Advertisement

Towards "Probability Literacy" for all Citizens: Building Blocks and Instructional Dilemmas

  • Iddo Gal
Part of the Mathematics Education Library book series (MELI, volume 40)

Keywords

Critical Question Statistical Literacy World Knowledge Knowledge Element Quantitative Literacy 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Albert, J. H. (2003). College students' conceptions of probability. The American Statistician, 57(1), 37–45.CrossRefGoogle Scholar
  2. American Association for the Advancement of Science (1995). Benchmarks for science literacy. Washington, DC: Author.Google Scholar
  3. Baker, D., & Street, B. (1994). Literacy and numeracy: Concepts and definitions. In T. Husen & E. A. Postlethwaite (Eds.), Encyclopedia of education (Vol. 6, pp. 3453–3459). New York: Pergamon Press.Google Scholar
  4. Baron. J. (2000). Thinking and deciding (3rd ed.). New York: Cambridge University Press.Google Scholar
  5. Beltrami, E. (1999). What is random? Chance and order in mathematics and life. New York: Copernicus/Springer-Verlag.Google Scholar
  6. Bennett, D. J. (1998). Randomness. Cambridge, MA: Harvard University Press.Google Scholar
  7. Beyth-Marom, R., & Dekel, S. (1985). An elementary approach to thinking under uncertainty. Hillsdale, NJ: Erlbaum.Google Scholar
  8. Clemen, R., & Gregory, R. (2000). Preparing adult students to be better decision makers. In I. Gal (Ed.), Adult numeracy development: Theory, research, practice (pp. 73–86). Cresskill, NJ: Hampton Press.Google Scholar
  9. Cosmides, L., & Tooby, J. (1996). Are humans good intuitive statisticians after all? Rethinking some conclusions from the literature on judgment under uncertainty. Cognition, 58, 1–73.CrossRefGoogle Scholar
  10. Dessart, D. (1989). Teaching probability and statistics in general secondary education. In R. Morris (Ed.), Studies in mathematics education: The teaching of statistics (pp. 139–154). Paris: UNESCO.Google Scholar
  11. Everitt, B. S. (1999). Chance rules: An informal guide to probability, risk, and statistics. New York: Copernicus/Springer-Verlag.Google Scholar
  12. Feldman, L. & Morgan, F. (2003). The pedagogy and probability of the dice game HOG. Journal of Statistics Education 11(2). [Online:www.amstat.org/publications/jse/v11n2/feldman.html]Google Scholar
  13. Fischhoff, B., Bostrom, A., & Quadrel, M. J. (1993). Risk perception and communication. Annual Review of Public Health, 14, 183–203.CrossRefGoogle Scholar
  14. Gal, I. (1999). Links between literacy and numeracy. In D. A. Wagner, B. Street, & R. L. Venezky (Eds.), Literacy: An international handbook (pp. 227–231). Boulder, CO: Westview Press.Google Scholar
  15. Gal, I. (2000). The numeracy challenge. In I. Gal (Ed.), Adult numeracy development: Theory, research, practice (pp. 9–31). Cresskill, NJ: Hampton Press.Google Scholar
  16. Gal, I. (2002a). Adult statistical literacy: Meanings, components, responsibilities, International Statistical Review, 70(1), 1–25.Google Scholar
  17. Gal, I. (2002b). Dispositional aspects of coping with interpretive numeracy tasks. Literacy and Numeracy Studies, 11(2), 47–61.Google Scholar
  18. Gal, I., & Baron, J. (1996). Understanding repeated simple choices. Thinking and Reasoning, 2(1), 1–18.CrossRefGoogle Scholar
  19. Gal, I., Ginsburg, L., & Schau, C. (1997). Monitoring attitudes and beliefs in statistics education. In I. Gal & J. B. Garfield (Eds.), The assessment challenge in statistics education (pp. 37–51). Amsterdam: IOS Press.Google Scholar
  20. Gal, I., Mahoney, P., & Moore, S. (1992). Children's use of statistical terms. In W. Geeslin & Graham K. (Eds.), Proceedings of the 16th annual meeting of the International Group for Psychology in Mathematics Education (Vol. 3, p. 160). Durham, New Hampshire.Google Scholar
