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Student Number 88522007
Author Jian-Xiang Ni(倪家祥)
Author's Email Address No Public.
Statistics This thesis had been viewed 1614 times. Download 845 times.
Department Computer Science and Information Engineering
Year 2000
Semester 2
Degree Master
Type of Document Master's Thesis
Language zh-TW.Big5 Chinese
Title 以網站行為的歷程建立具時間性學習者模式
Date of Defense 2001-06-28
Page Count 61
Keyword
  • 學習者模式
  • 序列探勘
  • 時序
  • 決策樹
  • 遠距教學
  • Abstract 由於網際網路之盛行,許多教師在網路上建立學習系統,使得學生可以在任何地點與時間上課。網際網路的另一個優點是學生在網路上的學習資料隨著時間變化完整地被記錄下來,因此可以用過去學生的學習歷程(Portfolio)與時序上的考量來作為觀察與預測學生成就的依據。然而這個工作要處理到許多的網站上站記錄,要觀察到他們與學習成就之間的關係是相當費時費力的。而老師的教學策略隨時影響著學生的學習行為改變,了解教學策略與學習歷程影響關係,可以幫助老師觀察學生及教學策略擬定的參考,而老師要從網站紀錄得知這些資訊也是相當費時和困難的。
    在這篇論文中,我們著力於建構具時間性的學習者模式中的兩個模組,(1)利用Dual model架構,將學生在網路學習環境中具時間性的學習行為歷程及學習成果等學習變數以Decision Tree的形式表示而成的學習成就預測模型 (2) 由老師平常所執行的教學策略和學生在網站上的學習行為歷程,以序列探勘(Sequential Pattern Mining)方法分析教學策略與學生學習行為改變的影響。
    本論文所建構的具時間性的學習者模式可以做到(1)幫助老師從學生的學習行為歷程中即時預測學生的學習狀況,若發現學習成果可能不佳的學生,老師可即早給予輔助。(2)幫助老師觀察其教學策略對於學生學習行為的影響,包含觀察和比較不同程度學生對於教學策略的學習行為改變狀況以及個別學生對於教學策略的學習行為改變狀況,以做為老師輔助學生依據及教學策略擬定的參考。
    Table of Content 目錄I
    圖形索引III
    表格索引IV
    第 1 章 緒論1
    1-1 研究背景與動機1
    1-2 研究目標3
    1-3 問題與對策4
    1-4 論文架構5
    第 2 章 相關研究與技術7
    2-1 學習者模式7
    2-2 作品集評量9
    2-3 DUAL MODEL架構12
    2-4 決策樹(DECISION TREE)14
    2-4-1 Decision Tree簡介14
    2-4-2 操作Decision tree的工具15
    2-5 序列探勘(SEQUENTIAL PATTERN MINING)16
    第 3 章 具時間性學習者模式的建立17
    3-1 學習者模式及系統架構圖17
    3-2 推測模型18
    3-2-1 資料的收集與整理19
    3-2-2 連續資料的離散化與時間點的切割20
    3-2-3 建立Decision Tree之結構20
    3-2-4 協調整合預測模型系統22
    3-2-5 成果範例23
    3-3 教學策略影響分析26
    3-3-1 資料整理26
    3-3-2 資料均線化與變化量處理 ( Delta )28
    3-3-3 序列探勘 ( Mining Sequential Patterns )29
    3-3-4 萃取序列規則32
    3-3-5 成果範例32
    第 4 章 教師輔助觀察系統34
    4-1 學習狀況預測系統35
    4-2 學生行為趨勢觀察系統38
    4-2-1 學生行為趨勢觀察系統之群體觀察系統38
    4-2-2 學生行為趨勢觀察系統之個人觀察系統39
    第 5 章 實驗結果與討論41
    5-1 測試資料環境與來源41
    5-2 預測模型及其正確率(TRAINING DATA)42
    5-3 驗證推測模型44
    5-4 教學策略影響討論45
    第 6 章 結論47
    參考文獻48
    附錄一51
    附錄二57
    Reference [1]陳國棟,劉寶鈞,張智凱“建立於全球資訊網上之虛擬教室之討論系統“ The 5th International Conference on Computer Assisted Instruction 1996 pp.16-23
    [2]Arter, J. A., V. Spandel and R. Culham, Portfolios For Assessment And Instruction, ERIC Digest: EDO-CG-95-10, 1995
    [3]Bark Cheung Chiu, Geoffrey I. Webb, Dual-Model: An Architecture for Utilizing Temporal Information in Student Modeling, 7th International Conference on Computers in Education,1999
    [4]Barrett, H. Collaborative Planning for Electronic Portfolios: Asking Strategic Questions, National Educational Computing Conference, June, 1997.
