Educational Technology Research and Development

, Volume 40, Issue 3, pp 63–79 | Cite as

A critical review of elaboration theory

  • Brent Wilson
  • Peggy Cole


In this article the authors examine elaboration theory (ET), a model for sequencing and organizing courses which was developed by Charles Reigeluth and associates in the late 1970s. The purpose of the article is to offer a critique of ET based on recent cognitive research and to offer suggestions for updating the model to reflect new knowledge.

Commentary by Charles Reigeluth follows this article.


Critical Review Educational Technology Cognitive Research Elaboration Theory 
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.


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  1. Alexander, P. A., Schallert, D. L., & Hare, V. C. (1991). Coming to terms: How researchers in learning and literacy talk about knowledge.Review of Educational Research, 61(3), 315–343.Google Scholar
  2. Anderson, J. R. (1990).Cognitive Psychology and Its Implications (3rd ed.). New York: Freeman.Google Scholar
  3. Bereiter, C. (1991, April). Implications of connectionism for thinking about rules.Educational Researcher, 20(3), 10–16.Google Scholar
  4. Bransford, J. D., & Vye, N. J. (1989). A perspective on cognitive research and its implications for instruction. In L. B. Resnick & L. E. Klopfer (Eds.),Toward the thinking curriculum: Current cognitive research (pp. 173–205). Alexandria, VA: Association for Supervision and Curriculum Development.Google Scholar
  5. Brown, J. S., Collins, A., & Duguid, P. (1989, January–February). Situated cognition and the culture of learning.Educational Researcher, 32–42.Google Scholar
  6. Bruner, J. S. (1966).Toward a theory of instruction. Cambridge, MA: The Belnap Press of Harvard University Press.Google Scholar
  7. Bunderson, C. V., Gibbons, A. S., Olsen, J. B., & Kearsley, G. P. (1981). Work models: Beyond instructional objectives.Instructional Science, 10, 205–215.CrossRefGoogle Scholar
  8. Burton, R. R., & Brown, J. S. (1979). An investigation of computer coaching for informal learning activities.International Journal of Man-Machine Studies, 11, 5–24.Google Scholar
  9. Burton, R. R., Brown, J. S., & Fischer, G. (1984). Skiing as a model of instruction. In B. Rogoff & J. Lave (Eds.),Everyday cognition: Its development in social context (pp. 139–150). Cambridge, MA: Harvard University Press.Google Scholar
  10. Case, R. (1978). A developmentally based theory and technology of instruction.Review of Educational Research, 48, 439–463.Google Scholar
  11. Case, R., & Bereiter, C. (1984). From behaviourism to cognitive behaviourism to cognitive development: Steps in the evolution of instructional design.Instructional Science, 13, 141–158.CrossRefGoogle Scholar
  12. Clancey, W. J. (1992). Representations of knowing: In defense of cognitive apprenticeship.Journal of Artificial Intelligence in Education, 3(2), 139–168.Google Scholar
  13. Collins, A., Brown, J. S., & Newman, S. E. (1989). Cognitive apprenticeship: Teaching the crafts of reading, writing, and mathematics. In L. B. Resnick (Ed.),Knowing, learning, and instruction: Essays in honor of Robert Glaser (pp. 453–494). Hillsdale, NJ: Lawrence Erlbaum.Google Scholar
  14. Collins, A., & Stevens, A. L. (1983). A cognitive theory of inquiry teaching. In C. M. Reigeluth (Ed.),Instructional-design theories and models: An overview of their current status (pp. 247–278). Hillsdale, NJ: Lawrence Erlbaum.Google Scholar
  15. Cunningham, D. J. (1991, May). Assessing constructions and constructing assessments: A dialogue.Educational Technology, 13–17.Google Scholar
  16. Dreyfus, H. L., & Dreyfus, S. E. (1986).Mind over machine: The power of human intuition and expertise in the era of the computer. New York: The Free Press.Google Scholar
  17. Education and the structure of knowledge. (1964). Fifth annual Phi Delta Kappa Symposium. Chicago: Rand McNally.Google Scholar
  18. Ford, G. W., & Pugno, L. (Eds.). (1964).The structure of knowledge and the curriculum. Chicago: Rand McNally.Google Scholar
  19. Gagné, E. (1985).The cognitive psychology of school learning. Chicago: Scott Foresman.Google Scholar