  21. Gigerenzer, G., Swijtink, Z., Porter, T., Daston, L., Beatty, J. & Kruger, L. (1989). The empire of chance: how probability changed science and everyday life. New York: Cambridge University Press.Google Scholar
  22. Gigerenzer, G., Todd, P. M., & the ABC Research Group (1999). Simple heuristics that make us smart. New York: Oxford University Press.Google Scholar
  23. Green, D. (1989). School pupils' understanding of randomness. In R. Morris (Ed.), Studies in mathematics education: The teaching of statistics (pp. 27–39). Paris: UNESCO.Google Scholar
  24. Grinstead, C. M., & Snell, L. J. (1997). Introduction to probability (2nd ed.). Washington, DC: American Mathematical Society. [Online:http://www.dartmouth.edu/~chance].Google Scholar
  25. Halliday, M. A. K. (1979). Language as social semiotic: The social interpretation of language and meaning. London: Edward Arnold Publishers Ltd.Google Scholar
  26. Hirsch, E. D., Kett, J. F., & Trefil, J. (2002). The new dictionary of cultural literacy, (3rd ed.). New York: Houghton Mifflin.Google Scholar
  27. Johnston, B. (1999). Adult numeracy. In D. A. Wagner, R. L. Venezky, & B. V. Street (Eds.), Literacy: An international handbook (pp. 242–247). Boulder, CO: Westview Press.Google Scholar
  28. Kahneman, D., Slovic, P., & Tversky, A. (Eds.) (1982). Judgment under uncertainty: Heuristics and biases. Cambridge: Cambridge University Press.Google Scholar
  29. Keeler, C., & Steinhorst, K. (2001). A new approach to learning probability in the first statistics course. Journal of Statistics Education, 9(3). [Online: www.amstat.org/publications/jse/v9n3/keeler.html]Google Scholar
  30. Kilpatrick, J. (2001). Understanding mathematical literacy: The contribution of research. Educational Studies in Mathematics 47(1), 101–116.CrossRefGoogle Scholar
  31. Konold, C. (1991). Understanding students' beliefs about probability. In E. von Glaserfeld (Ed.), Radical constructivism in mathematics education (pp. 139–156), Dordrecht, The Netherlands: Kluwer.Google Scholar
  32. Lovett, M. C., & Greenhouse, J. B. (2000). Applying cognitive theory to statistics instruction. The American Statistician, 54(3), 196–206.CrossRefGoogle Scholar
  33. McLeod, D. B. (1992). Research on affect in mathematics education: A reconceptualization, In D. A. Grouws (Ed), Handbook of research on mathematics teaching and learning pp (pp. 575–596). New York: Macmillan.Google Scholar
  34. Moore, D. S. (1990). Uncertainty. In L. A. Steen (Ed.), On the shoulders of giants: New approaches to numeracy (pp. 95–137). Washington, DC: National Academy Press.Google Scholar
  35. National Council of Teachers of Mathematics.(2000). Principles and standards for school mathematics. Reston, VA: Author.Google Scholar
  36. Nutbeam, D. (2000). Health literacy as a public health goal: A challenge for contemporary health education and communication strategies into the 21st century. Health Promotion International, 15(3), 259–267.CrossRefGoogle Scholar
  37. Packer, A. (1997). Mathematical Competencies that employers expect. In L. A. Steen (Ed.), Why numbers count: quantitative literacy for tomorrow's America (pp. 137–154). New York: The College Board.Google Scholar
  38. Paulos, J. A. (1995). A mathematician reads the newspaper. New York: Anchor Books/Doubleday.Google Scholar
  39. Peterson, I. (1998). The jungles of randomness: A mathematical safari. New York: Wiley.Google Scholar
  40. Pimm, D. (1987). Speaking mathematically: Communication in mathematics classrooms. London: Routledge.Google Scholar
