A new theory of knowledge and learning emerges out of the construction and navigation of knowledge networks: Connectivsm. Neural, conceptual (Burke) and external, networks manifest its connecting character allowing the flow of distributed knowledge. As an amazing fractal structure, we find networks at the three levels of learning. Based on networks structure in a complex changing environment and distributed congnition, Connectivism is being leveraged by technology.
If human mind can know and is basically a network, then any network can come to know? Seems that the network organization with its structure and dynamic is what makes possible to know. The brain responds to environmental demands, generating, creating, strengthening, weakening, losing and eliminating neural connections. So mind is a construct which is distributed from the brain to the environment (Kerr) and plasticity is its intrinsic core.
Any interaction in a network, makes the connections to change, resulting in storage of information. Learning results of integrating all information perceived and processed that leave a physical trace of its passage, generating new network organization patterns.
But how language, which is another specifically human cognitive function has also a role in developing knowledge? Connectivism must develop a answer to this question.
The discovery of patterns in the Universe shows great regularities. Inner structure of Internet, information linkage in the web, people interaction in social networks, all show a surprising bridge in between local properties or individual actions and the resulting collective interactions. The structure and dynamic of the system is determined by the collective interactions of all of its constitutive parts, and at the same time, it’s individual behavior are framed by the topology and dynamic that emerges.
Network Learning found in communications technologies and software developments, key drivers for its development.
We begin finding hidden laws that govern the formation, growth, evolution of these networks. In the last years, psychologists, biologists, mathematicians, physics and other scientist have shared their observations and built a new epistemological space that we could call the New Science of Networks. A new theoretical perspective that provides tools to physicists to battle against epidemics, engineering to prevent fails in cascades in large interconnected systems like the power grid or visionary economic analysts that anticipate financial meltdowns.
Kant argued that time and space are the natural and irreducible categories of mind, the way how we perceive reality. Reality manifests itself as complex interconnected networks. Stability, synchronicity, self similarity, threshold, cascades, epidemics, emergency, resiliency, keystones, phases, connectors, evolution, clustering are some of the new way of seeing and thinking the world. A simpler world that connects very diverse phenomenon, entities and realities. A world that needs to learn on networked thinking.
Social webs begun its development during the new century even though the first weblog appeared in 1995 and a year later blogs allowed readers to comment. The exchange of files in between PCs was facilitated by Kaza, Gnutella, Bit Torrent. Later Wikipedia, Technoarti, Flickr, Fotolog, Delicious, LinkedIn, My Space and FaceBook allowed social networking, bookmarking, blogging and dating including virtual reality environments like SecondLife. User contributed content was another important component like in YouTube were audience begun producing content. All this new ambient was named web2.0 and Kevin Kelly affirmed that “we are the web”. The wealth of the networks now is based on commons peer production and profits do not come from comments but from attention and banner clicks. The time spent became the central value of the Internet.
So, Network Learning backed by technology, merging fields and new theoretical views of learning, knowledge and cognition helped in paving a new epistemology space together with the massive participation in the web2.0 . May connectivism play this role?
Learning on learning with 2200 class mates on MOOC through networks make people, ideas and concepts being connected. The same platforms and tools to be used in this course are the one to be observed as a practice and collective experience on Connectivism. Wikis, Moodle, blogs, mails, groups, alerts, Twitter, Wordl, PageFlakes, e-lluminate, UStream, Facebook, Second Life and Flickr are just a selection of tools that me be used. Texts, graphs, cloud tags, audios and videos are enriched by same students with their comments, blogs and references.
Connectivism may be developed as new theory of learning. To do this, it must answer and provide a better understanding of language and its role in learning, knowledge and cognition. But probably, in its effort to become a new theory and in the middle of epistemological discussions, Connectivism may be losing its potential on the practical field of education and human organization.