advertisement
Home » News » To Optimize Learning, Fail 15 Percent of the Time

To Optimize Learning, Fail 15 Percent of the Time

Educators have long recognized there is a “sweet spot” when it comes to learning — we learn best when we are challenged to grasp something just outside the bounds of our existing knowledge.

When a challenge is too simple, we don’t learn anything new. But we also don’t learn anything new when a challenge is so difficult that we fail entirely or give up.

So where does the sweet spot lie? According to a new study, it’s when failure occurs 15 percent of the time.

“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,” said University of Arizona assistant professor of psychology and cognitive science Dr. Robert Wilson, lead author of the study.

Wilson and collaborators at Brown University, the University of California, Los Angeles, and Princeton came up with the “85 Percent Rule” after conducting a series of machine-learning experiments in which they taught computers simple tasks, such as classifying different patterns into one of two categories or classifying photographs of handwritten digits as odd versus even numbers or low versus high numbers.

The computers learned fastest in situations where they responded with 85 percent accuracy, according to the study’s findings.

“If you have an error rate of 15 percent or accuracy of 85 percent, you are always maximizing your rate of learning in these two-choice tasks,” Wilson said.

When researchers looked at previous studies of animal learning, they found that the 85 Percent Rule held true in those instances as well, he added.

When we think about how humans learn, the 85 Percent Rule would mostly likely apply to perceptual learning, in which we gradually learn through experience and examples, Wilson said.

For instance, it takes time for a radiologist to learn to tell the difference between images of tumors and non-tumors.

“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 percent right all the time and there’s nothing left to learn. If I give really hard examples, you’ll be 50 percent 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.”

Since the researchers were looking only at simple tasks in which there was a clear correct and incorrect answer, Wilson said he won’t go so far as to say that students should aim for a B average in school. However, he does think there might be some lessons for education that are worth further exploration.

“If you are taking classes that are too easy and acing them all the time, then you probably aren’t getting as much out of a class as someone who’s struggling but managing to keep up,” he said. “The hope is we can expand this work and start to talk about more complicated forms of learning.”

The study was published in the journal Nature Communications.

Source: University of Arizona

To Optimize Learning, Fail 15 Percent of the Time

Janice Wood

Janice Wood is a long-time writer and editor who began working at a daily newspaper before graduating from college. She has worked at a variety of newspapers, magazines and websites, covering everything from aviation to finance to healthcare.

APA Reference
Wood, J. (2019). To Optimize Learning, Fail 15 Percent of the Time. Psych Central. Retrieved on December 4, 2019, from https://psychcentral.com/news/2019/11/09/to-optimize-learning-fail-15-percent-of-the-time/151707.html
Scientifically Reviewed
Last updated: 10 Nov 2019 (Originally: 9 Nov 2019)
Last reviewed: By a member of our scientific advisory board on 10 Nov 2019
Published on Psych Central.com. All rights reserved.