When we produce an assessment, we need to know that it is measuring what it is intended to measure. We need to make sure that the results tell us something meaningful, so that any decisions based on those results are well-informed. This, broadly speaking, is the concept of assessment ‘validity’.
There are various different ways that people think about validity – colleagues have written about some of them on our blog 'In pursuit of reliability and validity'.
One way is to consider ‘predictive validity’. In practice, this means whether a test’s results can be used to predict outcomes in a related – but independent – measure.
For example, we might expect that students who scored higher on a mathematics baseline test at the start of the year should achieve higher grades at the end of the year. If this happened, we could conclude that the baseline test had good predictive validity. If, on the other hand, there was no relationship, we might question whether the baseline test really was measuring what we intended it to.
