Advertisement

Facilitating Domain-General Problem Solving: Computers, Cognitive Processes and Instruction

  • Richard E. Clark
Part of the NATO ASI Series book series (volume 84)

Abstract

Research on the transfer of problem solving between knowledge domains is reviewed. It is concluded that instructional and programming studies do not provide evidence for any essential contribution of the computer to problem solving. Instead, it is recommended that studies focus on the cognitive processes that are required for farther transfer and how these processes can be supported by instruction for students who fail to transfer. Two types of cognitive processes presumed to be active during problem solving are discussed: 1) The selecting of structural features of problem representations and 2) the connecting of features in two or more domains during transfer. The connecting process is discussed in depth and two types of connections are hypothesized, first, horizontal connections between knowledge structures in the form of analogies, and second, vertical connections within knowledge structures in the form of rule-example chains. It is suggested that analogies promote domain-general transfer because they provide horizontal connections between similar knowledge structures in different domains and induce rules that enlarge and extend the links between knowledge. Research focused on the use of analogies in problem solving is offered to support instructional prescriptions intended to facilitate domain-general problem solving.

Keywords

Computer research design Domain-general problem solving Metacognitive processes 

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    Anderson, J. R. (1983). The architecture of cognition. Cambridge, MA: Harvard University Press.Google Scholar
  2. 2.
    Anderson, J. R. (1985). Cognitive psychology and its implications. New York: Freeman.Google Scholar
  3. 3.
    Anderson, J. R., & Bower, G. H. (1973). Human Associative Memory. Washington, DC: Winston.Google Scholar
  4. 4.
    Bassok, E. (1990), Transfer of domain-specific problem-solving procedures. Journal of Experimental Psychology: Learning, Memory and Cognition, 16, 522–533.CrossRefGoogle Scholar
  5. 5.
    Bransford, J. D., Nitsch, K., & Franks, J. (1977). Schooling and the facilitation of knowledge. In R. C. Anderson, R. Spiro, & W. Montague (Eds.), Schooling and the acquisition of knowledge (pp. 31–55 ). Hillsdale, NJ: Lawrence Erlbaum.Google Scholar
  6. 6.
    Brown, A. (1978). Knowing when, where, and how to remember: a problem of metacognition. In R. Glaser (Ed.), Advances in instructional psychology (Vol. 1) (pp. 77–165 ). Hillsdale, NJ: Lawrence Erlbaum.Google Scholar
  7. 7.
    Chase, W. G., & Simon, H. A. (1973). Perception in chess. Cognitive Psychology, 55–81.Google Scholar
  8. 8.
    Chi, M. T. H., Glaser, R., & Rees, E. (1982). Expertise in problem solving. In R. Sternberg (Ed.), Advances in the psychology of human intelligence. Hillsdale, NJ: Lawrence Erlbaum.Google Scholar
  9. 9.
    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
  10. 10.
    Clark, R. E. (1983). Reconsidering research on learning from media. Review of Educational Research, 53, 445–459.Google Scholar
  11. 11.
    Clark, R. E. (1985). Confounding in educational computing research. Journal of Educational Computing Research, 1, 445–460.Google Scholar
  12. 12.
    Clark, R. E. (April, 1990 ). A cognitive theory of instructional method. Paper presented at the annual meeting of the American Educational Research Association, Boston, MA.Google Scholar
  13. 13.
    Clark, R. E., Blake, S., & Knostman, V. (1989). Metacognitive processes supporting far transfer: Selecting and connecting. Paper presented at the annual meeting of the American Educational Research Association, San Francisco, CA.Google Scholar
  14. 14.
    Clark, R. E., & Sugrue, B. M. (1989). Research on instructional media, 1978 - 1988. In D. Ely (Ed.), Educational Media Yearbook 1987-88. Littletown, CO: Libraries Unlimited.Google Scholar
  15. 15.
    Cormier, S. M., & Hagman, J. D. (1987). Transfer of learning: Contemporary research and applications. New York: Academic Press.Google Scholar
  16. 16.
