Document Type

Conference Proceeding

Publication Date

2023

Abstract

In this innovative practice work-in-progress paper, enrollment data from five institutions was used to examine equity in undergraduate research through Vertically Integrated Projects (VIP) Programs. VIP is a model for undergraduate research in which large student teams are embedded in faculty-driven projects. The American Association of Colleges and Universities recognizes undergraduate research as a high-impact experience, associated with higher graduation rates and greater learning gains in college. Participation in multiple high-impact experiences yields cumulative gains to students from all backgrounds, and compensatory gains for minoritized and marginalized students. Nationally however, minoritized students, first-generation college students, and transfer students participate in undergraduate research at lower rates than their peers. In this study, VIP enrollments at five institutions (N = 6,651 over two semesters) were compared to demographics of the institutions to determine the degree to which programs achieved equity among historically underserved minorities, transfer students, first-generation college students, and by gender. Analysis accounted for demographics and level of participation of the academic units involved, comparing enrollments with what would be expected under equitable enrollment. Analyses were done for each institution and across the pooled sample. By institution, equity across categories varied. Across the pooled sample, results show small effects sizes for status as a historically underserved minority, very small effect sizes for first-generation students and transfer students, and slightly higher participation among women than men. The large-scale nature of VIP teams enables institutions to scale-up their undergraduate research offerings. This paper begins answering the question of whether this scaling increases access for marginalized populations, and the results are encouraging. The paper is a work-in-progress, because data needs to be collected from more VIP institutions for a wider-ranging study. The chisquare test and the importance of using effect sizes in interpreting results will be explained, so others can apply the same method. Results, implications, and next steps are discussed.

Copyright Statement

© 2023 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. https://doi.org/10.1109/FIE58773.2023.10343518

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