AIED

The SEWS Framework: Bridging the Prediction-to-Action Gap in Educational Early Warning Systems

Mon Jun 29, 4:10 PM–4:35 PM · R1 (Auditorium Meeting 1)

Part of AI Inside Schools, Classrooms; Curricula

Predictive Modeling & Early Warning K-12 Education Classroom Orchestration

★ Notable speakers

Seiji Isotani ★★ — Intelligent tutoring systems, gamification, AIED for under-resourced contexts (AIED Unplugged), education policy

Thales Vieira ★ — Intelligent tutoring systems for underserved regions; MathAIde ITS; AI/computer vision in education

Ig Ibert Bittencourt ★ — Gamification of intelligent tutoring, AI in education for underserved populations in Latin America, ethics of AI in education

Cristian Cechinel ★ — Learning analytics; educational data mining; student dropout prediction; LMS data analysis in Latin America

A framework bridging the gap between early-warning-system predictions and the actions schools actually take to support at-risk students.

Authors

Emanuel Marques Queiroga, Fernanda Arantes, Marcelo Pessoa, Daniel Santana, Ricardo Madeira, Samara Fonteles Cunha, André Bezerra Oliveira, Felipe Roque, Leogildo Freires, Martim Ancona de Aguiar, Thales Vieira, Ig Ibert Bittencourt, Seiji Isotani, Cristian Cechinel