- Recognize anyone can learn almost anything with the right approach. 0:00 - Understand the role of prior knowledge in learning new skills. 1:03 - Acknowledge that working memory and fluid intelligence can improve with expertise. 2:09 - Realize the importance of cultural and societal context in determining learnable skills. 3:05 - Emphasize the need for mastery learning to allow students to catch up on skills they struggle with initially. 4:52 - Break down complex subjects into component skills to make learning more manageable. 5:37 - Consider the motivational factors that lead people to focus on their relative strengths. 5:51 - Enhance learning by focusing on background knowledge to fill gaps. 6:50
I completely agree with Scott on "talent does not mean high achievement", and that it's wrong that everyone selects for early learning rate. It often happens that the talent will have good skill progression at the early levels but will hit a wall afterwards at the high levels. You can see this happen in almost a lot of fields, math, chess rating etc... For example: There a lot of chess players that have insane early chess rating progression, but will stagnate afterwards at the higher levels and never even reach GM or super GM. The same is for IMO (International Math Olympiad), people seem to think that all Field Medalists are usually IMO Gold Medalists because IMO predicts the best mathematicians, but often that is not the case, even tough a lot of them are IMO gold medalists, the IMO Gold medal does not predict that you will win a Field Medal or produce ground-breaking research. Open Question: Maybe fun open discussion would be how to best predict for later achievement and potential, rather than learning rate, do you think Olympiads have good predictive power for later success for STEM fields or no? It seems like a multi-variate thing, and there is no simple answer, even tough psychologists like to believe that there is an answer with all the Standardized Tests (SAT, IQ tests, etc..), but those tests are looking for early learning rate.
While I agree with the generally idea of what's being said, the fact is that if you learn faster then you can cover more ground, where ground is skills and/or knowledge. Skills that are very deep within a "skill tree" may only be accessible to someone that dedicates their life to developing those skills AND learns sufficiently fast.
Seems like an obvious point and probably wasn't emphasized in the video because the tonnes of people not learning stuff because they think they can't, is a more widespread issue than the few people who reach a moderate-high level of mastery that are frustrated because they don't understand why they aren't at the genius level
@@user-dl9yy1zu80This is basically why I generally agree with the video. I find myself more in the camp, though, where rate of learning, available time and the amount of skills I'm interested in attaining are the source of my challenge.
Hi Scott, can u make a video about Prerequisite Chaining and how to use that for coding and other stuff. I’ve tried doing that for exemple I wanted to make a game or build an app. But I coudnt learn , find or understand what I needed to make my app or game. So I reverted to watching full tutorials because I was lost and it was easier
But I argue that We don't get the environment And the education system isn't changing to support ourselves to prepare a environment which improve our learning Instead mostly we are all independent learners Now what we could do to improve selfstudy ?
🎯 Key Takeaways for quick navigation: 00:00 🧠 *Muitas pessoas acreditam que algumas habilidades são inatas e inalcançáveis, mas a crença na "aprendibilidade universal" é apoiada por evidências sólidas.* 01:13 📚 *O conhecimento prévio sobre um assunto é um dos melhores indicadores de sucesso na aprendizagem, superando até mesmo a habilidade de leitura.* 02:22 🧠 *A capacidade de memória de trabalho aumenta com a expertise, permitindo que especialistas processem mais informações simultaneamente.* 03:19 🌍 *As habilidades consideradas "aprendíveis" variam ao longo do tempo e entre diferentes culturas, destacando a importância da priorização na sociedade.* 04:29 🎓 *A medida de sucesso na aprendizagem muitas vezes se baseia na velocidade de aquisição em vez do potencial total, resultando na seleção de talentos em detrimento do potencial total.* 05:10 📖 *Alguns assuntos parecem difíceis de aprender porque não são devidamente explicados e desmembrados, levando à lacuna na compreensão.* 06:07 🧐 *A motivação muitas vezes nos leva a focar em nossas habilidades relativas em vez de nossa capacidade absoluta, o que pode reforçar falsas crenças sobre nossas habilidades.* Made with HARPA AI
intelligence is a big factor, but it is not the only one, plus there are multiple types of intelligence. there are many factors involved, but in general, anybody with an average health can learn almost anything. however only a few geniuses will be able to reach the top in certain areas like math, people like Stephen Hawking for example.. it's just a different type of brain that the average person does not have. On the other hand, a person with an average brain could reach the top in other areas like sports..
It's so weird how in they geniunely believe women are naturally bad at math while in arab countries they dominante mathimatical fields. Brah Jordanian female engineers and mathematicians do calculus without a calculator xP
And in the 1960's in US a lot of black women were human "computers," contributing to the space program and things liek defense and even gps development with their contributions.
