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Mathematical Modeling in the Elementary Grades: Developing and Testing an Assessment

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Abstract

Mathematical modeling is a high-leverage topic, critical for college and career readiness, participation in STEM education, and civic engagement. Mathematical modeling involves connecting real-world situations, phenomenon, and/or data with mathematical models, and in this way applies across various STEM disciplines, including mathematics, engineering, and science. Although research has begun to explore mathematical modeling instruction in the elementary grades, questions remain about how to assess student learning at the elementary level. We addressed this need by designing an assessment of mathematical modeling competencies for students in grades 3 through 5. Informed by international research, our assessment includes a hybrid structure to assess mathematical modeling competencies holistically (as students engage in the complete modeling process) and atomistically (as students engage in different components of the modeling process, including making sense of phenomena and real-world situations, setting up and operating on mathematical models, and interpreting results in relation to the real-world context). We conducted student interviews, followed by two rounds of pilot testing to inform item development and ensure acceptable psychometric properties. The final assessment included 13 items (9 multiple choice, 3 open-response, and 1 complete modeling task). We describe our assessment development process, and provide sample assessment items and detailed coding rubrics. We summarize quantitative analyses which established high reliability and low standard error for our assessment, supporting its use for grades 3 to 5. Implications of our framework and assessment for mathematical modeling instruction and future research on STEM learning are discussed.

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  1. Please contact the first author for inquiries about accessing or using the MMSA instrument.

References

  • Abassian, A., Safi, F., Bush, S., & Bostic, J. (2020). Five different perspectives on mathematical modeling in mathematics education. Investigations in Mathematics Learning, 12(1), 53–65.

    Article  Google Scholar 

  • Aguirre, J., Anhalt, C., Cortez, R., Turner, E., & Simic-Muller, K. (2019). Engaging teachers in the powerful combination of mathematical modeling and social justice: The flint water task. Mathematics Teacher Educator, 7(2), 7–26.

    Article  Google Scholar 

  • American Educational Research Association [AERA], American Psychological Association [APA], and National Council on Measurement in Education [NCME]. (2014). Standards for educational and psychological testing. AERA.

  • Antonius, S. (2007). Modelling based project examination. In P. L. Galbraith, H.-W. Henn, & M. Niss (Eds.), Modelling and applications in mathematics education: The 14th ICMI Study (Vol. 10, New ICMI Study Series, pp. 409–416). Springer.

  • Arikan, S., Erktin, E., & Pesen, M. (2020). Development and validation of a STEM competencies assessment framework. International Journal of Science and Mathematics Education. https://doi.org/10.1007/s10763-020-10132-3.

  • Biccard, P., & Wessels, D. (2017). Six principles to assess modeling abilities of students working in groups. In G. Stillman, W. Blum, & G. Kaiser (Eds.), Mathematical modelling and applications: Crossing and researching boundaries in mathematics education (pp. 589–600). Springer.

  • Blomhøj, M., & Jensen, T. H. (2003). Developing mathematical modelling competence: Conceptual clarification and educational planning. Teaching mathematics and its applications, 22(3), 123–139.

    Article  Google Scholar 

  • Blum, W. (2011). Can modelling be taught and learnt? Some answers from empirical research. In G. Kaiser, W. Blum, R. B. Ferri, & G. Stillman (Eds.), Trends in teaching and learning of mathematical modelling: ICTMA 14 (pp. 15–30). Springer.

  • Blum, W., & Kaiser, G. (1997). Vergleichende empirische Untersuchungen zu mathematischen Anwendungsfähigkeiten von englischen und deutschen Lernenden [Comparative empirical studies on mathematical application skills of English and German learners]. Unpublished application to Deutsche forschungsgesellschaft.

  • Bostic, J. D., & Sondergeld, T. A. (2015). Measuring sixth-grade students’ problem solving: Validating an instrument addressing the mathematics Common Core. School Science and Mathematics, 115(6), 281–291.

    Article  Google Scholar 

  • Carlson, M. A., Wickstrom, M. H., Burroughs, E. A., & Fulton, E. W. (2016). A case for mathematical modeling in the elementary school classroom. In C. R. Hirsch (Ed.), Mathematical modeling and modeling mathematics (pp. 121–129). NCTM.

  • Chan, E. C. M., Ng, D. K. E., Widjaja, W., & Seto, C. (2012). Assessment of primary 5 students’ mathematical modelling competencies. Journal of Science and Mathematics Education in Southeast Asia, 35(2), 146–178.

    Google Scholar 

  • Cohen, J. (1960). A coefficient of agreement for nominal scales. Educational and Psychological Measurement, 20, 37–46.

    Article  Google Scholar 

  • Common Core State Standards for Mathematics (CCSSM). (2010). Washington, DC: National Governors Association Center for Best Practices and the Council of Chief State School Officers.

  • Core Team, R. (2020). R: A language and environment for statistical programming. R Foundation for Statistical Computing: R Foundation for Statistical Computing. Retrieved from https://www.r-project.org/.

