簡易檢索 / 詳目顯示

研究生: 林麗芬
Lin, Li-Fen
論文名稱: 鷹架式建模課程的設計與評估:以空氣品質複雜系統為例
Development and Evaluation of Modeling Curriculum: An Example of a Complex System in Air Quality
指導教授: 許瑛玿
Hsu, Ying-Shao
學位類別: 博士
Doctor
系所名稱: 地球科學系
Department of Earth Sciences
論文出版年: 2012
畢業學年度: 100
語文別: 中文
論文頁數: 248
中文關鍵詞: 建模學習分散式鷹架建模技能
英文關鍵詞: model-based learning, distributed scaffolding, modeling skills
論文種類: 學術論文
相關次數: 點閱:149下載:18
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
  • 本研究透過設計式研究法(design-based research),以兩個個案研究探討分散式鷹架對高中生之建模技能與空氣品質概念理解的影響,並據以發展與評估鷹架式建模課程的設計。在鷹架式建模課程中,學生使用空污建模軟體來建構與測試變因關係,並應用所建構出的模式至其他類似的問題情境。本研究收集兩個學校個案研究之探究測驗、晤談資料、學習單、紙本模式、電腦化模式、電腦側錄、錄影資料,以及會議紀錄等研究資料,並透過質性與量化的分析,來比較兩種版本的鷹架式建模課程設計對學生建模學習的影響,並且在每個個案班級中選取一組焦點組學生來分析他們的建模過程,以說明分散式鷹架如何協助學生參與複雜系統的建模學習。
    個案研究一的鷹架式建模學習課程具備三項設計特徵,包含融入以學生為中心的專家建模實務特徵、擬真的視覺化工具以支援建模、及提供引導學生學習策略的提示。施測結果顯示學生的建模技能與空氣品質的概念理解均有顯著進步,但在「辨識變因與關係」階段的建模技能進步則較不明顯,此外從焦點組建模過程的分析發現,(1)本課程能提供學生主動參與類似科學家建模實務的機會,(2)學生需要其他形式的鷹架系統支持,以有效運用預先規劃與設計好環境鷹架支持
    個案研究二中,根據個案研究一的發現來調整鷹架式建模課程,包括增加「引導式結構化建模」與「營造合作實務學習」兩項設計,以促進學習環境中分散式鷹架的協調整合。共變數分析顯示參與個案研究二的學生在整體的建模技能、辨識變因與關係階段的建模技能,以及大氣穩定度的理解皆顯著優於個案研究一的學生。綜合上述發現,顯示新增的兩項設計可促進分散式鷹架系統組成的互動,進而支持學生參與類似專家之複雜系統的建模實務。

    This study investigated how distributed scaffolding may influence the development of high-school students' modeling skills and conceptual understanding about the complex system in air quality. With better understanding of how students construct their modeling skills, this study further proposed and evaluated a modeling course with scaffolding. In the course, students were encouraged to test and construct cause-and-effect relationships between variables by using an modeling tool as well as to applying the models they constructed in similar problem situations. Multiple data were collected from two classes from the same school, including pre-tests and post-tests of modeling skills, interview transcripts, students’ worksheets,models they proposed on papers and in computers, screen-capture videos of students’ use of the modeling tool (process videos), classroom observations (class videos), and meeting
    minutes. Through quantitative and qualitative analyses, two versions of the scaffolding curricula were developed and evaluted for how they influenced the development of students' conceptual understanding and modeling skills. The modeling process of the target group from each class was further analyzed for seeing how the distributed scaffolding supported students to construct their models of complex
    systems.
    The scaffolding modeling curriculum in Study 1 was featured with student-centered modeling practices that was based novice-expert analysis results,modeling tools with authentic visualizations, and prompts that guided students to learn. Significant improvements were found on students’ modeling skills and conceptualization of air quality, but not on their modeling skills on “identifying variables and relationships.” After analyzing the modeling performance of the target groups modeling, I found that 1) the curriculum engaged students the opportunities that they could conduct expert-like modeling practices; and 2) students would be benefited if provided another types of scaffolding that facilitated them to better use of the scaffolding embedded in the curriculum.
