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Learning Progression During Modelling-Based Teaching

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Modelling-based Teaching in Science Education

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

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Abstract

Students will inevitably vary in the rate at which they become experts in modelling, that they acquire meta-modelling capability. If this variation is to be accommodated, the compulsory science curriculum must be structured so as to facilitate ‘ learning progression’ (LP) – the progress to expert status – in some way. The nature of a generic LP is presented that addresses both models and modelling. The attainment of an LP in models and modelling will be intertwined with an LP for each of visualisation, analogy, argumentation, and learning about science. Whilst the detailed structure and testing of such an LP has yet to be done, the issues associated with identifying suitable phenomena to be modelled, with gaining access to such phenomena, and with ensuring that transfer of learning occurs between modelling activities, can be discussed. Finally, the core issue of assessing what progression has taken place at any one time is confronted.

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  1. 1.

    Sonic Gun is a circular flexible membrane stretched over a circular frame is drawn back at its center and released. The force produces a shock wave in the air that is detectable at a short distance.

References

  • Abell, S. K., & Roth, M. (1995). Reflections on a fifth-grade life science lesson: Making sense of children’s understanding of scientific models. International Journal of Science Education, 17(1), 59–74.

    Article  Google Scholar 

  • Arnold, M., & Millar, R. (1996). Learning the scientific ‘story’: A case study in the teaching and learning of elementary thermodynamics. Science Education, 80(3), 249–281.

    Article  Google Scholar 

  • Aubusson, P. J., Harrison, A. G., & Ritchie, S. M. (2006). Metaphor and analogy in science education. Dordrecht, The Netherlands: Springer.

    Book  Google Scholar 

  • Aubusson, P. J., Treagust, D. F., & Harrison, A. G. (2009). Learning and teaching with analogies and metaphors. In S. M. Ritchie (Ed.), The world of science education: Handbook of research in Australasia (pp. 199–216). Rotterdam, The Netherlands: Springer.

    Google Scholar 

  • Bamberger, Y. M., & Davis, E. A. (2013). Middle-school science students’ scientific modelling performances across content areas and within a learning progression. International Journal of Science Education, 35(2), 213–238.

    Article  Google Scholar 

  • Barab, S. A., Hay, K. E., Barnett, M., & Keating, T. (2000). Virtual solar system project: Building understanding through model building. Journal of Research in Science Teaching, 37(7), 719–756.

    Article  Google Scholar 

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

    Google Scholar 

  • Chittleborough, G. D., Treagust, D. F., Mamiala, T. L., & Mocerino, M. (2005). Students’ perceptions of the role of models in the process of science and in the process of learning. Research in Science & Technological Education, 23(2), 195–212.

    Article  Google Scholar 

  • Corcoran, T., & Silander, M. (2009). Instruction in high schools: The evidence and the challenge. The Future of Children: America's High Schools, 19, 157–183. Retrieved from http://www.futureofchildren.org

  • Csapo, B. (2014). Report on a stretagy for the assessment of skills and competences suitable for IBSE. Dublin, Ireland: Dublin City University.

    Google Scholar 

  • Deng, F., Chen, D.-T., Tsai, C.-C., & Chai, C. S. (2011). Students’ views of the nature of science: A critical review of research. Science Education, 95(6), 961–999.

    Article  Google Scholar 

  • Driver, R., Leach, J., Millar, R., & Scott, P. (1996). Young people’s images of science. Buckingham, UK/Philadelphia, PA: Open University Press.

    Google Scholar 

  • Duschl, R., Maeng, S., & Sezen, A. (2011). Learning progressions and teaching sequences: A review and analysis. Studies in Science Education, 47(2), 123–182.

    Article  Google Scholar 

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

    Book  Google Scholar 

  • Erduran, S., & Jiménez-Aleixandre, M. P. (2008). Argumentation in science education: Perspectives from classroom-based research. Dordrecht, The Netherlands: Springer.

    Google Scholar 

  • Ford, M. J. (2015). Learning progressions and progress: An introduction to our focus on learning progression. Science Education, 99(3), 407–409.

    Article  Google Scholar 

  • Garcia-Mila, M., & Andersen, C. (2008). Cognitive foundations of learning argumentation. In S. Erduran & M. P. Jiménez-Aleixandre (Eds.), Argumentation in science education: Perspectivs from classroom-based research (pp. 29–45). Dordrecht, The Netherlands: Springer.

    Google Scholar 

  • Gick, M. L., & Holyoak, K. J. (1980). Analogical problem solving. Cognitive Psychology, 12(3), 306–355.

    Article  Google Scholar 

  • Gilbert, J. K., & Eilam, B. (2014). Developing science teachers’ representational competence and its impact on their teaching. In B. Eilam & J. K. Gilbert (Eds.), Science teachers’ use of visual representations (pp. 315–329). Dordrecht, The Netherlands: Springer.

