跳到主要內容

臺灣博碩士論文加值系統

(54.224.117.125) 您好!臺灣時間:2022/01/26 15:33
字體大小: 字級放大   字級縮小   預設字形  
回查詢結果 :::

詳目顯示

: 
twitterline
研究生:區國良
研究生(外文):Kuo-Liang Ou
論文名稱:依據群體模組監控之網路群體學習系統
論文名稱(外文):Group model monitor on network group learning system
指導教授:陳國棟陳國棟引用關係
指導教授(外文):Gwo-Dong Chen
學位類別:博士
校院名稱:國立中央大學
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:2001
畢業學年度:89
語文別:中文
論文頁數:100
中文關鍵詞:群體學習機器學習資料尋礦溝通網路小組角色
外文關鍵詞:group learningmachine learningdata miningcommunication networkmember-roles
相關次數:
  • 被引用被引用:6
  • 點閱點閱:317
  • 評分評分:
  • 下載下載:37
  • 收藏至我的研究室書目清單書目收藏:4
現有建構在全球資訊網環境下的遠距教學系統,學生之間因為缺乏理想的即時面對面互動環境,容易導致學生在個別學習時缺乏同儕支援及同儕壓力;而面對網站上龐大的學習歷程,教師亦無法有效地加以處理、適時地觀察學習狀態並擬定教學策略來提升學習效能。
為了增加網路學習環境下的互動性、發揮群體學習環境下的同儕互助以及同儕壓力,並助教師分析學習歷程並建立學習模型,本論文提出了一個在全球資訊網環境下的群體學習系統,提供學生群體學習的環境與機制,並提供教師對於學習歷程知識探索及學習模型建構之工具,以滿足學生及教師在遠距教學生的需求。
本論文在輔助學生學習上,引用社會學中的群體學習理論、人際溝通網路及角色扮演模型,提供學生在網路群體學習時利用,並且針對異質分組、資源共享、溝通討論及專案合作上設計了各種模組以滿足學生在學習活動上之需求;在輔助教師教學上,則利用資料庫系統記錄學生的學習行為及互動關係,並採用資料尋礦及溝通網路分析技術來幫助教師觀察及分析學生的學習特徵及互動關係,並幫助教師依此尋找影響群體學習成效的因素,預測學習表現 ,提供教學策略決策時所需的資訊,進而有效提升學生在網路環境中之學習效果。
When constructing a web group learning system to foster peer collaboration, teachers must monitor the group’s learning status and encourage groups to learn without face-to-face communication. Therefore, an adaptive model for web group learning must be developed to facilitate peer collaboration and to assist teachers in monitoring the group learning status.
This thesis presents a method in which computer science approaches and social science analysis are incorporated to support students learning on Internet, and to assist teachers in identifying the group learning status. By becoming aware of group learning status extracted from group learning behavior and communication, teachers can more understand the relationships between group learning behavior and group learning performance, and the relationships between group communication and group learning performance. Fully integrating data mining techniques, information retrieval techniques, machine learning techniques and social network analysis enables teachers to cope with a large quantity of learning web logs and monitor group learning on the Internet.
The experiment results show the significant relationships between group communication and group learning performance and the relationships between member-roles and group learning performance. The results enable teachers to monitor and encourage the group learning on Internet.
