August 8, 2008
I’ve been thinking a bit about deep and surface learning. The terms, primarily associated with the work of Ference Marton completed in the 80s, are now commonplace and mostly understood . . . or are they?
Surface learning is equated with memorization and rote learning as opposed to deep learning generally laid alongside understanding. Actually, I’ve been thinking that deep learning is something more.
Last summer I started knitting the most complicated pattern I’ve ever tackled. It was slow going, a meticulous following of the pattern, counting stitches and rows, checking the pattern, doing the sequence and then rechecking both the pattern and the stitches. I never knew what was coming next. Even though it was a pattern that repeated every 16 rows, the ebb and flow of the sequence was not apparent to me. I worked on the project when I was fresh and when it was quiet. Interruptions resulted in confusion and usually meant errors. I labored on—all summer and finally finished the first half of the project. I couldn’t make myself start the second half. I’d had enough. I decided I would tackle it again this summer.
Things didn’t start well this summer. I couldn’t remember the few details I’d finally figured out last summer. Then I decided to see if I could make sense of the pattern, not by following the directions but by looking at how it all went together. Upon close and concerted study, I saw things I’d never seen last summer—like how the cables crossed over and under each other. I started knitting. Much to my surprise, I’d look at a sequence of stitches and know what to do. I could do whole rows and not look at the pattern once. I started on the second half less than a month ago and I have 11 of the 15 pattern repeats done. Now I can’t figure out why I thought it was so hard, why it was such slow going and why I never figured out what was happening.
Deep learning means making something your own, owning it, and fitting it into the framework of your understanding so that no matter how you look at it, it makes sense. The understanding is so natural, so complete, and so obvious, it looks easy. It’s as if what made it difficult has evaporated. It not only isn’t there, but you can’t even reclaim how it looked when it was there.
Deep learning builds confidence. As I make my way across the complicated rows, I’m thinking about other patterns I’ve tried and failed to master. Some of them I’ll bet I can figure out now.
Deep learning brings happiness, a sense of satisfaction and great motivation. Now I don’t have to force myself to pick up that knitting. I’m on a roll, and if I keep rolling at this rate, I’ll be wearing this project before the summer is over.