An Analysis Model of Psychological Resilience of Outstanding Poor College Students Based on Network Big Data and Mobile Computing

Abstract

In recent years, the research on college students’ group resilience has come into the attention of the researchers, and many researchers have shown great interest in this issue. The development of college students’ psychological management system has become an important means for college students to monitor and prevent psychological crisis. The university student management database has accumulated a lot of data, but the data processing work is just simple statistics, storage, and query. Exploring the structure and development law of mental resilience of outstanding poor college students is of reference significance to the emotional education and spiritual growth of teenagers. When coping with setbacks, the outstanding poor college students have an elastic quality in mind, a firm goal in ideals and beliefs, good at thinking and summarizing cognitively, perseverance in will, self-confidence and indomitable personality, outstanding ability, and thinking about people’s interests in dealing with others; psychological protective factors include family, school, and social support. This paper analyzes the big data algorithm and the method of psychological elasticity construction using mobile computing technology and comes to the conclusion that under the background of big data, psychological elasticity construction plays a role in excellent poor college students. This paper studies the current situation of college students’ psychological elasticity, interpersonal trust, and subjective well-being and the relationship between them, discusses the interaction between them, and hopes to make a reasonable explanation for these problems, so as to provide effective help for college students’ mental health and future development.