COVER
CHINESE ABSTRACT
ABSTRACT
ACKNOWLEDGMENTS
CONTENTS
TABLES
FIGURES
CHAPTER 1 INTRODUCTION
1.1 BACKGROUND
1.2 MOTIVATION AND RESEARCH GOALS
1.3 ISSUES AND APPRACHES OF MONITORING GROUP MODEL ON NETWORK GROUP LEARNING SYSTEM
1.4 RELATED RESEARCHES
1.5 ORGANIZATION OF THIS THESIS
CHAPTER 2 GROUP LEARNING FEATURES SPACE FOR MONITORING GROUP LEARNING STATUS
2.1 RECORDING GROUP LEARNING BEHAVIOR ON WEB
2.2 ORGANIZING THE GROUP LEARNING FEATURE SPACE
2.3 USING ASSOCIATION RULES TO MONITOR GROUP LEARNING FEATURES
2.4 RESULTS AND DISCUSSION
2.5 SUMMARY
CHAPTER 3 CAUSAL NETWORK ANALYSIS FOR MONITORING GROUP LEARNING FEATURES
3.1 EXTRACTING THE COMMUNICATION TOPICS AND ABSTRACT
3.2 METHODOLOGICAL OVERVIEW
3.3 USING BAYESIAN BELIEF NETWORK ANALYSIS FOR EXTRACTING THE CAUSAL NETWORK OF GROUP LEARNING FEATURES AND LEARNING PERFORMANCE
3.4 PREDICTING GROUP PERFORMANCE FROM INITIAL GROUP DISCUSSIONS AND PORTFOLIO
3.5 DISCUSSION AND EXPERIENCE
3.6 SUMMARY
CHAPTER 4 EXTRACTING THE RELATIONSHIPS BETWEEN COMMUNICATION NETWORK AND GROU LEARNING PERFORMANCE
4.1 THE GROUP LEARNING COMMUNICATION NETWORK
4.2 METHODOLOGICAL OVERVIEW
4.3 RESULT AND EXPERIENCE
4.4 SUMMARY
CHAPTER 5 EXTRACTING THE RELATIONSHIPS BETGWEEN MEMBER ROLES AND GROU LEARNING PERFORMANCE
5.1 METHOD OVERVIEW
5.2 DETECTING THE MEMBER-ROLES ON WEB GROUP LEARNING ENVIRONMENT
5.3 RESULT AND EXPERIENCE
5.4 SUMMARY
CHAPTER 6 CONCLUSION
REFERENCES
[1]D. M. Adams, and M.E. Hamm, Cooperative Learning, Critical Thinking and Collaboration Across the Curriculum, Charles C Thomas Publisher, place, 1990.
[2]R. Agrawal, H. Mannila, R. Srikant, H. Toivonen, and I. Verkamo, Fast Discovery of Association Rules, Advances in Knowledge Discovery and Data Mining, publisher, pp. 307-328, 1996.
[3]V. Anantaraman, Group dynamics and the human relations organizational model, in Human resource management: concepts and perspective, (Anantaraman, V., Chong, L., Richardson, S. and Tan, C. eds). Singapore University Press, Singapore, 1984.
[4]C.J. Anderson, S. Wasserman, and B. Crouch, A p* primer: logit models for social networks. Social Networks, 21, pp. 37-66, 1999.
[5]L. Argote, Organizational learning: creating, retaining, and transferring knowledge. Kluwer Academic Publishers Group, MA, USA, 1999.
[6]G. Ayala and Y. Yano, A collaborative learning environment based on intelligent agents, Expert systems with applications, 14, pp.129-137, 1998.
[7]R. Baeza-Yates, and B. Ribeiro-Neto, Modern Information Retrieval. ACM Press, New York, 1999.
[8]T. Bayes, An Essay Toward Solving a Problem in the Doctrine of Chances, Philos. Trans. R. Soc. London, pp.370-418, 1763.
[9]R.M. Belbin, Management Teams. Wiley, New York, USA, 1981
[10]K.D. Benne, and P. Sheats, Functional roles of group members. Journal of Social Issues, 4:2, 41-49, 1948.
[11]B.J. Biddle, Role Theory: Expectations, Identities and Behaviors. Academic Press, New York, 1979
[12]B.B. Bnuker, and J.Z. Rubin, Introduciton — Conflict, Cooperation, and Justice. Conflict, Cooperation, and Justice. (Eds. Rubin, J.Z.) Joeesy-Bass Publishers, San Francisco, 1995.
[13]L.J. Bricker, S.L. Tanimoto, S.L., Rothenberg, A.I. Hutama, D.C. and T.H. Wong, Multiplayer Activityes that Develop Mathematical Coordination, Proceedings of CSCL, 95’ The First International Conference on Computer Support for Collaborative Learning, pp. 32-39, 1995.
[14]C.K. Chang, G.D. Chen, and K.L. Ou, Student portfolio analysis for decision support of Web based classroom teacher by data cube technology. Journal of Educational computing research, 19:3, pp. 307-328, 1998.
[15]C.K. Chang, G.D. Chen, K.L. Ou, and B.J. Liu, Student Portfolio Analysis for Decision Support of Web-Based Classroom Teacher by Data Cube Technology, Proceeding of ED-MEDIA/ED-TELECOM 98, pp.38-44, 1998.