    Modified from the curriculum in Study 1, the scaffolding modeling curriculum in Study 2 was added features of “guided structural modeling” and “collaboration-invited practices,” in order to improve the coordination of the distributed scaffolding. Results of ANCOVA showed students in Study 2 performed better than the ones in Study 1 on overall modeling skills, identification of variables
    and relationships, and conceptualization of air quality. All in all, the additional two features of the curriculum in Study 2 not only promote the coordination of elements in
    distributed scaffolding, but also support students to engage themselves in expert-like modeling practices in complex system.

    第一章 緒論 第一節 研究背景與目的……………………………………………………..1 第二節 研究問題……………………………………………………………..4 第三節 研究的重要性………………………………………………………..5 第四節 名詞釋義……………………………………………………………..7 第五節 研究範圍與限制……………………………………………………9 第二章 文獻探討 第一節 空氣品質與複雜系統………………………………………………11 第二節 鷹架的理論基礎……………………………………………………23 第三節 建模學習理論………………………………………………………31 第四節 模式與建模…………………………………………………………37 第五節 鷹架式建模課程設計..……………………………………………..51 第六節 建模學習環境的鷹架特性…………………………………………58 第三章 研究方法 第一節 設計式研究法………………………………………………………64 第二節 研究流程……………………………………………………………69 第三節 研究對象與教學情境………………………………………………73 第四節 研究工具……………………………………………………………75 第五節 資料收集與分析方法………………………………………………95 第四章 研究結果 第一節 個案研究一………………………………………………………..110 第二節 個案研究二………………………………………………………..156 第三節 版本綜合比較……………………………………………………..193 第五章 結論與建議 第一節 綜合討論…………………………………………………………..196 第二節 結論………………………………………………………………..205 第三節 建議………………………………………………………………..206 第四節 未來研究方向……………………………………………………..207 參考文獻 中文部分…………………………………………………………………….208 英文部分…………………………………………………………………….209 附錄 附錄一 晤談單與晤談注意事項………………………………………….220 附錄二 空污建模技能測驗……………………………………………….223 附錄三 高斯擴散模式…………………………………………………….227 附錄四 高斯擴散質性模式……………………………………………….229 附錄五 高斯擴散質性模式測驗………………………………………….231. 附錄六 空氣品質概念架構……………………………………………….233 附錄七 個案研究一學生學習單填寫狀況表…………………………….235 附錄八 課室錄影與電腦側錄轉譯稿之Events與Episode切割範例….237 附錄九 個案研究二焦點組課室錄影Episode內容摘要表……………..243 附錄十 個案研究一學習單之「引導學習學習策略的提示」設計…….245 附錄十一個案研究二學習單之「引導式結構化建模活動」設計……….247

    一、中文部分
    教育部(2003)。九年一貫中小學課程綱要。臺北市:教育部。
    教育部(2008)。普通高級中學課程綱要。臺北市:教育部。
    林政剛、林國雄、洪培元、黃政賢、劉光宇(1995)。空氣污染。高立。
    李岱螢(1997)。不同認知結構學生於鷹架式建模課程中科學概念學習之個案研究。國立臺灣師範大學碩士論文。
    許瑛玿、吳心楷、黃福坤、陳正平(2005)。鷹架式建模數位學習環境對學生科學學習影響之研究鷹架式建模數位學習環境對學生科學學習影響之研究-總計畫(2/3)。計畫編號:NSC95-2511-S-003-007。

    二、西文部分
    Assaraf, O. B.-Z., & Orion, N. (2005). Development of system thinking skills in the context of earth system education. Journal of Research in Science Teaching, 42(5), 518-560.
    Azevedo, R., Cromley, J., Winters, F., Moos, D., & Greene, J. (2005). Adaptive human scaffolding facilitates adolescents’ self-regulated learning with hypermedia. Instructional Science, 33(5), 381-412.
    Azevedo, R., & Hadwin, A. (2005). Scaffolding self-regulated learning and metacognition – implications for the design of computer-based scaffolds. Instructional Science, 33(5), 367-379.
    Barab, S. A., & Duffy, T. (2000). From practice fields to communities of practice. In D. Jonassen & S. M. Land (Eds.), Theoretical Foundations of Learning Environments (pp. 25-56): Lawrence Erlbaum Associates.
    Barab, S. A., Hay, K. E., Barnett, M., & Keating, T. (2000). Virtual solar system project: Building understanding through model building. Journal of Research in Science Teaching, 37(7), 719-756.
