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Leveraging Your Learning Management System

December 11, 2017

For nearly a decade, researchers and technologists have been building algorithms designed to help practitioners identify and support those students who are least likely to persist and graduate. As more data has become available, these risk algorithms have become more sophisticated and diverse.In EAB’s work with the 200+ members of the Student Success Collaborative, we’ve found that risk algorithms almost always involve a trade-off between timeliness, breadth of applicability, and feasibility. Algorithms that are built on core student records (such as coursework and grades) apply to a broad number of students and are relatively inexpensive to maintain, but can only be updated a handful of times a year as more transcript data becomes available.

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Leveraging Your Learning Management System