簡易檢索 / 詳目顯示

研究生: 林合彥
Ho-Yen Lin
論文名稱: 具有教學支援的網路化模擬學習環境
A Web-based Simulation Learning Environment with Instructional Supports
指導教授: 張國恩
Chang, Kuo-En
宋曜廷
Sung, Yao-Ting
學位類別: 碩士
Master
系所名稱: 資訊教育研究所
Graduate Institute of Information and Computer Education
論文出版年: 2004
畢業學年度: 92
語文別: 中文
論文頁數: 86
中文關鍵詞: 建構式學習科學發現式學習教學支援電腦模擬學習
英文關鍵詞: constructive learning, scientific discovery learning, instructional support, computer simulation learning
論文種類: 學術論文
相關次數: 點閱:175下載:37
分享至:
查詢本校圖書館目錄 查詢臺灣博碩士論文知識加值系統 勘誤回報
  • 本研究主要的目的為(1)建置具教學支援的網路化電腦模擬學習環境。(2)探討在教學支援下的網路化電腦模擬學習與傳統實驗室的活動在學習成效上的差異。(3)探討在教學支援下的網路化電腦模擬學習,對不同抽象推理能力的學生,在學習成效上的影響。
    研究採用的教學支援環境包含提供先備知識學習及評量、提供產生假設的支援、或提供循序進行之步驟及提供探索筆記以記錄學習過程。實驗對象為北部都會區國中二年級學生,在探討實驗室學習與電腦模擬學習之學習成效時,隨機選取4個班,班級隨機分派為學習單配合實驗室學習組39人、自訂假設配合電腦模擬學習組39人、選單組合假設配合電腦模擬學習組40人及依循步驟配合電腦模擬學習組35人,共153人。在探討教學支援方式與學生抽象推理能力的關係時,隨機選取6個班,班級隨機分派為自訂假設配合電腦模擬學習組78人、選單組合假設配合電腦模擬學習組79人及依循步驟配合電腦模擬學習組74人,共231人,學習內容以國中自然科光學透鏡成像性質為學習單元。
    實驗室學習與電腦模擬學習成效之研究結果顯示,在科學概念學習成效上,具教學支援的電腦模擬學習組均優於實驗室學習組。教學支援方法與學生抽象推理能力的關係研究結果顯示,教學支援方法與學生抽象推理能力間並沒有交互作用,高抽象推理能力組對後測成績之效果在不同的教學支援環境中,均顯著優於中低抽象推理能力組。自定假設及選單組合假設的教學支援方式,在電腦模擬學習對後測成績之效果,均顯著優於依循步驟之教學支援方式。在學習歷程的分析上,支援自定假設之模擬學習組在實驗設計的正確率上,顯著優於支援依循步驟的模擬學習組。另外,對具教學支援的網路化電腦模擬學習活動,多數學生均給予肯定之看法。

    The main objectives of this research are (1) to establish a web-based simulation learning environment with instructional supports (2) to investigate the difference of learning efficiency between the web-based simulation learning and the activity of traditional lab (3) to investigate the learning effects of students who have various inferential abilities under the web-based simulation learning environment with different instructional supports.
    The instructional support environment designed includes providing learners with pre-requisite knowledge and evaluation, the support of hypothesis generation, sequential guidance, and notes for recording the learning process. The target audience of this research is the second graders of junior high schools students who live in the megalopolis of North Taiwan. While investigating the learning effects of the web-based simulation learning and the activity of traditional lab, four classes were randomly chosen. One class was assigned to the traditional lab group, one class was assigned to the self-orientated hypothesis group, one class was assigned to the selective-composition hypothesis group, and the other was assigned to sequential guidance group. The total number of selected students is 153. While investigating the relationship between instructional supports and inferential ability of students, six classes were randomly chosen. Two classes were assigned to the self-orientated hypothesis group, two classes were assigned to the selective-composition hypothesis group, and the others were assigned to sequential guidance group. The total number of selected students is 231. The course in this experiment focused on the nature of image generation through optical lens which appears in Science Course of junior high schools..
