulving’s theory, memories are stored in combination with some of the information about the event of the original encoding. This includes the cue or cues that would be necessary to retrieve them.\r\n
    <\/div>\r\nIn Tulving’s account, this offers a single mechanism for explaining both recall and recognition. Recognition is just a more specialized type of recall where the cue needed to retrieve the knowledge, is the knowledge itself. Tulving can then explain why recognition is normally easier than recall, because, under normal circumstances a cue that is the information itself is a really good cue!\r\n\r\n<\/div>\r\n

    Why Recognition is Easier Than Recall<\/h2>\r\n
    <\/div>\r\n<\/div>\r\nAlthough researchers debate whether they rely on the same or separate mechanisms, it is the case that, under normal circumstances, recognition is easier than recall. Convincing yourself that you’ve seen something before, when presented it, is much easier than having to search for it given a prompt that does not contain the answer you’re searching for.\r\n
    <\/div>\r\nConsider our capital city example once more. Now, imagine if, instead of Paris, I had asked you the capital of Hungary. Many North Americans would rightly guess Budapest right away. But, many others might stumble, falsely giving the name of another eastern European capital (Prague or Belgrade), or even blank entirely. However, if I asked whether Budapest *is* the capital of Hungary, many more people would quickly assess that this is correct.\r\n\r\n<\/div>\r\n

    Why Metaknowledge is Much Harder with Explanations Than Facts<\/h2>\r\n<\/div>\r\n
    <\/div>\r\nUnderstanding, however, is different. This is because understanding isn’t all-or-nothing. You may\r\n\r\nfeel you know a little, but not enough.<\/a>\r\n
    \r\n\r\nfeel you know a little, but not enough.\r\n
    <\/div>\r\n

    Feeling of Knowing<\/h2>\r\n
    <\/div>\r\nResearchers have actually have a special term for the feeling you have that you know something, creatively called feeling of knowing<\/strong> or FOK.\r\n
    <\/div>\r\nOne of the first questions researchers had about FOK was where it came from. What it just a direct sense of memory strength? In other words, were subjects directly accessing memory engrams and using the strength of those to determine whether they knew something?\r\n
    <\/div>\r\nThrough some ingenious experiments, the answer to that question\r\n\r\nappears to be no.<\/a>\r\n
    \r\n\r\nappears to be no.\r\n
    <\/div>\r\nIn an experiment by Benjamin, Bjork and Schwartz (1998), researchers first asked subjects to answer easy questions. They then asked subjects how many of the answers they could recall freely afterwards if they weren’t presented the questions again. The more questions subjects initially got correct, the more they thought they would later recall. However, this turned out to be negatively correlated with free recall.\r\n
    <\/div>\r\nThis shouldn’t suggest that FOK is always fallible. In many normal circumstances it does predict your ability to know something later. This research merely implies that FOK is not based on direct access to the strength of a memory.\r\n

    Where Does Feeling of Knowing Come From?<\/h2>\r\n<\/div>\r\n
    <\/div>\r\nFOK isn’t based on direct-access to the memory strength but by using various\r\n\r\nmental cues to suggest whether the information is available.<\/a>\r\n
    \r\n\r\nmental cues to suggest whether the information is available.\r\n
    <\/div>\r\nThese mental cues are often related to fluency of processing. That is to say, if thinking about something is easier, you’re more likely to have higher FOK than if thinking about it is hard. Since you don’t actually know how strong a memory is that you aren’t able to access directly, you base your prediction off of something you do have access to, namely, ease of processing.\r\n
    <\/div>\r\nAs a clue to metaknowledge, ease of processing isn’t so bad. However, it can create difficulties when greater ease actually results in worse learning.\r\n
    <\/div>\r\nA great example of this was Hertzog, Dunkosky, Robinson and Kidder’s 2003 study where subjects memorized pairs of words\r\n\r\nusing visual imagery.<\/a>\r\n
    \r\n\r\nusing visual imagery.\r\n
    <\/div>\r\nThe method is fairly simple. Take two words you want to associate. This could be a foreign language word and its translation, a medical term and a plain English equivalent, or even two random words as in the case of these experiments. Now, if both words are easily visualizable, simply combine the images of those words in a random, crazy picture. (Duck > Boat might have a giant duck rowing a boat)\r\n
    <\/div>\r\nIf the words aren’t visualizable you can use a stand-in with an abstract symbol (a clock for time) or a “sounds-like” substitute (“shave an ear” for the French chavirer<\/em>) using visual imagery.\r\n
    <\/div>\r\n<\/div>\r\nSubjects assumed that the word pairs that they quickly formed images for would be the most likely to be remembered, but it\r\n\r\nwas actually the opposite.<\/a>\r\n
    was actually the opposite. This is most likely because longer processing, while being more difficult, also led to subjects holding the mental image longer, which contributed better to recalling the pairing later.<\/div>\r\n<\/div>\r\n<\/div>\r\n
    <\/div>\r\nThe result? People often think they\r\n\r\nunderstand things much better than they actually do.<\/a>\r\n
    \r\n\r\nunderstand things much better than they actually do.\r\n
    <\/div>\r\n

