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Update journal and documentation for IEEE standards in EdTech
- Added a reference to the new IEEE Standard 1484.12.1-2020 for Learner Object Metadata in the journal entry for April 30, 2025. - Created a new documentation page for the IEEE Standard 1484.12.1-2020, detailing its purpose, scope, and key concepts. - Updated the IEEE Standard for Sharable Competency Definitions to reflect the new date created and added relevant tags. - Expanded the Total Learning Architecture documentation to include detailed architecture components and related standards.
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‎journals/2025_04_30.md‎

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- [[IMS/Common Cartridge]]
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- #Filed
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- [[US/Gov/ADL/Report/2019 Modernizing Learning]]
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- [[US/Gov/ADL/TLA]]
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- [[IEEE/Term/Learning Engineering]]
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- [[IEEE/Grp/ICICLE]]
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- [[IEEE/Committee/LTSC]]
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- [[IEEE/Std/1484.20.3 Sharable Competency Definitions]]
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- [[IEEE/Std/P9274.1 Experience API xAPI 2.0]]
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- [[IEEE/Std/1484.12.1 Learner Object Metadata 2.0]]
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- [[IEEE/Std/1484.12.1-2020 Learner Object Metadata 2.0]]
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- [[IEEE/Std/2997 Enterprise Learning Record]]
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- [[EdTech/Co/eLearning Industry/Blog/21/05/5 elearning standards explained]]

‎pages/IEEE___Std___1484.12.1-2020 Learner Object Metadata 2.0.md‎

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alias:: [[IEEE LOM 2.0]], [[LOM]]
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tags:: [[IEEE]], [[Standard]], [[Metadata]], [[Learning Object]], [[EdTech]]
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- # IEEE Standard for Learning Object Metadata (1484.12.1-2020)
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- [IEEE Xplore](https://ieeexplore.ieee.org/servlet/opac?punumber=9262116)
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- ## 📖 Overview
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- A standard that defines metadata structure for describing learning objects
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- Enables interoperability and discovery of learning resources across systems
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- Part of [[US/Gov/ADL/TLA]]'s core standards for content description
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- ## 🎯 Purpose
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- Facilitate search, evaluation, acquisition, and use of learning objects by:
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- Learners
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- Instructors
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- Automated software processes
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- Enable sharing and exchange of learning objects through:
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- Development of catalogs and inventories
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- Support for diverse cultural and linguistic contexts
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- Ensure semantic interoperability between different LOM implementations
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- ## 📋 Scope
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- Defines metadata structure for learning objects where:
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- Learning object = any entity (digital or non-digital) used for learning
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- Metadata instance = description of learning object characteristics
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- Supports linguistic diversity of:
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- Learning objects themselves
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- Their metadata descriptions
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- ## 🏷️ Metadata Categories
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- ### Core Categories
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- General information
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- Life cycle
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- Meta-metadata
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- Educational aspects
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- Technical details
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- Rights management
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- Relationships
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- Annotations
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- Classifications
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- ## 💡 Key Concepts
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- ### Learning Object
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- Any entity (digital or non-digital) used for:
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- Learning
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- Education
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- Training
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- ### Metadata Instance
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- Describes relevant characteristics of a learning object
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- Enables systems to:
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- Manage learning objects
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- Locate resources
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- Evaluate content
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- Exchange data
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- ## 🔄 Implementation
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- Standard provides conceptual data schema
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- Actual implementation defined by other standards
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- Designed as base schema that can be extended
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- Enables automated scheduling of learning objects
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- ## 🌐 Interoperability
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- Supports transformation between different bindings
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- Ensures high degree of semantic interoperability
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- Facilitates cross-platform content sharing
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- Enables multi-language support
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- ## 📚 Standard Vocabulary
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- Terms from the IEEE Standards Dictionary
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- ### Category
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- A group of related data elements
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- Used to organize metadata into logical groups
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- ### Datatype
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- A property of distinct values
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- Defines:
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- Common features of values
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- Operations on those values
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- ### Extended Data Element
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- Element defined outside the standard
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- Permitted within data structure instance
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- Enables extensibility of the standard
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- ### LangString
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- Special datatype for character strings
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- Supports multiple equivalent strings:
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- Translations
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- Alternative descriptions
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- Enables multilingual metadata
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- ### Learning Object
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- Any entity used for learning purposes:
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- Can be digital or non-digital
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- Used in education or training
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- Basic unit of educational content
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- ### LOM Data Element
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- Standard-defined data element with:
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- Name
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- Explanation
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- Size
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- Ordering
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- Value space
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- Datatype
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- ### Smallest Permitted Maximum
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- For implementation-defined values
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- Defines minimum constraints
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- Referenced in section 4.5 of standard
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- ### Value Space
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- Set of values for a given datatype
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- Can be:
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- Explicitly enumerated
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- Defined by reference to other standards
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- Note: Definitions based on ISO/IEC 11404:1996

‎pages/IEEE___Std___1484.20.3 Sharable Competency Definitions.md‎

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created-by:: [[IEEE/Committee/LTSC]]
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date-created:: [[2022]]
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tags:: [[EdTech]]
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date-created:: [[2023/07]]
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tags:: [[EdTech]], [[US/Gov/ADL/TLA]]
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- # IEEE Standard for Learning Technology--Data Model for Shareable Competency Definitions
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- > Defined in this standard are a data model for describing, referencing, and sharing **competency definitions**, and **frameworks of competency definitions** and **rubrics** in the context of **online and distributed learning** and in employment and work.

