Enhancing the Early Student Dropout Prediction Model Through Clustering Analysis of Students’ Digital Traces

Educational Data Mining and learning analytics have gained significant prominence in recent years, garnering attention from researchers worldwide. This is primarily due to their potential to improve decision-making processes within higher education. This study utilizes Educational Data Mining to sug...

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Detalles Bibliográficos

Principais autores:	Janka Pecuchova, Martin Drlik
Formato:	Artigo
Idioma:	Inglês
Publicado:	IEEE 2024-01-01
Series:	IEEE Access
Assuntos:	Educational data mining learning analytics clustering analysis dropout prediction
Acceso en liña:	https://ieeexplore.ieee.org/document/10736593/
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