Advertisement

Expertise und Instructional Design

  • Lai-Chong Law
  • Ka-Ming Patrick Wong
Chapter

Zusammenfassung

In diesem Kapitel diskutieren wir die Konsequenzen, die sich aus der aktuellen Expertiseforschung für die Gestaltung von Lernumgebungen, also für das Instructional Design, ergeben. Dazu stellen wir zunächst traditionelle Unterrichtstheorien sowie die Schwierigkeiten, die aufgrund der ihnen inhärenten epistemologischen Annahmen entstehen, im Abriß dar. Möglichkeiten zur Überwindung dieser Schwierigkeiten sind in verschiedenen Strömungen des Konstruktivismus zu sehen, die die Unterrichtsforschung derzeit in neue Bahnen lenken. Wir stellen Vorzüge und Probleme verschiedener konstruktivistisch orientierter Ansätze zur situierten Kognition in bezug auf Instructional Design dar und besprechen einige konkrete, daraus resultierende Unterrichtsmodelle.

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

Literatur

  1. Anderson, J. R. (1985). Cognitive psychology and its implications ( 2nd ed. ). New York: Freeman.Google Scholar
  2. Andrews, D. H. & Goodson, L. A. (1991). A comparative analysis of models of instructional design. In G. J. Anglin (Ed.), Instructional technology: Past, present, and future (pp. 133–155 ). Englewood: Libraries Unlimited.Google Scholar
  3. Anzai, Y. (1991). Learning and use of representations for physics expertise. In K. A. Ericsson and J. Smith (Eds.), Toward a general theory of expertise. Prospects and limits (pp. 64–92 ). Cambridge: Cambridge University Press.Google Scholar
  4. Becker, H. (1972). A school is a lousy place to learn anything in. American Behavioral Scientist, 16, 85–105.CrossRefGoogle Scholar
  5. Bednar, A. K., Cunningham, D., Duffy, T. M. & Perry, J. D. (1991). Theory into practice; How do we link? In G. J. Anglin (Ed.), Instructional technology: Past, present, and future (pp. 88–101 ). Englewood: Libraries Unlimited.Google Scholar
  6. Bereiter, C. (1990). Aspects of an educational learning theory. Review of Educational Research, 60 (4), 603–624.CrossRefGoogle Scholar
  7. Blumenfeld, P. C., Soloway, E., Marx, R. W., Krajcik, J. S., Guzdial, M. & Palincsar, A. (1991). Motivating project-based learning: Sustaining the doing, supporting the learning. Educational Psychologist, 26, 369–398.Google Scholar
  8. Bonner, J. (1988). Implications of cognitive theory for instructional design: Revisited. Educational Communication and Technology, 36 (1), 3–14.Google Scholar
  9. Bransford, J. D., Goldman, S. R. & Vye, N. J. (1991). Making a difference in people’s abilities to think: Reflections on a decade of work and some hopes for the future. In L. Okagaki and R. J. Sternberg (Eds.), Directors of development: Influences on the development of children’s thinking (pp. 147–180 ). Hillsdale, NJ: Erlbaum.Google Scholar
  10. Brown, J. S., Collins, A. & Duguid, P. (1989). Situated cognition and the culture of learning. Educational Researcher, 18 (1), 32–42.CrossRefGoogle Scholar
  11. Bullock, D. H. (1982). Behaviorism and NSPI: The erractically applied discipline. Performance and Instruction, 21 (3), 4–8, 11.Google Scholar
  12. Carroll, J. M. (1990). The Nurnberg funnel: Designing minimalist instruction for practical computer skill. Cambridge, MA: MIT Press.Google Scholar
  13. 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
  14. Chase, W. G. & Simon, H. A. (1973). The mind’s eye in chess. In W. G. Chase (Ed.), Visual information processing (pp. 215–281 ). New York: Academic Press.Google Scholar
  15. Chi, M. T. H., Glaser, R. & Farr, M. J. (Eds.). (1988). The nature of expertise. Hillsdale, NJ: Erlbaum.Google Scholar
  16. Chomsky, A. N. (1973). For reasons of state. New York: Pantheon.Google Scholar
  17. Clancey, W. J. (1987). Knowledge-based tutoring: The GUIDON program. Cambridge, MA: MIT Press.Google Scholar
