Glossary

Learning analytics

3 min read
In short

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

What it is

In practice it spans several layers: platform data (logins, completions, assessment results), interaction data (clicks, submissions, forum activity), attention data (dwell, focus, drop-off), and outcome data (performance, retention, behaviour change).

Most deployments stop at the first layer, which is why 'learning analytics' so often means 'completion reporting with charts'.

Why it matters

Only 35% of organisations measure L&D impact beyond completion rates, and 67% of L&D leaders report struggling to demonstrate training impact. The gap between what learning analytics could be and what it usually is remains very wide.

A common confusion

Learning analytics describes learners; content analytics describes material. The second is usually more actionable — it produces a fix list rather than a report on individuals.

See also content effectiveness, completion rate and at-risk learner. See the full glossary for the rest, or the guide to measuring training effectiveness for the wider context.

See where your content loses people

Book a walkthrough and we will show you the engagement data on your own content.

Request a demo
Get Started

See what completion rates can't tell you

Find out exactly where your content works, where it fails, and what disengagement looks like before people leave.

Request a Demo