Skip to main content Accessibility help
×
Hostname: page-component-7c8c6479df-27gpq Total loading time: 0 Render date: 2024-03-29T00:56:47.145Z Has data issue: false hasContentIssue false

26 - Skilled Decision Theory: From Intelligence to Numeracy and Expertise

from Part V.I - Domains of Expertise: Professions

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
Get access

Summary

Image of the first page of this content. For PDF version, please use the ‘Save PDF’ preceeding this image.'
Type
Chapter
Information
Publisher: Cambridge University Press
Print publication year: 2018

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

Arkes, H. R. (1991). Costs and benefits of judgment errors: Implications for debiasing. Psychological Bulletin, 110, 486498.Google Scholar
Arkes, H. R. (2016). A levels of processing interpretation of dual-system theories of judgment and decision making. Theory & Psychology, 26, 459475.Google Scholar
Baron, J. (1985). Rationality and intelligence. Cambridge University Press.CrossRefGoogle Scholar
Baron, J. (2008). Thinking and deciding (4th edn.). Cambridge University Press.Google Scholar
Baron, J., & Brown, R. V. (eds.) (2012). Teaching decision making to adolescents. New York: Routledge.Google Scholar
Brase, G. L. (2014). The power of representation and interpretation: Doubling statistical reasoning performance with icons and frequentist interpretations of ambiguous numbers. Journal of Cognitive Psychology, 26, 8197.Google Scholar
Breakspear, S. (2012). The policy impact of PISA: An exploration of the normative effects of international benchmarking in school system performance. OECD Education Working Paper No. 71. Paris: OECD Publishing.Google Scholar
Bruine de Bruin, W., & Bostrom, A. (2013). Assessing what to address in science communication. Proceedings of the National Academy of Sciences USA, 110, 1406214068.Google Scholar
Bruine de Bruin, W., Parker, A. M., & Fischhoff, B. (2007). Individual differences in adult decision-making competence. Journal of Personality and Social Psychology, 92, 938956.Google Scholar
Carroll, J. B. (1993). Human cognitive abilities: A survey of factor-analytic studies. Cambridge University Press.Google Scholar
Chang, W., Chen, E., Mellers, B., & Tetlock, P. (2016). Developing expert political judgment: The impact of training and practice on judgmental accuracy in geopolitical forecasting tournaments. Judgment and Decision Making, 11, 509526.Google Scholar
Chater, N., Tenenbaum, J. B., & Yuille, A. (2006). Probabilistic models of cognition: Conceptual foundations. Trends in Cognitive Science, 10, 287291.Google Scholar
Clegg, B. A., McKernan, B., Martey, R. M., Taylor, S. M., Stromer-Galley, J., Kenski, K., … & Shaw, A. (2015). Effective mitigation of anchoring bias, projection bias, and representativeness bias from serious game-based training. Procedia Manufacturing, 3, 15581565.Google Scholar
Cokely, E. T. (2009). Beyond generic dual processes: How should we evaluate scientific progress? PsycCritiques, 54, Article 10.Google Scholar
Cokely, E. T., Allan, J., Ghazal, S., Feltz, A., & Garcia-Retamero, R. (Forthcoming). General decision making skill and numeracy: Component abilities.Google Scholar
Cokely, E. T., & Feltz, A. (2009a). Adaptive variation in judgment and philosophical intuition. Consciousness and Cognition, 18, 356358.Google Scholar
Cokely, E. T., & Feltz, A. (2009b). Individual differences, judgment biases, and theory-of-mind: Deconstructing the intentional action side effect asymmetry. Journal of Research in Personality, 43, 1824.Google Scholar
Cokely, E. T., & Feltz, A. (2014). Expert intuition. In Osbeck, L. M. & Held, B. S. (eds.), Rational intuition: Philosophical roots, scientific investigations (pp. 213238). Cambridge University Press.Google Scholar
Cokely, E. T., Galesic, M., Schulz, E., Ghazal, S., & Garcia-Retamero, R. (2012). Measuring risk literacy: The Berlin Numeracy Test. Judgment and Decision Making, 7, 2547.Google Scholar