[16]G.D. Chen, K.L. Ou, and C.C. Liu, Instructional Instruments for Grouping, Intervention, and Strategy Analysis on Web Group Learning Systems, Proceeding of International Conference on Compters in Education 99, pp.685-692, Japan, 1999.
[17]G.D. Chen, K.L. Ou, C.C. Liu, and B.J. Liu, B.J, Interventions and strategy analysis for web group-learning. Journal of Computer Assisted Learning, 17:1, pp.58-71, 2001.
[18]M. Chesler and R. Fox, Role-playing methods in the classroom. Chicago:Science Research Associates, 1966.
[19]B.A. Collis, T. Andernach, and N. Van Diepen, Web Environments for Group-Based Project Work in Higher Education. International Journal of Educational Telecommunications. 3:2 pp.109-130, 1997.
[20]B.A. Collis, Collaborative learning and CSCW: Research perspectives for interworked educational environments. Lessons from learning ,(R. Lewis and P. Mendelsohn, Eds.), pp. 81-104. Amsterdam: North-Holland, 1994.
[21]G.F. Cooper, The computational complexity of probabilistic inference using Bayesian belief networks. Artificial Intelligence, 42:3:, pp. 393-405, 1990.
[22]P Dagum, and M. Luby, Approximating probabilistic inference in Bayesian belief networks is NP-hard. Artificial Intelligence, 60:1, pp.141-153, 1993.
[23]H. Duin, and C. Hansen, C, Reading and writing on computer networks as social construction and social communication, Literacy and computers: The complications of teaching and learning with technology, New York: The Modern Language Association, pp. 89-112,1994.
[24]J. Elder, and D. Pregibon, A statistical perspective on KDD. Advances in Knowledge Discovery and Data Mining, (U. Fayyad, G. Piatetsky-Shapiro, P. Smyth, and R. Uthurusamy, Eds). AAAI/MIT Press, Cambridge, Mass., 1996.
[25]U. Fayyad, G. Piatetsky-Shapiro, and P. Smyth, From Data Mining to Knowledge Discovery: An Overview. Advances in Knowledge Discovery and Data Mining, Fayyad et. al. (Eds.) MIT Press, 1996
[26]L.C. Freeman, Turning a profit from mathematics: The case of social networks. Journal of Mathematical Sociology, 10, pp.343-360, 1984.
[27]L.C. Freeman, Visualizing social groups. Journal of social structure, Electronic journal: http://www.heinz.cmu.edu/project/INSNA/joss/index1.html, 1:1, 2000.
[28]A.S. Gertner, C. Conati, and K. VanLehn, Procedural Help in Andes: Generating, Hints Using a Bayesian Network Student Model. AAAI/IAAI, pp. 106-111, 1998.
[29]J. Han, Y. Fu, W. Wang, J. Chiang, W. Gong, K. Koperski, D. Li, Y. Lu, A. Rajan, N. Stefanovic, B. Xia, and R. Zane, DBMiner: A System for Mining Knowledge in Large Relational Databases. Proceeding of KDD 1996, pp.250-255, 1996.
[30]L. Harasom, S.R. Hiltz, L. Teles, and M. Turoff, Learning Networks. MIT press, Cambridge, Massachusett, USA, 1995.
[31]K. Heap, Group theory for social workers: an introduction. Oxford: Pergamon Press, 1977.
[32]E. Heeren, Technology support for collaborative distance learning. CTIT Doctoral Thesis Series No. 96-08. Centre for Telematice and Information Technology (CTIT), University of Twente, Enschede, The Netherlands, 1996.
[33]S. Henry, Group Skills in Social Work: a four dimensional approach, Pacific Grove, Ca.: Brooks/Cole Publishing Co, 1992.
[34]S.M. Henry and K.T. Stevens, Using Belbins’ leadership role to improve team effectiveness: An empirical investigation. The journal of systems and software, 44 241-250, 1999
[35]D.W. Johnson, and R.T. Johnson, Cooperation and Competition: Theroy and Research. Communication Book Company. Minnesota, USA, 1989.
