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ZDM

, Volume 50, Issue 1–2, pp 91–102 | Cite as

Open word problems: taking the additive or the multiplicative road?

  • Tine Degrande
  • Jo Van Hoof
  • Lieven Verschaffel
  • Wim Van Dooren
Original Article

Abstract

Previous studies have repeatedly shown that children often incorrectly use an additive model for multiplicative word problems, and a multiplicative model for additive word problems. The present study aimed to investigate which model upper primary school children tend to choose in word problems that are open to both ways of reasoning. In particular, a non-symbolic variant of the snake task of Lamon (Teaching fractions and ratios for understanding: Essential content knowledge and instructional strategies for teachers, Taylor & Francis Group, New York, NY, 2008) was administered to 279 children in fifth and sixth grade of primary education. Children were asked to indicate which of two snakes had grown the most, and to verbally explain the reasoning behind their answer. Results revealed that additive reasoning (i.e., absolute growth) was more frequently used than multiplicative reasoning (i.e., relative growth), although it appeared to be harder to verbalize. Second, both trends were more prominent for fifth than sixth graders. Third, contrary to previous studies with younger children, we did not find any differences between answers on discrete and continuous variants of the task. Nevertheless, children’s answers were more often explicitly verbalized in discrete than continuous items. Theoretical, methodological, and educational implications for solving word problems, and more generally for modelling in the domain of additive and multiplicative reasoning, are discussed.

Keywords

Modelling Word problem solving Additive reasoning Multiplicative reasoning Open word problems 

