Pedagogical transformation in the teaching of mathematics and physics in higher education: integration, challenges and opportunities of scientific computing
DOI:
https://doi.org/10.63688/czrqev25Keywords:
scientific computing, mathematics teaching, physics teaching, higher education, pedagogical transformationAbstract
Higher education is undergoing a process of renewal that demands moving beyond traditional practices used in teaching mathematics and physics. In this context, scientific computing offers resources such as simulations, programming languages, numerical methods, data modeling and visualization, which facilitate the understanding and application of complex content. The objective of this research was to analyze the integration of scientific computing into university teaching of both disciplines, considering its applications, challenges, and opportunities, as well as its contribution to pedagogical transformation and the development of scientific, digital, and cognitive competencies. Methodologically, a systematic literature review was conducted following the guidelines of the 2020 PRISMA statement, which allowed for the rigorous identification, selection, organization, and synthesis of the available evidence. The results showed that these tools brought theory closer to concrete situations, facilitated the understanding of abstract concepts, and promoted more active student participation. It was concluded that scientific computing strengthened logical reasoning, analysis and problem solving, favoring a more practical, dynamic teaching in line with the current needs of university education.
References
Amhag, L., Hellström, L., & Stigmar, M. (2019). Teacher educators’ use of digital tools and needs for digital competence in higher education. Journal of Digital Learning in Teacher Education, 35(4), 203–220. https://doi.org/10.1080/21532974.2019.1646169
Basilotta-Gómez-Pablos, V., Matarranz, M., Casado-Aranda, L. A., & Otto, A. (2022). Teachers’ digital competencies in higher education: A systematic literature review. International Journal of Educational Technology in Higher Education, 19, Article 8. https://doi.org/10.1186/s41239-021-00312-8
Bond, M., Marín, V. I., Dolch, C., Bedenlier, S., & Zawacki-Richter, O. (2018). Digital transformation in German higher education: Student and teacher perceptions and usage of digital media. International Journal of Educational Technology in Higher Education, 15, Article 48. https://doi.org/10.1186/s41239-018-0130-1
Falloon, G. (2020). From digital literacy to digital competence: The teacher digital competency (TDC) framework. Educational Technology Research and Development, 68, 2449–2472. https://doi.org/10.1007/s11423-020-09767-4
Faulconer, E. K., & Gruss, A. B. (2018). A review to weigh the pros and cons of online, remote, and distance science laboratory experiences. The International Review of Research in Open and Distributed Learning, 19(2), 155–168. https://doi.org/10.19173/irrodl.v19i2.3386
Gallagher, G., Vemuri, G., Maric, D., & Gavrin, A. (2026). Evaluating a department-wide initiative incorporating computational methods into the undergraduate physics curriculum. Physical Review Physics Education Research, 22(1), Article 010138. https://doi.org/10.1103/2zmq-2t62
Gouvea, J. S. (2023). Integrating computation into science education. CBE—Life Sciences Education, 22(3), Article fe2. https://doi.org/10.1187/cbe.23-05-0093
Hamerski, P. C., McPadden, D., Caballero, M. D., & Irving, P. W. (2022). Students’ perspectives on computational challenges in physics class. Physical Review Physics Education Research, 18(2), Article 020109. https://doi.org/10.1103/PhysRevPhysEducRes.18.020109
Henderson, M., Selwyn, N., & Aston, R. (2017). What works and why? Student perceptions of “useful” digital technology in university teaching and learning. Studies in Higher Education, 42(8), 1567–1579. https://doi.org/10.1080/03075079.2015.1007946
