Applying adaptive strategies of course caching and presentation to enhance m-learning environment

機構典藏 > College of Engineering > Graduate Institute & Department of Computer Science and Information Engineering > Thesis > Item 987654321/35106

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Title:	Applying adaptive strategies of course caching and presentation to enhance m-learning environment
Other Titles:	應用可調式內容呈現與課程快取策略於行動學習環境
Authors:	張玄菩;Chang, Hsuan-pu
Contributors:	淡江大學資訊工程學系博士班施國琛;Shih, Timothy K.
Keywords:	行動學習平台;課程快取;可調式課程內容呈現;SCORM，課程切割;多重課程版本;m-learning;SCORM;Common Cartridge;Adaptive Presentation;Course Caching;SCORM Sequencing and Navigation;Course Segmentation
Date:	2008
Issue Date:	2010-01-11 06:01:39 (UTC+8)
Abstract:	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.
Appears in Collections:	[Graduate Institute & Department of Computer Science and Information Engineering] Thesis

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