  18. Clancey, W. J. (1988). Acquiring, representing, and evaluating a competence model of diagnostic strategy. In M. T. H. Chi, R. Glaser and M. J. Farr (Eds.), The nature of expertise (pp. 343–418 ). Hillsdale, NJ: Erlbaum.Google Scholar
  19. Clancey, W. J. (1991). The frame of reference problem in the design of intelligent machines. In K. VanLehn (Ed.), Architectures for intelligence (pp. 357–423 ). Hillsdale, NJ: Erlbaum.Google Scholar
  20. Clancey, W. J. (1992). Representations of knowing: In defense of cognitive apprenticeship. Journal of Artificial Intelligence, 3, 139–168.Google Scholar
  21. Clancey, W. J. (1993). Situated action: A neuropsychological interpretation response to Vera and Simon. Cognitive Science, 17, 87–116.CrossRefGoogle Scholar
  22. Clancey, W. J. & Joerger, K. (1990). A practical authoring shell for apprenticeship learning. In M. Gardner, J. G. Greeno, F. Reif, A. H. Schoenfeld, A. diSessa and E. Stage (Eds.), Toward a scientific practice of science education (pp. 141–161 ). Hillsdale, NJ: Erlbaum.Google Scholar
  23. Clark, R. E. (1989). Current progress and future directions for research in instructional technology. Educational Technology Research and Development, 37, 57–66.CrossRefGoogle Scholar
  24. Clark, R. E. (1992). Media use in education. In M. C. Alkin (Ed.), Encyclopedia of educational research (Vol. 1, pp. 805–814 ). New York: Macmillan.Google Scholar
  25. Cognition and Technology Group at Vanderbilt (1991). Technology and the design of generative learning environments. Educational Technology, 31 (5), 34–40.Google Scholar
  26. Cognition and Technology Group at Vanderbilt (1992). The Jasper series as an example of anchored instruction: Theory, program, description, and assessment data. Educational Psychologist, 27, 291–315.Google Scholar
  27. Cognition and Technology Group at Vanderbilt (1993). Anchored instruction and situated cognition revisited. Educational Technology, 33 (3), 52–70.Google Scholar
  28. Collins, A. (1990). Reformulating testing to measure learning and thinking. In N. Frederiksen, R. Glaser, A. Lesgold and M. G. Shafto (Eds.), Diagnostic monitoring of skill and knowledge acquisition (pp. 75–87 ). Hillsdale, NJ: Erlbaum.Google Scholar
  29. Collins, A. (1991). Cognitive apprenticeship and instructional technology. In L. Idol and B. F. Jones (Eds.), Educational values and cognitive instruction: Implications for reform (pp. 121–138 ). Hillsdale, NJ: Erlbaum.Google Scholar
  30. Collins, A. (in press). Design issues for learning environments. In S. Vosniadou, E. de Corte, R. Glaser and H. Mandl (Eds.), Technology-supported learning environments: International perspectives Hillsdale, NJ: Erlbaum.Google Scholar
  31. 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 honour of Robert Glaser (pp. 453–494 ). Hillsdale, NJ: Erlbaum.Google Scholar
  32. Collins, A. & Stevens, A. L. (1983). A cognitive theory of inquiry teaching. In C. M. Reigeluth (Ed.), Instructional design theories and models: An overview (pp. 247–278 ). Hillsdale, NJ: Erlbaum.Google Scholar
  33. Cooke, N. J. (1992). Modeling human expertise in expert systems. In R. R. Hoffman (Ed.), The psychology of expertise: Cognitive research and empirical AI (pp. 29–60 ). New York: Springer.CrossRefGoogle Scholar
  34. Cooper, P. A. (1993). Paradigm shifts in designed instruction: From behaviorism to cognitivism to constructivism. Educational Technology, 33 (5), 12–19.Google Scholar
  35. De Groot, A. D. (1965). Thought and choice and chess. The Hague: Mouton.Google Scholar
  36. Dewey, J. (1916). Democracy and education. New York: Macmillan.Google Scholar
  37. Dick, W. (1991). An instructional designer’s view of constructivism. Educational Technology, 31 (5), 41–44.Google Scholar
