The Role and Potential Dangers of Visualisation when Learning about Sub-Microscopic Explanations in Chemistry Education
Keywords:
Chemistry education, Representational levels, Visualisation, Students’ misconceptions
Abstract
The core of theory-driven chemistry education consists of the constant shift between the different representational domains of chemical thinking: the macroscopic, the sub-microscopic, and the symbolic domains. Because the sub-microscopic domain can neither be seen nor directly visualised, it requires specific forms of visualisation, i.e. pictures and animations illustrating the model-based level of discrete particles, atoms, or molecular structures. This paper considers the central role visualisations play when learning about the model-based, sub-microscopic level, but it also reflects the dangers inherent in employing insufficiently examined, poorly considered, or even misleading visualisations. This is outlined using different examples taken from both textbooks for lower secondary chemistry education (for students aged 10 to 15) and from the internet. Implications for structuring and using sub-micro visualisations in chemistry education are also given.
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References
Andersson, B. (1990). Pupils’ conceptions of matter and its transformation (age 12–16). Studies in
Science Education, 18, 53–85.
Ardac, D., & Akaygun, S. (2005). Using static and dynamic visuals to represent chemical change at
molecular level. International Journal of Science Education, 27(11), 1269–1298.
Azevedo, R. (2004). Using hypermedia as a metacognitive tool for enhancing student learning? The role of self-regulated learning. Educational Psychologist, 40(4), 199–209.
Barnea, N., & Dori, Y. (1999). High-school chemistry students’ performance and gender differences in a computerised molecular modelling learning environment. Journal of Science Education and Technology, 8(4), 257–271.
Bodner, G. M. (1986). Constructivism – A theory of knowledge. Journal of Chemical Education,
63(10), 873–878.
Borges, A. T., & Gilbert, J. K. (1999). Mental models of electricity. International Journal of Science
Education, 21(1), 95–117.
Brandt, L., Elen, J., Hellemans, J., Heerman, L., Couwenberg, I., Volckaert, L., & Morisse, H. (2001).
The impact of concept mapping and visualization on the learning of secondary school chemistry
students. International Journal of Science Education, 23(12), 1303–1313.
Coll, R. K., & Treagust, D. F. (2001). Learners’ mental models of chemical bonding. Research in
Science Education, 31, S., 357–382.
Costa, N., Marques, L., & Kempa, R. (2000). Science teachers’ awareness of findings from education research. Chemistry Education Research and Practice, 1, 31–36.
de Jong, O. (2000a). Crossing the borders: chemical education research and teaching practice.
University Chemistry Education, 4(1), 29–32.
de Jong, O. (2000b). How to teach the concept of heat of reaction: A study of prospective teachers’ initial ideas. Chemistry Education Research and Practice, 1, 91–96.
Eilks, I. (2003). Students’ understanding of the particulate nature of matter and some misleading
illustrations from textbooks. Chemistry in Action, (69), 35–40.
Eilks, I., Möllering, J., & Valanides, N. (2007). Seventh-grade students’ understanding of chemical
reactions – Reflections from an action research interview study. Eurasia Journal of Mathematics,
Science and Technology Education, 4(3), 271–286.
Eilks, I., Witteck, T., & Pietzner, V. (2009). A critical discussion of the efficacy of using visual
learning aids from the Internet to promote understanding, illustrated with examples explaining the Daniell voltaic cell. Eurasia Journal of Mathematics, Science and Technology Education, 6(2), 145–152.
Eilks, I., Witteck, T., & Pietzner, V. (2010). Using multimedia learning aids from the Internet for
teaching chemistry – Not as easy as it seems? In S. Rodrigues (Ed.), Multiple Literacy and Science
Education: ICTS in Formal and Informal Learning Environments (pp. 49–69). Hershey: IGI Global.
Fehring, H. (2010). Multiple literacy in the ICT age: implications for teachers and teacher educators, an Australian perspective. In S. Rodrigues (Ed.), Multiple Literacy and Science Education: ICTS in Formal and Informal Learning Environments (pp. 180–206). Hershey: IGI Global.
Fischer, W., & Glöckner, W. (1994). Stoff und Formel [Matter and formula]. Bamberg: C. C. Buchner.
