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Cosmos visualized: Development of a qualitative framework for analyzing representations in cosmology education

Saeed Salimpour*

Russell Tytler

Urban Eriksson

Michael Fitzgerald

  • Deakin University, 221 Burwood Highway, Burwood, Victoria 3125 Australia; International Astronomical Union, Office of Astronomy for Education, MPIA-Campus Königstuhl 17, D-69117 Heidelberg, Germany; Haus der Astronomie, MPIA-Campus, Königstuhl 17, D-69117 Heidelberg, Germany, and Max Planck Institut für Astronomie, Königstuhl 17, D-69117 Heidelberg, Germany

  • Deakin University, 221 Burwood Highway, Burwood, Victoria 3125, Australia

  • Lund University Physics Education Research (LUPER) group, Lund University, Box 118, 221 00 Lund, Sweden

  • Deakin University, 221 Burwood Highway, Burwood, Victoria 3125, Australia and Las Cumbres Observatory, Goleta, California 93117, USA

  • *ssalimpour@deakin.edu.au
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Phys. Rev. Phys. Educ. Res. 17, 013104 – Published 24 May, 2021

DOI: https://doi.org/10.1103/PhysRevPhysEducRes.17.013104

Abstract

Our aesthetic response to the Universe, and the complexity of concepts through which we understand it, are inherently bound together in how we meaningfully interpret its nature. Over millennia the abstracted and intangible concepts of science have been developed and communicated through a rich array of representations across a variety of modes. The interpretation of such representations is a complex multidimensional and multimodal endeavor. This is particularly an issue in education where novices can struggle to engage with unfamiliar canonical representations. Learning in a discipline can be characterized as a process of developing disciplinary discernment in apprehending and using these representational systems. Using representations concerning the geometry of the Universe, evolution of the Universe, and cosmological expansion as examples, this paper provides an in-depth overview of the various multimodal representations through which concepts in cosmology are understood and communicated. In so doing this work unpacks the salient features of these representations in order to develop an underlying framework which we call the anatomy of representations (AOR). This study, in reviewing and analyzing representations in cosmology, explores this landscape of cosmology representations. This will allow for the characterization of how semiotic resources are mobilized, changed, and connections are made between various representational modes and levels, and an exploration of the landscape of cosmology and cosmology education. The AOR framework is intended as a guide for educators, including textbook authors, to support the development and interpretation of representations.

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References (113)