[36]D.W. Johnson, and R.T. Johnson, Learning together and alone (5th ed.). Allyn and Bacon Publishing, Massachusetts, USA, 1991
[37]D.W. Johnson, and R.T. Johnson, Meaningful and Manageable Assessment through Cooperative Learning. Communication Book Company, Minnesota, USA, 1996.
[38]H.F. Kaiser, The varimax criterion for analytic retation in analysis. Psychometrika, 23, pp.187-200, 1958.
[39]M. Kamber, J. Han, and J. Chiang, Metarule-Guided Mining of Multi-Dimensional Association Rules Using Data Cubes. Proceeding of KDD 1997, pp.207-210, 1997.
[40]J.L. Keedy, Examining teacher instructional leadership within the small group dynamics of collegial groups, Teaching and Teacher Education, 15:7,pp.785-799, 1999
[41]L. Kimball, Ten Ways to Make Online Learning Groups Work. Educational Leadership, October 1995.
[42]A. King, Verbal communication and problem-solving within computer-assisted cooperative learning groups. Journal of Educational Computing Research, 5:1, pp.1-15, 1989.
[43]H. Knowles, and M. Knowles, Introduction to group dynamics. New York: Association Press, 1959.
[44]P. Langley, W. Iba, and K. Thompson, An analysis of Bayesian classifier. In Proceedings of the National Conference on Artificial Intelligence, pp. 223-228, 1992.
[45]H.T. Lau, Algorithms on Graphs, TAB Books Inc. PA, USA, 1989.
[46]P.R. Laughlin, and J.M. Barth, Group-to-individual and individual-to-group problem-solving transfer. Journal of Personality and Social Psychology, 41, pp.1087-1093, 1981.
[47]J. Lave, and E. Wenger, Situated learning: legitimate peripheral participation. Cambridge, UK: Cambridge University Press, 1991.
[48]Y. Lin and M.J. Druzdzel, Computational advantages of relevance resoning in Bayesian Belief Networks, Proc. of thirteenth annual conference on uncertainty in artificial intelligence (UAI-97), pp. 342-350, 1997.
[49]C.C. Liu, G.D. Chen, K.L. Ou, B.J. Liu, and J.T. Horng, Managing Activity Dynamics of Web Based Collaborative Applications. International Journal of Artificial Intelligence Tools, 8:2, 2000.
[50]J.E. McGrath, and A.B. Hollingshead, Putting the “Group” Back in Group Support Systems: Some Theoretical Issues About Dynamic Process in Group with Technological Enhancements. Group Support Systems. (Jessup, L.M. and Valacich, J.S. editors.) Macmillan Publishing Company, USA, 1993.
[51]D. Michie, D.J. Spiegelhalter, and C.C. Taylor, Machine learning, neural and statistical classification, New York: Ellis Horwood, 1994.
[52]F. Milson, An Introduction to Group Work Skill, London: Routledge and Degan Paul, 1973.
[53]T.M. Mitchell, Bayesian Learning, Machine Learning, The McGraw-Hill Companies, pp.154-200, 1997.
[54]J.M. Monaghan, and J. Clement, Use of Collaborative Computer Simulation Activities to Facilitate Relative Motion Learning, Proceedings of CSCL, 95’ The First International Conference on Computer Support for Collaborative Learning, pp. 242-246, 1995.
[55]MSBN (Microsoft Belief Network Tools) developed by Microsoft, URL is http://www.research.microsoft.com/research/msbn/.
[56]M. Plutowski, S. Sakata, and H. White, Cross-Validation Estimates Integrated Mean Squared Error, Advances in Neural Information Processing Systems, (J. Cowan, G. Tesauro, and J. Alspector, eds.) San Francisco: Morgan Kaufmann, pp.391-398, 1994.
[57]K.L. Ou, C.K. Chang, and G.D. Chen, Web-based Asynchronous Discussion System. Proceeding of International Conference on Computers in Education, pp.108-117, 1998.
[58]K.L. Ou, G.D. Chen, and B.J. Liu, A Group Learning Environment in a Virtual Classroom Built on WWW. Proceeding of 6th International Conference on Computer Assisted Instruction, 1997
[59]J. Pearl, Probabilistic reasoning in intelligent systems: Networks of plausible inference. San Mateo, CA: Morgan-Kaufmann, 1988.