- Recognize anyone can learn almost anything with the right approach. 0:00
- Understand the role of prior knowledge in learning new skills. 1:03
- Acknowledge that working memory and fluid intelligence can improve with expertise. 2:09
- Realize the importance of cultural and societal context in determining learnable skills. 3:05
- Emphasize the need for mastery learning to allow students to catch up on skills they struggle with initially. 4:52
- Break down complex subjects into component skills to make learning more manageable. 5:37
- Consider the motivational factors that lead people to focus on their relative strengths. 5:51
- Enhance learning by focusing on background knowledge to fill gaps. 6:50
Breaking down a giant project into small, manageable tasks is an important skill.
reading Peak: Secrets from the new science of expertise and the studies of Anders Ericsson taught me this and changed my life
I completely agree with Scott on "talent does not mean high achievement", and that it's wrong that everyone selects for early learning rate.
It often happens that the talent will have good skill progression at the early levels but will hit a wall afterwards at the high levels.
You can see this happen in almost a lot of fields, math, chess rating etc...
For example:
There a lot of chess players that have insane early chess rating progression, but will stagnate afterwards at the higher levels and never even reach GM or super GM.
The same is for IMO (International Math Olympiad), people seem to think that all Field Medalists are usually IMO Gold Medalists because IMO predicts the best mathematicians, but often that is not the case, even tough a lot of them are IMO gold medalists, the IMO Gold medal does not predict that you will win a Field Medal or produce ground-breaking research.
Open Question:
Maybe fun open discussion would be how to best predict for later achievement and potential, rather than learning rate, do you think Olympiads have good predictive power for later success for STEM fields or no?
It seems like a multi-variate thing, and there is no simple answer, even tough psychologists like to believe that there is an answer with all the Standardized Tests (SAT, IQ tests, etc..), but those tests are looking for early learning rate.
How to learn anything easily -> 6:49
While I agree with the generally idea of what's being said, the fact is that if you learn faster then you can cover more ground, where ground is skills and/or knowledge. Skills that are very deep within a "skill tree" may only be accessible to someone that dedicates their life to developing those skills AND learns sufficiently fast.
Seems like an obvious point and probably wasn't emphasized in the video because the tonnes of people not learning stuff because they think they can't, is a more widespread issue than the few people who reach a moderate-high level of mastery that are frustrated because they don't understand why they aren't at the genius level
@@user-dl9yy1zu80This is basically why I generally agree with the video.
I find myself more in the camp, though, where rate of learning, available time and the amount of skills I'm interested in attaining are the source of my challenge.
Keep up the great work Scott! How did your Macedonian project work in the long run? What's your current level?
Hi Scott, can u make a video about Prerequisite Chaining and how to use that for coding and other stuff. I’ve tried doing that for exemple I wanted to make a game or build an app. But I coudnt learn , find or understand what I needed to make my app or game. So I reverted to watching full tutorials because I was lost and it was easier
But I argue that
We don't get the environment
And the education system isn't changing to support ourselves to prepare a environment which improve our learning
Instead mostly we are all independent learners
Now what we could do to improve selfstudy ?
Please consider starting a podcast!
What is an example for background knowledge? I feel a wide array could fit that criteria.
🎯 Key Takeaways for quick navigation:
00:00 🧠 *Muitas pessoas acreditam que algumas habilidades são inatas e inalcançáveis, mas a crença na "aprendibilidade universal" é apoiada por evidências sólidas.*
01:13 📚 *O conhecimento prévio sobre um assunto é um dos melhores indicadores de sucesso na aprendizagem, superando até mesmo a habilidade de leitura.*
02:22 🧠 *A capacidade de memória de trabalho aumenta com a expertise, permitindo que especialistas processem mais informações simultaneamente.*
03:19 🌍 *As habilidades consideradas "aprendíveis" variam ao longo do tempo e entre diferentes culturas, destacando a importância da priorização na sociedade.*
04:29 🎓 *A medida de sucesso na aprendizagem muitas vezes se baseia na velocidade de aquisição em vez do potencial total, resultando na seleção de talentos em detrimento do potencial total.*
05:10 📖 *Alguns assuntos parecem difíceis de aprender porque não são devidamente explicados e desmembrados, levando à lacuna na compreensão.*
06:07 🧐 *A motivação muitas vezes nos leva a focar em nossas habilidades relativas em vez de nossa capacidade absoluta, o que pode reforçar falsas crenças sobre nossas habilidades.*
Made with HARPA AI
great video
Thank you. First view, like and comment from me.
Hi there
intelligence is a big factor, but it is not the only one, plus there are multiple types of intelligence. there are many factors involved, but in general, anybody with an average health can learn almost anything. however only a few geniuses will be able to reach the top in certain areas like math, people like Stephen Hawking for example.. it's just a different type of brain that the average person does not have. On the other hand, a person with an average brain could reach the top in other areas like sports..
The video does not answer the premise, its just generic stuff before plugging your books...
6:47-7:05
Thank you. Second view
yes, sadly this is not wide spread belief, how can we believe this if never experiences ?
It's so weird how in they geniunely believe women are naturally bad at math while in arab countries they dominante mathimatical fields.
Brah Jordanian female engineers and mathematicians do calculus without a calculator xP
And in the 1960's in US a lot of black women were human "computers," contributing to the space program and things liek defense and even gps development with their contributions.