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<p>Many applied undergraduate institutions in China have recognized that the integration of industry and education is essential for the advancement and innovation of educational practices. To expedite the development of this integration within vocational education, this paper introduces the Genetic Automatic Coding Assisted Integration of Industry and Education Teaching Mode. This approach begins with the cultivation of vocational education talents in higher education institutions, offering a comprehensive analysis of the industry-education fusion mode and delineating its implementation strategies and guiding principles. Employing the principles of automatic coding, the curriculum content of this integration mode is represented through genetic algorithm gene coding. The model for genetic automatic coding in industry-education integration for vocational education is established by assessing the compatibility of the integration mode and incorporating mechanisms for conflict detection and mutation crossover. The empirical analysis reveals that in genetic automatic coding, the eigenvalues stabilize after approximately 200 iterations. This suggests that this method enhances scheduling effectiveness in the vocational education-oriented industry-education fusion mode. Moreover, the results indicate a significant improvement in educational outcomes: students in the experimental group, where this model was applied, achieved an average assessment score of 88.38, compared to 78.47 in the control group. This substantial improvement confirms that the industry-education fusion mode, underpinned by genetic automatic coding, not only enhances the quality of education but also boosts students’ mastery of professional courses.</p>
</abstract>

Many applied undergraduate institutions in China have recognized that the integration of industry and education is essential for the advancement and innovation of educational practices. To expedite the development of this integration within vocational education, this paper introduces the Genetic Automatic Coding Assisted Integration of Industry and Education Teaching Mode. This approach begins with the cultivation of vocational education talents in higher education institutions, offering a comprehensive analysis of the industry-education fusion mode and delineating its implementation strategies and guiding principles. Employing the principles of automatic coding, the curriculum content of this integration mode is represented through genetic algorithm gene coding. The model for genetic automatic coding in industry-education integration for vocational education is established by assessing the compatibility of the integration mode and incorporating mechanisms for conflict detection and mutation crossover. The empirical analysis reveals that in genetic automatic coding, the eigenvalues stabilize after approximately 200 iterations. This suggests that this method enhances scheduling effectiveness in the vocational education-oriented industry-education fusion mode. Moreover, the results indicate a significant improvement in educational outcomes: students in the experimental group, where this model was applied, achieved an average assessment score of 88.38, compared to 78.47 in the control group. This substantial improvement confirms that the industry-education fusion mode, underpinned by genetic automatic coding, not only enhances the quality of education but also boosts students’ mastery of professional courses.

Research on Industry-Education Integration Model of Vocational Education Applying Automatic Coding

Applied Mathematics and Nonlinear Sciences

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

Many applied undergraduate institutions in China have recognized that the integration of industry and education is essential for the advancement and innovation...

Research on Industry-Education Integration Model of Vocational Education Applying Automatic Coding

Pubblicato online: 07 giu 2024

Pagine: -

Ricevuto: 14 mar 2024

Accettato: 13 mag 2024

DOI: https://doi.org/10.2478/amns-2024-1398

Parole chiave
Genetic algorithm, Automatic coding, Adaptability, Industry-teaching integration model

© 2024 Shuguang Pei, published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

Research on Industry-Education Integration Model of Vocational Education Applying Automatic Coding

Pubblicato online: 07 giu 2024

Pagine: -

Ricevuto: 14 mar 2024

Accettato: 13 mag 2024

DOI: https://doi.org/10.2478/amns-2024-1398

Parole chiaveGenetic algorithm, Automatic coding, Adaptability, Industry-teaching integration model

© 2024 Shuguang Pei, published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

Parole chiave
Genetic algorithm, Automatic coding, Adaptability, Industry-teaching integration model