NSF EAGER (#1747580): Collaborative Research: Measuring the Effects of Academic Climate and Social Networks on Persistence of STEM Undergraduates

UConn Principal Investigator: Chrystal A. S. Smith, Ph.D., Department of Anthropology, University of Connecticut
USF Principal Investigator: Michelle Hughes Miller, Ph.D., Women’s and Gender Studies, University of South Florida
USF Co-Principal Investigator: Maralee Mayberry, Ph.D., Sociology, University of South Florida
Postdoctoral Scholar: Rebecca A. Campbell-Montalvo, Ph.D., Neag School of Education, University of Connecticut

Through a theoretical framework of social capital theory, this transformative research explores the effects of academic climate and social networks on the persistence of SGM STEM undergraduates, an understudied population. SGM refers to individuals who identify as Lesbian, Gay, Bisexual, Transgender, or Queer/Questioning (LGBTQ) or other sexual or gender minority positionalities (Shelton, 2017). Persistence is defined uniquely as the presence of academic affirming actions (e.g., enrolling in classes and maintaining a passing GPA) as well as strategic choice activities (e.g., intentionally changing advisors, majors, or institutions) that lead to progress toward students’ STEM goals. Academic climate refers to both student perceptions of others’ attitudes, behaviors, and practices and student experiences of discrimination, harassment, and abuse. Social networks are relationships that convey useful resources that benefit some majority group members, while groups that are traditional outsiders- such as SGM individuals are less likely to benefit.

Our collaborative exploratory interdisciplinary study addresses the question: How do STEM academic climate and social networks affect the persistence of SGM STEM undergraduates? To increase our understanding about their experiences of STEM academic climate, social networks, and persistence in STEM programs and reconceptualize their persistence as strategic choice, we have used a mixed-methods approach to:

• Gather 30 rich in-depth interview data from SGM STEM undergraduates, and
• Develop an online survey with open-ended questions from the interview data and relevant literature

We are testing the survey on a purposive sample of 30 SGM STEM undergraduates. Our goal is to create a reliable and validated survey that can be used to comparatively study SGM STEM students nationally, across disciplines. Consequently, survey respondents for the final survey will be recruited from six STEM-based national professional associations and discipline-specific societies with dedicated SGM subdivisions. We employ ego network analysis, multilevel logistic regression (MLR), and intersectional analysis using SAS 9.4 to analyze the survey results.