Skip to main content
Log in

Seeing chance: perceptual reasoning as an epistemic resource for grounding compound event spaces

  • Original Article
  • Published:
ZDM Aims and scope Submit manuscript

Abstract

The mathematics subject matter of probability is notoriously challenging, and in particular the content of random compound events. When students analyze experiments, they often omit to discern variations as distinct events, e.g., HT and TH in the case of flipping a pair of coins, and thus infer erroneous predictions. Educators have addressed this conceptual difficulty by engaging students in actual experiments whose outcomes contradict the erroneous predictions. Yet whereas empirical activities per se are crucial for any probability design, because they introduce the pivotal contents of randomness, variance, sample size, and relations among them, empirical activities may not be the unique or best means for students to accept the logic of combinatorial analysis. Instead, learners may avail of their own pre-analytic perceptual judgments of the random generator itself so as to arrive at predictions that agree rather than conflict with mathematical analysis. I support this view first by detailing its philosophical, theoretical, and didactical foundations and then by presenting empirical findings from a design-based research project. Twenty-eight students aged 9–11 participated in tutorial, task-based clinical interviews that utilized an innovative random generator. Their predictions were mathematically correct even though initially they did not discern variations. Students were then led to recognize the formal event space as a semiotic means of objectifying these presymbolic notions. I elaborate on the thesis via micro-ethnographic analysis of key episodes from a paradigmatic case study.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3

Similar content being viewed by others

Notes

  1. Strictly speaking, the physical marbles-scooping experiment is hypergeometric, not binomial, because as each marble is captured by a concavity in the scooper, there is one less of that color in the bin. However, the fairly minute ratio of the sample size (4) to the total number of marbles in the bin (hundreds) enables us to think of this experiment as quasi-binomial and, for all practical effects, as actually binomial. In this paper I do not expand on the computer-based simulations, because my thesis here pertains primarily to students’ perceptual judgments of the random generator itself and, in particular, how students coordinated these judgments with their guided perceptions of the event space. Moreover, my experimental design was such that students engaged the computer activities only after they had made sense of the event space, so that any observations of students grounding the actual outcome distribution in the event space are contaminated by the prior activities. That is, the study was designed as an experimental unit, not a comparison experiment.

  2. Square brackets communicate indexical information with respect to speech referents, which can be gleaned quite unequivocally from the agent’s gestures.

  3. An accompanying video clip of 2′15″ min duration can be viewed online at http://tinyurl.com/dor-tamar.

References

  • Abrahamson, D. (2006). The shape of things to come: The computational pictograph as a bridge from combinatorial space to outcome distribution. International Journal of Computers for Mathematical Learning, 11(1), 137–146.

    Article  Google Scholar 

  • Abrahamson, D. (2009a). Embodied design: Constructing means for constructing meaning. Educational Studies in Mathematics, 70(1), 27–47 (electronic supplementary material at http://edrl.berkeley.edu/publications/journals/ESM/Abrahamson-ESM/).

  • Abrahamson, D. (2009b). Orchestrating semiotic leaps from tacit to cultural quantitative reasoning—the case of anticipating experimental outcomes of a quasi-binomial random generator. Cognition and Instruction, 27(3), 175–224.

    Article  Google Scholar 

  • Abrahamson, D. (2012a). Discovery reconceived: Product before process. For the Learning of Mathematics, 32(1), 8–15.

    Google Scholar 

  • Abrahamson, D. (2012b). Rethinking intensive quantities via guided mediated abduction. Journal of the Learning Sciences (in press).

  • Abrahamson, D., Bryant, M. J., Gutiérrez, J. F., Mookerjee, A. V., Souchkova, D., & Thacker, I. E. (2009). Figuring it out: Mathematical learning as guided semiotic disambiguation of useful yet initially entangled intuitions. In S. L. Swars, D. W. Stinson, & S. Lemons-Smith (Eds.), Proceedings of the thirty-first annual meeting of the North-American chapter of the international group for the psychology of mathematics education (Vol. 5, pp. 662–670). Atlanta, GA: Georgia State University.

    Google Scholar 

  • Abrahamson, D., Gutiérrez, J. F., & Baddorf, A. K. (2012). Try to see it my way: The discursive function of idiosyncratic mathematical metaphor. Mathematical Thinking and Learning, 14(1), 55–80.

