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Epistemic Frames as an Analytical Framework for Understanding the Representation of Scientific Activity in a Modeling-Based Learning Unit

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Abstract

Set in the context of modeling-based learning (MBL), this research investigated the potential of epistemic frames as a theoretical and analytical framework for understanding teaching and learning practices used in classroom communities of practice. Epistemic frames are conceptualized as an orienting lens for a classroom community of practice that emerges out of how they organize knowledge structures and practices to support their ways of knowing. This research examined the types and organization of practices in the classroom where a MBL unit was implemented to understand what sense-making practices were used, and how these practices supported the classroom community’s negotiation of understanding. Through this analysis, a sense of the viability of epistemic frames as a productive theoretical and analytical lens was revealed in terms of providing a better understanding of the nuances and context dependencies of what students and teachers do to make sense of real-world scientific phenomena in classrooms.

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References

  • Banilower, E. R., Smith, P. S., Weiss, I. R., Malzahn, K. A., Campbell, K. M., & Weis, A. M. (2013). Report of the 2012 National survey of science and mathematics education. Chapel Hill, NC: Horizon Research.

    Google Scholar 

  • Bell, P., Bricker, L., Tzou, C., Lee, T., & Van Horne, K. (2012). Exploring the science framework: engaging learners in scientific practices related to obtaining, evaluating, and communicating information. Science Scope, 36(3), 17–22.

  • Berland, L. K. (2011). Explaining variation in how classroom communities adapt the practice of scientific argumentation. Journal of the Learning Sciences, 20(4), 625–664.

    Google Scholar 

  • Bing, T. J., & Redish, E. F. (2009). Analyzing problem solving using math in physics: epistemological framing via warrants. Physical Review Special Topics - Physics Education Research, 5(020108), 1–15.

    Google Scholar 

  • Brown, J. S., Collins, A., & Duguid, P. (1989). Situated cognition and the culture of learning. Educational Researcher, 18(1), 32–42.

    Google Scholar 

  • Broudy, H. (1977). Types of knowledge and purposes of education. In R. C. Anderson, R. J. Spiro, & W. E. Montague (Eds.), Schooling and the acquisition of knowledge (pp. 1–17). Hillsdale, NJ: Lawrence Erlbaum.

    Google Scholar 

  • Campbell, T. & Bohn, C. (2008). Science laboratory experiences of high school students across one state in the U.S.: Descriptive research from the classroom. Science Educator. 17(1), 36–48.

    Google Scholar 

  • Campbell, T., Zhang, D., & Neilson, D. (2011). Model based inquiry in the high school physics classroom: An exploratory study of implementation and outcomes. Journal of Science Education and Technology, 20(3), 258–269.

    Google Scholar 

  • Campbell, T., Neilson, D., & Oh, P. S. (2013). Developing and using models in physics: Grounding instruction around scientifically rich, often complex natural phenomena. The Science Teacher, 80(6), 35–41.

    Google Scholar 

  • Carlonne, H. (2012). Methodological considerations for studying identity in school science: an anthropological approach. In M. Varelas (Ed.), Identity constructions and science education researcher: learning, teaching, and being in multiple contexts (pp. 9–25). Rotterdam, Netherlands: Sense.

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

    Google Scholar 

  • Elby, A., & Hammer, D. (2010). Epistemological resources and framing: a cognitive framework for helping teachers interpret and respond to their students’ epistemologies. In L. D. Bendixon, & F. C. Feucht (Eds.), Personal epistemology in the classroom: theory, research, and implications for practice (pp. 409–434). Cambridge: Cambridge University Press.

  • Engle, R. A. (2006). Framing interactions to foster generative learning: a situative explanation of transfer in a community of learners classroom. Journal of the Learning Sciences, 15(4), 451–498.

    Google Scholar 

  • Flyvbjerg, B. (2006). Five Misunderstandings About Case-Study Research. Qualitative Inquiry, 12(2), 219–245.

  • Ford, M. (2008). ‘Grasp of practice’ as a reasoning resource for inquiry and nature of science understanding. Science & Education, 17(2–3), 147–177.

    Google Scholar 

  • Ford, M. J. (2015). Educational implications of choosing “practice” to describe science in the next generation science standards. Science Education, 99(6), 1041–1048.

