Reading List

Version 2, 24 October 2003

  1. Ainsworth, S. A., P. Bibby, et al. (1997). Information technology and multiple representations: new opportunities - new problems. Journal of Information Technology for Teacher Education 6(1).
  2. Allwein, G. and J. Barwise, Eds. (1996). Logical Reasoning with Diagrams. Oxford, Oxford University Press.
  3. Anderson, J. R. (1998). The atomic components of thought. Mahwah, N.J., Lawrence Erlbaum Associates.
  4. Anderson, J., R., A. Corbett, T., et al. (1995). Cognitive Tutors: Lessons Learned. The Journal Of The Learning Sciences 4(2): 167-207.
  5. Barwise, J. and J. Etchemendy (1995). Heterogenous logic. Diagrammatic Reasoning: Cognitive and Computational Perspectives. J. Glasgow, N. H. Narayanan and B. Chandrasekaran. Menlo Park, CA, AAAI Press: 211-234.
  6. Bechtel, W., & Richardson, R. C. (1991). Discovering complexity: Decomposition and Localization as Strategies in Scientific Research. Princeton, NJ: Princeton University Press. 
  7. Bertin, J. (1983). Seminology of Graphics: Diagrams, Networks, Maps. Wisconsin, University of Wisconsin Press.
  8. Boden, M. (1991). The Creative Mind: Myths and Mechanisms. London: Weidenfeld and Nicholson.
  9. Bradshaw, G. (1992). The airplane and the logic of invention. In R. N. Giere (Eds.), Cognitive Models of Science (pp. 239-250). Minneapolis, MN: University of Minnesota Press
  10. Bradshaw, G. and M. Leinert (1991). The invention of the airplane. Proceedings of the Thirtheenth Annual Conference of the Cognitive Science Society. Hillsdale, NJ, Lawrence Erlbaum: 605-610.
  11. Campbell, P. (1960). Blind variation and selective retention in creative thought and in other knowledge processes. Psychological Review, 67, 380-400.
  12. Card, S. K. and A. Newell (1983). The Psychology of Human Computer Interaction. Hillsdale, New Jersey, Lawrence Erlbaum Assoc.
  13. Card, S., J. MacKinlay, et al., Eds. (1999). Information Visualization: Using Vision to Think. Mawah, N.J., Morgan Kaufmann.
  14. Casner, S. M. (1991). A task-analytic approach to the automated design of graphic presentations. ACM Trans. on Graphics 10(2): 111-151.
  15. Chi, M. T. H. (1992). Conceptual change within and across ontological categories: examples from learning and discovery in science. In R. N. Giere (Eds.), Cognitive models of science (pp. 129-186). Minneapolis: University of Minnesota Press.
  16. Chi, M. T. H. and J. D. Slotta (1993). The ontological coherence of intuitive physics. Commentary on A. diSessa's Toward an epistemology of physics. Cognition and Instruction 10(2 & 3): 249-260.
  17. Chi, M. T. H., J. D. Slotta, et al. (1994). From things to processes: A theory of conceptual change for learning science concepts. Learning and Instruction 4: 27-43.
  18. Chi, M. T. H., P. J. Feltovich, et al. (1981). Categorization and representation of physics problems by experts and novices. Cognitive Science 5: 121-152.
  19. Chi, M. T. H., R. Glaser, et al., Eds. (1988). The Nature of Expertise. Hillsdale, N.J., L. Erlbaum Associates.
  20. Chinn, C. A. and W. F. Brewer (1993). Factors that influence now people respond to anomalous data. Proceedings of the Fifthteenth Annual Conference of the Cognitive Science Society. M. Polson. Hillsdale, N.J., Lawrence Erlbaum: 318-321.
  21. Chinn, C. A., & Brewer, W. F. (1992). Psychological responses to anomalous data. In Proceedings of the Fourteenth Annual Conference of the Cognitive Science Society (pp. 165-170). Hillsdale, N.J.: Lawrence Erlbaum.
  22. Clement, J. (1988). Observed Methods for Generating Analogies in Scientific Problem Solving. Cognitive Science, 12, 563-586.
