動態平衡是許多自然學科的基礎，但是，由於巨觀與微觀世界的差異，造成學習上的困難（van Driel, 2002）。而以Chi等人的觀點而言，動態平衡的困難點在於其本體屬性為突現本體，而非直接過程本體。於是許多研究開始設計各種教學策略，以幫助學生進行學習，而最常被提及的兩種教學方式，分別為類比（e.g. Johnstone, MacDonald, & Webb, 1977; Olney, 1988）與電腦動畫（e.g. Hameed , Hackling, & Garnett, 1993）。本研究結合這兩種方式發展出「動態類比」，以動畫的方式展現類比物與目標物的對應，冀望能夠為學生的學習帶來更多的助益。
　　依據上述的目的，本研究主要的研究問題為：一、經由類比及動態類比的教學方式，是否可以幫助學生於動態平衡單元的學習？二、經過教學之後，心智模式與概念本體的改變情形為何？三、心智模式、概念本體、學習態度對於概念學習的可能影響情形？因而本研究選擇溶解平衡、化學平衡、相平衡三個教學主題，選取三個八年級的班級，並隨機分派至對照組、類比組、以及動態類比組，以進行教學研究，並由每班中選出六位標目學生，進行晤談以瞭解學生心智模式的變動情形。
　　本研研究的結果如下：
　　1. 就概念整體的表現而言，動態類比組的表現是優於類比組的，而類比組的表現優於對照組。
　　2. 就概念本體得分而言，動態類比組與類比組於本體屬性的得分皆優於對照組，然而動態類比組與類比組有著相近的表現，兩組中產生概念跨越的學生其維持的情形也較佳。
　　3. 就心智模式而言，學生於動態平衡單元中的四種主要心智模式分別為：雙向心智模式、單向-雙向心智模式、單向心智模式、靜止模式。動態類比組後測晤談中，83%的學生其主要心智模式為雙向心智模式，而類比組為66%，對照組為50%。且關於心智模式的融貫性與一致性皆是動態類比組優於類比組，類比組優於類比組的情形。
　　4. 就情意面向而言，動態類比組認為此次教學可以幫助理解、較為有趣、而且並未造成學習上的負擔，對於本次教學所持的態度是最為正向的，而類比組次之，對照組則趨向於中性的看法。
　　5. 學生若具備較科學心智模式（R平方為0.67）、對於粒子運動的本體屬性有較好的認識（R平方為0.25）、對於本次的教學如果抱持較正向的態度（R平方0.09），那麼也就會有較佳的概念學習。研究中的發現是心智模式對於概念學習的影響最大，而本體概念次之，而情意面向的影響層面較小。

　　綜上所述，由於本研究之「類比物」──「舞者」與「目標物」──「粒子」的對應，因而在概念本體上的表現，類比組與動態類比組兩組的成效相近；而就概念完整性而言，則動態類比組較優，因此動畫似乎可以幫助建立較佳的心智模式。動態平衡概念雖難，但是，只要選擇適當的教學方式，例如：本研究的類比「舞會」或是動態類比的方式，還是可以增進學生的學習。

The concept of dynamic equilibrium has played an important role in learning chemistry. Because of the difference between macroscopic and microscopic view of phenomenon, students have difficulties to learn concepts related to equilibrium (van Driel, 2002). According to Chi’s point of view, difficulty of learning concepts of dynamic equilibrium lies in its ontological attribute which belongs to ‘emergent casual processes’, not ‘direct casual processes’. Therefore, many researchers have been engaged in designing meaningful teaching strategies helping students overcome this difficulty. Analogy (e.g. Johnstone, MacDonald, & Webb, 1977; Olney, 1988) and computer animation (e.g. Hameed, Hackling, Garnett, 1993) have been mentioned most often. This research integrated these two teaching approaches to develop Dynamic-analogy instruction, which intended to map between target domain and source domain in the filed of equilibrium. The purpose of this study was to examine how students could benefit from the instruction designed via simulation and analogies.
