Learning is Optimized When We Fail 15% of the Time

Learning is Optimized When We Fail 15% of the Time

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 and educational scholars 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 the bounds of our existing knowledge. When a challenge is too simple, we don't learn anything new; likewise, we don't enhance 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 in the journal Nature Communications, it's when failure occurs 15% of the time. Put another way, it's when the right answer is given 85% 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 UArizona assistant professor of psychology and cognitive science Robert Wilson, lead author of the study, titled "The Eighty Five Percent Rule for Optimal Learning."

Wilson and his collaborators at Brown University, the University of California, Los Angeles and Princeton 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 or classifying photographs of handwritten digits as odd versus even numbers, or low versus high numbers.

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," Wilson said.

Read the full article from UA News here

Published Date: 
11/06/2019 - 13:47