利用行動裝置如口袋型電腦(pocket PCs)與智慧型手機(smartphones)來進行數位學習相關活動並非是創新的概念。但很多的學習系統和學習活動則不斷地在行動科技領域發展，並探索各種數位學習應用的可能性。雖然各種的行動學習平台延伸了學習者的學習經驗並提供更彈性的學習環境，但是各種不同的硬體條件限制，在系統發展上，也同時變成必需面對克服的問題。

在本研究論文中提出四個主要模組來實現可調式的課程快取策略與課程內容呈現。主要目的在於針對符合SCORM數位學習標準的學習環境，提升系統在學習活動中的立即性、可及性與互動性。這四個模組分別為:

1. 課程切割模組(Course Segmentation Module)： 此模組能夠分割一個課程為數個容量較小的基本單位；稱之為課程叢集(course clusters)。在其他所提出的功能模組中，在此產生的課程叢集將被視為最基本的操作單元。

2. 課程內容呈現調整模組(Course Presentation Adaptation Module)：此模組加入模板(template)的概念，幫助課程開發人員或指導人員能夠輕易地將原本的課程內容排版作轉換，使其適合在各種行動學習平台上閱讀。

3. 課程快取模組(Course Caching Module)：此模組目的在於針對學習者在學習活動中，對於課程的存取預測。藉由精準的預測機制，系統可以在學習開始前，即預先儲存好即將要被使用的學習資源於使用者端。因此學習者在學習活動中，能立即取得所需的學習資源，如此不僅可以大幅減少等待下載學習資源的時間，也能提供暫時離線的學習情況。

4. 多重課程版本的包裝與發送模組(Course Rich-presentation Packaging/Delivering Module)：課程內容呈現調整模組為了適合在其他學習平台上進行閱讀，所產生的各種課程版本將由此模組負責進行動包裝與發送。此模組可以整合所有版本的課程並封裝成一個多重內容呈現版本的課程包裝，除此之外，正確地從多重版本的課程包裝中，發送正確的版本內容給學習者的學習平台，則是此模組的另一個目的。

為了實現並驗證我們的研究，在系統實作上，開發了許多的數位學習相關的網路服務(Web Service)並用來實現所提出來的四個系統模組。在本論文的最後，將介紹藉由加入這四個功能模組所建立的數位學習系統，並提出實驗結果，證明對於整個學習系統的立即性、可及性與互動性的提升。

The use of portable devices like pocket PCs and smartphones to support teaching and learning is not a new concept. Many innovative learning systems and activities have also been proposed to promote e-learning, as well as exploited the ways of e-learning. Although the variety of mobile platforms provide more flexible and extendable learning experience, the various hardware conditions and restrictions consequently becomes the challenges and barriers we need to overcome.

There are four main modules proposed to carry out the course caching strategy and presentation adaptation methods that aim at promoting the immediacy, accessibility, and interactivity for SCORM-compliance mobile learning environment. Firstly, Course Segmentation Module: The module can separate a course into several smaller unites namely course clusters. The produced smaller clusters are considered as basic operation units that are manipulated by other modules to carry out their specific functions under restricted memory capacity conditions. Secondly, Course Presentation Adaptation Module: The module is providing different adaptation templates to help the author
automatically and efficiently reproduce high-quality learning content presentation which is appropriate to read on specific mobile learning platforms. Thirdly, Course Caching Module: The module can precisely predict the access of courses and to download them before learning begins; the learning process can not only reduce the waiting time significantly but also offer the downloaded content for offline learning. Finally, Course Rich-presentation Packaging/Delivering Module: The user may use the Course Adaptation Module to create plural course versions for different presentations on specific mobile learning platforms such as pocket PCs and smartphones. The module can integrate all produced course versions and package as a standard Common Cartridge Course Package. Furthermore, correctly delivering the corresponding course version to the learner’s mobile learning platform is another purpose of this module.

In order to realize and verify our ideas, we develop numerous m-learning services based on Web Service technology supporting to implement the proposed modules. The final part of the dissertation will demonstrate the learning systems developed with the proposed modules and illustrate the significant performance according to experimental results.

