”I’m trying to demystify mathematics”: Exploring the goals for teaching mathematical models and modelling in interdisciplinary education
Keywords:
mathematicsAbstract
Mathematical models and modelling are essential tools in interdisciplinary education, particularly in fisheries biology. This study theorizes the teaching goals for mathematical modelling in a graduate biology course, focusing on how these goals unfold in an interdisciplinary discourse. The course was selected for its potential to illustrate how modelling activities unfold in graduate courses which engage with similar expert-level professional modelling practices. The data collection consists of a semi-structured interview with a fisheries biology professor, as well as written notes from the lectures. Using the commognitive perspective, the study identifies three hierarchical teaching goals: fostering familiarity with academic fisheries discourse; promoting a sense of belonging to multiple discourse communities; and supporting the engagement with technical language and professional software. The findings are discussed in light of other research about teaching practices for interdisciplinary engagement with mathematical modelling.
References
Aikens, M. L. (2020). Meeting the Needs of A Changing Landscape: Advances and Challenges in Undergraduate Biology Education. Bulletin of Mathematical Biology, 82(60), 1–20.
https://doi.org/10.1007/s11538-020-00739-6
Beverton, R. J. H., & Holt, S. J. (1957). On the dynamics of exploited fish populations (Vol. 19). Chapman and Hall. https://doi.org/10.1007/978-94-011-2106-4
Blomhøj, M., & Jensen, T. H. (2007). What’s all the fuss about competencies? In W. Blum, P. L. Galbraith, H.-W. Henn, & M. Niss (Eds.), Modelling and applications in mathematics education: The 14th ICMI Study (pp. 45–56). Springer. https://doi.org/10.1007/978-0-387-29822-1
Blum, W. (2015). Quality teaching of mathematical modelling: What do we know, what can we do? In S. J. Cho (Ed.), The proceedings of the 12th International Congress on Mathematical Education (pp. 73–96). Cham: Springer. https://doi.org/10.1007/978-3-319-12688-3_9
Borromeo Ferri, R., & Mousoulides, N. (2017). Mathematical modelling as a prototype for interdisciplinary mathematics education? Theoretical reflections. In T. Dooley & G. Gueudet (Eds.), Proceedings of the 10th Congress of the European Society for Research in Mathematics Education (CERME 10) (pp. 1009–1016). DCU Institute of Education & ERME. https://hal.science/hal-01949931
Campillay-Llanos, W., & Cárcamo-Mansilla, N. (2025). How do we model what we model? An interdisciplinary approach for educational integration between mathematics and biology. Discover Education, 4, Article 145. https://doi.org/10.1007/s44217-025-00584-6
Chiel, H. J., McManus, J. M., & Shaw, K. M. (2010). From biology to mathematical models and back: Teaching modeling to biology students, and biology to math and engineering students. CBE—Life Sciences Education, 9(3), 248–265. https://doi.org/10.1187/cbe.10-03-0016
Dapueto, C., & Parenti, L. (1999). Contributions and obstacles of contexts in the development of mathematical knowledge. Educational Studies in Mathematics, 39, 1–21. https://doi.org/10.1023/A:1003702003886
Diaz Eaton, C., Highlander, H. C., Dahlquist, K. D., Ledder, G., LaMar, M. D., & Schugart, R. C. (2019). A ”rule-of-five” framework for models and modeling to unify mathematicians and biologists and improve student learning. PRIMUS, 29(8), 799–829.
https://doi.org/10.1080/10511970.2018.1456949
Doig, B., & Williams, J. (2019). Introduction to interdisciplinary mathematics education. In B. Doig, J. Williams, D. Swanson, R. Borromeo Ferri, & P. Drake (Eds.), Interdisciplinary mathematics education: The state of the art and beyond (pp. 1–8). Springer Open.
https://doi.org/10.1007/978-3-030-11066-6_1
Gross, L. J. (2004). Interdisciplinarity and the undergraduate biology curriculum: Finding a balance. Cell Biology Education, 3(2), 85–87.
https://doi.org/10.1187/cbe.04-03-0040
Heilio, M. (2011). Modelling and the educational challenge in industrial mathematics. In G. Kaiser, W. Blum, R. Borromeo Ferri, & G. Stillman (Eds.), Trends in teaching and learning of mathematical modelling (pp. 479–488). Springer. https://doi.org/10.1007/978-94-007-0910-2_47
Hernandes-Gomes, G., & Gonzales-Martin, A. (2016). Teaching calculus in engineering courses: Different backgrounds, different personal relationships? In C. Winsløw & E. Nardi (Eds.), Proceedings of the Second Conference of the International Network for Didactic Research in University Mathematics (INDRUM 2016) (pp. 201–210). University of Montpellier & INDRUM.
