Proceedings of the 2022 3rd International Conference on Modern Education and Information Management (ICMEIM 2022)

An Empirical Study of Students’ Entrepreneurship Analysis Based on Data Mining Technology

Authors
Hong Zhang1, *
1Lianyungang Vocational and Technical College, Marxism College, Jiangsu, China
*Corresponding author. Email: 13605137369@163.com
Corresponding Author
Hong Zhang
Available Online 27 December 2022.
DOI
10.2991/978-94-6463-044-2_16How to use a DOI?
Keywords
data mining; data analysis; entrepreneurial intention; Entrepreneurship education
Abstract

Entrepreneurship and innovation can effectively promote economic development and social progress, so it is widely concerned by all sectors of society. College students are important objects of entrepreneurship, but the success rate of entrepreneurship of college students is low at present. How to improve their entrepreneurial willingness is an important problem that needs to be solved urgently at present. The quantitative analysis and prediction of college graduates are rare, so the data mining technology is applied to the analysis of college entrepreneurship. This study analyzes the relationship between entrepreneurship education and entrepreneurial willingness of college students, and introduces variable family income to analyze its regulatory role in the relationship between the two. Firstly, a questionnaire survey was conducted on college students, and the data were sampled and preprocessed. Secondly, the regression analysis and adjustment analysis method of data mining are applied to explore the influencing factors of college students’ entrepreneurship. The results show that entrepreneurship education and its four dimensions have a positive impact on college students’ entrepreneurial willingness. Family income has a significant positive regulatory correlation with the four dimensions of the relationship between entrepreneurial willingness and entrepreneurial education.

Copyright
© 2022 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.

Download article (PDF)

Volume Title
Proceedings of the 2022 3rd International Conference on Modern Education and Information Management (ICMEIM 2022)
Series
Atlantis Highlights in Social Sciences, Education and Humanities
Publication Date
27 December 2022
ISBN
10.2991/978-94-6463-044-2_16
ISSN
2667-128X
DOI
10.2991/978-94-6463-044-2_16How to use a DOI?
Copyright
© 2022 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.

Cite this article

TY  - CONF
AU  - Hong Zhang
PY  - 2022
DA  - 2022/12/27
TI  - An Empirical Study of Students’ Entrepreneurship Analysis Based on Data Mining Technology
BT  - Proceedings of the 2022 3rd International Conference on Modern Education and Information Management (ICMEIM 2022)
PB  - Atlantis Press
SP  - 114
EP  - 134
SN  - 2667-128X
UR  - https://doi.org/10.2991/978-94-6463-044-2_16
DO  - 10.2991/978-94-6463-044-2_16
ID  - Zhang2022
ER  -