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4 - Studies of Expertise from Psychological Perspectives

from PART II - OVERVIEW OF APPROACHES TO THE STUDY OF EXPERTISE – BRIEF HISTORICAL ACCOUNTS OF THEORIES AND METHODS

Paul J. Feltovich
Affiliation:
Florida Institute for Human and Machine Cognition (FIHMC)
Michael J. Prietula
Affiliation:
Goizueta Business School, Emory University
K. Anders Ericsson
Affiliation:
Department of Psychology, Florida State University
K. Anders Ericsson
Affiliation:
Florida State University
Neil Charness
Affiliation:
Florida State University
Paul J. Feltovich
Affiliation:
University of West Florida
Robert R. Hoffman
Affiliation:
University of West Florida
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Summary

Introduction

The study of expertise has a very long history that has been discussed in several other chapters in this handbook (Ericsson, Chapter 1; Amirault & Branson, Chapter 5). This chapter focuses on the influential developments within cognitive science and cognitive psychology that have occurred over the last three decades. Our chapter consists of two parts. In the first part we briefly review what we consider the major developments in cognitive science and cognitive psychology that led to the new field of expertise studies. In the second part we attempt to characterize some of the emerging insights about mechanisms and aspects of expertise that generalize across domains, and we explore the original theoretical accounts, along with more recent ones.

The Development of Expertise Studies

In this handbook there are several pioneering research traditions represented that were brought together to allow laboratory studies of expertise, along with the development of formal models that can reproduce the performance of the experts. One early stream was the study of thinking using protocol analysis, where participants were instructed to “think aloud” while solving everyday life problems (Duncker, 1945), and experts were asked to think aloud while selecting moves for chess positions (de Groot, 1946/1965; Ericsson, Chapter 13). Another stream developed out of the research on judgment and decision making, where researchers compared the judgments of experts to those of statistical models (Meehl, 1954; Yates & Tschirhart, Chapter 24).

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Publisher: Cambridge University Press
Print publication year: 2006

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References

Adelson, B. (1981). Problem solving and the development of abstract categories in programming languages. Memory and Cognition, 9, 422–433.CrossRef
Anderson, J. R. (Ed.) (1981). Cognitive skills and their acquisition. Hillsdale, NJ: Erlbaum.Google Scholar
Anderson, J. R. (1982). Acquisition of cognitive skill. Psychological Review, 89, 369–406.CrossRefGoogle Scholar
Anderson, J. R. (1987). Skill acquisition: Compilation of weak-method problem situations. Psychological Review, 94, 192–210.CrossRefGoogle Scholar
Austin, J. (2000). Performance analysis and performance diagnostics. In Austin, J. & Carr, J. E. (Eds.), Handbook of applied behavior analysis (pp. 321–349). Reno, NV: Context Press.Google Scholar
Baddeley, A. (2000). Short-term and working memory. In Tulving, E. & Craik, F. (Eds.), The Oxford handbook of memory (pp. 77–92). Oxford, UK: Oxford University Press.Google Scholar
Baddeley, A. (2002). Is working memory still working? European Psychologist, 7(2), 85–97.CrossRefGoogle Scholar
Barrows, H. S., Feightner, J. W., Neufeld, V. R., & Norman, G. R. (1978). Analysis of the clinical methods of medical students and physicians. Final Report, Ontario Department of Health Grants ODH-PR-273 & ODH-DM-226. Hamilton, Ontario: McMaster University.Google Scholar
