Research: RFE—Understanding graduate engineering student well-being for prediction of retention

点击翻译按钮获取中文摘要

Doctoral students frequently leave engineering, thereby reducing the supply of highly-trained engineers in the US and contributing to lost tuition investments made for doctoral student tuition. Graduate students face many stresses: from classwork, from their paid teaching and research commitments, and from other stressors outside of their graduate work. In this research on the formation of engineers, we will identify major stressors that PhD-level engineering students commonly face, create and validate a questionnaire to measure these stressors, and test how stress can predict students’ intentions to leave their doctoral programs. The project uses a workplace stress model in which having low control over job hindrances (e.g. course availability, graduation requirements, COVID-19) leads to harmful stress. The results of this study can inform a wide range of programs and personnel who support doctoral engineering students, including faculty advisors and engineering departments, counselling centers, career centers, writing centers, and others. Although prior research work has identified major stressors, little work has been done to compare sources of stress for graduate PhD students and the effects of these stressors on retention. With a research-backed identification of major stressors and their effects, these stakeholders above can be empowered to adopt programmatic changes or other strategies proactively addressing the stressors we will identify. The measure of doctoral students’ stressors that we produce can be broadly implemented by other universities to identify where more supports are needed, to expand available supports, and by other researchers seeking to understand effects of stress on STEM education.The goals of the project are to identify top stressors for doctoral students across different phases of engineering PhD programs and to predict the effects of top stressors on retention in those programs. In Year 1, we will interview a diverse set of students (N = 57) about stressors and coping, to identify which sources of stress occur the most frequently and are perceived by participants as being the most harmful. Participants will also complete existing questionnaires on stress and anxiety, and we will model changes in those variables over an academic year. In Year 2, we will develop a new questionnaire measuring the valence and frequency of top stressors, based on our results from work in Year 1. We will conduct cognitive interviews with doctoral engineering students to identify any confusing items and improve the questionnaire. Following this, we will test the psychometrics of the questionnaire in Year 2 with a diverse sample of 300 doctoral engineering students. In year 3, we will use the newly validated measure, together with other existing measures of stress and anxiety, to predict students’ intention of leaving a doctoral engineering program (N = 300). Outcomes of the project will be findings about the prevalence of different stressors by groups (e.g., groups under-represented in engineering, early/middle/late in doctoral studies, domestic vs. international PhD students), a validated questionnaire widely usable by programs and researchers, and estimates of the effect of stress on intention to remain in a doctoral engineering program. A technical manual and non-technical descriptions of the findings will be made available to the public, together with presentations at research- and practice-focused conferences. Updates will be available on the PI’s website.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.