　According to the purpose mentioned above, the main research questions were as follows. First, could analogy and dynamic-analogy help students learn dynamic equilibrium or not? Second, how students’ mental models and conceptual ontology would be changed after instruction? Third, what are the possible relations between students’ mental models, conceptual ontology, attitudes toward learning, and concept learning? Thus, this research chose three sub-topics among dynamic equilibrium: solution equilibrium, chemical equilibrium, and phase equilibrium to fulfill the purposes. There were three 8th-grade classes randomly assigned to three groups: the comparison group, the analogy group, and the dynamic-analogy group. Six target students were interviewed from each group.
　The major results of the research were as follows:
　1. As for concept learning, both dynamic-analogy group and analogy group performed better than the comparison group. In addition, the dynamic-analogy group had the a little higher achievement than the analogy group.
　2. As for the conceptual ontology, the dynamic-analogy group and the analogy group had similar scores that revealed a better performance than the comparison group. There were more students changed from ‘direct causal process’ to ‘ emergent causal process’ in these two groups, and the retaintion of the concepts was also better.
　3. The researcher identified four mental models of dynamic equilibrium from the students’ performance. They are: first, bidirectional model; second, unidirectional model; third, unidirectional model; fourth, static model. In the dynamic-analogy group, 83% target students’ major mental models were ‘bidirectional model’ which is the scientific model, 66% for the analogy group and 50% for the comparison group . Moreover, the dynamic-analogy group had the most consistent and coherent mental model.
　4. About learning attitude, students in dynamic-analogy group thought that this teaching was interesting, not too hard to understand, and might promote the understanding. Dynamic-analogy group had the most positive attitude.
　5. Students, who had better scientific mental model(R square is 0.67), had more correct conceptual ontology attributes (R square is 0.25), had more positive attitude toward learning (R square is 0.09), would have higher scores in post test and learn better. The finding in this research was that mental model had the greatest influence in conceptual learning.

　In summary, the analogy group and dynamic-analogy group got higher scores in concept ontology test, in a result from mapping between source domain--dancers and target domain--particles. In addition, dynamic-analogy group’s was more integrity. Therefore, dynamic representation may have high potential for helping students to develop more coherent and consistent mental models. However, the result revealed the difficulty of learning dynamical equilibrium still existed. Students could learn well as long as teachers could choose a suitable instruction to promote students’ learning, for instance, the analogy -- dancing party or dynamic-analogy.

中文文獻
　林孟慧(1998)：理化類比對國三學生地球科學概念學習之影響。國立台灣師範大學科學教育研究所碩士論文。(未出版)
　林靜雯(2000)：由概念改變及心智模式初探多重類比對國小四年級學生電學概念學習之影響。國立台灣師範大學科學教育研究所碩士論文。(未出版)
　邱美虹與林靜雯(2002)：以多重類比探究兒童電流心智模式之改變。科學教育學刊，第十卷第二期，109-134。
　邱美虹(2000)：概念改變研究的省思與啟示。科學教育學刊，第八卷第一期，1-34。
　施吉安(2002)：資訊融入國民小學自然科教學可行性之研究 : 以桃園縣新路國小為例。國立臺灣師範大學工業教育研究所碩士班論文。(未出版)。
　高淑芬(1997)：類比對國二學生科學概念學習之影響。國立台灣師範大學科學教育研究所碩士班論文。(未出版)
　蔡聰暉(2001)：由心智模式探討學生導引之類比教學對國二學生溫度與熱概念學習之研究。國立台灣師範大學科學教育研究所碩士班論文。(未出版)
　劉元生(1994)：實驗教學對於國中學生溶液概念改變的影響。國立臺灣師範大學化學學系碩士班論文。(未出版)。
　藍瑋煥(2002)：國一生在網路環境學習「水」的統整課程之研究。國立臺灣師範大學科學教育研究所碩士班論文。(未出版)。
　陳智源(2003)：電腦多媒體輔助教學在高一「力與運動」課程的教學成效探討。國立臺灣師範大學物理研究所碩士班論文。(未出版)。
　孟令珠(2002)：電腦化教學策略對中文輸入學習成效之影響探討。--國立臺灣師範大學資訊教育研究所碩士班論文。(未出版)
　廖淑苹(2000)：發展國中「分子」多元媒體與概念學習研究。國立臺灣師範大學化學研究所碩士班論文。(未出版)。
英文文獻
　Ainsworth, S. E., (1999). A functional taxonomy of multiple representations. Computers and Education, 33(2/3), 131-152. ISSN 0360-1315
　Ainsworth, S. E., Bibby, P. A., & Wood, D. J. (2002). Examining the effects of different multiple representational systems in learning primary mathematics. Journal of the Learning Sciences. 11(1), 25-62.
