My Master's thesis, in a sentence, was this: the model is not the reality, and therefore, the properties of the model (rules, syntax, representation) should not be assumed to exist in reality. It was informed by people like Quine, Lauden and Feyerabend who talked about things like theory-laden data and the vageries of scientific method. Fast forward three and a half decades and the problem is still with us. This article links the two by means of representation theory, where you use a 'key' to 'translate' from the model to the reality. But as the article notes, the model is an abstraction. There is no 1:1 key; "there are aspects of the target system that it makes no claims to represent." Models are also idealizations: "they distort aspects of the target system that they represent." So, as the authors argue, we should avoid "the sheen of precision" models appear to offer. Prediction only takes us so far, which is why we should think of education as rather more than a predictive science.
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