"All models are wrong but some are useful" - generally credited to George Box. A model, by definition, is a simplification, otherwise it wouldn't be a model (i

"All models are wrong but some are useful" - generally credited to George Box. A model, by definition, is a simplification, otherwise it wouldn't be a model (it would be the actual "thing"). Therefore, you shouldn't get caught up on whether or not the model is a perfect representation of the thing it describes (because it won't ever be), but rather if it is useful in the situation in which it is being applied. For example, sometimes it is useful to model light as waves, sometimes it is useful to model it as particles, but both models are technically wrong because they can't explain the full behavior of light by themselves. That doesn't mean we should just give up those models and never use them, since they both are useful in certain situations. So present the simplified model to the student, until that simplified model no longer can explain what you are trying to explain. In which case you present the more refined model. Just keep in mind there is overhead that comes along with that refined model. And perhaps more importantly: don't think in terms of "truthfulness", think in terms of "usefulness".