From Inquiry to STEM Identity

A Student-Led IB Mathematics Case Study Using Open Climate Data

Authors

  • Germán Collazos Guzmán Faculty of Communication, Universidad de La Sabana, Chía, Colombia
  • Mateo Collazos Roa Gimnasio Campestre Los Cerezos, Cajicá, Colombia https://orcid.org/0009-0008-0044-0926

DOI:

https://doi.org/10.33830/ijrse.v8i2.14479

Keywords:

STEM education, climate data literacy., mathematics education, student-led inquiry

Abstract

This article presents a research-informed educational case study based on a student-led International Baccalaureate (IB) Mathematics Internal Assessment examining the relationship between sea surface temperature (SST) and hurricane frequency in the North Atlantic. The study uses open-access climate data from the National Oceanic and Atmospheric Administration (NOAA), including SST records from Providencia (Colombia), Puerto Rico (United States), and the Azores (Portugal) for the period 1995–1998, together with historical hurricane data from the HURDAT2 database. The analysis applies inferential statistical methods, specifically Pearson correlation and simple linear regression, to explore associations between ocean temperature and cyclonic activity. Although statistical significance is constrained by the short temporal range, the results indicate consistent positive relationships between SST and hurricane frequency, with stronger associations observed in tropical regions, in line with established climatological theory. Beyond the empirical analysis, the study conceptualizes the student-led inquiry as a situated instance of STEM identity development. By formulating a researchable question, engaging with scientific datasets used in professional research, and applying statistical reasoning under conditions of uncertainty, the inquiry positions the student as an active participant in STEM knowledge production. The findings support the integration of authentic data inquiry within secondary mathematics education as a means to promote data literacy, interdisciplinary reasoning, and the development of STEM identity at the secondary education level.

References

Barton, A. C., & Tan, E. (2010). We be burnin’! Agency, identity, and science learning. Journal of the Learning Sciences, 19(2), 187–229. https://doi.org/10.1080/10508400903530044

Ben-Zvi, D., & Garfield, J. (2004). The challenge of developing statistical literacy, reasoning, and thinking. Kluwer Academic Publishers.

Boaler, J. (2016). Mathematical mindsets: Unleashing students’ potential through creative math, inspiring messages and innovative teaching. Jossey-Bass.

Brew, A. (2013). Understanding the scope of undergraduate research: A framework for curricular and pedagogical decision-making. Higher Education, 66(5), 603–618. https://doi.org/10.1007/s10734-013-9624-x

Carlone, H. B., & Johnson, A. (2007). Understanding the science experiences of successful women of color: Science identity as an analytic lens. Journal of Research in Science Teaching, 44(8), 1187–1218. https://doi.org/10.1002/tea.20237

Collazos Guzmán, G. (2025). Marco teórico-relacional para el análisis de identidad digital STEM. Revista Científica y Académica, 5(2), 2285–2303. https://doi.org/10.61384/r.c.a..v5i2.1276

Emanuel, K. (2005). Increasing destructiveness of tropical cyclones over the past 30 years. Nature, 436(7051), 686–688. https://doi.org/10.1038/nature03906

Fortus, D., Krajcik, J., Dershimer, R. C., Marx, R. W., & Mamlok-Naaman, R. (2016). Design-based science and real-world problem-solving. International Journal of Science Education, 27(7), 855–879. https://doi.org/10.1080/09500690500038165

Gee, J. P. (2000). Identity as an analytic lens for research in education. Review of Research in Education, 25, 99–125. https://doi.org/10.2307/1167322

Hazari, Z., Sonnert, G., Sadler, P. M., & Shanahan, M. C. (2010). Connecting high school physics experiences, outcome expectations, physics identity, and physics career choice. Journal of Research in Science Teaching, 47(8), 978–1003. https://doi.org/10.1002/tea.20363

Honey, M., Pearson, G., & Schweingruber, H. (Eds.). (2014). STEM integration in K–12 education: Status, prospects, and an agenda for research. National Academies Press. https://doi.org/10.17226/18612

Huang, B., Liu, C., Banzon, V. F., Freeman, E., Graham, G., Hankins, W., … Smith, T. M. (2021). Improvements of the daily optimum interpolation sea surface temperature (OISST) version 2.1. Journal of Climate, 34(8), 2923–2939. https://doi.org/10.1175/JCLI-D-20-0166.1

International Baccalaureate Organization. (2021). Mathematics: Analysis and approaches guide. International Baccalaureate.