    We found that the learning effects of the groups of web-based simulation learning are all superior than the group of lab learning. As for the relationship between instructional supports and inferential abilities of students, there is no interaction between instructional supports and inferential abilities. The post-test of high inferential group under different instructional support environments is obviously superior to the post-test of the middle-low group. The post-test of the self-orientated hypothesis and selective-composition hypothesis groups is apparently superior to the sequential guidance group. As for the analysis of learning process, the accurate rate of experimental design of the self-orientated hypothesis group is better than the sequential guidance group. Besides, most students just give affirmative attitude for the learning activity of the web-based simulation learning environment which has instructional supports.

    附表目錄 x 附圖目錄 xi 第一章 緒論 1 第一節 研究背景與動機 1 第二節 研究目的 4 第三節 待答問題與研究架構 5 第二章 文獻探討 7 第一節 建構學習理論 7 第二節 發現式學習理論 9 第三節 電腦模擬學習與教學 12 第四節 國中物理光的折射教學單元 22 第五節 歸納與結論 25 第三章 網路化模擬學習環境 26 第一節 設計理念與原則 26 第二節 學習環境的平台與架構 27 第三節 教學支援的學習活動設計 29 第四章 研究方法 46 第一節 研究對象 46 第二節 研究工具 48 第三節 研究設計 50 第四節 實施步驟 52 第五節 資料分析 55 第五章 結果與討論 56 第一節 成就測驗 56 第二節 學習歷程分析 63 第三節 態度問卷結果 67 第四節 討論 69 第六章 結論與建議 73 第一節 結論 73 第二節 建議 74 參考文獻 75 附錄一 先備知識試題 81 附錄二 電腦模擬學習成就測驗試題 84 附錄三 電腦模擬學習活動態度問卷 85 附錄四 實驗室學習單 86

    張春興(2001)。教育心理學。台北市:東華書局。
    格林,晏尼,布瑞登(民85)。科學學習心理學。(熊召弟等譯)。台北市:心理出版社。(原著出版年﹕1996年)
    Alessi, S.M. (1988). Fidelity in the design of instructional simulations. Journal of computer-based instruction, 15(2), 40-47.
    Bangert-Drowns, R., Kulik, J., & Kulik, C. (1985). Effectiveness of computer-based education in secondary schools. Journal of Computer Based Instruction, 12, 59-68.
    Berkum, J.J.A. van, & de Jong, T. (1991). Instructional environments for simulations. Education & Computing, 6, 305-358.
    Carlsen, D.D., & Andre, T. (1992). Use of a microcomputer simulation and conceptual change text to overcome student preconceptions about electric circuits. Journal of Computer-Based Instruction, 19, 105-109.
    Chang, K.E., Sung, Y.T., & Lee, C.L. (2003). Web-based collaborative inquiry learning. Journal of Computer Assisted Learning, 19, 56-69.
    Charney, D., Reder, L., & Kusbit, G.W. (1990). Goal setting and procedure selection in acquiring computer skills: A comparison of tutorials, problem solving, and learner exploration. Cognition and Instruction, 7, 323-342.
    Chinn, C.A., & Brewer, W.F. (1993). The role of anomalous data in knowledge acquisition: A theoretical framework and implications for science instruction. Review of Educational Research, 63, 1-49.
    de Jong, T. (1991). Learning and instruction with computer simulations. Education & Computing, 6, 217-229.
    de Jong, T., & Njoo, M. (1992). Learning and Instruction with computer simulations: learning processes involved. In E. de Corte, M. Linn, H. Mandl & L. Verschaffel (Eds.), Computer-based learning environments and problem solving (pp. 411-429). Berlin, Germany: Springer-Verlag.
    de Jong, T., Martin, E., Zamarro J-M., Esquembre, F., Swaak, J., & van Joolingen, W.R. (1995, April). Support for simulation-based learning; the effects of assignments and model progression in learning about collisions. Paper presented at the Annual Meeting of the American Educational Research Association, San Francisco, CA.
    de Jong, T., van Joolingen, W., Scott, D., de Hoog, R., Lapied, L., Valent, R. (1994). SMISLE: System for Multimedia Integrated Simulation Learning Environments. In T. de Jong & L. Sarti (Eds.), Design and production of multimedia and simulation based learning material (pp. 133-167). Dordrecht, The Netherlands: Kluwer Academic Publishers.
    de Jong, T., van Joolingen, W. R. (1998). Scientific discovery learning with computer simulations of conceptual domains. Review of Educational Research, 68(2), 179-201.
