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Research Questions: While community college transfer (i.e., upward transfer) represents an important mechanism for advancing equity across STEM fields, existing studies of gender and women’s participation within computer science have largely excluded the perspectives of upward transfer students. We address this gap in the literature by exploring transfer receptivity and gender discrimination within computer science, guided by the following questions: (1) How do upward transfer computer science students report their receptivity experiences, and how might this differ by gender? (2) How do upward transfer computer science students make meaning of receptivity experiences, and how might that meaning making be shaped by gender? Methods: We use a sequential mixed methods design, relying on longitudinal survey and interview data from upward transfer computer science majors, collected throughout students’ first year at the receiving university. Results: Findings reveal that, relative to men, upward transfer women report greater experiences of transfer stigma and challenges accessing resources at the receiving university. Qualitative findings document additional nuances in how upward transfer students—especially women—describe resilience as they navigate the university campus, encounter navigation challenges at the university, and make meaning of various manifestations of transfer stigma on campus. Contributions: In addition to implications for research and theory, we discuss what universities can do to foster a more receptive environment for upward transfer women. Specific recommendations focus on ensuring that spaces for women in computing are inclusive of transfer students and, likewise, creating supportive transfer cohort communities that are inclusive of women.

 

Graduate students’ mental health and well-being is a prominent concern across various disciplines. However, early predictors of mental health and well-being in graduate education, specifically doctoral education, have rarely been studied. The present study evaluated both the underlying latent classification of individuals’ mental well-being and predictors of those classifications. Results estimated two latent classes of students’ mental health and well-being: one class with generally high levels of mental well-being and one with lower levels of mental well-being. Regression analyses showed that mentoring in the second year of doctoral study, certainty of choice in the third year, and both academic development and sense of belonging in the fourth year were positive predictors of membership in the higher mental well-being class. In contrast to some prior studies, demographic variables were not related to the identified well-being classifications. Regression analyses further showed that mental well-being was negatively related to participants’ number of publications and research self-efficacy, indicating a problematic relationship between scholarly productivity and confidence and well-being. These findings may be used to identify and provide targeted support for students who are at-risk for having or developing lower levels of mental well-being in their graduate programs. 

While previous research documents that women in STEM doctoral programs tend to fare better when their advisor shares their gender identity, this study provides new insights into the role of student–advisor gender identity congruence, relying on a longitudinal sample of doctoral students in biology and using structural equation and latent growth curve modeling. Findings show that advisor gender played an inconsistent and typically indirect role in predicting student outcomes. Further, all students, regardless of gender, tended to report higher quality advising when their advisor was a woman, pointing to potential gender inequities in advising expectations of faculty. Implications for research, theory, and practice are discussed. 

Threshold concepts are transformative elements of domain knowledge that enable those who attain them to engage domain tasks in a more sophisticated way. Existing research tends to focus on the identification of threshold concepts within undergraduate curricula as challenging concepts that prevent attainment of subsequent content until mastered. Recently, threshold concepts have likewise become a research focus at the level of doctoral studies. However, such research faces several limitations. First, the generalizability of findings in past research has been limited due to the relatively small numbers of participants in available studies. Second, it is not clear which specific skills are contingent upon mastery of identified threshold concepts, making it difficult to identify appropriate times for possible intervention. Third, threshold concepts observed across disciplines may or may not mask important nuances that apply within specific disciplinary contexts. The current study therefore employs a novel Bayesian knowledge tracing (BKT) approach to identify possible threshold concepts using a large data set from the biological sciences. Using rubric-scored samples of doctoral students’ sole-authored scholarly writing, we apply BKT as a strategy to identify potential threshold concepts by examining the ability of performance scores for specific research skills to predict score gains on other research skills. Findings demonstrate the effectiveness of this strategy, as well as convergence between results of the current study and more conventional, qualitative results identifying threshold concepts at the doctoral level. 

