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Generative Modelling in Physics and in Physics Education: From Aspects of Research Practices to Suggestions for Education

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International Handbook of Research in History, Philosophy and Science Teaching

Abstract

The extensive use of modelling in physics research has many implications on how it is used in physics education. An interesting case is the use of models in producing of new knowledge, which we here refer to as generative modelling. Generative modelling can serve as a cognitive tool bridging conceptual reality and real phenomena by mutually fitting of simulations and experiments. In this fitting process of fitting, pursuing partial mimetic similarity in simulations and experiments acquires a central epistemological role. At the core of generative modelling is the creative use of theoretical and empirical elements of modelling as well as the explorative manipulation of real conditions to fit the models. We argue here that such modelling is also identifiable as authentic by the modelling practitioners themselves and that such a modelling approach supports constructively oriented and creative teaching solutions.

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Notes

  1. 1.

    See, e.g. Gobert and Buckley (2000), Justi and Gilbert (2000), and Izquierdo-Aymerich and Adúriz-Bravo (2003).

  2. 2.

    See, e.g. Justi and Gilbert (2002), Oh and Oh (2011), and Van Driel and Verloop (2002).

  3. 3.

    See, e.g. Adúriz-Bravo and Izquierdo-Aymerich (2005), Develaki (2007), and Nola (2004).

  4. 4.

    See, e.g. Crawford and Cullin (2004), Halloun (2007), Hestenes (1987, 1992), and Sensevy et al. (2008).

  5. 5.

    See, e.g. Adúriz-Bravo and Izquierdo-Aymerich (2005), Crawford and Cullin (2004), and Izquierdo-Aymerich and Adúriz-Bravo (2003).

  6. 6.

    See, e.g. Gilbert et al. (2000), Matthews (1994/2014, 1997), and Nola (1997).

  7. 7.

    See, e.g. Gilbert et al. (2000), Hestenes (1992), Justi and Gilbert (2000, 2002), and Nola (2004).

  8. 8.

    Analyses of science practice in fact provide evidence pointing to the opposite conclusions (see, e.g. Koponen (2007) and Tala (2011) and references therein).

  9. 9.

    See, e.g. Blum and Ferri (2009), Haines and Crouch (2010), and Uhden et al. (2012).

  10. 10.

    See, e.g. Chang (2004), Heidelberger (1998), and Riordan (2003).

  11. 11.

    See, e.g. Bozkurt and Ilik (2010), Finkelstein et al. (2005), Perkins et al. (2006), and White (1993).

  12. 12.

    See, e.g. Cartwright (1999), Hughes (1997), Morrison (1999), and Morrison and Morgan (1999).

  13. 13.

    See, e.g. Cartwright (1999), Morrison (1999), and Morrison and Morgan (1999).

  14. 14.

    Nine interviews were in Finnish, and one in English; the authors translated the excerpts.

References

  • Adúriz-Bravo, A. & Izquierdo-Aymerich, M. (2005). Utilising the ‘3P-model’ to Characterise the Discipline of Didactics of Science, Science & Education 14, 29–41.

    Article  Google Scholar 

  • Black, M. (1962). Models and Metaphors, Ithaca, NY: Cornell University Press.

    Google Scholar 

  • Blum, W. & Ferri, R. B. (2009). Mathematical Modelling: Can It Be Taught And Learnt?, Journal of Mathematical Modelling and Application 1, 45–58.

    Google Scholar 

  • Bunge, M. (1983). Epistemology & Methodology II: Understanding the World. Treatise on Basic Philosophy 6, Dordrecht: Reidel.

    Google Scholar 

  • Bozkurt E. & Ilika A. (2010). The Effect of Computer Simulations over Students’ Beliefs on Physics and Physics Success. Procedia Social and Behavioural Sciences 2, 4587–4591.

    Article  Google Scholar 

  • Cartwright, N. (1983). How the Laws of Physics Lie, Oxford, New York: Clarendon Press.

