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Comparative Study of the Persistence and Academic Success of Florida Community College Student-Athletes and Non-Athlete ...

Permanent Link: http://ufdc.ufl.edu/UFE0024321/00001

Material Information

Title: Comparative Study of the Persistence and Academic Success of Florida Community College Student-Athletes and Non-Athlete Students 2004 to 2007
Physical Description: 1 online resource (165 p.)
Language: english
Creator: Horton, David
Publisher: University of Florida
Place of Publication: Gainesville, Fla.
Publication Date: 2009

Subjects

Subjects / Keywords: athletes, community, florida, human, regression
Educational Administration and Policy -- Dissertations, Academic -- UF
Genre: Higher Education Administration thesis, Ph.D.
bibliography   ( marcgt )
theses   ( marcgt )
government publication (state, provincial, terriorial, dependent)   ( marcgt )
born-digital   ( sobekcm )
Electronic Thesis or Dissertation

Notes

Abstract: COMPARATIVE STUDY OF THE PERSISTENCE AND ACADEMIC SUCCESS OF FLORIDA COMMUNITY COLLEGE STUDENT-ATHLETES AND NON-ATHLETE STUDENTS: 2004 TO 2007 This study explored degree attainment and four-year transfer rates for Florida community college students that were financially supported through athletically-related financial aid and those in the general student population. Longitudinal data from the Florida Department of Education s PK-20 Data Warehouse and institutional data from the Integrated Postsecondary Education Data System (IPEDS) were used to examine the effects of athletically-related financial aid, individual characteristics, and institutional factors on student s academic success at the community college. For the purposes of this study, a student was deemed academically successful if he or she received a degree, transferred to a four-year institution, or earned a degree and transferred to a four-year institution within a maximum of 11 semesters or three and one-half years. A longitudinal multivariate methodology was employed to analyze institutional level and student level data, with special emphasis and focus on transfer and degree completion rates for student-athletes. Using logistic regression methods, results indicated that student-athletes at the community college were less likely than non-athlete students to earn a degree from the community college within three years of initial enrollment. No significant differences were found between non-athlete students and student-athletes when considering the probability of transfer to a four-year institution in the state of Florida or degree attainment and four-year transfer.
General Note: In the series University of Florida Digital Collections.
General Note: Includes vita.
Bibliography: Includes bibliographical references.
Source of Description: Description based on online resource; title from PDF title page.
Source of Description: This bibliographic record is available under the Creative Commons CC0 public domain dedication. The University of Florida Libraries, as creator of this bibliographic record, has waived all rights to it worldwide under copyright law, including all related and neighboring rights, to the extent allowed by law.
Statement of Responsibility: by David Horton.
Thesis: Thesis (Ph.D.)--University of Florida, 2009.
Local: Adviser: Ponjuan, Luis.
Electronic Access: RESTRICTED TO UF STUDENTS, STAFF, FACULTY, AND ON-CAMPUS USE UNTIL 2011-05-31

Record Information

Source Institution: UFRGP
Rights Management: Applicable rights reserved.
Classification: lcc - LD1780 2009
System ID: UFE0024321:00001

Permanent Link: http://ufdc.ufl.edu/UFE0024321/00001

Material Information

Title: Comparative Study of the Persistence and Academic Success of Florida Community College Student-Athletes and Non-Athlete Students 2004 to 2007
Physical Description: 1 online resource (165 p.)
Language: english
Creator: Horton, David
Publisher: University of Florida
Place of Publication: Gainesville, Fla.
Publication Date: 2009

Subjects

Subjects / Keywords: athletes, community, florida, human, regression
Educational Administration and Policy -- Dissertations, Academic -- UF
Genre: Higher Education Administration thesis, Ph.D.
bibliography   ( marcgt )
theses   ( marcgt )
government publication (state, provincial, terriorial, dependent)   ( marcgt )
born-digital   ( sobekcm )
Electronic Thesis or Dissertation

Notes

Abstract: COMPARATIVE STUDY OF THE PERSISTENCE AND ACADEMIC SUCCESS OF FLORIDA COMMUNITY COLLEGE STUDENT-ATHLETES AND NON-ATHLETE STUDENTS: 2004 TO 2007 This study explored degree attainment and four-year transfer rates for Florida community college students that were financially supported through athletically-related financial aid and those in the general student population. Longitudinal data from the Florida Department of Education s PK-20 Data Warehouse and institutional data from the Integrated Postsecondary Education Data System (IPEDS) were used to examine the effects of athletically-related financial aid, individual characteristics, and institutional factors on student s academic success at the community college. For the purposes of this study, a student was deemed academically successful if he or she received a degree, transferred to a four-year institution, or earned a degree and transferred to a four-year institution within a maximum of 11 semesters or three and one-half years. A longitudinal multivariate methodology was employed to analyze institutional level and student level data, with special emphasis and focus on transfer and degree completion rates for student-athletes. Using logistic regression methods, results indicated that student-athletes at the community college were less likely than non-athlete students to earn a degree from the community college within three years of initial enrollment. No significant differences were found between non-athlete students and student-athletes when considering the probability of transfer to a four-year institution in the state of Florida or degree attainment and four-year transfer.
General Note: In the series University of Florida Digital Collections.
General Note: Includes vita.
Bibliography: Includes bibliographical references.
Source of Description: Description based on online resource; title from PDF title page.
Source of Description: This bibliographic record is available under the Creative Commons CC0 public domain dedication. The University of Florida Libraries, as creator of this bibliographic record, has waived all rights to it worldwide under copyright law, including all related and neighboring rights, to the extent allowed by law.
Statement of Responsibility: by David Horton.
Thesis: Thesis (Ph.D.)--University of Florida, 2009.
Local: Adviser: Ponjuan, Luis.
Electronic Access: RESTRICTED TO UF STUDENTS, STAFF, FACULTY, AND ON-CAMPUS USE UNTIL 2011-05-31

Record Information

Source Institution: UFRGP
Rights Management: Applicable rights reserved.
Classification: lcc - LD1780 2009
System ID: UFE0024321:00001


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1 COMPARATIVE STUDY OF THE PERSISTENCE AND ACADEMIC SUCCESS OF FLORIDA COMMUNITY CO LLEGE STUDENT -ATHLETES AND NON -ATHLETE STUDENTS: 2004 TO 2007 By DAVID HORTON JR. A DISSERTATION PRESENTED TO THE GRADUATE SCHOOL OF THE UNIVERSITY OF FLORIDA IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF DOCTOR OF PHILOSOPHY UNIVERSITY OF FLORIDA 2009

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2 2009 David Horton Jr.

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3 To my family and our future generations

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4 ACKNOWLEDGMENTS This journey to the PhD has been a fantastic voyage but this journey has not been without its stumbling blocks and challenging moments. R egardless of the events that have transpired over the past five years God has place d several individuals in my life that have been willing to endure the rainy days and wonderful moments along the way Though impossible to acknowledge each and every individual by name, I take this opportun ity to express my sincerest thanks and appreciation to my friends, colleagues and extended family for their unconditional love, support, guidance, understanding, and patience. I extend my grateful indebtedness and love to my parents, David and Fay Horton, and my brothers and sisters, Andre Lisa Arcillia Aaron Daryl and Shalonda I am extremely thankful for the daily prayers and var ious ways in which my family has support ed and encourage d me along the way. I would also like to extend my appreciation to my Houston family and the scores of Blanks and Hortons that have supported me over the past five years My time in Florida has been extremely enriched because of the love and support provided by my Gainesville family the Gratto family I extend my sincere st gratitude and love to F red, Kathy, and the members of the Gratto family for welcoming me into your family providing great Thanksgiving meals and memories, and for the many ways you have illustrated sincere love, care, and support. I am truly thankful that God allowed our paths to cross and our families to be intertwined in ways we could have never imagined!! Throughout my academic studies I have been challenged and supported by some of the greatest mentors and colleagues one could ask for. I would like to give special thank s to my doctoral committee members, Dr. Luis Ponjuan, Dr. Linda Serra Hagedorn, Dr. Katherine Gratto, and Dr. Carl Barfield for their invaluable input, support, encouragement, patience, and unwavering commitment to seeing me through this process. I want to especially thank my

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5 advisor s Dr. Luis Ponjuan and Dr. Linda Hagedorn for their copious feedback on previous drafts of this document, for chall enging me throughout this process, and for making my graduate studies a memorable learning experience. I would like to give special thanks to my faculty members in the College of Education James Algina, Dale Campbell, Dave Honeyman, and Pilar Mendoza, fo r their individual and collective contributions to my academic studies Your counsel, assistance and mentorship over the past years have been invaluable and I look forward to working with you in years to come. Furthermore, I extend my gratitude and appreciation to Angela Rowe and Patty Lefevers in the Department of Educational Administration & Policy for all of their assistance ov er the past years. I know I have said it several times before, but I will say it again, MUCH THANK S I would also like to thank m y friends, colleagues and co travelers on this journey to the PhD from the various department s and colleges at the University of Florida. It has been a joy over the past five years to spend time with such great young scholar s and thinkers. I have learned so many valuable lessons from each of you that I will not soon forget. Specifically, I would like to thank the inner circle for the many hours we spent together brainstorming, studying, debating, writing, and for the many u nforgettable out -of -class diversionary experiences you have provided over the past few months This project would not have taken the current form without the assistance provided by the Florida Department of Education. Accordingly, I would like extend my gratitude to Tammy Duncan and Cesar Regazzoni at the FLDOE for providing me with access to data collected by the Education Data Warehouse (EDW) and the Community College and Technical Center Management Information System (CCTCMIS).

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6 Last, but no t least, I would like to express my grateful appreciation to the Association for Institutional Research (AIR) for their generous financial support over this past year. Being awarded the AIR fellowship has afforded me the resources and time over the past ye ar to focus on compiling a product that I believe others will find informative and beneficial to the study of community colleges and higher education. This material is based upon work supported by the Association for Institutional Research, the National Center for Education Statistics, the National Science Foundation and the National Postsecondary Education Cooperative under Association for Institutional Research Grant Number 08410. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author and do not necessarily reflect the views of the Association for Institutional Research, the National Center for Education Statistics, the National Science Foundation, or the National Postsecondary Education Cooperative.

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7 TABLE OF CONTENTS Page ACKNOWLEDGMENTS .................................................................................................................... 4 TABLE OF CONTE NTS ..................................................................................................................... 7 LIST OF TABLES .............................................................................................................................. 11 LIST OF FIGURES ............................................................................................................................ 13 ABSTRACT ........................................................................................................................................ 14 CHAPTER 1 INTRODUCTION ....................................................................................................................... 16 Benefits of Higher Education Participation ............................................................................... 16 Impact and Influence of the Community College ..................................................................... 18 Role of Athletics in Providing Access to Higher Education .................................................... 19 Purpose of Study ......................................................................................................................... 20 Research Questions ..................................................................................................................... 21 Statement of Problem .................................................................................................................. 22 Significance of Study .................................................................................................................. 24 Historical Perspective ................................................................................................................. 25 Contribution to the Study of Higher Education ......................................................................... 29 Definition of Terms ..................................................................................................................... 29 2 REVIEW OF LITERATURE ..................................................................................................... 31 Key Concepts and Terms ............................................................................................................ 31 Student Persistence .............................................................................................................. 32 Student Rete ntion ................................................................................................................. 33 Academic Success ............................................................................................................... 33 Cooling -out ................................................................................................................... 35 Warming up .................................................................................................................. 36 Transfer Students and Four Year Transfer ........................................................................ 37 Individual and Institutional Characteristics ............................................................................... 40 Community College Mission .............................................................................................. 41 Institutional Characteristics ................................................................................................. 44 Individual Background Characteristics .............................................................................. 45 Student -Athlete Experience ........................................................................................................ 47 Characteristics of Student -Athletes .................................................................................... 51 Benefits of Athletic Programs to Institutions and Student -Athletes ................................. 54 Support Services on Academic Success ............................................................................. 56 Academic and Athletic Motivation on Academic Success ............................................... 58 Summary of Literature Review .................................................................................................. 59

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8 Theoretical Framework ............................................................................................................... 62 Conceptual Model ....................................................................................................................... 65 Dependent Variable ............................................................................................................. 67 Individual Bac kground Characteristics .............................................................................. 67 Student -Athlete Status ......................................................................................................... 69 Pre -College Characteristics ................................................................................................. 70 Acad emic Experiences ........................................................................................................ 71 Institutional Characteristics ................................................................................................. 71 3 METHODOLOGY ...................................................................................................................... 73 Proposed Hypothese s .................................................................................................................. 74 Rationale and Benefits of Secondary Data Sources .................................................................. 75 Dependent Variables ................................................................................................................... 76 Independent Variables ................................................................................................................ 77 Student -Athlete Status ......................................................................................................... 77 Individual Background Characteristics .............................................................................. 78 Pre -College Characteristics ................................................................................................. 80 Academic Experiences ........................................................................................................ 82 Institutional Characteristics ................................................................................................. 83 An alytic Methods ........................................................................................................................ 86 Limitation of Study ..................................................................................................................... 88 Delimitations ............................................................................................................................... 89 4 DATA ANALYSIS AN D RESULTS ........................................................................................ 92 Preliminary Analysis ................................................................................................................... 92 Descriptive Statistics for Institutional Sample .......................................................................... 93 Distribution of Degrees Conferred ............................................................................................. 94 Descriptive Statistics for Student Samples ................................................................................ 96 Level of College Readiness by Race, Gender, and SES ................................................... 97 Students by Cognitive Content Area ................................................................................ 100 Students by Race and Gender (Geographic Location) .................................................... 101 Students by and Race and Gender (FTE Enrollment Size) ............................................. 102 Outcomes by Level of College Readiness, Race and Gender ................................................ 103 Degrees Earned by Level of College Readiness .............................................................. 104 Degrees Earned by Race and Gender ............................................................................... 105 Four Year Transfer by Race and Gender ......................................................................... 106 Degree Attainment and Four Year Transfer by Race and Gender ................................. 106 Descriptive Statistics for Continuous Independent Variables ................................................ 108 Independent Sample T Tests .................................................................................................... 108 Analysis of Variance (ANOVA) .............................................................................................. 111 Geographic Location ......................................................................................................... 111 FTE Enrollment Size ......................................................................................................... 112 General Linear Models (GLM) with Binary Dependent Outcome Variables ....................... 113 General Linear Model 1: Degree Attainment .......................................................................... 115 Student -Athlete Status ....................................................................................................... 115

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9 Individual Background Characteristics ............................................................................ 115 Pre -College Characteristics ............................................................................................... 117 Academic Experiences ...................................................................................................... 117 Institutional Characteristics ............................................................................................... 118 Interaction Terms ............................................................................................................... 118 General Linear Model 2: Four Year Transfer ......................................................................... 118 Student -Athlete Status ....................................................................................................... 119 Individual Background Characteristics ............................................................................ 119 Pre -College Characteristics ............................................................................................... 119 Academic Experiences ...................................................................................................... 121 Institutional Characteristics ............................................................................................... 121 In teraction Terms ............................................................................................................... 121 General Linear Model 3: Degree Attainment and Four Year Transfer ................................. 122 Student -Athlete Status ....................................................................................................... 122 Individu al Background Characteristics ............................................................................ 122 Pre -College Characteristics ............................................................................................... 124 Academic Experiences ...................................................................................................... 124 Institutio nal Characteristics ............................................................................................... 125 Interaction Terms ............................................................................................................... 125 Chapter Summary and Conclusion ........................................................................................... 125 5 DISCUSSION AND CONCLUSIONS ................................................................................... 127 Purpose of Study Revisited ....................................................................................................... 128 Impact of Athletic Participation ............................................................................................... 129 Academic Performance ..................................................................................................... 129 Degree Attainment and Four Year Transfer .................................................................... 131 Impact of Pre -College and Institutional Characteristics ......................................................... 134 Pre -College Characteristics ............................................................................................... 134 Institutional Characteristics ............................................................................................... 135 Contributions of this Study to the State of Florida ................................................................. 136 Implications for practice ........................................................................................................... 137 State and National Policy Recommendations .......................................................................... 139 Suggestions for Future Research .............................................................................................. 142 Closing Words ........................................................................................................................... 144 APPENDIX A NATIONAL COLLEGIATE ATHLETIC ASSOCIATION (NCAA) ELIGIBILITY SLIDING SCALE FOR GPA AND ENTRANCE TEST SCORES ...................................... 145 B CALCULATIONs OF OD DS RATIOS FOR CONTINUOUS VARIABLES IN GENERAL LINEAR MODELS (GLM) ................................................................................. 146 C INSTITUTIONAL REVIEW BOARD (IRB) APPROVAL LETTER ................................. 147

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10 D ASSOCIATION FOR INSTITUTIONAL RESEARCH (AIR) DISSERTATION FELLOWSHIP AWARD LETTER ......................................................................................... 148 LIST OF REFERENCES ................................................................................................................. 149 BIOGRAPHICAL SKETCH ........................................................................................................... 164

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11 LIST OF TABLES Table page 3 1 D ependent variables ............................................................................................................... 77 3 2 Independent variables and values .......................................................................................... 79 3 3 Summary of logistic regression models ................................................................................ 87 4 1 S tudents nested in institutions ............................................................................................... 93 4 2 Institutions by geographic location ....................................................................................... 94 4 3 Institutions by FTE enrollment size ...................................................................................... 94 4 4 D egrees conferred by institutions .......................................................................................... 95 4 5 S tudents by race ...................................................................................................................... 96 4 6 S tudents by gender ................................................................................................................. 97 4 7 S tudents by SES ..................................................................................................................... 97 4 8 S tudents by college readiness ................................................................................................ 98 4 9 College readiness by race ...................................................................................................... 98 4 10 College read iness by gender .................................................................................................. 99 4 11 College read iness by SES .................................................................................................... 100 4 12 College ready students in the content area math ................................................................ 100 4 13 College ready students in the content area reading ............................................................ 100 4 14 College ready students in the content area writing ............................................................ 101 4 15 S tudents by race and institutional geographical location ................................................... 101 4 16 S tudents by gender and geographic location ...................................................................... 102 4 17 S tudents by race and institutional FTE enrollment size .................................................... 103 4 18 S tudents by gender and institutional FTE enrollment size ................................................ 103 4 19 D egrees earned by level of college readiness ..................................................................... 104 4 20 De grees earned by student athlete status and race ............................................................. 105

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12 4 21 D egrees earned by gender .................................................................................................... 105 4 22 F our -year transfer by race .................................................................................................... 106 4 23 F our -year transfer by gender ............................................................................................... 106 4 24 D egrees earned and four year transfer completed by Race ............................................... 107 4 25 D egrees earned and four year transfer by gender .............................................................. 107 4 26 Descriptive Statistics for Continuous Independent Variables ........................................... 108 4 27 Analysis of mean GPA for student athletes and nonathlete students .............................. 109 4 28 Analysis of course credit hours earned for student athletes and non athlete students .... 110 4 29 One -way ANOVA of mean differences in student GPA by geographic location ............ 111 4 30 Bonferronis post -hoc tests of mean differences in GPA between institutional geographic locations ............................................................................................................ 112 4 31 One -way ANOVA of mean differences in student GPA by institutional FTE enrollment size ..................................................................................................................... 112 4 32 Bonferronis post -hoc tests of mean differences in GPA between institutional FTE enrollment size ..................................................................................................................... 113 4 33 Binary logistic regression model measures model 1: Degree attainment ......................... 115 4 34 Results for b inary logistic regression model 1: Degree attainment .................................. 116 4 35 Binary logistic regression model measures model 2: Four year transfer ......................... 119 4 36 Results for b inary logistic regression model 2: Four -year transfer ................................... 120 4 37 Binary logistic regression model measures model 3: Degree attai nment and four year transfer .................................................................................................................................. 122 4 38 Results for binary logistic regression model 3: Degree attainment and four -year transfer .................................................................................................................................. 123 A 1 NCAA Division I core GPA and test score sliding scale .................................................. 145

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13 LIST OF FIGURES Figure page 2 1 Conceptual model for a comparative study of the persistence and academic success of Florida community college student athletes and non athlete students: 2004 to 2007. ........................................................................................................................................ 68 3 1 Conceptual model for the comparative study of the persistence and academic success of Florida community college student athletes and non athlete students: 2004 to 2007. ........................................................................................................................................ 91

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14 Abstract of Dissertation Presented to the Graduate School of the University of Florida in Partial Fulfillment of the Requirements for the Degree of Doctor of Philosophy COMPARATIVE STUDY OF THE PERSISTENCE AND ACADEMIC SUCCESS OF FLORIDA COMMUNITY CO LLEGE STUDENT -ATHLETES AND NON -ATHLETE STUDENTS: 2004 TO 2007 By David Horton Jr. May 2009 Chair: Luis Ponjuan Major: Higher Education Administration This study explored degree attainment and four -year transfer rates for Florida c ommunity college students that were financially supported through athletically related financial aid and those in the general student population L ongitudinal data from t he Florida Department of Educations PK 20 Data Warehouse and institutional data from the Integrated Postsecondary Education Data System (IPEDS ) were used to examine the effects of athletically related financial aid individual characteristics, and institutional factors on students academic success at the community college For the purposes of this study, a student was deemed academically successful if he or she received a degree, transferred to a four -year institution, or earned a degree and transferred to a four year institution within a maximum of 11 semesters or three a nd one -half years. A longitudinal multivariate methodology was employed to analyze institutional level and student level data, with special emphasis and focus on transfer and degree completion rates for student athletes. U sing logistic regression methods results indicated that student athletes at the community college were less likely than non athlete students to earn a degree from the community college within three years of initial enrollment. No significant differences were

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15 found between non athlete stud ents and student athletes when considering the probability of transfer to a four -year institution in the state of Florida or degree attainment and four -year transfer.

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16 CHAPTER 1 INTRODUCTION It's no longer enough for community colleges to get students in the door. Now they must get more of them out the door with a degree or a ticket to a four year university. --Elyse Ashburn (2007) More than 70,000 students participate in intercollegiate athletics at public comm unity colleges in the United States each year ( National Junior College Athletic Association 2008). Yet, there presently exist s little empirical research that examine s the persistence, degree completion or transfer rates of student athletes at public commu nity college s The oversight of this student population in the literature is troubling given the mounting calls for increased institutional accountability and documentation of student outcomes within higher education (Ashburn, 2007; Dougherty & Kienzl, 2006) To this end, t h e present research inquiry is a forward step to ward enhancing our understanding and knowledge of the academic performance and outcomes of student athletes at the community college. T his study examine s the influence of individual and institutional characteristics on the academic success of students that were awarded athletically related financial aid while enrolled at the community college. This present examination begins with a discussion of the individual and soci et al benefits of higher education participation then discuss the role community colleges and athletic programs play in providing increased student access to higher education. Benefits o f H igher Education Participation H igher education literature provides several examples of the educational, developmental economic and societal benefits of higher education participation (King & Baxter Magolda, 1996; N ational Association of Student Person nel Administrators (N ASPA ) & A merican College Personnel Assoc iation, (A CPA ), 2004). T his body of literature suggests that individuals who attend college are more inclined to be actively involved in civic and community -based outreach

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17 programs, have higher career aspirations, an increased cognitive understanding, a se nse of personal maturity, and interpersonal effectiveness, as compared to those that do not attend college (King & Baxter Magolda, 1996; Kuh, 1995; Pascarella, & Terenzini, 1991; 2005). In addition to the above stated cognitive and civic benefits of higher education, the literature provides that there are several individual longterm financial benefits associated with college attendance such as higher annual salaries and increased probability of being full time employed. Individuals with increased levels of education beyond high school and those in jobs that require specialized training, are more likely to earn higher annual salaries and be full time employed, compared to i ndividuals that do not have college experience (Baum, & Ma, 2007; Marcotte, B ailey, Borkoski, & Kienzl, 2005). Accordingly, higher education is viewed as one of the most critical avenues to reducing persistent societal income inequalities (Dickert Colin and Rubinstein, 2007; Goldhaber & Peri, 2007). Though the importance of individ ual development increased citizenship, and financial security cannot be under stressed, one of the most important benefits of higher education is the influence it has on society as a whole. Society benefits from the advanced educational attainment of its citizens through increased tax revenues, lower crime rates, and decreased reliance of individual s and families on government support systems and programs (Boswell, 2004 ; Sorey & Duggan 2008). Furthermore, scholars suggest that a highly educated citizensh ip is essential to the global competitiveness of the United States in fields such as science, engineering and medicine all of which ultimately benefit the continued economic stability of our country (Sorey & Duggan, 2008; Spellings Report, 2006). As th e previous examples provide a glimpse of the associated benefits afforded to individuals who participate in higher education it must be dually noted that access to higher

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18 education and these benefits are only available to a select few A numbers of individuals in the U.S. are excluded from participating in higher education due to such constraints as high tuition costs, institutional location, a nd scholastic ability (Gleezer, 1998) For individuals constrained by these and other barrier s the community college provide s an alternative avenue to access higher education and other advanced training opportunities, which provide workers the necessary skills to b e successful in an increasingly competitive job market. Impact and Influence of the C ommunity C ollege Community colleges are a major provider of the postsecondary education and jobrelated training received by students enrolled in institution s of higher education ( Brewer & Gray, 1999). Since 2000, student enrollment at public community colleges has steadily increase d each year D uring the 2006 2007 academic year more than 6.2 million students (35% of all postsecondary students) attended a public community college ( Provasnik & Planty, 2008 ). The e nrollment trends witnessed at community college s over the past seven year s further illustrate the ever increasing role these institutions play in opening post -secondary education to students of all academic backgrounds and proficiency levels. Enrollment increases, in a large part, can also be contributed to the appeal of community colleges to minority and non -traditional students as a viable alternative to beginning their academic studies at a four -year institution (Bragg, 2001; Provasnik, & Pl anty, 2008; Wellman, 2002). Researchers suggest, that community colleges are most appealing to diverse student populations ( e.g. Students of color low income, women, adult learners) because of their open admission policies, low tuition rates, flexible c ourse scheduling and offerings, and their close proximity to an individuals home or place of employment (Culp, 2005; Jacobson, 2005) For many years community colleges have been viewed as i nclusive institutions (About Community Colleges, n.d.) that p rovide a quality learning experience for all students regardless

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19 of previous academic experience. Wattenbarger (1953) often used the term democratic education to describe community colleges because of their continued commitment to preserving principles of open access and educational opportunities for all students. Again, all of the above examples demonstrate the ways in which community colleges extend opportunities for diverse groups of men and women to participate in higher education. F or these reasons, increased numbers of individuals are drawn to community colleges for their academic and workforce training needs Moreover, i n addition to these pronounced characteristics of the community college, increased student participation in higher education is e xtended to prospective students through community colleges sponsorship of intercollegiate athletic programs Since the 1930s community colleges have provided thousands of students the opportunity to continue their academic studies and athletic participation beyond their high school years (Reapple, Peery, & Hohman, 1982). Role o f A thletics i n P roviding A ccess to Higher Education Through recruitment, institutions solicit student prospects for the p urpose of enrollment and athletic participation ( U.S. Department of Education 1996). In the state Florida during the 20042005 academic year more than 1,500 students participated in athletics at community college s (Office of Postsecondary Education, 2007), and more than 70,000 students participated in athletics at community college s nationwide (NJCAA, 2008). Based on these participation numbers it can be inferred that community colleges and athletics programs provide student athletes with an other viable avenue to access higher education There are a number of reasons why student s select to participate in athletics at the community college (Letawsky, Schneider, Pedersen, & Palmer, 2003). For some student s athletics is seen as a viable way to gain access t o higher education (Boulard, 2008; Peltier,

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20 Laden & Matranga, 1999; London, 1992); for other prospective students, athletics is seen as a way to enhance their collegiate experience ( Castaneda Katsinas & Hardy, 2006 ; William, 1990) Furthermore s cholars suggest that athletics, f or Students of color and those from minimal to modest financial means, is a path toward upward social mobility through degree attainment, transfer to a four -year institution, or a path to a professional athletic career (Gas ton -Gayles, 2004; Hawkins, 1999; Weatherspoon, 2007). Regardless of student s academic or professional motivation for attending college, institutions and athletics programs have maintained a long history of providing opportunities for students to experien ce higher education. T hrough these experiences, students have been able to earn degree s and/ or continue their academic studies at a four -year institution. While the current literature provides several illustrations and examples of the experiences of studen ts that begin their academic studies at the community college, little is known about the academic experiences and subsequent outcomes of individuals that utilize athletics at the community college to gain entry to higher education. Purpose o f S tudy The purpose of this study was to examine the persistence and academic success rates of students that received athletically related financial aid while enrolled at the community college. For the purposes of this study, a student was deemed academically successful if he or she met one of the following three criteria within a maximum of 11 semesters ( or three and one -half years): (a) complet ion of academic requirements leading to a certificate or associates degree; (b) transfer to a four -year institution; or (c) received a certificate or associates degree and transferred to a four -year institution. A maximum of 11 semesters was set as the parameter for this study due to limitations in the availability of data regarding the disbarment of athletically relate d to students in the state of Florida prior to the 20032004 academic year. Further attention and

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21 explanation regarding the utilized time parameter and the institutional and student samples will be provided in later chapters. In this study, particular f ocus is given to the analysis of data for students who were awarded athletically related financial aid during their initial enrollment year. The U.S. Department of Education (1996) has deemed the award of athleticallyrelated financial aid as, any scholar ship, grant, or other form of financial assistance, offered by an institution, and the terms of which require the recipient to participate in a program of intercollegiate athletics at the institution ( n.p. ). Though t he award of athletically related financ ial aid serve s as an indicator to distinguish student athletes from the general student population i t must be noted that this analysis does not encompass all student athletes from the 20042005 student cohort Due to the indicators used to select students for this study, it is possible that s ome students that participated in athletics during their tenure at the community college were excluded because they were not awarded athletically related financial aid. As a result the terms student athlete and ath lete used in this study refer only to those students who received athleticallyrelated financial aid while attending a community college in the state of Florida. Research Q uestions By addressing issues that have been neglected in previous literature th is study aim s to expand the knowledge base of information regarding student athletes at the community college. Accordingly, t he following research questions guide the focus of this empirical study: 1 To what extent do academic performance (i.e., GPA, credit hours enrolled, credit hours earned) degree attainment and four year transfer rates differ between full time first -time (FTFT) enrolled student athletes compared to t heir peers at the community college ?

