Why create additional KC models and import them to DataShop?
A primary reason for creating a new KC model is that an existing model is insufficient in some way—it may model some knowledge components too coarsely, producing learning curves that spike or dip, or it may be too fine-grained (too many knowledge components), producing curves that end after one or two opportunities. Or perhaps the model fails to model the domain sufficiently or with the right terminology. In any case, you may find value in creating a new KC model. By importing the resulting KC model that you created back into DataShop, you can use DataShop tools to assess your new model. Most reports in DataShop support analysis by knowledge component model, while some currently support comparing values from two KC models simultaneously—see the predicted values on the error rate Learning Curve, for example. We plan to create new features in DataShop that support more direct knowledge component model comparison.
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