研究生: |
蔡春風 Chun-Feng Tsai |
---|---|
論文名稱: |
透過建模與多重表徵教學探討高二學生的建模能力與概念改變-以空間概念為例 Investigating High School Students' Modeling Ability and Conceptual Change about the Concept of Three-Dimensional Space Using Modeling and Multiple Representation Approaches |
指導教授: |
邱美虹
Chiu, Mei-Hung |
學位類別: |
碩士 Master |
系所名稱: |
科學教育研究所 Graduate Institute of Science Education |
論文出版年: | 2009 |
畢業學年度: | 97 |
語文別: | 中文 |
論文頁數: | 196 |
中文關鍵詞: | 空間概念 、建模 、多重表徵 、心智模式 、概念改變 |
英文關鍵詞: | Three-Dimensional Space, Modeling, Multiple Representation, Mental Model, Conceptual Change |
論文種類: | 學術論文 |
相關次數: | 點閱:287 下載:54 |
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本研究旨在透過科學建模與科學概念改變理論的觀點來探討學生在學習數學上的空間概念時的建模能力與概念改變。在本研究中,研究者發展了一套為期六週、以建模與多重表徵為設計基礎的數學課程,並在一所普通高中內實際進行教學。研究者將三個班級(共125位高二學生)透過方便性取樣分為建模與表徵組(MR)、表徵組(R)與控制組(C)等三組。其中建模與表徵組(簡稱建表組)與表徵組由研究者進行教學,而控制組則由該校一位經驗豐富的數學教師進行教學。
在本研究中,研究者修改了張志康和邱美虹(2009)所提出的「建模能力分析指標(Modeling Ability Analytic Index, MAAI)」,發展了一套多面向的概念試題,在每單元結束後各施測一次,以作為評量與分析的依據。該試題共有五個單元,每個單元均包含許多開放性問題;學生必須完整地進行答題與解釋,才能獲得高分。在後測結束後,每位學生均接受為時20至30分鐘訪談,以協助研究者確認對學生所持之心智模式的歸類是合理的。此外,研究者尚挑選了27位持有不同心智模式與建模能力的標的學生進行為時1小時的深度訪談;此深度訪談旨在深入探討這些學生的心智模式與建模能力,以作為典型個案的呈現。本研究所有的研究工具均經過信效度檢驗,並達到合理標準。
經過資料編碼與分析,本研究顯示出以下結果:首先,三組學生在接受過建模與多重表徵教學後,在概念理解上均有顯著的進步,其中又以建表組的進步幅度最大,表徵組的學生次之,而控制組的學生進步幅度最小。在這當中,建表組與表徵組學生的進步幅度也顯著地較控制組來得大。其次,學生所持有的空間概念心智模式是多元且多樣的。本研究根據先前文獻與試測結果,將學生的心智模式分為科學模式、斜角模式、有界模式、符號模式、實體模式、二維延伸模式、以及其他等七類。在教學前,持有二維延伸模式與有界模式的學生是最多的,隨著教學活動的進展,二維延伸模式的學生開始減少,取而代之的是實體模式與符號模式。有界模式雖然一直都有學生持有,但卻不是比例最高的。在教學的尾聲以及教學完畢後,持有科學模式與符號模式的學生則是最多的。這樣的結果符合了研究者的教學目標,也符合了先前的研究發現。接下來,在學生所使用的建模歷程上,建表組的學生所使用的建模歷程顯著地較表徵組與控制組來得高。學生在六個建模歷程當中,以模型選擇、模型建立與模型應用的表現較為理想。建表組的學生在模型效化、模型調度與模型重建三個歷程上,所使用的次數與表徵組及控制組的學生有顯著的差異。接下來,在學生的建模能力方面,建表組學生的平均建模能力(2.81分)顯著地比表徵組(2.03分)與控制組(1.98分)來得高。56%的建表組學生在教學結束後具備了進階的建模能力,然而三組學生在答題層次上並未展現出顯著差異。接下來,在學生所採用的表徵形式與種類上,學生最常使用的表徵種類為數學表徵,其次是言語表徵與具體表徵。學生較少使用視覺與動作表徵。造成這樣的差異的主要來源,乃是由於建表組的學生在進階建模能力上的得分顯著地比其他兩組來得好。最後,根據回饋單、情意問卷與課堂錄影等資料顯示,學生對這樣的課程持有相當正向的態度,且在課程中有著良好的師生互動。根據本研究的結果,研究者建議教師設計建模與多重表徵課程,並以外顯化的方式實施,以提升學生的建模能力並促進概念改變。
This empirical study aims to investigate high school students' modeling ability and conceptual change about the concept of three-dimensional space in mathematics. In this study, the researcher developed a 6-week high school mathematics curriculum and put it into teaching via the use of modeling and multiple representation approaches. According to the research design, three different classes with 125 11th grade students in total were assigned into three different groups correspondingly, named as the Modeling and Multiple Representation Group (MR), the Multiple Representation Group (R), and the Control Group (C). During the 6-week teaching schedule, the two experimental groups were taught by the researcher, while the control group was taught by an experienced mathematics teacher in the same school.
