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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Bibliografiska uppgifter

Huvudupphov:	Janka Pecuchova, Martin Drlik
Materialtyp:	Artigo
Språk:	Inglês
Utgiven:	IEEE 2024-01-01
Serie:	IEEE Access
Ämnen:	Educational data mining learning analytics clustering analysis dropout prediction
Länkar:	https://ieeexplore.ieee.org/document/10736593/
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