隨著網際網路日益發達，網路學習己逐漸成為新的學習趨勢，在非同步遠距教學的環境中，因為無法直接面對面教學，使得當學生人數日益增加的時候，老師將很難掌握每個學生的狀況， 更難以利用其中隱含的資訊。本論文針對學生評鑑模式下，利用貝式定理進行分析，結合圖形結構，將學生針對作品的評鑑資訊建模，提供老師圖形化的觀察，並由系統分析推估其他學生或是學生其他的評鑑資訊。本研究主要在建置以學生歷程資訊為基礎之學生模型，並可應用至推薦、診斷、學生知識狀態的推估，以幫助教師教學提升學習成效。

With the advance of Internet technology, learning on-line has become one of the most common as well as popular ways to knowledge. However, in the environment of Asynchronous distance learning, it is difficult for teachers to have in hands all the students’ individual learning conditions and unrevealed information without face-to-face communication, especially when the numbers of students increase day by day. With the focus on student assessment model analyzed with Bayesian method, and the combining of graphic structure, this paper attempts to set up a system to model students’ assessment information, providing graphic vision to teachers, and moreover analyze and estimate other students’ assessment information (or their other assessment information). In short, this paper aims to build up a student model based on student portfolio, which can further apply to individual homework assignments, diagnoses of students’ learning problems, inference of students’ learning condition, and thus promotes teachers’ teaching performance.

元 智 大 學 1
資 訊 工 程 研 究 所 1
碩 士 論 文 1
指導教授：劉晨鐘 博士 1
研 究 生：鄭乃塵 1
目錄 I
圖形索引 II
表格索引 III
第一章 緒論 1
1.1研究背景與動機 1
1.2研究目標 6
1.3 問題與對策 7
1.4 論文架構 11
第二章 相關研究與技術 12
2.1 學生模式(STUDENT MODEL) 12
2.2 貝式網路(BAYESIAN NELIEF NETWORK) 13
2.3 交互信息(MUTUAL INFORMATION) 17
第三章 系統設計 20
3.1 個人構念結構擷取 21
3.2資料來源 23
3.3建立結構模組(STRUCTURE MODULE) 25
3.3.1 建立結構的方法 — Mutual Information Ranking 26
3.3.2 計算機率關係的方法 — Estimation 28
3.4 結構的應用 37
第四章 系統實作 40
4.1系統目的 40
4.2系統功能設計 40
第五章 實驗結果與討論 44
5.1 實驗環境與對象 44
5.2 實驗流程 44
5.3 數據評估 45
第六章 結論 52
參考文獻 53

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