The impact of pupil and school characteristics

TG Data Set: A collection for training AI models.
Post Reply
asimj1
Posts: 417
Joined: Tue Jan 07, 2025 4:36 am

The impact of pupil and school characteristics

Post by asimj1 »

Below, we summarise mobility overall, and separately for LA schools and academies.

Overall, inward mobility was slightly higher than outward mobility, meaning that there were slightly more joiners than leavers over the time period.

Outward mobility was roughly the same in LA schools and academies, while inward mobility was a little higher in LA schools than academies.

We can break the data down further by cambodia rcs data comparing academies which were part of big multi-academy trusts (MATs) with those which weren’t (a combination of single academies and academies which are part of smaller trusts). We define a big MAT as one with at least ten mainstream secondary schools.
Academies which were part of big MATs had higher rates of both inward and outward mobility compared to other types of academies and to LA schools.

That schools in big MATs have higher rates of mobility, particularly outward mobility, than other types of school might raise an eyebrow or two. However, so far, we haven’t looked at whether and how pupil characteristics varied across the different school types. Perhaps schools in large MATs had a greater proportion of disadvantaged pupils, for example.

To unpick this, we first assign each pupil in an academy a “predicted” probability of leaving, based on the observed proportion of pupils with the same characteristics[2] who left LA schools. We then compare the actual, observed outward mobility of pupils in academies (and the subset of big MATs) with these predictions. Here, we limit our analysis to mainstream schools only.
Post Reply