    The Problem of Explanatory Depth<\/h2>\r\n
    <\/div>\r\nWith a factual question, it is relatively easy to self-assess knowledge. You simply try to think of the answer, and if it comes up, you probably know it. The only risk here is that you have mistaken confidence in a wrong answer.\r\n
    <\/div>\r\nWith explanations, you can bring up many different pieces of knowledge at different levels of detail. It’s not possible to go through every single thing you know to accurately assess your knowledge, so you cheat. Instead of using actual knowledge as your cue, you base your feeling of understanding on how easily you’re able to bring up explanatory pieces or experiences of competence with the concept in question.\r\n
    <\/div>\r\nWhile this ease-of-processing judgement isn’t a terrible mechanism, it’s not a perfect one. It can lead you to confuse frequent exposure with deep understanding. It can also lead you to confuse competent use with competent understanding.\r\n
    <\/div>\r\n

    Can You Draw a Bicycle or Can Opener?<\/h2>\r\n<\/div>\r\n
    <\/div>\r\nOverconfidence of understanding is particularly strong with things which are familiar,\r\n\r\nlike bicycles or can openers.<\/a>\r\n
    \r\n\r\nlike bicycles or can openers.\r\n
    <\/div>\r\nWithout looking at a picture of one, could you successfully draw a picture of a bicycle? I’m not looking for artistic achievement, just a simple drawing that has the pedals, handles, frames and gears in the right places.\r\n
    <\/div>\r\nIn one of the most interesting studies<\/a> I’ve encountered in cognitive science so far, researchers asked participants to do exactly this. To everyone’s surprise, most people can’t do this! Typical drawings have numerous errors, many of which would render a bike completely non-functional, such as connecting both wheels to the gears or not connecting the gears with the pedals.\r\n
    <\/div>\r\n\"Many<\/a>\r\n
    <\/div>\r\nIt’s easy to look at these pictures and laugh, but the reason this happens is quite interesting. Bicycles are common. Most people know how to ride one. This results, upon introspection, in a fairly easy processing of bike-related ideas. This ease-of-processing is, incorrectly, translated as evidence of understanding how a bike works mechanically.\r\n
    <\/div>\r\nAnother great example of this is a can-opener.\r\n\r\nCould you describe how one works?<\/a>\r\n
    \r\n\r\nCould you describe how one works?\r\n
    <\/div>\r\nWriter and former AI-researcher David Chapman did this test himself and fell for the same trick<\/a>:\r\n
    <\/div>\r\n
    I did this after reading the Rozenblit paper<\/a>, and was surprised to find that my explanation had some details wrong, and significant missing parts. I also discovered, after playing with two ordinary manual crank-turning can openers, that they worked on completely different principles. I’ve used both types a million times, and never noticed this, because you use them exactly the same way. My rating of my original understanding went from 6 to 3. I’m estimating my new understanding at 6, but I’m worried I’m still overconfident! [link added]<\/blockquote>\r\n
    <\/div>\r\nCan openers are a great example because we use them a lot, they appear simple and the mechanism itself isn’t hidden. This all contributes to a heightened illusion that we understand them better than we do, in fact.\r\n\r\n<\/div>\r\n

