由於網際網路的普及與World Wide Web Service應用的快速崛起，目前已成為最廣為使用的資訊操作平台與教學傳播媒介，也發展出不受時間與空間的限制的Web-base教學/學習模式。本論文，提出一個具有系統延展性(Scalability) 與高可及性(Highly Available)的網路學習系統-Web-based Learning System(WebLS)，對於缺乏資源或專業技能，但想要透過網際網路提供學習課程的教師、自願者或機構提供學習/教學服務與數位學習教材儲存之Web入口網站的服務。
首先我們研究、設計與實作一網路學習管理系統-Learning Management System(LMS)，符合ADL所制訂的數位學習標準-SCORM 1.2規格，滿足網路線上學習所需求之功能，並針對學習行為分析之研究議題，提出一項尋找較佳學習路徑的研究成果-Experience Matrix System with Time Fragment Extraction(EMST)，分析數位環境中學習者之學習行為，用以發掘、分析學生的學習路徑，以找出更適合後續學習者的學習路徑。
此外，針對一般的學習管理平台在大量學習者連線存取，許多課程同時執行複雜的程式邏輯運算時，很快便達到效能瓶頸的問題;我們使用伺服器群組作為建立具延展性與高可及性解決方案的一種方法。不過，集合並管理從不同的擁有者所取得的大量且不同內容型態的學習教材，於一個分散式伺服器系統上，必須面對新的設計及管理的問題並且需要新的解決辦法。在本論文中將對這些問題提出我們的系統及解決之道。

This dissertation presents a scalable web framework leaning system, Web-based Learning System (WebLS), addressing the distance learning scenario. Since the speed popularity of the Internet infrastructure and World Wide Web Services that have become the most commonly used information platform and an important medium for education; and expand to the Web-based e-Learning model. The Web-based e-Learning is not subject to the boundary of time or space that has greatly enhanced the effectiveness of online distance learning.
The WebLS aims at bringing together the most promising web technologies and standards, in order to attain a scalability and highly availability online learning environment. Moreover, the scalable web framework includes a SCORM based learning management system (named LMS), a server cluster infrastructure, a learning content management service, an information and content repository (named LMS database), and an agent system supporting the innovative solutions taken to implement scalability, availability, portability, reusability, and standardization.
The WebLS can store and provide Web access portal to learning contents from teachers, voluntaries, and institutions that lack resources or expertise to offer curriculums over the Internet.
So, in the first we design and implement the web-based learning managemnt sytem, Learning Management System (LMS), which conform the e-Learning standard, SCORM 1.2 specification, that established by ADL, and satisfy the requirements of the basic functionality at online web-based learning. Besides, in point of the research topic of learning behavior analysis, we propose a study result for extracting better learning path, Experience Matrix System with Time Fragment Extraction (EMST), which can analyse the learner’s study behavior in Web-based learing environment. Then the information is used to explore, analyse students’ learning path in order to find out the suitable learning path for the more learners.
As masses of learners concurrently enter the learning system, the system is often unable to serve such a massive workload, particularly during peak periods of learning activity. We use the server-cluster architecture as a way to create scalable and highly available solutions. However, hosting a variety of learning contents from different owners on such a distributed server system faces new design and management problems and requires new solutions. This dissertation describes the research work we are pursuing for constructing a system to address the challenges faced by hosting learning content on a server farm environment.

中文摘要 ii
ABSTRACT iii
ACKNOWLEDGMENT v
CONTENTS i
FIGURE List iv
TABLE List vi
1 Introduction 1
1.1 Motivation 1
1.2 Scalable Web-based Learning System (SWebLS) 2
1.3 Issues of SWebLS on Server Cluster 5
1.4 System Architecture of SWebLS 6
1.5 Framework of SWebLS 7
1.6 Information Model of SWebLS 12
1.7 Dissertation Organization 14
2 Background 16
2.1 e-Learning Requirements 16
2.1.1 Instructor-Learner 16
2.1.2 Learner-Learner 17
2.1.3 Learner-Content 17
2.2 e-Learning Standards 18
2.3 Learning Management System 20
3 Learning Management Subsystem(LMS) 23
3.1 System Requirements 24
3.2 System Design 27
3.3 System Architecture 29
3.3.1 Framework of Modules 29
3.4 System Implementation 31
3.4.1 Development Platform 32
3.4.2 Interface Implementation 33
3.4.3 Functionalities 36
3.5 Run-Time Environment Module 41
3.5.1 SCORM Run-Time Environment Overview 41
3.5.2 Framework of RTE Module 43
3.5.3 The Components of LMS RTE Module 44
3.5.4 Implementation 52
3.6 Experience 54
4 Scalable Learning System on Server Clusters 55
4.1 Intelligent Request Distribution 55
4.1.1 Content-aware Routing 56
4.1.2 Content-aware Intelligence 58
4.1.3 Design of URL table 60
4.2 Java-based Management System 62
4.2.1 Analysis 62
4.2.2 Management Framework 64
4.2.3 Configuration Management 65
4.2.4 Learning Content Management 67
4.3 Support for Learning Content 68
4.3.1 URL Formalization of Learning Contents 68
4.3.2 Learning Content Management System 71
4.4 Performance Results 73
4.5 Discussion 76
5 Learning Path Extraction on LMS 78
5.1 Problem Definition 80
5.2 EMST 83
5.2.1 System Architecture 84
5.2.2 TA: Tracking Agent 84
5.2.3 TFE: Time Fragment Extraction 86
5.2.4 Concept of TFE 86
5.2.5 Operation procedure of TFE 87
5.2.6 Calculation of TFE 89
5.2.7 EMS: Experience Matrix System 90
5.2.8 Concept of EMS 90
5.2.9 Calculation of EMS 92
5.2.10 Algorithm of EMST 95
5.3 Experiments and Evaluation 96
5.3.1 User Interface 96
5.3.2 Simulation Data 98
5.3.3 Evaluation on EMS 98
5.3.4 Evaluation on EMST(EMS with TFE) 101
5.4 Discussion 101
6 Conclusion and Future Work 103
6.1 Conclusion 103
6.2 Future Work 104
REFERENCE 106
VITA 114

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