A cognitive scientist walks into a bar. . .

A very funny (to me, at least) cartoon by Bill Amend in the FoxTrot series was pointed out to me by my colleague Eric Ellefsen. Any cartoon that uses the phrase “10,000 hours of practice” more than once gets my attention!

This little piece compresses a huge amount of learning science into just a few panels. I thought it might be fun to deconstruct it a bit. (Yeah, I know, I should get out more. . .)

If you want to have some of the same fun I had, pull up the cartoon and follow along:

• Text and images work well together: From Rich Mayer's research work, what cartoonists do naturally is very good for learning: the right images and text together can lift learning by more than a standard deviation. Cartoons and graphic novels for learning may be underrated, eh?
• Informal language lifts learning: Another from Rich Mayer's work: informal language language drives learning.
• Positive mood helps learning: Whimsy works. Not a continuous Jay Leno (distracting), but we should look like we're enjoying ourselves and our topics and bring learners along for the fun.
• 10,000 hours of deliberate practice: This ties back to the work of Anders Ericsson (popularized in such works as Gladwell's Outliers and Colvin's Talent is Overrated). It is not raw early talent that predicts success, but rather many hours of focused, deliberate practice in a domain that leads to real expertise. This is good news for learners: it's work, yes, but many dreams can be achieved with deliberate practice, no matter where you start. Our job as educators is to set up practice environments, motivation, and enough meta-cognition about learning that our learners can efficiently do the (large amounts) of practice they need to fulfill the dreams they have.
• Starting matters: You have to start to get there, and it may start badly – but the first 30 hours is not what matters long term. Too often, learners, teachers, faculty, family, and friends judge long term success too quickly.
• Learning is hard work: When marketers say, “they won't even know they're learning!”, watch out. Except for the simplest topics, or things like early language acquisition that are pre-wired, learning is hard work. (John Sweller from the University of New South Wales in Australia has a theory that learning has evolved to be hard, to protect the human brain from picking up things through random exposures that don't repeatedly work, time after time.) The best educators (like good coaches) accept this, explain it – even celebrate it.
• Experts view things differently than novices: Whether an expert parent, teacher, musician, physicist, plumber, etc., expert minds process the world differently than novice minds do. Fast, fluent, sub-conscious information and decision-making operations produce different “chunks” of content for the conscious expert mind. They “see through” the clutter of information to the essentials of what's going on, almost literally.
• There is an expertise around the design of instruction: Too often, folks who've been students (for years) think that's enough to make good judgments about the design of learning - “I remember doing NNN in school/college and it worked for me – let's do that for thousands!” We need to pay attention to what learning science says about what works for learning – and look to gain from and develop real expertise (10,000 hours, remember?) in applying it to learning environments.
• Not every use of educational buzzwords leads to correct actions: As in any field (medicine comes to mind), combining technical terms and concepts from the domain in plausible paragraphs and PowerPoint presentations is not the same as getting something to work. We should feel an obligation to measure and evaluate before, during, and after we try something, no matter how plausible it looks on the surface.

Enough!

Still, isn't it fun to see learning science edging enough into the mainstream that a cartoonist who reaches millions uses it in a Sunday cartoon? Could it be that awareness of what empirically works for learning might edge into our learning environments at scale?

Would we dare hope that our learners and regulators might ask to see if learning environments incorporate at least as much learning science as a Sunday cartoon?

We can hope! We can try!