Barrows, H. S., & Tamblyn, R. M. (1980). Problem-based learning: An approach to medical education. New York: Springer.Google Scholar
Barsalou, L. W. (1999). Perceptual symbol systems. Behavioral and Brain Sciences, 22, 577–660.Google ScholarPubMed
Barsalou, L. W., Simmons, W. K., Barbey, A. K., & Wilson, C. D. (2003). Grounding conceptual knowledge in modality-specific systems. TRENDS in Cognitive Sciences, 7(2), 84–91.CrossRefGoogle ScholarPubMed
Bartlett, F. (1932). Remembering. Cambridge, UK: Cambridge University Press.Google Scholar
Bartlett, F. (1958). Thinking. New York: Basic Books.Google Scholar
Berlyne, D. E. (1965). Structure and direction in thinking. Oxford, UK: Wiley.Google Scholar
Bloom, B. (Ed.) (1985). Developing talent in young people. New York: Ballentine.Google Scholar
Brown, A. (1991). A review of the tip-of-the-tongue experience. Psychological Bulletin, 109, 204–223.CrossRefGoogle ScholarPubMed
Brown, R. W., & MacNeill, D. (1966). The “tip of the tongue” phenomenon. Journal of Verbal Learning and Verbal Behavior, 5, 325–337.CrossRefGoogle Scholar
Bruner, J. S., Goodnow, J. J., & Austin, G. A. (1956). A study of thinking. New York: John Wiley and Sons.Google Scholar
Buchanan, B. G., & Feigenbaum, E. A. (1978). DENDRAL and MetaDENDRAL: Their applications dimension. Artificial Intelligence, 11(1), 5–24.CrossRefGoogle Scholar
Charness, N. (1976). Memory for chess positions: Resistance to interference. Journal of Experimental Psychology: Human Learning and Memory, 2, 641–653.Google Scholar
Charness, N. (1979). Components of skill in bridge. Canadian Journal of Psychology, 33, 1–50.CrossRefGoogle Scholar
Charness, N. (1981). Search in chess: Age and skill differences. Journal of Experimental Psychology: Human Perception and Performance, 7, 467–476.Google Scholar
Chase, W. G. (Ed.) (1973). Visual information processing. New York: Academic Press.Google Scholar
Chase, W. G., & Simon, H. A. (1973a). The mind's eye in chess. In Chase, W. G. (Ed.), Visual information processing. New York: Academic Press.Google Scholar
Chase, W. G., & Simon, H. A. (1973b). Perception in chess. Cognitive Psychology, 1, 33–81.Google Scholar
Chi, M. T. H. (1978). Knowledge structures and memory development. In Siegler, R. S. (Ed), Children's thinking: What develops? (pp. 73–96). Hillsdale, NJ: Erlbaum. Google Scholar
Chi, M. T. H., Feltovich, P., & Glaser, R. (1981). Categorization and representation of physics problems by experts and novices. Cognitive Science, 5, 121–152.CrossRefGoogle Scholar
Chi, M. T. H., Glaser, R., & Farr, M. J. (Eds.) (1988). The nature of expertise. Hillsdale, NJ: Erlbaum.Google Scholar
Chiesi, H. L., Spilich, G. J., & Voss, J. F. (1979). Acquisition of domain-related information in relation to high and low domain knowledge. Journal of Verbal Learning and Verbal Behavior, 18, 257–274.CrossRefGoogle Scholar
Chomsky, N. (1957). Syntactic structures. The Hague: Mouton.Google Scholar
Clancey, W. J. & Letsinger, R. (1984). NEOMYCIN: Reconfigure a rule-based expert system for application to teaching. In Clancey, W. J. & Shortliffe, E. H., (eds.), Readings in medical artificial intelligence (pp. 361–381). Readings Addision.Google Scholar
Clancey, W. J., & Shortliffe, E. H. (1984). Readings in medical artificial intelligence: The first decade. Reading, MA: Addison-Wesley.Google Scholar
Cowan, N. (2001). The magical number 4 in short-term memory: A reconsideration of mental storage capacity. Behavioral and Brain Sciences, 24, 87–185.CrossRefGoogle ScholarPubMed