References

  1. Bailey, D. H., Littlefield, A., & Geary, D. C. (2012). The codevelopment of skill at and preference for use of retrieval-based processes for solving addition problems: Individual and sex differences from first to sixth graders. Journal of Experimental Child Psychology, 113, 78–92.  https://doi.org/10.1016/j.jecp.2012.04.014.CrossRefGoogle Scholar
  2. Blum, W., & Niss, M. (1991). Applied mathematical problem solving, modelling, applications, and links to other subjects: State, trends, and issues in mathematics instruction. Educational Studies in Mathematics, 22, 37–68.  https://doi.org/10.1007/BF00302716.CrossRefGoogle Scholar
  3. Boyer, T. W., Levine, S. C., & Huttenlocher, J. (2008). Development of proportional reasoning: Where young children go wrong. Developmental Psychology, 44, 1478–1490.  https://doi.org/10.1037/a0013110.CrossRefGoogle Scholar
  4. Cramer, K., Post, T., & Currier, S. (1993). Learning and teaching ratio and proportion: Research implications. In D. T. Owens (Ed.), Research ideas for the classroom: Middle grades mathematics (pp. 159–178). New York: Macmillan.Google Scholar
  5. Degrande, T., Verschaffel, L., & Van Dooren, W. (2014). How do Flemish children solve ‘Greek’ word problems? On children’s quantitative analogical reasoning in mathematically neutral word problems. Mediterranean Journal for Research in Mathematics Education, 13(1–2), 57–74.Google Scholar
  6. English, L. D., & Lesh, R. A. (2003). Ends-in-view problems. In R. A. Lesh & H. Doerr (Eds.), Beyond constructivism: A models and modeling perspective on mathematics problem solving, learning, and teaching (pp. 297–316). Mahwah: Lawrence Erlbaum.Google Scholar
  7. Gravemeijer, K. (2004). Emergent modelling as a precursor to mathematical modelling. In H.-W. Henn & W. Blum (Eds.), Applications and modelling in mathematics education (ICMI Study 14) (pp. 97–102). Dortmund: Universität Dortmund.Google Scholar
  8. Greer, B. (1987). Understanding of arithmetical operations as models of situations. In J. A. Sloboda & D. Rogers (Eds.), Cognitive processes in mathematics (pp. 60–80). Oxford: Clarendon.Google Scholar
  9. Greer, B. (1992). Multiplication and division as models of situations. In D. Grouws (Ed.), Handbook of research on learning and teaching mathematics (pp. 276–295). Reston: National Council of Teachers of Mathematics.Google Scholar
  10. Greer, B. (1997). Modelling reality in mathematics classroom: The case of word problems. Learning and Instruction, 7, 293–307.  https://doi.org/10.1016/S0959-4752(97)00006-6.CrossRefGoogle Scholar
  11. Greer, B., Verschaffel, L., & Mukhopadhyay, S. (2007). Modelling for life: Mathematics and children’s experience. In W. Blum, P. L. Galbraith, H.-W. Henn & M. Niss (Eds.), Modelling and applications in mathematics education (ICMI Study 14) (pp. 89–98). New York: Springer.CrossRefGoogle Scholar
  12. Hart, K. (1988). Ratio and proportion. In M. Behr & J. Hiebert (Eds.), Number concepts and operations in the middle grades (pp. 198–219). Reston: National Council of Teachers of Mathematics.Google Scholar
  13. Jeong, Y., Levine, S., & Huttenlocher, J. (2007). The development of proportional reasoning: Effect of continuous vs. discrete quantities. Journal of Cognition and Development, 8, 237–256.  https://doi.org/10.1080/15248370701202471.CrossRefGoogle Scholar
  14. Kaput, J. J., & West, M. M. (1994). Missing-value proportional reasoning problems: Factors affecting informal reasoning patterns. In G. Harel & J. Confrey (Eds.), The development of multiplicative reasoning in the learning of mathematics (pp. 235–287). New York: State University of New York Press.Google Scholar
  15. Karplus, R., Pulos, S., & Stage, E. (1983). Proportional reasoning of early adolescents. In R. Lesh & M. Landau (Eds.), Acquisition of mathematical concepts and processes (pp. 45–89). New York: Academic Press.Google Scholar
  16. Lamon, S. J. (2008). Teaching fractions and ratios for understanding: Essential content knowledge and instructional strategies for teachers (2nd edn.). New York: Taylor & Francis Group.Google Scholar
  17. Lamon, S. J., & Lesh, R. (1992). Interpreting responses to problems with several levels and types of correct answers. In R. Lesh & S. J. Lamon (Eds.), Assessment of authentic performance in school mathematics (pp. 319–342). Washington, DC: American Association for the Advancement of Science Press.Google Scholar
  18. Lesh, R., & Doerr, H. M. (2003). Beyond constructivism. Models and modelling perspectives on mathematical problem solving, learning, and teaching. Mawah: Lawrence Erlbaum.Google Scholar
  19. McMullen, J. A., Hannula-Sormunen, M. M., & Lehtinen, E. (2011). Young children’s spontaneous focusing on quantitative aspects and their verbalizations of their quantitative reasoning. In B. Ubuz (Ed.), Proceedings of the 35th Conference of the International Group for the Psychology of Mathematics Education (Vol. 3, pp. 217–224). Ankara, Turkey: PME.Google Scholar
  20. Ministerie van de Vlaamse Gemeenschap. (1997). Decreet van juli 1997 tot bekrachtiging van de ontwikkelingsdoelen en eindtermen van het gewoon basisonderwijs [Decree of July 1997 to ratify the development goals and standards of primary education]. Brussels: Author.Google Scholar
  21. Mix, K. S., Levine, S. C., & Huttenlocher, J. (1999). Early fraction calculation ability. Developmental Psychology, 35, 164–174.  https://doi.org/10.1037/0012-1649.35.1.164.CrossRefGoogle Scholar
  22. Noelting, G. (1980). The development of proportional reasoning and the ratio concept: Part 1. Differentiation of stages. Educational Studies in Mathematics, 11, 217–253.  https://doi.org/10.1007/BF00304357.CrossRefGoogle Scholar
  23. Nunes, T., & Bryant, P. (2010). Understanding relations and their graphical representation. Retrieved from http://www.nuffieldfoundation.org/sites/defaukt/files/P4.pdf.
