Predicting the Academic Success of Student-athletes Using SAT and Noncognitive Variables

Predicting the Academic Success of Student-athletes Using SAT and Noncognitive Variables PDF Author: William E. Sedlacek
Publisher:
ISBN:
Category : College athletes
Languages : en
Pages : 18

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Predicting the Academic Success of Student-athletes Using SAT and Noncognitive Variables

Predicting the Academic Success of Student-athletes Using SAT and Noncognitive Variables PDF Author: William E. Sedlacek
Publisher:
ISBN:
Category : College athletes
Languages : en
Pages : 18

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The Use of Noncognitive Variables to Predict the Academic Success of Student Athletes

The Use of Noncognitive Variables to Predict the Academic Success of Student Athletes PDF Author: Charles William Walker
Publisher:
ISBN:
Category :
Languages : en
Pages : 354

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The Use of Noncognitive Variables to Predict the Academic Success of Student Athletes

The Use of Noncognitive Variables to Predict the Academic Success of Student Athletes PDF Author: La Chanze M. Walker
Publisher:
ISBN:
Category :
Languages : en
Pages : 51

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Making the Grade

Making the Grade PDF Author: Roderick D. Perry
Publisher:
ISBN:
Category : College athletes
Languages : en
Pages : 147

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The purpose of this study was three-fold. The first purpose was to examine if there was a difference in the academic success of 239 first-year student-athletes between the type of institution they attended, public or private. These student-athletes represented 12 intercollegiate varsity sports at two NCAA Division I institutions in the Midwest during the 2007-2009 academic years, and the study used the five pre-college predictor variables of NCAA GPA, standardized test scores, gender, race, and institution type. The second purpose was to determine which of these predictor variables were statistically significant in predicting academic success of student-athletes by sport. The third purpose was to predict how well these predictor variables could distinguish between student-athletes attending the public institution and student-athletes attending the private institution. The study found that student-athletes at the private institution entered the institution with a better overall academic profile than did the student-athletes at the public institution as related to the predictor variables of high school GPA, NCAA GPA, ACT scores, SAT scores, and first-year college cumulative GPA. The statistically significant relationships between the predictors variables correlated between r = .94 and r = .17. Several stepwise multiple regression analyses were conducted to predict first-year academic success. The study concluded that, when ACT and SAT scores are included, separately, in the model with the predictor variables, then NCAA GPA, ACT scores, gender, and race are statistically significant predictors for student-athletes attending the public institution, while NCAA GPA and ACT scores are statistically significant predictors for student-athletes attending the private institution. NCAA GPA, SAT scores, and gender are statistically significant predictors for student-athletes attending the public institution, and NCAA GPA and SAT scores are statistically significant predictors for student-athletes attending the private institution. Together, these findings suggest that Non-White female student-athletes are predicted to have a higher first-year cumulative GPA than any other student-athlete at the public institution when ACT scores are added to the model, and female student-athletes are predicted to have a higher first-year cumulative GPA than any other student-athlete when SAT scores are added to the model. A stepwise discriminant analysis was conducted to predict how well the predictor variables distinguish between the public and private institutions. Based on the findings, NCAA GPA, standardized test scores, and race are the statistically significant variables in the model. Overall, 66.9% of the student-athletes in the study were classified correctly into public and private institution. The student-athletes attending the public institution were classified with slightly better accuracy (67.9%) than the student-athletes attending the private institution (66.2%).

A Study of the Factors that Predict Academic Success and Retention of Student-athletes

A Study of the Factors that Predict Academic Success and Retention of Student-athletes PDF Author: April A. Brecht
Publisher:
ISBN:
Category : Academic achievement
Languages : en
Pages : 232

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Collegiate Student-athletes' Academic Success

Collegiate Student-athletes' Academic Success PDF Author: Kai'Iah A. James
Publisher:
ISBN:
Category :
Languages : en
Pages :

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This dissertation study examines the impact of traditional and non-cognitive variables on the academic prediction model for a sample of collegiate student-athletes. Three hundred and fifty-nine NCAA Division IA male and female student-athletes, representing 13 sports, including football and men's and women's basketball provided demographic information (i.e., race, academic classification, gender, scholarship status) and provided responses to the Academic Communication Anxiety Test instrument. The Associate Athletic Director for Student-Athlete Services provided precollege and college academic information (high school GPA, SAT/ACT score, collegiate GPA) and this information along with data provided by the participants was entered into a multiple regression analysis. The purpose of the study was to determine which variables predicted student-athlete college GPA and if participation in a revenue-generating versus a nonrevenue-generating sport impacted college GPA. The analyses indicated that the ACAT was a valid and reliable measure (alpha = .94) with three factors. In addition, high school core GPA, study hall hour requirement, academic classification, and pre-college standardized test score made significant contributions to the prediction equation. Participation in a revenue-generating sport was found to significantly impact GPA.

