The Tool of Everything and the Theory of Everything

By far the most definitive week of discussions around PLENK for me, this week’s Friday discussion is worth multiple rounds of further investigation and discussion. I cam in a trifle late and it was difficult to catch up without a starting context, so I caught up with the recording later. Here are my notes and deductions – my version of the conversation between George and Stephen. As always, please feel free to add or correct me in case of any thing I missed or misinterpreted.

Stephen Downes

• There is a Tool selection or Dashboard approach to classifying technology experience
• There is no great application out there that allows me to read and write like gRSSHopper. This is the workflow approach. We need to model workflow, provide end-to-end functionality and that is the most daunting piece.
• Should we be looking at a theory of everything (like Atlas in geography or Set Theory of everything)? Technology will evolve over time, but the core patterns of use may not (in fact, they may).
• Is there was a way to hide the modalities, so that we focus on the core?What are these core ideas? Personal autonomy, distributed knowledge and social learning. There are frameworks like the 21st century skills frameworks. These are very widely  fragmented. I would add pattern recognition as a fundamental skill – is the optimal tool one that would be based on network theory and pattern recognition?
• Machine analysis can give us a syntax. The human side would give us semantics.
• Can we figure out, in technological terms, how humans do it – derive meaning? From the neurological sense, it is a very organic process that evolves over time, not intentional or deliberate, each new experience creating more understanding.
• Is the tool of everything going to be a pattern recognition tool?

George Siemens

• First time adoption of tools is difficult, not because of the tools, but because of concepts.This is where companies like MS or Facebook helped by aggregating functionality and establishing common ways of completing standard tasks
• Tools that are available but the level of integration is too low at this point. With connective specialization, it is an each to her own preference. Also at the point of adoption, it adds to the confusion.
• Do we need a tool of everything or do we need a way to build capacity?
• The theory of everything: maybe with a combination of critical literacies and attributes or ideas of the disciplines?
• The hiding of modalities is important.
• There are two dimensions to pattern recognition – technological and human. The technological example would be reading through a mass of data vs. navigating a structured analysis of the mass of data. On the human side, Learning Analytics tools provide valuable patterns of use. That is what computing can do and visualization is going to be very important.
• That does not mean that technology will be able to model personal or network use of the resources, but technology can help.
• We need to have a balance between what a computer does well and a human does well (form vs. meaning).
• Experts and novices think differently – experts think in patterns and novices think sequentially, or (Cris2B) plan ahead vs plan backwards. Conceptually, once some patterns are built up, some context, we are able to recognize more complex patterns.

My 2 cents.

I think that we must first start by presentation and analysis (as best as the computer can visualize in a simple way) and let humans and our networks derive the meaning. This is what I hope an NBT will achieve.

Maybe at some point, the insight from how humans use that information for semantics, through reflection and practice,  will start becoming progressively templatized as we understand or build tools and processes that can model how humans function – how we evolve from novices to experts in an area. I call this Native Collaboration and see it permeating every function in learning.

The discussions are fast evolving to a stage where some formal models of Native Collaboration (which attempts to model, functionally and technologically how we learn) and NBT (my terminology for Network Based Training – an evolution from Web Based Training or WBT) will emerge where the NBT environment encapsulates the modalities in a fairly standardized manner while allowing personal autonomy and includes specific connectivist techniques for Native Collaboration. This is really exciting!



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