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研究生:吳梓煊
研究生(外文):Tzu-Hsuan Wu
論文名稱:利用派翠網路建立學習診斷模型以進行學習回饋
論文名稱(外文):Applying Petri Net to Building Learning Diagnostic Model for Providing Learning Feedback
指導教授:賀嘉生賀嘉生引用關係
指導教授(外文):Jia-Sheng Heh
學位類別:碩士
校院名稱:中原大學
系所名稱:資訊工程研究所
學門:工程學門
學類:電資工程學類
論文種類:學術論文
論文出版年:2006
畢業學年度:94
語文別:中文
論文頁數:70
中文關鍵詞:學習回饋知識地圖迷思概念診斷學習模型派翠網路
外文關鍵詞:Learning FeedbackPetri NetKnowledge MapLearning ModelMisconception Diagnosis
相關次數:
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隨著網際網路與電腦科技的進步,線上的虛擬教室能對傳統教學提供了更多樣化的輔助工具。藉由遠距教學技術的發展,可以將相關的學習技術與理論應用在線上的學習平臺,如學生的迷思概念診斷,或學習回饋等。而這些應用主要的目的,即為增進學生在線上學習的成效。

本論文中提出了以派翠網路去模擬學生在學習活動的學習過程之模型,並在該學習活動模型上加入了回饋的機制。在回饋機制中,回饋有兩種方式:一種為基本回饋,回饋給學生的訊息為一些基本學習資訊,如學習活動名稱、活動進行時間等;另一種為進階回饋,除了前面所提到的基本學習資訊外,此回饋亦會提供與學習課程內容相關的訊息。除此之外,也根據學習過程模型與回饋機制模型設計了一學習計劃表給教師,方便教師設定學習活動模型的流程控制與回饋的參數。

根據以上的學習流程模型與回饋機制,本論文進行了以迷思概念診斷為回饋訊息的進階回饋實驗,主要為分析回饋是否有效,以及回饋方式對不同程度學生的效果。以T檢定的方式對不同實驗分組間進行檢定以驗證假設。並以偏序圖表示進行檢定後所產生的矩陣,以看出各實驗組別間的關係。實驗的結果證實回饋確實對學生學習有效,且回饋次數越多回饋效果越顯著。並發現基本回饋較適合程度好的學生,而進階回饋對程度較差的學生成效較為顯著。
Because of the speed development of Internet and computer science, virtual classrooms on Internet provide more various assistant tools for the traditional classroom. These assistant tools, such as learning feedback and learning diagnosis, could help teachers managing student’s learning status and give students more efficient information when they finish a stage of learning. In short, these learning techniques applied in e-learning platform are used for enhancing the learning effect of students.

This thesis proposed a method for modeling the learning process of students. Petri net is used for presenting the process of learning activities. A feedback service module is also designed in this research. The feedback service gives two types of feedback function. One is basic feedback function, which sends basic learning information to students, such as learning activity name, activity time, and so on. The other is advanced feedback function, which not only supports basic learning information but also offers part of learning material data.

To make this feedback service easy for teachers to operate, a friendly interface is important in the system design aspect. The learning planner is developed for this purpose and has a control panel for managing parameters in both learning process and feedback service. This learning planner could help teachers operating feedback services of different learning activities and give students information about their learning progress.

In the end, this learning process model with feedback service is experimented and integrated with misconception diagnosis as the advanced feedback information. The main purpose of this experiment is to analyze if the feedback is effective to students and which kind of feedback function is suitable for different grades of students. The analysis method used in this research is T-test, which is used for verifying the effect of feedback; and partial ordering graph, which is used to observe the result of the data tested by T-test.

Two major results are found in these analyses. One is that the effect of feedback would be more notable when the feedback service is given continuously. The other shows that the two types of feedback function, the tips of basic feedback and the diagnostic misconception of advanced feedback, have different effect to students of different grades.
目錄
摘要 I
Abstract II
圖目錄 VI
表目錄 VIII
第一章 緒論 1
1.1 研究動機與目的 1
1.2 論文貢獻 2
1.3 論文架構 2
第二章 文獻探討 3
2.1 電腦輔助教學 3
2.1.1 傳統教學與網路教學 3
2.1.2 遠距教學的實作與應用層次 3
2.1.3 學習回饋 3
2.2 派翠網路(Petri Nets) 5
2.2.1 派翠網路理論 5
2.2.2 派翠網路架構 5
2.2.3 派翠網路傳遞規則 6
2.3 學習概念診斷方法 8
2.3.1 概念圖與知識地圖 8
2.3.2 概念階層(Concept Hierarchy) 8
2.3.3 概念基模(Concept Schema) 10
2.3.4 試題之知識結構 11
2.3.5 隱含概念矩陣與計算 12
2.4 問題探討 14
第三章 學習活動模型與回饋機制 15
3.1 派翠網路於學習活動模型之應用 15
3.1.1 學習活動流程 15
3.1.2 派翠網路基本元件之對應 16
3.1.3 派翠網路的實際應用 17
3.2 學習活動模型之回饋機制 19
3.2.1 學習回饋分析 19
3.2.2 回饋模型 19
3.2.3 回饋事件之規則庫 21
3.3 學習計劃表 23
3.3.1 學習計劃表之設計 23
3.3.2 學習計劃表之實際應用 25
第四章 學習診斷分析與系統設計 28
4.1 學習迷思概念診斷 28
4.2 系統架構與流程 33
4.3 演算法 35
4.3.1 迷思概念診斷演算法 35
4.3.2 回饋訊息演算法 37
第五章 系統展示與實驗結果分析 41
5.1 實驗對象與實驗設計 41
5.2 實驗系統展示 43
5.3 實驗結果分析 47
5.3.1 回饋次數與回饋效果之數據分析 49
5.3.2 回饋方式與學生程度之數據分析 51
5.3.3 以偏序圖表示之數據分析 54
第六章 結論 57
6.1 結論與研究限制 57
6.2 未來工作 57
參考文獻 58
中文文獻 58
英文文獻 59

