Stop telling kids they are smart??? - Article by Sal Khan

Here are some interesting snippets from an article by Sal Khan titles, "The Learning Myth: Why I'll Never Tell My Son He's Smart."The Learning Myth: Why I'll Never Tell My Son He's Smart"
that can be found here.

My 5-year-­old son has just started reading. Every night, we lie on his bed and he reads a short book to me. Inevitably, he’ll hit a word that he has trouble with: last night the word was “gratefully.” He eventually got it after a fairly painful minute. He then said, “Dad, aren’t you glad how I struggled with that word? I think I could feel my brain growing.” I smiled: my son was now verbalizing the tell­-tale signs of a “growth­ mindset.” But this wasn’t by accident. Recently, I put into practice research I had been reading about for the past few years: I decided to praise my son not when he succeeded at things he was already good at, but when he persevered with things that he found difficult. I stressed to him that by struggling, your brain grows. Between the deep body of research on the field of learning mindsets and this personal experience with my son, I am more convinced than ever that mindsets toward learning could matter more than anything else we teach.

Researchers have known for some time that the brain is like a muscle; that the more you use it, the more it grows. They’ve found that neural connections form and deepen most when we make mistakes doing difficult tasks rather than repeatedly having success with easy ones.

For instance, praising someone’s process (“I really like how you struggled with that problem”) versus praising an innate trait or talent (“You’re so clever!”) is one way to reinforce a growth ­mindset with someone. Process­ praise acknowledges the effort; talent­ praise reinforces the notion that one only succeeds (or doesn’t) based on a fixed trait.

I see this as a part of the shift we need to make, teaching for understanding rather than teaching for success. Teaching a depth of knowledge rather than one strategy or method that gives a correct answer but doesn't easily transfer in real-world situations.