The purpose of this exploratory, retrospective study was to determine if student demographics and academic variables predicted student persistence and success in an associate degree nursing program in Florida and to investigate the variables in Tinto's Longitudinal Model of Dropout (1975).The sample population (N=304) for this study was students enrolled in one of the initial courses of the associate degree nursing program at Daytona Beach Community College (DBCC) in Daytona Beach, FL from August 2002 through August 2003. Students were assigned to one of three groups (a) passing group, (b) failing group, or (c) withdrawing group. The convenience sample of (N=304) included: 242 students who successfully completed the nursing program, 32 students who failed a nursing course, and 38 students who withdrew from a course prior to successful completion. Demographic variables, admission and college science course grade point averages, and Nurse Entrance Test (NET) scores were collected on the sample population. Descriptive statistics were used to identify any unique differences that may have existed between the three groups, and multinomial logistic regression was used to determine the variables that best predicted success in the associate degree nursing program. Students in the passing group were found to be slightly older than students in the failing and withdrawing groups. The passing group had a higher percentage of females; the failing and withdrawing groups had higher percentages of males. The failing and withdrawing groups also contained higher percentages of minority students and students with English as a second language. Ethnicity was considered a significant predictor for student success in this study. Grade point average (GPA) score at the time of admission to the nursing program and college mean science course GPA scores were significant predictors. Students in the passing group had higher mean admission grade point averages than the failing and withdrawing groups. Students in the passing group also had noticeably higher mean grade point averages in all college science courses. NET scores were not considered significant predictors, at least for students who met the requirements for admission, and minimal differences were noted between the three groups in the study. The results of the study supported the use of variables identified in Tinto's Longitudinal Model of Dropout (1975) for predicting program success with nursing students. Individual attributes and pre-college experiences were predictors of student success for this sample, and demographic differences were identified between successful and unsuccessful students. Based on the results, the nursing department should consider placing more emphasis on admission and college science course grade point averages during the application process. A future conceptual model should include college science course GPAs, specifically anatomy and physiology and microbiology, and admission grade point average. Remedial or support services should be emphasized for minority students and students with English as a second language. Strategies should be implemented to retain men in the nursing program.
| Identifer | oai:union.ndltd.org:ucf.edu/oai:stars.library.ucf.edu:etd-1937 |
| Date | 01 January 2006 |
| Creators | Miles, Linda |
| Publisher | STARS |
| 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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