    Driver, R., Guesne, E. and Tiberghien, A. (1985) Children’s ideas and learning of science. In R. Driver, E. Guesne and A. Tiberghien (Eds.), Children’s Ideas in Science. (Philadelphia: Open University Press).
    Duchastel, P. (1990-1991). Instructional strategies for simulation-based learning. Journal of Educational Technology Systems, 19, 265-276.
    Dunbar, K. (1993). Concept discovery in a scientific domain. Cognitive Science, 17, 397-434.
    Ellington, H.I., Addinall, E., Percival, R. (1981). Games and simulations in science education. London: Kogan Page.
    Friedler, Y., Nachmias, R., & Linn, M.C. (1990). Learning scientific reasoning skills in microcomputer-based laboratories. Journal of Research in Science Teaching, 27, 173-191.
    Galili, I., & Hazan, A., (2000). Learners’ knowledge in optics: interpretation, structure and analysis. International Journal of Science Education, 22(1), 57-88.
    Glaser, R., Schauble, L., Raghavan, K., & Zeitz, C. (1992). Scientific reasoning across different domains. In E. de Corte, M. Linn, H. Mandl & L. Verschaffel(Eds.), Computer-Based learning environments and problem solving(pp. 345-373). Berlin, Germany: Springer-Verlag.
    Grimes, P.W., & Willey, T.E. (1990). The effectiveness of microcomputer simulations in the principles of economics course. Computers & Education, 14, 81-86.
    Gruber, H., Graf, M., Mandl, H., Renkl, & Stark, R. (1995, August). Fostering applicable knowledge by multiple perspectives and guided problem solving. Paper presented at the conference of the European Association for Research on Learning and Instruction, Nijmegen, The Netherlands.
    Jonassen, D. H., Davidson, M., Collins, M., Campbell, J., & Haag, B. B. (1995). Constructivism and computer-mediated communication in distance education. The American Journal of Distance Education, 9(2), 7-27.
    Klahr, D., & Dunbar, K. (1988). Dual space search during scientific reasoning. Cognitive Science, 12, 1-48.
    Klahr, D., Fay, A.L., & Dunbar, K. (1993). Heuristics for scientific experimentation: A developmental study. Cognitive Psychology, 25, 111-146.
    Kuhn, D., Schauble, L., & Garcia-Mila, M. (1992). Cross-domain development of scientific reasoning. Cognition and Instruction, 9, 285-327.
    Lavoie, D.R., & Good, R. (1988). The nature and use of predictions skills in a biological computer simulation. Journal of Research in Science Teaching, 25, 335-360.
    Lewis, E.L., Stern, J.L., & Linn, M.C. (1993). The effect of computer simulations on introductory thermodynamics understanding. Educational Technology, 33, 45-58.
    Linn, M.C., & Songer, N.B. (1991). Teaching thermodynamics to middle school students: What are appropriate cognitive demands? Journal of Research in Science Teaching, 28, 885-918.
    Mokros, J.R., & Tinker, R.F. (1987). The impact of microcomputer based labs on children’s ability to interpret graphs. Journal of Research in Science Teaching, 24, 369-383.
    Njoo, M., & de Jong, T. (1993). Exploratory learning with a computer simulation for control theory: Learning processes and instructional support. Journal of Research in Science Teaching, 30, 821-844.
    Quinn, J., & Alessi, S. (1994). The effects of simulation complexity and hypothesis generation strategy on learning. Journal of Research on Computing in Education, 27, 75-91.
    Reigeluth, C.M., & Schwartz, E. (1989). An instructional theory for the design of computer-based simulations. Journal of Computer-Based Instruction, 16(1), 1-10.
    Reimann, P. (1991). Detecting functional relations in a computerized discovery environment. Learning and Instruction, 1, 45-65.
