Fostering Ph.D. aspirations among upward transfer students in computing

ABSTRACT

Background

Students who transfer from community colleges in pursuit of four-year degrees (i.e., upward transfer students) represent a diverse and talented group that is critical to advancing gender equity in STEM. However, research has not yet explored factors that promote Ph.D. aspirations among upward transfer computing students, resulting in missed opportunities to support this unique group.

Objective

We examine the predictors of upward transfer computing students’ Ph.D. aspirations, focusing on how these patterns might be unique for upward transfer women.

Method

Relying on longitudinal survey data from upward transfer students across 15 research universities, we use logistic regression with interaction terms to identify the predictors of Ph.D. aspirations.

Findings

We found that Ph.D. aspirations were especially frequent among upward transfer women, 14% of whom aspired to earn a Ph.D. Other results highlight the importance of faculty encouragement for graduate study in predicting all upward transfer students’ Ph.D. aspirations. Beyond the direct role of such faculty encouragement, perceptions of computing faculty uniquely predicted Ph.D. aspirations for upward transfer women.

Implications

Our findings provide insight into how to bolster more equitable access to faculty mentorship, support students throughout the transfer process, and create inclusive faculty policies, which impact students’ perceptions of academia.

KEYWORDS:

• Gender
• community college transfer
• graduate school aspirations
• regression

Disclosure of potential conflicts of interest

No potential conflict of interest was reported by the author(s).

Notes

1. Participating universities included 13 public and two private universities, representing all regions of the contiguous United States, except the Northwest. All participating universities are research-intensive.

2. Given that we focused on a subset of students who enrolled in an introductory-level computing course, we conducted analyses with related BRAID samples to assess how representative our sample was of all upward transfer students. We found that upward transfer students are 18% of computing majors in introductory computing courses and 18% of all computing majors across participating sites, regardless of introductory course enrollment. This suggests that our sample is largely capturing broader upward transfer student experiences, despite our narrower focus on introductory-level computing students.

3. While we restricted the scope of our study to focus on upward transfer students, research has documented how upward transfer students compare to non-upward transfer students in the BRAID survey samples (see Blaney, 2020a).

4. We were not able to run a model separately for non-binary students due to sample size constraints.

5. No other race variables were significant; as such, all other groups were collectively treated as the reference group in the final model.

Additional information

Funding

This research was made possible by a grant from the Spencer Foundation (#202000170). The views expressed are those of the author and do not necessarily reflect the views of the Spencer Foundation. The data used in this study were provided by the UCLA BRAID Research Project, whose collection of these data was supported by AnitaB.org and NSF (#1525737).

Notes on contributors

Jennifer M. Blaney

Jennifer M. Blaney is an Assistant Professor at Northern Arizona University. She received her Ph.D. in Higher Education and Organizational Change from UCLA, and her research agenda explores community college pathways as a mechanism for broadening women's participation in computing.

Annie M. Wofford

Annie M. Wofford is a Ph.D. candidate in Higher Education and Organizational Change at UCLA. Her research agenda examines (in)equity in collegiate STEM environments, with a critical focus on enhancing inclusive graduate school trajectories and mentoring relationships.