The document discusses learning analytics, outlining its use in academic settings to improve retention, success, and teaching quality. It highlights how educators and learners can utilize analytics to monitor progress, identify issues, and enhance performance. Additionally, it poses important questions for educators regarding learner engagement and challenges.

1. Learning
Analytics
Rebecca Ferguson
Simon Buckingham Shum
The Open University

2. Types of analytic
High-level figures
A brief overview for internal
and external reports
Academic analytics
Figures on retention and success, for
the institution to assess performance
Learning analytics
Use of big data to provide actionable
intelligence for learners and teachers

3. Educators use analytics to:
• Monitor the learning process
• Explore student data
• Identify problems
• Discover patterns
• Find early indicators for success
• Find early indicators for poor marks or drop-out
• Assess usefulness of learning materials
• Increase awareness, reflect and self reflect
• Increase understanding of learning environments
• Intervene, supervise, advise and assist
• Improve teaching, resources and the environment

4. Learners use analytics to:
• Monitor their own activities and interactions
• Monitor the learning process
• Compare their activity with that of others
• Increase awareness, reflect and self reflect
• Improve discussion participation
• Improve learning behaviour
• Improve performance
• Become better learners
• Learn!

5. Course Signals: Purdue

6. SNAPP: British Columbia

7. Identify questions
• Which elements are learners struggling with?
• Which sections engage them the most?
• What prompts them to ask questions?
• Are they finding assessment challenging?
• What misconceptions have learners shown?
• Are there any accessibility issues?
• How can analytics be used to obtain desired
learning outcomes?

8. Additional resources
bit.ly/1130R0Ybit.ly/VUGBfJ