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22 2 What effect do individual, pr e -college and institutional characteristics have on the academic performance, degree attainment and four year transfer rates for student athletes, compared to their non athlete peers ? Statement of P roblem Community college students and student athletes have been highlighted in much of the recent literature due to their proclivity to perform lower academically than their institutional peers. As a result, the impetus for this study stems from two primary issues that have received wide attention from schola rs and institutional leaders in recent years: 1) l ow degree completion and four -year transfer rates for students who begin their academic studies at the community college; and 2) high attrition and low graduation rates of student athletes at four year NCAA affiliated institutions. This study intends to examine academic performance, degree attainment, and four -year transfer rate s within the provided sample of community college student athletes When examining academic outcomes for community college students, it is quickly obvious that a large number of students have intentions of completing a degree and /or transferring to a four year institution but only a small percentage of these students actually complete these intended goals (Boswell 2004) R ecent esti mat es suggest only 20% of community college students who intend to transfer to a four -year institution will do so within three ye ars (Doyle, 2006; Laanan, 1996) Bailey, Calcagno, Jenkins, Keens and Leinbach (2005) using Student Right to -Know and Campus Security Act [SRK] data for the 20022003 academic year found that only 16% of full time first time ( FTFT ) enrolled community college students had transferred to a four -year institution after three years and only 22% earned a postsecondary degree or cer tificate within the same time period despite their initial intentions. The result of i ncreased enrollment (Provasnik & Planty, 2008) and decreased student success rates (i.e., degree completion, transfer) at community college s has attracted the attention

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23 of scholars, administrators, and higher education constituents. Dougherty and Townsend (2006) suggested With increased attention has come greater demand for community colleges to document their claims of success and allay cont inuing concerns over low transfer and degree attainment rates (p. 6). Alt hough this increased attention has also prompted a greater emphasis and focus on documenting degree attainment and four -year transfer rates for community college students within high er education (Dougherty and Townsend, 2006; Laanan, Hardy, and Katsinas, 2006) these concerns have only recently begun to focus on the success rates of student athletes. S everal institutional and national athletic governing board policies have been ins tituted to document the academic performance of student athletes at four -year colleges and universities but similar policies have not been proposed for documenting the academic performance of student athletes at institutions classified as less than four -y ear. The impetus for increased monitoring of student athletes performance at four -year institutions was due to the negative reputation held by colleges and universities for moving students from college freshmen to college graduate. For many years, across all sports and institutional types, student athletes at four year institutions have lagged behind their peers in degree completion and time to degree completion (Ferris, Finster, & McDonald, 2004). S ince the 1980s the academic performance record of stude nt athletes has led to increased monitoring of students behaviors at National Collegiate Athletic Association (NCAA) Division I (Division I) & Division II (Division II) member institutions M ore specifically greater focus has been placed on monitoring the academic performance of student athletes who participate in high profile sports often referred to as revenue generating sports (McArdle & Hamagami, 1994; Purdy, Eitzen, & Hufnagel, 1982). The cries of public citizens and educators for academic and ath letic reform have resulted in increased dialogue regarding the low degree completion and

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24 academic success rates of four -year student athletes (Watt & Moore, 2001) Again, these calls have been slow to illuminate the academic outcomes of community college student athletes, or provide substantial program s or policies to mitigate any potential barriers. A primary reason for this lack of concern regarding community college student athletes may be a product of minimal attention given to issues regarding student athletes by the academic community. E mpirical studies on community colleges have examined the impact of a number of individual and institutional factors such as race, gender, social -economic status (SES), college preparedness and institutional size on student outcomes, but few scholars and researcher s have extensively considered the impact of athletic participation in their analysis. Significance of S tudy The persistence and academic success of student athletes at the community college is a topic that has been neglected in the current literature on s tudent persistence and degree attainment. Few i nstitutional, statewide, or national studies are readily av ailable regarding athletics and athletes at community college s or the ir impact on institutional and system -wide retention (Peterman & Matz, 2000) M uch of the athletically related literature which is available is focused on topics exclusive to four -year institutions (Knapp & Raney, 1988). The tapered focus of the literature on athletics and student athletes at four -year institutions has created a sign ificant gap in the literature. One can assume that the community college student athlete population is included in the literature on four -y ear student athletes by default because all c ommunity college student athletes eventually become four -year student s and athletes. One can also assume that no inherent differences exist between student athletes at these different institutions. To date, these assumptions have yet to be proven conclusively in the literature. A continued focus of the factors which lead to increased student retention in general -and under -served students groups more specifically --is critical to the future success of the American

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25 higher education system. This study and its findings intend to assist community colleges in their quest to miti gate barriers that have plagued students academic success and persistence in recent years. This study also intends to provide community colleges and state policymakers with a progress report of the academic successes and shortcomings of students who are f inancially supported through their participation in institutionally sponsored athletic programs. Historical P erspective Until recently there has existed a great chasm between four year student athletes and non athlete students in degree completion rates and time to degree attainment (Sports Illustrated, 2008). In years prior to the present decade, stories abound of the low graduation rates of athletes participating in large, high profile athletic programs (DeBrock, Hendricks, & Koenker, 1996; Purdy, Eitzen, & Hufnagel, 1982). The publics request for reform has since resulted in increased dialogue and policies towa rd improving the degree completion and academic success rates of student athletes. In turn, increased dialogue and policies have lead to improved accountability standards regarding four -year institutions and their responsibility to graduate their student athletes (Watt & Moore, 2001) S ince 1965, new initiatives have been aimed at holding institutions accountable for the academic success of their student athletes (Heck & Taka hashi, 2006) However, as stated previously, these reforms were not focused on increasing degree completion rates for student athletes attending public community colleges in the U.S. For instance, Proposition 48 (1986), Proposition 16 (1996; 2003), and the S tudent R ight -to -K now Act of 1990( SRK ) were all intended to bring greater awareness and improve athletes academic success by minimiz ing corrupt academic practices by institutions and athletic programs through requiring greater transparency (DeBrock Hendricks, & Koenker, 1996; Heck & Takahashi, 2006; Waller, 2003).

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26 In an effort to enhance graduation rates and raise the caliber of students attending NCAA Division I and Division II institutions on athletic scholarships, Proposition 48 increased mini mum eligibility standards for recent high school graduates (Heck & Takahashi, 2006). Following the enactment of Proposition 48, high school graduates were required to have earn ed at least a 2.00 GPA in 11 core academic courses and a 700 on the Scholastic Aptitude Test (SAT) or a 17 on the ACT (Waller, 2003). In 1996, Proposition 16 (1996; 2003) again raised the minimum requirements set forth in Proposition 48 (Aries, McCarthy, Salovey, & Banaji, 2004) Approved in 1992, and effective for the 1996 freshmen student cohort, Proposition 16 increased GPA and core course completion GPA requirements to 2.0 in 13 approved high school academic core courses (e.g., English, math, natural or physical science), and required a 1010 SAT score and an 86 combined ACT score (Owings, McMillen, & Pinkerton 1995). Additionally, Proposition 16 initiated a new sliding scale to determine athletic eligibility (see Table A 1 ). The new NCAA sliding scale require d students who earned below the minimum required score on the SAT or ACT to have a high school GPA greater than 2.0 in their core courses to be eligible to participate in athletics at a Division I or Division II institution. As Propositions 48 and 16 were aimed at enforcing minimum pre -entry eligibility standards for high school students to participate in NCAA Division I and Division II intercollegiate athletic programs, the SRK (1990) focused more specifically on students pe rformance once they were admitted to an institution. In accordance with SRK (1990) legislation all postsecondary institutions (including community colleges) that receive federal funds are now required to publish student demographic information and 6 year graduation or completion rates (3 year rates for community colleges) for various categories of students (e.g.,

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27 race, sex, gender and student athletes) annually (Bailey, Calcagno, Jenkins, Leinbach, & Kienzl, 2006). L egislative measures to increase minimu m pre -entry eligibility standards for recent high school students (Propositions 48 and 16) were not applicable to student athletes entering the community college a s community colleges typically have minimum or no admission requirements. Provasnik and Planty (20 08) noted that approximately 95 percent of public community colleges in the U.S. have open admissions policies, which allow all students the opportunity to enroll and participate in intercollegiate athletics at the community college, regardless of pr evious academic record or entrance exam scores. Though Propositions 48 and 16 were not intended to directly impact community college athletics or athletes, re searchers suggest that these legislations did have an indirect impact on community colleges and co mmunity college student athletes To examine possible indirect effects on community colleges and students, Heck and Takahashi (2005) and Owings and associates (1995) examined the impact of Propositions 48 and 16 on college bound students eligibility under the new legislation s Heck and Takahashi (2005) examined the intended and unintended effects of Proposition 48 on 105 Division I football programs from 1983 to 1991. Their findings indicated an increase of approximately 7.5 percent in the number of commu nity college athletes recruited to Division I institutions, and a 4.5 percent decrease in the number of high school graduates recruited in 1991, compared to 1985 (one year prior to the enactment of Proposition 48). Heck and Takahashi concluded that this de cline in the number of recent high school graduates recruited by Division I and Division II institutions was attributed to a decreased pool of talented high school graduates who were also academically eligible to participate and compete at NCAA affiliated institutions.

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28 Owings and associates (1995) conducted a study to investigate the indirect impact of Proposition 16 on recent high school graduates potential to be eligible to participate in athletes at a four -year institution. U sing high school transcripts and entrance exam scores for a sample of 1992 high school seniors, Owings and associates (1995) found that approximately 64 percent of 1995 high school graduates were academically eligible to participate in athletics under Proposit ion 16, compared to 82 percent of the same population that would have been eligible under Proposition 48 athletic eligibility standards. Moreover, only 46 percent of Black and 54 percent of Hispanic high school seniors met the requirements put forth in Proposition 16, compared to approximately 67 percent of white and Asian college -bound high school seniors. From their study, it was further concluded that s tudents from low SES backgrounds were least likely to meet the Proposition 16 requirements (Owings, McM illen, Daniel, & Pinkerton 1995) The studies conducted by Heck and Takahashi (2005) and Owings and associates (1995) illustrate the dwindling opportunities that are available to under -performing high school students that desire to participate in athletics at four -year Division I and Division II institutions. Based on the findings from their reports, it stands to reason that community colleges will likely become the default institution for unprepared student athletes as minimum eligibility requirements steadily increase for student participation in Division I and Division II athletic programs (Hall, 2007; Prisbell, 2007; Wolverton, 2007). To further illustrate this point, the NCAA recently passed legislation to prohibit student enrollment in fraudulent c ollege preparatory schools in order to meet minimum eligibility standards for athletic participation at NCAA affiliated institutions. Effective August 2007, according to the recently enacted NCAA rule, prospective four year student athletes are prohibited from attending college preparatory schools to improve academic deficiencies (i.e. GPA, entrance test scores) in order to become academically eligible to compete

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29 at a Division I or Division II level institution (Prisbell, 20 07). The new NCAA rule states that athletes have four years from their initial enrollment year in high school to meet the eligibility standards in the requisite core academic courses. Following four years of high school a student may only take one additio nal core course at any high school recognized by the NCAA (Prisbell 2007). In the coming years unprepared student athletes may have no other option than to enroll in a community college if they desire to one day attend and participate in athletics at a D ivision I or Division II institution (Gerdy, 1997; Hall, 2007; Sperber, 2000; Wolverton, 2007). Contribution to the S tudy o f H igher Education The underlying purpose of this study is to examine the extent to which student athletes are being academically su ccessful at the community college. Consequently, t his study seeks to make a contributions to the current literature by: 1) focusing exclusively on the impact of athletic participation at the community college; 2) providing an analysis of the individual bac kground and academic performance characteristics of both student athletes and the general student population using longitudinal statewide and multi -institutional data; 3) providing further insight into the various pathways to degree completion and four ye ar attendance exhibited by students through multivariate analysis; and 4) proposing a view of student athlete s academic success at the community college within a production function framework to better understand the correlation of athletic participation to persistence, degree completion, and four -year transfer. In the end, this study strives to increase national and state awareness of the academic successes and/or failures of student athletes at the community college. Definition of Terms For the purpose of this study, the following definitions were used: Academic Success is the completion of ones academic program at the community college leading to : a) a certificate or associates degree, or b) completion of academic requirement necessary to be admitted to a four -year institution.

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30 Athletic eligibility is a set of minimum requirements as outlined by the institution, affiliated conference/league, or national governing board that a student must meet for initial eligibility, and maintain in subsequent terms, in order to continue participation in athletics. Athletically -related financial aid is any financial aid awarded to a student in which the terms require the recipient to participate in an institutions intercollegiate athletics program. College preparedness is determined by the number of content areas remediation is required prior to enrolling in college level credit courses. Commission of Athletics (COA) is the governing body which governs and oversees intercollegiate athletics and student participation at California community colleges. Delayed enro llment denotes any student that does not enter postsecondary education in the same calendar year in which they complete high school. Division I, II, and III denotes a NCAA member institutions division for legislative and competition purposes. Division I members sponsor at least seven sports for men and seven for women (or six for men and eight for women) with two team sports for each gender; Division II members sponsor at least five sports for men and five for women (or four for men and six for women), w ith two team sports for each gender, and each playing season represented by each gender; and Division III institutions have to sponsor at least five sports for men and five for women, with two team sports for each gender, and each playing season represente d by each gender. Division III member institutions do not provide athleticallyrelated financial aid for their student athletes. National Collegiate Athletic Association (NCAA) is the governing body which oversees and governs intercollegiate athletics an d student participation at four -year institutions. National Junior College Athletic Association (NJCAA) is the governing body for athletics at community colleges in the U nited S tates and Canada, except for parts of Oregon and the states of California and Washington. Pre -entry Characteristics include cognitive and academic variables such as level of college readiness, time between completion of high school and college entry, and college entrance exam scores ( SAT, ACT CPT) Student athlete is designated as any individual who receives athletically related financial aid while attending a community college Student Transfer is any student who first enrolled in a community college, and in a subsequent term, enrolled in a four -year institution in Florida aft er completing at least one academic term.

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31 CHAPTER 2 REVIEW OF LITERATURE In order to develop the conceptual model for this study and to better understand its contribution to the literature, I begin this chapter by operationally defining key terms and concepts that are essential to this topic and study. Next, I provide an overview of individual and institutional factors that have been found throughout the literature to affect community college students persistence a nd academic success; provide an overview of literature on the academic behaviors and co -curricular experiences of student athletes; and then describe previous theoretical frameworks that have been utilized in the literature to explain student persistence a nd success L astly, I present a view of student athletes academic success and persistence at the community college through the lens of a human capital theory (Becker, 1964; 1994) The review of the literature provided in this chapter was organized with t wo primary purposes in mind. First, to explore constructs that have been identified in the literature as significant factors in predicting community college students persistence and academic success and secondly, to develop a conceptual model in which to examine these constructs as a way of enhancing our understanding and general knowledge of the persistence and academic success of community college student athletes. Key Concepts a nd Terms Despite the abundance of empirical research on student persistenc e, retention, academic success and transfer, definitions applied to the preceding terms and appropriate methods for measuring these outcomes have remained ambiguous and ill -defined (Hagedorn, 2005). A major reason for this ambiguity is due to the fact that no true co nsensus exists among higher education researcher s and institutions on the most appropriate way in which to define or measure persistence and retention (Adelman, 1999; Hagedorn, 2005; Townsend, 2002) More specifically,

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32 i nconsistencies in the measurement of these student outcomes are most often found in the selection of students to include in the denominator of the utilized calculation formulas (Astin, 1971; Bean, 1990; Hagedorn, 2005; Tinto, 1987; Townsend, 2002). Throughout the followi ng section s of this chapter, using examples provided in the higher education literature I further discuss and operationally define persistence, retention, and other key terms and concepts that will be referred to throughout the remaining chapters of this study Student Persistence The following explanation has been used by scholars and researchers to differentiate persistence from retention: P ersistence is an individual measure of students continuous or progressive enrollment in higher education until a n intended educational outcome is accomplished, while r etention is an institutional or system measure of a students continuous enrollment from first year to second year (Hagedorn, 2005). Hagedorn (1995) also provides a rather easy to understand example to explain student persistence. She classified a persister as a student who enrolls in college and remains enrolled until degree completion and a nonpersister as one who leaves college without earning a degree and never returns (1995, p. 2). While, the above example s of persistence place major focus on the students successful completion of an intended outcome (i.e., degree or transfer), with no restriction on the time Horn and Berger (2004) provide an example of persistence that relies o n time and outcome to measure student persistence. In their study, Horn and Berger (2004) calculated five -year persistence rates and defined persistence as the percentage of students who were still enrolled or completed a degree after five years of initial enrol lment. Throughout the literature persistence rates are calculated for students based on their academic behaviors at a single institution However, such practices do not take into consideration students lateral or vertical movements from institution to institution. For example, a student may

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33 leave their initial institution to attend and subsequently earn a degree from another institution. In this example, the first institution may consider a student a non-persister because he or she left their initial ins titution prior to completing a degree, while the second institution considers the same student a completer or persister. Accordingly, many researchers suggest that system retention rates are more appropriate and accurate than formulas that only consider in stitutional retention or success rates (Hagedorn, 2005). Student Retention Retention rates are most often used as one -year institutional calculations of a students enrollment from first year to second year. When calculating retention rates at institu tions classified as less than four -year (i.e., community college), NCES only considers students that are first time fulltime (FTFT) enrolled and degree or certificate seeking (NCES, 2003). Not included in NCES retention calculations are students who initi ally enrolled during the fall term but did not re -enroll the following fall term due to death, permanent disability, service to federal government through armed forces or foreign aid programs, or due to participation in official church missions (Hagedorn, 2005; NCES, 2003). Also excluded from retention calculations are students who initially matriculated during the spring term of an academic year. Academic S uccess Within the context of higher education research, the term academic success can be applied to varying degrees of accomplishments experienced by students during their academic tenure. Because the term academic success is often loosely defined in the literature, the term has been described as a value laden term (Floyd, 1988, p.6) used to signify the completion of a students intended educational goal s or aspirations. Furthermore, Braxton (2003) asserted that academic success is defined by both institutions and individual as it relates to the extent to which each achieves their intended goal(s ). Within the context of the current higher education

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34 literature r esearchers have used various proxies to measure and quantify student success. Examples of p roxies used in the literature to measure student success at the community college include : communi ty college grade point average (GPA) (Schulz, 2007); job placement (Azari, 1996; Laanan, Hardy, & Katsinas, 2006); professional certificate and associates degree attainment (Opp, 2001; 2002); four -year transfer (Dougherty & Kienzl, 2006; Hagedorn & Lester, 2006; Hagedorn, Moon, Cypers, Maxwell, & Lester, 2006; McCormick & Carroll, 1997; Romano & Wisniewski, 2003); and four -year degree attainment (Alfonso, 2006; Lee, Mackie Lewis, & Marks, 1993; Philibert, Allen, & Elleven, 2008). Another important aspect to consider w hen measuring student success in addition to the selection of a proxy variable that appropriate for your population, is the selection of a time parameter in which to measure the selected outcome (i.e., two semesters, two years, 5 years etc.). Several examples of time parameters or time periods have been provided in the literature to measure student outcomes at community college and four -year institutions. For example, t he National Collegiate Athletic Association (NCAA) created the Grad uation Success Rate (GSR) and Academic Success Rate (ASR) measures to quantify six -year graduation rates for student athletes attending Division I and Division II institutions, respectively (NCAA). Another widely used index is the SRK (Public Law No: 1015 42) which set time parameters at one and one-half the normal time for degree completion. Per SRK guidelines, institution al completion or success rates are measured on the percentage of FTFT enrolled degree-seeking students who complete degree program requ irements within 150% of the estimated time for degree completion (Bailey, Calcagno, Jenkins, Leinbach, & Kienzl, 2005; Hagedorn, 2005). The above examples of student success rate calculations have been used to measure student success at both community col leges and four -year institutions. However, r egardless of the time

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35 parameter or the model selected researchers have noted several disclaimers and warnings that must be considered when calculating success rates for students attending community college s Th e following examples are provided to illustrate the atypical enrollment behaviors of community college students, and the effect these patterns have on student success rates. First, community college students often enroll in different community colleges pri or to earning a degree or transferring to a four -year institution. Second, a student may enroll at a community college with intentions of earning an associates degree, but may decide at a later time that completing additional courses without a degree will suffice. Likewise, a student may enroll with intentions of completing a course for job -related training and decide later to pursue a certificate or an associates degree (Hagedorn, 2005). Accordingly, these nomadic enrollment patterns and frequent changes in student s educational aspirations make calculating student success rates at the community college rather complicated (Hagedorn, 2005; Hagedorn & Castro, 1999; Maxwell, Hagedorn, Brocato, Moon, & Perrakis, 2002). As the above examples have illustrated, the enrollment behaviors of community college students can drastically affect institutions and researchers ability to gain an accurate picture of the true rates of success exhibited by students. S everal factors have been attributed to students movement between institutions and the frequent changes in their educational aspirations and goals in an attempt to better understand the causes of enrollment behaviors exhibited by students at the community college Researche rs have referred to these phenomena as cooling-out (Clark, 1960) and warmingup (Baird, 1971; Bragg, 1998; Hagedorn, 2004; Opp, 2001). Cooling -out Cooling -out (Clark, 1960) has been described as a process in which institutions or institutional representa tives knowingly or inadvertently re -direct students toward educational goals that are more compatible to their academic abilities to avoid future conflict,

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36 disappointment, or failure. Clark (1960) postulates that cooling-out in part diverts the education al aspirations and expectations of students by guiding them away from associate degree or four year transfer programs of study into certificate or non-degree programs. Clark considered cooling-out a major catalyst for student departure at the community col lege. Warming up In contrast, researchers suggest it is also likely that a students intended academic aspirations will increase as a result of their educational and personal experiences at the community college. The opposite behavior of cooling -out is ref erred to as warming up, which posits that students enroll with either no aspiration of obtaining a degree or with aspirations of completing a certificate program but eventually warm up or increase their degree aspirations to include an associates or b achelor degree (Baird, 1971; Bragg, 1998; Hagedorn, 2004; Opp, 2001). Factors leading to the cooling -out or warming up of students can greatly impact retention, persistence and student success rates, as well as the calculation of these outcomes by institutions, higher education systems and researchers. For example, students who declare graduation as a goal but decide later to obtain additional credits in lieu of a degree, will be counted as a non -completer or failure, regardless of the fact that they suc cessfully met their intended goal. Likewise, students who self -select a non -degree program of study but eventually transfer to a four -year institution will not be considered academically successful because they were not originally designated as a possible transfer student. These phenomena are important to this conversation of student athletes at the community college, as this study examines the impact of athletic participation on student persistence toward an earned degree or four -year transfer. More specif ically, the impact of athletic participation on the probability of cooling -out or as a warming agent to increase the likelihood of four -year transfer or degree attainment is examined.

