Schools at risk: mapping learning poverty in Italian schools

Abstract Early identification of schools with a high percentage of students at risk of learning poverty is crucial for effective and targeted interventions. This study investigates the use of an innovative combination of large-scale administrative datasets and advanced statistical techniques to predict schools at risk of learning poverty in Italy in the 2018–2019 academic year. The aim is to identify school-level factors associated with learning poverty, with a specific focus on socioeconomicall