Rural Postsecondary Institution Attributes and Their Relationship to Minority Student Enrollment, Graduation, and Completion

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Rural Postsecondary Institution Attributes and Their Relationship to Minority Student Enrollment, Graduation, and Completion
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1 online resource (162 p.)
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english
Creator:
Lynch, Lindsay Byron
Publisher:
University of Florida
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Gainesville, Fla.
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Thesis/Dissertation Information

Degree:
Doctorate ( Ed.D.)
Degree Grantor:
University of Florida
Degree Disciplines:
Higher Education Administration, Human Development and Organizational Studies in Education
Committee Chair:
CAMPBELL,DALE FRANKLIN
Committee Co-Chair:
VILLARREAL,PEDRO
Committee Members:
SANDEEN,CARL A
LEVERTY,LYNN H

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Subjects / Keywords:
colleges -- minority -- rural
Human Development and Organizational Studies in Education -- Dissertations, Academic -- UF
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Higher Education Administration thesis, Ed.D.
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theses   ( marcgt )
government publication (state, provincial, terriorial, dependent)   ( marcgt )
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Electronic Thesis or Dissertation

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Abstract:
This study evaluated the relationship between college and university attributes and success of their minority student populations in terms of enrollment, graduation, and completion. Data regarding each institution status as a minority-serving institution, support and services designed to target nontraditional and disadvantaged student populations, percentage of staff and faculty classified as a racial or ethnic minority, and whether or not it has targeted supplemental funding were captured from the National Center for Education Statistics Integrated Postsecondary Data System (IPEDS) and United States Department of Education. Institutional data was sub-divided into three geographic context categories: rural, suburban, and urban. Multiple regression analyses were used to establish a functional relationship between the independent variables and minority student rates of enrollment, graduation, and completion within each geographic context category. Based upon the IPEDS academic outcomes definitions, graduation refers to the rate at which students earn postsecondary credentials within 150% of the standard time and completion refers the rate at which students earn those same credentials, regardless of their length of study or other variables (www.ipeds.gov/glossary). Together, these relationships were used to develop a model of successful strategies for providing the most effective support system for minority students attending a rural college.
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In the series University of Florida Digital Collections.
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Includes vita.
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Includes bibliographical references.
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Description based on online resource; title from PDF title page.
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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 Lindsay Byron Lynch.
Thesis:
Thesis (Ed.D.)--University of Florida, 2014.
Local:
Adviser: CAMPBELL,DALE FRANKLIN.
Local:
Co-adviser: VILLARREAL,PEDRO.

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lcc - LD1780 2014
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UFE0046643:00001


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1 RURAL POSTSECONDARY INSTITUTION ATTRIBUTES AND THEIR RELATIONSHIP TO MINORITY STUDENT ENROLLMENT, GRADUATION, AND COMPLETION By LINDSAY LYNCH A DISSERTATION PRESENTED TO THE GRADUATE SCHOOL OF THE UNIVERSITY OF FLORIDA IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF DOCTOR OF EDUCATION UNIVERSITY OF FLORIDA 2014

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2 2014 Lindsay Lynch

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3 To my husband, Jeffery, and our children, Daniel, Nicholas, and Anna

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4 ACKNOWLEDGEMENTS The last five years have been a long and wonderful journey. Without the tireless support of my family, friends, and colleagues, this degree would not have been possible. First, I would like to acknowledge my husband, Jeffery, and our littl e gators, Daniel, Nicholas, and Anna. You let me chase my dreams and you shared me with my research and for that, I feel this degree is as much yours as it is mine. And to my parents and my sister for always being there for the last five years I could no t have done this without each of you. I would also like to acknowledge the amazing faculty with whom I have had the opportunity to work with in the College of Education. First, I would like to thank my committee. To my committee chair, Dr. Dale F. Campbel l, I could not have asked for a Pedro Villarreal III, my co chair, I could not have done this without your tireless support and tutelage. It is your encouragement and gui dance that helped me transition from a scholar to a researcher. To Dr. Dave Honeyman thank you for always asking the tough questions, but with wit and humor. You pushed me to think from day one. To Dr. Art Sandeen, thank you for sharing your passion for st udent services. Your support and encouragement has meant so much to me. And finally, to Dr. Lynn Leverty, thank you for always sharing your words of wisdom. Your perspective has been invaluable. Outside of my committee, the LEAD program is blessed with ou tstanding faculty members who have shaped my work from the first semester. I would like to extend a and introducing me to the theoretical framework that would shape my re search. IT is

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5 wealth of experience and knowledge with me, to Dr. Pilar Mendoza for making me really think outside of my comfort zone, and to Dr. Kathryn Birmingham for always amazing me with your endless research pursuits. And last but not least, thank you Angela Rowe for everything you do on a daily basis. I would also like to extend a very special thank you to my family at South Florida State College. To Don Appe lquist, I could not have done this without your support and understanding. Thank you for always encouraging me to put first things first. To Dr. Christopher van der Kaay for always being there to share war stories and talk tricky twenty one year old girl with no experience. I truly have you to thank for what I am now sure will be a lifelong love of community colleges and the students they serve.