  41. Rutherford, J. F. (1997). Thinking quantitatively about science. In L. A. Steen (Ed.), Why numbers count: quantitative literacyfor tomorrow's America (pp. 60–74). New York: The College Board.Google Scholar
  42. Rutherford, J. F., & Ahlgren, A. (1990). Sciencefor all Americans. New York: Oxford University Press.Google Scholar
  43. Rychen, D. S., & Salganic, L. H. (Eds) (2003). Key competencies for a successful life and a well-functioning society. Gottingen, Germany: Hogrefe & Huber.Google Scholar
  44. Scheaffer, R. L., Watkins, A. E., & Landwehr, J. M. (1998). What every high-school graduate should know about statistics. In S. P. Lajoie (Ed.), Reflections on statistics: Learning, teaching and assessment in Grades K-12 (pp. 3–31). Mahwah, NJ: Lawrence Erlbaum.Google Scholar
  45. Secretary of Labor's Commission on Achieving Necessary Skills (SCANS). (1991). What work requires ofschools: A SCANS reportfor America 2000. Washington, DC: U.S. Government Printing Office.Google Scholar
  46. Shamos, M. H. (1995). The myth ofscientific literacy. New Brunswick, NJ: Rutgers University Press.Google Scholar
  47. Snell, L. J. (1988). Introduction toprobability. New York: Random House.Google Scholar
  48. Snell, L. J. (2002). But how do you teach it? International Statistical Review, 70(1), 45–46.Google Scholar
  49. Steen, L. A. (2001). Mathematics and democracy: The casefor quantitative literacy. Washington, DC: Woodrow Wilson National Fellowship Foundation.Google Scholar
  50. Stein, S. (2000). Equipped for the future content standards: What adults need to know and be able to do in the 21st century. Washington, DC: National Institute for Literacy. [Online: www.nifl.gov/lincs/collections/eff/eff_publications.html]Google Scholar
  51. Thistlewaite, L. L. (1990). Critical reading for at-risk students. Journal of Reading, 33(8), 586–593.Google Scholar
  52. Utts, J. (1996). Seeing through statistics. Belmont, CA: Wadsworth.Google Scholar
  53. Utts, J. (2003). What educated citizens should know about statistics and probability. The American Statistician, 57(2), 74–79.CrossRefGoogle Scholar
  54. Venezky, R. L. (1990). Definitions of literacy. In R. L. Venezky, D. A. Wagner, & B. S. Ciliberti (Eds.), Towards defining literacy (pp. 2–16). Newark, DE: International Reading Association.Google Scholar
  55. Wallman, K. K. (1993). Enhancing statistical literacy: Enriching our society. Journal of the American Statistical Association, 88, 1–8.CrossRefGoogle Scholar
  56. Wallsten, T. S., Budescu, D. V., Rapoport, A., Zwick, R., & Forsyth, B. (1986). Measuring the vague meanings of probability terms. Journal of Experimental Psychology: General, 115(4), 348–365.CrossRefGoogle Scholar
  57. Wallsten, T. S., Fillenbaum, S., & Cox, J. A. (1986). Base rate effects on the interpretations of probability and frequency expressions. Journal of Memory and Language, 25, 571–587.CrossRefGoogle Scholar
  58. Watson, J. (1997). Assessing statistical literacy through the use of media surveys. In I. Gal & J. Garfield, (Eds.), The assessment challenge in statistics education (pp. 107–121). Amsterdam, The Netherlands: International Statistical Institute/IOS Press.Google Scholar
  59. Watson, J. M., & Callingham, R. (2003). Statistical literacy: A complex hierarchical construct. Statistics Education Research Journal, 2(2), 3–46.Google Scholar
  60. Yates, F. J. (2001). Outsider impressions of naturalistic decision making. In E. Salas & Klein G. (Eds). Linking expertise and naturalistic decision making (pp. 9–33). Mahwah, NJ: Erlbaum.Google Scholar

Copyright information

© Springer Science+Business Media, Inc. 2005

Authors and Affiliations

  • Iddo Gal

There are no affiliations available

Personalised recommendations