Pierre E-Learning Networked Environments and Architectures

A Knowledge Processing Perspective
1. Auflage 2010
ISBN: 978-1-84628-758-9
Verlag: Springer
Format: PDF
Kopierschutz: 1 - PDF Watermark

E-Book, Englisch, 440 Seiten

Reihe: Advanced Information and Knowledge Processing

This book provides state-of-the-art e-learning networked environments and architectures carried out over the last few years from a knowledge management perspective. It contains a comprehensive discussion of e-learning concepts, models, experiments and best practices. Presenting a wide-ranging survey of methods and applications from contributors from around the world, this book will be a valuable resource for researchers, practitioners and graduates.

Autoren/Hrsg.

Pierre, Samuel

Inhaltsverzeichnis

1;Title Page;4
2;Copyright Page;5
3;Table of Contents;6
4;List of Contributors;8
5;1 E-Learning Networked Environments:Concepts and Issues;12
5.1;1.1 Introduction;12
5.2;1.2 Basic Concepts and Background;14
5.3;1.3 Building Knowledge Scenarios;18
5.4;1.4 Building Knowledge Environments;21
5.5;1.5 Designing Knowledge Networks;26
5.6;1.6 Retrieving Resources and Knowledge;28
5.7;1.7 Conclusion;32
5.8;References;33
6;2 Bridging the Gap Between E-Learning Modeling and Delivery Through the Transformation of Learnflows into Workflows;37
6.1;2.1 Introduction;37
6.2;2.2 Context;39
6.2.1;2.2.1 Looking at the Problem;39
6.2.2;2.2.2 Looking at the Solution;40
6.2.3;2.2.3 The Goal: Bridging the Gap Between E-LearningEditing and Delivery;41
6.2.4;2.2.4 Methodological Approach;41
6.2.5;2.2.5 Main Results;42
6.3;2.3 IMS-Learning Design as an Educational Modeling Language;42
6.3.1;2.3.1 E-Learning System Reference Model;42
6.3.2;2.3.2 Educational Modeling Languages;42
6.3.3;2.3.3 Conceptual Elements of IMS-LD;44
6.3.4;2.3.4 Tools for Learnflows;45
6.4;2.4 XPDL as a Business Process Language;49
6.4.1;2.4.1 Workflow Reference Model;50
6.4.2;2.4.2 Process Description Languages or Workflow Models;50
6.4.3;2.4.3 The Conceptual Elements of XPDL;51
6.4.4;2.4.4 Tools for Workflows;53
6.5;2.5 Translation Scheme;56
6.5.1;2.5.1 Static Aspects of the Common Model;56
6.5.2;2.5.2 Dynamic Aspects of the Common Model;57
6.5.3;2.5.3 Model of Control of IMS-LD;58
6.5.4;2.5.4 Model of Control of XPDL;59
6.5.5;2.5.5 The Proposed Translation Scheme;60
6.6;2.6 LDX-Flow Tools;62
6.6.1;2.6.1 Functional Architecture;63
6.6.2;2.6.2 Logical Architecture;65
6.6.3;2.6.3 Physical Architecture;65
6.6.4;2.6.4 Evaluation of the Tools;66
6.7;2.7 Conclusion;66
6.8;References;67
7;3 A Toolkit for Building Geo-Referenced Lessons: Design, Implementation, and Praxis;70
7.1;3.1 Introduction;70
7.2;3.2 Experimentation;71
7.3;3.3 Pedagogical Strategies;76
7.4;3.4 Content in a Mobile Lesson;78
7.4.1;3.4.1 Design of the Lesson: Identifying Content;79
7.4.2;3.4.2 Presentation to Students: Introducing Content;79
7.4.3;3.4.3 Lesson on the Field: Acquiring Content;79
7.4.4;3.4.4 Back in the Classroom: Reflecting on Content;80
7.5;3.5 Administrative Tools;80
7.6;3.6 Technology: Devices and Software;81
7.6.1;3.6.1 Mobile Lessons, Release 1.0;83
7.6.2;3.6.2 Mobile Lessons, as Location-Based Services;83
