<abstract xmlns="http://www.w3.org/1999/xhtml">

<p>The development of modern digital technology provides a new way for the inheritance and innovation of the art of calligraphy. Digitization has dramatically enriched the dissemination carrier of calligraphy, enabling calligraphy education resources to be widely disseminated across physical boundaries, and realizing the personalization and intelligence of calligraphy education through the intelligent calligraphy cultural resources service model. The application of Digitization in higher calligraphy education analyzes the effective use of educational resources and promotes innovation in calligraphy education models through methods such as multi-layer linear regression. This study focuses on the digital dissemination of calligraphic educational resources, the intelligent calligraphic cultural resource service model, and the use of digital resources in higher calligraphic education. It has been found that teachers’ ability to apply digital resources is positively correlated with their academic qualifications. The educational background improves their application ability by 0.5 times. The study found a significant correlation between learning interaction activities and learning effectiveness by enhancing the random forest algorithm and analyzing students’ behavioral data. Higher calligraphy education should fully utilize big data technology to promote the digital transformation of educational resources and meet the needs of calligraphy education in the new era.</p>
</abstract>

The development of modern digital technology provides a new way for the inheritance and innovation of the art of calligraphy. Digitization has dramatically enriched the dissemination carrier of calligraphy, enabling calligraphy education resources to be widely disseminated across physical boundaries, and realizing the personalization and intelligence of calligraphy education through the intelligent calligraphy cultural resources service model. The application of Digitization in higher calligraphy education analyzes the effective use of educational resources and promotes innovation in calligraphy education models through methods such as multi-layer linear regression. This study focuses on the digital dissemination of calligraphic educational resources, the intelligent calligraphic cultural resource service model, and the use of digital resources in higher calligraphic education. It has been found that teachers’ ability to apply digital resources is positively correlated with their academic qualifications. The educational background improves their application ability by 0.5 times. The study found a significant correlation between learning interaction activities and learning effectiveness by enhancing the random forest algorithm and analyzing students’ behavioral data. Higher calligraphy education should fully utilize big data technology to promote the digital transformation of educational resources and meet the needs of calligraphy education in the new era.

Analysis of Chinese Higher Calligraphy Education in the Context of Big Data Era

Applied Mathematics and Nonlinear Sciences

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

{"article-title":"Analysis of Chinese Higher Calligraphy Education in the Context of Big Data Era"}

The development of modern digital technology provides a new way for the inheritance and innovation of the art of calligraphy. Digitization has dramatically...

Analysis of Chinese Higher Calligraphy Education in the Context of Big Data Era

Pubblicato online: 03 mag 2024

Pagine: -

Ricevuto: 25 mar 2024

Accettato: 14 apr 2024

DOI: https://doi.org/10.2478/amns-2024-0860

Parole chiave
Big data, Higher calligraphy education, Digital communication, Multilayer linear regression

© 2024 Weigang Fu, published by Sciendo

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

Analysis of Chinese Higher Calligraphy Education in the Context of Big Data Era

Pubblicato online: 03 mag 2024

Pagine: -

Ricevuto: 25 mar 2024

Accettato: 14 apr 2024

DOI: https://doi.org/10.2478/amns-2024-0860

Parole chiaveBig data, Higher calligraphy education, Digital communication, Multilayer linear regression

© 2024 Weigang Fu, published by Sciendo

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

Parole chiave
Big data, Higher calligraphy education, Digital communication, Multilayer linear regression