Learning analytics is the measurement, collection, analysis, and reporting of data about learners and their learning contexts — with the goal of understanding and improving learning outcomes and the environments in which they occur. For L&D professionals, learning analytics transforms training from a compliance checkbox into a data-driven function that can demonstrate real business impact.
Key Learning Analytics Metrics
- Course completion rates: Percentage of enrolled learners who finish a course — the most basic but widely reported metric
- Assessment scores: Average quiz and test results by course, cohort, department, or individual
- Time-on-task: Actual time learners spend engaged with content (not just logged in)
- Learning velocity: How quickly different learner groups progress through a curriculum
- Engagement rate: Proportion of learners who actively interact with content vs passively scroll through it
- Knowledge retention: Assessment scores on retests 30/60/90 days after initial completion
- At-risk learners: Predictive flags for learners unlikely to complete on time or likely to fail assessments
Learning Analytics vs Reporting
Basic LMS reporting tells you what happened — who completed what and when. Learning analytics goes further: it identifies patterns, surfaces insights, predicts outcomes, and suggests interventions. The shift from reporting to analytics is the shift from “we know 73% of employees completed POSH training” to “the 27% who didn’t complete are concentrated in three branches — here’s what we recommend.”
AI-powered learning analytics on EdzLMS
Real-time dashboards, at-risk learner flags, and training ROI reports — built for L&D managers, not data scientists.
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