Cokely, E. T., Ghazal, S., Galesic, M., Garcia-Retamero, R., & Schulz, E. (2013). How to measure risk comprehension in educated samples. In Garcia-Retamero, R. & Galesic, M. (eds.), Transparent communication of health risks: Overcoming cultural differences (pp. 2952). New York: Springer.Google Scholar
Cokely, E. T., Ghazal, S., & Garcia-Retamero, R. (2014). Measuring numeracy. In Anderson, B. L. & Schulkin, J. (eds.), Numerical reasoning in judgments and decision making about health (pp. 1138). Cambridge University Press.Google Scholar
Cokely, E. T., & Kelley, C. M. (2009). Cognitive abilities and superior decision making under risk: A protocol analysis and process model evaluation. Judgment and Decision Making, 4, 2033.Google Scholar
Cokely, E. T., Kelley, C. M., & Gilchrist, A. H. (2006). Sources of individual differences in working memory: Contributions of strategy to capacity. Psychonomic Bulletin & Review, 13, 991997.Google Scholar
Cokely, E. T., Schooler, L. J., & Gigerenzer, G. (2010). Information use for decision making. In Maack, M. N. & Bates, M. J. (eds.), Encyclopedia of library and information sciences (3rd edn.) (pp. 27272734). New York: Taylor & Francis.Google Scholar
Del Missier, F., Mäntylä, T., & Bruin, W. B. (2012). Decision-making competence, executive functioning, and general cognitive abilities. Journal of Behavioral Decision Making, 25, 331351.CrossRefGoogle Scholar
Drane, J. F. (1984). Competency to give an informed consent: A model for making clinical assessments. Journal of the American Medical Association, 252, 925927.Google Scholar
Duckworth, A. L., & Seligman, M. E. (2005). Self-discipline outdoes IQ in predicting academic performance of adolescents. Psychological Science, 16, 939944.Google Scholar
Edwards, W. (1954). The theory of decision making. Psychological Bulletin, 51, 380417.Google Scholar
Ericsson, K. A. (ed.) (1991). 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., Charness, N., Hoffman, R. R., & Feltovich, P. J. (eds.) (2006). The Cambridge handbook of expertise and expert performance. Cambridge University Press.CrossRefGoogle Scholar
Ericsson, K. A., Chase, W. G., & Faloon, S. (1980). Acquisition of a memory skill. Science, 208, 11811182.Google Scholar
Ericsson, K. A., & Kintsch, W. (1995). Long-term working memory. Psychological Review, 102, 211245.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., Prietula, M. J., & Cokely, E. T. (2007). The making of an expert. Harvard Business Review, 85, 114121.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. Cambridge, MA: MIT Press.Google Scholar
Eskreis-Winkler, L., Shulman, E. P., Young, V., Tsukayama, E., Brunwasser, S. M., & Duckworth, A. L. (2016). Using wise interventions to motivate deliberate practice. Journal of Personality and Social Psychology, 111, 728744.Google Scholar
Evans, J. S. B., & Frankish, K. E. (2009). In two minds: Dual processes and beyond. Oxford University Press.Google Scholar
Feltz, A. (2015). Ethical information transparency and sexually transmitted infections. Current HIV Research, 13, 421431.Google Scholar
Feltz, A., & Cokely, E. T. (2009). Do judgments about freedom and responsibility depend on who you are? Personality differences in intuitions about compatibilism and incompatibilism. Consciousness and Cognition, 18, 342350.CrossRefGoogle ScholarPubMed
Feltz, A., & Cokely, E. T. (2012). The philosophical personality argument. Philosophical Studies, 161, 227246.Google Scholar
Feltz, A., & Cokely, E. T. (2013). Predicting philosophical disagreement. Philosophy Compass, 8, 978989.Google Scholar
Feltz, A., & Cokely, E. T. (2016). Personality and philosophical bias. In Sytsma, J. & Buckwalter, W. (eds.), A companion to experimental philosophy (pp. 578589). New York: John Wiley.Google Scholar
Fischhoff, B. (2013). The sciences of science communication. Proceedings of the National Academy of Sciences USA, 110 (Supplement 3), 1403314039.Google Scholar
Fischhoff, B., Brewer, N. T., & Downs, J. T. (2012). Communicating risks and benefits: An evidence-based user’s guide. Silver Spring, MD: US Food and Drug Administration.Google Scholar