Cowan, N., Chen, Z., & Rouder, J. (2004). Constant capacity in an immediate serial-recall task: A logical sequel to Miller (1956). Psychological Science, 15(9), 634–640.CrossRefGoogle Scholar
Groot, A. (1946). Het denken van den schaker. Amsterdam: Noord-Hllandsche Uit. Mij.Google Scholar
Groot, A. (1965). Thought and choice in chess, 1st Edition. The Hague: Mouton.Google Scholar
Duncker, K. (1945). On problem solving. Psychological Monographs, 58 (Whole No. 270), 1–113.CrossRefGoogle Scholar
Ebbinghaus, H. (1885/1964). Memory: A contribution to experimental cognitive psychology (Henry A. Ruger & Clara E. Bussenius, Trans.). New York: Dover.Google Scholar
Egan, D. E., & Schwartz, B. J. (1979). Chunking in recall of symbolic drawings. Memory and Cognition, 7, 149–158.CrossRefGoogle ScholarPubMed
Eisenstadt, M., & Kareev, Y. (1979). Aspects of human problem solving: The use of internal representations. In Norman, D. A. & Rumelhart, D. E. (Eds.), Exploration in cognition. San Francisco: W. H. Freeman.Google Scholar
Elstein, A. S., Shulman, L. S., & Sprafka, S. A. (1978). Medical problem solving. Cambridge, MA: Harvard University Press.CrossRefGoogle Scholar
Engle, R. W., & Bukstel, L. (1978). Memory processes among bridge players of differing expertise. American Journal of Psychology, 91, 673–89.CrossRefGoogle Scholar
Ericsson, K. A. (Ed.) (1996a). The road to excellence: The acquisition of expert performance in the arts and sciences, sports, and games. Mahwah, NJ: Erlbaum.Google Scholar
Ericsson, K. A. (1996b). The acquisition of expert performance: An introduction to some of the issues. In Ericsson, K. A. (Ed.), The road to excellence: The acquisition of expert performance in the arts and sciences, sports, and games (pp. 1–50). Mahwah, NJ: Erlbaum.Google Scholar
Ericsson, K. A. (2003). The acquisition of expert performance as problem solving: Construction and modification of mediating mechanisms through deliberate practice. In Davidson, J. E. & Sternberg, R. J. (Eds.), Problem solving (pp. 31–83). New York: Cambridge University Press.Google Scholar
Ericsson, K. A., & Kintsch, W. (1995). Long-term working memory. Psychological Review, 102, 211–245.CrossRefGoogle ScholarPubMed
Ericsson, K. A., & Kintsch, W. (2000). Shortcomings of generic retrieval structures with slots of the type that Gobet (1993) proposed and modeled. British Journal of Psychology, 91, 571–588.CrossRefGoogle Scholar
Ericsson, K. A., & Kirk, E. P. (2001). The search for fixed generalizable limits of “pure STM” capacity: Problems with theoretical proposals based on independent chunks. Behavioral and Brain Sciences, 24, 120–121.CrossRefGoogle Scholar
Ericsson, K. A., Krampe, R. T., & Tesch-Römer, C. (1993). The role of deliberate practice in the acquisition of expert performance. Psychological Review, 100, 363–406.CrossRefGoogle Scholar
Ericsson, K. A., & Lehmann, A. C. (1996). Expert and exceptional performance: Evidence on maximal adaptations on task constraints. Annual Review of Psychology, 47, 273–305.CrossRefGoogle ScholarPubMed
Ericsson, K. A., Patel, V. L., & Kintsch, W. (2000). How experts' adaptations to representative task demands account for the expertise effect in memory recall: Comment on Vicente and Wang (1998). Psychological Review, 107, 578–592.CrossRefGoogle Scholar
Ericsson, K. A., & Smith, J. (Eds.) (1991a). Toward a general theory of expertise: Prospects and limits. Cambridge, MA: Cambridge University Press.Google Scholar
Ericsson, K. A., & Smith, J. (1991b). Prospects and limits in the empirical study of expertise: An introduction. In Ericsson, K. A. and Smith, J. (Eds.), Toward a general theory of expertise: Prospects and limits (pp. 1–38). Cambridge, MA: Cambridge University Press.
