Using Student Analytics for Online Course Improvement

Many instructors feel that they need to be experts in mathematics in order to understand analytics. But according to John Vivolo, director of online and virtual learning for New York University, every faculty member can learn to use the course analytics available through their LMS to improve student learning.
Vivolo’s aim is to help faculty “use analytics to proactively reach out to students.” Vivolo talks about what he calls “pocket data analytics.” These are small, easy-to-use pieces of data that are readily available to instructors through their LMS.
Pocket data analytics are a way to leverage the data that is collected, often automatically, by looking at smaller bits of data that show discrete happenings and student behaviors in a class. This allows instructors, deans, and instructional designers to move beyond simple surveys and student grades as metrics into more information that is easily understood and responded to.
In a paper for the International Conference on Analytics Driven Solutions in 2014, Vivolo explains the concept this way: “Rather than looking at large scale data, the purpose of this method is to get instructors to focus on smaller patterns within a single course, during a specific time period, such as a week. The intent is to have a method in which to introduce the concept of academic course analytics as a practical tool….”
Vivolo highlights three types of student analytics that are readily-available and easily-used:
Time-based measurement
Time-based measures are probably the type of …