    Book  Google Scholar 

  • Cartwright, N. (1999). The Dappled World, Cambridge: Cambridge University Press.

    Book  Google Scholar 

  • Chang, H. (2004). Inventing Temperature: Measurement and Scientific Progress, Oxford: Oxford University Press.

    Book  Google Scholar 

  • Crawford, B. & Cullin, M. (2004). Supporting Prospective Teachers’ Conceptions of Modeling in Science, International Journal of Science Education 26, 1379–1401.

    Article  Google Scholar 

  • Darling, K. M. (2002). The Complete Duhemian Underdetermination Argument: Scientific Language and Practice. Studies in History and Philosophy of Science 33, 511–533.

    Article  Google Scholar 

  • Develaki, M. (2007). The Model-Based View of Scientific Theories and the Structuring of School Science Programmes, Science & Education 16, 725–749.

    Article  Google Scholar 

  • Duhem, P. (1914/1954). The Aim and Structure of Physical Theory (translation of La Théorie Physique: Son Objet, Sa Structure, 2nd ed., 1914 Paris). Princeton: Princeton University Press.

    Google Scholar 

  • Finkelstein, N. D., Adams, W. K., Keller, C. J., Kohl, P. B., Perkins, K. K., Podolefsky, N. S. & LeMaster, R. S. (2005). When learning about the Real world is Better Done Virtually: A Study of Substituting Computer Simulations for Laboratory Equipment, Physical Review ST – PER 1, 010103.

    Google Scholar 

  • Giere, R. N. (1988). Explaining Science: A Cognitive Approach, Chicago: University of Chicago Press.

    Book  Google Scholar 

  • Giere, R. N. (1999). Science without Laws, Chicago: University of Chicago Press.

    Google Scholar 

  • Giere, R. N., Bickle, J. & Mauldin, R. F. (2006). Understanding Scientific Reasoning, 5th ed., Belmont, CA: Thomson Wadsworth,

    Google Scholar 

  • Gilbert, J. K., Pietrocola, M., Zylbersztajn, A. & Franco, C. (2000). Science and Education: Notions of Reality, Theory and Model, in J.K. Gilbert & C.J. Boulter (eds.), Developing Models in Science Education, Dordrecht: Kluwer Academic Publisher.

    Chapter  Google Scholar 

  • Gobert, J. D. & Buckley, B. C. (2000). Introduction to Model-based Teaching and Learning in Science Education, International Journal of Science Education 22, 891–894.

    Article  Google Scholar 

  • Grandy, R. E. (2003). What Are Models and Why Do We Need Them?, Science & Education 12, 773–777.

    Article  Google Scholar 

  • Hacking, I. (1983). Representing and Inventing: Introductory Topics in the Philosophy of Natural Science, Cambridge: Cambridge University Press.

    Book  Google Scholar 

  • Haines, C. R. & Crouch R. (2010). Remarks on a Modelling Cycle and Interpreting Behaviours, In R. Lesh, P. L. Galbraith, C. R. Haines, and A. Hurford (eds), Modeling Students’ Mathematical Modeling Competencies (ICTMA 13), Heidelberg: Springer. pp. 123–128.

    Google Scholar 

  • Halloun, I. A. (2007). Mediated Modeling in Science Education, Science & Education 16, 653–697.

    Article  Google Scholar 

  • Heidelberger, M. (1998). From Helmholtz’s Philosophy of Science to Hertz’ Picture Theory. In D. Baird, R.I.G. Hughes and A. Nordmann (eds.), Heinrich Hertz: Classical Physicist, Modern Philosopher, Dordrecht: Kluwer Academic Publisher.

    Google Scholar 

  • Hesse, M. B. (1963). Models and Analogies in Science, London: Seed and Ward.

    Google Scholar 

  • Hestenes, D. (1987). Toward A Modeling Theory of Physics Instruction, American Journal of Physics 55, 440–454.