　Anderson, B. (1990). Pupil’s conceptions of matter and its transformation (age 12-16). Studies in Science Education, 18, 53-85.
　Anderson, A., Tolmie, A., Howe, C. J., Mayes, J. T., & Mackenzie, M. (1992). Mental models of motion. In Rogers, Y., Rutherford, A., & Bibby, P. (eds.) Models in the mind: Theory, Perspective and Application. London: Academic Press, 57-71.
　Ausubel, David P. (1963). The Psychology of Meaningful Verbal Learning. New York: Grune & Stratton.
Baek, Y. K. & Layne, B. H. (1988). Color, graphics, and animation in a computer assisted learning tutorial lesson. Journal of Computer-Based Instruction, 15(4), 131-135.
　Bergqiust, W. & Heikkinen, H. (1990). Student ideas regarding chemical equilibrium. Journal of Chemical Education, 67, 1000-1003.
　Black, D. & Solomon, J. (1987). Can pupils use taught analogies for electic current? School Science Review, 69, 249-254.
　Brewer, W. F. (1987). Schemas versus mental models in human memory. In P. E. Morris (Ed.), Modeling cognition (pp. 187-197). New York: Wiley.
　Brown, D. E. (1992). Using Examples and Analogies to Remediate Misconceptions in Physics: Factors Influencing Conceptual Change. Journal of Research in Science Teaching, 29, 17-34.
　Brown, D. E. (1993). Refocusing core intuitions: a concretizing role for analogy in conceptual change. Journal of Research in Science Teaching, 30, 1273-1290.
Carson , S. R. (1999). An interactive pupil demonstration of the approach to dynamic equilibrium, Teaching Physics, 34(1), 32-33.
　Caas, J. J., Antol, A., & Quesada, J.F. (2001). The role of working memory on measuring mental models of physical systems. Psicologica, 22, 25-42.
Carey, S. (1985). Conceptual Changes in Childhood. Cambridge, MIT Press.
　Chi, M. T. H. (1992). Conceptual change within and across ontological categories: Implications for learning and discovery in sciences. In Giere R. (Ed.). Cognitive models of science: Minnesota studies in the philosophy of science (pp. 129–186). Minneapolis: University of Minnesota Press.
　Chi, M. T. H. (I997). Creativity: Shifting across ontological categories flexibly. In Ward, T. B., Smith, S. M., & Vaid J. (Eds.), Conceptual Structures and processes: Emergence, Discovery and Change. (209-234). Washington, D.C: American Psychological Association.
　Chi, M. T. H. (2000). Cognitive understanding levels. Encyclopedia of Psychology. In Kazkin, A. E. (Ed), 2:146-151. APA and Oxford University Press.
　Chi, M. T. H. (in press). Common Sense Conceptions of Emergent Processes. Journal of the Learning Sciences.
　Chi, M. T. H. & Hausmann, R. G. M. (2003). Do radical discoveries require ontological shifts? International Handbook on Innovation. Shavinina, L. V. (Ed.) Elsevier Science Ltd., 430-444.
　Chi, M. T. H. & Roscoe, R.D. (2002). The processes and challenges of conceptual change. In Limon M. & Mason, L. (Eds). Reconsidering Conceptual Change: Issues in Theory and Practice. Kluwer Academic Publishers, The Netherlands, 3-27.
　Chi, M. T. H., Slotta, J. D., & de Leeuw, N. (1994). From things to processes: A theory of conceptual change for learning science concepts. Learning and Instruction, 4, 27-43.
　Chiu, M. H., Chou, C. C., & Liu, C. J. (2002). Dynamic processes of conceptual change: analysis of constructing mental models of chemical equilibrium. Journal of research in Science Teaching, 39, 688-712.
　Clark, R. C. (2003). Building Expertise: Cognitive Methods for Training and Performance Improvement. Second Edition. International Society for Performance Improvement, Washington, D. C.