  38. Di Vesta, F. J. & Richer, L. P. (1987). Characteristics of cognitive engineering: The next generation of instructional systems. Educational Technology Research and Development, 35, 213–230.Google Scholar
  39. Dreyfus, H. L. & Dreyfus, S. E. (1988). Making a mind versus modeling the brain: Artificial intelligence hack at a branchpoint. In S. R. Graubard (Ed.), The artificial intelligence debate: False starts, real foundations (pp. 15–43 ). Cambridge, MA: MIT Press.Google Scholar
  40. Duffy, T. M. & Knuth, R. A. (1990). Hypermedia and instruction: Where is the match`? In D. H. Jonassen and H. Mandl (Eds.), Designing hypermedia for learning (pp. 199–225 ). Berlin: Springer.CrossRefGoogle Scholar
  41. Ericsson, K. A. & Charness, N. (1994). Expert performance: Its structure and acquisition. American Psychologist, 49, 725–747.CrossRefGoogle Scholar
  42. Ericsson, K. A. & Smith, J. (Eds.). (1991). Toward a general theory of expertise. Prospects and limits. Cambridge: Cambridge University Press.Google Scholar
  43. Fenstermacher, G. D. & Richardson, V. (1994). Promoting confusion in educational psychology: How is it done? Educational Psychologist, 29 (I), 49–55.CrossRefGoogle Scholar
  44. Fosnot, C. T. (1984). Media and technology in education: A constructivist view. Educational Communication and Technology, 32, 195–205.Google Scholar
  45. Gabrys, G., Weiner, A. & Lesgold, A. (1993). Learning by problem solving in a coached apprenticeship system. In M. Rabinowitz (Ed.), Cognitive science foundations of instruction (pp. 119–147 ). Hillsdale, NJ: Erlbaum.Google Scholar
  46. Gagné, R. M. (Ed.). (1987). Instructional technology: Foundations. Hillsdale, NJ: Erlbaum.Google Scholar
  47. Gagné, R. M. & Dick, W. (1983). Instructional psychology. Annual Review of Psychology, 34, 261–295.CrossRefGoogle Scholar
  48. Gerstenmaier, J. & Mandl, H. (1994). Wissenserwerb unter konstruktivistischer Perspektive (Forschungsbericht Nr. 33 ). München: Ludwig-Maximilians-Universität, Lehrstuhl für Empirische Pädagogik and Pädagogische Psychologie.Google Scholar
  49. Gibson, J. J. (1986). The theory of affordances. In J. J. Gibson (Ed.), The ecological approach to visual perception (pp. 127–143 ). Hillsdale, NJ: Erlbaum. (Original erschienen 1979 )Google Scholar
  50. Glaser, R. (1990). The reemergence of learning theory within instructional research. American Psychologist, 45 (I), 29–39.CrossRefGoogle Scholar
  51. Glaser, R. & Bassok, M. (1989). Learning theory and the study of instruction. Annual Review of Psychology, 40, 631–666.CrossRefGoogle Scholar
  52. Glasersfeld, E. A. von (1977). Radical constructivist view of knowledge. Symposium on constructivism and cognitive development conducted at the Annual Meeting of the AERA, New York.Google Scholar
  53. Gräsel, C. & Mandl, H. (1993). Förderung des Erwerbs diagnostischer Strategien in fallbasierten Lernumgebungen. Unterrichtswissenschaft, 21, 355–370.Google Scholar
  54. Greeno, J. G. (1989). Situations, mental models and generative knowledge. In D. Klahr and K. Kotovsky (Eds.), Complex information processing: The impact of Herbert A. Simon (pp. 285–318 ). Hillsdale, NJ: Erlbaum.Google Scholar
  55. Greeno, J. G. (1991). Mathematical cognition: Accomplishments and challenges in research. In R. R. Hoffman and D. S. Palermo (Eds.), Cognition and the symbolic processes: Applied and ecological perspectives (pp. 255–279 ). Hillsdale, NJ: Erlbaum.Google Scholar
  56. Gruber, H., Law, L.-C., Mandl, H. & Renkl, A. (in press). Situated learning and transfer. In P. Reimann and H. Spada (Eds.), Learning in humans and machines: Towards an interdisciplinary learning science Oxford: Elsevier.Google Scholar
  57. Harel, I. & Papert, S. (1992). Software design as a learning environment. In I. Harel and S. Papert (Eds.), Constructionism (pp. 41–84 ). Norwood, NJ: Ablex.Google Scholar
