Evaluation Method of College Students' Learning Autonomy Based on Social Network Support

Abstract

Social network plays an important role in college students’ life. The greater the social network support they have, the more adequate social network resources they get, and the stronger their ability to cope with the challenges of study and life is. Existing studies have overemphasized the influence of social environment on college students' academic success, and have not paid special attention to the influence of the outside world on the change of college students' learning attitude. Therefore, this article studies the evaluation method of college students' learning autonomy based on social network support. Firstly, the local and global features of network nodes are extracted, and the social network roles of college students are divided. Then, a new logical structure network is constructed based on the vector representation of each node, which maximizes the influence of relevant nodes on college students' social network support. Finally, based on the new network structure, the meta-path walking algorithm is introduced to evaluate college students' learning autonomy by obtaining the attribute features supported by social networks through network nodes. Experimental results verify the effectiveness of the proposed method.