Garnett, P. J., Garnett, P. J., & Hackling, M. W. (1995). Students´ alternative conceptions in chemistry: A review of research and implications for teaching and learning. Studies in Science Education, 25, 69–95.
Goodwin, A. (2000). The teaching of chemistry: Who is the learner? ChemistryEducation: Research
and Practice, 1, 51–60.
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(9), 799–822.
Häusler, K., & Schmidkunz, H. (1996). Elemente der Zukunft: Chemie [Elements of the future:
chemistry]. München: Oldenbourg.
Hill, D. (1988). Misleading illustrations. Research in Science Education, 18, 290–297.
Jones, L. L., Jordan, K. D., & Stillings, N. A. (2005). Molecular visualization in chemistry education:
the role of multidisciplinary collaboration. Chemistry Education Research and Practice, 6(3), 136–149.
Johnson, P. (1998). Progression in children’s understanding of a ‘basic’ particle theory: a longitudinal study. International Journal of Science Education, 20(4), 393–412.
Johnstone, A. H. (1991). Why is science difficult to learn? Things are seldom what they seem. Journal of Computer Assisted Learning, 7(2), 75–83.
Justi, R. S., & Gilbert, J. K. (2002a). Science teachers’ knowledge about and attitudes towards the
use of models and modelling in learning science. International Journal of Science Education, 24(12), 1273–1292.
Justi, R. S., & Gilbert, J. K. (2002b). Models and modelling in chemistry education. In J. K. Gilbert, O.
de Jong, R. Justi, D. F. Treagust & J. H. van Driel (Eds.), Chemical Education: Towards research-based practice (pp. 47–68). Dordrecht: Kluwer.
Kelly, R. M., & Jones, L. L. (2007). Exploring How Different Features of Animations of Sodium
Chloride Dissolution Affect Students’ Explanations. Journal of Science Education and Technology,
16(5), 413–429.
Kozma, R., & Russell, J. (2005a). Students becoming chemists: Developing representational
competence. In J. K. Gilbert (Ed.), Visualization in science education (pp. 121–145). Dordrecht:
Springer.
Kozma, R., & Russell, J. (2005b). Multimedia learning of chemistry. In R. Mayer (Ed.), The
Cambridge handbook of multimedia learning (pp. 409–428). New York: Cambridge University Press.
Kuhn, W. (1996). Lehrbuch der Physik [Textbook of physics]. Braunschweig: Westermann
Lee, H. (2007). Instructional design of web-based simulations for learners with different levels of
spatial ability. Instructional Science, 35, 467–479.
Lee, O., Eichinger, D. C., Anderson, C. W., Berkheimer, G. D., & Blakeslee, T. S. (1993). Changing
middle school students’ conceptions of matter and molecules. Journal of Research in Science Teaching, 30(3), 249–270.
Levie, W. H., & Lentz, R. (1982). Effects of text illustrations: A review of research. Educational
Communication and Technology Journal, 30(4), 195–232.
Mayer, R. E. (2003). The promise of multimedia learning using the same instructional design
methods across different media. Learning and Instruction, 13(2), 125–140.
Niaz, M., & Robinson, W. R. (1993). Teaching algorithmic problem solving or conceptual
understanding: Role of developmental level, mental capacity, and cognitive style. Journal of Science Education and Technology, 2(2), 407–416.
Niaz, M. (1998). From cathode rays to alpha particles to quantum of action: A rational reconstruction of structure of the atom and its implications for chemistry textbooks. Science Education, 82, 527–552.
Noh, T., & Scharmann, L. C. (1997). Instructional influence of a molecular-level pictorial
presentation of matter on students’ conceptions and problem-solving ability. Journal of Research in Science Teaching, 34(2), 199–217.
Novick, S., & Nussbaum, J. (1978). Junior high school pupils’ understanding of the particulate nature of matter: an interview study. Science Education, 62(3), 273–281.
Osborne, R. J., Bell, B. F., & Gilbert, J. K. (1983). Science teaching and children’s views of the world.
European Journal of Science Education, 5(1), 1–14.
