Conceptual Model for Predicting Academic Success in Prelicensure Nursing Programs Through Expanded Cognitive Aptitude Assessment

An evaluation of nursing students' learning self-efficacy: A multi-dimensional instrument development and structural validation

BACKGROUND

Nursing learning self-efficacy (NLSE) is essential in nursing students' learning, and since it is a task-dependent construct, accurate measurements require a multidimensional instrument.

OBJECTIVE

This research aimed to develop and validate a multidimensional NLSE instrument to measure Taiwanese nursing students' views of nursing learning self-efficacy.

DESIGN

The cross-sectional study design was used for this investigation.

PARTICIPANTS

The study included 1143 nursing students from a nursing junior college.

METHODS

To assess the validity and reliability of the instrument's factors, exploratory factor analysis (EFA) and confirmatory factor analysis (CFA) were utilized. Conceptual understanding, higher-order cognitive skills, practical work, everyday application, and nursing communication were identified as five factors. A comparison of five proposed models was also conducted.

RESULTS

The study found that the correlated and one-factor second-order models were acceptable and provided a simple structure for evaluating nursing students' perceptions of NLSE. Furthermore, a specific model with two second-order scales (Cognition and Application) and one first-order scale (nursing communication) was identified, highlighting the crucial role of nursing communication in nursing students' self-efficacy.

CONCLUSIONS

Evaluating nursing students' learning self-efficacy using a valid and reliable instrument is crucial for understanding their learning confidence. The creation of such a scale constitutes the primary contribution of this study.

Predictors of attrition and program dismissal in a nursing major

BACKGROUND

Increasing the representation of nurses and other health professionals from minority populations is one way to address health disparities. The purpose of this study was to investigate nursing admission criteria that predicted first, second, third semester attrition and program dismissal.

METHOD

A retrospective secondary data analysis was conducted on existing student records spanning from 2016 to 2020 in one BSN program from a Hispanic-serving institution to gain an understanding about program attrition and dismissal. A total of n = 349 student records were included in the analysis.

RESULTS

Pre-nursing science GPA, pre-nursing college GPA, and reading ability were found significant predictors for attrition and dismissal, respectively.

CONCLUSIONS

Aptitudes in the sciences and in reading should be emphasized in pre-nursing to enhance student success in nursing. Findings from this study could inform administrators in postsecondary and in secondary education about establishing infrastructures for at-risk students to better prepare the latter for a nursing major.

Do GPAs, Entrance Exams, or Course Grades Predict Outcomes in First Semester Nursing Students?

BACKGROUND

Previous studies employed varying methods, predictors, and endpoints to determine how to best predict student success.

PURPOSE

This study examined current admission criteria in predicting nursing students' success during two first semester courses.

METHODS

Grade point averages and Health Education Systems Incorporated entrance exam scores were extracted from student files while pre-nursing pathophysiology grades from electronic gradebooks were used as independent variables. A principal component analysis confirmed three components: Academic performance, logical/mathematical intelligence, and verbal/linguistic intelligence. Multiple regressions were performed using first semester nursing course grades as dependent variables.

RESULTS

A multiple regression using Pharmacology course grades as the dependent variable (R2 = 0.268, p ≤0.001) was more predictive than a regression using Concepts course grades as the dependent variable (R2 = 0.177, p ≤0.001). Bivariate analyses revealed that each independent variable significantly predicted Concepts course grades and all except math and reading scores predicted Pharmacology course grades.

CONCLUSIONS

Pathophysiology was a better predictor of both dependent variables. A high degree of shared variance necessitated bivariate analyses to elucidate the importance of each independent variable. Pharmacology course grades proved better predictors of success by the independent variables than Concepts course grades.