CCK09 Metaphors for the Social EcoSystems

Below is my first thoughts about the ecosystem that relates to the forum post:  Very sketchy still….

May need to spend a few days working on the “big picture” of Social Ecosystems.  I will try to link the digital habitat with the AI, the global changes – like global “warming” and “warning” in terms of climate changes (both financial, political and temperature change etc), technology (using the clouds, the Great Barrier reef (extinction of corals due to environmental impact), and the basic elements metaphor the “metal”, “non-metal”, “earth”, “water”, “fire”, the “water” as knowledge and learning metaphor, the Network metaphor using birds in the sky and fish in the sea, the micro-metaphor on digestive system, the neuroscience metaphor using chemicals (catalyst), electric sparks (small motors and generators inside our brain) (haven’t worked on it yet) and the chemical reactions metaphor based on chemical bonding.  Other metaphors could include magnetismENTROPY (Thermodynamics), Physics (potential and kinetic energy) – how one form of energy changes to another form, with conservation of energy, FORCE – from gravitational forces to force of attraction & repulsion (magnetism), electrostatic forces, to van der Waals forces (the weak force at molecular level), Learning as Planting of trees, and networks as woods, forests, Materials Science – the structure of matters based on (body centred cubic (bcc), face centred cubic (fcc), structure of metals, non-metals,  closed packed hexagonal (cph) for diamond, polymers (the thermoplastic and thermosets, their structure based on carbon chains – degradation for some plastic subject to ultra-violet light weakening of the bonds), plasticity (elastic and plastic regions) of metals, the hardness and impact testing – (i.e. hardness and toughness of networks) (how it impacts the emotions, leadership qualities, and dynamics and sustainability of networks) and these links to pseudo science (the yin and yang) and the multiple perspectives and interpretation and its links to Biology the Metaphors of eye lens (human natural lens) versus camera and video camera (artificial lens), and mirror (reflection of objects changing the left to right perspectives) and then to the senses metaphor – music – lyrics as language, a piece of music (rhythm and melody as emotions), popularity of songs or music measured by number of “tickets”, hits on the web sites (Youtube, Myspace, FB or twitter mention, and musical channel’s number of broadcasts, number of sales in concerts and the RESONANCE on blogs (see my resonance post on , wikis etc. And the MICRO AND MACRO metaphors could then be interacting, interfacing and articulating on the time, space and digital basis (with a dark hole stretching across the yet known space) ALL INTEGRATED in the SOCIAL ECOSYSTEMS (or even the MACRO SOCIAL ECOSYSTEMS AND MICRO NEURO-ECOSYSTEM INTEGRATED WITH TECHNO-ECOSYSTEM (COMPLEX ADAPTIVE SOCIAL NEURO TECHNO SYSTEM), and internet shrinking all the metaphors into a tiny summary like this!  Networks of the Real world ecml07_leskovec_mlg_Page_004_480From Networks of the real world.


From world techn


iceberg 3703386681_635d17d7ee

research-physicsFrom Research Physics



From flickr 

John [23/10/09]  I need to draw up all these on the CMap or Word document with lots of graphics. 

Postscripts: More metaphors – fishing

An interesting post on The wide open learning world: sea, land and ice views by Curt Bonk (just found at 9:12 pm 23/10/09)

Postscript: I found this learnscape of Jay Cross interesting


CCK09 Building a brain

You would surely enjoy this Builds a brain in a supercomputer

Every neuron is different

Pattern of circuitry does not change

What are the implications of such a “brain” talking to our brain?

CCK09 Is a scientific approach towards learning important?

Feynman in this video provides a unique perspective on social science.  It sounds challenging to most social scientists.

I agree on the rigorous checks that are necessary on any “Theory” based on a scientific approach.  It would be useful to adopt a scientific approach in exploring the multiple forms of truths.  May be it’s important to reflect on the “trial and error” approach towards learning and education that are prevalent at this digital age, especially with PLN/PLE and Web 2.0.  How about the pedagogy behind all these PLN/PLE in teaching and learning? 

My favourite is to adopt an empirical approach in understanding the science of learning and the associated learning theory – in particular Connectivism.  That’s why I like the research that we have just completed.   

Learning could be viewed both as art and science.  However I think a scientific approach is necessary, but not sufficient in understanding learning.  We also need an artistic approach in revealing the myths of learning.  But how?   May be the performance artists, the curators, the expert educators and our networkers could educate us more on these – with the repurposing, re-creating, re-producing of new forms of artefacts.  We may all appreciate the emergent learning experiences that we could “feel” and “sense” and way find with those learning, though such “learning” could be difficult to be proven using scientific methods. 

Enjoy this.

How could we improve our understanding of learning and education from an artistic and scientific point of view? 

Neuroscience, Network Theory, Complexity Theory, Actor Network Theory, Activity Theory, Situation Learning Theory, Cognitivism, Constructivism, and Connectivism.  These are all useful for understanding learning.  However, we may still be far from understanding the holistic “spirit” and “scientific basis” behind “postmodernism” of learning – our ecology of learning or the Complex Adaptive Ecology of Learning

Is a scientific approach towards learning still important to you? How would you apply such an approach?

CCK09 This is Your Brain

This video lecture This is Your Brain talks about Dualism and Materialism.

Are you just a pack of neurons?

What is Dualism? What is Materialism?

The mind is what the brain does.

Physical objects can do certain things.  Machines can play chess.

Brain does not taste good, but…

Neuroscience – How the brain gives thoughts?

Neurons – Basic building of thoughts

Three types of neurons – sensor, motor, and inter neurons (do the thinking)

Neurons relate to one another chemically…


You could compare our brain with the Android.

It could even sing.

What are the implications of these technology on our education, thinking and learning?

CCK09- Connectivism – Building a Circuit Diagram for the Brain

This Building a Circuit Diagram for the Brain provides a fantastic explanation about learning.

So, in learning, it involves neurons, synapse, circuits and stimulus.

These may be of interests to us:

Retention of learning

Generation of learning

Reversal of learning

Does this help in understanding human learning (at the neuronal or neural level)?