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Ideas foundational to calculus learning and their links to students’ difficulties

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Abstract

Existing literature reviews of calculus learning made an important contribution to our understanding of the development of mathematics education research in this area, particularly their documentation of how research transitioned from studying students’ misconceptions to investigating students’ understanding and ways of thinking per se. This paper has three main goals relative to this contribution. The first goal is to offer a conceptual analysis of how students’ difficulties surveyed in three major literature review publications originate in the mathematical meanings and ways of thinking students develop in elementary, middle and early high school. The second goal is to highlight a contribution to an important aspect that the articles in this issue make but was overshadowed by other aspects addressed in existing literature reviews: the nature of the mathematics students experience under the name “calculus” in various nations or regions around the world, and the relation of this mathematics to ways ideas foundational to it are developed over the grades. The third goal is to outline research questions entailed from these articles for future research regarding each of them.

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Notes

  1. We readily admit the power of using symbols to represent “unknowns”. For example, Schoenfeld (1988) posed this problem: Reverse the digits in 39 and 62. Then 39 × 62 = 93 × 26. Are there other pairs of numbers having this property? By representing digits’ place value you get (10a + b)(10c + d) = (10b + a) (10d + c), which reduces to ac = bd.

  2. Here we finesse the matter of function notation, which is notoriously confusing for students and teachers (Carlson, 1998; Even, 1990; Sajka, 2003).

  3. Thompson and Carlson (2017) were careful to define “variable” as a symbol which represents the value of a quantity (concrete or abstract) whose value varies. They distinguished among using a symbol as a variable, as a parameter, and as a constant, where the distinction resides in what the person intends to represent.

  4. Two quantities conceived as having fixed values cannot be thought to have a rate of change. It would be like asking, “What is the rate of change of 5 with respect to 3?”.

References

  • Artigue, M. (2002). Learning mathematics in a CAS environment: The genesis of a reflection about instrumentation and the dialectics between technical and conceptual work. International Journal of Computers for Mathematical Learning, 7(3), 245–274

    Article  Google Scholar 

  • Ayalon, M., Watson, A., & Lerman, S. (2015). Progression towards functions: Students’ performance on three tasks about variables from grades 7 to 12. International Journal of Science and Mathematics Education. https://doi.org/10.1007/s10763-014-9611-4

    Article  Google Scholar 

  • Bardini, C., Radford, L., & Sabena, C. (2005). Struggling with variables, parameters, and indeterminate objects or how to go insane in mathematics. In H. L. Chick, & J. L. Vincent (Eds.), Proceedings of the 29th conference of the International Group for the psychology of mathematics education (Vol. 2, pp. 129–136). PME.

  • Bingolbali, E., Monaghan, J., & Roper, T. (2007). Engineering students’ conceptions of the derivative and some implications for their mathematical education. International Journal of Mathematical Education in Science and Technology, 38(6), 763–777

    Article  Google Scholar 

  • Bishop, W. (1999). The California Mathematics Standards: They’re not only right; they’re the law. Phi Delta Kappan, 80(6), 439–440

    Google Scholar 

  • Blanton, M. L. (2008). Algebra and the elementary classroom: Transforming thinking, transforming practice. Heinemann.

    Google Scholar 

  • Blanton, M. L., Stephens, A., Knuth, E., Gardiner, A. M., Isler, I., & Kim, J.-S. (2015). The development of children’s algebraic thinking: The impact of a comprehensive early algebra intervention in third grade. Journal for Research in Mathematics Education, 46(1), 39–87

    Article  Google Scholar 

  • Blanton, M. L., Stroud, R., Stephens, A., Gardiner, A. M., Stylianou, D. A., Knuth, E., Isler-Baykal, I., & Strachota, S. (2019). Does early algebra matter? The effectiveness of an early algebra intervention in grades 3 to 5. American Educational Research Journal, 56(5), 1930–1972. https://doi.org/10.3102/0002831219832301

    Article  Google Scholar 

  • Boudreaux, A., Kanim, S. E., Olsho, A., Brahmia, S. W., Zimmerman, C., & Smith, T. I. (2020). Toward a framework for the natures of proportional reasoning in introductory physics. Proceedings of the Annual Physics Education Research Conference (pp. 45–50). American Association of Physics Teachers.

  • Brahmia, S.W., Boudreaux, A., & Kanim, S. E. (in press). Developing mathematical creativity with physics invention tasks. American Journal of Physics.

  • Bressoud, D. M. (2007). A radical approach to real analysis. Mathematical Association of America.

