#CCK11 Connective Knowledge and Emergent Learning

I am reflecting on my understanding of knowledge based on this post

Knowledge today is complex, ever changing, and information is overabundant. Knowledge no longer resides in a single place, in a brain, in one person or a cadre of experts – it is in the connections we make, our networks of learning (Siemens, 2006). Technology is evolving and affords us the opportunity to connect and share. As our network grows it impacts upon our assumptions regarding learning infrastructures, authority, and certainty of “knowing”. We need to recognize that a textbook, a professor is a node not a touchstone. Textbooks and professors can guide learners, can provide trusted nodes, a framework, a foundation and skill set that enables and maximizes the learner’s journey. Today’s learners have so much opportunity and so many resources available to them. It is truly an exciting and rewarding time for them. Encouraging learners to contribute their own viewpoints in a clear and thoughtful way is so much a part of the learning journey. We need to develop attitudes and skills to be able to balance technological and cognitive agility, and capacity in defining and achieving our goals (OCC2007, 2007b).

I would like to ask a few questions based on the above:

Knowledge no longer resides in a single place, in a brain, in one person or a cadre of experts – it is in the connections we make, our networks of learning (Siemens, 2006).  Here we assume that knowledge does reside in a single place, in a brain, in one person or a cadre of experts in the past.  Who made this assumption? Does knowledge reside in a brain (for human knowledge, in one’s brain)?  What does it mean when knowledge resides in a brain? When we said knowledge is pattern recognition, does it refer to recognition by the brain of a person or by the brain of a number of persons? So, can we say a person’s capacity to recognize pattern does mean that such “knowledge” is associated with one’s brain, and could also be associated with a number of persons’ brains? So, I reckon we need to distinguish such knowledge that is recognized by the human brain from other knowledge (the emergent knowledge, the social knowledge, the connective knowledge, or the collective knowledge).

As our network grows it impacts upon our assumptions regarding learning infrastructures, authority, and certainty of “knowing”.  What are the assumptions that we have made regarding learning infrastructures, authority, and certainty of “knowing”?  Who made those assumptions?

How about my suggested Assumption Theory?  Are we assuming that knowing is certain all the time?  At least, when we make a decision, aren’t we assuming our decision is “right”? Otherwise, we won’t make such a decision?  Are we really certain about the knowledge we “have”, even with the pattern recognition? This relates back to our experience and learning capacity, in that we can’t be always certain about the “knowledge” and information we “have”, but we just need to assume that such “knowledge” is at least “good enough” at this stage of time based on our limited knowledge.

There is a Chinese motto (from Zhuangzi, one of the wisest Thinker and Philosopher in Chinese history): I have a limited life, but I know there is unlimited boundary (knowledge, learning etc.) in my life.  To use my limited life (I can only live up to a certain age) to chase after unlimited boundary, that is like chasing after “death” (a tragic journey).   If I still insist on chasing after such unlimited boundary even with my limited knowledge, that is quite a tragedy.

Here is the translated version of Zhuangzi

Human life is limited, but knowledge is limitless. To drive the limited in pursuit of the limitless is fatal; and to presume that one really knows is fatal indeed!

I think it brings out the limitations when one is learning in solitude, especially in ancient Chinese learning environment, where knowledge was based principally on “books”, personal experiences and narratives, and that even a wise person would hardly be able to grapple with the knowledge available at the time.  Is this still true at this digital age?

I reckon there are still some “truths” and lights shed with such concepts, based on my perception, since even with the use of technology, where information and knowledge (pattern recognition) are abundant, may be even at our finger tips, by connecting with others, with networks, and interaction with the aids of various tools and technology, or attending formal education through institutions, etc. our individual “knowledge” capacity is still limited.

The SARS case illustrates the importance of connecting with people, having accurate and  up-to-date and information, and a reach to the information sources or artefacts, experts and professionals of the field, relevant knowledgeable others,  and the community in order to prevent, control and minimize the risks associated with SARS.  Also, this global outbreak alert and response network highlights the importance of using a network approach towards the prevention, identification and control of such disease.  It is through such collaborative and cooperative efforts that the networks, community and individuals could learn and solve problems together.

The Global Outbreak Alert and Response Network (GOARN) is a technical collaboration of existing institutions and networks who pool human and technical resources for the rapid identification, confirmation and response to outbreaks of international importance. The Network provides an operational framework to link this expertise and skill to keep the international community constantly alert to the threat of outbreaks and ready to respond.

How about the current devastation in Japan?  Aren’t we getting these updates as a result of technology (internet, news broadcast)?  Would networks help in minimizing the casualties or injuries as a result of such natural disasters?

Here is my interpretation of connectivism, where I posted here.

Connectivism is new in that it is:

about the distribution of knowledge in the network and oneself (including our brain – your and my brain), and the solution lies in one’s brain. All problems and solutions are there in the brain – your brain if you want to solve the problem, and my brain if it is my problem and solution.  And what connectivism differs from other learning theories is that we could connect one’s brain to others’ “brains” that will lead to continuously improved and innovative solutions for me and the network in this digital age – networks including yourself with collective wisdom with emergent knowledge.

This relates back to what connectivism is: Knowledge distributed, learning as networked process (i.e. forming connections), principles form base of all design.  And the three levels: Neural, Conceptual and External (people, information sources etc. (Siemens, 2008)

Here Roy, Jenny and Regina shared their learning, and Jenny says:

“The power point we used is here Emergent Learning presentation (PPT) You will see that there is not a lot in it. We tried to plan the session to allow for emergent learning :-)

The chat room transcript is here Emergent Learning Webinar Chat Transcript

This is The recording of the Elluminate session

So my understanding of emergent learning is that

Emergent Learning is: Self-organised learning within a network.

and connective knowledge (refer to Stephen Downes, What connectivism is)

Stephen mentions about networks power and ethics here:

In groups, the properties of autonomy, diversity, etc. tend to be thought of as inhibiting the function of the group. Notice how the person who has a different point of view, or who has different objectives (“their own agenda”) are depicted as obstacles to be overcome.

Nothing inherently in a network fosters autonomy, etc. and, depending on its make-up, a network can be used equally to promote or to eliminate autonomy. That is why it is possible for a network to effectively collapse into a group.

A reworking of this question would be, why are autonomy, etc., important? And I have tried to answer this in An Introduction to Connective Knowledge and elsewhere. Networks in which these values are promoted are robust, dynamic, stable, reliable – they are good knowledge engines. We can rely on them (the way we rely on scientific explanation and induction, as methodological paradigms, tweaked and adjusted over time).

Another way of stating the same thing is that networks in which autonomy, etc., are abridged are effectively dying. The resonation of connections from entity to entity will gradually cease.

If I reflect on Stephen’s assertion here, then there is a possibility of network – group – network – group cycle in order to survive and thrive amongst networks, as networks which limit autonomy (of individuals) would soon “suffocate” and degenerate into inactive networks, and thus “death”.  But how would re-vitalization happen with those networks?  Would the catalyst be through the emergence of crisis like the current one happening in Japan?

This catastrophe has become a wake-up call to institutions and governments on the need to develop closer “knowledge” and “rescue” networks and teams, and connective intelligence and global aids in response to disasters.  Through such “life” lesson, we could experience the power and importance of connective knowledge.  Would emergent learning add value to our human learning on a global scale?

What are those lessons we could learn from these disasters?

How could these relate to individual’s learning?

Postscript: This http://mashable.com/2011/03/17/social-media-crisis-responsibility/ on social media crisis responsibility comes at the right time.