  23. Cleveland, W. S. (1985). The Elements of Graphing Data. Monterey, CA., Wadsworth.
  24. Cleveland, W. S. and R. McGill (1985). Graphical perception and graphical methods for analysing scientific data.
  25. Cleveland, W. S., & McGill, R. (1985). Graphical perception and graphical methods for analysing scientific data. Science, 229, 828-833.
  26. Cosmides, L. and J. Tooby (1996). Are humans good intuitive statisticians after all? Rethinking some conclusions from the literature on judgement under uncertainty. Cognition 58: 1-73.
  27. Cowan (2001). The Magical number 4 in short-term memory. Behavioral and Brain Sciences, 24(1), 128-129.
  28. Cronbach, L. J. (1957). The two disciplines of scientific psychology. American Psychologist, 12, 671-684.
  29. Dempsey, J. V., L. L. Haynes, et al. (2002). Forty simple computer games and what they could mean to educators. Simulation & Gaming 33(2): 157-168.
  30. diSessa, A. A. (1985). A principled design for an integrated computational environment. Human-Computer Interaction 1: 1-47.
  31. diSessa, A. A. (1993). Towards an Epistemology of Physics. Cognition and Instruction 10(2 & 3): 105-225.
  32. Dunbar, K. (1993). How scientists really reason: scientific reasoning in real-world laboratories. In R. J. Sternberg & J. Davidson (Eds.), Mechanisms of Insight Cambridge, M.A.: MIT Press.
  33. Egan, D. E., & Schwartz, B. J. (1979). Chunking in recall of symbolic drawings. Memory and Cognition, 7(2), 149-158.
  34. Eisenstadt, M., J. Domingue, et al. (1990). Visual knowledge engineering. IEEE Transactions on Software Engineering 116(10): 1164-1177.
  35. Either: (i) Shepard, R. N. (1978). Externalization of mental images and the act of creation. In B. S. Randhawa & W. E. Coffman (Eds.), Visual Learning, Thinking, and Communication. New York: Academic Press. Or (ii) Shepard, R. N. (1988). The imagination of the scientist. In K. Egan & D. Nadaner (Eds.), Imagination and Education. New York: Teachers College Press.
  36. Ericsson, K. A. and H. A. Simon (1993). Protocol analysis: verbal reports as data. Cambridge, Mass, MIT Press.
  37. Evans, J. S. B. T. (1992). Biases in thinking and judgement. In M. T. Keane & K. Gilhooly (Eds.), Advances in the Psychology of Thinking (pp. 95-125). Hemel Hempstead, Hertfordshire: Harvester-Wheatsheaf.
  38. Eysenck, M. W., & Keane, M. T. (1990). Cognitive Psychology: A Student's Handbook . Hove, East Sussex: Lawrence Erlbaum Associates.  Ch. 11)
  39. Feist, G. J., & Gorman, M. E. (1998). The psychology of science: review and integration of a nascent discipline. Review of general psychology, 2(1), 3-47.
  40. Finke, R. A. (1989). Principles of Mental Imagery. Cambridge, MA: The MIT Press. 
  41. Finke, R. A. (1990). Creative Imagery: Discoveries and Inventions in Visualization. Hillsdale, NJ: Lawrence Erlbaum Associates. 
  42. Franklin, A. (1989). The epistemology of experiment. In D. Gooding, T. Pinch, & S. Schaffer (Eds.), The Uses of Experiment: Studies in the Natural Sciences (pp. 437-460). Cambridge: Cambridge University Press.
  43. Gattis, M., & Holyoak, K. (1996). Mapping conceptual to spatial relations in visual reasoning. Journal of Experimental Psychology:  Learning, Memory and Cognition,  22(1), 231-239.
  44. Gelernter, H., J. R. Hansen, et al. (1960). Empirical explorations of the geometry-theorem proving machine. Western Joint Computer Conference (WJCC'60).
  45. Gentner, D. and A. L. Stevens, Eds. (1983). Mental Models. Hillsdale, NJ, Lawrence Erlbaum.
  46. Gentner, D. and D. R. Gentner (1983). Flowing waters or teeming crowds: Mental models of electricity. Mental Models. D. Gentner and A. L. Stevens. Hillsdale, NJ, Lawrence Erlbaum: 99-129.
