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arXiv · 2106.06805

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

Rendani Mbuvha·Patience Zondo·Aluwani Mauda·Tshilidzi Marwala
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Abstract

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.

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Rendani Mbuvha, Patience Zondo, Aluwani Mauda, Tshilidzi Marwala. 2021-06-12. Predicting Higher Education Throughput in South Africa Using a Tree-Based Ensemble Technique. https://arxiv.org/abs/2106.06805

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