Abstract
Mathematicians’ use of external representations, such as symbols and diagrams, constitutes an important focal point in current philosophical attempts to understand mathematical practice. In this paper, we add to this understanding by presenting and analyzing how research mathematicians use and interact with external representations. The empirical basis of the article consists of a qualitative interview study we conducted with active research mathematicians. In our analysis of the empirical material, we primarily used the empirically based frameworks provided by distributed cognition and cognitive semantics as well as the broader theory of cognitive integration as an analytical lens. We conclude that research mathematicians engage in generative feedback loops with material representations, that they use representations to facilitate the use of experiences of handling the physical world as a resource in mathematical work, and that their use of representations is socially sanctioned and enabled. These results verify the validity of the cognitive frameworks used as the basis for our analysis, but also show the need for augmentation and revision. Especially, we conclude that the social and cultural context cannot be excluded from cognitive analysis of mathematicians’ use of external representations. Rather, representations are socially sanctioned and enabled in an enculturation process.
Similar content being viewed by others
Notes
The aspects of the interviews not discussed in the analysis in this paper mainly relate to the selection of mathematical problems and the choice of representation connected to different communicative contexts. These aspects of the investigation are reported in Misfeldt and Johansen (2015) and Johansen and Misfeldt (2016). We refer to the analysis from these papers where appropriate. A general description of the educational implication of the study has been given in Johansen and Misfeldt (2014). In contrast to the papers previously published, the paper at hand focuses on cognitive aspects of the use of representations and seeks to understand the relationship between the cognitive and the social aspects of representation use.
It should be noted that we do not interpret this to suggest that mathematics is always performed in solitude behind closed doors as an individual activity. Rather, the point is that the thinking process (alone or in groups) most often involves writing and sketching.
As pointed out by one of the anonymous reviewers the role of diagrams in mathematics is very diverse, and diagrams may also in some cases be used as epistemic artefact in a way similar to symbols (see e.g. De Toffoli and Giardino 2014).
As one of the anonymous reviewers kindly pointed out such dynamic processes are not confined to mathematical reasoning or reasoning with diagrams, but could also occur in connection to other representations (see e.g. Clark 1998).
In mathematics, a permutation is an operation that reorganizes the sequential ordering of the elements of a set.
See also Carter (2010) where the role played by the same type of circular diagrams in finding and constructing a mathematical proof is discussed in depth.
Square matrices have the same number of rows and columns and will consequently typically have a square typographical outline in the usual representational form. In contrast, in rectangular matrices, the number of rows does not coincide with that of the columns.
References
Barany, M. J., & MacKenzie, D. (2014). Chalk: Materials and concepts in mathematics research. In C. Coopman, J. Vertesi, M. Lynch, & S. Woolgar (Eds.), Representation in scientific practice revisited (pp. 107–129). Cambridge, MA: MIT Press.
Bloor, D. (1981). Hamilton and Peacock on the essence of algebra. In H. Mehrtens, H. M. Bos, & I. Schneider (Eds.), Social history of nineteenth century mathematics (pp. 202–232). Boston: Birkhäuser.
Burton, L. (2004). Mathematicians as enquirers: Learning about learning mathematics. Boston: Kluwer Academic Publishers.
Carter, J. (2010). Diagrams and proofs in analysis. International Studies in the Philosophy of Science, 24(1), 1–14. https://doi.org/10.1080/02698590903467085.
Charmaz, K. (2006). Constructing grounded theory. London, CA: Sage Publications.
Clark, A. (1989). Microcognition, philosophy, cognitive science, and parallel distributed processing. Cambridge, MA: MIT Press.
Clark, A. (1998). Magic words: How language augments human computation. In P. Carruthers & J. Boucher (Eds.), Language and thought: Interdisciplinary themes (pp. 162–183). Cambridge: Cambridge University Press.
De Cruz, H., & De Smedt, J. (2013). Mathematical symbols as epistemic actions. Synthese, 190(1), 3–19.
De Toffoli, S. (2017). ‘Chasing’ the diagram: The use of visualizations in algebraic reasoning. The Review of Symbolic Logic, 10(1), 158–186.
De Toffoli, S., & Giardino, V. (2014). Roles and forms of diagrams in knot theory. Erkenntnis, 79(3), 829–842.
Epple, M. (2004). Knot invariants in Vienna and Princeton during the 1920s: Epistemic configurations of mathematical research. Science in Context, 17(1/2), 131–164.
Fauconnier, G., & Turner, M. (2002). The way we think, conceptual blending and the mind’s hidden complexities. New York: Basic Books.
Feigenson, L., Dehaene, S., & Spelke, E. (2004). Core systems of number. Trends in Cognitive Sciences, 8(7), 307–314.
Frank, M. C., Everett, D. L., Fedorenko, E., & Gibson, E. (2008). Number as a cognitive technology: Evidence from Pirahã language and cognition. Cognition, 108(3), 819–824.
Greiffenhagen, C. W. K. (2014). The materiality of mathematics: Presenting mathematics at the blackboard. The British Journal of Sociology, 65(3), 502–528. https://doi.org/10.1111/1468-4446.12037.
Holland, J. D., Hutchins, E., & Kirsh, D. (2000). Distributed cognition: Toward a new foundation for human–computer interaction research. ACM Transactions on Computer–Human Interaction, 7(2), 174–196.
