Skip to main content

The Contribution of Visualisation to Modelling-Based Teaching

  • Chapter
  • First Online:
Modelling-based Teaching in Science Education

Part of the book series: Models and Modeling in Science Education ((MMSE,volume 9))

Abstract

Both the creation of models and their communication to other people involve visualisations. These are, respectively, ‘internal’ (or mental) and ‘external’ (or public) representations , with the latter confusingly also being called visualisations. Perceptions by one of the five senses provide external representations. The modes of external representation of particular importance in science education are the: gestural, concrete, static visual (pictures, diagrams, graphs, mathematical and chemical equations), dynamic visual (drama, animation, simulation), oral and auditory. The skills and abilities that constitute meta-visual competence in the modes are reviewed in this chapter, for they enable the central element of modelling – the design and conduct of thought experiments – to take place. Consequently, the skills and abilities of both modelling and of visualisation are mutually developed and employed during MBT.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 129.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 169.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 169.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Notes

  1. 1.

    Horizon is a BBC series exploring topical scientific and philosophical issues and their effects for the future, which has been broadcasted since 1964.

References

  • 3D Printing. (2015). What is 3D printing? Retrieved March, 2015, from http://3dprinting.com/what-is-3d-printing/-wt

  • Ainsworth, S. (2008). How do animations influence learning? In D. H. Robinson & G. Schraw (Eds.), Recent innovations in educational technology that facilitate student learning (pp. 37–67). Charlotte, NC: Information Age Publishing.

    Google Scholar 

  • Blackwell, A. F., & Engelhardt, Y. (1998). A taxonomy of diagram taxonomies. Paper presented at the thinking with diagrams 98: Is there a science of diagrams?

    Google Scholar 

  • Bloom, B. S. (1956). A taxonomy of educational objectives. New York: David McKay.

    Google Scholar 

  • Blum, W., & Leiß, D. (2007). How do students and teachers deal with modeling problems. In C. Haines, P. Galbraith, W. VBlum, & S. Khan (Eds.), Mathematical modelling: Education, engineering and economics (pp. 222–231). Chichester, UK: Horwood Publishing.

    Chapter  Google Scholar 

  • Brown, J. (1991). The laboratory of the mind. London: Routledge.

    Google Scholar 

  • Burges, D. (1980). Teaching applications of mathematics: Mathematical modelling in science and technology. European Journal of Science Education, 2(4), 365–376.

    Article  Google Scholar 

  • Cassels, J., & Johnstone, A. (1985). Words that matter in science. London: Royal Society of Chemistry.

    Google Scholar 

  • Di Fuccia, D. (2013). Mathematical models in chemistry lessons. Paper presented at the X Conference of the European Science Education Research Association, Nicosia, Cyprus.

    Google Scholar 

  • diSessa, A. A. (2004). Metarepresentation: Native competence and targets for instruction. Cognition and Instruction, 22(3), 293–331.

    Article  Google Scholar 

  • Dori, Y. J., Rodrigues, S., & Schanze, S. (2013). How to promote chemistry learning through the use of ICT. In I. Eilks & A. Hofstein (Eds.), Teaching chemistry: A studybook (pp. 213–240). Rotterdam: Sense.

    Chapter  Google Scholar 

  • Dorion, K. (2009). Science through drama: A multiple case exploration of the characteristics of drama activities used in secondary science lessons. International Journal of Science Education, 31(16), 2247–2270.

    Article  Google Scholar 

  • Eilam, B. (2012). Teaching, learning, and visual literacy. Cambridge, UK: Cambridge University Press.

    Book  Google Scholar 

  • Ferrucci, B. J., & Carter, J. A. (2003). Technology-active mathematical modelling. International Journal of Mathematical Education in Science and Technology, 34(5), 663–670.

    Article  Google Scholar 

  • Francoeur, E. (1997). The forgotten tool: The design and use of molecular models. Social Studies of Science, 27, 7–40.

    Article  Google Scholar 

  • Gilbert, J. K. (2005). Visualization: A metacognitive skill in science and science education. In J. K. Gilbert (Ed.), Visualization in science education (pp. 9–27). Dordrecht, Netherlands: Springer.

    Chapter  Google Scholar 

  • Gilbert, J. K. (2008). Visualization: An emergent field of practice and enquiry in science education. In J. K. Gilbert, M. Reiner, & M. Nakhleh (Eds.), Visualization: Theory and practice in science education (pp. 3–24). Dordrecht, Netherlands: Springer.

    Chapter  Google Scholar 

  • Gilbert, S. W. (2011). Models-based science teaching. Arlington, Virginia: NSTA Press.