    Improving Your Metaknowledge<\/h2>\r\n<\/div>\r\n
    <\/div>\r\nWhat can you do to\r\n\r\nimprove your metaknowledge?<\/a>\r\n
    \r\n\r\nimprove your metaknowledge?\r\n
    <\/div>\r\n

    Improving Metacognition and Metaknowledge<\/h2>\r\n
    <\/div>\r\nMetaknowledge is part of a broader concept known as\r\n\r\nmetacognition.<\/a>\r\n
    metacongition, which can be loosely translated to mean thinking about thinking. This includes not only metaknowledge, but also how the learner thinks about choosing strategies for effective learning, self-regulation and error correction. The whole enterprise of learning how to learn better can be said to be an effort to improve metacognition or metacognitive strategies.<\/div>\r\n
    <\/div>\r\nSome research finds that metacognition has an independent explanatory effect on learning performance beyond IQ. This implies that metacognitive abilities, might be more than just being smart, but represent a unique ability we use to improve learning.\r\n
    <\/div>\r\nMetacognition can be broken down into two particular abilities: monitoring and control. Monitoring, which includes metaknowledge, is the self-awareness of\r\n\r\nwhat you know and how well you’re learning.<\/a>\r\n
    \r\n\r\nwhat you know.\r\n
    <\/div>\r\n

    What is Declarative Metaknowledge?<\/h3>\r\n
    <\/div>\r\nDeclarative metaknowledge is the easiest to understand of the three components. It simply represents how well you know what it is you know. Poor declarative metaknowledge means you have difficulty determining what you know and what you don’t.\r\n\r\n<\/div>\r\nControl takes the insights of monitored cognition and applies it to\r\n\r\nchange your behavior.<\/a>\r\n
    \r\n\r\nchange your behavior.\r\n
    <\/div>\r\n

    Metacognitive Control<\/h2>\r\n
    <\/div>\r\nThere’s different types of control that take place in learning. Planning before the learning takes place. Monitoring and adjustment during the learning task. Finally, evaluation and error-correction that take place after one has learned.\r\n\r\n<\/div>\r\n
    <\/div>\r\nMany metacognitive improvements are relatively straightforward. If you feel like you’re not paying attention well (metacognitive monitoring) you may then decide to take notes or tune out distractions (metacognitive control).\r\n
    <\/div>\r\nOther metacognitive improvements comes from having a broader knowledge of different ways one can approach a learning problem and a\r\n\r\nsense of their differed effectiveness.<\/a>\r\n
    sense of their differed effectiveness. A clear example of this is the research by Rabinowitz, Ackerman, Craik and Hinchley (1982) which showed that students who used visual imagery to remember words, remembered far more that those who used only repetition. However their individual judgements of learning were the same in both cases.<\/div>\r\nMy efforts to uncover and promote learning methods essentially fall into this category of metacognitive improvements. It’s my belief that knowing more approaches to learning as well as why and how they work gives the learner a way to handle more and more problems effectively.\r\n
    <\/div>\r\n

    Tips for Improving Metaknowledge<\/h2>\r\n<\/div>\r\n
    <\/div>\r\nFirst, don’t trust yourself that you understand something.\r\n\r\nTest it.<\/a>\r\n
    \r\n\r\nTest it.\r\n
    <\/div>\r\nPractice testing is one of the only two studying methods investigated by this comprehensive meta-analysis<\/a> to have strong empirical support for its use. (The other was\r\n\r\ndistributed practice.<\/a>\r\n
    distributed practice, the idea of spacing your studying sessions over many smaller intervals instead of cramming in one big chunk.<\/div>\r\n)\r\n
    <\/div>\r\nPractice circumvents the need to rely on imperfect cues of metaknowledge. Instead of relying on ease of processing, familiarity or fluency to decide whether you understand something, you face down actual problems that test your knowledge.\r\n
    <\/div>\r\nNot every subject you want to understand will have practice problems, but practice, generally construed, is possible\r\n\r\nwith almost any subject.<\/a>\r\n
    \r\n\r\nwith almost any subject.\r\n
    <\/div>\r\n

