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Technology I, II, and III: criteria for understanding and improving the practice of instructional technology

  • Jason K. McDonald
  • Andrew S. Gibbons
DEVELOPMENT ARTICLE

Abstract

In this paper we describe the criteria of Technology I, II, and III, which some instructional theorists have proposed to describe the differences between a formulaic and a reflective approach to solving educational problems. In a recent study, we applied these criteria to find evidence of a technological gravity that pulls practitioners away from reflective practices into a more reductive approach. We compared published reports of an innovative instructional theory, problem-based learning, to the goals of the theory as it was originally defined. We found three reasons for technological gravity, as well as three approaches some practitioners have used to avoid this gravity. We recommend that instructional technologists adopt our three approaches, as well as the criteria of Technology III, so they may better develop instruction of a quality consistent with the innovative instructional principles they claim, and that best characterizes the goals they have for their practice.

Keywords

Critical thinking Innovation diffusion Instructional quality Reflective practice 

References

  1. Abdulrazzaq, Y. M., & Qayed, K. I. (1991). A study of the attitudes of the foundation staff of a new medical faculty to problem-based learning. Medical Teacher, 13(4), 281–288.CrossRefGoogle Scholar
  2. Abrandt Dahlgren, M., & Dahlgren, L. O. (2002). Portraits of PBL: Students’ experiences of the characteristics of problem-based learning in physiotherapy, computer engineering and psychology. Instructional Science, 30, 111–127.CrossRefGoogle Scholar
  3. Barrows, H. S. (1983). Problem-based, self-directed learning. Journal of the American Medical Association, 250(2), 3077–3080.CrossRefGoogle Scholar
  4. Barrows, H. S. (1985). How to design a problem-based curriculum for the preclinical years. New York: Springer Publishing Company.Google Scholar
  5. Barrows, H. S. (1986). A taxonomy of problem-based learning methods. Medical Education, 20, 481–486.CrossRefGoogle Scholar
  6. Barrows, H. S. (1994). Practice-based learning: Problem-based learning applied to medical education. Springfield, IL: Southern Illinois University School of Medicine.Google Scholar
  7. Barrows, H. S. (1996). Problem-based learning in medicine and beyond: A brief overview. In L. Wilkerson & W. H. Gijselaers (Eds.), Bringing problem-based learning to higher education: Theory and practice (Vol. 68, pp. 3–12). San Francisco: Jossey-Bass Publishers.Google Scholar
  8. Barrows, H. S., & Mitchell, D. L. M. (1975). An innovative course in undergraduate neuroscience: Experiment in problem-based learning with ‘problem boxes’. British Journal of Medical Education, 9, 223–230.Google Scholar
  9. Barrows, H. S., & Tamblyn, R. M. (1980). Problem-based learning: An approach to medical education. New York: Springer Pub. Co.Google Scholar
  10. Beckwith, D. (1988). The future of educational technology. Canadian Journal of Educational Communication, 17(1), 3–20.Google Scholar
  11. Bridges, E. M., & Hallinger, P. (1996). Problem-based learning in leadership education. In L. Wilkerson & W. H. Gijselaers (Eds.), Bringing problem-based learning to higher education: Theory and practice (Vol. 68, pp. 53–61). San Francisco: Jossey-Bass Publishers.Google Scholar
  12. Chen, S. E., Cowdroy, R. M., Kingsland, A., & Ostwald, M. (1994). Reflections on problem based learning. In S. E. Chen, R. M. Cowdroy, A. Kingsland, & M. Ostwald (Eds.), Reflections on problem based learning (pp. 7–13). Sydney, Australia: Australian Problem Based Learning Network.Google Scholar
  13. Clark, D. C. (2001). Lost in the mêlée. In P. Schwartz, M. Stewart, & G. Webb (Eds.), Problem-based learning: Case studies, experience and practice (pp. 34–39). Sterling, VA: Stylus Publishing Inc.Google Scholar