    Google Scholar 

  • Gilbert, J. K., & Reiner, M. (2000). Thought experiments in science education: Potential and current realisation. International Journal of Science Education, 22(3), 265–283.

    Article  Google Scholar 

  • Gilbert, J. K., & Watts, D. M. (1983). Conceptions, misconceptions, and alternative conceptions: Changing perspectives in science education. Studies in Science Education, 10(1), 61–98.

    Article  Google Scholar 

  • Givry, D., & Roth, M.-W. (2006). Towards a new conception of conceptions: Interplay of talk, gestures and structures in the setting. Journal of Research in Science Teaching, 14(10), 1096–1109.

    Google Scholar 

  • Goldin-Meadow, S. (2006). Nonverbal communication: The hand’s role in talking and thinking. In W. Damon & R. M. Lerner (Eds.), Handbook of child psychology (6th ed., Vol. 2, pp. 336–369). Hoboken, NJ: Wiley.

    Google Scholar 

  • Hand, B. M., Prain, V., Lawrence, C., & Yore, L. D. (1999). A writing in science framework designed to enhance scientific literacy. International Journal of Science Education, 21(10), 1021–1035.

    Article  Google Scholar 

  • Harvey, W. (1993). On the circulation of blood and other writings. London: Everyman Orion.

    Google Scholar 

  • Hayes, D., Symington, D., & Martin, M. (1994). Drawing during science activity in the primary school. International Journal of Science Education, 16(3), 265–277.

    Article  Google Scholar 

  • Hegarty, M., Carpenter, P., & Just, M. (1991). Diagrams in the comprehension of scientific texts. In R. K. Barr (Ed.), Handbook of reading research (Vol. 2, pp. 641–668). New York: Longman.

    Google Scholar 

  • Hegarty, M., & Waller, D. (2005). Individual differences in spatial abilities. In P. Shah & A. Miyake (Eds.), The Cambridge handbook of visuospatial thinking (pp. 121–169). Cambridge: Cambridge University Press.

    Chapter  Google Scholar 

  • Herrera, J. S., & Riggs, E. M. (2013). Relating gestures and speech: An analysis of students’ conceptions about geological sedimentary processes. International Journal of Science Education, 35(12), 1979–2003.

    Article  Google Scholar 

  • Hodson, D. (2009). Teaching and learning about science: Language, theories, methods, history, traditions and values. Rotterdam, Netherlands: Sense.

    Google Scholar 

  • IUPAC. (2014). Compendium of chemical terminology: Gold book. Washington, DC: IUPAC.

    Google Scholar 

  • Johnstone, A. H. (1993). The development of chemistry teaching: A changing response to changing demand. Journal of Chemical Education, 70(9), 701–705.

    Article  Google Scholar 

  • Justi, R., & Gilbert, J. K. (2002). Modelling, teachers’ views on the nature of modelling, implications for the education of modellers. International Journal of Science Education, 24(4), 369–387.

    Article  Google Scholar 

  • Kastens, K. A., Agrawal, S., & Liben, L. S. (2008). The role of gestures in geoscience teaching and learning. Journal of Geoscience Education, 56(4), 362–368.

    Google Scholar 

  • Kempe, A., & Ashwell, M. (2000). Progression in secondary drama. Harlow, UK: Pearson.

    Google Scholar 

  • Kind, V. (2004). Beyond appearances: Students’ misconceptions about basic chemical ideas (2nd ed.). London: Royal Society of Chemistry.

    Google Scholar 

  • Kosslyn, S. (2006). Graph design for the eye and mind. Oxford: Oxford University Press.

    Book  Google Scholar 

  • Kosslyn, S., Pinker, S., Smith, G., & Shwartz, S. (1982). On the demystification of mental imagery. In N. Block (Ed.), Imagery (pp. 131–150). Cambridge, MA: MIT Press.

    Google Scholar 

  • Kozma, R., & Russell, J. (2005). Students becoming chemists: Developing representational competence. In J. K. Gilbert (Ed.), Visualization in science education (pp. 121–146). Dordrecht, Netherlands: Springer.

    Chapter  Google Scholar 

  • Kuhn, T. S. (1996). The structure of scientific revolutions (3rd ed.). Chicago: University of Chicago Press.

    Book  Google Scholar 

  • Lakoff, G., & Johnson, M. (1980). Metaphors we live by. Chicago: University of Chicago Press.

    Google Scholar 

  • Lamon, S. J., Parker, W. A., & Houston, S. K. (Eds.). (2003). Mathematical modelling: A way of life. Chichester, UK: Horwood.

    Google Scholar 

  • Landriscina, F. (2013). Simulation and learning: A model-centered approach. New York: Springer.