[60]J.R. Quinlan, C4.5 Programs for machine learning, Morgan Kaufmann Publishers, San Mateo, California, 1993.
[61]J.R. Quinlan, Boosting, Bagging, and C4.5, Proceedings of the Thirteenth National Conference on Artificial Intelligence, pp. 725-730, 1996.
[62]J. Rabow, M.A. Charness, J. Kipperman, and S. Radcliffe-Vasile, William Fawcett Hill’s Learning through discussion, (3rd) pp.1-7. Sage Pub. CA. U.S.A., 1994.
[63]M. Ramoni, and P. Sebastiani, Discovering Bayesian Networks in Incomplete Databases, Technical Report KMi-TR-46, Knowledge Media Institute, The Open University, March, 1997.
[64]M. Ramoni, and P. Sebastiani, An introduction to the Robust Bayesian Classifier. Kmi Technical Report Kmi-TR-79, Knowledge Media Institute, The Open University, Milton Keynes, 1999.
[65]W. Reinhard, J. Schweitzer, and G. Volksen, CSCW Tools: Concepts and Architectures, IEEE Computer, May, pp.28-36, 1994.
[66]T. Reponen, Is leaderships possible at loosely coupled organization such as university ? Higher Education Policy, 12, pp.237-244, 1999
[67]L. Resnick, Knowing, learning and instruction. Hillsdale, NJ, 1989.
[68]M. Riel, Educational change in a technology-rich environment, Journal of Research on Computing in Education, 26:4, pp.452-474, 1994.
[69]S. Robbins, Organizational behavior: concepts, controversies and applications, Prentice Hall: Englewood Cliffs, NJ, USA, 1991.
[70]G. Salton, and C. Buckley. Text Weighting Approaches in Automatic Text Retrieval. Cornell University Technical Report, pp.87-881, 1987.
[71]M. Scardamalia, C. Bereiter, R.S. McLean, J. Swallow, and E. Woodruff, Computer-supported intentional learning environment. Journal of Educational Computing Research, 5, 51-68, 1989
[72]S.B. Seidman, and B.L. Foster, SONET-I: social network analysis and modeling system. Social Networks. 2, pp.85-90, 1978.
[73]J.X. Shi, The Chinese Full Text Retrieval Tools for Network Information and Learning System. Master Thesis of National Central University, 2000.
[74]P.G. Shotsberger, K.B. Smith, and C.G. Spell, Collaborative Distance Education on the World Wide Web: What Would That Look Like?, Proceeding of the First Computer Support for Collaborative Learning, (eds. John L. S., and Edward L. C.) pp.312-316, 1995.
[75]B.G. Silverman, Computer supported collaborative learning (CSCL), Computers Education, 25:3, pp.81-91, 1995.
[76]R.E. Slavin, Cooperative learning: Theory, research, and practice. Egnlewood Cliffs, NJ: Prentice Hall, 1990.
[77]B.M.H. Soong, H.C. Chan, B.C. Chua, and K.F. Loh, Critical success factors for on-line course resources. Computers & Education, 36 , pp.101-120, 2001.
[78]D.J. Spiegelhalter, A.P. Dawid, S.L., Lauritzen, and R.G. Cowell, R. G., Bayesian Analysis in Expert Systems, Statistical Science, 8, 219-283, 1993
[79]P. Spirtes, and C. Meek, Learning Bayesian Networks with Discrete Variables from Data. Proceeding of Knowledge Discovery and Data Mining, pp.294-299, 1995.
[80]SPSS developed by SPSS Inc., URL is http://www.spss.com/
[81]G. Stasser, Pooling of Unshared Information During Group Discussion, Group Process and Productivity, (Worchel, S., Wood, W., and Simpson, J.A. editors), Sage publications, USA, 1992.
[82]G. Stasser, and W. Titus, Effects of information load and percentage of shared information on the dissemination of unshared information during group discussion. Journal of Personality and Social Psychology, 53, pp.81-93, 1987.
[83]R. Sternberg, Thinking Styles , Cambridge University Press,1997.
[84]R. Slavin, Research on cooperative learning and achievement: what we know, what we need to know. Contemporary educational psychology, 21:1, 43-69, 1996.
