Abstract
This chapter focuses on how students used various multiple visual and auditory external representations to develop their understanding of limiting reagents. They used the Synchronized Multiple Visualizations of Chemistry (SMV Chem) program. SMV Chem allowed learners to use five external representations of a given chemistry topic in any order or combination that they chose. The four visual external representations consisted of a real time video of a chemical reaction (macroscopic level of understanding), a computer animation of the reaction (microscopic level), a graphical representation (symbolic level), and a text representation of a mathematical problem concerning limiting reagents. Each visual external representation had an accompanying audio track to narrate the action that occurred during the representation. The audio track could be selected or not, according to the user’s choice. The module demonstrated the limiting reagents concept with a vinegar and baking soda reaction. We chose this module because the topic of limiting reagents provided students with many opportunities to explore the macroscopic, microscopic, symbolic, and mathematical levels in developing their understanding of the chemistry. Specifically we sought to identify the representations that were useful and then the particular characteristics that made those representations effective in helping students create their understanding.
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References
Ainsworth, S. (1999). The functions of multiple representations. Computers & Education, 33, 131–152.
Ainsworth, S. E., Bibby, P. A., & Wood, D. (2002). Examining the effects of different multiple representational systems in learning primary mathematics. The Journal of the Learning Sciences, 11(1), 25–61.
Ainsworth, S. E., & van Labeke, N. (2004). Multiple forms of dynamic representation. Learning and Instruction, 14(3), 241–255.
Ainsworth, S. E., Wood, D. J., & Bibby, P. A. (1996). Co-ordinating multiple representations in computer based learning environments. In P. Brna, A. Paiva, & J. Self (Eds.), Proceedings of the European conference of artificial intelligence in education(pp. 336–342). Lisbon: Edicoes Colibri.
Ainsworth, S. E., Wood, D. J., & O’Malley, C. (1998). There’s more than one way to solve a problem: Evaluating a learning environment to support the development of children’s multiplication skills. Learning and Instruction, 8(2), 141–157.
Barnea, N., & Dori, Y. J. (1996). Computerized molecular modeling as a tool to improve chemistry teaching [Electronic version]. Journal of Chemical Information and Computer Sciences, 36, 629–636.
Clark, J. M., & Paivio, A. (1991). Dual coding theory and education. Educational Psychology Review, 3, 149–210.
Hakerem, G., Dobrynina, G., & Shore, L. (1993, April). The effects of interactive, three dimensional high speed simulations on high school students’ conceptions of the molecular structure of water. Paper presented at the annual meeting of the National Association for Research in Science Teaching, Atlanta, Ga. Retrieved June 17, 2003, from ERIC.
Harp, S. F., & Mayer, R. E. (1997). The role of interest in learning from scientific text and illustrations: on the distinction between emotional interest and cognitive interest. Journal of Educational Psychology, 89, 92–102.
Harp, S. F., & Mayer, R. E. (1998). How seductive details do their damage: a theory of cognitive interest in science learning. Journal of Educational Psychology, 90, 414–434.
, Kelly, R. M., & Jones, L. L. (2006, April). Exploring how animations of sodium chloride dissolution affect students’ explanations. Paper presented at the National Association for Research in Science Teaching, San Francisco, CA.
Kozma, R. B., & Russell, J. (1997). Multimedia and understanding: expert and novice responses to different representations of chemical phenomenon. Journal of Research in Science Teaching, 34, 949–968.
Lester, J. C., Stone, B. A., & Stelling, G. D. (1998). Lifelike pedagogical agents for mixed-initiative problem solving in constructivist learning environments. In A. Kosba (Ed.), User modeling and user-adapted interaction (pp. 1–46). Boston, MA: Kluwer Academic.
Mayer, R. E. (1997). Are we asking the right questions? Educational Psychologist, 32, 1–19.
Mayer, R. E., & Anderson, R. B. (1991). Animations need narrations: an experimental test of dual-coding hypothesis. Journal of Educational Psychology, 83, 484–490.
Mayer, R. E., & Anderson, R. B. (1992). The instructive animation: helping students build connections between words and pictures in multimedia learning. Journal of Educational Psychology, 84, 444–452.