Ernst, G., & Newell, A. (1969). GPS: A case-study in generality and problem solving. New York: Academic Press.Google Scholar
Feltovich, P., Ford, K. M., & Hoffman, R. R. (Eds.) (1997). Expertise in context: Human and Machine. Menlo Park, CA: AAAI Press.Google Scholar
Feltovich, P. J., Johnson, P. E, Moller, J., & Swanson, D. (1984). The role and development of medical knowledge in diagnostic reasoning. In. Clancey, W. & Shortliffe, E. (Eds.), Readings in medical artificial intelligence: The first decade (pp. 275–319). Reading, MA: Addison Wesley.Google Scholar
Feltovich, P., Spiro, R., & Coulson, R. (1997). Issues of expert flexibility in contexts characterized by complexity and change. In Feltovich, P., Ford, K., & Hoffman, R. (Eds.), Expertise in context: Human and machine. Menlo Park, CA: AAAI Press.Google Scholar
Ferster, C. B., & Skinner, B. F. (1957). Schedules of reinforcement. New York: Appleton-Century-Crofts. CrossRefGoogle ScholarPubMed
Fitts, P. M., & Posner, M. I. (1967). Human performance. Belmont, CA: Brookes Cole.Google Scholar
Flavell, J. (1979). Metacognition and cognition monitoring: A new area of cognitive-developmental inquiry. American Psychologist, 34, 906–911.CrossRefGoogle Scholar
Forbus, K. D. & Feltovich, P. J. (2001), Smart machines in education. Menlo PK, CA: AAAI/MIT Press. Google Scholar
Gentner, D. (1988). Metaphor as structure-mapping: The relational shift. Child Development, 59, 47–59.CrossRefGoogle Scholar
Glaser, R. (1976). Cognition and instructional design. In Klahr, D. (Ed.), Cognition and instruction (pp. 303–315). Hillsdale, NJ: Erlbaum. Google Scholar
Glaser, R., & Chi, M. T. H. (1988). Overview. In Chi, M. T. H., Glaser, R., & Farr, M. J. (Eds.), The nature of expertise (pp. ⅹⅴ-ⅹⅹⅷ). Hillsdale, NJ: Erlbaum.Google Scholar
Gobet, F., & Simon, H. A. (1996). Templates in chess memory: A mechanism for recalling several boards. Cognitive Psychology, 31, 1–40.CrossRefGoogle ScholarPubMed
Green, C. (1969). The application of theorem proving to question-answering systems. Doctoral dissertation Dept. of Electrical Engineering, Stanford University. Also Standford Artificial Intelligence Project Memo AI-96, June 1969.CrossRefGoogle Scholar
Groen, G. J., & Patel, V. L. (1988). The relationship between comprehension and reasoning in medical expertise. In Chi, M. T. H., Glaser, R., & Farr, M. J. (Eds.), The nature of expertise (pp. 287–310). Hillsdale, NJ: Erlbaum.Google Scholar
Hambrick, D., & Engle, R. (2002). Effects of domain knowledge, working memory capacity, and age on cognitive performance: An investigation of the knowledge-is-power hypothesis. Cognitive Psychology, 44, 339–387.CrossRefGoogle ScholarPubMed
Hatano, G., Miyake, Y., & Binks, M. B. (1977). Performance of expert abacus operators. Cognition, 5, 57–71.CrossRefGoogle Scholar
Hinsley, D., Hayes, J., & Simon, H. A.(1978). From words to equations: Meaning and representation in algebra word problems. In Just, M. & Carpenter, P. (Eds.), Cognitive processes in comprehension. Hillsdale, NJ: Erlbaum.Google Scholar
Hoffman, R. R. (Ed.) (1992). The psychology of expertise. New York: Springer-Verlag.CrossRefGoogle Scholar
Holyoak, K. J. (1991). Symbolic connectionism: toward third generation theories of expertise. In Ericsson, K. A. & Smith, J. (Eds.), Toward a general theory of expertise: Prospects and limits (pp. 301–335). Cambridge, MA: Cambridge University Press.Google Scholar
