Learning Analytics and Student Success

March 28, 2018

 

What are learning analytics? How do you use them? And how do you evaluate which features you’ll need to help your students succeed?

 

If you teach, you should be able to make sense of learning analytics. And decide what’s useful to you. You just need to ask the right questions.

 

To understand analytics, let’s start with the simple report—useful summary information that can save you time. For example, a Learning Management System might have an easy-to-read chart showing which students participate in online class discussions. This visualization allows you to identify the students who may be distracted, or afraid to participate. You might be able to figure this out without the software, but the report saves you time and reduces the chances that you’ll miss something.

 

Analytics combine several reports to give you a more sophisticated picture of what’s going on. For example, they might take into account students’ academic history. An honors student who’s quiet during class discussions may need a different kind of response than a student who’s on academic probation. In this case, analytics offer richer information about the individual students, providing insights that help you understand what kind of help each student may need.

 

Analytics can also help the students directly. For example, a student who’s distracted at home or at work may not have noticed that she hasn’t done well on a particular online homework question. An automated reminder from the analytics system may be all she needs to get back on track.

 

To judge whether a particular analytics feature is useful to you, there are three questions to ask:

 

One— what information is being used? Sometimes details that the analytics take into account are not relevant to you. For example, if student participation in online discussions isn’t important in your class, then analytics that weigh participation in online discussions are not going to be helpful.

 

Two— how is the information being gathered? For example, the analytics may be based on grades entered in your online grade book. But if you don’t use an online grade book, or don’t keep it up to date, then analytics based on that information are irrelevant.

 

And three— how are the various sources of information being combined? This is trickier because the software may be combining the information in complex ways. But the product developers should be able to give you enough of an idea how the information is combined for you to decide if the combination makes sense. For example, if the system is designed to warn you when a student is in trouble, then you’ll want to understand how the software is making this evaluation and judge for yourself whether it’s a sensible approach.

 

Analytics are designed to save you time by sorting through lots of information and combining it in ways that help you understand what’s going on with your students. As an educator, you are in a good position to understand how these tools work and assess whether they’ll be helpful. Before you adopt learning analytics, always ask those three questions and insist on getting answers that make sense. (see more blogs about education technology)

 

More education and edtech videos can be found here.

 

Please reload