Models For Predicting Academic Success And State Board Scores For Associate Degree Nursing Students

Author : Linda Lisa Esper
Publisher :
ISBN 13 :
Total Pages : 172 pages
Book Rating : 4.:/5 (464 download)

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Download or read book Admission Variables as a Predictor of First Semester Student Success written by Linda Lisa Esper and published by . This book was released on 2009 with total page 172 pages. Available in PDF, EPUB and Kindle. Book excerpt: The current national shortage of practicing registered nurses is exacerbated by an accompanying shortage of nurse educators, which limits program enrollments in Associate Degree Nursing (ADN) programs. Relatively low available enrollment in nursing programs is coupled with a national first year retention rate of 64% (National League for Nursing Accrediting Commission [NLNAC], 2008), which leaves ADN educational leaders struggling to find improved ways to increase graduation rates through better identification of qualified applicants. This exploratory, action research study examined commonly used ADN admission criteria in order to identify those indicators which best predict students' first semester success at a small private northeastern United States college. The predictive ability of common ADN admission variables (TEAS scores in the areas of math, science, and English; overall TEAS score; age; gender; and math, science, and English course grades) was determined with regard to student success outcome variables (medication/math exam grade, Nurse Fundamental course grade, Nurse Health Assessment course grade, and Assessment Technology Institute [ATI] Nursing I Fundamental Content Mastery Series scores). Using an exploratory, action research design, data from 120 freshman nursing students were examined to assess the relative contributions of each of the predictor variables on forecasting students' first semester success. The study's methodology involved a simple correlation and regression analysis of the data. Selected Admission's variables were shown to be correlated to certain outcome variables. These Admission's variables included, the TEAS overall score, the last science course grade on admission (ACGs), the TEAS score in English, and the student's last earned English course on admission (ACGe). Only the TEAS total score showed correlation with success over a broad range of success score, i.e. ATIs, FUNg, and HAg. Overall, it was concluded that the ability of the admission variables to predict a specific score on student outcome assessment was weak. As a result of this study, the college's Admission office and nursing department will use the information to modify Admission's policies, develop pre-admission workshops, and continue to implement program initiatives to further support student success in an ADN nursing program. Further studies are warranted in order to assist other colleges in determining the level of academic qualifications most desirable in selecting students capable of success in their ADN nursing program.