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研究生: 張家榮
論文名稱: 以電子筆書寫之特徵分析學生人格特質及輔助教師調整國中數學適性化教學策略之研究
Using digital-pen handwriting traits to analyze students’ personological and assist teachers to adapt teaching on junior high school mathematical course
指導教授: 區國良
口試委員:
學位類別: 碩士
Master
系所名稱: 南大校區系所調整院務中心 - 應用數學系所
應用數學系所(English)
論文出版年: 2008
畢業學年度: 96
語文別: 中文
論文頁數: 121
中文關鍵詞: 人格特質筆跡學機器學習決策樹貝氏網路
外文關鍵詞: personological attributes, graphology, machine learning, decision tree, Bayesian network
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  • 對於學生而言,學習成效除了教師素質與教材內容有關之外,根據學者研究學習成效與人格特質之間存在著關連性,對於教師瞭解學生人格特質將有助於提升學生學習效果,使用筆跡學之理論建立人格特質分析系統,採用機器學習技術來建立預測模組,並分析筆跡特徵與人格特質之間的關連性,以協助教師隨時掌握學生人格特質資訊,進而調整教學策略與輔導方式以達適性化教學目標。
    本論文建構具有人格特質判斷分析系統,包含一套記錄數位筆跡之工具與一套筆跡特徵分析之系統,採用了40種筆跡特徵以及四種人格特質,其中記錄數位筆跡之工具能重複使用並同時多人進行參與測驗;筆跡特徵分析之系統具有33項全自動化與6項半自動化分析筆跡特徵,測驗完後人格特質判斷分析系統將能立即給予教師回饋,與傳統筆跡測量方式相比,大大縮短人力與時間上的問題。
    本論文研究分析採用機器學習技術,使用決策樹與貝氏網路兩種方法,決策樹幫助教師快速判斷學生人格特質與分類規則,並以圖形方式表示讓教師清楚明瞭,進而探討筆跡特徵與人格特質之間的關連性;而貝氏網路則判斷筆跡特徵與人格特質之間的因果關係,作為筆跡治療法提供之依據,提出輔助方法以協助教師事後改善調整學生缺乏或過度之人格特質。


    Recent researches indicated that there exist relationships between students’ personality characteristic and learning performance. Therefore, teachers need to detect students’ personality characteristic and then promote students to learn in an efficient way. This paper established a system for teachers to detect and analysis students’ personality characteristic with graphology theory and machine learning technology.
    Two machine learning technologies were employed in this research: decision tree and Bayesian network. The decision tree assists teachers to predict students’ personality by the classification rules. It also illustrates the relationships between handwriting traits and personality graphlicaly. Meanwhile, the Bayesian network assists teachers to explore the causal relationship of handwriting traits and personality graphicaly. Therefore teachers can improve students to learn by considering students’ personality effects.
    The result illustrates that there were 40 kinds of handwriting traits and 4 kinds of personality characteristics extracted succefully in a short time. Thus, teachers can reduce the efforts to detect student’s personality characteristics by using this system, and then adjust his/her teaching strategy for adating students to learn.

    1. 緒論 1 1.1. 研究動機與背景 1 1.2. 研究目的 3 1.3. 研究問題 4 2. 相關研究 6 2.1. 適性化教學 6 2.2. 人格特質與數學表現關係 8 2.3. MBTI人格測量表 10 2.4. 筆跡研究 21 2.4.1. 筆跡 21 2.4.2. 筆跡學 23 2.4.3. 筆跡與人格關係 25 2.4.4. 筆跡測量之信度與效度 28 2.4.5. 筆跡特徵 31 2.4.6. 筆跡治療法 43 2.5. 機器學習 47 3. 研究方法及研究工具 51 3.1. 研究流程 51 3.2. 研究對象及限制 52 3.3. 筆跡樣本內容 53 3.4. 建構記錄數位筆跡之工具 54 3.5. 分析筆跡特徵之系統 67 4. 實驗結果 76 4.1. 筆跡記錄工具 76 4.2. 筆跡特徵萃取工具 83 4.3. 決策樹分析結果及應用 85 4.3.1. 決策樹分析結果 85 4.3.2. 筆跡特徵與人格特質關係 88 4.4. 貝氏網路分析結果及應用 88 5. 結論與建議 88 5.1. 結論 88 5.2. 後續研究建議 88 參考文獻 88 附錄 88

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