Mayer, R. E., Heiser, J., & Lonn, S. (2001). Cognitive constraints on multimedia learning: when presenting more material results in less understanding. Journal of Educational Psychology, 1, 187–198.
Mayer, R. E., & Moreno, R. (1998). A split-attention effect in multimedia learning: evidence for dual processing systems in working memory. Journal of Educational Psychology, 90, 312–320.
Moreno, R., & Mayer, R. E. (2002). Learning science in virtual reality multimedia environments: role of methods and media. Journal of Educational Psychology, 3, 598–610.
Moreno, R., & Mayer, R. E. (2002). Learning science in virtual reality multimedia environments: role of methods and media. Journal of Educational Psychology, 92, 117–125.
McKendree, J., Small, C., Stenning, K., & Conlon, T. (2002). The role of representation in teaching and learning critical thinking. Educational Review, 54, 57–67.
Nakhleh, M. B., Donovan, W. J., & Parrill, A. L. (2000). Evaluation of interactive technologies for chemistry websites: Educational materials for organic chemistry website (EMOC). Journal of Computers in Mathematics and Science Teaching, 19, 355–378.
Nakhleh, M. B., & Krajcik, J. S. (1993). A protocol analysis of the influence of technology on students’ actions, verbal commentary, and thought processes during the performance of acid-base titrations. Journal of Research in Science Teaching, 30(9), 1149–1168.
Nakhleh, M. B., & Krajcik, J. S. (1994). Influence of levels of information as presented by different technologies on students’ understanding of acid, base, and pH concepts, Journal of Research in Science Teaching, 31(10), 1077–1096.
Paivio, A. (1971). Imagery and cognitive processes. New York: Holt, Rinehart and Winston.
Paivio, A. (1990). Mental representations: A dual coding approach.. New York: Oxford University Press.
Pheasey, K., O’Malley, C., & Ding, S. (1997). A distributed collaborative micro-world to teach Newtonian mechanics. In S. Vosniadou, K. Matsagouras, K. Maridaki-Kassotaki, & S. Kotsanis, 7th European conference for research on learning and instruction. Athens: Gutenberg University Publications.
Russell, J. W., Kozma, R. B., Becker, D., & Susskind, T. (2000). Synchronized multiple visualizations of chemistry[CD-ROM]. John Wiley and Sons.
Russell, J. W., Kozma, R. B., Jones, T., Wykoff, J., Marx, N., & Davis, J. (1997). Use of simultaneous-synchronized macroscopic, microscopic and symbolic representations to enhance the teaching and learning of chemical concepts. Journal of Chemical Education, 74, 330–334.
Sanger, M. J., Brecheisen, D. M., & Hynek, B. M. (2001). Can computer animations affect college biology students’ conceptions about diffusion and osmosis? The American Biology Teacher, 63, 104–109.
Sanger, M. J., & Greenbowe, T. J. (2000). Addressing student misconceptions concerning electron flow in aqueous solutions with instruction including computer animations and conceptual change strategies. International Journal of Science Education, 22, 521–537.
Schoenfeld, A. H., Smith, J. P., & Arcavi, A. (1993). Learning: The microgenetic analysis of one students’ evolving understanding of a complex subject matter domain. In R. Glaser, Advances in instructional psychology volume 4,(pp. 55–175). Hillside, NJ: Earlbaum.
Strauss, A., & Corbin, J. (1998). Basics of qualitative research: Techniques and procedures for developing grounded theory (2nd ed.). Thousand Oaks, CA: Sage.
Williamson, V. M., & Abraham, M. R. (1995). The effects of computer animation on the particulate mental models of college chemistry students. Journal of Research in Science Teaching, 32, 521–534.
Wu, H., Krajcik, J., & Soloway, E. (2001). Promoting understanding of chemical representations: Students’ use of a visualization tool in the classroom. Journal of Research in Science Teaching, 38, 821–842.
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Nakhleh, M.B., Postek, B. (2008). Learning Chemistry Using Multiple External Representations. In: Gilbert, J.K., Reiner, M., Nakhleh, M. (eds) Visualization: Theory and Practice in Science Education. Models and Modeling in Science Education, vol 3. Springer, Dordrecht. https://doi.org/10.1007/978-1-4020-5267-5_10
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DOI: https://doi.org/10.1007/978-1-4020-5267-5_10
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