  58. Heinrich, R. (1984). The proper study of educational technology. Educational Communication and Technology Journal, 32, 67–87.Google Scholar
  59. Hoffman, R. R. (Ed.). (1992). The psychology of expertise: Cognitive research and empirical Al. New York: Springer.Google Scholar
  60. Honebein, P. C., Duffy, T. M. & Fishman, B. J. (1993). Constructivism and the design of learning environments: Context and authentic activities for learning. In T. M. Duffy, J. Lowyck & D. H. Jonassen (Eds.), Designing environments for constructive learning (pp. 87–108 ). Berlin: Springer.CrossRefGoogle Scholar
  61. Jonassen, D. H. (1990). Thinking technology: Toward a constructivist view of instructional design. Educational Technology, 30 (9), 32–34.Google Scholar
  62. Jonassen, D. H. (1991). Hypertext as instructional design. Educational Technology Research and Development, 39, 83–92.CrossRefGoogle Scholar
  63. Jonassen, D. H. (1992). Cognitive flexibility theory and its implications for designing CBI. In S. Dijkstra, H. P. M. Hein and J. J. G. van Merrienboer (Eds.), Instructional models in computer-based learning environments (pp. 385–403 ). Berlin: Springer.Google Scholar
  64. Jonassen, D. H., Campbell, J. P. & Davidson, M. E. (1994). Learning with media: Restructuring the debate. Educational Technology Research and Development, 42, 31–39.CrossRefGoogle Scholar
  65. Jonassen, D. H., Mayes, T. & McAleese, R. (1993). A manifesto for a constructivist approach to uses of technology in higher education. In T. M. Duffy. J. Lowyck & D. H. Jonassen (Eds.), Designing environments for constructive learning (pp. 231–247 ). Berlin: Springer.CrossRefGoogle Scholar
  66. Kommers, P. A. M., Jonassen, D. H. & Mayes, T. (1992). Cognitive tools for learning. Berlin: Springer.CrossRefGoogle Scholar
  67. Kozma, R. B. (1991). Learning with media. Review of Educational Research, 61, 179–211.CrossRefGoogle Scholar
  68. Lakoff, G. (1987). Women, fire, and dangerous things: What categories reveal about the mind. Chicago: Chicago University Press.Google Scholar
  69. Larkin, J. H., McDermott, J., Simon, D. P. & Simon, H. A. (1980). Models of competence in solving physics problems. Cognitive Science, 4, 317–345.CrossRefGoogle Scholar
  70. Lave, J. (1988). Cognition in practice: Mind, mathematics and culture in everyday life. Cambridge: Cambridge University Press.CrossRefGoogle Scholar
  71. Lave, J. (1990a). The culture of acquisition and the practice of understanding. In J. W. Stigler, R. A. Shweder and G. Herdt (Eds.), Cultural psychology: Essays on comparative human development (pp. 309–327 ). Cambridge: Cambridge University Press.CrossRefGoogle Scholar
  72. Lave, J. (1990b). Views of classroom: Implications for math and science learning research. In M. Gardner, J. G. Greeno, F. Reif, A. H. Schoenfeld, A. diSessa and E. Stage (Eds.), Toward a scientific practice of science education (pp. 251–263 ). Hillsdale, NJ: Erlbaum.Google Scholar
  73. Lave, J. (1991). Situating learning in communities of practice. In L. B. Resnick, J. M. Levine and S. D. Teasley (Eds.), Perspectives on socially shared cognition (pp. 63–82 ). Washington, DC: American Psychological Association.CrossRefGoogle Scholar
  74. Lave, J. & Wenger, E. (1991). Situated learning: Legitimate peripheral participation. Cambridge: Cambridge University Press.CrossRefGoogle Scholar
  75. Law, L.-C. (1994). Transfer of learning: Situated cognition perspectives (Research Report No. 32 ). München: Ludwig-Maximilians-Universität, Lehrstuhl für Empirische Pädagogik und Pädagogische Psychologie.Google Scholar
  76. Lebow, D. (1993). Constructivist values for instructional systems design: Five principles toward a new mindset. Educational Technology Research and Development, 41, 4–16.CrossRefGoogle Scholar