In order to improve the accuracy on investigating and measuring students' modeling ability and conceptual change, the researcher modified the "Modeling Ability Analytic Index (MAAI; Chang & Chiu, 2009)", and then developed and conducted a set of tests after each unit. Each test contained several open-ended problems, in which students' full explanations were required to score high and solve the problem progressively and completely. After the posttest, each student was interviewed to clarify the researcher's classification toward students' mental models. Furthermore, the researcher selected 20 target students with different mental models and different modeling abilities, interviewed individually for an hour to reveal their modeling and conceptual change paths as typical cases. All the research tools were examined with proper validity.
After data coding and analysis, the results showed: first, on the perspective of conceptual understanding, all the three groups of students scored significantly higher in the posttest and delayed test than in the pretest. Also, the improvement of students' conceptual understanding in both two experimental groups (MR & R) were significantly better than the students in the control group. Second, students' understanding of three-dimensional space was classified into seven different mental models, named as scientific model (SC), inclined angle model (CL), boundary model (BD), symbolic model (SY), concrete model (CN), two-dimensional extension model (EX), and others (OT). Most students held EX and CN mental models in the first two units, whereas many of them turned to held the SY model in the middle of the curriculum. After instruction, 47.2% students held the scientific model, but there was no significant difference among the three groups at this stage. Third, students showed different types of modeling processes in three groups. Students in the MR group conducted model validation, model deployment, and model reconstruction more frequently than those in the R and C groups. Fourth, students in the MR group scored significantly higher in modeling ability tests; 56% of them were able to retrieve advanced modeling ability. However, there was no significant difference in basic and advanced problem-response ability among the three groups. Fifth, students in MR & R groups used more concrete, verbal, visual and gestural representations than those in the control group. Finally, students in MR and R groups showed positive attitudes toward the curriculum. It is suggested that teachers should develop modeling and multiple representation curriculum and implement in their teaching.
