Effect of Deep Learning on College Students’ Career Planning

Abstract

It is difficult for college students to find jobs after graduation, which is the most important problem to be solved now. This paper chooses the statistical analysis method to analyze the career planning of college students under different circumstances. Four aspects are analyzed, which are decision-making action, current situation evaluation, career exploration, and self-understanding level. The main conclusions of this paper are as follows. In this study, the gender differences of college students have a certain impact on their career. Generally speaking, the career planning level of boys is higher than that of girls. The job-hunting needs of college graduates are students who enter social work. Family factors affect the level of college students’ career planning. It is found that students’ school experience is the most important factor affecting the level of career planning, and school experience is also reflected in whether students have class committee experience.