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37 Transfer Students a nd Four -Y ear Transfer The t raditional linear transfe r is a type of transfer that is most studied and perhaps most understood by researchers (Townsend, 2002). In linear transfer, the community college serves as a stepping stone for students toward upward educational and social mobility, which is realized through completion of their first years of general education requirements prior to attending a four year institution to complete a bachelors degree program of study (Laanan, 2003). Berkner, Horn, and Clune (2000) suggested the transition from the communit y college to a four -year institution is one of the most important forms of transfer because its success (or failure) is central to many dimensions of state higher education performance, including access, equity, affordability, cost effectiveness, degree productivity, and quality (p. 3). Beyond describing the transition of a student from the community college to a four -year institution, the term transfer encompasses a number of other possible transitions between institutions and institutional types that are likely to occur. Students are likely to make several transitions between community colleges, between four year institutions, and between four -year institutions and community colleges, before obtaining a degree or leaving college completely (Berkner et al., 2000; Hagedorn & Castro, 1999). As with other terms that have been discussed in this section, researchers have applied a range of definitions to the term transfer, what it means to be transfer ready, as well as utilized several methods for calculat ing student transfer rates. A four -year transfer student is defined as any student who attends a community college and who later enrolls in a four year institution during a subsequent academic term (Romano & Wisniewski, 2003). A frequently used control for measuring student transfer is any student who accumulates, within four -years of initial enrollment, 10 or more credits hours prior to attending a four year institution (Bradburn, Hurst, & Peng, 2001; Cohen & Brawer, 2003). T he Center for the Study of Community Colleges (2001) considers a transfer student as any student who enters

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38 the community college with no prior college experience and who earns at least 12 college credits hours at both the community colle ge and four -year institution; the National Effective Transfer Consortium (NETC) views a transfer student as a student who transfer s to a four year institution during the fall term after attending and completing at least 6 credit hours at a community college during the previous semester (Berman, Curry, Nelson, & Weiler, 1990; Townsend & Wilson, 2006). Researchers have also provided various models in the literature for calculating four -year transfer rates. These models have include transfer students or poss ible transfer students that have stated four -year transfer as a goal, were enrolled in a transfer degree program, or completed a transfer degree program (Bradburn Hurst, Peng, 2001; Hagedorn, 2005). Still other scholars consider any student who enters t he community college and subsequently earns any sum of course credits as a possible four -year transfer student. Dougherty and Kienzl (2006) examined the likelihood of student transfer to a four -year institution for all community college entrants, regardles s of intent or degree program of study. The authors proposed that by considering all community college entrants as possible transfer student s they can then explicitly bring into the analysis the question of the relationship between transfer propensity and having a certain level of educational aspirations upon entering college (Dougherty & Kienzl, 2006, p. 458). In contrast to previously discussed methods for calculating transfer rates, Hagedorn and Lester (2006) suggest transfer readiness as a less err or prone (p.835) method for measuring student transfer to the four year institution. Hagedorn and Lester (2006) define transfer readiness as the progress of a community college student on the path to transfer while still enrolled in the community college (p.835). Benefits of using transfer readiness over other methods is that transfer readiness is with in the purview of the community college it can be easily measured and

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39 it does not rely on time and place. In Florida, transfer readiness is accomplished if a student completes a 36 -hour general education block at any community college or state university. According to Florida bylaws public four -year institution s and community college s must accept, in total, general education credits hours previously earne d at another public institution in the state (Florida Department of Education). Regardless of the method used for measuring graduation and four year transfer rates, c ommunity college advocates have been adamant in recent years that student success rates are misleading. The arguments of c ommunity college administrators and their constituents are steeped in previous research which illustrat e that a majority of students enter the community college with no intention of graduating or transferring to a f our -year institution (Bailey, Calcagno, Jenkins, Leinbach, & Kienzl, 2006; Brint & Karabel, 1989; Dougherty, 1994). T hey further suggest that criticizing community colleges for low completion rates would reflect a misunderstanding of their mission and the diverse goals of their students (Bailey et al., 2006, p. 494). The preceding examples provide insight into the convoluted processes that have been utilized by researchers to measure student outcomes at the community college. Though not perfect, these ef forts to measure student success are essential to the continued efforts of higher education constituents to improve the performance of community college students, and to prepare students for employment or continued study at four -year institution s I n the present age of increased institutional accountability, the documentation of student outcomes is imperative to providing valuable information to stakeholders regarding student outcomes In sum the literature provides various definitions and methods in whi ch to measure persistence, transfer and student success within the context of community college s The present

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40 study utilized several of the examples provided in the literature to measure the academic success of student athletes in the state of Florida. Sp ecifically, using a maximum of three and one half years (or 11 academic semesters), the following definitions and interpretations of persistence, degree completion, and four year transfer were used in this analysis: a cademic success was measured by the att ainment of a degree ( one -year certificate associates degree ), or four -year transfer; p ersistence was measured by continuous enrollment to degree attainment (one -year certificate associates degree) or four year transfer; and four year transfer was accomplished if a student completed any sum of credits at the community college prior to subsequently enrolling in a public college or university in the Florida State University System. Additionally, w hen measuring four -year transfer rates, scholars have primarily focused on students enrolled in degree and/or transfer programs at the community college ( Dougherty & Kienzl, 2006). The reason many scholars have limited samples to students that express transfer as a goal is to gain a better understanding of student intentions and the effect these intentions on student outcomes. However, limiting analysis of transfer rates to students in transfer or degree programs and those who have earned a degree provide s a biased view of transfer rates (Dougherty & Kienzl ). This study does not set degree attainment or enrollment in a degree and/or transfer programs as a requisite for measuring four -year transfer. The above interpretations and definitions for persistence and academic success were utilized to provide the most accurate picture of the academic behaviors of student athletes, within the limitations of the utilized data set Further explanation and attention to these parameters will be provided in later chapter s. In dividual a nd Institutional Characteristics This study expands upon previous research on the impact of individual and institutional characteristics on the persistence and academic success of students attending the community

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41 college. The following section provides an overview of the individual and institutional factors utilized in this study and provides a literary foundation for the incorporation of these independent and dependent variables in the conducted analyses. Specifically, I will discuss the impac t of institutional enrollment size and location ( i.e., rural, urban, suburban), and individual background characteristics (i.e., race, gender, SES), college readiness and athletic participation on student outcomes at the community college. Over the past decade an increase has been seen in the volume of higher education research pertaining to the relationship of individual and institutional characteristics to community college students academic success ( Dougherty & Kienzl, 2006) Researchers have ex amined the impact of institutional mission (Bragg, 2001; Dougherty & Townsend, 2006; Dowd, 2003), institutional size and location (Bailey, Calcagno, Jenkins, Kienzl, & Leinbach, 2005), student support services ( Keim & Strickland, 2004), individual characte ristics (Flowers, 2006; Hagedorn & Cepeda, 2004; Hagedorn & Lester, 2006), s ocial and academic integration (Bailey, Calcagno, Jenkins, Leinbach, & Kienzl, 2006 ), and college readiness ( Haden, 2000; Roueche & Baker, 1987; Roueche & Roueche, 1994) on student goal attainment. The following section will provide an overview of studies and findings that are pertinent to this study and provide a review of the theoretical frameworks and models that have been previously employed t o explain the impact of institution al and individual factors on student success Community College M ission Community colleges are a substantial prong in the production wheel of the American higher education system. Over the past century community colleges have fulfilled a multiplicity o f roles by providing individuals open access to credit and non -credit educational and vocational training programs and services (Bragg, 2001). Because community colleges hold varied goals and objectives, they are often viewed as both reproducers of social inequality and purveyors of

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42 social mobility ( Alfonso, Sun, & Alfonso 2006; Lee, Mackie -Lewis, & Marks, 1993). The contradictory (Dougherty, 2004 ) community college mission began nearly a century ago when community colleges put at the forefront of their agenda four year transfer (Bragg). Since that time, community colleges have supplemented the transfer mission to include various educational and vocational programs designed for workforce training and, in many states, programs leading to a baccalaureate de gree (Anderson, Sun, & Alfonso, 2006; Brewer & Gray, 1999). Scholars assert that the institutional mission of community colleges can be categorized by core, vertical and horizontal dimensions (Bailey & Morest, 2004). The c ore dimension o f an institution s mission focus es on developmental and academic programs leading to associates degrees the vertical dimension include s duel enrollment, Tech Prep, four -year transfer, the community college baccalaureate (CCB), and undergraduate honors programs and the ho rizontal dimension encompasses noncredit courses intended for vocational training, continuing education, General Education Development (GED) preparation, English as a Second Language (ESL), and specialized educational summer camps for children (Bailey & Mo rest). The mission espoused by an institution or state community college system is what ultimately determines how the institution or system views, defines and measures student success (Bailey, Calcagno, Jenkins, Leinbach, & Kienzl, 2006). For example, articulation agreements between community colleges and four -year institutions indicate an emphasis being placed on student transfer from the community college to a four year institution. Articulation agreements are intended to facilitate easy transfer of s tudent credits from the community college to a four year institution (Anderson, Sun, & Alfonso, 2006; Brewer & Gray, 1999). There are varying degrees to which articulation agreements are developed between institutions in the U.S. There are currently 12 st ates (Alaska, Arkansas, Colorado, Florida, Kansas, Ohio, Rhode Island, Texas,

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43 Utah, Virginia, Washington, and West Virginia) with state -mandated articulation agreements (Anderson, Sun, & Alfonso, 2006). In addition to state mandated agreements, four -year i nstitutions have formed articulation agreements with community colleges within their state that are not endorsed or mandated by law (Anderson et al. 2006). In a review of the literature a number of studies can be found that have examined the varying de grees of state articulation agreements (i.e., formal and legally based policies, state system policies, voluntary agreements), but few have examined the impact of these agreements on student transfer rates (Anderson et al., 2006). T he study conducted by An derson and colleagues (2006) is one of the few studies available which examine s the relationship of mandated articulation agreements to student success. Anderson and colleagues (2006) examined the probability of student transfer in states with state -manda ted articulation agreements in place by 1991, compared to states with no state mandated articulation agreement. Their findings suggest when holding individual characteristics (demographic, educational, SES, enrollment characteristics) constant students i n states with articulation agreements were found to have the same probability of transferring within five years of initial enrollment, as students who enroll in states without agreements supported by law. A finding from Anderson and colleagues ( 2006) study that is most salient to the present study is that student transfer propensity increased when considering the interaction of state articulation agreements and the award of financial aid. The ir study suggested the award of financial aid was a significant factor in increas ing student transfer to a four -year institution within states with state mandated articulation agreements compared to states without agreements The findings from Anderson and colleagues (2006) study bring to the forefront the interacti on between individual

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44 characteristics and financial aid awards, suc h as athletically related aid, in increas ing transfer rates for student enrolled at the community college. Institutional C haracteristics The following section provides e xamples of the e ffect of institutional characteristics on student outcomes at the community college. To begin, Bailey, Calcagno, Jenkins, Kienzl, and Leinbach (2005) examined the relationship of institutional characteristics to student outcomes (i.e., persistence, complet ion, transfer) using a production function framework. The authors found that an institution s enrollment size was a significant factor in predicting student degree completion and four -year transfer. Bailey and colleagues (2005) proposed that students atten ding institution with enrollment sizes between 1,001 and 5,000 f ull t ime equivalency (FTE ) were approximately 15 percent less likely to have a successful outcome, compared to students attending institutions with enrollment sizes fewer than 1,000 FTEs. More over, Bailey and colleagues (2005) found that the percentage of part -time faculty members can be a significant factor in predicting student outcomes. I nstitutions with large percentages of part time faculty correlated with a decline in completion rates for students in associate degree programs. The findings from this study are consistent with previous studies that have credited smaller institutions with providing greater opportunities for students to be integrated and active participants in their environment, leading to higher completion rates (Astin, 1993; 200 5 ). Bailey and colleagues (2006) study, deep ly rooted in the literature on student social and academic integration ( Astin, Tsui, and Avalos 1996; Pascarella and Terenzini 2005, 2005), found lower st udent completion rates at institutions where more than 50 percent of the general student population consisted of women, minority, or part time students. Bailey and others (2006) concluded from their analysis of over 900 community colleges (using SRK (1990) degree completion time perimeters ) that large enrollments of part time students, Students of color and

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45 female students decreased the probability that FTFT enrolled students would complete a degree. The authors concluded that FTFT enrolled female students have a higher graduation rate than FTFT male students However, but large proportions of female students along with large proportions of part time students were associated with lower student degree completion rates for all students. Students attending in stitutions with 75 percent or more of the to tal student population comprised of ethnic/racial minority students were 28 percent less likely to graduate compared to students attending institutions with smaller minority student populations (Bailey et al., 2006) Individual Background C haracteristics Scholars have further suggested that specific individual characteristics have a strong relationship to student persistence, degree attainment, and four year transfer (Dougherty & Kienzl, 2006; Laanan, 2003). Do ugherty and Kienzl (2006) and Laanan (2003) found SES to be a significant factor in predicting degree aspirations and four year transfer for community college students. Dougherty and Kienzl (2006) using a social and academic integration model (Braxton, 2000; Tinto, 1993) and Laanan (2003) a status attainment (Blau & Duncan, 1967) and undergraduate socialization (Sewell & Hauser, 1972; Sewell, Haller, & Ohlendo rf, 1970) theoretical framework, each concluded that students from lower SES backgrounds were less likely to complete a degree compared to students from higher income families. Dougherty and Kienzl (2006) in their analysis of data from the National Education Longitudinal Study of the 8th Grade (NELS: 88) and beginning Postsecondary Student Longitudina l Study (BPS: 90) asserted that the probability of transferring from a community college to a four year institution was higher for single students with no dependents and for students were not employed or work less than 40 hours a week. Additionally, Dough erty and Kienzl (2006) concluded that students who se parents completed college and earn higher annual

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46 incomes had a significantly higher probability of transferring to a four -year institution than students from lower SES backgrounds. Scholars further suggest that gender and enrollment status (full time/parttime) play a significant role in predicting student academic performance and degree completion (Bailey, Calcagno, Jenkins, Leinbach, & Kienzl, 2006; Laanan, 2003). Bailey and others (2006) asserted tha t female students out perform male students and have an increased probability of completing a degree at the community college compared to their male peers. Recent studies have further suggested that students with higher degree aspirations have a greater p robability of graduating with an associates degree or transferring to a four -year institution. Bailey, Leinbach, and Jenkins (2006) suggested that students who enter the community college with intentions of eventually earning a bachelors or graduate degre e are more likely to complete a certificate, associates degree or transfer to a four year institution within six years, compared to students with no advanced degree aspirations. Bailey, Leinbach and Jenkins (2006) found that students who aspired to highe r educational attainment were 15 percent more likely to have a successful outcome at the community college than students with no bachelor degree aspirations. Horn, Peter, and Rooney (2002) explored the impact of individual characteristics on degree compl etion for community college students in a study conducted for the National Center for Educational Statistics. Using a national sample of the 19992000 undergraduate student cohort, Horn and colleagues (2002) found that 75 percent of students have at least one risk factor a student attribute or characteristic that was negatively correlated to degree completion. Student risk factors as noted by Horn and colleagues (2002) included: delayed entry to college, high school dropout or GED recipient, part -time e nrollment ; financially independent, single -parent status, have dependent children or spouse living within their household, or are employed full -

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47 time. Horn and colleagues (2002) argued that students with these particular risk factors were statistically less likely to complete college compared to students who were not restricted by such characteristics. The authors further suggested that some student groups are particularly disadv antaged when entering the community college such as Native American/Alaska Native, Black and disabled students Students from these backgrounds were found to have, on average, between two to three of the above risk factors Horn and colleagues (2002) stud y suggest s that Native American/Alaska Native, Black and disabled students enter college severely disadvantaged and are more likely to leave college without a degree. Student A thlete Experience The preceding section provided a review of the literature on the e ffect of institutional and individual factors on student outcomes. The forthcoming section will provide a review of the literature which speaks to the e ffect of institutional and individual characteristics on the experiences of student athletes at the community college. D espite the maturation of research on community college student outcomes, few studies have examined the academic behaviors of student athletes and the e ffect of individual and institutional factors on student athletes academic success at the community college (Knapp, 1988). This section provides an overview of both quantitative and qualitative studies that have explored the institutional experiences and academic outcomes of community college student athletes. Knapp and Raney (1988) and Sawyer (1993) each conducted institutional studies on the enrollment behaviors of community college student athletes over a decade ago. Knapp and Raney (1988) compared student athletes academic performance at the community college to their performance at the University of Nevada Las Vegas (UNLV), and to a group of UNLV students and student athletes with no prior community college experience. Though dated, Knapp and Raneys (1988) study provides a historical context in which to view the academic behaviors

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48 of student athletes at the community college. The authors found that physical education departments were the leading source of credits earned for all groups of students in their sample. Grades earned in physical education courses were also found to be on average higher than grades earned in other nonphysical education credit courses. Knapp and Raney (1988) attributed the excessive number of physical education credits earned by student athletes to a lack of oversight by institutions and community college athletic governing boards. However, r ecent legislation s put forth by the NJCAA and NCAA, have helped to curb the nu mber of physical education and other non-degree relevant courses taken at the community college (Hall, 2007). Specifically, new rules have been put in place by the NJCAA to ensure satisfactory progress within an approved college program or course (Eligibility Rules, 2008, p. 3), and NCAA require s community college transfer students to complete at least 40 percent of their course of study at the community college to be eligible for participation in athlet ics at a Division I institution. Sawyer (1 993) examined the impact of athletic participation on retention of community college transfer students attending a four -year institution in the California State University System (CSU) and the influence of individual characteristics (i.e., terms of admissi on, gender, ethnicity, age and sport category) between athlete and non athlete students. Using a social and academic integration lens (Astin, 1975; Bean & Metzner 1982, 1985; Pascarella, 1985; Spady, 1971; Tinto, 1975), Sawyer examined differences in five year retention rates betw een groups of transfer students based on athletic status (athlete/non athlete) and terms of admission to the CSU system (e.g., regular admission or special admission). According to Sawyer, students admitted to the four year inst itution based on standard admission requirements were retained at higher rates than special admitted students Additionally, special admitted students were retained at higher

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49 rates than student athletes female student athletes were retained at higher ra tes than male athletes and minor sport athletes (e.g., mens and womens cross -country track, tennis, and swimming) were retained at higher rates than students participating in major sports (e.g., mens baseball, football, basketball; and womens basketba ll, softball, volleyball). Palomar College (2002) tracked the persistence and academic performance of student athlete cohorts from the 19881989 and 20012002 academic years, and compared their performance to a sample of FTFT enrolled students in the gene ral student population over the same time period. Compared to the general student population, student athletes in their study earned proportionally more associates degrees, had higher five -year retention rates, and completed their studies in less time tha n students in the general population. It was found that 21 percent of athletes in the fall 2000 cohort received an associates degree by their fifth semester, compared to approximately 4 percent of students in the comparison group. It must be noted, howeve r, that the Palomar College (2002) report does not offer an explanation for the differences found in the academic performance and retention rates for athletes and non athlete students. The addition of information regarding the factors that contribute d to t heir results would be a valuable addition to the limited research on student athletes at the community college. The present study intends to add to the limited research provided on this topic by examining the impact of individual and institutional characte ristics on student athletes academic outcomes. Two additional studies are also important to understanding the academic performance of student athletes at the community college. Kanter and Lewis (1991) and Carr, Kangas, and Anderson (1992) conducted mult i institutional studies on the academic experiences of student athletes at the community college. Kanter and Lewis (1991) examined differences in educational

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50 goal achievement (measured in college GPA) between student athletes and non athlete students using transcript data from 11 community colleges in California. Similar to Sawyer (1993), Kanter and Lewis (1991) found that female athletes earned higher GPAs and completed more credit hours than men, and that all athletes completed more credit hours, earned slightly lower GPAs, and completed fewer transfer units per year compared to the general student population. Kanter and Lewis (1991) further suggested that differences exist in the academic performance of Student athletes of color and non athlete Students of color at the community college. Results from Kanter and Lewiss (1991) study indicated that Black and Hispanic male student athletes earned higher GPAs than Black and Hispanics male students in the general student population. In another reviewed study, Carr, Kangas, and Anderson (1992) examined the influence of athletic participation and specialized student support programs for Black male students on their persistence through four semesters at two California community colleges. From this multi institutional study, it was found that 100% of Black males participating on the basketball team persisted through four semesters, and 67% of all Black male athletic participants completed four semesters, compared to only 33% of Black male students in the general student population. Carr and others (1992) suggested that the proliferation of student social and academic integration manifested through sport participation, and the encouragement and mentorship provided by athletic coaches and oth er institutional members, contributed to the differences found in retention rates between Black male non athlete students and student athletes From their analysis, Carr and others (1992) suggested the development of student support programs for Black male and female non athlete students as a way to replicate rates of retention and graduation rates as those found within the student athletes sample

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51 In addition to the studies that have been discussed in the previous section, researchers have provided descr iptive analysis of community college student athlete participation (Brown, 1988; Castaneda, Katsinas, & Hardy, 2006; Reapple, Peery & Hohman, 1982), and explorative studies on the benefits of athletic participation on student experiences and development ( Nanney, 2008), the impact of academic support services on academic success ( Hall, 2007; Keim & Strickland, 2004), students academic achievement and the influence of athletic motivation (Cigliano, 2006), and student career development (Kornspan & Etzel, 2001). Unfortunately, many of the studies that will be discussed are limited in scope as the researchers examined a single institution or employed qualitative research conduct their analysis. T hat the scant empirical research on topics pertaining to student athletes and t he methodological limitations of the published studies as a whole, lends itself to further exploration of the successes, failures and academic behaviors of community college student athletes. Th e following section provides an overview lite rature specific to the individual characteristics and experiences of community college student athletes in order to expand our general knowledge Though several studies are available on the academic behaviors of student athletes at four -year institutions, this review focuses specifically on studies that are relevant to athletics and the experiences of student athletes at the community college. Characteristics o f Student A thletes There is little known about the characteristics of student athletes at the community college beyond gender and racial compositions provided in the descriptive analyses from institutional studies. T o better understand student athletes as a sub -student group, a deeper awar eness of the ways student athletes at the community college differ, both academically and demographically, from students in the general student population, is needed T he following

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52 section provides an overview of the available literature which speaks to th e academic and demographic characteristics of community college student athletes. Hall (2007) and Brown (2004) referred to community college student athletes as at -risk students because they are less likely to complete an associate degree or certificate, and are more inclined to perform lower academically than their non athlete peers Hall (2007) and Brown (2004) assert that the individual characteristics of a large percentage of student athletes can be characterized as first generation, academically unde rprepared, undecided on academic major learning disabled, and are more likely from an under represented ethnic/racial group. Previous research tells us that student characteristics such as first generation, academically underprepared, and learning disabl ed are likely to reduce the probability of student degree attainment and four -year transfer. Accordingly, Hall (2007) proposed that a different type of learning environment is needed to promote the success and retention of community college student athl etes (p. 3). In his 2007 qualitative analysis, Hall explored the impact of a learning community on student athletes retention and academic success at a single institution in California. From Halls institutional case study, the conclusion was drawn that student athletes categorized as academically at -risk performed better academically at the community college, when involved in a learning community organized to connect students with similar academic goals and co -curricular experiences. Hall (2007) suggeste d that learning communities comprised of students with similar academic and extracurricular activities, provide student athletes with peer support and the necessary motivation to succeed in higher education. In another institution al case study, Richards (1990) provide d a descriptive analysis of athletic participation by gender, age, race and educational aspiration (i.e., degree, four year

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53 transfer). In Richards (1990) report of Modesto Junior College (MDJ), a single campus community college located in Cal ifornia he found that a majority of student athletes attending MDJ during the 19881989 academic year were White (23% were Students of color ), 84 percent were traditional aged (under 21 years of age) and 96 percent had obtained a high school diploma pri or to their initial enrollment In comparison, 86 percent of students in the general student population had obtained a high school diploma prior to their initial enrollment Furthermore, s tudent athletes in the sample utilized by Richards (1990) maintained an overall mean 2.10 GPA (physical education courses not included) and 46 percent of the student athletes stated transfer to a four year institution as their intended goal. In addition to the studies that have been discussed, Lewis and Marcopulos (1989) conducted a five year longitudinal study of athletic participation in at San Joaquin Delta College (SJDC) during the 19831984 and 19871988 academic years From Lewis and Marcopulos (1989) analysis, it was concluded that Black students represented between 12% and 17% of the total student athlete population, but represented only 5 % to 7 % of general student population. Lewis and Marcopulos s (1989) report further illustrated that 25 percent of athletes enrolled in 1983 completed an associates degree and mai ntained a GPA between 2.08 and 2.21 over the five year period of the study. The literature also provides examples of studies that have utilized descriptive statistics to examine the enrollment patterns of student athletes, and the type of grades earned by athletes in various types of courses (i.e., remediation, college level courses) For example, Hobneck, Mudge, and Turchi (2003) in their single institutional study concluded that student athletes were not aptly prepared to handle the academic or athle tic requirements that were necessary to be successful in their freshmen year in college Hobneck and colleagues arrived at this troubling conclusion based on their analysis of transcript data for student athletes attending the single

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54 institution studied. T he authors found that 14% of credit hours attempted by all athletes resulted in a grade of F (failure) or W (withdraw), and 17% of the total hours attempted were in developmental or remediation courses. In sum, t he authors concluded from their institutiona l study that the combination of inflexibility in daily athletic schedules and the lack of academic preparedness decreased students year to year retention rates and the probability of maintaining minimum academic eligibility requirements necessary to cont inue athletic participation their sophomore year. Benefits o f Athletic Program s to Institutions a nd Student A thletes A review of the literature provides further insight into the overall institutional (Casteneda, 2004; Castan eda, Katsinas, and Hardy, 2006) and individual benefits ( Berson, 1996; Boulard, 2008; Cigliano, 2006) of athletic programs and teams at the community college. Overall, the literature on the institutional and individual benefits of athletic programs suggests that a thletic programs a nd teams at the community college are beneficial to both institutions and student participants alike (Ca s taneda, 2004; Castaneda, Katsinas, & Hardy, 2006). First, Cohen and Brawer (2003) wrote that Athletic programs [at the community college] are presumpt ively planned so that student athletes can enjoy the benefits of extracurricular activity along with academic programs (p. 209). Second, Castaneda (2004) and Castaneda, Katsinas, and Hardy (2006) posited that institutions benefit from the presence of an athletic program through increased enrollment of full -time students, both student athletes and non athlete students alike As p er National Junior College Athletic Association ( NJCAA ) eligibility standards, a student must be enrolled full time at the commun ity college to receive athletically related financial aid and to participate in intercollegiate athletics. As a result, athletic programs can be attributed with bringing more full time enrolled students to an institution. Castaneda (2004) and Castaneda an d colleagues (2006)

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55 further argue that athletic programs and increased institutional enrollment of full time students, benefit institutions through increased revenues to the college through state FTE based funding formulas. Researchers have also suggested that a thletic programs at community colleges have a significant impact on the increased enrollment of non athlete students as well. The benefits of sponsored athletics programs at the community college are extended to the general student population throug h opportunities to participate on athletic teams as non-scholarship participants, and by enhanc ing their overall collegiate experience of traditional aged students at the community college (Berson, 1996; Castaneda 2004; Castaneda, Katsinas, Hardy, 2006; Rishe, 2003). Last but not least, researchers and athletic administrators believe that athletic programs at the community college encourage student s from minority and disadvantaged backgrounds to attend college and participate in college sports The oppo rtunity to participate in athletics at the community college provides an avenue for many students that would have never considered attending college at all, if not afforded the opportunity through athletic participation (Boulard, 2008) In a recent article Boulard (2008) discussed the influence of athletic programs to draw diverse groups of prospective students and student athletes to the community college. Boulard (2008) suggested that a thletic programs and community colleges have been known for reaching out to athletically -talented Students of color first -generation college entrants, and those from lower SES backgrounds. For first generation students, Students of color and those from low SES athletic participation at the community college is considered a positive factor for nurturing the academic success of student athletes, rather than the common perception of athletics as a hindrance to students academic focus and attention.

