To guarantee the human right to education established by the fourth UNESCO’s Sustainable Development Goal, a deep understanding of a big set of non-linear relationships at different scales is need it, as well as to know how they impact on learning outcomes. In doing so, current methods do not provide enough evidence about interactions and, for this reason, some researchers have proposed to model education as a complex system for considering all interactions at individual level, as well as using computer simulation and network analysis to provide a comprehensive look at the educational processes, as well as to predict the outcomes of different public policies. The highlight of this paper is modeling the structure of the inequality of a national educational system as a complex network from learning outcomes and socio-economic, ethnicity, rurality and type of school funding, for providing a better understanding and measuring of the educational gaps. This new approach might help to integrate insights improving the theoretical framework, as well as to provide valuable information about non-trivial relationships between educational and non-educational variables in order to help policymakers to implement effective solutions for the educational challenge of ensuring inclusive and equitable education.

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Structural network,Large-scale assessments,Policy informatics

• Ciências da Computação e da Informação - Ciências Naturais
• Ciências da Educação - Ciências Sociais