Topological Properties of Inequality and Deprivation in an Educational System: Unveiling the Key-Drivers Through Complex Network Analysis

This research conceives an educational system as a complex network to incorporate a rich framework for analyzing topological and statistical properties of inequality and learning deprivation at different levels, as well as to simulate the structure, stability and fragility of the educational system. The model provides a natural way to represent educational phenomena, allowing to test public policies by computation before being implemented, bringing the opportunity of calibrating control parameters for assessing order parameters over time in multiple territorial scales. This approach provides a set of unique advantages over classical analysis tools because it allows the use of large-scale assessments and other evidences for combining the richness of qualitative analysis with quantitative inferences for measuring inequality gaps. An additional advantage, as shown in our results using real data from a Latin American country, is to provide a solution to concerns about the limitations of case studies or isolated statistical approaches.