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Predicting Higher Education Throughput in South Africa Using a Tree-Based Ensemble Technique

Domaine:

educationsocioeconomic

Type de record:

paper
Créateur:
Mbuvha, RendaniZonMauMar
Éditeur:
arXiv
Hôte:avatar
We use gradient boosting machines and logistic regression to predict academic throughput at a South African university. The results highlight the significant influence of socio-economic factors and field of study as predictors of throughput. We further find that socio-economic factors become less of a predictor relative to the field of study as the time to completion increases. We provide recommendations on interventions to counteract the identified effects, which include academic, psychosocial and financial support.

Visit

doi.orgarxiv.org

Tags

Applications (stat.AP)Machine Learning (cs.LG)FOS: Computer and information sciencesFOS: Computer and information sciences

Licenses

Creative Commons Attribution 4.0 Internationalhttps://creativecommons.org/licenses/by/4.0/legalcode

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