Hillmayr, D., Ziernwald, L., Reinhold, F., Hofer, S. I., & Reiss, K. M. (2020). The potential of digital tools to enhance mathematics and science learning in secondary schools: A context-specific meta-analysis. Computers & Education, 153, Article 103897. https://doi.org/10.1016/j.compedu.2020.103897
Hsu, T. C., Chang, S. C., & Hung, Y. T. (2018). How to learn and how to teach computational thinking: Suggestions based on a review of the literature. Computers & Education, 126, 296–310. https://doi.org/10.1016/j.compedu.2018.07.004
Koerfer, E., Polverini, G., Elmgren, M., Eriksson, L.-H., Freyhult, L., Herbert, R. B., Ho, F. M., Solders, A., & Eckerdal, A. (2025). Teachers’ conceptions of the role of mathematics in STEM higher education. Disciplinary and Interdisciplinary Science Education Research, 7, Article 15. https://doi.org/10.1186/s43031-025-00135-x
Lyon, J. A., & Magana, A. J. (2020). Computational thinking in higher education: A review of the literature. Computer Applications in Engineering Education, 28(5), 1174–1189. https://doi.org/10.1002/cae.22295
Maass, K., Geiger, V., Ariza, M. R., & Goos, M. (2019). The role of mathematics in interdisciplinary STEM education. ZDM–Mathematics Education, 51, 869–884. https://doi.org/10.1007/s11858-019-01100-5
Makransky, G., Terkildsen, T. S., & Mayer, R. E. (2019). Adding immersive virtual reality to a science lab simulation causes more presence but less learning. Learning and Instruction, 60, 225–236. https://doi.org/10.1016/j.learninstruc.2017.12.007
Mashood, K. K., Khosla, K., Prasad, A., V, S., CH, M. A., Jose, C., & Chandrasekharan, S. (2022). Participatory approach to introduce computational modeling at the undergraduate level, extending existing curricula and practices: Augmenting derivations. Physical Review Physics Education Research, 18(2), Article 020136. https://doi.org/10.1103/PhysRevPhysEducRes.18.020136
National Academies of Sciences, Engineering, and Medicine. (2018). Data science for undergraduates: Opportunities and options. The National Academies Press. https://doi.org/10.17226/25104
Odden, T. O. B., Lockwood, E., & Caballero, M. D. (2019). Physics computational literacy: An exploratory case study using computational essays. Physical Review Physics Education Research, 15(2), Article 020152. https://doi.org/10.1103/PhysRevPhysEducRes.15.020152
Ogegbo, A. A., & Ramnarain, U. (2022). A systematic review of computational thinking in science classrooms. Studies in Science Education, 58(2), 203–230. https://doi.org/10.1080/03057267.2021.1963580
Palmgren, E., Kokkonen, T., & Bruun, J. (2025). Roles of mathematics in physics education: A systematic review. Physical Review Physics Education Research, 21(2), Article 020602. https://doi.org/10.1103/wwww-gwp8
Palmgren, E., & Rasa, T. (2024). Modelling roles of mathematics in physics: Perspectives for physics education. Science & Education, 33, 365–382. https://doi.org/10.1007/s11191-022-00393-5
Potkonjak, V., Gardner, M., Callaghan, V., Mattila, P., Guetl, C., Petrović, V. M., & Jovanović, K. (2016). Virtual laboratories for education in science, technology, and engineering: A review. Computers & Education, 95, 309–327. https://doi.org/10.1016/j.compedu.2016.02.002
Redecker, C. (2017). European framework for the digital competence of educators: DigCompEdu (Y. Punie, Ed.). Publications Office of the European Union. https://doi.org/10.2760/159770
Shute, V. J., Sun, C., & Asbell-Clarke, J. (2017). Demystifying computational thinking. Educational Research Review, 22, 142–158. https://doi.org/10.1016/j.edurev.2017.09.003
Tang, X., Yin, Y., Lin, Q., Hadad, R., & Zhai, X. (2020). Assessing computational thinking: A systematic review of empirical studies. Computers & Education, 148, Article 103798. https://doi.org/10.1016/j.compedu.2019.103798
Weintrop, D., Beheshti, E., Horn, M. S., Orton, K., Jona, K., Trouille, L., & Wilensky, U. (2016). Defining computational thinking for mathematics and science classrooms. Journal of Science Education and Technology, 25(1), 127–147. https://doi.org/10.1007/s10956-015-9581-5
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