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Educational Technology Research and Development

, Volume 42, Issue 3, pp 15–28 | Cite as

The big wrench vs. integrated approaches: The great media debate

  • Robert D. Tennyson
Research

Abstract

This article sums up the current state of the media debate by comparing and contrasting the seven positions presented in the ETR&D special issue (Vol. 42(2), 1994). Presented first is a review of the science-wide conflict between advocates of a given approach versus proponents of integrated approaches to the solving of complex problems. Advocates of a given approach are characterized as offering a “big wrench” (i.e., panacea) solution that can be generalized across problems. While in contrast are integrated approaches (e.g., the Swiss knife) that attempt to solve problems by bringing together a variety of variables and conditions. In section two is presented an example of an integrated approach that deals directly with the role of media in learning. Finally, the positions of the seven authors are compared and contrasted employing eight instructional design variables.

Keywords

Design Variable Complex Problem Educational Technology Integrate Approach Instructional Design 
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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References

  1. Bartlett, F. (1932).Remembering. Cambridge: Cambridge University Press.Google Scholar
  2. Breuer, K., & Kummer, R. (1990). Cognitive effects from process learning with computer-based simulations.Computers in Human Behavior, 6, 69–81.CrossRefGoogle Scholar
  3. Clark, R. C. (1983). Reconsidering research on learning from media.Review of Educational Research, 53, 445–459.Google Scholar
  4. Clark, R.C. (1994). Media will never influence learning.Educational Technology Research and Development 42(2), 21–29.Google Scholar
  5. Gagné, R.M. (1985).The conditions of learning (4th ed.). New York: Holt, Rinehart and Winston.Google Scholar
  6. Jonassen, D., Campbell, J. & Davison, M. (1994). Learning with media: Restructuring the debate.Educational Technology Research and Development 42(2), 31–39.Google Scholar
  7. Kozma, R. (1994).Will media influence learning? Reframing the debate.Educational Technology Research and Development 42(2), 7–19.Google Scholar
  8. McKeachie, W.F. (1974). Instructional psychology.Annual Review of Psychology, 25, 161–193.CrossRefGoogle Scholar
  9. Morrison, G. (1994). The media effects question: “Unresolvable” or asking the right question.Educational Technology Research and Development 42(2), 41–44.Google Scholar
  10. Papert, S. (1990). Introduction by Seymour Papert. In I. Harel (Ed.),Constructionist learning. Boston: MIT Media Laboratory.Google Scholar
  11. Petkovich, M.D., & Tennyson, R.D. (1984). Clark's “Learning from media”: A critique.Educational Communication and Technology Journal, 32, 233–241.Google Scholar
  12. Rasco, R.W., Tennyson, R.D., & Boutwell, R.C. (1975). Imagery instructions and drawings in learning prose.Journal of Educational Psychology, 67, 188–192.Google Scholar
  13. Reiser, R. (1994). Clark's invitation to the dance: An instructional designer's response.Educational Technology Research and Development 42(2), 45–48.Google Scholar
  14. Reed, M. (1992). Computers and improvements in writing.Computers in Human Behavior, 8, 34–47.Google Scholar
  15. Shrock, S. (1994). The media influence debate: Read the fine print, but don't lose sight of the big picture.Educational Technology Research and Development 42(2), 49–53.Google Scholar
  16. Skinner, B.F. (1954). The science of learning and the art of teaching.Harvard Educational Review, 24, 86–97.Google Scholar
  17. Spiro, R. (1977). Remembering information from text: Theoretical and empirical issues concerning the “State of Schema” reconstruction hypothesis. In R. Anderson, R. Spiro, & W. Montague (Eds.),Schooling and the acquisition of knowledge (pp. 114–142). Hillsdale, NJ: Erlbaum.Google Scholar