    Article  Google Scholar 

  • Abrahamson, D., Trninic, D., Gutiérrez, J. F., Huth, J., & Lee, R. G. (2011). Hooks and shifts: A dialectical study of mediated discovery. Technology, Knowledge, and Learning, 16(1), 55–85.

    Google Scholar 

  • Abrahamson, D., & Wilensky, U. (2005). Understanding chance: From student voice to learning supports in a design experiment in the domain of probability. In G. M. Lloyd, M. Wilson, J. L. M. Wilkins, & S. L. Behm (Eds.), Proceedings of the twenty-seventh annual meeting of the North American chapter of the international group for the psychology of mathematics education (Vol. 7, pp. 1–8). Roanoke, VA: PME-NA.

    Google Scholar 

  • Abrahamson, D., & Wilensky, U. (2007). Learning axes and bridging tools in a technology-based design for statistics. International Journal of Computers for Mathematical Learning, 12(1), 23–55.

    Article  Google Scholar 

  • Arnheim, R. (1969). Visual thinking. Berkeley: UC Press.

    Google Scholar 

  • Bamberger, J., & diSessa, A. A. (2003). Music as embodied mathematics: A study of a mutually informing affinity. International Journal of Computers for Mathematical Learning, 8(2), 123–160.

    Article  Google Scholar 

  • Barsalou, L. W. (1999). Perceptual symbol systems. Behavioral and Brain Sciences, 22, 577–660.

    Google Scholar 

  • Barwell, R. (2009). Researchers’ descriptions and the construction of mathematical thinking. Educational Studies in Mathematics, 72(2), 255–269.

    Article  Google Scholar 

  • Barwise, J., & Etchemendy, J. (1991). Visual information and valid reasoning. In W. Zimmerman & S. Cunningham (Eds.), Visualization in teaching and learning mathematics (pp. 3–25). USA: Mathematical Association of America.

    Google Scholar 

  • Batanero, C., Navarro-Pelayo, V., & Godino, J. D. (1997). Effect of implicit combinatorial model on combinatorial reasoning in secondary school pupils. Educational Studies in Mathematics, 32, 181–199.

    Article  Google Scholar 

  • Bautista, A., & Roth, W.-M. (2012). Conceptualizing sound as a form of incarnate mathematical consciousness. Educational Studies in Mathematics, 79(1), 41–59.

    Article  Google Scholar 

  • Borovcnik, M., & Bentz, H.-J. (1991). Empirical research in understanding probability. In R. Kapadia, & M. Borovcnik (Eds.), Chance encounters: Probability in education (pp. 73–105). Dordrecht: Kluwer.

  • Braude, H. D. (2012). Intuition in medicine: A philosophical defense of clinical reasoning. Chicago: University of Chicago Press.

    Google Scholar 

  • Bruner, J. S., Oliver, R. R., & Greenfield, P. M. (1966). Studies in cognitive growth: A collaboration at the Center for Cognitive Studies. New York: Wiley.

    Google Scholar 

  • Carey, S. (2011). Précis of the origin of concepts. Behavioral and Brain Sciences, 34(3), 113–124. doi:10.1017/S0140525X10000919.

    Article  Google Scholar 

  • Cobb, P., Confrey, J., diSessa, A., Lehrer, R., & Schauble, L. (2003). Design experiments in educational research. Educational Researcher, 32(1), 9–13.

    Article  Google Scholar 

  • Collins, A. (1992). Towards a design science of education. In E. Scanlon & T. O’Shea (Eds.), New directions in educational technology (pp. 15–22). Berlin: Springer.

    Chapter  Google Scholar 

  • Damasio, A. R. (2000). Descartes’ error: Emotion, reason, and the human brain. New York: Harper Collins.

    Google Scholar 

  • Dehaene, S. (1997). The number sense. Oxford: Oxford University Press.

    Google Scholar 

  • Diénès, Z. P. (1971). An example of the passage from the concrete to the manipulation of formal systems. Educational Studies in Mathematics, 3(3/4), 337–352.

    Article  Google Scholar 

  • Fischbein, E. (1975). The intuitive sources of probabilistic thinking in children. London: Riedel.

    Book  Google Scholar 

  • Freudenthal, H. (1983). Didactical phenomenology of mathematical structures. Dordrecht: Kluwer.

    Google Scholar 

  • Froebel, F. (2005). The education of man (W. N. Hailmann, Trans.). New York: Dover Publications (Original work published 1885).

