Connectivism

Connectivism¹ is a learning theory where the central object of the theory are networks.

On this post, a few key ideas are presented; in the next post, a different interpretation of the theory is proposed.

Origins

Connectivism seems inspired by:

1. The Internet, and later on the World Wide Web,
   • These both were from the start problems about networking; heterogeneous devices or resources linked together,
   • These technologies opened up access to a network of resources and people.
   • The world changed towards quicker decision-making, but I argue pattern-matching, and thinking strategies have not changed much.
2. The view of an individual as a network of neurons,
3. The view of other systems as organisms, like organisations. The paper linked above states:

   The organization and the individual are both learning organisms. Increased attention to knowledge management highlights the need for a theory that attempts to explain the link between individual and organizational learning.

As said, networks are the main object of the theory, so let's briefly define them:

Networks: collections of linked nodes or items.

What is considered a node is defined by us. It could be an individual, a group, a government, countries that trade, libraries, and so forth.

There are types of nodes and edges (or links) with different properties. For example, a node may have restricted access to a resource. There are also topologies with specific wiring pattern.

Knowledge and Learning

The theory views knowledge and learning as properties of networks, and defines them as:

• Knowledge

  • Network view: it is stored distributed across the net (in nodes, edges) in a latent manner. Distributed knowledge means that no single node or edge is uniquely responsible for a concept, rather, many parts of the whole network are. There will be nodes that are more relevant in some situation than other, but the knowledge is still distributed across nodes and links.
  • Behavioural view: It is evidenced as an appropriate response to an input signal or stimuli.

• Learning

  • Network view: a change of network connections by exposure to experience and reasoning.
  • Behavioural view: a persisting change in knowledge. Learning is evidenced through a change towards more appropriate behavioural responses (to a signal or stimuli.)

In a network, one node or link changing means much more has changed due to the ripple effects given by the links.

Discussion on whether all networks really learn are left for the next post. This one focuses on learning-human-networks and how the theory can help understand and design them.

A human in the net

A promising area for connectivism is as a paradigm to think of human networks (or human-and-resources networks), how to organise them (or letting them self-organise), which properties make nodes and the net grow and so forth.

It appears of especial important in the digital, interconnected world; but also classrooms, organisations, and social networks in general.

Let's consider the case of a human or agent embedded in a wider network such as a classroom, a group, community, organisation.

This networks can be seen as an metaphorically organism, or just as a whole: when the connections and nodes change and so does the behaviour in response to input signals, which in certain cases will imply learning, and formation of knowledge.

Example

Think of the response of an organisation in the event of a fire or an emergency.

The input (fire alarm) ripples through the network as the nodes act and propagate activity: learning isn't only intra-personal, the whole network can be said to have learnt in this example.

In the case of a classroom, this framework may aid us with questions such as:

• Centralised human-learning-network guided by teacher or a decentralised network? Should the teacher be more like a routing node?
• Are all items considered part of it, such as resources, or agents such as humans? Is it useful to split or join different networks?
• An open network where agents can change resources, or closed networks where they only have read permissions (if even so)?

A human is a net (theory of mind)

We also want to focus on the individuals. Can connectivism help?

Their general claim is that any network can learn by modifying connections and nodes of the network. And stores distributed knowledge.

So can parts of the brain, which are networks of neurons, and learning is later on evidenced on the behaviour of individuals.

1. https://www.scispace.com/pdf/elearnspace-connectivism-a-learning-theory-for-the-digital-4dh6aurogw.pdf ↩