To learn new things, we must sometimes fail. But what's the right amount of failure? New research led by the University of Arizona proposes a mathematical answer to that question.
Educators have long recognized that there is something of a "sweet spot" when it comes to learning. That is, we learn best when we are challenged to grasp something just outside of our existing knowledge. When a challenge is too simple, we don't learn anything new; likewise, we don't expand our knowledge when a challenge is so difficult that we fail entirely or give up.
So where does the sweet spot lie? According to the new study, it's when failure occurs 15% of the time. Put another way, it's when the right answer is given 85%of the time.
Researchers at the University of Arizona came up with the so-called "85% 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.
The computers learned fastest in situations in which the difficulty was such that they responded with 85% accuracy.
"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," said Professor Robert Wilson.
When we think about how humans learn, the 85%Rule would mostly likely apply to perceptual(感知的)learning, in which we gradually learn through experience and examples, Wilson said. Imagine, for instance, a radiologist(放射科医生)learning to tell the difference between images of tumors(肿瘤)and non-tumors.
"You need examples to get better at figuring out there's a tumor in an image, "Wilson said. "If I give really easy examples, you get 100% right all the time and there's nothing left to learn. You're not going to be taking as much from that as a situation where you are struggling a little hit. If I give really hard examples, you'll he 50% correct and still not learning anything new, while if I give you something in between, you can he at this sweet spot where you are getting the most information from each particular example."
12. Which of the following is linked with the sweet spot?
A.15 percent accuracy. | B.50 percent accuracy. |
C.85 percent accuracy. | D.100 percent right. |
13. Why did the researchers teach computers simple tasks?
A.To find out where the sweet spot lies. | B.To see how well computers carry out tasks. |
C.To compare the results of their experiments. | D.To conduct some research on machine learning. |
14. What is the purpose of the "examples" mentioned in the last paragraph?
A.To teach what to do in the treatment of tumors. | B.To teach how to determine there is a tumor. |
C.To help to remember what is learned. | D.To help to learn how a tumor develops. |
15. According to the text, what is the most effective way of learning?
A.Not taking failure too seriously. | B.Learning through experience and examples. |
C.Struggling a little bit, but not too much. | D.Learning things that are completely new. |