1,579
Views
1
CrossRef citations to date
0
Altmetric
Articles

‘Voodoo maths’, asymmetric dependency and maths blame: why collaboration between school science and mathematics teachers is so rare

ORCID Icon & ORCID Icon
Pages 782-802 | Received 20 Jul 2018, Accepted 04 Feb 2019, Published online: 16 Mar 2019

References

  • Becker, K., & Park, K. (2011). Effects of integrative approaches among science, technology, engineering, and mathematics (STEM) subjects on students’ learning: A preliminary meta-analysis. Journal of STEM Education, 12, 23–37.
  • Bell, E. T. (1951). Mathematics: Queen and servant of science. Washington, DC: The Mathematical Association of America.
  • BERA. (2011). Ethical guidelines for educational research. London: BERA.
  • Berlin, D., & Lee, H. (2005). Integrating science and mathematics education: Historical analysis. School Science and Mathematics, 105(1), 15–24.
  • Berlin, D. F., & White, A. L. (1995). Connecting school science and mathematics. In P. House & A. Coxford (Eds.), Connecting mathematics across the curriculum (pp. 22–33). Reston, VA: National Council of Teachers of Mathematics.
  • Bernstein, B. (2000). Pedagogy, symbolic control and identity (2nd ed.). Lanham, MA: Rowman & Littlefield.
  • Boohan, R. (2016). The language of mathematics in science. Hatfield: ASE.
  • Braun, V., & Clarke, C. (2013). Successful qualitative research. London: Sage.
  • Cohen, L., Manion, L., & Morrison, K. (2011). Research methods in education. Abingdon: Routledge.
  • Department for Education. (2013). Programme of study for mathematics – key stage 4. Department for Education. Retrieved September 2014, from https://www.gov.uk/government/publications/national-curriculum-in-england-mathematics-programmes-of-study
  • Department for Education. (2015). Biology, chemistry and physics GCSE subject content. London: Department for Education.
  • Dierdorp, A., Bakker, A., van Maanen, J., & Eijkelhof, H. (2014). Meaningful statistics in professional practices as a bridge between mathematics and science: An evaluation of a design research project. International Journal of STEM Education, 1(9), 1–15.
  • Dodd, H., & Bone, T. (1995). To what extent does the national curriculum for mathematics serve the needs of science? Teaching Mathematics and its Applications, 14(3), 102–106.
  • Fairbrother, R. (2008). The validity of the key stage 3 science tests. School Science Review, 89(329), 107–113.
  • Fensham, P. (2009). The link between policy and practice in science education: The role of research. Science Education, 93(6), 1076–1095.
  • Frade, C., Winbourne, P., & Braga, S. M. (2009). A mathematics-science community of practice: Reconceptualising transfer in terms of crossing boundaries. For the Learning of Mathematics, 29, 14–22.
  • Gill, T. (2012). Uptake of two-subject combinations of the most popular A levels in 2011, by candidate and school characteristics, Statistics Report Series No.47. Cambridge: Cambridge Assessment. Retrieved April 2015, from http://www.cambridgeassessment.org.uk/Images/109936-uptake-of-two-subject-combinations-of-the-most-popular-a-levels-in-2011-by-candidate-and-school-characteristics.pdf
  • Glackin, M. (2016). ‘Risky fun’ or ‘Authentic science’? How teachers’ beliefs influence their practice during a professional development programme on outdoor learning. International Journal Science Education, 38(3), 1–25.
  • Goldsworthy, A., Watson, R., & Wood-Robinson, V. (1999). Getting to grips with graphs. Hatfield: ASE.
  • Grove, M., & Pugh, S. (2015). Is a conceptual understanding of maths vital for chemistry. Education in Chemistry, 52, 26–29.
  • Honey, M., Pearson, G., & Schweingruber, H. (2014). STEM integration in K-12 education: Status, prospects, and an agenda for research. Washington, DC: National Academies Press. Retrieved September 2014, from http://www.nap.edu/catalog.php?record_id=18612
  • Hoyles, C., Newman, K., & Noss, R. (2001). Changing patterns of transition from school to university mathematics. International Journal of Mathematical Education in Science and Technology, 32(6), 829–845.
  • Koenig, J. (2011). A Survey of the mathematics landscape within bioscience undergraduate and postgraduate UK higher education. Leeds: UK Centre for Bioscience, Higher Education Academy.
  • Kvale, S., & Brinkmann, S. (2009). Interviews: Learning the craft of qualitative research interviewing. Los Angeles: Sage.
  • Leinhardt, G., Zaslavsky, O., & Stein, M. (1990). Functions, graphs and graphing: Tasks, learning and teaching. Review of Educational Research, 60(1), 1–64.
  • Marcus, G., & Davis, E. (2013, April 13). Maths is the true language of science. Financial Times. Retrieved September 2014, from http://www.ft.com/cms/s/0/f1ec9a54-a35f-11e2-ac00-00144feabdc0.html#axzz3DTPlfiew