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6 TABLE OF CONTENTS page ACKNOWLEDGEMENTS ................................ ................................ ............................... 4 LIST OF TABLES ................................ ................................ ................................ ............ 9 LIST OF FIGURES ................................ ................................ ................................ ........ 13 LIST OF ABBREVIATIONS ................................ ................................ ........................... 14 ABSTRACT ................................ ................................ ................................ ................... 15 CHAPTER 1 INTRODUCTION ................................ ................................ ................................ .... 17 Purpose of the Study ................................ ................................ .............................. 17 Research Questions ................................ ................................ ............................... 19 Statement of the Problem ................................ ................................ ....................... 19 Minority Students in a Rural College Context ................................ ......................... 22 Minority Student Success ................................ ................................ ................. 24 Rural Minority Students: The Intersection of Disadvantage .............................. 25 Deficiencies in Previous Literature ................................ ................................ ... 26 Significance of the Study ................................ ................................ ........................ 27 Hi storical Perspective ................................ ................................ ....................... 28 Contribution to Higher Education Research and Practice ................................ 29 Organization of the Study ................................ ................................ ....................... 30 Definition of Terms ................................ ................................ ................................ .. 31 2 A REVI EW OF THE LITERATURE ................................ ................................ ......... 35 Institutional Factors and Minority Student Success ................................ ................ 35 Education in the Context of Rurality ................................ ................................ ........ 38 Serving Students in the Rural Institution ................................ ........................... 40 Learner Support Programs in the Rural Institution ................................ ........... 46 What Really Matters for Rural Minority Students ................................ .................... 47 Theoretical Framework ................................ ................................ ........................... 55 3 METHODOLOGY ................................ ................................ ................................ ... 62 Hypotheses ................................ ................................ ................................ ............. 63 Data Sources ................................ ................................ ................................ .......... 64 Dependent Variables ................................ ................................ .............................. 65 Independent Variables for Preliminary Analyses ................................ .................... 66 Geographic Context ................................ ................................ ......................... 67 HBCU, Trib al, and HSI Designation ................................ ................................ 68

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7 Support Services and Special Programs ................................ .......................... 68 Minority Faculty and Staff ................................ ................................ ................. 69 Targeted Supplemental Funding ................................ ................................ ...... 69 Analytic Methods ................................ ................................ ................................ .... 72 Delimitations ................................ ................................ ................................ ........... 75 Potential Limitations of This Study ................................ ................................ .......... 76 4 DATA ANALYSIS AND RESULTS ................................ ................................ .......... 77 Preliminary Analyses ................................ ................................ .............................. 77 Descriptive Statistics of Population ................................ ................................ ......... 78 Distributi on of Student Enrollment by Racial Groups ................................ .............. 79 Rural Institutions ................................ ................................ ............................... 79 Suburban Institutions ................................ ................................ ........................ 81 Urban Institutions ................................ ................................ ............................. 82 Graduation Rates ................................ ................................ ............................. 83 Completion Data ................................ ................................ ............................... 84 Support Services and Special Programs ................................ ................................ 85 Minority Faculty and Staff ................................ ................................ ....................... 86 Targeted F unding ................................ ................................ ................................ ... 86 Analysis of Variance (ANOVA) ................................ ................................ ............... 87 Overall Graduation Rate ................................ ................................ ................... 87 Minority Graduation Rate ................................ ................................ .................. 88 Mino rity Completers ................................ ................................ ......................... 90 Pearson Chi Square Test of Independence ................................ ............................ 91 Linear Regression ................................ ................................ ................................ ... 91 Rural College Regression Functions ................................ .......................... 92 Suburban College Regression Functions ................................ ................... 92 Urban College Regression Functions ................................ ........................ 92 Results of Linear Regression Functions ................................ ................................ 93 Multiple Linear Regression Functions by Geographic Context ............................... 94 Rural Colleges ................................ ................................ ................................ .. 94 Suburban Colleges ................................ ................................ ......................... 107 Urban Colleges ................................ ................................ ............................... 120 Summary of Data Analysis ................................ ................................ .................... 131 Enrollment ................................ ................................ ................................ ...... 132 Graduation ................................ ................................ ................................ ...... 132 Completion ................................ ................................ ................................ ..... 133 5 DISCUSSION AND CONCLUSION ................................ ................................ ...... 134 Minority Student Success across Geographic Contexts ................................ ....... 135 Graduation ................................ ................................ ................................ ...... 135 Completion ................................ ................................ ................................ ..... 136 Impact of Special Services and Learner Support Programs in a Rural Context .... 137 Flexible Course Offerings: Distance Education and Weekend/Evening Courses ................................ ................................ ................................ ....... 137

