Co-Principal Investigators: Kalamkarian, Hoori; Frank, Kenneth

Purpose: In this  mixed-methods project, researchers will describe the support networks and help-seeking preferences and behaviors of first-generation students at four public colleges in California, and explore relations between these preferences and behaviors and key postsecondary outcomes. By combining a qualitative analysis of students' social networks with a quantitative analysis of administrative data, the research team will generate insights that colleges may use to strengthen existing services or develop new approaches to supporting first-generation students. The team  will use social network analysis methods to explore the types of relationships and supports that first-generation students access, for what purposes, and with what results.

Project activities: First, using name and resource generators validated through previous social network studies, the team will design and administer two rounds of a panel survey to first-generation college students. Second, the team will conduct three-day field visits to conduct interviews with a subsample of students who completed the Wave 1 survey and with college personnel who are responsible for support services at each college. One year later, they will invite the students who completed the first round of interviews to participate in a second interview online. Third, the team will obtain student unit records to examine the relationships between network properties (type, strength, and function), college-based service use, and academic outcomes, especially year-to-year persistence.

Products: The research team will write and publish an interim and final report and submit a manuscript to a peer-reviewed academic journal. To reach practitioner audiences, they will conduct a webinar summarizing key findings following publication of their two reports. They will also produce a podcast in which they interview students about their social networks, and produce tools to support the improvement of academic, student support, and financial services.

Structured Abstract

Setting: This project  will take place at two campuses of the California State University (CSU) system and two campuses of the California Community Colleges (CCC) system, each purposefully selected in two distinct regions of the state. All four are Hispanic-serving Institutions and serve a large number of first-generation students.

Sample: The research team will administer the first wave of its panel survey to a random sample of 6,000 first-generation, first-time-in-college students (1,500 at each institution). The sample will include students who are enrolled at least half-time (defined as six credits or more) during the fall and spring semesters of the 2021-22 academic year. In spring 2023, the team will administer the second wave of the panel survey to all sample members who completed Wave 1, regardless of their enrollment status at Wave 2. Qualitative interviews will include a total of 60 students (15 students per college).

Factors: Colleges offer an array of academic support, student (or non-academic) support, and financial support services to guide students in transitioning to and matriculating through college. Academic support services, including tutoring and writing centers and learning labs, offer direct help with coursework and study skills. Student support services are intended to foster academic success by helping students clarify their goals, integrate into the college environment, and navigate college by selecting a program of study and developing/following a degree plan. Common student support services include orientation and academic advising. Financial support services include financial aid processing and basic needs assistance for food, transportation, childcare, and housing. Lessons learned from this study will contribute to colleges' understanding of ways to strengthen services in each of these three categories.

Research Design and Methods: The research team will use  a longitudinal, mixed methods approach to study the personal support networks of first-generation college students over their first and second year of college. The research design links three types of data: 1) a panel survey of first-generation college students; 2) qualitative interviews with students and college administrators and staff; and 3) student unit records. The qualitative subsample will be stratified by race/ethnicity, gender, and institution so that the characteristics of the subsample approximate the characteristics of the overall sample. The team will take an inductive approach to analyze the qualitative data. The design reflects an ego-centric approach to visualizing the support networks of first-generation students, which treats each student as central to their own network of support. To collect ego-centric social network data, the survey instrument will include interaction-based name generators and a resource generator. Using OLS and logistical regression models, the quantitative analysis will assess whether and to what extent social networks increase college persistence, GPA, and credit attainment both directly and as mediated by use of campus-based services.

Control condition: The correlational analysis will compare the outcomes of students with various types of support networks, controlling for additional factors such as academic enrollment and use of services.

Key Measures: The primary dependent variable is year-to-year persistence in college, specifically whether a student who completed the first year of college is still enrolled in the fall of the subsequent year. Additional dependent variables are college GPA and the number of college credits completed by the end of the second year. These measures will be captured through student unit records obtained from the colleges. Key measures of social relationships will include the person type (e.g., friend, family, employer, instructor), strength of the tie (operationalized as frequency of interaction), and the person's support function (e.g., instrumental, emotional, advising, oversight). These measures will be captured through a social network survey. Other qualitative measures will include constructs that describe the advising and student support provided at participating institutions.

Data Analytic Strategy: The research team will define a student's (ego's) network in terms of the people (alters) and demographic characteristics named by the survey respondent. Using conventional techniques (OLS, logistic regression), the team will model the dependent variables (persistence, grades earned, and number of college credits completed by the end of the second year) for egos as a function of ego characteristics and composites of the alter networks. The team will also use logistic regression models to estimate the effect of the social network on use of campus-based services and the effect of using college-based services on college persistence, with campus-bases services assessed as a mediating factor. For all rounds of qualitative analysis, the research team will use a first and second cycle coding strategy. In the first cycle, the team will begin analysis as data is collected to identify patterns and noteworthy findings as early as possible. The team will start with a set of theory-based codes. Then, taking an inductive approach, researchers will amend and expand the codebook as themes emerge from the data. The final stage of analysis will involve reviewing and organizing excerpts, identifying quotes and narratives that are particularly illustrative of a phenomenon or issue, and triangulating the qualitative findings with the Wave 1 and Wave 2 survey results.