  47. Giere, R. N. (1989). Explaining Science: a cognitive approach. Chicago, University of Chicago press.
  48. Giere, R. N. (1994). The cognitive structures of scientific theories. Philosophy of Science 61: 276-296.
  49. Giere, R. N., Ed. (1992). Cognitive models of science. Minneapolis, University of Minnesota Press.
  50. Gigerenzer, G. (1991). From tools to theories: a heuristic of discovery in cogntitive psychology. Psychological Review 98(2): 254-267.
  51. Gigerenzer, G. and P. M. Todd (1999). Simple heuristics that make us smart. Oxford, Oxford University Press.
  52. Gigerenzer, G., & Hoffrage, U. (1995). How to improve Bayesian reasoning without instruction: frequency formats. Psychological Review, 102(4), 684-704.
  53. Glasgow, J., Narayanan, N. H., & Chandrasekaran, B. (Ed.). (1995).  Diagrammatic Reasoning: Cognitive and Computational Perspectives. Menlo Park, CA:   AAAI Press.
  54. Glenberg, A. M., & Langston, W. E. (1992). Comprehension of illustrated text:  Pictures help to build mental models. Journal of Memory and Language, 31, 129-151.
  55. Glover, J. A., R. R. Ronning, et al., Eds. (1989). Handbook of Creativity. New York, NY, Plenum Press.
  56. Goel, V., & Pirolli, P. (1992). The structure of design problem spaces. Cognitive Science, 16(3), 395-429.
  57. Green, T. R. G. (1989). Cognitive dimensions of notations. People and Computers V. A. Sutcliffe and L. Maclaulay. Cambridge, Cambridge University Press.
  58. Gruber, H. E. (1989). Networks of enterprise in scientific creativity. In B. Gholson, W. R. j. Shadish, R. A. Neimeyer, & A. C. Houts (Eds.), The Psychology of Science: Contributions to Metascience (pp. 246-265). Cambridge: Cambridge University Press.
  59. Gruber, H. E. (1996). The Life Space of a Scientist:  The Visionary Function and Other Aspects of Jean Piaget's Thinking. Creativity Research Journal, 9(2 & 3), 251-265.
  60. Hacking, I. (1983). Representing and Intervening. Cambridge: Cambridge University Press.  (Part B, Chapters 9, 10, 11).
  61. Harre, R. (1983). Great Scientific Experiments. Oxford: Oxford University Press.  (All chapters are worth reading.)
  62. Hayes, J. R. (1989). Cognitive processes in creativity. In J. A. Glover, R. R. Ronning, & C. R. Reynolds (Eds.), Handbook of Creativity (pp. 135-145). New York, NY: Plenum Press. Glover, J. A., Ronning, R. R., & Reynolds, C. R. (Ed.). (1989).
  63. Hayes, J. R., & Simon, H. A. (1974). Understanding written problem instructions. In L.W. Gregg (Ed.), Knowledge and Cognition Hillsdale, N.J.: Erlbaum.
  64. Hayes, J. R., & Simon, H. A. (1977). Psychological differences among problem isomorphs. In N. J. Castellan, D. B. Pisoni, & G. R. Potts (Eds.), Cognitive theory Hillsdale, N.J.: Erlbaum.
  65. Hegarty, M. (1992). Mental Animation:  Inferring motion from static displays of mechanical systems. Journal of Experimental Psychology:  Learning, Memory and Cognition, 18, 1084-1102.
  66. Hegarty, M., & Just, M. A. (1993). Constructing mental models of machines from text and diagrams. Journal of Memory and Language, 32, 717-742.
  67. Hock, R. (1995).  Forty studies that changed psychology: explorations into the history of psychological research. Englewood Cliffs, N.J. : Prentice Hall. (All chapters are worth reading.)
  68. Holland, K., Holyoak, K., Nisbett, R., & Thagard, P. (1986). Induction: Processes of inference, learning, and discovery. Cambridge, MA: MIT Press.  (Scientific discovery, Chapter 11, p. 320-342)
  69. Kahneman, D., Slovic, P., & Tversky, A. (1982). Judgement Under Uncertainty. Cambridge: Cambridge University Press. 
  70. Kaplan, C. A., & Simon, H. A. (1990). In Search of Insight. Cognitive Psychology, 22(3).
  71. Kaput, J. J. (1989). Linking representations in systems of algebra. Research Issues in the Learning and Teaching of Algebra. S. Wagner and C. Kieran. Reston, VA, The National Council of Teachers of Mathematics. 4: 167-194.