    Corao, L., & Mandinach, E., (1983). The role of cognitive engagement in classroom learning and motivation. Educational Psychologist, 33, 88–108.Google Scholar
  17. 17.
    Cuban, L. (1986). A history of instructional technology. New York: Teachers College Press.Google Scholar
  18. 18.
    De Corte, E. (1990). Towards powerful learning environments for the acquisition of problem-solving skills. European Journal of Psychology of Education, 5, 5–19.CrossRefGoogle Scholar
  19. 19.
    De Corte, E., Verschaffel, L., & Schrooten, H. (1990). Cognitive effects of computer-oriented learning. Paper presented at the Seventh International Conference on Technology and Education, Brussels.Google Scholar
  20. 20.
    DiVesta, F. J., & Peverly, S. T. (1984). The effects of encoding variability, processing activity and rule example sequences on the transfer of conceptual rules. Journal of Educational Psychology, 76, 108–119.CrossRefGoogle Scholar
  21. 21.
    Duncker, K. (1945). On problem solving. Psychological Monographs, 58, (Whole No. 279).Google Scholar
  22. 22.
    Flavell, J. H. (1981). Cognitive monitoring. In W. P. Dickson (Ed.), Children’s oral communication skills. New York: Academic Press.Google Scholar
  23. 23.
    Gagne, R. M., & White, R. T. (1978). Memory structures and learning outcomes. Review of Educational Research, 48, 187–222.Google Scholar
  24. 24.
    Gardner, H. (1985). The mind’s new science: A history of the cognitive revolution. New York: Basic Books.Google Scholar
  25. 25.
    Gick, M. L., & Patterson, K. (1989) Contrasting examples, schema acquisition and problem solving transfer. Unpublished manuscript Google Scholar
  26. 26.
    Gick, M. L., & Holyoak, K. J. (1980). Analogical problem solving. Cognitive Psychology, 12, 306–355.CrossRefGoogle Scholar
  27. 27.
    Gick, M. L., & Holyoak, K. J. (1983). Schema induction and analogical transfer. Cognitive Psychology, 15, 1–38.CrossRefGoogle Scholar
  28. 28.
    Gick, M. L., & Holyoak, K. J. (1987). The cognitive basis of knowledge transfer. In S. M. Cormier & J. D. Hagman (Eds.), Transfer of learning. New York: Academic Press.Google Scholar
  29. 29.
    Glaser, R., & Bassok, M. (1989). Learning theory and the study of instruction. In M. R. Rosenwig & L. W. Porter (Eds.), Annual Review of Psychology (Vol. 40) (pp. 631–666 ). Palo Alto, CA: Annual Reviews.Google Scholar
  30. 30.
    Glass, A. L., & Holyoak, K. J. (1986). Cognition. New York: Random House.Google Scholar
  31. 31.
    Gray, L. E. (1983). Aptitude constructs, learning processes, and achievement. Unpublished dissertation, Stanford University.Google Scholar
  32. 32.
    Greeno, J. G. (1978). Nature of problem solving abilities. In W. K. Estes (Ed.), Handbook of Learning and Cognitive Processes (Vol. 5). Hillsdale, NJ: Lawrence Erlbaum.Google Scholar
  33. 33.
    Hayes-Roth, R., & McDermott, J. (1978). An interface matching technique for inducing abstractions. Communications of the ACM, 21, 401–410.Google Scholar
  34. 34.
    Holyoak, K. J. (1985). The pragmatics of analogical transfer. In G. H. Bower (Ed.), The psychology of learning and motivation (Vol. 19). New York: Academic Press.Google Scholar
  35. 35.
    Horn, J. L. (1976). Human abilities: A review of research and theory in the early 1970s. Annual Review of Psychology, 27, 437–485.PubMedCrossRefGoogle Scholar
  36. 36.
    Judd, C. H. (1908). The relation of special training to intelligence. Educational Review, 36, 28–42.Google Scholar
  37. 37.
    Kahneman, D., & Tversky, A. (1973). On the psychology of prediction. Psychological Review, 80, 237–251.Google Scholar
  38. 38.
    Keane, M. T. (1988). Analogical Problem Solving. New York: Halsted Press.Google Scholar
  39. 39.
    Klauer, K. J. (1989). Teaching for analogical transfer as a means of improving problem-solving, thinking and learning. Instructional Science, 18, 179–192.CrossRefGoogle Scholar
  40. 40.
    Linn, M. C., & Dalbey, J. (1989). Cognitive consequences of programming instruction. In E. Stolway & R.D. Spohrer (Eds.), Studying the Novice Programmer (pp. 57–81 ). Hillsdale, NJ: Lawrence Erlbaum.Google Scholar
  41. 41.
    Lohman, D. F. (1989). Human intelligence: An introduction to advances in theory and research. Review of Educational Research, 59, 333–373.Google Scholar
