Skip to main content

An Intellectual Need for Relationships: Engendering Students’ Quantitative and Covariational Reasoning

  • Chapter
  • First Online:
Quantitative Reasoning in Mathematics and Science Education

Part of the book series: Mathematics Education in the Digital Era ((MEDE,volume 21))

Abstract

Drawing on Harel’s construct of “intellectual need,” I propose an expansion in possible categories of such needs, to include an “intellectual need for relationships.” This is a need to explain how elements work together, as in a system. Freudenthal's term, “mathematizing,” can describe a category of a way of thinking that can emerge from an intellectual need for relationships. This need can engender students’ quantitative and covariational reasoning, important not only for their mathematical development, but also for being informed citizens. I put forward four facets of an intellectual need for relationships, addressing task design considerations for each: attributes in a situation (What are the things?), measurability of attributes (How can things be measured?), variation in attributes (How do things change?), and relationships between attributes (How do things change together?). I conclude with implications for theory and practice.

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

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 119.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 159.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 159.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  • Barnett, J. E. (1999). Time’s pendulum: From sundials to atomic clocks, the fascinating history of timekeeping and how our discoveries changed the world. Houghton Mifflin Harcourt.

    Google Scholar 

  • Carlson, M., 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 

  • Castillo-Garsow, C. (2012). Continuous quantitative reasoning. In R. Mayes & Hatfield (Ed.), Quantitative reasoning and mathematical modeling: A driver for STEM integrated education and teaching in context (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 

  • Desmos. (n.d.). How graphs work. bit.ly/HowGraphsWork.

    Google Scholar 

  • Ellis, A., Ely, R., Singleton, B., & Tasova, H. (2020). Scaling-continuous variation: Supporting students’ algebraic reasoning. Educational Studies in Mathematics, 104, 87–103.

    Article  Google Scholar 

  • Freudenthal, H. (1973). Mathematics as an educational task. D. Reidel Publishing.

    Google Scholar 

  • González, D. A. (2021). The progression of preservice teachers’ covariational reasoning as they model global warming. The Journal of Mathematical Behavior, 62, Article 100859.

    Google Scholar 

  • Gutiérrez, R. (2009). Framing equity: Helping students “play the game” and “change the game.” Teaching for Excellence and Equity in Mathematics, 1(1), 4–8.

    Google Scholar 

  • Harel, G. (1998). Two dual assertions: The first on learning and the second on teaching (or vice versa). The American Mathematical Monthly: The Official Journal of the Mathematical Association of America, 105(6), 497–507.

    Article  Google Scholar 

  • Harel, G. (2008a). DNR perspective on mathematics curriculum and instruction, part I: Focus on proving. ZDM: The International Journal on Mathematics Education, 40(3), 487–500.

    Google Scholar 

  • Harel, G. (2008b). A DNR perspective on mathematics curriculum and instruction. Part II: With reference to teacher’s knowledge base. ZDM: The International Journal on Mathematics Education, 40(5), 893–907.

    Google Scholar 

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

    Chapter  Google Scholar 

  • Johnson, H. L. (2012). Reasoning about variation in the intensity of change in covarying quantities involved in rate of change. The Journal of Mathematical Behavior, 31(3), 313–330.

    Article  Google Scholar 

  • Johnson, H. L. (2020). Task design for graphs: Rethink multiple representations with variation theory. Mathematical Thinking and Learning. https://doi.org/10.1080/10986065.2020.1824056

    Article  Google Scholar 

  • Johnson, H. L., Coles, A., & Clarke, D. (2017a). Mathematical tasks and the student: navigating “tensions of intentions” between designers, teachers, and students. ZDM: The International Journal on Mathematics Education. https://link.springer.com/article/https://doi.org/10.1007/s11858-017-0894-0

  • Johnson, H. L., & McClintock, E. (2018). A link between students’ discernment of variation in unidirectional change and their use of quantitative variational reasoning. Educational Studies in Mathematics, 97(3), 299–316.

    Article  Google Scholar 

  • Johnson, H. L., McClintock, E., & Gardner, A. (2020). Opportunities for reasoning: Digital task design to promote students’ conceptions of graphs as representing relationships between quantities. Digital Experiences in Mathematics Education, 6(3), 340–366.

