HESI Admission Assessment Scores: Predicting Student Success

Chen, Susie; Voyles, Denise

doi:10.1016/j.profnurs.2012.06.008

Cited by 13 publications

(4 citation statements)

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“…A plethora of studies evaluated combinations of factors related to nursing student success although no studies were found using the combination of predictors of success in a MLA, Bachelor of Science in Nursing (BSN) programme. (Chen & Voyles, 2013;Cherkis & Rosciano, 2015;Shulruf, Wang, Zhao, & Baker, 2011).…”

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confidence: 99%

Quantitative evaluation of variables to student success in a mastery learning baccalaureate nursing programme

2019

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Aim This study evaluated the relationship of student input and throughput variables in a mastery learning baccalaureate nursing programme to licensure success. Design This study used a quantitative, correlational design. Methods Retrospective analysis of records of 367 graduates over a 6‐year period tested the relationship of pass rate on the licensing examination to six variables: overall pre‐admission grade point average, entrance assessment scores, interview scores, remediation, programme length and exit assessment using point‐biserial correlations, and chi‐square analysis and logistic regression analysis. Results Overall pre‐admission grade point average, entrance assessment scores, interview scores and exit assessment scores were positively correlated with student success. Although remediation and programme length were not correlated with success, 87% of the students participated in remediation. Most students (95%) successfully passed the Registered Nurse licence examination on their first attempt. While specific criteria were related to student success, further research is needed to determine the role of remediation.

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Quantitative evaluation of variables to student success in a mastery learning baccalaureate nursing programme

2019

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“…The element most often pointed out to is the fact that assessment systems vary greatly at universities that offer studies of the first degree in the area of objective tools that help evaluate knowledge and skills of students. This diversity in evaluation systems in different educational institutions, particularly in the area of applying standardised evaluation method may contribute to the low level of reliability of the qualification process for candidates when this criterion is applied [ 56 ]. Bearing that fact in mind, GPA may be recommended as a criterion for acceptance, however, it ought to be complemented by another criterion (other criteria), preferably standardized ones, such as entrance examination and/or interview.…”

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Evidence-based selection process to the Master of Public Health program at Medical University

et al. 2017

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BackgroundEvaluation of the predictive validity of selected sociodemographic factors and admission criteria for Master’s studies in Public Health at the Faculty of Health Sciences, Medical University of Warsaw (MUW).MethodsFor the evaluation purposes recruitment data and learning results of students enrolled between 2008 and 2012 were used (N = 605, average age 22.9 ± 3.01). The predictive analysis was performed using the multiple linear regression method. In the proposed regression model 12 predictors were selected, including: sex, age, professional degree (BA), the Bachelor’s studies grade point average (GPA), total score of the preliminary examination broken down into five thematic areas. Depending on the tested model, one of two dependent variables was used: first-year GPA or cumulative GPA in the Master program.ResultsThe regression model based on the result variable of Master’s GPA program was better matched to data in comparison to the model based on the first year GPA (adjusted R2 0.413 versus 0.476 respectively). The Bachelor’s studies GPA and each of the five subtests comprising the test entrance exam were significant predictors of success achieved by a student both after the first year and at the end of the course of studies.ConclusionsCriteria of admissions with total score of MCQs exam and Bachelor’s studies GPA can be successfully used for selection of the candidates for Master’s degree studies in Public Health. The high predictive validity of the recruitment system confirms the validity of the adopted admission policy at MUW.Electronic supplementary materialThe online version of this article (10.1186/s12909-017-1007-z) contains supplementary material, which is available to authorized users.

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“…while quantitative data is relatively easy to obtain and analyze, it can also be problematic due to possible grade inflation in prerequisite courses and differing grading systems. This can be a particular problem for programs that attract a high number of transfer students (Chen & Voyles, 2013). It has also been argued that use of the statistical model might lead to decreased diversity within the nursing workforce.…”

Section: Pre-admission Predictors Of Student Success In a Baccalaureamentioning

confidence: 99%

“…Attrition results in waste of critical resources, thus much effort is spent by admission committees in an attempt to select the students who will be most likely to complete the program. There are limited studies which examine the use of grade point average (GPA) and entrance exam scores to predict success in the first semester of a nursing program, and several studies have looked at the relationships between nursing course grades, standardized exit tests and NCLEX success (Chen & Voyles, 2013;Newton, Smith, Moore, & Magnan, 2007; Underwood, Williams, Lee, & Brunnert, 2013;Yoho, Young, Adamson, & Britt, 2007). But fewer studies have examined the best use of admission data to differentiate between successful and non-successful students within a nursing program.…”

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Preadmission Predictors of Student Success in a Baccalaureate of Science in Nursing Program

Bennett

Bormann²,

Lovan³

et al. 2016

Journal of Nursing Regulation

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Attrition can be a serious problem for nursing programs and students. Loss of students during a nursing program or through NCLEX failure is a waste of resources and results in inefficiency in the production of nurses for the workforce. Using data from 341 students admitted over a threeyear period, the goal of this study was to determine which factors best predicted student success in a Baccalaureate of Science in Nursing (BSN) Program. These factors were then used to develop an admission formula which was tested retroactively to determine its ability to differentiate between successful and non-successful students. Authors defined student success as passing all nursing courses on the first attempt with a grade of C or above, on time program completion, and passing the NCLEX on the first attempt. Logistic regression for prediction of the probability of success found the following three variables accounted for 76% of the variance:Preprogram grade point average (GPA), Science GPA, and scores on the HESI A 2 Anatomy and Physiology subscale. The formula derived was validated by retrospective analysis to determine what the effect of using this model would have been if it had been used to select students for admission. Results demonstrated that use of this model would have eliminated 40.1% of the unsuccessful students, while retaining 84% of the successful students.Keywords: Nursing Student Retention; Admission Formula; Predictors of Student Success 2 Pre-admission Predictors of Student Success in a Baccalaureate of Science in Nursing ProgramAttrition is a concern for many nursing programs in the United States (U.S.), with some programs reporting graduation rates as low as 50% (Newton & Moore, 2009). Attrition results in waste of critical resources, thus much effort is spent by admission committees in an attempt to select the students who will be most likely to complete the program. There are limited studies which examine the use of grade point average (GPA) and entrance exam scores to predict success in the first semester of a nursing program, and several studies have looked at the relationships between nursing course grades, standardized exit tests and NCLEX success (Chen & Voyles, 2013;Newton, Smith, Moore, & Magnan, 2007; Underwood, Williams, Lee, & Brunnert, 2013;Yoho, Young, Adamson, & Britt, 2007). But fewer studies have examined the best use of admission data to differentiate between successful and non-successful students within a nursing program.Using data from 341 students admitted over a three-year period, the goal of this study was to determine which factors best predicted student success in a Baccalaureate of Science in Nursing (BSN) Program. These factors were then used to develop an admission formula which was tested retroactively to determine its ability to differentiate between successful and nonsuccessful students. For this study, student success was defined as graduating within four semesters of entering the nursing program, no nursing course grades below a grade of "C", and passing the NCLE...

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HESI Admission Assessment Scores: Predicting Student Success

Cited by 13 publications

References 5 publications

Quantitative evaluation of variables to student success in a mastery learning baccalaureate nursing programme

Quantitative evaluation of variables to student success in a mastery learning baccalaureate nursing programme

Evidence-based selection process to the Master of Public Health program at Medical University

Preadmission Predictors of Student Success in a Baccalaureate of Science in Nursing Program

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