“How We Learn” by Benedict Carey covers a vast body of research on learning science and challenges some commonly accepted learning practices. In this series of posts, I summarize my interpretation of the practical advice presented in the book. I am looking at the contents from several perspectives: are there better ways to learn myself, are there better ways to teach, and how can I help my kids to study more efficiently.

The book is entertaining, informative, and provides specific recipes for making learning more effective that one can easily incorporate into everyday life. A common thread throughout the book is about the positive effects of alternating different aspects of learning: physical places, noise level, context, types of problems, sleep, distractions, focus periods, etc. A condensed list of findings includes the following (however, read more to understand the context!):

• Studying in the same quiet place at the same time of day is overrated. Varying the setting (where and how we study, what sounds we hear while we study, etc.) can help retention.
• Spacing the study time instead of cramming it all at once before the test gives a “free” boost to results.
• Testing is learning, so self-examination and flash cards are good, as long as we don’t cheat by looking at the answers.
• Fluency illusion is when, looking at the material, we think we know it. Self-examination can bring the gaps to light.
• Teaching someone else what you just learned is in itself a learning technique.
• Distraction is not all that bad when we are stuck. Short and long-term distractions work slightly differently, and both can get us “unstuck.”
• Interrupting an activity keeps it top-of-mind and attunes our brains to relevant information, which can be used on purpose to keep thinking about the problem in the background.
• Start on complicated long-term projects as soon as possible: it prevents the project from growing on you, and because you keep thinking about it, it may not be as difficult as it seems at first.
• Mixing different skills during practice enhances the benefit of repetition by making what we learn applicable to a previously unseen or a real-life situation. This approach works for sports, music, math, and almost any other subject.
• Sleep improves learning by consolidating and processing what we learned, and it’s good to have at least a 1-1.5 hour nap before the test.
• Perceptual learning, which is when we learn automatically without thinking by discerning patterns among closely related subjects (paintings, equations, etc.), is a subject of its own and has exciting implications for creators of educational apps and video games.

In the three follow-up posts, I summarize what’s behind these findings, and the book itself has much, much more.

• Part 2 – The Basics
• Part 3 – Distraction
• Part 4 – Interleaving and Perceptual Learning

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The post Summary of “How We Learn” by Sergei Izrailev appeared first on Life Around Data.

This is Part 2 of 4 of my summary of “How We Learn” by Benedict Carey. Other parts:

• Part 1 – Summary
• Part 3 – Distraction
• Part 4 – Interleaving and Perceptual Learning

Memory strengths: storage and retrieval

The theory of learning states, among other things, that memory has two strengths: storage and retrieval. Once we store something in memory, it is there forever (more or less) – the size of the storage in the brain is more than enough to save every second of one’s life. The learning strength “builds up steadily with studying, and more sharply with use,” and it can only increase. On the other hand, much of learning is about retrieval strength. It is how easily we can remember what we learned or experienced previously. The retrieval strength also increases with studying and with use, however, it drops off quickly without reinforcement. Also, the “capacity [of retrieval] is relatively small, compared to storage. At any given time, we can pull up only a limited number of items in connection with any given cue or reminder.” Improvements to the learning process are then aimed at increasing the retrieval strength, especially long term and as applied to situations and problems that we didn’t study directly (generalization).

The power of forgetting

Think of learning as building a muscle: forgetting is important because “the harder we have to work to retrieve a memory, the greater the subsequent spike in retrieval and storage strength (learning).” The practical use cases of this finding include (more details to follow):

• Spacing of study sessions: let yourself forget some of what you studied to make it harder (but still possible) to retrieve by breaking your study time in multiple sessions.
• Self-testing and testing in general – unaided retrieval of what you’ve already learned is in itself a learning process. In my opinion, this speaks in favor of more tests in school, but only if they are low-pressure, i.e., not carrying the weight of future admissions to the next level of education.

