This study was designed to address the issue of low retention in online K–12 courses. The goal of this research was to explore educator and student perceptions of factors impacting retention. This qualitative exploratory case study design collected and analyzed data at Southeastern Virtual School (SVS/pseudonym), a state-wide online public high school in the southeastern United States. The phenomenon analyzed for this study was factors impacting retention in English 1 at SVS. Data collection tools included a focus group interview (n=7) and student surveys (n=774). Thematic analysis was conducted on both data sets. The research results of this study provided Southeastern Virtual School with recommendations that the organization could implement to increase student retention and offer early intervention for those the study found to be most at risk for withdrawal. The study demonstrated that major factors impacting retention in K–12 online courses included the following: (a) student-teacher interactions, (b) student support, (c) instructional design, (d) course policies, (e) parental involvement, (f) external complications, (g) previous academic performance, and (h) student age. Implications for practice and future research were discussed. Recommendations for improvement of student retention determined by the study findings included: (a) teacher professional development, (b) continued support for online students, (c) professional learning communities focused on student retention, and (d) continued opportunities for student surveys. The study's findings offered implications for teachers and educational leadership to inform their pedogeological and organizational practices and policies on retention. The findings of this study also provided strategies for K–12 leaders and policy makers to address retention.
| Identifer | oai:union.ndltd.org:ucf.edu/oai:stars.library.ucf.edu:etd2020-1923 |
| Date | 01 December 2021 |
| Creators | Rowe, Ashley |
| Publisher | STARS |
| Source Sets | University of Central Florida |
| Language | English |
| Detected Language | English |
| Type | text |
| Format | application/pdf |
| Source | Electronic Theses and Dissertations, 2020- |
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