Health care professionals and nurse educators are concerned about increasing percentage of first time test takers failing the NCLEX-RN exam. The purpose of this retrospective study was to examine predictive accuracy of the Assessment Technologies Institute (ATI) RN Comprehensive Predictor for passing or failing the NCLEX-RN exam in a cohort of nursing students (N = 195). South Eastern Technical College in South Carolina is in jeopardy of losing accreditation for their nursing program because of the low percentage of first time test takers failing. The college's pass rate on the NCLEX-RN exam has been below the national and state averages for the last 2 years. Guided by Bloom's taxonomy and Knowles' andragogical model of learning as the theoretical mainstay, factors that predict success with the NCLEX-RN exam for first time test takers were examined. Inferential and descriptive statistics were used to determine if a relationship existed between NCLEX-RN scores and the independent variables. A Pearson r correlation test was conducted to address whether the ATI Comprehensive Predictor accurately predict student success with the NCLEX-RN exam on first attempt. Multiple regression was employed to test for a significant relationship between prenursing GPA, final GPA, age, gender, and ATI predictor scores. Regression analysis results showed ATI Predictor scores to significantly predict student success with the NCLEX-RN exam on first attempt. Based on findings, a Structured Learning Assistance program was proposed to assist in preparing students for NCLEX-RN success. Positive social change occurs within the community, nursing programs, and health care by increased NCLEX-RN pass rates enhancing the number of nurses entering into health care.
Identifer | oai:union.ndltd.org:waldenu.edu/oai:scholarworks.waldenu.edu:dissertations-2621 |
Date | 01 January 2015 |
Creators | Grant, Annie Ruth |
Publisher | ScholarWorks |
Source Sets | Walden University |
Language | English |
Detected Language | English |
Type | text |
Format | application/pdf |
Source | Walden Dissertations and Doctoral Studies |
Page generated in 0.0031 seconds