  20. Gagné, E. D., Yekovich, C. W., & Yekovich, F. R. (in press).The cognitive psychology of school learning (2nd ed.). New York: Harper Collins.Google Scholar
  21. Gagné, R. M., Briggs, L. J., & Wager, W. W. (1988).Principles of instructional design (3rd ed.). New York: Holt, Rinehart and Winston.Google Scholar
  22. Gillian, C. (1982).In a different voice: Psychological theory and women's development. Cambridge, MA: Harvard University Press.Google Scholar
  23. Harel, I. (1991, April).When mathematical ideas, programming knowledge, instructional design, and playful learning are intertwined. The Instructional Software Design Project. Paper presented at the meeting of the American Educational Research Association, Chicago.Google Scholar
  24. Harel, I., & Papert, S. (1990). Software design as a learning environment.Interactive Learning Environments, 1(1), 1–32.Google Scholar
  25. Hidi, S. (1990). Interest and its contribution as a mental resource for learning.Review of Educational Research, 60(4), 549–571.Google Scholar
  26. Johnson-Laird, P. N. (1982).Mental models. Cambridge, MA: Harvard University Press.Google Scholar
  27. Jonassen, D. H. (Ed.). (1982).The technology of text: Principles for structuring, designing, and displaying text. Englewood Cliffs, NJ: Educational Technology Publications.Google Scholar
  28. Jonassen, D. H. (Ed.). (1985).The technology of text: Principles for structuring, designing, and displaying text (vol. 2). Englewood Cliffs, NJ: Educational Technology Publications.Google Scholar
  29. Jonassen, D. H. (1990, February). Chaos in instructional design.Educational Technology, 30(2), 32–34.Google Scholar
  30. Jonassen, D. H., Hannum, W. H., & Tessmer, M. (1989).Handbook of task analysis procedures. New York: Praeger.Google Scholar
  31. Kosslyn, S. M. (1980).Image and mind. Cambridge, MA: Harvard University Press.Google Scholar
  32. Lakoff, G. (1987).Women, fire, and dangerous things. Chicago: University of Chicago Press.Google Scholar
  33. Laurel, B. (1991).Computers as theatre. Reading, MA: Addison-Wesley.Google Scholar
  34. Mannes, S. M., & Kintsch, W. (1987). Knowledge organization and text organization.Cognition and Instruction, 4, 91–115.CrossRefGoogle Scholar
  35. Mayer, R. E. (1980). Elaboration techniques that increase the meaningfulness of technical text: An experimental test of the learning strategy hypothesis.Journal of Educational Psychology, 72(6), 770–784.Google Scholar
  36. McDonald, D. (1988).Drawing inferences from expository text. Unpublished doctoral dissertation, New Mexico State University, Las Cruces.Google Scholar
  37. McDaniel, M. A., & Schlager, M. S. (1990). Discovery learning and transfer of problem-solving skills.Cognition and Instruction, 7(2), 129–159.CrossRefGoogle Scholar
  38. Merrill, M. D., Kowallis, T., & Wilson, B. G. (1981). Instructional design in transition. In F. Farley & N. Gordon (Eds.),Psychology and education: The state of the union. Chicago: McCutcheon.Google Scholar
  39. Merrill, M. D., Wilson, B. G., & Kelety, J. C. (1981). Elaboration theory and cognitive psychology.Instructional Science, 10, 217–235.CrossRefGoogle Scholar
  40. Montague, W. E. (1988). Promoting cognitive processing and learning by designing the learning environment. In D. Jonassen (Ed.),Instructional designs for microcomputer courseware (pp. 125–149). Hillsdale, NJ: Lawrence Erlbaum.Google Scholar
  41. Nelson, W. A., & Orey, M. A. (1991, April).Reconceptualizing the instructional design process: Lessons learned from cognitive science. Paper presented at the annual meeting of the American Educational Research Association, Chicago.Google Scholar
  42. Newman, D., Griffin, P., & Cole, M. (1989).The construction zone: Working for cognitive change in school. Cambridge: Cambridge University Press.Google Scholar
  43. Norman, D., Gentner, D., & Stevens, A. (1976). Comments on learning schemata and memory representation. In D. Klahr (Ed.),Cognition and instruction (pp. 177–196). Hillsdale, NJ: Lawrence Erlbaum.Google Scholar
  44. Papert, S. (1988). The conservation of Piaget: The computer as grist to the constructivist mill. In G. Forman & P. B. Pufall (Eds.),Constructivism in the computer age (pp. 3–13). Hillsdale, NJ: Lawrence Erlbaum.Google Scholar
  45. Perkins, D. A. (1991, September). What constructivism demands of the learner.Educational Technology, 19–21.Google Scholar