    Barab, S. A., Hay, K. E., Barnett, M., & Kurt, S. (2001). Constructing virtual worlds: Tracing the historical development of learner practices. [Article]. Cognition & Instruction, 19(1), 47-94.
    Barab, S. A., & Kurt, S. (2004). Design-based research: Putting a stake in the ground. Journal of the Learning Sciences, 13(1), 1-14.
    Boyes, E., Myers, G., Skamp, K., Stanisstreet, M., & Yeung, S. P.-m. (2007). Air quality: a comparison of students' conceptions and attitudes across the continents. Compare: A Journal of Comparative Education, 37(4), 425-445.
    Brown, A. L. (1992). Design experiments: Theoretical and methodological challenges in creating complex interventions in classroom settings. Journal of the Learning Sciences, 2(2), 141.
    Brown, J. S., Collins, A., & Duguid, P. (1989). Situated cognition and the culture of learning. Educational Researcher, 18(1), 32-42.
    Buckley, B. C. (2000). Interactive multimedia and model-based learning in biology. International Journal of Science Education, 22(9), 895-935.
    Cazden, C. (1979). Peekaboo as an Instructional Model: Discourse Development at Home and at School. Papers and Reports on Child Language Development, No. 17.
    Cazden, C. (1988). Classroom discourse: The language of teaching and learning. Portsmouth, NH: Heinemann.
    Chi, M. T. H., Glaser, R., & Farr, M. J. (1988). The Nature of Expertise. Hillsdale, NJ: Erlbaum.
    Clement, J. (2000). Model based learning as a key research area for science education. [Article]. International Journal of Science Education, 22(9), 1041-1053.
    Cobb, P., Confrey, J., diSessa, A., Lehrer, R., & Schauble, L. (2003). Design experiments in educational research. Educational Researcher, 32(1), 9-13.
    Coll, R., France, B., & Taylor, I. (2005). The role of models and analogies in science education: implications from research. International Journal of Science Education, 27(2), 183-198.
    Collective, T. D.-B. R. (2003). Design-based research: An emerging paradigm for educational inquiry. Educational Researcher, 32(1), 5-8.
    Collins, A. (1990). Toward a Design Science of Education. Technical Report No. 1.
    Collins, A. (1992). Toward a design science of education. In E. Scanlon & T. O'Shea (Eds.), New directions in educational technology (pp. 15-20): Springer-Verlag.
    Collins, A., Brown, J. S., & Newman, S. (1989). Cognitive Apprenticeship: Teaching the Crafts of Reading, Writing and Mathematics. In L. Resnick (Ed.), Knowing, Learning, and Instruction. Essays in Honor of Robert Glaser (pp. 453-494): Lawrence Erlbaum Associates.
    Davis, E. A., & Linn, M. C. (2000). Scaffolding students' knowledge integration: prompts for reflection in KIE. International Journal of Science Education, 22(8), 819-837.
    Duncan, R. G., & Reiser, B. J. (2005). Designing for complex system understanding in the high school biology classroom. Paper presented at the Proceedings of the NARST 2005 Annual Meeting, Dallas, TX, United States.
    Edelson, D. C. (2001). Learning-for-use: A framework for the design of technology-supported inquiry activities. Journal of Research in Science Teaching, 38(3), 355-385.
    Edelson, D. C. (2002). Design research: What we learn when we engage in design. Journal of the Learning Sciences, 11(1), 105-121.
    Fretz, E. B., Wu, H.-K., Zhang, B., Davis, E. A., Krajcik, J. S., & Soloway, E. (2002). An investigation of software scaffolds supporting modeling practices. Research in Science Education, 32(4), 567-589.
    Gagne, E. D., Yekovich, C. W., & Yekovich, F. R. (1998). 教學心理學 : 學習的認知基礎 The cognitive psychology of school learning(2nd ed) (岳修平, Trans.): 臺北市 : 遠流.
    Ge, X., & Land, S. (2003). Scaffolding students’ problem-solving processes in an ill-structured task using question prompts and peer interactions. Educational Technology Research and Development, 51(1), 21-38.
    Gilbert, J. K., Reiner, M., & Nakhleh, M. (2008). Visualization: Theory and practice in science education. Dordrecht: Springer.