李吉彬(2006)。資訊科技融入高中數學資優教育的實務研究。國立交通大學理學院網路學習學程碩士論文(未出版)。
李虹霈(2005)。高職生幾何中空間概念之研究。國立高雄師範大學數學教育研究所碩士論文(未出版)。
李哲迪(2006)。高中物理教科書與學生關於力的話語與合法化的語言策略。國立台灣師範大學科學教育研究所博士論文(未出版)。
周金城(2007)。探究中學生對科學模型的分類與組成本質的理解。論文發表於第二十三屆中華民國科學教育學術研討會,高雄,台灣。
林文杰和楊文金(2007)。高一學生對物理文本過程詞隱含之連接關係的理解。物理教育學刊,9(1),1-18。
林國源(2005)。高中數學建模課程與實踐之研究。國立交通大學理學院網路學習學程碩士論文(未出版)。
林福來、陳冒海、陳順宇、陳創義、邱顯義、徐正梅、許清土、葉善雲和林信安(2008)普通高級中學數學(第三冊)。南一書局出版,台南,台灣。
林福來、楊凱琳、陳嘯虎和呂又寧(2003)。透過數學建模活動培養高中生的數學創造力。教育部顧問室創造力教育計畫結案報告。
林靜雯和邱美虹(2007)。從認知方法論之向度初探高中學生模型及建模歷程之知識以真實性評量探究建模能力。論文發表於第二十三屆中華民國科學教育學術研討會,高雄,台灣。
吳怡嫺(2006)。跨年級學生氣體心智模式演變歷程之探究與分析。國立台灣師範大學科學教育研究所碩士論文(未出版)。
邱美虹(2006)。化學教育中建模模式的研發與實踐-子計畫四:以認知師徒制探討建模能力與歷程對學生學習物質科學中氧化與還原之影響。行政院國家科學委員會專題研究計畫成果報告,計畫編號NSC95-2511-S-003-025-MY2。
邱美虹(2007)。模型與建模能力之理論架構與研究工具之開發。論文發表於第二十三屆中華民國科學教育學術研討會,高雄,台灣。
邱美虹(2009)。以建模與認知師徒制開發新興科技融入高中課程之教學研究-子計畫六:建國中學高瞻計畫課程評鑑之研究。行政院國家科學委員會專題研究計畫成果報告,計畫編號NSC97-2514-S-003-003-GJ。
財團法人九九文教基金會(2000)。台灣區TRML高中數學競賽活動計畫書。2008年8月10日取自http://www.99cef.org.tw。
教育部(2004)。高級中學必修數學課程綱要草案修訂版。台北:行政院。
陳盈吉(2004)。探究動態類比對於科學概念學習與概念改變歷程之研究:以國二學生學習氣體粒子概念為例。國立台灣師範大學科學教育研究所碩士論文(未出版)。
陳婉茹(2004)。探討動態類比對於化學平衡概念學習之研究:八年級學生概念體及心智模式之變化。國立台灣師範大學科學教育研究所碩士論文(未出版)。
陳瑞麟(2004)。科學理論版本的結構與發展。台北:台灣大學出版。
張志康和邱美虹(2009)。建模能力分析指標的發展與應用-以電化學為例。(已接受)。
楊凱琳和林福來(2006)。探討高中數學教學融入建模活動的支撐策略及促進參與教師反思的潛在機制。科學教育學刊,14(5),517-543。
蔡春風和邱美虹(2007)。探討高等數學中的概念學習-以大學生解釋收斂、連續與可微之概念為例。論文發表於第二十三屆中華民國科學教育學術研討會,高雄,台灣。
鍾曉蘭、江文瑋、劉俊庚和邱美虹(2007)。以建模與認知師徒制教學探究高二學生氧化還原反應的心智模式類型及概念改變。論文發表於第二十三屆中華民國科學教育學術研討會,高雄,台灣。
蘇祐琮(2004)。全像立體影像輔助三維視覺化能力圖像表現之研究。崑山科技大學視覺傳達設計研究所碩士論文(未出版)。
Ainsworth, S. (1999). The Functions of Multiple Representations. Computer and Education, 33, 131-152.
Biggs, J. (1999). Formulating and Clarifying Curriculum Objectives: Setting up Criterion-Referenced Objectives. Teaching for Quality Learning at University (pp. 46-49). Buckingham, Society for Research into Higher Education and Open University Press.
Blomhoj, M., & Jensen, T. H. (2007). What’s All the Fuss about Competencies. In W. Blum, H. W. Henn, P. L. Galbraith, & M. Niss (Eds.), Modeling and Applications in Mathematics Education (pp. 45-56). New York, NY: Springer.
Boulter, C. J., & Buckley, B. C. (2000). Constructing a Typology of Models for Science Education. In J. K. Gilbert, & C. J. Boulter (Eds.), Developing Models in Science Education (pp. 41-57). The Netherlands: Kluwer Academic Publishers.
