Microcredential LA-1 · Learning Analytics

Learning Analytics
for Educators

Master the skills to interpret educational data, identify at-risk students early, and make evidence-based decisions that improve learning outcomes and institutional success.

Now Available
Duration15 Hours
LevelIntermediate
LanguageEnglish
Format100% Self-Paced
Learning Analytics for Educators
Learning Outcomes

What you will be able to do

Analyze student performance data to identify patterns and risks
Build effective learning analytics dashboards for real courses
Detect at-risk students before it's too late to intervene
Design data-driven intervention plans with measurable outcomes
Select the right KPIs for different educational contexts
Apply AI to accelerate analytics and decision-making
Interpret engagement metrics and behavioral learning patterns
Lead a data-driven continuous improvement cycle
"Learning Analytics is the measurement, collection, analysis and reporting of data about learners, for the purpose of understanding and optimizing learning."
— George Siemens, 1st International Conference on Learning Analytics (2011)
68%of higher education institutions already
use some form of learning analytics
— EDUCAUSE, 2023
3×higher success rates with early
warning systems in place
— UNESCO IITE, 2021
40%of at-risk students never receive
timely academic intervention
— EDUCAUSE Horizon, 2023
Course Structure

3 Modules · 3 AI-Powered Simulators

01
Student Success Analytics Simulator

Understanding Learning Analytics & Student Performance

Analyze a real simulated course dataset. Play the role of Academic Success Coordinator, identify at-risk students, detect engagement patterns, and prioritize interventions — confirmed and deepened by AI analysis.

Live Dataset AnalysisAI Risk AssessmentIntervention Prioritizer
02
Dashboard Builder Studio

Dashboard Design & Educational Data Visualization

Build your own learning analytics dashboard by selecting KPIs, engagement metrics, and risk indicators. AI evaluates your design, identifies blind spots, and provides expert recommendations.

KPI SelectorDashboard BuilderAI Design Review
03
Student Retention Crisis Simulator

Data-Driven Intervention & Continuous Improvement

Face a live retention crisis: course completion dropped 23 points in 3 weeks. Diagnose the root causes, select interventions — then AI generates your full recovery plan with phases, timelines, and success metrics.

Crisis DashboardRoot Cause AnalyzerAI Intervention Plan

Learning Analytics Specialist for Educators

Duration15 hours
Modules3 + Assessment
LevelIntermediate
LanguageEnglish
FormatSelf-paced
AI Tools3 simulators
CertificateIncluded
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