Proceedings of the 2023 4th International Conference on Artificial Intelligence and Education (ICAIE 2023)

Design and Application of Entrepreneurship Education Platform in Colleges and Universities Under the Background of Big Data

Authors
Fanmin Kong1, *
1Department of Economic Management, Wuhai Vocational and Technical College, Wuhai, 016000, Inner Mongolia, China
*Corresponding author. Email: 78065791@qq.com
Corresponding Author
Fanmin Kong
Available Online 22 September 2023.
DOI
10.2991/978-94-6463-242-2_58How to use a DOI?
Keywords
Big data; Entrepreneurship education; User portrait; Data mining; Software application program
Abstract

With the gradual deepening of education informatization construction, colleges and universities should adhere to the development concept of “data-driven entrepreneurship education”, promote entrepreneurship education to achieve deep-seated changes in the underlying logic, development model and management mechanism, and build a teaching system of entrepreneurship education that meets social needs and national development strategies. In this regard, based on the problems existing in the current mode of entrepreneurship education in colleges and universities, such as lack of educational resources, lack of pertinence and lack of evaluation, this paper puts forward a set of construction scheme of entrepreneurship education platform in colleges and universities based on big data technology, and creates a new ecology of entrepreneurship education teaching in colleges and universities. The whole platform is B/S architecture, with Javaweb technology as the core to complete the design and development of front-end functional service interface and back-end server, and combined with Hadoop, the basic framework of big data, a comprehensive application program with online learning, personalized analysis, assessment and other functions is formed. Practice has proved that the system can not only meet the needs of students’ teaching application, but also create students’ user portraits to realize personalized analysis with the help of data mining models such as K-means, Pearson and FP-growth, which improves the pertinence and effectiveness of entrepreneurship education in colleges and universities and provides new ideas for the development of entrepreneurship education in the new era.

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 2023 4th International Conference on Artificial Intelligence and Education (ICAIE 2023)
Series
Atlantis Highlights in Computer Sciences
Publication Date
22 September 2023
ISBN
10.2991/978-94-6463-242-2_58
ISSN
2589-4900
DOI
10.2991/978-94-6463-242-2_58How to use a DOI?
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.

Cite this article

TY  - CONF
AU  - Fanmin Kong
PY  - 2023
DA  - 2023/09/22
TI  - Design and Application of Entrepreneurship Education Platform in Colleges and Universities Under the Background of Big Data
BT  - Proceedings of the 2023 4th International Conference on Artificial Intelligence and Education (ICAIE 2023)
PB  - Atlantis Press
SP  - 466
EP  - 473
SN  - 2589-4900
UR  - https://doi.org/10.2991/978-94-6463-242-2_58
DO  - 10.2991/978-94-6463-242-2_58
ID  - Kong2023
ER  -