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56 Berson (1996) found that student athletes attributed their continuation in college to t heir participation in athletics and factors as full -time attendance requirements as being partially responsible for their continu ed enrollment. Cigliano (2006) interviewed administrators, coaches, and students in the Tennessee Board of Regents community college system and found that student mentoring by coaches and the academic and personal assistance made available to them by faculty and staff members were most beneficial to their students academic success and progress toward degree completion Cigliano posits the opportunities to participate in athletics at the community college gave them [student athletes] guidance and assistance in obtaining educational opportunities and planning their career paths (p. 92). Support S ervices on A cademic S uccess Student affairs offices at the community college also play a major role in assisting student athletes to be successful in accomplishing their academic pursuits. Significant progress has been made over the past four decades to increase the scope and availability of services offered to students and student athletes at the community college (Mattox & Creamer, 1998) Since this time m any community colleges have instituted support services and made available financial resources to hire support staff speci fically to assist student athletes in their academic pursuits (Druehl, 1992; Mattox & Creamer, 1998). In 1992, Druehl explored the impact of student services on the success of student athletes at the community college. Specifically, Druehl (1992) examined the relationship between the academic achievement of football players (measured by semester GPA) and the support services provided to them at their institution. Druehl (1992) u sing a social system model (Getzels 196 8), found n o significant relationship between football players grade point average during the sport season even when considering the combination of counselor contact, participation in orientation and the development of an education plan. However, when counselor contact was isolated from

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57 part icipation in orientation and the development of an education plan, Druehl (1992) found a significant positive effect on students GPA during their sport season Druehl (1992) proposed that football players benefited academically from increased counselor contact which suggests that support services have a positive effect on student athletes academic performance when considering students GPA. Two additional studies also examined the impact of programs and services at the community college on student ath letes academic success First, Hobneck, Mudge, and Turchi (2003) conducted an assessment of an institutional program aimed at improving the academic success and retention of student athletes at a single campus community college in Illinois. According to H obneck and colleagues (2003) the completion of student educational development plans, enrollment in life skills classes, and regularly administered academic progress reports from athletes faculty members, were essential elements in promoting and encourag ing the academic success of athletes. Mora (1997) examined the existence of academic support programs for student athletes at a California community college. Mora (1997) concluded that institutions had a substantial number of programs in place to support s tudent athletes academically, including programs specifically designed to assist students to make the transition t o a four -year institution The studies conducted by Hobneck, Mudge, and Turchi (2003) and Mora (1997) highlight the impact student services a nd support staff have on the academic success of student athletes at the community college. As previous literature discussed in this chapter have vehemently argued for the importance of athletics at the community college ( e.g. provide access to higher edu cation for students from diverse backgrounds ), Hobneck, Mudge, and Turchi (2003) and Mora (1997) illustrate the importance and necessity of support services at community colleges to support

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58 student athletes once they arrive on campus. From the studies cond ucted by Hobneck and colleagues (2003) and Mora (1997), the conclusion can be made that athletic programs and institutional support services are essential to the subsequent support of student athletes at the community college. A cademic and A thletic M otivation on Academic Success The literature on the academic motivation of student athletes at the community college provides yet another context in which to explore differences between student athletes and non athlete students at the community college W hile there are no variables included in the present analysis to measure athletic and academic motivation due to limitations of the data, students motivation toward sport and academics is salient to this conversation. Throughout the literature, authors have provided evidence that student participation in athletics is a significant motivation and catalyst for students academic success (Gaston -Gayles, 2004; Hawkins, 1999; Parmer, 1994; Weatherspoon, 2007) and others have suggested that athletic motivation i s a major enticement for prospective student athletes to attend college. For instance, Parmer (1994) termed the desire to employ sports as a means to ward social mobility as the the athletic dream (n p ). Palmer (1994) defined the athletic dream as a mu ltidimensional set of behaviors and fantasies propelled by the desire to pursue super -stardom and upward mobility through sport participation: the ultimate result is a potential professional athletic career where the dream can be lived out (n p ). I n ad dition to the idea that athletics is a vehicle for social mobility via sport participation at the professional level, researchers have also explored the impact of athletic participation in increasing the desire of student athletes t o succeed academically (i.e., higher GPA), a nd the impact of sports in increasing student athletes academically related goals, such as degree completion and four -year transfer (Berson, 1996; Schulz, 2007).

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59 Schulz (2007) and Berson (1996) suggested participation in athletics at the community college, and full time enrollment eligibility requirements as instituted by junior college athletic governing boards, contributed to students academic success. U sing the Student -A thlete Motivation toward Sport and Academics Questionnaire (SAMSAQ), Schulz (2007) examined the impact of academic and athletic motivators on student athletes desire to succeed academically (measured by college GPA) at the community college Schulz (2007) found that female athletes performed better, or were more motivated, than male athletes; White athletes were more motivated than Student athletes of color Additionally, t he academic motivation of student athletes can also be measured in aggregate by exam ining student athlete degree aspirations and degree completion rates as illustrated in the study conducted by Richards (1990) In his report, Richards (1990) observed that nearly half of all student athletes at the studied institution were motivated to tr ansfer to four -year institution once they completed their academic studies at the community college Additionally, Lewis and Marcopulos (1989) noted that 25% of the student athletes enrolled at a single community college during the 19831984 academic year completed an associate degree within five years and 81 percent had completed at least 30 credit hours with GPAs averaging between 2.54 and 2.61 during the same time period. Summary of L iterature R eview I began this chapter with definitions of key terms and concepts, and then discussed the impact of individual and institutional characteristics on students academic success at the community college I t hen provided an overview of the literature pertaining to the academic behaviors and collegiate experienc es of student athletes at the community college, with special attention given to student athletes individual characteristics (i.e., demographic, academic performance) Additionally, I discussed the benefit of athletics to individuals and institutions,

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60 student support services to student athletes, and some of the academic and athletic motivational factors contribut ing to the success of student athletes at the community college. In sum, the literature suggests that the combination of national athletic a ssociation academic eligibility requirements, academic support services the community college environment and the academic motivation and encouragement provided by peers, coaches, faculty, and staff members serve as warming agents to students increased educational goal aspirations and goal attainment. All of the above factors individually and in aggregate, cultivate the accumulation of student athletes human capital through providing access to higher education opportunities to complete a degree incre ase job related skills necessary to enter the work place and provid e the academic foundation for student athletes to continue their academic studies at a four -year institution. Studies highlighted in this review utilized a number of frameworks and models to examine the retention, persistence, transfer, and degree attainment of students and student athletes at the community college. For example, r esearchers utilized academic and social integration frameworks (Bailey, Calcagno, Jenkins, Leinbach, & Kienzl, 2006; Dougherty & Kienzl, 2006; Sawyer, 1993; Carr, Kangas, & Anderson, 1992), production function frameworks (Bailey, Calcagno, Jenkins, Kienzl, & Leinbach, 2005) and status attainment and undergraduate socialization models (Druehl, 1992; Laanan, 2003) i n order to explain differences found in GPA, degree completion, retention and transfer rates within and between student populations at the community college A prevalent explanation for the successes and/or failures of college students in the literature has been grounded in both social and academic integration/involvement theories and models. Social and academic integration models and theories suggest that there are

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61 intermediating factors experienced at the institutional level which translate institutiona l policies and practices into student achievement or into a quantifiable outcome (Astin, 1999). T hese theories and models further postulate that the more students are actively involved in their academic studies and their college community and environment the higher the probability that students will reach a successful academic outcome ( e.g., degree completion). On the other hand, status attainment theories such as those advanced by Blau and Duncan (1967) purport that there are causal relationships bet ween parents educational and occupational attainment, and the educational and occupational attainment of later generations. These studies focus on the impact of individuals highest level of education achieved on labor market outcomes and highlight the i mpact and importance of social class, race, and gender in understanding the distribution of educational credentials among individuals (Zang & Thomas, 2005). In essence, researchers that utilize status attainment theories suggest, that children from higher socio -economic backgrounds have higher education and occupational goals than those from working or lower class families (Laanan, 2003). Laanan (2003) selected an undergraduate socialization lens to explore the degree aspirations of community college students. Th e undergraduate socialization model takes into account the influence of family social networks in developing students future educational and occupational goals. The undergraduate socialization model as used by Laanan (2003) views students educati onal goal attainment as a function of their environment and the influence and support provided to students through their given social environment and network The above models have approached student outcomes as a function of both their environment and th eir ties to social networks Theories provided by economist s provide yet another lens in which to view the academic behaviors and outcomes of students at the

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62 community college. In production function models, the value of higher education participation is m easured using either input or output methods (Bailey, Calcagno, Jenkins, Kienzl, & Lienbach, 2005; Psacharopoulos, 2006) To illustrate further, Bailey and others (2005) and Laanan and colleagues (2006) describe the maximum output (e.g., degree attainment higher wages, etc ) tha t can be expected given the type and volume of inputs invested (i.e., higher education experience, level of education achieved number and type of degree earned ). Input methods also consider resources committed by families, students, and others on behalf of individuals (e.g., institutional scholarships, athletically -related financial aid, support services) as investment in human capital mean while the output method considers the value of additional educational attainment, s uch as higher standard of living or greater purchasing power ( Psacharopoulos, 2006) Theoretical F ramework In the present study, I offer a model developed with consideration given to the impact of investment s in human capital by individuals and institut ions as the primary stimulus for student athletes academic success. The basic premise of human capital theory entails the effect of investments in activities on building capital -assets or goods that generate income -for future benefit (Psacharopoulos, 2006). Human capital theory views increase in intellectual capacity and job -related skills acquired through additional years of formal education or training programs as capital -c apital which facilitates ones increased future income, or increases oth er assets used to foster upward social and economic mobility (Becker, 1993; Blaug, 1976; Graf, 2006). E conomist Theodore Schultz first introduced the idea of human capital to the literature in 1960, but this idea was later advanced by Becker in his 1964 work entitled Human Capital I n Beckers (1964) original examination of human capital he focused primarily on the economic return increased education yields over an individuals lifetime compared to individuals that

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63 choose not to invest in higher education or specialized job training A ccording to Becker (1964) t he value or internal rate of return to costs associated with participation in higher education or other training opportunities is quantified in the net difference between investment cost s (i.e., forgone earning, expenses for tuition, books, and other supplies) and future gains in income (Becker, 1964; Lleras 2004). A byproduct of an investment in education and training, in addition to increased wages, is the accumulation of certain skill s which have the propensity to enhance productivity and increase educational credentials which convey a certain level of competency for productivity to future employers (Becker, 1964; Carnevale & Desrochers, 2001; Lleras 2004). Within the context of human capital theory, several studies have documented the role of community colleges in developing capital (Laanan, Hardy, & Katsinas, 2006). As mentioned previously, t he accumulation of capital (i.e., skills development, increased knowledge, higher future earning potential) at the community college is realized through job-training, certificate or associate degree attainment and through the academic preparation provided by community colleges necessary to facilitate continuation of t heir academic studies at a four -year institution (Ehrenberg & Smith, 2004; Grubb, 2002; Kane & Rouse, 1995, 1999; Leigh & Gill, 2003; Rouse, 1995). Cohen and Brawer wrote: [community colleges] maintain open channels for individuals, enhancing the social mobility that has characte rized America; and they accept the idea that society can be better, just as individuals can better their lot within it" (1996, p.37). A review of recent literature provides illustration of the positive earnings effect from community college attendance (Mar cotte, Bailey, Borkoski, & Kienzl, 2005). Goldhaber and Peri (2007) suggested that the community college has the propensity to increase individuals yearly earnings above that of individuals that do not attend college or earn a college degree Brint (2003) using

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64 the National Longitudinal Study of High School Class of 1972 and the National Longitudinal Study of Youth data bases found that a ssociate s degree recipients have a higher rate of return on their investment than individuals that attend a four year institution but never complete a degree Baum and Ma (2007) suggested that community college students who earn a degree within two years after high school graduation have total salary earnings net educational expenditures which exceed total ear nings for individuals that enter the workforce with only a high school diploma Baum and Mas (2007) study suggest that students with a degree from a community college will earn more annually than their peers who have a high diploma after nine years of ful l time work even when considering the financial debt associated with attending a community college for two years. Additionally, s everal other studies have explored the economic return of community college attendance through analysis of wage and employmen t data via national and state data sets (e.g., Azari, 1996; Laanan, Hardy, & Katsinas, 2006 ; Marcotte, Bailey, Borkoski, Kienzl, 2005). However, the present study views institutions and states investment (i.e., access to higher education through athletic recruitment and the award of athletically related financial aid ) in student athletes professional and academic future as a form of human capital The desired and ultimate product of institutions and states investment in student athletes being the successful completion of course credits enrolled at the community college, degree attainment and/ or four year transfer Based on the literature reviewed for this study, the conclusion can be made that the investment of resources (i.e., athletically -relate d financial aid, student services support) by institutions and states have an impact on the success of student athletes at the community college, as measured by retention, degree completion and four year transfer. More specifically,

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65 the reviewed studies p osit that s tudent athletes are more likely to graduate and/or transfer to four year institutions from the community college than non athlete students because of the investment s made by institutions toward student athletes academic studies via monetary and human resources Using a human capital lens I explored these assumptions using state -wide data from the Florida Department of Educations PK 20 Data Warehouse. Specifically, I explored the following two questions: 1 To what extent do academic performance (i.e., GPA, credit hours enrolled, credit hours earned), degree attainment and four year transfer rates differ between full time first -time (FTFT) enrolled student athletes and their peers at the community college? 2 What effect do individual, pre -college, and institutional characteristics have on the academic performance, degree attainment and four year transfer rates for student athletes, compared to their non athlete peers? Conceptual M odel There are s everal theoretical frameworks and conceptual mode l s provided in the literature that are helpful to better understanding the academic performance of community college student athletes and differences found between the performance of athletes and non-athlete students. Accordingly, many of the framework and models that have been discussed throughout the preceding pages were used to develop the conceptual model for this study, as well as provided guidance in the selection of a theoretical lens in which to best view the academic performance of student athletes at the community college and conduct the statistical analyses Specifically, t he presented model was inspired, in part, by the work of Dougherty and Kienzl (2006). Dougherty and Kienzl (2006) examined the impact of fo ur sets of independent variables on the likelihood of four year transfer for a sample of community college students The variables in Dougherty and

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66 Kienzls (2006) model included: 1) social background (SES, race -ethnicity, gender, age); 2) other precollege personal characteristics (academic preparation in high school, educational and occupational aspirations); 3) external demands (marital and parental status, extent and intensity of work); and 4) experiences during college (enrollment status, major, academi c and social integration). Th e conceptual model for this study has been augmented to include athletic participation in addition to students individual background characteristics, pre college characteristics, academic performance, and institutional charac teristics on the impact of the accumulation of student athletes human capital (i.e., degree attainment, four -year transfer) (see Figure 2 1 ). Recent studies highlighted in the literature review have evidence d of the impact of s tudent and institutional characteristics on the likelihood that students will complete four -year transfer or earn a degree at the community college. In addition to the literature on the impact of individual and institutional characteristics on student outc omes, the literature on h uman capital theory argue that investments in higher education provide a net positive return on individuals institutions, and state financial investment s Within this context, it is appropriate to view student participation in athletics and the award of athletically related financial aid as an investment in the educational and professional future of community college student athletes T he literature support s the appropriateness of a human capital lens as a way in which to view the success of student athletes at the community college To begin, Boulard (2008) proposed that athletics provide an opportunity for diverse groups of individuals to attend college, many of whom would not have considered college at all we re it not for the opportunity to participate in athletics. Schulz (2007) and Berson (1996) attributed students college attendance and persistence to participation in athletics and other complementary factors such as full time

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67 enrollment requirements. Cigl iano (2006) asserted that mentoring provided by coaches as well as the academic and personal assistance provided to student athletes by faculty and staff members were most beneficial to students academic success and progress toward degree attainment. The following sections will discuss in more detail the dependent variables, and the blocks of individual and institutional variables which make up the conceptual model utilized to explore the impact of individual and institutional characteristics on studenta thletes accumulation of human capital at the community college. Dependent V ariable The dependent variable, accumulation of human capital, is captured in three proxy binary variables. Each proxy dependent variable was dummy -coded (0/1) to represent degre e attainment, four -year transfer, and students completion of a degree and four -year transfer. In the utilized model, human capital accumulation is viewed as a product of athletic participation and the interaction of institutional and individual student ch aracteristics. When examining community college outcomes several studies have utiliz ed either degree attainment or transfer as the student dependent outcome (Dougherty & Kienzl, 2006; Hagedorn & Lester, 2006; McCormick & Carroll, 1997; Romano & Wisniewski 2003). In order to capture a broader range of paths travelled by community college students this study widened the scope of analysis to include all certificates and degrees earned by students at the community college Individual Background C haracteristics S tudent individual background characteristics have been incorporated into v irtually every study on persistence and degree attainment within the field of higher education. The evidence provided in many of these studies is clear that White and Asian students from higher SES backgrounds perform better academically, than students from lower SES backgrounds and

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68 Figure 2 1 Conceptual m odel for a c omparative s tudy of the p ersistence and a cademic s uccess of Florida c ommunity c ollege s tudent a thletes and n ona thlete s tudents: 2004 to 2007. Social background characteristics Student athlete status Human capital Accumulation Pre -college characteristics Academic experiences Institutional characteristics

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69 Students of color ( Dougherty & Kienzl 2006; Flowers, 2006; Horn, 1996; Horn & Premo, 1995; Laanan 2003). Additionally, studies conducted by Bailey, Calcagno, Jenkins, Leinbach, and Kienzl (2006) and Laanan (2003) have suggest ed that gender also play s a significant role in student s academic performance and degree attainment at the community college. Bailey and colleagues (2006) suggested that female students out -perform male students, and that female students also have an increased probability of completing a degree at the community college compared to their male peers. These findings suggest that perhaps student characteristics such as race, gender and SES status exert a considerable inf luence on student goal attainment. Therefore, students social background is an important aspect to consider in the discussion of student outcomes at the community college. Within the scope and limitations of this study and the utilized data, students ind ividual background characteristics were restricted to students race, gender and SES status. Student Athlete Status The impact of athletic participation at the community college is the primary focus of this empirical study. The higher education literature is replete with examples regarding the impact of athletic participation on students academic outcomes at four year institutions, but little evidence of the impact of athletic participation at the community college is available. The institutional study con ducted by Palomar College (2002) and other studies that have been highlighted herein provide further insight into the academic experiences of student athletes. Palomar Colleges report revealed that student athletes earned more associates degrees, had higher five -year retention rates, and completed academic programs in less time than students in the general student population When considering gender, Kanter and Lewis (1991) asserted that female athletes earned higher GPAs and completed more credit hour s than male students and student athletes. In the study conducted by Berson (1996) student athletes were found to have attributed

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70 their continuation in college to participation in athletics and full time attendance requirements Lastly Cigliano (2006) su ggested athletic participation at the community college is a source of guidance in student athletes educational and professional goal planning. On the contrary, Kanter and Lewis (1991) suggested that student a thletes are less successful academically than students in the general student population. Kanter and Lewis (1991) found that student athletes earned slightly lower GPAs and completed fewer transfer units per year than students in the general student population. Additionally, Schulz (2007) found that female athletes were more motivated than male athletes and White athletes more motivated than Student athletes of color Based on the findings from these, the presented model t ake s into account sport participation when examining outcomes at the community college. Pre -C ollege Characteristics In addition to students social background characteristics pre -college characteristics were included the model for this study. The group of pre -college characteristics incorporate variables which include number of years between high school and college entrance, entrance exam scores (ACT, SAT, CPT), high school GPA and the content areas and number of content areas remediation is needed (i.e., math, reading, writing). Specifically, entrance exam scores (ACT, SAT, CP T) were used as prox ies to quantify students level of college readiness. The utilization of pre -college characteristics in the model provides further insight into the factors that support or impede students academic performance at the community college. Accordingly, s cholars have long considered academic readiness as a significant factor in predicting student success. Roueche and Baker (1987) wrote over two decades ago about the over representation of underprepared students at the community college, and the impact of academic under -preparedness on student success in higher education Roueche and Baker (1987) wrote in their book titled Access and Excellence, The diversity among community college

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71 students is accompanied, for the most part, by academic achi evement scores skewed toward the lower levels (p. iii). They continued by saying, From this situation arises a question all too familiar to those who work in community colleges: Can both access and high academic standards be achieved? (p. iii). Roueche and Baker (1987) concluded that findings clearly support the contention that open access can be maintained and excellence achieved at the same time (p. iv). Since that time scholars have continued to explore the impact of academic readiness and time to college on student outcomes at the community college. Academic E xperiences In addition to academic readiness the academic experiences of students in college (i.e., GPA, cou rse credits enrolled, course credits earned ) have a substantial impact on their persistence to degree attainment or transfer (Cabrera, Burkum, LaNasa, 2005; Peng, Lee, & Ingersoll, 2002) Scholars further suggest that gender and enrollment status (full -tim e/part time) also play a significant role in predicting student s academic performance and degree completion at the community college (Bailey, Calcagno, Jenkins, Leinbach, & Kienzl, 2006; Laanan, 2003). From the examples provided in the literature, this st udy was restricted to students who were FTFT enrolled, and built in community college GPA, number of course credits enrolled and earned into the presented model to document the academic experiences of students at the community college. Institutional C haracteristics The impact of institutional enrollment size and geographic locale are also factors that have been examined in much of the literature on student success Several researchers have found that rural institution s with small FTE enrollment sizes are more conducive to higher student success rates than large urban or large suburban institutions (Astin, 1993; Pascarella & Terenzini, 1991). Bailey, Calcagno, Jenkins, Kienzl, and Leinbach (2005) found that students

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72 who attend ed institution s with enrollmen t sizes less than 1,000 FTEs were more likely to have a successful outcome than students attending institutions with higher FTE enrollments. Accordingly, variables for institutional enrollment size (i.e., small, medium, large, and very large) and geographi c locale (i.e., suburban, urban, and rural) have been included in the model of this study. Providing institutional characteristics in the model allows for exploration of the interaction of the preceding factors and institutional characteristics on student success The present study takes into account all of the above variables when exploring the various paths in which students and student athletes travel toward degree completion and four year transfer. The expectation and intent is that the included independent variables will provide a comprehensive picture of student athletes academic performance and subsequent academic outcomes at the community college. The results and findings from the present empirical study will be valuable to answering the presented research questions and other pressing questions regarding student athletes at the community college

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73 CHAPTER 3 METHODOLOGY The purpose of this empirical study was to examine the influence of athletic participation at the community college on the academic outcomes of FTFT enrolled student s A longitudinal multivariate methodology was employed to analyze student level record data with special emphasis on transfer and degree completion rates for student athletes. D egr ee completion and four year transfer rates were examined for all FTFT enrolled student athletes with no restriction s to students academic intentions or degree aspirations. An analysis of both student level and institutional level data were conducted t o an swer the following research questions : 1 To what extent do academic performance (i.e., GPA, credit hours enrolled, credit hours earned), degree attainment and four year transfer rates differ between full time first -time (FTFT) enrolled student athletes and their peers at the community college; 2 What effect do individual, pre -college, and institutional characteristics have on the academic performance, degree attainment and four year transfer rates for student athletes, compared to their non athlete peers ? A nswers to the presented research questions will be pursued through analysis of student level data from the Florida Department of Education s PK 20 Data Warehouse and institutional data from IPEDS. The s ubsequent findings are intended to provide supply a better understanding of current trends in the academic performance, degree completion, and transfer rates of student athletes attending Florida community colleges. In addition to the above research questions two research hypotheses are proposed

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74 Propos ed H ypothes es As previously stated, there is limited literature available on the academic performance, degree completion and four year transfer rates of community college student athletes. Furthermore, the scant literature on student athletes at community colleges provide conflicting findings in regards to the influence of athletic participation on student outcomes. For example, institutional case studies provide evidence that student athletes have higher GPAs, earn more credit hours per semester, earn mor e degrees, and complete four -year transfer more often than non athlete students (Lewis & Marcopulos 1989; Palomar College 2002). However, multi institutional studies suggest that student athletes lag behind their peers in academic performance number of degree s earned, and in the number of successful four year transfer that are completed (Carr, Kangas, & Anderson 1992; Kanter & Lewis, 1991). Based on the contradictory results found in the literature on the influence of athletic participation at the community college the following null -hypotheses are proposed: Hypothesis 1 : There are no differences in academic performance, degree attainment and four year transfer rates for FTFT enrolled student athl etes and non athlete students Hypothesis 2: Individual, pre -college and institutional characteristics equally effect s tudent athletes and non athlete students at the community college, thus there are no differences in the academic performance, degree com pletion, or four -year transfer rates between groups. I begin this chapter by present ing the research questions and associated hypothes es that will guide this exploration I will then discuss the data sources and the rationale for selecting and using secondary data and provide a description of the groups of dependent and independent var iables that have been incorporated into this study. Next, I p rovide a brief su mmary of the quantitative analytic methods that were used Chapter Three concludes with a discussion of the limitations and delimitations of the study

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75 Rationale and Benefits of Secondary D ata S ource s Secondary data for this study were provided by the Florida Department of Educations PK 20 Education Data Warehouse (EDW) and Community College a nd Technical Center MIS (CCTCMIS). The initial application to the Florida Department of Education for data in part, included a request for student demographic characteristics, pre -entry test scores, transcript data (from community college s and four -year i nstitutions ), and type and amount of financial aid awarded to all FTFT enrolled students during the 20042005 academic year. Data provided by the state of Florida were used in aggregate, as well as utilized to create new variables that were desired for thi s analysis, but not available in the data set provided by the state. Institutional level d ata from the Integrated Postsecondary Education Data System (IPEDS) were also incorporated in to the data set for this study. Since 1993, the National Center for Education Statistics (NCES) has collected data on institutions, and students attending institutions, that participate in federal student financial aid assistance programs via annual IPEDS surveys (NCES, IPEDS History). IPEDS collect primary data for all postsecondary education institutions that receive federal funds and serve s as the primary data collec tion program for NCES. For the purpose of this study, data made available in the 200 5 IPEDS survey pertaining to Florid a community colleges (i.e., geographic location and enrollment size ) were incorporated. Secondary longitudinal data were utilized from the FLDOE in order to provide a more complete picture of the community college student athlete population in the state of Florida Under the direction of the department of education, t he EDW and CCTC extract and collect longitudinal student level data from multiple educational sources and institutions Accordingly, the EDW is considered one of the most extensive education da ta warehouses in the nation (Hansen, 2006). S ince the 19951996 academic year t he EDW and CCTCMIS has served as the

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76 single repository of student level data for students attending public secondary schools, community colleges, career and technical education institutions, adult education and four year institutions in the state university system (Hansen). Florida is one of 16 states (Arkansas, Delaware, Florida, Georgia, Hawaii, Kentucky, Louisiana, Mississippi, New Mexico, Ohio, Rhode Island, South Carolina, Tennessee, Utah, West Virginia, and Wyoming) in the U.S. with a educational data warehouse that collects K 12 student data and 1 of 6 states (Arkansas, Georgia, Louisiana, Ohio, and Tennessee) with a system that allows for student level data collection and student track ing across secondary and post -secondary institutions (Hansen, 2006). The ability to analyze individual transcript data for student athletes who attended a public community college in the state is a great benefit of using data collected by EDW and CCTCMIS in this study Other available national data sources (e.g., Beginning Postsecondary Students Longitudinal Study [BPS], High School and Beyond [HS&B], National Postsecondary Student Aid Study [NPSAS]) do not provide comparable access to ind ividual student record data or have the ability to differentiate records based on the award of athletically related financial aid. Dependent V ariables The dependent variables for this study were the award of a n academic degree (professional certificate or associates degree), four year transfer, and the combination of an academic degree earned and successful completion of four -year transfer. The dichotomous dependent variables utilized in this study were created directly from data provided by the EDW and CCTCMIS. A student who first gained entry to higher education through a publicly controlled community college and earned an academic degree was considered to have reached a successful outcome. Community college students that transferred to a four-year instit ution and/or earned a degree were also considered to have reached a successful outcome. A maximum of 11 academic semesters (three and one half years ) was used to measure the successful completion of

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77 these student outcomes. T he use of multiple binary dependent variables was employed due to limitations in the data. The utilized data source did not provide information to differentiate student degree or transfer goals Providing a liberal definition of academic success is intended to capture the greatest possib le number of outcomes accomplished by community college students and student athletes (see Table 3 1 ). Table 3 1 Summary of dependent variables Dependent Variables Data Source Variable Type Scale Range Earned a cademic degree (DGCRT) CCMIS Dichotomous 0=No, 1= Yes Four year transfer (TRANS) EDW Dichotomous 0=No, 1=Yes Earned a cademic degree four year transfer (DGTRANS) EDW and CCMIS Dichotomous 0=No, 1=Yes Independent V ariables The independent variables utilized in this study were provided by the EDW and CCTCMIS and i nstitutional data w ere acquired from the IPEDS 2005 survey (see Table 3 2 ). Independent variables were separated by the following categories as represented in the co nceptual model: 1) Student athlete status 2) Individual background characteristics, 3) Pre c ollege characteristics 4) Academic experiences, and 5) Institutional characteristics Student Athlete Status The primary focus of this study was t he impact of at hletic participation on student outcomes at the community college. As stated previously, student participation in athletics was evidenced through the award of athletically-related financial aid. The Florida Department of Education has collected data on the award of athletic ally related financial aid since the 20032004 academic year Based on the award of athletically related financial aid a binary variable for s tudent athlete status (SA) was created (non athlete students is the reference group ). Student athletes in the sample represented a total of eight different sports which included: Basketball, baseball, g olf, soccer, softball, swimming/diving, tennis, and volleyball.