  72. Kaput, J. J. (1992). Technology and Mathematics Education. Handbook of Research on Mathematics Teaching and Learning. D. A. Grouws. New York, NY, MacMillan: 515-556.
  73. Karmiloff-Smith, A. (1990). Constraints on representational change: evidence from children's drawings. Cognition, 34, 57-83.
  74. Karmiloff-Smith, A. (1992). Beyond Modularity: A developmental perspective on cognitive science. Cambridge, MA: MIT Press. 
  75. Klahr, D. (2000). Exploring Science: The Cognition and Development of Discovery Processes. Cambridge, MA: MIT Press.  (Chapter 2.)
  76. Klahr, D. and H. A. Simon (1999). Studies in scientific discovery: complementary approaches and convergent findings. Psychological bulletin 125: 524-543.
  77. Klahr, D., & Dunbar, K. (1988). Dual space search during scientific reasoning.  Cognitive Science, 12, 1-48.  Or Klahr, D. (2000). Exploring Science: The Cognition and Development of Discovery Processes. Cambridge, MA: MIT Press.  (Chapter 3 and 4.)
  78. Klahr, D., & Simon, H. A. (1999). Studies in scientific discovery: complementary approaches and convergent findings. Psychological bulletin, 125, 524-543.
  79. Klahr, D., P. Langley, et al. (1987). Production System Models of Learning and Development. Cambridge, Mass, MIT Press.
  80. Klayman, J. and Y.-W. Ha (1987). Confirmation, disconfirmation, and information in hypothesis testing. Psychological Review 94(2): 211-228.
  81. Klayman, J., & Ha, Y.-W. (1987). Confirmation, disconfirmation, and information in hypothesis testing. Psychological Review, 94(2), 211-228.
  82. Koedinger, K. R. (1992). Emergent properties and structural constraints : Advantages of diagrammatic representations for reasoning and learning. AAAI Technical Report on Reasoning with Diagrammatic Representations (SS-92-02). N. H. Narayanan. Menlo Park, CA, AAAI.
  83. Koedinger, K. R. and J. R. Anderson (1990). Abstract planning and perceptual chunks: Elements of expertise in geometry. Cognitive Science 14: 511-550.
  84. Kosslyn, S. M. (1989). Understanding charts and graphs. Applied cognitive psychology, 3, 185-226.
  85. Kotovsky, K., & Fallside, D. (1989). Representation and transfer in problem solving. In D. Klahr & K. Kotovsky (Eds.), Complex Information Processing: The Impact of Herbert A. Simon Hillsdale, New Jersey: Lawrence Erlbaum Associates.
  86. Kotovsky, K., Hayes, J. R., & Simon, H. A. (1985). Why are some problems hard? Cognitive Psychology, 17, 248-294.
  87. Kulkarni, D., & Simon, H. A. (1988). The processes of scientific discovery: The strategy of experimentation. Cognitive Science, 12, 139-75.
  88. Langley, P. (1981). Data Driven Discovery of Physical Laws.  Cognitive Science, 5, 31-54.
  89. Langley, P., H. A. Simon, et al. (1987). Scientific Discovery: Computation Explorations of the Creative Processes. Cambridge, MA, MIT Press.
  90. Langley, P., Zytkow, J. M., Simon, H. A., & Bradshaw, G. L. (1986).  The search for regularity: four aspects of scientific discovery.  In R.  S.  Michalski, J. G. Carbonell, & T. M. Mitchell (Eds.), Machine Learning An Artificial Intelligence Approach II Los Altos, CA: Morgan Kaufmann. 
  91. Langley, Simon, Bradshaw, & Zytkow (1987). Scientific Discovery : Computation Explorations of the creative processes.
  92. Langley, Simon, Bradshaw, & Zytkow (1987). Scientific Discovery: Computation Explorations of the creative processes.  (Chapter 3, p. 65-114); or (II) Simon, H. A., Langley, P., & Bradshaw, G. (1981). Scientific discovery as problem solving. Synthese, 47, 1-27; or (III) Langley, P. (1981). Data Driven Discovery of Physical Laws. Cognitive Science, 5, 31-54.