‎pages/US___Gov___ADL___TLA.md‎

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tags:: [[EdTech/Acronym]]
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alias:: [[Total Learning Architecture]]
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tags:: [[EdTech]], [[US/Gov/ADL]], [[Standard]], [[Architecture]], [[Learning Engineering]]
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- # [Total Learning Architecture (TLA)](https://www.adlnet.gov/projects/tla/)
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- [[IEEE]] standards
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- [[IEEE/Std/P9274.1 Experience API xAPI 2.0]] ([[xAPI]]) – Learning activity tracking uses the xAPI to capture learning activity streams. The xAPI standard also includes xAPI Profiles such as cmi5 and the TLA’s Master Object Model (MOM). xAPI 2.0 is targeted for approval in 2020.
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- [[IEEE/Std/1484.12.1 Learner Object Metadata 2.0]] – Descriptions of learning activities and their associated content are stored in the TLA’s Experience Index and use a modified version of the Learning Resource Metadata Initiative standard. A draft standard is being submitted for finalization in early 2020.
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- [[IEEE/Std/1484.20.3 Sharable Competency Definitions]] – The definition of a competency, the relationship to other competencies, and the alignment of evidence to help measure proficiency of the competency, are included in this standard. This standard is expected for approval in 2022.
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- [[IEEE/Std/2997 Enterprise Learning Record]] – Learner profile standards do not currently meet all TLA requirements. These new standards are actively being developed and modified based on input from numerous industry groups and associations.
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- # Total Learning Architecture (TLA)
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- A research and development project by [[US/Gov/ADL]] to create an integrated learning services environment
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- [Official Project Page](https://www.adlnet.gov/projects/tla/)
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- ## 🎯 Core Purpose
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- Enable personalized, data-driven, technology-enabled lifelong learning across:
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- Department of Defense
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- Other Federal Government agencies
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- Beyond government sectors
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- Create a "continuum of learning" that is:
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- Continuous (career-long vs episodic)
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- Blended (formal + informal)
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- Enterprise-focused
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- Learner-centric
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- Data-driven
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- Competency-based
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- On-demand
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- Cloud-based
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- ## 🏗️ Architecture Components
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- ### Data Standards
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- Built on key [[IEEE]] specifications:
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- [[IEEE/Std/P9274.1 Experience API xAPI 2.0]] for activity tracking
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- Includes [[xAPI]] Profiles like [[cmi5]]
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- Features TLA's Master Object Model (MOM)
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- [[IEEE/Std/1484.12.1-2020 Learner Object Metadata 2.0]] for content description
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- [[IEEE/Std/1484.20.3 Sharable Competency Definitions]] for competency frameworks
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- [[IEEE/Std/2997 Enterprise Learning Record]] for learner profiles
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- ### Key Projects
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- #### Competency and Skills System (CaSS)
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- Manages competency frameworks
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- Creates sharable learner profiles
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- Integrates with existing [[LMS]]s
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- #### Data Analytics and Visualizations (DAVE)
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- Extends [[xAPI]] capabilities
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- Provides analysis and visualization tools
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- #### DATASIM
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- Open-source testing tool
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- Generates datasets for TLA validation
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- Helps evaluate [[xAPI]] implementations
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- #### Privacy Support (PS4TLA)
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- Implements user-tailored privacy
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- Creates personalized privacy models
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- #### FLUENT
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- Adaptive recommendation system
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- Analyzes [[xAPI]] data for learning patterns
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- Identifies effective learning sequences
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- ## 🤝 Implementation Partners
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- ### Military
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- Air Force Learning Services Environment (AFLSE)
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- Army Futures Command
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- Defense Health Agency (DHA)
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- ### Intelligence Community
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- Office of the Under Secretary of Defense for Intelligence
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- Defense Counterintelligence and Security Agency
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- ## 📚 Related Standards
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- Builds upon and integrates with:
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- [[SCORM]] (historical foundation)
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- [[xAPI]] (core data standard)
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- [[cmi5]] (launching and tracking)
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- [[IMS/Common Cartridge]] (content packaging)
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- ## 🔄 Development Process
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- Started in 2016
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- Uses spiral design-based research
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- Focus on:
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- Technical specifications
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- Standards development
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- Policy guidance
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- Reference implementations
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- Emphasis on "plug and play" interoperability
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- ## 🎯 Future Direction
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- Moving toward:
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- AI and machine learning integration
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- Enhanced data analytics
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- Improved competency tracking
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- Greater system interoperability
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- Goal: Create a unified learning ecosystem that supports:
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- Multiple learning modalities
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- Various delivery points
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- Comprehensive data collection
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- Advanced analytics
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- Personalized learning paths

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