  1. U. Eriksson, C. Linder, J. Airey, and A. Redfors, Who needs 3D when the Universe is flat?, Sci. Educ. 98, 412 (2014).
  2. R. Gray, The distinction between experimental and historical sciences as a framework for improving classroom inquiry, Sci. Educ. 98, 327 (2014).
  3. M. Vogelsberger, S. Genel, V. Springel, P. Torrey, D. Sijacki, D. Xu, G. Snyder, D. Nelson, and L. Hernquist, Introducing the Illustris Project: Simulating the coevolution of dark and visible matter in the Universe, Mon. Not. R. Astron. Soc. 444, 1518 (2014).
  4. J. North, Cosmos: An Illustrated History of Astronomy and Cosmology (University of Chicago Press, Chicago, IL, 2008).
  5. R. P. Norris, The Challenge of Astronomical Visualisation, in Astronomical Data Analysis Software and Systems III ASP Conference Series, edited by D. R. Crabtree, R. J. Hanisch, and J. Barnes, Vol. 61 (Astronomical Society of the Pacific, 1994), p. 51, http://adsabs.harvard.edu/abs/1994ASPC...61...51N.
  6. G. R. Kress and T. van Leeuwen, Reading Images: The Grammar of Visual Design, 2nd ed., reprinted (Routledge, London, 2010).
  7. S. Galano, A. Colantonio, S. Leccia, I. Marzoli, E. Puddu, and I. Testa, Developing the use of visual representations to explain basic astronomy phenomena, Phys. Rev. Phys. Educ. Res. 14, 010145 (2018).
  8. V. R. Lee, How different variants of orbit diagrams influence student explanations of the seasons, Sci. Educ. 94, 985 (2010).
  9. B. M. Pena and M. J. G. Quilez, The importance of images in astronomy education, Int. J. Sci. Educ. 23, 1125 (2001).
  10. R. Tytler, Re-imagining science education: Engaging students in science for Australia’s future, Review No. 51, Australian Education Review - Australian Council for Educational Research, 2007, https://research.acer.edu.au/aer/3.
  11. V. Prain and R. Tytler, Representing and Learning in Science, in Constructing Representations to Learn in Science (Sense Publishers, Rotterdam, 2013), pp. 1–14.
  12. Visualization in Science Education, edited by J. K. Gilbert (Springer Netherlands, Dordrecht, 2005).
  13. J. K. Gilbert, Visualization: An emergent field of practice, and enquiry in science education, in Visualization: Theory, and Practice in Science Education, edited by J. K. Gilbert, M. Reiner, and M. Nakhleh (Springer Netherlands, Dordrecht, 2008), pp. 3–24.
  14. S. Salimpour, M. T. Fitzgerald, R. Tytler, and U. Eriksson, Educational design framework for a web-based interface to visualise authentic cosmological “big data” in high school, J. Sci. Educ. Technol., 10.1007/s10956-021-09915-2 (2021).
  15. S. Salimpour et al., The gateway science: A review of astronomy in the OECD school curricula, including China and South Africa, Res. Sci. Educ., 10.1007/s11165-020-09922-0 (2020).
  16. S. Salimpour, R. Tytler, M. T. Fitzgerald, and U. Eriksson, Is the Universe infinite? Exploring high student conceptions of cosmology concepts using open-ended surveys (to be published).
  17. Constructing Representations to Learn in Science, edited by R. Tytler, V. Prain, P. Hubber, and B. Waldrip (SensePublishers, Rotterdam, 2013).
  18. R. Tytler, The role of visualisation in science: a response to “science teachers’ use of visual representations”, Studies Sci. Educ. 57, 129 (2020).
  19. P. J. E. Peebles, Principles of Physical Cosmology (Princeton University Press, Princeton, NJ, 1993).
  20. B. Ryden, Introduction to Cosmology, 2nd ed. (Cambridge University Press, Cambridge, England, 2016).
  21. L. Jiang et al., Evidence for GN-Z11 as a luminous galaxy at redshift 10.957, Nat. Astron. 5, 256 (2021).
  22. P. A. Oesch et al., A remarkably luminous galaxy at Z=11.1 measured with Hubble Space Telescope Grism spectroscopy, Astrophys. J. 819, 129 (2016).
  23. P. A. R. Ade et al. (Planck Collaboration), Planck 2015 results. XIII. Cosmological parameters, Astron. Astrophys. 594, A13 (2016).
  24. G. R. Blumenthal, S. M. Faber, J. R. Primack, and M. J. Rees, Formation of galaxies and large-scale structure with cold dark matter, Nature (London) 311, 517 (1984).
  25. P. Bull et al., Beyond ΛCDM: Problems, solutions, and the road ahead, Phys. Dark Universe 12, 56 (2016).
  26. A. Einstein, Die Feldgleichungen Der Gravitation, Sitzungsberichte Der Königlich Preußischen Akademie Der Wissenschaften (Berlin), Seite 844 (1915).
  27. A. Friedmann, Über Die Krümmung Des Raumes, Z. Physik 10, 377 (1922).
  28. A. Friedmann, Über die Möglichkeit einer Welt mit konstanter negativer Krümmung des Raumes, Z. Physik 21, 326 (1924).
