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Part II - Overview of Approaches to the Study of Expertise: Brief Historical Accounts of Theories and Methods

Published online by Cambridge University Press:  10 May 2018

K. Anders Ericsson
Affiliation:
Florida State University
Robert R. Hoffman
Affiliation:
Florida Institute for Human and Machine Cognition
Aaron Kozbelt
Affiliation:
Brooklyn College, City University of New York
A. Mark Williams
Affiliation:
University of Utah
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Print publication year: 2018

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References

References

Anderson, J. R. (1982). Acquisition of cognitive skill. Psychological Review, 89, 369406.CrossRefGoogle Scholar
Anderson, J. R. (1987). Skill acquisition: Compilation of weak-method problem situations. Psychological Review, 94, 192210.Google Scholar
Anderson, J. R., & Lebiere, C. (2003). The Newell Test for a theory of cognition. Behavioral and Brain Sciences, 26, 587640.Google Scholar
Anthony, G., Hunter, J., & Hunter, R. (2015). Prospective teachers’ development of adaptive expertise. Teaching and Teacher Education, 49, 108117.CrossRefGoogle Scholar
Ashby, F. G., & Crossley, M. J. (2012). Automaticity and multiple memory systems. WIREs Cognitive Sciences, 3, 363376.Google Scholar
Ashby, W. R. (1952). Design for a brain. London: Chapman & Hall.Google Scholar
Augier, M., & March, J. G. (2011). The roots, rituals, and rhetorics of change: North American business schools after the Second World War. Stanford University Press.Google Scholar
Augier, M., & Prietula, M. J. (2009). Historical roots of the A Behavioral Theory of the Firm model at GSIA. Organization Science, 18, 507522.CrossRefGoogle Scholar
Baker, J., & Farrow, D. (eds.) (2015). Routledge handbook of sport expertise. London: Routledge.Google 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, ON: McMaster University.Google Scholar
Barrows, H. S., & Tamblyn, R. M. (1980). Problem-based learning. New York: Springer.Google Scholar
Bartlett, F. (1958). Thinking. New York: Basic Books.Google Scholar
Berliner, D. C. (1988). Implications of studies of expertise in pedagogy for teacher education and evaluation. In Pfleiderer, J. (ed.), New directions for teacher assessment: Proceedings of the 1988 ETS Invitational Conference (pp. 3967). Princeton, NJ: Educational Testing Service.Google Scholar
Bilalić, M., McLeod, P., & Gobet, F. (2008). Inflexibility of experts – reality or myth? Quantifying the Einstellung effect in chess masters. Cognitive Psychology, 56, 73102.CrossRefGoogle ScholarPubMed
Bloom, B. (ed.) (1985). Developing talent in young people. New York: Ballantine.Google Scholar
Boden, M. A. (2006). Mind as machine: A history of cognitive science. Oxford University Press.Google Scholar
Borko, H. (ed.) (1962). Computer applications in the behavioral sciences. Englewood Cliffs, NJ: Prentice-Hall.Google Scholar
Brick, N., MacIntyre, T., & Campbell, M. (2015). Metacognitive processes in the self-regulation of performance in elite distance runners. Psychology of Sport and Exercise, 19, 19.Google Scholar
Bruner, J. S., Goodnow, J. J., & Austin, G. A. (1956). A study of thinking. New York: John Wiley.Google Scholar
Buchanan, B. G., Davis, R., & Feigenbaum, E. A. (2006). Expert systems: A perspective from computer science, In Ericsson, K. A., Charness, N., Hoffman, R. R., & Feltovich, P. J. (eds.), The Cambridge handbook of expertise and expert performance (pp. 87103). Cambridge University Press.CrossRefGoogle Scholar
Buchanan, B. G., & Feigenbaum, E. A. (1978). DENDRAL and MetaDENDRAL: Their applications dimension. Artificial Intelligence, 11, 524.Google Scholar
Camerer, C. E, & Johnson, E. J. (1991). The process-performance paradox in expert judgment: How can the experts know so much and predict so badly? In Ericsson, K. A. & Smith, J. (eds.), Toward a general theory of expertise: Prospects and limits (pp. 195217). Cambridge University Press.Google Scholar
Charlin, B., Boshuizen, H. P. A, Custers, E., & Feltovich, P. J. (2007). Scripts and clinical reasoning. Medical Education, 41, 11781184.Google Scholar
Charness, N. (1976). Memory for chess positions: Resistance to interference. Journal of Experimental Psychology: Human Learning and Memory, 2, 641653.Google Scholar
Charness, N. (1979). Components of skill in bridge. Canadian Journal of Psychology, 33, 150.CrossRefGoogle Scholar
Charness, N. (1981). Search in chess: Age and skill differences. Journal of Experimental Psychology: Human Perception and Performance, 7, 467476.Google Scholar
Chase, W. G. (1983). Spatial representations of taxi drivers. In Rogers, D. & Sloboda, J. A. (eds.), The acquisition of symbolic skills (pp. 391406). New York: Plenum Press.Google Scholar
Chase, W. G., & Simon, H. A. (1973a). The mind’s eye in chess. In Chase, W. G. (ed.), Visual information processing (pp. 215281). New York: Academic Press.Google Scholar
Chase, W. G., & Simon, H. A. (1973b). Perception in chess. Cognitive Psychology, 1, 3381.Google Scholar
Chi, M. T. H. (1978). Knowledge structures and memory development. In Siegler, R. S. (ed.), Children’s thinking: What develops? (pp. 7396). Hillsdale, NJ: Erlbaum.Google Scholar
Chi, M. T. H., Feltovich, P. J., & Glaser, R. (1981). Categorization and representation of physics problems by experts and novices. Cognitive Science, 5, 121152.Google 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, 257274.Google Scholar
Choudhry, N. K., Fletcher, R. H., & Soumerai, S. B. (2005). Systematic review: The relationship between clinical experience and quality of health care. Annals of Internal Medicine, 142, 260273.Google Scholar
Collins, A. (1977). Why cognitive science? Cognitive Science, 1, 12.Google Scholar
Dawes, R. M. (1994). House of cards: Psychology and psychotherapy built on myth. New York: Free Press.Google Scholar
de Groot, A. (1946). Het denken van den schaker. Amsterdam: Noord-Hollandsche Uit. Mij.Google Scholar
de Groot, A. (1965). Thought and choice in chess. The Hague: Mouton.Google Scholar
Duncker, K. (1945). On problem solving. Psychological Monographs, 58, 1113.Google Scholar
Dutton, J. M., & Starbuck, W. H. (eds.) (1971). Computer simulation of human behavior. New York: John Wiley.Google Scholar
Elstein, A. S., Shulman, L. S., & Sprafka, S. A. (1978). Medical problem solving. Cambridge, MA: Harvard University Press.Google Scholar
Epstein, D. (2013). The sports gene: Inside the science of extraordinary athletic performance. New York: Current.Google Scholar
Ericsson, K. A. (ed.) (1996). 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. (2004). Deliberate practice and the acquisition and maintenance of expert performance in medicine and related domains. Academic Medicine, 10, S1S12.Google Scholar
Ericsson, K. A. (ed.) (2009). Development of professional expertise: Toward measurement of expert performance and design of optimal learning environments. Cambridge University Press.Google Scholar
Ericsson, K. A. (2014). Why expert performance is special and cannot be extrapolated from studies of performance in the general population: A response to criticisms. Intelligence, 45, 81103.Google Scholar
Ericsson, K. A. (2015). Acquisition and maintenance of medical expertise: A perspective from the expert-performance approach with deliberate practice. Academic Medicine, 90, 14711486.Google Scholar
Ericsson, K. A., & Charness, N. (1994). Expert performance: Its structure and acquisition. American Psychologist, 49, 725747.Google Scholar
Ericsson, K. A., & Charness, N. (1995). Abilities: Evidence for talent or characteristics acquired through engagement in relevant activities. American Psychologist, 50, 803804.Google Scholar
Ericsson, K. A., Charness, N., Hoffman, R. R., & Feltovich, P. J. (eds.) (2006). The Cambridge handbook of expertise and expert performance. Cambridge University Press.Google Scholar
Ericsson, K. A., & Kintsch, W. (1995). Long-term working memory. Psychological Review, 102, 211245.Google Scholar
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, 571588.Google 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, 363406.Google Scholar
Ericsson, K. A., & Lehmann, A. C. (1996). Expert and exceptional performance: Evidence on maximal adaptations on task constraints. Annual Review of Psychology, 47, 273305.Google Scholar
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, 578592.Google Scholar
Ericsson, K. A., & Pool, R. (2016). Peak: Secrets from the new science of expertise. New York: Houghton Mifflin Harcourt.Google Scholar
Ericsson, K. A., Prietula, M., & Cokely, E. (2007). The making of an expert. Harvard Business Review, July–August, 114121.Google Scholar
Ericsson, K. A. Roring, R. W., & Nandagopal, K. (2007). Misunderstandings, agreements, and disagreements: Toward a cumulative science of reproducibly superior aspects of giftedness. High Ability Studies, 18, 97115.Google Scholar
Ericsson, K. A., & Simon, H. A. (1980). Verbal reports as data. Psychological Review, 87, 215251.Google Scholar
Ericsson, K. A., & Simon, H. A. (1993). Protocol analysis: Verbal reports as data (revised edn.). Cambridge, MA: Bradford Books/MIT Press.Google Scholar
Ericsson, K. A., & Smith, J. (eds.) (1991a). Toward a general theory of expertise: Prospects and limits. 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. 138). Cambridge University Press.Google Scholar
Ericsson, K. A., & Ward, P. (2007). Capturing the naturally occurring superior performance of experts in the laboratory: Toward a science of expert and exceptional performance. Current Directions in Psychological Science, 16, 346350.Google Scholar
Ericsson, K. A., Whyte, J., & Ward, P. (2007). Expert performance in nursing: Reviewing research on expertise in nursing within the framework of the expert-performance approach. Advances in Nursing Science, 30, E58E71.Google Scholar