  77. Leinhardt, G. (1989). Math lessons: A contrast of novice and expert competence. Journal for Research in Mathematics Education, 20, 52–75.Google Scholar
  78. Linn, M. C. (1986). Science. In R. F. Dillon and R. J. Sternberg (Eds.), Cognition and instruction (pp. 155–204 ). San Diego, NY: Academic Press.Google Scholar
  79. Mandl, H., Gruber, H. & Renkl, A. (1993). Misconceptions and knowledge compartmentalization. In G. Strube and F. Wender (Eds.), The cognitive psychology of knowledge (pp. 161–176 ). Amsterdam: Elsevier.CrossRefGoogle Scholar
  80. Maturana, H. R. & Varela, F. J. (1987). Der Baum der Erkenntnis: Die biologischen Wurzeln des menschlichen Erkennens. Bern: Scherz.Google Scholar
  81. Merrill, M. D. (1994). The descriptive component display theory. In M. D. Merrill and D. G. Twitchell (Eds.), Instructional design theory (pp. 111–235 ). Englewood Cliffs, NJ: Educational Technology Publications.Google Scholar
  82. Merrill, M. D., Li, Z. & Jones, M. K. (1990). Second generational instructional design (ID:). Educational Technology, 30 (2), 7–14.Google Scholar
  83. Norman, D. A. (1993). Cognition in the head and in the world: An introduction to the special issue on situated action. Cognitive Science, 17, 1–6.CrossRefGoogle Scholar
  84. Palincsar, A. S. (1989). Less charted waters. Educational Researcher, 18 (4), 5–7.Google Scholar
  85. Papert, S. (1990). Introduction by Seymour Papert. In 1. Haret (Ed.), Constructionist learning (pp. 18 ). Boston: MIT Media Laboratory.Google Scholar
  86. Patel, V. L. & Groen, G. J. (1991). The general and specific nature of medical expertise: A critical look. In K. A. Ericsson and J. Smith (Eds.), Toward a general theory of expertise. Prospects and limits (pp. 93–125 ). Cambridge: Cambridge University Press.Google Scholar
  87. Perelman, L. J. (1992). School’s out. Hyperlearning, the new technology, and the end of education. New York: Morrow.Google Scholar
  88. Perkins, D. N. (1993). Person-plus: A distributed view of thinking and learning. In G. Salomon (Ed.), Distributed cognitions: Psychological and educational considerations (pp. 89–110 ). Cambridge: Cambridge University Press.Google Scholar
  89. Prawat, R. S. & Floden, R. E. (1994). Philosophical perspectives on constructivist views of learning. Educational Psychologist, 29 (1), 37–48.CrossRefGoogle Scholar
  90. Reigeluth, C. M. (Ed.). (1983). Instructional design: Theories and models. Hillsdale, NJ: Erlbaum.Google Scholar
  91. Reigeluth, C. M. (Ed.). (1987). Instructional theory in action. Hillsdale, NJ: Erlbaum.Google Scholar
  92. Resnick, L. B. (1987). Learning in school and out. Educational Researcher, 16 (9), 13–20.Google Scholar
  93. Resnick, L. B. (1989). Introduction. In L. B. Resnick (Ed.), Knowing, learning and instruction: Essays in honour of Robert Glaser (pp. 1–24 ). Hillsdale, NJ: Erlbaum.Google Scholar
  94. Resnick, L. B. (1991). Shared cognition: Thinking as social practice. In L. B. Resnick, J. M. Levine and S. D. Teasley (Eds.), Perspectives on socially shared cognition (pp. 1–20 ). Washington, DC: American Psychological Association.CrossRefGoogle Scholar
  95. Rogoff, B. (1990). Apprenticeship in thinking: Cognitive development in social context. New York: Oxford University Press.Google Scholar
  96. Salomon, G. & Perkins, D. N. (1989). Rocky roads to transfer: Rethinking mechanism of a neglected phenomenon. Educational Psychologist, 24, 113–142.CrossRefGoogle Scholar
  97. Salomon, G., Perkins, D. N. & Globerson, T. (1991). Partners u cognition: Extending human intelligence with intelligent technologies. Educational Researcher, 20 (3), 2–9.CrossRefGoogle Scholar
  98. Schön, D. A. (1983). The reflective practitioner: How professionals think in action. New York: Basic.Google Scholar
