Chunking, schemata and prototypes

By Gordon Rugg and Sue Gerrard

What are chunking, schemata and prototypes, and why should anybody care?

The second question has a short answer. These are three core concepts in how people process and use information, so they’re centrally important to fields as varied as education and customer requirements gathering.

The first question needs a long answer, because although these concepts are all fairly simple in principle, they have a lot of overlap with each other. This has frequently led to them being confused with each other in the popular literature, which has in turn led to widespread conceptual chaos.

This article goes through the key features of these concepts, with particular attention to potential misunderstandings. It takes us through the nature of information processing, and through a range of the usual suspects for spreading needless confusion.

bannerOriginal images from Wikipedia; details at the end of this article

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“Natural” and “artificial” learning

By Gordon Rugg

There’s a widespread belief that there’s a useful distinction between “natural” learning and “artificial” learning.

There’s also a widespread belief that Elvis is still alive.

In this article, I’ll explain why the natural/artificial distinction is worse than useless in the context of education, and I’ll describe a more useful, solidly-grounded set of categorisations.

Natural and unnatural skills: The handaxe and the razor


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Parallel processing and “natural” learning: Inside the black box

By Gordon Rugg

There’s a widespread idea that before entering formal education, people learn via “natural” learning.

It’s a warm, cosy concept; “natural” evokes thoughts of wildflowers and meadows and beauty and fluffy kittens. There’s even a certain amount of truth in it; formal education does generally involve something different from non-formal education. However, when you start looking for clear, practical, explanations of how “natural” learning actually works, you encounter a sudden silence.

There are plenty of descriptions of what “natural learning” looks like, but there’s very little discussion of how it might work, in terms of plausible cognitive or neurophysiological mechanisms. This absence makes a sceptical reader start to wonder whether there actually is such a thing as “natural learning” and whether this strand of education theory is chasing something that doesn’t exist.

In fact, there is a well-understood mechanism that accounts for the phenomena being lumped together as “natural learning” and “formal learning” (or whatever term is being used in juxtaposition to “natural learning”). However, when you look in detail at this mechanism, it soon becomes apparent that using a two-way distinction between “natural” and “non-natural” is simplistic and misleading. This is one reason that the “natural/non-natural” debate in education theory is still rumbling on, after more than two thousand years of fruitless and inconclusive argument.

In this article, I’ll discuss the mechanisms of parallel processing and serial processing, and I’ll outline some implications for education theory and practice.

The joys of nature and of fluffy kittens – not always quite the same thing…

fluffy kittens2

Original images from Wikimedia


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