  93. Larkin, J. (1981). Cognition of learning physics. American Journal of Physics 49: 534-541.
  94. Larkin, J. H. (1983). The role of problem representation in physics. Mental Models. D. Gentner and A. L. Stevens. Hillsdale, New Jersey, Lawrence Earlbaum & Associates.
  95. Larkin, J. H. (1989). Display-based Problem Solving. In D. Klahr & K. Kotovsky (Eds.), Complex Information Processing: The Impact of Herbert A. Simon (pp. 319-341). Hillsdale, New Jersey: Lawrence Erlbaum Associates. 
  96. Larkin, J. H., & Simon, H. A. (1987). Why a diagram is (sometimes) worth ten thousand words. Cognitive Science, 11, 65-99.
  97. Larkin, J., J. McDermott, et al. (1980). Expert and Novice Performance in Solving Physics Problems. Science 208: 1335-42.
  98. Lohse, G. L. (1993). A cognitive model for understanding graphical perception. Human-Computer Interaction 8: 353-388.
  99. Lohse, G., K. Biolsi, et al. (1994). A classification of visual representations. Communications of the ACM 37(12): 36-49.
  100. Mayer, R. E. (1991). Thinking, Problem Solving, Cognition (2nd ed.). New York: Freeman. 
  101. Mayer, R. E. and J. K. Gallini (1990). When is an illustration worth ten thousand words? Journal of Educational Psychology 82(4): 715-726.
  102. McLean, R. S., & Gregg, L. W. (1967). Effects of induced chunking on temporal aspects of serial recitation. Journal of Experimental Psychology, 74, 455-459.
  103. Meehl, P. E. (1967). Theory-testing in psychology and physics: A methodological paradox. Philosophy of Science, 34, 103-115.
  104. Meehl, P. E. (1978). Theoretical risks and tabular asterisks; Sir Karl, Sir Ronald and the slow progress of soft psychology. Journal of Consulting and Clinical Psychology 46: 806-834.
  105. Mynatt, C. R., Doherty, M. E., & Tweney, R. D. (1978). Consequences of confirmation and disconfirmation in a simulated research environment. Quarterly Journal of Experimental Psychology, 30, 395-406.
  106. Newell, A. (1973). You can't play 20 questions with nature and win: Projective comments on the papers of this symposium. In W. G. Chase (Eds.), Visual Information Processing (pp. 283-308). New York, N.Y.: Academic Press.
  107. Newell, A. (1990). Unified theories of cognition. Cambridge, MA, Harvard University Press.
  108. Newell, A., & Simon, H. A. (1972). Human Problem Solving. Englewood Cliffs, NJ: Prentice-Hall.
  109. Newell, A., & Simon, H. A. (1976). Computer science as empirical enquiry: symbols and search. Communications of the Association for Computing Machinery 19(113-126.).
  110. Newell, A., & Simon, H. A. (1981). Computer science as empirical enquiry: symbols and search. Mind Design: Philosophy, Psychology and Artificial Intelligence. J. Haugland. Cambridge, MA, MIT Press: 35-66.
  111. Norman, D. A. (1988). The Psychology of Everyday Things. New York, NY, Basic Books.
  112. Norman, D. A. and S. W. Draper, Eds. (1986). User Centered System Design: New Perspectives on Human Computer Interaction. Hillsdale, N.J., Lawrence Erlbaum.
  113. Ohlsson, S. (1992). Information-processing explanations of insight and related phenomena. Advances in the Psychology of Thinking. M. T. Keane and K. Gilhooly. Hemel Hempstead, Hertfordshire, Harvester-Wheatsheaf. 1: 1-44.
  114. Okada, T. and H. A. Simon (1997). Collaborative discovery in a scientific domain. Cognitive Science 21(2): 109-146.
  115. Oliver, J. (1991). Incomplete Guide to the Art of Discovery. New York, Columbia University Press.
  116. Palmer, S. E. (1977). Hierarchical structure in perceptual representation. Cognitive Psychology 9: 441-474.
  117. Palmer, S. E. (1978). Fundamental aspects of cognitive representation. Cognition and Catergorization. E. Rosch and B. B. Lloyd. Hillsdale, N.J., Lawrence Erlbaum: 259-303.