7.6.3;3.6.3 Mobile Lessons, Toward New Services;83
7.7;3.7 Conclusion;85
7.8;3.8 Acknowledgment;85
7.9;References;85
8;4 TELOS: A Service-Oriented Framework to Support Learning and Knowledge Management;88
8.1;4.1 Introduction;88
8.2;4.2 TELOS Orientation and Vision;91
8.2.1;4.2.1 Orientation Principles;91
8.2.2;4.2.2 System’s Levels and Main Actors;93
8.3;4.3 User Operations and Main Service Components;95
8.3.1;4.3.1 Three Operational Levels;95
8.3.2;4.3.2 Basic Operations on a Resource;97
8.3.3;4.3.3 Resource Life-Cycle Operations;98
8.3.4;4.3.4 System Generation Cascade Operations;101
8.3.5;4.3.5 Semantic Referencing of a Resource;102
8.4;4.4 TELOS Framework Organization;104
8.4.1;4.4.1 TELOS Core and Kernel Structure and Extension;104
8.4.2;4.4.2 Core Use for LKMS Construction;106
8.4.3;4.4.3 LKMS Use and LKMA Construction;109
8.4.4;4.4.4 LKMA Use and LKMP Construction;111
8.4.5;4.4.5 Summary of TELOS Services;115
8.5;4.5 Conclusion;116
8.6;References;117
9;5 Cognitive Modeling of Personalized Software Design Styles: A Case Study in E-Learning;119
9.1;5.1 Introduction;119
9.2;5.2 The Limits of Current Modeling Approaches;120
9.2.1;5.2.1 Representing Knowledge with Abstraction Layers;121
9.2.2;5.2.2 A Class of Adaptive Systems;122
9.3;5.3 A Tutoring System for OODP;124
9.3.1;5.3.1 An Example Session;125
9.3.2;5.3.2 Perceived Affordances and Software Design;127
9.3.2.1;5.3.2.1 Perceived Affordances;127
9.3.2.2;5.3.2.2 A Simple Cognitive Model for Software Design;128
9.3.3;5.3.3 Representing Perceived Affordances for OOP Design;128
9.3.4;5.3.4 Recombination Aspects;130
9.3.4.1;5.3.4.1 Target Platform for the Prototype;131
9.3.4.2;5.3.4.2 Recombination Cycle for the Prototype;132
9.3.5;5.3.5 Overall Software Architecture;133
9.3.6;5.3.6 OODP Classifier;134
9.3.6.1;5.3.6.1 OODP Case Library;135
9.3.7;5.3.7 Algorithm Families;137
9.3.7.1;5.3.7.1 Weka Algorithms;138
9.3.7.1.1;5.3.7.1.1 Extracting Boolean Features from OOCD;138
9.3.7.1.2;5.3.7.1.2 Weka Subsystem Architecture;139
9.3.7.2;5.3.7.2 Keyword-Based Algorithms;140
9.4;5.4 Empirical Evaluation;141
9.4.1;5.4.1 Evaluation Process;142
9.4.2;5.4.2 Experimentation Prototype;143
9.4.3;5.4.3 Results;143
9.4.3.1;5.4.3.1 Pedagogical Effectiveness;145
9.4.3.2;5.4.3.2 Classifiers Results;146
9.5;5.5 Related Work;147
9.5.1;5.5.1 Metamodel Reuse;148
9.5.2;5.5.2 Object Oriented Design Patterns;148
9.5.2.1;5.5.2.1 Teaching Object Oriented Design Patterns;149
9.5.3;5.5.3 Schema Matching Algorithms;149
9.5.4;5.5.4 Comparison with an Existing ITS System;150
9.5.5;5.5.5 The Proposed Approach and the Existing Literature;152
9.6;5.6 Conclusion;152
9.7;References;154
10;6 Skills SuperStore: Online Interactive Study Skills Environment;156
10.1;6.1 Introduction;156
10.1.1;6.1.1 Background and Rationale;156
10.1.2;6.1.2 Skills SuperStore: Project Aim and Objectives;158
10.1.3;6.1.3 Chapter Organization;158
10.2;6.2 Need for Study Skills;159
10.2.1;6.2.1 Retention Issues in Third-Level Institutions;159
10.2.2;6.2.2 Study and Transferable Skills Needed;160
10.2.3;6.2.3 Importance of Study and Transferable Skills;162
