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系統識別號 U0026-2703201815332400
論文名稱(中文) 探討新翻轉教室的學習成效並建構考量社群資訊之學習型主題地圖
論文名稱(英文) Exploring the Effects of the In-flip Classroom and Considering Social Information in Constructing Learning Topic Maps
校院名稱 成功大學
系所名稱(中) 工業與資訊管理學系
系所名稱(英) Department of Industrial and Information Management
學年度 106
學期 2
出版年 107
研究生(中文) 蔣昱弘
研究生(英文) Yu-Hung Chiang
學號 r38001019
學位類別 博士
語文別 英文
論文頁數 65頁
口試委員 口試委員-林懿貞
口試委員-莊宗嚴
口試委員-高宏宇
口試委員-王維聰
口試委員-劉任修
指導教授-王惠嘉
中文關鍵字 In-flipped Learning  混合式學習  大學教室環境量表  文字探勘  主題地圖  社群資訊 
英文關鍵字 In-flipped Learning  Blended Learning  College and University Classroom Environment Inventory  Topic Map  Text Mining  Social Information 
學科別分類
中文摘要 隨著資訊科技的發達,教學科技媒體運用愈來愈普遍,數位學習也愈來愈興盛。如何藉由資訊科技的便利性和其不受時空限制的特色,改進教師教學和增進學生學習,已經成為當今教育發展的重要議題。翻轉教室(flipped classroom)是一種特定類型的混合學習環境,允許學習者在課堂外藉助於資訊科技的學習,並於上課時間與老師和同學們互相交流學習上的問題。雖然翻轉教室有許多的優點,但仍有一些問題有待改進。因此,本研究設計出一個新穎的教學方式(In-flipped Learning),以克服現有翻轉教室中所產生的問題,並在碩士課程中的資料庫之課程中使用大學教室環境量表(College and University Classroom Environment Inventory, CUCEI)來評估學習者們的學習成效。
此外,如何應用多元的線上資訊來幫助學生補充及完備所需要的課程相關知識並幫助學習是為教學領域中重要的研究議題之一。因此,本研究將進一步地應用研討會資訊 (視為線上資訊中的一種) 作為課程的教學輔助資源,並結合於In-flipped Learning教學環境中。然而,線上非結構化的資訊會隨著時間持續快速地增加,要在混雜且大量的資訊中有效地找到學生所需要的學習內容並連結問題間複雜概念的關係是相當困難的。因此,本研究應用知識管理之概念對線上資訊進行進一步的分析。藉由設計一套自動分析線上與教學知識有關內容的主題地圖,並結合文字探勘技術將研討會資訊進行分類,並以本研究所提出之主題地圖建構方法找出資料集中的主題間的關聯性,視覺化後供學習者查詢與瀏覽並完成建構主題地圖之知識本體。期望藉此主題地圖提供學生在in-flipped learning的環境中獲得更完整的學習資源與參考資料,並提高其學習成效與表現。
英文摘要 Information technology (IT) has led to changes in teaching methods. How to improve teaching effectiveness and enhance students’ learning using IT has become an important issue. A “flipped” classroom is a blended learning environment that allows learners to study outside the classroom using IT and then interact with the teacher inside the classroom. Although flipped classrooms have many advantages, some issues, such as low motivation prior to lectures, remain and should be improved. This study proposes an in-flipped classroom to overcome the problems found in flipped classrooms and evaluates this type of classroom using a Database Engineering course in a master’s program. This study uses the College and University Classroom Environment Inventory (CUCEI) to investigate the learning performance of the proposed in-flipped teaching environment.
Moreover, how to apply diverse online information to help students acquire knowledge relevant to course work is an important research issue. This study adopts conference information, a kind of online information, as a teaching assistant resource for in-flipped classrooms. However, as the amount of unstructured and messy conference information expands rapidly, it becomes increasingly difficult for students to find the content they need and understand the relationships between complex areas of knowledge. Therefore, it would be helpful to design topic maps that can automatically analyze conference knowledge information and relevant content. This study classifies course topics using text mining technology and then extracts the relationships between topics using the proposed method. Finally, topic maps are visualized to help students easily query and browse information. The proposed method is expected to provide students with more complete learning resources and improve their learning performance.
論文目次 Chapter 1. Introduction 1
1.1 Research background and motivation 1
1.2 Research purposes 6
1.3 Research scope and limitations 8
1.4 Research procedure 9
Chapter 2. Literature Review 11
2.1Traditional Education 11
2.2 Problem-Based Learning 12
2.3 Collaborative Learning 12
2.4 E-learning 13
2.5 Blended Learning and flipped learning 14
2.6 Ontology and Topic Maps 15
2.6.1 The Topic Maps model 15
2.6.2 Construction methods of Topic Maps 16
2.6.2 Classification resource - Open Directory Project (ODP) 17
2.6.3 Evaluation of Topic Maps 18
2.7 Social Information 19
2.8 Summary 20
Chapter 3 Research Methodology 21
3.1 Research Framework 21
3.2 Academic Context and In-flipped Setting of Database Engineering 22
3.3 Data Collection and Design in In-flipped Classroom 22
3.4 Research Architecture of Topic Maps 24
3.5 Data Collection Module 27
3.6 Topic Maps Element Extraction Module 29
3.6.1 Topic Extraction 29
3.6.2 Association Extraction 31
3.6.3 Occurrence Extraction 35
3.7 Social Information Analysis Module 35
3.8 Topic Map Visualization Module 36
3.9 Summary of Topic Maps 37
Chapter 4. Implementation and Verification 38
4.1 Analysis Results for In-flipped Classroom 38
4.2 Implementation and Evaluation of Topic Maps 42
4.2.1 Source and Experimental Methods 42
4.2.2 Analysis of weights and coverage rates 47
4.2.3 Analysis of subjective evaluation 48
4.2.4 Performance of All Associations 50
4.2.5 Example of System Interface 50
Chapter 5. Discussion and Conclusion 52
5.1 Conclusions of In-flipped Classroom 52
5.2 Conclusions for topic maps 53

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