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Admission Variables as a Predictor of First Semester Student Success

Author : Linda Lisa Esper

Publisher :

Page : 172 pages

File Size : 44,61 MB

Release : 2009

Category : Nurses

ISBN :

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Book Description

The current national shortage of practicing registered nurses is exacerbated by an accompanying shortage of nurse educators, which limits program enrollments in Associate Degree Nursing (ADN) programs. Relatively low available enrollment in nursing programs is coupled with a national first year retention rate of 64% (National League for Nursing Accrediting Commission [NLNAC], 2008), which leaves ADN educational leaders struggling to find improved ways to increase graduation rates through better identification of qualified applicants. This exploratory, action research study examined commonly used ADN admission criteria in order to identify those indicators which best predict students' first semester success at a small private northeastern United States college. The predictive ability of common ADN admission variables (TEAS scores in the areas of math, science, and English; overall TEAS score; age; gender; and math, science, and English course grades) was determined with regard to student success outcome variables (medication/math exam grade, Nurse Fundamental course grade, Nurse Health Assessment course grade, and Assessment Technology Institute [ATI] Nursing I Fundamental Content Mastery Series scores). Using an exploratory, action research design, data from 120 freshman nursing students were examined to assess the relative contributions of each of the predictor variables on forecasting students' first semester success. The study's methodology involved a simple correlation and regression analysis of the data. Selected Admission's variables were shown to be correlated to certain outcome variables. These Admission's variables included, the TEAS overall score, the last science course grade on admission (ACGs), the TEAS score in English, and the student's last earned English course on admission (ACGe). Only the TEAS total score showed correlation with success over a broad range of success score, i.e. ATIs, FUNg, and HAg. Overall, it was concluded that the ability of the admission variables to predict a specific score on student outcome assessment was weak. As a result of this study, the college's Admission office and nursing department will use the information to modify Admission's policies, develop pre-admission workshops, and continue to implement program initiatives to further support student success in an ADN nursing program. Further studies are warranted in order to assist other colleges in determining the level of academic qualifications most desirable in selecting students capable of success in their ADN nursing program.



Student Success

Author : Lianne Briggs

Publisher :

Page : 302 pages

File Size : 28,9 MB

Release : 2012

Category : Universities and colleges

ISBN :

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Despite retention being a significant focus of higher education research, graduation rates remain of concern. Increased numbers of students are advancing to college bringing with them a wider range of abilities, attributes, and characteristics. There is much we know about what predicts success for these students but our knowledge is far from complete. My study therefore explores to what extent pre-admission variables of academic preparation, personal attributes, and demographic characteristics are predictive of graduation with the goal of identifying students who are more or less likely to do well than their high school academic preparation would suggest. The study examines the records of 6,400 first-time-in-any-college freshmen (FTIACs) at one mid-sized university as it transitioned from an open admission policy to higher admission standards over a seven-year period. Twenty-two independent variables drawn from the student record system and ACT Interest Inventory were examined, as broken down by each admission standard cohort, data set, and field of study. Logistic regression analysis was used to find variables predictive of first- and second-year retention as well as graduation. Results revealed that for all groups, high school grade point average (HSGPA) was significant in predicting both retention and graduation. Standardized test scores such as the ACT were not significant. Other factors with a positive influence on retention and graduation among the groups included: living in a residence hall, extracurricular activities, AP credits, CLEP credits, and being female. Variables with a negative influence were being Pell eligible, higher educational aspirations, higher estimated first year GPA, distance from campus, and being a minority. Pell eligibility was significant for almost every group tested. For the weakest students the only variable which predicted retention or graduation was HSGPA. Findings indicated the two most important variables in predicting graduation were HSGPA and Pell eligibility. Focusing admission standards and retention programs on these two factors would have the greatest impact on graduation rates, as well as setting realistic shorter-term educational aspirations and estimated GPA goals. This research strongly suggests setting minimum admission standards based on HSGPA alone could be an appropriate option for higher education leaders.



