Development of a Model of Intelligent Mobile Learning System (Imls) Using Multiagents

ABSTRACT A model of Intelligent Mobile Learning System (IMLS) Using Multi-Agents has been developed and tested in the course of the project reported in this thesis. The IMLS was tailored to match the peculiarities of developing countries especially in terms of limited communications infrastructure and unsteady power supply. Mobile devices communicating over wireless networks are used to provide interaction between learners and teachers anywhere, anytime. In addition to the MultiAgent based IMLS, a non-agent based M-learning software alternative was developed as the basis for assessing the advantages of the multi-agent model developed in this project. This multiagent IMLS acts as template on which teachers can build learning contents and provides an authentic learning environment on which teachers can build learning contents which students can access through their mobile devices. This model when tested showed a response time that was eight times faster than its non-agent counterpart. It also showed other significant advantages over a number of other M-learning models in terms of packet data management capabilities.

Table of Contents

Abstract i

Table of Contents ii

List of Figures vi

List of Tables viii

Approval Page ix

Certification Page x

Dedication xi

Acknowledgement xii

Chapter One: Introduction 1

1.1 Background To The Study 1

1.2 M-Learning Vs E-Learning 2

1.3 Agents 3

1.4 The Structure Of Agents 4

1.5 Component Of M-Learning Agents 5

1.6 Intelligent Mobile Agents 6

1.7 Research Problem 6

1.8 Research Questions 8

1.9 Research Objectives 8

1.10 Research Methodologies 9

1.11 Research Contributions 9

1.12 Scope Of The Research 9

1.13 Thesis Organization 10

Chapter Two: Literature Review 11

2.1 Literature Review 11

2.1.1 The MOBILearn Project 11

2.1.2 Functional Definition of Mobile Learning 12

2.1.3 Mobile Learning System Based on Education Component 13

2.1.4 Framework for Analyzing Mobile Learning 14

2.1.5 M-learning using Mobile Agents 17

2.1.6 Intelligent Mobile Learning Systems 19

2.2 E-Learning Models 20

2.2.1 E-learning Theories, Frameworks, Models and Taxonomies 20

2.2.2 Review of E-learning Models 21

2.3 M-Learning Models 27

2.3.1 Model for M-learning Adoption 27

2.3.2 DeLone and McLean’s Model 28

2.3.3 Open Learner Model 30

2.3.4 Pedagogical Model Developed for Mobile Tutoring 31

4 Development of a Model of Intelligent Mobile Learning System using Multi Agents

2.3.5 A Model for M-learning in Africa 32

2.3.6 Model for Web-based Intelligent Learning Environment 33

2.3.7 The Multi-agent Model – The Bee-gent Framework 34

2.3.8 Shih’s Mobile Learning Model 36

2.3.9 Framework for Mobile Learning based on Education Component System 37

2.4 Classification of M-learning Systems 38

Chapter Three: Theoretical Framework: Agent Systems 41

3.1 Multi-Agent Systems 41

3.2 Agent Architectures 42

3.2.1 Logic Based 43

3.2.2 Reactive Architecture 43

3.3.3 BDI – Belief Desire Intention 44

3.3.4 Layered (hybrid) Architecture 45

3.3 Agent Communication and Coordination 46

3.3.1 Organizational Structuring 47

3.3.2 Contracting 48

3.3.3 Multi-agent Planning 48

3.3.4 Negotiation 49

3.4 Agent Programming Languages and Tools 49

3.4.1 Agent-Oriented Programming Language (AOP) 49

3.5 Application of Multi-Agent Systems 51

3.6 FIPA Specifications 53

3.6.1 History and Goals of FIPA 53

3.6.2 Achievements of FIPA 54

3.6.3 Agent Communication 55

3.6.4 FIPA Sub-Layers 56

3.6.5 Agent Management 58

3.6.6 Abstract Architecture 60

3.6.7 A selection of key FIPA Specifications 61

3.7 JADE Framework 63

3.7.1 Background of JADE 64

3.7.2 The JADE agent Paradigm 64

3.7.3 JADE Architecture 65

3.8 Intelligent Tutoring System 68

3.8.1 The Structure of an ITS 69

3.9 Pedagogical Perspectives of M-Learning 70

3.9.1 Behaviourist Learning 70

3.9.2 Contructivist Learning 71

3.9.3 Situated Learning 71

5 Development of a Model of Intelligent Mobile Learning System using Multi Agents

3.9.4 Problem-based Learning 72

3.9.5 Context awareness Learning 73

3.9.6 Sociocultural Theory of Learning 73

3.9.7 Collaborative Learning 74

3.9.8 Conversational Learning 74

Chapter Four: The IMLS Model 75

4.1 The Proposal IMLS Model 75

4.1.1 The Client 76

4.1.2 The Server, Web Services Producer 78

4.1.3 The JADE Agent 80

4.1.4 The IMLS Model Sub-module 80

4.1.5 The Data Store 81

4.1.6 The Network 82

4.1.7 The Extent of Mobility 82

4.2 The Mathematical Model for Performance Indicators 82

4.2.1 Response Time 82

4.2.2 Throughput 87

4.2.3 Noise Factor 88

4.3 A Comparison of IMLS Model with Other M-Learning Models 90

Chapter Five: System Analysis and Design 91

5.1 Prototype Software Design 91

5.2 Analysis of Related System 91

5.2.1 Information Retrieval System 91

5.2.2 M-learning for Android using Web Services 92

5.2,3 M-learning Application for Ubiquitous Learning Environment 93

5.2.4 Intelligent M-learning System using JADE 94

5.2.5 Mobile Technologies and Learning 96

5.3 Analysis and Design of the Proposed System 97

5.3.1 Architecture of the System 97

5.3.2 Application Service Producer 98

5.3.3 Mobile Client Application 99

5.3.4 Design Methodology 101

5.3.5 Modeling Tools Used 102

5.3.6 Use Cases 102

5.3.7 UML Class Model Diagrams 103

5.3.8 Data Design 106

5.4 IMLS Mobile Client Design 107

5.5 System Specification 111