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Agreeing to Disagree: Students Negotiating Visual Ambiguity Through Scientific Argumentation

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Towards a Framework for Representational Competence in Science Education

Part of the book series: Models and Modeling in Science Education ((MMSE,volume 11))

Abstract

Visual representations are commonly used as evidence for scientific claims. However, their potential for ambiguity can lead to multiple different interpretations. Both historical and contemporary cases exist of graphs that, by virtue of their ambiguity, have propelled public debate and misunderstanding of science. For instance, temperature graphs can be differently interpreted to support opposing views on global climate change; and questions over the choices of data and the formats of their displays have pitted designers against engineers over the causes of high profile space shuttle disasters. These examples demonstrate that a degree of representational competence is necessary to deal with ambiguity in visual evidence, and to ultimately engage effectively in scientific argumentation. This chapter considers the notion of ambiguity in graphs, and the skills necessary for engaging with that ambiguity in the context of scientific argumentation. I present an episode of dispute between two middle school students during a computer-supported inquiry project. Using the students’ argument over the interpretation of a graph of global temperatures, I illustrate how individual prior knowledge and expectations framed their differing interpretations, and how the same visual artifact served as evidence for their opposing claims. Analysis of this case highlights opportunities for learning to argue when instruction acknowledges ambiguity and legitimizes disagreement.

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References

  • Amann, K., & Knorr Cetina, K. (1988). The fixation of (visual) evidence. Human Studies, 11(2), 133–169.

    Google Scholar 

  • Avola, D., Caschera, M.C., Ferri, F., Grifoni, P. (2007). Ambiguities in sketch-based interfaces, Proceedings of the 40th Hawaii International Conference on System Science (HICSS ‘07), Hawaii.

    Google Scholar 

  • Barthes, R. (1977). Rhetoric of the image. In S. Heath (Ed.), Image, Music, Text. New York: Hill and Wang.

    Google Scholar 

  • Bell, P., & Linn, M. C. (2000). Scientific arguments as learning artifacts: Designing for learning from the web with KIE. International Journal of Science Education, 22, 797–817.

    Article  Google Scholar 

  • Berland, L. K., & Reiser, B. J. (2009). Making sense of argumentation and explanation. Science Education, 93(1), 26–55.

    Article  Google Scholar 

  • Bowen, G. M., Roth, W. M., & McGinn, M. K. (1999). Interpretations of graphs by university biology students and practicing scientists: Toward a social practice view of scientific representation practices. Journal of Research in Science Teaching, 36(9), 1020–1043.

    Article  Google Scholar 

  • Carter, B. (2006, April 9). There IS a problem with global warming... it stopped in 1998. The Telegraph Newspaper.

    Google Scholar 

  • Chi, M. T. H., Leeuw, N. D., Chiu, M. H., & Lavancher, C. (1994). Eliciting self-explanations improves understanding. Cognitive Science, 18(3), 439–477.

    Google Scholar 

  • Chin, C., & Osborne, J. (2010). Students’ questions and discursive interaction: Their impact on argumentation during collaborative group discussions in science. Journal of Research in Science Teaching, 47(7), 883–908.

    Article  Google Scholar 

  • Coleman, E. B. (1998). Using explanatory knowledge during collaborative problem solving in science. Journal of the Learning Sciences, 7(3&4), 387–427.

    Article  Google Scholar 

  • Collins, H. M. (1998). The meaning of data: Open and closed evidential cultures in the search for gravitational waves. American Journal of Sociology, 104(2), 293–338.

    Article  Google Scholar 

  • de Vries, E., Lund, K., & Michael, B. (2002). Computer-mediated epistemic dialogue: Explanation and argumentation as vehicles for understanding scientific notions. Journal of the Learning Sciences, 11(1), 63–103.

    Article  Google Scholar 

  • Dillenbourg, P., Baker, M., Blaye, A., & O’Malley, C. (1995). The evolution of research on collaborative learning. In P. Reimann & H. Spada (Eds.), Learning in humans and machines: Towards an interdisciplinary learning science (pp. 189–211). Oxford: Elsevier.

