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研究生:楊家偉
研究生(外文):Chia-Wei Yang
論文名稱:設計以語意為基礎的知識管理系統以支援不同的知識類型與適性化學習
論文名稱(外文):Designing a Semantic-based Knowledge Management System to Support Different Types of Knowledge and Adaptive Learning
指導教授:黃旭立黃旭立引用關係
指導教授(外文):Shiu-Li Huang
學位類別:碩士
校院名稱:銘傳大學
系所名稱:資訊管理學系碩士班
學門:電算機學門
學類:電算機一般學類
論文種類:學術論文
論文出版年:2008
畢業學年度:96
語文別:英文
論文頁數:94
中文關鍵詞:知識管理適性化學習知識本體語意網社會軟體合作式學習
外文關鍵詞:collaborative learningadaptive learningknowledge managementsocial softwareSemantic Webontology
相關次數:
  • 被引用被引用:2
  • 點閱點閱:360
  • 評分評分:
  • 下載下載:100
  • 收藏至我的研究室書目清單書目收藏:1
知識可以擁有不同的類型與觀點。此外,一個學習管理系統能否改善學習成效的關鍵在於能否提供適合學習者學習目標和知識水準的教材。目前已有許多以維基或部落格為基礎的知識管理系統,但現在的維基與部落格平台無法支援多種知識類型和適性化學習。本研究的目的在於設計一個以語意為基礎的知識管理系統來處理這些問題。本研究開發一個新的社會軟體平台,整合了部落格與維基平台,並採用語意網技術來組織知識的類型與知識本體以支援多種知識類型。為了幫助適性化學習,系統提供一個書籍的功能,使用者可以藉由後設認知知識與協同的方式編排書籍的章節與順序,並設定符合需求的內容與難易度,以產生一本具有適性化學習路徑的書籍。本研究安排一項實驗以評估這個系統,評估指標包含知識的種類數、學習的成效和系統的滿意度。實驗的結果顯示本系統包含多種的知識類型,可以幫助學習者提升學習的成效並獲得高度的使用滿意度。
Knowledge may have different types and viewpoints. Additionally, a learning management system adapts learning materials to learners’ learning objectives and to knowledge levels is crucial to improving their learning performance. Many wiki and blog platforms have been used to support knowledge management, but they cannot support different types of knowledge and adaptive learning. This research aims to design a semantic-based knowledge management system to tackle these problems. To support various types of knowledge, this research develops a new social software platform that combines blog with wiki platforms and adopts Semantic Web technology to organize knowledge types and ontology. To aid adaptive learning, a function called Book is provided that allows learners to arrange book chapters and sequences, and to set learning contents and difficulty degrees according to their metacognitive knowledge and collaborative activities. An experiment is conducted to evaluate this system and the experimental results show that this system comprehends various types of knowledge, is able to improve users learning performance and has high satisfaction ratings.
Chapter 1 Introduction 1
1.1 Research Background 1
1.2 Research Motivation 2
1.3 Research Objectives 5
Chapter 2 Literature Review 6
2.1 Knowledge Perspectives 6
2.2 Knowledge Types 10
2.2.1 Knowledge Taxonomy Summarized by Alavi and Leidner 11
2.2.2 Knowledge Taxonomy Summarized by Anderson and Krathwohl 14
2.2.3 Summary of Knowledge Types 17
2.3 E-learning 19
2.3.1 Adaptive Learning 20
2.3.2 Collaborative Learning 22
2.3.3 Learning Path 25
2.4 Social Software 26
2.5 Semantic Web 30
2.5.1 Ontology Language 30
2.5.2 Semantic-based KMS 34
Chapter 3 System Architecture 37
3.1 Main Functions 37
3.1.1 Supporting various knowledge types 37
3.1.2 Supporting adaptive and collaborative learning 45
3.2 Other Functions 47
Chapter 4 System Evaluation and Result 50
4.1 Experimental Procedure 50
4.2 Experimental Results 53
4.2.1 Analysis of learning performance 53
4.2.2 Analysis of adaptive learning performance 62
4.2.3 Analysis of collaborative learning performance 66
4.2.4 Analysis of satisfaction with system 68
4.2.5 Analysis of knowledge types 71
Chapter 5 Conclusion 74
References 76
Appendix 83
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