    Google Scholar 

  • Gilbert, J. K., Justi, R., & Queiroz, A. S. (2010). The use of a Model of Modelling to develop visualization during the learning of ionic bonding. In M. F. Taşar & G. Çakmakcı (Eds.), Contemporary science education research: International perspectives (pp. 43–51). Ankara, Turkey: Pegem Akademi.

    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 

  • Gobert, J. D., & Pallant, A. (2004). Fostering students’ epistemologies of models via authentic model-based tasks. Journal of Science Education and Technology, 13(1), 7–22.

    Article  Google Scholar 

  • Goswami, U. (1992). Analogical reasoning in children. Hillsdale, NJ: Erlbaum.

    Google Scholar 

  • Gotwals, A. W., & Alonzo, A. C. (2012). Introduction: Leaping into learning progressions in science. In A. C. Alonzo & A. W. Gotwals (Eds.), Learning progressions in science – current challenges and future directions (pp. 3–12). Rotterdam, The Netherlands: Sense.

    Google Scholar 

  • Grosslight, L., Unger, C., Jay, E., & Smith, C. L. (1991). Understanding models and their use in science: Conceptions of middle and high school students and experts. Journal of Research in Science Teaching, 28(9), 799–822.

    Article  Google Scholar 

  • Gullickson, A. R. (Ed.). (2002). The student evaluation standards: How to improve evaluations of students. Thousand Oaks, CA: Corwin Press.

    Google Scholar 

  • Halbern, D., & Collaer, M. (2005). Sex difference in visuospatial abilities: More than meets the eye. In P. Shah & A. Miyake (Eds.), The Cambridge handbook of visuospatial thinking (pp. 170–212). Cambridge, UK: Cambridge University Press.

    Chapter  Google Scholar 

  • Halloun, I. A. (1998). Schematic concepts fro schematic models of the real world: The Newtonian concept of force. Science Education, 82(2), 239–263.

    Article  Google Scholar 

  • Harrison, A. G., & Treagust, D. F. (2006). Teaching and learning with analogies: Friend or foe? In P. Aubusson, A. Harrison, & S. M. Ritchie (Eds.), Metaphor and analogy in science education (pp. 11–24). Dordrecht, The Netherlands: Springer.

    Chapter  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, UK: Cambridge University Press.

    Chapter  Google Scholar 

  • Hofstein, A., & Lunetta, V. (1982). The role of the laboratory in science teaching: Neglect aspects of research. Review of Educational Research, 52(2), 201–217.

    Article  Google Scholar 

  • Hogan, K. (2000). Exploring a process view of students’ knowledge about the nature of science. Science Education, 84(1), 51–70.

    Article  Google Scholar 

  • James, M., Black, P., McCormick, R., & Wiliam, D. (2006). Learning how to learn, in classrooms, schools and networks: Aims, design and analysis. Research Papers in Education, 21(2), 101–118.

    Article  Google Scholar 

  • Justi, R., Gilbert, J. K., & Ferreira, P. F. M. (2009). The application of a ‘model of modelling’ to illustrate the importance of metavisualization in respect of the three levels of representation. In J. K. Gilbert & D. F. Treagust (Eds.), Multiple representations in chemical education (pp. 285–307). Dordrecht, The Netherlands: Springer.

    Chapter  Google Scholar 

  • Kang, S., Scharmann, L. C., & Noh, T. (2005). Examining students’ views on the nature of science: Results from Korean 6th, 8th, and 10th graders. Science Education, 89(2), 314–334.

    Article  Google Scholar 

  • Kenyon, L., Schwarz, C. V., & Hug, B. (2008). The benefits of scientific modeling. Science and Children, 46(2), 40–44.

    Google Scholar 

  • Khishfe, R. (2008). The development of seventh graders’ views of nature of science. Journal of Research in Science Teaching, 45(4), 470–496.

    Article  Google Scholar 

  • Leach, J., Hind, A., & Ryder, J. (2003). Designing and evaluating short teaching interventions about the epistemology of science in high school classrooms. Science Education, 87(6), 831–848.

    Article  Google Scholar 

  • Lehrer, R., & Schauble, L. (2012). Seeding evolutionary thinking by engaging children in modeling its foundations. Science Education, 96(4), 701–724.

    Article  Google Scholar 

  • Louca, L. T., Zacharia, Z. C., & Constantinou, C. P. (2011). In quest of productive modeling-based learning discourse in elementary school science. Journal of Research in Science Teaching, 48(8), 919–951.

    Article  Google Scholar 

  • Luxford, C. J., & Bretz, S. L. (2013). Moving beyond definitions: What student-generated models reveal about their understanding of covalent bonding and ionic bonding. Chemistry Education Research and Practice, 14(2), 214–222.