    Gobert, J. D. (2000). A typology of causal models for plate tectonics: Inferential power and barriers to understanding. International Journal of Science Education, 22(9), 937-977.
    Gobert, J. D., & Buckley, B. C. (2000). Introduction to model-based teaching and learning in science education. International Journal of Science Education, 22(9), 891-894.
    Gobert, J. D., Snyder, J., & Houghton, C. (2002). The Influence of Students' Understaning of Models on Model-Based Reasoning. Paper presented at the Annual Meeting of American Educational Research Association, New Orleans, LO.
    Greca, I. M., & Moreira, M. A. (2000). Mental models, conceptual models, and modelling. International Journal of Science Education, 22(1), 1-11.
    Hakkarainen, K. (2003). Progressive inquiry in a computer-supported biology class. Journal of Research in Science Teaching, 40(10), 1072-1088.
    Hansen, J. A., Barnett, M., MaKinster, J. G., & Keating, T. (2004). The impact of three-dimensional computational modeling on student understanding of astronomical concepts: a quantitative analysis. [Article]. International Journal of Science Education, 26(11), 1365-1378.
    Harrison, A. G., & Treagust, D. F. (2000). A typology of school science models. International Journal of Science Education, 22(9), 1011-1026.
    Hestenes, D. (1992). Modeling games in the Newtonian world. American Journal of Physics, 60(8), 732-748.
    Hmelo-Silver, C. E., & Azevedo, R. (2006). Understanding complex systems: some core challenges. Journal of the Learning Sciences, 15(1), 53-61.
    Hmelo-Silver, C. E., Holton, D. L., & Kolodner, J. L. (2000). Designing to learn about complex systems. Journal of the Learning Sciences, 9(3), 247-298.
    Hmelo-Silver, C. E., Marathe, S., & Liu, L. (2007). Fish Swim, Rocks Sit, and Lungs Breathe: Expert-Novice Understanding of Complex Systems. Journal of the Learning Sciences, 16(3), 307-331.
    Hogan, K., & Thomas, D. (2001). Cognitive comparisons of students' systems modeling in ecology. Journal of Science Education and Technology, 10(4), 319-345.
    Hsu, Y.-S., Lin, L.-F., Ke, I.-C., Wu, H.-K., & Hwang, F.-K. (2007, 15-18 April). A comparison of experts, intermediates, novice, and naives in modeling. Paper presented at the NARST, New Orleans, USA.
    Hsu, Y.-S., Lin, L.-F., Wu, H.-K., Lee, D.-Y., & Hwang, F.-K. (2012). A Novice-Expert Study of Modeling Skills and Knowledge Structures about Air Quality. Journal of Science Education and Technology, 1-19.
    Ingham, A. M., & Gilbert, J. K. (1991). The use of analogue models by students of chemistry at higher education level. International Journal of Science Education, 13(2), 193-202.
    Jacobson, M. J. (2000). Problem solving about complex systems: Differences between experts and novices. Paper presented at the International Conference on the Learning Sciences, Ann Arbor, MI: University of Michigan.
    Jacobson, M. J., & Wilensky, U. (2006). Complex systems in education: Scientific and educational importance and implications for the learning sciences. [Article]. Journal of the Learning Sciences, 15(1), 11-34.
    Johnson-Laird, P. N. (1983). Mental models. Cambridge: Havard University Press.
    Jonassen, D., Strobel, J., & Gottdenker, J. (2005). Model Building for Conceptual Change. Interactive Learning Environments, 13(1), 15-37.
    Justi, R., & Gilbert, J. K. (2000). History and philosophy of science through models: some challenges in the case of 'the atom'. International Journal of Science Education, 22(9), 993-1009.
    Kaberman, Z., & Dori, Y. (2009). Question posing, inquiry, and modeling skills of chemistry students in the case-based computerized laboratory environment. International Journal of Science and Mathematics Education, 7(3), 597-625.
    Kearney, M. (2004). Classroom use of multimedia-supported predict–observe–explain tasks in a social constructivist learning environment. Research in Science Education, 34(4), 427-453.
    Kelly, A. (2004). Design research in education: Yes, but is it methodological? Journal of the Learning Sciences, 13(1), 115-128.