　Cooke, N. J. & Schvaneveldt, R. W. (1987). Effects of computer programming on network representations of abstract programming concepts. International Journal of Man-Machine Studies, 29, 407-427.
　Cox, R. & Brna, P. (1995). Supporting the use of external representations in problem solving: The need for flexible learning environments. Journal of Artificial Intelligence in Education, 6, 239-302
　Craik, K. (1943). The Nature of Explanation. Cambridge: Cambridge University Press.
　Curtis, R. V. & Reigeluth, C. M. (1984). The Use of Analogies in Written Text. Instructional Science, 13, 99-117.
　Davidson, R. E. (1979). The Role of Metaphor and Analogy in Learning. In levin, J, R. & Allen, V. L. (Eds) Cognitive Learning in Children: Theories and Strategies. New York.
　Davis, P. M. & Davidson, G. V. (1994). Language Is Like the Human Body: Teaching Concepts Through Analogy. Educational Technology, 34(5), 27-32.
　diSessa, A. (1993). Towards an epistemology of physics. Cognition and Instruction, 10, 2/3, 105-226.
　Driver, R., Leach, J., Scott, P., & Wood-Robinson, C. (1994). Young people's understanding of science concepts: inplications of cross-age studies for curriculum planing. Studies in Science Educatoin, 24, 75-100.
　Driver R. & Russel T. (1982). An investigation of the ideas of heat temperature and change of state of children aged between 8 and 14 years. Disponibile scrivendo a Driver, R., University of Leeds.
　Dufour-Janvier, B., Bednarz, N., & Belanger, M. (1987). Pedagogical Considerations Concerning the Problem of Representation. In: Janvier, C. (Ed.), Problems of Representation in the Teaching and Learning of Mathematics, Lawrence Erlbaum Associates, Publishers, Hillsdale, New Jersey, London.
　Duit, R. (1991). On the role of analogies and metaphors in learning science. Science Education, 75(6), 649 – 672.
Ebenezer, J. V. & Erikson, G. L. (1996). Chemistry students' concepts of solubility: A phenomenography. Science Education, 80(2), 181-201.
　Erickson, G. L. (1979). Children's Conceptions of Heat and Temperature. Science Education, 63, 221-230.
　Erickson, G. & Tiberghien, A. (1985). Heat and temperature. In Driver, R., Guesne, E., & Tiberghien, A. (Eds.), Children's ideas in science (52-83). Philadelphia, PA: Open University Press.
　Falkenhainer, B., Forbus, K., & Gentner, D. (1989). The Structure Mapping Engine: Algorithm and examples. Artificial Intelligence.
　Ferrari, M. & Chi, M. T. H. (1998). The nature of naive explanations of natural selection. International Journal of Science Education, 20 (10), 1231-1256.
　Flick, L. (1991). Where concepts meet percepts: stimulating analogical thought in children. Science Education, 75(2), 215-230.
　Genter, D. & Jeziorski, M. (1990). Historical Shifts in the Use of Analogy in Science.
　Gentner, D. (1983). Structure-mapping: A theoretical framework for analogy. Cognitive Science, 7, 155-170.
　Gentner, D. (1989). Mechanisms of analogical learning. In S. Vosniadou & A. Ortony (Eds.) Similarity and analogical reasoning. Cambridge University Press, London.
　Gentner, D. & Stevens, A. (1983). Mental Models. Hillsdale, NJ: Erlbaum.
　Glynn, S. M., Britton, B. K., Semrud-Clikeman, M., & Muth, K. D. (1989). Analogical reasoning and problem solving in textbooks. In Glover, J. A., Running, R. R., & Reynolds, C. R. (Eds.), Handbook of Creativity : Assessment, Theory and Research (383-393). New York, Plenum.
　Glynn, S. M., Duit, R., & Thiele, R. B. (1995). Teaching science with analogies:A strategy for constructing knowledge. In Glynn, S. M. & Duit, R. (Eds.). Learning science in the schools: Research reforming practice (247-273). Mahwah, NJ: Erlbaum.
　Gorodetsky, M. & Gussarsky, E. (1986). Misceonceptuallization of the chemical equilibrium concept as revealed by different evaluation methods. European Journal of Science Education, 8, 427-441.
