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Articles

Asymmetric translation between multiple representations in chemistry

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Pages 644-662 | Received 05 May 2015, Accepted 18 Jan 2016, Published online: 16 Mar 2016

References

  • Ainsworth, S. (1999). The functions of multiple representations. Computers & Education, 33(2–3), 131–152. doi: 10.1016/S0360-1315(99)00029-9
  • Ainsworth, S., Wood, D., & Bibby, P. (1996). Coordinating multiple representations in computer based learning environments. In P. Brna, A. Paiva, & J. A. Self (Eds.), Proceedings of the European conference on Artificial Intelligence in Education (pp. 336–342). Lisbon: Edicoes Colibri.
  • Ainsworth, S., Wood, D., & Bibby, P. (1998). Analysing the costs and benefits of multi-representational learning environments. In S. Vosniadou, K. Matsagouras, K. Mardaki-Kassotaki, & S. Kotsanis (Eds.), 7th European conference for research on learning and instruction (pp. 500–501). Athens: Gutenberg University.
  • Ben-Zvi, R., Eylon, B., & Silbemein, J. (1986). Is an atom of copper malleable? Journal of Chemical Education, 63(1), 64–66. doi: 10.1021/ed063p64
  • Bibby, P. A., & Payne, S. J. (1993). Internalizing and the use specificity of device knowledge. Human-Computer Interaction, 8(1), 25–56. doi: 10.1207/s15327051hci0801_2
  • Brenner, M. E., Mayer, R. E., Moseley, B., Brar, T., Duran, R., Reed, B. S., & Webb, D. (1997). Learning by understanding: The role of multiple representations in learning algebra. American Educational Research Journal, 34(4), 663–689. doi: 10.3102/00028312034004663
  • Chi, M., Feltovich, P., & Glaser, R. (1981). Categorization and representation of physics problems by experts and novices. Cognitive Science, 5, 121–152. doi: 10.1207/s15516709cog0502_2
  • Dienes, Z. P. (1973). The six stages in the process of learning mathematics. Windsor, Ontario: NFER Publishing.
  • Dugdale, S. (1982). Green globs: A micro-computer application for graphing of equations. Mathematics Teacher, 75, 208–214.
  • Freudenthal, H. (1983). Didactical phenomenology of mathematical structure. Dordrecht: Kluwer Academic.
  • Fyfe, E. R., McNeil, N. M., Son, J. Y., & Goldstone, R. L. (2014). Concreteness fading in mathematics and science instruction: A systematic review. Educational Psychology Review, 26(1), 9–25. doi:10.1007/s10648-014-9249-3
  • Gabel, D. L. (1993). Use of the particle nature of matter in developing conceptual understanding. Journal of Chemical Education, 70(3), 193–194. doi: 10.1021/ed070p193
  • Gabel, D. L., Samuel, K. V., & Hunn, D. (1987). Understanding the particulate nature of matter. Journal of Chemical Education, 64(8), 695. doi:10.1021/ed064p695
  • Gentner, D., & Markman, A. B. (1997). Structure mapping in analogy and similarity. American Psychologist, 52(1), 45–56. doi: 10.1037/0003-066X.52.1.45
  • Georgiadou, A., & Tsaparlis, G. (2000). Chemistry teaching in lower secondary school with methods based on: a) psychological theories; b) the macro, representational, and submicro levels of chemistry. Chemistry Education Research and Practice, 1(2), 217–226. doi: 10.1039/A9RP90023C
  • Gilbert, J. K., & Treagust, D. F. (Eds.). (2009a). Multiple representations in chemical education. Dordrecht: Springer.
  • Gilbert, J. K., & Treagust, D. F. (2009b). Towards a coherent model for macro, submicro, and symbolic representations in chemical education. In J. K. Gilbert & D. F. Treagust (Eds.), Multiple representations in chemical education (pp. 333–350). Dordrecht: Springer.
  • Goldstone, R. L., & Son, J. Y. (2005). The transfer of scientific principles using concrete and idealized simulations. The Journal of the Learning Sciences, 14(1), 69–110. doi: 10.1207/s15327809jls1401_4
  • Griffiths, A. K., & Preston, K. R. (1992). Grade-12 students’ misconceptions relating to fundamental characteristics of atoms and molecules. Journal of Research in Science Teaching, 29(6), 611–628. doi:10.1002/tea.3660290609
