The purpose of this quantitative study is to assess if perceptions of academic and institutional support as well as demographic factors, predict intention to return to school amongst online first-generation college students enrolled at traditional higher educational institutions. To complete the causal-comparative study, the researcher analyzes data from students who completed the National Survey on Student Engagement during the Spring of 2018. Before data was analyzed, a literature review was conducted. The reviewed literature found that despite increasing popularity, retention rates between in-person and online courses vary (Bawa, 2016; Bacon, 2016; Cho & Tobias, 2016). Furthermore, past empirical assessments have provided a deep understanding of FGCS's intention to return to physical campuses (Adams & McBrayer, 2020). However, academic literature investigating the impact of academic and institutional support and demographic factors to predict intention to return to school in FGCS at online college settings is absent.Participants in this study were in their first (n = 141, 58%) and second years (n = 69, 28.4%) of college. The independent variables within this study include perceptions of academic and institutional support and demographic variables. The dependent variable is retention and will be the student’s answer to the question, “Do you intend to return to this institution next year?” with answers dichotomized as “yes” or “no/not sure.” The findings from this study indicate that perceptions of academic and institutional support, as well as participant age, significantly predict online FGCS intent to re-enroll in their current institution. Additionally, the data showed FGCS satisfaction levels with the entire online educational experience.
| Identifer | oai:union.ndltd.org:siu.edu/oai:opensiuc.lib.siu.edu:dissertations-3110 |
| Date | 01 May 2023 |
| Creators | Lewis, Danna |
| Publisher | OpenSIUC |
| Source Sets | Southern Illinois University Carbondale |
| Detected Language | English |
| Type | text |
| Format | application/pdf |
| Source | Dissertations |
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