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<p>Exploring the application of new media communication technology in vocational education teaching is better for improving the skill level of vocational school students. In this paper, starting from the KNN algorithm in the context of big data, the basic principle and process of the algorithm are explained, and the principle and model of the wolf pack optimization algorithm are introduced. The parameters of the KNN algorithm are optimized using the wolf pack search algorithm, and the definition of the objective function, initialization and solution of the optimal K value are given, which leads to the WPOA-KNN analysis model. The new media communication technology is analyzed, including teaching media, new media teaching technology and the advantages of new media communication technology applied to vocational education teaching. The WPOA-KNN analysis model was used to analyze and demonstrate the teaching of new media technology for vocational education in a higher education institution. From the satisfaction evaluation, the percentage of those who said they liked it was 76.06%, and the percentage of those who disliked it was only 9.09%. In terms of students’ learning behavior, the overall percentage of those who rated above C grade was 92.37%. This shows that using new media communication technology for vocational education teaching can enhance students’ learning enthusiasm, make them have a more exquisite technical level, and meet the diversified talent needs of employing enterprises.</p>
</abstract>

Exploring the application of new media communication technology in vocational education teaching is better for improving the skill level of vocational school students. In this paper, starting from the KNN algorithm in the context of big data, the basic principle and process of the algorithm are explained, and the principle and model of the wolf pack optimization algorithm are introduced. The parameters of the KNN algorithm are optimized using the wolf pack search algorithm, and the definition of the objective function, initialization and solution of the optimal K value are given, which leads to the WPOA-KNN analysis model. The new media communication technology is analyzed, including teaching media, new media teaching technology and the advantages of new media communication technology applied to vocational education teaching. The WPOA-KNN analysis model was used to analyze and demonstrate the teaching of new media technology for vocational education in a higher education institution. From the satisfaction evaluation, the percentage of those who said they liked it was 76.06%, and the percentage of those who disliked it was only 9.09%. In terms of students’ learning behavior, the overall percentage of those who rated above C grade was 92.37%. This shows that using new media communication technology for vocational education teaching can enhance students’ learning enthusiasm, make them have a more exquisite technical level, and meet the diversified talent needs of employing enterprises.

The application of new media communication technology in vocational education teaching under the background of big data

Applied Mathematics and Nonlinear Sciences

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

Exploring the application of new media communication technology in vocational education teaching is better for improving the skill level of vocational school...

The application of new media communication technology in vocational education teaching under the background of big data

Publicado en línea: 06 sept 2023

Páginas: -

Recibido: 24 sept 2022

Aceptado: 17 mar 2022

DOI: https://doi.org/10.2478/amns.2023.2.00295

Palabras clave
KNN algorithm, Wolf Pack Optimization algorithm, WPOA-KNN model, New media technology, Vocational education

© 2023 Xueying Wang, published by Sciendo

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

The application of new media communication technology in vocational education teaching under the background of big data

Publicado en línea: 06 sept 2023

Páginas: -

Recibido: 24 sept 2022

Aceptado: 17 mar 2022

DOI: https://doi.org/10.2478/amns.2023.2.00295

Palabras claveKNN algorithm, Wolf Pack Optimization algorithm, WPOA-KNN model, New media technology, Vocational education

© 2023 Xueying Wang, published by Sciendo

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

Palabras clave
KNN algorithm, Wolf Pack Optimization algorithm, WPOA-KNN model, New media technology, Vocational education