  • Hennessy, S., Twigger, D., Driver, R., O'Shea, T., O'Malley, C. E., Byard, M., … Scanlon, E. (1995). Design of a computer-augmented curriculum for mechanics. International Journal of Science Education, 17(1), 75–92. doi: 10.1080/0950069950170106
  • 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. doi:10.1080/10508400701413401
  • Holland, J. J. H. (2006). Studying complex adaptive systems. Journal of Systems Science and Complexity, 19(1), 1–8. doi: 10.1007/s11424-006-0001-z
  • Jaber, L. Z., & BouJaoude, S. (2012). A macro–micro–symbolic teaching to promote relational understanding of chemical reactions. International Journal of Science Education, 34(7), 973–998. doi:10.1080/09500693.2011.569959
  • Johnstone, A. H. (1982). Macro and microchemistry. School Science Review, 64, 377–379.
  • Johnstone, A. H. (2000a). Chemical education research: Where from here. University Chemistry Education, 4, 34–38.
  • Johnstone, A. H. (2000b). Teaching of chemistry – Logical or psychological? Chemistry Education Research and Practice Europe, 1(1), 9–15. doi: 10.1039/A9RP90001B
  • Johnstone, A. H. (2009). Multiple representations in chemical education. International Journal of Science Education, 31(16), 2271–2273. doi:10.1080/09500690903211393
  • Justi, R., Gilbert, J. K., & Ferreira, P. F. M. (2009). The application of a ‘model of modeling’ to illustrate the importance of metavisualisation in respect of the three types of representation. In J. K. Gilbert & D. F. Treagust (Eds.), Multiple representations in chemical education (pp. 285–307). Dordrecht: Springer.
  • Kaput, J. J. (1989). Linking representations in the symbol systems of algebra. In S. Wagner & C. Kieran (Eds.), Research issues in the learning and teaching of algebra (pp. 167–194). Reston, VA: NCTM.
  • Kohl, P., & Finkelstein, N. (2008). Patterns of multiple representation use by experts and novices during physics problem solving. Physical Review Special Topics – Physics Education Research, 4(1), 010111. doi:10.1103/PhysRevSTPER.4.010111
  • Kohl, P. B., Rosengrant, D., & Finkelstein, N. D. (2007). Strongly and weakly directed approaches to teaching multiple representation use in physics. Physical Review Special Topics – Physics Education Research, 3(1), 010108. doi:10.1103/PhysRevSTPER.3.010108
  • Kotovsky, L., & Gentner, D. (1996). Comparison and categorization in the development of relational similarity. Child Development, 67, 2797–2822. doi: 10.2307/1131753
  • Kozma, R. (2003). The material features of multiple representations and their cognitive and social affordances for science understanding. Learning and Instruction, 13(2), 205–226. doi: 10.1016/S0959-4752(02)00021-X
  • Kozma, R., Chin, E., Russell, J., & Marx, N. (2000). The roles of representations and tools in the chemistry laboratory and their implications for chemistry learning. The Journal of the Learning Sciences, 9(2), 105–143. doi: 10.1207/s15327809jls0902_1
  • Kozma, R. B., & Russell, J. (1997). Multimedia and understanding: Expert and novice responses to different representations of chemical phenomena. Journal of Research in Science Teaching, 34, 949–968. doi: 10.1002/(SICI)1098-2736(199711)34:9<949::AID-TEA7>3.0.CO;2-U
  • Larkin, J., & Simon, H. (1987). Why a diagram is (sometimes) worth ten thousand words. Cognitive Science, 99, 65–99. doi: 10.1111/j.1551-6708.1987.tb00863.x
  • Larkin, J. H., McDermott, J., Simon, D. P., & Simon, H. A. (1980). Models of competence in solving physics problems. Cognitive Science, 4(4), 317–345. doi: 10.1207/s15516709cog0404_1
  • 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. doi: 10.1002/tea.3660300304
  • McNeil, N. M., & Fyfe, E. R. (2012). ‘Concreteness fading' promotes transfer of mathematical knowledge. Learning and Instruction, 22(6), 440–448. doi:10.1016/j.learninstruc.2012.05.001
  • Nurrenbern, S. C., & Pickering, M. (1987). Concept learning versus problem solving: Is there a difference? Journal of Chemical Education, 64, 508. doi: 10.1021/ed064p508
  • Nyachwaya, J. M., Warfa, A. R. M., Roehrig, G. H., & Schneider, J. L. (2014). College chemistry students’ use of memorized algorithms in chemical reactions. Chemistry Education Research and Practice, 15(1), 81. doi:10.1039/C3RP00114H