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78 Individual Background C haracteristics The basis for the incorporation of specific individual student characteristics (i.e., race, gender, and SES ) in this study is provided in the higher education literature Scholars have suggested that race, gender, enrollment status, and SES have a strong causal relationship to persistence, degree attainment, and four -year transfer. Previously conducted studies have provided evidence that family socio economic status (SES) is a significant factor in predicting degree aspirations and four -year transfer for community college students (Doughert y & Kienzl 2006; Laanan 2003). Scholars further suggest that gender race, and enrollment status (full time/part -time) play a significant role in predicting student academic performance and degree completion (Bailey, Calcagno, Jenkins, Leinbach, & Kienzl 2006; Horn, Peter, & Rooney 2002; Laanan, 2003). Bailey and colleagues (2006) asserted that female students out -perform male students at the community college, and female students have increased odds of completing a degree compared to their male peers. Horn, Peter, and Rooney (2002) argued students from disadvantag ed ethnic/racial backgrounds and those with physical or learning disabilities were statistically less likely to complete college compared to students who were not restricted by such characteris tics. The group of variables for individual characteristics included race (RACE), gender (SEX) and SES status (PELL). Race (RACE) was dummy -coded (White = 0 and Students of color (SOC) = 1) due to a low representation of student athletes from Asian or P acific Islander (1.1%), Hispanic (6.4%), and American Indian (0.2%) racial/ethnic groups. White students comprised a majority of students in the nonathlete and student athlete samples. White students comprised 59.2% (n = 8646) of the non athlete student s ample and 61.7% (n = 345) of student athlete sample Students with missing data for race/ethnicity were excluded from analysis. A total of 311

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79 (2.1%) nonathlete students and nine (1.6%) student athletes had missing or non reported data for race/ethnicity. Table 3 2 Summary of i ndependent v ariables and v alues Variable s V alues STUDENT ATHLETE STATUS 0= Non athlete Student 1= Student athlete INDIVIDUAL BACKGROUND CHARACTERISTICS Gender (SEX) 0= Male 1= Female Race (RACE) 0= White 1= Students of color Socio economic status (PELL) 0 = No 1 = Yes PRE COLLEGE CHARACTERISTICS Time to college (DELAY) 0 = 1 year or less 1 = other Remediation content areas (REMD) 0= None, 1= 1 of 3, 2= 2 of 3, 3 = 3 of 3 Math 0= College ready 1= Not college ready Reading 0= College ready 1= Not college ready Writing 0= College ready 1= Not college ready ACADEMIC EXPERIENCES Community college GPA (CCGPA) Continuous variable (range 0.01 4.00) Credit hours enrolled per semester (MCRL) Continuous variable (range 1.00 42.00) Credit hours earned per semester (MCRE) Continuous variable (range 0 23.00) INSTITUTIONAL CHARACTERISTICS Geographic location (GEOLOC) 1=Suburban 2=Urban, and 3=Rural Urban 1= Urban, 0= other Rural 1= Rural, 0= other FTE Enrollment size (ESIZE) 1= Small; 2= Medium; 3= Large; and 4= Very l arge Small 1= Small (500 1,999), 0= other Medium 1= Medium (2,000 4,999), 0= other Large 1= Large (5,000 9,999), 0= other Denotes reference group The variable for gender was dummy -coded with males serving as the reference group. Gender was reported for a total of 15,457 students (nonathlete and student -athletes combined). A total of 21 (0.1%) nonathlete students and three (0.5%) student athlete s were excluded due to missing or non reported data for gender. Overall, female students had the highest representation across student athlete and nonathlete samples. Female students comprised 61% (n= 9087) of the non athlete student sample and 56.1% (n= 317) of the student athlete sample.

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80 To understand the influence of SES on student outcomes at the community college a proxy variable was created based on the receipt of a Pell Grant. Pell Grants are need based financial awards given to students from low i ncome backgrounds attending public colleges and universities in the U.S. For classification purposes, Pell Grant recipients were classified as low SES and all other students as high SES A pproximately 68% of all students in both samples were classified as low SES. A pproximately 69 % (10,307) of nonathlete students and 36% (207) of student athletes in this study were considered low SES. Pre -C ollege C haracteristics The group of pre -college variables includes academically -related characteristics such as time to college (DELAY) and readiness for college level courses in math, reading, and writing (COLPREP). Since prospective students are not required to submit ACT or SAT score s to enroll in courses at the community college, some cases in the data set had missing data for ACT and SAT scores. However, students who enroll at the community college must sit for the College Placement Test (CPT) if they do not have an ACT or SAT score, to determine their academic proficiency in the content areas math, reading and writing. The variable COLPREP was constructed from data provided by the FLDOE and recoded using a multiple step process. First student scores for the ACT were converted to SAT scores using the ACT/S AT C onversion T able provided by The Princeton Review (n.d.). Next, student scores from the CPT were converted to SAT scores using the Florida Department of Education Remedial Cutoff Score table (Florida Department of Education, 200 5). The Remedial Cutoff Score T able was used to determine students academic readiness for college level math, reading, and writing In Florida students are placed in either remediation or college level courses based on their presented entrance exam sco res S tudents who score above 440 on the SAT verbal and math sections are permitted to take college level credit courses at the community college. Students that fail to meet

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81 these minimum requirements must successfully complete a prescribed set of remedial courses before moving on to college level courses. T he categorical variable, college readiness (COLPREP), was created to indicate the number of content areas remediation was needed for students in the sample. B inary variables were then recoded for each content area (0= no remediation, 1= remediation required) from the college readiness variable Thirty -five percent (n= 5,361) of nonathlete students and 38.2% (n= 217) of student athletes were not required to complete remedial courses prior to e nrolling in college level co urses at the community college. Overall, 26% (n= 4,065) of all students were deficient in at least one content area, 18.6% (n= 2,886) required remediation in two content areas and 19.1% (n= 2,952) required remediation in all th ree content areas. The variable DELAY was incorporated into the group of pre -entry characteristics to capture the impact of time elapsed between high school completion and college entrance on student outcomes. The binary variable DELAY was coded as 0 to identify students that entered college within one year or less of receipt of a high school diploma and 1 to indicate students that waited more than one year to enroll in college after high school Based on previous literature, and within the limitations of the utilized data set, the above pre -college student characteristics were included in this study. The impact of college preparedness and time between high school completion and college entrance has been examined by researchers over the past decade (Rou eche & Baker, 1987). Given the fact that a majority of community colleges allow students access, regardless of previous academic record or entrance exam scores ( Provasnik and Planty 20 08), the academic performance of less -prepared students is an important aspect to consider in this analysis. The level of college readiness of students is especially important when considering the academic

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82 performance of athletes at the community college Hall (2007) suggested that student athletes at community colleges are a t risk students because they are generally less likely to complete an associate degree or certificate and more inclined to perform lower academically than their non athlete peers R esearchers have also found that student athletes are often unprepared for college work and required to enroll in remedial or developmental courses prior to enrolling in course s for college credits ( Hobneck, Mudge, & Turchi 2003) S cholars have suggested that students who delay entry to college do not perform at the same caliber of students that immediately enroll in college immediately following receipt of a high school diploma. Horn, Peter, and Rooney (2002) suggested that students who enroll in college within a year of high school graduation are more likely to earn a degree a t the community college, compared to those that delay entry. Academic E xperiences The academic experiences of community college students were measured using three continuous variables. First, a continuous variable was created to capture students overall community college GPA. This variable was calculated using transcript data provided by the Florida Department of Education In order to calculate the overall GPA for students in the sample, the t otal grade points earned by each student was divided by the total number of credit hours they received credit for, based on their transcript records. Continuous variables for the mean credit hours enrolled (MCREN) and mean credit hours earned per semester (MCREA) were also created. To calculate mean credit hours earned and credit hours enrolled for students in the sample, the total number of semesters each student was enrolled at the community college was calculated for each student. The total credit hours enrolled and earned for each student was then divided by the total number of semesters the student had enrolled to obtain a mean average

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83 The academic experiences of students are important factors to consider when exploring degree attainment and four -year transfer rates for students at the com munity college. As mentioned in the review of the literature for this study, researchers have attributed enrollment status and the number of course credits enrolled per semester when examining the probability of a student reaching a successful outcome (Cab rera, Burkum, LaNasa, 2005; Horn, Peter, & Rooney 2002) Accordingly, the present study gives consideration to the impact of course credits enrolled and credit hours earned on degree attainment and four year transfer for students at the community college Institution al Characteristics The higher education literature speaks at length about the impact of institutional enrollment size and location on student success at the community college. Recent studies have found that students attending institutions with smaller enrollment sizes are more likely to have a successful outcome than students attending institutions with larger FTE enrollments (Astin, 1993; Bailey, Calcagno, Jenkins, Kienzl, & Leinbach, 2005; Pascarella & Terenzini, 1991; 2005). Including institu tional characteristics in the model for this study allows for the exploration of both individual background factors and institutional characteristics on success of student athletes at the community college. Institutional data were obtained from the 200 5 IPEDS survey. A categorical variable was created for geographic location (GEOLOC) to examine the impact of geographic locale on the outcomes of student athletes at the community college V ariables representing geographic locale were categorized as follows: 1=Suburban, 2=Urban, and 3=Rural. Each geographic location indicator was then dummy -coded to create two separate binary variables ( i.e., Urban = 1, other = 0; Rural = 1, other = 0). The variable for suburban was excluded from the logistic regression equa tions as it served as the reference group.

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84 Institutional FTE enrollment size provide s another index in which to examine the effect of institutional characteristics on the academic success of student athletes at the community college The variable for FTE Enrollment size (ESIZE) encompassed the following values: 1= Small (500 1,999); 2= Medium (2,000 4,999); 3= Large (5,000 9,999); and 4= Very Large (at least 10,000). The variable for institutional FTE enrollment size was dummy -code d to create three separate binary variables ( i.e., Small =1, others =0; Medium =1, others =0; and Very large =1, others =0). A dummy -variable for large institutions was not created since large institutions served as the reference group in the logistic reg ression equations The Florida Community College System is comprised of a total of 28 publically controlled institutions However, institutions included in this study were limited to institution s in the state that sponsored athletic program s during the 20042005 academic year. Due to the above criteria, Edison State College, Florida Keys Community College, and Valencia Community College and students who first matriculated at these institutions were excluded from this study. Five additional community colleg es ( Lake Sumter, Miami Dade, Okaloosa -Walton, St. Petersburg, and South Florida ) and students attending these institutions were also excluded from this study due to no representation of student athletes at these institutions in the provided data set. Lake Sumter, Miami -Dade, Okaloosa -Walton, St. Petersburg, and South Florida each sponsored athletic program s during the 20042005 academic year, but student athletes from these institutions were not represented in the data set provided by the FLDOE. No explanat ion is currently available for exclusion of data for student athletes at these institutions in the data sample. Twenty percent ( n= 4 ) of the institutions in this study are classified as rural The Integrated Postsecondary Education Data System ( IPEDS ) distinguishes institutions located in

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85 rural areas into three categories: fringe, distant, and remote. Rural institutions, per IPEDS definition, include institutions that are located in areas that can be classified as: 1) Less than or equal to five miles f rom an urbanized area, as well as rural territor ies that are less than or equal to 2.5 miles from an urban cluster (fringe); 2) m ore than five miles but less than or equal to 25 miles from an urbanized area, as well as rural territor ies that are more than 2.5 miles but less than or equal to 10 miles from an urban cluster (distant); or 3) m ore than 25 miles from an urbanized area and is also more than 10 miles from an urban cluster (remote). Twenty -five percent (n= 5 ) of the remaining institutions are classi fied as suburban and 55% (n= 11) as urban. P er IPEDS definition, suburban institutions are those institutions that are located in territories o utside a principal city and inside an urbanized area with : 1) a population of 250,000 or more (large); 2) a popul ation less than 250,000 and greater than or equal to 100,000 (midsize); or 3) a population less than 100,000 (small). Urban institutions are institutions located in territories that are classified as inside an urbanized area and inside a principal city wit h: 1) a total population of 250,000 or more (large); 2) a population less than 250,000 and greater than or equal to 100,000 (midsize); or 3) a population less than 100,000 (small). Using 2005 IPEDS survey d ata institutions in the sample were delineated by FTE enrollment size into the following categories: 1) small, 2) medium, 3) large, and 4) large. Small institutions were those with FTE enrollment sizes between 500 and 1,999, m edium institutions with enrollments between 2,000 and 4,999, l arge between 5, 000 and 9,999, and very large institutions were those with at least 10,000 FTE s. I nstitutions with medium (2,0004,999) and very large (at least 10,000) enrollments comprised 75% of all institutions included in the sample. Specifically, 50% of the institutional sample had an FTE enrollment size of 10,000 or more and 25% had an FTE enrollment size between 2,000 and 4,999.

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86 Analytic M ethods D ata analysis for this study was conducted in two stages: preliminary and advanced analysis. The preliminary analysis st age included descriptive analysis, t -t ests and analysis of variance (ANOVA) for student level and institutional level data. The advanced stage included three multivariate logistic regression s which utilized degree completion, four -year transfer, and degre e attainment and transfer as the binary dependent variables Preliminary analyses were used to compare student athletes to non athlete students on two of the three continuous independent variables that have been discussed E ight t tests were conducted to compare students on community college GPA (CCGPA) and mean course credit hours earned (MCRE), with respect to athletic status, race, gender, and socio economic status. ANOVA statistical methods were also utilized in the present study. The purpose of ANOVA analytic methods is to examine whether observed differences between two or more groups represent a chance occurrence or a systematic effect (Shavelson, 1996). ANOVAs were employed to compare GPA and mean course credit hours earned (MCRE) for athlete and no n athlete students Comparisons between athletes and nonathletes were performed with respect to institutional geographic location ( i.e., suburban urban, rural) and FTE enrollment size ( i.e., small, medium, large, very large). The utilization of state -wide longitudinal data provide d a sufficient sample size for student athletes and non athletes to conduct between group comparisons. Furthermore, p reliminary findings suggest that data for the studied samples do not violate assumptions for ANOVA procedures (e. g., independence, equal variance or normal distribution ) (Gravetter & Wallnau, 2004; Shavelson, 1996). The data analyses conducted in the advanced stage of this study included three logistic regression s Logistic regression methods were utilized to explor e the impact of multiple student and institutional factors in predicting student four -year transfer degree attainment and the

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87 combination of four year transfer and degree attainment The dependent variables under study have been coded as three separate d ichotomous variables. Traditionally, in higher education research, logistical regression methods are preferred when conducting studies that incorporate dichotomous dependent variables such as persistence, transfer, major and degree attainment and both di chotomous and continuous independent variables (Cabrera, 1994; Hossler, 1991; McArdle & Hamagami, 1994 ). L ogistic regression methods were utilized over other available quantitative statistical methods (e.g., Discriminant Analysis ) as these methods are more familiar to researchers in the social science field and results for are easier to interpret compared other available statistical methods (Terenzini, Springer, Yaeger, Pascarella & Nora 1996). Table 3 3 Summary of l ogistic r egression m odels Independent variables Block 0 Block 1 Block 2 Block 3 Block 4 STUDENT ATHLETE STATUS Athletic status (Non athlete) X X X X X INDIVIDUAL BACKGROUND CHARACTERISTICS Gender (Male) X X X X X Race (White) X X X X X SES (High SES) X X X X X PRE COLLEGE CHARACTERISTICS Delayed college entry (1 year or less) X X X X Math ready (Math ready) X X X X Reading ready (Reading ready) X X X X Writing ready (Writing reading) X X X X ACADEMIC EXPERIENCES GPA X X X Credit hours earned X X X INSTITUTIONAL CHARACTERISTICS Rural (Suburban) X X Urban (Suburban) X X Small (Very large) Medium (Very large) X X Large (Very large) X X INTERACTION TERMS Athletic status Individual characteristics X Athletic status Pre college characteristics X Athletic status Academic experiences X

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88 L ogistic regressions were conducted to explore the effect of individual and pre -college characteristics, institutional characteristics, athletic participation, and student s academic experiences on student degree attainment, four -year transfer, and the combination of degree attainment and four -year transfer. Independent variables were placed in blocks and added in succession to a baseline model to be regressed against each dependent variable (see Table 3 3 ). The baseline model (Block 1 ) for all logistic regressions that were conducted was: Y10 + 1(SA) + 2(RACE) 3(SEX)+ 3(SES)+ 1, where Y1 represents a single dependent variable (four year transfer, degree attainment, or four -j the coefficient, and 1 Limitation of S tudy the constant or error term. Using data from multiple academic years (20042007) made available through the Florida Department of Educations K 20 Educational Data Warehouse (EDW) and Community College and Technical Center MIS (CCTCMIS), this study specifically examined the persistence and academic success of community college student athletes that were awarded athletically related financial aid Data were used to measure student s academic success through community college GPA, credit hours earned, four -year transfer, and degree attainment. Full time firstti me (FTFT) enrolled student athletes in this study were identified and compared to FTFT non athlete students at the community college A s with any study that uses secondary data for analysis this particular dataset has its own limitations As this study a nd its analyses relied solely on data collected by institutions and reported to the state of Florida, errors in data collection and extraction by EDW are very likely. Thus, these errors, if any, may have resulted in erroneous results and/or findings. Seco ndly, this study is limited somewhat in its generalizability to students and institutions outside the Florida Community College System Data were analyzed for a designated sample of

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89 institutions and students within the Florida community college system. The institutional sample was limited to 20 institutions in the state that sponsored an intercollegiate athletic program during the 20042005 academic year and d ata were only attainable for student athletes who received athletically related financial aid. More specifically, f ive institutions in the state that sponsored intercollegiate athletic programs were omitted due to a lack of available data regarding the award of athletically related financial aid. Based on these limitations, d ata were not collected for A LL student athletes in the state as the only indicator of a students participation in athletics is the award of athletically related financial aid. S tudents who did not receive athletically related financial aid but participated in intercollegiate athlet ics at the community college may have been omitted. It must also be noted that some pre and post -enrollment data for students who graduated from a high school outside of Florida or who transferred to a four year institution outside the state were not att ainable. Delimitations Based on these limitations, this study does not claim to provide insight into or represent a national sample of the academic behaviors of all student athletes at the community college. Any statements included in this study are based solely on the analysis of the academic behaviors of community college student athletes in Florida. Furthermore, examining the relationship between financial aid and enrollment and persistence is a complicated endeavor ( Cellini, 2008; Dowd, 2008; Nora, Barlow, & Crisp, 2006), which involves many variables that are not available or explainable in the present data set. Though made reference to in this work, this study does not claim to discuss or explore the impact of financial aid ( e.g., athletically related grants, loans or academic scholarships) when examining the persistence and retention of students in Florida. And lastly, this study does not provide any insight into the number of students who were recruited

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90 provided with athletically -related financial aid, or invited to participate in intercollegiate athletics at the four -year institution. Such data were not available and is outside the scope of this study

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91 Social background characteristics SES Status Race Gender Student athlete status Athletic participation Figure 3 1 Conceptual m odel for the c omparative s tudy of the p ersistence and a cademic s uccess of Florida c ommunity c ollege s tudent a thletes and n ona thlete s tudents: 2004 to 2007. Human capital accumulation Degree attainment Four -year transfer Degree attainment*four year transfer Institutional characteristics Geographic location FTE enrollment size Academic experiences Community college GPA Credit hours enrolled Credit hours earned Credit hours earned/enrolled ratio Pre college characteristics Remediation content areas Math ready Reading ready Writing ready Delayed entry

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92 CHAPTER 4 DATA ANALYSIS AND RESULTS I begin c hapter four with a presentation of r esults for the descriptive statistics (univariate and bivariate), t t ests, analysis of variance (ANOVA), and General Linear Models (GLM) with binary dependent outcome variables The GLM regression model s were constructed using identical blocks of independent v ariables which will be further described and discussed in th is chapter. The selected independent variables for the regression models were regressed against the d ependent variables representing: 1) d egree attainment, 2) four year transfer, and 3) degree attainment and four -year transfer. C hapter Four concludes with a brief summary of noteworthy results from the statistical analyses that were performed. Preliminary A nalysis The preliminary analysis section of this study will provide a foundation for the advanced statistical methods (multivariate logistic regressions) that were employed The preliminary analysis section begins with a presentation of r esults from the descriptive analyses of the institutional sample, including the distribution of the students within each institution Additionally, t his section includes a discussion of the distribution of institution s in the sample by geographic locale, FTE enrollment size and number of d egree s conferred The preliminary analysis section will be followed by a presentation of results from the descriptive analysis of student level data. Next, results from the conducted t -tests and ANOVAs will be presented and discussed. The final portion of the preliminary analysis section will provide results for the descriptive analyses for the three continuous three independent variables (i.e., GPA, mean credit hours enrolled, mean credit hours earned), delineated by student athlete status.

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93 Descriptive Statist ics for I nstitutional S ample A total of 14,913 nonathlete students were included in this study, of the students included in the sample, Broward College had the largest percentage of enrolled students with 11.5% (n= 1,722) while only 0.6% (n=93) of all nonathlete student s in the sample were enrolled at North Florida (see Table 4.1 ). A total of 568 student athletes were distributed between the 20 institutions. Indian River Community College had the largest percentage of student athletes at 9% o f the total athlete population Brevard County Community College had the smallest percentage ( 2% ) of student athletes enrolled of any institution in the sample Table 4 1. Frequency of s tudents n ested in in stitution s Non Athlete Students Student Athletes Institutions Frequency Percent Frequency Percent Brevard 576 3.8 11 1.9 Broward 1,722 11.5 39 6.8 Central Florida 456 3.0 18 3.1 Chipola 209 0.4 19 3.3 Daytona Beach a 992 6.6 30 5.2 Florida CC at Jacksonville 1,409 9.4 41 7.2 Gulf Coast 404 2.7 36 6.3 Hillsborough 1,408 9.4 37 6.5 Indian River 454 3.0 51 8.9 Lake City 286 1.9 21 3.6 Manatee 750 5.0 36 6.3 North Florida 93 0.6 18 3.1 Palm Beach 1,082 7.2 23 4.0 Pasco Hernando 737 4.9 30 5.2 Pensacola 909 6.0 40 7.0 Polk 359 2.4 19 3.3 St. Johns River 391 2.6 35 6.1 Santa Fe 963 6.4 20 3.5 Seminole 889 5.9 28 4.9 Tallahassee 824 5.5 16 2.8 Total 14,913 100 % 568 100 % a Daytona Beach changed their name to Daytona State College in 2008.

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94 U sing data provided by the Integrated Postsecondary Education Data System ( IPEDS), the frequency of institution s by geographic locale within the state of Florida was explored (see Table 4 2 ). Eleven institutions (55%) in the sample were classified as urban 20% (n= 4 ) as rural, and the five remaining institutions were categorized as suburban according to the applied IPEDS definitions. Table 4 2. Frequency of i nstitutions by geographic location Geographic location Frequency Percentage S uburban 5 25.0 U rban 11 55.0 R ural 4 20.0 A descriptive analysis of institutions by FTE enrollment size was also conducted using IPEDS d ata Combined, institutions with medium (2,0004,999) and very large (at least 10,000) enrollments comprised 75% of all institutions in the utilized four level FTE enrollment classification system (see Table 4 3 ). Specifically, 50% (n = 10) of institution s in the sample had an enrollment size of 10,000 FTE or more and 25% (n = 5) had an FTE enrollment size between 2,000 and 4,999. Only two institutions (Chipola and North Florida) in the sample had an enrollment size between 200 and 1,999 FTE s Table 4 3. Frequency of i nstitutions by FTE e nrollment s ize Enrollment Size (FTE) Frequency Percentage Small ( 500 1,999 ) 2 10.0 Medium ( 2,000 4,999 ) 5 25.0 Large ( 5,000 9,999 ) 3 1 5.0 Very large (at least 10,000 ) 1 0 50.0 Distribution of D egrees C onferred This study consi dered a ll associate degrees (Associates of Arts, Associates of Science) and professional certificates ( Associate of Science Certificate, Vocational Certificate) awarded to students i n order to present a more inclusive picture of the degrees earned by students and

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95 student athletes Table 4 4 presents t he distribution of degrees awarded to student athletes and non athlete students prior to the spring 2008 term Table 4 4 Distribution of d egrees a conferred by i nstitution s Non Athlete Students Student Athletes Institution Count Percent b Count Percent b Brevard 158 4.9 5 2.9 Broward 296 9. 0 7 4.0 Central Florida 120 3.7 8 4.6 Chipola 64 2.0 7 4.0 Daytona Beach 197 6.0 14 8.0 Florida CC at Jacksonville 309 9.5 12 6.9 Gulf Coast 61 1.9 13 7.4 Hillsborough 163 5.0 10 5.7 Indian River 122 3.8 13 7.4 Lake City 81 2.5 5 2.9 Manatee 124 3.8 14 8.0 North Florida 24 0.7 4 2.3 Palm Beach 212 6.5 6 3.4 Pasco Hernando 185 5.7 6 3.4 Pensacola 178 5.5 12 6.9 Polk 90 5.0 5 2.9 St. Johns River 75 2.3 6 3.4 Santa Fe 384 11.8 10 5.7 Seminole 224 6.9 10 5.7 Tallahassee 178 5.5 8 4.6 a D egrees represents Associates of Arts, Associates of Science, Associate of Science Certificate, and Vocational Certificate. b Percentages for all institutions may not total 100 percent due to rounding. A total of 3,245 degrees were awarded to non athlete students and 175 awarded to student athletes during the three and one -half years examined. Santa Fe Community College conferred the most academic awards (n= 38 4 ) and North Florida awarded the fewest academic awards (n= 24) to non athlete students Daytona Beach and Manatee Community College each conferred a total of 14 degrees to student athletes the most academic degrees awarded to athletes. North

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96 Florida conferred the fewest a cademic credentials to student athletes. Only 2.3% of all degrees awarded to student athletes were conferred by North Florida community college Descripti ve Statistics for S tudent S ample s Frequencies and crosstabs for the student sample s were first conducted with respect to race (White and Students of color ), then gender SES, and level of college readiness. Additional analyses were conducted to explore the frequency of college ready student athletes and nonathlete students, by race and SES, for the each content area (i.e., math, reading and writing ). When considering the student samples by race, W hite students comprised the majority ethnic/racial group for both non athlete and student athlete samples. Specifically, 59 .2 % (n = 8646) of non athlete student s and 61.7 % (n = 345) of student athlete s in the sample were White (see Table 4 5 ). Students with missing data for race/ethnici ty were excluded from this analysis These exclusions include d a total of 311 (2.1%) non athlete students and nine (1.6%) student athletes that had missing or non reported data for race/ethnicity. Table 4 5. Frequency of s tudents by r ace Non athlete Stud ents Student athletes Race Frequency Percent Frequency Percent White 8,646 59.2 345 6 1 .7 Students of color a 5,956 40.8 214 38.3 a Students of color represents Black, Hispanic, Asian, and American Indian ethnic/racial backgrounds Data for g ender was reported for a combined total of 15,457 student athletes and nonathlete students It must be noted that there were missing data for the variable race. Twenty -one non athlete students (0.1%) and three (0.5%) student athletes were excluded from this analysis due to missing or nonreported data for gender Female students comprised 61% (n= 9 087) of the non athlete student sample and 56.1% (n = 317) of the student athlete sample (see Table 4 6 ).

