Adaptive learning adjusts content, sequence or difficulty in response to individual learner data — typically assessment performance, and increasingly engagement signals.
What it is
Implementations range from simple branching (fail this check, see the remedial path) to model-driven systems that maintain an estimate of learner knowledge and select the next item accordingly.
Engagement-adaptive systems are a newer variant: if attention is dropping, shorten the path, surface a worked example, or offer a break point.
Why it matters
Engagement data makes adaptation possible without an assessment gate. You do not have to wait for someone to fail a question to know they have stopped absorbing the material.
A common confusion
Adapting to engagement is a low-risk intervention — invisible to the learner, no cost to a false positive. Adapting based on inferred emotional state is a different proposition entirely, and in EU workplace and education contexts it is prohibited.
Related
See also disengagement prediction, engagement index and at-risk learner. See the full glossary for the rest, or the learner engagement guide for the wider context.
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