    Book  Google Scholar 

  • Levin, J. R., & Mayer, R. E. (1993). Understanding illustrations in text. In B. K. Britton, A. Woodward, & M. Binkley (Eds.), Learning from textbooks: Theory and practice (pp. 95–113). Hillsdale, NJ: Lawrence Erlbaum.

    Google Scholar 

  • Levin, J. R., Shriberg, I., & Berry, J. (1983). A concrete strategy to remembering abstract prose. American Educational Research Journal, 20(2), 277–290.

    Article  Google Scholar 

  • Liu, Y., Won, M., & Treagust, D. F. (2014). Secondary biology teachers’ use of different types of diagrams for different purpose. In B. Eilam & J. K. Gilbert (Eds.), Science teachers’ use of visual representations (pp. 103–121). Dordrecht, Netherlands: Springer.

    Google Scholar 

  • Loughran, J. (2014). Slowmation: A process of explicit visualization. In B. Eilam & J. K. Gilbert (Eds.), Science teachers’ use of visual representations (pp. 85–102). Dordrecht, Netherlands: Springer.

    Google Scholar 

  • Mayer, R. E., & Pilegard, C. (2005). Principles for managing essential processing in multimedia learning: Segmenting, pre-training, and modality principles. In R. E. Mayer (Ed.), The Cambridge handbook of multimedia learning (pp. 316–344). New York: Cambridge University Press.

    Chapter  Google Scholar 

  • McGregor, D. (2012). Dramatising science learning: Findings from a pilot study to re-invigorate elementary science pedagogy for five- to seven-year olds. International Journal of Science Education, 34(8), 1145–1165.

    Article  Google Scholar 

  • McNeill, D. (2005). Gesture and thought. Chicago: University of Chicago Press.

    Book  Google Scholar 

  • Newcombe, N. S., & Learmonth, A. E. (2005). Development of spatial competence. In P. Shah & A. Miyake (Eds.), The Cambridge handbook of visuospatial thinking (pp. 213–256). Cambridge: Cambridge University Press.

    Chapter  Google Scholar 

  • Newcombe, N. S., & Stieff, M. (2012). Six myths about spatial thinking. International Journal of Science Education, 34(6), 955–971.

    Article  Google Scholar 

  • Niss, M. (1987). Applications of modelling in the mathematics curriculum: State and trends. International Journal of Mathematical Education in Science and Technology, 18(4), 487–505.

    Article  Google Scholar 

  • Niss, M. (2010). Modeling a crucial aspect of students’ mathematical modeling. In R. Lesh, P. L. Galbraith, C. R. Haines, & A. Hurford (Eds.), Modeling students’ mathematical modeling competencies (pp. 43–59). New York: Springer.

    Chapter  Google Scholar 

  • Padalkar, S., & Ramadas, J. (2011). Designed and spontaneous gestures in elementary astronomy education. International Journal of Science Education, 33(12), 1703–1739.

    Article  Google Scholar 

  • Parnafes, O., & Trachtenberg-Maslaton, R. (2014). Transforming instruction: Teaching in a student-generated representations learning environment. In B. Eilam & J. K. Gilbert (Eds.), Science teachers’ use of visual representations (pp. 271–290). Dordrecht, Netherlands: Springer.

    Google Scholar 

  • Paton, R. (1990). Bird wings and matrices. Journal of Biological Education, 24(4), 273–276.

    Article  Google Scholar 

  • Paton, R. (1991a). An application of mathematical modelling to school biotechnology. International Journal of Mathematical Education in Science and Technology, 22(2), 291–296.

    Article  Google Scholar 

  • Paton, R. (1991b). Modelling biological processes using simple matrices. Journal of Biological Education, 25(1), 37–43.

    Article  Google Scholar 

  • Pozzer, L. L., & Roth, M.-W. (2003). Prevalence, function, and structure of photographs in high school biology textbooks. Journal of Research in Science Teaching, 40(10), 1089–1114.

    Article  Google Scholar 

  • Prain, V., & Tytler, R. (2012). Learning through constructing representations in science: A framework of representation construction affordances. International Journal of Science Education, 34(17), 2751–2773.

    Article  Google Scholar 

  • Reiner, M. (1998). Thought experiments and collaborative learning in physics. International Journal of Science Education, 20(9), 1043–1059.

    Article  Google Scholar 

  • Roth, M.-W., & Welzel, M. (2001). From activity to gestures and scientific language. Journal of Research in Science Teaching, 38(1), 103–136.

    Article  Google Scholar 

  • Rothbart, D. (Ed.). (2004). Modeling: Gateway to the unknown: A work by Rom Harré. Amsterdam: Elsevier.

