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The Multi-model, Metadata-driven Approach to Content and Layout Adaptation

University of Dublin Trinity College. The Multi-model, Metadata-driven Approach to Content and Layout Adaptation. Owen.Conlan@cs.tcd.ie Knowledge and Data Engineering Group (KDEG) Trinity College, Dublin. University of Dublin Trinity College. Overview.

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The Multi-model, Metadata-driven Approach to Content and Layout Adaptation

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  1. University of Dublin Trinity College The Multi-model, Metadata-driven Approach to Content and Layout Adaptation Owen.Conlan@cs.tcd.ie Knowledge and Data Engineering Group (KDEG) Trinity College, Dublin

  2. University of Dublin Trinity College Overview • Adaptive Hypermedia Systems and Services • Methods of Adaptivity • Metadata for Representing Adaptivity • Multi-Model, Metadata Driven Approach to Adaptive Hypermedia Services • Narrative, Architecture • Adaptive Layout • Layout Model • Multiple Adaptive Engines

  3. University of Dublin Trinity College Adaptive Hypermedia Systems • What are the components of a typical AHS? • A User model (may be individual or stereotypical) • A mechanism to produce personalized content • Why are AHSs difficult to maintain? • The content and the rules that govern how that content is personalized are usually intertwined • This makes it difficult to – • Add/Modify new content • Change the structure of the content • Use only a sub-section of the content

  4. University of Dublin Trinity College User Model Repository Narrative /Content Repository Adaptive Hypermedia Systems AHS Engine Personalized Content

  5. University of Dublin Trinity College Data about the User Collects User modelling Processes User Model System Processes Adaptation Adaptation Effect User, Device, Environment, etc. Context Modelling Context Information

  6. University of Dublin Trinity College Methods of Adaptivity • Adaptive Presentation • Personalization of content delivered • Adaptive Navigation • Dynamically generated navigation and paths • Historical Adaptation • Time context • Structural Adaptation • Spatial representations

  7. University of Dublin Trinity College Multi-model, Metadata Driven Approach • Metadata to describe Adaptive Resources • Multi-model • Two versions of the approach • 3 Models – Content, Learner and Narrative (PLS) • N Models – At least one Narrative, the rest are metadata based (APeLS)

  8. University of Dublin Trinity College Metadata for describing Adaptive Resources 1 • Developed as part of EASEL (IST Project 10051) • Educator Access to Services in the Electronic Landscape • Appropriate Descriptive Metadata to facilitate discovery and reuse of Adaptive Electronic Learning Objects • Extension of IEEE LOM and IMS LRM

  9. University of Dublin Trinity College Metadata for describing Adaptive Resources 2 • Current specifications don’t facilitate the description of Adaptive Resources • Full Adaptive Hypermedia Systems • Reusable Adaptive Components • As part of EASEL the IMS Learning Resource Metadata v1.2 was extended to facilitate the complex nature of Adaptive Learning Resources

  10. University of Dublin Trinity College XML Metadata Representation <adaptivity> <adaptivitytype name=“competencies.required” ref=“…”> <set type=“all”> <candidate> <langstring lang=“en”>Functions.Concept</langstring> <langstring lang=“de”>Funktionen.Konzept</langstring> </candidate> <candidate> ... </candidate> </set> </adaptivitytype> </adaptivity>

  11. University of Dublin Trinity College Basic Schema View for Adaptivity adaptivitytype* name=<langstring> ref=<URI>? set? type=“one-or-more“|“all“|... set* candidate* langstring*

  12. University of Dublin Trinity College Multi-Model, Metadata Driven Approach • The Multi-model, Metadata Driven approach separates the models used in adaptation (e.g. Narrative, Learner and Content) from each other • Provides a generic run-time engine for interpreting Narratives and reconciling models to produce an adaptation effect.

