The internet has often been described as a "dumb network" with intelligence residing at the edges (meaning that the network only cares about distributing content - doing anything with the content is the task of protocols and devices at end points). I've been thinking about how this translates to the creation of a personal learning network. Connectivism presents "rapid knowledge growth" as the process of adding on or plugging into new networks (an example is a web programmer who is trying to learn a new programming language. Instead of taking a course, she might find it easier to join an existing development community, subscribe to list servs, read and modify code others have produced...in essence, she doesn't possess the knowledge, but competence in a knowledge economy isn't only about possessing something - it's about finding it when it is needed).

For the purpose of learning, I believe that we have to ascribe some level of intelligence to the network. The network primarily delivers content, but the network also carries a sense of learning (serendipity, aggregation). Learning (being defined as knowledge that can be or is actuated) can reside in non-human appliances. The creation and formation of a network then is an attempt on the part of the learner to create a structure that allows him to stay current in a certain field. Learning is not a state at which we arrive. Learning is a process. It could be argued that we know something once we connect with a network that enables us to continue to know more. Back to the web programmer example - if a web programmer leaves the community...and a new member joins, within several releases of new versions of the language, the new member is at that stage more knowledgeable than the experienced developer who has left. Why? Because she is able to function optimally within the existing environment with the existing tools. If the experienced programmer decides to rejoin the community to increase his understanding of changes to the programming language, he may be able to "get up to speed" very quickly. Again, the network, not what is known now, is what's important. Connecting to a new network results in instant access to know more...severing from a network results in immediate flow of new learning...

Learning is usually viewed as something that happens to a person. A person learns how to solve a physics problem, how to skate, or how to communicate. The assumption is that we are fairly autonomous beings, and that we can acquire within ourselves what we need to know to do the things we want to do. This model works well in areas where one can know everything within a field of knowledge. The model breaks apart as complexity and abundance of knowledge increases. For many, this is a very real problem today. It feels that we simply can't stay on top of our own fields. Forget trying to stay aware of occurrences in other fields. How do we learn in such an environment? Abundance=dysfunctionality in a silo learning model. "Superman's Learning Theory" - the notion that I can know in myself what I need to know - is obsolete today.

Why? Designing elearning is a simple example. No one person can be subject matter expert, instructional designer, media specialist, and graphic designer. It takes a combination of specialized skills (connected specialization). Take that concept to more complex fields like medicine, astronomy, physics, or launching a space shuttle. It immediately becomes obvious that we need to create a network to hold the points of knowledge. The network is the learning. The aggregation of network nodes is the learning structure. If any critical nodes are removed from a learning network, the entire organism loses effectiveness. Learning is evolutionary. Learning is not an event or end goal. Learning is a process. Our personal network is continually being augmented and enhanced by new nodes and connections.

I'm very confident that this is the model that we need to use for successful learning in today's environment. We can't stand alone on our own knowledge. We have to aggregate with other nodes (people, content, knowledge) in order to meet the challenges of a complex information climate. Unfortunately, education (K-12, higher and corporate) are built on the model that we can fit what is important into one person's head. The network becomes valuable once we combine and connect separate nodes of knowledge.

One of the original points I assigned to connectivism was that "learning exists in diversity of opinions". The ability to formulate a network that provides diverse assessments of a problem (with potential solutions) requires multiplicity. A network can have seemingly contradictory points of information (something that is false today may be true tomorrow as the underlying foundations change). Exploring diverse opinions enables greater likelihood of making healthy decisions. Who knows, perhaps conservatives and liberals can recognize points of value in each other...:).

A Crash Course On Complexity, Emergence and Collective Intelligence: "These are exciting times. We have an opportunity to watch and study the development of an emergent intelligence rooted deep within the interconnections of the net. The interconnections in this case, are not only the physical real-world network connections but also the interconnections within the web itself, the blogshere and the flow of human consciousness that "surfs" across the datascape."