Fisher, R. A. (1952). The design of experiments. London: Macmillan.Google Scholar
Fong, G. T., Krantz, D. H., & Nisbett, R. E. (1986). The effects of statistical training on thinking about everyday problems. Cognitive Psychology, 18, 253292.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.CrossRefGoogle ScholarPubMed
Fox, M. C., & Mitchum, A. L. (2013). A knowledge-based theory of rising scores on “culture-free” tests. Journal of Experimental Psychology: General, 142, 9791000.Google Scholar
Fox, M. C., & Mitchum, A. L. (2014). Confirming the cognition of rising scores: Fox and Mitchum (2013) predicts violations of measurement invariance in series completion between age-matched cohorts. PloS One, 9, e95780.Google Scholar
Frederick, S. (2005). Cognitive reflection and decision making. Journal of Economic Perspectives, 19, 2542.CrossRefGoogle Scholar
Gal, I. (2003). Teaching for statistical literacy and services of statistics agencies. American Statistician, 57, 8084.Google Scholar
Garcia-Retamero, R., & Cokely, E. T. (2011). Effective communication of risks to young adults: Using message framing and visual aids to increase condom use and STD screening. Journal of Experimental Psychology: Applied, 17, 270287.Google ScholarPubMed
Garcia-Retamero, R., & Cokely, E. T. (2013). Communicating health risks with visual aids. Current Directions in Psychological Science, 22, 392399.Google Scholar
Garcia‐Retamero, R., & Cokely, E. T. (2014). The influence of skills, message frame, and visual aids on prevention of sexually transmitted diseases. Journal of Behavioral Decision Making, 27, 179189.Google Scholar
Garcia-Retamero, R., & Cokely, E. T. (2017). Designing visual aids that promote risk literacy: A systematic review of health research and evidence-based design heuristics. Human Factors, 59, 582627.CrossRefGoogle ScholarPubMed
Garcia-Retamero, R., Cokely, E. T., Ghazal, S., & Joeris, A. (2016a). Measuring graph literacy without a test: A brief subjective assessment. Medical Decision Making, 36, 854867.Google Scholar
Garcia-Retamero, R., Cokely, E. T., & Hoffrage, U. (2015). Visual aids improve diagnostic inferences and metacognitive judgment calibration. Frontiers in Psychology, 6, 932.Google Scholar
Garcia-Retamero, R., Cokely, E. T., Wicki, B., & Joeris, A. (2016b). Improving risk literacy in surgeons. Patient Education and Counseling, 99, 11561161.Google Scholar
Garcia-Retamero, R., Wicki, B., Cokely, E. T., & Hanson, B. (2014). Factors predicting surgeons’ preferred and actual roles in interactions with their patients. Health Psychology, 33, 920928.Google Scholar
Ghazal, S. (2014). Component numeracy skills and decision making. PhD Dissertation, Michigan Technological University.Google Scholar
Ghazal, S., Cokely, E. T., & Garcia-Retamero, R. (2014). Predicting biases in very highly educated samples: Numeracy and metacognition. Judgment and Decision Making, 9, 1534.Google Scholar
Gigerenzer, G. (2015). Risk savvy: How to make good decisions. New York: Penguin.Google Scholar
Gigerenzer, G., & Gaissmaier, W. (2011). Heuristic decision making. Annual Review of Psychology, 62, 451482.Google Scholar
Gigerenzer, G., & Goldstein, D. G. (1996). Reasoning the fast and frugal way: Models of bounded rationality. Psychological Review, 103, 650669.Google Scholar
Gigerenzer, G., Todd, P. M., & the ABC Research Group (1999). Simple heuristics that make us smart. Oxford University Press.Google Scholar
Ginsburg, L., Manly, M., & Schmitt, M. J. (2006). The components of numeracy. NCSALL Occasional Paper. Boston, MA: National Center for the Study of Adult Learning and Literacy.Google Scholar
Goldman, S. R., & Pellegrino, J. W. (1984). Deductions about induction. Advances in the Psychology of Human Intelligence, 2, 149197.Google Scholar
Gould, S. J. (1996). The mismeasure of man. New York: W. W. Norton.Google Scholar
Hacking, I. (2006). The emergence of probability: A philosophical study of early ideas about probability, induction and statistical inference. Cambridge University Press.Google Scholar
