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Enterprise LMS with Adobe Learning Manager

You're reading from   Enterprise LMS with Adobe Learning Manager Design and develop world-class learning experiences for your employees, partners, and customers

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Product type Paperback
Published in Jun 2023
Publisher Packt
ISBN-13 9781804618875
Length 502 pages
Edition 1st Edition
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Author (1):
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Damien Bruyndonckx Damien Bruyndonckx
Author Profile Icon Damien Bruyndonckx
Damien Bruyndonckx
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Table of Contents (23) Chapters Close

Preface 1. Part 1 – Publishing Learning Content
2. Chapter 1: Introduction to Adobe Learning Manager FREE CHAPTER 3. Chapter 2: Customizing the Look and Feel of Adobe Learning Manager 4. Chapter 3: Uploading Learning Content and Managing the Content Library 5. Chapter 4: Creating Skills and Courses 6. Part 2 – Managing Learners and Tracking Learning Data
7. Chapter 5: Managinswg Users 8. Chapter 6: Enrolling Learners in Courses 9. Chapter 7: Reviewing the Learner Experience 10. Chapter 8: Exploring the Instructor Role 11. Chapter 9: Configuring and Using Feedback 12. Chapter 10: Reporting in Adobe Learning Manager 13. Part 3 – Enhancing the Learner Experience
14. Chapter 11: Badges and Gamification 15. Chapter 12: Enabling and Managing Social Learning 16. Chapter 13: AI-Powered Recommendations for Learners 17. Part 4 – Administering the Platform
18. Chapter 14: Working with Catalogs and Peer Accounts 19. Chapter 15: Working with Messages and Announcements 20. Chapter 16: Exploring the Integration Admin Role 21. Index 22. Other Books You May Enjoy

Recommendations Based on Peer Activity

The default learner home page of Adobe Learning Manager contains several widgets whose content is provided by the built-in AI. In the previous section, you discovered the Recommended based on your areas of interest widget.

In this section, you will explore the Recommended based on peer activity widget and the admin options that affect the recommendations it produces.

To come up with these recommendations, the artificial intelligence must analyze how you and your peers behave on the account. This includes analyzing the courses learners have enrolled in, the skills covered by those courses, the L1 and L3 feedback received, whether or not new courses published on the platform are successful, current industry trends, and more. All this data is fed into the artificial intelligence that generates the content of the Recommended based on peer activity widget.

This complex process is mostly automatic and takes place behind the scenes without any...

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