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E-raamat: E-Learning Paradigms and Applications: Agent-based Approach

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Teaching and learning paradigms have attracted increased attention especially in the last decade. Immense developments of different ICT technologies and services have paved the way for alternative but effective approaches in educational processes.

Many concepts of the agent technology, such as intelligence, autonomy and cooperation, have had a direct positive impact on many of the requests imposed on modern e-learning systems and educational processes.

This book presents the state-of-the-art of e-learning and tutoring systems and discusses their capabilities and benefits that stem from integrating software agents.

We hope that the presented work will be of a great use to our colleagues and researchers interested in the e-learning and agent technology.



This book presents the state-of-the-art of e-learning and tutoring systems, and discusses their capabilities and benefits that stem from integrating software agents. It includes various case studies to validate the usefulness of the presented paradigms.

Arvustused

From the reviews:

The primary focus of this book illustrates the best examples of current research on learning environments that utilize software agents to enhance the learning experience. I would recommend this book for educational practitioners working with technology and those looking to see what is occurring at the cutting edge of the teaching/technology environment. (S. M. Godwin, Computing Reviews, April, 2014)

1 RoboNewbie: A Framework for Experiments with Simulated Humanoid Robots
1(38)
Monika Domanska
Hans-Dieter Burkhard
1.1 Introduction
1(3)
1.2 Robots in Education
4(6)
1.2.1 Experimenting with Hardware
4(2)
1.2.2 Experimenting with Simulated Robots
6(2)
1.2.3 Experimenting with RoboNewbie
8(2)
1.3 Soccer Playing Robots: RoboCup
10(2)
1.4 SimSpark RoboCup 3D Soccer Simulation
12(1)
1.5 Communication Between Agents and SimSpark RCSS
13(2)
1.6 The RoboNewbie Project
15(1)
1.7 The Resources of the RoboNewbie Project
16(1)
1.8 RoboNewbie Framework
17(8)
1.8.1 Low Level Interface Functionalities
17(2)
1.8.2 Perception
19(2)
1.8.3 Motions
21(2)
1.8.4 Control Cycle and Decision Making
23(1)
1.8.5 Logger
24(1)
1.9 Exercises
25(2)
1.9.1 Hello World: Structure of Agents, Simple Actions
25(1)
1.9.2 Examples for Perception
26(1)
1.9.3 Examples for Motion
26(1)
1.9.4 Examples for Control
27(1)
1.10 Evaluation by Courses
27(9)
1.10.1 Local Requirements for the Courses
28(3)
1.10.2 Evaluation and Results
31(5)
1.11 Conclusion
36(3)
References
37(2)
2 Designing Intelligent Agent in Multilevel Game-Based Modules for E-Learning Computer Science Course
39(26)
Kristijan Kuk
Ivan Milentijevic
Dejan Rancic
Petar Spalevic
2.1 Introduction
40(1)
2.2 Related Work
41(2)
2.3 Method
43(3)
2.3.1 Problem Statement
43(1)
2.3.2 Characteristics of Students
44(1)
2.3.3 Simulations and Games
45(1)
2.4 Game-Based Modules
46(6)
2.4.1 Implementation of GBMs
48(4)
2.5 Student Modelling in E-Learning System GBMs
52(7)
2.5.1 Pedagogical Agent and System
53(2)
2.5.2 Designing Intelligent Agent Model
55(4)
2.6 Evaluation Results and Discussion
59(6)
References
62(3)
3 E-Learning and the Process of Studying in Virtual Contexts
65(32)
Dragos Gheorghiu
Livia Stefan
Alexandra Rusu
3.1 Introduction
66(2)
3.1.1 The Vanishing Identity of the Traditional Societies
66(1)
3.1.2 A Brief History of Rural Romania
66(1)
3.1.3 The Maps of Time Project
67(1)
3.2 Related Work
68(5)
3.2.1 Theoretical Basis of the Educational Applications' Design
68(1)
3.2.2 Hypermedia Learning Environments
69(1)
3.2.3 Mobile Augmented Reality
70(2)
3.2.4 Agent-Based Approaches
72(1)
3.3 Description of the Agent-Based Learning Paradigm
73(10)
3.3.1 Motivations for Present Work
73(1)
3.3.2 General Presentation of the E-Learning Solution
74(1)
3.3.3 Basic Concepts of Software Agents
75(2)
3.3.4 Components of the Agent-Based Learning Paradigm
77(4)
3.3.5 Description of the Software Agents
81(2)
3.4 Implementation Details
83(5)
3.4.1 Software Integration Challenges
83(1)
3.4.2 The Android Platform
84(1)
3.4.3 The Mobile Augmented Reality Application
84(2)
3.4.4 The Multimedia Educational Content
86(1)
3.4.5 Social Media Integration