  13. University of Dublin Trinity College Learner Model Content Model Learner Interface Learner Narrative Adaptive Engine Simple 3 Model Architecture Narrative Models Content Learner Models

  14. University of Dublin Trinity College Multi-model Approach – Requirements • Separate – • User Model • Pertinent information that the system can use to personalize to the user’s preferences • Content Model • Describes the individual pieces of content • Narrative Model • Describes how the content can be structured/sequenced for different needs • Other Models • Device, Environment, Layout etc. • Provide appropriate alternative candidates • Provide an abstraction layer and selection criteria

  15. University of Dublin Trinity College Multi-model Approach – Narrative 1 • The Narrative Model is – • The Embodiment of a Domain Experts Knowledge • Represented in Jess (Expert System Shell for Java) • Responsible for assembling the personalized course • The Narrative can access any metadata in the repositories • Narrative is described at a conceptual level, i.e. it does not refer directly to learning content.

  16. University of Dublin Trinity College Multi-model Approach – Narrative 2 • There may be multiple Narrative Models for a single course • There is a Candidate Narrative Repository • Each Narrative also has associated metadata • A Narrative may be comprised of sub-narratives

  17. University of Dublin Trinity College Multi-model Approach - Candidates • What are candidates? • Elements that fulfil the same role… • Pieces of content that cover the same material • Narratives that produce courses from the same content body • …but achieve that role differently • The content candidates may be textual, graphical or interactive • Narrative candidates may support different approaches to learning

  18. University of Dublin Trinity College Candidate Content Groups • A Content Candidate is a pagelet and its associated metadata • A Candidate Content Group contains Candidates that fulfil the same learning objective, but are implemented differently • The Narrative can refer to Groups rather than individual pieces of content • Most appropriate Candidate selected at runtime by looking at the Learner model

  19. University of Dublin Trinity College Multi-model Approach – Abstraction and Selection • Abstraction • Narratives are built using concept names rather than content identifiers • Enables the service to use the most appropriate candidate • Selection • There criteria used to select a candidate from a group of potential candidates are based upon – • The candidates metadata • The learner’s metadata

  20. University of Dublin Trinity College A Generic Architecture • The Adaptive Hypermedia Service is designed to facilitate multiple tiers • Each tier can achieve one (or more) axes of adaptivity • Facilitated by metadata • Supported by an extensible AI mechanisms

  21. University of Dublin Trinity College Adaptive Hypermedia Service – APeLS Architecture Learner Modeler Learner Metadata Repository Learner Input Adaptive Engine Transform Content Metadata Repository Personalized Course Model (XML) Rules Engine Candidate Selector Candidate Content Groups Personalized Course Content Candidate Narrative Groups Narrative Metadata Repository Content Repository Narrative Repository

  22. University of Dublin Trinity College Learner Model Context Adaptive Engine What about Layout? Context Information Layout Strategy Stylesheet Elements Stylesheet Elements Learner Models Tailored Layout Model Layout

  23. University of Dublin Trinity College Adaptive Layout Learner Modeler Learner Metadata Repository Learner Input Adaptive Engine XSLT Transform Content Metadata Repository Personalized Course Model (XML) Rules Engine Candidate Selector Candidate Content Groups Personalized Course Content Candidate Narrative Groups Narrative Metadata Repository Tailored Layout Model Content Repository Narrative Repository

  24. University of Dublin Trinity College AE AE AE Adapted Output Adapted Output Adapted Output Adaptive Service Adaptive Service Adaptive Service Metadata Metadata Strategy Strategy Strategy Adaptive Engine Adapted Output Strategy Multiple Adaptive Services(APeLS II) Metadata

  25. University of Dublin Trinity College Summary • Adaptive Hypermedia Services can deliver information personalised for the user’s needs • They can also tailor delivery towards environment and device (Context) • Personalization and Adaptation may be facilitated by appropriate metadata • The tiers of the multi-model, metadata approach may be used to implement different axes of adaptivity

  26. University of Dublin Trinity College Thank You! Owen.Conlan@cs.tcd.ie Knowledge and Data Engineering Group (KDEG) Trinity College, Dublin www.iclass.info http://kdeg.cs.tcd.ie www.m-zones.org

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