Mathematics and Decisions
Abstract
Introduction. While there is broad consensus that mathematics is important across all education levels, decision-making is often treated as secondary in most curricula. Objective. This paper explores the relationship between mathematical ability and decision-making. Topics for Reflection. It suggests three models: one where mathematical ability influences decisions, another where decision-making influences mathematical ability, and a third proposing mutual influence. The authors review existing research supporting the first two models, highlighting the role of numeracy and decision parameters. Finally, they argue for the likelihood of a mutual influence model, emphasizing the importance of considering both mathematical skills and decision-making processes in understanding mathematical achievement. Conclusions. The mutual influence model has consequences for the future of mathematical education because it would require explicit training in decision making abilities at some point in school. Students need to be aware of such influence.
References
1. Mirzakhani M. Interview with Research Fellow. Maryam Mirzakhani [Internet]. London: Claymath; 2008. Available from: https://www.claymath.org/library/annual_report/ar2008/08Interview.pdf
2. Moutoussis M, Garzón B, Neufeld S, Bach DR, Rigoli F, Goodyer I, et al. Decision-making ability, psychopathology, and brain connectivity. Neuron [Internet]. 2021;109(12):2025-2040.e7. doi: https://doi.org/10.1016/j.neuron.2021.04.019
3. Peters E, Västfjäll D, Slovic, P, Mertz CK, Mazzocco K, Dickert S. Numeracy and Decision Making. Psychol Sci [Internet]. 2006;17(5):407–413. doi: https://doi.org/10.1111/j.1467-9280.2006.01720.x
4. de Bruin WB, Slovic P. Low numeracy is associated with poor financial well-being around the world. PLoS ONE [Internet]. 2021;16:1–15. doi: https://doi.org/10.1371/journal.pone.0260378
5. Estrada-Mejia C, de Vries M, Zeelenberg M. Numeracy and wealth. J Econ Psychol [Internet]. 2016;54(1):53–63. doi: https://doi.org/10.1016/j.joep.2016.02.011
6. Boyce-Jacino C, Peters E, Galvani AP, Chapman GB. Large numbers cause magnitude neglect: The case of government expenditures. Proc Natl Acad Sci USA [Internet]. 2022;119(28):e2203037119. doi: https://doi.org/10.1073/pnas
7. Lipkus IM, Peters E. Understanding the role of Numeracy in Health: Proposed Theoretical Framework and Practical Insights. Health Educ Behav [Internet]. 2009;36(6):1065–1081. doi: https://doi.org/10.1177/1090198109341533
8. Dehaene S. The number sense: How the Mind Creates Mathematics. Oxford University Press [Internet]. 1997. Available from: https://cognitionandculture.net/wp-content/uploads/the-number-sense-how-the-mindcreates-mathematics.pdf
9. Peters E, Slovic P, Vastfjall D, Mertz CK. Intuitive numbers guide decisions. Judgm Decis Mak [Internet]. 2008;3(8):619–635. Available from: https://www.cambridge.org/core/journals/judgment-and-decisionmaking/article/intuitive-numbers-guide-decisions/DAA7308D7EDA088EEAABCD673FC496E1
10. Schley DR, Peters E. Assessing “Economic Value”:Symbolic-Number Mappings Predict Risky and Riskless Valuations. Psychological Science [Internet]. 2014;25(3):753–761. doi: https://doi.org/10.1177/0956797613515485
11. Nieder A. The neuronal code for number. Nat Rev Neurosc [Internet]. 2016;17(6):366–382. doi: https://doi.org/10.1038/nrn.2016.40
12. Barretto-García M, de Hollander G, Grueschow M, Polanía R, Woodford M, Ruff CC. Individual risk attitudes arise from noise in neurocognitive magnitude representations. Nat Hum Behav [Internet]. 2023;7(9):1551–1567. doi: https://doi.org/10.1038/s41562-023-01643-4
13. Ratcliff R, McKoon G. The diffusion decision model: theory and data for two-choice decision tasks. Neural Comput [Internet]. 2008;20(4):873–922. doi: https://doi.org/10.1162/neco.2008.12-06-420
14. Gold JI, Shadlen MN. The neural basis of decision making. Annu Rev Neurosc [Internet]. 2007;30:535–574. doi: https://doi.org/10.1146/annurev.neuro.29.051605.113038
15. Ratcliff R, Thompson CA, Mckoon G. Modeling individual differences in response time and accuracy in numeracy. Cognition [Internet]. 2015;137:115–136. doi: https://doi.org/10.1016/j.cognition.2014.12.004
16. Alonso-Diaz S, Cantlon JF, Piantadosi ST. A thresholdfree model of numerosity comparisons. PLoS One [Internet]. 2018;13(4):e0195188. doi: https://doi.org/10.1371/journal.pone.0195188
17. Alonso-Diaz S, Giraldo-Huertas JJ. Choice Velocity in AQS Tasks and its Relation to Symbolic Mathematics in 4th and 6th grade students. PsyArXiv Preprints [Internet]. 2024. doi; https://osf.io/preprints/psyarxiv/z492x
18. Anobile G, Arrighi R, Castaldi E, Burr DC. A Sensorimotor Numerosity System. Trends Cogn Sci [Internet]. 2021;25(1):24–36. doi: https://doi.org/10.1016/j.tics.2020.10.009
19. Villani C. Birth of a theorem: A mathematical adventure [Internet]. Farrar, Straus and Giroux; 2015. Available from: https://pdfarchived.net/docs/Birth%20Of%20A%20Theorem%20A%20Mathematical%20Adventure-4934488
20. Dehaene S. Symbols and quantities in parietal cortex : elements of a mathematical theory of number representation and manipulation [Internet]. Attention and Perfomance: Sensorimotor Foundations of Higher Cognition: 2007;527–574. Available from: https://www.researchgate.net/publication/237443138_Symbols_and_quantities_in_parietal_Cortex_Elements_of_a_mathematical_theory_of_number_representation_and_manipulation
21. Bruguier AJ, Quartz SR, Bossaerts P. Exploring the Nature of “Trader Intuition.” The Journal of Finance [Internet]. 2010;LXV(5). Available from: https://www.its.caltech.edu/~squartz/jfinance.pdf
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