Should I have "normal" sampled data in my dataset?
In short, yes.

If your goal is to understand the drivers behind poor school performance (or even model + predict school performance), you will need both "positive" and "negative" outcomes in your dataset.

Of course, you need to be careful that the positive outcomes are "similar" enough to the negative outcomes to avoid introducing distortions into your data - i.e. ensure that the data you are adding are from middle-class families with access to facilities etc.

You should also consider the ratio of positive:negative outcomes in your final data set, as you will ideally like to avoid imbalanced data. However, there are techniques and approaches to handle imbalanced data if necessary.