and developing continuous predictive models that can be used in real time to identify students at risk of dropingout out of MOOCs. The current thesis explores a light weight approach based on as little data as possible since different MOOCs store different data on their users and thus strive to create a truly generalisable method. This goal was successfully achieved using different approaches such as statistical data analysis
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