  29. E. Hubble, A Relation between distance and radial velocity among extragalactic nebulae, Proc. Natl. Acad. Sci. U.S.A. 15, 168 (1929).
  30. G. Lemaître, Expansion of the Universe, a homogeneous universe of constant mass and increasing radius accounting for the radial velocity of extra-galactic nebulae, Mon. Not. R. Astron. Soc. 91, 483 (1931).
  31. M. Davis, J. Huchra, D. W. Latham, and J. Tonry, A survey of galaxy redshifts. II—the large scale space distribution, Astrophys. J. 253, 423 (1982).
  32. J. Huchra, M. Davis, D. Latham, and J. Tonry, A survey of galaxy redshifts. IV—the data, Astrophys. J. Suppl. Ser. 52, 89 (1983).
  33. M. Colless et al., The 6dF galaxy survey: Final redshift release (DR3) and southern large-scale structures, Mon. Not. R. Astron. Soc. 399, 683 (2009).
  34. M. R. Blanton et al., Sloan digital sky survey IV: Mapping the Milky Way, nearby galaxies, and the distant universe, Astrophys. J. 154, 28 (2017).
  35. M. Skrutskie et al., The two micron all sky survey (2MASS), Astron. J. 131, 1163 (2006).
  36. A. A. Penzias and R. W. Wilson, A measurement of excess antenna temperature at 4080 Mc/s., Astrophys. J. 142, 419 (1965).
  37. D. N. Spergel et al., First-Year Wilkinson microwave anisotropy probe (WMAP) observations: Determination of cosmological parameters, Astrophys. J. Suppl. Ser. 148, 175 (2003).
  38. M. A. K. Halliday, Language as Social Semiotic: The Social Interpretation of Language and Meaning (Edward Arnold, London, 1978).
  39. R. Hodge and G. Kress, Social Semiotics (Cornell University Press, Ithaca, NY, 1988).
  40. G. R. Kress and T. van Leeuwen, Reading Images: The Grammar of Visual Design (Psychology Press, London, 1996).
  41. G. R. Kress, Multimodality: A Social Semiotic Approach to Contemporary Communication (Routledge, London, New York, 2010).
  42. J. Airey and C. Linder, Social semiotics in university physics education, in Multiple Representations in Physics Education (Springer, Cham, 2017), pp. 95–122.
  43. J. L. Lemke, Social semiotics and science education, Am. J. Semiotics 5, 217 (1987), http://search.proquest.com/docview/213748355/abstract/41EA2A5CDB0C4CC4PQ/3.
  44. T. van Leeuwen, Introducing Social Semiotics (Routledge, London, 2005).
  45. U. Eriksson, Reading the sky: From starspots to spotting stars, Doctoral thesis, Uppsala University, 2014, http://urn.kb.se/resolve?urn=urn:nbn:se:hkr:diva-13268.
  46. U. Eriksson, C. Linder, J. Airey, and A. Redfors, Introducing the anatomy of disciplinary discernment: An example from astronomy, Eur. J. Sci. Math. Educ. 2, 167 (2014).
  47. A. A. diSessa and B. L. Sherin, Meta-representation: An introduction, J. Math. Behav. 19, 385 (2000).
  48. R. Kozma and J. Russell, Students becoming chemists: Developing representational competence, in Visualization in Science Education, edited by J. K. Gilbert (Springer Netherlands, Dordrecht, 2005), pp. 121–145.
  49. P.-O. Wickman, Aesthetic Experience in Science Education: Learning and Meaning-Making As Situated Talk and Action (Routledge, Mahwah, NJ, 2006).
  50. D. Gentner, Structure-mapping: A theoretical framework for analogy, Cogn. Sci. 7, 155 (1983).
  51. J. Airey and C. Linder, A disciplinary discourse perspective on university science learning: Achieving fluency in a critical constellation of modes, J. Res. Sci. Teach. 46, 27 (2009).
  52. V. Prain and R. Tytler, Learning through constructing representations in science: A framework of representational construction affordances, Int. J. Sci. Educ. 34, 2751 (2012).
  53. M. J. Ford and E. A. Forman, Chapter 1: Redefining disciplinary learning in classroom contexts, Rev. Res. Educ. 30, 1 (2006).
  54. R. Lehrer and L. Schauble, Seeding evolutionary thinking by engaging children in modeling its foundations, Sci. Educ. 96, 701 (2012).
  55. P. Hubber and R. Tytler, Enacting a representation construction approach to teaching and learning astronomy, in Multiple Representations in Physics Education (Springer, Cham, 2017), pp. 139–161.
  56. P. Hubber and R. Tytler, Models and Learning Science, in Constructing Representations to Learn in Science (SensePublishers, Rotterdam, 2013), pp. 109–133.
  57. S. W. Gilbert, Model building and a definition of science, J. Res. Sci. Teach. 28, 73 (1991).
  58. A. G. Harrison and D. F. Treagust, Teaching and learning with analogies, in Metaphor and Analogy in Science Education, edited by P. J. Aubusson, A. G. Harrison, and S. M. Ritchie (Springer Netherlands, Dordrecht, 2006), pp. 11–24.
