雲端環境下普適學習輔助之智慧型導引機制;Cloud-Based Intelligent Tutoring Mechanism for Pervasive Learning

NCUIR > College of Electrical Engineering & Computer Science > Department of Computer Science and information Engineering > Research Project > Item 987654321/49676

Please use this identifier to cite or link to this item: http://ir.lib.ncu.edu.tw/handle/987654321/49676

Title:	雲端環境下普適學習輔助之智慧型導引機制;Cloud-Based Intelligent Tutoring Mechanism for Pervasive Learning
Authors:	施國琛
Contributors:	資訊工程系
Keywords:	pervasive learning;adaptive delivery;cloud computing;context prefetching;personalization;asynchronous caching;location-aware;研究領域：科學教育
Date:	2011-04-01
Issue Date:	2012-01-17 19:07:28 (UTC+8)
Publisher:	行政院國家科學委員會
Abstract:	隨著知識經濟時代的來臨，人類對於知識的渴望亦與日俱增。藉由資訊傳輸科技的發展與可攜式裝置的普及，數位學習不僅跳脫了以往時間與空間的限制，更使研究人員獲得了開放的環境及強大的雲端運算能力來進行相關服務的開發。本團隊承襲著過去於數位學習工具開發之實務經驗，希望藉由此次產學合作計畫之執行，更加強化於普適學習活動之支援。本計劃旨在開發三個主要的核心機制：非同步資料快取（Asynchronous Caching）機制、適性化學習資源傳送（Adaptive Delivery）機制以及內容調適（Context Prefetching）機制。非同步快取機制藉由背景排程的方式，使學習資源從後端資料庫下載時亦可同時對其內容進行閱覽；適性化資源傳送則著重於當下情境（如地理資訊、時間…等外部資訊）之判斷來傳遞個人化學習內容；最後，透過內容可調式機制來對所取得之學習資源進行重點萃取，並按照使用者所持之裝置來進行內容之調整。透過以上三種機制於雲端上之運算，藉以優化普適學習之環境。本技術將於國科會相關單位的同意下轉移給合作廠商並執行後續的產品製作，同時，所開發之應用程式將可於Android Market 中免費下載供使用者進行後續測試。With coming of the age of Knowledge Economy, the desire to knowledge has been growing gradually. The e-Learning not only escapes from the limitation of time and space but allows researchers to develop related services via an open and powerful environment (i.e. Cloud Computing) through development of information communication technique and popularity of portable devices. Followed by the experiences on development of tools related to e-Learning, our group aims at strengthening the supports to Pervasive Learning through this industry-academy project. Three core mechanisms, Asynchronous Caching, Adaptive Delivery, and Context Prefetching, will be presented and developed through implementation of the project. The first mechanism takes advantage of background scheduling to allow partial content processing and downloading in parallel way. The second one pays more attention on personalization services provision in accordance with situation such as location, time, and any external information. The last one then emphasizes on reorganizing the content through context extraction to fit the screen of client device. We try to optimize the pervasive learning environment through processing of mechanisms mentioned above on the cloud-based environment. The know-how will be transferred to partner, MINE Co., to proceed the commercial products under agreement of National Science Council, Taiwan. Meanwhile, the pre-released implementation can also be downloaded and tested from Android Market for free. 研究期間：10004 ~ 10103
Relation:	財團法人國家實驗研究院科技政策研究與資訊中心
Appears in Collections:	[Department of Computer Science and information Engineering] Research Project

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