10.2.4;6.2.4 Approaches Currently Employed in Higher Education to Train Study Skills;163
10.2.5;6.2.5 Study Skills Training: Limitations of Current Approaches;164
10.3;6.3 The Way Forward and a Solution;165
10.3.1;6.3.1 Investigation of Current Approaches;165
10.3.2;6.3.2 Surveys and Analysis;166
10.3.3;6.3.3 Pedagogical Underpinning of the SkillsSuperStore System;167
10.3.4;6.3.4 System Requirements and Initial Architecture;174
10.4;6.4 System Design and Development;176
10.4.1;6.4.1 Requirements Gathering;177
10.4.2;6.4.2 Analysis;177
10.4.3;6.4.3 Design;185
10.4.4;6.4.4 Implementation;187
10.4.5;6.4.5 Testing and Evaluation;190
10.5;6.5 Conclusion;193
10.6;References;193
11;7 E-MEMORAe: A Content-Oriented Environment for E-Learning;195
11.1;7.1 Introduction;195
11.2;7.2 Content Management for E-Learning;196
11.2.1;7.2.1 Content Sharing;197
11.2.2;7.2.2 Learning Objects Repositories and Thematic Resources Bases;197
11.2.2.1;7.2.2.1 Learning Object Repositories;197
11.2.2.2;7.2.2.2 Thematic Resources Bases;198
11.2.2.3;7.2.2.3 The MEMORAe Approach;198
11.3;7.3 A Course Memory : the MEMORAe Model;199
11.3.1;7.3.1 Contents of the Memory;199
11.3.1.1;7.3.1.1 Resources;199
11.3.1.2;7.3.1.2 Topics;199
11.3.1.3;7.3.1.3 Ontologies;200
11.3.1.3.1;7.3.1.3.1 Building the Ontologies;200
11.3.1.3.2;7.3.1.3.2 Application Ontology;200
11.3.1.3.3;7.3.1.3.3 Domain Ontology;201
11.3.1.3.4;7.3.1.3.4 Linking the Two Ontologies;202
11.3.2;7.3.2 The Choice of the Formalism: Topic Maps [14];202
11.3.3;7.3.3 Memory Modeling: An Example;204
11.3.3.1;7.3.3.1 Ontologies;204
11.3.3.2;7.3.3.2 Course Objectives;205
11.4;7.4 The E-MEMORAe Environment;206
11.4.1;7.4.1 The User Interface;207
11.4.2;7.4.2 Learning by Exploration in the Memory;208
11.4.3;7.4.3 Learning by Querying the Memory;210
11.5;7.5 Architecture;210
11.6;7.6 Experiments;211
11.6.1;7.6.1 Conditions of the Experiment;211
11.6.2;7.6.2 First Results;212
11.7;7.7 Conclusion;213
11.8;References;213
12;8 Designing and Testing an Open-Source Learning Management System for Small-Scale Users;216
12.1;8.1 Introduction;216
12.2;8.2 Learning Management Systems to Learning ContentManagement Systems;218
12.3;8.3 Reusability and Interoperability;219
12.3.1;8.3.1 Reusability;220
12.3.2;8.3.2 Interoperability;221
12.4;8.4 Metadata;222
12.5;8.5 Learning Objects (LOs);223
12.5.1;8.5.1 Combination;225
12.5.2;8.5.2 Granularity;225
12.6;8.6 Standards;226
12.6.1;8.6.1 Standards Evolution;227
12.6.2;8.6.2 Learning Object Metadata Standards;230
12.7;8.7 Learning Object Metadata (LOM);232
12.7.1;8.7.1 Dublin Core Metadata Initiative;234
12.7.2;8.7.2 Modifying the IEEE Learning Object Metadata (LOM);234
12.7.3;8.7.3 Taxonomy Models and Ontology;238
12.7.4;8.7.4 Final Schema of Our System;243
12.8;8.8 The Phoenix System;244
12.8.1;8.8.1 Implementing Phoenix;246
12.9;8.9 Phoenix System Architecture and Functionality;247
12.9.1;8.9.1 Unique Features for the SMEs;248
12.10;8.10 Delivery, Evaluation, and Results;250
12.11;8.11 Conclusion;254
12.12;References;255
13;9 Reinforcement Agents for E-Learning Applications;258
13.1;9.1 Introduction;258
13.2;9.2 Multiagent Systems and Interaction with Users;259
