Effectiveness of motivationally adaptive computer-assisted instruction on the dynamic aspects of motivation

  • Sang H. Song
  • John M. Keller
Research

Abstract

The purpose of this study was to examine the effects of a prototype of motivationally-adaptive computer-assisted instruction (CAI). The foundation for motivational theory and design was provided by the ARCS model (an acronym formed from attention, relevance, confidence, and satisfaction). This model provides a definition of motivation, a motivational design process, and recommendations for motivational strategies. Three treatment conditions were considered: (a) motivationally adaptive CAI, (b) motivationally saturated CAI, and (c) motivationally minimized CAI. Dependent variables were effectiveness, perceived motivation (both overall motivation and each of A, R, C, & S components), efficiency, and continuing motivation. The motivationally adaptive CAI showed higher effectiveness, overall motivation, and attention than the other two CAI types. For efficiency, both motivationally adaptive CAI and motivationally minimized CAI were higher than motivationally saturated CAI. For continuing motivation, there were no significant differences among the three CAI types, but a significant correlation was found between overall motivation and continuing motivation across the three CAI types. This study supports the conclusion that CAI can be designed to be motivationally adaptive to respond to changes in learner motivation that may occur over time. It also illustrates that the ARCS model can be useful and effective in support of designing for these dynamic aspects of motivation.