    Kolodner, J. L., Camp, P. J., Crismond, D., Fasse, B., Gray, J., Holbrook, J., . . . Ryan, M. (2003). Problem-Based Learning Meets Case-Based Reasoning in the Middle-School Science Classroom: Putting Learning by Design(tm) into Practice. Journal of the Learning Sciences, 12(4), 495-547.
    Krajcik, J. S., McNeill, K. L., & Reiser, B. J. (2008). Learning-goals-driven design model: Developing curriculum materials that align with national standards and incorporate project-based pedagogy. Science Education, 92(1), 1-32.
    Kuhn, D. (2007). Reasoning about multiple variables: Control of variables is not the only challenge. Science Education, 91(5), 710-726.
    Kuhn, D., Black, J., Keselman, A., & Kaplan, D. (2000). The development of cognitive skills to support inquiry learning. Cognition & Instruction, 18(4), 495-523.
    Kundel, H., & Polansky, M. (2003). Measurement of observer agreement. Radiology, 228, 303-308.
    Löhner, S., van Joolingen, W. R., & Savelsbergh, E. R. (2003). The effect of external representation on constructing computer models of complex phenomena. Instructional Science, 31(6), 395-418.
    Löhner, S., van Joolingen, W. R., Savelsbergh, E. R., & van Hout-Wolters, B. (2005). Students’ reasoning during modeling in an inquiry learning environment. Computers in Human Behavior, 21(3), 441-461.
    Lajoie, S. (2005). Extending the scaffolding metaphor. Instructional Science, 33(5), 541-557.
    Larkin, J. H., & Simon, H. A. (1987). Why a Diagram is (Sometimes) Worth Ten Thousand Words. Cognitive Science, 11(1), 65-100.
    Lave, J., & Wenger, E. (1991). Situated learning: legitimate peripheral participation. New York: Cambridge University.
    Lee, H.-S., & Sogner, N. B. (2003). Making authentic science accessible to students. International Journal of Science Education, 25(8), 923-948.
    Lin, L.-F., Hsu, Y.-S., & Yeh, Y.-F. (2012). The role of computer simulation in an inquiry-based learning environment: Reconstructing geological events as geologists. Journal of Science Education and Technology, 21(3), 370-383. doi: 10.1007/s10956-011-9330-3
    Linn, M. C. (2000). Designing the knowledge integration environment. International Journal of Science Education, 22(8), 781-796.
    Liu, L., & Hmelo-Silver, C. E. (2009). Promoting complex systems learning through the use of conceptual representations in hypermedia. Journal of Research in Science Teaching, 46(9), 1023-1040.
    Lopes, J. B., & Costa, N. (2007). The evaluation of modelling competences: Difficulties and potentials for the learning of the sciences. International Journal of Science Education, 29(7), 811-851.
    Louca, L. T., & Zacharia, Z. C. (2007). The use of computer‐based programming environments as computer modelling tools in rarly Science education: The cases of textual and graphical program languages. International Journal of Science Education, 30(3), 287-323.
    Mayer, R. E. (1989). Models for understanding. Review of Educational Research, 59(1), 43-43.
    McNeill, K. L., Lizotte, D. J., Krajcik, J. S., & Marx, R. W. (2006). Supporting students' construction of scientific explanations by fading scaffolds in instructional materials. Journal of the Learning Sciences, 15(2), 153-191.
    Millar, R., & Driver, R. (1987). Beyod processes. Studies in Science Education, 14(1), 33-62.
    Myers, G., Boyes, E., & Stanisstreet, M. (2004). School students' ideas about air pollution: Knowledge and attitudes. Research in Science & Technological Education, 22(2), 133-152.
    Palincsar, A. S. (1998). Keeping the metaphor of scaffolding fresh--A response to C. Addison Stone's "The Metaphor of Scaffolding: Its Utility for the Field of Learning Disabilities", Journal of Learning Disabilities, pp. 370-373.
    Palinscar, A. S., & Brown, A. L. (1984). Reciprocal teaching of comprehension-fostering and comprehension-monitoring activities. Cognition & Instruction, 1(2), 117.
    Papaevripidou, M., Constantinou, C. P., & Zacharia, Z. C. (2007). Modeling complex marine ecosystems: an investigation of two teaching approaches with fifth graders. Journal of Computer Assisted Learning, 23(2), 145-157.
    Passmore, C., & Stewart, J. (2002). A modeling approach to teaching evolutionary biology in high schools. Journal of Research in Science Teaching, 39(3), 185-204.