    Google Scholar 

  • Ford, M. J., & Forman, E. A. (2006). Redefining disciplinary learning in classroom contexts. Review of Research in Education, 30(1), 1–32.

    Google Scholar 

  • Ford, M. J., & Wargo, B. M. (2012). Dialogic framing of scientific content for conceptual and epistemic understanding. Science Education, 96(3), 369–391.

    Google Scholar 

  • Giere, R. N. (1999). Using models to represent reality. In L. Magnani, N. J. Nersessian, & P. Thagard (Eds.), Model-based reasoning in scientific discovery (pp. 41–57). New York, NY: Kluwer Academic/Plenum Press.

    Google Scholar 

  • Giere, R. (2004). How models are used to represent reality. Philosophy of Science, 71(5), 742–752.

    Google Scholar 

  • Goffman, E. (1974). Frame analysis: an essay on the organization of experience. New York, NY: Harper & Row.

    Google Scholar 

  • Groenewald, T. (2004). A phenomenological research design illustrated. International Journal of Qualitative Methods, 3(1), 1–25.

    Google Scholar 

  • Halloun, I. A. (2004). Modeling theory in science education. Dordrecht, The Netherlands: Kluwer Academic Publishing House.

    Google Scholar 

  • Hammer, D., Elby, A., Scherr, R. E., & Redish, E. F. (2005). Resources, framing, and transfer In J. P. Mestre (Ed.), Transfer of learning from a modern multidisciplinary perspective (pp. 89–120). Greenwich, CT: Information Age Publishing.

  • Hutchison, P., & Hammer, D. (2009). Attending to student epistemological framing in a science classroom. Science Education, 94(3), 506–524.

    Google Scholar 

  • Kelly, G. J. (2008). Inquiry, activity, and epistemic practice. In R. Duschl, & R. Grandy (Eds.), Teaching scientific inquiry (pp. 99–117). Rotterdam, Netherlands: Sense.

  • Knorr-Cetina. (1991). Epistemic cultures: forms of reason in science. History of Political Economy, 23(1), 105–122.

    Google Scholar 

  • Knorr-Cetina, K. (1999). Epistemic cultures: how the sciences make knowledge. Cambridge, MA: Harvard University Press.

    Google Scholar 

  • Lave, J., & Wenger, E. (1991). Situated learning: legitimate peripheral participation. Cambridge, UK: Cambridge University Press.

    Google Scholar 

  • Lehrer, R., & Schauble, L. (2006). Scientific thinking and scientific literacy. In K. A. Renninger & I. E. Siegel (Eds.), Handbook of child psychology, 6 (Vol. 4, pp. 153–196). Hoboken, NJ: Wiley.

    Google Scholar 

  • Manz, E. (2015). Representing student argumentation as functionally emergent from scientific activity. Review of Educational Research, 85(4), 553–590.

    Google Scholar 

  • Manz, E., & Saurez, E. (2017). Supporting teachers to negotiate uncertainty for science, students, and teaching. Science Education, 102, 771–795. https://doi.org/10.1002/sce.21343.

    Article  Google Scholar 

  • Mendonça, P. C. C., & Justi, R. (2013). The relationships between modelling and argumentation from the perspective of the model of modelling diagram. International Journal of Science Education, 35(14), 2407–2434.

    Google Scholar 

  • Morrison, M., & Morgan, M. S. (1999). Models as mediating instruments. In M. S. Morgan & M. Morrison (Eds.), Models as mediators: perspectives on natural and social science (pp. 10–37). Cambridge, UK: Cambridge University Press.

    Google Scholar 

  • National Research Council (NRC). (2012). A framework for K-12 science standards: practices, crosscutting concepts, and core ideas. Washington, DC: National Academy Press.

  • Neilson, D., Campbell, T., & Allred, B. (2010). Model-based inquiry in physics: A buoyant force module. The Science Teacher, 77(8), 38–43.

    Google Scholar 

  • Nersessian, N. J. (1999). Model-based reasoning in conceptual change. In L. Magnani, N. J. Nersessian, & P. Thagard (Eds.), Model-based reasoning in scientific discovery (pp. 5–22). New York: Kluwer Academic/Plenum Press.

