Rhizome or network in #change11

My network view of knowledge is simple: entities (broadly defined as well, anything: people, a chemical substance, information, etc) have attributes. When entities are connected to other entities, different attributes will be activated based on the structure of those connections and the nature of other entities that are being connected. This fluidity of attribute activation appears to be subjective, but in reality, is the contextual activation of the attributes of entities based on how they are related to other entities. Knowledge then is literally the connections that occur between entities. [http://www.connectivism.ca/?p=329]

in my drawing: E n (an) :  Entity  has attributes.
aa n: activated attributes.

1. Could we know all attributes of Entities?

2. Could we know which attributes will be activated?

3. Could we know the structure of the connections, and how this structure influences the activation of attributes?

4. If E 1 is connected to E 2 and to E 3 lots of attributes do get activated. Can we know how the activated attributes influence Entities, structure of connections, other Attributes?

Can we know all attributes?

If Entity is a person, I do not know all attributes that influence learning. (health, drug use, personal history, earlier learning, motivation). I cannot know all attributes that do influence learning, and I cannot know how all these attributes do influence learning.
If Entity is information, attributes are name, value, authority of source, source, quality, minimum and maximum values, reliability, etc.
I cannot know all attributes because every attribute of Entity information is another Entityinformation

Information seems to be an infinite set.

Can we describe the knowledge network of a person or of a group?

Some networks have boundaries. the network of cells in a human body has boundaries. But do networks of knowledge have boundaries? Or maybe a better question, can we know the boundaries of the network of knowledge of a person or a group? Could we describe and make an inventory of all the knowledge and attributes and connections in a given network?
Could we make a difference between a network of knowledge and a rhizome in this regard? “…Rhizomatic learning is about embracing uncertainty. That’s the goal. Getting to the point in oneself, or helping someone else to get to the point where they are able to confront a particular system, challenge, situation whatever not knowing the answer and feeling like they can decide about it. I try to thinking of teaching, then, as mimicking the process of being confronted with uncertain situations, that develop the literacies required to deal with uncertainty…” [Dave Cormier]

Structure of connections in a learning knowledge network

Structure of connections could be: direction, one-way, two or more directions, capacity of connection, nature of connection, selectivity of connection, conscious or unconscious connection, etc.
Could I know what will be the structure of connections in a learning network?

Creativity

In a network of knowledge that is well known, mapped, described, creativity would be difficult, because creativity could be “connecting in a new way”. If creativity exists, than the network has some unknown corners.

I do not know if the differences between the metaphors of a network and a rhizome are that big.

I almost forget this: metaphors are not facts, metaphors are not theories.

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4 thoughts on “Rhizome or network in #change11

  1. Jaap – not being afraid of a bit of maths I was attracted to your diagram but with little in the way of definitions I guess your main intention was to make some useful and interesting points about the nature of networks. “Knowledge then is literally the connections that occur between entities” is something about connectivism that I’ve never quite come to terms with. Apart from an obvious relevance to networked learning, it seems to sit uneasily with common sense notions of the meaning of knowledge. Now this is quite in contrast with Information Theory (ie Shannon’s http://en.wikipedia.org/wiki/Information_theory ) where ‘Information’ is mathematically well-defined (also embraces uncertainty!) albeit with a restricted meaning – although not too out of line with the normal use of the word. Information Theory has led to countless advances in reliable communication, video and speech coding etc etc. I would love to see a Knowledge Theory develop in a similar way!
    Gordon

  2. Gordon, thanks for this interesting comment. The “knowledge in the connections” is not yet a very clear subject for me too.
    I am trying to understand this “connections-knowledge”.
    For now my thoughts are that connectivism says (I am very careful) that people do connect information in some special way to make it knowledge. I do make a difference between information and knowledge. George Siemens writes about connections with different structures.
    In the diagram I tried to make visible the different structures of connections.
    The structure of connections could be:
    – Connecting information and combining it to a “story” or as parts of a greater entity.
    – making conclusions, about causes, influences, effects.
    – making sense.
    – etc.
    Gordon, your comment did cause me to connect nodes or bits of information to get a better (?) knowledge of the connections in connectivist theory, Thank you for that.

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