Optimization of Ecological Mode of College Students’ Innovation and Entrepreneurship Education Based on a Big Data Analysis Model
However, the number of college students enrolling in our country has only begun to increase on a large scale in the 21st century. As educational big data gets more and more attention, it has its own distinct characteristics in the field of education and at the same time consolidates the overall tren...
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Format: | Article |
Language: | English |
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Wiley
2022-01-01
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Series: | Journal of Function Spaces |
Online Access: | http://dx.doi.org/10.1155/2022/4357354 |
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author | Miao Yu Yanju Lu Hongliang Wang |
author_facet | Miao Yu Yanju Lu Hongliang Wang |
author_sort | Miao Yu |
collection | DOAJ |
description | However, the number of college students enrolling in our country has only begun to increase on a large scale in the 21st century. As educational big data gets more and more attention, it has its own distinct characteristics in the field of education and at the same time consolidates the overall trend of big data development. The countermeasure analysis of innovation and entrepreneurship education under the reform of the education supply side has become a subject to be explored in an all-round way. This paper is mainly aimed at the importance of a big data analysis model to college students, explores the current development status of innovation and entrepreneurship education for college students, finds some problems in the application of big data, and improves the existing problems based on the purpose. |
format | Article |
id | doaj-art-7db5da13fd604265aa8f861438c05160 |
institution | Kabale University |
issn | 2314-8888 |
language | English |
publishDate | 2022-01-01 |
publisher | Wiley |
record_format | Article |
series | Journal of Function Spaces |
spelling | doaj-art-7db5da13fd604265aa8f861438c051602025-02-03T05:50:38ZengWileyJournal of Function Spaces2314-88882022-01-01202210.1155/2022/4357354Optimization of Ecological Mode of College Students’ Innovation and Entrepreneurship Education Based on a Big Data Analysis ModelMiao Yu0Yanju Lu1Hongliang Wang2College of Teacher EducationCollege of TourismCollege of Artificial IntelligenceHowever, the number of college students enrolling in our country has only begun to increase on a large scale in the 21st century. As educational big data gets more and more attention, it has its own distinct characteristics in the field of education and at the same time consolidates the overall trend of big data development. The countermeasure analysis of innovation and entrepreneurship education under the reform of the education supply side has become a subject to be explored in an all-round way. This paper is mainly aimed at the importance of a big data analysis model to college students, explores the current development status of innovation and entrepreneurship education for college students, finds some problems in the application of big data, and improves the existing problems based on the purpose.http://dx.doi.org/10.1155/2022/4357354 |
spellingShingle | Miao Yu Yanju Lu Hongliang Wang Optimization of Ecological Mode of College Students’ Innovation and Entrepreneurship Education Based on a Big Data Analysis Model Journal of Function Spaces |
title | Optimization of Ecological Mode of College Students’ Innovation and Entrepreneurship Education Based on a Big Data Analysis Model |
title_full | Optimization of Ecological Mode of College Students’ Innovation and Entrepreneurship Education Based on a Big Data Analysis Model |
title_fullStr | Optimization of Ecological Mode of College Students’ Innovation and Entrepreneurship Education Based on a Big Data Analysis Model |
title_full_unstemmed | Optimization of Ecological Mode of College Students’ Innovation and Entrepreneurship Education Based on a Big Data Analysis Model |
title_short | Optimization of Ecological Mode of College Students’ Innovation and Entrepreneurship Education Based on a Big Data Analysis Model |
title_sort | optimization of ecological mode of college students innovation and entrepreneurship education based on a big data analysis model |
url | http://dx.doi.org/10.1155/2022/4357354 |
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