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<p>Based on the objectives of innovation and entrepreneurship education for college students, this paper constructs the evaluation index system, utilizes the improved Apriori algorithm to mine the association rules between the indicators, and reflects the relevant influence between the evaluation indicators through the association rules with higher support and confidence. Meanwhile, based on the big data platform, an evaluation system for innovation and entrepreneurship education for college students is established, and the level of innovation and entrepreneurship education for students is evaluated. The analysis of the correlation rules between the evaluation indicators found that the support degree of the rule that students with stronger independent ability are better at grasping innovation and entrepreneurship opportunities is 29.97%, which provides a reference for the teachers’ teaching objectives and content development. The results of the empirical analysis of the evaluation system of innovation and entrepreneurship education show that the modular application of the evaluation system created in this paper has a positive effect, and there is a highly significant difference in the evaluation of the “Z13 personal willingness” index before and after the application (P=0.000&lt;0.001). The correlation rule of evaluation indexes in this study lays a theoretical foundation for the effective development of innovation and entrepreneurship teaching, and the modularized application of the innovation and entrepreneurship evaluation system constructed in this paper can improve the level of innovation and entrepreneurship education in colleges and universities to a certain extent.</p>
</abstract>

Based on the objectives of innovation and entrepreneurship education for college students, this paper constructs the evaluation index system, utilizes the improved Apriori algorithm to mine the association rules between the indicators, and reflects the relevant influence between the evaluation indicators through the association rules with higher support and confidence. Meanwhile, based on the big data platform, an evaluation system for innovation and entrepreneurship education for college students is established, and the level of innovation and entrepreneurship education for students is evaluated. The analysis of the correlation rules between the evaluation indicators found that the support degree of the rule that students with stronger independent ability are better at grasping innovation and entrepreneurship opportunities is 29.97%, which provides a reference for the teachers’ teaching objectives and content development. The results of the empirical analysis of the evaluation system of innovation and entrepreneurship education show that the modular application of the evaluation system created in this paper has a positive effect, and there is a highly significant difference in the evaluation of the “Z13 personal willingness” index before and after the application (P=0.000<0.001). The correlation rule of evaluation indexes in this study lays a theoretical foundation for the effective development of innovation and entrepreneurship teaching, and the modularized application of the innovation and entrepreneurship evaluation system constructed in this paper can improve the level of innovation and entrepreneurship education in colleges and universities to a certain extent.

Modular Application of Evaluation System for Innovation and Entrepreneurship Education of College Students--Based on Big Data Platform Analysis

Applied Mathematics and Nonlinear Sciences

This work is licensed under the Creative Commons Attribution 4.0 International License.

Based on the objectives of innovation and entrepreneurship education for college students, this paper constructs the evaluation index system, utilizes the...

Modular Application of Evaluation System for Innovation and Entrepreneurship Education of College Students--Based on Big Data Platform Analysis

Online veröffentlicht: 07. Juni 2024

Seitenbereich: -

Eingereicht: 07. März 2024

Akzeptiert: 10. Mai 2024

DOI: https://doi.org/10.2478/amns-2024-1407

Schlüsselwörter
Evaluation index system, Big data platform, Apriori algorithm, Association rules, Innovation and entrepreneurship education

© 2024 Zhen Wang, published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 International License.

Modular Application of Evaluation System for Innovation and Entrepreneurship Education of College Students--Based on Big Data Platform Analysis

Online veröffentlicht: 07. Juni 2024

Seitenbereich: -

Eingereicht: 07. März 2024

Akzeptiert: 10. Mai 2024

DOI: https://doi.org/10.2478/amns-2024-1407

SchlüsselwörterEvaluation index system, Big data platform, Apriori algorithm, Association rules, Innovation and entrepreneurship education

© 2024 Zhen Wang, published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 International License.

Schlüsselwörter
Evaluation index system, Big data platform, Apriori algorithm, Association rules, Innovation and entrepreneurship education