ZML Didaktik / Innovative Learning Scenarios

Dealing with connectivism – George Siemens, 2008

Posted on: Mai 1, 2012

My summary and understanding of George Siemens: What is Connectivism? September 8, 2008 – with many direct quotations

Five principles that conform the foundation of any learning theory

  • Externalise … (Langauge, artefacts)
  • Frameworks / structure for sensemaking
  • Socialise and negotiate (shaped by discussion with others)
  • Patterning mind (recognition of face)
  • To extend (exeed?) out humanity through technology

Connectivism

  • Knowledge = networked and distributed, being connected
  • Forming new neural, conceptual and external networks
  • In complex and chaotic environments
  • Aided by technology

To better understand learning we need to better understand how and why connections form, to understand the nature of those connections

In what manner does learning occur in networks – we need to better understand the context. There are 3 types of learning networks:

  • Neuro-biological – learning is the formation of new neural connections (connectionism & AI, neuroscience)
  • Conceptual – relatedness, connectedness, association between ideas and concepts. Deep understanding is related to conceptual networks. New points of information can be learned easier if there already exist concepts of the topic. Connections create meaning. Open question: do network properties exist at conceptual level
  • External-social – here the most existing research about: how are we connected to other people, how are we connected to information itself (information flow in organisations)

Learning in a connectivism sense is a function of:

  • Depth and diversity of connections (valid for all 3 types of networks)
  • Frequency of exposure
  • Integration with existing ideas and concepts
  • Strong and weak ties (strong ties: typically defined as small world phenomena where we are well connected to other nodes; weak ties bridge such worlds, it has been argued that we get much of new information from weak ties as they exist in networks we don’t have regular and consistent contact with.)

Different types of networks with different types of attributes will serve different types of learning needs. Active learning = forming of a connection. Much of the discussion of network principles comes from other disciplines. Important to understand learning networks, how they operate, why they possess the characteristics they have.

Networks of learning are implicit to humanity.

Through technology we

  • have more possibilities to create and share content (abundance)
  • increase ability to dialogue with others (complexification)
  • simulate experiences (enlargement, expansion)

The society in which we exist, the information world that we inhabit, has becoming so complex which such an abundance of information that we need networks to survive.

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