Proceedings of the International Conference on Information Economy, Data Modeling and Cloud Computing, ICIDC 2022, 17-19 June 2022, Qingdao, China

Research Article

An Empirical Analysis of Employment Motivation and Career Choice of Graduates of Master of Engineering ——Based on Principal Component Factor Analysis and Binary Logit Regression Model

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  • @INPROCEEDINGS{10.4108/eai.17-6-2022.2322785,
        author={Wei  Liu},
        title={An Empirical Analysis of Employment Motivation and Career Choice of Graduates of Master of Engineering  ------Based on Principal Component Factor Analysis and Binary Logit Regression Model},
        proceedings={Proceedings of the International Conference on Information Economy, Data Modeling and Cloud Computing, ICIDC 2022, 17-19 June 2022, Qingdao, China},
        publisher={EAI},
        proceedings_a={ICIDC},
        year={2022},
        month={10},
        keywords={graduates of engineering masters; employment motivation and career choice; influencing factors; principal component factor analysis; binary logit regression model},
        doi={10.4108/eai.17-6-2022.2322785}
    }
    
  • Wei Liu
    Year: 2022
    An Empirical Analysis of Employment Motivation and Career Choice of Graduates of Master of Engineering ——Based on Principal Component Factor Analysis and Binary Logit Regression Model
    ICIDC
    EAI
    DOI: 10.4108/eai.17-6-2022.2322785
Wei Liu1,*
  • 1: Shaoyang University
*Contact email: liuwei052040087@163.com

Abstract

Taking 205 graduates of Masters of Engineering as the survey objects, their employment motivation, career choice and training evaluation were analyzed by principal component factor analysis and binary logit regression model. The study found that: the average year-end employment rate of the 2015-2020 engineering master students reached 99.31%; Factors, such as the industry background and guidance frequency of the tutor, the development and investment of professional practice, the course setting and teaching method, the patent acquisition situation, satisfaction with the professional level as well as knowledge and skills, have a significant impact on the employment motivation and career choice of graduate students of engineering masters.