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Product details
File Size: 821 KB
Print Length: 330 pages
Page Numbers Source ISBN: 0674729013
Publisher: Harvard University Press; 1 edition (April 14, 2014)
Publication Date: April 14, 2014
Sold by: Amazon Digital Services LLC
Language: English
ISBN-10: 0674729013
ISBN-13: 978-0674729018
ASIN: B00JQ3FN7M
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Amazon Best Sellers Rank:
#24,286 Paid in Kindle Store (See Top 100 Paid in Kindle Store)
Okay, well maybe I am overstating that a little. But the main "thesis" of Peter Brown's book - aside from being a summary of what cognitive science data shows about how we learn - is basically that many of the things we often assume about learning are wrong. Here are some of them: we learn best by reading and rereading a passage until we really understand it. WRONG! We learn best when we isolate a skill and practice it over and over again. WRONG! We all have learning styles that are the way we learn best. WRONG! IQ (or something like it) imposes relatively firm limits on how much information we can absorb. WRONG!In this pretty easy-reading book, Peter Brown summarizes some of the latest findings in cognitive science, and many of these findings contradict what is often assumed about learning. First, many k-12 and college students are taught to (and do) use the 'reread and highlight' method to try and absorb content. Well, while this works to an extent, it leads more to an illusion of mastery than mastery. What works better? Read the content and quiz yourself; information retrieval is the key. Retrieving helps to build stronger connections in the brain that will lock information into memory. What's more - and this is another chapter - the harder the retrieval, the stronger your retention of what is retrieved. (So, writing a short essay recalling the concepts works better than true/false and multiple choice recall.)Another myth? While we all certainly have learning preferences (I like to receive my information in written form), that doesn't mean we learn best when receiving information in that form (I can do as well when I receive information audibly as when it is written, even though I prefer the latter). Brown reviews literature that shows that, at least as of now, there is no evidence that shows that how one receives information substantially affects how well we learn the material (after all, hearing or reading a phone number is immaterial to what i am remembering: not the sound or sight of the number, but the number itself). But what they do find is that whether one is an "example learner" or a "rule learner" does have an impact in how well one learns. That is, those who see and practice a math problem and are able to see what the rules are behind the example and commit the rule, rather than the example, to memory will tend to learn better. Also, another factor that affects how well we learn is our mindset, whether we learn for mastery or learn for performance. Those who learn for performance - so that they can show how good they are - tend to tackle learning new things (things that might make them look bad) with trepidation, but those who learn for mastery aspire to acquire new skills openly, without regard to whether they will fail before mastering.These are just some of the lessons from this book. Whether you are a student, teacher, professor, coach, trainer, or any other professional whose job entails teaching others, this is a good book to have. (I'm a professor in a College of Education, and I definitely plan on allowing what I've gleaned from this book to inform my practice.) It is quite informative not only by way of learning theory, but backs up the theory with both empirics and suggestions for practice. Good one.
“People generally are going about learning the wrong ways. Empirical research into how we learn and remember shows that much of what we take for gospel about how to learn turns out to be largely wasted effort. Even college and medical students—whose main job is learning—rely on study techniques that are far from optimal. At the same time, this field of research, which goes back 125 years but has been particularly fruitful in recent years, has yielded a body of insights that constitute a growing science of learning: highly effective, evidence-based strategies to replace less effective but widely accepted practices that are rooted in theory, lore, and intuition. But there’s a catch: the most effective learning strategies are not intuitive. ...This is a book about what people can do for themselves right now in order to learn better and remember longer. ...We write for students and teachers, of course, and for all readers for whom effective learning is a high priority: for trainers in business, industry, and the military; for leaders of professional associations offering in-service training to their members; and for coaches. We also write for lifelong learners nearing middle age or older who want to hone their skills so as to stay in the game.While much remains to be known about learning and its neural underpinnings, a large body of research has yielded principles and practical strategies that can be put to work immediately, at no cost, and to great effect.â€~ Peter Brown, Henry Roediger, Mark McDaniel from Make It StickWant to learn about the science of successful learning?Then this is the book for you. Make It Stick is written by story-teller Peter Brown and two leading cognitive scientists who have spent their careers studying learning and memory: Henry Roediger and Mark McDaniel.It’s a fascinating exploration of what science says about the most effective learning techniques— shining light on the techniques that actually work and those that do not work—even though we may think they do!Hint: Rereading, massed “practice-practice-practice†sessions, and cramming are not wise strategies. Active retrieval, interleaving, spaced repetition, reflection, elaboration, getting your mind right and practicing like an expert, on the other hand, are very good strategies.Here are some of my favorite Big Ideas:1. Fluency vs. Mastery - Don't just go w/your feelings.2. Cranberries + Testing - Active retrieval is where it's at.3. Curveballs - Interleave yourself some curves.4. Elaboration - Explain it like I'm 5.5. Testing - Static vs. Dynamic.To optimizing and actualizing and making it stick!
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