Emerging Methodological Challenges for Educational Research

  • Peter GoodyearEmail author
Part of the Methodos Series book series (METH, volume 9)


This concluding chapter surveys some of the conceptual and practical challenges encountered by producers and users of educational research. It synthesises some of the implications of earlier chapters in the book, but also draws on ideas about the changing relationships between evidence, theory and action in educational prac-tice. The chapter explores the argument that exponential growth in the availability of raw information about educational activities and outcomes raises questions about the value that (professional) educational researchers can offer to the primary actors in teaching and learning. The shift from data scarcity to information over-load and competition for attention puts a premium on methods for linking com-plex, heterogeneous evidence to action. Seen in this light, a major challenge and opportunity for educational researchers is to help develop and disseminate meth-ods for moving between different sources of knowledge and ways of knowing.


Educational Research Pedagogical Content Knowledge Design Pattern Boundary Object Pedagogical Content 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


  1. Aubusson, P., Ewing, R. & Hoban, G. (2009). Action learning in schools: Reframing teachers’ professional learning and development. London: Routledge.Google Scholar
  2. Barab, S. & Plucker, J. (2002). Smart people or smart contexts? Cognition, ability and talent development in an age of situated approaches to knowing and learning. Educational Psychologist, 37, 165–182.CrossRefGoogle Scholar
  3. Bereiter, C. (2002). Education and mind in the knowledge age. Mahwah NJ: Lawrence Erlbaum Associates.Google Scholar
  4. Biesta, G. (2007). Bridging the gap between educational research and educational practice: The need for critical distance. Educational Research and Evaluation, 13, 295–301.CrossRefGoogle Scholar
  5. Briggs, L. (1977). Instructional design. Englewood Cliffs, NJ, Educational Technology Publications.Google Scholar
  6. Broekkamp, H. & Van Hout-Wolters, B. (2007). The gap between educational research and practice: A literature review, symposium and questionnaire. Educational Research and Evaluation, 13, 203–220.CrossRefGoogle Scholar
  7. Brown, A. (1992). Design experiments: Theoretical and methodological challenges in creating complex interventions in classroom settings. Journal of the Learning Sciences, 2, 141–178.CrossRefGoogle Scholar
  8. Brown, J. S. & Duguid, P. (1996). Toward a unified view of working, learning and innovation. In M. Cohen & L. Sproul, (Eds.), Organisational learning. New York: Sage. 58–82.Google Scholar
  9. Bull, S., Brna, P., Critchley, S., Davie, K. & Holzherr, C. (1999). The missing peer, artificial peers and the enhancement of human-human collaborative student modelling. In S.P. Lajoie & M. Vivet (Eds.), Proceedings of International Conference on Artificial Intelligence in Education. IOS Press, Amsterdam, 269–276.Google Scholar
  10. Burkhardt, H. & Schoenfeld, A. (2003). Improving educational research: Toward a more useful, more influential and better-funded enterprise. Educational Researcher, 32, 3–14.CrossRefGoogle Scholar
  11. Button, G. (2008) Against 'distributed cognition'. Theory, Culture & Society, 25, 87–104.CrossRefGoogle Scholar
  12. Chan, T.-W, & Baskin, A. B. (1988). Studying with the Prince: The computer as a learning companion, Proceedings of International Conference on Intelligent Tutoring Systems, Montreal, 194–200.Google Scholar
  13. Clark, R. & Mayer, R. (2008). E-learning and the science of instruction: Proven guidelines for consumers and designers of multimedia learning. San Francisco CA: Pfeiffer.Google Scholar
  14. Collins, A. (1990). Toward a design science of education. (Tech. Rep. No. 1). New York, Center for Technology in Education, Bank Street College.Google Scholar
  15. Confrey, J. (2006). The evolution of design studies as methodology. In K. Sawyer (Ed.), The Cambridge handbook of the learning sciences. Cambridge: Cambridge University Press.Google Scholar
  16. Corlett, D., Sharples, M., Bull, S. & Chan, T. (2005). Evaluation of a mobile learning organiser for university students. Journal of Computer Assisted Learning, 21, 162–170.CrossRefGoogle Scholar
  17. Crumlish, C. & Malone, E. (2009). Designing social interfaces: Principles, patterns, and practices for improving the user experience. Sebastopol, CA: O’Reilly.Google Scholar
  18. Cuban, L. (2001). Oversold and underused: Computers in the classroom. Cambridge, MA: Harvard University Press.Google Scholar
  19. Davidson, C. & Goldberg, D. (2010). The future of thinking: Learning institutions in a digital age. Cambridge, MA: MIT Press.Google Scholar
  20. deBotton, A. (2006). The architecture of happiness. London: Hamish Hamilton.Google Scholar