87(1)
3.4.6 Software Agents Implementation
87(1)
3.5 Application Experimentation
88(2)
3.6 Educational Novelty and Outcomes
90(2)
3.7 Conclusions and Future Work
92(5)
References
93(4)
4 Inter-university Virtual Learning Environment
97(24)
Andrej Tibaut
Danijel Rebolj
Karsten Menzel
Ricardo Jardim-Goncalves
4.1 Introduction
98(1)
4.2 Review of Related Work
99(6)
4.2.1 Inter-university Collaboration Concepts
99(2)
4.2.2 Taxonomy for Inter-university Interoperability
101(1)
4.2.3 Interoperability Technologies
102(3)
4.3 Use Case: ITC Euromaster
105(4)
4.3.1 The ITCEM Course Pool
106(2)
4.3.2 Technology: A Robust E-Learning Environment
108(1)
4.4 Specification of the Federated Inter-university Virtual Learning Environment
109(5)
4.4.1 Resolving Disharmony Between Federation and New ITCEM Members
112(2)
4.5 Requirements for Further Development of the ITCEM
114(2)
4.6 Conclusions
116(5)
References
116(5)
5 An Agent Based E-Learning Framework for Grid Environment
121(24)
Sarbani Roy
Ajanta De Sarkar
Nandini Mukherjee
5.1 Introduction
121(2)
5.2 Related Work
123(1)
5.3 Grid as Infrastructure
124(4)
5.3.1 Grid Computing
125(1)
5.3.2 Grid Middleware
125(2)
5.3.3 Service Oriented Architecture
127(1)
5.4 E-Learning System
128(2)
5.5 Architecture of the E-Learning Grid
130(5)
5.6 E-Learning Grid as Multi-agent System
135(4)
5.7 Implementation of E-Learning Service with Globus Toolkit
139(2)
5.8 Benefits of E-Learning Grid
141(1)
5.9 Conclusion
142(3)
References
143(2)
6 Determining the Usability Effect of Pedagogical Interface Agents on Adult Computer Literacy Training
145(40)
Ntima Mabanza
Lizette de Wet
6.1 Introduction
146(1)
6.2 Background
147(4)
6.2.1 Terms and Terminology
147(3)
6.2.2 Research Objectives and Approaches
150(1)
6.2.3 Research Limitations and Contributions
150(1)
6.3 Related Work
151(6)
6.3.1 Studies on Pedagogical Interface Agents
151(1)
6.3.2 Pedagogical Interface Agent Systems
152(2)
6.3.3 Simulated Microsoft Office System
154(3)
6.4 Research Design and Methodology
157(7)
6.4.1 Research Design
157(1)
6.4.2 Research Methodology
158(6)
6.5 Data Analysis and Interpretation
164(9)
6.5.1 Demographic Data
164(1)
6.5.2 Statistical Analyses of Usability Performance Data
165(4)
6.5.3 Post-test Questionnaire Analysis
169(4)
6.6 Conclusions
173(12)
6.6.1 Overview
173(1)
6.6.2 Findings
174(2)
6.6.3 Possible Future Research
176(6)
References
182(3)
7 MASECO: A Multi-agent System for Evaluation and Classification of OERs and OCW Based on Quality Criteria
185(44)
Gabriela Moise
Monica Vladoiu
Zoran Constantinescu
7.1 Introduction
186(2)
7.2 Quality Assurance for OERs and OCW
188(3)
7.3 Related Work: QA and Classification of OER/OCW
191(5)
7.4 The Research Methodology
196(5)
7.5 Using MASECO for QA and Classification of OERs and OCW
201(19)
7.5.1 The INTERRAP Architecture
203(1)
7.5.2 The Architecture of MASECO
204(4)
7.5.3 How MASECO Classifies OERs/OCW Using Artificial Neural Networks
208(8)
7.5.4 Classification of OERs and OCW Using Bayesian Belief Networks
216(1)
7.5.5 Discussion
217(3)
7.6 Conclusions and Future Work
220(9)
References
223(6)
8 E-Assessment Systems and Online Learning with Adaptive Testing
229(22)
Marjan Gusev
Goce Armenski
8.1 Introduction
229(2)
8.2 State of the Art
231(7)
8.2.1 Computer Based Testing
231(1)
8.2.2 Architecture and Design
232(3)
8.2.3 Algorithms and Procedures
235(3)
8.3 Description of the Online Learning with Adaptive Testing
238(7)
8.3.1 Interactive Response Learning System
238(1)
8.3.2 Navigation Algorithm
239(1)
8.3.3 Decision Strategy
240(2)
8.3.4 Software Agents
242(2)
8.3.5 Related Work About Adaptive Testing
244(1)
8.4 Conclusion and Future Work
245(6)
References
247(4)
9 Mechanism for Adaptation of Group Decision-making in Multi-agent E-Learning Environment
251(20)
Denis Music
9.1 Introduction
251(2)
9.2 Literature Review
253(1)
9.3 Agents with Personality, Emotions and Mood
254(4)
9.3.1 Agent Personality
255(1)
9.3.2 Agent Mood
256(1)
9.3.3 Agent Emotions
257(1)
9.4 Patience and Experience Within Emotional Agents
258(6)
9.4.1 Patience Within Emotional Agents
259(2)
9.4.2 Experience Within Emotional Agents
261(3)
9.5 Model Evaluation
264(2)
9.6 Conclusion and Future Work
266(5)
References
267(4)
About the Editors 271(2)
Author Index 273
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