Advertisement

Accessing Expert Understanding: The Value of Visualising Knowledge Structures in Professional Education

  • Ian M. KinchinEmail author
Chapter

Abstract

Effective, expert practice requires the activation of complementary knowledge structures. The visible, linear chains of practice that characterise a professional’s activity are underpinned by elaborate networks of understanding that are less visible to the casual observer or to the student in the discipline. The application of concept mapping makes these knowledge structures explicit and also provides a mechanism to visualise the trajectories of learning that are required to achieve expertise and enable the interaction of theory and practice to develop powerful knowledge. The knowledge structures that are made visible can be contextualised using established theoretical frameworks to support the professional development of teachers, and also to evaluate the progression of students through the curriculum. Theoretical aspects of professional learning (such as adaptive expertise, pedagogic frailty, threshold concepts and semantic gravity) become more tangible and applicable when practical examples are visualised using concept maps so that educational theory can be embedded in the articulation of practice. These ideas have profound implications for the evaluation of teaching and for curriculum design in professional education settings.

Keywords

Powerful knowledge Adaptive expertise Concept mapping 

References

  1. Bailey, G. (2014). Accountability and the rise of ‘play safe’ pedagogical practices. Education + Training, 56(7), 663–674.CrossRefGoogle Scholar
  2. Bernstein, B. (1999). Vertical and horizontal discourse: An essay. British Journal of Sociology of Education, 20(2), 157–173.CrossRefGoogle Scholar
  3. Bernstein, B. (2000). Pedagogy, symbolic control and identity. Oxford: Rowman & Littlefield.Google Scholar
  4. Blackie, M. A. L. (2014). Creating semantic waves: Using legitimation code theory as a tool to aid the teaching of chemistry. Chemistry Education Research and Practice, 15(4), 462–469.CrossRefGoogle Scholar
  5. Blackie, M. (2017). Semantic waves and pedagogic frailty. In I. M. Kinchin & N. E. Winstone (Eds.), Pedagogic frailty and resilience in the university (pp. 49–61). Rotterdam: Sense Publishers.CrossRefGoogle Scholar
  6. Bohle Carbonell, K., Stalmeijer, R. E., Könings, K. D., Segers, M., & van Merriȅnboer, J. J. G. (2014). How experts deal with novel situations: A review of adaptive expertise. Educational Research Review, 12, 14–29.CrossRefGoogle Scholar
  7. Bradley, J. H., Paul, R., & Seeman, E. (2006). Analyzing the structure of expert knowledge. Information Management, 43, 77–91.CrossRefGoogle Scholar
  8. Cañas, A. J., Novak, J. D., & Reiska, P. (2015). How good is my concept map? Am I a good Cmapper? Knowledge Management & E-Learning, An International Journal, 7(1), 6–19.Google Scholar
  9. Clarke, F. (2011). Injecting expertise: Developing an expertise-based pedagogy for teaching local anaesthesia in dentistry. Higher Education Network Journal, 2, 29–43.Google Scholar
  10. Elvira, Q., Imants, J., Dankbaar, B., & Segers, M. (2017). Designing education for professional expertise development. Scandinavian Journal of Educational Research, 61(12), 187–204.  https://doi.org/10.1080/00313831.2015.1119729CrossRefGoogle Scholar
  11. Fontaine, S. I. (2002). Teaching with the beginner’s mind: Notes from my karate journal. College Composition and Communication, 54(2), 208–221.CrossRefGoogle Scholar
  12. Gibbs, G. (2013). Reflections on the changing nature of educational development. International Journal for Academic Development, 18(1), 4–14.CrossRefGoogle Scholar