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97 Table 4 6. Frequency of s tudents by g ender Non athlete Student s Student athlete s Frequency Percent Frequency Percent Male 5,805 39 .0 248 43.9 Female 9,087 61.0 317 56 .1 As suggested in the review of literature, student background characteristics are an important factor to consider when examining student outcomes at the community college Accordingly, a descriptive analysis of the student sample by socio-economic status (SES) was conducted to explore the distribution of low and high SES students within each sample. Results f rom the conducted descriptive analysis suggest that 69% (n = 10,307) of nonathlete students and 36.4% (n = 207) of student athletes were low SES (see Table 4 7 ). Results indicate a proportionally high number of nonathlete students at the community college are low SES compared to student athletes. Table 4 7. Frequency of s tudents by SES Non athlete Student s Student athlete s Socio Economic Status (SES) Frequency Percent Frequency Percent Low SES 10,307 69.1 207 36.4 High SES 4,606 30.9 361 63.6 Level of C ollege R eadiness by R ace, G ender, and SES Some interesting and noteworthy results were found w hen exploring the college readiness of students in the samples (see Table 4.8 ). Less than half of all student athletes and nonathlete students were considered college ready --not requiring remedi ation at the community college -in any of the three tested content areas (i.e., math, reading, and writing). Thirty -six percent (n = 5,361) o f nonathletes and 38% (n = 217) of student athletes were found to be college ready in all three content areas A pproximately 18% of nonathlete students required remediation in two of the three content areas and another 18.8% required remediation in all three areas. Nineteen

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98 percent of student athletes required remediation in two of the three content areas, and 26% required remediation in all three cognitive areas. Nineteen percent (n = 2 952) of all nonathlete and student athletes required remediation i n all three content areas. Table 4 8 Frequency of s tudents by c ollege r eadiness Non Athlete Student s Student Athlete s Frequency Percent Frequency Percent No remediation needed 5,361 35.9 217 38.2 1 of 3 content areas 3,970 26.6 95 16.7 2 of 3 content areas 2,778 18.6 108 19.0 3 of 3 content areas 2,804 18.8 148 26.1 Next, an analysis of the distribution of students in each level of college readiness was conducted by race to explore differences and similarities in college readiness for specific sub groups of students (see Table 4.9 ). Forty nine percent (n=170) of White student athletes and 45% (n= 3,906) of nonathlete White students were found to be college ready in all three content areas Ten percent of White nonathlete s and 14.8% of White student athletes required remediation in all three content areas On the other hand, only 22.5% ( 1,342) o f nonathlete Students of color and 20.6% of Student athletes of color were college ready in all three content areas. Thirty -eight percent (n = 1832) of nonathlete Students of color and 45.3% (n= 97) of Student athletes of color required remediation in all three content areas. Table 4 9 Frequency of c ollege r eady s tudents by r ace Non Athlete Students ( n=14,602) Student Athletes (n=559) White Students of color White Students of color # of Content areas Count (%) Count (%) Count (%) Count (%) None 3,906 (45.2) 1,342 (22.5) 170 (49.3) 44 (20.6) 1 of 3 2,573 (29.8) 1,322 (22.2) 67 (19.4) 26 (12.1) 2 of 3 1,250 (14.5) 1,460 (24.5) 57 (16.5) 47 (22.0) 3 of 3 917 (10.6) 1832 (30.8) 51 (14.8) 97 (45.3)

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99 The following section presents results from the analyses conducted for students level of college readiness by gender and socio-economic status. Table 4 10 illustrates students level of college readiness by gender and Tab le 4 11 provides results for the distribution of students in each level of college readi ness by SES. It was found that 42.3% (n = 2,455) of nonathlete male students and 36.3% (n = 90) of male student athletes were college ready in all three content areas. Conversely, 31.9% (n = 2,902) of female nonathlete s and 39.7% (n=126) of female studen t athletes were college ready in all three content areas. Table 4 10 Frequency of c ollege r eady s tudents by g ender Non Athlete Students (n = 14,892) Student Athletes (n = 565) Male Female Male Female # of Content areas Count (%) Count (%) Count (%) Count (%) None 2,455 (42.3) 2,902 (31.9) 90 (36.3) 126 (39.7) 1 of 3 1,421 (24.5) 2,543 (28.0) 39 (15.7) 56 (17.7) 2 of 3 965 (16.6) 1,808 (19.9) 46 (18.5) 61 (19.2) 3 of 3 964 (16.6) 1,834 (20.2) 73 (29.4) 74 (23.3) T here were also noticeable differences discovered in the level of college readiness between groups of students when considering SES (see Table 4 11). For instance, over 60% (n = 2791) of high SES non athlete s were college ready in all three cont ent areas compared to only 24.9% (n = 2570) of low SES non athlete s were college ready in all three content areas A v ery similar dichotomy between low SES and high SES students in regards to level of college readiness was found when examining student ath letes Forty -five percent (n = 163) of high SES student athletes were college ready in all three content areas compared to only 26% (n= 54) of low SES student athletes. These findings underscore the connection between SES and college readiness as discussed previously in the review of literature. Furthermore, a decrease in the distribution of high SES non athlete s in elevated levels of remediation was evident from the conducted analysis (i.e., one content area, two content areas,

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100 and three content areas) H owever, for low SES students, in general, the distribution of students at each level of college readiness remained fairly consistent There were however, s light decrease s in the distribution of high SES student athletes in elevated levels of college readi ness Table 4 11 Frequency of c ollege r eady s tudents by SES Non Athlete Students ( n=14,913) Student Athletes (n=568) Low SES High SES Low SES High SES # of Content areas Count (%) Count (%) Count (%) Count (%) No remediation required 2570 (24.9) 2791 (60.6) 54 (26.1) 163 (45.2) 1 of 3 2963 (28.7) 1007 (21.9) 28 (13.5) 67 (18.6) 2 of 3 2320 (22.5) 458 (9.9) 44 (21.3) 64 (17.7) 3 of 3 2454 (23.8) 350 (7.6) 81 (39.1) 67 (18.6) S tudents by C ognitive C ontent A rea The above sections presented data on the student samples regarding the total number of content areas in which remediation was required by race, gender, and SES for student athletes and non athlete students. In continuing an exploration of students level o f college readiness the following section provides data on the distribution of college ready students, delineated only by student athlete status, for each content area. Table 4 12 provides information on the frequency of studen ts that were college ready in math Table 4 13 the number of students college ready in reading, and Table 4 14 the number of college ready students in the content area writing. Table 4 12. Frequency of college ready students in the content area math College Ready Not College Ready Frequency Percentage Frequency Percentage Non athlete s tudent s 6,574 44.1 8,339 55.9 Student athlete s 306 53.9 262 46.1 Table 4 13. Frequency of college ready students in the content area reading College Ready Not College Ready Frequency Percentage Frequency Percentage Non athlete s tudent s 9,284 62.3 5,629 37.7 Student athlete s 294 51.8 274 48.2

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101 Table 4 14. Frequency of college ready students in the content area writing College Ready Not College Ready Frequency Percentage Frequency Percentage Non athlete s tudent s 10,943 73.4 3,970 26.6 Student athlete s 349 61.4 219 38.6 Fifty -six percent (n = 8,339) of nonathlete s who were not college ready required remediation in math while the largest percentage of non-college ready student athletes were found to be deficient in the content area reading (48.2% ). Conversely, the largest percentage s of student athletes and non athlete s were fou nd to be college ready in the content area writing. Seventy-three percent (n= 10,943) of nonathlete students and 61.4% (n= 349) of student athletes did not require reme diation in writing. Table 4 1 5. Frequency of s tudents by r ace and i nstitutional g eographical l ocation Non Athlete Students Student Athletes Race Geographic location Count Percent Count Percent White Suburban 2368 16.2 83 14.8 Urban 5561 38.1 201 36.0 Rural 717 4.9 61 10.9 Students of color Suburban 1295 8.9 59 10. 6 Urban 4409 30.2 125 22.4 Rural 252 1.7 30 5.4 Note. Data used for this analysis were taken from the IPEDS 200 5 survey. Students by Race and Gender (Geographic Location) The following section discusses the distribution of student s within institutional characteristics with respect to race and gender ( Table 4 1 5 ). Non athlete Students of color and Student athletes of color were found to be most represented at urban institutions Approximately 30% (n= 4409) of nonathlete Student s of color and 22.4% (n= 125) of Student athletes of color attended an institution located in an urban geographic area. Overall, Students of color were least represented at institutions located in rural geographic locations Likewise, White students had th e largest representation at institutions located in urban areas, and the lowest representation s at

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102 rural ly located institutions. Only 5% (n= 717) of White non athlete s and 10.9% (n= 61) of White student athletes attended a rural institution. Twenty -six percent (n = 3,931) of male nonathletes and 25% (n = 141) of male student athletes attended an institution located in an urban area (see Table 4 1 6 ). Rural serving institutions had the smallest representation of male and female student athletes. Approximately 8% of male student athletes and 8.5% of female student athletes attended an institution classified as rural. Table 4 1 6 Frequency of s tudents by g ender and g eographic l ocation Non Athlete Students Student Athle tes Gender Geographic location Count Percent Count Percent Male Suburban 1527 10.3 62 11.0 Urban 3931 26.4 141 25.0 Rural 347 2.3 45 8.0 Female Suburban 2195 14.7 80 14.2 Urban 6264 42.1 189 33.5 Rural 628 4.2 48 8.5 Note. Data used for this analysis were taken from the IPEDS 200 5 survey. Students by and Race and Gender (FTE Enrollment Size) Thirty -six percent of White nonathlete s and 30.9% of White student athletes attended a very large institution but were least represented at small institutions (see Table 4 1 7 ). Only 1.4% of all nonathlete s and 3.6% of all student athletes attended small institutions ( between 500 and 1,999 FTE enrollment ). From an analysis of the student samples by gender and institutional enrollment size, results concluded that that 20% (n = 4,090) of male nonathlete s and 41.7% (n = 6,212) of female nonathlete s were represented at very large institutions (see Table 4 18). The smallest proportion of male and female student athletes and n on athlete students were enrolled at institutions with FTE enrollments sizes between 500 and 1,999.

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103 Table 4 1 7 Frequency of s tudents by r ace and i nstitutional FTE e nrollment s ize Non Athlete Students Student Athletes Race Enrollment Size (FTE) Count Percent Count Percent White Small ( 500 1,999 ) 202 1.4 20 3.6 Medium ( 2,000 4,999 ) 1397 9.6 79 14.1 Large ( 5,000 9,999 ) 1,760 12.1 73 13.1 Very large (at least 10,000 ) 5287 36.2 173 30.9 Students of color Small ( 500 1,999 ) 100 0.7 17 3.0 Medium ( 2,000 4,999 ) 469 3.2 47 8.4 Large ( 5,000 9,999 ) 616 4.2 33 5.9 Very large (at least 10,000 ) 4,771 32.7 117 20.9 Note. Data used for this analysis were taken from the IPEDS 200 5 survey. Table 4 18. Frequency of s tudents by g ender and i nstitutional FTE e nrollment s ize Non Athlete Students Student Athletes Gender Enrollment Size Count Percent Count Percent Male Small ( 500 1,999 ) 125 0.8 15 2.7 Medium ( 2,000 4,999 ) 698 4.7 60 10.6 Large ( 5,000 9,999 ) 892 6.0 48 8.5 Very large (at least 10,000 ) 4,090 27.5 125 22.1 Female Small ( 500 1,999 ) 175 1.2 22 3.9 Medium ( 2,000 4,999 ) 1,196 8.0 69 12.2 Large ( 5,000 9,999 ) 1,504 10.1 58 10.3 Very large (at least 10,000 ) 6,212 41.7 168 29.7 Note. Data used for this analysis were taken from the IPEDS 200 5 survey. Outcomes by Level of College Readiness, R ace and Gender The following section provides the frequency of degree s earned and four -year transfer completed by level of college readiness, race and gender The present analysis utilized a time parameter of 11 academic semesters (including summer terms) to measure student persistence and the degree completion and four -year transfer. Approximately 18% (n= 2,700) of the total non athlete student sample and 4.7% (n= 27) of the student athlete sample were still enrolled during the fall 2007 term A total of 3,305 nonathletes and 177 student athletes had either earned a degree or transferred to a four year institution during the fall 2007 term. The following section will further discuss outcomes for specific sub -groups of student athletes and non athlete students.

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104 Degrees Earned by Level of College Readiness In Table 4 19, the distribution of degrees earned by level of college readiness is presented. For nonathlete students, a large majority of the total degrees awarded were earned by students that did not require remediation at the community college. Specifically, 56.6% (n=1837) of all degrees were awarded to students that were college ready. In comparison, 23.7% (n=772) of all degrees earned were earned by students requiring remediation in one content and 12.4% (n=404) by students who required remediation in two content areas O nly 7.1% (n=232) of the degrees awarded to non athlete students were earned by students that required remediation in math, reading and writing. Table 4 19. Percentage of d egrees e arned by l evel of c ollege r eadiness Level of college readiness Frequency Percent Non A thlete S tudents (n=3,176) No remediation required 1837 56.6 1 of 3 772 23.7 2 of 3 404 12.4 3 of 3 232 7.1 Student A thletes (n=175) No remediation required 88 50.2 1 of 3 32 18.2 2 of 3 27 15.4 3 of 3 28 16.0 Of the total degrees earned by student athletes, 50 .2 % (n=88) were awarded to students that were college ready in all thre e content areas. Within remaining levels of college readiness, there were only small percentage differences found between the degrees earned by students that required remediation in one content area (18.2%), two content areas (15.4%), a nd three content areas (16.0%).

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105 Degrees Earned by Race and Gender The present study also incorporate s an analysis of the distribution of degree earned by race. The conducted descriptive analysis revealed that a total of 909 non athlete Students of color and 2,267 Wh ite non athlete s earned a degree from the community college (see Table 4 2 0 ). A combined total of 173 student athletes earned an academic degree: Fifty Students of color and 123 White students. In regards to the total percentage of degrees earned for all students in the sample, White student athletes had the highest group percentage of degrees earned and non athlete Students of color had the lowest percentage of degrees earned Thirty -six percent of all White student athletes earned a degree ; only 15.3% of all nonathlete Students of color earned a degree within 11 semesters of initial enrollment. Table 4 20. Percentage of d egrees a e arned by student athlete status and r ac e Non Athletes Students Student Athletes Race Count Percent Count Percent White 2,267 26.2 123 35.7 Students of color b 909 15.3 50 23.4 Note. Total degrees earned do not include students for which race/ethnicity is unknown. Percentages equal the percentage of total degrees earned for each race by student athlete status. a Associates of Arts, Associates of Science, Associate of Science Certificate, Vocational Certificate. Similar to previous research (e.g., Bailey, Calcagno, Jenkins, Leinbach, and Kienzl 2006), female students had the highest group percentage of academic degrees earned for both athlete and non athlete samples Sixty percent (n= 1,960) of the degrees earned by nonathlete s were earned by fema le students, and 63.7% (n= 111) of degrees earned by student athletes were earned by female student s (see Table 4 2 1 ). Table 4 21. Frequency of d egrees a e arned by g ender Non Athletes Students Student Athletes Gender Count Percent Count Percent Male 1,283 39.5 63 36 .2 Female 1,960 60.4 111 63.7

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106 F our -Y ear Transfer by R ace and G ender When considering race and four year transfer, overall, the conducted descriptive statistics revealed that a higher percentage of W hite students transferred to four year institutions than Students of color Approximately 77% (n= 184) of all White nonathlete s and 86% of all White student athletes transferred to a four -year institution (see Table 4 2 2 ). Interestingly, Student athletes of color constituted only 14% of all student athletes that transferred to a four -year institution Table 4 22. Percentage of f our year t ransfer by r ace Non Athletes Students Student Athletes Race Count Percent Count Percent White 184 77.3 12 86 .0 Students of color 54 22.6 2 14 .0 a Associates of Arts, Associates of Science, Associate of Science Certificate, Vocational Certificate b Students of color includes students from Black, Hispanic, Asian, and American Indian ethnic/racial backgrounds When examining four year transfer by gender, female students had the highest percentage of four year transfer s completed across student athlete and non athlete samples (see Table 4 2 3 ). A pproximately 70 % of all student transfers completed by nonathletes were completed by female students. To put these findings into further perspective, a c ombined t otal of 254 students transferred to a four year institution and w ithin this total 176 of the se transfers were successfully completed by female students. Table 4 23. Percentage of f our year transfer by g ender Non Athlete Students Student Athletes Gender Count Percent Count Percent Male 72 30.0 6 43 Female 168 70.0 8 57 D egree A ttainment and F our -Y ear Transfer by R ace and G ender As seen in the preceding results, very few students in the given samples completed a degree or transferred to a four -year institution. In total, considering athlete and nonathlete

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107 student samples, only 1.9% (n=192) of students completed a degree and transferred to a four year institution. This section discusses the frequency o f non athlete students and student athletes that earned a degree and transferred to a four year institution prior to the spring 2008 academic term. White nonathlete students and student athletes had the highest group percentage s of academic degrees earne d and four -year transfer completed. N early 80% (n= 141) of all White non athlete s and 92% (n=11) of all White student athletes who successfully completed a degree also transferred to a four year institution (see Table 4 2 4 ). Table 4 2 4 Frequency of a cademic d egrees a R ace e arned and f our year t ransfer c ompleted by Non Athlete Student Student Athletes Race Count Percent Count Percent White 141 79 .2 11 92 Students of color b 37 20.7 1 8.3 a Associates of Arts, Associates of Science, Associate of Science Certificate, Vocational Certificate b Students of color includes students from Black, Hispanic, Asian, and American Indian ethnic/racial backgrounds Female students in the given samples represented th e highest percentage of academic degrees earned and four -year transfer completed for student athletes and non athletes students (see Table 4 2 5 ). Seventy-one percent of female non athlete s and 67% of female student athletes who completed a degree also transfe rred to a four year institution. Table 4 25. Frequency of d egrees a e arned and f our year t ransfer by g ender Non Athlete Student Student Athletes Gender Count Percentage Count Percentage Male 52 28.8 4 33 .0 Female 128 71.1 8 67 .0 a Academic degrees represents Associates of Arts, Associates of Science, Associate of Science Certificate, Vocational Certificate

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108 Descriptive S tatistics for C ontinuous I ndependent V ariables The following section examines the mean credit hours enrolled per semester credit hours earned and GPA for the non athlete s and student athletes in the included samples (see Table 4 2 6 ). The results from the descriptive analysis for the continuous variables indicated that s tudent athletes had a mean GPA of 2.59 (SD = 0.84) compared to non athlete students who had a mean GPA of 2.29 (SD = 1.17). Moreover, student athletes (M= 10.08, SD = 4. 005) were also found to have earned more credit hours per semester than non athlete s (M = 9.00, SD = 3.128). Further exploration using ANOVA and t t ests statistical methods were employed to see if differences in GPA and course credits hours earned were statistically significant. Table 4 26. Descriptive Statistics for Continuous Independent Variables Student athlete status N Mean Std. Dev iation Non Athlete Students Credit hours enrolled per semester 14,913 9.007 3.128 Credit hours earned per semester 14,891 6.186 3.691 Grade point average (GPA) 14,913 2.295 1.175 Student Athletes Credit hours enrolled per semester 568 12.539 2.942 Credit hours earned per semester 561 10.087 4.005 Grade point average (GPA) 568 2.592 0.846 Independent Sample T -Tests Independent sample t tests were conducted to explore if differences between non athlete students and student athlete s GPA and credit hours earned were significantly different Between group comparisons were made for athlete and non athlete students, and selected sub -groups of athletes and nonathlete students (e.g., Students of color female, and low SES students ). The results for the conducted t tests will be presented in this section and have been divided in to two separate parts. The f irst portion will compare groups and sub -groups on GPA and the second w ill explore group mean differences in course credits hours earned.

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109 Independent sample t t ests were conducted on the premise that the assumptions of independent t -test s (e.g., normal distribution of data, homogeneity of variance, data are independent ) were not violated. A significant p value (p < .05) on Levenes Test of Equality of Variance, h owever, suggested that the equal variance assumption had bee n violated in the analysis of GPA for selected group members in the student samples. The violation of this assumption has no substantial effect on the presented results (Hays, 1963) as the results do not assume groups have equal variance s Table 4 2 7. Ana lysis of mean GPA for s tudent athletes and n on athlete s tudents Comparisons Levenes test of equal variance Df t Mean difference Std. Error p F Sig Non athletes vs. Athletes 134.01 0 .000 653.265 8.081 .2972 0.036 .000 Non athletes (SOC) vs. Athletes (SOC) 71.16 0 .000 247.226 7.481 .4114 0.0550 .000 Non athletes (Female) vs. Athletes (Female) 90.95 0 .000 368.480 7.237 .3253 0.0449 .000 Non athletes (Low SES) vs. Athletes (Low SES) 62.07 0 .000 223.371 4.718 .2760 0.0585 .000 M ean difference is significant at the at the p < .0 5 significance level From conducted t tests significant differences were found for m ean GPA between athletes and non athlete students at the community college (see Table 4 2 7 ). A difference in GPA of .2972 was found between athletes and non athlete students. The found differences between student athletes and non athlete students GPA were significant at the .001 alpha level (t = 8.08, df = 653.265, p < .0 5 ). From the result for t he t test, conclusions can be drawn, based on the student sample for this study that non athlete s have significantly lower GPAs than student athletes Further examination into sub -groups of students illustrate d that non athlete s also have significantly lower GPAs when considering nonathlete Students of color and Student athletes of color (t = 7.48, df = 247.226, p < .0 5 ), non athlete female students and female student athletes (t =

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110 7.23, df = 368.480, p < .0 5 ), and low SES non athlete s and low SES student -athletes (t = 4.71, df = 223.371, p < .0 5 ). Additional, subsequent analyse s also revealed there were significant differences in mean credit hours earned per semester between select sub -groups of athletes and non athlete students Based on a non-significant p value ( p > .05) for Levenes Test of Equality of Variance, the equal variance assumption was met. A difference of 3 .90 (t= 2 4.49, df = 15,450, p < .0 5 ) in mean credit hours earned per semester for nonathlete s and student athle tes was found and concluded to be si gnificant at the p < .0 5 alpha level (see Table 4 2 8 ). Findings for the t tests provide evidence that nonathlete s earn significantly fewer credit hours per semester than student athletes. Further analysis illustrate d that differences between student athletes and nonathlete students were maintained, even when considering select sub -groups of non-athlete s and student athletes in the samples For instance, non athlete Students of color earned fewer credit hours than Student athletes of color (t= 1 7. 20, df = 6163, p < .0 5 ), high SES non athlete s earned fewer credit hours t han high SES student athletes (t= 14.98, df = 4949, p < .0 5 ), and low SES non athlete s earned fewer hours than low SES student athletes (t= 15.52, df = 10499, p < .0 5 ). Table 4 2 8. Analysis of c ourse c redit h ours e arned for s tudent athletes and n on athlete s tudents Comparisons Levenes test of equal variance D f t Mean difference Std. Error p F Sig. Non athletes vs. Athletes 1.140 0 .286 154 50 2 4.4 9 2 3. 90 159 .000 Non athletes (SOC) vs. Athletes (SOC) 0.162 0 .687 6163 17.270 4.21582 .24412 .000 Non athletes (High SES) vs. Athletes (High SES) 0.066 0 .797 4949 14.980 3.09020 .20629 .000 Non athletes (Low SES) vs. Athletes (Low SES) 2.285 0 .131 10499 15.528 3.92119 .2525 .000 M ean difference is significant at the at the p < .0 5 significance level

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111 Analysis of Variance (ANOVA) Between group comparisons were also incorporated into the present study to explore if differences in student s academic performance (GPA) at the community college were significantly different across institutional characteristics. The constructed ANOVA models were not intended to compare differences in GPA between student athletes and non athlete students specifically, but intended to examine differences within institutional characteristics as a whole Geographic Location T he first ANOVA model provides an analysis of s tudents academic performance at institutions located in rural, urban and suburban geographic location (see Table 4 2 9 ). The ANOVA suggested that s ignificant d ifference s in GPA were present between students at institutions located in rural, urban, and suburban geographic loca les (F = 8.68, p < .001). To better understand where specific differences were found, o rthogonal contrasts were conducted using Bonferronis P ost hoc T ests Bonferronis P ost -hoc test uses multiple t T ests to perform pairwise comparisons between group means An advantage of Bonferronis Post -hoc is that it controls the overall error rate by adjusting the experimentwise error rate according to the number of individual comparisons t hat are conducted (Field, 2005) Table 4 2 9. One way ANOVA of m ean d ifferences in s tudent GPA by g eographic l ocation Sum of squares df Mean square F p Between Groups 23.603 2 11.802 8.684 .000 *** Within Groups 21033.843 15478 1.359 Total 21057.446 15480 S ignificant differences in student s academic performance as measured by GPA were found between students attending suburban and urban institutions, and between students at suburban and rural institutions (see Table 4 3 0 ). Results from the ANOVA for GPA differences based on institutions geographic location suggests that students at suburban institutions have

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112 significantly higher GPAs than students attending urban (0 .084, p < .05 ) and rural institutions (0 .120, p < .05 ). No significant differences were found in GPA between student at urban and rural institutions. Table 4 30. Bonferronis post hoc tests of mean differences in GPA between institutional geographic locations (I ) Geographic location (group mean) (J) Geographic L ocation Mean Difference (I J) Std. Error Suburban (2.371) Urban 0 .08418 0 .02189 Rural 0 .12081 0 .04022 Urban (2.287) Suburban 0 .08418 0 .02189 Rural 0 .03663 0 .03737 Rural (2.251) Suburban 0 .12081 0 .04022 Urban 0 .03663 0 .03737 M ean difference is significant at the at the p < .0 5 significance level FTE Enrollment Size A second ANOVA was performed to examine if significant differences were present for students academic performance (GPA) at institutions with small, medium, large and very large FTE enrollment sizes. Results from the one -way ANOVA suggested that there were indeed significant differences between students academic performance (F = 7.77, p < .001) when considering an institutions FTE enrollment size (see Table 4 3 1 ). Table 4 31. One way ANOVA of mean differences in student GPA by institutional FTE enrollment size Sum of Squares D f Mean Square F p Between Groups 31.655 3 10.552 7.767 .000 *** Within Groups 21025.791 15477 1.359 Total 21057.446 15480 M ultiple comparisons of institutional characteristics using Bonferronis Post -hoc tests provided further insight into where specific differences could be found (see Table 4 3 2 ). From the performed orthogonal comparisons, results concluded that students GPA at institutions with small enrollment sizes were significantly higher than students GPA at institutions with medium

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113 FTE enrollments sizes (0 .25545, p < .05) Moreover, students GPA at institutions with medium enrollment sizes were significantly lower than students GPA at institutions with large enrollm ent sizes ( .02858, p < .05) as well as significantly lower than the GPAs earned for student s at institutions with very large FTE enrollments sizes ( .11089, p < .05) Table 4 32. Bonferroni s p ost hoc t ests of m ean d ifferences in GPA b etween i nstitutional FTE e nrollment s ize (I) Institutional FTE E nrollment Size (group mean) (J) Institutional FTE Enrollment S ize Mean Difference (I J) Std. Error Small (2.459) Medium 0 .25545 0 .06840 [500 1,999] Large 0 .12687 0 .06746 Very large 0 .14457 0 .06431 Medium (2.203) Small 0 .25545 0 .06840 [2,000 4,999] Large 0 0 12858 0 .03484 Very large 0 .11089 0 .02826 Large (2.332) Small 0 .12687 0 .06746 [5,000 9,999] Medium 0 .12858 0 .03484 Very large 0 .01769 0 .02590 Very large (2.314) Small 0 .14457 0 .06431 [at least 10,000] Medium 0 .11089 0 .02826 Large 0 .01769 0 .02590 *Mean difference is significant at the p < .0 5 significance level General L inear M odel s (GLM) with B inary Dependent O utcome V ariable s Logistic regression statistical methods were employed to better understand the factors that best predict the likelihood student s will earn a degree transfer to a four year institution, or receiv e a degree and transfer to a four -year institution Logistic regress ion s are the preferred method of analysis when dependent variables are dichotomous (Cabrera, Burkum, LaNasa, 2005; Peng, Lee, & Ingersoll, 2002; Powers & Xie, 2000) Logistic regression statistical procedures are help ful when researcher s are interested in estimating the probability that an event will occur (i.e., college enrollment, persistence, success, failure), for students with specific characteristics (Cabrera, Burkum, LaNasa, 2005; Peng, Lee, & Ingersoll, 2002; P owers & Xie, 2000).