  18. Tennyson, R.D. (1987, February). Computer-based enhancements for the improvement of learning. In M. Simonson (Chair),“... Mere vehicles”: Discussion of what the research says by those who are doing the saying. Invited symposium presented at the meeting of the Association for Educational Communication and Technology, Atlanta.Google Scholar
  19. Tennyson, R.D. (1990a). Artificial intelligence and computer-based learning. In C.N. Hedley, J. Houtz, & A. Baratta (Eds.),Cognition, curriculum, and literacy (pp. 95–104). Norwood, NJ: Ablex.Google Scholar
  20. Tennyson, R.D. (1990b). Computer-based enhancements for the improvement of learning. In S. Dijkstra, B.H.A.M. van Hout Wolters, & P.C. van der Sijde (Eds.),Research on instruction: Design and effects (pp. 101–109). Englewood Cliffs, NJ: Educational Technology.Google Scholar
  21. Tennyson, R.D. (1991). Tracing cognitive processes of learning and cognition to computer-based enhancements.Information Technology in Sociology and the Policy Sciences, 3, 11–17.Google Scholar
  22. Tennyson, R.D. (1993). A framework for automating instructional design. In J.M. Spector, M.C. Polson, & D.J. Muraida (Eds.),Automating instructional design: Concepts and issues (pp. 191–212). Englewood Cliffs, NJ: Educational Technology.Google Scholar
  23. Tennyson, R.D., & Bagley, C. (1992). Structured versus constructed instructional strategies for improving concept acquisition by domain-experienced and domain-novice learners.Journal of Structural Learning, 12, 67–81.Google Scholar
  24. Tennyson, R.D., & Breuer, K. (1984). Cognitive-based design guidelines for using video and computer technology in course development. In O. Zuber-Skerritt (Ed.),Video in higher education (pp. 26–63). London: Kogan.Google Scholar
  25. Tennyson, R.D., & Breuer, K. (1991). Complex-dynamic simulations to improve higher-order thinking strategies.Journal of Structural Learning, 11, 311–326.Google Scholar
  26. Tennyson, R.D., & Breuer, K. (1993). ISD EXPERT: An automated approach to instructional design. In R. D. Tennyson (Ed.),Automating instructional design, development, and delivery (pp. 139–162). Berlin: Springer.Google Scholar
  27. Tennyson, R.D., & Breuer, K. (in press). Instructional design theory: Psychological perspectives. In R.D. Tennyson & F. Schott (Eds.),Instructional design: International perspectives, vol. I: Theory and research. Hillsdale, NJ: Erlbaum.Google Scholar
  28. Tennyson, R.D., Elmore, R., & Snyder, L. (1992). Advancements in instructional design theory: Contributions from cognitive science and educational technology.Educational Technology Research and Development, 40, 9–22.Google Scholar
  29. Tennyson, R.D., & Park, O. (1987). Artificial intelligence and computer-assisted learning. In R. Gagné (Ed.),Instructional technology: Foundations (pp. 319–342). Hillsdale, NJ: Erlbaum.Google Scholar
  30. Tennyson, R.D., & Rasch, M. (1988). Linking cognitive learning theory to instructional prescriptions.Instructional Science, 17, 369–385.CrossRefGoogle Scholar
  31. Tennyson, R.D., Steve, M.W., & Boutwell, R.C. (1975). Instance sequence and analysis of instance attribute representation in concept acquisition.Journal of Educational Psychology, 67, 821–827.CrossRefGoogle Scholar
  32. Tennyson, R.D., Welsh, J.C., & Christensen, D.L. (1985). Interactive effect of content structure, sequence, and process learning time on rule learning using computer-based instruction.Educational Communication and Technology Journal, 33, 213–223.Google Scholar
  33. White, (1993). ThinkerTools: Causal models, conceptual change, and science education.Cognition and Instruction, 10(1), 1–100.CrossRefGoogle Scholar

Copyright information

© the Association for Educational Communications and Technology 1994

Authors and Affiliations

  • Robert D. Tennyson
    • 1
  1. 1.the Department of Educational Psychologythe University of Minnesota at MinneapolisUSA

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