    Article  Google Scholar 

  • Johnson, H. L., McClintock, E., & Hornbein, P. (2017b). Ferris wheels and filling bottles: A case of a student’s transfer of covariational reasoning across tasks with different backgrounds and features. ZDM: The International Journal on Mathematics Education, 49(6), 851–864.

    Google Scholar 

  • Kerslake, D. (1977). The understanding of graphs. Mathematics in School, 6(2), 22–25.

    Google Scholar 

  • Leinhardt, G., Zaslavsky, O., & Stein, M. K. (1990). Functions, graphs, and graphing: Tasks, learning, and teaching. Review of Educational Research, 60(1), 1–64.

    Article  Google Scholar 

  • Moore, K. C., Liang, B., Tasova, H. I., & Stevens, I. E. (2019a). Abstracted quantitative structures. In S. Otten, A. Candela, Z. de Araujo, C. Haines, & C. Munter (Eds.), Proceedings of the forty-first annual meeting of the north American chapter of the international group for the psychology of mathematics education (pp. 1879–1883). University of Missouri.

    Google Scholar 

  • Moore, K. C., Silverman, J., Paoletti, T., & LaForest, K. (2014). Breaking conventions to support quantitative reasoning. Mathematics Teacher Educator, 2(2), 141–157.

    Article  Google Scholar 

  • Moore, K. C., Stevens, I. E., Paoletti, T., Hobson, N. L. F., & Liang, B. (2019b). Pre-service teachers’ figurative and operative graphing actions. The Journal of Mathematical Behavior, 56, Article 100692.

    Google Scholar 

  • Paoletti, T., & Moore, K. C. (2017). The parametric nature of two students’ covariational reasoning. The Journal of Mathematical Behavior, 48, 137–151.

    Article  Google Scholar 

  • Shell Centre for Mathematical Education (University of Nottingham). (1985). The language of functions and graphs: An examination module for secondary schools. JMB/Shell Centre for Mathematical Education.

    Google Scholar 

  • Simon, M. A., & Tzur, R. (2004). Explicating the role of mathematical tasks in conceptual learning: An elaboration of the hypothetical learning trajectory. Mathematical Thinking and Learning, 6(2), 91–104.

    Article  Google Scholar 

  • Thompson, P. W. (1994). The development of the concept of speed and its relationship to concepts of rate. In G. Harel & J. Confrey (Eds.), The development of multiplicative reasoning in the learning of mathematics (pp. 179–234). State University of New York Press.

    Google Scholar 

  • Thompson, P. W. (2002). Didactic objects and didactic models in radical constructivism. In K. Gravemeijer, R. Lehrer, B. Van Oers, & L. Verschaffel (Eds.), Symbolizing, modeling and tool use in mathematics education (pp. 197–220). Springer.

    Chapter  Google Scholar 

  • Thompson, P. W. (2011). Quantitative reasoning and mathematical modeling. In Chamberlain, S. A., & Hatfield, L. (Ed.), New perspectives and directions for collaborative research in mathematics education: Papers from a planning conference for wisdom^e (Vol. 1, pp. 33–56). University of Wyoming College of Education.

    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 

Download references

Acknowledgements

U.S. National Science Foundation Grants (DUE-1709903, DUE-2013186) have supported the development and implementation of the Ferris wheel Techtivity. Opinions and conclusions are those of the author. I thank Evan McClintock for his feedback on this manuscript.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Heather Lynn Johnson .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2022 The Author(s), under exclusive license to Springer Nature Switzerland AG

About this chapter

Check for updates. Verify currency and authenticity via CrossMark

Cite this chapter

Johnson, H.L. (2022). An Intellectual Need for Relationships: Engendering Students’ Quantitative and Covariational Reasoning. In: Karagöz Akar, G., Zembat, İ.Ö., Arslan, S., Thompson, P.W. (eds) Quantitative Reasoning in Mathematics and Science Education. Mathematics Education in the Digital Era, vol 21. Springer, Cham. https://doi.org/10.1007/978-3-031-14553-7_2

Download citation

Publish with us

Policies and ethics