eLearning analytics is like a crystal ball. It allows you to see what has happened, what is happening, and predict what will happen. It measures the success, usefulness, and popularity of specific eLearning courses. If one e-course has a poor passing rate, eLearning analytics can pinpoint issues. Maybe most learners don’t complete a module activity. This could mean the instructions are confusing or learners need more knowledge before attempting the task. Or perhaps not many learners are not logging in to the eLearning course. Maybe they don’t understand how to log in or they don’t realize how important it is to their success to complete the course.
But unlike a crystal ball, you don’t need a wizard to see the analytics for any online course. You can find the data you need in your learning management system. Here are five common eLearning analytic measurements that can direct you down a path of growth.
Perhaps this measurement and the ratio of users to log-ins are the most important. Session time measures how long each user is logged on to an e-course. Knowing the average length of time a user spends logged on can guide how course information and activities are chunked. Providing instructors with resources on how to chunk lessons can help them help their learners to make the most of the time learners are logged on.
Users versus log-ins
Let’s say one eLearning course has 100 registered students. On a typical day, 65 students log in to the e-course, but the number of log-ins is 85. This means 24% of students are logging in more than once. This could be because a task requires research and more time, or it could mean the content isn’t engaging enough to keep a typical learner’s attention. Adding multimedia and interactive tasks can increase engagement.
This data tells you how learners access an e-course, whether it’s on a computer or smartphone. If smartphone usage suddenly drops off and computer usage stays the same or increases, perhaps the LMS isn’t rendering correctly on mobile devices.
eLearning analytics can give you an insight into learner preferences. For example, online course pages with embedded videos may get more unique visits than course pages with bulleted lists. Preferences like this can vary between subjects, too. After looking at eLearning analytics, it may become clear that learners prefer videos or webinars for some subjects but short and sweet text for others. Knowing these kinds of preferences may help allocate resources to departments.
An online course’s built-in assessments measure a class’s overall proficiency. A class with high proficiency could mean a well-constructed course, or it could mean a very easy course or simple assessment questions. A class with low proficiency may need reviewed for learner outcome alignment, or a prerequisite course may need to be required.
Looking at eLearning analytics can give you great insight into the success of online courses. The data can guide improvements that support the success of learners and educational institutions. Though getting eLearning analytics from a computer may not be as novel as using a crystal ball, the information is more accurate.