Research Design For Predicting Nursing Students’ Success

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Research Design for Predicting Nursing Students’ Success on the NCLEX-RN Exam

Choosing a research design is a fundamental procedure in maintaining rigor, validity, and applicability of a study. In the proposed study where the researcher aims to investigate the strength of the relationship between GPA, ATI Predictor scores, and NCLEX-RN exam scores with the success of nursing students on the NCLEX-RN board exam at the first attempt, a quantitative, correlational, predictive design is the best option. This method will enable the systematic analysis of quantifiable variables and their correlations, which is consistent with the main objective of the study to determine predictors of first-time NCLEX-RN success.

Rationale for the Chosen Design

Correlational research involves the study of the relationship between two or more measurable variables without controlling them, which is particularly appropriate in nursing education studies. Flowers et al. (2022) discovered that GPA and standardized predictor scores, such as the ATI Predictor, are robust academic predictors of first-time NCLEX-RN outcomes. Their results emphasize the importance of correlational designs in detecting at-risk students and informing readiness interventions. Likewise, Kirwan (2018) used a predictive correlational design to investigate the connection between achievement emotions and academic performance of nursing students, proving the practicality of predictive analytics in learning studies. Simon (2011) further asserted that predictive designs are especially effective in situations where the aim is not to determine causation but to approximate the probability of events, which clearly fits in the objective of the current study.

Appropriateness to the Research Questions

The suggested research questions will involve examining variations in predictive power, the joint influence of GPA and ATI scores, and how threshold scores affect NCLEX-RN outcomes. The predictive correlational design enables you to answer these questions using statistical models like regression and logistic regression. Flowers et al. (2022) particularly observed the applicability of predictor scores to reinforce the prediction of exam results, which substantiates the emphasis on combined and threshold effects. The analysis by Kirwan (2018) continues to demonstrate that correlational techniques can help identify subtle relationships between several academic variables, which supports the suitability of this design in studying the interactions between GPA and ATI Predictor scores.

Considerations in the Decision-Making Process

The choice to adopt this design was based on both methodological and practical considerations. Flowers et al. (2022) highlighted the legitimacy of academic measures, including GPA and standardized exam scores, as predictors, as they are quantifiable, objective, and ethically accessible. Kirwan (2018) made an argument that correlational predictive designs are suitable when researcher cannot manipulate variables but can still find meaningful association that can inform practice. Moreover, Simon (2011) characterized predictive analytics as a vital program evaluation instrument that educators may use to develop interventions that can enhance student achievements. Combined, these views show that the selected design is both methodologically sound and practically applicable to the nursing education domain.

Challenges in Selecting the Design

Even though predictive correlational designs are suitable, they carry some challenges. Flowers et al. (2022) warned that unpredictability in predictor scores might complicate the accuracy of threshold analysis, and that substantial sample sizes are needed to ensure credible results. Kirwan (2018) reported that low sample sizes may undermine the power of statistical tests, and correlational studies may not produce strong conclusions. Simon (2011) also highlighted that predictive designs are vulnerable to misinterpretation when correlations are presented as causal and that researchers need to frame their findings carefully to stakeholders. These challenges must be addressed in ensuring that the study results become valid and meaningful.

Conclusion

In conclusion, the most suitable study design in this case is a quantitative, correlational, predictive study since it enables the researcher to analyse measurable variables, develop predictive models, and aligns with the applied objectives of enhancing nursing education outcomes. Despite the necessity to overcome the challenges posed by the need to avoid causal inference and adequate sample sizes, this design offers the methodological background to respond to the research questions effectively. Finally, the evidence-based interventions informed by this research can be used to help nursing students pass the NCLEX-RN.

References

Flowers, M., Olenick, M., Maltseva, T., Simon, S., Diez-Sampedro, A., & Allen, L. R. (2022). Academic factors predicting NCLEX-RN success. Nursing Education Perspectives, 43(2), 112–114. https://doi.org/10.1097/01.NEP.0000000000000893

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