    Book  Google Scholar 

  • Bressoud, D. M. (2020). Opportunities for change in the first two years of college mathematics. Bulletin of Mathematical Biology, 82(5), 1–12. https://doi.org/10.1007/s11538-020-00738-7

    Article  Google Scholar 

  • Bressoud, D. M., Ghedamsi, I., Martinez-Luaces, V., & Törner, G. (2016). Teaching and learning of calculus. Springer. https://doi.org/10.1007/978-3-319-32975-8_1

    Book  Google Scholar 

  • Brizuela, B. M., & Earnest, D. (2007). Multiple notational systems and algebraic understandings: The case of the “Best Deal” problem. In J. J. Kaput, D. W. Carraher, & M. L. Blanton (Eds.), Algebra in the early grades. (pp. 273–302). Erlbaum.

    Google Scholar 

  • Byerley, C. (2019). Calculus students’ fraction and measure schemes and implications for teaching rate of change functions conceptually. The Journal of Mathematical Behavior. https://doi.org/10.1016/j.jmathb.2019.03.001

    Article  Google Scholar 

  • Carli, M., Lippiello, S., Pantano, O., Perona, M., & Tormen, G. (2020). Testing students ability to use derivatives, integrals, and vectors in a purely mathematical context and in a physical context. Physical Review Physics Education Research, 16(1), 010111. https://doi.org/10.1103/PhysRevPhysEducRes.16.010111

    Article  Google Scholar 

  • Carlson, M. P. (1998). A cross-sectional investigation of the development of the function concept. In J. J. Kaput, A. H. Schoenfeld, & E. Dubinsky (Eds.), Research in Collegiate Mathematics Education, 3. (Vol. 7, pp. 114–162). Mathematical Association of America.

    Chapter  Google Scholar 

  • Carlson, M. P., Larsen, S., & Jacobs, S. (2001). An investigation of covariational reasoning and its role in learning the concepts of limit and accumulation. In: Proceedings of the 23rd annual meeting of the North American Chapter of the International Group for the psychology of mathematics education, 1, pp. 145–153.

  • Carlson, M. P., Jacobs, S., Coe, E., Larsen, S., & Hsu, E. (2002). Applying covariational reasoning while modeling dynamic events: A framework and a study. Journal for Research in Mathematics Education, 33(5), 352–378

    Article  Google Scholar 

  • Carpenter, T. P., Franke, M. L., & Levi, L. (2003). Thinking mathematically: Integrating arithmetic and algebra in elementary school (12914424). Heinemann.

    Google Scholar 

  • Carraher, D. W., Schliemann, A. D., & Brizuela, B. M. (2000). In: M. Fernandez (Eds.), Early algebra, early arithmetic: Treating operations as functions (vol. 1, pp. 1–26). PME-NA.

  • Castillo-Garsow, C. C. (2012). Continuous quantitative reasoning. In R. Mayes, R. Bonillia, L. L. Hatfield, & S. Belbase (Eds.), Quantitative reasoning: Current state of understanding. (Vol. 2, pp. 55–73). University of Wyoming.

    Google Scholar 

  • Castillo-Garsow, C., Johnson, H. L., & Moore, K. C. (2013). Chunky and smooth images of change. For the Learning of Mathematics, 33(3), 31–37

    Google Scholar 

  • Christensen, W. M., & Thompson, J. R. (2012). Investigating graphical representations of slope and derivative without a physics context. Physical Review Special Topics Physics Education Research, 8(2), 023101. https://doi.org/10.1103/PhysRevSTPER.8.023101

    Article  Google Scholar 

  • Confrey, J., & Smith, E. (1994). Exponential functions, rates of change, and the multiplicative unit. Educational Studies in Mathematics, 26(2–3), 135–164

    Article  Google Scholar 

  • Confrey, J., & Smith, E. (1995). Splitting, covariation and their role in the development of exponential function. Journal for Research in Mathematics Education, 26(1), 66–86

    Article  Google Scholar 

  • Cornu, B. (1981). Apprentissage de la notion de limite: Modèles spontanés et modèles propres. In: Actes Du Cinquième Colloque Du Groupe Internationale PME (pp. 322–326).

  • Cornu, B. (1983). Apprentissage de la notion de limite: Conceptions et obstacles [Ph.D. dissertation]. University of Grenoble.

  • Cornu, B. (1991). Limits. In D. Tall (Ed.), Advanced mathematical thinking. (pp. 153–166). Kluwer.