  • Gelman, R. (1998). Domain specificity in cognitive development: Universals and nonuniversals. In M. Sabourin, F. Craik, & M. Robert (Eds.), Advances in psychological science (Vol. 2, pp. 50–63)., Biological and cognitive aspects Hove: Psychology Press.

    Google Scholar 

  • Gigerenzer, G. (1998). Ecological intelligence: An adaptation for frequencies. In D. D. Cummins & C. Allen (Eds.), The evolution of mind (pp. 9–29). Oxford: Oxford University Press.

    Google Scholar 

  • Goldin, G. A. (2000). A scientific perspective on structured, task-based interviews in mathematics education research. In A. E. Kelly & R. A. Lesh (Eds.), Handbook of research design in mathematics and science education (pp. 517–545). Mahwah, NJ: Lawrence Erlbaum Associates.

    Google Scholar 

  • Harel, G. (2012). Intellectual need in mathematical practice: A theoretical perspective. In K. Leatham (Ed.), Vital directions for mathematics education research. New York: Springer (in press).

  • Jones, G. A., Langrall, C. W., & Mooney, E. S. (2007). Research in probability: Responding to classroom realities. In F. K. Lester (Ed.), Second handbook of research on mathematics teaching and learning (pp. 909–955). Charlotte, NC: Information Age Publishing.

    Google Scholar 

  • Kahneman, D., Slovic, P., & Tversky, A. (Eds.). (1982). Judgment under uncertainty: Heuristics and biases. Cambridge, MA: Harvard University Press.

    Google Scholar 

  • Karmiloff-Smith, A. (1988). The child is a theoretician, not an inductivist. Mind & Language, 3(3), 183–195.

    Article  Google Scholar 

  • Koschmann, T., Kuuti, K., & Hickman, L. (1998). The concept of breakdown in Heidegger, Leont’ev, and Dewey and its implications for education. Mind, Culture, and Activity, 5(1), 25–41.

    Article  Google Scholar 

  • Lakoff, G., & Johnson, M. L. (1980). Metaphors we live by. Chicago: The University of Chicago Press.

    Google Scholar 

  • Mariotti, M. A. (2009). Artifacts and signs after a Vygotskian perspective: The role of the teacher. ZDM: The international Journal on Mathematics Education, 41, 427–440.

    Article  Google Scholar 

  • Mauks-Koepke, K. P., Buchanan, K., Relaford-Doyle, J., Souchkova, D., & Abrahamson, D. (2009). The double-edged sword of constructivist design. Paper presented at the annual meeting of the American Educational Research Association, San Diego, April 13–17.

  • Montessori, M. (1967). The absorbent mind (E. M. Standing, Trans.). New York: Holt, Rinehart, and Winston (Original work published 1949).

  • Nemirovsky, R. (2011). Episodic feelings and transfer of learning. Journal of the Learning Sciences, 20(2), 308–337.

    Article  Google Scholar 

  • Newman, D., Griffin, P., & Cole, M. (1989). The construction zone: Working for cognitive change in school. New York: Cambridge University Press.

    Google Scholar 

  • Núñez, R. E., Edwards, L. D., & Matos, J. F. (1999). Embodied cognition as grounding for situatedness and context in mathematics education. Educational Studies in Mathematics, 39, 45–65.

    Article  Google Scholar 

  • Piaget, J., & Inhelder, B. (1969). The psychology of the child (H. Weaver, Trans.). NY: Basic Books (Original work published 1966).

  • Polanyi, M. (1967). The tacit dimension. London: Routledge & Kegan Paul Ltd.

    Google Scholar 

  • Pratt, D. (2000). Making sense of the total of two dice. Journal for Research in Mathematics Education, 31(5), 602–625.

    Article  Google Scholar 

  • Pratt, D., & Noss, R. (2010). Designing for mathematical abstraction. International Journal of Computers for Mathematical Learning, 15(2), 81–97.

    Article  Google Scholar 

  • Radford, L. (2000). Signs and meanings in students’ emergent algebraic thinking: A semiotic analysis. Educational Studies in Mathematics, 42(3), 237–268.

    Article  Google Scholar 

  • Radford, L. (2003). Gestures, speech, and the sprouting of signs: A semiotic–cultural approach to students’ types of generalization. Mathematical Thinking and Learning, 5(1), 37–70.

    Article  Google Scholar 

  • Rogoff, B. (1990). Apprenticeship in thinking: Cognitive development in social context. NY: Oxford University Press.

    Google Scholar 

  • Rousseau, J.-J. (1972). Emile or on education (B. Foxley, Trans.). New York: Dutton.