    Google Scholar 

  • Driver, R., Newton, P., & Osborne, J. (2000). Establishing the norms of scientific argumentation in classrooms. Science Education, 84(3), 287–312.

    Article  Google Scholar 

  • d’Ulizia, A., Grifoni, P., & Rafanelli, M. (2008). Visual notation interpretation and ambiguities. In F. Ferri (Ed.), Visual languages for interactive computing: Definitions and formalizations. Information Science Reference Hershey: IGI GLobal.

    Google Scholar 

  • Easterling, D. R., & Wehner, M. F. (2009). Is the climate warming or cooling? Geophysical Research Letters, 36, L08706. https://doi.org/10.1029/2009GL037810.

    Article  Google Scholar 

  • Edwards, J. L., & Winkler, C. K. (1997). Representative form and the visual ideograph: The Iwo Jima image in editorial cartoons. Quarterly Journal of Speech, 83(3), 289–310.

    Article  Google Scholar 

  • Eisenberg, E. M. (1984). Ambiguity as strategy in organizational communication. Communication monographs, 51(3), 227–242.

    Article  Google Scholar 

  • Empson, W. (1932). Seven types of ambiguity. Cambridge: Cambridge University Press.

    Google Scholar 

  • Eppler, M. J., Mengis, J., & Bresciani, S. (2008, July). Seven types of visual ambiguity: On the merits and risks of multiple interpretations of collaborative visualizations. In Information Visualisation, 2008. IV’08. 12th International Conference (pp. 391–396). IEEE.

    Google Scholar 

  • Eppler, M. J., & Sukowski, O. (2000). Managing team knowledge: Core processes, tools and enabling factors. European Management Journal, 18(3), 334–342.

    Article  Google Scholar 

  • Fischer, F., Bruhn, J., Gräsel, C., & Mandl, H. (2002). Fostering collaborative knowledge construction with visualization tools. Learning and Instruction, 12(2), 213–232.

    Article  Google Scholar 

  • Friel, S. N., Curcio, F. R., & Bright, G. W. (2001). Making sense of graphs: Critical factors influencing comprehension and instructional implications. Journal for Research in Mathematics Education, 32, 124–158.

    Article  Google Scholar 

  • Futrelle, R.P. (2000). Ambiguity in visual language theory and its role in diagram parsing, IEEE Symposium on Visual Language, 172–175, Tokio IEEE Computer Society.

    Google Scholar 

  • Gaver, W. W., Beaver, J., & Benford, S. (2003). Ambiguity as a resource for design, proceedings of the conference of human factors in computing system, 5–10 April 2003, Fort Lauderdale, FL. New York ACM Press.

    Google Scholar 

  • Glazer, N. (2011). Challenges with graph interpretation: A review of the literature. Studies in Science Education, 47(2), 183–210. https://doi.org/10.1080/03057267.2011.605307.

    Article  Google Scholar 

  • Grunbaum, A. (1960). The Duhemian argument. Philosophy of Science, 27(1), 75–87.

    Article  Google Scholar 

  • Kaput, J. J. (1987). Representation and mathematics. In C. Janvier (Ed.), Problems of representation in mathematics learning and problem solving (pp. 19–26). Hillsdale: Erlbaum.

    Google Scholar 

  • Karl, T. R., Arguez, A., Huang, B., Lawrimore, J. H., McMahon, J. R., Menne, M. J., et al. (2015). Possible artifacts of data biases in the recent global surface warming hiatus. Science, 348(6242), 1469–1472.

    Article  Google Scholar 

  • Kosslyn, S. M. (1989). Understanding charts and graphs. Applied Cognitive Psychology, 3(3), 185–225.

    Article  Google Scholar 

  • Latour, B., & Woolgar, S. (2013). Laboratory life: The construction of scientific facts. Princeton: Princeton University Press.

    Book  Google Scholar 

  • Lehrer, R., & Schauble, L. (2006). Cultivating model-based reasoning in science education. New York: Cambridge University Press.

