Advertisement

Journal of Computing in Higher Education

, Volume 21, Issue 1, pp 4–18 | Cite as

Translating research into new instructional technologies for higher education: the active ingredient process

  • Richard E. Clark
Article
First Online:

Abstract

This article describes a research-based approach for developing new instructional technologies for higher education. The argument is made that the most common instructional methods used by faculty and educational technology in colleges and universities are based on adult learning theories that have not been supported in the past half-century of research. A four-stage process is offered to guide the analysis of research on adult learning and motivation in order to increase the effectiveness of classroom, lecture hall and media delivered higher education instruction. The process emphasizes the identification and application of the “active ingredients” of effective instructional methods and a strategy for translating active ingredients into the most effective instructional technologies for diverse higher education organizational and individual cultural orientations.

Keywords

Research and development cycle Research design Intervention design Instructional technology development External validity 
This is a preview of subscription content, log in to check access.

References

  1. Campbell, D. T., & Stanley, J. C. (1966). Experimental and quasi-experimental designs for research. Chicago: Rand McNally.Google Scholar
  2. Chi, M. T. H., Feltovich, P. J., & Glaser, R. (1981). Categorization and representation of physics problems by experts and novices. Cognitive Science, 5, 121–152.CrossRefGoogle Scholar
  3. Clark, R. E. (1982). Antagonism between achievement and enjoyment in ATI studies. Educational Psychologist, 17(2), 92–101.Google Scholar
  4. Clark, R. E. (1989). Questions and designs for research in instructional technology. Educational Technology Research and Development, 1(1), 27–36.Google Scholar
  5. Clark, R. E. (2001). Learning from media: Arguments, analysis and evidence. Greenwich, CT: Information Age Publishers. ISBN 1-930608-77-2.Google Scholar
  6. Clark, R. E. (2005). Motivating individuals, teams and organizations. In J. Pershing (Ed.), Handbook of human performance improvement (Third ed., pp. 268–286). San Francisco: Jossey-Bass Pfeiffer.Google Scholar
  7. Clark, R. E. (2009a). Resistance to change: Unconscious knowledge and the challenge of unlearning. In D. C. Berliner & H. Kupermintz (Eds.), Changing institutions, environments and people (pp. 75–94). New York: Routledge.Google Scholar
  8. Clark, R. E. (2009b). How much and what type of guidance is optimal for learning from instruction? In S. Tobias & T. M. Duffy (Eds.), Constructivist theory applied to instruction: Success or failure? (pp. 158–183). New York: Routledge, Taylor and Francis.Google Scholar
  9. Clark, R. E., & Elen, J. (2006). When less is more: Research and theory insights about instruction for complex learning. In J. Elen & R. Clark (Eds.), Handling complexity in learning environments: Research and theory (pp. 283–297). Oxford: Elsevier Science Limited.Google Scholar
  10. Clark, R. E., & Estes, F. (1998). Technology or craft: What are we doing? Educational Technology, 38(5), 5–11.Google Scholar
  11. Clark, R. E., & Estes, F. (1999). The development of authentic educational technologies. Educational Technology, 37(2), 5–16.Google Scholar
  12. Clark, R. E., & Estes, F. (2008). Turning research into results: A guide to selecting the right performance Solutions (2nd ed.). Greenwich Conn: Information Age Publishers.Google Scholar
  13. Clark, R. E., Yates, K., Early, S., & Moulton, K. (in press). An analysis of the failure of electronic media and discovery-based learning: Evidence for the performance benefits of guided training methods. In K. H. Silber & R. Foshay (Eds.), Handbook of training and improving workplace performance, volume I: Instructional design and training deliver. International Society for Performance Improvement.Google Scholar
  14. Colquitte, J. A., LePine, A. A., & Noe, R. A. (2000). Toward an integrative theory of training motivation: A meta-analytic path analysis of the past 20 years of research. Journal of Applied Psychology, 85(5), 678–707.CrossRefGoogle Scholar
  15. Cook, T. D., Appleton, H., Conner, R. F., Shaffer, A., Tamkin, G., & Weber, S. J. (1975). “Sesame Street” revisited. New York: Russell Sage Foundation.Google Scholar
  16. Cronbach, L. J., & Snow, R. E. (1977). Aptitudes and instructional methods: A handbook for research on interactions. New York: Irvington Publishers.Google Scholar
