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The USA’s higher education leaders and professional organizations have called for increased professional development programming at graduate colleges to better prepare US graduate students for their future careers. This study aims to investigate the demographic characteristics of graduate students participating in co-curricular professional development (PD) and sociocultural development (SD) programming at a graduate college at a large, selective and research-intensive public university in the Midwestern USA.

Using institutional data from six semesters, the authors examined the characteristics of students that attended the graduate college’s programs at one university. The authors analyzed which students were most likely to attend PD and SD programs using multinomial logistic regression models.

Female students, students from US historically marginalized racial groups, and US Pell Grant recipients (low-income students) were found to have a higher likelihood of attending both PD and SD programs at the centralized graduate college.

The findings will be of interest to graduate deans and educators who support graduate students. Further evaluative research on the usefulness of such programs at other institutions would help graduate colleges better understand the role they play in meeting graduate students’ needs.

The findings contribute to the understanding of the important role of the US graduate college in the development of graduate students. To the best of the authors’ knowledge, it is the first study to evaluate the backgrounds of graduate students who pursue co-curricular PD and SD opportunities.

Education researchers have been urged to utilize causal inference methods to estimate the policy effect more rigorously. While randomized controlled trials (RCTs) are the gold standard for assessing causality, RCTs are infeasible in some educational settings, particularly when ethical concerns or high cost are involved. Quasi-experimental research designs are the best alternative approach to study educational topics not amenable to RCTs, as they mimic experimental conditions and use statistical techniques to reduce bias from variables omitted in the empirical models. In this chapter, we introduce and discuss the core concepts, applicability, and limitations of three quasi-experimental methods in higher education research (i.e., difference-in-differences, instrumental variables, and regression discontinuity). By introducing each of these techniques, we aim to expand the higher education researcher's toolbox and encourage the use of these quasi-experimental methods to evaluate educational interventions.