Pfundt, H. (1975). Ursprüngliche Erklärungen der Schüler für chemische Vorgänge [Original
students’ explanations of chemical phenomena]. Der Mathematische und Naturwissenschaftliche
Unterricht, 28(3), 157–162.
Pfundt, H. (1982). Vorunterrichtliche Vorstellungen von stofflicher Veränderung [Pre-instructional
imaginations of material change]. Chimica Didactica, 8, 161–180.
Plass, J. L., Milne, C., Homer, B. D., Schwartz, R. N., Hayward, E. O., Jordan, T., Verkuilen, J., Ng,
F., Wang, Y., & Barrientos, J. (2012). Investigating the effectiveness of computer simulations for
chemistry learning. Journal of Research in Science Teaching, 49(3), 394–419.
Ploetzner, R., Bodemer, D., & Neudert, S. (2008). Successful and less successful use of dynamic
visualizations. In R. Lowe & W. Schnotz (Eds.), Learning with Animation – Research Implications for Design (pp. 71–91). New York: Cambridge University Press.
Posner, G. J., Strike, K. A., Hewson, P. W., & Gertzog, W. A. (1982). Accommodation of a scientific
conception: Toward a theory of conceptual change. Science Education, 66(2), 211–227.
Sanger, M. J., & Greenbowe, T. J. (2000). Addressing student misconceptions concerning electron
flow in electrolyte solutions with instruction including computer animations and conceptual change strategies. International Journal of Science Education, 22(5), 521–537.
Schnotz, W., & Bannert, M. (2003). Construction and interference in learning from multiple
respresentations. Learning and Instruction, 13(2), 117–123.
Schwartz, N., Andersen, C., Hong, N., Howard, B., & McGee, S. (2004). The influence of
metacognitive skills on learners’ memory of information in a hypermedia environment. Journal of
Educational Computing Research, 31(1), 77–93.
Sprotte, J. A., & Eilks, I. (2007). Introducing the particulate nature of matter – Results from a case
study on experienced German Science Teachers’ PCK of models and modelling. Paper presented at the 6th Conference of the European Science Education Research Association, Malmoe, Sweden.
Stavy, R. (1990). Children’s conception of changes in the state of matter: from liquid (or solid) to gas. Journal of Research in Science Teaching, 30(3), 247–266.
Stavy, R. & Stachel, D. (1985). Children’s ideas about ‘solid’ and ‘liquid’. European Journal of Science Education, 7, 407–421.
Stieff, M. (2011). Improving representational competence using molecular simulations embedded in inquiry activities. Journal of Research in Science Teaching, 48(10), 1137–1158.
Taber, K. S. (2001a). Constructing chemical concepts in the classroom: Using research to inform
practice. Chemistry Education Research and Practice, 2, 43–51.
Taber, K. S. (2001b). Building the structural concepts of chemistry: some considerations from
educational research. Chemistry Education Research and Practice, 2, 123–158.
Taber, K. (2008). Towards a curricular model of the nature of science. Science & Education, 17(2–3), 179–218.
Tausch, M., & von Wachtendonk, M. (1996). Stoff, Formel, Umwelt [Matter, formula, envrionment].
Bamberg: C. C. Buchner.
Tsui, C.-Y., & Treagust, D. (2004). Motivational aspects of learning genetics with interactive
multimedia. The American Biology Teacher, 66(4), 277–285.
Valanides, N. (2000a). Primary student teachers’ understanding of the particulate nature of matter and its transformations during dissolving. Chemistry Education Research and Practice, 1, 249–262.
Valanides, N. (2000b). Primary student teachers’ understanding of the process and effects of
distillation. Chemistry Education Research and Practice, 1, 355–364.
Van Driel, J. H., & Verloop, N. (1999). Teachers’ knowledge of models and modelling in science.
International Journal of Science Education, 21(11), 1141–1153.
Wandersee, J. H., Mintzes, J. J., & Novak, J. D. (1994). Research on alternative conceptions in science. In D. L. Gabel (Ed.), Handbook of research in science teaching and learning (pp.177–210). New York: Macmillan.
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(5), 521–534.