    Google Scholar 

  • Djepaxhija, B., Vos, P., & Fuglestad, A. B. (2017). Assessing mathematizing competences through multiple-choice tasks: Using students’ response processes to investigate task validity. In G. Stillman, W. Blum, & G. Kaiser (Eds.), Mathematical modelling and applications: Crossing and researching boundaries in mathematics education (pp. 601–611). Springer.

  • Doerr, H., & Tripp, J. (1999). Understanding how students develop mathematical models. Mathematical Thinking and Learning, 1(3), 231–254.

    Article  Google Scholar 

  • Drijvers, P., Kodde-Buitenhuis, H., & Doorman, M. (2019). Assessing mathematical thinking as part of curriculum reform in the Netherlands. Educational Studies in Mathematics, 102(3), 435–456.

    Article  Google Scholar 

  • English, L. D. & Watters, J. J. (2005). Mathematical modelling with 9-year-olds. In H. L. Chick & J. L. Vincent (Eds.), Proceedings of the 29th Annual Conference of the International Group for the Psychology of Mathematics Education (Vol. 2, pp. 297–304). PME.

  • Eu Leong, K. E. (2012). Assessment of mathematical modeling. Journal of Mathematics Education at Teachers College, 3(1), 61–65.

    Google Scholar 

  • Frejd, P. (2013). Modes of modelling assessment—A literature review. Educational Studies in Mathematics, 84(3), 413–438.

    Article  Google Scholar 

  • Garfunkel, S., & Montgomery, M. (Eds.). (2016). GAIMME: Guidelines for assessment & instruction in mathematical modeling education. SIAM.

    Google Scholar 

  • Haines, C., & Crouch, R. (2001). Recognizing constructs within mathematical modelling. Teaching Mathematics and Its Applications: International Journal of the IMA, 20(3), 129–138.

    Article  Google Scholar 

  • Haines, C., Crouch, R., & Davis, J. (2000). Mathematical modelling skills: A research instrument (Technical Report No. 55). University of Hertfordshire.

  • Hankeln, C., Adamek, C., & Greefrath, G. (2019). Assessing sub-competencies of mathematical modelling—Development of a new test instrument. In G. Stillman & J. Brown (Eds.), Lines of inquiry in mathematical modelling research in education: ICME-13 Monographs (pp. 143–160). Springer.

  • Jensen, T. H. (2007). Assessing mathematical modelling competency. In C. P. Haines, P. Galbraith, W. Blum, & S. Khan (Eds.), Mathematical modelling (ICTMA 12): Education, engineering and economics (pp. 141–148). Horwood.

  • Kaiser, G. (2007). Modelling and modelling competencies in school. In C. Haines, P. Galbraith, W. Blum, & S. Khan (Eds.), Mathematical modelling: Education, engineering and economics (pp. 110–119). Horwood.

  • Kaiser, G. (2017). The teaching and learning of mathematical modeling. In J. Cai (Ed.), Compendium for Research in Mathematics Education (pp. 267–291). The National Council of Teachers of Mathematics, Inc.

  • Kaiser, G., & Brand, S. (2015). Modelling competencies: Past development and further perspectives. In G. A. Stillman, W. Blum, & M. S. Biembengut (Eds.), Mathematical modelling in education research and practice (pp. 129–149). Springer.

  • Kaiser, G., & Sriraman, B. (2006). A global survey of international perspectives on modelling in mathematics education. ZDM, 38(3), 302–310. https://doi.org/10.1007/BF02652813.

    Article  Google Scholar 

  • Kaiser, G., Sriraman, B., Blomhøj, M., & Garcia, F. J. (2007). Report from the working group modelling and applications—Differentiating perspectives and delineating commonalties. In D. Pitta-Pantazi & G. Philippou (Eds.), Proceedings of the 5th congress of the European society for research in mathematics education (pp. 2035–2041). ERME.

  • Kaiser-Meβmer, G. (1986). Modelling in calculus instruction-empirical research towards an appropriate introduction of concepts. In J. Berry, D. Burghes & I. Huntley (Eds.), Mathematical modelling methodology, models and micros (pp. 36-47). Ellis Horwood.

  • Kline, R. B. (2015). Principles and practice of structural equation modeling (4th ed.). Guilford Press.

    Google Scholar 

  • NGSS Lead States. (2013). Next generation science standards: For states, by states. The National Academies Press.

    Google Scholar 

  • Lesh, R., Hoover, M., Hole, B., Kelly, A., & Post, T. (2000). Principles for developing thought-revealing activities for students and teachers. In A. E. Kelly & R. A. Lesh (Eds.), Handbook of research design in mathematics and science education (pp. 591–645). Lawrence Erlbaum Associates.

  • Llinares, S., & Roig, A. (2008). Secondary school students’ construction and use of mathematical models in solving word problems. International Journal of Science and Mathematics Education, 6, 505–532.

    Article  Google Scholar 

  • Maaß, K. (2006). What are modelling competencies? ZDM, 38(2), 113–142.