Hester, S., Buxner, S., Elfring, L., & Nagy, L. (2014). Integrating quantitative thinking into an introductory biology course improves students’mathematical reasoning in biology contexts. CBE—Life Sciences Education, 13(1), 54–64. https://doi.org/10.1187/cbe.13-07-0129
Heyd-Metzuyanim, E., & Shabtay, G. (2019). Narratives of ‘good’instruction: teachers’identities as drawing on exploration vs. acquisition pedagogical discourses. ZDM—Mathematics Education, 51, 541–554.
https://doi.org/10.1007/s11858-018-01019-3
Hoffman, K., Leupen, S., Dowell, K., Kephart, K., & Leip, J. (2016). Development and assessment of modules to integrate quantitative skills in introductory biology courses. CBE—Life Sciences Education, 15(2), 1–12. https://doi.org/10.1187/cbe.15-09-0186
Jungck, J. R., Robeva, R. & Gross, L.J. (2020). Mathematical Biology Education: Changes, Communities, Connections, and Challenges. Bulletin of Mathematical Biology, 82(117), 1–14.
https://doi.org/10.1007/s11538-020-00793-0
Kaasila, R. (2007). Using narrative inquiry for investigating the becoming of a mathematics teacher. ZDM—Mathematics Education, 39, 205–213.
https://doi.org/10.1007/s11858-007-0023-6
Lehrer, R., & Schauble, L. (2010). What kind of explanation is a model? In M. Stein & L. Kucan (Eds.), Instructional explanations in the disciplines (pp. 9–22). Springer. https://doi.org/10.1007/978-1-4419-0594-9_2
Lofgren, E. T. (2016). Unlocking the black box: Teaching mathematical modeling with popular culture. FEMS Microbiology Letters, 363(20).
https://doi.org/10.1093/femsle/fnw225
Ludwig, P., Tongen, A., & Walton, B. (2017). Two project-based strategies in an interdisciplinary mathematical modeling in biology course. PRIMUS, 28(4), 300–317. https://doi.org/10.1080/10511970.2016.1246495
Metz, A. M. (2008). Teaching statistics in biology: Using inquiry-based learning to strengthen understanding of statistical analysis in biology laboratory courses. CBE—Life Sciences Education, 7(3), 317–326.
https://doi.org/10.1187/cbe.07-07-0046
Poladian, L. (2013). Engaging life-sciences students with mathematical models: Does authenticity help? International Journal of Mathematical Education in Science and Technology, 44(6), 865–876.
https://doi.org/10.1080/0020739X.2013.811301
Sfard, A. (2008). Thinking as communicating: Human development, the growth of discourses, and mathematizing. Cambridge University Press.
https://doi.org/10.1017/CBO9780511499944
Siller, H.-S., Geiger, V., & Greefrath, G. (2023). The role of digital resources in mathematical modelling in extending mathematical capability. In B. Pepin, G. Gueudet, & J. Choppin (Eds.), Handbook of digital resources in mathematics education (pp. 1–20). Springer.
https://doi.org/10.1007/978-3-030-95060-6_18-1
Tetaj, F., & Viirman, O. (2023). Analysing the mathematical discourse of biology assignments: The case of a graduate fisheries management course. International Journal of Research in Undergraduate Mathematics Education, 9, 375–397. https://doi.org/10.1007/s40753-022-00205-9
Treffert-Thomas, S., Viirman, O., Hernández-Martínez, P., & Rogovchenko, Y. (2017). Mathematics lecturers’views on the teaching of mathematical modelling. Nordic Studies in Mathematics Education, 22(4), 121–145.
https://doi.org/10.7146/nomad.v22i4.148923
van Hemmen, J. L. (2007). Biology and mathematics: A fruitful merger of two cultures. Biological Cybernetics, 97(1), 1–3.
https://doi.org/10.1007/s00422-007-0163-3
Vos, P. (2011). What is ”authentic” in the teaching and learning of mathematical modelling? In G. Kaiser, W. Blum, R. Borromeo Ferri, & G. Stillman (Eds.), Trends in teaching and learning of mathematical modelling (pp. 713–722). Springer. https://doi.org/10.1007/978-94-007-0910-2_68
Weisstein, A. E. (2011). Building mathematical models and biological insight in an introductory biology course. Mathematical Modelling of Natural Phenomena, 6(6), 198–214. https://doi.org/10.1051/mmnp/20116610
Yin, R. K. (2014). Case study research: Design and methods (5th ed.). Sage.
Downloads
Published
How to Cite
Issue
Section
License
This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.
