School Performance Gaps in Italian Regions: Estimating the Impact of Individual, School, and Territorial Factors. INVALSI 2021/22 Data Analysis

The introduction of the INVALSI standardized assessment system in Italy has revealed significant variations in upper secondary school students learning achievements across different regions. Several factors may play a role in these inequalities, and there is a theoretical debate about their different way to affect performance. The aim of the study is to investigate the territorial differentiations on student’s reading performance in Italy, by analysing the impact of three families of factors - individual, school, and territorial - that act and interact at different levels. From a methodological perspective, the study uses an adapted version of the ‘Coleman boat’ model, originally introduced by James Coleman (1990:702). The model is specifically designed to describe the macro-micro-macro transition in the Italian educational context considered. The analyses use a specially created dataset: information on the characteristics of students and schools comes from the INVALSI 2021/22 dataset; whereas regional socio-economic information comes from the Noi.Italia (i.Stat). Because of the hierarchical structure of the dataset, the multilevel regression model technique is used besides the multiple linear regression model. This technique helps to analyse the link between the individual and contextual factors and how they affect student performance at different level, either directly or indirectly. It is hypothesized that contextual territorial factors have an impact along with individual and school variables. The results confirm the relevance of considering multiple factors at different levels when analysing the gap in reading performance among Italian students. At the micro level, differences between geographical areas primarily stem from factors such as family socio-economic background and school track preferences. School composition's importance becomes clear when advancing to a higher level in the analysis models. However, these factors alone do not fully clarify these inequalities. Analysis of third-level factors reveals the significant role played by the characteristics of the territorial context. Results stemming from these analyses are part of a broader research project on students’ expectations and life trajectories.