  • National Academies Press. (2012). A framework for K-12 science education practices, crosscutting concepts, and core ideas. Washington, DC: National Academies Press.
  • OED. (n.d.). Retrieved from Oxford English Dictionary: http://www.oed.com
  • Ofqual. (2015). GCSE subject level conditions and requirements for single science (biology, chemistry and physics). London: Department for Education. Retrieved October 2017, from https://www.gov.uk/government/uploads/system/uploads/attachment_data/file/600867/gcse-subject-level-conditions-and-requirements-for-single-science.pdf
  • Orton, T., & Roper, T. (2000). Science and mathematics: A relationship in need of counselling? Studies in Science Education, 35(1), 123–153.
  • Osborne, J. (2011). Science teaching methods: A rationale for practices. School Science Review, 93(343), 93–103.
  • Osborne, J. (2014). Teaching scientific practices: Meeting the challenge of change. Journal of Science Teacher Education, 25, 177–196.
  • Pajares, M. F. (1992). Teachers’ beliefs and educational research: Cleaning Up a messy construct. Review of Educational Research, 62(3), 307–332.
  • Pang, J., & Good, R. (2000). A review of the integration of science and mathematics: Implications for further research. School Science and Mathematics, 100(2), 73–82.
  • Rebello, N. S., Zollman, D., Allbaugh, A., Engelhardt, P., Gray, K., Hrepic, Z., & Itza-Ortiz, S. (2005). Dynamic transfer – a perspective from physics education. In J. Mestre (Ed.), Transfer of learning from a modern multidisciplinary perspective (pp. 217–250). Greenwich, Connecticut: Information Age Publishing.
  • Redish, E. F., & Kuo, E. (2015). Language of physics, language of math: Disciplinary culture and dynamic epistemology. Science and Education, 24, 561–590.
  • Rubin, H., & Rubin, I. (1995). Qualitative interviewing: The art of hearing data. Thousand Oaks, CA: Sage.
  • Smith, A. (2004). Making mathematics count. London: The Stationary Office.
  • Turşucu, S., Spandaw, J., Flipse, S., & de Vries, M. J. (2017). Teachers’ beliefs about improving transfer of algebraic skills from mathematics into physics in senior pre-university education. International Journal of Science Education, 39(5), 587–604.
  • Tytler, R., Prain, V., & Hubber, P. (2013). Constructing representations to learn in science. Rotterdam: Sense Publishers.
  • Venville, G., Wallace, J., Rennie, L., & Malone, J. (2002). Curriculum Integration: Eroding the high ground of science as a school subject.  Studies in Science Education, 37(1), 43–83.
  • Wallace, C. (2014). Overview of the role of teacher beliefs in science education. In R. Evans, J. Luft, C. Czerniak, & C. Pea (Eds.), The role of science teachers’ beliefs in international classrooms: From teacher actions to student learning (pp. 17–31). Rotterdam: Sense Publishers.
  • Williams, J., Roth, W.-M., Swanson, D., Doig, B., Groves, S., Omuvwie, M., … Mousoulides, N. (2016). Interdisciplinary mathematics education. Springer Open. Retrieved September 2016, from http://download.springer.com/static/pdf/540/bok%253A978-3-319-42267-1.pdf?originUrl=http%3A%2F%2Flink.springer.com%2Fbook%2F10.1007%2F978-3-319-42267-1&token2=exp=1473326793~acl=%2Fstatic%2Fpdf%2F540%2Fbok%25253A978-3-319-42267-1.pdf%3ForiginUrl%3Dhttp%25
  • Wilson, E. O. (2013, April 5). Great scientist (not equal to) good at math. Wall Street Journal. Retrieved September 2014, from http://online.wsj.com/news/articles/SB10001424127887323611604578398943650327184?mg=reno64-wsj&url=http%3A%2F%2Fonline.wsj.com%2Farticle%2FSB10001424127887323611604578398943650327184.html
  • Wong, V. (2017). Variation in graphing practices between mathematics and science: Implications for science teaching. School Science Review, 98(365), 109–115.
  • Wong, V. (2018). The relationship between school science and mathematics education. PhD Thesis, King’s College London, London.
  • Wong, V., Dillon, J., & King, H. (2016). STEM in England: Meanings and motivations in the policy arena. International Journal of Science Education, 38(15), 2346–2366.
  • Zhang, D., Orrill, C., & Campbell, T. (2015). Using the mixture Rasch model to explore knowledge resources students invoke in mathematic and science assessments. School Science and Mathematics, 115, 356–365.

Reprints and Corporate Permissions

Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?

To request a reprint or corporate permissions for this article, please click on the relevant link below:

Academic Permissions

Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?

Obtain permissions instantly via Rightslink by clicking on the button below:

If you are unable to obtain permissions via Rightslink, please complete and submit this Permissions form. For more information, please visit our Permissions help page.