Learning Conversations

Link: http://it.coe.uga.edu/itforum/paper92/paper92.html

There is a lot in Stephen's recent paper that I don't yet understand. At some point it will be interesting to explore the links he provides to delve into the various philosophies and theories that can be used to understand learning. But, for the moment, I'm going to focus on some of the implications that arise from his reasoning and try to work out how his theories fit into the realities that we work within.

There has been a lot of thinking recently about "learning networks". I have followed Stephen's thinking on it over the past couple of years, along with the work done by George Siemens. This fed into my paper this year on Social Networks & Teacher Professional Development where I tried to analyse, based on theories of developing social capital, how social networking tools can support teacher CPD.

Using network ideas to support learning seems to be an ideal way forward; it fits my understanding of how learning actually happens, and fits what I see happening in the real world around informal learning - people learning through the connections they make with resources and other people.

Networks are about people

What I find hard to do is to square the current state of "formal" learning with network ideas. By formal, I mean where there is a curriculum or an agenda set by a person other than the learner. For example at school, in college, or in the workplace.

Networks consist of individual nodes, each of which can make connections with other nodes. In a computer network the connections are made by virtue of software seeking out other nodes, or through hardware that has been used to join the node to the network. When we talk about networks of people we need to remember that every individual has a choice as to whether they connect and who they connect to. When the connections are made information can flow; conversations can happen. But there must be a level of motivation to make each connection - the individual will need to have some sort of knowledge of "what's in it for them". The level of intrinsic motivation (and confidence), required to contribute to a network, is vast. How is that change in culture going to going to happen?

When an organisation is setting the learning goals for a group of individuals (or nodes in the network), how do they persuade those individuals to make the appropriate connections? How do they encourage them to begin to allow the flow of information to happen? I suppose it's the role of the teacher/mentor/facilitator to devise appropriate activities that will engage and support connection making. Terry Anderson and Donna Cameron's work on developing "collaborative learning activities using social software tools" is very useful in this scenario. It's similar, in a way, to the face-to-face facilitator who is trying to encourage a group of people to collaborate/network in a training room. The difference being at least you've got people motivated enough to come to the training room in the first place!

The mentor/facilitator role is going to be critical in this new world; playing, as Stephen describes, the role of "aggregator, assimilator, analyst and advisor". In the workplace this is perhaps the role of the manager (but in the knowledge that that role may be usurped at any time by any other person on the network)? The question then is how do organisations standardise on policies, procedures and practice that are essential for the organisation to run effectively? And how do those standards get "pushed out" to the people who will apply them - which is the focus for a lot of workplace learning at the moment?

Research & Evaluation

Stephen's paper ends with a description of how we might research the effectiveness of learning in a networked environment. The current causal models of evaluation - where researchers try to establish links between variables - are just not possible when dealing with chaotic, non-linear systems. Instead we need to bring in the research methods used by fields such as meteorology - modelling, simulation, pattern recognition etc.

But, at least with meteorology and other non-linear sciences, there is a behaviour or output that can be measured, such as the height of a wave, or the strength of a storm. What is the equivalent when we talk about human behaviour? Perhaps we need to be using "intelligence" techniques that analyse thousands of conversations, looking for patterns. So, rather than saying "we need to measure x", instead, as Stephen describes, we need to look at everything, conversations, links, activity etc and see what patterns emerge.

Will these patterns emerge only in large networks, eg. the network of bloggers? In which case, how do you "measure" the effectiveness of a particular intervention in a small organisation? Or with an individual? And if networks are inherently self-selecting, are we actually measuring how effective we have been at marketing the network?

Lots of questions, no answers yet - but I'm starting to see where my dissertation might be heading...