  59. S. W. Gilbert, Models-Based Science Teaching (NSTA Press, Arlington, VA, 2011).
  60. D. Gooding, Visualisation, inference and explanation in the sciences, in Studies in Multidisciplinarity, edited by G. Malcolm (Elsevier, 2005), Vol. 2, pp. 1–25.
  61. J. K. Gilbert, Visualization: A metacognitive skill in science and science education, in Visualization in Science Education (Springer, Dordrecht, 2005), pp. 9–27.
  62. Science Teachers’ Use of Visual Representations, edited by B. Eilam and J. K. Gilbert (Springer International Publishing, New York, 2014).
  63. T. Fredlund, J. Airey, and C. Linder, Exploring the role of physics representations: An illustrative example from students sharing knowledge about refraction, Eur. J. Phys. 33, 657 (2012).
  64. U. Eriksson, Disciplinary discernment: Reading the sky in astronomy education, Phys. Rev. Phys. Educ. Res. 15, 010133 (2019).
  65. J. Airey, Social Semiotics in Higher Education: Examples from Teaching and Learning in Undergraduate Physics (Swedish Foundation for International Cooperation in Research in Higher Education (STINT), Sweden, 2015), p. 103, http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-266049.
  66. M. Lynch and S. Y. Edgerton, Aesthetics and digital image processing: Representational craft in contemporary astronomy, Sociological Rev. 35, 184 (1987).
  67. T. A. Rector, Z. G. Levay, L. M. Frattare, K. K. Arcand, and M. Watzke, The aesthetics of astrophysics: How to make appealing color-composite images that convey the science, Publ. Astron. Soc. Pac. 129, 058007 (2017).
  68. S. Salimpour, Capturing the cosmos: Teaching astronomy (and more) through astrophotography in middle school, Robotic Telescopes, Student Research, and Education Proceedings 2, 1 (2019).
  69. S. Salimpour, Capturing the Cosmos: Art, Science or Both?, MSc Project Report, Swinburne University of Technology, 2014.
  70. J. English, Canvas and cosmos: Visual art techniques applied to astronomy data, Int. J. Mod. Phys. D 26, 1730010 (2017).
  71. J. Dewey, Art as Experience (Paragon Books, New York, 1979).
  72. J. Dewey, Aesthetic experience as a primary phase and as an artistic development, J. Aesthetics Art Criticism 9, 56 (1950).
  73. J. Dewey, The aesthetic element in education, in The Early Works of John Dewey, Volume 5, 1882-1898: Early Essays, 1895–1898 (Republished 1972), edited by J. A. Boydston, 1st ed. (Southern Illinois University Press, Carbondale, IL, 1897).
  74. J. Lemke, Feeling and meaning: A unitary bio-semiotic account, in International Handbook of Semiotics, edited by P. P. Trifonas (Springer Netherlands, Dordrecht, 2015), pp. 589–616.
  75. D. Malin and E. E. A. Slarke, Night Skies: The Art of Deep Space: An Exhibition of Astronomical Photographs, edited by N. S. W. Edgecliff and N. S. W. Epping (British Council, Anglo-Australian Observatory 1996).
  76. D. F. Treagust, A. G. Harrison, and G. J. Venville, Teaching science effectively with analogies: An approach for preservice and inservice teacher education, J. Sci. Teach. Educ. 9, 85 (1998).
  77. A. G. Harrison and D. F. Treagust, Secondary students’ mental models of atoms and molecules: Implications for teaching chemistry, Sci. Educ. 80, 509 (1996).
  78. R. Duit, On the role of analogies and metaphors in learning science, Sci. Educ. 75, 649 (1991).
  79. W. F. McComas, Analogies in science teaching, in The Language of Science Education: An Expanded Glossary of Key Terms and Concepts in Science Teaching and Learning, edited by W. F. McComas (SensePublishers, Rotterdam, 2014), pp. 6–6.
  80. S. M. Ritchie, A. Bellocchi, H. Poltl, and M. Wearmouth, Metaphors and analogies in transition, in Metaphor and Analogy in Science Education, edited by P. J. Aubusson, A. G. Harrison, and S. M. Ritchie (Springer Netherlands, Dordrecht, 2006), pp. 143–153.
  81. D. Heywood, The place of analogies in science education, Cambridge J. Educ. 32, 233 (2002).
  82. J. Wiley, A. J. Jaeger, A. R. Taylor, and T. D. Griffin, When analogies harm: The effects of analogies on metacomprehension, Learning Instr. 55, 113 (2017).
  83. B. G. Glaser and A. L. Strauss, The Discovery of Grounded Theory: Strategies for Qualitative Research (Aldine, London, 1967).
  84. J. Corbin and A. Strauss, Basics of Qualitative Research: Techniques and Procedures for Developing Grounded Theory, 4th ed. (SAGE Publications, Inc, Los Angeles, 2014).
  85. Multimodal Teaching and Learning: The Rhetorics of the Science Classroom, edited by C. Jewitt, G. R. Kress, J. Ogborn, and C. Tsatsarelis (Bloomsbury Academic, 2014).