  14. Danziger, K. (1985). The methodological imperative in psychology. Philosophy of the Social Sciences, 15, 1–13.CrossRefGoogle Scholar
  15. Davies, I. K. (1973). Competency based learning: Technology, management, and design. New York: McGraw-Hill.Google Scholar
  16. Davies, I. K. (1978). Educational technology: Archetypes, paradigms, and models. In J. Hartley & I. K. Davies (Eds.), Contributions to an educational technology (Vol. 2, pp. 9–24). New York: Crane, Russak & Company, Inc.Google Scholar
  17. Davies, I. K. (1989). Total educational technology (TET): Challenging current limits. Canadian Journal of Educational Communication, 18(2), 132–136.Google Scholar
  18. Davies, I. K. (1997). Paradigms and conceptual ISD systems. In C. R. Dills, & A. J. Romiszowski (Eds.), Instructional development paradigms (pp. 31–44). Englewood Cliffs, NJ: Educational Technology Publications.Google Scholar
  19. du Boulay, B. (2000). Can we learn from ITSs? In G. Gauthier, C. Frasson, & K. VanLehn (Eds.), Intelligent tutoring systems: 5th international conference, ITS 2000, Montrâeal, Canada, June 19–23, 2000: Proceedings (pp. 9–17). New York: Springer.Google Scholar
  20. Galanter, E. (1959). The ideal teacher. In E. Galanter (Ed.), Automatic teaching: The state of the art (pp. 1–11). New York: Wiley.Google Scholar
  21. Gibbons, A. S. (2001). Model-centered instruction. Journal of Structural Learning and Intelligent Systems, 14, 511–540.Google Scholar
  22. Gibbons, A. S. (2003). What and how do designers design? A theory of design structure. TechTrends, 47(5), 22–27.CrossRefGoogle Scholar
  23. Gilbert, T. F. (1960). On the relevance of laboratory investigation of learning to self-instructional programming. In A. A. Lumsdaine & R. Glaser (Eds.), Teaching machines and programmed learning: A source book (pp. 475–485). Washington, DC: National Education Association of the United States.Google Scholar
  24. Glaser, R. (1977). Adaptive education: Individual diversity and learning. New York: Holt, Rinehart and Winston.Google Scholar
  25. Glew, R. H. (2003). The problem with problem-based medical education: Promises not kept. Biochemistry and Molecular Biology Education, 31(1), 52–56.CrossRefGoogle Scholar
  26. Gordon, J., & Zemke, R. (2000). The attack on ISD. Training, 37(4), 42–53.Google Scholar
  27. Häkkinen, P. (2002). Challenges for design of computer-based learning environments. British Journal of Educational Technology, 33(4), 461–469.CrossRefGoogle Scholar
  28. Heestand, D. E., Templeton, B. B., & Adams, B. D. (1989). Responding to perceived needs of the twenty-first century: A case study in curriculum design. Medical Teacher, 11(2), 157–167.CrossRefGoogle Scholar
  29. Herreid, C. F. (2003). The death of problem-based learning? Journal of College Science Teaching, 32(3), 364–366.Google Scholar
  30. Hlynka, D., & Nelson, B. (1985). Educational technology as metaphor. Programmed Learning and Educational Technology, 22(1), 7–15.Google Scholar
  31. Inouye, D. K., Merrill, P. F., & Swan, R. H. (2005). Help: Toward a new ethics-centered paradigm for instructional design and technology [Electronic Version]. IDT Record. Retrieved August 26, 2006 from http://www.indiana.edu/∼idt/articles/documents/Inouye_print_version.pdf.
  32. Januszewski, A. (2001). Educational technology: The development of a concept. Englewood, CO: Libraries Unlimited, Inc.Google Scholar
  33. Jonassen, D. H. (1994). Technology as cognitive tools: Learners as designers. Retrieved August 26, 2006, from http://itech1.coe.uga.edu/itforum/paper1/paper1.html.Google Scholar
  34. Kaufman, A., Mennin, S., Waterman, R., Duban, S., Hansbarger, C., Silverblatt, H., et al. (1989). The New Mexico experiment: Educational innovation and institutional change. Academic Medicine, 64, 285–294.CrossRefGoogle Scholar
  35. Kirschner, S. R. (2005). Toward critical openness. In B. D. Slife, J. S. Reber, & F. C. Richardson (Eds.), Critical thinking about psychology: Hidden assumptions and plausible alternatives (pp. 267–277). Washington, DC: American Psychological Association.Google Scholar