    How to Practice Without Questions<\/h2>\r\n
    <\/div>\r\nWhen I mention the robust research supporting practice in learning, many interested learners bemoan that this might work for math or physics with ample problem sets, but what about history, art, psychology or any numerous other subjects without well-defined problem sets and solutions to test oneself on?\r\n
    <\/div>\r\nMy answer to this is that everything you are learning has some end-use situation. This doesn’t mean that all knowledge is ultimately practical, in some hands-on sense. Many times, what you want to learn is for the purpose of learning other things or in participating in intellectual discussions. I’m curious about art history, not because it has real practical significance, but so that I can interpret what I see in an art museum or participate in discussions about those topics.\r\n
    <\/div>\r\nThe answer of how to practice these subjects is embedded in their end-use case. As an example, if I want to assure myself I really understand some psychology, and my reason is that I want to be able to discuss it in another context, a good practice task would be to be able to write an article about the topic in question. When the real-use case is too onerous, I might substitute it with a modified,\r\n\r\nrelated practice task.<\/a>\r\n
    \r\n\r\nrelated practice task.\r\n
    <\/div>\r\nI usually like to think of the real-world usage case as a starting point in the reflection of how to practice, not always an end-point. When learning, however, there can be two good reasons to deviate from this starting point: drills and accessibility. Drills allow you to focus on subproblems of the learning\r\n\r\nactivity more directly.<\/a>\r\n
    \r\n\r\nactivity more directly.\r\n
    <\/div>\r\n

    Using Drills<\/h2>\r\n
    <\/div>\r\nA good learner first starts by thinking about what the real-use case is for knowledge. This is because if you copy the learning strategies of someone who has different aims, you may end up learning inefficiently. This might sound esoteric, but it’s really a\r\n\r\ncommon, practical problem.<\/a>\r\n
    \r\n\r\ncommon, practical problem.\r\n
    <\/div>\r\nConsider learning a language. There are many, many different reasons to learn a language. You might want to learn to travel easily. To work in a different country. To become a translator. To watch foreign movies or read foreign literature.\r\n
    <\/div>\r\nAll of these goals have considerable overlap. But they also differ in emphases. When Vat and I were traveling in China<\/a> to learn Mandarin, for instance, one of my goals was eventually being able to read literature. Vat had no interest in this. As a result, we opted for somewhat different starting strategies. I pursued an approach that involved both character learning and spoken practice, while his focused exclusively on the latter.\r\n\r\n<\/div>\r\n
    <\/div>\r\nHowever, expert practice often\r\n\r\ndoesn’t spend most of its time on real-use cases.<\/a>\r\n
    \r\n\r\ndoesn’t spend most of its time on real-use cases.\r\n
    <\/div>\r\n