Hanushek, E. A., & Woessmann, L. (2010). The economics of international differences in educational achievement. NBER Working Paper No. 15949. Cambridge, MA: National Bureau of Economic Research.CrossRefGoogle Scholar
Hastie, R., & Dawes, R. M. (eds.) (2010). Rational choice in an uncertain world: The psychology of judgment and decision making. Thousand Oaks, CA: Sage Publications.Google Scholar
Heckman, J. J. (1995). Lessons from the bell curve. Journal of Political Economy, 103, 10911120.Google Scholar
Herrnstein, R. J., & Murray, C. (1994). The bell curve: Intelligence and class structure in American life. New York: Free Press.Google Scholar
Holland, J. H., Holyoak, K. J., Nisbett, R. E., & Thagard, P. R. (1986). Induction: Processes of inference, learning, and discovery. Cambridge, MA: MIT Press.Google Scholar
Holyoak, K. J., & Morrison, R. G. (eds.) (2005). The Cambridge handbook of thinking and reasoning. Cambridge University Press.Google Scholar
Huff, D. (1954). How to lie with statistics. New York: W. W. Norton.Google Scholar
Hunt, E., & Wittmann, W. (2008). National intelligence and national prosperity. Intelligence, 36, 19.Google Scholar
Jaeggi, S. M., Buschkuehl, M., Jonides, J., & Shah, P. (2011). Short- and long-term benefits of cognitive training. Proceedings of the National Academy of Sciences USA, 108, 1008110086.Google Scholar
Jasper, J. D., Bhattacharya, C., & Corser, R. (2017). Numeracy predicts more effortful and elaborative search strategies in a complex risky choice context: A process‐tracing approach. Journal of Behavioral Decision Making, 30, 224235.Google Scholar
Jaynes, E. T. (2003). Probability theory: The logic of science. Cambridge University Press.Google Scholar
Kahan, D. M., Jenkins‐Smith, H., & Braman, D. (2011). Cultural cognition of scientific consensus. Journal of Risk Research, 14, 147174.Google Scholar
Kahneman, D. (2003). A perspective on judgment and choice: Mapping bounded rationality. American Psychologist, 58, 697720.CrossRefGoogle ScholarPubMed
Kahneman, D. (2011). Thinking, fast and slow. New York: Farrar, Straus & Giroux.Google Scholar
Keller, N., Cokely, E. T., Katsikopoulos, K. V., & Wegwarth, O. (2010). Naturalistic heuristics for decision making. Journal of Cognitive Engineering and Decision Making, 4, 256274.Google Scholar
Klein, G. (1999). Sources of power: How people make decisions. Cambridge, MA: MIT Press.Google Scholar
Kutner, M., Greenburg, E., Jin, Y., & Paulsen, C. (2006). The health literacy of America’s adults: Results from the 2003 National Assessment of Adult Literacy. NCES 2006-483. Washington, DC: National Center for Education Statistics.Google Scholar
Kyllonen, P. C., & Christal, R. E. (1990). Reasoning ability is (little more than) working-memory capacity?! Intelligence, 14, 389433.Google Scholar
Larrick, R. P. (2014). Debiasing. In Koehler, D. J. & Harvey, N. (eds.), Blackwell handbook of judgment and decision making (pp. 316338). Malden, MA: Blackwell Publishing.Google Scholar
Larrick, R. P., Morgan, J. N., & Nisbett, R. E. (1990). Teaching the use of cost-benefit reasoning in everyday life. Psychological Science, 1, 362370.Google Scholar
Lindsay, D. S. (2015). Replication in psychological science. Psychological Science, 26, 18271832.Google Scholar
Lindskog, M., Winman, A., Juslin, P., & Poom, L. (2013). Measuring acuity of the approximate number system reliably and validly: The evaluation of an adaptive test procedure. Frontiers in Psychology, 4, Article 510.Google Scholar
Lipkus, I. M., Samsa, G., & Rimer, B. K. (2001). General performance on a numeracy scale among highly educated samples. Medical Decision Making, 21, 3744.Google Scholar
McCabe, D. P., Roediger, H. L. III, McDaniel, M. A., Balota, D. A., & Hambrick, D. Z. (2010). The relationship between working memory capacity and executive functioning: Evidence for a common executive attention construct. Neuropsychology, 24, 222243.Google Scholar