Yang, E.-M., Greenbowe, T. J., & Andre, T. (2004). The effective use of an interactive software
program to reduce students’ misconceptions about batteries. Journal of Chemical Education, 81(4), 587–595.
Zhang, Z. H., & Linn, M. C. (2011). Can generating representations enhance learning with dynamic
visualizations? Journal of Research in Science Teaching, 48(10), 1177–1198.
Science Education, 18, 53–85.
Ardac, D., & Akaygun, S. (2005). Using static and dynamic visuals to represent chemical change at
molecular level. International Journal of Science Education, 27(11), 1269–1298.
Azevedo, R. (2004). Using hypermedia as a metacognitive tool for enhancing student learning? The role of self-regulated learning. Educational Psychologist, 40(4), 199–209.
Barnea, N., & Dori, Y. (1999). High-school chemistry students’ performance and gender differences in a computerised molecular modelling learning environment. Journal of Science Education and Technology, 8(4), 257–271.
Bodner, G. M. (1986). Constructivism – A theory of knowledge. Journal of Chemical Education,
63(10), 873–878.
Borges, A. T., & Gilbert, J. K. (1999). Mental models of electricity. International Journal of Science
Education, 21(1), 95–117.
Brandt, L., Elen, J., Hellemans, J., Heerman, L., Couwenberg, I., Volckaert, L., & Morisse, H. (2001).
The impact of concept mapping and visualization on the learning of secondary school chemistry
students. International Journal of Science Education, 23(12), 1303–1313.
Coll, R. K., & Treagust, D. F. (2001). Learners’ mental models of chemical bonding. Research in
Science Education, 31, S., 357–382.
Costa, N., Marques, L., & Kempa, R. (2000). Science teachers’ awareness of findings from education research. Chemistry Education Research and Practice, 1, 31–36.
de Jong, O. (2000a). Crossing the borders: chemical education research and teaching practice.
University Chemistry Education, 4(1), 29–32.
de Jong, O. (2000b). How to teach the concept of heat of reaction: A study of prospective teachers’ initial ideas. Chemistry Education Research and Practice, 1, 91–96.
Eilks, I. (2003). Students’ understanding of the particulate nature of matter and some misleading
illustrations from textbooks. Chemistry in Action, (69), 35–40.
Eilks, I., Möllering, J., & Valanides, N. (2007). Seventh-grade students’ understanding of chemical
reactions – Reflections from an action research interview study. Eurasia Journal of Mathematics,
Science and Technology Education, 4(3), 271–286.
Eilks, I., Witteck, T., & Pietzner, V. (2009). A critical discussion of the efficacy of using visual
learning aids from the Internet to promote understanding, illustrated with examples explaining the Daniell voltaic cell. Eurasia Journal of Mathematics, Science and Technology Education, 6(2), 145–152.
Eilks, I., Witteck, T., & Pietzner, V. (2010). Using multimedia learning aids from the Internet for
teaching chemistry – Not as easy as it seems? In S. Rodrigues (Ed.), Multiple Literacy and Science
Education: ICTS in Formal and Informal Learning Environments (pp. 49–69). Hershey: IGI Global.
Fehring, H. (2010). Multiple literacy in the ICT age: implications for teachers and teacher educators, an Australian perspective. In S. Rodrigues (Ed.), Multiple Literacy and Science Education: ICTS in Formal and Informal Learning Environments (pp. 180–206). Hershey: IGI Global.
Fischer, W., & Glöckner, W. (1994). Stoff und Formel [Matter and formula]. Bamberg: C. C. Buchner.
Garnett, P. J., Garnett, P. J., & Hackling, M. W. (1995). Students´ alternative conceptions in chemistry: A review of research and implications for teaching and learning. Studies in Science Education, 25, 69–95.
Goodwin, A. (2000). The teaching of chemistry: Who is the learner? ChemistryEducation: Research
and Practice, 1, 51–60.
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(9), 799–822.
Häusler, K., & Schmidkunz, H. (1996). Elemente der Zukunft: Chemie [Elements of the future:
chemistry]. München: Oldenbourg.
Hill, D. (1988). Misleading illustrations. Research in Science Education, 18, 290–297.