Ernst, G., & Newell, A. (1969). GPS: A case-study in generality and problem solving. New York: Academic Press.Google Scholar
Farrow, D., & Baker, J. (eds.) (2013). Developing sport expertise: Researchers and coaches put theory into practice (2nd edn.). London: Routledge.Google Scholar
Feigenbaum, J., & Feldman, J. (eds.) (1963). Computers and thought. New York: McGraw-Hill.Google Scholar
Feldon, D. F. (2006). The implications of research on expertise for curriculum and pedagogy. Educational Psychology Review, 19, 91110.Google Scholar
Feltovich, P. J., & Barrows, H. S. (1984). Issues of generality in medical problem solving. In Schmidt, H. G. & De Volder, M. L. (eds.), Tutorials in problem based learning: New directions in teaching the health professions (pp. 128140). Assen: Van Gorcum.Google Scholar
Feltovich, P. J., 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 expertise. In Clancey, W. & Shortliffe, E. (eds.), Readings in medical artificial intelligence: The first decade (pp. 275319). Reading, MA: Addison-Wesley.Google Scholar
Feltovich, P. J., Spiro, R. J., & Coulson, R. L. (1997). Issues of expert flexibility in contexts characterized by complexity and change. In Feltovich, P. J., Ford, K. M., & Hoffman, R. R. (eds.), Expertise in context: Human and machine (pp. 125146). Menlo Park, CA: AAAI Press.Google Scholar
Fitts, P. M., & Posner, M. I. (1967). Human performance. Belmont, CA: Brookes Cole.Google Scholar
Fox, M. C., Ericsson, K. A., & Best, R. (2011). Do procedures for verbal reporting of thinking have to be reactive? A meta-analysis and recommendations for best reporting methods. Psychological Bulletin, 137, 316344.Google Scholar
Gagné, F. (2013). Yes, giftedness (aka “innate” talent) does exist! In Kaufman, S. B. (ed.), The complexity of greatness: Beyond talent or practice (pp. 191221). Oxford University Press.Google Scholar
Gardner, A. K., Jabbour, I. J., Williams, B. H., & Huerta, S. (2015). Different goals, different pathways: The role of metacognition and task engagement in surgical skill acquisition. Journal of Surgical Education, 73, 6165.Google Scholar
Gardner, H. (1995). Why would anyone become an expert? [Commentary on Ericsson & Charness, 1994]. American Psychologist, 50, 802803.Google Scholar
Glaser, R. (1976). Cognition and instructional design. In Klahr, D. (ed.), Cognition and instruction (pp. 303315). 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. xvxxviii). Hillsdale, NJ: Erlbaum.Google 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. 287310). Hillsdale, NJ: Erlbaum.Google Scholar
Hacker, D. J., Dunlosky, J., & Graesser, A. C. (eds.) (2009). Handbook of metacognition in education. New York: Routledge.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, 339387.Google Scholar
Hatano, G., & Inagaki, K. (1986). Two courses of expertise. In Stevenson, H., Azum, A., & Hakuta, K. (eds.), Child development and education in Japan (pp. 262272). San Francisco: Freeman.Google Scholar
Hebb, D. O. (1949). The organization of behavior: A neuropsychological approach. New York: John Wiley.Google Scholar
Hélie, S., & Cousineau, D. (2011). The cognitive neuroscience of automaticity: Behavioral and brain signatures. Cognitive Sciences, 6, 2543.Google Scholar
Hoffman, R. R. (ed.) (1992). The psychology of expertise. New York: Springer-Verlag.Google Scholar
Hoffman, R. R. (ed.) (2007). Expertise out of context: Proceedings of the Sixth International Conference on Naturalistic Decision Making. Mahwah, NJ: Erlbaum.Google Scholar
Hoffman, R. R., & Deffenbacher, K. (1992). A brief history of applied cognitive psychology. Applied Cognitive Psychology, 6, 148.Google Scholar
Hoffman, R. R., & Militello, L. G. (2008). Perspectives on cognitive task analysis: Historical origins and modern communities of practice. Boca Raton, FL: CRC Press/Taylor & Francis.Google Scholar
Hoffman, R. R., Ward, P., Feltovich, P. J., DiBello, L., Fiore, S. M., & Andrews, D. (2014). Accelerated expertise: Training for high proficiency in a complex world. New York: Psychology Press.Google Scholar
Horn, J., & Masunaga, H. (2006). A merging theory of expertise and intelligence. In Ericsson, K. A., Charness, N., Hoffman, R. R., & Feltovich, P. J. (eds.), The Cambridge handbook of expertise and expert performance (pp. 587611). Cambridge University Press.Google Scholar
Hovland, C. I. (1960). Computer simulation of thinking. American Psychologist, 15, 687694.Google Scholar
Hunt, E. B., & Hovland, C. I. (1961). Programming a model of human concept formation. Paper presented at the 1961 Western Joint Computer Conference, May 9–11.Google Scholar
Hunt, M. (1993). The story of psychology. New York: Anchor Books.Google Scholar
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 (pp. 255283). 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, 235283.Google Scholar
Kaub, K., Karbach, J., Spinath, F., & Brunken, R. (2016). Person–job fit in the field of teacher education: An analysis of vocational interests and requirements among novice and professional science and language teachers. Teaching and Teacher Education, 55, 217227.Google Scholar
Keller, N., Cokely, E., Katsikopoulos, K., & Wegwarth, O. (2010). Naturalistic heuristics for decision making. Journal of Cognitive Engineering and Decision Making, 4, 256274.CrossRefGoogle Scholar
Klein, D., Woods, D., Klein, G., & Perry, S. (2016). Can we trust best practices? Six cognitive challenges of evidence-based approaches. Journal of Cognitive Engineering and Decision Making, 10, 244254.Google Scholar
Klein, G. (1998). Sources of power: How people make decisions. Cambridge, MA: MIT Press.Google Scholar
Klein, G. (2008). Naturalistic decision making. Human Factors, 50, 456460.Google Scholar
Klein, G. (2016). The ShadowBox approach to cognitive skills training: An empirical evaluation. Journal of Cognitive Engineering and Decision Making, 10, 268280.Google Scholar
Klein, G., Calderwood, R., & Clinton-Cirocco, A. (1986). Rapid decision making on the fireground. Proceedings of the Human Factors and Ergonomics Society, 1, 576580.Google Scholar
Klein, G., & 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
Kruglanski, A. W., & Gigerenzer, G. (2011). Intuitive and deliberate judgments are based on common principles. Psychological Review, 118, 97109.Google Scholar
Larkin, J., McDermott, J., Simon, D., & Simon, H. A. (1980). Expert and novice performance in solving physics problems. Science, 208, 13351342.Google Scholar
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. 311342). Hillsdale, NJ: Erlbaum.Google Scholar
Liu, H., Agam, Y., Madsen, J. R., & Kreiman, G. (2009). Timing, timing, timing: Fast decoding of object information from intracranial field potentials in human visual cortex. Neuron, 62, 281290.Google Scholar
MacIntyre, T. E., Igour, E. R., Campbell, M. J., Moran, A. P., & Matthews, J. (2014). Metacognition and action: A new pathway to understanding social and cognitive aspects of expertise in sport. Frontiers in Psychology, 5, e1155.Google Scholar
McCorduck, P. (1979). Machines who think: A personal inquiry into the history and prospects of artificial intelligence. San Francisco: W. H. Freeman.Google Scholar
McCulloch, W. S., & Pitts, W. (1943). A logical calculus of ideas immanent in nervous activity. Bulletin of Mathematical Biophysics, 5, 115133.Google Scholar
McGugin, R. W., Newton, A. T., Gore, J. C., & Gauthier, I. (2014). Robust expertise effects in right FFA. Neuropsychologia, 63, 135144.Google Scholar
Miller, G. A. (1956). The magical number seven plus or minus two: Some limits on our capacity for processing information. Psychological Review, 63, 8197.Google Scholar
Miller, G. A., Galanter, E., & Pribram, K. H. (1960). Plans and the structure of behavior. New York: Holt.CrossRefGoogle Scholar
Moxley, J. H., Ericsson, K. A., Charness, N., & Krampe, R. T. (2012). The role of intuition and deliberative thinking in experts’ superior tactical decision making. Cognition, 124, 7278.Google Scholar
Newell, A. (1969). Heuristic programming: Ill-structured problems. In Aronofsky, J. S. (ed.), Progress in operations research (pp. 361414). New York: John Wiley.Google Scholar
Newell, A. (1990). Unified theories of cognition. Cambridge, MA: Harvard University Press.Google Scholar
Newell, A., & Shaw, J. C. (1957). Programming the logic theory machine. Paper presented at the 1957 Western Joint Computer Conference, February 26–28.Google Scholar
Newell, A., Shaw, J. C., & Simon, H. A. (1958). Elements of a theory of problem solving. Psychological Review, 65, 151166.Google Scholar
Newell, A., & Simon, H. A. (1956). The logic theory machine: A complex information processing system. IRE Transactions on Information Theory, IT-2, No. 3, 6179.Google Scholar
Newell, A., & Simon, H. A. (1961). GPS, a program that simulates human thought. In Billing, H. (ed.), Lernende Automaten (pp. 109124). Munich: Oldenbourg.Google Scholar
Newell, A., & Simon, H. A. (1972). Human problem solving. Englewood Cliffs, NJ: Prentice-Hall.Google Scholar
Noice, H., & Noice, T. (2006). Artistic performance: Acting, ballet and contemporary dance. In Ericsson, K. A., Charness, N., Hoffman, R. R., & Feltovich, P. J. (eds.), The Cambridge handbook of expertise and expert performance (pp. 489503). Cambridge University 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: Prospects and limits (pp. 93125). Cambridge University Press.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, 981996.Google Scholar
Pelaccia, T., Tardif, J., Triby, E., Ammirati, C., Bertrand, C., Dory, V., & Charlin, B. (2016). From context comes expertise: How do expert emergency physicians use their know-who to make decisions? Annals of Emergency Medicine, 67, 747751.Google Scholar
Prietula, M. J. (2011). Thoughts on complexity and computational models. In Allen, P., Maguire, S., & McKelvey, B. (eds.), The SAGE handbook of complexity and management (pp. 93110). Thousand Oaks, CA: Sage Publications.CrossRefGoogle Scholar