    Pata, K., & Sarapuu, T. (2006). A comparison of reasoning processes in a collaborative modelling environment: Learning about genetics problems using virtual chat. International Journal of Science Education, 28(11), 1347-1368.
    Pea, R. D. (2004). The social and technological dimensions of scaffolding and related theoretical concepts for learning, education, and human activity. Journal of the Learning Sciences, 13(3), 423-451.
    Penner, D. E. (2000). Cognition, computers, and synthetic science: building knowledge and meaning through modeling. Review of Research in Education, 25, 1-35.
    Penner, D. E., Giles, N. D., Lehrer, R., & Schauble, L. (1997). Building functional models: Designing an elbow. Journal of Research in Science Teaching, 34(2), 125-143.
    Penner, D. E., Lehrer, R., & Schauble, L. (1998). From physical models to biomechanics: A design-based modeling approach. Journal of the Learning Sciences, 7(3/4), 429.
    Prins, G. T., Bulte, A. M. W., van Driel, J. H., & Pilot, A. (2008). Selection of authentic modelling practices as contexts for chemistry education. International Journal of Science Education, 30(14), 1867-1890.
    Puntambekar, S., & Kolodner, J. L. (2005). Toward implementing distributed scaffolding: Helping students learn science from design. Journal of Research in Science Teaching, 42(2), 185-217.
    Quintana, C., Reiser, B. J., Davis, E. A., Krajcik, J. S., Fretz, E., Duncan, R. G., . . . Soloway, E. (2004). A scaffolding design framework for software to support science inquiry. Journal of the Learning Sciences, 13(3), 337-386.
    Reiser, B. J. (2004). Scaffolding Complex Learning: The Mechanisms of Structuring and Problematizing Student Work. The Journal of the Learning Sciences, 13(3).
    Reiser, B. J., Krajcik, J. S., Moje, E., & Marx, R. (2003). Design Strategies for Developing Science Instructional Materials. Paper presented at the the annual meeting of the National Association for Research in Science Teaching, Philadelphia, PA.
    Roehler, L. R., & Cantlon, D. J. (1996). Scaffolding: a powerful tool in social constructivist classrooms
    Rogat, A., & Reiser, B. J. (2006). Scientific modeling. Paper presented at the the annual meeting of the National Association for Research in Science Teaching, San Francisco.
    Roschelle, J. (1992). Learning by collaborating: Convergent conceptual change. Journal of the Learning Sciences, 2(3), 235.
    Roth, W.-M. (1996). Knowledge diffusion in a grade 4-5 classroom during a unit on civil engineering: An analysis of a classroom community in terms of its changing resources and practices. Cognition & Instruction, 14(2), 179-220.
    Salomon, G., & Globerson, T. (1987). Skill may not be enough: The role of mindfulness in learning and transfer. International Journal of Educational Research, 11(6), 623-637.
    Schwarz, C. V., Reiser, B. J., Davis, E. A., Kenyon, L., Achér, A., Fortus, D., . . . Krajcik, J. (2009). Developing a learning progression for scientific modeling: Making scientific modeling accessible and meaningful for learners. Journal of Research in Science Teaching, 46(6), 632-654.
    Shwartz, Y., Rogat, A., Merritt, J., & Krajcik, J. S. (2007). The effect of classroom practice on students understanding of models. Paper presented at the the annual meeting of the National Association of Research in Science Teaching, New Orleans, LA.
    Sins, P. H. M., Savelsbergh, E. R., & van Joolingen, W. R. (2005). The difficult process of scientific modelling: An analysis of novices' reasoning during computer‐based modelling. International Journal of Science Education, 27(14), 1695-1721.
    Skamp, K., Boyes, E., & Stanisstreet, M. (2004). Students' ideas and attitudes about air quality. Research in Science Education, 34(3), 313-342.
    Stewart, J., Hafner, R., Johnson, S., & Finkel, E. (1992). Science as model building: Computers and high-school genetics. Educational Psychologist, 27(3), 317-336.
    Stone, C. A. (1998). The metaphor of scaffolding: Its utility for the field of learning disabilities. Journal of Learning Disabilities, 31(4), 344-364.
