The Learning Analytics Certificate program spans eight hours and is completed online, over the course of two half days. When you complete this program, you’ll take part in a multi-day live, virtual instructor-led (VILT) class that includes ample time for discussion, analysis and application. We will define learning analytics and review how to gather, analyze and report on your findings.

PREWORK

For prework, you will be asked to gather information on the current state of learning analytics in your organization. You will also read a case study that will be used in application activities throughout the live session.

DAY 1

WHAT IS LEARNING ANALYTICS?

• The four-step process for learning analytics
• Current state of learning analytics
• Aligning analytics and KPIs to organizational strategy
• Analytics versus measurement, evaluation and assessment

UNDERSTANDING THE 4-STEP PROCESS

GATHER

• Identifying key data sources
• Data collection methods and technology
• Navigating common obstacles to data collection
  • Activity: Identifying sources and how to collect data

PREPARE

• Data quality and managing demographic data
• Cleaning and securing your data

ANALYZE

• Quantitative and qualitative analysis
• Data filtering and comparisons to uncover meaningful patterns
  • Activity: Filtering data for improved insights

REPORT

• Data visualization
  • Activity: Match graphs to data reporting
• Storytelling with data

DAY 2

APPLYING THE 4-STEP PROCESS

COLLECTING DATA

• Maintaining data over time and ensuring accuracy
• Ensuring quality data
• Identifying types of data available

PREPARING DATA

• Data cleaning and preparation deep dive

ANALYZING DATA

• Interpreting data to uncover insights
• Approaches to analysis
• Validating findings before reporting

REPORTING DATA

• Structuring your report
• Optimizing visualizations for stakeholder needs
• Integrating generative AI into your learning analytics workflow
• Capstone Activity: Data analytics case study: Applying the 4-step Process

Ethical Considerations

• Navigating privacy, bias and responsible use of data

WANT TO LEARN MORE?

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