Reitman, W. R. (1965). Cognition and thought. New York: John Wiley.Google Scholar
Rosenbaum, D. A., Augustyn, J. S., Cohen, R. G., & Jax, S. A. (2006). Perceptual-motor expertise. In Ericsson, K. A., Charness, N., Hoffman, R. R., & Feltovich, P. J. (eds.), The Cambridge handbook of expertise and expert performance (pp. 505520). 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, 210229.Google Scholar
Shanteau, J., & Stewart, T. R. (1992). Why study expert decision making? Some historical perspectives and comments. Organizational Behavior and Human Decision Processes, 53, 95106.Google Scholar
Shortliffe, E. H. (1976). Computer-based medical consultations: MYCIN. New York: American Elsevier.Google Scholar
Simon, H. A. (1969). The sciences of the artificial. Cambridge, MA: MIT Press.Google Scholar
Simon, H. A. (1990). Invariants of human behavior. Annual Review of Psychology, 41, 119.Google Scholar
Simon, H. A., & Chase, W. G. (1973). Skill in chess. American Scientist, 61, 394403.Google Scholar
Sonnentag, S., Niessen, C., & Volmer, J. (2006). Expertise in software design. In Ericsson, K. A., Charness, N., Hoffman, R. R., & Feltovich, P. J. (eds.), The Cambridge handbook of expertise and expert performance (pp. 373387). Cambridge University Press.Google 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, 506522.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
Sun, R. (ed.) (2008). The Cambridge handbook of computational psychology. Cambridge University Press.Google Scholar
von Neumann, J. (1958). The computer and the brain. New Haven, CT: Yale University Press.Google Scholar
Voss, J. F., & Post, T. A. (1988). On the solving of ill-structured problems. In Chi, M. T. H., Glaser, R., & Farr, M. J. (eds.), The nature of expertise (pp. 261285). Hillsdale, NJ: Erlbaum.Google Scholar
Ward, P., Williams, A. M., & Hancock, P. A. (2006). Simulation for performance and training. In Ericsson, K. A., Charness, N., Hoffman, R. R., & Feltovich, P. J. (eds.), The Cambridge handbook of expertise and expert performance (pp. 243262). Cambridge University Press.Google Scholar
Wason, P. M., & Johnson-Laird, P. N. (1972). Psychology of reasoning: Structure and content. Cambridge, MA: Harvard University Press.Google Scholar
Wears, R., & Schuber, C. (2016). Visualising expertise in context. Annals of Emergency Medicine, 67, 752754.CrossRefGoogle ScholarPubMed
Wilding, J. M., & Valentine, E. M. (2006). Exceptional memory. In Ericsson, K. A., Charness, N., Hoffman, R. R., & Feltovich, P. J. (eds.), The Cambridge handbook of expertise and expert performance (pp. 457470). Cambridge University Press.Google Scholar
Winne, P. H., & Nesbit, J. C. (2009). The psychology of academic achievement. Annual Review of Psychology, 61, 653678.Google Scholar
Wolfe, J. M. (1998). What can 1 million trials tell us about visual search? Psychological Science, 9, 3339.Google Scholar
Yu, B., Honda, T., Sharqawy, M., & Yang, M. (2016). Human behavior and domain knowledge in parameter design of complex systems. Design Studies, 45, 242267.Google Scholar
Zimmerman, B. J. (2008). Investigating self-regulation and motivation: Historical background, methodological developments, and future prospects. American Educational Research Journal, 45, 166183.Google Scholar

References

Ambrosino, R., & Buchanan, B. G. (1999). The use of physician domain knowledge to improve the learning of rule-based models for decision support. In Proceedings of the AMIA Annual Symposium (pp. 192196). Washington, DC.Google Scholar
Anderson, J. R. (1982). Acquisition of cognitive skill. Psychological Review, 89, 369406.Google Scholar
Arocha, J. F., & Patel, V. L. (1995). Novice diagnostic reasoning in medicine: Accounting for evidence. Journal of the Learning Sciences, 4, 355384.Google Scholar
Berg, C. A., & Sternberg, R. J. (1992). Adults’ conception of intelligence across the adult life span. Psychology and Aging, 7, 221231.Google Scholar
Berners-Lee, T., Hendler, J., & Lassila, O. (2001). The semantic web. Scientific American, 284 (May), 3443.Google Scholar
Bobrow, D. G., & Hayes, P. J. (1985). Artificial intelligence: Where are we? Artificial Intelligence, 25, 375415.Google Scholar
Boose, J. H. (1989). A survey of knowledge acquisition techniques and tools. Knowledge Acquisition, 1, 3958.Google Scholar
Brynjolfsson, E., & McAfee, A. (2014). The second machine age: Work, progress, and prosperity in a time of brilliant technologies. New York: Norton.Google Scholar
Buchanan, B. G. (1994). The role of experimentation in artificial intelligence. Philosophical Transactions of the Royal Society of London A: Mathematical, Physical and Engineering Sciences, 349, 153166.Google Scholar
Buchanan, B. G. (1995). Verification and validation of knowledge-based systems: A representative bibliography. Workshop on Evaluation of Knowledge-Based Systems, Lister Hill Center, National Library of Medicine, Bethesda, MD, December. www.quasar.org/21698/tmtek/biblio.html.Google Scholar
Buchanan, B. G., & Shortliffe, E. H. (eds.) (1984). Rule-based expert systems: The MYCIN experiments of the Stanford Heuristic Programming Project. Reading, MA: Addison-Wesley.Google Scholar
Buchanan, B. G., Smith, D. H., White, W. C., Gritter, R. J., Feigenbaum, E. A., Lederberg, J., & Djerassi, C. (1976). Application of artificial intelligence for chemical inference XXII: Automatic rule formation in mass spectrometry by means of the Meta-DENDRAL program. Journal of the American Chemical Society, 98, 6168.Google Scholar
Buchanan, B. G., & Smith, R. G. (1988). Fundamentals of expert systems. In Traub, J. F., Grosz, B. J., Lampson, B. W., et al. (eds.), Annual review of computer science (Vol. 3, pp. 2358). Palo Alto, CA: Annual Reviews Inc.Google Scholar
Buchanan, B. G., & Wilkins, D. C. (1993). Readings in knowledge acquisition and learning. San Mateo, CA: Morgan Kaufmann.Google Scholar
Byford, S. (2016). Google’s AlphaGo AI beats Lee Se-dol again to win Go series 4–1. The Verge. www.theverge.com/2016/3/15/11213518/alphago-deepmind-go-match-5-result.Google Scholar
Chandrasekaran, B., Josephson, J. R., & Benjamins, V. R. (1999). What are ontologies, and why do we need them? IEEE Intelligent Systems, 14, 2026.Google Scholar
Chang, M. D., & Forbus, K. D. (2014). Using analogy to cluster hand-drawn sketches for sketch-based educational software. AI Magazine, 35, 7684.Google Scholar
Cheetham, W. E. (2004). Tenth anniversary of the plastics color formulation tool. In Proceedings of the Sixteenth Conference on Innovative Applications of Artificial Intelligence (IAAI-04) (pp. 770776). San Jose, CA: Association for the Advancement of Artificial Intelligence.Google Scholar
Chi, M., Glaser, R., & Farr, M. J. (eds.) (1988). The nature of expertise. Hillsdale, NJ: Erlbaum.Google Scholar
Chun, H. W. C., & Suen, T. Y. T. (2014). Engineering works scheduling for Hong Kong’s rail network. In Proceedings of the Twenty-Sixth Conference on Innovative Applications of Artificial Intelligence (IAAI-14) (pp. 28902897). Quebec City: Association for the Advancement of Artificial Intelligence.Google Scholar
Clancey, W. J. (1985). Heuristic classification. Artificial Intelligence, 27, 289350.Google Scholar
Davis, R. (1979). Interactive transfer of expertise: Acquisition of new inference rules. Artificial Intelligence, 12, 121157.Google Scholar
Davis, R. (1980). Meta-rules: Reasoning about control. Artificial Intelligence, 15, 179222.Google Scholar
Davis, R. (1984). Diagnostic reasoning based on structure and behavior. Artificial Intelligence, 24, 347410.Google Scholar
Davis, R. (1989). Expert systems: How far can they go? Part I. AI Magazine, 10, 6167; Part II: AI Magazine, 10, 65–77.Google Scholar
Davis, R., & King, J. (1984). The origin of rule-based systems in AI. In Buchanan, B. G. & Shortliffe, E. H. (eds.), Rule-based expert systems: The MYCIN experiments of the Stanford Heuristic Programming Project (pp. 2952). Reading, MA: Addison-Wesley.Google Scholar
Davis, R., Shrobe, H. E., & Szolovits, P. (1993). What is a knowledge representation? AI Magazine, 14, 1733.Google Scholar
Dzierzanowski, J. M., Chrisman, K. R., MacKinnon, G. J., & Klahr, P. (1989). The authorizer’s assistant: A knowledge-based credit authorization system for American Express. In Proceedings of the First Conference on Innovative Applications of Artificial Intelligence (IAAI-89) (pp. 168172). Stanford, CA: Association for the Advancement of Artificial Intelligence.Google Scholar
Elstein, A. S., Shulman, L. S., & Sprafka, S. A. (1978). Medial problem solving: An analysis of clinical reasoning. Cambridge, MA: Harvard University Press.Google Scholar
Engelmore, R. S. (ed.) (1993). JTEC Panel on KNOWLEDGE-BASED SYSTEMS IN JAPAN, Distributed by National Technical Information Service, ISBN-10: 1883712009, ISBN-13: 978–1883712006. www.wtec.org/loyola//pdf/kb.pdf.Google Scholar
Engelmore, R., & Morgan, T. (1988). Blackboard systems. Reading, MA: Addison-Wesley.Google Scholar
Erman, L. D., Hayes-Roth, F., Lesser, V. R., & Reddy, D. R. (1980). The Hearsay II Speech Understanding System: Integrating knowledge to resolve uncertainty. ACM Computing Surveys, 12, 213253.Google Scholar
Feigenbaum, E. A., & Feldman, J. (1963). Computers and thought. New York: McGraw-Hill.Google Scholar
Feigenbaum, E. A., McCorduck, P., & Nii, P. (1988). The rise of the expert company. New York: Times Books.Google Scholar
Forbus, K., Usher, J., Lovett, A., Lockwood, K., & Wetzel, J. (2011). CogSketch: Sketch understanding for cognitive science research and for education. Topics in Cognitive Science, 3, 648666.Google Scholar
Forsythe, D. E., & Buchanan, B. G. (1992). Nontechnical problems in knowledge engineering: Implications for project management. Expert Systems With Applications, 5, 203212.Google Scholar
