Abstract
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.
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Acknowledgments
We would like to thank ISCTE’s Programme in Complexity Sciences, the University of Lisbon and the Latin American Agency for Evaluation and Public Policy, for their support to the project as well as the authors of the articles mentioned in the references.
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Sánchez-Restrepo, H., Louçã, J. (2020). Topological Properties of Inequality and Deprivation in an Educational System: Unveiling the Key-Drivers Through Complex Network Analysis. In: Ahram, T., Karwowski, W., Pickl, S., Taiar, R. (eds) Human Systems Engineering and Design II. IHSED 2019. Advances in Intelligent Systems and Computing, vol 1026. Springer, Cham. https://doi.org/10.1007/978-3-030-27928-8_71
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DOI: https://doi.org/10.1007/978-3-030-27928-8_71
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