    Article  Google Scholar 

  • Hestenes, D. (1992). Modeling Games in the Newtonian World, American Journal of Physics 60, 732–748.

    Article  Google Scholar 

  • Hestenes, D. (2010). Modeling Theory for Math and Science Education. In R. Lesh, C. R. Haines, P. L. Galbraith and A. Hurford (eds.), Modeling Students’ Mathematical Modeling Competencies (ICTMA 13), Heidelberg: Springer, pp. 13–41.

    Google Scholar 

  • Hughes, R. I. G. (1997). Models and Representations, Philosophy of Science 67, S325-S336.

    Article  Google Scholar 

  • Hughes, R. I. G. (1999). The Ising Model, Computer Simulation, and Universal Physics. In M. S. Morgan and M. Morrison (eds.), Models as Mediators, Cambridge: Cambridge University Press.

    Google Scholar 

  • Humphreys, P. (2004). Extending Ourselves, Oxford: Oxford University Press.

    Book  Google Scholar 

  • Izquierdo-Aymerich, M. & Adúriz-Bravo, A. (2003). Epistemological foundations of school science, Science & Education 12, 27 – 43.

    Article  Google Scholar 

  • Justi, R.S. & Gilbert, J.K. (2000). History and Philosophy of Science through Models: Some Challenges in the Case of “the atom”, International Journal of Science Education 22, 993–1009.

    Article  Google Scholar 

  • Justi, R.S. & Gilbert, J.K. (2002). Modelling, Teachers’ Views on the Nature of Modelling and Implications for the Education of Modellers, International Journal of Science Education 24, 369–387.

    Article  Google Scholar 

  • Koponen, I. T. (2007). Models and Modelling in Physics Education: A Critical Re-analysis of Philosophical Underpinnings and Suggestions for Revisions, Science & Education 16, 751–773.

    Article  Google Scholar 

  • Matthews, M. R. (1994/2014). Science Teaching: The Role of History and Philosophy of Science, New York: Routledge.

    Google Scholar 

  • Matthews, M.R. (1997). Introductory Comments on Philosophy and Constructivism in Science Education, Science & Education 6, 5–14.

    Article  Google Scholar 

  • Morrison, M. (1999). Models as autonomous agents. In M. S. Morgan and M. Morrison M. (eds.), Models as Mediators, Cambridge: Cambridge University Press.

    Google Scholar 

  • Morrison, M. S. & Morgan, M. (1999). Models as Mediating instruments. In M. S. Morgan and M. Morrison (eds.), Models as Mediators, Cambridge: Cambridge University Press.

    Google Scholar 

  • Nersessian, N. (1995). Should Physicists Preach What They Practice? Constructive Modeling in Doing and Learning Physics, Science & Education 4, 203–226.

    Article  Google Scholar 

  • Nersessian, N. (2008). Creating Scientific Concepts. Cambridge, MA: MIT Press.

    Google Scholar 

  • Neves, R. G. (2010). Enhancing Science and Mathematics Education with Computational Modelling, Journal of Mathematical Modelling and Application 1, 2–15

    Google Scholar 

  • Nola, R. (1997). Constructivism in Science and Science Education: A Philosophical Critique, Science & Education 6, 55–83.

    Article  Google Scholar 

  • Nola, R. (2004). Pendula, Models, Constructivism and Reality, Science & Education 13, 349–377.

    Article  Google Scholar 

  • Oh, P. S. & Oh, S. J. (2011). What Teachers of Science Need to Know about Models: An Overview, International Journal of Science Education 33, 1109–1130.

    Article  Google Scholar 

  • Perkins K., Adams W., Dubson M., Finkelstein N., Reid S., Wieman C. & LeMaster R. (2006). PhET: Interactive Simulations for Teaching and Learning Physics. The Physics Teacher 44, 18–22.

    Article  Google Scholar 

  • Pluta, W. J., Chinn. C. A. & Duncan, R. G. (2011) Learners’ Epistemic Criteria for Good Scientific Models, Journal of Research in Science Teaching 48, 486–511.