Forsythe, D. E., Osheroff, J. A., Buchanan, B. G., & Miller, R. A. (1991). Expanding the concept of medical information: An observational study of physicians’ needs. Computers and Biomedical Research, 25, 181200.Google Scholar
Glasgow, B., Mandell, A., Binney, D., Ghemri, L., & Fisher, D. (1997). MITA: An information-extraction approach to the analysis of free-form text in life insurance applications. AI Magazine, 19, 5972.Google Scholar
Goldstein, I., & Papert, S. (1977). Artificial intelligence, language, and the study of knowledge, Cognitive Science, 1, 84123.Google Scholar
Gordon, J., & Shortliffe, E. H. (1985). A method for managing evidential reasoning in a hierarchical hypothesis space. Artificial Intelligence, 26, 323357.Google Scholar
Halevy, A. Y., Norvig, P., & Pereira, F. (2009). The unreasonable effectiveness of data. IEEE Expert / IEEE Intelligent Systems – EXPERT, 24, 812.Google Scholar
Hammond, T., & Davis, R. (2004). Automatically transforming symbolic shape descriptions for use in sketch recognition. In Proceedings of the Nineteenth National Conference on Artificial Intelligence (AAAI-04) (pp. 450456). San Jose, CA: Association for the Advancement of Artificial Intelligence.Google Scholar
Hayes, J. R. (1985). Three problems in teaching general skills. In Chipman, S. F., Segal, J. W., & Glaser, R. (eds.), Thinking and learning skills, Vol. 2: Research and open questions (pp. 391405). Hillsdale, NJ: Erlbaum.Google Scholar
Hayes-Roth, F., Waterman, D. A. & Lenat, D. B. (eds.) (1983). Building expert systems. Reading, MA: Addison-Wesley.Google Scholar
Hearn, A. C. (1966). Computation of algebraic properties of elementary particle reactions using a digital computer. Communications of the ACM, 9, 573577.Google Scholar
Hendler, J. A., & Feigenbaum, E. A. (2001). Knowledge is power: The semantic web vision. In Proceedings of the First Asia-Pacific Conference on Web Intelligence: Research and Development, Maebashi City, Japan (pp. 1829). London: Springer Verlag.Google Scholar
Hoffman, R., Baur, E., Dumer, J., Hanratty, T., & Ingham, H. (1999). Turbine engine diagnostics (TED). AI Magazine, 20, 6976.Google Scholar
Kahneman, D. (2011). Thinking, fast and slow. New York: Farrar, Straus & Giroux.Google Scholar
Kirkland, J. D., Senator, T. E., Hayden, J. J., Dybala, T., Goldberg, H. G., & Shyr, P. (1999). The NASD regulation Advanced-Detection System (ADS). AI Magazine, 20, 5568.Google Scholar
Kolodner, J. (1993). Case-based reasoning. San Mateo, CA: Morgan Kaufmann.Google Scholar
Larkin, J., McDermott, J., Simon, D. P., & Simon, H. A. (1980). Expert and novice performance in solving physics problems. Science, 208, 13351342.Google Scholar
Leake, D. B. (ed.) (1996). Case-based reasoning: Experiences, lessons, and future directions. Menlo Park, CA: AAAI Press/MIT Press.Google Scholar
Lenat, D., & Feigenbaum, E. A. (1987). On the thresholds of knowledge. In Proceedings of the Tenth International Joint Conference on Artificial Intelligence (IJCAI-87), Milan, Italy (pp. 11731182). San Mateo, CA: Morgan Kaufmann.Google Scholar
Lindsay, R. K. (2012). Understanding understanding: Natural and artificial intelligence. CreateSpace. ISBN-13: 978–1466450585.Google Scholar
Lindsay, R. K., Buchanan, B. G., Feigenbaum, E. A., & Lederberg, J. (1980). Applications of artificial intelligence for chemical inference: The DENDRAL project. New York: McGraw-Hill.Google Scholar
McDermott, J. (1982). A rule-based configurer of computer systems. Artificial Intelligence, 19, 3988.Google Scholar
Michie, D. (ed.) (1979). Expert systems in the micro-electronic age. Edinburgh University Press.Google Scholar
Minsky, M. (1981). A framework for representing knowledge. In Haugland, J. (ed.), Mind design: Philosophy, psychology, artificial intelligence (pp. 95128). Montgomery, VT: Bradford Books.Google Scholar
Moses, J. (1971). Symbolic integration: The stormy decade. Communications of the ACM, 14, 548560.Google Scholar
Moskowitz, A. J., Kuipers, B. J., & Kassirer, J. P. (1988). Dealing with uncertainty, risks, and tradeoffs in clinical decisions: A cognitive science approach. Annals of Internal Medicine, 108, 435449.Google Scholar
Motta, E. (2013). Editorial: 25 years of knowledge acquisition. International Journal of Human–Computer Studies, 71 (Special Issue), 131134.Google Scholar
Muratore, J. F., Heindel, T. A., Murphy, T. B., Rasmussen, A. N., & McFarland, R. Z. (1989). Applications of artificial intelligence to space shuttle mission control. In Proceedings of the First Conference on Innovative Applications of Artificial Intelligence (IAAI-89) (pp. 1522). Stanford, CA: Association for the Advancement of Artificial Intelligence.Google Scholar
Nayak, P., & Williams, B. C. (1998). Model-directed autonomous systems. AI Magazine, 19, 126.Google Scholar
Newell, A. (1985). Artificial intelligence: Where are we? Artificial Intelligence, 2, 375415.Google Scholar
Newell, A., & Simon, H. A. (1972). Human problem solving. Englewood Cliffs, NJ: Prentice-Hall.Google Scholar
Nilsson, N. J. (1995). Eye on the prize. AI Magazine, 16, 917.Google Scholar
O’Dell, C., & Hubert, C. (2011). The new edge in knowledge: How knowledge management is changing the way we do business. Hoboken, NJ: John Wiley.Google Scholar
Pan, S. J., & Yang, Q. (2010). A survey on transfer learning. IEEE Transactions on Knowledge and Data Engineering, 22, 13451359.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: Prospects and limits (pp. 93125). Cambridge University Press.Google Scholar
Pauker, S. P., & Szolovits, P. (1977). Analyzing and simulating taking the history of the present illness: Context formation. In Schneider, W. & Sagvall-Hein, A. L. (eds.), IFIP Working Congress on Computational Linguistics in Medicine (pp. 109118). Amsterdam: North-Holland.Google Scholar
Pazzani, M. J., & Brunk, C. A. (1991). Detecting and correcting errors in rule-based expert systems: An integration of empirical and explanation-based learning. Knowledge Acquisition, 3, 157173.Google Scholar
Pearl, J. (2001). Direct and indirect effects. In Proceedings of the Seventeenth Conference on Uncertainty in Artificial Intelligence (pp. 411420). San Francisco, CA: Morgan Kaufmann.Google Scholar
Polanyi, M. (1958). Personal knowledge. University of Chicago Press.Google Scholar
Polya, G. (1954). Mathematics and plausible reasoning, 2 vols. Princeton University Press.Google Scholar
Pople, H. E., Myers, J., & Miller, R. (1975). DIALOG: A model of diagnostic logic for internal medicine. In Proceedings of the Fourth International Joint Conference on Artificial Intelligence (IJCAI-75), Tbilisi, Georgia (pp. 848855). San Mateo, CA: Morgan Kaufmann.Google Scholar
Rennels, G. D., Shortliffe, E. H., & Miller, P. L. (1987). Choice and explanation in medical management: A multiattribute model of artificial intelligence approaches. Medical Decision Making, 7, 2231.Google Scholar
Richards, D., & Compton, P. (1998). Taking up the situated cognition challenge with ripple down rules, International Journal of Human–Computer Studies, 49, 895926.Google Scholar
Robinson, J. A. (1968). The generalized resolution principle. In Michie, D. (ed.), Machine Intelligence 3. Edinburgh University Press.Google Scholar
Robinson, J. A., & Sibert, E. E. (1982). LOGLISP: An alternative to PROLOG. In Hayes, J. E., Michie, D., & Pao, Y.-H. (eds.), Machine intelligence 10. Chichester: Ellis Horwood.Google Scholar
Rulequest (2017). Rulequest editors. C5.0: An informal tutorial. www.rulequest.com/see5-unix.html.Google Scholar
Rychtyckyj, N. (1999). DLMS: Ten years of AI for vehicle assembly process planning. In Proceedings of the Eleventh Conference on Innovative Applications of Artificial Intelligence (IAAI-99) (pp. 821828), Orlando, FL: Association for the Advancement of Artificial Intelligence.Google Scholar
Samuel, A. (1959). Some studies in machine learning using the game of checkers. IBM Journal of Research and Development, 3, 535554.CrossRefGoogle Scholar
Scott, A. C., Clayton, J. E., & Gibson, E. L. (1991). A practical guide to knowledge acquisition. Boston: Addison-Wesley Longman.Google Scholar
Shadbolt, N. R., & Burton, A. M. (1989). Empirical studies in knowledge elicitation. ACM-SIGART Bulletin (Special Issue on Knowledge Acquisition), 108, 1518.Google Scholar
Shanteau, J. (1988). Psychological characteristics and strategies of expert decision makers. Acta Psychologica, 68, 203215.Google Scholar
Shaw, M. L. G., & Gaines, B. R. (1987). An interactive knowledge elicitation technique using personal construct technology. In Kidd, A. (ed.), Knowledge elicitation for expert systems: A practical handbook (pp. 109136). New York: Plenum Press.Google Scholar
Shortliffe, E. H. (1976). Computer-based medical consultation: MYCIN. New York: American Elsevier.Google Scholar
Simon, H. A., & Chase, W. G. (1973). Skill in chess. American Scientist, 621, 394403.Google Scholar
Smith, R., & Eckroth, J. (2016). Building AI applications: Yesterday, today, and tomorrow. AI Magazine, in press.Google Scholar
Smith, R., & Farquhar, A. (2000). The road ahead for knowledge management: An AI perspective. AI Magazine, 21, 1740.Google Scholar
Tecuci, G., Marcu, D., Boicu, M., & Schum, D. A. (2015). Knowledge engineering: Building personal learning assistants for evidence-based reasoning. Cambridge University Press.Google Scholar
Thompson, D. (2015). A world without work. The Atlantic (July–August). www.theatlantic.com/magazine/archive/2015/07/world-without-work/395294/.Google Scholar
Thompson, E. D., Frolich, E., Bellows, J. C., Bassford, B. E., Skiko, E. J., & Fox, M. S. (2015). Process Diagnosis System (PDS): A 30 year history. In Proceedings of the Twenty-Seventh Conference on Innovative Applications of Artificial Intelligence (IAAI-13) (pp. 39283933). Austin, TX: Association for the Advancement of Artificial Intelligence.Google Scholar
Tversky, A., & Kahneman, D. (1974). Judgment under uncertainty: Heuristics and biases. Science, 185, 11241131.Google Scholar