    Article  Google Scholar 

  • Matsuzaki, A. (2007). How might we share models through cooperative mathematical modelling? Focus on situations based on individual experiences. In P. L. Galbraith, H.-W. Henn, & M. Niss (Eds.), Modelling and applications in mathematics education: The 14th ICMI Study (Vol. 10, New ICMI Study Series, pp. 357–364). Springer.

  • Matsuzaki, A., & Kawakami, T. (2010). Situation models reformulation in mathematical modelling: The case of modelling tasks based on real situations for elementary school pupils. In Proceedings of the 5th East Asia Regional Conference on Mathematics Education (Vol. 2, pp. 164-171).

  • Mousoulides, N., Sriraman, B., & Christou, C. (2007). From problem solving to modelling. Education, 12(1), 23–47.

    Google Scholar 

  • Niss, M. (1993). Assessment of mathematical modelling and applications in mathematics teaching. In J. de Lange, C. Keitel, I. Huntley, & M. Niss (Eds.), Innovation in mathematics education by modelling and applications (pp. 41–51). Horwood.

  • Niss, M., Blum, W., & Galbraith, P. L. (2007). Introduction. In P. L. Galbraith, H.-W. Henn, & M. Niss (Eds.), Modelling and applications in mathematics education: The 14th ICMI Study (Vol. 10, New ICMI Study Series, pp. 3–32). Springer.

  • Petterson, A., & Braeken, J. (2019). Mathematical competency demands of assessment items: A search for empirical evidence. International Journal of Science and Mathematics Education, 17, 405–425.

    Article  Google Scholar 

  • Rosseel, Y. (2012). Lavaan: An R package for structural equation modeling. Journal of Statistical Software, 48(2), 1–36. Retrieved from http://www.jstatsoft.org/v48/i02/.

    Article  Google Scholar 

  • Saldaña, J. (2016). The coding manual for qualitative researchers. SAGE Publications Ltd.

    Google Scholar 

  • Sawilowsky, S. S. (2009). New effect size rules of thumb. Journal of Modern Applied Statistical Methods, 8(2), 597–599. https://doi.org/10.22237/jmasm/1257035100.

    Article  Google Scholar 

  • Schukajlow, S., Kaiser, G., & Stillman, G. (2018). Empirical research on teaching and learning of mathematical modelling: A survey on the current state-of-the-art. ZDM, 50(1–2), 5–18.

    Article  Google Scholar 

  • Smith, J. E., Turner, E., & Roth-McDuffie, A. (2021). Mathematical modeling competency in upper-elementary: Validity evidence at the item level. In K. Johnson, D. Olanoff, & S. M. Spritzer (Eds.), Productive struggle: preserving through challenges. Proceedings of the 43rd Meeting of the North American Chapter of the International Group for the Psychology of Mathematics Education. https://www.pmena.org/pmenaproceedings/PMENA%2043%202021%20Proceedings.pdf.

    Google Scholar 

  • Stillman, G. (1998). The emperor’s new clothes? Teaching and assessment of mathematical applications at the senior secondary level. In P. L. Galbraith et al. (Eds.), Mathematical modelling: Teaching and assessment in a technology-rich world (pp. 243–254). Horwood.

  • Suh, J., Matson, K., & Seshaiyer, P. (2017). Engaging elementary students in the creative process of mathematizing their world trough mathematical modeling. Education Sciences, 7(62). https://doi.org/10.3390/educsci7020062.

  • Turner, E., Chen, M.-K., Roth McDuffie, A., Smith, J., Aguirre, J., Foote, M., & Bennett, A. (in press). Validating a student assessment of mathematical modeling at the elementary school level. School Science and Mathematics.

  • Verschaffel, L., & De Corte, E. (1997). Teaching realistic mathematical modeling in the elementary school: A teaching experiment with fifth graders. Journal for Research in Mathematics Education, 28(5), 577–601.

    Article  Google Scholar 

  • Vos, P. (2013). Assessment of modelling in mathematics examination papers: Ready-made models and reproductive mathematising. In G. Kaiser, W. Blum, R. Borromeo Ferri, & G. Stillman (Eds.), Trends in the teaching and learning of mathematical modelling (pp. 479–488). Springer.

  • Wickstrom, M. H., & Aytes, T. (2018). Elementary modeling: Connecting counting with sharing. Teaching Children Mathematics, 24(5), 300–307.

    Article  Google Scholar 

  • Zöttl, L., Ufer, S., & Reiss, K. (2011). Assessing modelling competencies using a multidimensional IRT approach. In G. Kaiser, W. Blum, R. Borromeo Ferri, & G. Stillman (Eds.), Trends in the teaching and learning of mathematical modelling (pp. 427–437). Springer.

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Acknowledgements

This material is based upon work supported by the National Science Foundation under the EHR Core Research (ECR) Program, grant numbers 1561305, 1561304, 1561331, and 156274. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the National Science Foundation.

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Correspondence to Erin E. Turner.

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Turner, E.E., Roth McDuffie, A., Bennett, A.B. et al. Mathematical Modeling in the Elementary Grades: Developing and Testing an Assessment. Int J of Sci and Math Educ 20, 1387–1409 (2022). https://doi.org/10.1007/s10763-021-10195-w

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