  46. Posner, G. J., & Rudnitsky, A. N. (1986).Course design: A guide to curriculum development for teachers (3rd ed.). New York: Longman.Google Scholar
  47. Posner, G. J., & Strike, K. A. (1976). A categorization scheme for principles of sequencing content.Review of Educational Research, 46, 665–690.Google Scholar
  48. Putnam, R. W. (1991). Recipes and reflective learning: “What would prevent you from saying it that way?” In D. A. Schön (Ed.),The reflective turn: Case studies in and on reflective practice (pp. 145–163). New York: Teachers College Press.Google Scholar
  49. Reigeluth, C. M. (Ed.). (1983).Instructional-design theories and models: An overview of their current status. Hillsdale, NJ: Lawrence Erlbaum.Google Scholar
  50. Reigeluth, C. M. (1987). Lesson blueprints based on the elaboration theory of instruction. In C. M. Reigeluth (Ed.),Instructional theories in action: Lessons illustrating selected theories and models (pp. 245–288). Hillsdale, NJ: Lawrence Erlbaum.Google Scholar
  51. Reigeluth, C. M., & Darwazeh, A. N. (1982). The elaboration theory's procedure for designing instruction: A conceptual approach.Journal of Instructional Development, 5, 22–32.Google Scholar
  52. Reigeluth, C. M., Merrill, M. D., & Wilson, B. G. (1979, February).The structural strategy diagnostics profile project: Final report. Provo, UT: David O. McKay Institute, Brigham Young University.Google Scholar
  53. Reigeluth, C. M., Merrill, M. D., Wilson, B. G., & Spiller, R. T. (1978, July).Final report on the structural strategy diagnostic profile project. A final report submitted to the Navy Personnel Research and Development Center, San Diego.Google Scholar
  54. Reigeluth, C. M., & Rodgers, C. A. (1980). The elaboration theory of instruction: Prescriptions for task analysis and design.NSPI Journal, 19, 16–26.Google Scholar
  55. Reigeluth, C. M., & Stein, R. (1983). Elaboration theory. In C. M. Reigeluth (Ed.),Instructional-design theories and models: An overview of their current status. Hillsdale, NJ: Lawrence Erlbaum.Google Scholar
  56. Resnick, L. B. (1983). Toward a cognitive theory of instruction. In S. G. Paris, G. M. Olson, & H. W. Stevenson (Eds.),Learning and motivation in the classroom (pp. 5–38). Hillsdale, NJ: Lawrence Erlbaum.Google Scholar
  57. Rickards, J. P. (1978). Instructional psychology: From a behavioristic to a cognitive orientation.Improving Human Performance Quarterly, 7(4), 256–266.Google Scholar
  58. Rosch, E., Mervis, C., Gray, W., Johnson, D., & Boyes-Braem, P. (1976). Basic objects in natural categories.Cognitive Psychology, 8, 382–349.CrossRefGoogle Scholar
  59. Rossett, A. (1991, February).Coaching successful performance. Paper presented at the meeting of the Association for Educational Communications and Technology, Orlando.Google Scholar
  60. Rumelhart, D. E., & Norman, D. A. (1981). Analogical processes in learning. In J. R. Anderson (Ed.),Cognitive skills and their acquisition (pp. 335–359). Hillsdale, NJ: Lawrence Erlbaum.Google Scholar
  61. Ryle, G. (1949).The concept of mind. London: Hutchinson's University Library.Google Scholar
  62. Salomon, G. (1974). What is learned and how it is taught: The interaction between media, message, task and learner. In D. R. Olson (Ed.),Media and symbols: The forms of expression, communication, and education (73rd Yearbook of NSSE, pp. 383–406). Chicago: University of Chicago Press.Google Scholar
  63. Salomon, G., & Sieber, J. E. (1970). Relevant subjective response uncertainty as a function of stimulus-task interaction.American Educational Research Journal, 7, 337–350.Google Scholar
  64. Salmoni, A. W., Schmidt, R. A., & Walter, C. B. (1984). Knowledge of results and motor learning: A review and critical reappraisal.Psychological Bulletin, 95(3), 355–386.Google Scholar
  65. Schank, R. C., & Jona, M. Y. (1991). Empowering the student: New perspectives on the design of teaching systems.The Journal of the Learning Sciences, 1(1), 7–35.Google Scholar
  66. Schoenfeld, A. H. (1985).Mathematical problem solving. New York: Academic Press.Google Scholar
  67. Schön, D. (1983).The reflective practitioner. New York: Basic Books.Google Scholar
