Learning Analytics Explained

Learning Analytics Explained draws extensively from case studies and interviews with experts in order to discuss emerging applications of the new field of learning analytics. Educational institutions increasingly collect data on students and their learning experiences, a practice that helps enhance courses, identify learners who require support, and provide a more personalized learning experience. There is, however, a corresponding need for guidance on how to carry out institutional projects, intervene effectively with students, and assess legal and ethical issues. This book provides that guidance while also covering the evolving technical architectures, standards, and products within the field.

Table of Contents

PART I: Background
Chapter 1. The Evolution Of A New Field
Chapter 2. Expert Motivations

PART II: Applications
Chapter 3. Early Alert And Student Success
Chapter 4. Course Recommendation
Chapter 5. Adaptive Learning
Chapter 6. Curriculum Design
Chapter 7. Expert Thoughts On Applications

PART III: Logistics
Chapter 8. Data
Chapter 9. Metrics And Predictive Modelling
Chapter 10. Visualisation
Chapter 11. Intervention
Chapter 12. Student-Facing Analytics
Chapter 13. Expert Thoughts On Logistics

PART IV: Technologies
Chapter 14. Architecture
Chapter 15. Standards
Chapter 16. Products
Chapter 17. Expert Thoughts On Technologies

PART V: Deployment
Chapter 18. Institutional Readiness
Chapter 19. Project Planning
Chapter 20. Ethics
Chapter 21. Transparency And Consent
Chapter 22. Privacy And Data Protection
Chapter 23. Expert Thoughts On Deployment

PART VI: Future Directions
Chapter 24. Emerging Techniques
Chapter 25. Expert Visions