Can Undergraduate Research Participation Reduce the Equity Gap?

Abstract

Undergraduate research (UGR), one of several high-impact practices (HIPs) in education, can positively impact student retention and graduation rates. However, not all students take advantage of UGR opportunities, with fewer students from underrepresented minority groups, those with first-generation status, and students eligible for a Pell grant or federally subsidized loan. We obtained retention and graduation data from our Office of Institutional Research and Planning for all UGR participants for academic years 2009–2010 to 2016–2017. We specifically focused on data for UGR participants from underrepresented demographics that historically have lower retention and graduation rates than those of the overall student body. We created Sankey-like ribbon diagrams to analyze the characteristics of UGR participants, whether they participated in UGR for 1 year or longer, their class standings when they started UGR, retention rates for 1st- and 2nd-year students for the year following their UGR participation, and graduation rates for all participants. Our data show that irrespective of demographics, students who participated in UGR were significantly more likely to persist in college and graduate within 6 years compared to students who did not. Persistence and success in college may depend on students’ socioeconomic status, sense of belonging, and other factors. Assessing the impact of a single HIP, such as UGR, on retention and graduation rates, can, therefore, be complicated. However, our study indicates that UGR participation can significantly improve persistence and success for students traditionally considered “at-risk,” irrespective of their socioeconomic status, family background, or class standing.. This information can be important for campus leaders and other stakeholders interested in facilitating student success and reducing the equity gap by incorporating UGR in more students’ college experiences. We describe our analytical methods and discusses our findings. We also demonstrate the effectiveness of Sankey-like diagrams for visualizing and analyzing large programmatic data sets, and as a tool for communicating program impacts to a general audience.