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    题名: 以開放式申論題為主之輔助教學系統
    Intelligent Tutoring System Based on Open-Ended Questions
    作者: 廖君興
    Liao, Chun-Hsin
    贡献者: 李蔡彥
    張俊彥

    Li, Tsai-Yen
    Chang, Chun-Yen

    廖君興
    Liao, Chun-Hsin
    关键词: 開放式申論題
    智慧型輔助教學
    open-ended question
    Intelligent Tutoring
    日期: 2009
    上传时间: 2010-12-08 12:01:00 (UTC+8)
    摘要: 本研究的目的,是在實作一個以開放式問答題的作答方式為基礎的線上輔助學習系統,藉以提升評量及學習的效果。我們選定的問題領域在地球科學,以極光的發生為例,將問題所涉及的觀念進一步拆解細分成許多小觀念,建立階層化使用者知識模型,以評估學生於各個觀念的分別表現。學生於作答時,系統會即時分析學生的答案,以評估學生在各觀念的表現,並在適當的時機提供回饋,嘗試協助學生思考原本未能答好的觀念。我們以不同的回饋時機及回饋內容為獨立變因,嘗試瞭解對使用者答題表現的影響。我們也以個案分析的方式將學生的對於系統學習態度分類,藉以瞭解不同類型學生對此類系統的接受程度。我們認為此系統可以提供學生作答歷程予教學者進行分析,用以找出學生缺漏的觀念,進而協助提升教學效果。
    The purpose of this research is to use an open-ended based on-line learning system to improve the effects of evaluation and learning. We set the question domain at Earth Science. Taking the occurrence of polar lights, we divide the related concept into many small concepts, and build the hierarchical user knowledge model to evaluate student’s reactions to each concept. While students take the test, the system will analyze the answers to evaluate the students, and provide feedbacks timely to help the student think over the missing concept. Taking the different feedback timing and feedbacks as independent factors, we try to understand the influence to the users’ performance. By using case study, we classify the students’ learning attitudes to understand the different types of students’ acceptance of this system. We think that this system can provide student’s answering process to teachers for analyzing. By using this, teachers can find out students’ missing concept and to provide teaching effectiveness.
    參考文獻: [1] C.C. Huang, H.C. Wang, T.-Y. Li and C.Y. Chang, “An Online Testing and Analysis System for Students’ Creative Problem-Solving Ability in Sciences,” in Proceedings of the Tenth Global Chinese Conference of Computers in Education, China, 2006.
    [2] H.C. Wang T.Y. Li, C.C. Huang, and C.Y. Chang, “VIBRANT: A Brainstorming Agent for Computer Supported Creative Problem Solving,” in PM. Ikeda, K. Ashley, and T.-W. Chan (Eds.): Italic, LNCS 4053, pp. 787 – 789, 2006.
    [3] H.-C. Wang, T.-Y. Li, & C-Y. Chang, “A user modeling framework for exploring creative problem-solving ability,” in Proceedings of 12th International Conference on Artificial Intelligence in Education, pp. 941-943, 2005.
    [4] H.-C. Wang, T.-Y. Li, & C-Y. Chang, “Automated scoring for creative problem solving ability with ideation-explanation modeling,” in Proceedings of 13th Interna-tional Conference on Computers in Education, 2005.
    [5] S. Carberry, “Techniques for Plan Recognition,” User Modeling and User-Adapted Interaction, 2001.
    [6] C.-C. Huang, C.-Y. Chang, T.-Y. Li, and H.-C. Wang, “A Collaborative Support Tool for Divergent Thinking: Idea Storming Cube,” in Proceedings of 2008 Annual International Conference of National Association for Research in Science Teaching, 2008.
    [7] R. Kumar, C. Rose, V. Aleven ,A. Iglesias & Robinson, “A Evaluating the Effec-tiveness of Tutorial Dialogue Instruction in an Exploratory Learning Context,” in Proceedings of International Conference on Intelligent Tutoring Systems, 2006.
    [8] C-Y. Chang, Y-H. Weng, “An Exploratory Study on Students` Problem-Solving Ability in Earth Sciences,” International Journal of Science Education, 24(5), pp. 441-451, 2002.
    [9] H-C. Wang, C-Y. Chang & T-Y. Li, “Automated Scoring for creative prob-lem-solving ability with ideation-explanation modeling,” in Proceedings of 13th In-ternational Conference on Computers in Education (ICCE 2005), pp.522-529, 2005.