  21. Dillenbourg, P. & Goodyear, P. (1989). Towards reflective tutoring systems: Self-representation and self-improvement. In D. Bierman, J. Breuker, & J. Sandberg (Eds.), Artificial intelligence and education: Synthesis and reflection. Springfield, VA: IOS, 92–99.Google Scholar
  22. Dillenbourg, P. & Self, J. (1992). A computational approach to socially distributed cognition. European Journal of Psychology of Education, 7, 353–372.CrossRefGoogle Scholar
  23. diSessa, A. (1991). Local sciences: Viewing the design of human-computer systems as cognitive science. In J. M. Carroll (Ed.), Designing interaction: Psychology at the human-computer interface. Cambridge: Cambridge University Press.Google Scholar
  24. Drachsler, H., Hummel, H. & Koper, R. (2008). Personal recommender systems for learners in lifelong learning networks: The requirements, techniques and model. International Journal of Learning Technology, 3, 404–423.CrossRefGoogle Scholar
  25. Edwards, R., Biesta, G. & Thorpe, M. (Eds.). (2009). Rethinking contexts for learning and teaching: Communities, activites and networks. Abingdon: Routledge.Google Scholar
  26. Ellis, R. & Goodyear, P. (2010). Students' experiences of e-learning in higher education: The ecology of sustainable innovation. New York: Routledge Falmer.Google Scholar
  27. Ellsworth, E. (2005). Places of learning: Media, architecture, pedagogy. New York: Routledge.Google Scholar
  28. Emad, G. & Roth, W.-M. (2009). Policy as boundary object: A new way to look at educational policy design and implementation. Vocations and Learning, 2, 19–35.CrossRefGoogle Scholar
  29. Engestrom, Y. (2007). Enriching the theory of expansive learning: Lessons from journeys toward coconfiguration. Mind, Culture, and Activity, 14, 23–39.Google Scholar
  30. Figgis, J., Zubrick, A., Butorac, A. & Alderson, A. (2000). Backtracking policies and practice to research. The impact of educational research. Canberra, ACT: Higher Education Division, Dept of Education, Training and Youth Affairs.Google Scholar
  31. Goodyear, P. (1999). Educational technology, virtual learning environments and architectural practice. In D. Ely, L. Odenthal, & T. Plomp (Eds.), Educational science and technology: Perspectives for the future. Enschede: Twente University Press.Google Scholar
  32. Goodyear, P., de Laat, M. & Lally, V. (2006). Using pattern languages to mediate theory-praxis conversations in design for networked learning. Journal of the Association for Learning Technology, 14, 211–223.Google Scholar
  33. Goodyear, P. & Markauskaite, L. (2009). Teachers’ design knowledge, epistemic fluency and reflections on students’ experiences. In H. Wozniak & S. Bartoluzzi (Eds.), Proceedings, 32nd annual HERDSA conference. Darwin.Google Scholar
  34. Goodyear, P. & Retalis, S. (Eds.). (2010). Technology-enhanced learning: Design patterns and pattern languages. Rotterdam: Sense Publishers.Google Scholar
  35. Goodyear, P. & Zenios, M. (2007). Discussion, collaborative knowledge work and epistemic fluency. British Journal of Educational Studies, 55, 351–368.CrossRefGoogle Scholar
  36. Gore, J. M., & Gitlin, A. D. (2004). [Re]Visioning the academic-teacher divide: Power and knowledge in the educational community. Teachers and Teaching: Theory and Practice, 10, 35–58.CrossRefGoogle Scholar
  37. Hall, R. (2002). Collaboration and learning as contingent responses to designed environments. In T. Koschmann, R. Hall, & N. Miyake (Eds.), CSCL2: Carrying forward the conversation. (pp.185–196.) Mahwah, NJ: Lawrence Erlbaum Associates.Google Scholar
  38. Hargreaves, D. (1996). Teaching as a research-based profession: Possibilities and prospects. Teacher training agency annual lecture. London.Google Scholar
  39. Hoadley, C. (2010). Roles, design, and the nature of CSCL. Computers in Human Behavior, 26, 551–555.CrossRefGoogle Scholar
  40. Hutchins, E. (1995). Cognition in the wild. Cambridge, MA: MIT Press.Google Scholar
  41. Kay, J. (2006). Scrutable adaptation: Because we can and must. Adaptive hypermedia and adaptive web-based systems: Proceedings of the 4th International Conference, AH 2006. Dublin: Springer.Google Scholar
  42. Kirschner, P., Strijbos, J.-W., Kreijns, K. & Beers, P. (2004). Designing electronic collaborative learning environments. Educational Technology Research & Development, 52, 47–66.CrossRefGoogle Scholar
  43. Kumar, V., Gress, C., Hadwin, A. & Winne, P. (2010). Assessing process in CSCL: An ontological approach. Computer in Human Behavior, 26, 825–834.CrossRefGoogle Scholar
  44. Latour, B. (2005). Reassembling the social: An introduction to actor-network-theory. Oxford: Oxford University Press.Google Scholar
  45. Latour, B. (1995). Mixing humans and nonhumans together: The sociology of a door-closer. In S. L. Star (Ed.), Ecologies of knowledge. New York: State University of New York Press.Google Scholar
  46. Luckin, R. (2010). Re-designing learning contexts: Technology-rich, learner-centred ecologies. New York: Routledge.Google Scholar
