Distributed Cognition: Supporting the Knowledge Ecosystem

Distributed cognition is a theory that seeks to model how social and technological influences intersect and influence cognition (Hutchins, 1995). According to this theory, an individual’s knowledge is not embodied in the individual alone, but instead is distributed amongst the individual, members of his/her social group, and the technology used by the individual/group. Instructional designers creating digital learning experiences (elearning, mlearning) have to consider how information flows between these different agents to create an ecosystem of knowledge sharing.

The role of technology

In the distributed cognition model, technology has a number of critical functions:

  • Aiding memory
  • Promoting more efficient decision-making
  • Changing the nature of tasks by making actions more efficient
  • Creating short-cuts for the creation of mental models
  • Limiting abstraction

(Zhang, 1997).

Consider how important technology is to your personal learning network. It helps you to find, filter, organize, and  annotate large volumes of data. Perhaps, most importantly, it allows you to create mashups between different media platforms. Technology can be transformative (with more than a little human intervention).

The role of community

As you’re probably already noting, people are also integral parts of personal learning networks and in distributed cognition, social structures are as critical as technological structures.

But social interactions can have both beneficial and detrimental effects. On the positive side, groups can increase individual efficiencies by:

  • Providing more resources
  • Distributing task load
  • Reducing errors (provide more eyes to cross-check)
  • Bringing new approaches to bear on a task

However, in some instances individual efficiencies can be lost because of:

  • Lack of sharing
  • Time constraints
  • Communication barriers

In other words, two minds aren’t always better than one (Zhang & Patel, 2006). Similarly, culture both enriches and restricts knowledge acquisition and transformation. You gain the benefit of a world view that is as big as the world you allow yourself to be in.

An Ecosystem of Balanced Elements

Given that technology isn’t transformative without the innovative perspectives of those who use it and social groups aren’t perfect conduits of knowledge,  another opportunity arises for the instructional designer. The instructional designer must consider how technology can be used, not just to engage individuals but to support more productive environments in which social and cultural interactions can take place.

These supports must balance perceptions of creative autonomy, shared  goals, and a sense of interdependence (which includes valuing the contributions of other members in a social group). These are pretty lofty outcomes and certainly not achievable through technology alone. Providing collaborative software does little to ensure that collaboration occurs.

While technology is just a mediator of collaboration, it does extend the range of communication opportunities available both in terms of space and time. The evolving role of the instructional designer is perhaps to model boundary-crossing interactions (Lipnack & Stamps, 2000), in which the emphasis is not on authority or on social identity but on trust.

More about boundary-crossing interactions in the next post.

References

Hutchins, E. (1995). Cognition in the Wild. Cambridge, MA: The MIT Press.

Lipnack, J., & Stamps, J. (2000). Virtual teams: People working across boundaries with technology (2nd ed.). New York: John Wiley & Sons.

Zhang, J. (1997). The nature of external representations in problem solving. Cognitive Science, 21, 179–217.

Zhang, J., & Patel, V. L. (2006). Distributed cognition, representation, and affordance. Pragmatics & Cognition, 14(2), 333–34.

Photo credit

Social media dataflows by Anne Helmond

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