Skip to main content

Advertisement

Log in

Toward a reconceptualization of model development from models-and-modeling perspective in mathematics education

  • Published:
Educational Studies in Mathematics Aims and scope Submit manuscript

Abstract

Models-and-modeling perspective (MMP) is a problem-solving and learning perspective in mathematics education. Although modeling processes have been addressed widely in the international discussion on mathematical modeling, a homogeneous understanding has not been established yet. Hence, the field needs studies addressing the epistemological grounds of model development. Therefore, in this study, I aimed to scrutinize the latent aspects of modeling in MMP-based research. Based on the analysis of 143 chapter-sized documents, I aimed to articulate the characteristics of the modeling process and the models. The thematic analysis that was incorporated in document analysis revealed four latent aspects, namely, modeling (1) is a subjective and also inter- and intra-subjective process, (2) encompasses both structural and systematic properties, (3) produces models that are both implicit and explicit to a certain degree, and (4) culminates in an incomplete — but not inadequate — model. These aspects of model development led me to reconceptualize what a model conveys in MMP-based research and articulate the potential and limits of the models. This is particularly important for teachers and researchers in understanding what models indicate in relation to students’ ways of thinking, and such a systematic and analytical investigation can contribute to the scholarly conversation about modeling in the field of mathematics education.

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

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5

Similar content being viewed by others

Notes

  1. Since the document analysis was held in 2019, the data corpus partially included the documents that were published in 2019.

  2. The keyword search in databases for years 2000–2019 resulted with 70 documents. During the initial data analysis phases, four additional documents that were cited by modeling researchers were identified as relevant. Therefore, these four additional documents two of which were published in 1990s, one document was in 1980s, and one in late 1970s were included in the data corpus.

References

  • Ärlebäck, J. B. (2009). On the use of realistic Fermi problems for introducing mathematical modelling in school. The Montana Mathematics Enthusiast, 6(3), 331–364.

    Article  Google Scholar 

  • Ärlebäck, J. B., & Doerr, H. M. (2018). Students’ interpretations and reasoning about phenomena with negative rates of change throughout a model development sequence. ZDM-Mathematics Education, 50(1), 187–200. https://doi.org/10.1007/s11858-017-0881-5

    Article  Google Scholar 

  • Ärlebäck, J., & Albarracín, L. (2017). Developing a classification scheme of definitions of Fermi problems in education from a modelling perspective. In The Proceedings of CERME 10 (pp. 884–891).

  • Biembengut, M. S. (2007). Modelling and applications in primary education. In W. Blum, P. L. Galbraith, H.-W. Henn, & M. Niss (Eds.), Modelling and applications in mathematics education: The 14th ICMI study (New ICMI Study Series, Vol. 10) (pp. 451–456). Springer. https://doi.org/10.1007/978-0-387-29822-1_50

  • Binkley, M., Erstad, O., Herman, J., Raizen, S., Ripley, M., Miller-Ricci, M., & Rumble, M. (2012). Defining twenty-first century skills. In P. Griffin, B. McGraw, & E. Care (Eds.), Assessment and teaching of 21st century skills (pp. 17–66). Springer. https://doi.org/10.1007/978-94-007-2324-5_2

  • Blum, W., & Borromeo Ferri, R. (2009). Mathematical modelling: Can it be taught and learnt? Journal of Mathematical Modelling and Application, 1(1), 45–58.

    Google Scholar 

  • Blum, W., & Leiß, D. (2007). How do students and teachers deal with mathematical modelling problems? In Haines et al. (Eds.), Mathematical modelling (ICTMA 12): Education, engineering and economics. Horwood Publishing.

  • 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

    Article  Google Scholar 

  • Borromeo Ferri, R. (2006). Theoretical and empirical differentiations of phases in the modelling process. ZDM-Mathematics Education, 38(2), 86–95. https://doi.org/10.1007/BF02655883

    Article  Google Scholar 

  • Borromeo Ferri, R. (2018). Learning how to teach mathematical modeling in school and teacher education. Springer. https://doi.org/10.1007/978-3-319-68072-9

    Article  Google Scholar 

  • Borromeo Ferri, R., & Lesh, R. (2013). Should interpretation systems be considered to be models if they only function implicitly?. In G. A. Stillman, G. Kaiser, W. Blum, & J.P Brown (Eds.), Teaching mathematical modelling: Connecting to research and practice (pp. 57–66). Springer. https://doi.org/10.1007/978-94-007-6540-5_4