Urmson, C., Baker, C., Dolan, J., Rybski, P., Salesky, B., Whittaker, W., … & Darms, M. (2009). Autonomous driving in traffic: Boss and the urban challenge. AI Magazine, 30, 1728.Google Scholar
Weiss, S. M., Kulikowski, C. A., Amarel, S., & Safir, A. (1978). A model-based method for computer-aided medical decision-making. Artificial Intelligence, 11, 145172.Google Scholar
Wilkins, D. C., Clancey, W. J., & Buchanan, B. G. (1987). Knowledge base refinement by monitoring abstract control knowledge. International Journal of Man–Machine Studies, 27, 281293.Google Scholar
Zadeh, L. (1965). Fuzzy sets. Information and Control, 8, 338353.Google Scholar

References

Ackerman, P. L. (2005). Ability determinants of individual differences in skilled performance. In Sternberg, R. J. & Pretz, J. E. (eds.), Cognition and intelligence: Identifying the mechanisms of the mind (pp. 142159). Cambridge University Press.Google Scholar
Anderson, J. R. (1982). Acquisition of cognitive skill. Psychological Review, 89, 369406.Google Scholar
Baartman, L. K. J., & de Bruijn, E. (2011). Integrating knowledge, skills and attitudes: Conceptualising learning processes towards vocational competence. Educational Research Review, 6, 125134.Google Scholar
Baldwin, J. M. (1894). Personality-suggestion. Psychological Review, 1, 274279.Google Scholar
Barsalou, L. W. (2003). Situated simulation in the human conceptual system. Language and Cognitive Processes, 18, 513562.Google Scholar
Billett, S. (1996). Situated learning: Bridging sociocultural and cognitive theorising. Learning and Instruction, 6, 263280.Google Scholar
Billett, S. (2000). Guided learning at work. Journal of Workplace Learning, 12, 272285.Google Scholar
Billett, S. (2001). Knowing in practice: Re-conceptualising vocational expertise. Learning and Instruction, 11, 431452.Google Scholar
Billett, S. (2003). Sociogeneses, activity and ontogeny. Culture and Psychology, 9, 133169.Google Scholar
Billett, S. (2006). Constituting the workplace curriculum. Journal of Curriculum Studies, 38, 3148.Google Scholar
Billett, S. (2009a). Personal epistemologies, work and learning. Educational Research Review, 4, 210219.Google Scholar
Billett, S. (2009b). Realising the educational worth of integrating work experiences in higher education. Studies in Higher Education, 34, 827843.Google Scholar
Billett, S. (2011). Workplace curriculum: Practice and propositions. In Dorchy, D. G. F. (ed.), Theories of learning (pp. 1736). London: Routledge.Google Scholar
Billett, S. (2013). Recasting transfer as a socio-personal process of adaptable learning. Educational Research Review, 8, 513.Google Scholar
Billett, S. (2014). Mimetic learning at work: Learning in the circumstances of practice. Dordrecht: Springer.Google Scholar
Billett, S. (2015). Integrating practice-based learning experiences into higher education programs. Dordrecht: Springer.Google Scholar
Billett, S., Harteis, C., & Gruber, H. (eds.) (2014). International handbook of research in professional and practice-based learning. Dordrecht: Springer.Google Scholar
Bloor, G., & Dawson, G. (1994). Understanding professional culture in organizational context. Organization Studies, 15, 275295.Google Scholar
Boshuizen, H. P. A., & Schmidt, H. G. (1992). On the role of biomedical knowledge in clinical reasoning by experts, intermediates and novices. Cognitive Science, 16, 153184.Google Scholar
Boshuizen, H. P. A., Schmidt, H. G., Custers, E. J. F. M., & van de Wiel, M. W. (1995). Knowledge development and restructuring in the domain of medicine: The role of theory and practice. Learning and Instruction, 5, 269289.Google Scholar
Breckwoldt, J., Gruber, H., & Wittmann, A. (2014). Simulation learning. In Billett, S., Harteis, C., & Gruber, H. (eds.), International handbook of research in professional and practice-based learning (pp. 673698). Dordrecht: Springer.Google Scholar
Bunn, S. (1999). The nomad’s apprentice: Different kinds of apprenticeship among Kyrgyz nomads in Central Asia. In Ainely, P. & Rainbird, H. (eds.), Apprenticeship: Towards a new paradigm of learning (pp. 7485). London: Kogan Page.Google Scholar
Chan, S. (2013). Learning through apprenticeship: Belonging to a workplace, becoming and being. Vocations and Learning: Studies in Vocational and Professional Education, 6, 367383.Google Scholar
Collins, A., Brown, J. S., & Newman, S. E. (1989). Cognitive apprenticeship: Teaching the crafts of reading, writing and mathematics. In Resnick, L. B. (ed.), Knowing, learning and instruction: Essays in honour of Robert Glaser (pp. 453494). Hillsdale, NJ: Erlbaum.Google Scholar
Dalton, G. W., Thompson, P. H., & Price, R. L. (1977). The four stages of professional careers: A new look at performance by professionals. Organizational Dynamics, 6, 1942.Google Scholar
Damasio, A. (2012). Self comes to mind: Constructing the conscious brain. London: Vintage.Google Scholar
Davies, B. (2000). A body of writing 1990–1999. New York: Altamira.Google Scholar
De Jong, T., & Ferguson-Hessler, M. G. M. (1996). Types and qualities of knowledge. Educational Psychologist, 31, 105113.Google Scholar
Dornan, T., & Teunissen, P. W. (2014). Medical education. In Billett, S., Harteis, C., & Gruber, H. (eds.), International handbook of research in professional and practice-based learning (pp. 561589). Dordrecht: Springer.Google Scholar
Dreyfus, H. L., & Dreyfus, S. E. (1986). Mind over machine: The power of human intuition and expertise in the era of the computer. New York: Free Press.Google Scholar
Elmore, C., & Massey, B. (2012). Need for instruction in entrepreneurial journalism: Perspective of full-time freelancers. Journal of Media Practice, 13, 109124.Google Scholar
Engeström, Y., & Sannino, A. (2010). Studies of expansive learning: Foundations, findings and future challenges. Educational Research Review, 5, 124.Google Scholar
Eraut, M. (2000). Non-formal learning and tacit knowledge in professional work. British Journal of Educational Psychology, 70, 113136.Google Scholar
Eraut, M. (2004a). Informal learning in the workplace. Studies in Continuing Education, 26, 247273.Google Scholar
Eraut, M. (2004b). Transfer of knowledge between education and workplace settings. In Rainbird, H., Fuller, A., & Munro, A. (eds.), Workplace learning in context (pp. 201221). London: Routledge.Google Scholar
Ericsson, K. A. (2014). Why expert performance is special and cannot be extrapolated from studies of performance in the general population: A response to criticisms. Intelligence, 45, 81103.Google Scholar
Ericsson, K. A., Charness, N., Hoffman, R. R., & Feltovich, P. J. (eds.) (2006). The Cambridge handbook of expertise and expert performance. Cambridge University Press.Google 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, 363406.Google Scholar
Ericsson, K. A., & Smith, J. (1991). Towards a general theory of expertise. Cambridge University Press.Google Scholar
Fitts, P. M. (1964). Perceptual-motor skill learning. In Melton, A. W. (ed.), Categories of human learning (pp. 243285). New York: Academic Press.Google Scholar
Gartmeier, M., Bauer, J., Gruber, H., & Heid, H. (2008). Negative knowledge: Understanding professional learning and expertise. Vocations and Learning: Studies in Vocational and Professional Education, 1, 87103.Google Scholar
Goller, M., & Billett, S. (2014). Agentic behaviour at work: Crafting learning experiences. In Harteis, C., Rausch, A., & Seifried, J. (eds.), Discourses on professional learning: On the boundary between learning and working (pp. 2544). Dordrecht: Springer.Google Scholar
Goodnow, J. J. (1986). Some lifelong everyday forms of intelligent behaviour: Organizing and reorganizing. In Sternberg, R. J. & Wagner, R. K. (eds.), Practical intelligence: Nature and origins of competence in the everyday world (pp. 143166). Cambridge University Press.Google Scholar
Goody, E. (1989). Learning, apprenticeship and division of labor. In Coy, M. W. (ed.), Apprenticeship: From theory to method and back again (pp. 233256). Albany: SUNY Press.Google Scholar
Gott, S. (1989). Apprenticeship instruction for real-world tasks: The coordination of procedures, mental models, and strategies. Review of Research in Education, 15, 97169.Google Scholar
Gowlland, G. (2012). Learning craft skills in China: Apprenticeship and social capital in an artisan community of practice. Anthropology and Education Quarterly, 43, 358371.Google Scholar
Greenwood, D., Davids, K., & Renshaw, I. (2012). How elite coaches’ experiential knowledge might enhance empirical research on sport performance. International Journal of Sports Science and Coaching, 7, 411422.Google Scholar
Greinert, W.-D. (2004). European vocational training systems: The theoretical context of historical development. In Greinert, W.-D. & Hanf, G. (eds.), Towards a history of vocational education and training (VET) in Europe in a comparative perspective. Proceedings of the First International Conference, October 2002, Florence (pp. 127). Luxembourg: Office for Official Publications of the European Communities.Google Scholar
Groen, G. J., & Patel, P. (1988). The relationship between comprehension and reasoning in medical expertise. In Chi, M. T. H., Glaser, R., & Farr, R. (eds.), The nature of expertise (pp. 287310). Hillsdale, NJ: Erlbaum.Google Scholar
Gruber, H., Lehtinen, E., Palonen, T., & Degner, S. (2008). Persons in the shadow: Assessing the social context of high abilities. Psychology Science Quarterly, 50, 237258.Google Scholar
Guberman, S. R., & Greenfield, P. M. (1991). Learning and transfer in everyday cognition. Cognitive Development, 6, 233260.Google Scholar
Guile, D., & Griffiths, T. (2001). Learning through work experience. Journal of Education and Work, 14, 113131.Google Scholar
Hacker, W. (2003). Action regulation theory: A practical tool for the design of modern work processes? European Journal of Work and Organizational Psychology, 12, 105130.Google Scholar