  13. Gosling, D. (2009). Educational development in the UK: A complex and contradictory reality. International Journal for Academic Development, 14(1), 5–18.CrossRefGoogle Scholar
  14. Green, D. A. (2009). New academics’ perceptions of the language of teaching and learning: Identifying and overcoming linguistic barriers. International Journal for Academic Development, 14(1), 33–45.CrossRefGoogle Scholar
  15. Hay, D. B., Williams, D., Stahl, D., & Wingate, R. (2013). Using drawings of the brain cell to exhibit expertise in neuroscience: Exploring the boundaries of experimental culture. Science Education, 97(3), 468–491.CrossRefGoogle Scholar
  16. Hoffman, R. R., & Lintern, G. (2006). Eliciting and representing the knowledge of experts. In K. A. Ericsson, N. Charness, P. J. Feltovich, & R. R. Hoffman (Eds.), The Cambridge handbook of expertise and expert performance (pp. 203–222). Cambridge, UK: Cambridge University Press.CrossRefGoogle Scholar
  17. Kinchin, I. M. (1994). The biology of Tardigrades. London: Portland Press.Google Scholar
  18. Kinchin, I. M. (2014). Concept mapping as a learning tool in higher education: A critical analysis of recent reviews. The Journal of Continuing Higher Education, 62(1), 39–49.CrossRefGoogle Scholar
  19. Kinchin, I. M. (2016). Visualising powerful knowledge: A knowledge structures perspective on teaching and learning at university. Rotterdam: Sense Publishers.CrossRefGoogle Scholar
  20. Kinchin, I. M., Alpay, E., Curtis, K., Franklin, J., Rivers, C., & Winstone, N. E. (2016). Charting the elements of pedagogic frailty. Educational Research, 58(1), 1–23.CrossRefGoogle Scholar
  21. Kinchin, I. M., Baysan, A., & Cabot, L. B. (2008). Towards a pedagogy for clinical education: Beyond individual learning differences. Journal of Further and Higher Education, 32(4), 373–387.CrossRefGoogle Scholar
  22. Kinchin, I. M., & Cabot, L. B. (2010). Reconsidering the dimensions of expertise: From linear stages towards dual processing. London Review of Education, 8(2), 153–166.CrossRefGoogle Scholar
  23. Kinchin, I. M., Cabot, L. B., & Hay, D. B. (2008a). Visualising expertise: Towards an authentic pedagogy for higher education. Teaching in Higher Education, 13(3), 315–326.CrossRefGoogle Scholar
  24. Kinchin, I. M., Cabot, L. B., & Hay, D. B. (2008b). Using concept mapping to locate the tacit dimension of clinical expertise: Towards a theoretical framework to support critical reflection on teaching. Learning in Health and Social Care, 7(2), 93–104.CrossRefGoogle Scholar
  25. Kinchin, I. M., Lygo-Baker, S., & Hay, D. B. (2008). Universities as centres of non-learning. Studies in Higher Education, 33(1), 89–103.CrossRefGoogle Scholar
  26. Kinchin, I. M., & Miller, N. L. (2012). ‘Structural transformation’ as a threshold concept in university teaching. Innovations in Education and Teaching International, 49(2), 207–222.CrossRefGoogle Scholar
  27. Kinchin, I. M., & Winstone, N. E. (2017). Pedagogic frailty and resilience in the university. Rotterdam: Sense Publishers.CrossRefGoogle Scholar
  28. Macnaught, L., Maton, K., Martin, J. R., & Matruglio, E. (2013). Jointly constructing semantic waves: Implications for teacher training. Linguistics and Education, 24, 50–63.CrossRefGoogle Scholar
  29. Maton, K. (2009). Cumulative and segmented learning: Exploring the role of curriculum structures in knowledge building. British Journal of Sociology of Education, 31(1), 43–57.CrossRefGoogle Scholar
  30. Maton, K. (2014). Knowledge and knowers: Towards a realist sociology of education. London: Routledge.Google Scholar
  31. McLeod, P. J., Meagher, T., Steinert, Y., Schuwirth, L., & McLeod, A. H. (2004). Clinical teachers’ tacit knowledge of basic pedagogic principles. Medical Teacher, 26, 23–27.CrossRefGoogle Scholar