Carey, S., & Spelke, E. (1994). Domain Specificity and Conceptual Change. In L. A. Hirschfeld, & S. A. Gelman (Eds.), Mapping the Mind: Domain Specificity in Cognition and Culture (pp. 169-200). New York: Cambridge University Press.
Chi, M. T. H., & Roscoe, R. D. (2002). The Processes and Challenges of Conceptual Change. In M. Limon, & L. Mason (Eds.), Reconsidering Conceptual Change: Issues in Theory and Practice (pp. 3-27). The Netherlands: Kluwer Academic Publishers.
Chi, M. T. H., Slotta, J. D., & deLeeuw, N. (1994). From Things to Processes: A Theory of Conceptual Change for Learning Science Concepts. Learning and Instruction, 4, 27-43.
Clements, D. H., & Battista, M. T. (1992). Geometry and Spatial Reasoning. In D. A. Grouws (Ed.), Handbook of Research on Mathematics Teaching and Learning (pp. 420-464). New York, NY: McMillan.
Corry, L. (1993). Kuhnian Issues, Scientific Revolutions, and the History of Mathematics. Studies in History and Philosophy of Science, 24, 95-117.
Crowe, M. (1992). Afterword: A Revolution in Historiography of Mathematics? In D. Gilies (Ed.), Revolutions in Mathematics (pp. 306-316). Oxford: Oxford University Press.
Dauben, J. (1984). Conceptual Revolutions and the History of Mathematics: Two Studies in the Growth of Knowledge. In E. Mendelsohn (Ed.), Transformation and Tradition in the Sciences, Essays in Honor of I. Bernard Cohen (pp. 81-103). New York: Cambridge University Press.
deBock, D., Dooren, W. V., & Janssens, D. (2007). Studying and Remedying Students’ Modeling Competencies: Routine Behavior or Adaptive Expertise. In W. Blum, H. W. Henn, P. L. Galbraith, & M. Niss (Eds.), Modeling and applications in Mathematics Education (pp. 241-248). New York, NY: Springer.
Dehaene, S. (1998). The Number Sense: How the Mind Creates Mathematics. Harmondsworth Middlesex, England: The Penguin Press.
deJong, T., Ainsworth, S., Dobson, M., van der Hulst, A., Levonen, J., Reimann, P., Sime, J. A., Maarten, W., Spada, H., & Swaak, J. (1998). Acquiring Knowledge in Science and Mathematics: The Use of Multiple Representations in Technology-Based Learning Environments. In W. Maarten, & V. Someren (Eds.), Learning with Multiple Representations (pp. 9-40). Amsterdam: Pergamon.
Driver, R., Asoko, H., Leach, J., Mortimer, E., & Scott, P. (1994). Constructing Scientific Knowledge in the Classroom. Educational Researcher, 23(7), 5-12.
Duit, R., & Glynn, S. (1996). Mental Modeling. In G. Welford, J. Osborne, & P. Scott (Eds.), Research in Science Education in Europe (pp. 166-176). London: Falmer Press.
Fischbein, E. (1987). Intuition in Science and Mathematics. Dordrecht: Kluwer Academic Press.
Gelman, R. (2000). The Epigenesis of Mathematical Thinking. Journal of Applied Developmental Psychology, 21, 27-37.
Gilbert, J. K. (1993). Models and Modeling in Science Education. Hartfield Herts, UK: Association for Science Education.
Gilbert, J. K., Boulter, C. J., & Elmer, R. (2000). Developing Models in Science Education. Boston: Kluwer Academic Publishers.
Gravemeijer, K. (1994). Developing Realistic Mathematics Education. Utrecht: CD Beta.
Greeno, J. G. (1991). Number Sense as Situated Knowing in a Conceptual Domain. Journal for Research in Mathematics Education, 22, 170-218.