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114 In this study, each regression model was constructed using identical predictor factors (i.e., student athlete status individual characteristics, pre -college characteristics, institutional characteristics) The following section will p resent and discuss significant findings from the conduc ted logistic regression analyses. Results will be discussed in term of odd s ratios ( E xp ( )) which represent the odds change for a one unit change in the predictor or independent variable w hen all other predictor variables in the equation are held at a constant value ( Peng, S o, S tage, & S t. John, 2002). Additionally, probabilities are another common ly used term to express odds ratios in this study P robability value s serve as a method in which to ex plain the likelihood of an event occurring for one designated group over another group (e.g., male students versus female students), and are discussed as a percentage ( Exp ( ) x 100) or decimal value ( Exp ( ) = .469). However, odds ratio calculations for continuous predictor variables are more complicated to interpolate than the presented odds ratio for categorical predictor variable s (Powers & Xie, 2000) For instances where results will be discussed for continuous variables included in the regression models, the odds ratios of an event occurring were calculated at different values of the continuous variable using the following formula: { 1( + 1 ) } ( 1 ) = { 1( ) }, 1 is the coefficients beta weight, and is the selected value of t he independent continuous variable (see Appendix B for all calculations that were performed using the above formula ). The presentation of results for the logistic regression s will begin with results for regression Model 1 (degree completion), followed by a presentation and discussion of the results for the logisti c regressions conducted for the remaining dependent variables: four year transfer (Model 2) and the interaction variable for degree attainment and four -yea r transfer (Model 3)

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115 General Linear Model 1 : Degree A ttainment A significant p value of less than p < .001 for M odel 1was found, which suggests that the regression equation including the predictor variables was significantly improved, or better fitted, than the model considering only the constant. The regression model predicted degree attainment correctly for 82.1% of the students in the sample. Model 1 contained a number of factors that were significant in predicting students propensity to earn a degre e from a Florida community college (see Table 4 3 3 ). Ten of the 24 predictor variables in the equation were found to be significant (see Table 4 34). Table 4 3 3 Binary logistic regression model measur es m odel 1: Degree attainment Chi square df Sig. Nagelkerke R Square % predicted Correctly Probability of d egree 4520.351 24 0 .000 *** 396 82.1 *** Significant at the p < .001 level Student A thlete S tatus For model 1, s tudent athlete status was a significant factor in predicting degree attainment for community college students. Specifically, s tudent athletes were found to be 0 .118 times less likely 2.140, p < .01) than non athlete students to earn a degree from the community colleg e, holding all other variables constant. Individual Background C haracteristics Individual characteristics in this study included gender, race, and SES. When considering these factors on the probability of degree attainment, no significant differences in t he probability of degree attainment were found between students, with respect to a race and gender. Student SES was the only factor for individual characteristic that was found to be significant in model 1. Results indicated that low SES students were extr emely disadvantaged compared to high SES

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116 students. L ow SES students were 883 times less likely = 0 .125, p < .0 5 ) than high SES students to complete a degree at the community college Table 4 3 4 Results for b inary l ogistic r egression model 1: Degree attainment Variable Exp ( ) Std. Error Wald Student Athlete Status Student athlete 2.140 0 .118 ** 0 .774 7.654 Individual Background Characteristics Female 0.039 1.040 0 .050 0 .615 Student of color 0.043 0 .958 0 .056 0 .594 Low SES 0.125 0 .883 0 .054 5.253 Pre College Characteristics Delayed entry to college 0.503 0 .605 *** 0 .056 79.901 Not college ready (Math) 0.404 0 .667 *** 0 .055 53.976 Not college ready (Reading) 0 .000 1.000 0 .068 0 .000 Not college ready (Writing) 0.174 0 .840 0 .077 5.138 Academic Experiences Comm. c ollege GPA 0.984 a 2.675 *** 0 .040 607.111 Mean credit hours earned 0.249 a 1.283 *** 0 .009 807.201 Institutional Characteristics Small FTE enrollment 0.133 0 .876 0 .199 0 .444 Medium FTE enrollment 0.020 1.020 0 .087 0 .051 Large FTE enrollment 0.252 .777 *** 0 .066 14.775 Urban institution 0.142 .867 0 .056 6.567 Rural institution 0.082 1.086 0 .146 0 .317 Interaction Terms Student athlete*Female 0.390 1.477 0 .233 2.789 Student athlete* Students of color 0.029 0 .971 0 .285 0 .010 Student athlete*Low SES 0.006 0 .994 0 .272 0 .000 Student athlete*Not college ready (Math) 0.148 0 .863 0 .271 0 .297 Student athlete*Not college ready (Reading) 0.020 0 .980 0 .328 0 .004 Student athlete*Not college ready (Writing) 0.402 1.495 0 .329 1.498 Student athlete*Comm. College GPA 0.395 a 1.484 0 .241 2.678 Student athlete*Rural 0.758 0 .469 0 .376 4.068 Student athlete*Urban 0.369 1.446 0 .271 1.856 Constant 5.252 0 .005 *** 0 .143 1340.439 p < .05, ** p < .01, *** p < .001 Note: a Indicates the independent variable is contuous

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117 Pre -C ollege C haracteristics Three of the four variables included in pre college characteristics were found to be significant in predicting degree completion. S tudents who delayed entry to college beyond one calendar year and those that were not college ready in math or writing were found to have decreased odds of completing a degree at the community college compared to their inverse reference group. S tudents who delayed college entry beyond one year after high school were nearly 61% 0.503, p < .001) to earn a degree compared to students who immed iately enroll in college. Overall, 60% (n=9,282) of students in the sample entered college within a year of completing a high school diploma. T he odds of completing a degree drastically decreased for students that were not college ready in math and writing The probability of earning a degree decreased 0 .404, p < .001) for students not ready in math, and decreased by 84% 0 .174, p < .05) for students not college ready in writing, compared to students that were college ready in math and writing, respectively. Academic E xperiences The results for regression model 1 concluded that students academic experiences (i.e., GPA and credit hours earned per semester) at the community college were highly significant in predicting degree completion. As would be expected, s tudents who earned higher GPAs, and those that earned more credit hours per semester while enrolled in the community college were more likely tha n their peers to earn a degree. For instance, students who earned a GPA of 2.30 (mean GPA for all students) were 2.42 times more likely 0 984, p < .0 01) to earn a degree than student s who accumulated a GPA of 1.30; and students who earned a GPA of 3.30 were 6.49 times more likely 0 984, p < .0 01) to earn a degree than student s with a 2.30 grade point average.

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118 In regards to the impact of credit hours earned on degree attainment, s tudents who earned 11 credit hours each semester were 3.41 times more likely ( 0 249, p < .0 01) to ea rn a degree than student who only earned 10 credit hours each semester ; and students who earned 12 credit hours each semester were 4.37 more times likely to earn a degree than students who earned 11 credit hours each semester. Institutional C haracteristic s When considering the impact of institutional characteristics on student outcomes, only two predictor variables ( i.e., l arge FTE enrollment, u rban) were found to be significant. Students who attended institutions with large FTE enrollment sizes ( 5,000 to 9,999) were 0 .777 times less likely ( 0 252, p < .0 01) to earn a degree than students at very large institutions (FTE 10,000 or more). When considering the impact of geographic locale, s tudents who attended urban institution s were found to be 0 .867 time l ess likely ( 0 142, p < .0 1 ) to earn a degree, compared to students attending institutions in suburban areas. Interaction T erms Several interaction terms were incorporated in the model s to specifically explore the influence of athletic status on groups of predictor variables for predicting student degree completion A total of nine interaction terms that were included in the regression model but only one interaction term (student athlete status*rural) was found to be significant. S tudent athlete s at u rban institutions were found to be 0 0 .758, p < 0 .05) to earn a degree than student athletes at suburban institutions General Linear Model 2 : Four -Y ear Transfer As with regression Model 1 (degree completion) a significant p valu e of less than p < 0 .001 indicated that the model was better fitted than when considering only the constant variable (see Table 3 3 5 ). Model 2 correctly predicted four -year transfer for 98.4% of the students in the

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119 samples (see Table 4 3 6 ). Only eight of the 24 predictor variables included in the model were found to be significant in predicting four -year transfer. Table 4 35. Binary l ogistic r egression m odel m easures m odel 2 : Four year transfer Chi square df Sig. Nagelkerke R Square % predicted Correctly Probability of f our year transfer 639 638 24 .000 0 270 *** 98.4 *** Significant at the p < .001 level Student A thlete S tatus The results for regression model 2 indicated that student athlete status was not a significant factor in predicting four -year transfer. In essence, the results indicate that student athletes have the same odds of transferring to a four -year institution from the community college as nonathlete students. Individual Background C haracteristics The logistic regression for Model 2 resulted in significant values for the variables g ender and SES which suggests gender and SES are h ighly significant factors to considering when considering the probability of student transfer at the community college. In particular, female students were found to be nearly two t imes more likely 0 600, p < .0 01) than male students to successfully transfer to a four -year institution when holding all other predictor variable constant. A s previous literature has suggested, students in the study from low SES backgrounds were severely disadvantaged in regards to their odds of successfully transferring to a four year institution. Results from the statistical analysis indicated that low S ES students were approximately 51% less likely 0 675, p < 0 .0 01) to transfer than high SES students. Pre -C ollege C haracteristics Net all other predictor variables in the model, d elayed entry and college readiness in math and writing were found to be significant factors in predicting student transfer. The effect s of pre college characteristics on four year transfer were similar to the effects found for the group of

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120 Table 4 3 6 Results for b inary logistic regression model 2: F our year transfer Variab les Exp ( ) Std. Error Wald Intercollegiate Athletics Student athlete 1.414 4.113 2.080 0 .462 Individual Background Characteristics Female 0 .600 1.822 *** 0 .152 15.566 Student of color 0.223 1.250 0 .174 1.634 Low SES 0.675 0 .509 *** 0 .159 17.965 Pre College Characteristics Delayed entry to college 0.576 0 .562 ** 0 .204 7.945 Not college ready (Math) 0.732 0 .481 *** 0 .205 12.721 Not college ready (Reading) 0.322 0 .725 0 .280 1.326 Not college ready (Writing) 1.491 0 .225 ** 0 .543 7.548 Academic Experiences Comm. College GPA 1.251 a 3.493 *** 0 .156 64.403 Mean credit hours earned 0.232 a 1.262 *** 0 .026 81.995 Institutional Characteristics Small FTE enrollment 0.700 2.014 0 .551 1.615 Medium FTE enrollment 0.056 0 .946 0 .245 0 .052 Large FTE enrollment 0.465 0 .628 0 .204 5.183 Urban institution 0.297 1.345 0 .170 3.045 Rural institution 0.057 0 .945 0 .469 0 .015 Interaction Terms Student athlete*Female 0.845 0 .430 0 .594 2.021 Student athlete* Students of color 1.113 0 .329 0 .930 1.431 Student athlete*Low SES 0.593 1.809 0 .779 0 .579 Student athlete*Not college ready (Math) 0.350 1.420 0 .811 0 .187 Student athlete*Not college ready (Reading) 0.608 1.838 0 .837 0 .528 Student athlete*Not college ready (Writing) 1.088 2.968 1.120 0 .944 Student athlete*Comm. College GPA 0.338 0 .713 0 .624 0 .293 Student athlete*Rural 0.998 0 .369 0 .956 1.089 Student athlete*Urban 0.665 0 .514 0 .667 0 .995 Constant 9.620 0 .000 *** 0 .556 299.003 p < .05, ** p < .01, *** p < .001 Note: a Indicates the independent variable is contuous. pre college characteristics in predicting degree completion (Model 1). Specifically, students who delayed entry to college were 0 .562 times less likely 0.576, p < 0 .01) to transfer to a four year institution compared to students that did not delay entry.

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121 Taking into account college readiness in math, non -college ready students were 0 481 0 .732, p < .001) to transfer than students that were college ready in math. T he odds of transfer for student s that were not college ready in the content area writing were also shown to decrease. Non -college ready students were approximately 23% less likely 1 491, p < 0 .0 1 ) to transfer compared to student s that were college ready in writing Academic E xperiences When holding all other predictor variables constant, s tudent GPA and the number of credit hours earned were highly significant in predicting student transfer. A one unit increase in GPA from 2.30 to 3.30 increased the odds of student transfer by 810% ( < .001) Results for the logistic regression further suggest that a one unit increase in the number of credit hours earned per semester from 1 0 credit hours to 11 credit hours increased the likelihood that a student would of transfer to a four -year institution by approximately 266% ( 0.232, p < .001) Institutional C haracteristics The variable LARGE was the only significant factor in the group of institutional characteristics variables to have an impact on student transfer. Students enrolled at community college in the state of Florida with large FTE enrollment sizes (5,000 to 9,999) were 0 .628 times less likely to transfer than students attending community colleges in the state with very large FTE enrollments sizes (10,000 or more) Interaction Terms There were n o significant results found within the interaction terms included in m odel 2. Accordingly, s ince no significant facto rs were found reveals that student athletes and nonathlete students have equals odds of transferring to a four -year institution, even when considering gender, college readiness in math, writing and reading, GPA, and an institutions geographic location.

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122 General L inear M odel 3 : Degree A ttainment and F our -Y ear Transfer The final regression m odel examined the likelihood of degree completion and four year transfer for student athletes and non athlete students enrolled at community colleges As in the previ ous two model s that have been discussed, m odel 3 was also significant at the p < 001 significance level A significant p value indicates the regression model was better fitted than when considering only the constant variable. The logistic regression model correctly predicted group membership (0/1) for 98% of the students in the samples (see Table 4 3 7 ). E ight of 24 predictor variables included in model 3 were found to have a significant impact on predicting the likelihood of degr ee attainment and four year transfer (see Table 4 3 8 ). Table 4 3 7 Binary logistic regression model measures m odel 3 : Degree attainment and four year transfer Chi square df Sig. Nagelkerke R Square % predicted Correctly Probability of degree *four year transfer 593.647 23 0 .000 *** 0 310 98.8 p < 0 .05, ** p < 0 .01, *** p < 0 .001 Student A thlete S tatus Student athlete status was not a significant factor in model 3 Accordingly, from the logistic regression analysis the conclusion can be drawn that no significant differences exists in the probability of degree completion and four -year transfer between community college student athletes and nonathlete s tudent s in the state of Florida Individual Background C haracteristi cs When considering the probability of degree attainment and transfer, gender and socio economic status were found to highly significant factors. F 0 .630, p < .001) more likely than male students to complete both a degree an d four -year transfer Students from low SES backgrounds were also found to be severely disadvantaged in regards to the ir probability of earning a degree and transferring to a four -year institution at the community

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123 college Low SES students were 5 7.4 % less likely 0 554, p < .0 1 ) than high SES students to successfully complete both outcomes. Table 4 38 Results for bi nary l ogistic r egression model 3: D egree a ttainment and f our year t ransfer Variables Exp ( ) Std. Error Wald Student Athlete Status Student athlete 3.341 28.238 2.345 2.029 Individual Background Characteristics Female 0.630 1.877 *** 0 .179 12.357 Student of color 0.159 1.172 0 .207 0 .588 Low SES 0.554 0 .574 ** 0 .184 9.101 Pre College Characteristics Delayed entry to college 0.967 0 .380 *** 0 .258 14.010 Not college ready (Math) 0.481 0 .618 0 .236 4.160 Not college ready (Reading) 0.319 0 .727 0 .338 0 .890 Not college ready (Writing) 1.818 0 .162 0 .754 5.811 Academic Experiences Comm. College GPA 1.810 a 6.112 *** 0 .205 77.626 Mean credit hours earned 0.269 a 1.309 *** 0 .030 79.591 Institutional Characteristics Small FTE enrollment 0.713 2.039 0 .616 1.336 Medium FTE enrollment 0.090 0 .914 0 .288 0 .097 Large FTE enrollment 0.588 0 .555 0 .242 5.926 Urban institution 0.224 1.251 0 .196 1.308 Rural institution 0.140 1.150 0 .519 0 .072 Interactions Terms Student athlete*Female 0.447 0 .639 0 .686 0 .426 Student athlete* Students of color 1.757 0 .172 1.218 2.081 Student athlete*Low SES 0.960 2.612 0 .801 1.438 Student athlete*Not college ready (Math) 0.228 0 .796 0 .956 0 .057 Student athlete*Not college ready (Reading) 0.608 1.837 0 .892 0 .464 Student athlete*Not college ready (Writing) 1.226 3.407 1.431 0 .733 Student athlete*Comm. College GPA 0.888 0 .411 0 .697 1.623 Student athlete*Rural 18.580 0 .000 3936.030 0 .000 Student athlete*Urban 0.626 0 .535 0 .684 0 .836 Constant 12.219 0 .000 *** 0 .752 263.969

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124 Pre -C ollege C haracteristics As in the preceding two models, delayed entry, college readiness in math and writing were found to be significant in Model 3 Delayed entry and college readiness in math and writing have been found to be highly significant factors in predicting student outcomes at the community college. Within the context of results for Model 3, s tudents who delayed college entry were 38 % 0. 967, p < .001) to earn a degree and transfer t han students who immediately enrolled in college. The odds of degree attainment and transfer were drastically decreased for students that were not college ready in math and writing. Students not ready in math were 0 .618 times less likely 0 .4 81, p < 0 .0 5 ) to earn a degre e and transfer ; students not college ready in writing were 0 .162 times less likely 1 818, p < 0 .05) to earn a degree and transfer compared to students that were college ready in math and writing, respectively. Academic E xperiences As with previous regre ssion models that have been discussed, GPA and credit hours earned were significant factors in predicting degree attainment and transfer The odds of degree completion and transfer increased as each independent variable (i.e., GPA, credit hours earned) increased in value For example, students who earned a 2.30 GPA (mean GPA for all students) were 1.16 times more likely 810, p < .0 01) to earn a degree and transfer than students who accumulated a GPA of 1.30. Moreover, students who earned a GPA of 3.30 (a one unit increase from the mean GPA for all students) were 7.09 times more likely ( 810, p < .0 01) to earn a degree and transfer than students who acquired a GPA of 2.30. The regression model for the dependent variable, degree attainment and four -y ear transfer, revealed that the number of credit hours earned each semester was a significant indicator in estimating the probability of degree completion and transfer for students at the community college. S tudents who earned 1 1 credit hours per academic semester were 4.54 times more likely

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125 0 .269, p < .001) to earn a degree and transfer than students who earned ten course credit hours per semester (a one unit change) Students who earned 12 credit hours were nearly six times m ore likely 0 .269, p < .001) to earn a degree and transfer than student that accumulated only 11 credit hours each semester. Institutional C haracteristics Overall, institutional characteristics were not found to be extremely relevant in predicting degr ee attainment and four -year transfer. For the variables included in institutional characteristics, the variable representing large institutions was the only variable found to have a significant impact on degree completion and transfer. S tudents attending c ommunity college in the state with large FTE enrollment sizes (5,000 9,999) were approximately 56% less likely = 0 .588, p < .05) to earn a degree and transfer than a student attending community college with very large FTE enrollment sizes (10,000 or more). Interaction Terms There were no significant results found within the interaction terms included in model 3. From the conducted analysis performed for degree attainment and four -year transfer, results conclude that student athletes and non athlete students at the community college have equal odds of transferring to a four -year institution, even when considering athletic status and gender, college readiness in math, writing and reading, GPA, and an institutions geographic location. Chapter S ummary and Conclusion The preliminary and advanced analytic methods employed in this study w ere intended to produce an overall picture of the similarities and differences between student ath letes and non athlete students at the community college. In sum, the des criptive analyses provided further evidence to conclude that major differences in students academic performance and outcomes at the community college do exist between racial/ethnic gender, and SES groups. Additionally,

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126 results from the descriptive analys es indicate that female students have higher rates of degree attainment and four -year transfer than men ; and White students have higher rates of degree attainment and four -year transfer than Students of color Moreover, greater percentages of low SES stude nts were required to complete remediation in one or more of the tested content areas than students from high SES backgrounds. In regards to similarities between students as a whole, the statistical analys es revealed that half of all students in the samples required some form of remediation at the community college. These finding s further underscore the positive attributes of community college s (i.e., provid ing students access to higher education regardless of past academic record), but they also illuminate how vulnerable non-college ready students are for failure or departure before reaching a successful outcome. To f urther illustrate this point, in all three of the conducted logistic regression models c ollege readiness in math and writing were significant factors in predicting the likelihood that a student would earn a degree and/or transfer to a four year institution. The primary purpose of this study was to address questions regarding the impact of athlet ic participation on student outcomes at the community college In sum, the evidence abounds that there are significant differences between student athletes and nonathlete students S tudent athletes earn ed more credits hours per semester and had higher GPA s than non athlete students. Though, results from the conducted ANOVA models indicated that student athletes out perform non athlete students, results from the logistic regression s suggest that student athletes were still less likely to earn a degree from the community college, compared to their non athlete peers. The final chapter of this study will further discuss the results of the conducted preliminary and advanced analyses juxtaposed to the previous literature on this topic.

