Admission Variables as Predictor of Success in an Associate Degree Nursing Program

Admission Variables as Predictor of Success in an Associate Degree Nursing Program PDF Author: Lorraine LeHew Hultquist
Publisher:
ISBN:
Category : Nursing schools
Languages : en
Pages : 270

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Admission Variables as Predictor of Success in an Associate Degree Nursing Program

Admission Variables as Predictor of Success in an Associate Degree Nursing Program PDF Author: Lorraine LeHew Hultquist
Publisher:
ISBN:
Category : Nursing schools
Languages : en
Pages : 270

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Book Description


Admission Variables as a Predictor of First Semester Student Success

Admission Variables as a Predictor of First Semester Student Success PDF 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.

Predicting Tirst Term Success in an Associates Degree Nursing Program Using Cognitive and Noncognitive Factors

Predicting Tirst Term Success in an Associates Degree Nursing Program Using Cognitive and Noncognitive Factors PDF Author: Richard Hilton Turner
Publisher:
ISBN:
Category : Academic achievement
Languages : en
Pages : 125

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Book Description
Since the late 1990s the nursing field has experienced increased demand for RN’s as well as a number of internal and external factors that have worsened this problem. College admissions officers have struggled to identify those students who are most likely to persist in an associate degree nursing (ADN) program. Estimates of programmatic attrition vary, but fall somewhere between 25-50%. A great deal of research has been expended in an attempt to determine which preadmission variables are most likely to indicate programmatic success. Unfortunately, no “best set” of admissions variables has been identified. The purpose of this research was to identify cognitive and noncognitive predictors of success in an ADN program. These variables can then be used by nursing program administrators to help identify students during the admissions phase who are most likely to persist through the first term and potentially to degree completion. Bloom’s theory of school learning serves as the theoretical framework for this research. The participants in this study were 188 students (summer and fall cohorts) in the Associate of Science in Nursing (ASN) program at a large state college in the southeastern region of the United States. The research design was a quantitative, non-experimental, correlational design to predict the relationship between four input predictor variables and one criterion variable. The Health Education Systems Inc A2 assessment (HESI A2) and the Grit-S Scale were used to measure these input variables. Binary regression was used to analyze the resulting data. This research is critical in addressing nursing shortfalls, a pressing real world problem facing society at large, nursing in general, and college admissions departments for ADN programs in particular.

Evaluation of Admission Criteria as Predictor for Success in the First Semester of an Associate Degree in Nursing Program

Evaluation of Admission Criteria as Predictor for Success in the First Semester of an Associate Degree in Nursing Program PDF Author: Ludivina R. Cometa
Publisher:
ISBN:
Category : Nursing
Languages : en
Pages : 0

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Book Description
Attrition in the first semester of an ADN program tends to be high and remains a concern for nursing program administrators. Most unsuccessful students in nursing programs leave in the first or second semesters; therefore, studies are needed focused on this early part of ADN programs. One of the challenges for the admissions committee is to determine which admission criteria lead to student success. Nursing schools should choose applicants with the academic aptitude that can meet the demands of rigorous nursing coursework. The purpose of this descriptive correlational study was to evaluate the current admission criteria for a private, nonprofit college's ADN program and determine which criteria correlate with students' success in the first semester. Why some students fail the initial course, Fundamentals of Nursing (NUR101), is an important area of research. Analysis of admission criteria was conducted to determine the predictors of student success in this early part of the ADN program. This study used descriptive and inferential statistics to analyze the data. The independent variables were students' pre-nursing GPA, math grades, science grades, composite score on the TEAS V standardized nursing admission examination, and the college's selection point system (SPS). Also, student's demographic information: gender, age, marital status, student status (full-time/part-time), employment status (working/not working), household income, and prior degree (whether or not a student has an associate degree or higher) were included in the IV's. The dependent variable is the student's final grade in the first semester course of the ADN program. A nonprobability convenience sampling of 130 students comprised two cohorts of first-semester ADN students in the fall 2015 and spring 2016 semesters. The current admission criteria found significant were: Math Grade (p = .041), college GPA (p = .001), and Selection Point System (p =

Variables that Predict Success with Associate Degree Nursing Students at a Community College in Florida

Variables that Predict Success with Associate Degree Nursing Students at a Community College in Florida PDF 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.

Pre- and Post-admission Criteria as Predictors of Academic Success in an Associate Degree Nursing Program

Pre- and Post-admission Criteria as Predictors of Academic Success in an Associate Degree Nursing Program PDF Author: Nancy Lee Conzett Muecke
Publisher:
ISBN:
Category : Academic achievement
Languages : en
Pages : 0

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Identifying Predictor Variables for Success on NCLEX-RN in an Associate Degree Nursing Program

Identifying Predictor Variables for Success on NCLEX-RN in an Associate Degree Nursing Program PDF Author: Jill Lynette Keyser
Publisher:
ISBN:
Category :
Languages : en
Pages : 186

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Admissions Predictors of Success of Returning Nursing Students in a Baccalaureate Degree Nursing Program

Admissions Predictors of Success of Returning Nursing Students in a Baccalaureate Degree Nursing Program PDF Author: Linda Margaret Perry
Publisher:
ISBN:
Category :
Languages : en
Pages : 158

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Models for Predicting Academic Success and State Board Scores for Associate Degree Nursing Students

Models for Predicting Academic Success and State Board Scores for Associate Degree Nursing Students PDF Author: Carolyn W. Jones
Publisher:
ISBN:
Category : Associate degree nurses
Languages : en
Pages : 212

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Relationship of Admission Variables to Success for Licensed Practical Nurses in Associate Degree in Nursing Ladder Program

Relationship of Admission Variables to Success for Licensed Practical Nurses in Associate Degree in Nursing Ladder Program PDF Author: Sally Kathryn Johnson
Publisher:
ISBN:
Category : Nursing
Languages : en
Pages : 228

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