Speakers:
Sponsored Session: Use Case: Carl Remigius Fresenius Education AG – Machine-Learning-driven Analysis to avoid student churn
Date:
Wednesday, November 15, 2023
Time:
9:50 am
Room:
Saphir 1
Summary:
Insights into our data science solution based on KNIME: On average, more than one in four students leaves higher education without a degree. This not only has economic consequences for the education companies, but is also a waste of resources and time for those beeing affected. The goal should therefore be to focus as an educational institution on retaining students, moreover making the study and learning environment as attractive as possible. Here, machine learning can provide significant churn factors and predictions in order to gain awareness and help educational institutions to implement more targeted approaches to support student retention and reduce churn.