Book contents
- The Cambridge Handbook of Expertise and Expert Performance
- The Cambridge Handbook of Expertise and Expert Performance
- Copyright page
- Contents
- Notes on Contributors
- Acknowledgments
- Part I Introduction and Perspectives
- Part II Overview of Approaches to the Study of Expertise: Brief Historical Accounts of Theories and Methods
- Part III Methods for Studying the Structure of Expertise
- 10 Perception in Expertise
- 11 Eliciting and Representing the Knowledge of Experts
- 12 Capturing Expert Thought with Protocol Analysis: Concurrent Verbalizations of Thinking during Experts’ Performance on Representative Tasks
- 13 Methods for Studying the Structure of Expertise: Psychometric Approaches
- 14 Studies of the Activation and Structural Changes of the Brain Associated with Expertise
- Part IV Methods for Studying the Acquisition and Maintenance of Expertise
- Part V.I Domains of Expertise: Professions
- Part V.II Domains of Expertise: Arts, Sports, Games, and Other Skills
- Part VI Generalizable Mechanisms Mediating Types of Expertise
- Part VII General Issues and Theoretical Frameworks
- Index of Subjects
- References
13 - Methods for Studying the Structure of Expertise: Psychometric Approaches
from Part III - Methods for Studying the Structure of Expertise
Published online by Cambridge University Press: 10 May 2018
Book contents
- The Cambridge Handbook of Expertise and Expert Performance
- The Cambridge Handbook of Expertise and Expert Performance
- Copyright page
- Contents
- Notes on Contributors
- Acknowledgments
- Part I Introduction and Perspectives
- Part II Overview of Approaches to the Study of Expertise: Brief Historical Accounts of Theories and Methods
- Part III Methods for Studying the Structure of Expertise
- 10 Perception in Expertise
- 11 Eliciting and Representing the Knowledge of Experts
- 12 Capturing Expert Thought with Protocol Analysis: Concurrent Verbalizations of Thinking during Experts’ Performance on Representative Tasks
- 13 Methods for Studying the Structure of Expertise: Psychometric Approaches
- 14 Studies of the Activation and Structural Changes of the Brain Associated with Expertise
- Part IV Methods for Studying the Acquisition and Maintenance of Expertise
- Part V.I Domains of Expertise: Professions
- Part V.II Domains of Expertise: Arts, Sports, Games, and Other Skills
- Part VI Generalizable Mechanisms Mediating Types of Expertise
- Part VII General Issues and Theoretical Frameworks
- Index of Subjects
- References
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- The Cambridge Handbook of Expertise and Expert Performance , pp. 213 - 232Publisher: Cambridge University PressPrint publication year: 2018
References
Ackerman, P. L. (1987). Individual differences in skill learning: An integration of psychometric and information processing perspectives. Psychological Bulletin, 102, 3–27.Google Scholar
Ackerman, P. L. (1988). Determinants of individual differences during skill acquisition: Cognitive abilities and information processing. Journal of Experimental Psychology: General, 117, 288–318.Google Scholar
Ackerman, P. L. (1990). A correlational analysis of skill specificity: Learning, abilities, and individual differences. Journal of Experimental Psychology: Learning, Memory, and Cognition, 16, 883–901.Google Scholar
Ackerman, P. L. (1992). Predicting individual differences in complex skill acquisition: Dynamics of ability determinants. Journal of Applied Psychology, 77, 598–614.Google Scholar
Ackerman, P. L. (1996). A theory of adult intellectual development: Process, personality, interests, and knowledge. Intelligence, 22, 229–259.Google Scholar
Ackerman, P. L. (2000). Domain-specific knowledge as the “dark matter” of adult intelligence: Gf/Gc, personality and interest correlates. Journal of Gerontology: Psychological Sciences, 55B, P69–P84.Google Scholar
Ackerman, P. L. (2014). Nonsense, common sense, and science of expert performance: Talent and individual differences. Intelligence, 45, 6–17.Google Scholar
Ackerman, P. L., Bowen, K. R., Beier, M. B., & Kanfer, R. (2001). Determinants of individual differences and gender differences in knowledge. Journal of Educational Psychology, 93, 797–825.Google Scholar
Ackerman, P. L., & Cianciolo, A. T. (2000). Cognitive, perceptual speed, and psychomotor determinants of individual differences during skill acquisition. Journal of Experimental Psychology: Applied, 6, 259–290.Google Scholar
Ackerman, P. L., & Heggestad, E. D. (1997). Intelligence, personality, and interests: Evidence for overlapping traits. Psychological Bulletin, 121, 219–245.Google Scholar
