IS diffusion theory research – hints for e-learning implementation

I’ve previously written here about the value I believe which diffusion theory brings to helping understand, design and support the implementation of e-learning within a university context.

Diffusion of Innovations theory has been “>used significantly within the information systems research community. That research has consistently found that three perceived characteristics of an innovation are important antecedents to the adoption of an innovation

  1. Technical compatibility.
    How similar is the innovation to what the potential adopters are currently doing?
  2. Technical complexity.
    How complex is for potential adopters to understand and adopt the innovation?
  3. Relative advantage.
    How much do the potential adopters perceive that they need the innovation?

An innovation that has HIGH compatibility, LOW complexity and HIGH advantage is much more likely to be adopted.

These measures are subjective and are based on the perceptions of the individual participants.

Lessons for Web3dx

My previous post about diffusion theory used the theory to understand what we might need to do with the Web3Dx project.

Concentrating just on these three characteristics, I feel that for most staff their perception will of Web3D will be

  • Low compatibility
    Immersive 3D worlds are very different from what they’ve done before. They will need to have and use new software to get into this.
  • High complexity
    For non-gaming staff using these 3D worlds will be difficult. Understanding and incorporating them into their teaching will also be very difficult.
  • Uncertain relative advantage
    Staff will be uncertain just how to use the technology and what advantage it might have.

So it doesn’t look good. As we’re involved in the project we need to develop tactics we can use to turn around the above perceptions.

Lessons for e-learning development

The above, at least to me, is further evidence to support the proposition that ateleological development is a “better way” to develop university e-learning systems.

Ateleological development, would by its nature, concentrate on implementing innovations that are more likely to have high compatibility (the innovation would be a small change from current practice), low complexity (it would be implemented in as simple and transparent a way as possible) and high relative advantage (it would be chosen to solve a specific problem identified by folk within the system).

Based on diffusion theory, such an approach would lead to greater levels of adoption.

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