Learning Analytics: The Future is Now

GUEST COLUMN | By Deb Everhart

Everyone is talking about analytics applied to education and how “big data” can (will?) transform many aspects of our educational institutions. And for those of us passionate about improving opportunities for learning, the phrase “learning analytics” is particularly intriguing.

So what do we mean by “learning analytics”? In short, it’s “the use of data and models to predict student progress and performance, and the ability to act on that information,” as defined in the Next Generation Learning Challenges (see the useful EDUCAUSE Learning Initiative brief). Learning analytics overlaps with the somewhat broader phrase “academic analytics,” which encompasses other institutional bodies of data such as enrollments, graduation rates, and institutional outcomes tracking. A combination of learning analytics and academic analytics can provide an environment where administrators, advisors, faculty, and the students themselves have the data visualization tools they need for learner success.

Learning Analytics for Students

What happens when students can see their own course participation and grade data, and anonymously compare results to others in the same course? This type of exposure to learning analytics can be a powerful motivator. Students become more aware of their activities and time on task in their courses. And having access to analytics while the course is in progress, students are able to change their behavior mid-course for better end results. While the technology is not comprehensive because some courses have more online activities than others, the balance between online and offline activities can be understood by the student despite the lack of data on the offline activities, once the student has crossed that important threshold of self-awareness.

Based on this increased understanding of the value of specific behaviors, students can make better informed decisions about how to use their limited time and whether or not to change their behaviors. More detailed data can help students make more granular decisions, such as whether to spend more time reading and contributing to discussion forums or more time reviewing lectures to prepare for a test, based in part on comparisons to what other students are doing—which of course is varying in real time.

Learning Analytics for Faculty and Administrators  

Now, imagine the power of analytics in the hands of academic leaders. Instructors could instantaneously address gaps and challenges, and make necessary changes in course delivery. If the course content isn’t resonating with the collective whole of the class, the instructor may rework the assignments and materials in the LMS to ensure students are actively engaging, finding value and grasping overall course concepts. With on-demand access to data, instructors are also able to identify at-risk students early in the course and to provide one-on-one support to help ensure course completion and student retention.

It’s also important to consider what learning analytics can reveal over time. Department heads may better understand the needs of students and how that changes year-to-year to guide their overall programs. They may also discover best practices in online course delivery and design – models that see the most student engagement and lead to improved learning outcomes. Administrators may also understand the overall impact of online and blended learning to justify investments and expenditures.

This is learning analytics in action.

Here is just a sampling of critical questions that can be addressed in part using learning analytics:

  • How does student activity in the LMS correlate to student success?
  • How can we identify and promote effective teaching practices?
  • How can we support student retention and degree completion?
  • Can we predict when, where, and why learners hit challenges in their learning progress so that we can provide the right support at the right time?

There are extensive opportunities in this arena using solutions that are already available. For example, Blackboard Analytics for Learn helps institutions begin the path of data exploration and fosters the ability to make better informed decisions.

As Mark Milliron has put it, let’s “put our technology on purpose” and apply learning analytics to helping students succeed in very real ways, today.


Deborah Everhart is Chief Architect at Blackboard Learn, where she provides leadership in product strategy and development. Her responsibilities include researching, analyzing, and designing Blackboard solutions. She is a Director in Blackboard’s Exemplary Course Program and teaches as an adjunct at Georgetown University.


Leave a Reply