The effect of context on learning

Studies show that changing the context of where and when we learn helps retrieval. For example, contextual cues, such as the place where we study, the background music, the light and color of the environment, weave themselves into the learning and when present again help trigger the memory of what we learned. “We can easily multiply the number of perceptions connected to a given memory — most simply, by varying where we study.”

Breaking up the study time

Spacing out study sessions has been proven to help for improving retention of memorized material. “If the test is in a week, and you want to split your study time in two, then do a session today and tomorrow, or today and the day after tomorrow. If you want to add a third, study the day before the test ( just under a week later ).” The book provides a specific recipe for varying time intervals for preparing for a test. This technique works well for memorizing facts such as foreign languages, names, places, etc.

Testing is learning

Many of us had used a technique when someone is asking us questions about the material that we expect to be on the test, and we try to answer these questions from memory. It turns out that not only the process checks our knowledge, but also by remembering the answers without looking at the notes or textbook, we are improving our retrieval strength of the material. Such testing can be a test given by the teacher or a self-examination, for example, trying to recite a poem by heart. An essential aspect of this process is providing the correct answer immediately or shortly after the test. Many online corporate training programs use this technique (on purpose or not) by providing short quizzes and highlighting correct answers afterward.

Another interesting concept is pre-testing, i.e., testing for something you haven’t learned yet — the mere process of guessing the right answer wires our brains to the material taught after the pre-testing. As a result, we have a much better recall during the tests performed after the learning is complete.

To summarize, “testing does not = studying, after all. In fact, testing > studying, and by a country mile, on delayed tests.”

Teaching someone is an effective learning technique

There is a saying to the effect of “you haven’t learned the subject until you can teach it to others.” Trying to explain to someone what you’ve just learned triggers better learning and elucidates the gaps in your understanding. A long time ago, I read a book about a woman who made a living teaching foreign languages in Poland after World War II. She only knew Polish when she started. She then achieved fluency in seven languages by studying them herself lesson by lesson from books and then teaching the same lessons to her students. She was always just a couple of lessons behind with her students than what she was learning herself. In my own experience, explaining a concept to someone brings clarity that is rarely achieved by just reading about it. By the way, writing this article also has this effect!

Fluency illusion

The fluency illusion is “the belief that because facts or formulas or arguments are easy to remember right now, they’ll remain that way tomorrow or the next day.” When we look at notes, highlighted sections, or outlines, we feel that we know the material. However, when the notes are not available, we can’t remember anything. The illusion is so strong that is it is easy to convince yourself that you are ready for the test if you can recall something you just read. This illusion is a consequence of the fact that “the easier it is to call a fact to mind, the smaller the effect on learning.” Self-examination mentioned above is an ample antidote to the fluency illusion.

The role of sleep

Sleep has a consolidating effect on learning. Experiments showed that people who had a 1-1.5 hour nap or slept overnight between studying and testing performed better on the tests. The book explains the 5 phases of sleep and makes an interesting point that a full cycle nap of 1-1.5 hours was shown to affect learning similar to a full 8-hour overnight sleep. I conjecture that for those pulling all-nighters before the exam, even a couple of hours of sleep can improve the results. “Unconscious downtime clarifies memory and sharpens skills — that it’s a necessary step to lock in both. In a fundamental sense, that is, sleep is learning .”

Next: Summary of “How We Learn” – Part 3: Distraction

All quotes above are from the book “How We Learn“.

Photo by Alexis Brown on Unsplash.

The post Summary of “How We Learn” – Part 2: The Basics by Sergei Izrailev appeared first on Life Around Data.