  • Bowen, G. A. (2009). Document analysis as a qualitative research method. Qualitative Research Journal, 9(2), 27–40. https://doi.org/10.3316/QRJ0902027

    Article  Google Scholar 

  • Brady, C. (2018). Modelling and the representational imagination. ZDM-Mathematics Education, 50(1), 45–59. https://doi.org/10.1007/s11858-018-0926-4

    Article  Google Scholar 

  • Braun, V., & Clarke, V. (2012). Thematic analysis. In H Cooper (Ed.), APA handbook of research methods in psychology, Vol 2: Research designs: Quantitative, qualitative, neuropsychological, and biological. (pp. 57–71). American Psychological Association. https://doi.org/10.1037/13620-004

  • Care, E. (2018). Twenty-first century skills: From theory to action. In E. Care, P. Griffin, & M. Wilson (Eds.), Assessment and teaching of 21st century skills: Research and applications (pp. 3–17). Springer. https://doi.org/10.1007/978-3-319-65368-6_1

  • Cash, P., & Snider, C. (2014). Investigating design: A comparison of manifest and latent approaches. Design Studies, 35(5), 441–472. https://doi.org/10.1016/j.destud.2014.02.005

    Article  Google Scholar 

  • Chamberlin, M. (2004). Design principles for teacher investigations of student work. Mathematics Teacher Education and Development, 6, 52–62.

    Google Scholar 

  • Civil, M. (1994). Connecting the home and school: Funds of knowledge for mathematics teaching and learning. Paper presented at American Educational Research Association (AERA) 1994, New Orleans, LA. Retrieved from http://files.eric.ed.gov/fulltext/ED370987.pdf.

  • Clark, K. K., & Lesh, R. (2003). A modeling approach to describe teacher knowledge. In R. Lesh & H. Doerr (Eds.), Beyond constructivism: A models and modelling perspective on mathematics problem solving; learning and teaching (pp. 159–173). Lawrence Erlbaum.

    Google Scholar 

  • Csapó, B., & J. Funke. (2017). The nature of problem solving: Using research to inspire 21st century learning. OECD Publishing. https://doi.org/10.1787/9789264273955-en

  • Czocher, J. A. (2018). How does validating activity contribute to the modeling process? Educational Studies in Mathematics, 99(2), 137–159. https://doi.org/10.1007/s10649-018-9833-4

    Article  Google Scholar 

  • De Bock, D., Van Dooren, W., & Janssens, D. (2007). Studying and remedying students’ modelling competencies: Routine behaviour or adaptive expertise. In W. Blum, P. L. Galbraith, H.-W. Henn, & M. Niss (Eds.), Modelling and applications in mathematics education: The 14th ICMI study (New ICMI Study Series, Vol. 10) (pp. 241–248). Springer. https://doi.org/10.1007/978-0-387-29822-1_25

  • English, L. D. (2004). Mathematical modelling in the primary school. In I. Putt, R. Faragher, & M. McLean (Eds.), Mathematics education for the third millennium: Towards 2010 (Vol. 2010, pp. 207–214). Mathematics Education Research Group of Australasia.

  • English, L. D. (2006). Mathematical modeling in the primary school: Children’s construction of a consumer guide. Educational Studies in Mathematics, 63(3), 303–323. https://doi.org/10.1007/s10649-005-9013-1

    Article  Google Scholar 

  • English, L. D. (2009). Promoting interdisciplinarity through mathematical modelling. ZDM-Mathematics Education, 41(1–2), 161–181. https://doi.org/10.1007/s11858-008-0106-z

    Article  Google Scholar 

  • English, L. D., Lesh, R, & Fennewald, T. (2008). Methodologies for investigating relationships between concept development and the development of problem solving abilities. In Proceedings of the 11th International Congress on Mathematical Education (ICME 11) (pp. 1–15).

