Get to grips with the basics of learning analytics—what it is, where the data comes from, and how to use it ethically and effectively.

What you'll learn:

• What Is Learning Analytics?

  Explore key definitions, frameworks (e.g. Kirkpatrick), and practical applications in education and L&D.

• Understanding Learning Data

  Examine common data types (LMS logs, SCORM, LTI, surveys), the role of xAPI and LRS, and challenges with temporal data.

• Ethics & Privacy

  Learn about GDPR principles and risks like over-tracking and learner profiling. Case study: Purdue Signals and predictive analytics.

Build and analyse meaningful reports from your LMS using built-in tools and custom plugins.

What you'll learn:

• LMS Report Types

  Work with course completion, activity logs, quiz stats, and participation reports in Moodle and Totara.

• Custom Reporting

  Use the Configurable Reports plugin and Report Builder to write queries, apply filters, and create visual reports.

• Interpreting & Communicating Data

  Share findings with peers, identify patterns (e.g. drop-off points), and avoid common reporting pitfalls.

Learn how to track learning beyond the LMS, identify at-risk learners, and use AI to enhance insight and evaluation.

What you'll learn:

• Web Analytics for Learning

  Use tools like Matomo to analyse content usage, navigation, and learner drop-offs across platforms.

• At-Risk Learner Identification

  Apply rule-based logic to LMS data to flag engagement risks and discuss the ethics of intervention.

• AI in Learning Analytics

  Try out ChatGPT or Gemini to summarise learner feedback and detect behavioural patterns in open data.