    Google Scholar 

  • Lewandowsky, S., & Spence, I. (1989). The perception of statistical graphs. Sociological Methods & Research, 18(2–3), 200–242. Chicago.

    Article  Google Scholar 

  • Linn, M. C., Eylon, B.–. S., & Davis, E. A. (2004). The knowledge integration perspective on learning. In M. C. Linn, E. A. Davis, & P. Bell (Eds.), Internet environments for science education (pp. 29–46). Mahwah: Erlbaum.

    Google Scholar 

  • Mayer, R. E. (1993). Comprehension of graphics in texts: An overview. Learning and Instruction, 3, 239–245.

    Article  Google Scholar 

  • McNeill, K. L., & Krajcik, J. (2007). Middle school students’ use of appropriate and inappropriate evidence in writing scientific explanations. In M. C. Lovett & P. Shah (Eds.), Thinking with data: The proceedings of the 33rd Carnegie symposium on cognition (pp. 233–265). Mahwah: Erlbaum.

    Google Scholar 

  • McNeill, K. L., Lizotte, D. J., Krajcik, J., & Marx, R. W. (2006). Supporting students’ construction of scientific explanations by fading scaffolds in instructional materials. Journal of the Learning Sciences, 15(2), 153–191.

    Article  Google Scholar 

  • Mehan, H. (1979). What time is it, Denise?: Asking known information questions in classroom discourse. Theory Into Practice, 18(4), 285–294.

    Article  Google Scholar 

  • Mooney, C. (2013, 7 October). Who created the global warming “pause”?. Mother Jones. Retrieved 27 July 2015 from http://www.motherjones.com/environment/2013/09/global-warming-pause-ipcc.

  • Mulkay, M. (1979). Science and the sociology of knowledge. London: George AlIen and Unwin.

    Google Scholar 

  • Nachmias, R., & Linn, M. C. (1987). Evaluations of science laboratory data: The role of computer-presented information. Journal of Research in Science Teaching, 24, 491–505.

    Article  Google Scholar 

  • National Research Council. (1996). National Science Education Standards. Washington, DC: The National Academies Press.

    Google Scholar 

  • Nemirovsky, R., & Noble, T. (1997). On mathematical visualization and the place where we live. Educational Studies in Mathematics, 33(2), 99–131.

    Article  Google Scholar 

  • Nussbaum, E. M. (2008). Collaborative discourse, argumentation, and learning: Preface and literature review. Contemporary Educational Psychology, 33(3), 345–359.

    Article  Google Scholar 

  • Quintana, C., Eng, J., Carra, A., Wu, H., & Soloway, E. (1999). Symphony: A case study in extending learner-centered design through process space analysis, paper presented at CHI 99: Conference on human factors in computing systems, may 19–21, 1999. Pennsylvania: Pittsburgh.

    Google Scholar 

  • Radinsky, J., Oliva, S., & Alamar, K. (2010). Camila, the earth, and the sun: Constructing an idea as shared intellectual property. Journal of Research in Science Teaching, 47(6), 619–642. https://doi.org/10.1002/tea.20354.

    Article  Google Scholar 

  • Reiser, B. J., Tabak, I., Sandoval, W. A., Smith, B., Steinmuller, F., & Leone, T. J. (2001). BGuILE: Stategic and conceptual scaffolds for scientific inquiry in biology classrooms. In S. M. Carver & D. Klahr (Eds.), Cognition and instruction: Twenty five years of progress. Mahvah: Erlbaum.

    Google Scholar 

  • Robison, W., Boisjoly, R., & Hoeker, D. (2002). Representation and misrepresentation: Tufte and the Morton Thiokol engineers on the challenger. Science and Engineering Ethics, 8(1), 59–81.

    Article  Google Scholar 

  • Rye, J. A., Rubba, P. A., & Wiesenmayer, R. L. (1997). An investigation of middle school students’ alternative conceptions of global warming. International Journal of Science Education, 19(5), 527–551.

    Article  Google Scholar 

  • Scardamalia, M., & Bereiter, C. (1994). Computer support for knowledge-building communities. Journal of the Learning Sciences, 3, 265–283.