  68. Schön, D. (1987).Educating the reflective practitioner: Toward a new design for teaching and learning in the professions. San Francisco: Jossey-Bass.Google Scholar
  69. Siegler, R. S. (1991).Children's thinking (2nd ed.). Englewood Cliffs, NJ: Prentice-Hall.Google Scholar
  70. Simon, H. (1980). Problem solving and education. In D. T. Tuma & F. Reif (Eds.),Problem solving and education: Issues in teaching and research (pp. 81–96). Hillsdale, NJ: Lawrence Erlbaum.Google Scholar
  71. Smith, P. L., & Wedman, J. F. (1988). The effects of organization of instruction on cognitive processing. In M. Simonson (Ed.),Selected research papers. Washington, DC: Association for Educational Communications and Technology.Google Scholar
  72. Spiro, R. J., Feltovich, P. J., Coulson, R. L., & Anderson, D. K. (1989). Multiple analogies for complex concepts: Antidotes for analogy-induced misconception in advanced knowledge acquisition. In S. Vosniadou & A. Ortony (Eds.),Similarity and analogical reasoning (pp. 498–531). Cambridge UK: Cambridge University Press.Google Scholar
  73. Spiro, R. J., & Jehng, J-C. (1990). Cognitive flexibility and hypertext: Theory and technology for the nonlinear and multidimensional traversal of complex subject matter. In D. Nix & R. J. Spiro (Eds.),Cognition, education, and multimedia: Exploring ideas in high technology (pp. 163–205). Hillsdale, NJ: Lawrence Erlbaum.Google Scholar
  74. Strike, K. A., & Posner, G. J. (1976). Epistemological perspectives on conceptions of curriculums organization and learning.Review of Research in Education, 4, 106–141.Google Scholar
  75. Taylor, R. (1991, Spring). NSPI president challenges instructional design profs.ITED Newsletter, 1, 4–5.Google Scholar
  76. Tessmer, M. (1991, April). Personal communication.Google Scholar
  77. Tessmer, M., Wilson, B., & Driscoll, M. (1990). A new model of concept learning and teaching.Educational Technology Research and Development, 38(1), 45–53.Google Scholar
  78. Tulving, E. (1985). How many memory systems are there?American Psychologist, 40(4), 385–398.CrossRefGoogle Scholar
  79. Wedman, J., & Tessmer, M. (1990). Adapting instructional design to project circumstance: The layers of necessity model.Educational Technology, 31(7), 48–52.Google Scholar
  80. Wertsch, J. V. (1985).Vygotsky and the social formation of mind. Cambridge, MA: Harvard University Press.Google Scholar
  81. White, B. Y., & Frederiksen, J. R. (1986).Progressions of quantitative models as a foundation for intelligent learning environments [Technical Report #6277]. Cambridge, MA: Bolt, Beranek & Newman.Google Scholar
  82. Wilson, B. G. (1985). Techniques for teaching procedures.Journal of Instructional Development, 8(2), 42–51.Google Scholar
  83. Wilson, B. G. (1985–86). Using content structure for course design.Journal of Educational Technology Systems, 14(2), 137–147.CrossRefGoogle Scholar
  84. Wilson, B. G., & Cole, P. (in press-a). An instructional-design review of cognitive teaching models emerging from cognitive psychology.Educational Technology Research & Development Journal.Google Scholar
  85. Wilson, B., & Cole, P. (in press-b). Cognitive dissonance as an instructional variable.Ohio Media Spectrum.Google Scholar
  86. Wilson, B. G., & Merrill, M. D. (1980). General-to-detailed sequencing of concepts in a taxonomy is in general agreement with learning hierarchy analysis.Performance and Instruction, 19, 11–14.Google Scholar
  87. Wilson, B. G., & Tessmer, M. (1990). Adults' perceptions of concept learning outcomes: An initial study and discussion. In M. Simonson (Ed.),Proceedings of selected research presentations. Washington, DC: Association for Educational Communications and Technology, Research and Theory Division.Google Scholar
  88. Winn, W. (1990). Some implications of cognitive theory for instructional design.Instructional Science, 19, 53–69.CrossRefGoogle Scholar
  89. Winograd, T., & Flores, F. (1986).Understanding computers and cognition: A new foundation for design. Norwood, NJ: Ablex.Google Scholar

Copyright information

© Association for Educational Communications and Technology 1992

Authors and Affiliations

  • Brent Wilson
    • 1
  • Peggy Cole
    • 1
  1. 1.University of Colorado at DenverDenver

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