Many educational institutions are using predictive models to leverage actionable insights using student data and drive student success. A common task has been predicting students at risk of dropping out for the necessary interventions to be made. However, issues of discrimination by these predictive models based on protected attributes of students…

Although apprenticeships ease the school-to-work transition for youth, many apprentices seriously consider dropping out. While associated with noncompletions, dropout considerations are important to study in their own right, because they reflect a negative quality of apprenticeship experience and can impact apprentices' quality of learning and…

We perform two approaches of machine learning, logistic regressions and decision trees, to predict student dropout at the Karlsruhe Institute of Technology (KIT). The models are computed on the basis of examination data, i.e. data available at all universities without the need of specific collection. Therefore, we propose a methodical approach…

Currently in Kenya, secondary school government bursaries are administered through committees set up at the level of parliamentary constituencies. However, there is widespread consensus that this system is not functioning adequately, as the process is often haphazard and funds are often spread too thinly across students. The Ministry of Education…