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系統識別號 U0026-0812200913351570
論文名稱(中文) 應用智慧型技術於網路學習系統
論文名稱(英文) Applying Intelligent Techniques to Web Learning System
校院名稱 成功大學
系所名稱(中) 工程科學系碩博士班
系所名稱(英) Department of Engineering Science
學年度 95
學期 1
出版年 96
研究生(中文) 陳瑞男
研究生(英文) Juei-Nan Chen
學號 n9890112
學位類別 博士
語文別 英文
論文頁數 129頁
口試委員 口試委員-林志敏
口試委員-施國琛
指導教授-黃悅民
口試委員-朱治平
口試委員-朱正忠
口試委員-游寶達
口試委員-楊錦潭
中文關鍵字 動態模糊派翠網  數位學習  資料探勘  知識分享  人類專家論壇系統  標準化課程產生流程  SCORM  軟體代理人  模糊資訊擷取  人工智慧  FP增長  FP樹  跨階層經常性樣板 
英文關鍵字 Data Mining  Cross-level Frequent Pattern  Fuzzy Information Retrieval  Human-expert Forum System  FP-tree  FP-growth  Artificial Intelligence  Standardized Course Generation Process  Knowledge Sharing  Dynamic Fuzzy Petri Net  SCORM  e-Learning  Software Agent 
學科別分類
中文摘要 本研究目的在於利用智慧型技術於數位學習研究領域。目前而言,大部份數位學習之研究在於,如何將現實生活的學習行為成功的轉移至數位學習環境,或是探討如何開發一個符合國際標準 – SCORM相容的網路教學平台。然而,不同於這些研究方向,本研究著重於利用智慧型技術來幫助學習者以及教師簡化其工作並提升其學習成效。本論文將以這個主題,分成以下項目來探討:(1)利用動態模糊派翠網於數位學習系統之應用;(2)利用動態模糊派翠網技術產生標準化課程流程;(3)以模糊資訊擷取技術開發一智慧型人類專家論壇系統;(4)跨階層經常性樣板探勘於數位學習之應用領域。
在本論文的第三章中,系統提供老師一個利用動態模糊派翠網製作的數位教材編輯工具,用於規劃其課程學習路徑圖,而該規劃的結果會依據每個學生的學習反應給予不同的學習路徑,系統會依照每個學生的學習成效給予相對應的學習課程章節內容,如此一來,學生便可依照老師的規劃進行引導式學習。然而,系統中存在許多的學習課程單元,老師無法逐一找尋其彼此之間的相關性,因此,本論文在第四章延伸上述之研究方法,自動地在系統中找尋相關輔助課程提供老師規劃課程時參考,此外,第四章也提出一個符合SCORM國際標準的課程產生流程及系統架構,使得產生出來的多媒體課程內容得以與其他標準化平台交流共享。
近年來,網路上出現越來越多的論壇系統,用以提供使用者上網討論問題或是心得交流,論壇問題交流的最大優點在於使用者可利用自然語言的表達方式進行提問或是答覆的動作,因此,許多學生會透過論壇來進行學習交流或是討論,本論文的第五章探討以專家使用者輔助之論壇系統,用以進行群體合作學習,該部份利用模糊資訊擷取的技巧來找尋網路論壇中相關議題的專家使用者,並邀請該專家使用者進行問題的答覆。一旦學生找到令其疑惑的癥結點之後,便可於學習管理系統中找尋相關的議題內容進行學習,本論文的第六章提出一個跨階層經常性樣板探勘的方法,該資料探勘之結果可提供學習者更多樣性的學習參考建議,不同於其他階層經常性樣板探勘方法,於多階層式概念架構中,本方法提供之探勘結果包含較抽象偏高階的學習建議,亦或較具體偏低階之學習內容均可。
英文摘要 The purpose of this dissertation is concerning the applications of artificial intelligence in e-Learning domain. The majority of e-Learning research is putting such web learning system into practice, or standardizing a SCORM conformable learning system environment. However, different from those researches, this study focuses attention on applying artificial intelligence technique to facilitate learners and lecturers simplifying their works and enhancing learning effects. This dissertation may consider the subject under the following heads: (1) applying Dynamic Fuzzy Petri Net to an e-learning system; (2) Standardized Course Generation Process using Dynamic Fuzzy Petri Nets; (3) an intelligent human-expert forum system based on fuzzy information retrieval technique; (4) a method of cross-level frequent pattern mining for web-based instruction.