    Rieber, L.P., & Parmley, M.W. (1995). To teach or not to teach? Comparing the use of computer-based simulations in deductive versus inductive approaches to learning with adults in science. Journal of Educational Computing Research, 14, 359-374.
    Rieber, L.P., Boyce, M., & Assad, C. (1990). The effects of computer animation on adult learning and retrieval tasks. Journal of Computer-Based Instruction, 17, 46-52.
    Rivers, R.H., & Vockell, E. (1987). Computer simulations to stimulate scientific problem solving. Journal of Research in Science Teaching, 24, 403-415.
    Schauble, L., Glaser, R., Duschl, R.A., Schulze, S., & John, J. (1995). Students’ understanding of the objectives and procedures of experimentation in the science classroom. The Journal of the Learning Sciences, 4, 131-166.
    Schauble, L., Glaser, R., Raghavan, K., & Reiner, M. (1991). Causal models and experimentation strategies in scientific reasoning. The Journal of the Learning Sciences, 1, 201-239.
    Schauble, L., Klopfer, L., & Raghavan, K. (1991). Students’ transitions from an engineering to a science model of experimentation. Journal of Research in Science Teaching, 28, 859-882.
    Showalter, V.M. (1970). Conducting science investigations using computer simulated experiments. The Science Teacher, 37, 46-50.
    Shute, V.J. (1993). A comparison of learning environments: All that glitters .... In S.P. Lajoie & S.J. Derry (Eds.), Computers as cognitive tools (pp. 47-75). Hillsdale, NJ: Erlbaum.
    Shute, V.J., & Glaser, R. (1990). A large-scale evaluation of an intelligent discovery world: Smithtown. Interactive Learning Environments, 1(1), 51-77.
    Shute, V.J., & Towle, B. (2003). Adaptive E-Learning. Educational Psychologist, 38(2), 105-114
    Simmons, P.E., & Lunetta, V.N. (1993). Problem-solving behaviors during a genetics computer simulation: beyond the expert/novice dichotomy. Journal of Research in Science Teaching, 30, 153-173.
    Swaak, J., van Joolingen, W.R., & de Jong, T. (1996). Support for simulation based learning; The effects of model progression and assignments on learning about oscillatory motion. Enschede, The Netherlands: University of Twente, Centre for Applied Research on Education.
    Tabak, I., Smith, B.K., Sandoval, W.A., & Reiser, B.J. (1996). Combining general and domain-specific strategic support for biological inquiry. In C. Frasson, G. Gauthier & A. Lesgold (Eds.), Intelligent Tutoring Systems (pp. 288-297). Berlin, Germany: Springer-Verlag.
    Thomas, R., & Neilson, I. (1995). Harnessing simulations in the service of education: the Interact simulation environment. Computers & Education, 25, 21-29.
    van Joolingen, W.R., & de Jong, T. (1991). Supporting hypothesis generation by learners exploring an interactive computer simulation. Instructional Science, 20, 389-404.
    Veenman, M.V.J., & Elshout, J.J. (1994). Differential effects of instructional support on learning in simulation environments. Instructional Science, 22(5), 363-383.
    White, B.Y. (1984). Designing computer games to help physics students understand Newton’s laws of motion. Cognition and Instruction, 1, 69-108.
    White, B.Y. (1993). ThinkerTools: causal models, conceptual change, and science education. Cognition and Instruction, 10, 1-100.
    White, B.Y., & Frederiksen, J.R. (1990). Causal model progressions as a foundation for intelligent learning environments. Artificial Intelligence, 24, 99-157.
    Willis, J., Hovey, L., Hovey, K.G. (1987). Computer simulations. A sourcebook to learning in an electronic environment. New York: Garland.
    Wolfgang, C., Mario, B., (2000). Physlets: Teaching physics with interactive curricular material. New Jersey: Prentice Hall
    Zietsman, A.I., & Hewson, P.W. (1986). Effect of instruction using microcomputers simulations and conceptual change strategies on science learning. Journal of Research in Science Teaching, 23, 27-39.

    QR CODE