Jakobovits, L. A. & Miron, M. S. (1967). Readings in the Psychology of language. Englewood, cliffs, NJ: Prentice-Hall.Google Scholar
Jansma, J., Ramsey, N., Slagter, H., & Kahn, R. (2001). Functional anatomical correlates of controlled and automatic processing. Journal of Cognitive Neuroscience, 13(6), 730–743.CrossRefGoogle ScholarPubMed
Jeffries, R., Turner, A. A., Polson, P. G, & Atwood, M. E. (1981). The processes involved in software design. In Anderson, J. R. (Ed.), Cognitive skills and their acquisition. Hillsdale, NJ: Erlbaum. Google Scholar
Johnson, P. E., Duran, A. S., Hassebrock, F., Moller, J., Prietula, M. J., Feltovich, P. J., & Swanson, D. B. (1981). Expertise and error in diagnostic reasoning. Cognitive Science, 5, 235–283.CrossRefGoogle Scholar
Klein, G. A. (1998). Sources of power: How people make decisions. Cambridge, MA: MIT Press.Google Scholar
Klein, G. A., & Hoffman, R. R. (1993). Seeing the invisible: Perceptual-cognitive aspects of expertise. In Rabinowitz, M. (Ed.), Cognitive science foundations of instruction. Hillsdale, NJ: Erlbaum. Google Scholar
Koschmann, T. D., LeBaron, C., Goodwin, C., & Feltovich, P. J. (2001). Dissecting common ground: Examining an instance of reference repair. In Proceedings of the 23rd Conference of the Cognitive Science Society. Mahwah, NJ: Erlbaum.Google Scholar
Kruger, J., & Dunning, D. (1999). Unskilled and unaware of it: How difficulties in recognizing one's own incompetence lead to inflated self-assessments. Journal of Personality and Social Psychology, 77, 1121–1134.CrossRefGoogle ScholarPubMed
Kuiper, R., & Pesut, D. (2004). Promoting cognitive and metacognitive reflective reasoning skills in nursing practice: Self-regularities learning theory. Journal of Advanced Nursing, 45, 381–391.CrossRefGoogle ScholarPubMed
Larkin, J., McDermott, J., Simon, D. & Simon, H. A. (1980). Expert and novice performance in solving physics problems. Science, 208, 1335–1342.CrossRefGoogle ScholarPubMed
Lamme, V. (2003). Why visual attention and awareness are different. Trends in Cognitive Sciences, 7(1), 12–18.CrossRefGoogle ScholarPubMed
Lesgold, A. M., & Resnick, L. (1982). How reading difficulties devlop: Perspectives from a longitudinal study. In Das, J., Mulcahey, R., & wall, A. (Eds.), Theory and research in learning disabilities (pp. 155–187). New York: Plenum Press. CrossRef
Lesgold, A. M., Rubinson, H., Feltovich, P. J., Glaser, R., Klopfer, D., & Wang, Y. (1988). Expertise in a complex skill: Diagnosing x-ray pictures. In Chi, M. T. H., Glaser, R., & Farr, M. J. (Eds.), The nature of expertise (pp. 311–342). Hillsdale, NJ: Erlbaum. Google Scholar
Logan, G. (1985). Skill and automaticity: Relations, implications and future directions. Psychological Review, 95, 492–527.CrossRefGoogle Scholar
Lumsdaine, A. A., & Glaser, R. (1960). Teaching machines and programmed learning: A source book. Washington, DC: National Education Assoc. Google Scholar
McKeithen, K. B., Reitman, J. S., Reuter, H. H., & Hirtle, S. C., (1981). Knowledge organization and skill differences in computer programmers. Cognitive Psychology, 13, 307–325.CrossRefGoogle Scholar
