Greg Tang

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Greg Tang

Greg Tang

@gregtangmath

Speaker, Educator, Children's Author, Math Author, and Idealist. My goal is simple. Help kids become smart, well-rounded people who love to learn!

Henderson, NV Katılım Nisan 2009
4 Takip Edilen23.6K Takipçiler
Greg Tang
Greg Tang@gregtangmath·
I love this!!
Ihtesham Ali@ihtesham2005

A Hungarian psychologist raised three daughters to prove that any child could become a chess grandmaster through early specialization. He succeeded. Two of them became grandmasters. One became the greatest female chess player who ever lived. Then a sports scientist looked at the data and found something nobody wanted to hear. His name is David Epstein. The book is called "Range." The Polgar experiment is one of the most famous case studies in the history of deliberate practice. Laszlo Polgar wrote a book before his daughters were even born arguing that geniuses are made, not born. He homeschooled all three girls in chess from age four. By their teens, Susan, Sofia, and Judit were dominating tournaments against grown men. Judit became the youngest grandmaster in history at the time, breaking Bobby Fischer's record. The story became the gospel of early specialization. Pick a domain young, drill it hard, and you can manufacture excellence. Epstein opens his book by telling that story honestly and then quietly demolishing the conclusion most people drew from it. Chess works that way. Most things do not. Here is the distinction that took him four years of research to articulate, and that almost nobody who quotes the 10,000 hour rule has ever read. There are two kinds of environments in which humans develop expertise. Psychologists call them kind and wicked. A kind environment has clear rules, immediate feedback, and patterns that repeat reliably. Chess is the cleanest example. Every game ends with a winner and a loser. Every move is recorded. The board never changes shape. The pieces never invent new ways to move. A child who plays ten thousand games will see most of the patterns that exist in the game, and pattern recognition is exactly what chess mastery is built on. A wicked environment is the opposite. Feedback is delayed or misleading. Rules shift. The patterns that worked yesterday may be exactly the wrong patterns to apply tomorrow. Most of the real world looks like this. Medicine is wicked. Investing is wicked. Building a company is wicked. Scientific research is wicked. Almost every job that involves a complex changing system with humans in it is wicked. The Polgar sisters trained in the kindest environment any human can train in. Their success was real and the method was correct. The mistake was generalizing the method to fields where the underlying structure of the environment is completely different. Epstein's research is what made the implication impossible to ignore. He looked at the careers of elite athletes outside of chess and golf and found that the pattern was almost the inverse of what people assumed. The athletes who reached the very top of their sports were overwhelmingly people who had played multiple sports as children, specialized late, and often switched disciplines well into their teens. Roger Federer played squash, badminton, basketball, handball, tennis, table tennis, and soccer before tennis became his focus. The kids who specialized in tennis at age six and trained year-round for a decade mostly burned out, got injured, or topped out at lower levels of the sport. The same pattern showed up everywhere he looked outside of kind environments. Inventors with the most patents had worked in multiple unrelated fields before their breakthrough work. Comic book creators with the longest careers had drawn for the most different genres before settling. Scientists who won Nobel Prizes were dramatically more likely than their peers to be serious amateur musicians, painters, sculptors, or writers. The skill that mattered in wicked environments was not depth in one pattern. It was the ability to recognize when a pattern from one domain applied unexpectedly in another. That kind of thinking cannot be built by drilling a single subject. It can only be built by accumulating mental models from many subjects and learning to move between them. The deeper finding is the one that should change how you think about your own career. Specialists in wicked environments often get worse with experience, not better. Epstein cites studies of doctors, financial analysts, intelligence officers, and forecasters showing that years of experience in a narrow domain frequently produce more confident judgments without producing more accurate ones. The expert builds elaborate mental models that feel comprehensive and turn out to be increasingly disconnected from the actual structure of the problem. They stop noticing what does not fit their framework. They mistake fluency for understanding. Generalists do better in wicked domains for a reason that sounds almost mystical until you understand the mechanism. They have less invested in any single mental model, so they abandon broken models faster. They are used to being a beginner, so they are not threatened by the discomfort of not knowing. They have seen enough different domains that they can usually find an analogy from one field that unlocks a problem in another. The technical name for this is analogical thinking, and the research on it is one of the most underrated bodies of work in cognitive science. The single most useful sentence in the entire book is the one Epstein puts almost as a throwaway. Match quality matters more than head start. A person who tries six different fields in their twenties and finds the one that genuinely fits them will outperform a person who picked one field at fourteen and stuck to it on willpower alone. The lost years were not lost. They were the search process that produced the match. Every field they walked away from taught them something they later imported into the field they finally chose. The reason this is so hard to accept is cultural, not empirical. We tell children to pick a path early. We reward the prodigy who knew at six. We treat the late bloomer as someone who failed to launch on time, when the data suggests they were running an entirely different and often more effective optimization process underneath. The Polgar sisters were not wrong. The conclusion the world drew from them was. If your environment is genuinely kind, specialize early and drill hard. If it is wicked, and almost every interesting human problem is, then the people who win are the ones who refused to specialize until they had seen enough to know what was actually worth specializing in. You are not behind. You were running the right experiment all along.

