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Moodle 4 Administration

You're reading from   Moodle 4 Administration An administrator's guide to configuring, securing, customizing, and extending Moodle

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Product type Paperback
Published in Oct 2022
Publisher Packt
ISBN-13 9781801816724
Length 640 pages
Edition 4th Edition
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Author (1):
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Alex Büchner Alex Büchner
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Alex Büchner
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Table of Contents (24) Chapters Close

Preface 1. Chapter 1: Installing Moodle 2. Chapter 2: Exploring the Moodle System FREE CHAPTER 3. Chapter 3: Exploring Courses, Users, and Roles 4. Chapter 4: Managing Courses and Enrolments 5. Chapter 5: Managing Users, Cohorts, and Authentication 6. Chapter 6: Managing Permissions, Roles, and Capabilities 7. Chapter 7: Enhancing Moodle’s Look and Feel 8. Chapter 8: Understanding Moodle Plugins 9. Chapter 9: Configuring Educational Features 10. Chapter 10: Configuring Technical Features 11. Chapter 11: Enabling Mobile Learning 12. Chapter 12: Gaining Insights through Moodle Reporting and Analytics 13. Chapter 13: Ensuring Moodle Security 14. Chapter 14: Complying with Data Protection Regulations 15. Chapter 15: Optimizing Moodle Performance 16. Chapter 16: Avoiding Sleepless Nights – Moodle Backup and Restore 17. Chapter 17: Working with Moodle Admin Tools 18. Chapter 18: Integrating External Systems Using Moodle Web Services 19. Chapter 19: Setting Up Moodle Networking 20. Chapter 20: Supporting Multi-Tenancy 21. Index 22. Other Books You May Enjoy Appendix: Configuration Settings

Making predictions with Moodle Analytics

In this section, you will learn about Moodle Analytics, including how to create learning analytics models.

Custom and log-based reports are descriptive; they tell viewers what happened but not why, and don’t predict outcomes or advise users on how to improve. While reporting tells us about who, what, when, and where, learning analytics aims to explain why and how well.

Important note

Moodle Analytics predicts or detects unknown aspects of learning based on (historical) log data and current behavior.

There are two types of models that Moodle Analytics supports:

  • Machine learning-based models: Sophisticated models use mathematical tools to make predictions; for instance, students with a high likelihood of failing a course
  • Static models: Simple models are based on assumptions and do not require sophisticated analyses; for example, students who have not enrolled in a course

The following diagram illustrates the...

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