2 nd international workshop on managing ubiquitous communications and services
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2 nd International Workshop on Managing Ubiquitous Communications and Services. Trinity College, Dublin December 13 th & 14 th , 2004 http://www.MUCS2004.org [email protected] Submission Deadline: 27 th September 2004. Context-Informed Adaptive Hypermedia. Alexander O’Connor

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2 nd International Workshop on Managing Ubiquitous Communications and Services

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2 nd international workshop on managing ubiquitous communications and services

2nd International Workshop on Managing Ubiquitous Communications and Services

Trinity College, Dublin

December 13th & 14th, 2004

http://www.MUCS2004.org

[email protected]

Submission Deadline: 27th September 2004


Context informed adaptive hypermedia

Context-Informed Adaptive Hypermedia

Alexander O’Connor

Owen Conlan

Vincent Wade

{oconnoat, Owen.Conlan, [email protected]

Knowledge & Data Engineering Group

Trinity College, Dublin


Overview

Overview

  • Introduction to Adaptive Hypermedia

  • APeLS

  • Context for Adaptive Hypermedia

  • Mechanisms for Context-Informed Adaptive Hypermedia

  • Analysis

  • Conclusions


Adaptive hypermedia for elearning

Adaptive Hypermedia for eLearning

  • Developed from Intelligent Tutoring Systems (ITS) and Hypertext

  • Adaptive Hypermedia[1] systems compose content based on rules and course design with reference to model of learner

  • Models are generally highly detailed.


Apels 2

APeLS[2]

  • Adaptive Personalised eLearning Service

  • Multi-Model Metadata Driven Adaptive Hypermedia System

  • Uses Jess to build an XML document of the course

    • Narrative compares attributes of the Content and the Learner Model

    • Content is referred to indirectly

      • Candidate Groups


Apels architecture

Learner

Model

Content

Model

Learner Portal

Learner

Narrative

Adaptive Service

APeLS Architecture

Narrative

Models

Content

Learner

Models


Context for adaptive hypermedia

Context for Adaptive Hypermedia

  • Context in Adaptive Hypermedia is composed of a variable set of axes with the following properties:

    • Not core model components

    • Potentially interesting to the system

  • Context-Informed Adaptive Hypermedia has ‘deep’ and ‘shallow’ models

  • Context for one system might not be context for another


Why add context

Why Add Context?

  • AH systems already have methods for modeling relevant data.

    • These methods are tailored and effective

    • But, the models tend to be complex

      • ‘Deep Models’

  • Need some way to handle extra concerns easily

    • Define Context as data that would be useful, but is not core to the AH

      • ‘Shallow models’


Context informed ah

Context-Informed AH

  • Context supports additional concerns for the AH

    • Factors not specified when the course was created

  • A Context Interpreter translates these extra factors into a known vocabulary

  • This is done by providing mechanisms to pass information about the state of the narrative and models to the CI, which can make changes

    • Decisions on a list of concepts/entities passed


Context informed apels

Context Interpreter

Learner

Model

Content

Model

Learner Portal

Learner

Narrative

Adaptive Service

Context-Informed APeLS

Narrative

Models

Content

Learner

Models


Mechanisms

Mechanisms

  • Complete Model Enrichment

    • Pass the contents of a model to the Adaptive engine, which alters it

    • User Model Update

  • Selected Model Enrichment

    • Context decides on the membership or order of a portion of the model from a list provided

    • Candidate Group Manipulation

  • Collaborative Dialogue

    • Define Decision points which are answered by Context

    • Narrative Choice

Different Mechanisms impose different requirements for shared knowledge


Advantages

Advantages

  • This method permits Adaptive Hypermedia to make use of a wider knowledge set.

    • Without having to model it directly

    • Increases Adaptivity

    • Provides Interoperability framework

  • The integrity of AH core ‘deep’ models is maintained

    • While the CI is able to employ ‘shallower’ techniques


Conclusions

Conclusions

  • Separated Architecture

    • Core concerns are modeled deeply by Adaptive Hypermedia

    • Context handles extra inputs separately

      • Translated to terms known to the Adaptive Engine

    • Use of shared vocabulary

  • Applications to other systems


References

References

  • Brusilovsky, P.: Methods and techniques of adaptive hypermedia. In P. Brusilovsky and J. Vassileva (eds.), Spec. Iss. On Adaptive Hypertext and Hypermedia, User Modeling and User-Adapted Interaction 6 (2-3), 87-129

  • Conlan, O.; Wade, V.; Bruen, C.; Gargan, M. Multi-Model, Metadata Driven Approach to Adaptive Hypermedia Services for Personalized eLearning. Second International Conference on Adaptive Hypermedia and Adaptive Web-Based Systems, Malaga, Spain, May 2002


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