Dave Snowden on The 21st Century University

Notes from Dave Snowden’s Presentation to Week 17 of ChangeMooc, 18-01-12

Recording of his presentation

Learning and the Human Brain

The assumption that the human brain is a computational device has led to an information focus in learning. There is a dominance of machine-type metaphors. We have been seduced by machines, leading to an education system dominated by input/output models (promoted by some types of systems thinking) and a view of the brain as an information-processing device (see All Watched Over by Machines of Loving Grace ).

The human brain is a pattern processing intelligence not an information-processing machine. We need to avoid the pattern entrainment  that results from group think. The human brain evolved to handle messy coherence, not structure and order. It allows us to innovate, have insights and see things in a different way

Knowledge Acquisition

We need more generalists, people with a mix of generalised and deep knowledge, for working in a complex world – people who can work quickly across subjects and in contexts of high levels of uncertainty.

There are whole tracts of knowledge that can only be understood through interaction, e.g. through an apprenticeship model of education, which allows for imitation and failure, such as for London taxi drivers. Failure is key to human knowledge acquisition and the two-year apprenticeship of London taxi drivers has been shown to change the hippocampus area of the brain

The minute a measure becomes a target it ceases to be a measure, e.g. as when academics are measured on the number of papers they produce  rather than the originality of their ideas. PhDs destroy intelligence rather than build it. In universities we are training recipe book users and assessing whether they can reproduce the recipe. We are not training chefs who can achieve a huge amount without a recipe. Chefs have a mix of practical and theoretical wisdom and willingness to engage conceptually and theoretically with real world problems.

We need to avoid the anti-intellectualism that is endemic in Europe and N. America i.e. don’t use big words or read books, keep things simple and become simplistic as a consequence.

Complex Adaptive Systems

Complex adaptive systems are not causal but dispositional, i.e. they are pre-disposed to evolve in random ways which cannot be predicted. So models based on cause and effect which do not have a predictive capacity are of no use in complex spaces.

A way of handling uncertainty is to make use of collective or distributed cognition. Complex spaces need experts to compete/disagree with each other to increase diversity, rather than a consensus based approach. For emergence we need to force conflict by bringing in different people with different backgrounds. In complex systems we should also bring in safe-to-fail experiments and prevent premature convergence by moving people around into different groups.

By contrast, complicated spaces need experts whose judgment we trust.

Innovation and Creativity

Deception is the heart of innovation in any system. Play the game and innovate (under the radar).

Creativity is a symptom of innovation not a cause. Innovative people are creative. Pressure, starvation and perspective shift produce innovation which produces creativity.

Failure, consensus and facilitation

Negative stories carry more learning than positive stories. Appreciative Inquiry is often unethical and used in inappropriate contexts; it tells people what stories they are allowed to tell.  Open space is also like this in that it rewards consensus and punishes dissent. Anyone who survives in an open space does so because the only people there are those who listen – everyone else votes with their feet. Knowledge Management which focuses on best practice also entrains past practice and fosters consensus. In a complex system we have to increase diversity and conflict so that emergent possibilities become visible and can be consolidated.

If you haven’t failed, you have failed.

Any technique which relies on really good facilitation isn’t going to work on a consistent basis. We need processes that don’t require facilitation. It’s not about creating spaces to enable thing, but about creating processes (e.g. Ritual Dissent).

Final Message from Dave Snowden

Don’t give up on formal education, but interact with the ‘real world’ and read outside your subject.

Complexity and critical literacies

Is a critical literacy for networked learning to know something about Complexity Theory?

Dave Snowden was today’s speaker on the Critical Literacies open online course, talking about complexity. We had technical difficulties and had to move from ‘Open Meetings’ to ‘Elluminate’ (many thanks to Carmen) and when we finally got going it all seemed like a bit of a rush.  I’m not completely ignorant about complexity theory, but it was too fast for me and I will have to listen again to the recording when it finally gets posted (probably more than once), as there was a lot packed in there. We were also given this link which I have dipped into and looks as though it will be very useful.

http://learningtobeprofessional.pbworks.com/From-induction-to-abduction,-a-new-approach-to-research-and-productive-inquiry

My interest in complexity theory is related to what it has to say about teaching and learning – which comes back to critical literacies. My understanding is that a complex system is one in which you cannot predict what is going to happen and just that over-simplified one statement presents huge challenges for our education system (UK), which seems to want to prescribe and measure everything in sight. In an article that I read this afternoon, this question was asked about what complexity theory might mean for the philosophy of education:

Complexity theory poses a major question: What do the following mean for the philosophy of education: emergence and self-organization; connectedness; order without control; diversity and redundancy; unpredictability and non-linearity; co-evolution; communication and feedback; open, complex adaptive systems; and distributed control?

Any teacher will know the challenges that these ideas present,  just as anyone who took part in CCK08 might also recognise these as characteristics of a complex system.

I found this article (cited below) very helpful as an introduction to thinking about teaching and learning in terms of complexity theory.  Unfortunately it is not available online and I can’t post the pdf because of copyright restrictions, but it is likely to be in a University library if you have access to one.

Morrison, K. (2008). Educational Philosophy and the Challenge of Complexity Theory. Philosophy, 40(1).

So plenty to think about and plenty to come back to! Is complexity theory ever included in a teacher trainee’s degree course? It wasn’t in any of the courses that I was ever involved in, but it seems to me to be important in helping teachers to manage the inevitable uncertainty, unpredictability and emergent learning which is going to increasingly occur as students become more and more connected and networked.