This research in Chapter 3 provides an authoring tool, which is model by DFPN (Dynamic Fuzzy Petri Net), and LMS (Learning Management System) to provide lecturers mapping out their course learning map. Therefore, the learners can study the whole concept of a certain course based on the course learning map and their learning result. The lecturer needs to arrange some auxiliary learning materials to assist learners when they get into trouble. However, there are too many SCOs (Sharable Content Objects) in the system, and the lecturer cannot easily find out the interrelations between each learning material. Therefore, the research in Chapter 4 extends the above research and provides lecturer finding out the relevant auxiliary learning materials automatically. Furthermore, a SCGP (Standardized Course Generation Process) is also introduced in Chapter 4. By means of this automatic process, standardized courses not only correspond to the SCORM standard but also arrange adaptive auxiliary materials dynamically. The generated multimedia course is interoperable, reusable, and standardized.
Recently, there are more and more online forum systems for problem solving and discussion. The most important benefit of these forum systems is users can receive the tailored answers from peers by formulating the problem with natural language. Especially in e-Learning field, learners often announce their problems on the forum system and communicate their comments subjectively. Therefore, the research in Chapter 5 introduces a human-expert oriented forum system for collaborative learning. The system uses fuzzy information retrieval techniques to discover important discussion knowledge and actively invites human-experts who may answer the question to participate the discussion. Following that, learners can indicate the crux of the problem by the human-experts’ advisements. Hence, they can precisely search their needs in LMS (Learning Management System). The research in Chapter 6 introduces a cross-level frequent pattern mining methodology for further study. It collects all of users’ learning access data which connote a hierarchical scheme to provide cross-level learning suggestions for the next learning course. With this system, a learner can get multiple levels of abstract suggestions instead of merely single level frequent pattern mining results.
論文目次 摘 要 II
Abstract IV
誌 謝 VI
TABLE OF CONTENTS VII
LIST OF TABLES X
LIST OF FIGURES XII

CHAPTER 1 INTRODUCTION 1
CHAPTER 2  RESEARCH BACKGROUND 4
CHAPTER 3  APPLYING DYNAMIC FUZZY PETRI NET TO AN E-LEARNING SYSTEM 7
3.1 Dynamic Fuzzy Petri Net 8
3.1.1 Formal Definitions and the Proposed Model 8
3.1.2 Dynamic Fuzzy Production Rules 10
3.1.3 Extend DFPN’s Constraints to incorporate Browsing Time, Browsing Count and Related Time Limit 12
3.1.4 Generating Tokens 14
3.2 Dynamic Fuzzy Petri Net Reasoning Algorithm 16
3.3 Example Case 20
3.4 Evaluations 28
CHAPTER 4 STANDARDIZED COURSE GENERATION PROCESS USING DYNAMIC FUZZY PETRI NETS 30
4.1 Standardized Course Generation Process 31
4.1.1 Learning Resource Management System 33
4.1.2 Agent-based Navigational Training System 35
4.1.3 Mobile E-learning Authoring Tool 37
4.1.4 Material Arrangement Agent 39
4.2 Extended DFPN Model 41
4.3 Course Design by using DFPN Reasoning Algorithm and the Extended Model 44
4.4 Example Case 45
4.5 Evaluations 51
CHAPTER 5 AN INTELLIGENT HUMAN-EXPERT FORUM SYSTEM BASED ON FUZZY INFORMATION RETRIEVAL TECHNIQUE 56
5.1 Human-Expert Oriented Forum System 59
5.1.1 Discussion Knowledge Search Engine 60
5.1.2 Discussion Repository 60
5.1.3 Human-Expert Set Discover Mechanism 61
5.1.4 Knowledge-based Forum System 61
5.2 Definitions and Methodologies 62
5.2.1 Definitions 63
5.2.2 Terms Correlation Matrix 66
5.2.3 Fuzzy Term-Document Membership Degree 66
5.2.4 Fuzzy Query Term Expansion 67
5.2.5 Fuzzy Query 68
5.2.6 Expert-Term Correlation Matrix 69
5.2.7 Candidate Human-Expert Discovery 70
5.3 Dynamic Maintenance 71
5.3.1 Incrementally Update of Term Correlation Matrix 72
5.3.2 Maintenance of Expert-Term Correlation Matrix 73
5.3.3 The Example of Maintenance Expert-Term Correlation Matrix 75
5.4 Experimental Results 76
CHAPTER 6 A METHOD OF CROSS-LEVEL FREQUENT PATTERN MINING FOR WEB-BASED INSTRUCTION 89
6.1 Taxonomy of the Curriculum Scheme 92
6.2 FP-tree Construction 96
6.3 Mining Association Rules using the FP-tree 100
6.4 Experimental Results 105
6.4.1 The Average Length of each Sequential Transaction 105
6.4.2 The Upgrading Proposition of each Level 106
6.4.3 Confidence Analysis 107
6.4.4 The Accuracy between Multiple Support Threshold and Single Support Threshold 108
6.5 Discussion 110
CHAPTER 7 CONCLUSIONS AND PERSPECTIVES 115

REFERENCE 118
自述 126
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