The video below is a perfect demonstration of why it’s so important to model learning for students.
What it highlights is what most motivated people do when not instructed properly: we improvise. Sometimes it works for us. Lots of times, unfortunately, it doesn’t. Oh, how much easier it would have been, all those hundreds of times opening the stock packet to have known how to do it as it was intended to be done. Oh the time we could have saved; how much better our cooking may have been with the stock evenly distributed. Oh the lament thinking of the times when the stock didn’t completely dissolve: the looks of disdain not even nearly disguised on my kids’ strained faces.
I use the 1st person plural pronouns deliberately, because actually when we teach a class, there is collective learning, learning that is taken out into the world by our students and disseminated. If it’s incorrect, or just not as good as it could be, lots of people can be affected.
Careful and precise modelling of the learning we want our students to engage in is crucial. Andy Tharby discusses ‘live modelling’ and ‘worked examples here, as does Tom Needham here. If we don’t, success in the task is only possible by passing through several hoops.
- The first is the student’s level of motivation. Joe Kirby explores motivation wonderfully well in this post citing a Willingham hypothesis of what drives motivation: it is not so much the relevance of the content as the challenge of the task. ‘Curiosity has staying power if we judge that the mental work will pay off – we quickly evaluate the mental work it will take to solve the problem’. In other words, when students are finding the task difficult to do in the absence of effective modelling with incremental steps and appropriate amounts of practice, if the perceived chance of success is 50% or less, which includes social success, most will give up.
- Despite this probability, if students are able to hang on through this and attempt the second hoop, they are now at the mercy of having to hope that their efforts do not expend too much cognitive load in processing the task. Again, if this overload renders perceptions of success low, students will give up.
- However, some students will show remarkable resilience, which can be trained, and persist in tackling the task and producing learning. But the learning is a lottery, sometimes producing success, often not. The proof is in the OXO example.
If we want students to learn what we want them to learn, we have to show them what it is we want them to learn.
I’m Paul Moss. Follow me on Twitter @edmerger, and follow this blog for more on educational discussions and English teaching.
LEARNING DESIGN by Paul G Moss 