Holistic Admissions

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Page : pages

File Size : 36,78 MB

Release : 2020-12

Category :

ISBN : 9781578581283

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Predicting Academic Success

Author : Cecilia Myburgh

Publisher :

Page : 0 pages

File Size : 29,40 MB

Release : 2019

Category :

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The study aimed to develop a model predictive of academic success based on variables assessed during the admission process and the relationships of the variables with academic progress and academic success at a South African university. To do this, the study investigated if school exiting results and admission tests were significant predictors of first-year grade point average and of final academic grade point average over a period of six years, taking into account different race and gender groups, as well as different school examination authorities. The relationship between first-year and final grade point average was also assessed in order to develop a comprehensive and integrated model predictive of academic success. The disaggregation of the dataset (N=3418) into different race and gender subgroups and different school examination authorities revealed to be useful and necessary as differences in mean scores of the predictor and criterion variables were observed and vastly different predictive models were presented, indicating that an overall model to predict academic success for all students is not appropriate. The results of this study highlighted the reality of significant inequalities in university outcomes for students of different race and gender subgroups in particular. The results of this study should be interpreted in the context of guiding admission decisions, and developing policies and rules that are fair, equitable, reliable and justifiable in terms of the ability and probability of students to succeed, bearing in mind individual differences in the prediction model with regard to race, gender and different school examination authorities.



Predictors of Academic Success for Conditionally Admitted First-time Freshmen at a Four-year Public University

Author : Robert S. Hornberger

Publisher :

Page : 174 pages

File Size : 38,91 MB

Release : 2010

Category : Academic achievement

ISBN :

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This quantitative study examined a sample of 249 conditionally admitted firsttime freshman at a four year public university to answer four research questions pertaining to the potential prediction of academic success and college retention for conditional admits. The single-stage, convenience sample (Creswell, 2003) included variables related to student demographic, academic admission, first year academic success, and college admission factors were included in the study. The findings of the study revealed that an emphasis on core curriculum classes taken during high school, especially the senior year, and the core curriculum coursework GPA should be emphasized by policymakers as determinants for admission exceptions. The results also highlighted the ACT English sub score for the full sample, and the high school GPA for the male sub group, as significant predictors of academic success and college retention. Other factors analyzed in the study, including the type of high school, whether a student earned college credit prior to college, whether a student participated in high school athletics, whether a student was an athlete at the college of study, ethnicity and race, whether the student received application for admission fee waiver, and the type of conditional admit, did not qualify as significant predictors in the final statistical model.



The Predictive Relationship of Pre-enrollment Cognitive and Non-cognitive Variables to Student Academic Success and Persistence During the First to Second Academic Year for First-year Students Enrolled at a Christian Liberal Arts University

Author : Andy Denton

Publisher :

Page : 294 pages

File Size : 21,38 MB

Release : 2012

Category : College attendance

ISBN :

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Each year in the United States, nearly one million new students enroll at a four-year post-secondary institution. However, one third of these students do not enroll for their second year of college. Researchers and practitioners say that the period between the freshman and sophomore years is the most critical time regarding student retention and persistence. They have spent considerable time and energy producing studies and developing theories as to why students persist or leave an institution. Admission pressures and competition for students at colleges and universities are expected to continue to increase. Greater challenges to attract new students enhance the significance of developing methodologies to retain the students. Admissions offices are attempting to design predictive models that enable them to determine which students are most likely to experience academic success and persist. This study analyzed the predictive relationship of pre-enrollment cognitive and non-cognitive variables to student academic success and persistence during the first to second academic year for first-year students enrolled at a Christian liberal arts university in the Midwest. A quantitative approach was used to predict academic success and student persistence utilizing hierarchical multiple and logistic regression analyses to answer the research questions. The independent cognitive and non-cognitive variables resulted in a model which was a statistically significant predictor of both the dependent variables, first-year grade point average and second-year retention. The two strongest predictors of first-year grade point average were ACT score and high school grade point average. Results showed ACT score, high school grade point average, and having a parent or sibling as an alumnus of Evangel University were significant predictors of persistence.



Predicting First Year Academic Success of the Student-athlete Population at the University of Missouri

Author : Joseph M. Scogin

Publisher :

Page : pages

File Size : 18,98 MB

Release : 2007

Category : Academic achievement

ISBN :

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This study compares the predictive validity of the Office of University Admission's model to predict first year grade point average for student athletes at the University of Missouri. In a majority of the cases, it was found that student athletes had higher first year grade point averages than the campus prediction. Based on these findings, the researcher used a stepwise multiple regression to identify variables that account for a significant portion of the variance in first year grade point average for student athletes. The research was able to identify a significant model including three variables that explained 50% of the total variance in first year GPA. High school GPA (42%), ACT composite (5%), and aid status (2.5%) were significant predictors of first year academic performance for student athletes at the University of Missouri.