    Google Scholar 

  • Cottrill, J., Dubinsky, E., Nichols, D., Schwingendorf, K., Thomas, K., & Vidakovic, D. (1996). Understanding the limit concept: Beginning with a coordinated process schema. Journal of Mathematical Behavior, 15(2), 167–192

    Article  Google Scholar 

  • Doughty, L., McLoughlin, E., & van Kampen, P. (2014). What integration cues, and what cues integration in intermediate electromagnetism. American Journal of Physics, 82(11), 1093–1103. https://doi.org/10.1119/1.4892613

    Article  Google Scholar 

  • Drijvers, P. (2002). Learning mathematics in a computer algebra environment. ZDM, 34(5), 221–228

    Google Scholar 

  • Duijzer, C., Van den Heuvel-Panhuizen, M., Veldhuis, M., & Doorman, M. (2019). Supporting primary school students’ reasoning about motion graphs through physical experiences. ZDM, 51(6), 899–913. https://doi.org/10.1007/s11858-019-01072-6

    Article  Google Scholar 

  • Ellis, A. B., Özgur, Z., Kulow, T., Dogan, M. F., & Amidon, J. (2016). An exponential growth learning trajectory: Students’ emerging understanding of exponential growth through covariation. Mathematical Thinking and Learning, 18(3), 151–181. https://doi.org/10.1080/10986065.2016.1183090

    Article  Google Scholar 

  • Even, R. (1990). Subject matter knowledge for teaching and the case of functions. Educational Studies in Mathematics, 21(6), 521–544

    Article  Google Scholar 

  • Feudel, F., & Biehler, R. (2020). Students’ understanding of the derivative concept in the context of mathematics for economics. Journal Für Mathematik Didaktik. https://doi.org/10.1007/s13138-020-00174-z

    Article  Google Scholar 

  • Franke, M. L., Carpenter, T. P., & Battey, D. (2007). Content matters: Algebraic reasoning. In J. J. Kaput, D. W. Carraher, & M. L. Blanton (Eds.), Algebra in the early grades. (pp. 333–360). Erlbaum.

    Google Scholar 

  • Freudenthal, H. (1983). Didactical phenomenology of mathematical structures. D. Reidel.

    Google Scholar 

  • Fuad, Y., Ekawati, R., Sofro, A., & Fitriana, L. D. (2019). Investigating covariational reasoning: what do students show when solving mathematical problems? Journal of Physics Conference Series, 1417, 012061. https://doi.org/10.1088/1742-6596/1417/1/012061

    Article  Google Scholar 

  • González, D. A. (2021). The progression of preservice teachers’ covariational reasoning as they model global warming. The Journal of Mathematical Behavior, 62, 100859. https://doi.org/10.1016/j.jmathb.2021.100859

    Article  Google Scholar 

  • Graham, A. T., & Thomas, M. O. J. (2000). Building a versatile understanding of algebraic variables with a graphic calculator. Educational Studies in Mathematics, 41(3), 265–282. https://doi.org/10.1023/A:1004094013054

    Article  Google Scholar 

  • Harel, G. (2013). Intellectual need. In K. Leatham (Ed.), Vital directions for research in mathematics education. (pp. 119–151). Springer.

    Chapter  Google Scholar 

  • Hickman, L. A. (1990). John Dewey’s pragmatic technology (565957). Indiana University Press.

    Google Scholar 

  • Jacob, B. (2001). The math wars. Phi Delta Kappan, 83(3), 264–272

    Article  Google Scholar 

  • Jones, S. R. (2013). Understanding the integral: Students’ symbolic forms. The Journal of Mathematical Behavior, 32(2), 122–141. https://doi.org/10.1016/j.jmathb.2012.12.004

    Article  Google Scholar 

  • Kouropatov, A., & Dreyfus, T. (2013). Constructing the integral concept on the basis of the idea of accumulation: Suggestion for a high school curriculum. International Journal of Mathematical Education in Science and Technology, 44(5), 641–651. https://doi.org/10.1080/0020739x.2013.798875

    Article  Google Scholar 

  • Kouropatov, A., & Dreyfus, T. (2014). Learning the integral concept by constructing knowledge about accumulation. ZDM. https://doi.org/10.1007/s11858-014-0571-5

    Article  Google Scholar 

  • Kruger, K. (2019). Functional thinking: The history of a didactical principle. In H.-G. Weigand, W. McCallum, M. Menghini, M. Neubrand, & G. Schubring (Eds.), The legacy of Felix Klein. (pp. 35–53). Springer. https://doi.org/10.1007/978-3-319-99386-7_3

    Chapter  Google Scholar 

  • Küchemann, D. (1978). Children’s understanding of numerical variables. Mathematics in School, 7(4), 23–26. https://doi.org/10.2307/30213397

    Article  Google Scholar 

  • Küchemann, D. (1981). Algebra. In K. Hart (Ed.), Children’s understanding of mathematics: 11–16. (pp. 102–119). John Murray.

