eLearning has a satisfactory set of options if your goal is information delivery or procedural training, but what about creating meaningful eLearning for complex skill development or for the not-so-procedural kinds of problems that show up more and more in the workplace? What about creating learning for those situations where your SME can’t tell you what good performance looks like except to say, “Well, you know it when you see it”?
In situations like these, frameworks from complexity science and the science of expertise development can help you diagnose complex learning problems, and they also help point to eLearning design strategies that can actually address and support complex skill development. In this session, you’ll discuss how variables like frequency of use, tacitness or explicitness, and level of automaticity affect skill development. You’ll find out how to use these variables and models to craft effective eLearning design and assessment strategies for complex learning.
In this session, you will learn:
- How to diagnose a complex skill problem
- How to use complexity models such as the Cynefin framework for learning
- How to use alternative assessment and feedback strategies for complex learning environments
- How to use learner self-assessment as a tool for complex learning
Audience:
Intermediate to advanced designers and managers. Some instructional
design experience is recommended.
Technology
discussed in this session:
eLearning-specific examples, the Cynefin
complexity model, and Ericsson’s skill development research.
Handouts
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