  36. Kovalik, C. L. (1999). Technology integration and problem-based learning: Implications for teaching and learning. Unpublished Thesis (Ph. D.), Kent State University, School of Education.Google Scholar
  37. Lumsdaine, A. A. (1964). Educational technology, programed learning, and instructional science. In E. R. Hilgard (Ed.), Theories of learning and instruction: The sixty-third yearbook of the National Society for the Study of Education (pp. 371–401). Chicago: The National Society for the Study of Education.Google Scholar
  38. Maudsley, G. (1999). Do we all mean the same thing by “Problem-based learning”? A review of the concepts and a formulation of the ground rules. Academic Medicine, 74(2), 178–185.CrossRefGoogle Scholar
  39. McDonald, J. K. (2006). Technology I, II, and III: Criteria for understanding and improving the practice of instructional technology. Unpublished Thesis (Ph. D.), Brigham Young University, Department of Instructional Psychology and Technology.Google Scholar
  40. Mitchell, P. D. (1989). The future of educational technology is past. Canadian Journal of Educational Communication, 18(1), 3–27.Google Scholar
  41. Osguthorpe, R. T., & Osguthorpe, R. D. (2002). Re-examining the foundations of instructional design: Toward a conscience of craft. Paper presented at the annual meeting of the Association for Educational Communications and Technology, Dallas, TX.Google Scholar
  42. Reeves, T. C., Herrington, J., & Oliver, R. (2004). A development research agenda for online collaborative learning. Educational Technology Research and Development, 52(4), 53–65.CrossRefGoogle Scholar
  43. Reigeluth, C. M. (2001). What every AECT member needs to know about systemic change: The beginning of a dialogue. TechTrends, 46(1), 12–15.Google Scholar
  44. Rogers, E. M. (2003). Diffusion of innovations (5th ed.). New York: Free Press.Google Scholar
  45. Salomon, G. (2002). Technology and pedagogy: Why don’t we see the promised revolution? Educational Technology, 42(2), 71–75.Google Scholar
  46. Savin-Baden, M. (2000). Problem-based learning in higher education: Untold stories. Philadelphia: Open University Press.Google Scholar
  47. Schor, N. F. (2001). No money where your mouth is. In P. Schwartz, M. Stewart, & G. Webb (Eds.), Problem-based learning: Case studies, experience and practice (pp. 20–26). Sterling, VA: Stylus Publishing Inc.Google Scholar
  48. Slife, B. D. (1998). Raising the consciousness of researchers: Hidden assumptions in the behavioral sciences. Adapted Physical Activity Quarterly, 15(3), 208–221.Google Scholar
  49. Slife, B. D., & Williams, R. N. (1995). What’s behind the research: Discovering hidden assumptions in the behavioral sciences. Thousand Oaks, CA: SAGE Publications, Inc.Google Scholar
  50. Suppes, P. (1969). Personalizing education through computers. In R. C. Atkinson & H. A. Wilson (Eds.), Computer-assisted instruction: A book of readings (pp. 41–47). New York: Academic Press, (Reprinted from Phi Delta Kappan, 49(8), 420–423, 1968).Google Scholar
  51. Williams, R. N. (2005). The language and methods of science: Common assumptions and uncommon conclusions. In B. D. Slife, J. S. Reber, & F. C. Richardson (Eds.), Critical thinking about psychology: Hidden assumptions and plausible alternatives (pp. 235–249). Washington, DC: American Psychological Association.Google Scholar
  52. Wilson, B. G. (1997). The postmodern paradigm. In C. R. Dills & A. J. Romiszowski (Eds.), Instructional development paradigms (pp. 297–309). Englewood Cliffs, NJ: Educational Technology Publications.Google Scholar
  53. Wilson, B. G. (2005). Broadening our foundation for instructional design: Four pillars of practice. Educational Technology, 45(2), 10–15.Google Scholar

Copyright information

© Association for Educational Communications and Technology 2007

Authors and Affiliations

  1. 1.Salt Lake CityUSA
  2. 2.ProvoUSA

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