Regression tree analysis of factors influencing career adaptability in college students

被引:0
作者
Li, Xiujun [1 ]
Tao, Wanrong [1 ]
Zhang, Jing [1 ]
Luo, Jinxi [1 ]
Cai, Yang [2 ]
Deng, Mianlin [1 ]
Hou, Lulu [1 ]
Yang, Yongyong [3 ]
Xu, Dezhen [1 ,4 ]
Wang, Gong [1 ]
Shi, Wendian [1 ]
机构
[1] Shanghai Normal Univ, Shanghai, Peoples R China
[2] Tsinghua Univ, Beijing, Peoples R China
[3] Shanxi Normal Univ, Linfen, Peoples R China
[4] Shanghai Polytech Univ, Shanghai, Peoples R China
来源
EDUCATION AND TRAINING | 2025年
关键词
Career adaptability; Regression tree; Machine learning; Emotional intelligence; Big five personality; Social support; EMOTIONAL INTELLIGENCE; SOCIOECONOMIC-STATUS; MEDIATING ROLE; SELF-EFFICACY; CONSTRUCTION; SATISFACTION; PERSONALITY; FAMILY; WORK; LIFE;
D O I
10.1108/ET-03-2024-0108
中图分类号
G40 [教育学];
学科分类号
040101 ; 120403 ;
摘要
PurposeWe seek to systematically explore the joint effects of individual and environmental factors on college students' career adaptability.Design/methodology/approachThis study employed convenience sampling to collect individual and environmental data from 2,021 college students. The interaction between individual and environmental factors affecting the career adaptability of college students was then analyzed based on a regression tree model. Factors including emotional intelligence, cognitive flexibility, personality traits, role accumulation, experience (internships) and skills (professional certificates), parenting styles, family socioeconomic status and social support were included in the analysis.FindingsAmong the initial 20, the regression tree model identified seven key variables (emotional intelligence, conscientiousness, emotional warmth, number of certificates, openness, career-related support from teachers and cognitive flexibility) as significant. Emotional intelligence emerged as the most influential factor in predicting college students' career adaptability. The samples were segmented into 16 subgroups based on the interactions among these variables. College students with high emotional intelligence and substantial support from parents and teachers exhibited maximum levels of career adaptability, while those with low emotional intelligence and lacking conscientiousness demonstrated the lowest levels of career adaptability.Originality/valueThis study represents the first instance of using machine learning methods to systematically investigate the joint effects of individual and environmental factors on college students' career adaptability. The decision tree model established in this study can identify the unique characteristics exhibited by individuals at different career adaptability levels, offering opportunities to discover the boundary conditions for enhancing career adaptability.
引用
收藏
页数:17
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