Mellers, B., Stone, E., Atanasov, P., Rohrbaugh, N., Metz, S. E., Ungar, L., … & Tetlock, P. (2015a). The psychology of intelligence analysis: Drivers of prediction accuracy in world politics. Journal of Experimental Psychology: Applied, 21, 114.Google Scholar
Mellers, B., Stone, E., Murray, T., Minster, A., Rohrbaugh, N., Bishop, M., … & Ungar, L. (2015b). Identifying and cultivating superforecasters as a method of improving probabilistic predictions. Perspectives on Psychological Science, 10, 267281.Google Scholar
Mellers, B., Ungar, L., Baron, J., Ramos, J., Gurcay, B., Fincher, K., & … Tetlock, P. E. (2014). Psychological strategies for winning a geopolitical forecasting tournament. Psychological Science, 25, 11061115.Google Scholar
Morewedge, C. K., Yoon, H., Scopelliti, I., Symborski, C. W., Korris, J. H., & Kassam, K. S. (2015). Debiasing decisions: Improved decision making with a single training intervention. Policy Insights from the Behavioral and Brain Sciences, 2, 129140.CrossRefGoogle Scholar
Moshman, D. (2000). Diversity in reasoning and rationality: Metacognitive and developmental considerations. Educational Psychology Papers and Publications, 46, 689690.Google 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
Newall, P. W. (2016). Downside financial risk is misunderstood. Judgment and Decision Making, 11, 416422.Google Scholar
Nisbett, R. E., Aronson, J., Blair, C., Dickens, W., Flynn, J., Halpern, D. F., & Turkheimer, E. (2012). Intelligence: New findings and theoretical developments. American Psychologist, 67, 130159.Google Scholar
Okan, Y., Garcia-Retamero, R., Cokely, E. T., & Maldonado, A. (2015). Improving risk understanding across ability levels: Encouraging active processing with dynamic icon arrays. Journal of Experimental Psychology: Applied, 21, 178194.Google Scholar
Osman, M. (2004). An evaluation of dual-process theories of reasoning. Psychonomic Bulletin & Review, 11, 9881010.Google Scholar
Paas, F. G. (1992). Training strategies for attaining transfer of problem-solving skill in statistics: A cognitive-load approach. Journal of Educational Psychology, 84, 429434.Google Scholar
Pachur, T., & Galesic, M. (2013). Strategy selection in risky choice: The impact of numeracy, affect, and cross‐cultural differences. Journal of Behavioral Decision Making, 26, 260271.Google Scholar
Parker, A. M., & Fischhoff, B. (2005). Decision‐making competence: External validation through an individual‐differences approach. Journal of Behavioral Decision Making, 18, 127.Google Scholar
Paulos, J. A. (1988). Innumeracy: Mathematical illiteracy and its consequences. London: Macmillan.Google Scholar
Peters, E. (2012). Beyond comprehension: The role of numeracy in judgments and decisions. Current Directions in Psychological Science, 21, 3135.Google Scholar
Peters, E. (2017). Educating good decisions. Behavioural Public Policy, 1, 162176.Google Scholar
Peters, E., & Bjalkebring, P. (2015). Multiple numeric competencies: When a number is not just a number. Journal of Personality and Social Psychology, 108, 802822.Google Scholar
Peters, E., Hibbard, J., Slovic, P., & Dieckmann, N. (2007). Numeracy skill and the communication, comprehension, and use of risk-benefit information. Health Affairs, 26, 741748.Google Scholar
Peters, E., Shoots-Reinhard, B., Tompkins, M. K., Schley, D., Meilleur, L., Sinayev, A., … & Crocker, J. (2017). Improving numeracy through values affirmation enhances decision and STEM outcomes. PloS ONE, 12, e0180674.Google Scholar
Peters, E., Västfjäll, D., Slovic, P., Mertz, C. K., Mazzocco, K., & Dickert, S. (2006). Numeracy and decision making. Psychological Science, 17, 407413.Google Scholar
Petrova, D., Garcia-Retamero, R., Catena, A., Cokely, E. T., Herredia Carrasco, A., Arrebola Moreno, A., & Ramírez Hernández, J. A. (2017a). Numeracy predicts risk of pre-hospital decision delay: A retrospective study of acute coronary syndrome survival. Annals of Behavioral Medicine, 51, 292306.Google Scholar
Petrova, D., Garcia-Retamero, R., & Cokely, E. T. (2015). Understanding the harms and benefits of cancer screening: A model of factors that shape informed decision making. Medical Decision Making, 35, 847858.Google Scholar