Noncognitive Attributes as a Measure for College Admission

Author : Amanda E. Craddock

Publisher :

Page : 155 pages

File Size : 43,99 MB

Release : 2021

Category : Academic achievement

ISBN :

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Book Description

Cognitive factors, such as standardized test scores and high school grade point average, have historically been used to predict college success. Many colleges and universities place great importance on these cognitive factors when making admissions decisions. However, enrollment leaders question the predictive validity of these factors due to recent studies advocating for the use of noncognitive assessments. The purpose of this study was to examine the role that noncognitive attributes have in predicting college student success and whether their predictive power is greater than that of standardized test scores and high school grade point average. This study employed a quantitative methodology using a correlational predictive research design. The study investigated the Student Strengths Inventory (SSI) assessment results on 1,104 first-year students at a mid-sized public regional comprehensive university in the southeast United States. The SSI results were analyzed to determine if the SSI noncognitive subscales (educational commitment, academic engagement, academic self-efficacy, resiliency, social comfort, and campus engagement) predict first-year grade point average and retention better than standardized test scores and high school grade point average. The study's findings showed that academic self-efficacy, academic engagement, resiliency, campus engagement, high school GPA, and SAT score were statistically significant in predicting first-year GPA. The study's second finding showed that the only significant predictor of retention was high school GPA. Implications of this study are to quantify the role that noncognitive attributes have in predicting student success and how higher education institutions might assess these variables as part of the admissions process.



Using Noncognitive Assessment to Predict Academic Success for At-risk Students

Author : Paul Orscheln

Publisher :

Page : 85 pages

File Size : 31,90 MB

Release : 2012

Category : Electronic Dissertations

ISBN :

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Book Description

The purpose of this study was to determine if noncognitive variables, alone or in combination with standardized test score (ACT or SAT) and/or high school grade point average, can predict student success (first-semester grade point average, first to second year retention and five year graduation rate) for 154 academically at-risk college freshmen admitted into the Conditional Admissions Program (CAP) at the University of Central Missouri for the Fall 2007 semester. In this investigation, student success was defined as a first semester GPA of 2.0 or higher, retaining to the second year and graduating within a five year time frame. Through the six- question short answer-style Insight Resume, noncognitive attributes were evaluated based on each student's life experiences and what they learned from those experiences. Correlations were calculated measuring the relationship between the Insight Resume and the dependent variables. Findings revealed there were only slight correlations between Insight Resume score and earning a first semester GPA of 2.0 or greater, retaining from the first to the second year, and graduating in five years. In addition, logistic regression was used to measure the predictive value of the combination of the Insight Resume scores, HSGPA and composite ACT scores on predicting first semester GPA of 2.0 or higher, retention from year one to year two, or five year graduation rate. Results indicated that there was no indication any of the predictor variables significantly improved the ability to predict earning a first semester GPA of 2.0 or higher or whether a student would retain or graduate.



Correcting Correlations When Predicting Success in College

Author : Joe L. Saupe

Publisher :

Page : 17 pages

File Size : 21,39 MB

Release : 2010

Category :

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The purpose of this study is to illustrate techniques for correcting a correlation between a predictor of success in college (admission test score or indicator of high school performance) with a measure of success in college (one-year retention or first-year GPA) given the restricted variances in the population used to calculate the correlations. In other words, this study demonstrates procedures for estimating correlations in the unrestricted population (students who attend college and students who do not attend college) based upon correlations calculated for the restricted population (students who attend college). A secondary purpose is to set the foundation for and stimulate additional studies designed to estimate these correlations in other unrestricted higher education and college student populations. This study focuses on correlations involving admission test scores, indicators of success in high school, and first-year college GPA. The data for this study come from a population of first-time freshmen who entered a major research university with moderately selective admission standards in the fall 2008 semester, whose high school class percentile rank was 50 or greater, who entered the fall semester as full-time, degree-seeking students, and who completed both semesters with complete data for the study variables. There are 3,668 students in this population. In sum, the true relationships between predictor variables and college success measures can be masked by restricted range as well as other extraneous variables. The present study demonstrates the influence that restricted range can have on this relationship and suggests that these predictor variables are probably more accurate than what is generally shared in the literature and in practice. This study will have been successful if it stimulates others to explore the use of the correction formulas to estimate correlations between predictor variables and indicators of success in college for unselected populations. (Contains 3 tables.).