I was, perhaps not surprisingly, impressed by George Siemens‘ recent presentation on Learning in complex knowledge spaces not so much for the radical recommendations for the future of learning, but rather for the logical and balanced presentation of the narrative. It flows, builds, and makes sense from start to finish and that is a talent, the talent of presenting the complex in accessible terms. Luckily enough the topic itself is complexity. So the presentation first and then a few comments. 

Croatia: CARNET [slideshare id=10163878&w=425&h=355&sc=no]
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Slide 7: Each iteration increases level of abstraction
I think this is the nature of complex systems the world over, language itself being one of them. We used words to represent objects, letters to construct words, books to contain them, and now visualizations and representations to represent large chunks of text.
Each time we pass through the cycle of creating tools to deal with more information, we move the knowledge center, that cultural cognitive capacity for understanding a bit further from simplicity. Kind of like the old days of DOS or even the difference between a Word doc and some elaborate multimedia narrative. When I was studying for a Masters in Information Science, we were forced to learn Dialog Basic (command line database searching) to more fully appreciate what was underneath the hood, so to speak. It was an attempt to get past the abstraction a bit to learn information flow as developers and programmers might know it. As chunks of complexity represented in particular ways. I think that ship has sailed in terms of learning that level of complexity (we are like 5 iterations away from this command line search interfaces now) but abstraction is movement and it is important to occasionally reflect on where we are coming from. 
The truly pervasive tools and ideas are so powerful they become completely ubiquitous, flooding our cognitive spaces with utility. They become the context in which we wonder ‘what in god’s name ever came before this?’ That feeling of what could have been before this is a few layers of abstraction convoluting the narrative of learning development. The complexity increases our need for tools to make sense of the complexity which in turn iterates our societies away from that original complexity. I suppose that is the point and not necessarily a bad thing, but something to be mindful of in terms of learning design. The center cannot hold as it has iterated itself a couple hundred miles away from that center. Things fall apart.
Slide 22: Think of these examples not as specific tools, but as new affordances; new action potential
I love this one as it pushes us beyond the simplistic dichotomy of learning technology or not technology. Tools, back to the simplest stick used to poke at a hole, are affordances for new actions. They allow for new things. And truly great affordances flood environments with capacity, becoming ubiquitous rapidly. Layering over the past with a shiny new floor of capability. We offload manual dexterity and operational intelligence onto tools and networks precisely because that is what we have always done and should always do. For example, books were containers of information with the occasional side effect of producing disciplined (ideally) long-form thinking. I didn’t need to know everything if I had a large enough collection or a library nearby. I offloaded this static intelligence onto reference sources, freed up cognitive capacity for operational intelligence. Problem solving. Innovation, even reflection. The internet (as information store) and the internet (as social network) free me even further from the tyranny of information recall. They free me up for new action potential. A new ambient, dsitributed kind of intelligence, made possible by my community, amplified by these same channels. So, yes, I agree; not tools but action potential. 
Slide 29: Working different
I see these products (and many thanks for pointing them out in the presentation) as a reevaluation of the units of work, how they constitute the whole output, and some dabbling in how they can be reengineered for greater efficiency (and distribution). Mechanical Turk or Solyent or any number of initiatives designed to microtask complexity and distribute it amongst the community for greater efficiency. Freeing up your cognitive capacity for innovative thought in teams, organizations, universities, even corporations and nations. Distributing tasks to process. I think music would be a nice example here. Separating the task of creating/composing and playing/writing sheet music. These are not inherently the same thing. A creative person should be freed to create in whatever medium speaks to them regardless of the mechanical acumen necessary to facilitate that interaction. In short, I can compose with a violin without ever learning how to play one. That might be an automated distribution (tool) rather than a community distribution (crowdsource a composition) but the effect is more or less the same. It frees me up for new activity. 
These aren’t the main points George Siemens is trying to make. His focus is on the need for a comprehensive rethink of our learning structures and what exactly their purpose is in a community-driven, informationally abundant age. What knowledge constructs are they trying to create? What outputs would society need? What does it all look like? I enjoyed this narrative of tools, connectedness, and pedagogy (MOOCs) as it had enough narrative momentum to carry the audience to a conclusion even if that conclusion wasn’t overtly described. Like I said, a real convincing, comfortable narrative. 

By Michael Gallagher

My name is Michael Sean Gallagher. I am a Lecturer in Digital Education at the Centre for Research in Digital Education at the University of Edinburgh. I am Co-Founder and Director of Panoply Digital, a consultancy dedicated to ICT and mobile for development (M4D); we have worked with USAID, GSMA, UN Habitat, Cambridge University and more on education and development projects. I was a researcher on the Near Futures Teaching project, a project that explores how teaching at The University of Edinburgh unfold over the coming decades, as technology, social trends, patterns of mobility, new methods and new media continue to shift what it means to be at university. Previously, I was the Research Associate on the NERC, ESRC, and AHRC Global Challenges Research Fund sponsored GCRF Research for Emergency Aftershock Forecasting (REAR) project. I was an Assistant Professor at Hankuk University of Foreign Studies (한국외국어대학교) in Seoul, Korea. I have also completed a doctorate at University College London (formerly the independent Institute of Education, University of London) on mobile learning in the humanities in Korea.

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