  47. Markauskaite, L. & Reimann, P. (2008). Enhancing and scaling-up design-based research: The potential of e-research. International conference of the learning sciences. Utrecht.Google Scholar
  48. Mol, A. (2002). Cutting surgeons, walking patients: Some complexities involved in comparing. In J. Law & A. Mol (Eds.), Complexities: Social studies of knowledge practices. Durham, NC: Duke University Press.Google Scholar
  49. Morrison, D. & Collins, A. (1996). Epistemic fluency and constructivist learning environments. In B. Wilson (Ed.), Constructivist learning environments. Englewood Cliffs, NJ: Educational Technology Publications.Google Scholar
  50. Munro, A., Hook, K. & Benyon, D. (Eds.). (1999). Social navigation in information space. London: Springer.Google Scholar
  51. Nelson, S. R., Leffler, J. C. & Hansen, B. A. (2009). Toward a research agenda for understanding and improving the use of research evidence. Portland, OR: Northwest Regional Educational Laboratory.Google Scholar
  52. Nonaka, I. & Takeuchi, H. (1995). The knowledge-creating company. Oxford: Oxford University Press.Google Scholar
  53. Paas, F., Renkl, A. & Sweller, J. (2004). Cognitive load theory: instructional implications of the interaction between information structures and cognitive architecture. Instructional Science, 32, 1–8.CrossRefGoogle Scholar
  54. Pedler, M., Boydell, T., & Burgoyne, J. (1989). The learning company. Studies in Continuing Education, 11, 91–101.CrossRefGoogle Scholar
  55. Peterson, D. & Levene, M. (2003). Trail records and navigational learning. London Review of Education 1(3). 207–216.CrossRefGoogle Scholar
  56. Reigeluth, C. & Carr-Chellman, A. (Eds.). (2009). Instructional design theories and models. Volume 3. New York: Routledge.Google Scholar
  57. Reimann, P. (2009). Time is precious: Variable- and event-centred approaches to process analysis in CSCL research. International Journal of Computer-supported Collaborative Learning, 4, 239–257.CrossRefGoogle Scholar
  58. Ruthven, K., Laborde, C., Leach, J. & Tiberghien, A. (2009). Design tools in didactical research: Instrumenting the epistemological and cognitive aspects of the design of teaching sequences. Educational Researcher, 38, 329–342.CrossRefGoogle Scholar
  59. Salomon, G. (Ed.). (1993). Distributed cognitions: Psychological and educational considerations. Cambridge: Cambridge University Press.Google Scholar
  60. Saunders, M. (2006). The 'presence' of evaluation theory and practice in educational and social development: Toward an inclusive approach. London Review of Education, 4, 197–215.CrossRefGoogle Scholar
  61. Scardamalia, M. & Bereiter, C. (2006). Knowledge building: Theory, pedagogy and technology. In K. Sawyer (Ed.), Cambridge handbook of the learning sciences. Cambridge: Cambridge University Press.Google Scholar
  62. Self, J. (1974). Student models in computer-aided instruction. International Journal of Man-Machine Studies, 6, 261–276.CrossRefGoogle Scholar
  63. Sharples, M. (2000). The design of personal mobile technologies for lifelong learning. Computers & Education, 34, 177–193.CrossRefGoogle Scholar
  64. Shavelson, R. & Towne, L. (2002). Committee on scientific principles for educational research. Washington, DC: National Academy Press.Google Scholar
  65. Shulman, L. (1986). Those who understand: Knowledge growth in teaching. Educational Researcher, 14, 4–14.Google Scholar
  66. Spikol, D., Mildrad, M., Maldonado, H. & Pea, R. (2009). Integrating co-design practices into the development of mobile science collaboratories. 9th IEEE International Conference on Advanced Learning Technologies (ICALT). Riga, Latvia.Google Scholar
  67. Star, S. & Griesemer, J. (1989). Institutional ecology, 'translations' and boundary objects: Amateurs and professionals in Berkeley's Museum of Vertebrate Zoology, 1907–1939. Social Studies of Science, 19, 387–420.CrossRefGoogle Scholar
  68. Thrift, N. (2005). From born to made: Technology, biology and space. Transactions of the Institute of British Geographers, 30, 463–476.CrossRefGoogle Scholar
  69. Tooley, J. (1998). Educational research: A critique. A survey of published educational research. London, OFSTED.Google Scholar
  70. Vanderlinde, R. & van Braak, J. (2010). The gap between educational research and practice: Views of teachers, school leaders, intermediaries and researchers. British Educational Research Journal, 36, 299–316.CrossRefGoogle Scholar
  71. Voigt, C. (2010). A pattern in the making: The contextual analysis of electronic case-based learning. In Goodyear, P. & Retalis, S. (Eds.), Technology-enhanced learning: Design patterns and pattern languages. Rotterdam: Sense Publishers.Google Scholar
  72. Wang, F., & Hannafin, M. (2005). Design-based research and technology enhanced learning environments. Educational Technology Research and Development, 53, 5–23.CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media B.V. 2011

Authors and Affiliations

  1. 1.Faculty of Education and Social WorkThe University of SydneySydneyAustralia

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