    Google Scholar 

  • NGSS Lead States. (2013). Next generation science standards: for states, by states. Washington, DC: The National Academies Press.

  • Oh, P. S., & Oh, S. J. (2011). What teachers of science need to know about models: an overview. International Journal of Science Education, 33(8), 1109–1130.

    Google Scholar 

  • Passmore, C. M., & Svoboda, J. (2012). Exploring opportunities for argumentation in modeling classrooms. International Journal of Science Education, 34(10), 1535–1554.

    Google Scholar 

  • Passmore, C., Gouvea, J. S., & Giere, R. (2014). Models in science and in learning science: focusing scientific practice on sense-making. In M. R. Matthews (Ed.), International handbook of research in history, philosophy and science teaching (pp. 1171–1202). Dordrecht, Netherlands: Springer Verlag.

  • Pickering, A. (1995). Themangle of practice: time, agency, and science. Chicago, IL: University of Chicago Press.

    Google Scholar 

  • Rouse, J., (2007). Practice Theory. Division I Faculty Publications. Paper 43. Retrieved fromhttp://wesscholar.wesleyan.edu/div1facpubs/43http://wesscholar.wesleyan.edu/div1facpubs/43

  • Russ, R. S., Coffey, J. E., Hammer, D., & Hutchison, P. (2009). Making classroom assessment more accountable to scientific reasoning: a case for attending to mechanistic thinking. Science Education, 93(5), 875–891.

    Google Scholar 

  • Russ, R. S., & Luna, M. J. (2013). Inferring teacher epistemological framing from local patterns in teacher noticing. Journal of Research in Science Teaching, 50(3), 284–314.

    Google Scholar 

  • Sandoval, W. A. (2005). Understanding students’ practical epistemologies and their influence on learning through inquiry. Science Education, 89(4), 634–656.

    Google Scholar 

  • Schwarz, C., & Passmore, C. (2012). Preparing for the next generation science standards—developing and using models. [Webinar] National Science Teachers Association. Retrieved from http://learningcenter.nsta.org/products/symposia_seminars/Ngss/webseminar6.aspx.

  • Shaffer, D. W. (2004). Pedagogical praxis: the professions as models for post-industrial education. Teachers College Record, 106(7), 1401–1421.

    Google Scholar 

  • Shaffer, D. W. (2006). Epistemic frames for epistemic games. Computers and Education, 46(3), 223–234.

    Google Scholar 

  • Stewart, J., Cartier, J. L., & Passmore, C. M. (2005). Developing understanding through model-based inquiry. In S. Donovan & J. Bransford (Eds.), How students learn (pp. 515–565). Washington DC: National Academies Press.

    Google Scholar 

  • United States Census Bureau. (2010). Diversity. Retrieved from http://www.census.gov/2010census/popmap/ipmtext.php?fl=49.

  • Wenger, E. (1998). Communities of practice: learning, meaning, and identity. Cambridge, UK: Cambridge University Press.

    Google Scholar 

  • Windschitl, M. (2003). Inquiry projects in science teacher education: what can investigative experiences reveal about teacher thinking and eventual classroom practice? Science Education, 87(1), 112–143.

    Google Scholar 

  • Windschitl, M. (2012), Ambitious teaching as the “new normal” in American science classrooms: how will we prepare the next generation of professional educators?. Lecture. University: Pennsylvania State.

  • Windschitl, M. & Calabrese Barton, A. (2016) Rigor and equity by design: seeking a core of practices for the science education community. AERA Handbook of Research on Teaching, 5th Edition.

  • Windschitl, M., & Thompson, J. (2013). The modeling toolkit: making student thinking visible with public representations. The Science Teacher, 80(6), 63–69.

    Google Scholar 

  • Windschitl, M., Thompson, J., & Braaten, M. (2008). Beyond the scientific method: model-based inquiry as a new paradigm of preference for school science investigations. Science Education, 92(5), 941–967.

    Google Scholar 

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Campbell, T., Fazio, X. Epistemic Frames as an Analytical Framework for Understanding the Representation of Scientific Activity in a Modeling-Based Learning Unit. Res Sci Educ 50, 2283–2304 (2020). https://doi.org/10.1007/s11165-018-9779-7

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