Developing research self-efficacy is an important part of doctoral student preparation. Despite the documented importance of research self-efficacy, little is known about the progression of doctoral students’ research self-efficacy over time in general and for students from minoritized groups. This study examined both within- and between-person stability of research self-efficacy from semester to semester over 4 years, focusing on doctoral students in biological sciences ( N = 336). Using random intercept autoregressive analyses, we evaluated differences in stability across gender, racially minoritized student status, and first-generation student status. Results showed similar mean levels of self-efficacy across demographic groups and across time. However, there were notable differences in between-person and within-person stability over time, specifically showing higher between-person and lower within-person stability for racially minoritized and first-generation students. These findings indicate that racially minoritized and first-generation students’ research self-efficacy reports were less consistent from semester to semester. Such results may indicate that non-minoritized and continuing-generation students’ experiences from semester to semester typically reinforce their beliefs about their own abilities related to conducting research, while such is not the case for racially minoritized nor first-generation students. Future research should examine what types of experiences impact self-efficacy development across doctoral study to offer more precise insights about factors that influence these differences in within-person stability. 

In the laboratory-based disciplines, selection of a principal investigator (PI) and research laboratory (lab) indelibly shapes doctoral students’ experiences and educational outcomes. Framed by the theoretical concept of person–environment fit from within a socialization model, we use an inductive, qualitative approach to explore how a sample of 42 early-stage doctoral students enrolled in biological sciences programs made decisions about fitting with a PI and within a lab. Results illuminated a complex array of factors that students considered in selecting a PI, including PI relationship, mentoring style, and professional stability. Further, with regard to students’ lab selection, peers and research projects played an important role. Students actively conceptualized trade-offs among various dimensions of fit. Our findings also revealed cases in which students did not secure a position in their first (or second) choice labs and had to consider their potential fit with suboptimal placements (in terms of their initial assessments). Thus, these students weighted different factors of fit against the reality of needing to secure financial support to continue in their doctoral programs. We conclude by presenting and framing implications for students, PIs, and doctoral programs, and recommend providing transparency and candor around the PI and lab selection processes. 

Purpose This study aims to examine how science, technology, engineering, and mathematics doctoral students interact with postdocs within the research laboratory, identifying the nature and potential impacts of student–postdoc mentoring relationships. Design/methodology/approach Using a sample of 53 doctoral students in the biological sciences, this study uses a sequential mixed-methods design. More specifically, a phenomenological approach enabled the authors to identify how doctoral students make meaning of their interactions with postdocs and other research staff. Descriptive statistics are used to examine how emergent themes might differ as a product of gender and race/ethnicity and the extent to which emergent themes may relate to key doctoral student socialization outcomes. Findings This study reveals six emergent themes, which primarily focus on how doctoral students receive instrumental and psychosocial support from postdocs in their labs. The most frequent emergent theme captures the unique ways in which postdocs provide ongoing, hands-on support and troubleshooting at the lab bench. When examining how this theme plays a role in socialization outcomes, the results suggest that doctoral students who described this type of support from postdocs had more positive mental health outcomes than those who did not describe this type of hands-on support. Originality/value Literature on graduate student mentorship has focused primarily on the impact of advisors, despite recent empirical evidence of a “cascading mentorship” model, in which senior students and staff also play a key mentoring role. This study provides new insights into the unique mentoring role of postdocs, focusing on the nature and potential impacts of student–postdoc interactions. 

High attrition rates have been a defining characteristic of doctoral education for decades, representing a loss of time, talent, and effort for departing students and their faculty. This qualitative study uses a biomedical science doctoral student sample to collect “real time” data on attrition within the first 2 years of doctoral training. Eighteen students, who represented 16 distinct universities, were interviewed as they engaged in the withdrawal process. Using the conceptual frames of socialization and social cognitive career theory, we explored experiences that preceded these students’ doctoral program withdrawals. Furthermore, we examined how expressed roles of students’ self-efficacy, outcome expectations, and professional goals contributed to the withdrawal process. Findings indicate that faculty advising (both positive and negative), laboratory rotation experiences, self-efficacy components, and changing professional goals all play a role in the early doctoral program attrition process.