Table of Contents
List of Figures	III
List of Tables	VI
Chapter1 Introduction	1
1.1	The Proposed Modules	5
1.2 The demonstration systems	7
Chapter 2 Related Works	9
2.1 Mobile Learning	9
2.2 International e-Learning Standard	9
2.2.1 ADL SCORM Specification	9
2.2.2 SCORM Sequencing and Navigation (S&N)	11
2.2.3 IMS Common Cartridge Specification	14
2.3 Related Research Literatures	15
Chapter 3 Proposed Modules for Adaptive Course Caching and Presentation	19
3.1 Course Segmentation Module	19
3.2 Course Caching Module	22
3.2.1 The Prediction Factors	23
3.2.2 Factors of Specific Devices	29
3.2.3 Factors of Learning Record	30
3.2.4 Automata of Course Caching Strategy in Learning System	30
3.3 Course Presentation Adaptation Module	33
3.3.1 Semantic Unit (SU) and Presentation Unit (PU)	35
3.3.2 Textual Adaptation Model	36
3.3.3 Image adaptation Model	41
3.3.4 Layout Adaptation Model	42
3.4 Course Rich-presentation Packaging/Delivering Module	42
Chapter 4 Implementation	49
4. 1 MINE SCORM m-Learning Web Service API Implementation	50
4.2 Pocket SCORM with Course Caching System	51
4.3 Pocket SCORM Demonstration	62
4.4 Learning Content Adaptation Authoring Tool Demonstration	66
Chapter 5 Experimental Results and Discussion	72
5.1 Simulator	72
5.2 Testing Courses	75
5.3 Experimental Results	77
5.3 Discussion	81
Chapter 6 Conclusion and Future Work	83
Bibliography	85
 
List of Figures
Figure 1 Overall Proposed System Modules and Demonstration Systems	5
Figure 2 An illustration of Clusters within a Course	20
Figure 3 An Example of Course Segmentation	22
Figure 4 Prediction Factor for VMM mode—Size of a Cluster	25
Figure 5 Prediction Factor for COD mode—Size of a Cluster	25
Figure 6 Possible Accessing Clusters according to SCORM Sequencing Setting: Sequencing Control Flow	27
Figure 7 Possible Accessing Clusters according to SCORM Sequencing Setting: Sequencing Control Choice	27
Figure 8 Possible Accessing Clusters according to SCORM Sequencing Setting: Sequencing Control Forward Only	28
Figure 9 Path length between two individual clusters	29
Figure 10 Automata of the proposed course caching system	31
Figure 11 A PU progressively displays the text in three states	34
Figure 12 Construct a dictionary of weighted words	38
Figure 13 Processing of the learning content adaptation	40
Figure 14 Common Cartridge package interchange file	45
Figure 15 An example of rich-presentation course package	46
Figure 16 IEEE LOM General Category	47
Figure 17 The imsmanifest.xml in the Rich-presentation Course Package	48
Figure 18 Entire Architecture of Implementation Systems	49
Figure 19 WSDL of Developed m-Learning Web Service	50
Figure 20 Learning Presentation Functions on LMS based on SCORM m-Learning Web Service API	51
Figure 21 Pocket SCORM System Architecture	52
Figure 22 Course Clusters Stored in Back-end Server.	53
Figure 23  Architecture of the Proposed Course Caching System	54
Figure 24 Flow Chart of Download Management Model	55
Figure 25 Kernel Class of Download Management Model	57
Figure 26 A Cluster Order Suggested by Download Management Service	58
Figure 27 Flow Chart of Replacement Management Model	59
Figure 28 Kernel Class of Replacement Management Model	61
Figure 29 Entry Page of Pocket SCORM	62
Figure 30 Course List Received From LMS	62
Figure 31 Download a Cluster	63
Figure 32 The Clusters Downloaded at Client Device in Advance	63
Figure 33 Original Course Presentation Displayed on Pocket PC	64
Figure 34 Adapted Course Presentation Displayed on Pocket PC	64
Figure 35 Writing the Personal Notes	65
Figure 36 The Personal Note added on Course Page	65
Figure 37 Pocket SCORM Learning Interface on Smarthpone	66
Figure 38 System Architecture of Course Presentation Adaptation Authoring Tool	67
Figure 39 Uploading learning contents to on-line adaptation application	68
Figure 40 Adapting Content according to the pocket PC template	69
Figure 41 Select indexes of PUs to Eliminate the Insignificant Content	69
Figure 42 Course Presentation Adaptation for Smartphone	70
Figure 43 Previewing the adapted learning content with pocket PC simulator	71
Figure 44 Simulator Components	72
Figure 45 Select Device Specifications and Caching Mode	73
Figure 46 Load Testing Courses	74
Figure 47 Learning Sequencing Order Creator	75
Figure 48 Total Waiting Time (s) for Learning Photoshop_None Course	78
Figure 49 Internet Reconnection Frequency for Learning Photoshop_None Course	78
Figure 50 Total Waiting Time (s) for Learning Photoshop_KnowledgePaced	79
Figure 51 Internet Reconnection Frequency for Learning Photoshop_KnowledgePaced	79
Figure 52 Course Structure of Customized Course	80
Figure 53 Total Waiting Time (s) for Learning Customized Course	81
Figure 54 Internet Reconnection Frequency for Learning Customized Course	81
Figure 55 Accuracy of VMM Course Caching Strategy during Learning Customized Course	82
Figure 56 Accuracy of COD Course Caching Strategy during Learning Customized Course	82
 
List of Tables
Table 1 Loading Time of Display Online Learning Content with Smartphone	3
Table 2 Loading Time of Local Course with Smarthpone	4
Table 3 Common Cartridge supported resource types	44

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