Berkeley Hosts a Learning Analytics Summit

July 8, 2016

Earlier this year, UC Berkeley hosted the first cross-UC “Learning Analytics” summit. This two-day event brought together leadership, teaching pedagogy experts, learning technology experts, and more to discuss the emerging teaching concept of learning analytics and what it means to UC schools.

“Learning analytics is the measurement, collection, analysis and reporting of data about learners and their contexts, for purposes of understanding and optimising learning and the environments in which it occurs.”*

The January event, held at Clark Kerr Conference Center focused on the ways data could be used for predictive analysis of student progress to best help students succeed by providing instructors real-time feedback on student performance to assist instructors and advisors in teaching, learning, and advising. ETS assisted the Vice Chancellor for Undergraduate Education, Catherine Koshland, in coordinating the event, and hosting a panel discussion on day two.

The application of learning analytics data provides institutions a data-driven insight into students trends like performance by cohort. Sharing information empowers students to make changes to their behavior to positively affect their learning, enables faculty to assist individual students as well as see trends in their courses and pedagogy, and give advisors additional tools to help students towards academic success.

ETS and campus have begun to apply the lessons of the day towards a new pilot with the Athletic Study Center on the practical application of information towards student academic success as well as examining ways services like bCourses can be utilized to provide students, instructors and advisors timely info on student progress.   

*1st International Conference of Learning Analytics & Knowledge, Banff, Alberta 2011

Learning Records Store graphic

A Learning Record Store is a key component to surfacing Learning Analytics. Systems such as bCourses (Canvas) and CalCentral feed information into a Learning Record Store, a data and information storage and management system. That information is combined with inputs from predictive analysis tools, departments/academic units, and campus thresholds to provide analytics that help identify campuswide and individual-level information. These analytics can be used to better understanding learning outcomes and performance measurements for individual students, cohorts, or campus-wide.