Introduction
We worked to build a simple, practical way to spot young people who might become NEET after year 11. (NEET is short for not in education, employment or training). The aim is to help schools, colleges and the council act earlier, so more students make a smooth move into post 16 options. It is a preventative approach. It supports statutory duties while focusing support where it will make the biggest difference.
How the research was done
We used suitably anonymised council data for pupils. From this we brought key information together into a single risk picture for each student. The model looks at:
attendance
exclusions
care experience
special educational needs and disabilities (SEND)
and education, health and care plans (EHCP)
plus other context schools and the council already hold. The tool applies weights to these and produces one overall score that signals relative risk. This makes it easier for teams to prioritise help without revealing sensitive details.
While shaping the tool, we tried different ways of combining factors and setting sensible cut offs. The goal was to keep the number of pupils flagged as likely to need support to a level staff can actually work with. The indicator is a decision aid, not a verdict. It should sit alongside professional judgement from education, social care and careers colleagues.
Results
Three signals come through strongly:
very low attendance
frequent fixed term exclusions
and being looked after by the local authority.
These matter, but if we push them too hard in the scoring, they can drown out other needs. By contrast, some poverty related measures schools already track add limited value here. They are given less weight in this core model.
On that basis, we recommended also looking at a second version of the RONI that reduces how much attendance drives the score. This gives a broader view of risk instead of concentrating only on persistent absentees. It keeps SEND and EHCP in the mix so learners with additional needs aren’t missed. Running this model with the main tool will help Cornwall see how different factors contribute in practice. We can also fine‑tune the framework over time.
To understand impact, we’ll monitor how well the indicator finds pupils who would otherwise become NEET. We will check that flagged groups are treated fairly across characteristics. And we will track whether targeted support improves:
attendance
behaviour
attainment
and progression into suitable post 16 routes.
Overall, this modelling offers a clear, locally grounded way to identify risk early and support young people. It also keeps professional judgement at the centre of every case.