Skip to main content

Representation Construction: A Guided Inquiry Approach for Science Education

  • Chapter
  • First Online:
STEM Education in the Junior Secondary

Abstract

This chapter outlines a guided inquiry approach, called representation construction, which was successfully developed within an Australian Research Council (ARC) project that links student learning and engagement with the knowledge production practices of science. This approach involves challenging students to generate and negotiate the representations (text, graphs, models, diagrams) that constitute the discursive practices of science, rather than focusing on the text-based, definitional versions of concepts. The representation construction approach is based on sequences of representational challenges which involve students constructing representations to actively explore and make claims about phenomena. It thus represents a more active view of knowledge than traditional structural approaches and encourages visual as well as the traditional text-based literacies. The approach has been successful in demonstrating enhanced outcomes for students, in terms of sustained engagement with ideas, and quality learning, and for teachers enhanced pedagogical knowledge and understanding of how knowledge in science is developed and communicated. This chapter draws on specific examples of how the approach was implemented in a variety of topics, such as energy, forces, astronomy and ideas about matter within junior secondary science classrooms. It will also draw on the issues associated with the adoption of the approach in laptop/tablet classrooms where part of the curriculum is delivered in the cloud.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 84.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 109.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 109.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Notes

  1. 1.

    Pseudonym for the school

  2. 2.

    Pseudonyms are given for all teacher names.

References

  • Ainsworth, S. (2006). DEFT: A conceptual framework for learning with multiple representations. Learning and Instruction, 16(3), 183–198.

    Article  Google Scholar 

  • Ainsworth, S. (2008). The educational value of multiple representations when learning complex scientific concepts. In J. K. Gilbert, M. Reiner, & M. Nakhlel (Eds.), Visualization: Theory and practice in science education (pp. 191–208). New York: Springer.

    Chapter  Google Scholar 

  • Ainsworth, S., Prain, V., & Tytler, R. (2011). Drawing to learn in science. Science, 333(26), 1096–1097.

    Article  Google Scholar 

  • Chi, M. (2009). Active-constructive-interactive: A conceptual framework for differentiating learning activities. Topics in Cognitive Science, 1, 73–105.

    Article  Google Scholar 

  • Chubb, I. (2014). Office of the Chief Scientist: Science, Technology, Engineering and Mathematics: Australia’s Future. Australian Government, Canberra, Australia. Retrieved from http://www.chiefscientist.gov.au/wp- content/uploads/STEM_AustraliasFuture_Sept2014_Web.pdf

  • Cox, R. (1999). Representation construction, externalized cognition and individual differences. Learning and Instruction, 9, 343–363.

    Article  Google Scholar 

  • diSessa, A. (2004). Metarepresentation: Native competence and targets for instruction. Cognition and Instruction, 22(3), 293–331.

    Article  Google Scholar 

  • Dreher, A., Kuntze, S., & Lerman, S. (2016). Why use multiple representations in the mathematics classroom? Views of English and German preservice teachers. International Journal of Science and Mathematics Education, 14(2), 363–381. doi:10.1007/s10763-015-9633-6.

    Article  Google Scholar 

  • Duval, R. (2006). A cognitive analysis of problems of comprehension in a learning of mathematics. Educational Studies in Mathematics, 61, 103–131. doi:10.1007/s10649-006-0400-z.

    Article  Google Scholar 

  • Elkins, J. (2011). Visual practices across the University: A report. In O. Grau (Ed.), Imagery in the 21st century. Cambridge, MA: MIT Press.

    Google Scholar 

  • Furtak, E., Seidel, T., Iverson, H., & Briggs, D. (2012). Experimental and quasi-experimental studies of inquiry-based science teaching: A meta-analysis. Review of Educational Research, 82(3), 300–329.

    Article  Google Scholar 

  • Gibson, J. (1977). The theory of affordances. In R. Shaw & J. Bransford (Eds.), Perceiving, acting, and knowing: Toward an ecological psychology (pp. 67–82). Hillsdale, NJ: Erlbaum.

    Google Scholar 

  • Gilbert, J. K. (2005). Visualization in science education. New York: Springer.

