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

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.