    Article  Google Scholar 

  • Scardamalia, N., Bereiter, C., & Lamon, M. (1994). The CSILE Project: Trying to bring the classroom into the world. In K. McGilly (Ed.), Classroom Lessons: Integrating Cognitive Theory and Classroom Practice. Cambridge, MA: MIT Press.

    Google Scholar 

  • Schoenfeld, A. H., Smith, J. P., & Arcavi, A. (1991). Learning: The microgenetic analysis of one student’s evolving understanding of a complex subject matter domain. In R. Glaser (Ed.), Advances in instructional psychology (pp. 55–175). Hillsdale: Erlbaum.

    Google Scholar 

  • Shah, P., Freedman, E. G., & Vekiri, I. (2005). The comprehension of quantitative information in graphical displays. In P. Shah & A. Miyake (Eds.), The Cambridge handbook of visuospatial thinking (pp. 426–476). New York: Cambridge University Press.

    Chapter  Google Scholar 

  • Shah, P., & Hoeffner, J. (2002). Review of graph comprehension research: Implications for instruction. Educational Psychology Review, 14(1), 47–69.

    Article  Google Scholar 

  • Sandoval, W. A., & Millwood, K. A. (2005). The quality of students’ use of evidence in written scientific explanations. Cognition and Instruction, 23(1), 23–55.

    Article  Google Scholar 

  • Shepardson, D. P., Niyogi, D., Choi, S., & Charusombat, U. (2009). Seventh grade students’ conceptions of global warming and climate change. Environmental Education Research, 15(5), 549–570.

    Article  Google Scholar 

  • Stocker, T. F., Qin, D., Plattner, G. K., Alexander, L. V., Allen, S. K., Bindoff, N. L., et al. (2013). Technical summary. In Climate Change 2013: The Physical Science Basis. Contribution of Working Group I to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change (pp. 33–115). Cambridge University Press.

    Google Scholar 

  • Svihla, V., & Linn, M. C. (2012). A design-based approach to fostering understanding of global climate change. International Journal of Science Education, 34(5), 651–676.

    Article  Google Scholar 

  • Tufte, E. (1997). Visual explanations: Images and quantities, evidence and narrative. Cheshire (CT): Graphics Press.

    Google Scholar 

  • Tversky, B. (2002). Some ways that graphics communicate. In N. Allen (Ed.), Working with words and images: New steps in an old dance. Westport: Ablex Publishing Corporation.

    Google Scholar 

  • Wells, G., & Mejía-Arauz, R. (2006). Toward dialogue in the classroom. The Journal of the Learning Sciences, 15(3), 379–428.

    Article  Google Scholar 

  • Winn, W. D. (1987). Charts, graphs and diagrams in educational materials. In D. M. Willows & H. A. Houghton (Eds.), The psychology of illustration (Vol. 1, pp. 152–198). New York: Springer.

    Chapter  Google Scholar 

  • Zacks, J., Levy, E., Tversky, B., & Schiano, D. (2002). Graphs in print. In Diagrammatic representation and reasoning (pp. 187–206). London: Springer.

    Book  Google Scholar 

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Acknowledgements

This research was supported by the National Science Foundation, grant number 0918743. A preliminary version of this work was presented at CSCL 2011, the Conference on Computer Supported Collaborative Learning.

Funding information Matuk, C. F., Sato, E., & Linn, M. C. (2011). Agreeing to disagree: Challenges with ambiguity in visual evidence. Proceedings of the 9th International conference on computer supported collaborative learning CSCL2011: Connecting computer supported collaborative learning to policy and practice, (Vol. 2, pp. 994–995). Hong Kong: The University of Hong Kong.

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Matuk, C. (2018). Agreeing to Disagree: Students Negotiating Visual Ambiguity Through Scientific Argumentation. In: Daniel, K. (eds) Towards a Framework for Representational Competence in Science Education. Models and Modeling in Science Education, vol 11. Springer, Cham. https://doi.org/10.1007/978-3-319-89945-9_4

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