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Research on the Intervention Mechanism of Career Choice Anxiety among College Students Based on Big Data

Published: 30 May 2024 Publication History

Abstract

Career choice anxiety among college students has become an undeniable phenomenon. In order to explore the internal mechanism of career choice anxiety among college students, we established a structural equation model with professional identity as the independent variable, career choice anxiety as the dependent variable, and self-efficacy as the mediating variable. SPSS22.0 software, AMOS210 software, and MPLUS7.0 software were used to process and analyze data from 647 college students. The results show that (1) There is a significant correlation between professional identity, career choice anxiety, and self-efficacy. Career choice anxiety is significantly negatively correlated with professional identity and self-efficacy, while professional identity and self-efficacy are significantly positively correlated. (2) Professional identity associated with career choice anxiety (p<0.001) mediated by self-efficacy (proportion of effect mediated = 48.7%). Specifically, college students' professional identity can not only directly affect career choice anxiety but also indirectly affect it through the intermediary effect of self-efficacy. Finally, some solutions targeted at the problem of career choice anxiety among college students were proposed.

References

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Ministry of Education of the People's Republic of China. The Expected Number of College Graduates in 2023 is 11.58 Million. http://www.moe.gov.cn/jyb_xwfb/s5147/202211/t20221118_995344.html?authkey=boxdr3.
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Zhao Liangling. The Relationship Between Career Choice Anxiety and Career Exploration Behavior Among University Students: The Mediating Role of the Cult of Money[J]. Psychological Monthly, 2023, 18(04): 82-84.
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  1. Research on the Intervention Mechanism of Career Choice Anxiety among College Students Based on Big Data

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    ICIEAI '23: Proceedings of the 2023 International Conference on Information Education and Artificial Intelligence
    December 2023
    1132 pages
    ISBN:9798400716157
    DOI:10.1145/3660043
    Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than the author(s) must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected].

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    Published: 30 May 2024

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