    Google Scholar 

  • Küchemann, D. (1984). Stages in understanding algebra. Journal of Structural Learning, 8(2), 113–124

    Google Scholar 

  • Larsen, S., Marrongelle, K., Bressoud, D. M., & Graham, K. (2017). Understanding the concepts of calculus: Frameworks and roadmaps emerging from educational research. In J. Cai (Ed.), Compendium for research in mathematics education. (pp. 526–550). National Council of Teachers of Mathematics.

    Google Scholar 

  • Lehrer, R., Schauble, L., & Wisittanawat, P. (2020). Getting a grip on variability. Bulletin of Mathematical Biology, 82(8), 106. https://doi.org/10.1007/s11538-020-00782-3

    Article  Google Scholar 

  • Lucas, L. L., & Lewis, E. B. (2019). High school students’ use of representations in physics problem solving. School Science and Mathematics, 119(6), 327–339. https://doi.org/10.1111/ssm.12357

    Article  Google Scholar 

  • McDermott, L., Rosenquist, M., & vanZee, E. (1987). Student difficulties in connecting graphs and physics: Examples from kinematics. American Journal of Physics, 55(6), 503–513

    Article  Google Scholar 

  • Moss, D. L., Boyce, S., & Lamberg, T. (2019). Representations and conceptions of variables in students’ early understandings of functions. International Electronic Journal of Mathematics Education. https://doi.org/10.29333/iejme/6257

    Article  Google Scholar 

  • Nemirovsky, R. (1996). A functional approach to algebra: Two issues that emerge. In N. Bernarz, C. Kieran, & L. Lee (Eds.), Approaches to algebra: Perspectives for research and teaching. (Vol. 18, pp. 295–313). Springer. https://doi.org/10.1007/978-94-009-1732-3_20

    Chapter  Google Scholar 

  • Nemirovsky, R., & Rubin, A. (1991). “It makes sense if you think about how the graphs work. But in reality ….”. Paper presented at the Annual Meeting of the American Educational Research Association, Chicago, IL.

  • Nguyen, D.-H., & Rebello, N. S. (2011). Students’ understanding and application of the area under the curve concept in physics problems. Physical Review Special Topics Physics Education Research, 7(1), 010112. https://doi.org/10.1103/PhysRevSTPER.7.010112

    Article  Google Scholar 

  • O’Brien, T. C. (1999). Parrot math. Phi Delta Kappan, 80(6), 434–438

    Google Scholar 

  • Oehrtman, M. C. (2009). Collapsing dimensions, physical limitation, and other student metaphors for limit concepts. Journal for Research in Mathematics Education, 40(4), 396–426

    Article  Google Scholar 

  • Oehrtman, M. C., Carlson, M. P., & Thompson, P. W. (2008). Foundational reasoning abilities that promote coherence in students’ understandings of function. In M. P. Carlson & C. Rasmussen (Eds.), Making the connection: Research and practice in undergraduate mathematics. (Vol. 73, pp. 27–42). Mathematical Association of America.

    Chapter  Google Scholar 

  • Orton, A. (1983a). Students’ understanding of differentiation. Educational Studies in Mathematics, 14(3), 235–250

    Article  Google Scholar 

  • Orton, A. (1983b). Students’ understanding of integration. Educational Studies in Mathematics, 14(1), 1–18

    Article  Google Scholar 

  • Orton, A. (1984). Understanding rate of change. Mathematics in School, 13(5), 23–26

    Google Scholar 

  • Palha, S., & Spandaw, J. (2019). The integral as accumulation function approach: A proposal of a learning sequence for collaborative reasoning. European Journal of Science and Mathematics Education, 7(3), 109–136

    Article  Google Scholar 

  • Rabin, J. M., Burgasser, A., Bussey, T. J., Eggers, J., Lo, S. M., Seethaler, S., Stevens, L., & Weizman, H. (2021). Interdisciplinary conversations in STEM education: Can faculty understand each other better than their students do? International Journal of STEM Education, 8(1), 11. https://doi.org/10.1186/s40594-020-00266-9

    Article  Google Scholar 

  • Radford, L. (1996). Some reflections on teaching algebra through generalization. In N. Bernarz, C. Kieran, & L. Lee (Eds.), Approaches to algebra. (pp. 107–111). Springer. https://doi.org/10.1007/978-94-009-1732-3_7

    Chapter  Google Scholar 

  • Rasmussen, C., Marrongelle, K., & Borba, M. C. (2014). Research on calculus: What do we know and where do we need to go? ZDM - The International Journal on Mathematics Education. https://doi.org/10.1007/s11858-014-0615-x.

