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

<p>As teachers struggle with the usage of high-quality digital educational resources, small coverage and weak pertinence characteristics of traditional evaluation methods are the reasons for this. In this paper, three aspects including the connotation, operation mechanism and evaluation of ‘Artisan Workshop’ are analysed, and the classification factors are explored based on the collected educational data. By using these objective characteristics, the application ability of teachers to use digital educational resources is quantified, and the prediction model of sustainable development in ‘Artisan Workshop’ is constructed by adopting random forest regression, extreme gradient boost regression and light gradient boost regression models. According to the application of educational resources and teachers’ ability, this paper proposes an optimized scheme for the sustainable development of ‘Artisan Workshop’, which provides a reference for improving the quality of talent training in China.</p>
</abstract>

As teachers struggle with the usage of high-quality digital educational resources, small coverage and weak pertinence characteristics of traditional evaluation methods are the reasons for this. In this paper, three aspects including the connotation, operation mechanism and evaluation of ‘Artisan Workshop’ are analysed, and the classification factors are explored based on the collected educational data. By using these objective characteristics, the application ability of teachers to use digital educational resources is quantified, and the prediction model of sustainable development in ‘Artisan Workshop’ is constructed by adopting random forest regression, extreme gradient boost regression and light gradient boost regression models. According to the application of educational resources and teachers’ ability, this paper proposes an optimized scheme for the sustainable development of ‘Artisan Workshop’, which provides a reference for improving the quality of talent training in China.

Research on sustainable development mechanism of regional ‘Artisan Workshop’ under big data environment

Department of Artificial Intelligence and Big Data

Applied Mathematics and Nonlinear Sciences

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

As teachers struggle with the usage of high-quality digital educational resources, small coverage and weak pertinence characteristics of traditional evaluation...

Research on sustainable development mechanism of regional ‘Artisan Workshop’ under big data environment

Publié en ligne: 16 sept. 2022

Pages: 857 - 866

Reçu: 22 mars 2022

Accepté: 14 avr. 2022

DOI: https://doi.org/10.2478/amns.2022.1.00039

Mots clés
Artisan Workshop, regression model, sustainable development

© 2023 Jianxun Deng, published by Sciendo

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

Research on sustainable development mechanism of regional ‘Artisan Workshop’ under big data environment

Publié en ligne: 16 sept. 2022

Pages: 857 - 866

Reçu: 22 mars 2022

Accepté: 14 avr. 2022

DOI: https://doi.org/10.2478/amns.2022.1.00039

Mots clésArtisan Workshop, regression model, sustainable development

© 2023 Jianxun Deng, published by Sciendo

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

Mots clés
Artisan Workshop, regression model, sustainable development