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Book: Semantic Web and Education

Table of Contents

Preface

Introduction to Web-based education

1.   E-Learning

1.1   Alternative definitions
1.2   Objectives, perspectives, tools, and learning modes
1.3   Pros and cons
1.4   Organizing e-Learning material

2.   Distance Education

2.1   Features
2.2   Pros and cons

3.   Virtual Classrooms

3.1   Architecture and modes of interaction
3.2   Technology and software
3.3   Problems, challenges, and open issues

4.   Prerequisites for Acceptance

4.1   Educational workflow issues
4.2   Quality-of-service in WBE

5.   Intelligence and Adaptivity

5.1   Intelligent tutoring systems

5.1.1    Architecture
5.1.2    Instructional design
5.1.3    Web-based ITSs

5.2   Adaptive learning

5.2.1   Adaptive hypermedia
5.2.2   Adaptive educational hypermedia systems

6.   Summary

Introduction to the Semantic Web

1.   From the Web of Information to the Web of Knowledge

2.   Ontologies

2.1   Basic Concepts

2.1.1   Definitions
2.1.2    What do ontologies look like?
2.1.3    Why ontologies?
2.1.4    Key application areas
2.1.5    Examples

2.2   Ontological engineering

2.2.1    Ontology development tools
2.2.2    Ontology development methodology
2.3   Applications

3.    Semantic Web languages

3.1   XML and XML Schema
3.2   RDF and RDF Schema
3.3   OWL
3.4   SPARQL

4.    The Role of Ontologies

5.    Semantic markup

6.    Semantic Web services

7.    Open Issues

8.    Summary

9.    End Notes

The Setting for Semantic Web-Based Education

1.    The Actors and the Support

1.1   Key issues
1.2   The learner's view
1.3   The teacher's (instructor's) view
1.4   The author's view
1.5   The system developer's view

2.    Educational Content

2.1   The concept of learning objects
2.2   Educational modeling languages

3.    Educational Servers

4.    Educational Web Services

5.    Pedagogical Agents

6.    Educational Ontologies

6.1   An example scenario
6.2   Categories of educational ontologies

7.    Current Efforts

8.    Summary

Architectural Issues

1.    Architectural reference model

2.    Learning Objects

2.1   Learning object size and structure
2.2   Learning objects and instructional design
2.3   Learning object metadata
2.4   Learning object repositories

3.    Architectures of Web-Based ITSs

4.    P2P Networking

4.1   P2P computing essentials
4.2   P2P architectures for exchanging learning objects

5.    Adaptive Learning Systems

6.    Ontology Processor

7.    Adopting Software Engineering Trends

7.1   Model-Driven Architecture
7.2   SWBE perspective on MDA

8.    Summary

Learning Technology Standardization Efforts

1.    The Basics

1.1   Definitions
1.2   Relevant standardization bodies
1.3   Standardization process

2.    Important Standards in Learning Technologies

2.1   Types of standards
2.2   Dublin Core
2.3   IEEE LOM
2.4   IMS Content Packaging
2.5   IMS LD
2.6   IMS QTI
2.7   IMS LIP
2.8   IEEE PAPI Learner
2.9   ADL SCORM
2.10 Other standards

3.    Semantic Web Issues Related To Learning Technology Standards

3.1   Additional requirements
3.2   Advanced bindings
3.3   Knowledge organization systems
3.4   Development practices

4.    Summary

Personalization Issues

1.    The Basics

1.1   The Role of Personalization
1.2   Types of personalization
1.3   Approaches to personalization

1.3.1    Personalization with ITSs
1.3.2    Personalization with Web-based ITSs
1.3.3    Personalization with AEHSs
1.3.4    Personalization with pedagogical agents
1.3.5    Ontology-based personalization
1.3.6    Semantic Web services and personalization
1.3.7    Web mining-based personalization
1.3.8    Extending and adapting standards to capture personalization
1.3.9    Formal methods
1.3.10      Support for whole-person personalization

2.    Learner Modeling

2.1   Learner model specifications and markup languages
2.2   Generic learner modeling
2.3   Ontology-driven learner modeling
2.4   Learner model ontology
2.5   Open learner models
2.6   Learner model servers and brokers
2.7   Learner modeling and LO metadata
2.8   RDF binding and API for learner model exchange
2.9   Web mining for learner models
2.10 Open issues and best practices

3.    A case study

3.1   Learning object decomposition
3.2   TANGRAM and its ontologies
3.3   Personalization with TANGRAM

3.3.1    User model ontology
3.3.2    Dynamic assembly of personalized learning content

4.    Summary

Ontological Engineering for Semantic Web-Based Education

1.    The coverage

2.    Rationale for Ontological Engineering of e-Learning

2.1   Conceptual issues
2.2   Technological issues
2.3   Tools-related issues

3.    Methodological Aspects

3.1   Modeling and metamodeling
3.2   e-Learning-specific ontological engineering

4.    Achieving Interoperability

5.    Ontology visualization

5.1   Visual languages for knowledge representation
5.2   Concept maps
5.3   Topic maps
5.4   Cluster Maps
5.5   Visualizing role concepts and hierarchies

6.    Semantic Annotation of Learning Material

6.1   Authoring tools perspective
6.2   Annotation tools perspective
6.3   Semantic links perspective

7.    Ontological Engineering of Instructional Design

7.1   Key characteristics of instructional design
7.2   Instructional design theories and learning objects

7.2.1    New metaphors
7.2.2    Learning object taxonomies
7.2.3    Instructional engineering and content packaging

7.3   Needs and representations
7.4   Ontology of instructional design
7.5   Facilitating instructional design using ontologies
7.5.1    Learning scenarios and competencies

7.5.2    Ontology of instructional design theories
7.5.3    Instructional design and recommender systems
7.5.4    Ontological support for lesson plans

7.6   An example

8.    Task Ontology

8.1   Basic ideas

8.1.1    Task ontology of an intelligent learning environment
8.1.2    The relation between task ontology and domain ontology

8.2   Training task ontology
8.3   Authoring task ontology

9.    Authoring Frameworks

10.      Automatic Construction of Learning Ontologies

10.1 Constructing ontologies from online dictionaries
10.2 Exploiting Web service descriptions

11.      Summary

Applications and research

1.    Learning management and the Semantic Web

1.1   Introduction to learning management systems
1.2   Intelligent Learning Management Systems

1.2.1    The need for intelligence in learning management systems
1.2.2    Synergy between Web-based ITSs and LMSs
1.2.3    Architectural issues
1.2.4    Ontology management

1.3   Learning content management

1.3.1    Learning content repurposing
1.3.2    The course ontology

2.    Collaborative learning and the Semantic Web

2.1   A brief introduction to CSCL
2.2   Ontology of collaborative learning

2.2.1    Theoretical background
2.2.2    Overall structure
2.2.3    Learning goal ontology and negotiation ontology
2.2.4    Interactions and interaction patterns
2.2.5    Applications

3.    Learning communities and the Semantic Web

3.1   The learners' needs in learning communities
3.2   The vision of semantic learning webs
3.3   Learning portals
3.4   Semantic learning organizations

4.    Personalized Educational Services

4.1   Architecture
4.2   Authoring and annotation
4.3   Examples of personalization services

5.    Representing learner's personality

5.1   Assessing emotional intelligence and cognitive traits online
5.2   Personality-based adaptivity

6.    Summary

References

Index