Topological properties of inequality and deprivation in an educational system: Unveiling the key-drivers through complex network analysis - Sánchez-Restrepo, H.; Louçã, J. (Human systems engineering and design II. Advances in Intelligent Systems and Computing, 2019)
This research conceives an educational system as a complex network to incorporate a rich framework for analyzing topological and statistical proper-ties of inequality and learning deprivation at different levels, as well as to simu-late 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 oppor-tunity 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 con-cerns about the limitations of case studies or isolated statistical approaches.