    Book  Google Scholar 

  • Gooding, D. (2004). Visualization, inference and explanation in the sciences. In G. Malcolm (Ed.), Studies in Multidisciplinarity (Vol. 2, pp. 1–25). Elsevier.

    Google Scholar 

  • Gooding, D. (2006). From phenomenology to field theory: Faraday’s visual reasoning. Perspectives on Science, 14(1), 40–65.

    Article  Google Scholar 

  • Goodrum, D., Druhan, A., & Abbs, J. (2012). The status and quality of year 11 and 12 science in Australian schools. Canberra, Australia: Australian Academy of Science. Retrieved April 2016 from http://www.science.org.au/publications/research-reports-and-policy.html

  • Greeno, J. G., & Hall, R. P. (1997). Practicing representation: Learning with and about representational forms. Phi Delta Kappan, 78(5), 361–368.

    Google Scholar 

  • Hackling, M., & Prain, V. (2005). Primary connections: Stage 2 trial. Canberra, Australia: Australian Academy of Science.

    Google Scholar 

  • Honey, M., Pearson, G., & Schweingruber, H. (Eds.). (2014). STEM Integration in K-12 education: Status, prospects and an Agenda for research. Washington, DC: The National Academies Press.

    Google Scholar 

  • Hubber, P., Tytler, R., Chittleborough, G., Campbell, C., & Jobling, W. (2012). Evaluation of delivery of the switched on secondary science professional learning (SOSSPL) program (2011–2012). Waurn Ponds, Victoria: Deakin University.

    Google Scholar 

  • Hubber, P., Tytler, R., & Haslam, F. (2010). Teaching and learning about force with a representational focus: Pedagogy and teacher change. Research in Science Education, 40(1), 5–28.

    Article  Google Scholar 

  • Johri, A., Roth, W., & Olds, B. (2013). The role of representations in engineering practices: Taking a turn towards inscriptions. Journal of Engineering Education, 102(1), 2–19. doi:10.1002/jee.20005.

    Article  Google Scholar 

  • Kapur, M. (2008). Productive failure. Cognition and Instruction, 26(3), 379–424. doi:10.1080/07370000802212669.

    Article  Google Scholar 

  • Kozma, R., & Russell, J. (2005). Students becoming chemists: Developing representational competence. In J. Gilbert (Ed.), Visualization in Science Education (pp. 121–145). Springer.

    Google Scholar 

  • Latour, B. (1999). Pandora’s hope: Essays on the reality of science studies. Cambridge, MA: Harvard University Press.

    Google Scholar 

  • Lehrer, R., & Chazan, D. (1998). Designing learning environments for developing understanding of geometry and space. Mahwah, NJ: Lawrence Erlbaum Associates.

    Google Scholar 

  • Lehrer, R., & Schauble, L. (2006a). Cultivating model-based reasoning in science education. In K. Sawyer (Ed.), Cambridge handbook of the learning sciences (pp. 371–388). Cambridge, MA: Cambridge University Press.

    Google Scholar 

  • Lehrer, R., & Schauble, L. (2006b). Scientific thinking and science literacy. In W. Damon & R. Lerner (Eds.), Handbook of child psychology (6th ed., Vol. 4).

    Google Scholar 

  • Lemke, J. L. (1990). Talking science: Language, learning and values. Greenwood Publishing Group.

    Google Scholar 

  • Lemke, J. (2004). The literacies of science. In E. W. Saul (Ed.), Crossing borders in literacy and science instruction: Perspectives on theory and practice (pp. 33–47). Newark, NJ: International Reading Association/National Science Teachers Association.

    Google Scholar 

  • Leviston, Z., Price, J., Malkin, S., & McCrea, R. (2014). Fourth annual survey of Australian attitudes to climate change: Interim report. CSIRO: Perth, Australia.

    Google Scholar 

  • Linn, M., Lewis, C., Tsuchida, I., & Songer, N. (2000). Beyond fourth grade science: Why do U.S. and Japanese students diverge? Educational Researcher, 29(3), 4–14.

