Prediction and Explainability of School Dropout in Peru Using Machine Learning and Explainable Artificial Intelligence

School dropout represents a critical challenge for educational systems in developing countries. This study proposes an integral framework that combines machine learning techniques and explainable artificial intelligence to predict and explain school dropout in the Peruvian context. The proposal inco...

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Hlavní autoři:	Andree Barboza, Jhonatan Huamani, Jose Santisteban, Nelson Maculan, David Mauricio
Médium:	Artigo
Jazyk:	Inglês
Vydáno:	IEEE 2026-01-01
Edice:	IEEE Access
Témata:	School dropout machine learning explainable artificial intelligence SHAP educational predictors dropout prediction
On-line přístup:	https://ieeexplore.ieee.org/document/11443270/
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