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Stephen Downes

Knowledge, Learning, Community

Jul 27, 2010

Originally posted on Half an Hour, July 27, 2010.

Responding to Heli, which you should read first...

> I love to analyze and conceptualize .. but why I have a feeling that it was not allowed here in CritLit2010? I should have been an excellent student but I only gave some fragmented knowledge and occasional comments. What is my problem actually? Fine question :)

Interesting question. It certainly isn’t because you were not allowed in CritLit2010 – there was no prohibition whatsoever against analyzing and conceptualizing.

Because it was a small course, much of your interaction would have been with me. So perhaps you felt that analysis and concepts would not have been an effective strategy in our interactions? If so, you may have been correct.

Let’s consider the question of whether interesting learning happened in CritLit2010. The usual, traditional, method of addressing such a problem is to seek out some evidence, and to infer, through a process of analysis and conceptualization, to the existence of some instance of learning (perhaps a second calculation would be required to show that it is ‘interesting’).

This reflects an approach to learning where what is learned is observable, and measurable, is discrete wholes – precisely the sort of things that reveal themselves through analysis. It is, if you will, an atomistic definition of learning, where after learning we can observe some sort of increase in the mass of atoms (or perhaps an exchange of atoms, if we have had to reject old concepts along the way). These atoms (by definition?) would produce some evidence of their existence, given an appropriately designed experimental mechanism (which, in learning, is called a ‘test’ or ‘assessment’).

When I am asked to account for whether interesting learning happened in CritLit2010, I don’t want to commit myself to any such picture. Not because I think connectivism resists such an approach – I’m sure we could probably build it in, and I see no shortage of efforts among my colleagues to do exactly that (”where is the ‘learning’ in the PLE,” they ask me, as though assuming we could add some atoms of learning to the mix and detect them coming out the other end). But because the idea of ‘atoms of learning’ runs contrary to the idea of a learning network.

Let me offer an analogy to explain what I mean. Imagine that you have travelled to a new city for the first time. Imagine, especially, that it is based in a culture different from your own. You return home from the city refreshed, exhilarated. Clearly, you have “learned” from your visit. But what is the evidence that interesting learning happened in your visit to the new city?

If you were asked such a question, you would find yourself almost at once fishing for particular things you might have learned: the foreign word for ‘please’, perhaps, or the existence of a festival, or the funny way people there line up for and order food. But even were you to be able to elicit the totality of such atoms, it would still not constitute what you learned. Indeed, it would actually misrepresent what you really learned.

Moreover, even if you were not able to come up with any atoms of learning, it would be incorrect to say you hadn’t learned anything. As a result of your visit to the new city, you see food slightly differently, your understanding of social organization has become more sophisticated, your expectations of behaviour slightly changed. It may be that you cannot even articulate these new bits of learning (this is what it sounds to me like when you say “it is not easy to follow learning happenings. I cannot follow mine and I should be expert”). But this is not grounds for believing that learning did not happen, only that it is not atomic and identifiable through analysis.

What did you learn from travel to a new city? You might not be able to articulate it at all. An observer might be more perceptive, noticing perhaps a slight change in the way you pronounce words, or slight variations in your menu selections at restaurants. It would be difficult, even impossible, to articulate, and it would definitely not show up over a short period of time – some things might not become evident until you have visited your second, or third, new city.

So my response to the question “how do I know whether interesting learning happened in CritLit2010″ is that the whole model of “discrete cause -> discrete effect” is mistaken here. Asking “did interesting learning happen” is an inappropriate question to ask. It treats learning as (a) something concrete, and (b) an effect, that can be reliably produced by a cause. Yes, you may be able to identify concrete things that were produced by a cause. The mistake lies is saying “aha! *this* was what I learned.” When in fact it is probably the least important of the things you learned.

So how do you know? Never mind the quest for discrete bits of learning, how do you know whether taking the course was a valuable activity. As I suggested before, an observer, familiar with your behaviour before and after, may be able to detect slight changes. Your use of language, your behaviour in certain communities, may have become more appropriate in ineffable ways. And your perceptions (untrustworthy and unreliable as always) may also offer clues: you feel a sense of dissonance, which means your existing thought patterns have been challenged, or you feel more comfortable with a group of people, or you feel a sense of exhilaration similar to what you feel after visiting a new city. Or something else.

What *would* show that learning occurred, if we could measure it, would be the formation of new connections, or strengthening (and weakening) of existing connections, between neurons in your brain. Your neural network was altered by the experience of taking the course (and, concurrently, by everything else that happened to you over the six weeks). What *would* show that learning occurred would be an isolation of those changes that happened as a direct result of the course, a comparison with prior states, and then some sort of semantic measure such that the new neural state contains ‘more truth’ than the old.

Barring such an account (and sketching the account reveals some of the absurdities, such as the idea that one neural state contains ‘more truth’ than another) we are left with vague generalizations.

But this, at least, seems true: there is no correct one-to-one mapping between (1) a verbal description of facts retained, propositions now believed to be true, or other atomistic bits of knowledge, and (2) the full description of the change of neural state that occurred as a result of the learning. We can’t get from ‘content language’, which is atomistic, to ‘neural language’, which is not.

When you think about this, you see that this is true, I think. When you think of the proposition that “Paris is the capital of France,” you see that there is no neural state that corresponds to ‘knowing’ or ‘having learned’ this proposition. Ergo, if we say that learning is the change of neural state, then it is inaccurate and wrong to say that we “learned” that “Paris is the capital of France”, and that it is a mistake to treat utterances of such as evidence for that.

Learning is not atomic. There are not ‘atoms’ of learning. Learning is not something we can count and measure, as though it were cumulative. The assessment of learning through measurement of ‘bits of knowledge’ is fundamentally in error. A connectivist course does not try to teach ‘bits of learning’ and hence to ask ‘what learning happened?’ is the wrong question to ask. At best, we can ask only whether a person is more of a certain sort of person – are they ‘more German’ for having stayed in Germany for a month, are they ‘more of a physicist’ for having stayed in the community of physicists for a month. Knowing that there are no necessary or sufficient conditions for being ‘more’ of any of these, knowing that there is no gauge that measures being ‘more German’ or ‘more of a Physicist’.

Stephen Downes Stephen Downes, Casselman, Canada

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