This is Part 3 of 4 of my summary of “How We Learn” by Benedict Carey. Other parts:

• Part 1 – Summary
• Part 2 – The Basics
• Part 4 – Interleaving and Perceptual Learning

Distraction

Have you ever felt a solution to a problem spontaneously come to you after you’ve been distracted from focusing on the problem? Any great ideas in the shower? It is a common phenomenon, which is the primary subject of another book, “The Net and the Butterfly” by Olivia Fox Cabane and Judah Pollack. They argue that there are two networks in our brain: the top-of-the-mind “executive” network and a default “background” network. The book “How We Learn” breaks the interruptions that allow the background network to kick in into short-term (incubation) and long-term (percolation). Incubation is a distraction lasting for some number of minutes and involving playing a video game, just spacing out, reading a book, whereas percolation is a longer-term repeated interruption spanning days, weeks and months.

Short-term distraction: Incubation

Incubation refers to distraction periods of 5-20 minutes that work best for problems that have a single solution that is not readily apparent. The process involving incubation consists of three stages. The first is preparation that can last hours or days (or longer) when we struggle to solve a problem at hand. The second is incubation that starts when we temporarily abandon the problem. It is essential that at this point we’ve reached an impasse and got stuck rather than just experienced a bump. “Knock off and play a videogame too soon and you get nothing.” The third stage is illumination, or the “aha” moment. The final stage is verifying that the idea that came during illumination works.

“The Net and the Butterfly” tells us that the “aha” moments are fleeting and that we need to write down the ideas and insights before they fade away. Also, several practical techniques are useful to increase the frequency of the “aha” moments by understanding how and when they occur.

There are “two mental operations that aid incubation: picking up clues from the environment, and breaking fixed assumptions.” An example of a fixed assumption is the “puzzle” of “A doctor in Boston has a brother who is a doctor in Chicago, but the doctor in Chicago doesn’t have a brother at all.” The fixed assumption is that a doctor must be a male, and the answer is, of course, that the doctor in Boston is a woman. Numerous puzzles and experiments investigate the fixed assumptions. Incubation helps break the fixed assumptions and therefore solve problems from a different angle.

Long-term distraction: Percolation

Percolation is a long-term cumulative process that is distinct from the short-term incubation. “Percolation is for building something that was not there before, whether it’s a term paper, a robot, an orchestral piece, or some other labyrinthine project.” In my mind, percolation is a process of thinking about a project or a problem on and off, keeping it in mind the whole time. The “off” time is when percolation happens, often, subconsciously. Again, the trick is to catch the moment and write down the ideas coming from percolation before they disappear.

“Quitting before I’m ahead doesn’t put the project to sleep; it keeps it awake. That’s Phase 1, and it initiates Phase 2, the period of … casual data collecting. Phase 3 is listening to what I think about all those incoming bits and pieces. Percolation depends on all three elements, and in that order.”

Interruptions

Part of the discussion of percolation in the book deals with interruptions. Studies show that an activity that was interrupted, especially in the worst possible moment, remains top-of-mind for some time because we tend to think of unfinished tasks as goals. This finding leads to two distinct use cases, one of which is described in “How We Learn.” Deliberate self-interruption causes the brain to keep being attuned to information that may be relevant to the problem at hand, and make connections with already stored information, while in the “background” mode.

A different use case is described in the book “Deep Work” by Cal Newport and has to do with purging out unfinished tasks from your at the end of the workday so that you can relax at night and not think about work.

Next: Summary of “How We Learn” – Part 4: Interleaving and Perceptual Learning

All quotes above are from the book “How We Learn“.

Photo by JESHOOTS.COM on Unsplash.

The post Summary of “How We Learn” – Part 3: Distraction by Sergei Izrailev appeared first on Life Around Data.

This is Part 4 of 4 of my summary of “How We Learn” by Benedict Carey. Other parts:

• Part 1 – Summary
• Part 2 – The Basics
• Part 3 – Distraction

Interleaving

We’ve all heard the advice of using repetition when practicing a skill. Without a doubt, the repetition of a single skill works. As it turns out, practicing mixed skills works much better. “Varied practice produces a slower apparent rate of improvement in each single practice session but a greater accumulation of skill and learning over time.” For example, badminton players who practiced three different types of serves in random order did better in a slightly different setting (serving to the other side of the court) than players who practiced the same serves in blocks, one type of serve per training session. Another example comes from learning about art. “Counterintuitive as it may be to art history teachers … interleaving paintings by different artists was more effective than massing all of an artist’s paintings together.”

