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The '85% Rule': Why a dose of failure optimizes learning
If you're always succeeding, you're probably not learning much.
- A recent study examined the rates at which machine-learning algorithms learned to recognize images of tumors.
- The results showed that learning was optimized when the algorithms guessed incorrectly about 15 percent of the time.
- The researchers suggested that their findings apply to human and animal learning, too.
In learning, most people intuitively recognize that a bit of a challenge is a good thing. The task shouldn't be too hard, nor too easy. This conventional wisdom explains, for example, why the levels of a video game become incrementally more difficult, or why a piano instructor would choose to teach a beginning student "Twinkle Twinkle Little Star" instead of a Chopin Étude.
But exactly how difficult should learning be? Is there a "sweet spot"?
The answer seems to be yes, according to a recent study which found learning is optimized when the learner gets it right about 85 percent of the time. To get that number, scientists trained machine-learning algorithms to recognize images of tumors at various levels of difficulty. They found that the algorithms learned most efficiently when the failure rate was about 15 percent.
The 85% rule for machines and humans
"These ideas that were out there in the education field — that there is this 'zone of proximal difficulty,' in which you ought to be maximizing your learning – we've put that on a mathematical footing," Robert Wilson, an assistant professor of psychology and cognitive science at the University of Arizona, and lead author of the study, told UA News. "If you have an error rate of 15% or accuracy of 85%, you are always maximizing your rate of learning in these two-choice tasks."
Of course, the study involved algorithms, not humans. However, the researchers wrote that their findings also describe optimal learning in humans and animals, "from perception, to motor control to reinforcement learning." In the study, the researchers tweaked their model to reflect the ways in which monkeys learn a task over time. The results showed that, in all scenarios, learning was optimized with an accuracy rate of about 85 percent.
Lung cancer, MRI
Photo by: BSIP/Universal Images Group via Getty Images
Wilson said the 85 percent rule would be particularly applicable in perceptual learning, in which we gradually learn tasks by interacting with the environment, such as learning to identify tumors in images.
"You get better at figuring out there's a tumor in an image over time, and you need experience and you need examples to get better," Wilson said. "I can imagine giving easy examples and giving difficult examples and giving intermediate examples. If I give really easy examples, you get 100% right all the time and there's nothing left to learn. If I give really hard examples, you'll be 50% correct and still not learning anything new, whereas if I give you something in between, you can be at this sweet spot where you are getting the most information from each particular example."
Grit and flow states
But there's another reason why it's important for us to incorporate a healthy dose of failure into learning: it prepares people for the inevitable challenges of life. Tom Hoerr, former leader of the New City School in St. Louis, Mo., said students need to learn not only curriculum, but also the emotional tools necessary to withstand challenges.
"If our kids have graduated from here with nothing but success, then we have failed them, because they haven't learned how to respond to frustration and failure,"Hoerr told KQED.
There's also reason to think following the 85 percent rule could help people enter a flow state — a feeling of being "in the zone" that occurs when you're fully immersed in a task that's appropriately challenging.
"Boredom is where you're not learning, and your accuracy is at 100 percent," Wilson told Psychology Today. "And anxiety is where you're not learning, and your accuracy is at 50 percent or chance. This is pure speculation, but that's something we're excited to think about going forward."
A Mercury-bound spacecraft's noisy flyby of our home planet.
- There is no sound in space, but if there was, this is what it might sound like passing by Earth.
- A spacecraft bound for Mercury recorded data while swinging around our planet, and that data was converted into sound.
- Yes, in space no one can hear you scream, but this is still some chill stuff.
First off, let's be clear what we mean by "hear" here. (Here, here!)
Sound, as we know it, requires air. What our ears capture is actually oscillating waves of fluctuating air pressure. Cilia, fibers in our ears, respond to these fluctuations by firing off corresponding clusters of tones at different pitches to our brains. This is what we perceive as sound.
All of which is to say, sound requires air, and space is notoriously void of that. So, in terms of human-perceivable sound, it's silent out there. Nonetheless, there can be cyclical events in space — such as oscillating values in streams of captured data — that can be mapped to pitches, and thus made audible.
Image source: European Space Agency
The European Space Agency's BepiColombo spacecraft took off from Kourou, French Guyana on October 20, 2019, on its way to Mercury. To reduce its speed for the proper trajectory to Mercury, BepiColombo executed a "gravity-assist flyby," slinging itself around the Earth before leaving home. Over the course of its 34-minute flyby, its two data recorders captured five data sets that Italy's National Institute for Astrophysics (INAF) enhanced and converted into sound waves.
Into and out of Earth's shadow
In April, BepiColombo began its closest approach to Earth, ranging from 256,393 kilometers (159,315 miles) to 129,488 kilometers (80,460 miles) away. The audio above starts as BepiColombo begins to sneak into the Earth's shadow facing away from the sun.
The data was captured by BepiColombo's Italian Spring Accelerometer (ISA) instrument. Says Carmelo Magnafico of the ISA team, "When the spacecraft enters the shadow and the force of the Sun disappears, we can hear a slight vibration. The solar panels, previously flexed by the Sun, then find a new balance. Upon exiting the shadow, we can hear the effect again."
In addition to making for some cool sounds, the phenomenon allowed the ISA team to confirm just how sensitive their instrument is. "This is an extraordinary situation," says Carmelo. "Since we started the cruise, we have only been in direct sunshine, so we did not have the possibility to check effectively whether our instrument is measuring the variations of the force of the sunlight."
When the craft arrives at Mercury, the ISA will be tasked with studying the planets gravity.
The second clip is derived from data captured by BepiColombo's MPO-MAG magnetometer, AKA MERMAG, as the craft traveled through Earth's magnetosphere, the area surrounding the planet that's determined by the its magnetic field.
BepiColombo eventually entered the hellish mangentosheath, the region battered by cosmic plasma from the sun before the craft passed into the relatively peaceful magentopause that marks the transition between the magnetosphere and Earth's own magnetic field.
MERMAG will map Mercury's magnetosphere, as well as the magnetic state of the planet's interior. As a secondary objective, it will assess the interaction of the solar wind, Mercury's magnetic field, and the planet, analyzing the dynamics of the magnetosphere and its interaction with Mercury.
Recording session over, BepiColombo is now slipping through space silently with its arrival at Mercury planned for 2025.
Research suggests that aging affects a brain circuit critical for learning and decision-making.
As people age, they often lose their motivation to learn new things or engage in everyday activities. In a study of mice, MIT neuroscientists have now identified a brain circuit that is critical for maintaining this kind of motivation.
Researchers find a key clue to the evolution of bony fish and tetrapods.
- A new study says solar and lunar tide impacts led to the evolution of bony fish and tetrapods.
- The scientists show that tides created tidal pools, stranding fish and forcing them to get out of the water.
- The researchers ran computer simulations to get their results.
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