Meehl, P. E. (1954). Clinical versus statistical prediction: A theoretical analysis and a review of the evidence. Minneapolis: University of Minnesota Press.CrossRefGoogle Scholar
Meyer, D. E., & Kieras, D. E. (1997). A computational theory of executive cognitive processes and multiple-task performance: Part 2. Accounts of psychological refractory-period phenomena. Psychological Review, 104, 749–791.CrossRefGoogle Scholar
Miller, G. A. (1956). The magical number seven plus or minus two: Some limits on our capacity for processing information. Psychological Review, 63, 81–97.CrossRefGoogle ScholarPubMed
Miller, G. A., Galanter, E., & Pribram, K. H. (1960). Plans and the structure of behavior. New York: Holt, Rinehart & Winston.CrossRefGoogle Scholar
Neisser, U. (1967). Cognitive psychology. New York: Appleton-Century-Crofts.Google Scholar
Newell, A. (1973). Artificial intelligence and the concept of mind. In Schank, R. C. & Colby, K. M. (Eds.), Computer models of language and thought (pp. 1–60). San Franciso: W. H. Freeman.Google Scholar
Newell, A., & Simon, H. A. (1956). The logic theory machine: A complex information processing system. IRE Transactions on Information Theory, Vol IT-2, No. 3, 61–79.CrossRefGoogle Scholar
Newell, A., & Simon, H. A. (1972). Human problem solving. Englewood Cliffs, NJ: Prentice Hall.Google Scholar
Newell, A., & Simon, H. A. (1976). Computer science as empirical inquiry: Symbols and search. Communications of the ACM, 19(3), 113–126.CrossRefGoogle Scholar
Norman, D. A., Rumelhart, D. E., & the LNR group (1979). Explorations in cognition. San Francisco: W. H. Freeman.Google Scholar
Osgood, C. E. (1963). On understanding and creating sentences. American Psychologist, 18, 735–751.CrossRefGoogle Scholar
Paris, S., & Winograd, P. (1990). How metacognition can promote academic learning and instruction. In Jones, B. & Idol, L. (Eds.), Dimensions of thinking and cognitive instruction (pp. 15–51). Hillsdale, NJ: Erlbaum.Google Scholar
Patel, V. L., Arocha, J. F., & Kaufman, D. R. (1994). Diagnostic reasoning and medical expertise. In Medin, D. (Ed.), The psychology of learning and motivation. Vol. 30 (pp. 187–251). New York: Academic Press.Google Scholar
Patel, V. L., & Groen, G. J. (1991). The general and specific nature of medical expertise: A critical look. In Ericsson, K. A. & Smith, J. (Eds.), Toward a general theory of expertise (pp. 93–125). Cambridge, MA: Cambridge University Press.Google Scholar
Patil, R. S., Szolovitz, P., & Schwartz, W. B. (1981). Causal understanding of patient illness in medical diagnosis. In Proceedings of the seventh international conference on artificial intelligence. Vol. 2 (pp. 893–899). Los Altos, CA: William Kaufman.Google Scholar
Pauker, S. G., Gorry, G. A., Kassirer, J. P., & Schwartz, W. B. (1976). Towards simulation of clinical cognition: Taking a present illness by computer. American Journal of Medicine, 60, 981–996.CrossRefGoogle Scholar
Pellegrino, J. W., & Glaser, R. (1982a). Improving the skills of learning. In Detterman, D. K. & Sternberg, R. J. (Eds.), How much and how can intelligence be increased. Norwood, NJ: Ablex.Google Scholar
Pellegrino, J. W., & Glaser, R. (1982b). Analyzing aptitudes for learning: Inductive reasoning. In Glaser, R. (Ed.), Advances in instructional psychology. Vol. 2 (pp. 269–345). Hillsdale, NJ: Erlbaum.