Predicting Student-athlete Academic Success with Preadmission, Social-contextual, and Sport Variables

Predicting Student-athlete Academic Success with Preadmission, Social-contextual, and Sport Variables PDF Author: Michael Wallace McCall
Publisher:
ISBN:
Category : College athletes
Languages : en
Pages : 190

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Universities are required by the NCAA to ensure student-athletes make progress towards earning a degree. In 2004, The NCAA created the Academic Progress Rate (APR) metric to assess if universities were facilitating academic success for student-athletes. Athletic programs that fail to meet an APR score of 925 receive a variety of penalties. These penalties not only hurt the athletic program but also tarnish an institution's image. Predicting which student-athletes are at-risk can provide an opportunity for athletic programs to change procedures to reduce risk. Although the NCAA provides information about APR risk, results are calculated based on aggregated data across a variety of institutions ranging from regional colleges to elite private universities. The risk factors provided by the NCAA may not accurately reflect risk within a specific institution. The present study assessed risk factors related to losing APR points for student-athletes attending a Division I institution in a BCS conference. Archival data were collected from the institution and the NCAA for 829 student-athletes receiving athletic scholarships between 2003-2009 school years. Predictor variables included high school GPA, SAT scores, conditions of admission, SES, race/ethnicity, sex, playing time, red shirting, distance from home, and sport risk. Results of the analysis indicate that male and female student-athletes have different risk factors and should be analyzed separately. There is an interesting relationship between high school GPA and SAT scores for minority student-athletes. Finally, a combination of preadmission, social-contextual, and sport variables were associated with student-athletes at-risk for losing APR points.

Predicting Student-athlete Success

Predicting Student-athlete Success PDF Author: Shanna Lei Autry
Publisher:
ISBN:
Category :
Languages : en
Pages : 77

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ABSTRACT: Student-athletes are a highly visible subgroup of students whose performance and visibility can influence the formation of an institution's image (Zimbalist, 1999). Research must continue to advance understanding of the variables that lead to student-athlete academic success in order to enhance opportunities for student-athletes, improve institutional performance, and address important national priorities for intercollegiate athletics and higher education. The purpose of this study is to identify those precollege and college experience variables that influence student-athlete success at a major Division I institution in the Southeastern United States during a three year period from 2000 to 2003. Study variables included: race; gender; residency; high school grade point average; SAT composite score; scholarship amount; classification; major; Pell Grant eligibility; GPA for each of the first three semesters; number of degree hours each of the first three semesters; number of withdrawals for each of the first three semesters; and participation in an enrichment program.

Cognitive, Learning and Study Strategy Predictors of Student-athlete Academic Success and Academic Progress Rates

Cognitive, Learning and Study Strategy Predictors of Student-athlete Academic Success and Academic Progress Rates PDF Author: Janet Cain Moore
Publisher:
ISBN:
Category : Electronic dissertations
Languages : en
Pages : 188

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The purpose of this research was to explore a range of predictor variables believed to influence the academic success of student-athletes as measured by cumulative grade point averages (CGPA) and academic progress rates (APR). This study included 210 scholarship student-athletes participating in intercollegiate athletics at a National Collegiate Athletic Association (NCAA) limited-resource institution. Multiple regression analysis found standardized test scores (Test), high school core grade point averages (HSGPA), the Will composite scale of the Learning and Study Strategies Inventory, 2nd Edition (LASSI-II), gender, and generational status (i.e. first-generation or non-first-generation) to be most predictive of student-athlete cumulative grade point averages (CGPA). Independent t-tests were conducted on all predictor variables in the study and found significant differences between males and females on the variables of HSGPA, Test, and CGPA with female student-athletes scoring higher on all of these measures. Significant differences were also found between first-generation and non-first-generation student-athletes on variables of HSGPA, Test, Skill, Will, and CGPA with non-first-generation student-athletes scoring higher on all of these measures. Student-athletes participating in non-revenue sports had significantly higher scores on the HSGPA, Test, and CGPA variables. Logistic regression analyses using found standardized test scores to be the only predictor variable in this study to consistently contribute to the prediction of APR point loss.

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

Using Noncognitive Assessment to Predict Academic Success for At-risk Students PDF Author: Paul Orscheln
Publisher:
ISBN:
Category : Electronic Dissertations
Languages : en
Pages : 85

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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.