Using data to reduce dropout

Using data to reduce dropout

Follow the ABC’s of good indicators  The types of learner information that are measured and tracked are called ‘indicators’. If accurately collected and monitored, these could help schools to identify who is disengaging at school and therefore at risk of dropout:  Academic Results, Behaviour Problems and Chronic Absenteeism.Our education system would benefit hugely from collecting accurate, detailed and regular information about schools and learners. Collecting the right types of information (data) over time can help us to better understand the needs in our education system, design better policy and programming, and track our progress.

South Africa simply does not have the right types of records (datasets) to measure and monitor school dropout properly. While there are several datasets tracking matric exam results, annual school surveys, and master school lists, this information is only at the ‘aggregate’ (collective) level, not at the level of individual learners. Learner-level information could help us flag which young people are most at risk of dropping out. However, the way in which dropout information is currently recorded in the South African Schools Administration and Management System (SA-SAMS)
is not well designed for this.

Resources

The value of tracking absenteeism

One of the most important changes we can make in our collective effort to reduce school dropout is to start keeping better records about our learners. By tracking individual learners’ absenteeism, academic performance and behaviour, we can better understand their struggles and pathways through school. This will allow us to identify learners at risk of […]

Posted on 1 December 2020

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VIDEO: Using data to reduce dropout

South Africa simply does not have the right types of records (datasets) to measure and monitor school dropout properly. While there are several datasets tracking matric exam results, annual school surveys, and master school lists, this information is only at the ‘aggregate’ level, not at the level of individual learners. Learner-level information could help us […]

Posted on 6 October 2020

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Spotlight on Data-driven approaches

This is a case study of the use of Early Warning Systems (EWS) for the prevention of school dropout. The Zero Dropout Campaign has been providing strategic and M&E support to four organisations focused on reducing dropout. This report was compiled by the New Leaders Foundation.

Posted on 9 June 2020

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