    Article  Google Scholar 

  • Robinson, A. (1966). Non-standard analysis (280363). North-Holland Pub.

    Google Scholar 

  • Rodriguez, J.-M.G., Bain, K., Towns, M. H., Elmgren, M., & Ho, F. M. (2018). Covariational reasoning and mathematical narratives: Investigating students’ understanding of graphs in chemical kinetics. Chemistry Education Research and Practice. https://doi.org/10.1039/C8RP00156A

    Article  Google Scholar 

  • Roth, W.-M., & Temple, S. (2014). On understanding variability in data: A study of graph interpretation in an advanced experimental biology laboratory. Educational Studies in Mathematics, 86(3), 359–376. https://doi.org/10.1007/s10649-014-9535-5

    Article  Google Scholar 

  • Sajka, M. (2003). A secondary school student’s understanding of the concept of function—a case study. Educational Studies in Mathematics, 53(3), 229–254. https://doi.org/10.1023/A:1026033415747

    Article  Google Scholar 

  • Schifter, D., Monk, S., Russell, S. J., & Bastable, V. (2007). Early algebra: What does understanding the laws of arithmetic mean in the elementary grades. In J. J. Kaput, D. W. Carraher, & M. L. Blanton (Eds.), Algebra in the early grades. (pp. 413–448). Erlbaum.

    Google Scholar 

  • Schliemann, A., Carraher, D. W., Brizuela, B., Earnest, D., Goodrow, A., Lara-Roth, S., & Peled, I. (2003). Algebra in elementary school. In: S. Dawson, & J. Zilliox (Eds.), Proceedings of the 27th meeting of the international group for the psychology of mathematics education (Vol. 4, pp. 127–134). PME.

  • Schoenfeld, A. H. (2004). The math wars. Education Policy, 18(1), 253–286

    Article  Google Scholar 

  • Schoenfeld, A. H., & Arcavi, A. A. (1988). On the meaning of variable. Mathematics Teacher, 81(6), 420–427

    Article  Google Scholar 

  • Sealey, V. (2008). Calculus students’ assimilation of the Riemann integral [Dissertation]. Arizona State University.

  • Sealey, V. (2014). A framework for characterizing student understanding of Riemann sums and definite integrals. The Journal of Mathematical Behavior, 33, 230–245. https://doi.org/10.1016/j.jmathb.2013.12.002

    Article  Google Scholar 

  • Smith, D. A. (1970). A calculus-with-computer experiment. Educational Studies in Mathematics, 3, 1–11

    Article  Google Scholar 

  • Smith, E., & Confrey, J. (1994). Multiplicative structures and the development of logarithms: What was lost by the invention of function. In G. Harel & J. Confrey (Eds.), The development of multiplicative reasoning in the learning of mathematics. (pp. 333–360). SUNY Press.

    Google Scholar 

  • Sokolowski, A. (2020). Developing covariational reasoning among students using contexts of formulas. The Physics Educator, 2(4), 2050016

    Article  Google Scholar 

  • Steen, L. A., & Dossey, J. A. (1986). Letter endorsed by the governing boards of the Mathematical Association of America and the National Council of Teachers of Mathematics concerning calculus in the secondary schools. https://macalester.edu/~bressoud/misc/1986letter.pdf

  • Swidan, O. (2020). A learning trajectory for the fundamental theorem of calculus using digital tools. International Journal of Mathematical Education in Science and Technology, 51(4), 542–562. https://doi.org/10.1080/0020739X.2019.1593531

    Article  Google Scholar 

  • Swidan, O., & Naftaliev, E. (2019). The role of the design of interactive diagrams in teaching–learning the indefinite integral concept. International Journal of Mathematical Education in Science and Technology, 50(3), 464–485. https://doi.org/10.1080/0020739X.2018.1522674

    Article  Google Scholar 

  • Szydlik, J. E. (2000). Mathematical beliefs and conceptual understanding of the limit of a function. Journal for Research in Mathematics Education, 31(3), 258–276

    Article  Google Scholar 

  • Tall, D. O., & Vinner, S. (1981). Concept images and concept definitions in mathematics with particular reference to limits and continuity. Educational Studies in Mathematics, 12, 151–169

    Article  Google Scholar 

  • Thomas, M. O. J., de Druck, I.F., Huillet, D., Ju, M.-K., Nardi, E., Rasmussen, C., & Xie, J. (2015). Key mathematical concepts in the transition from secondary school to university. In: The Proceedings of the 12th international congress on mathematical education, pp. 265–284.