Ackerman, P. L., & Kanfer, R. (1993). Integrating laboratory and field study for improving selection: Development of a battery for predicting air traffic controller success. Journal of Applied Psychology, 78, 413–432.Google Scholar
Ackerman, P. L., Kanfer, R., & Beier, M. E. (2013). Trait complex, cognitive ability, and domain knowledge predictors of baccalaureate success, STEM persistence, and gender differences. Journal of Educational Psychology, 105, 911–927.Google Scholar
Ackerman, P. L., Kanfer, R., & Goff, M. (1995). Cognitive and noncognitive determinants and consequences of complex skill acquisition. Journal of Experimental Psychology: Applied, 1, 270–304.Google Scholar
Ackerman, P. L., & Rolfhus, E. L. (1999). The locus of adult intelligence: Knowledge, abilities, and non-ability traits. Psychology and Aging, 14, 314–330.Google Scholar
Ackerman, P. L., & Woltz, D. J. (1994). Determinants of learning and performance in an associative memory/substitution task: Task constraints, individual differences, and volition. Journal of Educational Psychology, 86, 487–515.CrossRefGoogle Scholar
Adams, J. A. (1987). Historical review and appraisal of research on the learning, retention, and transfer of human motor skills. Psychological Bulletin, 101, 41–74.Google Scholar
Anastasi, A., & Urbina, S. (1997). Psychological testing (7th edn.). New York: Prentice-Hall.Google Scholar
Bandura, A. (1977). Self-efficacy: Toward a unifying theory of behavioral change. Psychological Review, 84, 191–215.CrossRefGoogle Scholar
Bar-Eli, M., Avugos, S., & Raab, M. (2006). Twenty years of “hot hand” research: Review and critique. Psychology of Sports and Exercise, 7, 525–553.Google Scholar
Barrett, G. V., Alexander, R. A., & Doverspike, D. (1992). The implications for personnel selection of apparent declines in predictive validities over time: A critique of Hulin, Henry, and Noon. Personnel Psychology, 45, 601–617.Google Scholar
Barrick, M. R., & Mount, M. K. (1991). The Big Five personality dimensions and job performance: A meta-analysis. Personnel Psychology, 44, 1–26.Google Scholar
Beier, M. E., & Ackerman, P. L. (2012). Time in personnel selection. In Schmitt, N. (ed.), The Oxford handbook of personnel selection and assessment (pp. 721–739). Oxford University Press.Google Scholar
Binet, A., & Simon, Th. (1973). The development of intelligence in children (trans. Kite, E.). New York: Arno Press.Google Scholar
Byrk, A. S., & Raudenbush, S. W. (1992). Hierarchical linear models: Applications and data analysis methods. Newbury Park, CA: Sage Publications.Google Scholar
Chi, M. T. H., Glaser, R., & Rees, E. (1982). Expertise in problem solving. In Sternberg, R. J. (ed.), Advances in the psychology of human intelligence (Vol. 1, pp. 7–76). Hillsdale, NJ: Erlbaum.Google Scholar
Cronbach, L. J., & Furby, L. (1970). How we should measure “change” – or should we? Psychological Bulletin, 74, 68–80.Google Scholar
Dawis, R. V., & Lofquist, L. H. (1984). A psychological theory of work adjustment: An individual differences model and its applications. Minneapolis, MN: University of Minnesota Press.Google Scholar
Feltz, D. L. (1982). Path analysis of the causal elements in Bandura’s theory of self-efficacy and anxiety-based model of avoidance behavior. Journal of Personality and Social Psychology, 42, 764–781.Google Scholar
Ferguson, L. W. (1952). A look across the years 1920 to 1950. In Thurstone, L. L. (ed.), Applications of psychology (pp. 1–17). New York: Harper & Brothers.Google Scholar
Fleishman, E. A., & Hempel, W. E. Jr. (1955). The relation between abilities and improvement with practice in a visual discrimination reaction task. Journal of Experimental Psychology, 49, 301–312.Google Scholar
Guilford, J. P., Christensen, P. R., Bond, N. A. Jr., & Sutton, M. A. (1954). A factor analysis study of human interests. Psychological Monographs, 68 (Whole no. 375).Google Scholar
Guttman, L. (1954). A new approach to factor analysis: The radex. In Lazarsfeld, P. F. (ed.), Mathematical thinking in the social sciences (pp. 258–348). New York: Free Press.Google Scholar
Hoffman, R. R. (1987). The problem of extracting the knowledge of experts from the perspective of experimental psychology. The AI Magazine, 8, 53–67.Google Scholar
Holland, J. L. (1959). A theory of vocational choice. Journal of Counseling Psychology, 6, 35–45.Google Scholar
Holland, J. L. (1997). Making vocational choices: A theory of vocational personalities and work environments (3rd edn.). Odessa, FL: Psychological Assessment Resources.Google Scholar
Honzik, M. P., MacFarlane, J. W., & Allen, L. (1948). The stability of mental test performance between two and eighteen years. Journal of Experimental Education, 17, 309–324.Google Scholar
