Comparing Grade Point Averages and Standardized Test Scores as Predictors of Successful Completion of Undergraduate Baccalaureate Programs

Intro: Aging population demographics contribute greatly to an unprecedented nursing shortage as many aging RNs are predicted to retire when the demand is highest (Buerhaus, Staiger, & Auerbach, 2000). Replacing those RNs will be very difficult because more than half of current nursing faculty will retire by 2021 (Aiken, 2011). Currently, nursing faculty members serving on admission committees struggle with deciding “how to” identify the best applicants who are most likely to graduate and achieve licensure-on time. This presentation will focus on sharing the quantitative data from one school collected over several years to highlight the importance of testing assumptions. Many surprise discoveries along the way were vital in informing admission policies and practices.

Background:  In the past, Grade Point Average (GPA) was considered a good predictor of success but recent history has failed to uphold that assumption in many cases. Students with pre-admission GPAs of 3.5-4.0/4.0 were sometimes noted to be poorly prepared for the rigors of nursing education and were ultimately unsuccessful despite strong GPAs. Although GPA provides information about earlier academic success, it is not consistently reliable in predicting success in undergraduate baccalaureate nursing programs. In recent years, a number of proprietary companies have begun to offer standardized testing instruments as another quantitative method of predicting success. However, it was not always clear how and when to use the testing instruments or how the varied company products performed against one another. Schools of nursing developed relationships with testing companies in hopes of improving admission decisions and NCLEX readiness. Assessment Technologies Institute (ATI) was the company whose testing products were adopted at the study site.

Problem statement: During competitive applicant cycles, only about half of qualified students could be admitted due to capacity limitations including shortages of faculty, clinical sites, and classroom space. Despite a careful review of applicant academic history and entrance examinations, many students (up to 1/3) were not able to successfully complete the nursing program at the research site, a Midwestern US BSN program. Some schools report completion rates of only 50% (Peterson, 2009; Seago, Wong, Keane, & Grumbach, 2008).  

Review of Literature: Although several qualitative and quantitative studies have been published about academic predictors of success in schools of nursing, little empirical research is represented (Kenny, 2010). We know that qualitative social factors such as stable emotional and financial support make a huge difference in educational persistence in college students of any major. The rigorous demands of the nursing major require these and more, including but not limited to skills in managing time, stress, studying, and test taking.  Generalizability of predictive admission nursing education research has been very limited due to inconsistent definitions of terms and variations in pre-requisite course work, program length, content delivery methods, and overall curricula. Because most of the unsuccessful students will exit a nursing program within the first year, and 83% of those will leave during the first semester, early predictors of persistence and success are needed (Peterson, 2009).

Methodology: A descriptive, non-experimental retrospective study of extant data compared admission GPAs against standardized test scores taken before and during the program of BSN study. Hypotheses were developed and data were collected at three data points in time on each student. Data collection points included the start of the program, halfway through, and finally at the end of the two year nursing program. Simple descriptive statistics, multiple regressions and T tests were run and analyzed.

Results: Grade point averages and standardized testing scores were both predictive of student outcomes. However, the significance of standardized test scores were statistically superior in contrast to GPA findings. The preadmission TEAS composite score, science, and reading scores were strong predictors of success but of these, TEAS science scores best correlated with positive and negative student outcomes. Supporting literature has been published by Wolkowitz and Kelley (2010).

Discussion:  It’s time to critically question the validity and reliability of grade point average as a quantitative variable. Because GPA is based on course grades and course grades are based on unlimited possible variations within and across schools, it becomes apparent that without valid and reliable components, GPAs are not the best predictors of nursing success. Although GPAs should be noted as measures of previous academic achievement, they are not reliable predictors of future academic success in nursing. Traditional measures such as grade point average (GPA) are not standardized and fail to capture the evidence of the students’ competency with important pre-requisite content.

Limitations: Confounding variables included changes in leadership, faculty turnover, NCLEX test plan revisions, curriculum changes, and the availability of student support services over the time period covered by the study. No demographic or qualitative data were collected intentionally which may have influenced outcomes.

Recommendations: More quantitative studies are needed to provide the evidence base upon which to build admission policies. Replication studies will allow for greater generalizability and meaningful future meta-analyses.  Each school of nursing should establish an ongoing local data base for primary and secondary analyses alone or in combination with similar schools. Graduation yields will likely improve through the use of data driven processes helping close the looming supply and demand discrepancies of RNs in the future.

References

Aiken, L. H. (2011). Nurses for the Future. New England Journal of Medicine, 364(3),        

              196-198.

Buerhaus, P.I., Staiger, D.O., & Auerbach, M.S. (2000). Implications of an aging

              registered nurse workforce. Journal of the American Medical Association,

              283(22), 2948-2954. doi: 10.1001/jama.28322.2948

Kenny, C. J. (2010). Meta-analysis of entrance standards for undergraduate nursing

              and selected allied health programs. (Unpublished doctoral dissertation). Kent

              State University, Kent, OH.

Peterson, V.M. (2009). Predictors of academic success in first semester baccalaureate

              nursing students. Social Behavior and Personality 37(3), 411-418. doi

              10.2224/sbp.2009.37.3.411

Seago, J. A., Wong, S. T., Keane, D., & Grumbach, K. (2008). Measuring attributes of

              Success of college students in nursing programs: A psychometric analysis.

              Journal of Nursing Measurement, 16(3), 184-200.

Wolkowitz, A., and Kelley, J. A. (2010). Academic predictors of success in a nursing program.      Journal of Nursing Education, 49(9