What are recommendations?
  • 06 Sep 2024
  • 1 minute to read

What are recommendations?


Article summary

Totara's recommendations engine allows users to find both formal learning content (e.g. courses) and informal content (e.g. resources or playlists).

The recommendations shown to users will be limited in a number of important ways to ensure that they are relevant:

  • Users will be shown recommendations for content in languages they speak
  • Content that users have already seen or courses they are enrolled on will be ranked lower than undiscovered content
  • Workspaces a user has already joined will be excluded
Find out more about how the recommendation engine's text processing works in the technical documentation.
In Totara 15 onwards, recommendations run in the Machine Learning Service. If you were using the recommendations engine in Totara 14 or earlier you will need to upgrade from the legacy recommender. Please note that the legacy ml_recommender service is now deprecated as of Totara 17.

When viewing user-generated content or workspaces, users will be able to access a side information panel showing additional details about the content.

Within this panel, users can click the Related tab to see a list of similar content. The following content will be displayed in this tab for each type of content:

  • Resources: The Related tab displays similar resources with the resource image, title, time to read, and number of likes
  • Playlists: The Related tab displays similar playlists with the playlist image, title, playlist creator, and rating

Recommendations blocks

There are two blocks which can be used to display recommendations, both of which can be added to various dashboards or the user profile.

You can add the Recommended for you block and the Recently viewed block.

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