Predicting early academic achievement in a baccalaureate nursing program.
Baccalaureate nursing programs are under increased pressure to graduate greater numbers of students to meet the demands of the nurse workforce of the future. Schools of nursing are admitting larger cohorts of students, but early academic achievement in the nursing major and retention are problematic. Historical predictors of early academic achievement, such as scholastic aptitude, may not be the best for identifying students at risk of early academic failure. Increasingly, baccalaureate nursing programs are relying on standardized nursing aptitude tests to evaluate the readiness of applicants for the nursing major. However, reliable predictors of early academic achievement have yet to be identified. The purpose of this study was to explore whether scholastic aptitude and nursing aptitude are predictive of early academic achievement in a baccalaureate nursing program. Using an exploratory descriptive design, data from 164 sophomore nursing students were examined. The data indicated that scholastic aptitude and nursing aptitude together predicted 20.2% of the variance in early academic achievement, with scholastic aptitude accounting for 15.4% of the variance.
Newton
Sarah E
SE
Oakland University School of Nursing, Rochester, MI 48309, USA.
Smith
Laureen H
LH
Moore
Gary
G
Magnan
Morris
M
D000124:Achievement; D000704:Analysis of Variance; D001077:Aptitude Tests / Q000592:standards*; D004508:Education, Nursing, Baccalaureate; D004521:Educational Measurement / Q000379:methods* / Q000592:standards; D004522:Educational Status; D005260:Female; D006301:Health Services Needs and Demand; D006801:Humans; D008297:Male; D008433:Mathematics; D015146:Midwestern United States; D015402:Nursing Education Research; D011237:Predictive Value of Tests; D011594:Psychometrics; D011932:Reading; D012044:Regression Analysis; D012570:School Admission Criteria; D012586:Science / Q000193:education; D013332:Student Dropouts; D013338:Students, Nursing / Q000523:psychology / Q000706:statistics & numerical data