  • Frejd, P., & Bergsten, C. (2018). Professional modellers’ conceptions of the notion of mathematical modelling: Ideas for education. ZDM-Mathematics Education, 50, 117–127. https://doi.org/10.1007/s11858-018-0928-2

    Article  Google Scholar 

  • Frey, B. (2018). The SAGE encyclopedia of educational research, measurement, and evaluation (Vols. 1–4). Sage Publications. https://doi.org/10.4135/9781506326139

  • Funke, J., Fischer, A., & Holt, D. V. (2018). Competencies for complexity: Problem solving in the twenty-first century. In E. Care, P. Griffin, and M. Wilson (Eds.), Assessment and teaching of 21st century skills (pp. 41–53). Springer. https://doi.org/10.1007/978-3-319-65368-6_3

  • Giddens, A. (1976). Functionalism: Après la lutte. Social Research, 43(2), 325–366. https://www.jstor.org/stable/40970227

  • Giddens, A. (1984). The constitution of society: Outline of the theory of structuration. University of California Press.

  • Goldin, G. A. (2007). Aspects of affect and mathematical modeling processes. In R. Lesh, E. Hamilton, & J. Kaput (Eds.), Foundations for the future in mathematics education (pp. 281–296). Lawrence Erlbaum Associates.

    Google Scholar 

  • Gravemeijer, K. (2004). Local instruction theories as means of support for teachers in reform mathematics education. Mathematical Thinking and Learning, 6(2), 105–128. https://doi.org/10.1207/s15327833mtl0602_3

    Article  Google Scholar 

  • Gravemeijer, K. (2007). Emergent modelling as a precursor to mathematical modelling. In W. Blum, P. L. Galbraith, H.-W. Henn, & M. Niss (Eds.), Modelling and applications in mathematics education: The 14th ICMI study (New ICMI Study Series, Vol. 10) (pp. 137–144). Springer. https://doi.org/10.1007/978-0-387-29822-1_12

  • Gravemeijer, K., & Doorman, M. (1999). Context problems in realistic mathematics education: A calculus course as an example. Educational Studies in Mathematics, 39(1–3), 111–129. https://doi.org/10.1023/A:1003749919816

    Article  Google Scholar 

  • Gravemeijer, K., & Stephan, M. (2002). Emergent models as an instructional design heuristic. In K. Gravemeijer, R. Lehrer, B. V. Oers, & L. Verschaffel (Eds.), Symbolizing, modeling and tool use in mathematics education (pp. 145–170). Springer Science & Business. https://doi.org/10.1007/978-94-017-3194-2_10

  • Gravemeijer, K., Stephan, M., Julie, C., Lin, F. L., & Ohtani, M. (2017). What mathematics education may prepare students for the society of the future? International Journal of Science and Mathematics Education, 15(1), 105–123. https://doi.org/10.1007/s10763-017-9814-6

    Article  Google Scholar 

  • Gruber, H. E., & Vonèche, J. J. (Eds.). (1977). The essential Piaget. Basic Books.

  • Hamilton, E., Lesh, R., Lester, F., & Brilleslyper, M. (2008). Model-eliciting activities (MEAs) as a bridge between engineering education research and mathematics education research. Advances in Engineering Education, 1(2), 1–25.

    Google Scholar 

  • Hjalmarson, M., & Lesh, R. (2008). Engineering and design research: Intersections for education research and design. In A. Kelly, R. Lesh, & K. Baek (Eds.), Handbook of design research methods in education: Innovations in science, technology, engineering, and mathematics learning and teaching (pp. 96–110). Routledge.

    Google Scholar 

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

    Article  Google Scholar 

  • Lave, J. (1988). Cognition in practice: Mind, mathematics and culture in everyday life. Cambridge University Press.

    Book  Google Scholar 

  • Lesh, R. (2006). New directions for research on mathematical problem solving. In P. Grootenboer, R. Zevenbergen, & M. Chinnappan (Eds.), Identities, cultures and learning spaces, Proceedings of the 29th annual conference of the mathematics education research group of Australasia, Canberra (Vol. 1, pp. 15–34). MERGA.

  • Lesh, R. (2010). Tools, researchable issues & conjectures for investigating what it means to understand statistics (or other topics) meaningfully. Journal of Mathematical Modelling and Application, 1(2), 16–49.

    Google Scholar 

  • Lesh, R., & Caylor, B. (2007). Introduction to the special issue: Modeling as application versus modeling as a way to create mathematics. International Journal of Computers for Mathematical Learning, 12(3), 173–194. https://doi.org/10.1007/s10758-007-9121-3

    Article  Google Scholar 

  • Lesh, R., Cramer, K., Doerr, H., Post, T., & Zawojewski, J. (2003a). Model development sequences. In R. Lesh & H. Doerr (Eds.), Beyond constructivism: A models and modelling perspective on mathematics problem solving; learning and teaching (pp. 35–58). Lawrence Erlbaum Associates.