    Article  Google Scholar 

  • Moje, E. (2007). Developing socially just subject-matter instruction: A review of the literature on disciplinary literacy learning. Review of Research in Education, 31, 1–44.

    Article  Google Scholar 

  • Osborne, J. (2006). Towards a science education for all: The role of ideas, evidence and argument. In Proceedings of the ACER research conference: Boosting science learning –What will it take? (pp. 2–5). Retrieved from http://research.acer.edu.au/cgi/viewcontent.cgi?article=1000&context=research_conference_2006

  • Prain, V., & Tytler, R. (2012). Learning through constructing representations in science: A framework of representational construction affordances. International Journal of Science Education, 34(17), 2751–2773.

    Article  Google Scholar 

  • Schwab, J. J. (1962). The teaching of science as enquiry. Cambridge, MA: Harvard University Press.

    Google Scholar 

  • Schwartz, D. L. (1995). The emergence of abstract representations in dyad problem solving. The Journal of the Learning Sciences, 4(3), 321–354.

    Article  Google Scholar 

  • Stieff, M. (2011). Improving representational competence using molecular simulations embedded in inquiry activities. Journal of Research in Science Teaching, 48(10), 1137–1158.

    Article  Google Scholar 

  • Stieff, M., & DeSutter, D. (2016, June). Drawing from dynamic visualisations. Paper presented at the International Conference of the Learning Sciences, Singapore.

    Google Scholar 

  • Tytler, R., Ferguson, J., Aranda, G., Gorur, R., & Prain, V. (2016, June). Drawing within experimental exploration as part of core epistemological and epistemic practices in science. Paper presented at the International Conference of the Learning Sciences, Singapore.

    Google Scholar 

  • Tytler, R., Haslam, F., Prain, V., & Hubber, P. (2009). An explicit representational focus for teaching and learning about animals in the environment. Teaching Science, 55(4), 21–27.

    Google Scholar 

  • Tytler, R., Peterson, S., & Prain, V. (2006). Picturing evaporation: Learning science literacy through a particle representation. Teaching Science, the Journal of the Australian Science Teachers Association, 52(1), 12–17.

    Google Scholar 

  • Tytler, R., Prain, V., Hubber, P., & Waldrip, B. (Eds.). (2013). Constructing representations to learn science. Rotterdam, The Netherlands: Sense Publishers.

    Google Scholar 

  • Van Meter, P., Aleksic, M., Schwartz, A., & Garner, J. (2006). Learner-generated drawing as a strategy for learning from content area text. Contemporary Educational Psychology, 31, 142–166.

    Article  Google Scholar 

  • Van Meter, P., & Garner, J. (2005). The promise and practice of learner-generated drawing: Literature review and synthesis. Educational Psychology Review, 17(4), 285–325.

    Article  Google Scholar 

  • Vygotsky, L. (1981). Thought and language (Rev. and Ed. by A. Kozulin). Cambridge, MA: MIT Press.

    Google Scholar 

  • Waldrip, B., Prain, V., & Carolan, J. (2010). Using multi-modal representations to improve learning in junior secondary science. Research in Science Education, 40(1), 65–80.

    Article  Google Scholar 

  • Zhang, Z., & Linn, M. (2008). Using drawings to support learning from dynamic visualizations. In Proceedings of the 8th international conference on the learning sciences (Vol. 3, pp. 161–162).

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Peter Hubber .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2018 Springer Nature Singapore Pte Ltd.

About this chapter

Cite this chapter

Hubber, P., Tytler, R., Chittleborough, G. (2018). Representation Construction: A Guided Inquiry Approach for Science Education. In: Jorgensen, R., Larkin, K. (eds) STEM Education in the Junior Secondary. Springer, Singapore. https://doi.org/10.1007/978-981-10-5448-8_5

Download citation

  • DOI: https://doi.org/10.1007/978-981-10-5448-8_5

  • Published:

  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-10-5447-1

  • Online ISBN: 978-981-10-5448-8

  • eBook Packages: EducationEducation (R0)

Publish with us

Policies and ethics