13.3;9.3 Reinforcement Learning;260
13.3.1;9.3.1 Temporal-Difference Learning;262
13.3.2;9.3.2 Hybrid Techniques;264
13.4;9.4 RL Perspectives for E-Learning;265
13.4.1;9.4.1 Design Requirements;265
13.4.2;9.4.2 Reinforced Learner-Oriented Search Engines;266
13.4.3;9.4.3 Learning Object ID (LOID);269
13.4.4;9.4.4 Learning Speed Considerations;270
13.4.5;9.4.5 Example for Designing Human–Agent Interaction;273
13.4.6;9.4.6 Reinforcement Reliability and Adjustable Autonomy;276
13.5;9.5 Advanced Issues in Reinforcement Learning;277
13.6;9.6 Conclusion;279
13.7;References;280
14;10 Secure Communication Layer for Scalable Networks of Learning Object Repositories;283
14.1;10.1 Introduction;283
14.2;10.2 Major Interoperability Efforts in E-Learning;284
14.3;10.3 IMS Digital Repository Interoperability;287
14.4;10.4 eduSource: An Open Network for Connecting Communities;288
14.5;10.5 ECL: eduSource Communication Layer;291
14.5.1;10.5.1 General Approach;291
14.5.2;10.5.2 ECL Connector;293
14.5.3;10.5.3 ECL Gateway;295
14.5.4;10.5.4 ECL Registry;296
14.5.5;10.5.5 ECL Federated Searching Across Multiple Repositories;297
14.6;10.6 Scalable Security Solution;297
14.6.1;10.6.1 Motivations for Federated Security Solution;299
14.6.1.1;10.6.1.1 Case Study: Course Management Systems;299
14.6.1.2;10.6.1.2 Case Study: Secure P2P Network LionShare;300
14.6.2;10.6.2 Federated Security;300
14.6.2.1;10.6.2.1 Shibboleth;300
14.6.2.2;10.6.2.2 Web Services and Federated Security;301
14.6.3;10.6.3 Security Infrastructure Components;301
14.6.3.1;10.6.3.1 Certification Authority;301
14.6.3.2;10.6.3.2 Local Attribute Authority;302
14.6.3.3;10.6.3.3 ECL Registry;302
14.6.4;10.6.4 ECL Security Profiles;303
14.6.4.1;10.6.4.1 Repository Controlled Security Profile;303
14.6.4.2;10.6.4.2 Federated Security Profile;303
14.7;10.7 Implementation and Deployment;305
14.8;10.8 Discussion;306
14.8.1;10.8.1 Pragmatics of Following the IMS DRI;307
14.8.2;10.8.2 Document-Style Web Services;307
14.8.3;10.8.3 Comparison with Other Approaches;308
14.9;10.9 Conclusion;309
14.10;References;310
15;11 Quality of Service and Collaboration Aspects in a Distributed E-Laboratory Environment;313
15.1;11.1 Introduction;313
15.2;11.2 Background and Related Work;314
15.2.1;11.2.1 Electronic Learning Concepts;315
15.2.2;11.2.2 Virtual Environments and Learning Management Systems;316
15.2.3;11.2.3 QoS and Collaboration in Virtual Learning Environments;317
15.3;11.3 The E-Laboratory Environment;318
15.3.1;11.3.1 The Telecommunication Platform;318
15.3.2;11.3.2 The Collaborative E-Learning Architecture;319
15.3.3;11.3.3 Process in Collaboration;321
15.3.4;11.3.4 Collaboration Scenarios;325
15.3.5;11.3.5 Collaborative Architecture Supporting Quality of Service;328
15.4;11.4 Implementation and Results;330
15.4.1;11.4.1 Implementation of QoS in theCollaborative Environment;331
15.4.2;11.4.2 Model Definition, Results, and Analyses;332
15.4.3;11.5 Conclusion;339
15.5;References;339
16;12 Quality Rating and Recommendation of Learning Objects;343
16.1;12.1 Introduction;343
16.2;12.2 Online Learning and Learning Objects;344
16.2.1;12.2.1 Learning Objects;345