Greer, B., & Verschaffel, L. (2007). Modeling Competencies: Overview. In W. Blum, H. W. Henn, P. L. Galbraith, & M. Niss (Eds.), Modeling and applications in Mathematics Education (pp. 219-224). New York, NY: Springer.
Grosslight, L., Unger, C., Jay, E., & Smith, C. (1991). Understanding Models and Their Use in Science: Conceptions of Middle and High School Students and Experts. Journal of Research in Science Teaching, 28, 799-822.
Halliday, M. A. K. (1995). Language and the Reshaping of Human Experience. Paper Presented at the International Symposium on Critical Discourse Analysis, Athens, Greece.
Halloun, I. (1996). Schematic Modeling for Meaningful Learning of Physics. Journal of Research in Science Teaching, 33(9), 1019-1041.
Halloun, I. A. (2004). Modeling Theory in Science Education. Dordrecht: Kluwer Academic Publishers.
Harrison, A. G., & Treagust, D. F. (2000). A Typology of School Science Models. International Journal of Science Education, 22(9), 1011-1026.
Hartnett, P. M., & Gelman, R. (1998). Early Understandings of Number: Paths or Barriers to the Construction of New Understandings? Learning and Instruction, 8, 341-374.
Hatano, G. (2003). Foreword. In A. J. Baroody, & A. Dowker (Eds.), The Development of Arithmetic Concepts and Skills (pp. 6-7). Mahwah, NJ: Lawrence Erlbaum Associates.
Henning, H., & Keune, M. (2007). Levels of Modeling Competencies. In W. Blum, H. W. Henn, P. L. Galbraith, & M. Niss (Eds.), Modeling and applications in Mathematics Education (pp. 225-232). New York, NY: Springer.
Hestenes, D. (1995). Modeling Software for Learning and Doing Physics. In C. Bernardini, C. Tarsitani, & M. Vincentini (Eds.), Thinking Physics for Teaching (pp. 25-66). New York: Plenum.
Hestenes, D. (1996). Modeling Methodology for Physics Teachers. Proceedings of the International Conference on Undergraduate Physics Education. College Park, August.
Houston, K. (2007). Assessing the “Phases” of Mathematical Modeling. In W. Blum, H. W. Henn, P. L. Galbraith, & M. Niss (Eds.), Modeling and applications in Mathematics Education (pp. 249-256). New York, NY: Springer.
Ingham, A., & Gilbert, J. K. (1991). The Use of Analog Models by Students of Chemistry at Higher Education Level. International Journal of Science Education, 13(2), 193-202.
Ioannides, C., & Vosniadou, S. (2001). The Changing Meanings of Force: From Coherence to Fragmentation. Cognitive Science Quarterly, 2(1), 5-62.
Johnson-Laird, P. N. (1983). Mental Models: Towards a Cognitive Science of Language, Inference, and Consciousness. Cambridge, MA: Harvard University Press.
Johnson-Laird, P. N. (1989). Mental Models. In M. I. Posner (Ed.), Foundations of Cognitive Science (pp. 469-499). A Bradford Book London, England.
Johnstone, A. H. (1993). The Development of Chemistry Teaching. Journal of Chemical Education, 70(9), 701-705.
Justi, R., & Gilbert, J. K. (2002). Models and Modeling in Chemical Education. In J. K. Gilbert, O. deJong, R. Justi, D. F. Treagust, & J. H. van Driel (Eds.), Chemical Education: Towards Research-Based Practice (pp. 47-68). Dordrecht, The Netherlands: Kluwer Academic Publishers.
Kitcher, P. (1992). The Nature of Mathematical Knowledge. Oxford: Oxford University Press.
Knuth, E. J. (2000). Student Understanding of the Cartesian Connection: An Exploratory Study. Journal of Research in Mathematics Education, 31(4), 500-507.
Kuhn, T. (1970). The Structure of Scientific Revolutions (2nd ed.). Chicago: Chicago Press.
