2020 Learning Impact Leadership Institute

Thanks in part to data interoperability standards, data lakes for teaching and learning data are now mature and rich enough to practically support a range of student success stakeholders in the fields of learning analytics, advising, educational data mining, and in-course analytics. In this session, we share lessons from building a workbench of analytics tools and data services to serve the University across the enterprise. We will share our approaches to catalyzing the use of data across the University; an evaluation of what has worked and what has not; and, finally, a report on how we intend to build on successes for the future. We hope this session provides practical information regarding how to effectively use teaching and learning data at scale.