    Chapter  Google Scholar 

  • Lesh, R., & Doerr, H. M. (Eds.). (2003). Beyond constructivism: Models and modeling perspectives on mathematics problem solving learning, and teaching. Lawrence Erlbaum Associates.

  • Lesh, R., English, L., Riggs, C., & Sevis, S. (2013). Problem solving in the primary school (K-2). [Special issue]. The Mathematics Enthusiast, Special Issue: International Perspectives on Problem Solving Research in Mathematics Education, 10 (1 & 2), 35–60. https://scholarworks.umt.edu/tme/vol10/iss1/4

  • Lesh, R., & Harel, G. (2003). Problem solving, modeling, and local conceptual development. Mathematical Thinking and Learning, 5(2–3), 157–189. https://doi.org/10.1080/10986065.2003.9679998

    Article  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. Kelly & R. Lesh (Eds.), Handbook of research design in mathematics and science education (pp. 113–149). Lawrence Erlbaum Associates.

    Google Scholar 

  • Lesh, R., & Lehrer, R. (2003). Models and modeling perspectives on the development of students and teachers. Mathematical Thinking and Learning, 5(2, 3), 109–129. https://doi.org/10.1080/10986065.2003.9679996

  • Lesh, R., Lester, F. K., & Hjalmarson, M. (2003b). A models and modeling perspective on metacognitive functioning in everyday situations where problem solvers develop mathematical constructs. In R. Lesh & H. M. Doerr (Eds.), Beyond constructivism: A models and modelling perspective on mathematics problem solving; learning and teaching (pp. 383–403). Lawrence Erlbaum Associates.

    Chapter  Google Scholar 

  • Lesh, R., Mierkiewicz, D., & Kantowski, M. (1979). Applied mathematical problem solving. ERIC Clearinghouse for Science, Mathematics, and Environmental Education.

  • Lesh, R., & Yoon, C. (2004). Evolving communities of mind-in which development involves several interacting and simultaneously developing strands. Mathematical Thinking and Learning, 6(2), 205–226. https://doi.org/10.1207/s15327833mtl0602_7

    Article  Google Scholar 

  • Lesh, R., & Zawojewski, J. (2007). Problem solving and modeling. In F. K. Lester (Ed.), Second handbook of research on mathematics teaching and learning (pp. 763–804). Information Age.

    Google Scholar 

  • Lincoln, Y. S., & Guba, E. G. (1985). Naturalistic inquiry. Sage.

    Book  Google Scholar 

  • Peled, I., & Balacheff, N. (2011). Beyond realistic considerations: Modeling conceptions and controls in task examples with simple word problems. ZDM-Mathematics Education, 43(2), 307–315. https://doi.org/10.1007/s11858-011-0310-0

    Article  Google Scholar 

  • Piaget, J. (1985). The equilibration of cognitive structures: The central problem of intellectual development. University of Chicago Press.

  • Pusey, M. (1988). Jurgen Habermas. Routledge.

    Google Scholar 

  • Resnick, L. B. (1987). The 1987 presidential address: Learning in school and out. Educational Researcher, 16(9), 13–20. https://doi.org/10.3102/0013189X016009013

    Article  Google Scholar 

  • Saldaña, J. (2009). The coding manual for qualitative researchers. Sage Publications.

  • Schorr, R., & Lesh, R. (2003). A modeling approach for providing teacher development. In R. A. Lesh & H. M. Doerr (Eds.), Beyond constructivism: Models and modeling perspectives on mathematics problem solving; learning; and teaching (pp. 141–158). Lawrence Erlbaum.

    Google Scholar 

  • Sevinc, S., & Brady, C. (2019). Kindergarteners’ and first-graders’ development of numbers representing length and area: Stories of measurement. In K. Robinson, H. Osana, & D. Kotsopoulos (Eds), Mathematical learning and cognition in early childhood (pp. 115–137). Springer. https://doi.org/10.1007/978-3-030-12895-1_8

  • Sevinc, S., Kaplan Can, G., & Haser, C. (2019). 21. yuzyilda matematik ogrenme hedefli sinif-ici degerlendirme [In-class assessment for learning mathematics in the 21st-century]. In G. Haciomeroglu & K. Tarim (Eds), Matematik ogretiminin temelleri: Ortaokul (pp. 431–456). Ani Yayincilik.