16.2.2;12.2.2 Learning Object Repositories;346
16.2.3;12.2.3 Pedagogical Metadata;347
16.3;12.3 Evaluation and Recommendation Systems;348
16.3.1;12.3.1 Evaluating Quality;349
16.3.2;12.3.2 Recommendation and Trust;350
16.4;12.4 Learning Object Quality Rating Using Bayesian Belief Networks;356
16.4.1;12.4.1 What We Propose;356
16.4.2;12.4.2 Bayesian Belief Networks: A Quick Introduction;359
16.4.3;12.4.3 Unit Quality Rating;360
16.4.4;12.4.4 Integrated Quality Rating;364
16.5;12.5 Discussion;367
16.5.1;12.5.1 Simulated Test Cases for Individual Rating;367
16.5.2;12.5.2 Simulated Test Cases for Integrated Rating;369
16.5.3;12.5.3 Reliability and Validity of Our Approach;371
16.5.4;12.5.4 Equating Scaling;372
16.5.5;12.5.5 Personalised and Collaborative Recommendation and Distribution of BBN;372
16.5.6;12.5.6 Share Learning Objects Among Multiple Repositories;374
16.5.7;12.5.7 BBN Drawback;374
16.5.8;12.5.8 Further Research Angles;374
16.5.9;12.5.9 Conclusion;376
16.6;References;376
17;13 Data Mining in E-Learning;380
17.1;13.1 Introduction;380
17.2;13.2 Phrase-Based Document Model;382
17.2.1;13.2.1 Vector Space Model;382
17.2.2;13.2.2 Graph Space Model;383
17.2.2.1;13.2.2.1 DIG Structure Overview;384
17.2.2.2;13.2.2.2 DIG Construction;385
17.3;13.3 Document Similarity Using Phrase Matching;387
17.3.1;13.3.1 Phrase Matching Using DIG;387
17.3.2;13.3.2 A Phrase-Based Similarity Measure;389
17.3.3;13.3.3 Combining Single-Term and Phrase Similarities;390
17.3.4;13.3.4 Effect of Phrase-Based Similarity on Clustering Quality;391
17.4;13.4 Document Clustering Using Similarity Histograms;392
17.4.1;13.4.1 Similarity Histogram-Based Incremental Clustering;395
17.4.2;13.4.2 Similarity Histogram-Based Clustering Evaluation;397
17.5;13.5 Key-Phrase Extraction from Document Clusters;398
17.5.1;13.5.1 Extraction of Candidate Key Phrases;400
17.5.2;13.5.2 Phrase Features;402
17.5.3;13.5.3 Phrase Ranking;403
17.5.4;13.5.4 Key-Phrase Extraction Evaluation;404
17.5.5;13.5.5 Key-Phrase Extraction Results;404
17.6;13.6 Conclusion;408
17.7;References;409
18;14 LORNAV: Virtual Reality Tool for Navigation of Distributed Learning Objects Repositories;411
18.1;14.1 Introduction;411
18.2;14.2 Learning Objects and Virtual Environment;412
18.2.1;14.2.1 Definition of Learning Objects;412
18.2.2;14.2.2 Learning Object Metadata;413
18.2.3;14.2.3 Learning Object Repositories;413
18.2.4;14.2.4 3D Visualization and Virtual Reality;414
18.2.5;14.2.5 Virtual Reality Modeling Language;415
18.2.6;14.2.6 The Need for 3D Visualization;415
18.3;14.3 Navigation of Learning Object Repositories;416
18.3.1;14.3.1 Use Case Model;416
18.3.2;14.3.2 Overall Architecture;417
18.3.3;14.3.3 3D Visualization of Learning Objects;419
18.3.4;14.3.4 Data Clustering;422
18.3.5;14.3.5 Dynamic 3D View Generation;422
18.3.6;14.3.6 Navigation Model;424
18.3.7;14.3.7 Interaction Model;425
18.3.8;14.3.8 Data Access;426
18.4;14.4 Implementation;428
18.4.1;14.4.1 Example Interfaces;430
18.4.1.1;14.4.1.1 Navigation Interfaces;430
18.4.1.2;14.4.1.2 Interaction Interfaces;432
18.5;14.5 Conclusion and Future Work;434
18.6;References;434
19;Index;436

