Learning @ Scale

eeLocation: Salon 3
This is an expertise exchange in the Cyberlearning 2017 Expertise Exchange session

Amy Ogan, Carnegie Mellon University
Stephanie Teasley, University of Michigan
Timothy O’Shea, University of Edinburgh

This expertise exchange will provide participants with a foundation for understanding what research on Learning @ Scale is all about and provide information about the communities that are focused on this research. A brief overview of Learning Analytics and Educational Data Mining will be presented (expanding and updating the primer available on the CIRLC website) along with an exploration of the special issues that arise from scaling up data on student learning. Covered topics will include achieving diversity and equity for learners, and innovative delivery models for online learning such as real time MOOCs. This will be followed by discussions in which participants will reflect how access and use of large scale data on learning can inform theory and practice, and how they can incorporate L@S in their own work.

This session is for everyone who is curious about L@S and wondering how/if their Cyberlearning research could be advanced through the use of large scale learning analytics data.