  • Sevinc, S., & Melek, Z. (2020). Investigation of individual and group development of prospective mathematics teachers in modeling activity. Baskent University Journal of Education, 7(1), 1–19.

    Google Scholar 

  • Shahbari, J. A., & Peled, I. (2017). Modelling in primary school: Constructing conceptual models and making sense of fractions. International Journal of Science and Mathematics Education, 15(2), 371–391. https://doi.org/10.1007/s10763-015-9702-x

    Article  Google Scholar 

  • Simon, M. A., Placa, N., & Avitzur, A. (2016). Participatory and anticipatory stages of mathematical concept learning: Further empirical and theoretical development. Journal for Research in Mathematics Education, 47(1), 63–93. https://doi.org/10.5951/jresematheduc.47.1.0063

    Article  Google Scholar 

  • Sriraman, B., & English, L. (2005). Theories of mathematics education: A global survey of theoretical frameworks/trends in mathematics education research. ZDM-Mathematics Education, 37(6), 450–457. https://doi.org/10.1007/BF02655853

    Article  Google Scholar 

  • Stillman, G., & Brown, J. P. (2014). Evidence of implemented anticipation in mathematising by beginning modellers. Mathematics Education Research Journal, 26(4), 763–789. https://doi.org/10.1007/s13394-014-0119-6

    Article  Google Scholar 

  • Sullivan, P., Clarke, D., & Clarke, B. (Eds.). (2012). Teaching with tasks for effective mathematics learning. Springer. https://doi.org/10.1007/978-1-4614-4681-1

  • Thorndike, R. M. (2005). Measurement and evaluation in psychology and education. Pearson Prentice Hall.

  • Treffers, A. (1987). Three dimensions. A model of goal and theory description in mathematics instruction - The Wiscobas Project. D. Reidel Publ. Co.

  • VERBI Software. (2019). MAXQDA 2020 [computer software]. Berlin, Germany: VERBI Software. Available from maxqda.com.

  • Verschaffel, L., Schukajlow, S., Star, J., & Van Dooren, W. (2020). Word problems in mathematics education: A survey. ZDM-Mathematics Education, 52(1), 1–16. https://doi.org/10.1007/s11858-020-01130-4

    Article  Google Scholar 

  • Von Glasersfeld, E. (1995). Radical constructivism: A way of knowing and learning (Vol. 6 of Studies in Mathematics Education Series). Falmer.

  • Yoon, C. (2006). A conceptual analysis of the models and modeling characterization of model-eliciting activities as “thought-revealing activities”. (Indiana University). ProQuest Dissertations and Theses.

  • Zawojewski, J., Lesh, R., & English, L. (2003). A models and modeling perspective on the role of small group learning activities. In R. Lesh & H. M. Doerr (Eds.), Beyond constructivism: A models and modelling perspective on mathematics problem solving; learning and teaching (pp. 337–358). Lawrence Erlbaum Associates.

    Google Scholar 

Download references

Acknowledgements

I would like to thank Emeritus Professor Richard Lesh, who developed the MMP with his colleagues and who contributed a lot to this document and thematic analysis by discussing each of the four aspects of the modeling presented in this study.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Serife Sevinc.

Additional information

Publisher's note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Appendix. Thematic maps of the latent aspects of modeling from MMP

Appendix. Thematic maps of the latent aspects of modeling from MMP

Fig. 6
figure 6

Latent aspect #1 — inter/intra-subjective aspect of modeling

Fig. 7
figure 7

Latent aspect #2 — structural and systemic aspect of modeling

Fig. 8
figure 8

Latent aspect #3 — implicit and explicit aspects of models of modeling

Fig. 9
figure 9

Latent aspect #4 — incomplete aspect of modeling

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Sevinc, S. Toward a reconceptualization of model development from models-and-modeling perspective in mathematics education. Educ Stud Math 109, 611–638 (2022). https://doi.org/10.1007/s10649-021-10096-3

Download citation

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10649-021-10096-3

Keywords

Navigation