Hakkarainen, K., Hytönen, K., Lonka, K., & Makkonen, J. (2014). How does collaborative authoring in doctoral programs socially shape practices of academic excellence? Talent Development and Excellence, 6, 1129.Google Scholar
Hakkarainen, K., Palonen, T., Paavola, S., & Lehtinen, E. (2004). Communities of networked expertise: Educational and professional perspectives. Amsterdam: Elsevier.Google Scholar
Harteis, C., & Billett, S. (2013). Intuitive expertise: Theories and empirical evidence. Educational Research Review, 9, 145157.Google Scholar
Herbig, B., & Müller, A. (2014). Implicit knowledge and work performance. In Billett, S., Harteis, C., & Gruber, H. (eds.), International handbook of research in professional and practice-based learning (pp. 781806). Dordrecht: Springer.Google Scholar
Hofmann, W., Schmeichel, B. J., & Baddeley, A. D. (2012). Executive functions and self-regulation. Trends in Cognitive Sciences, 16, 174180.Google Scholar
Jordan, B. (1989). Cosmopolitical obstetrics: Some insights from the training of traditional midwives. Social Science and Medicine, 28, 925944.Google Scholar
Kirschner, P. A. (2002). Cognitive load theory: Implications of cognitive load theory on the design of learning. Learning and Instruction, 12, 110.Google Scholar
Kolodner, J. L. (1983). Towards an understanding of the role of experience in the evolution from novice to expert. International Journal of Man–Machine Studies, 19, 497518.Google Scholar
Kosslyn, S. M., Thompson, W. L., & Ganis, G. (2006). The case for mental imagery. Oxford University Press.Google Scholar
Lakoff, G., & Johnson, M. (1999). Philosophy in the flesh: The embodied mind and its challenge to western thought. New York: Basic Books.Google Scholar
Lave, J. (1990). The culture of acquisition and the practice of understanding. In Stigler, J. W., Shweder, R. A., & Herdt, G. (eds.), Cultural psychology (pp. 259286). Cambridge University Press.Google Scholar
Lehmann, A. C., & Gruber, H. (2006). Music. In Ericsson, K. A., Charness, N., Hoffman, R. R., & Feltovich, P. J. (eds.), The Cambridge handbook of expertise and expert performance (pp. 457470). Cambridge University Press.Google Scholar
Lehmann, A. C., & Kristensen, F. (2014). “Persons in the shadow” brought to light: Parents, teachers, and mentors. How guidance works in the acquisition of musical skills. Talent Development and Excellence, 6, 5770.Google Scholar
Malle, B. F., Moses, L. J., & Baldwin, D. A. (2001). Introduction: The significance of intentionality. In Malle, B. F., Moses, L. J., & Baldwin, D. A. (eds.), Intentions and intentionality: Foundations of social cognition (pp. 126). Cambridge, MA: MIT Press.Google Scholar
Mandl, H., Gruber, H., & Renkl, A. (1996). Learning to apply: From “school garden instruction” to technology-based learning environments. In Vosniadou, S., De Corte, E., Glaser, R., & Mandl, H. (eds.), International perspectives on the design of technology-supported learning environments (pp. 307321). Mahwah, NJ: Erlbaum.Google Scholar
Marchand, T. H. J. (2008). Muscles, morals and mind: Craft apprenticeship and the formation of person. British Journal of Educational Studies, 56, 245271.Google Scholar
Marsh, C. J. (2004). Key concepts for understanding curriculum. London: Routledge Falmer.Google Scholar
Martin, L., & Scribner, S. (1991). Laboratory for cognitive studies of work: A case study of the intellectual implications of a new technology. Teachers College Record, 92, 592602.Google Scholar
Miller, P. H. (1996). Mapping the mind: Where are the state lines? Cognitive Development, 11, 141155.Google Scholar
Newton, J., Billett, S., Jolly, B., & Ockerby, C. (2011). Preparing nurses and engaging preceptors. In Billett, S. & Henderson, A. (eds.), Developing learning professionals: Integrating experiences in university and practice settings (pp. 4358). Dordrecht: Springer.Google Scholar
Nonaka, I., & Takeuchi, H. (1995). The knowledge-creating company: How Japanese companies create the dynamics of innovation. Oxford University Press.Google Scholar
OECD (2013). OECD skills outlook 2013: First results from the survey of adult skills. Paris: OECD.Google Scholar
Palincsar, A. S., & Brown, A. L. (1984). Reciprocal teaching of comprehension-fostering and comprehension-monitoring activities. Cognition and Instruction, 1, 117175.Google Scholar
Palonen, T., Boshuizen, H. P. A., & Lehtinen, E. (2014). How expertise is created in emerging professional fields. In Halttunen, T., Koivisto, M., & Billett, S. (eds.), Promoting, assessing, recognizing and certifying lifelong learning (pp. 131150). New York: Springer.Google Scholar
Pelissier, C. (1991). The anthropology of teaching and learning. Annual Review of Anthropology, 20, 7595.Google Scholar
Perkins, D., Jay, E., & Tishman, S. (1993). Beyond abilities: A dispositional theory of thinking. Merrill-Palmer Quarterly, 39, 121.Google Scholar
Reber, A. S. (1989). Implicit learning and tacit knowledge. Journal of Experimental Psychology: General, 118, 219235.Google Scholar
Reber, A. S. (1992). An evolutionary context for the cognitive unconscious. Philosophical Psychology, 5, 3351.Google Scholar
Rehrl, M., Palonen, T., Lehtinen, E., & Gruber, H. (2014). Experts in science: Visibility in research communities. Talent Development and Excellence, 6, 3145.Google Scholar
Resnick, L. (1987). Learning in school and out. Educational Researcher, 16, 1320.Google Scholar
Rice, T. (2010). Learning to listen: Auscultation and the transmission of auditory knowledge. Journal of the Royal Anthropological Institute (NS), 16, S41S61.Google Scholar
Rogoff, B. (1990). Apprenticeship in thinking: Cognitive development in social context. Oxford University Press.Google Scholar
Rogoff, B. (1995). Observing sociocultural activity on three planes: Participatory appropriation, guided participation, apprenticeship. In Wertsch, J. W., Alvarez, A., & del Rio, P. (eds.), Sociocultural studies of mind (pp. 139164). Cambridge University Press.Google Scholar
Rohbanfard, H., & Proteau, L. (2011). Learning through observation: A combination of expert and novice models favors learning. Experimental Brain Research, 215, 183197.Google Scholar
Rosenthal, T. L., & Zimmerman, B. J. (2014). Social learning and cognition. New York: Academic Press.Google Scholar
Roth, W. M. (2001). Modeling design as situated and attributed process. Learning and Instruction, 11, 211239.Google Scholar
Schaap, H., de Bruijn, E., van der Schaaf, M. F., & Kirschner, P. A. (2009). Students’ personal professional theories in competence-based vocational education: The construction of personal knowledge through internalisation and socialisation. Journal of Vocational Education and Training, 61, 481494.Google Scholar
Schmidt, H. G., & Boshuizen, H. P. A. (1992). Encapsulation of biomedical knowledge. In Evans, D. A. & Patel, V. L. (eds.), Advanced models of cognition for medical training and practice (pp. 265282). New York: Springer.Google Scholar
Schmidt, H. G., & Boshuizen, H. P. A. (1993). On acquiring expertise in medicine. Educational Psychology Review, 5, 205221.Google Scholar
Schmidt, H. G., Norman, G. R., & Boshuizen, H. P. A. (1990). A cognitive perspective on medical expertise: Theory and implications. Academic Medicine, 65, 611621. Erratum in Academic Medicine, 67, 287.Google Scholar
Schmidt, H. G., & Rikers, R. M. J. P. (2007). How expertise develops in medicine: Knowledge encapsulation and illness script formation. Medical Education, 41, 11331139.Google Scholar
Scribner, S. (1984). Studying working intelligence. In Rogoff, B. & Lave, J. (eds.), Everyday cognition: Its development in social context (pp. 940). Cambridge, MA: Harvard University Press.Google Scholar
Scribner, S. (1985). Knowledge at work. Anthropology & Education, 16, 199206.Google Scholar
Shuell, T. J. (1990). Phases of meaningful learning. Review of Educational Research, 60, 531547.Google Scholar
Sinclair, S. (1997). Making doctors: An institutional apprenticeship. Oxford: Berg.Google Scholar
Singleton, J. (1989). The Japanese folkcraft pottery apprenticeship: Cultural patterns of an educational institution. In Coy, M. W. (ed.), Apprenticeship: From theory to method and back again (pp. 1330). New York: SUNY Press.Google Scholar
Skule, S. (2004). Learning conditions at work: A framework to understand and assess informal learning in the workplace. International Journal of Training and Development, 8, 820.Google Scholar
Sun, R., Merrill, E., & Peterson, T. (2001). From implicit skills to explicit knowledge: A bottom-up model of skill development. Cognitive Science, 25, 203244.Google Scholar
Thornton Moore, D. (2004). Curriculum at work: An educational perspective on the workplace as a learning environment. Journal of Workplace Learning, 16, 325340.Google Scholar
Tigelaar, D. E. H., & van der Vleuten, C. P. M. (2014). Assessment of professional competence. In Billett, S., Harteis, C., & Gruber, H. (eds.), International handbook of research in professional and practice-based learning (pp. 12371269). Dordrecht: Springer.Google Scholar
Tomasello, M. (2004). Learning through others. Daedalus, 133, 5158.Google Scholar
Tynjälä, P. (2008). Perspectives into learning in the workplace. Education Research Review, 3, 130154.Google Scholar
Valsiner, J. (2000). Culture and human development. London: Sage Publications.Google Scholar
Valsiner, J., & van der Veer, R. (2000). The social mind: Construction of the idea. Cambridge University Press.Google Scholar
Wagner, R. K., & Sternberg, R. J. (1986). Tacit knowledge and intelligence in the everyday world. In Sternberg, R. J. & Wagner, R. K. (eds.), Practical intelligence: Nature and origins of competence in the everyday world (pp. 5183). Cambridge University Press.Google Scholar
Webb, E. (1999). Making meaning: Language for learning. In Ainely, P. & Rainbird, H. (eds.), Apprenticeship: Towards a new paradigm of learning (pp. 100110). London: Kogan Page.Google Scholar
