Just So Stories

I vividly recall Rudyard Kipling’s Just So Stories from my childhood. They were a collection of tales with imaginative and wonderful accounts of how things came to be the way that they are – like ‘How the Leopard Got His Spots’ or ‘The Elephant’s Child’ (on how elephants came to have trunks).

When you look at the natural world, in all its sprawling complexity, you would be forgiven for thinking that there is no single account of how organisms came to be as they are – that there are just so many contexts, so much complexity, that we need so many different stories to account for such varied phenomena.

You would be forgiven for thinking this, but you would be wrong. 

Today we know that the enormous complexity of the natural world is, indeed, subject to a single simple explanation: natural selection. We do not need an encyclopaedia of accounts for why things are the way that they are.

A proliferation of competing narratives is characteristic of the phase Thomas Kuhn calls ‘proto-science’. Before we have a firm theoretical foundation for our understanding of a domain (such as species diversity) there is an ecosystem of competing narratives. Some of these will have some evidential basis – some will merely be fables.

This is where learning/training/education is today: proto-science. A mixed bag of popular stories about how people learn. I write this having recently read a number of comments/posts to the effect that learning ‘is just too complicated’ that there are always ‘many right answers’ or ‘everything depends on context’. This is the pre-evolutionary position: it’s all too complicated for a simple answer.

One of the tell-tale signs is the sheer number of learning theories which are ‘creationist’ in nature – by which I mean that they are stories one can only tell about humans. Any time a learning theory can only meaningfully be applied to humans (for example ‘learning styles’, ‘cognitive load theory’, ‘instructional design’) we should take care – there is every risk that it is a creationist account.

So this is the problem I have endeavoured to solve with the affective context model: a single, simple explanatory framework for a hitherto irreconcilable variety of cognitive phenomena and narratives.

In presenting this explanation I generally encounter two reactions:

The first reflects the extent to which people’s thinking is profoundly authoritarian – that is to say they are more concerned with who an answer comes from than whether or not an answer is any good. Ideally, we prefer our answers from a ‘father figure’ or ‘teacher-type’ – ideally some bearded, bespecled chap. This feeling is so deeply ingrained that we even feel obliged to turn our great discoverers – for example Einstein and Darwin – into this image.

The second is a kind of post-rationalisation; an instinctive reaction that because things have seemed complicated so far, they cannot be reduced to a simple explanation: there are entire journals devoted to educational theory – you can’t possibly reduce it all to a simple explanation!

And so we remain on this journey, just at different points on the path.