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Researchers from the University of Arizona in the US have discovered that learning the & # 39; sweet spot & # 39; is when we get the right answer 85 percent of the time (stock)

Failing to spend 15 percent of the time is the best recipe for success, because it provides just the right amount of challenge without scaring people, study finds

  • Educational experts have long agreed that there is a & # 39; sweet spot & # 39; is for the amount of failure
  • Researchers from the University of Arizona suggested an optimal failure level
  • They believe that when a challenge is too simple, we learn nothing new
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Finding 15 percent of the time is the best recipe for success, more than not failing, according to research.

A study led by researchers from the University of Arizona suggested a mathematically conceived optimum failure level.

Educational experts have long agreed that there is a & # 39; sweet spot & # 39; is when it comes to learning, reasoning that people learn best when they are challenged to understand something just beyond the limits of our existing knowledge.

When a challenge is too simple, we learn nothing new. Similarly, our knowledge does not improve when a challenge is so difficult that we give up completely.

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Researchers from the University of Arizona in the US have discovered that learning the & # 39; sweet spot & # 39; is when we get the right answer 85 percent of the time (stock)

Researchers from the University of Arizona in the US have discovered that learning the & # 39; sweet spot & # 39; is when we get the right answer 85 percent of the time (stock)

Now, researchers from the University of Arizona in the US, have discovered that learning & # 39; sweet spot & # 39; is when we get the right answer 85 percent of the time.

Lead author Dr. Robert Wilson, assistant professor at the University of Arizona, said: & # 39; There were these ideas in the field of education – that there was a & # 39; zone of proximal difficulty, where you should maximize your learning process.

& # 39; We have placed that on a mathematical basis. & # 39;

Dr. Wilson, along with colleagues from Brown University, the University of California, Los Angeles and Princeton, devised the & # 39; 85% rule & # 39; after performing a series of experiments with machine learning.

They taught computers simple tasks, such as classifying different patterns into one of two categories or classifying photos of handwritten numbers as odd versus even numbers, or low versus high numbers.

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The computers learned the fastest with the difficulty being such that they responded with 85 percent accuracy.

Dr. Wilson said: & # 39; If you have a 15 percent error rate or an 85 percent accuracy, you are always maximizing your learning pace in these two-choice tasks. & # 39;

When it comes to people, the & # 39; 85% line is & # 39; probably applicable to perceptual learning, in which we gradually learn through experience and examples – such as a radiologist who learns to tell the differences between tumors and non-tumors.

When a challenge is too simple, we learn nothing new. Similarly, our knowledge does not improve when a challenge is so difficult that we give up completely

When a challenge is too simple, we learn nothing new. Similarly, our knowledge does not improve when a challenge is so difficult that we give up completely

When a challenge is too simple, we learn nothing new. Similarly, our knowledge does not improve when a challenge is so difficult that we give up completely

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Dr. Wilson said: & # 39; You get better at finding out that a tumor is in an image over time, and you need examples to get better.

& # 39; I can imagine giving simple examples and giving difficult examples and giving interim examples.

& # 39; If I give very simple examples, you will always be 100 percent right and nothing can be learned anymore.

& # 39; If I give really difficult examples, you are 50 percent correct and you still learn nothing new, while if I give you something in between, you are in the right place where you get the most information from each specific example. & # 39;

The researchers do not go so far as to suggest that students should aim for a B at school. But they do believe that some educational lessons are worth exploring.

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Dr. Wilson added: & # 39; If you follow classes that are too easy and busy all the time, then you probably won't get as much out of a class as someone who is struggling but keeps up.

& # 39; The hope is that we can expand this work and start talking about more complicated forms of learning. & # 39;

HUMAN BRAIN HAS A & # 39; POOR DECISION DETECTOR &, # 39 ;, STUDY Reveals

There is a part of the brain associated with the ability to recognize bad decisions that are uniquely human

There is a part of the brain associated with the ability to recognize bad decisions that are uniquely human

There is a part of the brain associated with the ability to recognize bad decisions that are uniquely human

A part of the brain that helps prevent people from making bad decisions and that functions as our conscience has been discovered by scientists.

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The small ball of neural tissue, called the lateral frontal pole, is vital for thinking about the & # 39; what if & # 39; life, the researchers said.

Other parts of the brain keep an eye on how well decisions work, but this new region is thinking about what we could have done instead.

Scientists from the University of Oxford made the discovery last year after scanning human brains in two different ways.

Scans of 25 men and women showed that this part of the brain consists of ten smaller sections. The scans were then compared to monkey brains.

The scans showed that there is nothing in the macaque monkey's brain, despite being one of our closest relatives.

Eleven of the 12 sections in the network were similar – they were found in both humans and monkeys and were connected in similar ways to other, more remote brain regions.

But one, the lateral frontal pole prefrontal cortex, was missing in the macaques, despite being one of our closest relatives.

Differences in the brain of humans and monkeys have been found before, but this is special because it is the first time that such a clear change has been observed in the area behind flexible thinking.

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