    Deliberate Practice and Drills<\/h2>\r\n
    <\/div>\r\nIn the literature on mastery Anders Ericsson makes it clear that a big difference between elite performers and those of middling achievements is the amount of time spent on deliberate practice. This type of practice is directly put in contrast with “real use” situations. Given this prominent contrast, why am I nonetheless advocating real use as a reasonable way to learn things well?\r\n
    <\/div>\r\nIn my mind, real-usage is a starting point, not a destination. What Ericsson notes is that real usage (say playing games for an athlete or complete songs for a musician) isn’t insufficiently focused.\r\n
    <\/div>\r\nImagine that you’re trying to become an elite violinist. Any given song may only have a few key tricky parts, with the rest being within the threshold of your current ability. Playing a piece that takes several minutes may only really test your ability a small percentage of the time. By doing drills, you increase that to nearly one-hundred percent.\r\n
    <\/div>\r\nAdditionally, focusing on drills allows one to more closely monitor and correct one’s performance. In a basketball game, your cognitive resources are split between many different factors requiring your attention. Doing a layup drill, however, you can focus all of your mental resources exclusively on the mechanics of that one action.\r\n
    <\/div>\r\nNote, however, that all of these activities support the end use–namely, playing actual games or pieces. The performer (or coach) will decide what subproblems of the learning task require attention and focus learning on those areas.\r\n\r\n<\/div>\r\nElite musicians don’t just play a lot of music. Basketball players don’t just play games. They do drills.\r\n
    <\/div>\r\nThe reason why is that drills allow them to focus their learning efforts on the particular sub-problems of learning which are creating the most difficulty. These are then integrated backwards into the whole learning pursuit. This is a difficult activity that requires considerable self-awareness and often benefits from guided coaching.\r\n\r\n<\/div>\r\nAccessibility allows you to practice more effectively when real-use practice is\r\n\r\ndifficult to obtain.<\/a>\r\n
    \r\n\r\ndifficult to obtain.\r\n
    <\/div>\r\n

    Modifying Learning for Accessibility<\/h2>\r\n
    <\/div>\r\nModifying practice for accessibility is a common practice because the real-use case might not be easy to access or participate in.\r\n
    <\/div>\r\nFor instance, your end goal for knowledge might be to use the knowledge in a writing situation. But writing an essay for every concept you learn would take way too much time. As a result, you substitute the real-use case with a different practice activity that might be flawed, but benefits from being easier to apply. In this case, you might opt for pausing after each chapter to speak a brief summary of the ideas to yourself.\r\n
    <\/div>\r\nThese modified activities are often weaker than the full practice. This means that they might miss important elements of the original practice activity. However, because they are easier, they might occupy\r\n\r\nmore practice time than the real-use situation.<\/a>\r\n
    \r\n\r\nmore practice time than the real-use situation.\r\n
    <\/div>\r\nFor an example of how this might play out, imagine you’re trying to learn AI and deep learning. There’s so many concepts that you decide to triage your efforts. You know that implementing a real-world AI application is the end-use. But you decide that easier, substitute activities are: doing a mock problem, explaining the concept to yourself and just reading the material. You then decide to split your time so on a few of the most useful ideas you do a real implementation, on more of the ideas you do some kind of toy problem, on many of the smaller details you just do a self-explanation and finally for a bulk of the details you satisfy yourself to just have read the material.\r\n\r\n<\/div>\r\n<\/div>\r\n<\/div>\r\n
    <\/div>\r\nPractice may not always be obvious, but figuring out how to practice inevitably involves asking deep questions about your motivations for learning.\r\n\r\n<\/div>\r\n<\/div>\r\n
    <\/div>\r\nWalking through an explanation can be a good way to\r\n\r\nimmediately find holes in your understanding.<\/a>\r\n
    \r\n\r\nimmediately find holes in your understanding.\r\n
    <\/div>\r\n

    The Feynman Technique<\/h2>\r\n
    <\/div>\r\nOne of my favorite methods for this is something I call the\r\n\r\nFeynman Technique.<\/a>\r\n
    \r\n\r\nFeynman Technique.\r\n
    <\/div>\r\nThis process was inspired by reading Richard Feynman’s autobiography where he detailed a problem he had understanding a difficult physics paper. His sister told him to go back and read through the paper as if he was a student at school:\r\n
    <\/div>\r\n
    “No, what you mean is not<\/em> that you can’t understand it, but that you didn’t invent<\/em> it. You didn’t figure it out on your own<\/em> way, from hearing the clue. What you should do is imagine you’re a student again, and take this paper upstairs, read every line of it, and check the equations. Then you’ll understand it very easily.” [emphasis in original]<\/blockquote>\r\n
    <\/div>\r\nWhile I’m uncertain on the exact details of how Feynman did this, my own process has a similar outcome. Instead of throwing your hands up to say you don’t understand something, go through it systematically to find out what you don’t understand.\r\n\r\n<\/div>\r\nYou can see a demo here:\r\n
    <\/div>\r\n