  118. Pinker, S. (1990). A theory of graph comprehension. Artificial Intelligence and the Future of Testing. R. Freedle. Hillsdale, NJ, Lawrence Erlbaum: 73-126.
  119. Qin, Y. and H. A. Simon (1990). Laboratory replication of scientific discovery processes. Cognitive Science 14: 281-312.
  120. Reif (1987). Interpretation of scientific or mathematical concepts: Cognitive issues and instructional implications. Cognitive Science 11: 395-416.
  121. Reif, F. and J. I. Heller (1982). Knowledge structure and problem solving in physics. Educational Psychologist 17(2): 102-127.
  122. Rosewein, R. E. (1994). Social influence in science: agreement and dissent in achieving scientific consensus. In W. R. Shadish & S. Fuller (Eds.), The Social Psychology of Science (pp. 262-285). New York, NY: Guilford Press.
  123. Scaife, M., & Rogers, Y. (1996). External cognition: how do graphical representations work? International Journal of Human-Computer Studies, 45, 185-213.
  124. Schraagen, J. M. (1993). How experts solve a novel problem in experimental design. Cognitive Science, 17, 285-309.
  125. Shadish, W. R. j., A. C. Houts, et al. (1989). The psychology of science: an introduction. Psychology of Science: Contributions to the Meta-science. B. Gholson, W. R. j. Shadish, R. A. Neimeyer and A. C. Houts. Cambridge, Cambridge University Press: 1-16.
  126. Shrager, J. and P. Langley, Eds. (1990). Computational Models of Scientific Discovery and Theory Formation. San Mateo, CA, Morgan Kaufmann.
  127. Shunn, C. D. and D. Klahr (1996). The problem of problem spaces: When and how to go beyond a 2-space model of scientific discovery. Proceedings of the Eighteenth Annual Conference of the Cognitive Science Society. G. W. Cottrell. Mahwah, N.J., Lawrence Erlbaum: 25-26.
  128. Simon, H. A. (1966). Scientific discovery and the psychology of problem solving.  In H. A. Simon (Eds.), Models of Discovery and other topics in the methods of Science (pp. 286-303). Dordrect: Reidel.
  129. Simon, H. A. (1973). Does scientific discovery have a logic. Philosophy of Science, 40, 471-480. (Reprinted in H. A. Simon (Eds.), Models of Discovery and other topics in the methods of Science (pp. 326-337). Dordrect: Reidel.)
  130. Simon, H. A. (1973). The structure of ill-structured problems. Artificial Intelligence, 4, 181-201. (Reprinted in H. A. Simon (Ed.), Models of Discovery and other topics in the methods of Science (pp. 304-325). Dordrect: Reidel.
  131. Simon, H. A. (1975). The functional equivalence of problem solving skills. Cognitive Psychology, 7, 268-288.
  132. Simon, H. A. (1977). On judging the plausibility of theories. In H. A. Simon (Ed.), Models of Discovery and other topics in the methods of Science Dordrect: Reidel.
  133. Simon, H. A. (1980). How to win at twenty questions with nature. In R. A. Cole (Eds.), Perception and Production of Fluent Speech Hillsdale, N.J.: Erlbaum. (Reprinted in H. A. Simon (Ed.), Models of Thought (Vol.II) New Haven: Yale University Press.)
  134. Simon, H. A. (1981). Sciences of the Artificial (2nd ed.). Cambridge, MA: MIT Press.  (The Architecture of complexity, Chapter 7, p. 192-229) Or (ii) Simon, H. A. (1977). The organization of complex systems. In H. A. Simon (Eds.), Models of Discovery and Other Topics in the Methods of Science (pp. 245-261). Dordrect: Reidel.
  135. Simon, H. A. (1981). Sciences of the Artificial (2nd ed.). Cambridge, MA: MIT Press.  (The science of design, Chapter 5, p.129-159)
  136. Simon, H. A., & Hayes, J. R. (1976). The understanding process: Problem isomorphs. Cognitive Psychology, 8, 165-190.