　Gussarsky, E. & Gorodetsky, M. (1990). On the concept ‘ chemical equilibrium.’ : The associative framework. Journal of Research in Science Teaching, 27, 197-204.
　Hackling, M. W. & Garnett, P. J. (1985). Misconceptions of chemical equilibrium. European Journal of Science Education, 7, 205-214.
　Halpern, D. F., Hansen, C., & Riefer, D. (1990). Analogies as an aid to understanding and memory. Journal of Educational Psychology, 82, 298-305.
　Hameed, H., Hackling, M. W., & Garnett, P. J. (1993). Facilitating conceptual change in chemical equilibrium using a CAI strategy. International Journal of Science Education, 15(2), 221-230.
　Heywood, D. (2002). The Place of Analogies in Science Education. Cambridge Jounral of Education, 2(2), 233-247.
　Howe, C., Tolmie, A., Anderson, A., & Mackenzie, M. (1992). Conceptual knowledge in physics: The role of group interaction in computer-supported teaching. Learning and Instruction, 2, 161-183.
　Huddle, P. A., White, M., & Rogers, F. (2000). Simulations for Teaching Chemical Equilibrium. Journal of Chemical Education, 77(7), 920-926.
　Hewson, P. W. & Hewson, M. G.(1988). An Appropriate Conception of Teaching Science: A View from Studies of Science Learning. Science Education, 72(5), 597–614.
　Jih, H. J. & Reeves, T. C. (1992). Mental models: A research focus for interactive learning systems. Educational Technology Research and Development, 40 (3), 39-53.
　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 Posner, M. I. (Ed.), Foundations of Cognitive Science (469-499). A Bradford Book London, England.
　Johnstone, A. H. (1993). The development of chemistry teaching. Journal of Chemical Education, 70(9), 701-705.
　Johnstone, A. H., MacDonald, J. J. ,& Webb, G. (1977). Chemical equilibrium and its conceptual difficulties. Education in Chemistry, 14, 169-171.
　Keil, F. C. (1979). Semantic and conceptual development. Cambridge, MA: Harvard University Press.
　Keller, J. M. (1983). Motivational Design Of Instruction. In Reigeluth, C. M. (Eds). Instructional Design Theories and Models: An Overview of Their Current Status. Lawrence Arlbaum Associates, Inc. New Jersey.
　Kesidou, S. & Duit, R. (1993). Student‘s con- ceptions of the second law of thermodynamics – an interpretive study. Journal of Research in Science Teaching, 30(1), 85-106.
　Kuhn, T. S. (1977) The Essential Tension. Selected Studies in Scientific Tradition and Change. Chicago, University of Chicago Press
　Lee, O., Eichinger, D. C., Anderson, C. W., Berkheimer, G. D., & Blakeslee, T. D. (1993). Changing middle school students’ conceptions of matter and molecules. Journal of Research in Science Teaching, 30(3), 249-270.
　Lesh, R., Post, T., & Behr, M. (1987). Representations and translations among representations in mathematics learning and problem solving. In: Janvier C. (Ed.) Problems of representation in the teaching and learning of mathematics. Hillsdale, NJ: Lawrence Erlbaum Associates. 33-40.
　Levin, J. R., Anglin, G. J., & Carney, R. N. (1987). On empirically validating functions of pictures in prose, in: Willows, D.M. & Houghton, H.A. (Eds.), The Psychology of Illustration. Vol. 1: Basic Research, New York: Springer, 1-50.
　Levin, J. R. & et Lesgold, A. M. (1978). On pictures in prose. Educational Communication and Technology Journal, 26, 233-243.
　Longden, K., Black, P., & Solomon, J. (1991). Children’s interpretation of dissolving. International Journal of Science Education, 13(1), 59-68.
　Mayer, R. E. (1997). Multimedia learning: Are we asking the right questions? Educational Psychologist, 32, 1-19
　Mayer, R. E. & Sims, V. K. (1994). For whom is a picture worth a thousand words? Extensions of a dual-coding theory of multimedia learning, Journal of Educational Psychology , 86(3), 389-401.
　Morecroft, J. D. W., & Sterman, J. D. (1994). Modeling for Learning Organizations. Portland, OR: Productivity Press.