  • Thompson, P. W. (1994a). Images of rate and operational understanding of the fundamental theorem of calculus. Educational Studies in Mathematics, 26(2–3), 229–274

    Article  Google Scholar 

  • Thompson, P. W. (1994b). Students, functions, and the undergraduate mathematics curriculum. In E. Dubinsky, A. H. Schoenfeld, & J. J. Kaput (Eds.), Research in collegiate mathematics education, 1. (Vol. 4, pp. 21–44). American Mathematical Society.

    Chapter  Google Scholar 

  • Thompson, J. R. (2006). Assessing student understanding of partial derivatives in thermodynamics. AIP Conference Proceedings, 818, 77–80. https://doi.org/10.1063/1.2177027

    Article  Google Scholar 

  • Thompson, P. W. (2008, June 22). One approach to a coherent K-12 mathematics: Or, it takes 12 years to learn calculus. Paper Presented at the Pathways to Algebra Conference, Mayenne, France. http://bit.ly/15IRIPo.

  • Thompson, P. W., & Ashbrook, M. (2019). Calculus: Newton, Leibniz, and Robinson meet technology. Arizona State University.

    Google Scholar 

  • Thompson, P. W., & Carlson, M. P. (2017). Variation, covariation, and functions: Foundational ways of thinking mathematically. In J. Cai (Ed.), Compendium for research in mathematics education. (pp. 421–456). National Council of Teachers of Mathematics.

    Google Scholar 

  • Thompson, P. W., & Silverman, J. (2008). The concept of accumulation in calculus. In M. P. Carlson & C. Rasmussen (Eds.), Making the connection: Research and teaching in undergraduate mathematics. (Vol. 73, pp. 43–52). Mathematical Association of America.

    Chapter  Google Scholar 

  • Thompson, P. W., Carlson, M. P., Byerley, C., & Hatfield, N. (2014). Schemes for thinking with magnitudes: A hypothesis about foundational reasoning abilities in algebra. In L. P. Steffe, L. L. Hatfield, & K. C. Moore (Eds.), Epistemic algebra students: Emerging models of students’ algebraic knowing. (Vol. 4, pp. 1–24). Wyoming: University of Wyoming.

    Google Scholar 

  • Trigueros, M., & Ursini, S. (1999). Does the understanding of variable evolve through schooling? In O. Zaslavsky (Ed.), Proceedings of the International Group for the Psychology of Education (Vol. 4, pp. 273–280). PME.

  • Van Hoof, J., Vandewalle, J., Verschaffel, L., & Van Dooren, W. (2014). In search for the natural number bias in secondary school students’ interpretation of the effect of arithmetical operations. Learning and Instruction. https://doi.org/10.1016/j.learninstruc.2014.03.004

    Article  Google Scholar 

  • Vérillon, P., & Rabardel, P. (1995). Cognition and artifacts: A contribution to the study of thought in relation to instrumented activity. European Journal of Psychology of Education, 10(1), 77–101

    Article  Google Scholar 

  • Weinberg, A., Dresen, J., & Slater, T. (2016). Students’ understanding of algebraic notation: A semiotic systems perspective. The Journal of Mathematical Behavior, 43, 70–88. https://doi.org/10.1016/j.jmathb.2016.06.001

    Article  Google Scholar 

  • White, P., & Mitchelmore, M. C. (1996). Conceptual knowledge in introductory calculus. Journal for Research in Mathematics Education, 27(1), 79–95

    Article  Google Scholar 

  • Winograd, T., & Flores, F. (1986). Understanding computers and cognition: A new foundation for design. Ablex.

    Google Scholar 

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Thompson, P.W., Harel, G. Ideas foundational to calculus learning and their links to students’ difficulties. ZDM Mathematics Education 53, 507–519 (2021). https://doi.org/10.1007/s11858-021-01270-1

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