Leseproben

"10 Secure Communication Layer for Scalable Networks of Learning Object Repositories (p. 276-277)

MAREK HATALA, GRIFF RICHARDS, TIMMY EAP, AND ASHOK SHAH

Abstract. The eduSource Communication Layer (ECL) de?nes a set of services, middleware, and communication conventions that enable repositories and tools to communicate with each other. ECL was designed and implemented within the scope of the recommendations in the IMS DRI speci?cation. The ECL has been deployed worldwide and connects repositories in Canada, the United States, Australia, the United Kingdom, and Europe.

In this chapter we describe the design of ECL, its architecture, and its middleware components. We also describe novel ECL security infrastructure (ECL-SI) for Web services that provide the security framework for object repositories based on a trust federation. The security solution de?nes security pro?les, infrastructure services, and middleware component for a low-barrier adoption by existing repositories. Although this infrastructure can scale to large networks; it is particularly sensitive to the needs of medium-sized and small organizations, which have complex attributes and accessing policies.

10.1 Introduction

Over the last few years we have seen signi?cant progress in the area of crucial technologies and standards for the Semantic Web’s XML and Resource Description Framework (RDF). They have gained wide acceptance in the industry, and the semanticWeb group atW3Cis ?nalizing the recommendation for next essential semanticWeb component—the OntologyWeb Language. Metadata are in use across all vertical layers of the systems, and several large-scale initiatives are trying to build usable networked systems for object and knowledge sharing and to further our understanding of the related issues.

All these activities promise to develop systems that can discover and share information with other systems in the near future. One of the leading areas where integration and sharing are in high demand is education, particularly in e-learning. The wholesale adoption of Internet technology as a channel for education and training has resulted in an abundance of learning resources in Web-ready digital format. Typically, these digital learning objects [33] may be lesson content stored as text, audiovisual or interactive media ?les, or simply learning activity templates expressed in a learning design format [18].

Despite their apparent ubiquity, locating and reusing learning objects are hampered by a lack of coordinated effort in addressing issues related to their storage, cataloging, and rights management. Strident efforts have been made to create portal repositories by communities such as Merlot,1 SMETE,2 RDN3 and, in Canada, by BCcampus4 and CAREO5. Not surprisingly, each entity produces a rather individual re?ection of its own perceived organizational needs, and the concept of making all these repositories work together, while laudable, has received less attention. The e-learning community has seen fruitful initiatives in the standardization of learning object metadata by the Institute of Electrical and Electronics Engineers (IEEE) [16] and the emergence of speci?cations toward the standardization of other aspects of learning objects and learning processes by organizations such as IMS and ADL.

More recently, the e-learning community has been focusing on the ability to connect and use resources located in distributed and heterogeneous repositories. This process of federation closely resembles the initiatives in the domain of digital libraries, to the extent that there have been initiatives such as the IMS Alt-i Lab meetings to bring these two communities together."