I taught this course with Prof Dragan Gašević during 2017 to 2019 as part of the MSc Digital Education Programme at the University of Edinburgh.
Summary
This course provides a framework for understanding and critically discussing the emerging field of learning analytics. Students will learn about the distinction between learning analytics, educational data mining, and big data, and the relationship of learning analytics and existing fields. Perspectives on what learning analytics should be will be connected to philosophy and theory on the nature of design and inquiry. We will consider what it means for a learning analytics analysis or model to be valid, and the key challenges to the effective and appropriate use of learning analytics.
Structure
1. Foundations of Learning Analytics
- Learning Analytics
- Educational Data Mining
2. Learning Analytics Methods
- Social Network Analysis
- Epistemic Network Analysis
3. Learning Analytics Tools
4. Theory and Practice of Learning Analytics
- Influential Practice and Policy
- Theories Shaping Learning Analytics
- Privacy and Ethics in Learning Analytics
5. Assignments
- A literature review on learning analytics related topics
- A Learning analytics research proposal