  17. Druckman, D., Singer, J. E., & Van Cott, H. (Eds.). (1997). Enhancing organizational performance. Washington, DC: National Academy Press.Google Scholar
  18. Gage, N. (1985). Hard gains in the soft sciences: The case of pedagogy. Bloomington, IN: Phi Delta Kappa, Center on Evaluation, Development and Research.Google Scholar
  19. Handelsman, J., Egert-May, D., Beichner, R., Bruns, P., Change, A., DeHaan, R., et al. (2004). Scientific teaching. Science, 304, 521–522.CrossRefGoogle Scholar
  20. Hofstede, G. (2001). Culture’s consequences: Comparing values, behaviors, institutions and organizations across nations (2nd ed.). Thousand Oaks, CA: Sage.Google Scholar
  21. Hofstede, G., & McCrae, R. R. (2004). Personality and culture revisited: Linking traits and dimensions of culture. Cross-Cultural Research, 38(1), 52–88.CrossRefGoogle Scholar
  22. Kirschner, P., Sweller, J., & Clark, R. E. (2006). Why minimally guided learning does not work: An analysis of the failure of discovery learning, problem-based learning, experiential learning and inquiry-based learning. Educational Psychologist, 41(1), 75–86.Google Scholar
  23. Landa, L. N. (1983). The algo-heuristic theory of instruction. In C. Reigeluth (Ed.), Instructional design theories and models (pp. 163–211). Hillsdale, NJ: Lawrence Erlbaum Publishers.Google Scholar
  24. Mayer, R. (2004). Should there be a three-strikes rule against pure discovery learning? The case for guided methods of instruction. American Psychologist, 59(1), 14–19.CrossRefGoogle Scholar
  25. Mayer, R. (Ed.). (2005). Cambridge handbook of multimedia learning. Cambridge: Cambridge University Press.Google Scholar
  26. Merrill, M. D. (1983). Component display theory. In C. M. Reigeluth (Ed.), Instructional design theories and models (pp. 279–333). Hillsdale, NJ: Erlbaum.Google Scholar
  27. Merrill, M. D. (2002). First principles of instruction. Educational Technology Research and Development, 50(3), 43–59.CrossRefGoogle Scholar
  28. Merrill, M. D. (2006). Hypothesized performance on complex tasks as a function of scaled instructional strategies. In J. Elen & R. Clark (Eds.), Handling complexity in learning environments: Research and theory (pp. 265–282). Oxford: Elsevier Science Limited.Google Scholar
  29. Pintrich, P. R., & Schunk, D. H. (2002). Motivation in education: Theory, research and applications (2nd ed.). Englewood Cliffs, NJ: Prentice Hall.Google Scholar
  30. Prochaska, J. M., Norcross, J., & DiClemente, C. (1994). Changing for good. New York: Avon Press.Google Scholar
  31. Prochaska, J. M., Prochaska, J. O., & Levesque, D. A. (2001). A transtheoretical approach to changing organizations. Administration and Policy in Mental Health, 28(4), 247–261.CrossRefGoogle Scholar
  32. Ravitch, D., & Viteritti, J. P. (2001). Making good citizens: Education and Civil Society. New Haven: Yale University Press.Google Scholar
  33. Reigeluth, C. M. (1983). Instructional design, what is it and why is it? In C. Reigeluth (Ed.), Instructional design theories and models (pp. 4–31). Hillsdale, NJ: Lawrence Erlbaum Publishers.Google Scholar
  34. Rossett, A. (1999). First things fast: A handbook for performance analysis. SF: Jossey Bass.Google Scholar
  35. Rossett, A., & Czech, C. (1996). They really wanna but…The aftermath of professional preparation in performance technology. Performance Improvement Quarterly, 8(4), 114–132.Google Scholar
  36. Sitzman, T., Kraiger, K., Stewart, D., & Wisher, R. (2006). The comparative effectictiveness of web-based and classroom instruction: A meta-analysis. Personnel Psychology, 59, 623–664.CrossRefGoogle Scholar
  37. Sweller, J. (2006). How the human cognitive system deals with complexity. In J. Elen & R. E. Clark (Eds.), Handling complexity in learning environments: Research and theory (pp. 13–26). Oxford, GB: Elsevier Science Limited.Google Scholar
  38. Sweller, J., Kirschner, P. A., & Clark, R. E. (2007). Why minimally guided teaching techniques do not work: A reply to commentaries. Educational Psychologist, 42(2), 115–121.Google Scholar
  39. Winthrop, H. (1963). Some considerations concerning the status of phenomenology. Journal of General Psychology, 68, 127–140.Google Scholar

Copyright information

© Springer Science+Business Media, LLC 2009

Authors and Affiliations

  1. 1.Center for Cognitive Technology, Rossier School of EducationUniversity of Southern CaliforniaRedondo BeachUSA

Personalised recommendations

Cite article

Buy options