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8 Placement Services f or Completers ................................ ............................... 138 Connection between Campus Services and Academic Success .................... 140 Impact of Institutional Attributes in a Rural Context ................................ .............. 143 Implications for Practice ................................ ................................ ........................ 144 Policy Recommendations ................................ ................................ ..................... 149 Suggestions for Further Research ................................ ................................ ........ 151 Conclu sion ................................ ................................ ................................ ............ 152 APPENDIX A SUMMARY OF FACTORS WITH POSITIVE RELATIONSHIP TO MINORITY STUDENT SUCCESS ................................ ................................ ........................... 154 B SUMMARY OF FACTORS RELATED TO HIGHER GRADUATION RATES ....... 155 REFERENCE LIST ................................ ................................ ................................ ...... 156 BIOGRAPHICAL SKETCH ................................ ................................ .......................... 162

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9 LIST OF TABLES Table page 3 1 Summary table of dependent variables ................................ .............................. 66 3 2 Independent variables. ................................ ................................ ....................... 70 4 1 Frequency of HBCU institutions ................................ ................................ .......... 78 4 2 Frequency of tribal colleges ................................ ................................ ................ 79 4 3 Frequency of HSIs ................................ ................................ .............................. 79 4 4 Rural college enrollment distr ibution by racial grouping ................................ ..... 80 4 5 Rural minority serving institution enrollment distribution ................................ ..... 80 4 6 Suburban college enrollment distribution by racial grouping .............................. 81 4 7 Suburban minority serving institution enrollment distribution .............................. 82 4 8 Urban institution en rollment distribution ................................ .............................. 83 4 9 Urban college minority serving institution enrollment distribution ....................... 83 4 10 Distribution of graduation rates by racial groupings across geographic context ................................ ................................ ................................ ................ 84 4 11 Mean completers by racial category for each geographic context ...................... 84 4 12 Frequency of support services and special programs in rural colleges .............. 85 4 13 Frequency of support services and special programs in suburban colleges ....... 85 4 14 Frequency of support services and special programs in urban colleges ............ 86 4 1 5 Distribution of faculty by geographic region ................................ ........................ 86 4 16 Targeted funding by geographic context ................................ ............................ 87 4 17 One way ANOVA of mean differences in graduation rate by geographic context ................................ ................................ ................................ ................ 87 4 18 Post hoc tests using Bonferroni Adjustment for mean differences in graduation rate by geographic context ................................ ............................... 88 4 19 One way ANOVA of mean differences in minority student graduation rate by geographic context ................................ ................................ ............................. 89

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10 4 20 Post hoc tests using Bonferroni Adjustment for mean differences in graduation rate by geographic context ................................ ............................... 89 4 21 One way ANOVA of mean differences in minority completers by geographic context ................................ ................................ ................................ ................ 90 4 22 Post hoc tests using Bonferroni Adjustment for mean differences in completers by geographic context ................................ ................................ ...... 90 4 23 Chi Square analysis of geographic context and support services ...................... 91 4 24 Rural institution variables regressed for minority student enrollment .................. 95 4 25 Results of regression function for minority enrollment in rural institutions .......... 95 4 26 Rural institution variables regressed for minority stud ent graduation ................. 96 4 27 Results of regression function for minority graduation at rural institutions .......... 96 4 28 Rural institutions variables regressed for minority student completion ............... 97 4 29 Results of regression function for minority completers in rural institutions ......... 98 4 30 Rural institution variables regressed for black student enrollment ...................... 99 4 31 Results of regression function for rural institution Black student enrollment ....... 99 4 32 Rural institution variables regressed for black student graduation .................... 100 4 33 Results of regression function for black student graduation in rural institutions 101 4 34 Rural institution variables regressed for black student completion ................... 101 4 35 Results of regression function for black completers in rural institutions ............ 102 4 36 Rural institution variables regressed for Hispanic student enrollment .............. 103 4 37 Results of regression function for rural instit ution Hispanic student enrollment 104 4 38 Rural institution variables regressed for Hispanic student graduation .............. 104 4 39 Results of regression function for Hispanic student graduation rates in rural institutions ................................ ................................ ................................ ......... 105 4 40 Rural institution variables regressed for Hispanic completers .......................... 106 4 41 Results of regression function for Hispanic completers in rural institutions ...... 106 4 42 Suburban institution variables regressed for minority student enrollment ......... 108

