Glossary
What Is Learning Analytics?
Learning analytics is the measurement, collection, analysis, and reporting of data about learners and their context to understand and optimize learning outcomes.
Last Updated: May 2026
Learning analytics encompasses the systematic collection and interpretation of data generated during training to improve learner outcomes, course effectiveness, and program ROI. The field developed in parallel with the rise of digital learning platforms that produce continuous behavioral data — login frequency, time on task, completion rates, assessment scores, video engagement, discussion participation, and so on. Modern LMS analytics dashboards provide three layers of insight: descriptive analytics that report what happened (course completion rates, average scores), diagnostic analytics that explain why (which lessons cause drop-off, which assessments fail most learners), and predictive analytics that forecast outcomes (which learners are at risk of failing, which courses correlate with retention). For L&D leaders, the strategic value of learning analytics is the ability to tie training outcomes to business metrics — connecting course completion to performance reviews, certifications to revenue, or onboarding speed to first-year retention. Arythmatic's analytics dashboard surfaces all three layers and exports cleanly to BI tools for executive reporting.
Key Benefits
Frequently Asked Questions
What metrics matter most in learning analytics?
Completion rates, average assessment scores, time-to-competency, and engagement signals like discussion participation are the core metrics. The strategic ones tie training to business outcomes — retention, revenue per trained employee, and ramp time.
Can I export analytics from Arythmatic to my BI tool?
Yes. Arythmatic's analytics layer exports CSV, JSON, and webhook events that flow cleanly into BI tools like Looker, Tableau, and Power BI.