Petrova, D., Kostopoulou, O., Delaney, B. C., Cokely, E. T., & Garcia-Retamero, R. (2017b). Strengths and gaps in physicians’ risk communication: A scenario study of the influence of numeracy on cancer screening communication. Medical Decision Making. DOI: 0272989X17729359.Google Scholar
Petrova, D., van der Pligt, J., & Garcia‐Retamero, R. (2014). Feeling the numbers: On the interplay between risk, affect, and numeracy. Journal of Behavioral Decision Making, 27, 191199.Google Scholar
Raiffa, H. (1968). Decision analysis: Introductory lectures on choices under uncertainty. New York: Random House.Google Scholar
Reyna, V. F. (2004). How people make decisions that involve risk: A dual process approach. Current Directions in Psychological Science, 13, 6066.Google Scholar
Reyna, V. F. (2008). A theory of medical decision making and health: Fuzzy trace theory. Medical Decision Making, 28, 850865.Google Scholar
Reyna, V. F., & Brainerd, C. J. (1995). Fuzzy-trace theory: An interim synthesis. Learning and Individual Differences, 7, 175.Google Scholar
Reyna, V. F., Nelson, W. L., Han, P. K., & Dieckmann, N. F. (2009). How numeracy influences risk comprehension and medical decision making. Psychological Bulletin, 135, 943973.Google Scholar
Rittle-Johnson, B., & Koedinger, K. R. (2001). Using cognitive models to guide instructional design: The case of fraction division. Proceedings of the Cognitive Science Society, 23.Google Scholar
Rubinstein, A. (2013). Response time and decision making: An experimental study. Judgment and Decision Making, 8, 540551.Google Scholar
Savage, L. J. (1954). The foundations of statistics. New York: John Wiley.Google Scholar
Schlaifer, R., & Raiffa, H. (1961). Applied statistical decision theory. Cambridge, MA: Harvard University Press.Google Scholar
Schley, D. R., & Peters, E. (2014). Assessing “economic value”: Symbolic-number mappings predict risky and riskless valuations. Psychological Science, 25, 753761.Google Scholar
Schulz, E., Cokely, E. T., & Feltz, A. (2011). Persistent bias in expert judgments about free will and moral responsibility: A test of the expertise defense. Consciousness and Cognition, 20, 17221731.Google Scholar
Schwartz, L. M., Woloshin, S., Black, W. C., & Welch, H. G. (1997). The role of numeracy in understanding the benefit of screening mammography. Annals of Internal Medicine, 127, 966972.Google Scholar
Simon, H. A. (1956). Rational choice and the structure of the environment. Psychological Review, 63, 129138.Google Scholar
Simon, H. A. (1957). A bounded-rationality model of rational choice. In Simon, H. A., Models of man, social and rational: Mathematical essays on rational human behavior in a social setting. New York: John Wiley.Google Scholar
Simon, H. A. (1990). Invariants of human behavior. Annual Review of Psychology, 41, 120.Google Scholar
Simons, D. J., Boot, W. R., Charness, N., Gathercole, S. E., Chabris, C. F., Hambrick, D. Z., & Stine-Morrow, E. A. (2016). Do “brain-training” programs work? Psychological Science in the Public Interest, 17, 103186.Google Scholar
Soll, J. B., Milkman, K. L., & Payne, J. W. (2015). A user’s guide to debiasing. In Keren, G. & Wu, G. (eds.), The Wiley Blackwell handbook of judgment and decision making (pp. 924951). Malden, MA: Wiley-Blackwell.Google Scholar
Stanovich, K. E. (1999). Who is rational? Studies of individual differences in reasoning. New York: Psychology Press.Google Scholar
Stanovich, K. E. (2016). The comprehensive assessment of rational thinking. Educational Psychologist, 51, 2334.Google Scholar
Stanovich, K. E., & West, R. F. (2000). Advancing the rationality debate. Behavioral and Brain Sciences, 23, 701717.Google Scholar
Stanovich, K. E., West, R. F., & Toplak, M. E. (2016). The rationality quotient: Toward a test of rational thinking. Cambridge, MA: MIT Press.Google Scholar
Steen, L. A. (ed.) (1990). On the shoulders of giants: New approaches to numeracy. Washington, DC: National Academies Press.Google Scholar