Hunt, E. (1995). Will we be smart enough? A cognitive analysis of the coming workforce. New York: Russell Sage Foundation.Google Scholar
Jensen, A. R. (1998). The G factor: The science of mental ability. Westport, CT: Praeger.Google Scholar
Jones, M. B. (1962). Practice as a process of simplification. Psychological Review, 69, 274–294.Google Scholar
Kanfer, R. (1987). Task-specific motivation: An integrative approach to issues of measurement, mechanisms, processes, and determinants. Journal of Social and Clinical Psychology, 5, 251–278.Google Scholar
Kanfer, R., & Ackerman, P. L. (1989). Motivation and cognitive abilities: An integrative/aptitude-treatment interaction approach to skill acquisition. Journal of Applied Psychology, 74, 657–690.Google Scholar
Kant, I. (1987). Critique of judgment (trans. Pluhar, W. S.). Indianapolis, IN: Hackett. (Original work published 1790)Google Scholar
Lohman, D. F. (1999). Minding our P’s and Q’s: On finding relationships between learning and intelligence. In Ackerman, P. L., Kyllonen, P. C., & Roberts, R. D. (eds.), Learning and individual differences: Process, trait, and content determinants (pp. 55–76). Washington, DC: American Psychological Association.Google Scholar
McClelland, D. C., & Boyatzis, R. E. (1982). Leadership motive pattern and long-term success in management. Journal of Applied Psychology, 67, 737–743.Google Scholar
McNemar, Q. (1940). A critical examination of the University of Iowa studies of environmental influences upon the IQ. Psychological Bulletin, 37, 63–92.Google Scholar
Meehl, P. E., & Rosen, A. (1955). Antecedent probability and the efficiency of psychometric signs, patterns, or cutting scores. Psychological Bulletin, 52, 194–216.Google Scholar
Motowidlo, S. J., & Beier, M. E. (2010). Differentiating specific job knowledge from implicit trait policies in procedural knowledge measured by a situational judgment test. Journal of Applied Psychology, 95, 321–333.Google Scholar
Murray, H. A. (1938). Explorations in personality: A clinical and experimental study of fifty men of college age. Oxford University Press.Google Scholar
Ployhart, R. E., & Hakel, M. D. (1998). The substantive nature of performance variability: Predicting interindividual differences in intraindividual performance. Personnel Psychology, 51, 859–901.Google Scholar
Ployhart, R. E., & Vandenberg, R. J. (2010). Longitudinal research: Theory, design, and analysis of change. Journal of Management, 36, 94–120.Google Scholar
Simonton, D. K. (1994). Greatness: Who makes history and why. New York: Guilford Press.Google Scholar
Snow, R. E. (1989). Aptitude-treatment interaction as a framework for research on individual differences in learning. In Ackerman, P. L., Sternberg, R. J., & Glaser, R. (eds.), Learning and individual differences: Advances in theory and research (pp. 13–59). New York: W. H. Freeman.Google Scholar
Spangler, W. D. (1992). Validity of questionnaire and TAT measures of need of achievement: Two meta-analyses. Psychological Bulletin, 112, 140–154.Google Scholar
Stanovich, K. E. (1986). Matthew effects in reading: Some consequences of individual differences in the acquisition of literacy. Reading Research Quarterly, 21, 360–406.Google Scholar
Super, D. E. (1940). Avocational interest patterns: A study in the psychology of avocations. Stanford, CA: Stanford University Press.Google Scholar
Terman, L. M. (1926). Genetic studies of genius: Mental and physical traits of a thousand gifted children. Stanford, CA: Stanford University Press.Google Scholar
Thorndike, E. L. (1908). The effect of practice in the case of a purely intellectual function. American Journal of Psychology, 19, 374–384.Google Scholar
Warr, P. (1994). Age and employment. In Dunnette, M. D. & Triandis, H. C. (eds.), Handbook of industrial and organizational psychology (Vol. 4, pp. 485–550). Palo Alto, CA: Consulting Psychologists Press.Google Scholar
Watson, J. D. (2001). The double helix: A personal account of the discovery of the structure of DNA. New York: Simon & Schuster.Google Scholar
Willingham, W. W. (1974). Predicting success in graduate education. Science, 183, 273–278.Google Scholar
Wittmann, W. W., & Süß, H.-M. (1999). Investigating the paths between working memory, intelligence, knowledge, and complex problem-solving performances via Brunswik symmetry. In Ackerman, P. L., Kyllonen, P. C., & Roberts, R. D. (eds.), Learning and individual differences: Process, trait, and content determinants (pp. 77–108). Washington, DC: American Psychological Association.Google Scholar
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