Jones, L. L., Jordan, K. D., & Stillings, N. A. (2005). Molecular visualization in chemistry education:
the role of multidisciplinary collaboration. Chemistry Education Research and Practice, 6(3), 136–149.
Johnson, P. (1998). Progression in children’s understanding of a ‘basic’ particle theory: a longitudinal study. International Journal of Science Education, 20(4), 393–412.
Johnstone, A. H. (1991). Why is science difficult to learn? Things are seldom what they seem. Journal of Computer Assisted Learning, 7(2), 75–83.
Justi, R. S., & Gilbert, J. K. (2002a). Science teachers’ knowledge about and attitudes towards the
use of models and modelling in learning science. International Journal of Science Education, 24(12), 1273–1292.
Justi, R. S., & Gilbert, J. K. (2002b). Models and modelling in chemistry education. In J. K. Gilbert, O.
de Jong, R. Justi, D. F. Treagust & J. H. van Driel (Eds.), Chemical Education: Towards research-based practice (pp. 47–68). Dordrecht: Kluwer.
Kelly, R. M., & Jones, L. L. (2007). Exploring How Different Features of Animations of Sodium
Chloride Dissolution Affect Students’ Explanations. Journal of Science Education and Technology,
16(5), 413–429.
Kozma, R., & Russell, J. (2005a). Students becoming chemists: Developing representational
competence. In J. K. Gilbert (Ed.), Visualization in science education (pp. 121–145). Dordrecht:
Springer.
Kozma, R., & Russell, J. (2005b). Multimedia learning of chemistry. In R. Mayer (Ed.), The
Cambridge handbook of multimedia learning (pp. 409–428). New York: Cambridge University Press.
Kuhn, W. (1996). Lehrbuch der Physik [Textbook of physics]. Braunschweig: Westermann
Lee, H. (2007). Instructional design of web-based simulations for learners with different levels of
spatial ability. Instructional Science, 35, 467–479.
Lee, O., Eichinger, D. C., Anderson, C. W., Berkheimer, G. D., & Blakeslee, T. S. (1993). Changing
middle school students’ conceptions of matter and molecules. Journal of Research in Science Teaching, 30(3), 249–270.
Levie, W. H., & Lentz, R. (1982). Effects of text illustrations: A review of research. Educational
Communication and Technology Journal, 30(4), 195–232.
Mayer, R. E. (2003). The promise of multimedia learning using the same instructional design
methods across different media. Learning and Instruction, 13(2), 125–140.
Niaz, M., & Robinson, W. R. (1993). Teaching algorithmic problem solving or conceptual
understanding: Role of developmental level, mental capacity, and cognitive style. Journal of Science Education and Technology, 2(2), 407–416.
Niaz, M. (1998). From cathode rays to alpha particles to quantum of action: A rational reconstruction of structure of the atom and its implications for chemistry textbooks. Science Education, 82, 527–552.
Noh, T., & Scharmann, L. C. (1997). Instructional influence of a molecular-level pictorial
presentation of matter on students’ conceptions and problem-solving ability. Journal of Research in Science Teaching, 34(2), 199–217.
Novick, S., & Nussbaum, J. (1978). Junior high school pupils’ understanding of the particulate nature of matter: an interview study. Science Education, 62(3), 273–281.
Osborne, R. J., Bell, B. F., & Gilbert, J. K. (1983). Science teaching and children’s views of the world.
European Journal of Science Education, 5(1), 1–14.
Pfundt, H. (1975). Ursprüngliche Erklärungen der Schüler für chemische Vorgänge [Original
students’ explanations of chemical phenomena]. Der Mathematische und Naturwissenschaftliche
Unterricht, 28(3), 157–162.
Pfundt, H. (1982). Vorunterrichtliche Vorstellungen von stofflicher Veränderung [Pre-instructional
imaginations of material change]. Chimica Didactica, 8, 161–180.
Plass, J. L., Milne, C., Homer, B. D., Schwartz, R. N., Hayward, E. O., Jordan, T., Verkuilen, J., Ng,
F., Wang, Y., & Barrientos, J. (2012). Investigating the effectiveness of computer simulations for
chemistry learning. Journal of Research in Science Teaching, 49(3), 394–419.