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127 CHAPTER 5 DISCUSSION AND CONCL USIONS Intercollegiate athle tics and community colleges serve as entryways for increased student participation in higher education and are viewed as viable avenues toward advancement of social mobility for individuals that par ticipate (Brint, 2003; Castaeda, Katsinas, & Hardy, 2006). For students who attend the community college social mobility is the product of degree completion and/or successful transfer to a four -year institution. However, findings for this empirical study reveal that a considerable number of students who utilize the community college and athletics as channels to access higher education do not persist to degree completion or continue their academic studies at a four -year institution in the Florida State Un iversity System. More specifically, findings strongly suggest that Student athletes of color are not benefiting from the opportunity to attend college and earn a degree or transfer to a four -year institution. This comparative analysis extends the previous literature on the academic success of community college students and brings further awareness to the academic performance and outcomes of student athletes more specifically C hapter F ive begins with a focus on the significant factors included in the research models which result in differences in GPA, credit hours earned, degree completion and transfer rates for student athletes and non athlete students Next, I discuss differences in GPA, credit hours earned, degree completion and tra nsfer rates within racial, gender and SES sub groups of athletes and nonathlete students I will then direct the discussion to individual pre college characteristics and institutional characteristics t hat r esult in differences in outcomes for athletes and nonathlete students Throughout this study I have relied on a perspective borrowed from economi cs known as human capital theory to provide a framework to develop the research questions and conceptual model. In the final chapter of this study I conti nue to rely on this framework to interpret and

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128 contextualize the empirical results and to propose implications of findings for community college practitioners. As I bring this study to an end, I conclude C hapter F ive with a discussion of the contribution of this body of work to the state of Florida ; provide suggestions for new policies toward the improved academic success of students athletes in Florida and nationally; and lastly I offer suggestions for future res earch regarding student athletes at the community college. Purpose of Study Revisited T his study extend s the current literature base by challenging assumption s that there are no inherent differences in GPA, credit hours earned, degree attainment or transfer rates for community college student athletes and nonathlete students. Specifically, three main issues regarding student athletes and non athlete students are addressed in this study First, t his study addresses the idea that athletic participatio n is a major factor for increased rates of academic success for students, and for select racial gender and SES sub -groups more specifically In earlier chapters of this study I proposed that no differences would be found when examining the academic performance, degree attainment or four -year transfer rates of FTFT enrolled student athletes and nonathlete students or within racial, gender and SES sub groups of student athletes and non athlete students enrolled at the community college Sec ond, this study addresses the influence of pre -college characteristics ( e.g., college readiness and delayed entry to college) on students propensity to be academically successful at the community college. The hypothesis was proposed that t here are no diff erences in the academic performance, degree attainment or four -year transfer rates between student athletes and non athlete students in the state of Florida when comparisons are based on students pr e college characteristics

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129 And lastly this study addresses the influence of institutional characteristics on students academic performance, degree att ainment and four year transfer rates at the community college I proposed that no differences would be found between student athletes and non athlete stu dents when considering GPA, degree completion and four year transfer rates for groups of students enrolled a t institutions of varying FTE enrollment sizes and geographic locales. Impact of Athletic Participation To what extent do academic performance (GP A, credit hours earned) degree attainment and four -year transfer rates differ between full time first-time (FTFT) enrolled student athletes and their peers at the community college? Academic Performance The results for this study dispute the hypothesis that student athletes and nonathlete students maintain similar GPAs and successfully complete a comparable number of credits hours each semester while enrolled at the community college. Specifically, results suggest that student athletes outperform non at hlete students in both GPA and credit hours earned while enrolled at the community college D ifferences in GPA between athletes and non athlete students held constant even for sub -group comparisons with respect to ge nder, race, and SES. To illustrate, the findings indicate that female student athletes Student athletes of color and student athletes from low SES backgrounds earn higher GPAs than nonathlete students with i dentical backgrounds characteristics (i.e., female students Students of color and s tudents from low SES backgrounds ) The r esults infer that athletic participation is a positive factor for students academic performance measured in GPA when considering student s background characteristics such as race, gender and SES status. Furthermore, a thletic participation seems to have the greatest impact on female students at the community college Female student athletes earn higher GPAs

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130 and accumulate more credit hours each semester than their peers regardless of race or gender Diffe rences found between t he number of successfully completed credit hours earned by student athletes and nonathlete students further suggests that significant differences exist in the academic performance at the community college between athletes and non ath lete students. Statistical r esults for this study r eveal that student athletes successfully complete four more credits hours each semester than their non athlete peers. Even when considering subgroups comparisons (i.e., Students of color students from hig h and low SES backgrounds ), student athletes still earn more credits hours per semester The results for the descriptive analysis are in support of previous literature that female student athletes do better academically than their peers at the community college (Bailey, Calcagno, Jenkins, Leinbach, & Kienzl, 2006; Kanter & Lewis 1991; Sawyer 1993) Additionally, when examining the influence of athletic participation an d race on the academic success of student athletes at the community college, s imilarities can be drawn from the results for this study and examples provided in the literature. For example, Kanter and Lewis (1991) found similar positive relationships betwee n athletic participation and increased GPA for Black and Hispanic male student athletes However, the results of this study do conflict with Kanter and Lewis (1991) study in that this study strongly suggest that student athletes earn substantially higher GPAs and earn more credits hours than their peers, whereas Kanter and Lewis s (1991) study suggested that athletes earned slightly lower GPAs and complete d fewer transfer units per year than the students in the general population When considering the results of this study and those from previous literature, the findings present a case that athletic participation does have an impact on students performance at the community college. R esults are conclusive that for Students of color female students, and

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131 students from low SES backgrounds, the investment of athletically related financial aid by institutions does have a positive effect on students academic performance, measured in community college GPA and credit hours successfully completed by students each semester. However, caution must be taken when examining results for student athletes GPA The utilized data set does not lend itself to differentiate the type of courses enrolled or the rigorous nature of courses for which student GPA was calculated (e.g., a physics course versus a course on Lifetime fitness and wellness). Knapp and Raney (1988) found that student athletes GPAs at the community college are inflated due to the tendency of athletes to enroll in easy courses and programs of study in order to maintain GPA requirements for athletic participation. Furthermore, Lewis and Marcopulos (1989) indicated that up to a quarter of all credits hours earned by student athletes at the community college are earned in physical education and athletic related courses which can inflate student athletes overall GPA at the community college D egree A ttainment and F our -Y ear Transfer The following section discusses factors that lead to differences in degree attainment and four year transfer for student athletes, with respect to respect to rac e and gender. T his study suggests that White student athletes earn substantially more degrees at the community college, transfer to four -year institutions, and complete both a degree and transfer at greater rate s tha n Students athletes of color In addition to differences found between student -athletes of different racial backgrounds, results further suggest that differences exist between male and female student athletes at the community college Results ind icate that f emale student athletes surpass male student athletes in degree completion, four -year transfer, and the combination of degree completion and four -year transfer. Similar f indings have been reported in the literature to support the results for thi s study. These findings underscore the investment of athleticallyrelated

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132 financial in the development of human capital for students at the community college. Results suggest that the greatest return of institutions investment in students social mobility is realized through female student athletes. Female student athletes are more likely to leave the community college with a degree in hand or with plans to attend a four -year institution. A combination of explanations offered in the literature may shed m ore light on why male and female athletes and Students of color and White student athletes, do not have comparable degree completion or four -year transfer rates at the community college The literature provides that differences between groups are a result of students level of motivation for their academic studies. Several authors have suggested that Students athletes of color and male student athletes are more athletically -motivated than academically -motivated compared to their White and female peers, respectfully (Berson, 1996; Parmer 1994; Schultz, 2007). Schulz (2007) found that f emale athletes at the community college were more academically -motivated and held higher degree aspirations than male athletes and that White student athletes were more academically motivated towards these same goals than Student athletes of color Palmer (1994) also speculated that particular groups of students hold sports as a more profitable means toward social mobility than a degree. Palmer (1994) and other studies postulate that student s from particular groups, such as males and Students of color tend to focus more on activities that improve their prospects for professional athletic stardom than on activities that lead to degree attainment or continuation of their ac ademic studies at a four year institution. While results from the descriptive analyses indicate that athletic participation is a positive influence on student GPA and the number of credit hours earned for student s at the community college, the results for conducted logistic regressions indicat e that athletic participation alone does not correlate to increased degree completion or transfer rates for student athletes. Despite

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133 the finding that student athletes earn more credit hours each semester than their pe ers student athletes were significantly less likely to earn a degree within three and one -half years of their initial enrollment However, non athlete students and student athletes have equals odds of completing four -year transfer and completing a degree at the community college and transferring to a four year institution The question then arises, if student athletes perform better academically than their non athletes students enrolled at the community college, why are student athletes found to be less likely than their peers to graduate? One explanation for differences in degree completion rates could be the lack of emphasis athletic coaches and the National Junior College Athletic Association (NJCAA) place on student athletes degree completion a t the community college. To illustrate this point further, currently the NJCAA set s eligibility standards for student s athletic participation based on full time enrollment status and minimum semester/quarter GPA standards Accordingly, student athletes ar e more inclined to earn higher GPAs than non athletes students, due to their desire to stay academically eligible. However, the NJCAA does not recommend or enforce graduation standards for institutions which sponsor athletic programs. S tudent athletes and coaches are more inclined to focus on meeting semester enrollment and GPA requirements (Lewis and Marcopulos, 1989) than completing academic programs of study which lead to completion of a degree prior to a student leaving their respective institution. The findings for this study which suggests student athletes outperform their peers but are still less likely to earn a degree from the community college are disconcerting I nstitutions and athletic administrators often publicize athletic programs as portal s to increased college attendance for students especially students from under represented backgrounds (Boulard, 2008) However, results suggest that athletic programs are not supporting or not encouraging

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134 student athletes to complete a degree once they enroll An essential element of building individual human capital is the investment in education or training that lead to a credential (or output) which facilitate increased individual social mobility. Institutions are making an investment in student athle tes, but these investments are not paying off for the institutions or for the students that are supported through the award of athleticallyrelated financial aid at the community college. Impact of Pre -College and Institutional Characteristics To what extent do pre -college and institutional characteristics impact the academic performance (i.e., GPA, credit hours earned) degree attainment and four -year transfer rates of student athletes, compared to their nonathlete peers? Pre -College Characteristics A considerable number of students who enter the community college each year require some form of remediation prior to enrolling in college level courses for credit ( Kozeracki 2002; Oudenhoven, 2002) The large numbers of unprepared students that require re mediation in math, reading and writing at the community college place a substantial strain on already scarce institutional resources ( Kozeracki 2002). Results for this study also indicate that a majority o f community college student athletes and nonathlete students in the 20042005 student cohort, required remediation in at least one content area. Alt hough the percentage of student athletes and non athlete students requiring remediation are very similar the impact of students level of college readiness did not have the same impact on both groups. As a whole, results for the logistic regression suggest that the likelihood of degree completion and transfer decreased substantially for students not college ready in math and writing. R esults do not indicate however, that level of college readiness is a significant barrier to student athletes academic success at the community college In fact, when considering results

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135 for the descriptive analysis, a larger percentage of student athletes that requir ed remediation in all three content areas completed a degree compared to the percentage of non athletes students of comparable levels of college readiness that successfully completed a degree at the community college An explanation for differences betwee n the percentage rates of degree completion for non college ready student athletes and non athlete students is difficult to explain using the utilized data set. However, two possible explanations can be surmised based on the previous literature and the res ults for this study. First, d ifferences in degree completion rates between groups are likely a product of student athletes motivation to earn passing grades in their enrolled courses in order to maintain athletic eligibility (Lewis and Marcopulos 1989), regardless if enrolled courses are for college credit or to fulfill remediation requirements. Second, d ifferences may be contributed to student athletes resilience and aptitude to overcome possible boundaries, a lesson learned from their athletic training. Sparent (1988) posited that student athletes must transfer existing skills from their athletic training to the academic environment in order to be effective and successful in their academic world. The above explanations are both feasible ration alizations for differences in degree completion rates between athletes and nonathletes students and merit future investigation th r ough both qualitative and quantitative research methods Institutional Characteristics While the r esults for this study ind icate that institutional characteristic do play a role in the success of students at the community college institutional characteristics were not found to impact academic outcomes for student athletes and non athlete students in the same manner Results f rom the logistic regression s reveal that i nstitutional enrollment size is a barrier for non athlete students but enrollment size does not affect the likelihood of degree completion for

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136 student athletes. N on athlete students who attend institutions in the state of Florida with FTE enrollment sizes between 5,000 and 9,999 are at greatest risk of not earning a degree compared to their peers at institution in the state with FTE enrollment sizes at or above 10,000 FTEs. Conversely, results reveal that s tudent athletes at rural institutions throughout the state are at greatest risk of not completing a degree while attending a community college, compared to their p eers at suburban institutions. These findings juxtaposed to the literature deserve further at tention. Previous research has suggested that rural institutions are most welcoming to athletic programs and to student athletes and that nearly fifty percent of all community college student athletes attend a rural institution (Castaneda, Katsinas, & Ha rdy, 2006) According to Castaneda, Katsinas & Hardy (2006), rural institutions account for nearly three quarters all athletic scholarships that are awarded to student athletes at community colleges within the U.S. Considering results from this study, whic h suggest s tudent athletes at rural institutions are most likely not to complete a degree it may come to reason that the investments in student s via athletically related financial aid at rural institutions is not a wise investment on the part of instituti ons unless support system are in place at the institution to support student athletes to succeed academically. Contributions of this Study to the State of Florida This study make s a contribution to the state of Florida by providing a report of student athletes performance at community colleges within the state of Florida Applying a longitudinal methodology highlight the importance of tracking the academicallyrelated behaviors of student athletes and the exploration of factors which affect stu dent athletes likelihood to leave the community college prior earning a degree. Additionally, this longitudinal model provides a benchmark for future comparative studies of student athletes and non athletes at the community

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137 college and the continued exami nation of student athletes academic behaviors at the community college In the same vein, this study make s a contribution to the study of higher education by providing a model, the support and impetus for continued monitoring of the academic successes, f ailures and outcomes of student athletes at community colleges in the state of Florida This study further seeks to advance awareness of the impact of student participation in athletics and the influence of individual and institutional characteristics on the academic success of student athletes Athletic programs at community college s have the capacity to make a great impact on institutions and student athletes alike. This study highlights the barriers and vast opportunities sports at community colleges provide in hopes that institutions and the state will use such data to optimize the positive impact of sports to benefit both the success of institutions and student athlete s And lastly, this study provides state legislators and institutions a receipt detailing the return of their financial investment in student athletes academic studies at the community college This study not only provides indication that athletically related aid benefits students at the community college, but also suggests areas i n which more human and financial resources should be directed in the future to obtain the greatest return on the investments made by the state and institutions, toward increased student success. Implications for practice Many debates have transpired t hroughout higher education and within political circles regarding degree completion and four year transfer rates for students who begin their academic studies at a community college. A number of these debates have center ed on the paradoxical expectations p laced on community colleges to maintain open access while also producing large quantities of academically prepared students (Bailey & Morest, 2006; Oudenhoven, 2002; Roueche & Baker, 1987) From these debates and conversations and as evidenced in this

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138 emp irical study, it is unequivocally clear that aims for increased student participation in higher education via community colleges and athletics must be accompanied by zealous attempts to support students academically o nce they enroll ( Ashburn, 2007; Dougher ty & Kienzl, 2006) Based on results from this study, I provide four recommendations for ways in which institutions and practitioner at the community college can better support the academic pursuits of student athletes at their institution First, create institutional culture s that encourage and challenge student athletes to enroll in college level courses which lead to a degree or professional certificate. The development of such a culture devoted to student athlete s degree completion must begin with the institutional administrators, but also include the support and endorsement of coaches athletic support staff members and faculty members Through this joint initiative, student athletes will have support through a network of community college offices f ocused on helping them achieve these outcomes (i.e. degree, certificate, or transfer). Second, encourage athletic coaches to recruit prospective student athletes that are able to handle the academic and athletic responsibilities associated with being a col lege athlete. This includes, but is not limited to, considering prospective students level of college readiness in math, reading, and writing prior to making an offer to compete athletically or awarding athletically related financial aid. Though, athletic programs are a great recruiting tool for many prospective students and athletes, athletic participation and the associated academic responsibilities may be a too much to manage for students with below average academic records. Accordingly, institutions and administers must assume the responsibility of making sure students leave their institutions with the academic skills and/or work skills to enter a four year institution or the workforce

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139 Third, ensure focus and care is given to provide the necessary support and attention student athletes f rom low SES backgrounds need to be successful. The opportunity to participate in college athletics and t he award of athletically related financial aid are both entici ng for students from low SES backgrounds to access higher education. However, students from low SES backgrounds are more likely to struggle academically and leave an institution prior to completing a degree. The additional personal responsibilities associated with athletic participation have the propensity to severely hinder the probability low SES students will be successful at the community college. Accordingly, it is important for institutions to put in place ongoing, intentional efforts to support students beyond providing financial incentives for attending the community college and participating in intercollegiate athletics. Fourth, find additional ways to incorporate faculty members in the implementation of programs and services to assist student athletes at the community college. Facul ty members work with students daily, and they may have a broad er understanding of the academic and social barriers confronting student athletes at the community college. Developing programs where faculty members can serve as ambassadors to the athletic pro gram provide additional avenues for student athletes to obtain valuable information about future academic and professional planning, which may not be available through services provided by athletic programs. State and National Policy Recommendations Over four decades ago, the National Collegiate Athletic Association (NCAA) instituted a set of policies aimed at enhancing the quality of students recruited by institutions to participate in varsity athletic s at NCAA affiliated institutions (Heck and Takahashi 2006). Since 1965, the NCAA has steadily increased minimum eligibility requirements for prospective student athletes to participate in athletics at Division I and Division II institutions. The lineage of NCAA policies began with the 1.6 rule (1965), which required prospective student athletes to have high school

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140 academic records that are able to predict a minimum college grade point average of 1.6 on a 4.0 scale (NCAA, n.d.) to the most recent legislation, Proposition 26 (2003) which increased the number of required core courses a high school student must complete that was originally put forth in Proposition 16 (1992). Minimum eligibility standards for athletic participation are intended to increase students degree completion, and often exceed th e minimum requirements of institutions admissions offices (DeBrock, Hendricks, and Koenker 1996; Heck and Takahashi 2006) However, the national athletic governing boards for junior/community college athletics have yet to institute such safe guards for student participation M inimum eligibility requirements serve as the preliminary screening of students to protect both the student and institution from future academic failures In order words, only students that are qualified to handle their academic studies and athletic participation are granted clearance to participate in athletics at the college level, even at open access community colleges Unlike four year institutional governing bodies, boards that govern athletics at the community college have not gone to such lengths to protect the prospective student athlete or the institution which sponsor athletic teams Instituting minimum eligibility requirements also protect the investment made by institutions and athletic programs. If financial resources are being set aside for a student to attend an institution and participate in athletics, care must be given to the type and cal iber of students that benefit from these resources. I f providing increased access to higher education is the goal of athletic programs and institutions so should consideration of mechanism to ensure student athletes receive a degree and/or prepared for academic studies at four -year institutions Currently t he onus is on community colleges in the state to set the standard s for policies regarding the academic standards for student athletes. The time is quickly approaching when important decisions regarding community college student athletes future will be made by four -

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141 year institutions and governing bodies which may not have the best interest of the community college or community college student athlete in mind. Accordingly, I propose possible institution al and state policies to enhance the probability of success for both student athletes and. First, consideration should be given to the creation of minimum academic requirements (e.g., high school grade point average entrance exam score) for participat ion in athletics at public community college state -wide. For students that are interested in participating in athletic programs at the community college minimum requirements would have to be met prior to the award of athletically related financial aid and prior to being permitted to participate in scheduled practices or athletic competitions. The establishment of minimum athletic requirements may limit the number of students that are able to participate in athletics but such requirements would also reinforce the importance of academics to prospective students, parents/guardian, and coaches. Second, institutions with athletic programs should consider working directly with academic support services to create d egree programs plans for all student athle tes, based on students desired academic and professional goals. Providing guidance to student athletes in regards to degree requirements and transfer requirement will help to decrease student enrollment in non -transfer courses Most importantly, academic advising and course registration should not be conducted by athletic coaches or athletic staff members not familiar with degree requirements at the respective institution. Providing appropriate and thoughtful academic advising will also encourage and facil itate timely degree completion S upport staff that work directly with student athletes should be well versed in minimum eligibility requirements for transfer and athletic participation at four year institutions in the state, as well as transfer guidelines for all four year athletic confe rences represented in the state

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142 Third, the state of Florida should consider an annual census of three year degree completion and transfer rates for student athletes at community college s A formula should be developed with consideration given to the typical academic behaviors and frequent movement between institutions often witnessed in community college student populations. The establishment of three year guidelines also provide institutional standards and expectations t hat financially supported students should put forth deliberate efforts to earn a degree while enrolled in classes and participating in athletics. T hree -year degree completion and transfer rates also provide institutions with standards in which to measure t he success of athletic programs. Such standards are essential to evaluating programs annually, and if necessary, evaluating programs to eliminate during times of limited or depleting financial resources. In future years, consideration may also be given to penalizing athletic programs ( e.g., decrease in number of athletic scholarships available, decrease number of competitions for a sport or all sports) that annually struggle to graduate or transfer their student athletes. Suggestions for Future Research The hope is that this present inquiry will inspire and encourage future empirical research on the experiences of student athletes at the community coll ege throughout Florida and nationally. There are endless possibilities for future research focused on st udent athletes at the community college Based on the findings from this study, I provide areas where future research is necessary to expand the current literature on the impact of athletics and athletic participation at the community college and the acade mic performance and outcomes of community college student athletes. A dditional quantitative and qualitative inquiry is needed to explore the impact of college readiness on the degree completion and transfer rates for student athletes at the community coll ege Gaining a greater understanding of how college readiness impacts student athletes

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143 degree completion is essential to the academic success of athletes as well as the creation and implementation of programs and services to assist nonathlete students t hat are not college ready to earn a degree or continue their education at a four year institution Next increased research focused on the impact of student athlete s individual characteristics, such as learning disabilities on degree completion and four -year Many athletic programs at four -year institutions have instituted programs specifically designed to test students for learning disabilities and to support student athletes that are found to have such disabilities. Continued research on the extent to which students are inhibited by such learning disabilities is essential to developing a holistic approach to supporting student athletes at the community college. Finally I suggest future quantitative research on the i nfluence of athletically related financial aid and other financial aid and loan packages on student athletes success at the community college Many student athletes, as seen in this study, receive other forms of aid in addition to athletically related aid (e.g., Pell grants merit based f inancial aid ). A greater understanding of the ultimate impact of these programs on students success versus nonscholarship student athletes and students that work more than 30 hours per week, will increase our awareness of the impact of athletic participa tion and the award of all types of financial aid. Fourth, continued research on the persistence of community college student -athletes to bachelor and masters degree attainment is essential to understanding the foundation and importance initial access t o higher education via athletics play in the subsequent enrollment and success of former community college student athletes. If community colleges and intercollegiate athletics are truly viable paths toward social mobility, understanding the specific ways, and to

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144 what extent, athletics and the community college benefit students progression in higher education is paramount Lastly, additional research is necessary to explore the role faculty members play in recruiting, mentoring, and advising student athl etes and impact of faculty members on the academic success of student athletes at the community college. Not much information is available about the multifaceted roles faculty member hold at community college or the impact they have on student athletes and athletic departments. Closing Words If we examine the turbulent situations many four year athletic programs have found themselves in over the past 20 years ( e.g., cheating, falsifying transcripts, improper gifts to athletes, etc.), a majority of these problems are the product of institutions increased focus on winning and developing successful athletic programs rather than staying focused on the fundamental establishment of college sport (Duderstadt 2002; Reapple et al., 1982). Athletics, as an exte nsion of the institutional mission, provide a mechanism in which institutions can further support the personal and athletic goals of its student athlete population. This balanced approach of providing both students and athletic programs support is manifest ed through institutions evenly balanced financial commitment and implementation of policies geared toward athletic program s growth and the academic success of those that participate. This study was intended to illuminate the importance of a continued focus on the student athlete, and not on the sport or athletic success of institutions athletic programs or the s tudent athlete. For a majority of student athletes at the community college, athletics serve as a foundation on whic h increased human capital can prevail. When the final pitch is thrown, and the final whistle blows, the student athletes that are truly viewed as successful are those that have a degree or the training to survive and excel in the game of life.

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145 APPENDIX A NATIONAL COLLEGIATE ATHLETIC ASSOCIATION (NCAA) ELIGIBILITY S LIDING SCALE FOR GPA AND EN TRANCE TEST SCORES Table A 1 NCAA Division I c ore GPA and t est s core s liding s cale Core GPA SAT ACT Core GPA SAT ACT 3.550 & above 400 37 2.750 720 59 3.525 410 38 2.725 730 59 3.500 420 39 2.700 730 60 3.475 430 40 2.675 740 750 61 3.450 440 41 2.650 760 62 3.425 450 41 2.625 770 63 3.400 460 42 2.600 780 64 3.375 470 42 2.575 790 65 3.350 480 43 2.550 800 66 3.325 490 44 2.525 810 67 3.300 500 44 2.500 820 68 3.275 510 45 2.475 830 69 3.250 520 46 2.450 840 850 70 3.225 530 46 2.425 860 70 3.200 540 47 2.400 860 71 3.175 550 47 2.375 870 72 3.150 560 48 2.350 880 73 3.125 570 49 2.325 890 74 3.100 580 49 2.300 900 75 3.075 590 50 2.275 910 76 3.050 600 50 2.250 920 77 3.025 610 51 2.225 930 78 3.000 620 52 2.200 940 79 2.975 630 52 2.175 950 80 2.950 640 53 2.150 960 80 2.925 650 53 2.125 960 81 2.900 660 54 2.100 970 82 2.875 670 55 2.075 980 83 2.850 680 56 2.050 990 84 2.825 690 56 2.025 1000 85 2.800 700 57 2.000 1010 86 2.775 710 58 Source: National Collegiate Athletic Association 200 8 2009 Guide for the college bound student athlete (2008).

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146 APPENDIX B CALCULATION S OF ODDS RATIOS FOR CONTINUOU S VARIABLES IN GENER AL LINEAR MODELS (GLM) Formula for calculating odds ratios for continuous variable s : { 1( + 1 ) } ( 1 ) = { 1( ) } One unit change in GPA (1.30 to 2.30) = { 0 984 ( 1 30 + 1 00 ) } ( 0 984 ( 1 30 ) =9 6138 3 5937 = 2 42 Model 1: Degree attainment One unit change in GPA (2.30 to 3.30) = { 0 984 ( 2 30 + 1 00 ) } ( 0 984 ( 2 30 ) =3 247 2 2 2632 = 6 49 One unit change in credit hours earned (10 to 11) = { 249 ( 10 + 1 00 ) } ( 249 ( 10 ) =2 739 2 49 = 3 410 One unit change in credit hours earned (11 to 12) = { 249 ( 11 + 1 00 ) } ( 249 ( 11 ) =2 988 2 739 = 4 374 One unit ch ange in GPA (2.30 to 3.30) = { 1 251 ( 2 30 + 1 00 ) } ( 1 251 ( 2 30 ) =4 1283 2 8898 = 8 1026 Model 2: Four -year transfer One unit change in credit hours earned (10 to 11) = { 232 ( 10 + 1 00 ) } ( 232 ( 10 ) =2 552 2 889 = 2 657 One unit change in GPA (1.30 to 2.30) = { 1 810 ( 1 30 + 1 00 ) } ( 1 810 ( 1 30 ) =4 163 2 353 = 1 161 Model 3: Degree attainment and four -year transfer One unit change in GPA (2.30 to 3.30) = { 1 810 ( 2 30 + 1 00 ) } ( 1 810 ( 2 30 ) =5 973 4 163 = 7 097 One unit change in credit hours earned (10 to 11) = { 269 ( 10 + 1 00 ) } ( 269 ( 10 ) =2 959 2 69 = 4 54 One unit change in credit hours earned (11 to 12) = { 269 ( 11 + 1 00 ) } ( 269 ( 11 ) =3 228 2 959 = 5 95

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147 APPENDIX C INSTITUTIONAL REVIEW BOARD (IRB) APPROVAL LETTER

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148 APPENDIX D ASSOCIATION FOR INST ITUTIONAL RESEARCH (AIR) DISSE RTATION FELLOWSHIP AWARD LETTER

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BIOGRAPHICAL SKETCH David Horton Jr. was born to David and Ollie Fay Horton in 1977, in Austin Texas The youngest of four children, David grew up in Austin and graduated from A. N. McCallum High School in 1996. Upon completion of his high school diploma, he attended and participated on the varsity baseball team at Panola College in Carthage, Texas. After earning his associate s degree from Panola College in 1997, David moved to Dallas Texas to continue his academic studies at Dallas Baptist University (DBU) At DBU, h e continued to par ticipate in intercollegiate athletics, and eventually earn ed a Bachelor of Science (B.S.) degree and a M aster of Liberal Arts (M.L.A) degree in History in 2001 and 2003, respectively. While working on his masters degree David was employed full time as t he Coordinator for Graduate Admission at DBU. Upon completion of his masters degree in August of 2003, he began his college teaching career at DBU as an adjunct History professor for the College of Humanities and Social Sciences During his doctoral studi es at the University of Florida David continued to teach courses in American History during his w inter breaks. In 2004, David resigned from his position as the Coordinator of Graduate Admiss ion and moved to Gainesville, Florida to begin his academic studies at the University of Florida. David held a number of part time positions at UF during his academic studies. He began working as the Recruitment Coordinator for the Office of Recruitment, Retention and Multicultural Affairs in the College of Education. After a year in this position, he transitioned to the Department of Housing and Residence E ducation where he worked for two and one half years as a Graduate Hall Director, and intermittently as a Interim Residence Hall Director, before beginning his work as a Research Assistant for Dr. Linda Serra Hagedorn and Luis Ponjuan in the Department of Educational Administration and Policy in the College of Education.

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Over his academic studies at the University of Florida David has be en awarded a number of awards and acknowledgements from the College of Education and national organizations During the 20062007 and 20072008 academic years he was nominated as a Barbara L. Jackson S cholar In this position he served as the College of Education representative at the University Council for Educational Administrators (UCEA) annual conference In the final year of his academic studies David was awarded the prestigious Association for Institutional Research (AIR) dissertation fellowship.