Curriculum Reform and Teaching Methodology for Project-Driven Machine Learning Course in the Context of New Engineering
DOI: 10.23977/curtm.2024.070612 | Downloads: 25 | Views: 831
Author(s)
Na Lu 1, Xiaomin Zhang 1
Affiliation(s)
1 Wuhan Technology and Business University, Wuhan, China
Corresponding Author
Na LuABSTRACT
With the rise of new engineering education and the rapid development of artificial intelligence technology, the traditional machine learning course teaching mode can no longer meet the current educational needs. On the basis of analyzing the current teaching situation, this article proposes a project-based machine learning course teaching reform plan, aiming to cultivate students' practical ability and innovative thinking to meet the demand for engineering and technical talents in the new era.
KEYWORDS
New Engineering; Machine learning; Project drivenCITE THIS PAPER
Na Lu, Xiaomin Zhang, Curriculum Reform and Teaching Methodology for Project-Driven Machine Learning Course in the Context of New Engineering. Curriculum and Teaching Methodology (2024) Vol. 7: 77-81. DOI: http://dx.doi.org/10.23977/curtm.2024.070612.
REFERENCES
[1] Zhang B, Zhang J, Zhang C, et al. Curriculum Reform and Exploration Under the Background of Artificial Intelligence and New Engineering[J]. Computer Education, 2021. DOI:10.1007/978-981-16-6502-8_22.
[2] Liu S, W J. Ice and snow talent training based on construction and analysis of artificial intelligence education informatization teaching model [J]. Journal of Intelligent & Fuzzy Systems, 2021, 40(2).
[3] Li D, Liu S. Problems and Countermeasures of Local Governments in Promoting Innovation and Entrepreneurship Education for College Students under the New Development Concept [J]. Sci-tech Innovation and Productivity, 2022(04):7-10.
[4] Li R. Analysis on the Innovation Research of the New Era College Student Entrepreneurship Team Participating in Innovation and Entrepreneurship Training [J]. Auto Time, 2021(01):24-25.
[5] Sima Sabahi, Mahour Mellat Parast. The impact of entrepreneurship orientation on project performance: A machine learning approach [J]. International Journal of Production Economics, 2020: 1-14.
[6] Ahmad K, Iqbal W, El-Hassan A, et al. Data-driven artificial intelligence in education: A comprehensive review [J]. IEEE Transactions on Learning Technologies, 2023.
[7] Lee D, Huh Y, Lin C-Y, et al. Differences in personalized learning practice and technology use in high-and low-performing learner-centered schools in the United States[J]. Educational Technology Research and Development, 2021, 69:1221-1245.
[8] Luan H, Tsai C-C. A review of using machine learning approaches for precision education[J]. Educational Technology & Society, 2021, 24(1):250-266.
[9] Majjate H, Bellarhmouch Y, Jeghal A, et al. AI-Powered Academic Guidance and Counseling System Based on Student Profile and Interests [J]. Applied System Innovation, 2023, 7(1):6.
Downloads: | 36694 |
---|---|
Visits: | 1492659 |