    Google Scholar 

  • Royal Society of Chemistry. (2014). CPD for teachers. Retrieved July, 2014, from http://www.rsc.org/careers/cpd/teachers

  • Savec, V. F., Vrtacnik, M., & Gilbert, J. K. (2005). Evaluating the educational value of molecular structure representations. In J. K. Gilbert (Ed.), Visualization in science education (pp. 269–297). Dordrecht, Netherlands: Springer.

    Chapter  Google Scholar 

  • Savory, C. (1976). A survey of cristal and molecular models. Education in Chemistry, 13, 136–141.

    Google Scholar 

  • Scott, P., Asoko, H., & Leach, J. (2007). Students conceptions and conceptual learning in science. In S. K. Abell & N. G. Lederman (Eds.), Handbook of research in science education (pp. 31–56). Mahwah, N.J.: Lawrence Erlbaum.

    Google Scholar 

  • Sorensen, R. (1992). Thought experiments. New York: Oxford University Press.

    Google Scholar 

  • Swetz, F. (1989). A Historical example of mathematical modelling: The trajectory of a cannonball. International Journal of Mathematical Education in Science and Technology, 20(5), 731–741.

    Article  Google Scholar 

  • Taber, K. S. (2002). Chemical misconceptions: Prevention, diagnosis and cure (Vol. 1). London: Royal Society of Chemistry.

    Google Scholar 

  • Taber, K. S. (2009). Learning at the symbolic level. In J. K. Gilbert & D. F. Treagust (Eds.), Multiple representations in chemical education (pp. 75–108). Dordrecht, Netherlands: Springer.

    Chapter  Google Scholar 

  • Talanquer, V. (2007). Explanation and teleology in chemical education. International Journal of Science Education, 29(7), 853–870.

    Article  Google Scholar 

  • Thomas, N. J. T. (2014). Mental imagery. In E. N. Zalta (Ed.), The stanford encyclopedia of philosophy (Fall 2014 ed.). Stanford: Stanford University. http://plato.stanford.edu/archives/fall2014/entries/mental-imagery/.

  • Tuckey, H., & Selvaratnam, M. (1993). Studies involving three-dimensional visualisation skills in chemistry: A review. Studies in Science Education, 21, 99–121.

    Article  Google Scholar 

  • Tytler, R., Petersen, S., & Prain, V. (2006). Picturing evaporation: Learning science literacy through a particle representation. Teaching Science, 52(1), 12–17.

    Google Scholar 

  • Urhahne, D., Sabine, N., & Schanze, S. (2009). The effect of three-dimensional simulations on the understanding of chemical structures and their properties. Research in Science Education, 39(4), 495–513.

    Article  Google Scholar 

  • Voges, E., & Joubert, S. (2008). The singing wineglass: An exercise in mathematical modelling. International Journal of Mathematical Education in Science and Technology, 39(6), 725–739.

    Article  Google Scholar 

  • Waldrip, B., & Prain, V. (2012). Learning from and through representation in science. In B. J. Fraser, K. G. Tobin, & C. J. McRobbie (Eds.), Second international handbook of science education (Vol. 2, pp. 145–156). Dordrecht, Netherlands: Springer.

    Chapter  Google Scholar 

  • Wellington, J., & Osborne, J. (2001). Language and literacy in science education. Buckingham, UK: Open University Press.

    Google Scholar 

  • Wilkes, K. V. (1988). Real people: Personal identity without thought experiments. Oxford: Oxford University Press.

    Google Scholar 

  • Willows, D. (1978). A picture is not always worth a thousand words: Pictures as distractors in reading. Journal of Educational Psychology, 70(2), 255–262.

    Article  Google Scholar 

  • Wilson, M. (2002). Six views of embodied cognition. Psychonomic Bulletion and Review, 9(4), 625–636.

    Article  Google Scholar 

  • Winn, W. (1991). Learning from maps and diagrams. Educational Psychology Review, 3(3), 211–247.

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Rights and permissions

Reprints and permissions

Copyright information

© 2016 Springer International Publishing Switzerland

About this chapter

Cite this chapter

Gilbert, J.K., Justi, R. (2016). The Contribution of Visualisation to Modelling-Based Teaching. In: Modelling-based Teaching in Science Education. Models and Modeling in Science Education, vol 9. Springer, Cham. https://doi.org/10.1007/978-3-319-29039-3_7

Download citation

  • DOI: https://doi.org/10.1007/978-3-319-29039-3_7

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-29038-6

  • Online ISBN: 978-3-319-29039-3

  • eBook Packages: EducationEducation (R0)

Publish with us

Policies and ethics