Science proceeds by developing models to approximate reality and then testing the predictions of these models through observation or experiment.
Science does not deny the existence of an underlying reality and yet it does not claim to know or describe it. All it claims is the predictive and explanatory power of its various models.
While I have only recently come to explicitly draw this distinction, this is something I think I have implicitly known for a long time due to my physics training. In physics, we are constantly confronted by the incompleteness of our models. The best example of this is wave-particle duality where we have two conflicting models that both accurately predict different aspects of the behaviour of fundamental particles; the model of a wave and the model of a particle. These two models can be reconciled in a mathematical framework that is impossible to put into words by drawing on analogies from the everyday world.
Why is this important? Because there is a tendency for people to dismiss models in cognitive science by pointing out that they are incomplete or that they do not describe every aspect of the working of the mind. This is a misunderstanding.
For instance, in ‘Why don’t students like school’, Dan Willingham posits a simple model of the mind in order to help explain some constraints on learning. This model consists of the environment, the working memory and the long term memory. Some have criticised it on the basis that it is an oversimplification; that the working memory has sub-components – such as the phonological loop – and that the model excludes elements such as the sensory buffers. It may be an oversimplication, but it order to demonstrate this we would need to see how the addition of these elements would change the predictions Willingham makes on the basis of this model. If they don’t change these predictions then they are irrelevant to Willingham’s argument. If they do change these predictions to ones that are less aligned with experiment and observation then we should definitely leave them out. The only case where we should include them is if they change the predictions of the model in a way that is relevant to Willingham’s argument and that represents a superior description of reality. Otherwise, there is value in keeping it simple.
After all, it’s models all the way down.