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Jang-Tucci, K., Benbow, R. J., & Bañuelos, N., (2023). Using Multiple Generator Random Interpreters (MGRIs) for Studying Undergraduate Student Support Networks. Networks & Cultural Assets Project. Center for Research on College-Workforce Transitions. University of Wisconsin–Madison, Division of Continuing Studies.

Abstract: Researchers in higher education who study social support networks—groups of interpersonal relationships through which individuals exchange help, advice, and guidance (Wasserman & Faust, 1994)—widely use name generators and interpreters in surveys. “Name generators” are questions that elicit the names of people with whom survey respondents exchange information or discuss certain topics. After collecting these names, surveys often include “name interpreters” that ask respondents to provide information on the people who have been listed, including, for example, each person’s role in the respondent’s life, their education level, how close the respondent feels affectively to each person, etc. This research brief introduces the Multiple Generator Random Interpreter (MGRI; Marin & Hampton, 2007), a method for collecting personal or “ego” network data, as an alternative to traditional name generators and interpreters in social network research. Specifically, we focus on: (1) How MGRIs are different from Traditional Name Generators and Interpreters (TNGIs), and (2) What new insights can be yielded from using MGRIs when assessing college students’ support networks. We answer  with a review of social network literature, and then focus on  describing research methods and empirical evidence from two studies we have conducted of Latino/a/x/e (hereinafter “Latine”) college students in two U.S. states. We conclude with insights from our analyses and links to resources for implementing MGRIs in online surveys.

Bañuelos, N.,  Jang-Tucci, K., & Benbow, R. (2023). Forming Science Identity in Personal Networks: A Quantitative Study of Social Support for Latine STEM Students. Center for Research on College-Workforce Transitions. University of Wisconsin–Madison.

Abstract: Although Latine students and their families maintain high aspirations for their achievement in STEM (Science,Technology, Engineering, and Mathematics), they continue to face barriers to STEM degree completion and remain underrepresented in the STEM workforce. Social support systems are key to science identity formation and sense of belonging, two important predictors of persistence and attainment in STEM, particularly among historically marginalized students (Chemers et al., 2011; Strayhorn, 2012). For this reason, documenting Latine college students’ social networks – including their strengths, structure, and how they change over time– can help researchers understand trajectories in STEM.

Using the Community Cultural Wealth framework (CCW) – a theory focused on strengths within Communities of Color (Yosso, 2005) – this study examines survey responses from Latine STEM majors across the University of Texas System and measures important contours of Latine STEM students’ social networks, including (1) the features of these social networks, (2) the forms of CCW students possess in their social networks, and (3) the relationships that exist between students’ networks, science identity, and sense of belonging.

Hora, M., Lee, C. (2023). Cultural Scripts for Teaching Transferable Skills: Exploring the Role of Industry Experience and Pedagogical Situations on Skills-Focused Instruction in College Classrooms. Center for Research on College-Workforce Transitions. University of Wisconsin–Madison, Division of Continuing Studies.

Abstract: Why do postsecondary faculty teach the way they do, and what predicts their use of particular teaching methods and student engagement strategies in the classroom? Based on research over the last 40 years in both K-12 and postsecondary settings, consensus exists that no single predictor of instructional practice exists, but that a myriad of forces (e.g., individual, socio-cultural, and contextual) interact to shape how an instructor plans and teaches their classes (Shavelson & Stern, 1981; Lattuca & Stark, 2011; Posselt et al., 2020).

In this paper, we address this question by examining the potential role of a specific type of instructor attribute – that of prior experience in non-academic workplaces (hereafter called industry experience) – that is theorized to be associated with students’ acquisition of skills known variously as “soft,” “non-cognitive” or “transferable” (Deming, 2017; Pellegrino & Hilton, 2002). We address how culture is conceptualized in higher education in general, and in studies of faculty teaching in particular, especially the unit of analysis wherein cultural elements reside and then change (or not) over time (Välimaa, 1998). Following a brief exposition of the theoretical and empirical foundations of this approach, we then report findings from an exploratory mixed-methods study where these ideas were explored in the context of teaching in science, technology, engineering, mathematics and medical (STEMM) fields. We conclude the paper with an analysis of the implications of these data for faculty development, but also concerns that cultural scripts can encode ideologies and norms antithetical to a liberal, democratic, and equity-oriented education (Cronon, 1988; Harris & Patton, 2019; Urciuoli, 2008).

Image of cover of report. Photo is of two workers in yellow hard hats inspecting machinery.
Research Report

Hora M.T., Thompson M., Jang-Tucci K., Pasqualone A., Akram-Turenne T., Wolfgram M., Lee C. (2023). What are the longitudinal impacts of a college internship (during a pandemic)? Findings from the College Internship Study on program participation, quality, equitable access, and student outcomes. Center for Research on College-Workforce Transitions. University of Wisconsin–Madison, Division of Continuing Studies.

Image of report cover. Photo is of students of various identities speaking with employers at an internship fair.
Executive Summary

Abstract: The College Internship Study wrapped up its third and final wave of data collection in the Spring of 2022. This report provides a summary of key findings from the longitudinal analyses across eight institutions that participated in the third and final wave of data collection. As an excerpt of the extensive dataset, this summary addresses the most pressing issues in college internship research and practice, as suggested in the Internship Scorecard (Hora et al., 2020). Developed for assessing the purpose, quality, and equity of internship programs, the Internship Scorecard provides a framework for this report to address three main issues of college internships: (a) access and barriers to internships, (b) internship program features and quality, and (c) effects of internships on post-graduate outcomes. Each of these issues are examined in this report, with special considerations for how the COVID-19 pandemic impacted student experiences in college, life, and work.