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.
Related
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.
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