Predictive Learning Analytics for Student Success

Data gleaned from academic technologies, student information systems, and other learning systems can act as "power sources" to fuel predictive analytics efforts. These analytics can enable institutions to see individual variables and more complex trends that are early predictors of student success and support the creation of meaningful interventions that lead to long-term improvements. In this session, members of the ECAR/ELI ANALYTICS Working Group will discuss real-world applications of predictive analytics, the ranges of learning data being used, and strategic issues that can help institutions better leverage data for improved student success.

OUTCOMES: Understand how predictive learning analytics has changed the landscape of education * Learn how predictive learning analytics can be used to positively affect student outcomes * Identify practical steps and challenges to implementing predictive learning analytics