    Stoof, A., Martens, R. L., van Merriënboer, J. J. G., & Bastiaens, T. J. (2002). The boundary approach of competence: A constructivist aid for understanding and using the concept of competence. Human Resource Development Review, 1(3), 345-365.
    Stratford, S. J., Krajcik, J. S., & Soloway, E. (1998). Secondary students' dynamic modeling processes: Analyzing, reasoning about, synthesizing, and testing models of stream ecosystems. Journal of Science Education and Technology, 7(3), 215-234.
    Tabak, I. (2004). Synergy: A complement to emerging patterns of distributed scaffolding. Journal of the Learning Sciences, 13(3), 305-335.
    Tabak, I., & Reiser, B. J. (1997, December 10-14). Complementary roles of software-based scaffolding and teacher-student interactions in inquiry learning. Paper presented at the Computer Support for Collaborative Learning, Toronto, Canada.
    Tao, P.-K. (2004). Developing understanding of image formation by lenses through collaborative learning mediated by multimedia computer-assisted learning programs. International Journal of Science Education, 26(10), 1171-1197.
    van Borkulo, S., van Joolingen, W., Savelsbergh, E., & de Jong, T. (2012). What can be learned from computer modeling? Comparing expository and modeling approaches to teaching dynamic systems behavior. Journal of Science Education and Technology, 21(2), 267-275.
    Verhoeff, R. P., Waarlo, A. J., & Boersma, K. T. (2008). Systems modelling and the development of coherent understanding of cell biology. International Journal of Science Education, 30(4), 543-568.
    Vygotsky, L. S. (1978). Mind in society: The development of higher psychological processes. Cambridge, MA: Harvard University Press.
    Webb, M. E. (1994). Beginning computer-based modelling in primary schools. Computers & Education, 22(1–2), 129-144.
    Webb, N. M. (1989). Peer interaction and learning in small groups. International Journal of Educational Research, 13(1), 21-39.
    Wenger, E. (1998). Communities of practices: learning, meaning, and identity. London: Cambridge University.
    White, B. Y. (1993). ThinkerTools: Causal models, conceptual change, and science education. Cognition & Instruction, 10(1), 1-100.
    White, B. Y., & Frederiksen, J. R. (1998). Inquiry, modeling, and metacognition: Making science accessible to all students. [Article]. Cognition & Instruction, 16(1), 3-120.
    Wilensky, U., & Resnick, M. (1999). Thinking in Levels: A dynamic systems approach to making sense of the world. Journal of Science Education and Technology, 8(1), 3-19.
    Williams, M., & Linn, M. C. (2002). WISE inquiry in fifth grade biology. Research in Science Education, 32(4), 415-436.
    Wood, D., Bruner, J. S., & Ross, G. (1976). The role of tutoring in probleming solving. [Article]. Journal of Child Psychology & Psychiatry & Allied Disciplines, 17(2), 89-100.
    Wu, H.-K. (2002). Middle school students ' development of inscriptional practices in inquiry-based science classroomsMiddle school students ' development of inscriptional practices in inquiry-based science classrooms. doctor of Philosophy (Education), The University of Michigan.
    Wu, H.-K. (2010). Modelling a complex system: Using novice-expert analysis for developing an effective technology-enhanced learning environment. International Journal of Science Education, 32(2), 195-219.
    Wu, H.-K., & Krajcik, J. S. (2006). Exploring middle school students' use of inscriptions in project-based science classrooms. Science Education, 90(5), 852-873.
    Yeung, S. P.-m., Boyes, E., & Stanisstreet, M. (2004). Air pollution: The knowledge and attitudes of secondary school students in Hong Kong. International Research in Geographical & Environmental Education, 13(1), 21-37.
    Zhang, B. H. (2003). Exploring middle school science students; computer-based modeling practices and their changes over time. doctor of Philosophy (Education), The University of Michigan.
    Zhang, B. H., Liu, X., & Krajcik, J. S. (2006). Expert models and modeling processes associated with a computer-modeling tool. Science Education, 90(4), 579-604.
    Zhang, B. H., Wu, H.-K., Fretz, E. B., Krajcik, J. S., Marx, R., Davis, E. A., & Soloway, E. (2002, April 6 - 10). Comparison of modeling practices of experts and novice learners using a dynamic, learner-centered modeling tool. Paper presented at the NARST Annual Meeting, New Orleans, LA.

    下載圖示
    QR CODE