Stephen Downes

Knowledge, Learning, Community

Half an Hour, Oct 25, 2017

Responding to George Couros, Thinking About Research, Innovation, Test-Scores, and Creativity

You write (and this is the theme of the whole post, really): "One thing I am still adamant about…know the people you serve and move backward from there.  That is always your best bet."

My experience is that you can't know who you are serving before you begin to serve them, and that there is an inexhaustible and always changing store of knowledge about a person.

So I don't try to know people before I serve them. Here's how it works for me:

- I bring things to the table - background knowledge, communication skills. a big grey cat sitting on my desk...

- People come to me for those things, and we begin.

- I experiment, using some of my existing tools, creating new tools, interacting with the person or the audience

So how does this related to research and innovation. Well, I think the same stipulations hold.

- the whole idea of 'know your customer' or 'know your market' is overrated. I think that you have to bring something to the table. It may or may not serve a previously identified need.

- the research and development programme is also iterative. You start, you work back and forth with a potential market, you iterate and you develop creatively

Which leads us to what we mean by 'innovation':

- innovation is the *outcome* of an interaction with a market, not what leads to it. The idea of some genius working in advance with a pile of research and coming up with an 'innovation' is nonsense

- what makes the creative process work, and what makes some development or invention an 'innovation' is the fact that it creates some *benefit* for both the creator and the market (you need both)

Which leads to the items in this post:

- the only 'evidence' is in the interaction. The 'research literature' (including studies and data etc) are a source for ideas, but serve as 'evidence' only after the fact, as a rationalization

- the biases in the research aren't what people think they are - they are biases in the way research is conducted, and of the values served by the research, and not with respect to belief or support in some fact or another

- there's another set of 'biases' which aren't really biases, they're errors of reasoning - the confirmation bias, for example (the example you cite is a case of this), and people *can* be free of these errors (though they often don't want to be)

- my bias is toward practical application. As they say, 'quality ships'. I won't say I'm always successful in this, but this is were I put my efforts.

- what counts as evidence always depends on the context.  I don't care about course completion or test grades, for example. I do care about personal empowerment, self actualization, and broader social benefit.

I think that most of the research that constitutes 'evidence' for 'evidence-based decision making' is bunk (this includes Hatties stuff - ). It's not real research, but instead a type of busy-work intended to provide the authors with credentials.

The types of generalizations we can reach by conducting trials with fixed and mutable variables is extremely limited. Individual variability in cognitive function is far greater than in physical function (and even in fields like medicine, doctors are wary of applying generalizations to specific cases)

The best (and most innovative) researchers are not those who master statistical syllogisms, but rather, those who are creative and imaginative, who have strong core skills (pattern recognition, sense of value, contextual awareness, practicality, inference and change processes) and a willingness to engage with the technology, the people, and with other researchers.

Stephen Downes Stephen Downes, Casselman, Canada

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Last Updated: Mar 30, 2021 8:52 p.m.