Predictors of Academic Success in Associate Degree Nursing PDF Download
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Author: Joyce I. Lyford
Publisher:
ISBN:
Category : Nursing
Languages : en
Pages : 74
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Book Description
Author: Joyce I. Lyford
Publisher:
ISBN:
Category : Nursing
Languages : en
Pages : 74
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Book Description
Author: Nancy Lee Conzett Muecke
Publisher:
ISBN:
Category : Academic achievement
Languages : en
Pages : 0
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Book Description
Author: Linda Sheffield Miles
Publisher:
ISBN:
Category : College dropouts
Languages : en
Pages : 126
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Book Description
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.
Author: Lloyd Robert Pierson
Publisher:
ISBN:
Category : Nurses
Languages : en
Pages : 222
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Book Description
Author: Dolores Brown
Publisher:
ISBN:
Category : Predictors of scholastic success
Languages : en
Pages : 280
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Book Description
Author: Linda Lisa Esper
Publisher:
ISBN:
Category : Nurses
Languages : en
Pages : 172
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Book Description
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.
Author: Kathy A. Manning
Publisher:
ISBN: 9781109819571
Category :
Languages : en
Pages : 77
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Book Description
The growing nursing shortage will call for accessible and flexible nursing education. Online learning, uniquely at the associate degree nursing level, can provide nursing education without the barriers of the traditional classroom. Selecting appropriate applicants for success in the online environment is critical. The purpose of this study was to determine pre-admission predictors of success in the first and second semester nursing courses among online associate degree nursing students. Stepwise multiple regression analysis explored academic skills, learning style preferences, and personal habits for their contribution to academic success in 202 online nursing students. A composite score of the Test of Essential Academic Skills instrument by Assessment Technologies Institute (ATI), LLC, predicted success. Utilizing ATI's Self Assessment Inventory instrument, there were no positive correlations between learning styles and personal habits and nursing course success. A lesser important negative relationship was an individual learning style preference and second semester nursing course success.
Author:
Publisher:
ISBN:
Category : Dissertations, Academic
Languages : en
Pages :
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Author: Tabitha Anderson Service
Publisher:
ISBN:
Category :
Languages : en
Pages :
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Author: Carol A. Velas
Publisher:
ISBN:
Category : Nurses
Languages : en
Pages : 118
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Book Description
This research addresses the larger social context of a nursing shortage and the supply of registered nurses. This quantitative, correlational, predictive design has explored the use of prerequisite coursework grade point average, and the Test of Essential Academic Skills (TEAS) sub scores in English, math, reading, and science to predict retention in the first semester, program completion, and mastery of the National Council Licensure Exam.