  42. 42.
    Mayer, R. E. (1989). Models for Understanding. Review of Educational Research, 59, 43–64.Google Scholar
  43. 43.
    Mayer, R., Dyck, J. L., & Vilberg, W. (1989). Learning to program and learning to think: What’s the connection? In E. Stolway & R.D. Spohrer (Eds.), Studying the Novice Programmer (pp. 83–111 ). Hillsdale, NJ: Lawrence Erlbaum.Google Scholar
  44. 44.
    Newell, A., & Simon, H. (1972). Human problem solving. New Jersey: Prentice Hall.Google Scholar
  45. 45.
    Norman, D. A. (1986). Reflections on cognition and parallel distributed processing. In D. E. Rumelhart, J. L. McCelland, & the PDP Research Group (Eds.), Parallel distributed processing: Vol. 2 Psychological and biological models (pp. 531–546 ). Cambridge, MA: MIT Press.Google Scholar
  46. 46.
    Osgood, C. E. (1949). The similarity paradox in human learning: A resolution. Psychological Review, 56, 132–143.PubMedCrossRefGoogle Scholar
  47. 47.
    Palumbo, D. B. (1990). Programming language/problem solving research: A review of relevant issues. Review of Educational Research, 60, 65–89.Google Scholar
  48. 48.
    Phye, G. B., & Andre, T. (1986). Cognitive classroom education: Understanding, thinking and problem solving. New York: Academic Press Google Scholar
  49. 49.
    Pribram, K. H. (1986). The role of analogy in transcending limits in the brain sciences. Journal of Educational Psychology, 75, 450–459.Google Scholar
  50. 50.
    Royer, J. M. (1979). Theories of the transfer of learning. Educational Psychologist, 14, 53–69.CrossRefGoogle Scholar
  51. 51.
    Rumelhart, D. E., & Norman, D. A. (1981). Analogical processes in learning. In J. R. Anderson (Ed.), Cognitive skills and acquisition. Hillsdale, NJ: Lawrence Erlbaum.Google Scholar
  52. 52.
    Rumelhart, D. E., & Norman, D. A. (1988). Representation in memory. In R. C. Atkinson, R. J. Herrastein, G. Lindzey, &R. D. Luce (Eds.), Steven’s handbook of experimental psychology, Second Edition, Volume 2: Learning and Cognition. New York: Wiley.Google Scholar
  53. 53.
    Salomon, G., & Gardner, H. (1984). The computer as educator: Lessons from television research. Educational Researcher, 13, 4–8.Google Scholar
  54. 54.
    Salomon, G., & Perkins, D. N. (1987). Transfer of cognitive skills from programming: When and how? Journal of Educational Computing Research, 3, 149–170.CrossRefGoogle Scholar
  55. 55.
    Schramm, W. (1977). Big Media: Little Media. Beverly Hills, CA: Sage.Google Scholar
  56. 56.
    Simon, D. P., & Simon, H. A. (1978). Individual differences in solving physics problems. In R. Siegler (Ed.), Children’s thinking: What develops? (pp. 325–348 ). Hillsdale, NJ: Lawrence Erlbaum.Google Scholar
  57. 57.
    Snow, R. E. (1986). Individual differences and the design of instructional programs. American Psychologist, 41, 1029–1039.CrossRefGoogle Scholar
  58. 58.
    Snow, R. E., & Lohman, D. F. (1984). Toward a theory of aptitude for learning from instruction. Journal of Educational Psychology, 76, 347–378.CrossRefGoogle Scholar
  59. 59.
    Spencer, R. M., & Weisberg, R. W. (1986). Context-dependent effects on analogical transfer. Memory & Cognition, 14, 442–449.CrossRefGoogle Scholar
  60. 60.
    Sugrue, B. M. (1991). A comparative review of European and American approaches to computer-based instruction in schools. In T. Schlechter (Ed.), Problems and promises of computer-based training. Norwood, NJ: Ablex.Google Scholar
  61. 61.
    Thorndike, E. L. (1903). Educational psychology. New York: Lemcke & Buechner.CrossRefGoogle Scholar
  62. 62.
    Tversky, A. (1977). Features of similarity. Psychological Review, 84, 327–352.CrossRefGoogle Scholar
  63. 63.
    Tversky, A., & Gati, I. (1978). Studies in similarity. In E. Rosch & B. B. Lloyd (Eds.), Cognition and categorization. Hillsdale, NJ: Lawrence Erlbaum.Google Scholar
  64. 64.
    Vosniadou, S., & Brewer, W. F. (1987). Theories of knowledge restructuring in development. Review of Educational Research, 57, 51–67.Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 1992

Authors and Affiliations

  • Richard E. Clark
    • 1
  1. 1.Educational PsychologyUniversity of Southern CaliforniaLos AngelesUSA

Personalised recommendations