Social capital at school: a tool to measure students’ endowments

Authors

DOI:

https://doi.org/10.71014/sieds.v80i3.552

Keywords:

social capital, assessment at primary school, social preferences, economic games

Abstract

This study presents an innovative methodology for measuring social capital among students to detect variations in its distribution across different territorial contexts. The proposed model is based on a multidimensional perspective of social capital, encompassing structural, relational, and cognitive dimensions, and utilizes three tools: a questionnaire, sociometric mapping, and age-appropriate economic games. The work provides a solid methodological framework that is helpful in exploring how social networks, trust relationships, and prosocial preferences develop and differ in relation to the living environment and school. The study aims to contribute to the understanding of social capital as a relational and value-based resource that promotes social cohesion, educational inclusion, and civic participation within school and territorial contexts.

Author Biography

Stefania Badiglio, Institute for Studies on the Mediterranean, National Research Council of Italy

Stefania Badiglio earned her Master’s Degree in Economics and Business Administration from the University of Palermo. In 2024, she completed her Ph.D. in Applied Economics at LUMSA University in Palermo.

Since 2016, she has been a lecturer at LUMSA University in Palermo, where she teaches Mathematical Methods for Economics, Financial Mathematics, and Microeconomics. Since 2022, she has also been teaching the Basic Mathematics Skills course at the Faculty of Psychology at the University of Palermo.

Her research activities focus on applied, experimental, and behavioral economics. She has developed expertise in managing experimental interventions in the field of Behavioral Economics, designing experimental protocols to measure social capital through economic games applied to the school context, and analyzing the impact of Artificial Intelligence on specific cognitive biases. Additionally, she has experience in survey design as well as in data processing and statistical analysis, using R and STATA software.

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2026-02-26

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