Thaler, R. H., & Sunstein, C. R. (2008). Nudge: Improving decisions about health, wealth, and happiness. New Haven, CT: Yale University Press.Google Scholar
Thompson, V. A., Turner, J. A. P., & Pennycook, G. (2011). Intuition, reason, and metacognition. Cognitive Psychology, 63, 107140.Google Scholar
Torgerson, C., Porthouse, J., & Brooks, G. (2005). A systematic review of controlled trials evaluating interventions in adult literacy and numeracy. Journal of Research in Reading, 28, 87107.Google Scholar
Traczyk, J., & Fulawka, K. (2016). Numeracy moderates the influence of task-irrelevant affect on probability weighting. Cognition, 151, 3741.Google Scholar
Trevena, L. J., Zikmund-Fisher, B. J., Edwards, A., Gaissmaier, W., Galesic, M., Han, P. K., … & Ozanne, E. (2013). Presenting quantitative information about decision outcomes: A risk communication primer for patient decision aid developers. BMC Medical Informatics and Decision Making, 13, S2S7.Google Scholar
Tversky, A., & Kahneman, D. (1985). The framing of decisions and the psychology of choice. In Covello, V. T., Mumpower, J. L., Stallen, P. J. M., & Uppuluri, V. R. R. (eds.), Environmental impact assessment, technology assessment, and risk analysis (pp. 107129). Berlin: Springer.Google Scholar
Von Neumann, J., & Morgenstern, O. (1944). Theory of games and economic behavior. Princeton University Press.Google Scholar
Weller, J. A., Dieckmann, N. F., Tusler, M., Mertz, C. K., Burns, W. J., & Peters, E. (2013). Development and testing of an abbreviated numeracy scale: A Rasch analysis approach. Journal of Behavioral Decision Making, 26(2), 198212.Google Scholar
Woller-Carter, M. (2016). Development of the intelligent graphs for everyday risky decisions tutor. PhD Dissertation, Michigan Technological University.Google Scholar
Woller-Carter, M., Okan, Y., Cokely, E. T., & Garcia-Retamero, R. (2012). Communicating and distorting risks with graphs: An eye-tracking study. In Proceedings of the Human Factors and Ergonomics Society Annual Meeting (Vol. 56, No. 1, pp. 17231727). Newbury Park, CA: Sage Publications.Google Scholar
Xin, Y. P., & Jitendra, A. K. (1999). The effects of instruction in solving mathematical word problems for students with learning problems: A meta-analysis. Journal of Special Education, 32, 207225.Google Scholar
Yates, J. F. (1990). Judgment and decision making. Upper Saddle River, NJ: Prentice-Hall.Google Scholar
Ybarra, V. T., Cokely, E. T., Adams, C., Woller-Carter, M., Allan, J. N., Feltz, A., & Garcia-Retamero, R. (2017). Training graph literacy: Developing the RiskLiteracy.org Outreach Platform. Proceedings of the Cognitive Science Society, 29.Google Scholar

Save book to Kindle

To save this book to your Kindle, first ensure coreplatform@cambridge.org is added to your Approved Personal Document E-mail List under your Personal Document Settings on the Manage Your Content and Devices page of your Amazon account. Then enter the ‘name’ part of your Kindle email address below. Find out more about saving to your Kindle.

Note you can select to save to either the @free.kindle.com or @kindle.com variations. ‘@free.kindle.com’ emails are free but can only be saved to your device when it is connected to wi-fi. ‘@kindle.com’ emails can be delivered even when you are not connected to wi-fi, but note that service fees apply.

Find out more about the Kindle Personal Document Service.

Available formats
×

Save book to Dropbox

To save content items to your account, please confirm that you agree to abide by our usage policies. If this is the first time you use this feature, you will be asked to authorise Cambridge Core to connect with your account. Find out more about saving content to Dropbox.

Available formats
×

Save book to Google Drive

To save content items to your account, please confirm that you agree to abide by our usage policies. If this is the first time you use this feature, you will be asked to authorise Cambridge Core to connect with your account. Find out more about saving content to Google Drive.

Available formats
×