Using Contents from Machine Learning and Real Engineering Applications to Improve the Quality of Math Teaching in Universities

Jing Wang; Qi Xi

doi:10.2991/978-94-6463-560-7_3

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Using Contents from Machine Learning and Real Engineering Applications to Improve the Quality of Math Teaching in Universities

Authors

Jing Wang¹, Qi Xi¹^{, *}

¹School of Data Science & Engineering, South China Normal University, Shanwei, Guangdong, 516625, China

^*Corresponding author. Email: 20219094@m.scnu.edu.cn

Corresponding Author

Qi Xi

Available Online 1 November 2024.

DOI: 10.2991/978-94-6463-560-7_3 How to use a DOI?
Keywords: machine learning; artificial neural networks; real engineering applications; undergraduate education; math teaching
Abstract: Mathematics is very important for undergraduate students majoring in computer science. However, current undergraduate students from computer science have not developed strong interests and enthusiasms in learning mathematics. Therefore, in the higher education of cultivating computer talents, the content of mathematics courses should be improved to stimulate students’ interests and enthusiasms for learning. In the field of computer science, there are many topics that students are very interested in, for instance, popular technologies such as artificial intelligence, machine learning, artificial neural networks, unmanned aerial vehicle, etc. These technologies contain a large amount of mathematical knowledge and can be used as teaching materials for university mathematics courses. In addition, university teachers can also introduce practical engineering cases into university mathematics classrooms based on their research projects, which can make mathematics classes practical and interesting, and improve student learning effect.
Copyright: © 2024 The Author(s)
Open Access: Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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Volume Title: Proceedings of the 2024 4th International Conference on Internet Technology and Educational Informatization (ITEI 2024)
Series: Atlantis Highlights in Social Sciences, Education and Humanities
Publication Date: 1 November 2024
ISBN: 978-94-6463-560-7
ISSN: 2667-128X
DOI: 10.2991/978-94-6463-560-7_3 How to use a DOI?
Open Access: Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

Cite this article

ris enw bib

TY  - CONF
AU  - Jing Wang
AU  - Qi Xi
PY  - 2024
DA  - 2024/11/01
TI  - Using Contents from Machine Learning and Real Engineering Applications to Improve the Quality of Math Teaching in Universities
BT  - Proceedings of the 2024 4th International Conference on Internet Technology and Educational Informatization (ITEI 2024)
PB  - Atlantis Press
SP  - 10
EP  - 19
SN  - 2667-128X
UR  - https://doi.org/10.2991/978-94-6463-560-7_3
DO  - 10.2991/978-94-6463-560-7_3
ID  - Wang2024
ER  -

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