Lakatos, I. (1970). Falsification and the Methodology of Scientific Research Programmes. In I. Lakatos, & A. Musgrave (Eds.), Criticism and the Growth of Knowledge (pp. 91-196). Cambridge: Cambridge University Press.
Leatherdale, W. H. (1974). The Role of Analogy, Model and Metaphor in Science. New York: Elsevier.
Lesh, R., Cramer, K., Doerr, H., Post, T., & Zawojewski, J. (2003). Using a Translation Model for Curriculum Development and Classroom Instruction. In R. Lesh & H. Doerr (Eds.), Yond Constructivism: Models and Modeling Perspectives on Mathematics Problem Solving, Learning, and Teaching (pp. 449-464). Mahwah, NJ: Lawrence Erlbaum Associates.
Lesh, R., & Lehrer, R. (2003). Models and Modeling Perspectives on the Development of Students and Teachers. Mathematical Thinking and Learning, 5, 109-129.
Lesh, R., Post, T., & Behr, M. (1987). Representations and Translations among Representations in Mathematics Learning and Problem Solving. In C. Janvier (Ed.), Problems of Representation in the Teaching and Learning of Mathematics (pp. 33-40). Hillsdale, NJ: Lawrence Erlbaum Associations.
Lipton, J. S., & Spelke, E. S. (2003). Origins of Number Sense: Large Numbers Discrimination in Human Infants. Psychological Science, 4, 396-401.
Maab, K. (2004). Mathematics Modeling in Unterricht: Ergebnisse einer Empirischen Studie. Hildesheim: Franzbecker.
Mayer, R. E. (1989). Models for Understanding. Review of Educational Research, 59(1), 43-64.
Merenluoto, K., & Lehtinen, E. (2002). Conceptual Change in Mathematics: Understanding the Real Numbers. In M. Limon, & L. Mason (Eds.), Reconsidering Conceptual Change: Issues in Theory and Practice (pp. 233-258). Dordrecht: Kluwer Academic Publishers.
Moskal, B. M., & Magone, M. E. (2000). Making Sense of What Students Know: Examining the Referents, Relationships and Modes Students Displayed in Response to a Decimal Task. Educational Studies in Mathematics, 43, 313-335.
National Council of Teachers of Mathematics (1989). Curriculum and Evaluation Standards for School Mathematics. Reston, VA: Author.
Niss, M. (2002). Mathematical Competencies and the Learning of Mathematics: The Danish KOM Project. Retrieved April 23, 2008, from http:// www7.nationalacademies.org/mseb/mathematical_competencies_and_the_learning_of_mathematics.pdf.
Niss, M., Blum, W., & Galbraith, P. L. (2007). Introduction. In W. Blum, H. W. Henn, P. L. Galbraith, & M. Niss (Eds.), Modeling and applications in Mathematics Education (pp. 3-32). New York, NY: Springer.
Norman, D. A. (1983). Some Observations on Mental Models. In D. Gentner, & A. Stevens (Eds.), Mental Models (pp. 15-34). Hillsdale, NJ: Lawrence Erlbaum.
Organization for the Economic Cooperation and Development (1999). Measuring Student Knowledge and Skills: A New Framework for Assessment. Paris: OECD.
Paivio, A. (1971). Imagery and Verbal Processes. New York, NY: Holt, Rinehart and Winston.
Posner, G. J., Strike, K. A., Hewson, P. W., & Gertzog, W. A. (1982). Accommodation of a Scientific Conception: Towards a Theory of Conceptual Change. Science Education, 66, 211-227.
Pratt, D. (2000). Making Sense of the Total of Two Dice. Journal for Research in Mathematics Education, 31(5), 602-625.
Resnick, L. B., Nesher, P., Leonard, F., Magone, M., Omanson, S., & Peled, I. (1989). Conceptual Bases of Arithmetic Errors: The Case of Decimal Fractions. Journal for Research in Mathematics Education, 20, 8-27.
Saari, H. (2003). A Research-Based Teaching Sequence for Teaching the Concept of Modeling to Seventh-Grade Students. International Journal of Science Education, 25(11), 1333-1352.