Perfetti, C. A., & Lesgold, A. M. (1979). Coding and comprehension in skilled reading. In Resnick, L. B. & Weaver, P. (Eds.), Theory and practice of early reading. Hillsdale, NJ: Erlbaum.Google Scholar
Phelps, R. H., & Shanteau, J. (1978). Livestock judges: How much information can an expert use? Organizational Behavior and Human Performance, 21, 209–219.CrossRefGoogle Scholar
Petrusa, E. R. (2002). Clinical performance assessments. In Norman, G. R., Vleuten, C. P. M., & Neuble, D. I. (Eds.), International handbook of research in medical education. Dordrecht: Kluwer Academic Publishers.CrossRefGoogle Scholar
Posner, M., & Snyder, C. (1975). Attention and cognitive control. In Solso, R. L. (Ed.), Information processing and cognition: The Loyola symposium. Hillsdale, NJ: Erlbaum.Google Scholar
Prietula, M., & Augier, M. (2005). Adventures in software archeology: Seeking (ABTOF) theory in the code. Proceedings of the 2005 Annual Academy of Management Meeting, August 5–10, Honolulu HI.Google Scholar
Prietula, M., & Simon, H. (1989). The experts in your midst. Harvard Business Review, Jan–Feb, 120–124.Google Scholar
Quillian, R. (1969). The teachable language comprehender: A Simulation program and theory of language. Communications of the ACM, 12 459–476.CrossRefGoogle Scholar
Reder, L., & Shunn, C. (1996). Metacognition does not imply awareness: Strategy choice is governed by implicit learning and memory. In Reder, L. (Ed.), Implicit memory and metacognition. Mahwah, NJ: Erlbaum.Google Scholar
Reitman, J. (1976). Skilled perception in GO: Deducing memory structure from inter-response times. Cognitive Psychology, 8, 336–356.CrossRefGoogle Scholar
Reitman, W. R. (1965). Cognition and thought. New York: Wiley.Google Scholar
Richman, H. B., Gobet, F., Staszewski, J. J., & Simon, H. A. (1996). Perceptual and memory processes in the acquisition of expert performance: The EPAM model. In Ericsson, K. A. (Ed.), The road to excellence: The acquisition of expert performance in the arts and sciences, sports, and games (pp. 167–187). Mahwah, NJ: Erlbaum.Google Scholar
Rieger, M. (2004). Automatic keypress activation in skilled typists. Journal of Experimental Psychology: Human Perception and Performance, 3, 555–565.Google Scholar
Rumelhart, D. E. (1979). Analogical processes and procedunal representations. CHIP Report # 81. Center for Human Information Processing, Univ. California, San Diego: February, 1979.Google Scholar
Sacerdoti, E. D. (1977). A structure for plans and behavior. New York: Elsevier-North Holland Publishing.Google Scholar
Salthouse, T. A. (1991). Expertise as the circumvention of human processing limitations. In Ericsson, K. A. and Smith, J. (Eds.), Toward a general theory of expertise: Prospects and limits (pp. 286–300). Cambridge, MA: Cambridge University Press.Google Scholar
Samuel, A. L. (1959). Some studies in machine learning using the game of checkers. IBM Journal of Research and Development, 3, 210–229.CrossRefGoogle Scholar
Schneider, W., & Fisk, A. (1982). Concurrent automatic and controlled visual search: Can processing occur without resource cost? Journal of Experimental Psychology, 8, 261–278.Google Scholar
Schneider, W., & Shiffrin, R. M. (1977). Controlled and automatic human information processing: 1. Detection, search and attention. Psychological Review, 84, 1–66.CrossRefGoogle Scholar
Schmidt, J. A., McLaughlin, J. P., & Leighton, P. (1989). Novice strategies for understanding paintings. Applied Cognitive Psychology, 3, 65–72.CrossRefGoogle Scholar
Schumacher, E. H., Seymour, T. L., Glass, J. M., Fencsik, D. E., Lauber, E. J., Kieras, D. E., & Meyer, D. E. (2001). Virtually perfect time sharing in dual-task performance: Uncorking the central cognitive bottleneck. Psychological Science, 12, 101–108.CrossRefGoogle ScholarPubMed
Shaffer, L. H. (1975). Multiple attention in continuous verbal tasks. In Rabbitt, P. M. A. & Dornic, S. (Eds.) Attention and performance V. New York: Academic Press.Google Scholar
Shiffrin, R. M., & Schneider, W. (1977). Controlled and automatic human information processing: II. Perceptual learning, automatic attending and a general theory. Psychological Review, 84, 127–189.CrossRefGoogle Scholar