圖目錄
圖2.1 派翠網路模組架構 5
圖2.2 一對一傳遞規則 6
圖2.3 一對多選擇傳遞規則 6
圖2.4 一對多平行傳遞規則 6
圖2.5 多對一選擇傳遞規則 6
圖2.6 多對一平行傳遞規則 7
圖2.7 知識的網路結構[COQ69] 9
圖2.8 元素物質的概念階層圖 9
圖2.9 元素物質的知識地圖 11
圖2.10 概念階層 12
圖3.1 學習的次序 15
圖3.2 學習次序的分岔 15
圖3.3 範例:學習活動流程 16
圖3.4 學習的狀態 16
圖3.5 學習的事件 17
圖3.6 具方向性的線段 17
圖3.7 學生狀態的轉移 17
圖3.8 測驗之派翠網路模型 18
圖3.9 回饋模組之派翠網路模型.20
圖3.10 學習流程控制 (C 為CHECK POINT) 23
圖3.11 回饋之派翠網路模型 24
圖3.12 學習活動測驗之派翠網路 26
圖4.1 診斷流程 29
圖4.2 概念Θ之概念階層 31
圖4.3 系統架構圖 33
圖4.4 系統使用流程圖 34
圖5.1 系統登入畫面 43
圖5.2 學習計劃表的管理介面 44
圖5.3 學習活動的新增畫面 44
圖5.4 學生所見學習計劃表之學習活動 45
圖5.5 基本回饋訊息(與課程內容無關) 46
圖5.6 進階回饋訊息(與課程內容相關) 46
圖5.7 前次錯誤概念比例 47
圖5.8 本次錯誤概念比例 47
圖5.9 錯誤概念比例變化 .47
圖5.10 X 組之範例 48
圖5.11 Y 組之範例 48
圖5.12 分析1─有回饋組(501, 503, 505, 506)與 49
圖5.13 分析1─無回饋組(502, 504)與基本回饋組(501, 506)與進階回饋組(503, 505) 49
圖5.14 分析1─以班級為組 49
圖5.15 分析2─有回饋組(501, 503, 505, 506)與 50
圖5.16 分析2─無回饋組(502, 504)與基本回饋組(501, 506)與進階回饋組(503, 505) 50
圖5.17 分析2─以班級為組 50
圖5.18 分析3─有回饋組(501, 503, 505, 506)與 51
圖5.19 分析3─無回饋組(502, 504)與基本回饋組(501, 506)與進階回饋組(503, 505) 51
圖5.20 分析3─以班級為組 51
圖5.21 分析3A─有回饋組(501, 503, 505, 506)與 52
圖5.22 分析3A─無回饋組(502, 504)與基本回饋組(501, 506)與進階回饋組(503, 505) 52
圖5.23 分析3A─以班級為組 52
圖5.24 分析3B─有回饋組(501, 503, 505, 506)與 52
圖5.25 分析3B─無回饋組(502, 504)與基本回饋組(501, 506)與進階回饋組(503, 505) 52
圖5.26 分析3B─以班級為組 52
圖5.27 分析3C─有回饋組(501, 503, 505, 506)與 53
圖5.28 分析3C─無回饋組(502, 504)與基本回饋組(501, 506)與進階回饋組(503, 505) 53
圖5.29 分析3C─以班級為組 53
圖5.30 分析3.4─有回饋組(501, 503, 505, 506)與 53
圖5.31 分析3.4─無回饋組(502, 504)與基本回饋組(501, 506)與進階回饋組(503, 505) 53
圖5.32 分析3.4─以班級為組 54
圖5.33 組別互相T 檢定後的矩陣 54
圖5.34 偏序圖 54
圖5.35 分析1 之偏序圖─以班級為組 55
圖5.36 分析2 之偏序圖─以班級為組 55
圖5.37 分析3 偏序圖─以班級為組 56

表目錄
表2.1 元素物質的概念基模 10
表2.2 概念資料表 12
表2.3 EMBEDDED CONCEPT MATRIX, ECM 13
表2.4 CUMULATIVE EMBEDDED CONCEPT MATRIX, CECM 13
表3.1 學習計劃表範例 25
表3.2 學習計劃表範例 27
表4.1 CUMULATIVE EMBEDDED CONCEPT MATRIX, CECM 28
表4.2 學生答題矩陣A(Q) 29
表4.3 試題中隱含概念矩陣CECM 29
表4.4 轉換後的A(Q) 30
表4.5 學生錯誤概念矩陣Σ(Q) 30
表4.6 試卷概念累加矩陣CCD(Q) 30
表4.7 錯誤概念比例矩陣ER(Q) 31
表4.8 迷思概念比例矩陣Θ(Q) 32
表4.9 演算法1 35
表4.10 演算法1 之範例 36
表4.11 概念缺乏度語句對應表 37
表4.12 演算法2 38
表4.13 演算法2 之範例1 39
表4.14 演算法2 之範例2 (接續演算法1─範例1) 39
表5.1 實驗計劃 42
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