Predicting pupil absence rates in Newcastle upon Tyne using machine learning

Context:

Newcastle City Council faces one of the highest pupil absence rates in England, posing risks to children’s education, wellbeing and long‑term outcomes.  

Action:

Dr Wasim Iqbal led a project using machine learning to analyse historical school data, forecast future absence rates and identify key reasons for pupil absences. This work was carried out in partnership with the Children and Families Directorate.

Result:

The models show strong potential to support data‑driven interventions and decision‑making across the council. The research has been recognised externally, with an abstract accepted for publication in the BMJ Journal of Epidemiology and Community Health.