Shipp, S. (2004). The brain circuitry of attention. Trends in Cognitive Sciences, 8, 223–230.CrossRefGoogle Scholar
Shortliffe, E. H. (1976). Computer-based medical consultations: MYCIN. New York: American Elsevier.Google Scholar
Simon, H. A., & Chase, W. G. (1973). Skill in chess. American Scientist, 61, 394–403.Google Scholar
Simon, H. A., & Newell, A. (1958). Heuristic problem solving: The next advance in operations research. Operations Research, 6, 1–10.CrossRefGoogle Scholar
Skinner, B. F. (1960). The science of learning and the art of teaching. In Lumsdaine, A. A. & Glaser, R. (Eds.), Teaching machines and programmed learning: A source book (pp. 99–113). Washington, DC: National Education Assoc. Google Scholar
Sleeman, D., & Brown, J. S. (1982). Intelligent tutoring systems. New York: Academic Press.Google Scholar
Spelke, E., Hirst, W., & Neisser, U. (1976). Skills of divided attention. Cognition, 4, 215–30.CrossRefGoogle Scholar
Spilich, G. J., Vesonder, G. T., Chiesi, H. L., & Voss, J. F. (1979). Text processing of domain-related information for individuals with high and low domain knowledge. Journal of Verbal Learning and Verbal Behavior, 14, 506–522.Google Scholar
Spiro, R. J., Collins, B. P. Thota, J. J., & Feltovich, P. J. (2003). Cognitive flexibility theory: Hypermedia for complex learning, adaptive knowledge application, and experience acceleration. Educational technology, 44, 5–10.Google Scholar
Starkes, J. L., & Allard, F. (Eds.) (1993). Cognitive issues in motor expertise. Amsterdam: North Holland.Google Scholar
Starkes, J., & Ericsson, K. A. (Eds.) (2003). Expert performance in sport: Recent advances in research on sport expertise. Champaign, IL: Human Kinetics.Google Scholar
Steier, D., & Mitchell, T. (Eds) (1996). Knowledge matters: A tribute to Allen Newell. Mahwah, NJ: Erlbaum.Google Scholar
Sternberg, R. (1984). Toward a triarchic theory of human intelligence. Behavioral and Brain Sciences, 7, 269–287.CrossRefGoogle Scholar
Tulving, E. (1994). Forward. In Metcalfe, J. & Shimamura, A. (Eds.), Metacognition: Knowing about knowing. Cambridge, MA: MIT Press.Google Scholar
Van Gelder, T., & Port, R. (1995). It's about time: An overview of the dynamical approach to cognition. In Gelder, T. & Port, R. (Eds.), Mind as motion (pp 1–43). Cambridge, MA: MIT Press.Google Scholar
VanLehn, K., & Brown, J. S. (1979). Planning nets: A representation for formalizing analogies and semantic models of procedural skills. In Snow, R. E. & Montague, W. E. (Eds.), Aptitude, learning and instruction: Cognitive process analyses. Hillsdale, NJ: Erlbaum. Google Scholar
Voss, J. F., Greene, T. R., Post, T. A., & Penner, B. C. (1983). Problem solving skill in the social sciences. In Bower, G. H. (Ed.), The psychology of learning and motivation: Advances in research theory. Vol. 17 (pp. 165–213). New York: Academic Press.Google Scholar
Voss, J. F., Tyler, S., & Yengo, L. (1983). Individual differences in the solving of social science problems. In Dillon, R. & Schmeck, R. (Eds.), Individual differences in cognition (pp. 205–232). New York: Academic Press.Google Scholar
Wason, P. M., & Johnson-Laird, P. N. (1972). Psychology of reasoning: Structure and content. Cambridge, MA: Harvard University Press.Google Scholar
Watson, J. B. (1913). Psychology as the behaviorist views it. Psychological Review, 20, 158–77.CrossRefGoogle Scholar
Watson, J. B. (1920). Is thinking merely the action of language mechanisms? British Journal of Psychology, 11, 87–104.Google Scholar
Winograd, T. (1975). Frame representations and the declarative procedural controversy. In Bobrow, D. G. & Collins, A. M. (Eds.), Representation and understanding. New York: Academic Press.Google Scholar
Zeitz, C. M. (1997). Some concrete advantages of abstraction: How experts' representations facilitate reasoning. In Feltovich, P. J., Ford, K. M., & Hoffman, R. R. (Eds.), Expertise in context: Human and machine (pp. 43–65). Menlo PK, CA: AAAI/MIT Press.
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