Exploration of digital labor education path for college students under the impact of public health events based on big data analysis

As one of the cores of economic development in the new era, ecological civilization and public health construction are mainly reflected by environmental improvement and green and healthy development, which can only be put into practice through more actions and labor practices. As an important part of the combination of the theory and practice of ecological civilization construction, labor education needs to be objectively evaluated through more intelligent methods. This paper aims at providing an objective indicator for labor education in colleges and universities. First, RNN network completes the state identification of the theoretical learning stage; then combined with the offline practical action acquisition technology based on wearable devices, the KNN method was used to complete the action recognition in the practice process. Finally, SVR technology is used to complete the evaluation regression analysis based on online and offline learning features. The proposed model performs well in RMSE and related coefficient indicators, providing technical support for the objective evaluation of labor education in colleges and universities in the future.