The admission process at higher education institutions has not adapted for online distance education classes taken in high schools, such as those offered by the Florida Virtual School. The purpose of this study was to determine whether online distance education courses taken in high school can serve as an indicator of student success in post-secondary education. An honors program at a large public research university provided the data examined. This honors program stored online distance education information in a database, which allowed for analysis. Presently, the institution's primary undergraduate admission office does not collect or store this type of information. I used SPSS Statistics to calculate logistical regression on this data. My goal was to discover what effect the high school online distance education variables had on the outcome of graduating in four or six years. Graduation rate is a key metric for colleges and universities as an indicator of success. For this reason, I wanted to determine through this study whether high school online distance education assisted in predicting which students will graduate. At least two stakeholders will find this information useful. Admission officers and, more specifically, honors admission officers will gain more insight into the student selection process as this study examines students in the top 10% of the incoming class. The other group, future researchers, will learn from this study and other new studies for even more understanding on this topic. Although the results indicated that high-achieving Florida Virtual School students do not graduate at higher rate than students who have not completed distance education classes, more research is required to understand how the other 90% of student applicants are affected by distance education courses completed in high school.
| Identifer | oai:union.ndltd.org:ucf.edu/oai:stars.library.ucf.edu:etd-6662 |
| Date | 01 January 2017 |
| Creators | Callahan, Michael |
| Publisher | University of Central Florida |
| Source Sets | University of Central Florida |
| Language | English |
| Detected Language | English |
| Type | text |
| Format | application/pdf |
| Source | Electronic Theses and Dissertations |
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