Hutchins, E. (2005). Material anchors for conceptual blends. Journal of Pragmatics, 37(10), 1555–1577.
Hutchins, E. (2011). Enculturating the supersized mind. Philosophical Studies, 152(3), 437–446.
Johansen, M. W. (2010). Embodied strategies in mathematical cognition. In B. Löwe & T. Müller (Eds.), PhiMSAMP. Philosophy of mathematics: Sociological aspects and mathematical practice, texts in philosophy (Vol. 11, pp. 179–196). London: College Publications.
Johansen, M. W. (2014). What’s in a diagram? On the classification of symbols, figures and diagrams. In L. Magnani (Ed.), Model-based reasoning in science and technology (Studies in applied philosophy, epistemology and rational ethics 8) (pp. 89–108). Berlin: Springer.
Johansen, M. W., & Misfeldt, M. (2014). Når matematikere undersøger matematik-og hvilken betydning det har for undersøgende matematikundervisning. MONA, 2014(4), 42–59.
Johansen, M. W., & Misfeldt, M. (2015). Semiotic scaffolding in mathematics. Biosemiotics, 8(2), 325–340. https://doi.org/10.1007/s12304-014-9228-6.
Johansen, M. W., & Misfeldt, M. (2016). An empirical approach to the mathematical values of problem choice and argumentation. In B. Larvor (Ed.), Mathematical cultures: The London meetings 2012–2014 (pp. 259–269). Switzerland: Springer.
Kirsh, D., & Maglio, P. (1994). On distinguishing epistemic from pragmatic action. Cognitive Science, 18(4), 513–549.
Kjeldsen, T. H. (2009). Egg-forms and measure-bodies: Different mathematical practices in the early history of the modern theory of convexity. Science in Context, 22(1), 85–113.
Kvale, S. (1996). InterViews. An introduction to qualitative research interviewing. Thousand Oaks, CA: Sage Publications.
Lakoff, G., & Johnson, M. (1980). Metaphors we live. Chicago: University of Chicago Press.
Lakoff, G., & Núñez, R. (2000). Where mathematics comes from: How the embodied mind brings mathematics into being. New York: Basic Books.
Larkin, J. H., & Simon, H. A. (1987). Why a diagram is (sometimes) worth ten thousand words. Cognitive Science, 11(1), 65–100.
Marghetis, T., & Núñez, R. (2010). Dynamic construals, static formalisms: Evidence from co-speech gesture during mathematical proving. In A. Pease, M. Guhe, & A. Smaill (Eds.), Proceedings of the international symposium on mathematical practice and cognition (pp. 23–29). New York: AISB.
Menary, R. (2015). Mathematical cognition: A case of enculturation. In T. Metzinger & J. M. Windt (Eds.), Open MIND: 25(T). Frankfurt am Main: MIND Group. https://doi.org/10.15502/9783958570818.
Misfeldt, M. (2011). Computers as medium for mathematical writing. Semiotica, 186, 239–258.
Misfeldt, M., & Johansen, M. W. (2015). Research mathematicians’ practices in selecting mathematical problems. Educational Studies in Mathematics, 89(3), 357–373.
Mumma, J. (2010). Proofs, pictures and euclid. Synthese, 175(2), 255–287.
Núñez, R. (2009). Numbers and arithmetic: Neither hardwired nor out there. Biological Theory, 4(1), 68–83.
Núñez, R. (2004). Do real numbers really move? Language, thought, and gesture: The embodied cognitive foundations of mathematics. In F. Iida, R. Pfeifer, L. Steels, & Y. Kuniyoshi (Eds.), Embodied artificial intelligence (pp. 54–73). Berlin: Springer.
Pycior, H. (1997). Symbols, impossible numbers, and geometric entanglements. British algebra through the commentaries on Newton’s Universal Arithmetick. Cambridge: Cambridge University Press.
Schlimm, D., & Neth, H. (2008). Modeling ancient and modern arithmetic practices: Addition and multiplication with Arabic and Roman numerals. In V. Sloutsky, B. Love, & K. McRae (Eds.), 30th Annual conference of the cognitive science society (pp. 2097–2102). Austin, TX: Cognitive Science Society.
Shin, S. (1994). The logical status of diagrams. Cambridge: Cambridge University Press.
Steensen, A. K., & Johansen, M. W. (2016). The role of diagram materiality in mathematics. Cognitive Semiotics, 9(2), 183–201.
Thurston, W. P. (1994). On proof and progress in mathematics. Bulletin of the American Mathematical Society, 30(2), 161–177.
Zhang, J., & Norman, D. A. (1995). A representational analysis of numeration systems. Cognition, 57(3), 271–295.
Acknowledgements
This paper was developed as part of an investigation of mathematicians’ practice. The investigation and the analysis presented here springs from conversations we have had with a number of mathematicians. These mathematicians were extremely generous with their time and allowed us to learn about their concerns and strategies while conducting mathematical research. We are truly thankful for their indispensable contribution to our work.
Author information
Authors and Affiliations
Corresponding author
Rights and permissions
About this article
Cite this article
Johansen, M.W., Misfeldt, M. Material representations in mathematical research practice. Synthese 197, 3721–3741 (2020). https://doi.org/10.1007/s11229-018-02033-4
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s11229-018-02033-4