臺灣博碩士論文加值系統

雲端運算(Cloud Computing)已經被視為下一產業的重要商機，隨著技術的發展，使用者對於網際網路的使用模式也正在改變中，雲端運算背後隱含龐大商機，國際科技大廠與網路服務商紛紛加入雲端運算的領域。然而，許多研究並未針對學生使用雲端運算進行評估與討論，因此，本研究結合雲端運算服務與學生為研究為主題，以學生學習成績作為評估依據，使用不同評估指標對雲端運算服務進行調查，並以灰色理論(Gray System Theory)中的灰關連排序(Grey Relational Analysis, GRA)來探討這些雲端運算服務對學生學習成績的重要性評比；並依據灰關聯排序之結果，進行灰色多屬性決策分析(Grey Multiple Attribute Decision Analysis, GMADA)探討雲端運算服務之評估與選取最佳方案。灰關聯排序之結果顯示雲端硬碟、雲端文書處理與雲端閱讀相較於其他雲端運算服務對學生的較為重要；而灰色多屬性決策分析之結果在雲端硬碟中最佳方案為4shared；雲端文書處理中最佳方案為Google Docs；雲端閱讀中最佳方案為Google Reader。最後，針對研究結果加以分析與討論。

Cloud computing is seen as an important industrial business opportunity, as the development of technology facilitates the changing usage patterns of Internet users. Huge business opportunities lie in the field of cloud computing as the major players of international science and technology and Internet service providers enter the domain of cloud computing. However, most studies fail to evaluate and discuss how students use cloud computing. Therefore, using the integration of cloud computing services and students as the research subjects, this study applied different evaluation indicators to investigate cloud computing services, as based on student academic achievements. Moreover, we apply GRA (Grey Relational Analysis) of the gray system theory to discuss the importance rating of the impact of such cloud computing services on student academic achievements. According to grey relational sorting results, this study employed the GMADA (Grey Multiple Attribute Decision Analysis) to explore the best solution for the evaluation and selection of cloud computing services, and conducted analysis and discussion regarding the conclusions.

中文摘要 I
Abstract II
致謝 III
目錄 IV
表目錄 VI
圖目錄 VII
第一章 緒論
1.1 研究背景 1
1.2 研究動機與目的 2
1.3 研究架構 4
第二章 文獻探討
2.1 雲端運算(Cloud Computing) 6
2.1.1 雲端運算的興起與演進 6
2.1.2 雲端運算的定義 8
2.1.3 雲端運算的五大特徵 11
2.1.4 雲端運算的三大服務模式 13
2.1.5 雲端運算的四大佈署模型 15
2.1.6 雲端運算的優勢與挑戰 17
2.1.7 雲端運算目前的應用 20
2.1.8 雲端與教育 22
2.2 灰色理論 24
2.2.1 灰色理論之概念 24
2.2.2 灰色理論之研究範疇 25
2.2.3 灰色理論之相關研究 26
2.3 多屬性決策 28
2.3.1 多屬性決策之概念 28
2.3.2 多屬性決策方法的種類 30
第三章 研究方法
3.1 灰關連排序 33
3.2 灰色多屬性決策 36
第四章 資料分析與討論
4.1灰關聯排序之結果 40
4.1.1 研究設計與衡量 40
4.1.2資料分析 41
4.1.3結果 47
4.2灰色多屬性決策之結果 48
4.2.1 研究設計與衡量 48
4.2.2資料分析 49
4.2.3結果 56
第五章 結論與建議
5.1研究結論 58
5.2後續研究之建議 60
參考文獻 61
附錄 67

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網站及網路資料
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