  • Oliver, M. J. (1997). Visualisation and manipulation tools for modal logic (Unpublished doctoral dissertation). Open University, UK.
  • Petersen, L. a, & McNeil, N. M. (2013). Effects of perceptually rich manipulatives on preschoolers’ counting performance: Established knowledge counts. Child Development, 84(3), 1020–1033. doi:10.1111/cdev.12028
  • PhET States of Matter: Basic Simulation. (n.d.). University of Colorado, Boulder.
  • Prain, V., Tytler, R., & Peterson, S. (2009). Multiple representation in learning about evaporation. International Journal of Science Education, 31(6), 787–808. doi: 10.1080/09500690701824249
  • Prain, V., & Waldrip, B. (2006). An exploratory study of teachers’ and students’ use of multi-modal representations of concepts in primary science. International Journal of Science Education, 28(15), 1843–1866. doi:10.1080/09500690600718294
  • Ramnarain, U., & Joseph, A. (2012). Learning difficulties experienced by grade 12 South African students in the chemical representation of phenomena. Chemistry Education Research and Practice, 13(4), 462–470. doi: 10.1039/C2RP20071F
  • Rider, R. (2007). Shifting from traditional to nontraditional teaching practices using multiple representations. Mathematics Teacher, 100(7), 494–500.
  • Schnotz, W., & Kulhavy, R. W. (Eds.). (1994). Comprehension of graphics (Vol. 108). North Holland: Elsevier.
  • Schwartz, D. L. (1995). The emergence of abstract representations in dyad problem solving. The Journal of the Learning Sciences, 4(3), 321–354. doi:10.1207/s15327809jls0403_3
  • Smith, K., & Metz, P. (1996). Evaluating student understanding of solution chemistry through microscopic representations. Journal of Chemical Education, 73(3), 233–235. doi:10.1021/ed073p233
  • Son, J. Y., Smith, L. B., & Goldstone, R. L. (2011). Connecting instances to promote children's relational reasoning. Journal of Experimental Child Psychology, 108(2), 260–277. doi:10.1016/j.jecp.2010.08.011
  • Tabachneck, H., Koedinger, K., & Nathan, M. (1994). Toward a theoretical account of strategy use and sense-making in mathematics problem solving. In A. Ram & K. Eiselt (Eds.), Proceedings of the 16th annual conference of the cognitive science society (pp. 836–841). Hillsdale, NJ: LEA.
  • Tabachneck, H. J. M., Leonardo, A. M., & Simon, H. A. (1994). How does an expert use a graph? A model of visual and verbal inferencing in economics. In A. Ram & K. Eiselt (Eds.), Proceedings of the 16th annual conference of the cognitive science society (pp. 842–847). Hillsdale, NJ: LEA.
  • Taber, K. S. (2013). Revisiting the chemistry triplet: Drawing upon the nature of chemical knowledge and the psychology of learning to inform chemistry education. Chemistry Education Research and Practice, 14(2), 156–168. doi:10.1039/C3RP00012E
  • Talanquer, V. (2011). Macro, submicro, and symbolic: The many faces of the chemistry ‘triplet'. International Journal of Science Education, 33(2), 179–195. doi:10.1080/09500690903386435
  • Thompson, P. W. (1992). Notations, conventions, and constraints: Contributions to effective uses of concrete materials in elementary mathematics. Journal for Research in Mathematics Education, 23, 123. doi:10.2307/749497
  • Treagust, D., Chittleborough, G., & Mamiala, T. (2003). The role of submicroscopic and symbolic representations in chemical explanations. International Journal of Science Education, 25(11), 1353–1368. doi:10.1080/0950069032000070306
  • Tsui, C., & Treagust, D. F. (2013). Multiple representations in biological education (Vol. 7). Springer Science & Business Media. doi:10.1007/978-94-007-4192-8
  • Yarroch, W. L. (1985). Student understanding of chemical equation balancing. Journal of Research in Science Teaching, 22(5), 449–459. doi:10.1002/tea.3660220507
  • Yerushalmy, M. (1991). Student perceptions of aspects of algebraic function using multiple representation software. Journal of Computer Assisted Learning, 7, 42–57. doi: 10.1111/j.1365-2729.1991.tb00223.x

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