　Mccoy, S. H. (1996). A study of the use of analogy and models to promote conceptual change and overcome misconceptions about chemical equilibrium.
　National Council of Teachers of Mathematics. (1989) Curriculum and Evaluation Standards for School Mathematics. Reston, VA: Author.
　Navarro, R.; Caas, J. J.; & Bajo, M. T. (1996) Pictorial aids in computer use. In Green, T. R. G.; Caas, J. J.; Warren, C. (eds.). Proc. of the 8 Th European Conference on Cognitive Ergonomics. 77-82. Granada.
　Norman, D. A. (1983). Some observations on mental models. In Gentner, D. & Stevens, A. (Eds.), Mental models (15-34). Hillsdale, NJ: Lawrence Erlbaum.
　Olney, D. (1988). Some analogies for teaching rates/equilibrium, Journal of. Chemical. Education. 65 (1988) 696.
　Osborne, R. J. & Cosgrove, M. M. (1983). Children’s conceptions of the changes of water. Journal of Research in Science Teaching, 20(9), 825-835.
　Paivio, A. (1971). Imagery and Verbal Processes. New York: Holt, Rinehart & Winston.
　Park, O. C. & Gittelman, S. S. (1992). Selective Use of Animation and Feedback in Computer-Based Instruction. Educational Technology, Research and Development, 40(4), 27-38.
　Park, O. C. & Gittelman, S. S. (1995). Dynamic characteristics of mental models and dynamic visual displays. Instructional Science, 23, 303-320.
　Park, O. C. & Hopkins, R. (1993). Instructional conditions for using dynamic visual displays. Instructional Science, 21, 427-449.
　Pedrosa, M. A. & Dias, M. H. (2000). Chemistry textbook approaches to chemical equilibrium and student alternative conceptions. Chemistry Education: Research and Practice in Europe, 1(2), 227-236.
　Peters, H. J. & Daiker, K. C. (1982). Graphics and animation as instructional tools. Pipeline, 7 , 11-13.
　Pintrich, P., Marx, R., & Boyle, R. (1993). Beyond cold conceptual change: The role of motivational beliefs and classroom contextual factors in the process of conceptual change. Review of Educational Research, 63, 167-199.
　Posner, G., Strike, K., Hewson, P., & Gertzog, W. (1982). Accommmodation of a scientific conception: Toward a theory of conceptual change. Science Education, 66(2), 211-227.
　Reigeluth, C. M. & Stein, F. S. (1983). The elaboration theory of instruction. In Reigeluth, C. M. (Ed.), Instructional-design theories and models: An overview of their current status (Vol. 1). Hillsdale, NJ: Lawrence Erlbaum Associates.
　Rickheit, G. & Sichelschmidt, L. (1999). Mental Models: Some Answers, Some Questions, Some Suggestions. In: Rickheit, G. & Habel, C. (eds.), Mental Models in Discourse Processing and Reasoning, Amsterdam: Elsevier, 1999, S. 9-38.
　Rieber, L. P. (1989). A Review of Animation research in Computer-based Instruction. In Proceedings of Selected Research Papers presented at the Annual Meeting of the Association for Educational Communications and Technology. Dallas, Texas.
　Rieber, L. P. (1990). Animation in computer based instruction. ETR&D, 38(1), 77-86.
　Rieber, L. P., Boyce, M. J., & Assad, C. (1990). The effects of computer animation on adult learning and retrieval tasks. Journal of Computer-Based Instruction, 17(2), 46-52.
　Rieber, L. & Hannafin, M. (1988). The effects of textual and animated orienting activities and practice on learning from computer based instruction. Computers in the Schools, 5, 77-89.
　Rigney, J. W. & et Lutz, K. A. (1976). Effect of graphic analogies of concepts in chemistry on learning and attitude. Journal of Educational Psychology, 68 (3), 305-311.
　Roberts, D. L. & Stephens, L. J. (1999). The Effect of the Frequency of Usage of Computer Software in High School Geometry. Journal of Computers in Mathematics and Science Teaching. 18(1), 23-30.
　Rochowicz, J. J. (1996). The Impact of Using Computers and Calculators on Calculus Instruction: Various Perceptions. Journal of Computers in Mathematics and Science Teaching 15(4), 387-399.