    [5]Burton, R. B., Diagnosing bugs in a simple procedural skill. In D.Sleeman & J. S. Brown(Eds.), Intelligent Tutoring Systems, London: Academic Press, 1982.
    [6]C. K. Chang, and G. D. Chen, “Student portfolio analysis for decision support of Web based classroom teacher by data cube technology” Proceedings of Education Multimedia and Education telecom 1998 Friburg Germany .
    [7]Chen-Chung Liu, Gwo-Dong Chen, Chin-Yeh Wang “Student modeling for performance assessment using Bayesian network on web portfolios”, Journal of Educational Computing Research
    [8]Chi, M.T.H, R. Glaser and E. Rees, Expertise in problem solving. In R.J. Sternberg(Ed.) Advances in the Psychology of Human Intelligence, Vol. 1, 1982.
    [9]Clementine at http://www.isl.co.uk/
    [10]Feigenbaum, E. A., McCorduck, P., and Nii, H. P. The Rise of the Expert Company. New York: Times Books. ,1998
    [11]Fletcher, J.D., Modeling of learner in computer-based instruction, Journal of Computer-Based Instruction, vol. 1, pp. 118-126, 1975.
    [12]Gürer, D. W., M. desJardins, and M. Schlager. Representing a Student's Learning States and Transitions. In the 1995 AAAI Spring Symposium on Representing Mental States and Mechanisms, Stanford, CA; published as a AAAI technical report.
    [13]IBM DB2 Intelligent Miner for Data. In http://www-4.ibm.com/software/data/iminer/fordata/
    [14]Jiawei Han, Micheline Kamber, Data Mining : Concepts and Techniques, MORGAN KAUFMANN PUBLISHERS , 2001
    [15]Marsha Leeman-Conley, The How and the Why of Electronic Portfolios in Higher Education, Technology in Education International Conference 1999.
    [16]Microsoft SQL Server 2000-Analysis Services develop by Microsoft at http://www.microsoft.com/sql/techinfo/BI/analysis.asp
    [17]Mitrovic, A., S. Djordjevic-Kajan, L. Stoimenov, INSTRUCT: Modeling Students by Asking Questions. In User Modeling and User-Adapted Interaction, Vol. 6, No. 4, pp. 273-302, 1996.
    [18]Perkowitz, M., O. Etzioni: Adaptive Web Sites: an AI Challenge, In proceeding of the 17th International Joint Conferences on Artificial Intelligence, Vol. 1, pp. 16-23, 1997.
    [19]portfolio system at Illinois State University, URL at http://portfolio.ilstu.edu/
    [20]Quinlan, J. R. C4.5 Programs for machine learning, Morgan Kaufmann Publishers, San Mateo, California, 1993.
    [21]Stiggins, Richard J. Student-Centered Classroom Assessment, New York: Merrill Publishing Co, 1994
    [22]Tekinerdogan, B, Design of a Reflective Tutoring System Shell. Technical rreport:ITSSEL-95-4 in Memorandum of Dep. Of Computer Science, University of Twente, 1995
    [23]Tom M. Mitchell , Machine Learing , McGRAW-HILL INTERNATIONAL EDITIONS,1997
    [24]TopClass develop by WBT Systems at http://www.wbtsystems.com/
    [25]VanLehn, K., Student modeling. In M. Polson & Richardson(Eds), Foundations of Intelligent Tutoring Systems, Hillsdale, 1988.
    [26]Virtural-U developed by Simon Fraser University at http://www.vlei.com
    [27]WebCT: World Wide Web Course Tools at http://www.webct.com
    [28]Wolf, D. (1989). Portfolio assessment: Sampling student work, Educational Leadership, 46, 35-37.
    [29]Wolf, Kenneth; Siu-Runyan, Yvonne Portfolio purposes and possibilities, Journal of Adolescent & Adult Literacy, Sep96, Vol. 40 Issue 1, p30, 8p, 3 charts
    Advisor
  • Gwo-Dong Chen(陳國棟)
  • Files
  • 88522007.pdf
  • approve immediately
    Date of Submission 2001-06-28

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