Rational Versus Empirical Prediction of Nursing Student Success

Undergraduate and graduate nursing education programs can offer a very limited number of positions to a very large number of student applicants. Although practices vary widely across schools of nursing, it is common in many programs to use rational or holistic judgment when determining which student applicants to admit. The present applied study demonstrates a method and several examples of alternative selection models that can improve administrators' ability to efficiently and effectively identify student applicants with the highest probability of success. The example models are also tested within a sample of students (N = 283) from a very active bachelor of science in nursing program, and recommendations for use are provided. Results clearly support the use of admission formula scores generated from regression-based methods versus admission formula scores generated from a typical rational points-based method of weighting applicant admission criteria.