Abstract
Education systems are webs of interconnected students, teachers, programs, institutions, and decisions. This chapter argues that a network-based view of education can improve learning, social integration, well-being, and decision making by using institutional records, experiments, and computational social science methods to map relational structures across scales.
Publication
In Handbook of Computational Social Science

Associate Professor, Data Science Institute, School of Engineering, Universidad del Desarrollo, Chile. Director of CRiSS-LAB.
Cristian Candia is a computational social scientist studying human and collective behavior with large-scale data, network science, experiments, and AI.

Physics Department, Universidad del Bío Bío

NOVA IMS, Universidade Nova de Lisboa