So… I wonder what some good examples of those abstractions are, and what it means when you test them? Is defining a quadrilateral with 4 congruent sides as a special type of quadrilateral an abstraction? Clearly testing that abstraction wouldn’t just be looking up the definition of rhombus in the back of the book… What makes that definition robust, useful, etc.?

We are no longer just talking about which are the extraneous details that can be dropped in describing the attributes of a given situation. i.e “Which are the efficient abstractions?”

we are now talking about making a prediction about the *behavior* of a system. Instead of a building a full- or reduced-scale model, we replace parts of the system with equations (an abstraction, yes), that describe the behavior of specific components. If we get this right, our model has predictive ability; a necessary feature for a model to be valid.

Models-with-predictive-ability is such a powerful concept, some of them acquire the status of a theory in physics. (e.g. The Standard Model)

This aspect, the predictive ability of models, is sufficiently key, that I feel our students ought to become familiar with that term – model – used in appropriate context.

So I vote for “Test your model”