Proceedings of the 2020 International Conference on Social Science, Economics and Education Research (SSEER 2020)

Correlation Analysis on the Courses of Civil Engineering Based on Association Rules Mining

Authors
Chuanteng Huang, Shuang Pu
Corresponding Author
Chuanteng Huang
Available Online 1 August 2020.
DOI
10.2991/assehr.k.200801.006How to use a DOI?
Keywords
association rules, Apriori, Civil Engineering, course, correlation analysis
Abstract

The talent training program is the overall design and planning of higher professional education, and has a decisive role in ensuring the quality of talent training. The training objectives, graduation requirements, curriculum system, syllabus and evaluation system contained in the talent training program have a strict logical relationship. The curriculum setting and course structure are the key points for the implementation of the talent training program. Professional education courses in Civil Engineering include mathematics curriculum group, mechanics curriculum group and design curriculum group. In this paper, seven representative courses in the three curriculum groups are selected. The final academic records of 249 students in three grades are used as research objects. By using the association rule mining algorithm — Apriori, this paper discusses the implementation process of data mining technology and clarifies the degree of relationship among the courses. The analysis results can provide important references for the curriculum system setting and structure adjustment, targeting the key and difficult curriculum, teaching reform and academic learning monitoring and forecasting.

Copyright
© 2020, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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Volume Title
Proceedings of the 2020 International Conference on Social Science, Economics and Education Research (SSEER 2020)
Series
Advances in Social Science, Education and Humanities Research
Publication Date
1 August 2020
ISBN
10.2991/assehr.k.200801.006
ISSN
2352-5398
DOI
10.2991/assehr.k.200801.006How to use a DOI?
Copyright
© 2020, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

Cite this article

TY  - CONF
AU  - Chuanteng Huang
AU  - Shuang Pu
PY  - 2020
DA  - 2020/08/01
TI  - Correlation Analysis on the Courses of Civil Engineering Based on Association Rules Mining
BT  - Proceedings of the 2020 International Conference on Social Science, Economics and Education Research (SSEER 2020)
PB  - Atlantis Press
SP  - 28
EP  - 32
SN  - 2352-5398
UR  - https://doi.org/10.2991/assehr.k.200801.006
DO  - 10.2991/assehr.k.200801.006
ID  - Huang2020
ER  -