    [10] I.H. Witten, E. Frank, L. Trigg, M. Hall, G. Holmes, and S.J. Cunningham, “Weka: Practical machine learning tools and techniques with Java implementations,” in Proceedings of the ICONIP/ANZIIS/ANNES`99 Workshop on Emerging Knowledge Engineering and Connectionist-Based Information Systems”, pp. 192-196, Dunedin, New Zealand, 1999.
    [11] D. J. Treffinger, E. C. Selby, and S. G. Isaksen, “Understanding individual prob-lem-solving style: A key to learning and applying creative problem solving,” Learning and Individual Differences, Elsevier, 2008.
    [12] K. Ferguson, I. Arroyo, S. Mahadevan, B. Woolf and A. Barto, “Improving Intelli-gent Tutoring Systems: Using Expectation Maximization to Learn Student Skill Levels,” in Proceeding of Intelligent Tutoring System, 2006.
    [13] N. Baghaei, A. Mitrovic, “A constraint-based collaborative environment for learning UML class diagrams,” in Lecture Notes in Computer Science, Springer, 2006.
    [14] M. Gonzalez ,and D. Suthers, “Coaching Collaboration in a Computer Mediated Learning Environment,” in Stahl, G. (eds.) CSCL2002, pp.583-584, 2002.
    [15] C.-C. Huang, T.-Y. Li, H.-C. Wang, and C.-Y. Chang, ”Idea Storming Cube: A Game-based System to Support Creative Thinking,” in Proceedings of the First IEEE International Workshop on Digital Game and Intelligent Toy Enhanced Learning (DIGITEL2007), 2007.
    [16] H.-C. Wang, C.-Y. Chang, and T.-Y. Li, ”Assessing creative problem-solving with automated text grading,” Computer and Education, 51, pp.1450-1466, 2008.
    [17] A. Mitrovic, M. Mayo, P. Suraweera, and B. Martin, “Constraint-based Tutors: a Success Story,” in Proceedings of 14th Int. Conf. Industrial and Engineering Ap-plications of Artificial Intelligence and Expert Systems, pp.931-940, 2001.
    [18] A. Dempster, N. Laird, and D. Rubin, “Maximization-likelihood from Incomplete Data via the EM Algorithm,” Journal of Royal Statistical Society, Series B, 1977.
    [19] E. Hannan, and B. Quinn, “The determination of the order of an autoregression,” Journal of the Royal Statistical Society, 1979.
    [20] D. M. Johnson, Systemic introduction to the psychology of thinking, New York: Harper & Row, 1972.
    [21] D. J. Treffinger, S. G. Isaksen, & K. B. Stead-Dorval, Creative problem solving: An introduction (4th ed.), 2006.
    [22] A. F. Osborn, Applied imagination: Principles and procedures of creative thinking, New York: Charles Scribner’s Sons,1953.
    [23] D. J. Treffinger, E. C. Selby, S. G. Isaksen, & J. H. Crumel, Problem solving style: Introduction and overview, Sarasota, FL: Center for Creative Learning,2007.
    [24] I. Myers, & M. McCaulley, Manual: A guide to the development and use of the Myers-Briggs Type Indicator Palo, 1985.
    [25] R. Dunn and K. Dunn, Teaching secondary students through their individual learn-ing styles, Boston: Allyn & Bacon, 1993.
    [26] O. Martinsen, & G. Kaufmann, Cognitive style and creativity ,1999.
    [27] R. Roscoe, J. Wagster and G.Biswas, “Using Teachable Agent Feedback to Support Effective Learning by Teaching,” in The Thirtieth Annual Meeting of the Cognitive Science Society, pp. 2381-2386, Washington, DC, July 2008.
    [28] W. Ma and K. Chen “Introduction to CKIP Chinese word segmentation system for the first international Chinese word segmentation bakeoff,” in Proceedings of the second SIGHAN workshop on Chinese language processing, 2003.
    [29] Flex:http://www.adobe.com/products/flex/
    描述: 碩士
    國立政治大學
    資訊科學學系
    94753030
    98
    資料來源: http://thesis.lib.nccu.edu.tw/record/#G0094753030
    数据类型: thesis
    显示于类别:[資訊科學系] 學位論文

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