Ploetzner, R., Bodemer, D., & Neudert, S. (2008). Successful and less successful use of dynamic
visualizations. In R. Lowe & W. Schnotz (Eds.), Learning with Animation – Research Implications for Design (pp. 71–91). New York: Cambridge University Press.
Posner, G. J., Strike, K. A., Hewson, P. W., & Gertzog, W. A. (1982). Accommodation of a scientific
conception: Toward a theory of conceptual change. Science Education, 66(2), 211–227.
Sanger, M. J., & Greenbowe, T. J. (2000). Addressing student misconceptions concerning electron
flow in electrolyte solutions with instruction including computer animations and conceptual change strategies. International Journal of Science Education, 22(5), 521–537.
Schnotz, W., & Bannert, M. (2003). Construction and interference in learning from multiple
respresentations. Learning and Instruction, 13(2), 117–123.
Schwartz, N., Andersen, C., Hong, N., Howard, B., & McGee, S. (2004). The influence of
metacognitive skills on learners’ memory of information in a hypermedia environment. Journal of
Educational Computing Research, 31(1), 77–93.
Sprotte, J. A., & Eilks, I. (2007). Introducing the particulate nature of matter – Results from a case
study on experienced German Science Teachers’ PCK of models and modelling. Paper presented at the 6th Conference of the European Science Education Research Association, Malmoe, Sweden.
Stavy, R. (1990). Children’s conception of changes in the state of matter: from liquid (or solid) to gas. Journal of Research in Science Teaching, 30(3), 247–266.
Stavy, R. & Stachel, D. (1985). Children’s ideas about ‘solid’ and ‘liquid’. European Journal of Science Education, 7, 407–421.
Stieff, M. (2011). Improving representational competence using molecular simulations embedded in inquiry activities. Journal of Research in Science Teaching, 48(10), 1137–1158.
Taber, K. S. (2001a). Constructing chemical concepts in the classroom: Using research to inform
practice. Chemistry Education Research and Practice, 2, 43–51.
Taber, K. S. (2001b). Building the structural concepts of chemistry: some considerations from
educational research. Chemistry Education Research and Practice, 2, 123–158.
Taber, K. (2008). Towards a curricular model of the nature of science. Science & Education, 17(2–3), 179–218.
Tausch, M., & von Wachtendonk, M. (1996). Stoff, Formel, Umwelt [Matter, formula, envrionment].
Bamberg: C. C. Buchner.
Tsui, C.-Y., & Treagust, D. (2004). Motivational aspects of learning genetics with interactive
multimedia. The American Biology Teacher, 66(4), 277–285.
Valanides, N. (2000a). Primary student teachers’ understanding of the particulate nature of matter and its transformations during dissolving. Chemistry Education Research and Practice, 1, 249–262.
Valanides, N. (2000b). Primary student teachers’ understanding of the process and effects of
distillation. Chemistry Education Research and Practice, 1, 355–364.
Van Driel, J. H., & Verloop, N. (1999). Teachers’ knowledge of models and modelling in science.
International Journal of Science Education, 21(11), 1141–1153.
Wandersee, J. H., Mintzes, J. J., & Novak, J. D. (1994). Research on alternative conceptions in science. In D. L. Gabel (Ed.), Handbook of research in science teaching and learning (pp.177–210). New York: Macmillan.
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(5), 521–534.
Yang, E.-M., Greenbowe, T. J., & Andre, T. (2004). The effective use of an interactive software
program to reduce students’ misconceptions about batteries. Journal of Chemical Education, 81(4), 587–595.
Zhang, Z. H., & Linn, M. C. (2011). Can generating representations enhance learning with dynamic
visualizations? Journal of Research in Science Teaching, 48(10), 1177–1198.
Published
2012-03-31
How to Cite
Eilks, I., Witteck, T., & Pietzner, V. (2012). The Role and Potential Dangers of Visualisation when Learning about Sub-Microscopic Explanations in Chemistry Education. Center for Educational Policy Studies Journal, 2(1), 125–145. https://doi.org/10.26529/cepsj.398
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