    Article  Google Scholar 

  • Maia, P. F., & Justi, R. (2009). Learning of chemical equilibrium through modelling-based teaching. International Journal of Science Education, 31(5), 603–630.

    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), 2007–2034.

    Article  Google Scholar 

  • Mirza, N. M., & Perret-Clermont, A.-N. (2009). Argumentation and education – theoretical foundations and practices. Dordrecht, The Netherlands: Springer.

    Google Scholar 

  • Mozzer, N. B., & Justi, R. (2012). Students’ pre- and post-teaching analogical reasoning when they draw their analogies. International Journal of Science Education, 34(3), 429–458.

    Article  Google Scholar 

  • Namdar, B., & Shen, J. (2015). Modeling-oriented assessment in K-12 science education: A synthesis of research from 1980 to 2013 and new directions. International Journal of Science Education, 37(7), 993–1023.

    Article  Google Scholar 

  • Newberry, M. (2006). Using the ‘Thinking Frames’ approach to improve pupil engagement and attainment in science. Paper presented at the teacher research conference, London, UK.

    Google Scholar 

  • Newberry, M., & Cams Hill Science Consortium. (2007). Thinking frame. Retrieved from http://www.thinkingframe.com

  • Newberry, M., & Cams Hill Science Consortium. (2014). Science pathways. Retrieved from http://www.sciencepathways.co.uk

  • Newberry, M., & Gilbert, J. K. (2007). Bringing learners and scientific expertise together. In K. S. Taber (Ed.), Science education for gifted learners (pp. 212–217). London, UK: Routledge.

    Google Scholar 

  • Newberry, M., Grevatt, A., & Gilbert, J. K. (2009). Science pathways for year 7. Stevenage, UK: Badger.

    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, UK: Cambridge University Press.

    Chapter  Google Scholar 

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

    Google Scholar 

  • Nicolau, C. T., & Constantinou, C. P. (2014). Assessment of modelling competence: A systematic review and synthesis of empirical research. Educational Research Review, 13, 52–73.

    Article  Google Scholar 

  • Niss, M. (2009). Metamodelling messages conveyed in five statistical mechanical textbooks from 1936 to 2001. International Journal of Science Education, 31(5), 697–719.

    Article  Google Scholar 

  • Passmore, C. M., & Stewart, J. (2002). A modeling approach to teaching evolutionary biology in high schools. Journal of Research in Science Teaching, 39(3), 185–204.

    Article  Google Scholar 

  • Press, H. (1995). The little book of scientific experiments. New York, NY: Strirling.

    Google Scholar 

  • Prins, G. T., Bulte, A. M. W., & Pilot, A. (2011). Evaluation of a design principle for fostering students’ epistemological views on models and modelling using authentic practices as contexts for learning in chemistry education. International Journal of Science Education, 33(11), 1539–1569.

    Article  Google Scholar 

  • Prins, G. T., Bulte, A. M. W., van Driel, J., & Pilot, A. (2008). Selection of authentic modelling practices as contexts for chemistry education. International Journal of Science Education, 30(14), 1867–1890.

    Article  Google Scholar 

  • Redfors, A., & Ryder, J. (2001). University physics students’ use of models in explanations of phenomena involving interaction between metals and electromagnetic radiation. International Journal of Science Education, 23(12), 1283–1301.

    Article  Google Scholar 

  • Ryder, J., Leach, J., & Driver, R. (1999). Undergraduate science students’ images of science. Journal of Research in Science Teaching, 36(2), 201–219.

    Article  Google Scholar 

  • Schwarz, C. V., Reiser, B. J., Davis, E. A., Kenyon, L., Achér, A., Fortus, D., … 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(6), 632–654.

    Google Scholar 

  • Shulman, L. S. (1987). Knowledge and teaching: Foundations of the new reform. Harvard Educational Review, 51(1), 1–22.

    Article  Google Scholar 

  • Sins, P. H. M., Savalsberg, E. R., & van Joolingen, W. (2005). The difficult process of scientific modelling: An analysis of novice’s reasoning during computer-based modelling. International Journal of Science Education, 27(14), 1695–1721.

    Article  Google Scholar 

  • The Concord Consortium. (2014). Showcase. Retrieved from http://mw.concord.org/modeler/showcase

  • Treagust, D. F., Harrison, A., & Venville, G. J. (1998). Teaching science effectively with analogies: An approach for preservice and inservice teacher education. Journal of Science Teacher Education, 9(2), 85–101.

    Article  Google Scholar 

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Authors and Affiliations

  1. The University of Reading, Berkshire, UK

    John K. Gilbert

  2. Universidade Federal de Minas Gerais, Belo Horizonte, Brazil

    Rosária Justi

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  2. Rosária Justi
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Gilbert, J.K., Justi, R. (2016). Learning Progression During 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_10

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  • DOI: https://doi.org/10.1007/978-3-319-29039-3_10

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