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Predicting biases in very highly educated samples: Numeracy and metacognition

Author

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  • Saima Ghazal
  • Edward T. Cokely
  • Rocio Garcia-Retamero

Abstract

We investigated the relations between numeracy and superior judgment and decision making in two large community outreach studies in Holland (n=5408). In these very highly educated samples (e.g., 30--50% held graduate degrees), the Berlin Numeracy Test was a robust predictor of financial, medical, and metacognitive task performance (i.e., lotteries, intertemporal choice, denominator neglect, and confidence judgments), independent of education, gender, age, and another numeracy assessment. Metacognitive processes partially mediated the link between numeracy and superior performance. More numerate participants performed better because they deliberated more during decision making and more accurately evaluated their judgments (e.g., less overconfidence). Results suggest that well-designed numeracy tests tend to be robust predictors of superior judgment and decision making because they simultaneously assess (1) mathematical competency and (2) metacognitive and self-regulated learning skills.

Suggested Citation

  • Saima Ghazal & Edward T. Cokely & Rocio Garcia-Retamero, 2014. "Predicting biases in very highly educated samples: Numeracy and metacognition," Judgment and Decision Making, Society for Judgment and Decision Making, vol. 9(1), pages 15-34, January.
  • Handle: RePEc:jdm:journl:v:9:y:2014:i:1:p:15-34
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    References listed on IDEAS

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    1. Ellen Peters & Irwin P. Levin, 2008. "Dissecting the risky-choice framing effect: Numeracy as an individual-difference factor in weighting risky and riskless options," Judgment and Decision Making, Society for Judgment and Decision Making, vol. 3(6), pages 435-448, August.
    2. Amalia Di Girolamo & Glenn W. Harrison & Morten I. Lau & J. Todd Swarthout, 2013. "Characterizing Financial and Statistical Literacy," Experimental Economics Center Working Paper Series 2013-04, Experimental Economics Center, Andrew Young School of Policy Studies, Georgia State University.
    3. Edward T. Cokely & Mirta Galesic & Eric Schulz & Saima Ghazal & Rocio Garcia-Retamero, 2012. "Measuring risk literacy: The Berlin Numeracy Test," Judgment and Decision Making, Society for Judgment and Decision Making, vol. 7(1), pages 25-47, January.
    4. repec:aph:ajpbhl:10.2105/ajph.2009.160234_9 is not listed on IDEAS
    5. Guadagnoli, Edward & Ward, Patricia, 1998. "Patient participation in decision-making," Social Science & Medicine, Elsevier, vol. 47(3), pages 329-339, August.
    6. Valerie F. Reyna, 2012. "A new intuitionism: Meaning, memory, and development in Fuzzy-Trace Theory," Judgment and Decision Making, Society for Judgment and Decision Making, vol. 7(3), pages 332-359, May.
    7. Shane Frederick, 2005. "Cognitive Reflection and Decision Making," Journal of Economic Perspectives, American Economic Association, vol. 19(4), pages 25-42, Fall.
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    Cited by:

    1. André Mata & Tiago Almeida, 2014. "Using metacognitive cues to infer others' thinking," Judgment and Decision Making, Society for Judgment and Decision Making, vol. 9(4), pages 349-359, July.
    2. Philip W. S. Newall, 2016. "Downside financial risk is misunderstood," Judgment and Decision Making, Society for Judgment and Decision Making, vol. 11(5), pages 416-423, September.

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