First published on November 2011.
If creative learning is the creation of one’s own ideas, or learning to create one’s own ideas – or even understanding that learning is the creation of new ideas – and if every human has the capacity to do this, then we are talking about something very significant and complex. And we are talking not only about something significant and complex, but about a resource that happens to be endlessly renewable. In a world where such resources are required for sustainability, are we not also talking about something of fundamental importance? If we are, then we need to get serious about it and work out how we want to nurture this precious resource.
But, over the last ten years, creative learning has not been afforded the importance it might have been. Often it has been presented as the splash in Archimedes’ bath; rather missing the point, if I may say so. It has so many interpretations, meanings, assimilations and resistances notwithstanding its political allies and enemies, that it can be difficult to see what’s going on at all. Yet if we do value this human generative resource, how do we go about understanding how creative learning operates or how creativity is created? And can we ever be sure that this capacity will ever be maintained and given value if we don’t keep a measure on activity and account for what causes the splash?
Complex learning requires complex analysis, but how does one measure the emergence of a new idea or the distance travelled from one idea to the next? Measuring human behaviour has never been an exact science, to say the least, but there are indicators blinking away in learning that signal that creativity is taking place. In Signposting Creative Learning (2006) I tried to identify some of this blinking. I argued that it was clear that experts across various fields have shared views on indicators worth the measure; but I have to ask why, then, have so few (other) measures been taken?
In the pursuit of accounting for the movement between two ideas, I turned to the mathematics of movement in the form of calculus. To my horror, I discovered that what calculus reveals is that every measure of movement amounts to an approximation: a ‘best guess’. I didn’t turn to mathematics for best guesses and approximations! I had rerouted in search of a robust system in which the wonders of the world and human behaviour could be captured in numerical order. I wanted a system that was already trusted and valued and had clever professors involved who have won prizes and who hold unquestionable status; a system I could pick up and transfer neatly onto my own subject of enquiry which sadly enjoys a somewhat lower cultural status than maths.
But the problem with even this kind of measuring, as with any measuring that involves counting, is that it tends to count things that don’t actually count. It can’t measure the complexity of a learning situation that involves humans. Humans with feelings, thoughts, behaviours and points of arrival and departure in any given situation, humans that are at a different point even from themselves later on the same day. It seems that the movement of human difference is too elusive to measure, even with the mathematics of movement.
That said, measuring in most forms for creativity and, indeed, learning, aside from those in academia, is based on economic models that assume that counting is possible. Policy wonks and industry professionals tend to measure creative learning as units of X that are equal to units of Y, instead of understanding what constitutes X and the range of journeys that may take us to Y or perhaps Z. Such accounting is driven by economics and public accountability and it often leads us to fixed outcomes, because Y has to be a given unit of economic value. Measuring in this manner guarantees a lack of difference, the very opposite of what we need to understand about the movements present within creative learning and how to establish the best conditions for its growth.
I’m not saying that public accountability doesn’t matter; it does, but right now, I’m not sure that we understand what we are accounting for. We need to start measuring the difference creative learning makes with different tools that are equipped to do so. This means measuring value systems and ideas with a different kind of ‘best guessing’ involving better theories and better questions built from the practice of creative learning itself. I think a good place to start is to shift from economic models to ecological models of assessing the value of creative learning. This would give insight into the processes of learning rather than its perceived outcomes, which turn out to be nothing more than approximations and best guesses anyway, the big splashes which actually veil, rather than illuminate, and account for the complexity of the creative learning taking place.
Illustrations by Paul Davis - http://copyrightdavis.blogspot.com/