  99. Schön, D. A. (1987). Educating the reflective practitioner. San Francisco, CA: Jossey Bass.Google Scholar
  100. Schoenfeld, A. H. & Herrmann, D. (1982). Problem perception and knowledge structures in expert and novice mathematical problem solvers. Journal of Experimental Psychology: Learning, Memory, and Cognition, 8, 484–494.Google Scholar
  101. Seels, B. (1989). The instructional design movement in educational technology. Educational Technology, 29 (5), 11–15.Google Scholar
  102. Segal, J. W., Chipman, S. F. & Glaser, R. (Eds.). (1985). Thinking and learning skills. Vol. 1: Relating instruction to research. Hillsdale, NJ: Erlbaum.Google Scholar
  103. Shrock, S. A. (1991). A brief history of instructional development. In G. J. Anglin (Ed.), Instructional technology: Past, present, and future (pp. 11–19 ). Englewood: Libraries Unlimited.Google Scholar
  104. Simon, H. A. (1989). Models of thought (Vol. 2). New Haven, CT: Yale University Press.Google Scholar
  105. Soloway, E., Adelson, B. & Ehrlich, K. (1988). Knowledge and processes in the comprehension of computer programs. In M. T. H. Chi, R. Glaser and M. J. Farr (Eds.), The nature of expertise (pp. 129–152 ). Hillsdale, NJ: Erlbaum.Google Scholar
  106. Spiro, R. J. (1988). Cognitive flexibility theory: Advanced knowledge acquisition in ill-structured domains (Technical Report No. 441 ). Champaign, IL: Center for the Study of Reading.Google Scholar
  107. Spiro, R. J., Feltovich, P. J., Jacobson, M. J. & Coulson, R. L. (1991). Cognitive flexibility, constructivism, and hypertext: Random access instruction for advanced knowledge acquisition in ill-structured domains. Educational Technology, 31 (5), 24–33.Google Scholar
  108. Streibel, M. J. (1989). Instructional plans and situated learning: The challenge of Suchman’s theory of situated action for instructional designers and instructional systems. Proceedings of selected research papers presented at the Annual Meeting of the Association for Educational Communication and Technology ( Dallas, TX, February 1–5 ).Google Scholar
  109. Suchman, L. (1987). Plans and situated actions: The problem of human-machine communication. Cambridge: Cambridge University Press.Google Scholar
  110. Suchman, L. (1993). Responses to Vera and Simon’s situated action: A symbolic interpretation. Cognitive Science, 17, 71–75.CrossRefGoogle Scholar
  111. Tripp, S. D. (1993). Theories, traditions, and situated learning. Educational Technology, 33 (3), 7177.Google Scholar
  112. Vessey, I. (1988). Expert-novice knowledge organization: An empirical investigation using computer program recall. Behaviour and Information Technology, 7, 153–171.CrossRefGoogle Scholar
  113. Wineburg, S. S. (1991). Remembrance of theories past. In M. Yazdani and R. W. Lawler (Eds.), Artificial intelligence and education, (Vol. 2, pp. 276–282 ). Norwood, NJ: Ablex.Google Scholar
  114. Winn, W. (1989). Toward a rationale and theoretical basis for educational technology. Educational Technology Research and Development, 37, 35–46.CrossRefGoogle Scholar
  115. Winn, W. (1990). Some implications of cognitive theory for instructional design. Instructional Science, 19, 53–69.CrossRefGoogle Scholar
  116. Winn, W. (1993). A constructivist critique of the assumptions of instructional design. In T. M. Duffy, J. Lowyck & D. H. Jonassen (Eds.), Designing environments for constructive learning (pp. 189–212 ). Berlin: Springer.CrossRefGoogle Scholar
  117. Winograd, T. & Flores, F. (1986). Understanding computers and cognition: A new foundation for design. Norwood, NJ: Ablex.Google Scholar

Copyright information

© Springer Fachmedien Wiesbaden 1996

Authors and Affiliations

  • Lai-Chong Law
  • Ka-Ming Patrick Wong

There are no affiliations available

Personalised recommendations