  24. Obersteiner, A., Bernhard, M., & Reiss, K. (2015). Primary school children’s strategies in solving contingency table problems: The role of intuition and inhibition. ZDM, 47, 825–836.  https://doi.org/10.1007/s11858-015-0681-8.CrossRefGoogle Scholar
  25. Pellegrino, J. W., & Glaser, R. (1982). Analyzing aptitudes for learning: Inductive reasoning. In R. Glaser (Ed.), Advances in instructional psychology (Vol. 2, pp. 269–345). Hillsdale: Lawrence Erlbaum.Google Scholar
  26. Resnick, L. B., & Singer, J. A. (1993). Protoquantitative origins of ratio reasoning. In T. P. Carpenter, E. Fennema & T. A. Romberg (Eds.), Rational numbers: An integration of research (pp. 107–130). Hillsdale: Lawrence Erlbaum.Google Scholar
  27. Schukajlow, S., & Krug, A. (2014). Do multiple solutions matter? Prompting multiple solutions, interest, competence, and autonomy. Journal for Research in Mathematics Education, 45, 497–533.CrossRefGoogle Scholar
  28. Schukajlow, S., Krug, A., & Rakoczy, K. (2015). Effects of prompting multiple solutions for modelling problems on students’ performance. Educational Studies in Mathematics, 89, 393–417.  https://doi.org/10.1007/s10649-015-9608-0.CrossRefGoogle Scholar
  29. Siegler, R. S. (2000). Unconscious insights. Current Directions in Psychological Science, 9, 79–83.CrossRefGoogle Scholar
  30. Siemon, D., Breed, M., & Virgona, J. (2005). From additive to multiplicative thinking—The big challenge of the middle years. In J. Mousley, L. Bragg, & C. Campbell (Eds.), Proceedings of the 42nd Conference of the Mathematical Association of Victoria. Bundoora, Australia.Google Scholar
  31. Sophian, C. (2000). Perceptions of proportionality in young children: Matching spatial ratios. Cognition, 75, 145–170.  https://doi.org/10.1016/S0010-0277(00)00062-7.CrossRefGoogle Scholar
  32. Sowder, L. (1988). Children’s solutions of story problems. The Journal of Mathematical Behavior, 7, 227–238.Google Scholar
  33. Spinillo, A. G., & Bryant, P. (1999). Proportional reasoning in young children: Part–part comparisons about continuous and discontinuous quantity. Mathematical Cognition, 5, 181–197.  https://doi.org/10.1080/135467999387298.CrossRefGoogle Scholar
  34. Star, J. R., & Rittle-Johnson, B. (2008). Flexibility in problem solving: The case of equation solving. Learning and Instruction, 18, 565–579.  https://doi.org/10.1016/j.learninstruc.2007.09.018.CrossRefGoogle Scholar
  35. Usiskin, Z. (2007). The arithmetic operations as mathematical models. In W. Blum, P. L. Galbraith, H.-W. Henn & M. Niss (Eds.), Modelling and applications in mathematics education (ICMI Study 14) (pp. 257–264). New York: Springer.CrossRefGoogle Scholar
  36. Van Dooren, W., De Bock, D., Evers, M., & Verschaffel, L. (2009). Students’ overuse of proportionality on missing-value problems: How numbers may change solutions. Journal for Research in Mathematics Education, 40, 187–211.Google Scholar
  37. Van Dooren, W., De Bock, D., Hessels, A., Janssens, D., & Verschaffel, L. (2005). Not everything is proportional: Effects of age and problem type on propensities for overgeneralization. Cognition and Instruction, 23, 57–86.  https://doi.org/10.1207/s1532690xci2301_3.CrossRefGoogle Scholar
  38. Van Dooren, W., De Bock, D., Janssens, D., & Verschaffel, L. (2008). The linear imperative: An inventory and conceptual analysis of students’ overuse of linearity. Journal for Research in Mathematics Education, 39, 311–342.  https://doi.org/10.2307/30034972.Google Scholar
  39. Van Dooren, W., De Bock, D., & Verschaffel, L. (2010). From addition to multiplication … and back. The development of students’ additive and multiplicative reasoning skills. Cognition and Instruction, 28, 360–381.  https://doi.org/10.1080/07370008.2010.488306.CrossRefGoogle Scholar
  40. Van Dooren, W., Verschaffel, L., Greer, B., & De Bock, D. (2006). Modelling for life: Developing adaptive expertise in mathematical modelling from an early age. In L. Verschaffel, F. Dochy, M. Boekaerts & S. Vosniadou (Eds.), Instructional psychology: Past, present and future trends. Sixteen essays in honour of Erik De Corte (pp. 91–112). Oxford: Elsevier.Google Scholar
  41. Vergnaud, G. (1983). Multiplicative structures. In R. Lesh & M. Landau (Eds.), Acquisition of mathematics concepts and processes (pp. 127–174). New York: Academic Press.Google Scholar
  42. Vergnaud, G. (1988). Multiplicative structures. In J. Hiebert & M. Behr (Eds.), Number concepts and operations in the middle grades (pp. 141–161). Reston: Lawrence Erlbaum & National Council of Teachers of Mathematics.Google Scholar
  43. Verschaffel, L., De Corte, E., & Lasure, S. (1994). Realistic considerations in mathematical modeling of school arithmetic word problems. Learning and Instruction, 4, 273–294.  https://doi.org/10.1016/0959-4752(94)90002-7.CrossRefGoogle Scholar
  44. Verschaffel, L., Greer, B., & De Corte, E. (2000). Making sense of word problems. Lisse: Swets & Zeitlinger.Google Scholar
  45. Verschaffel, L., Greer, B., & De Corte, E. (2007). Whole number concepts and operations. In F. Lester (Ed.), Second handbook of research on mathematics teaching and learning (pp. 557–628). Charlotte: Information Age Publishing.Google Scholar
  46. Verschaffel, L., Van Dooren, W., Greer, B., & Mukhopadhyah, S. (2010). Reconceptualising word problems as exercises in mathematical modeling. Journal für Mathematik-Didaktik, 31, 9–29.CrossRefGoogle Scholar
  47. Wynn, K. (1997). Competence models of numerical development. Cognitive Development, 12, 333–339.  https://doi.org/10.1016/S0885-2014(97)90005-8.CrossRefGoogle Scholar

Copyright information

© FIZ Karlsruhe 2017

Authors and Affiliations

  • Tine Degrande
    • 1
  • Jo Van Hoof
    • 1
  • Lieven Verschaffel
    • 1
  • Wim Van Dooren
    • 1
  1. 1.KU Leuven, Centre for Instructional Psychology and TechnologyLeuvenBelgium

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