  32. Novak, J. D. (2010). Learning, creating, and using knowledge: Concept maps as facilitative tools in schools and corporations (2nd ed.). Oxford: Routledge.CrossRefGoogle Scholar
  33. Novak, J. D., & Cañas, A. J. (2006). The origins of concept maps and the continuing evolution of the tool. Information Visualization Journal, 5(3), 175–184.CrossRefGoogle Scholar
  34. Novak, J. D., & Cañas, A. J. (2007). Theoretical origins of concept maps, how to construct them, and uses in education. Reflecting Education, 3(1), 29–42.Google Scholar
  35. Novak, J. D., & Symington, D. J. (1982). Concept mapping for curriculum development. Victoria Institute for Educational Research Bulletin, 48, 3–11.Google Scholar
  36. Patel, V. L., Arocha, J. F., & Kaufman, D. R. (1999). Expertise and tacit knowledge in medicine. In R. J. Sternberg & J. A. Horvath (Eds.), Tacit knowledge in professional practice: Researcher and practitioner perspectives (pp. 75–99). Mahwah, NJ: Lawrence Erlbaum.Google Scholar
  37. Salmon, D., & Kelly, M. (2015). Using concept mapping to foster adaptive expertise: Enhancing teacher metacognitive learning to improve student academic performance. New York: Peter Lang.CrossRefGoogle Scholar
  38. Schneider, M., & Stern, E. (2010). The developmental relations between conceptual and procedural knowledge: A multimethod approach. Developmental Psychology, 46(1), 178–192.CrossRefGoogle Scholar
  39. Schon, D. (1971). Beyond the stable state. New York: W.W. Norton & Co.Google Scholar
  40. Shay, S., & Steyn, D. (2016). Enabling knowledge progression in vocational curricula: Design as a case study. In K. Maton, S. Hood, & S. Shay (Eds.), Knowledge-building: Educational studies in legitimation code theory. London: Routledge.Google Scholar
  41. Steinert, Y., Mann, K., Centeno, A., Dolmans, D., Spencer, J., Gelula, M., & Prideaux, D. (2006). A systematic review of faculty development initiatives designed to improve teaching effectiveness in medical education, BEME Guide No. 8. Medical Teacher, 28(6), 497–526.CrossRefGoogle Scholar
  42. Stronach, I., Corbin, B., McNamara, O., Stark, S., & Warne, T. (2002). Towards an uncertain politics of professionalism: Teacher and nurse identities in flux. Journal of Education Policy, 17(1), 109–138.CrossRefGoogle Scholar
  43. Stuart, H. A. (1985). Should concept maps be scored numerically. The European Journal of Science Education, 7(1), 73–81.CrossRefGoogle Scholar
  44. Talbot, M. (2004). Monkey see, monkey do: A critique of the competency model in graduate medical education. Medical Education, 38, 587–592.CrossRefGoogle Scholar
  45. Taylor, K. (2000). Teaching with developmental intention. In J. Mezirow & Associates (Eds.), Learning as transformation: Critical perspectives on a theory in progress (pp. 151–180). San Francisco, CA: Jossey-Bass.Google Scholar
  46. Wheelahan, L. (2007). How competency-based training locks the working class out of powerful knowledge: A modified Bernsteinian analysis. British Journal of Sociology of Education, 28(5), 637–651.CrossRefGoogle Scholar
  47. Wilson, J., Mandich, A., & Magalhães, L. (2015). Concept mapping: A dynamic, individualized and qualitative method for eliciting meaning. Qualitative Health Research, 26(8), 1151–1161.CrossRefGoogle Scholar
  48. Wingate, R., & Kwint, M. (2006). Imagining the brain cell: The neuron in visual culture. Nature Reviews Neuroscience, 7, 745–752.CrossRefGoogle Scholar
  49. Young, M., & Muller, J. (2013). On the powers of powerful knowledge. Review of Education, 1(3), 229–250.CrossRefGoogle Scholar

Copyright information

© The Author(s) 2019

Authors and Affiliations

  1. 1.University of SurreyGuildfordUK

Personalised recommendations