谷歌浏览器插件
订阅小程序
在清言上使用

Engineer identity and degree completion intentions in doctoral study

JOURNAL OF ENGINEERING EDUCATION(2023)

引用 1|浏览6
暂无评分
摘要
Background: Degree completion rates for doctoral engineering students remain stagnant at levels lower than necessary to meet national and global workforce needs. Increasing degree completion can improve opportunities for individuals and provide the human resources needed to address engineering challenges.Purpose/Hypothesis: In this work, we measure the association of engineering identity variables with degree completion intentions for students who have persisted in doctoral study. We add to existing literature that suggests the importance of advisor and peer relationships, and the number of years in the doctoral program.Design/Method: We use data collected via a national cross-sectional survey of doctoral engineering students, which included measures of social and professional identities, graduate school experiences, and demographics. Surveys were collected from 1754 participants at 98 US universities between late 2017 and early 2018. The analyses reported here use multiple regression to measure associations with engineering doctoral degree completion intentions.Results: Research interest and scientist performance/competence are individually associated with degree completion intentions in students who are persisting in doctoral study. Overall, graduate engineering identity explains significant portions of variation in degree completion intentions (9.5%) beyond advisor and peer relationship variables and the number of years in graduate programs.Conclusions: Researcher interest and scientist performance/competence may be key opportunities to engage doctoral student engineering identity to improve degree completion rates. Accordingly, institutions can foster students' interest in research and build their confidence in their scientific competence to support students as they complete the doctoral degree.
更多
查看译文
关键词
graduate education,identity,persistence,quantitative,survey
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要