References

  1. Alschuler, A.S. (1973).Developing achievement motivation in adolescents: Education for human growth Englewood Cliffs, NJ: Educationl Technology Publications.Google Scholar
  2. Alschuler, A.S., Tabor, D. & McIntyre, J. (1971).Teaching achievement motivation: Theory and practice in psychological education. Middletown, CT: Education Ventures, Inc.Google Scholar
  3. Astleitner, J., & Keller, J.M. (1995). A model for motivationally adaptive computer-assisted instruction.Journal of Research on Computing in Education, 27(3), 270–280.Google Scholar
  4. Atkinson, R.C. (1976). Adaptive instructional systems: Some attempts to optimize the learning process. In D. Klahr (Ed.),Cognition and instruction (pp. 81–108). New York: Wiley & Sons.Google Scholar
  5. Bickford, N.L. (1989).The systematic application of principles of motivation to the design of printed instructional materials. Unpublished doctoral dissertation. Florida State University, Florida.Google Scholar
  6. Brown, J. (1986). Some motivational issues in computer-based instruction.Educational Technology, 26(4), 27–29.Google Scholar
  7. Clark, R.E. (1983). Reconsidering research on learning from media.Review of Educational Research, 53(4), 445–459.CrossRefGoogle Scholar
  8. del Soldato, T., & du Boulay, B. (1995). Implementation of motivational tactics in tutoring systems.Journal of Artificial Intelligence in Education, 6(4), 337–378.Google Scholar
  9. Dempsey, J., Lucassen, B., Gilley, W., & Rasmussen, K. (1993). Since Malone's theory of intrinsically motivating instruction: What's the score in the gaming literature?Journal of Educational Technology Systems, 22(2), 173–184CrossRefGoogle Scholar
  10. Dick, W. & Carey, L. (1996).The systematic design of instruction (4th ed.). New York: Harper Collins.Google Scholar
  11. Farmer, T. M. (1989).A refinement of the ARCS motivational design procedure using a formative evaluation methodology. Unpublished doctoral dissertation, Indiana University, Indiana.Google Scholar
  12. Gagné, R. M. (1985).The conditions of learning and theory of instruction (4th ed.). New York: Holt, Rinehart & Winston.Google Scholar
  13. Goodman, H.D., et al. (1989).Biology, Orlando, FL: Harcourt Brace Jovanovich.Google Scholar
  14. Hativa, N., & Lesold, A. (1991). The computer as a tutor—Can it adapt to the individual learner?Instructional Science, 20(1), 49–78.CrossRefGoogle Scholar
  15. Holland, J.G. (1977). Variables in adaptive decisions in individual instruction.Educational Psychologist, 12(2), 146–161.CrossRefGoogle Scholar
  16. Houlihan, P.A., Finkelstein, M.W., & Johnson, L.A. (1992). Adaptive use of the DDx&Tx system.Journal of Computer-Based Instruction, 19(4), 125–130.Google Scholar
  17. Johnson, D.W., & Johnson, R.T. (1986). Computerassisted cooperative learning.Educational Technology, 26(1), 12–18.Google Scholar
  18. Keller, J.M. (1979). Motivation and instructional design: A theoretical perspective.Journal of Instructional Development, 2(4), 26–34.Google Scholar
  19. Keller, J.M. (1983). Motivational design of instruction In C.M. Reigeluth (Ed.),Instructional-design theories and models: An overview of their current status (pp. 386–434). Hillsdale, NJ: Lawrence Erlbaum Associates.Google Scholar
  20. Keller, J.M. (1987a). Strategies for stimulating the motivation to learn.Performance and Instruction Journal, 26(8), 1–7.Google Scholar
  21. Keller, J.M. (1987b). The systematic process of motivational design.Performance and Instruction Journal, 26(9/10), 1–8.Google Scholar
  22. Keller, J.M. (1987c). Development and use of the ARCS model of instructional design.Journal of Instructional Development, 10(3), 2–10.Google Scholar
  23. Keller, J.M. (1993).Motivation by design. Unpublished manuscript, Florida State University, Florida.Google Scholar
  24. Keller, J.M. (1997). Motivational design and multimedia: Beyond the novelty effect.Strategic Human Resource Development Review, 1(1), 188–203.Google Scholar
  25. Keller, J.M. (1999). Motivational systems. In H. Stolovitch, & E. Keeps (Eds.),Handbook of human performance technology (2nd ed.). San Francisco: Jossey-Bass Inc. Publishers.Google Scholar
  26. Keller, J.M., & Burkman, E. (1993). Motivation principles. In M. Fleming & W.H. Levie (Eds.),Instructional message design: Principles from the behavioral and cognitive sciences. Englewood Cliffs, NJ: Educational Technology Press.Google Scholar
  27. Keller, J.M. & Suzuki, K. (1988). Use of the ARCS motivation model in courseware design. In D.H. Jonassen (Ed.),Instructional designs for microcomputer courseware (pp. 401–434). Hillsdale, NJ: Lawrence Erlbaum Associates.Google Scholar
  28. Klein, J.D., & Freitag, E.T. (1982). Training students to utilize self-motivational strategies.Educational Technology, 32(3), 44–48.Google Scholar