  86. C. Jewitt, J. J. Bezemer, and K. L. O’Halloran, Introducing Multimodality (Routledge, London, New York, 2016).
  87. W. J. Gibson and A. Brown, Working with Qualitative Data (SAGE, Thousand Oaks, CA, 2009).
  88. G. Kress and T. van Leeuwen, Structures of visual representation, J. Literary Semantics 21, 91 (2009).
  89. C. S. Peirce, The Essential Peirce, Volume 1: Selected Philosophical Writings. 1867–1893 (Indiana University Press, Bloomington, 1992).
  90. C. S. Peirce, The Essential Peirce, Volume 2: Selected Philosophical Writings, 1893–1913 (Indiana University Press, Bloomington, 1998).
  91. S. Salimpour, R. Tytler, and M. T. Fitzgerald, Exploring the cosmos: The challenge of identifying patterns and conceptual progressions from student survey responses in cosmology, in Methodological Approaches to STEM Education Research, edited by R. Tytler, P. White, J. Ferguson, and J. C. Clark (Cambridge Scholars Publishing, Cambridge, England, 2020), Vol. 1, https://www.cambridgescholars.com/product/978-1-5275-5551-8.
  92. V. Braun and V. Clarke, Using thematic analysis in psychology, Qualitative Res. Psychol. 3, 77 (2006).
  93. J. Saldaña, The Coding Manual for Qualitative Researchers, 3rd ed. (SAGE, London, 2016).
  94. W. Xu and K. Zammit, Applying Thematic Analysis to Education: A Hybrid Approach to Interpreting Data in Practitioner Research, Int. J. Qualitative Methods 19 (2020).
  95. C. O’Connor and H. Joffe, Intercoder Reliability in Qualitative Research: Debates and Practical Guidelines, Int. J. Qualitative Methods 19 (2020).
  96. K. Svensson and U. Eriksson, Concept of a Transductive Link, Phys. Rev. Phys. Educ. Res. 16, 026101 (2020).
  97. C. Linder, Disciplinary discourse, representation, and appresentation in the teaching and learning of science, Eur. J. Sci. Math. Educ. 1, 7 (2013).
  98. D. Gentner, Analogical Inference and Analogical Access (Illinois University at Urbana, Department of Computer Science, Urbana, IL, 1987).
  99. M. B. Hesse and M. B. Hesse, Models and Analogies in Science (University of Notre Dame Press, South Bend, IN, 1966).
  100. G. J. Venville and D. F. Treagust, The role of analogies in promoting conceptual change in Biology, Instr. Sci. 24, 295 (1996).
  101. R. Freedman, R. Geller, and W. J. Kaufmann, Universe, 9th ed. (W. H. Freeman and Company, San Francisco, CA, 2011).
  102. A. Fraknoi, D. Morrison, and S. Wolff, OpenStax Astronomy Textbook (OpenStax, 2020), https://openstax.org/details/books/astronomy.
  103. A. G. Lemaître and A. S. Eddington, The expanding Universe, Mon. Not. R. Astron. Soc. 91, 490 (1931).
  104. R. A. Knop et al., New constraints on Ωm, Ωλ, and w from an independent set of 11 high-redshift supernovae observed with The Hubble Space Telescope, Astrophys. J. 598, 102 (2003).
  105. J. R. Pritchard and A. Loeb, Constraining the unexplored period between the dark ages and reionization with observations of the global 21 cm signal, Phys. Rev. D 82, 023006 (2010).
  106. J. Pritchard and A. Loeb, Hydrogen was not ionized abruptly, Nature (London) 468, 772 (2010).
  107. W. Hu and M. White, The cosmic symphony, in Scientific American (2004), 10.1038/scientificamerican0204-44.
  108. J. Airey and U. Eriksson, Unpacking the Hertzsprung-Russell diagram: A social semiotic analysis of the disciplinary and pedagogical affordances of a central resource in astronomy, Designs for Learning 11, 99 (2019).
  109. M. E. Lira and M. Stieff, Using gesture analysis to assess students’ developing representational competence, in Towards a Framework for Representational Competence in Science Education, edited by K. L. Daniel (Springer International Publishing, Cham, 2018), pp. 205–228.
  110. A. A. diSessa, Metarepresentation: Native competence and targets for instruction, Cognit. Instr. 22, 293 (2004).
  111. R. Tytler and V. Prain, Representation construction to support conceptual change, in International Handbook of Research on Conceptual Change, edited by S. Vosniadou, 2nd ed. (Routledge, New York, 2013), pp. 1009–1042, 10.4324/9780203154472.
  112. J. Ojala, The Third Planet, Int. J. Sci. Educ. 14, 191 (1992).
  113. I. Testa, S. Leccia, and E. Puddu, Astronomy textbook images: Do they really help students?, Phys. Educ. 49, 332 (2014).

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Phys. Rev. Phys. Educ. Res. 17, 013104– Published 24 May, 2021
  • Received 14 October 2020
  • Accepted 19 April 2021
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