Study on the Learning Path Selection of Beautiful China Construction Based on CBW Method
It is the connotation of the construction practice of beautiful China to adhere to local conditions,explore and create beautiful China construction samples by districts and classifications.At present,a large number of evaluations have been carried out in pilot construction activities such as the beautiful China pioneer area.In the screening model,zoning classification and other aspects have been fully explored.Although the evaluation system is becoming more and more mature,there are still some problems such as the lack of clear learning path of role models,sufficient recognition but insufficient classification guidance.In order to solve such problems,CBW(Category-Better-Way)method system based on big data is proposed,which fully integrates big data technology and ecological civilization construction practice.Based on the three elements of benchmarking management"classification,benchmarking and learning path",a universal auxiliary performance evaluation system and learning path selection mechanism for beautiful China construction is established,which can not only helps auxiliary evaluation institutions to determine ecological case classification categories,establish classification benchmarks and extract benchmarking learning paths,but also helps all places to locate the learning benchmark of the new case of beautiful China construction and find the learning path.The results are compared with the original classification and are basically consistent.The generality of this method is good,and can be applied to the construction of beautiful China.
NETL
NSTL
万方数据