  29. Klein, J.D., & Keller, J.M. (1990). Influence of student ability, locus of control, and type of instructional control on performance and confidence.Journal of Educational Research, 83(3), 140–146.Google Scholar
  30. Lee, S.H. & Boling, E. (1996).Motivational screen design guidelines for effective computer-mediated instruction. Proceedings of Selected Research and Development Presentations at the 1996 National Convention of the Association for Educational Communications and Technology, Indianapolis, Indiana, 401–412.Google Scholar
  31. Lepper, M.R. (1985). Microcomputers in education: Motivational and social issues.American Psychologist, 40(1), 1–18.CrossRefGoogle Scholar
  32. Maehr, M.L. (1976). Continuing motivation: An analysis of a seldom considered educational outcome.Review of Educational Research, 46(3), 443–462.CrossRefGoogle Scholar
  33. Malone, T. (1981). Toward a theory of intrinsically motivation instruction.Cognitive Science, 4, 333–369.CrossRefGoogle Scholar
  34. Malouf, D.B. (1988). The effect of instructional computer games on continuing student motivation.The Journal of Special Education, 21(4), 27–38.CrossRefGoogle Scholar
  35. McCombs, B.L., Eschenbrenner, A.J. Jr., & O'Neill, H.F., Jr. (1973). An adaptive model for utilizing learner characteristics in computer based instructional systems.Educational Technology, 13(4), 47–51.Google Scholar
  36. Means, T.B., Jonassen, D.H., & Dwyer, F.M. (1997). Enhancing relevance: Embedded ARCS strategies vs. purpose.Educational Technology Research and Development, 45(1), 5–18.CrossRefGoogle Scholar
  37. Mills, S.C., & Ragan, T.J. (1994).Adapting instruction to individual learner differences: A research paradigm for computer-based instruction. Proceedings of Selected Research and Development Presentations at the 1994 National Convention of the Association for Educational Communications and Technology, Nashville, Tennessee, 525–546.Google Scholar
  38. Newby, T.J. (1991), Classroom motivation: Strategies of first-year teachers.Journal of Educational Psychology, 83(2), 195–200.CrossRefGoogle Scholar
  39. Nwagbara, C.I. (1993).Effects of the relevance component of the ARCS model of motivational design. Unpublished doctoral dissertation. Purdue University, Indiana.Google Scholar
  40. Osman, M. (1992).The effects of think-ahead questions and prior knowledge on learning and retention. Unpublished Doctoral Dissertation, Florida State University, Florida.Google Scholar
  41. Park, I.W. (1993).The effects of orienting questions and prior knowledge on learning in hypertext. Unpublished doctoral dissertation, Florida State University, Florida.Google Scholar
  42. Pintrich, P.R., & Schunk, D.H. (1996).Motivation in education: Theory, research, and applications, Englewood, Cliffs, NJ: Prentice Hall.Google Scholar
  43. Relan, A. (1992).Motivational strategies in computerbased instruction: Some lessons from theories and models of motivation. Proceedings of Selected Research and Development Presentations at the Conventions of the Association for Educational Communications and Technology, 612–624.Google Scholar
  44. Rezabek, R.H. (1994).Utilizing intrinsic motivation in the design of instruction. Proceedings of Selected Research and Development Presentations at the National Convention of the Association for Educational Communications and Technology, Nashville, Indiana, 695–704.Google Scholar
  45. Ross, S.M., & Morrison, G.R. (1988). Adapting instruction to learner performance and background variables. In D.H. Jonassen (Ed.),Instructional designs for microcomputer courseware (pp 227–243). Hillsdale, NJ: Lawrence Erlbaum Associates.Google Scholar
  46. Small, R.V., & Gluck, M. (1994). The relationship of motivational conditions to effective instructional attributes: A magnitude scaling approach.Educational Technology, 34(8), 33–40.Google Scholar
  47. Tennyson, R.D., & Christensen, D.L. (1988). MAIS: an intelligent learning system. In D. Jonassen, (Ed.),Instructional designs for micro computer courseware (pp. 247–274). Hillsdale, NJ: Lawrence Erlbaum.Google Scholar
  48. Tennyson, R.D., & Park, S. (1984). Process learning time as an adaptive design variable in concept learning using computer-based instruction.Journal of Educational Psychology, 76, 452–465.CrossRefGoogle Scholar
  49. Tuckman, B.W. (1994).Conducting educational research (4th ed.), New York: Harcourt Brace & Company.Google Scholar
  50. Visser, J., & Keller, J.M. (1990). The clinical use of motivational messages: An inquiry into the validity of the ARCS model of motivational design.Instructional Science, 19, 467–500.CrossRefGoogle Scholar
  51. Wlodkowski, R.J. (1999).Enhancing adult motivation to learn (2nd ed.). San Francisco: Jossey-Bass.Google Scholar

Copyright information

© Association for Educational Communications and Technology 2001

Authors and Affiliations

  • Sang H. Song
    • 1
  • John M. Keller
    • 2
  1. 1.Andong National UniversityKorea
  2. 2.Florida State UniversityUSA

Personalised recommendations