AIED
Territorial Fairness in Large-Scale Academic Risk Prediction: Comparing National and State-Level Machine Learning Models in Brazil
Mon Jun 29, 4:10 PM–4:35 PM · North 201
Part of Interoperability of AIED Systems
Predictive Modeling & Early Warning Equity, Fairness & Inclusion Educational Data Mining Methods Higher Education
★ Notable speakers
Diego Dermeval
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— Gamification in intelligent tutoring systems; teacher co-design of AIED tools; AIED policy in Brazil
Cristian Cechinel
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— Learning analytics; educational data mining; student dropout prediction; LMS data analysis in Latin America
Thales Vieira
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— Intelligent tutoring systems for underserved regions; MathAIde ITS; AI/computer vision in education
Compares national and state-level ML models for academic risk prediction in Brazil, examining territorial fairness across geographic scales.
Authors
Tobias Vieira Francisco, Abílio Nogueira Barros, Felipe Vieira Roque, Tiago Paulino, Augusto Schmidt, Flavia Galvani, Rafael Oliveira, Leonardo Brandão Marques, Diego Dermeval, Pedro Barreto, Anita Gea Martinez Stefani, Marisa de Santana da Costa, Emanuel Marques Queiroga, Elthon Oliveira, Cristian Cechinel, Thales Vieira