Research on the Practice and Application of Modeling Ideas in Higher Vocational Mathematics Teaching

Shuaijing Yu

doi:10.54097/d8crqd74

Authors

Shuaijing Yu

DOI:

https://doi.org/10.54097/d8crqd74

Keywords:

Higher Vocational Mathematics; Teaching Reform; Mathematical Modeling Ideas.

Abstract

With the continuous deepening of educational reform, higher requirements have been put forward for higher vocational education. Higher vocational mathematics includes content such as advanced mathematics and linear algebra, which are highly abstract and difficult. Additionally, the teaching methods in higher vocational mathematics mainly focus on solving problems, which can easily lead students to mistakenly believe that the knowledge of vocational mathematics is only used to solve mathematical problems. As a result, students generally have a passive attitude towards learning subjects such as advanced mathematics and linear algebra. Vocational mathematics teaching should aim at cultivating students' core mathematical literacy and actively explore more scientific teaching models. Given the logical characteristics of mathematics, there are many commonalities with modeling ideas. Therefore, using this as a medium to help students develop modeling thinking can enhance the quality of vocational mathematics teaching. Thus, applying mathematical modeling ideas in vocational mathematics teaching plays a crucial role in promoting the reform of higher vocational mathematics teaching.

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References

[1] Chick, H. L., & Watson, J. M. (2003). Stochastics education: growth, goals, and gaps in a maturing discipline. Mathematics Education Research Journal, 15(3), 203–206.

[2] Doorman, L. M., & Gravemeijer, K. P. E. (2009). Emergent modeling: discrete graphs to support the understanding of change and velocity. ZDM--Mathematics Education, 41(1), 199–211.

[3] Ferrarello, D., & Mammana, M. F. (2018). Graph theory in primary, middle, and high school. In E. W. Hart & J. Sandefur (Eds.), Teaching and learning discrete mathematics worldwide: Curriculum and research (pp. 183–200). Springer.

[4] Cevikbas, M., Kaiser, G., & Schukajlow, S. (2021). A systematic literature review of the current discussion on mathematical modelling competencies: state-of-the-art developments in conceptualizing, measuring, and fostering. Educational Studies in Mathematics.

[5] Hankeln, C., & Greefrath, G. (2021). Mathematische Modellierungskompetenz fördern durch Lösungsplan oder Dynamische Geometrie-Software? Empirische Ergebnisse aus dem LIMo-Projekt. Journal für Mathematik-Didaktik, 42(2), 367–394.

[6] Castillo-Garsow, C., Johnson, H. L., & Moore, K. C. (2013). Chunky and smooth images of change. For the Learning of Mathematics, 33(3), 31–37.

[7] Greefrath, G., Hertleif, C., & Siller, H.-S. (2018). Mathematical modelling with digital tools—A quantitative study on mathematising with dynamic geometry software. ZDM—Mathematics Education, 50 (1–2), 233–244.

[8] Coenen, T., Hof, F., & Verhoef, N. (2018). Combinatorial reasoning to solve problems. In E. W. Hart & J. Sandefur (Eds.), Teaching and learning discrete mathematics worldwide: Curriculum and research (pp. 69-79). Springer.

[9] Beutelspacher, A., & Zschiegner, M.-A. (2014). Diskrete Mathematik für Einsteiger. Springer.

[10] Greefrath, G., & Siller, H.-S. (2017). Modelling and simulation with the help of digital tools. In G. Stillman, W. Blum, & G. Kaiser (Eds.), Mathematical modelling and applications (pp. 529–539). Springer.

[11] Caron, F. (2019). Approaches to investigating complex dynamical systems. In G. Stillman & J. P. Brown (Eds.), Lines of inquiry in mathematical modelling research in education (pp. 83–103).