Zimmerman, B. J. (2006). Development and adaptation of expertise: The role of self-regulatory processes and beliefs. In Ericsson, K. A., Charness, N., Hoffman, R. R., & Feltovich, P. J. (eds.), The Cambridge handbook of expertise and expert performance (pp. 705722). Cambridge University Press.Google Scholar

References

Abbott, A. (1988). The system of professions: An essay on the division of expert labor. University of Chicago Press.Google Scholar
Adams, T. L. (2015). Sociology of professions: International divergences and research directions. Work, Employment & Society, 29, 154165.Google Scholar
Adler, P. S., Kwon, S. W., & Heckscher, C. (2008). Professional work: The emergence of collaborative community. Organization Science, 19, 359376.Google Scholar
Becker, G. (2011). Challenging Merton’s Protestantism–science hypothesis: The historical impact of sacerdotal celibacy on German science and scholarship. Journal for the Scientific Study of Religion, 50, 351365.Google Scholar
Ben-David, J. (1965). The scientific role: The conditions of its establishment in Europe. Minerva, 4, 1554.Google Scholar
Ben-David, J. (1972). The profession of science and its powers. Minerva, 10, 362383.Google Scholar
Berkes, F. (1999). Sacred ecology. London: Routledge.Google Scholar
Brante, T. (2010). Professional fields and truth regimes: In search of alternative approaches. Comparative Sociology, 9, 843886.Google Scholar
Braudel, F. (1992). The wheels of commerce: Civilization and capitalism, 15th–18th century (Vol. II). Berkeley, CA: University of California Press. (Original work published 1979)Google Scholar
Cadden, J. (2013). The organization of knowledge: Disciplines and practices. In Lindberg, D. C. & Shank, M. H. (eds.), The Cambridge history of science, Vol. 2: Medieval science (pp. 240267). Cambridge University Press.Google Scholar
Callon, M. (1999). The role of lay people in the production and dissemination of scientific knowledge. Science, Technology and Society, 4, 8194.Google Scholar
Carlile, P. R. (2004). Transferring, translating, and transforming: An integrative framework for managing knowledge across boundaries. Organization Science, 15, 555568.Google Scholar
Carlton, E. (1996). The few and the many: A typology of elites. Brookfield, VT: Scolar Press.Google Scholar
Carolan, M. S. (2006). Sustainable agriculture, science and the co-production of “expert” knowledge: The value of interactional expertise. Local Environment, 11, 421431.Google Scholar
Carr-Saunders, A. M., & Wilson, P. A. (1933). The professions. Oxford: Clarendon Press.Google Scholar
Casadevall, A., & Fang, F. C. (2012). Reforming science: Methodological and cultural reforms. Infection and Immunity, 80, 891896.Google Scholar
Chubin, D. E., & Hackett, E. J. (1990). Peerless science. Albany: SUNY Press.Google Scholar
Clark, G. L., Gertler, M. S., Feldman, M. P., & Williams, K. (2003). The Oxford handbook of economic geography. Oxford University Press.Google Scholar
Collins, H., & Evans, R. (2007). Rethinking expertise. University of Chicago Press.Google Scholar
Collins, R. (1979). The credential society: An historical sociology of education and stratification. New York: Academic Press.Google Scholar
Cooper, D., Lowe, A., Puxty, A., Robson, K., & Willmott, H. (1988). Regulating the U.K. accountancy profession: Episodes in the relation between the profession and the state. Paper presented at the ESRC Conference on Corporatism, London, January.Google Scholar
Davies, C. (1995). Gender and the professional predicament in nursing. Buckingham: Open University Press.Google Scholar
Dubar, C. (2000). La crise des identités: L’interprétation d’une mutation. Paris: Presses Universitaires de France.Google Scholar
Durkheim, E. (1992). Professional ethics and civic morals. London: Forgotten Books.Google Scholar
Edelenbos, J., van Buuren, A., & van Schie, N. (2011). Co-producing knowledge: Joint knowledge production between experts, bureaucrats and stakeholders in Dutch water management projects. Environmental Science & Policy, 14, 675684.Google Scholar
Edwards, A. (2011). Building common knowledge at the boundaries between professional practices: Relational agency and relational expertise in systems of distributed expertise. International Journal of Educational Research, 50, 3339.Google Scholar
Edwards, P. N., & Schneider, S. H. (2001). Self-governance and peer review in science-for-policy: The case of the IPCC Second Assessment Report. In Miller, C. A. & Edwards, P. N. (eds.), Changing the atmosphere: Expert knowledge and environmental governance (pp. 219246). Cambridge, MA: MIT Press.Google Scholar
Engeström, Y. (2007). Enriching the theory of expansive learning: Lessons from journeys toward coconfiguration. Mind, Culture, and Activity, 14, 2339.Google Scholar
Ericsson, K. A. (1996). 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. 150). Mahwah, NJ: Erlbaum.Google Scholar
Ericsson, K. A. (2006). The influence of experience and deliberate practice on the development of superior expert performance. In Ericsson, K. A., Charness, N., Hoffman, R. R., & Feltovich, P. J. (eds.), The Cambridge handbook of expertise and expert performance (pp. 683703). Cambridge University Press.Google Scholar
Ericsson, K. A. (2014). Why expert performance is special and cannot be extrapolated from studies of performance in the general population: A response to criticisms. Intelligence, 45, 81103.Google Scholar
Etzioni, A. (1969). The semi-professions and their organization: Teachers, nurses, social workers. New York: Free Press.Google Scholar
Etzioni-Halevy, E. (1993). The elite connection: Problems and potential of western democracy. Cambridge: Polity Press.Google Scholar
Evetts, J. (2003). The sociological analysis of professionalism. International Sociology, 18, 395415.Google Scholar
Evetts, J. (2011). Sociological analysis of professionalism: Past, present and future. Comparative Sociology, 10, 137.Google Scholar
Evetts, J. (2013). Professionalism: Value and ideology. Current Sociology Review, 61, 778796.Google Scholar
Faulconbridge, J. R., & Muzio, D. (2011). Professions in a globalizing world: Towards a transnational sociology of the professions. International Sociology, 27, 136152.Google Scholar
Feyerabend, P. (1978). Science in a free society. London: New Left Books.Google Scholar
Foucault, M. (1979). Governmentality. Ideology and Consciousness, 6, 521.Google Scholar
Foucault, M. (1980). Power/knowledge: Selected interviews and other writings 1972–1977. Brighton: Harvester Press.Google Scholar
Fournier, V. (1999). The appeal to professionalism as a disciplinary mechanism. Social Review, 47, 280307.Google Scholar
Freidson, E. (1986). Professional powers: A study of the institutionalization of formal knowledge. University of Chicago Press.Google Scholar
Freidson, E. (1994). Professionalism reborn: Theory, prophecy and policy. Cambridge: Polity Press.Google Scholar
Freidson, E. (2001). Professionalism: The third logic. London: Polity Press.Google Scholar
Gibbons, M., Limoges, C., Nowotny, H., Schwartzman, S., Scott, P., & Trow, M. (1994). The new production of knowledge: The dynamics of science and research in contemporary societies. Newbury Park, CA: Sage Publications.Google Scholar
Gobet, F. (2015). Understanding expertise: A multi-disciplinary approach. Basingstoke: Palgrave Macmillan.Google Scholar
Gorman, E. H., & Sandefur, R. L. (2011). “Golden Age,” quiescence, and revival: How the sociology of professions became the study of knowledge-based work. Work and Occupations, 38, 275302.Google Scholar
Gribbin, J. R. (2008). The Britannica guide to the 100 most influential scientists. London: Running Press.Google Scholar
Guthrie, W. K. C. (2004). The Greek philosophers from Thales to Aristotle. London: Routledge. (Original work published 1950)Google Scholar
Haas, P. M. (1992). Introduction: Epistemic communities and international policy coordination. In Haas, P. M. (ed.), Knowledge, power and international policy coordination (pp. 135). Cambridge, MA: MIT Press.Google Scholar
Hakkarainen, K., Palonen, T., Paavola, S., & Lehtinen, E. (2004). Communities of networked expertise. Amsterdam: Elsevier.Google Scholar
Halliday, T. C. (1987). Beyond monopoly: Lawyers, state crises and professional empowerment. University of Chicago Press.Google Scholar
Hambrick, D. Z., Oswald, F. L., Altmann, E. M., Meinz, E. J., Gobet, F., & Campitelli, G. (2014). Deliberate practice: Is that all it takes to become an expert? Intelligence, 45, 3445.Google Scholar
Hoffman, R. R., Feltovich, P. J., & Ford, K. M. (1997). A general framework for conceiving of expertise and expert systems in context. In Feltovich, P. J., Ford, K. M., & Hoffman, R. R. (eds.), Expertise in context: Human and machine (pp. 543580). Menlo Park, CA: AAAI Press.Google Scholar
Hughes, E. C. (1958). Men and their work. New York: Free Press.Google Scholar
Hughes, E. C. (1965). Professions. In Lynn, K. S. (ed.), The professions in America (pp. 114). Boston: Houghton Mifflin.Google Scholar
Jacoby, S., & Gonzales, P. (1991). The constitution of expert-novice in scientific discourse. Issues in Applied Linguistics, 2, 149181.Google Scholar
Jasanoff, S. (ed.) (2004). States of knowledge: The co-production of science and social order. London: Routledge.Google Scholar
Jensen, K., Lahn, L. C., & Nerland, M. (eds.) (2012). Professional learning in the knowledge society. Rotterdam: Sense Publishers.Google Scholar
Johnson, T. (1972). Professions and power. London: Macmillan.Google Scholar
Johnson-Laird, P. N. (1983). Mental models. Cambridge University Press.Google Scholar
Jones, N. A., Ross, H., Lynam, T., Perez, P., & Leitch, A. (2011). Mental models: An interdisciplinary synthesis of theory and methods. Ecology and Society, 16, 46.Google Scholar