　Rumelhart, D. E. & Norman, D. A. (1981). Analogical Processes in Learning. In Anderson, J. R. (Eds). Cognitive Skills and Their Acquisitions. Lawrence Erlbaum Associates. Hillsdale, new Jersey.
　Sales, G. C. & Williams, M. D. (1988). The effect of adaptive control of feedback in computer-based instruction. Journal of Research in Computing in Education, 21 (1), 97-111.
　Schnotz, W. (2002) Towards an integrated view of learning from text and visual displays,Educational Psychology Review, 14 (1), pp. 101-120.
　Segre, G. & Giani, U. (1987). Analogical reasoning and formalization in transport processes. In Novak, J. (Ed.), Proceedings of the 2nd International Seminar Misconceptions and Educational Strategies in Science and Mathematics. Ithaca, NY: Cornell University, vol. 1, 420-424.
　Simons, P. R. J. (1984). Instructing with Analogies. Journal of Educatonal Psychology, 76(3), 513-527.
　Slotta, J. D., Chi, M. T. H., & Joram, E. (1995). Assessing students’ misclassifications of physics concepts: An ontological basis for conceptual change. Cognition and Instruction, 13, 373-400.
　Spiro, R. J., Feltovich, P. J., Coulson, R. L., & Anderson D. K. (1989). Multiple analogies for analogy-induced misconception in advanced knowledge acquisition. In Vosniadou, S.& Ortony, A. (Eds.), Similarity and Analogical Readoning. Cambridge, England: Cambridge University Press, pp. 498-531.
　Stepick, D. A. & Newby, T. J. (1988). Analogizing as an Instructional Strategy. Performance and Instruction, 27(9), 21-23.
　Thagard P. (1992a). “Analogy, Explanation and Education”,Journal of Research in Science Teaching , 29 (6), 537-544.
　Thagard, P. (1992b). Conceptual revolutions. Princeton,. NJ: Princeton University Press.
　Thomas, P. L. & Schwenz, R. W. (1998). College physical chemistry students’ conceptions of equilibrium and fundamental thermodynamics. Journal of Research in Science Teaching, 35, 1151-1160.
　Tyson, L. M., Venville, G. J., Harrison, A. G., & Treagust, D. F. (1997). A multidimensional framework for interpreting conceptual change events in the classroom. Science Education, 81, 387-404.
　Van Driel, J. H., De Vos, W., Verloop, N., & Dekkers, H. (1998). Developing secondary students’ conceptions of chemical reactions: the introduction of chemical equilibrium. International Journal of Science Education, 20, 379-392.
　Van Driel, J. H.& Graber W. (2002). The teaching and learning of chemical equilibrium.
　Venville, G. J. & Treagust, D. F. (1998). Exploring conceptual change in genetics using a multidimensional interpretative framework. Journal of Research in Science Teaching, 35, 1031-1055.
　Vosniadou, S. (1992). Knowledge acquisition and conceptual change. Applied Psychology: An International Review, 41(4), 347-357.
　Vosniadou, S. & Brewer, W. F. (1987). Theories of knowledge restructuring in development. Review of Educational Research, 57, 51-67.
　Vosniadou, S. & Brewer, W. F. (1992). Mental models of the earth: A study of conceptual change in childhood. Cognitive Psychology, 24, 535-585.
　Vosniadou, S. & Brewer, W. F., (1994). Mental models of the day/night cycle. Cognitive Science, 18, 123-124.
　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. & Ortony, A. (1989). Similarity and analogical reasoning, Cambridge University Press.
　Wheeler, A. E. & Kass, H. (1978). Student misconceptions in chemical equilibrium. Science Education, 62, 223-232.
　White, B. Y. & Frederiksen, J. R. (1990). Causal model progressions as a foundation for intelligent learning environments. Artificial Intelligence, 42, 99-157.
　Westbrook, S. L. & Marek, E. A. (1991). A cross-age study of student understanding of the concept of diffusion. Journal of Research in Science Teaching. 28(8):649-660.
　Young, R. M. (1983). Surrogates and mappings: two kinds of conceptual models for interactive devices. In Gentner, D. & Stevens, A. L. (Eds.) Mental Models. Hillsdale: NJ: LEA.