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An Exploration of the Impact of Student Employment and Retention: A Correlational Analysis

2021
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Metric Options:   Counts1 Year3 Year

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Thesis / Dissertation Description

"With so many students working, and such large numbers devoting a considerable amount of time to one or more jobs, work is – after going to class- the most common activity in which undergraduates engage" (Kuh, 2018, p. ix). An under-researched factor to investigate why students retain, is participation in an on-campus student employment program. The purpose of the study is to explore the relationship between a student's participation in student employment and if the student retains from their first to second year. Understanding this relationship can provide an opportunity to create positive impact for both the student and institution with minimal institutional financial investment. Additionally, this study explores if the level of participation in the program impacts if a student will retain. Utilizing a quantitative approach, the researcher used logistic regression to predict the relationship between student employment participation and retention. Tinto's Model of Institutional Departure and Astin's Student Involvement Theory framed the research questions for this study. Exploring the variable of student employment participation on retention might provide a valuable opportunity for institutions to invest in programming that provides financial, educational, and social support for the student while positively impacting their likelihood to retain. This study's analysis provides a prediction of the positive impact a student's participation in an on-on campus student employment program can have on whether a student retains at the institution. This study found that student participants were about 46% more likely to retain from their first year to the next at their institution. Additionally, the study found that for each hour the student participates in the program, they are .4% more likely to retain. Though significant, the study violated some assumptions on the logistic regression, restricting the generalizability of the study.

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