研究生: |
簡嘉建 Chia-Chien Chien |
---|---|
論文名稱: |
建構在語意網上之分散式電子化學習物件分享機制:以「物料需求規劃」之學習為例 Constructing the Mechanism of Distributed e-Learning Objects Sharing Based on the Semantic Web : Learning“Material Requirements Planning”as An Example |
指導教授: |
朱 詣 尹
Yee-Yeen Chu |
口試委員: | |
學位類別: |
碩士 Master |
系所名稱: |
工學院 - 工業工程與工程管理學系 Department of Industrial Engineering and Engineering Management |
論文出版年: | 2003 |
畢業學年度: | 91 |
語文別: | 中文 |
論文頁數: | 99 |
中文關鍵詞: | 電子化學習 、語意網 、本體論 |
外文關鍵詞: | e-Learning, Semantic Web, Ontology |
相關次數: | 點閱:2 下載:0 |
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在資訊時代,學習不是奠基在擁有的資訊量,而是取決於將資訊形成連接的「連接數」。電子化學習可以幫助瀏覽這些連結,最後並形成競爭優勢。電子化學習可由網路促成學習策略,當網路上充滿著各式各樣的學習資源,要找到「合適」的教材來教學或學習,有兩項要件:(1) 學習資源如何精確地描述它所提供的內容? (2) 何謂對學習者「合適」的教材?
本論文以語意網之發展機制為藍圖,提出一個在分散式的環境下學習資源分享的機制。這機制包括建構領域知識本體論和學習物件本體論,並實作在語意網上,且以此來精確地描述學習物件,並間接地說明分散的學習物件之間的關聯。而透過此機制的產生,與學習理論做結合,探討其伴隨而起的相關應用,包括學習/教學情境的模式化、協同學習和知識管理。並以系統化的方法整合現有的資訊技術,建立一屬於分散式環境的以代理人為基之智慧學習管理雛型系統,並以物料需求規劃(Material Requirements Planning)為學習領域,來具體地呈現前述概念的實作情形。
In the age of Information, learning depends less on the amount of information one has than on the number of connections one can form and reform to link information. It is the navigation of these linkages that can facilitate the e-Learning and ultimately constitutes competitive advantage. e-Learning strategy may be contributed by the Web, but the question is how to get the learning materials which is distributed on the web to teach or learn. To meet the requirements above, we need to (1) describe learning material precisely and (2) adapt them to learners.
This paper introduced a mechanism of distributed e-Learning objects sharing based on the Semantic Web. The mechanism included construcing domain knowledge ontologies and learning object ontology which were implemented on the Semantic Web, and using them to describe learning materials precisely and to disclose the relationships between distributed learning materials indirectly. Forthemore this study related the mechanism to other possible applications taken in the field of learning including learning/instruction modeling, collaborative learning and knowledge management. Finally, the study provided a prototypical agent-based Intelligent Learning Management System, and demonstrated the use with learning “Material Requirements Planning” as an example.
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