Teaching and Learning in Nursing
Volume 2, Issue 3 , Pages 80-84 , July 2007

The predictive accuracy of Health Education Systems, Inc., examinations for associate degree nursing students

  • Mary J. Yoho, PhD, RN

      Affiliations

    • Elsevier Review and Testing, Houston, TX 77042, USA
    • Tomball College, Tomball, TX 77375, USA
    • Corresponding Author InformationCorresponding author. 11011 Richmond Avenue, Suite 450, Houston, TX 77042, USA. Tel.: +1 713 346 6913 (office); fax: +1 713 346 6977.
  • ,
  • Anne Young, EdD, RN

      Affiliations

    • Texas Woman's University, College of Nursing, Houston, TX 77030, USA
  • ,
  • Carolyn Adamson, PhD, RN

      Affiliations

    • Texas Woman's University, College of Nursing, Houston, TX 77030, USA
  • ,
  • Robin Britt, EdD, RNC, WHCNP

      Affiliations

    • Texas Woman's University, College of Nursing, Houston, TX 77030, USA

References 

  1. Briscoe V, Amena M. The relationship of academic variables as predictors of success on the National Council Licensure Examination for Registered Nurses (NCLEX-RN) in a selected associate degree program. The Association of Black Nursing Faculty Journal. 1999;10(4):80–84
  2. Cloud-Hardaway S. Relationship among “Mosby's Assess Test” scores, academic performance, and demographic factors and associate degree nursing students. Dissertation Abstracts International. 1988;49(07):2567B;[UMI No. 8817018]
  3. Collins P. Predicting a passing outcome on the National Council Licensure Examination for Registered Nurses by associate degree graduates. Dissertation Abstracts International. 2002;64(01):142B;[UMI No. 3077374]
  4. Daley L, Kirkpatrick B, Frazier S, Chung M, Moser D. Predictors of NCLEX-RN success in a baccalaureate nursing program as a foundation for remediation. Journal of Nursing Education. 2002;42(9):390–398
  5. Drake C. The predictive validity of selected achievement variables relative to a criterion of passing or failing the National Council Licensure Examination (NCLEX) for nursing students in a two-year associate degree program. Dissertation Abstracts International. 1996;57(01):182A;[UMI No. 9614016]
  6. Gallagher PA, Bomba C, Crane L. Using an admissions exam to predict student success in an ADN program. Nurse Educator. 2001;26(3):132–135
  7. Haas R, Nugent K, Rule R. The use of discriminant function analysis to predict students' success on the NCLEX-RN. Journal of Nursing Education. 2004;43(10):440–446
  8. Hardin, J. (2005). Predictors of success on the National Council Licensing Examination Computerized exam (CAT-NCLEX-RN) in associate degree nursing programs: A logistic regression analysis. Unpublished doctoral dissertation. Texas A&M University, Commerce.
  9. Higgins B. Strategies for lowering attrition rates and raising NCLEX-RN pass rates. Journal of Nursing Education. 2005;44(12):541–547
  10. Johnson A. Panel urges revamp of nursing schools. Retrieved December 28, 2006, from www.nursezone.com2003;
  11. Lauchner K, Newman M, Britt R. Predicting license success with a computerized comprehensive nursing exam: The HESI Exit Exam. Computers in Nursing. 1999;17(3):120–128
  12. Lewis C. Predictive accuracy of the HESI Exit Exam on NCLEX-RN pass rates and effects of progression policies on nursing student exit exam scores. Dissertation Abstracts International. 2005;66(11):154B;[UMI No. 3195986]
  13. Milan C. Identifying predictors of performance for the associate degree graduate nurse on the National Council Licensure Examination for Registered Nurses. Dissertation Abstracts International. 1997;58(08):4143B;[UMI No. 980575]
  14. Morrison S, Adamson C, Nibert A, Hsia S. HESI exams: An overview of reliability and validity. CIN: Computers, Informatics, Nursing. 2004;22(4):220–226
  15. Morrison S, Nibert A, Flick J. Critical thinking and test item writing. 2nd ed.. Houston, TX: Health Education Systems, Inc; 2006;
  16. National Council of State Boards of Nursing . NCLEX statistics from NCSBN. Retrieved December 28, 2006, from http://www.ncsbn.org/461.htm2006;
  17. National Council of State Boards of Nursing . NCLEX statistics from NCSBN. Retrieved January 3, 2007, from http://www.ncsbn.org/Reliability.pdf2007;
  18. Newman M, Britt R, Lauchner K. Predictive accuracy of the HESI Exit Exam: A follow-up study. Computers in Nursing. 2000;18(3):132–136
  19. Nibert A, Young A. A third study on predicting NCLEX success with the HESI Exit Exam. Computers in Nursing. 2001;19(4):172–178
  20. Nibert A, Young A, Adamson C. Predicting NCLEX success with the HESI Exit Exam: Fourth annual validity study. CIN: Computers, Informatics, Nursing. 2002;20(6):261–267
  21. Percoco T. Variables predictive of program and NCLEX success for associate degree nursing students. Dissertation Abstracts International. 2001;62(08):3358B;[UMI No. 3023360]
  22. Swenty C. Use of the RNEE, ACT, and grades as predictors of success in associate degree nursing programs. Masters Abstracts International. 1998;36(05):1333;[UMI No. 1389177]
  23. U.S. Department of Labor . Occupations with the largest job growth, 2004–2014. Retrieved December 28, 2006, from http://www.bls.gov/emp/emptab3.htm2005;

PII: S1557-3087(07)00036-4

doi: 10.1016/j.teln.2007.04.004

Teaching and Learning in Nursing
Volume 2, Issue 3 , Pages 80-84 , July 2007