High Quality Resources Sharing of College Students’ Career Guidance Course Teaching Based on Decision Tree Classification Algorithm

In order to improve the quality and efficiency of sharing high-quality teaching resources and achieve ideal results, a decision tree classification algorithm based method for sharing high-quality teaching resources in college student employment guidance courses is proposed. Firstly, before resource sharing and transmission, design a security key for public information and encrypt the public information of high-quality teaching resources. Secondly, the decision tree classification algorithm is used to construct a classification standard for electronic archives, and regional partitioning is performed to extract resource sharing classification codes. At the same time, establish a database of teaching resources for employment guidance courses to store information related to high-quality teaching resources for college students’ employment guidance courses. Finally, establish a blockchain based teaching resource security sharing model to achieve information sharing of high-quality teaching resources. Experimental analysis shows that the proposed method can complete the high-quality resource sharing task of college student employment guidance course teaching within 5–8.5 ms after application, with a significant advantage in resource sharing efficiency.