Literature DB >> 23586200

Predictor variables for NCLEX-RN readiness exam performance.

Elizabeth B Simon1, Shawn P McGinniss, Beatrice J Krauss.   

Abstract

AIM: To understand the relationship among NLCLEX-RN readiness exam scores and influencing variables.
BACKGROUND: First-time NCLEX-RN pass rates are a visible measure of program quality.Therefore, schools have adopted aggressive prediction and remediation measures to improve NCLEX-RN pass rate success and therefore the number of licensed and practicing nurses.
METHOD: This descriptive correlational study used regression analysis to investigate multivariate relationship between NCLEX-RN readiness exam scores and predictors.
RESULTS: This study's findings suggest that while the input variables measured by grades in prerequisites initially appear predictive, only the presence of transfer credits, a potential marker for age and motivation, remains significant.
CONCLUSION: Most transfer students are nontraditional adult learners.Therefore, it can be theorized that student personal system has a significant impact on the outcome. The first nursing course, adult health nursing plus maternal-child health nursing, appears foundational for the NCLEX readiness exam.

Entities:  

Mesh:

Year:  2013        PMID: 23586200     DOI: 10.5480/1536-5026-34.1.18

Source DB:  PubMed          Journal:  Nurs Educ Perspect        ISSN: 1536-5026


  4 in total

1.  Developing a Social Determinants of Learning™ Framework: A Case Study.

Authors:  Carla D Sanderson; Linda M Hollinger-Smith; Karen Cox
Journal:  Nurs Educ Perspect       Date:  2021 Jul-Aug 01

2.  Students' Midprogram Content Area Performance as a Predictor of End-of-Program NCLEX Readiness.

Authors:  Jennifer A Brussow; Michelle Dunham
Journal:  Nurse Educ       Date:  2018 Sep/Oct       Impact factor: 2.082

3.  Quantitative evaluation of variables to student success in a mastery learning baccalaureate nursing programme.

Authors:  Marie Rolf; Margaret Kroposki; Susan Watson
Journal:  Nurs Open       Date:  2019-04-07

4.  Assessment of determinants predicting success on the Saudi Nursing Licensure Examination by employing artificial neural network.

Authors:  Vincent Edward Butcon; Eddieson Pasay-An; Maria Charito Laarni Indonto; Liza Villacorte; Jupiter Cajigal
Journal:  J Educ Health Promot       Date:  2021-10-29
  4 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.