Enhanced Learning Catalog Search Advisor

Redwood Platform

Learning Catalog Search Advisor now uses enriched learning data, learner language preference, job-related context, and, for supported self-paced learning types, knowledge from learning content to improve search results.

Learning enrichment adds AI-generated information, such as suggested skills, job titles, topics, summaries, descriptions, learning objectives, and ideal learner details. This additional information helps the advisor better understand what each learning covers. For supported self-paced learning types, the advisor can also use the actual learning content, not just the catalog information entered by learning specialists.

Here's how these enhancements improve search results:

  • Returning results that better match the learner's request.
  • Recommending supported self-paced learning based on its actual content, when that content is indexed and learning enrichment is enabled.
  • Prioritizing results in the learner's preferred or session language.
  • Returning recommendations that better reflect the learner's job context.
  • Showing only learning the learner can access.

Business benefit: Help learners find more relevant learning while improving the overall Learning Catalog Search Advisor search experience

Steps to enable and configure

If you're already using Learning Catalog Search Advisor, complete these setup steps to take advantage of the enhanced search capabilities. Some steps might already be complete.

  1. Verify whether the ORA_WLF_AI_COMPANY_INFO profile option has a site-level value set. If not, add an appropriate value and enter a description of the organization. This description will provide context when summarizing entities.

    1. Go to Setup and Maintenance > Tasks panel > Search > Manage Administrator Profile Values.
  2. If it's not enabled already, set the site-level value to Yes for the ORA_WLF_ADVISOR_SEARCH_SUGGESTIONS_ENABLED profile option.
  3. Set the site-level profile value to Yes for the ORA_WLF_LEARNING_ENRICHMENT_ENABLED profile option. Learning created after you enable the profile option is enriched automatically.
  4. Run the enrichment setup agent once to enrich all learning in your catalog with private metadata. 
    1. Go to Tools > AI Agent Studio > Agent Teams and search for Learning Enrichment Setup Assistant. 
    2. Run it by giving a simple prompt, such as Run or Start. 
  5. Run the Create Summaries Using Generative AI process once to make the enriched data usable by the Learning Search Advisor agent.   
    • Run Type: Full
    • Content Source: Business Object
    • Object Type:  Learning Items
  1. Schedule the Create Summaries Using Generative AI process to run weekly so indexed content and enriched data stay current.  
      • Run Type: Incremental
      • Content Source: Business Object
      • Object Type:  Learning Items.

Tips and considerations

  • Learning enrichment is optional but recommended. Without it, Learning Catalog Search Advisor might not provide the same level of search relevance and recommendation quality.
  • Learning enrichment applies to active Redwood-compatible learning types: courses, self-paced learning, learning events, and learning paths.
  • Learning Catalog Search Advisor no longer requires that Dynamic Skills be enabled.
  • Knowledge from self-paced learning content can only be extract for certain types that support it. For details, see the release 26C What's New: Self-paced learning content knowledge indexing.

Key resources

Access requirements

Learning specialists need this duty role and privilege to use Learning Enrichment Setup Assistant and Learning Catalog Search Advisor.

Purpose Name Code Description
Run Learning Enrichment Setup Assistant from AI Studio to enrich the learning catalog Learning Setup 

ORA_WLF_LEARNING_SETUP_DUTY 

 Allows the user to perform learning setup tasks.
Use Learning Catalog Search Advisor Access Learning Common Components

ORA_WLF_LEARNING_COMMON

 Access Learning Common Components