  137. Simon, H. A., & Lea, G. (1974). Problem solving and rule induction: a unified view. In L. W. Gregg (Eds.), Knowledge and Cognition (pp. 105-127). Potomac, MA: Lawrence Erlbaum.
  138. Simonton, D. K. (1989). Chance-configuration theory of scientific creativity. In B. Gholson, W. R. jr. Shadish, R. A. Neimeyer, & A. C. Houts (Eds.), Psychology of Science: Contributions to the Meta-science (pp. 170-213). Cambridge: Cambridge University Press.
  139. Smith, S., Ward, T., & Finke, R. (1995). The Creative Cognition Approach. Cambridge, MA: MIT Press.
  140. Tabachneck-Schijf, H. J. M., A. M. Leonardo, et al. (1997). CaMeRa: A computational model of multiple representations. Cognitive Science 21(3): 305-350.
  141. Thagard, P. (1989). Explanatory coherence. Behavioral and Brain Sciences, 12(3), 435-67.  There are commentaries to this article; read some that look interesting (e.g., Cheng, P. C.-H., & Keane, M. T. (1989). Explaining explanatory coherence psychologically. Behavioral and Brain Science, 12(3), 470-471.)
  142. Thagard, P. (1992). Conceptual Revolutions. Princeton, N.J.: Princeton University Press. 
  143. Tufte, E. R. (1983). The visual display of quantitative information. Cheshire, Conn, Graphics Press.
  144. Tufte, E. R. (1989). Envisioning Information. Cheshire, CT, Graphics Press.
  145. Tukey, J. W. (1977). Exploratory data analysis. Reading, MA., Addison-Wesley.
  146. Tversky, B., J. Bauer Morrison, et al. (2002). Animation: can it faciliate? International Journal of Human-Computer Studies 57: 247-262.
  147. Tweney, R. D. (1989). A framework for the cognitive psychology of science. In B. Gholson, W. R. j. Shadish, R. A. Neimeyer, & A. C. Houts (Eds.), Psychology of Science: Contributions to the Meta-science (pp. 342-366). Cambridge: Cambridge University Press.
  148. Van Sommers, P. (1989). A system for drawing and drawing-related neuropsychology. Cognitive Neuropsychology, 6, 117-164.
  149. Vinter, A. (1999). How meaning modifies drawing behavior. Child Development, 70, 33-49.
  150. White, B. (1993). ThinkerTools: Causal models, conceptual change, and science education. Cognition and Instruction 10(1): 1-100.
  151. White, B. and J. Frederiksen (1990). Causal model progressions as a foundation for intelligent learning environments. Artificial Intelligence 24: 99-157.
  152. Wickelgren, Wayne A.  How to solve problems : elements of a theory of problems and problem solving.  (George Green Library: QA95 WIC).
  153. Wickens, C. D. (1993). Engineering psychology and human performance, 2nd ed. New York, HarperCollins.
  154. Wiser, M., & Carey, S. (1983). When heat and temperature were one. In D. Gentner & A. L. Stevens (Eds.), Mental Models. (pp. 267-297). Hillsdale, New Jersey: Lawrence Earlbaum & Associates.
  155. Zhang, J. (1996). A representational analysis of relational information displays. Internation Journal of Human Computer Studies 45: 59-74.
  156. Zhang, J. (1997). The nature of external representations in problem solving. Cognitive Science 21(2): 179-217.
  157. Zhang, J. (1997). The nature of external representations in problem solving. Cognitive Science, 21(2), 179-217.
  158. Zhang, J. and D. A. Norman (1993). A cognitive taxonomy of numeration systems. Proceedings of the Fifthteenth Annual Conference of the Cognitive Science Society. M. Polson. Hillsdale, N.J., Lawrence Erlbaum: 1098-1103.
  159. Zhang, J. and D. A. Norman (1994). A representational analysis of numeration systems. Cognition 57: 271-295.
  160. Zhang, J. and D. A. Norman (1994). The representation of relation information. Proceedings of the Sixteenth Annual Conference of the Cognitive Science Society. A. Ram and K. Eiselt. Hillsdale, NJ., Lawrence Erlbaum: 952-957.
  161. Zhang, J., & Norman, D. A. (1994). Representations in distributed cognition tasks. Cognitive Science, 18(1), 87-122.





Peter Cheng  24/10/03