[85]J. Sommerville, and S. Dalziel, Project teambuilding — the applicability of Belbin’s team-role self-perception inventory. International Journal of Project Management. 16:3. 165-171, 1998.
[86]G.L. Stewart, C.C. Manz, and H.P. Sims, Team Work and Group Dynamics, pp.81-90. John Wiley & Sons, Inc. USA, 1999.
[87]K. Stott, and A. Walker, Team Roles. Teams: teamwork & teambuilding. Prentice Hall: Englewood Cliffs, NJ, USA, 1995.
[88]J.S. Thousand, R.A. Villa, and A.I. Nevin, Creativity and Collaborative Learning- a practical guide to empowering students and teachers. Paul H Brookes Publishing, Baltimore, MD. USA, 1994.
[89]D. Tkach, Text Mining Technology — Turning Information Into Knowledge. A White paper from IBM. URL is http://www-4.ibm.com/software/data/iminer/fortext/library.html), 1998.
[90]A. Udvari-Solner, A Decision-Making Model for Curricular Adaptaitons in Cooperative Groups. Creativity and Collaborative Learning, Paul.H. Brookes Publishing, 1994.
[91]L.S. Vygotsky. Mind in society, Cambridge, MA: Harvard University Press, 1978.
[92]M. Waugh, Group communication and student questioning patterns in an instructional telecommunications course for teachers, Journal of computers in mathematics and science teaching, 15:4, pp. 353-382, 1996.
[93]N.M. Webb, Peer communication and learning in small groups. International Journal of Educational Research, 13:1, pp. 21-29, 1989.
[94]S. Wasserman, and K. Faust, Social network analysis: methods and applications. Cambridge University Press, NY, USA, 1994.
[95]S. Wasserman, and P. Pattison, Logit models and logistic regressions for social networks: I. An introduction to Markov random graphs and p*. Psychometrika, 60, pp.401-426, 1996.
[96]P. Watzlawick, J. Beavin, D. Jackson, Pragmatics of Human Communication: A Study of Communicational Patterns, Pathologies & Paradoxes. NY: W.W. Norton, 1967.
[97]M. X. Zaïane. and J. Han, Discovering Web Access Patterns and Trends by Applying OLAP and Data Mining Technology on Web Logs. Proceedings of Advances in Digital Libraries Conference, (ed. R.S. Terence), pp.19—29. IEEE Press, Los Alamitos, CA, USA, 1998.
QRCODE
 
 
 
 
 
                                                                                                                                                                                                                                                                                                                                                                                                               
第一頁 上一頁 下一頁 最後一頁 top
1. 1、丁希如(1998),「租書店的新經營型態」,出版界,第55卷,1998
2. 岳修平(民88)。網路教學於學校教育之應用。課程與教學季刊,2(4),61-76。
3. 林慧貞(民88)。隔空教育學習者支持系統初探。成人教育,48,36-43。
4. 林奇賢(民87)。網路學習環境的設計與應用。資訊與教育雜誌,67,34-50。
5. 李麗君(民85a)。隔空教育理念之析論。隔空教育論叢,8,109-129。
6. 尹清海(民87)。教育部推動遠距教學與終身學習之現況。資訊與教育,66期,2-8。
7. 王曉璿(民87)。網路環境與教學應用。教師之友,39(1),7-13。
8. 王唯孝(2000)。網路服務的新趨勢─智慧型資訊代理搜尋程式。網際先鋒February2000,102-105。
9. 王政彥(民88)。利多或利空?網際網路自我學習的前景。成人教育,52,46-52。
10. 吳明隆(民87)。電腦網路學習特性及其相關問題的省思。教育部電子計算機中心簡訊,8709,23-39。
11. 陳年興、楊子青、賴宏仁(民86)。以網際網路為基礎之學習環境。電腦學刊,9(2),667-674。
12. 張瓊瑩(民82)。從成人參與學習理論兼述隔空教學的涵義。教學科技與媒體,9,23-30。
13. 楊家興(民82)。超媒體:一個新的學習工具。教學科技與媒體,12,28-39。
14. 楊家興(民88)。虛擬學校:資訊網路下整合性的教學環境。教學科技與媒體47:12-23。
15. 楊國德(民88)。網路學習的趨勢與策略。成人教育,45,53-54。