Schwarz, C. V., & White, B. Y. (2005). Metamodeling Knowledge: Developing Students’ Understanding of Scientific Model. Cognition and Instruction, 23(2), 165-205.
Sfard, A. (1991). On the Dual Nature of Mathematical Conceptions: Reflections on Processes and Objects as Different Sides of the Same Coin. Educational Studies in Mathematics, 22, 1-36.
Skovsmose, O. (2000). Aphorism and Critical Mathematics Education. For the Learning of Mathematics, 20(1), 2-8.
Spada, H. (1994). Conceptual Change or Multiple Representations? Learning and Instruction, 4, 113-116.
Stafylidou, S., & Vosniadou, S. (2004). Students’ Understanding of the Numerical Value of Fractions: A Conceptual Change Approach. In L. Verschaffel and S. Vosniadou (Eds.), Extending the Conceptual Change Approach to Mathematics Learning and Teaching (pp. 503-518). Elsevier: Commenced Publication.
Sutton, C. (1992). Figuring out a Scientific Understanding. Journal of Research in Science Teaching, 30, 1215-1228.
Usiskin, Z. (2007). The Arithmetic Operations as Mathematical Models. In W. Blum, H. W. Henn, P. L. Galbraith, & M. Niss (Eds.), Modeling and applications in Mathematics Education (pp. 257-264). New York, NY: Springer.
Vergnaud, G. (1989). Obstacle of Negative Numbers in Introductive Algebra. In N. Bednarz, & C. Garnier (Eds.), Construction des Saviors (pp. 76-83). Ottawa: Agence d’ARC.
Verschaffel, L. (2002). Taking the Modeling Perspective Seriously at the Elementary School Level: Promises and Pitfalls (Plenary Lecture). In A. D. Cockburn, & E. Nardi (Eds.), Proceedings of the 26th Annual Meeting of the International Group for the Psychology of Mathematics Education, Vol.1 (pp. 64-80). Norwich, England: University of East Anglia.
Verschaffel, L., Greer, B., & deCorte, E. (2000). Making Sense of Word Problems. Lisse, the Netherlands: Swets and Zeitlinger.
Vosniadou, S. (1994). Capturing and Modeling the Process of Conceptual Change. Learning and Instruction, 4, 45-69.
Vosniadou, S. (2003). Exploring the Relationships between Conceptual Change and Intentional Learning. In G. M. Sinatra, & P. R. Pintrich (Eds.), Intentional Conceptual Change (pp. 377-406). Mahwah, NJ: Lawrence Erlbaum Associates.
Vosniadou, S., & Brewer, W. F. (1992). Mental Model of the Earth: A Study of Conceptual Change in Childhood. Cognitive Psychology, 24, 535-585.
Vosniadou, S., & Brewer, W. F. (1994). Mental Model of the Day-Night Circle. Cognitive Science, 18, 123-183.
Vosniadou, S., & Ioannides, C. (1998). From Conceptual Development to Science Education: A Psychological Point of View. International Journal of Science Education, 20(10), 1213-1230.
Vosniadou, S., & Verschaffel, L. (2004). Extending the Conceptual Change Approach to Mathematics Learning and Teaching. Learning and Instruction, 14, 445-451.
Weinert, F. E. (2001). Vergleichende Leistungsmessung in Schulen: Eine Umstrittene Selbstverstandlichkeit. In. F. E. Weinert (Ed.), Leistungsmessung in Schulen (pp. 17-31). Weinheim, Basel: Beltz Verlag.
Winn, B. (1987). Charts, Graphs, and Diagrams in Educational Materials. The Psychology of Illustration, 1, 152-198.
Wu, H. K., Krajcik, J. S., & Soloway, E. (2001). Promoting Conceptual Understanding of Chemical Representations: Students’ Use of a Visualization Tool in the Classroom. Journal of Research in Science Teaching, 38, 821-842.