Abstract:Background Immigrant-origin students are the fastest growing new population in community colleges, making up nearly a third of the community college population. To date, little is known about how immigrant-origin students make use of their time on community college campuses. Purpose This study sought to understand in what ways and to what extent immigrant-origin students—defined as first-generation (foreign-born) or second-generation (born in the United States to immigrant parents)—used their out-of-class camp… Show more
“…Additionally, Lewis et al (2021) found that African American students at a PWI experienced particularly high rates of racism, which negatively impacted their sense of belonging. Similarly, for other minoritized students, researchers have found that marginalization and hostile campus climates affect students’ belongingness, academic achievement, and well-being (Burgos-Cienfuegos et al, 2015; Hernandez et al, 2019; Hurtado & Carter, 1997; Stephens et al, 2012). Greater college belongingness also correlates positively with life satisfaction for first-generation college students (Duffy et al, 2020) and negatively with anxiety and depression, with stronger associations for first-generation and racially/ethnically minoritized students (Gopalan et al, 2022).…”
Sense of belonging is theorized to be a fundamental human need and has been shown to have important implications in many domains of life, including academic achievement. The Sense of Social Fit scale (SSF; Walton & Cohen, 2007) is widely used to assess college belongingness, particularly to study differences in academic experiences along lines of gender and race. Despite its wide use, the instrument’s latent factor structure and measurement invariance properties have not been reported in the published literature to date. Consequently, researchers regularly use subsets of the SSF’s items without psychometric justification. Here, we explore and validate the SSF’s factor structure and other psychometric properties, and we provide recommendations about how to score the measure. A one-factor model in Study 1 showed poor fit, and exploratory factor analyses extracted a four-factor solution. Study 2’s confirmatory factor analyses demonstrated superior fit of a bifactor model with four specific factors (from Study 1) and one general factor. Ancillary analyses supported a total scale scoring method for the SSF and did not support computing raw subscale scores. We also tested the bifactor model’s measurement invariance across gender and race, compared latent mean scores between groups, and established the model’s criterion and concurrent validity. We discuss implications and suggestions for future research.
“…Additionally, Lewis et al (2021) found that African American students at a PWI experienced particularly high rates of racism, which negatively impacted their sense of belonging. Similarly, for other minoritized students, researchers have found that marginalization and hostile campus climates affect students’ belongingness, academic achievement, and well-being (Burgos-Cienfuegos et al, 2015; Hernandez et al, 2019; Hurtado & Carter, 1997; Stephens et al, 2012). Greater college belongingness also correlates positively with life satisfaction for first-generation college students (Duffy et al, 2020) and negatively with anxiety and depression, with stronger associations for first-generation and racially/ethnically minoritized students (Gopalan et al, 2022).…”
Sense of belonging is theorized to be a fundamental human need and has been shown to have important implications in many domains of life, including academic achievement. The Sense of Social Fit scale (SSF; Walton & Cohen, 2007) is widely used to assess college belongingness, particularly to study differences in academic experiences along lines of gender and race. Despite its wide use, the instrument’s latent factor structure and measurement invariance properties have not been reported in the published literature to date. Consequently, researchers regularly use subsets of the SSF’s items without psychometric justification. Here, we explore and validate the SSF’s factor structure and other psychometric properties, and we provide recommendations about how to score the measure. A one-factor model in Study 1 showed poor fit, and exploratory factor analyses extracted a four-factor solution. Study 2’s confirmatory factor analyses demonstrated superior fit of a bifactor model with four specific factors (from Study 1) and one general factor. Ancillary analyses supported a total scale scoring method for the SSF and did not support computing raw subscale scores. We also tested the bifactor model’s measurement invariance across gender and race, compared latent mean scores between groups, and established the model’s criterion and concurrent validity. We discuss implications and suggestions for future research.
Community colleges may face challenges supporting the unique needs of language minority (LM) students whose primary language is not English. Florida provides a unique context for examining whether LM students who are considered underprepared for college-level coursework benefit more from traditional developmental education programs in reading and writing, or reformed programs that allow most students to accelerate or even bypass developmental requirements while providing additional support services. Utilizing statewide data from firsttime-in-college students at all 28 Florida College System institutions, we use an interrupted time series design with an analysis of heterogenous effects to compare first year coursetaking outcomes in English before and after Florida’s developmental education reform for LM versus non-LM students. We also consider the intersecting identities of LM students by further disaggregating results based on whether students took high school courses in English for Speakers of other Languages (ESOL), and for native-born versus foreign-born students. The findings suggest that while the reform’s benefits are similar for LM and non-LM students overall, there are importance differences among LM subgroups which indicate that ESOL and foreign-born students may benefit most.
Objective: Although much research on community colleges focuses on institutional challenges or student deficits, emerging evidence suggests that student–instructor relationships have the potential to impact student success. The current study examined factors that could influence community college students’ development of relationships with instructors and how these relationships are associated with academic engagement and achievement. Drawing on literature exploring student–instructor relationships at 4-year institutions, we hypothesized that students’ relationships with instructors may partially account for the association between student demographic and relational characteristics and academic outcomes (i.e., cognitive and behavioral engagement, grade point average [GPA]). Method: Survey data were collected from 646 ethnically and racially diverse participants, many of whom were first-, second-, or third-generation immigrants, or first-generation college students. Employing a between-subjects, cross-sectional design, we tested the main study hypotheses of mediation through a series of path analysis models using Mplus. Results: Students with higher support-seeking attitudes and students with a mentor reported closer relationships with instructors, whereas part-time students reported weaker relationships with instructors. In turn, student–instructor relationships were significantly associated with both cognitive and behavioral aspects of academic engagement and GPA. Conclusion: This study provides insight into the various factors that may influence community college students’ development of relationships with instructors and highlights the direct and indirect influence of these relationships on student success. Implications for future practice include finding strategies that can be implemented at community colleges to foster student–instructor relationships. Future research should further explore these associations using longitudinal data to gain a deeper understanding of current findings.
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