Doctoral advisor selection processes in science, math, and engineering programs in the United States

Abstract

Although advising relationships are key for doctoral student success, little research has addressed how they form. Understanding the formation of advising relationships can help contextualize their later development and ultimately support a student’s decision to persist in the doctorate. To understand relationship formation, the purpose of this qualitative study is to identify and describe the types of advisor–advisee selection processes that exist in engineering, science, and math doctoral programs and examine patterns across disciplines within those fields. We conducted interviews with doctoral program directors and engaged in document analysis of graduate student handbooks from 55 doctoral programs in the aforementioned fields in high research institutions across the United States. Using principal–agent theory as a theoretical lens, our findings showed that engineering programs tend to decentralize the advisor selection process by funding students across different funding sources upon enrollment. Contrariwise, science and math programs tended to fund all students in a cohort from a common funding source, which allowed students to have more time to gather information, meet, and select an advisor. These findings also show important nuances when comparing graduate education in these programs that directly impact the doctoral student experience and reiterates the necessity to study these fields separately.

Learning Goals and Priorities Identified by an Examination of Chemistry Graduate Handbooks

“…Lab rotation is a period where students interact with advisors, postdocs, and other graduate students in several laboratories for defined periods of time and decide on which laboratories to join. , While only a third of the programs studied implement them, LR received the greatest proportion of chemistry departments that state learning goals (Figure ). Six unique learning goals were identified for lab rotations , the most common of which was for a student to select a formal research advisor followed by conducting research (Figure S2), consistent with previous reports showing increases in lab rotations .…”

Mitigating Ceiling Effects in a Longitudinal Study of Doctoral Engineering Student Stress and Persistence

“…While this reduction in explained variance from the original model to the adjusted model may be interpreted as bad thing, we posit that the revised model provides a more realistic estimation of the influence of stress on departure considerations, providing space for other constructs to be added to more sophisticated models of early departure in the future, rather than trying to explain early departure solely through the lens of stress. Indeed, through theory and literature on doctoral education, although chronic stress in graduate school is significant and meaningful, we know from the literature that many other constructs significantly impact considerations to depart or remain in engineering graduate study, including advisor and peer relationships, non-academic events, gender and race-based discrimination, costs, and employment opportunities (Artiles & Matusovich, 2020;Bahnson et al, 2022;Berdanier et al, 2020;Lott et al, 2009;Sallai et al, 2023;Zerbe et al, 2023). Further, most studies of stress in doctoral programs focus on academic stress (e.g., Cornér et al, 2017;Cornwall et al, 2019;Pyhältö et al, 2012), or a systems-level understanding of stress related to career attainment after graduate school (e.g., Bekkouche et al, 2022), instead of also capturing pressures from life outside of the academy.…”

“…During graduate school, some students experience critical events that alter their worldviews on remaining in graduate school, which have been shown to lead to departure considerations and eventual early departure (Lott et al, 2009;Zerbe et al, 2023). While many life experiences can be critical events for students (Zerbe et al, 2022), many factors influence departure considerations, including advisor and peer relationships, discrimination, and employment opportunities (Artiles & Matusovich, 2020;Bahnson et al, 2022;Berdanier et al, 2020;Lott et al, 2009;Sallai et al, 2023;Zerbe et al, 2023). In other students, more general dissatisfaction and unhappiness build with no identifiable critical event leading to departure.…”

Development and initial validation of the Discrimination in Engineering Graduate Education (DEGrE) Scale.

“…In this apprenticeship model, the interpersonal relationship is often defined by a power structure in which the experienced researcher or research advisor maintains significant influence over the success and persistence of graduate students. The advisor–advisee relationship generates imposing power relationships that define the graduate student’s experience, where good advisor relationships lead to good graduate experiences or bad relationships to bad experiences (Artiles & Matusovich, 2020; NASEM, 2018).…”