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Citation Information

Type Thesis or Dissertation - Masters Thesis
Title Investigating similarities and differences between South African and Sierra Leonean school outcomes using Machine Learning
Author(s)
Publication (Day/Month/Year) 2020
URL https://arxiv.org/abs/2004.11369
Abstract
Available or adequate information to inform decision making for resource allocation in support of school improvement is a critical issue globally. In this paper, we apply machine learning and education data mining techniques on education big data to identify determinants of high schools’ performance in two African countries: South Africa and Sierra Leone. The research objective is to build predictors for school performance and extract the importance of different community and school-level features. We deploy interpretable metrics from machine learning approaches such as SHAP values on tree models and odds ratios of LR to extract interactions of factors that can support policy decision making. Determinants of performance vary in these t

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Sengeh, David, Vukosi Marivate, and Henry Wandera. "Investigating similarities and differences between South African and Sierra Leonean school outcomes using Machine Learning." Masters Thesis, University of Pretoria, 2020.
Copyright DataFirst, University of Cape Town