Knorr Cetina, K. (1981). The manufacture of knowledge: An essay on the constructivist and contextual nature of science. Oxford: Pergamon.Google Scholar
Knorr Cetina, K. (1999). Epistemic cultures: How the sciences make knowledge. Cambridge, MA: Harvard University Press.Google Scholar
Kolabinska, M. (1912). La circulation des élites en France. Lausanne: Imp. réunies.Google Scholar
Larkin, G. (1983). Occupational monopoly and modern medicine. London: Tavistock.Google Scholar
Larson, M. S. (1977). The rise of professionalism. Berkeley, CA: University of California Press.Google Scholar
Latour, B., & Woolgar, S. (1986). Laboratory life: The construction of scientific facts. Beverly Hills, CA: Sage Publications.Google Scholar
Lave, J., & Wenger, E. (1991). Situated learning: Legitimate peripheral participation. Cambridge University Press.Google Scholar
Lerner, R., Nagai, A. K., & Rothman, S. (1996). American elites. New Haven, CT: Yale University Press.Google Scholar
Lindberg, D. C., & Shank, M. H. (eds.) (2013). The Cambridge history of science, Vol. 2: Medieval science. Cambridge University Press.Google Scholar
Luhmann, N. (1995). Social systems (trans. Bednarz, J. & Baecker, D.). Stanford University Press.Google Scholar
MacDonald, K. M. (1995). The sociology of the professions. London: Sage Publications.Google Scholar
Marsh, H. W., & Ball, S. (1989). The peer review process used to evaluate manuscripts submitted to academic journals. Journal of Experimental Education, 57, 151169.Google Scholar
Marshall, T. H. (1950). Citizenship and social class and other essays. Cambridge University Press.Google Scholar
McClelland, C. E. (1990). Escape from freedom? Reflections on German professionalization 1870–1933. In Torstendahl, R. & Burrage, M. (eds.), The formation of professions: Knowledge, state and strategy (pp. 97113). London: Sage Publications.Google Scholar
Merton, R. K. (1973a). The normative structure of science. In Storer, N. W. (ed.), The sociology of science (pp. 267278). University of Chicago Press. (Original work published 1942)Google Scholar
Merton, R. K. (1973b). The Puritan spur to science. In Storer, N. W. (ed.), The sociology of science (pp. 228253). University of Chicago Press. (Original work published 1938)Google Scholar
Merton, R. K., & Zuckerman, H. (1973). Age, aging, and age structure in science. In Storer, N. W. (ed.), The sociology of science (pp. 479560). University of Chicago Press. (Original work published 1972)Google Scholar
Mieg, H. A. (2001). The social psychology of expertise. Mahwah, NJ: Erlbaum. (New paperback edition, 2012)Google Scholar
Mieg, H. A. (2006). System experts and decision making experts in transdisciplinary projects. International Journal of Sustainability in Higher Education, 7, 341351.Google Scholar
Mieg, H. A. (2009). Two factors of expertise? Excellence and professionalism of environmental experts. High Ability Studies, 20, 91115.Google Scholar
Mieg, H. A. (2014). The organisational embedding of expertise: Centres of excellence. Talent Development and Excellence, 6, 7193.Google Scholar
Mieg, H. A., de Sombre, S., & Naef, M. A. (2013). How formality works: The case of environmental professionals. Professions & Professionalism, 3. http://dx.doi.org/10.7577/pp.564.Google Scholar
Mieg, H. A., & Frischknecht, P. M. (2014). Multidisziplinär, antidisziplinär, disziplinär? Die Geschichte der Umweltnaturwissenschaften an der ETH Zürich (History of environmental sciences at ETH Zurich). In Engler, B. (ed.), Disziplin/Discipline (pp. 135169). Fribourg Academic Press.Google Scholar
Miller, P., & Rose, N. (1990). Governing economic life. Economy and Society, 19, 131.Google Scholar
Moran, B. T. (2006). Courts and academies. In Park, K. & Daston, L. (eds.), The Cambridge history of science, Vol. 3: Early modern science (pp. 251271). Cambridge University Press.Google Scholar
Moscovici, S. (1993). Toward a social psychology of science. Journal for the Theory of Social Behavior, 23, 343374.Google Scholar
Noordegraaf, M. (2007). From “pure” to “hybrid” professionalism. Administration & Society, 39, 761785.Google Scholar
Nowotny, H., Scott, P., & Gibbons, M. (2001). Re-thinking science. Cambridge: Polity Press.Google Scholar
OECD (1999). Managing national innovation systems. Paris: OECD.Google Scholar
OECD (2005). Oslo manual: Proposed guidelines for collecting and interpreting innovation data. Paris: OECD.Google Scholar
Olgiati, V., Orzack, L. H., & Saks, M. (eds.) (1998). Professions, identity and order in comparative perspective. Onati: International Institute for the Sociology of Law.Google Scholar
Pareto, V. (1963). The mind and society: A treatise on general sociology (ed. Livingstone, A.). New York: Dover. (Italian original from 1916: Trattato di sociologia generale)Google Scholar
Parsons, T. (1951). The social system. New York: Free Press.Google Scholar
Parsons, T. (1968). Professions. In Sills, D. L. (ed.), International encyclopedia of the social sciences (Vol. 12, pp. 536547). London: Macmillan.Google Scholar
Peltokorpi, V. (2008). Transactive memory systems. Review of General Psychology, 12, 378394.Google Scholar
Perera, A. H., Drew, C. A., & Johnson, C. (eds.) (2012). Expert knowledge and its application in landscape ecology. New York: Springer.Google Scholar
Rau, D., & Haerem, T. (2010). Applying an organizational learning perspective to new technology deployment by technological gatekeepers. Information Systems Frontiers, 12, 287297.Google Scholar
Ross, S. (1962). Scientist: The story of a word. Annals of Science, 18, 6585.Google Scholar
Rucht, D. (1990). The strategies and action repertoires of new movements. In Dalton, R. J. & Kuechler, M. (eds.), Challenging the political order: New social and political movements in Western democracies (pp. 156175). Cambridge: Polity Press.Google Scholar
Sagasti, F. (2000). The twilight of the Baconian age and the future of humanity. Futures, 32, 595602.Google Scholar
Saks, M. (1995). Professions and the public interest. London: Routledge.Google Scholar
Saks, M. (2010). Analyzing the professions: The case for the neo-Weberian approach. Comparative Sociology, 9, 887915.Google Scholar
Scholz, R. W., Mieg, H. A., & Oswald, J. (2000). Transdisciplinarity in groundwater management: Towards mutual learning of science and society. Water, Air, & Soil Pollution, 123, 477487.Google Scholar
Scholz, R. W., & Tietje, O. (2002). Embedded case study methods: Integrating quantitative and qualitative knowledge. Thousand Oaks, CA: Sage Publications.Google Scholar
Sciulli, D. (2005). Continental sociology of professions today: Conceptual contributions. Current Sociology, 53, 915942.Google Scholar
Shank, M. H. (2013). Schools and universities in medieval Latin science. In Lindberg, D. C. & Shank, M. H. (eds.), The Cambridge history of science, Vol. 2: Medieval science (pp. 207239). Cambridge University Press.Google Scholar
Shanteau, J. (1988). Psychological characteristics and strategies of expert decision makers. Acta Psychologica, 68, 203215.Google Scholar
Shanteau, J. (1992). Competence in experts: The role of task characteristics. Organizational Behavior and Human Decision Processes, 53, 252266.Google Scholar
Shanteau, J. (2015). Why task domains (still) matter for understanding expertise. Journal of Applied Research in Memory and Cognition, 4, 169175.Google Scholar
Spier, R. (2002). The history of the peer-review process. Trends in Biotechnology, 20, 357358.Google Scholar
Stasser, G., Stewart, D. D., & Wittenbaum, G. D. (1995). Expert roles and information exchange during discussion: The importance of knowing who knows what. Journal of Experimental Social Psychology, 31, 244265.Google Scholar
Stasser, G., & Titus, W. (2003). Hidden profiles: A brief history. Psychological Inquiry, 14, 304313.Google Scholar
Stewart, D. D., & Stasser, G. (1995). Expert role assignment and information sampling during collective recall and decision making. Journal of Personality and Social Psychology, 69, 619628.Google Scholar
Stichweh, R. (1992). The sociology of scientific disciplines: On the genesis and stability of the disciplinary structure of modern science. Science in Context, 5, 315.Google Scholar
Stutt, A., & Motta, E. (1998). Knowledge modelling: An organic technology for the knowledge age. In Eisenstadt, M. & Vincent, T. (eds.), The knowledge web (pp. 211224). London: Kogan Page.Google Scholar
Tawney, R. H. (1921). The acquisitive society. New York: Harcourt Brace.Google Scholar
Thompson Klein, J. (2014). Discourses of transdisciplinarity: Looking back to the future. Futures, 63, 6874.Google Scholar
Toma, C., Vasiljevic, D., Oberlé, D., & Butera, F. (2013). Assigned experts with competitive goals withhold information in group decision making. British Journal of Social Psychology, 52, 161172.Google Scholar
Turner, S. P. (2014). The politics of expertise. London: Routledge.Google Scholar
von Schomberg, R. (2013). A vision of responsible research and innovation. In Owen, R., Bessant, J., & Heintz, M. (eds.), Responsible innovation (pp. 5174). Chichester: John Wiley.Google Scholar
Weber, M. (1917). Wissenschaft als Beruf (Science as a vocation). Tübingen: Mohr.Google Scholar
Weber, M. (1979). Economy and society (trans. Roth, G. & Wittich, C.). Berkeley, CA: University of California Press.Google Scholar
Wegner, D. M. (1987). Transactive memory: A contemporary analysis of the group mind. In Mullen, B. & Goethals, G. R. (eds.), Theories of group behavior (pp. 185208). New York: Springer.Google Scholar
Weiss, D. J., & Shanteau, J. (2014). Who’s the best? A relativistic view of expertise. Applied Cognitive Psychology, 28, 447457.Google Scholar
Wilensky, H. L. (1964). The professionalization of everyone? American Journal of Sociology, 70, 137158.Google Scholar
Zuckerman, H., Cole, J., & Bruer, J. (eds.) (1991). The outer circle: Women in the scientific community. New York: Norton.Google Scholar

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