Knutson, T. R., Camargo, S. J., Chan, J. C. L., Emanuel, K., Ho, C.-H., Kossin, J., … Walsh, K. (2020). Tropical cyclones and climate change assessment: Part II. Bulletin of the American Meteorological Society, 101(3), E303–E322. https://doi.org/10.1175/BAMS-D-18-0194.1

Konold, C., & Higgins, T. (2003). Reasoning about data. Educational Studies in Mathematics, 45(1–3), 5–32. https://doi.org/10.1023/A:1013838715874

Kossin, J. P., Emanuel, K. A., & Vecchi, G. A. (2017). The poleward migration of the location of tropical cyclone maximum intensity. Nature, 509(7500), 349–352. https://doi.org/10.1038/nature13278

Landsea, C. W., & Franklin, J. L. (2013). Atlantic hurricane database uncertainty and presentation of a new database format. Monthly Weather Review, 141(10), 3576–3592. https://doi.org/10.1175/MWR-D-12-00254.1

Lehrer, R., & Schauble, L. (2015). Learning progressions: The whole world and the classroom. Science, 347(6218), 1269–1271. https://doi.org/10.1126/science.aaa5601

Nasir, N. S., & Hand, V. (2008). From the court to the classroom: Opportunities for engagement, learning, and identity in basketball and classroom mathematics. Journal of the Learning Sciences, 17(2), 143–179. https://doi.org/10.1080/10508400801986108

National Academies of Sciences, Engineering, and Medicine. (2018). How people learn II: Learners, contexts, and cultures. National Academies Press. https://doi.org/10.17226/24783

National Research Council. (2012). A framework for K–12 science education: Practices, crosscutting concepts, and core ideas. National Academies Press. https://doi.org/10.17226/13165

Reynolds, R. W., Smith, T. M., Liu, C., Chelton, D. B., Casey, K. S., & Schlax, M. G. (2007). Daily high-resolution blended analyses for sea surface temperature. Journal of Climate, 20(22), 5473–5496. https://doi.org/10.1175/2007JCLI1824.1

Schoenfeld, A. H. (2014). What makes for powerful classrooms, and how can we support teachers in creating them? Educational Researcher, 43(8), 404–412. https://doi.org/10.3102/0013189X14554450

Talley, L. D., Pickard, G. L., Emery, W. J., & Swift, J. H. (2011). Descriptive physical oceanography: An introduction (6th ed.). Academic Press.

Trenberth, K. E., & Fasullo, J. T. (2007). Water and energy budgets of hurricanes and implications for climate change. Journal of Geophysical Research: Atmospheres, 112(D23). https://doi.org/10.1029/2006JD008303

Webster, P. J., Holland, G. J., Curry, J. A., & Chang, H.-R. (2005). Changes in tropical cyclone number, duration, and intensity in a warming environment. Science, 309(5742), 1844–1846. https://doi.org/10.1126/science.1116448

Wilkerson, M. H., & Polman, J. L. (2016). Situating data science: Exploring how relationships between data and phenomena are recontextualized during data analysis activities. Journal of Research in Science Teaching, 53(3), 317–347. https://doi.org/10.1002/tea.21301

Wilkinson, M. D., Dumontier, M., Aalbersberg, I. J., Appleton, G., Axton, M., Baak, A., … Mons, B. (2016). The FAIR guiding principles for scientific data management and stewardship. Scientific Data, 3, Article 160018. https://doi.org/10.1038/sdata.2016.18

Wilks, D. S. (2019). Statistical methods in the atmospheric sciences (4th ed.). Academic Press.

Downloads

Published

06-11-2026

How to Cite

Collazos Guzmán, G., & Collazos Roa, M. (2026). From Inquiry to STEM Identity: A Student-Led IB Mathematics Case Study Using Open Climate Data. International Journal of Research in STEM Education, 8(2), 84–95. https://doi.org/10.33830/ijrse.v8i2.14479

Issue

Section

Research Articles