    Article  Google Scholar 

  • Riordan, M. (2003). Science Fashions and Scientific Fact’, Physics Today, August 2003, 50.

    Article  Google Scholar 

  • Schwarz C. V., Reiser B. J., Davis E. A., Kenyon L., Acher A., Fortus D., Shwartz Y., Hug B. & Krajcik, J. (2009). Developing a Learning Progression for Scientific Modeling: Making Scientific Modeling Accessible and Meaningful for Learners, Journal of Research in Science Teaching 46, 632–654.

    Article  Google Scholar 

  • Sensevy, G., Tiberghien, A., Santini, J., Laube, S. & Griggs, P. (2008). An Epistemological Approach to Modeling: Case Studies and Implications for Science Teaching, Science Education 92, 424–446.

    Article  Google Scholar 

  • Suárez, M. (1999). The Role of Models in Application of Scientific Theories: Epistemological Implications. In M. S. Morgan and M. Morrison (eds.), Models as Mediators, Cambridge: Cambridge University Press.

    Google Scholar 

  • Suppe, F. (1977). The Structure of Scientific Theories, 2nd ed., Urbana: University of Illinois Press.

    Google Scholar 

  • Suppes, P. (1962). Models of Data. In E. Nagel, P. Suppes and A. Tarski (eds.), Logic, Methodology and Philosophy of Science: Proceedings of the International Congress, Stanford, CA: Stanford University Press.

    Google Scholar 

  • Tala, S. (2011). Enculturation into Technoscience: Analysis of the Views of Novices and Experts on Modelling and Learning in Nanophysics, Science & Education 20, 733–760.

    Article  Google Scholar 

  • Uhden, O., Karam R., Pietrocola M. & Pospiech G. (2012). Modelling Mathematical Reasoning in Physics Education, Science & Education 21, 485–506.

    Article  Google Scholar 

  • Van Driel, J. & Verloop, N. (2002). Experienced Teachers’ Knowledge of Teaching and Learning of Models and Modelling in Science Education, International Journal of Science Education 24, 1255–1272.

    Article  Google Scholar 

  • Van Fraassen, B. C. (1980). Scientific Image, Oxford: Clarendon Press.

    Book  Google Scholar 

  • Wells, M., Hestenes, D. & Swackhamer, G. (1995). A modeling method for high school physics instruction, American Journal of Physics 63, 606–619.

    Article  Google Scholar 

  • White, B. Y. (1993). ThinkerTools: Causal Models, and Science Education Conceptual Change, Cognition and Instruction 10, 1–100.

    Article  Google Scholar 

  • Winsberg, E. (2001). Simulations, Models and Theories: Complex Physical Systems and their Representations, Philosophy of Science 68, 442–454.

    Article  Google Scholar 

  • Winsberg, E. (2003) Simulated Experiments: Methodology for a Virtual World, Philosophy of Science 70, 105–125.

    Article  Google Scholar 

  • Winsberg, E. (2006). Models of Success versus the Success of Models: Reliability without Truth, Synthese 152, 1–19.

    Article  Google Scholar 

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Acknowledgements

 This work has been supported by grant 1136582 from the Academy of Finland.

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Authors and Affiliations

  1. Department of Physics, University of Helsinki, Helsinki, Finland

    Ismo T. Koponen & Suvi Tala

Authors
  1. Ismo T. Koponen
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  2. Suvi Tala
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Correspondence to Ismo T. Koponen .

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  1. School of Education, University of New South Wales, Sydney, New South Wales, Australia

    Michael R. Matthews

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Koponen, I.T., Tala, S. (2014). Generative Modelling in Physics and in Physics Education: From Aspects of Research Practices to Suggestions for Education. In: Matthews, M. (eds) International Handbook of Research in History, Philosophy and Science Teaching. Springer, Dordrecht. https://doi.org/10.1007/978-94-007-7654-8_35

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