  • Ruthven, K., Laborde, C., Leach, J., & Tiberghien, A. (2009). Design tools in didactical research: Instrumenting the epistemological and cognitive aspects of the design of teaching sequences. Educational Researcher, 38(5), 329–342.

    Article  Google Scholar 

  • Saxe, G. B. (2004). Practices of quantification from a sociocultural perspective. In K. A. Demetriou & A. Raftopoulos (Eds.), Developmental change: Theories, models, and measurement (pp. 241–263). NY: Cambridge University Press.

    Google Scholar 

  • Schoenfeld, A. H., Smith, J. P., & Arcavi, A. (1991). Learning: The microgenetic analysis of one student’s evolving understanding of a complex subject matter domain. In R. Glaser (Ed.), Advances in instructional psychology (pp. 55–175). Hillsdale, NJ: Erlbaum.

    Google Scholar 

  • Schön, D. A. (1983). The reflective practitioner: How professionals think in action. New York: Basic Books.

    Google Scholar 

  • Sfard, A. (2007). When the rules of discourse change, but nobody tells you—making sense of mathematics learning from a commognitive standpoint. Journal of Learning Sciences, 16(4), 567–615.

    Article  Google Scholar 

  • Shank, G. (1998). The extraordinary ordinary powers of abductive reasoning. Theory & Psychology, 8(6), 841–860.

    Article  Google Scholar 

  • Skemp, R. R. (1983). The silent music of mathematics. Mathematics Teaching, 102(58), 287–288.

    Google Scholar 

  • Smith, J. P., diSessa, A. A., & Roschelle, J. (1993). Misconceptions reconceived: A constructivist analysis of knowledge in transition. Journal of the Learning Sciences, 3(2), 115–163.

    Article  Google Scholar 

  • Steinbring, H. (1991). The theoretical nature of probability in the classroom. In R. Kapadia & M. Borovcnik (Eds.), Chance encounters: Probability in education (pp. 135–168). Dordrecht: Kluwer.

    Chapter  Google Scholar 

  • Streefland, L. (1984). Search for the roots of ratio: Some thoughts on the long-term learning process (towards a theory). Part 1: Reflections on a teaching experiment. Educational Studies in Mathematics, 15, 328–340.

    Article  Google Scholar 

  • Suzuki, S., & Cavanagh, P. (1998). A shape-contrast effect for briefly presented stimuli. Journal of Experimental Psychology: Human Perception and Performance, 24(5), 1315–1341.

    Article  Google Scholar 

  • Vagle, M. D. (2010). Re‐framing Schön’s call for a phenomenology of practice: A post‐intentional approach. Reflective Practice, 11(3), 393–407. doi:10.1080/14623943.2010.487375.

    Google Scholar 

  • von Glasersfeld, E. (1987). Learning as a constructive activity. In C. Janvier (Ed.), Problems of representation in the teaching and learning of mathematics (pp. 3–18). Hillsdale, NJ: Lawrence Erlbaum.

    Google Scholar 

  • Vygotsky, L. S. (1962). Thought and language. Cambridge, MA: MIT Press (Original work published 1934).

  • Wilensky, U. (1995). Paradox, programming and learning probability. Journal of Mathematical Behavior, 14(2), 231–280.

    Article  Google Scholar 

  • Wilensky, U. (1996). Modeling rugby: Kick first, generalize later? International Journal of Computers for Mathematical Learning, 1(1), 125–131.

    Article  Google Scholar 

  • Wilensky, U. (1997). What is normal anyway? Therapy for epistemological anxiety. Educational Studies in Mathematics, 33(2), 171–202.

    Article  Google Scholar 

  • Xu, F., & Garcia, V. (2008). Intuitive statistics by 8-month-old infants. Proceedings of the National academy of Sciences of the United States of America, 105(13), 5012–5015.

    Article  Google Scholar 

Download references

Acknowledgments

The original research reported in this paper was conducted with the support of a National Academy of Education/Spencer Postdoctoral Fellowship. I wish to thank the ZDM Editor-in-Chief as well as three anonymous reviewers for very helpful critiques.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Dor Abrahamson.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Abrahamson, D. Seeing chance: perceptual reasoning as an epistemic resource for grounding compound event spaces. ZDM Mathematics Education 44, 869–881 (2012). https://doi.org/10.1007/s11858-012-0454-6

Download citation

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11858-012-0454-6

Keywords

Navigation