The discussion of mixed practice also touches on a phenomenon that I also observed in the past, when “kids who do great on unit tests — the weekly, or biweekly reviews — often do terribly on cumulative exams on the same material.” The same happens in sports when someone who performs very well during practice seems to lose it during an actual game. The reason is thought to be the inability of choosing a strategy for solving a problem on a test. In unit tests, we typically practice a single approach that we just learned. On a cumulative test (and in real life!), one needs first to decide which strategy is appropriate, and then apply it. Interleaving different types of problems during learning helps the skills to be more applicable under varying conditions.

Interleaving increases our ability to generalize and apply learnings in different situations. “The science suggests that interleaving is, essentially, about preparing the brain for the unexpected.” In practical terms, the advice is to mix learning new material with a dose of “stuff you already know but haven’t revisited in a while.”

Perceptual learning

What is a “good eye”? How can a chess grandmaster understand the position on the board in a few seconds, a professional baseball player decide to hit the ball, and an experienced airplane pilot to quickly make sense of the navigation panel with so many dials? Experience is critical here, but apparently, there is a type of learning that happens automatically without thinking and can help us develop a “good eye” for specific situations. Moreover, we can do it “cheap, quick and dirty.”

Perceptual learning happens automatically, i.e., without our conscious participation, when we are repeatedly exposed to whatever we want to learn to distinguish from one another – painting styles, airplane control readings, similar squiggles, sounds, pictures of birds – and given correct answers. “We have to pay attention, of course, but we don’t need to turn it on or tune it in.” During this process, “the brain doesn’t solely learn to perceive by picking up on tiny differences in what it sees, hears, smells, or feels. … it also perceives to learn. It takes the differences it has detected between similar – looking notes or letters or figures, and uses those to help decipher new, previously unseen material.”

An example of a practical application of perceptual learning is a “perceptual learning module” (PLM) – a computer program that trains pilots to read the airplane instrument panels. It displays the instrument panels with a choice of 7 possible answers describing the state of the plane, such as “Straight & Level” or “Descending Turn.” When the trainee gives a wrong answer, it flashes and provides the right one. Initially, novices are merely guessing. However, “after one hour [of training] they could read the panels as well as pilots with an average of one thousand flying hours.” Note that “it’s a supplement to experience, not a substitute.” The pilots still need to fly the plane.

In another example, the author describes a training system that he devised for himself to learn 12 painting styles by using a PLM loaded with images of 120 paintings, 10 per style, with interleaving of different styles. After one hour of practicing, he was able to identify the styles of previously unseen paintings with an 80% accuracy.

The implications of the success of PLMs are enormous. One can imagine a whole plethora of learning apps that build the “good eye” from learning Chinese characters and math equations to radiology and chemistry. It follows that in situations when an experienced professional would say that something is not right and then investigate, we can train ourselves to recognize such circumstances, given labeled data, without having years and years of experience.

Being a data scientist, I find perceptual learning to be fascinating since on the surface the process resembles so much how AI algorithms “learn” patterns in the data by “looking” at examples with correct labels. In deep neural networks, just like in our brains, we don’t necessarily understand exactly how the connections are made and why the system can recognize pictures of cats or human faces.

Conclusion

In this series of posts, I attempted to summarize the book’s findings and suggestions that I found interesting. There’s a lot more in the book itself, so I encourage you to read the original.

All quotes above are from the book “How We Learn“.

Photos by Tadas Mikuckis and Arie Wubben on Unsplash.

The post Summary of “How We Learn” – Part 4: Interleaving and Perceptual Learning by Sergei Izrailev appeared first on Life Around Data.