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Standardized Computer-Based Tests as Predictors of Completion of an Associate of Science in Nursing Curriculum and NCLEX-RN Success or Failure

Saturday, 29 October 2011: 3:35 PM

Patsy Fasnacht, PhD, RN, CNE1
Cheryl Grab, MSN, RN1
Sandra Zerby, PhD2
(1)Division of Nursing, Lancaster General College of Nursing and Health Sciences, Lancaster, PA
(2)Enrollment Management, Lancaster General College of Nurisng and Health Sciences, Lancaster, PA

Learning Objective 1: examine the role of computer based standardized assessments in predicting successful completion of an Associate Degree Nursing Curriculum.

Learning Objective 2: explore the use of computer based standardzed assessments in predicting success or failure on the NCLEX-RN.

Purpose:  The purpose of this study was to identify predictors of successful graduation and NCLEX-RN passage rates for Associate Degree Nursing students (N = 464). This is a retrospective analysis of existing student records of all students enrolled in an Associate Degree Nursing Program between 2005 and 2007. 

Methods: Data were collected from paper records, computerized student records, and Assessment Technologies Institute (ATI) student assessment results and combined into one data set for analysis.  Binary logistic regression analysis was used to determine variables that would significantly predict program completion and NCLEX-RN passage.

Results: The final predictive model for program success vs. voluntary/involuntary attrition was statistically significant chi square (5, n = 464) 28.163, p =<.001 indicating that the model was able to distinguish between those who completed the program (graduated) and those who did not (voluntary or involuntary attrition). Significant variables in the model include the Test of Essential Academic Skills, the years from high school graduation to entrance in the first nursing course and the total number of transferred credits to be the strongest predictors of program completion.  

The final model for ATI assessments as predictors of NCLEX-RN passage rates includes two variables, the Leadership Assessment scores and the Medical Surgical Assessment scores and is statistically significant, chi square (5, n = 324) = 29.176, p =<.001 indicating that the model is able to distinguish between those who passed and did not pass the NCLEX-RN.

Conclusions: Standardized computer based tests are useful as predictors of program completion and NCLEX-RN success or failure.  Traditional methods of evaluating applicants for admission, Scholastic Achievement Test scores, high school grade point average, and class rank are not significant predictors of success or failure.

Funding: This research was funded by a grant from Sigma Theta Tau International and ATI.

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