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Restricted footage
Restricted footage@Restrictfootage·
Marriage in a nutshell… 😂
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Greg Tang
Greg Tang@gregtangmath·
What's WAY more important than engagement? Learning! Engagement is not a measure of learning. Taught a 30-min virtual lesson on measurement to 9 Gr 1 classes. How do I know they were learning? They used sign language & white boards to show me their thinking. 100% engagement, too!
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Greg Tang
Greg Tang@gregtangmath·
@d_besch Goal is to have fluency games for every topic, in every unit, in every grade level, for next year's program. Think it's going to be a game changer! If you want to test some out this year, please email me. I always welcome your thoughts, Dana!
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Greg Tang
Greg Tang@gregtangmath·
5 year old Theo & younger brother playing Tammy's new game. On Friday, needed to use his fingers to figure out number bonds to 10. By Monday, could make ALL the number bonds for ALL the numbers from 2 to 10 in a few seconds. No counting or using fingers. A new day is dawning!
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Greg Tang
Greg Tang@gregtangmath·
I like this! Insights can be applied to math and many other pursuits as well. At this year's Fresh Thinking Conference, Professor Margaret Keane will be offering insights on memory and learning. July 20-21 in Purchase, NY. Can't wait! freshthinkingfoundation.org
Ihtesham Ali@ihtesham2005

A Harvard psychologist quietly admitted something that destroys the way most people study. She said it during a routine advising session, and a student posted it in a study group that eventually reached hundreds of thousands of people. Her name is Jessie Schwab, and she works inside the Harvard College Writing Program. Here's what she said: "Learners are often bad judges of their own learning. Memorization seems like learning, but we probably haven't deeply processed that information enough to remember it days or even hours later." That one sentence explains why you can study for three hours and still blank on the exam. Here's the system she actually teaches Harvard students instead. Before you read a single word of a new chapter, stop and write down what you already know about the topic and what you expect to learn. This primes your brain to treat new information as an update, not a cold upload. While you read, take notes about connections to other things you know, not just definitions. The brain doesn't store isolated facts well, but it stores relationships between ideas extremely well. After you finish, close the material and try to summarize what you learned from memory. The struggle of retrieval is the actual learning. Reading it again is just comfortable, not effective. The researchers she references call this "desirable difficulties," and the analogy is perfect: reading your notes is like watching someone else lift weights. Testing yourself is actually going to the gym. The students who use this system at Harvard aren't necessarily smarter. They've just stopped confusing the feeling of familiarity with the fact of retention. Those are two completely different things, and most people never figure that out.

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Greg Tang
Greg Tang@gregtangmath·
Loved working with this terrific team of 1st Grade teachers from Massachusetts. Greg Jr and I are happy to answer questions, help with lesson planning, and teach students virtually whenever our teachers need help. We go all out for our schools and districts!
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Greg Tang
Greg Tang@gregtangmath·
Join us this summer in New York! We are co-hosting our summer math conference with Rockland Teachers Institute & Manhattanville University on July 20-21 in Purchase, NY. @RocklandTeacher @Mville_U It's a new paradigm for what summer PD can be. Join us! FreshThinkingFoundation.org
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Greg Tang
Greg Tang@gregtangmath·
@Amypbarrett Not yet. We are creating games for every unit of every grade level. Will be ready to go in August. Imagine kids practicing the exact skills they need thru cleverly-designed math games. Email us if you'd like to try a few this spring!
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Greg Tang
Greg Tang@gregtangmath·
My favorite musical for the third time!
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Greg Tang@gregtangmath·
So happy to see Greg Jr at your school! We love teachers like Amy who are passionate about teaching, math, and teaching math. If you are, too, then join us for Year 2 of our Fresh Thinking Conference. Math – and you – will never be the same! FreshThinkingFoundation.org
Amy Crenshaw@abcrenshaw

@gregtangmath Mr. T Jr in the wild! @ClaytonCardinal teachers spend an afternoon fine tuning their math skills with the best of the best! 🤸🏻‍♀️

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NBC Olympics & Paralympics
NBC Olympics & Paralympics@NBCOlympics·
JACK HUGHES DELIVERS AMERICA'S GOLDEN MOMENT IN OVERTIME.
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Greg Tang
Greg Tang@gregtangmath·
@loomiunite I wrote Math Fables and Math Fables Too while watching my 3 kids play hockey. I would sit by myself with my laptop, watch their shift, then work on my poems until their next shift!
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Greg Tang
Greg Tang@gregtangmath·
Proud of these kids. And thank you to their teachers, parents, and volunteers! If you liked this challenge, just wait until you see what we are working on for next year. Fluency + Tons of Practice = Automaticity!
Moore Elementary@fssdMES

We were able to celebrate @gregtangmath challenge successes yesterday with ice cream floats for 4th grade & ice cream sundaes for 3rd grade! Thanks to the parent volunteers who showed up to help make it happen during recess time

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Marc Nixon
Marc Nixon@MarcNixon24·
BREAKING: Olympic US women’s hockey team scores a goal in overtime, BEATING Canada and winning the Olympic gold medal, 2-1 x.com/nicksortor/sta…
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