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11 4 43 Results of regression function for minority enrollment in suburban institutions 108 4 44 Suburban institution variables regressed for minority student graduation rates 109 4 45 Results of regression funct ion for minority graduation rates in suburban institutions ................................ ................................ ................................ ......... 110 4 46 Suburban institution variables regressed for minority completers ..................... 110 4 47 Results of regression function for minority completers at suburban institutions 111 4 48 Suburban institution variables regressed for black student enrollment ............. 112 4 49 Results of regression function for black student enrollment in suburban institutions ................................ ................................ ................................ ......... 112 4 50 Suburban institution variables regressed for black student graduation ............. 113 4 51 Results of regr ession function for black student graduation rates at suburban institutions ................................ ................................ ................................ ......... 113 4 52 Suburban Institution variables regressed for black completers ........................ 114 4 53 Results of regression function for black completers at suburban institutions .... 115 4 54 Suburban institution variables regressed for Hispanic student enrollment ....... 116 4 55 Results of regression function for Hispanic student enrollment in suburban institutions ................................ ................................ ................................ ......... 116 4 56 Suburban institution variables regressed for Hispanic student graduation ....... 117 4 57 Results of the regression function for Hispanic student graduation in suburban institutions. ................................ ................................ ........................ 118 4 58 Suburban institution variables regressed for Hispanic completers ................... 118 4 59 Results of regression function for Hispanic completers at suburban institutions ................................ ................................ ................................ ......... 119 4 60 Urban institution variables regressed for minority student enrollment .............. 120 4 61 Results of regression function for minority student enrollment in urban institutions ................................ ................................ ................................ ......... 121 4 62 Urban institution variables regressed for minority student graduation rate ....... 121 4 63 Results of regression function for minority student graduation rates in urban institutions ................................ ................................ ................................ ......... 122

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12 4 64 Urban institution variables regressed for minority completers .......................... 122 4 65 Results of regression function for minority completers at urban institutions ..... 123 4 66 Urban institution variables regressed for black student enrollment ................... 124 4 67 Results of regression function for black student enrollment in urban institutions ................................ ................................ ................................ ......... 125 4 68 Urban institution variables regressed for black student graduation rates ......... 125 4 69 Results of regression for black student graduation rates at urban institutions .. 126 4 70 Urban institution variables regressed for black completers .............................. 127 4 71 Results of regression function for black completers at urban institutions ......... 127 4 72 Urban institution variables regressed for Hispanic student enrollment ............. 128 4 73 Results of regression function for urban Hispanic student enrollment .............. 128 4 74 Urban institution variables regressed for Hispanic student graduation ............. 129 4 75 Results of regression function for Hispanic student graduation rate at urban institutions ................................ ................................ ................................ ......... 130 4 77 Urban institution variables regressed for Hispanic completers ......................... 131 4 78 Results of regression function for Hispanic completers at urban institutions .... 131

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13 LIST OF FIGURES Figure page 2 1 Intersection of disadvantage experienced by rural minority students. ................ 54 2 2 Conceptual model of how the ecological system framework describes the interaction between a college student and support programs within the campus environ ment. ................................ ................................ ......................... 57 2 3 Application of the ecological systems framework to the factors impacting rural minority student success in the college/university environment. ......................... 61 3 1 Regression functions by geographic context ................................ ...................... 73 4 1 Regression functions ................................ ................................ .......................... 92 5 1 A new model for supporting rural minority students. ................................ ......... 148

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14 LIST OF ABBREVIATIONS FGIC First Generation in College FTIC First Time in College HBCU Historically Black College or University HSI Hispanic S erving Institution PWI Predominantly White Institution USDA United States Department of Agriculture USDOE United States Department of Education TRIO TRIO is not a traditional acronym, but rather re fers to a group of federal grants administered by the USDOE that support postsecondary access and success of low income, first generation in college, disabled, and other nontraditional student populations. TRIO began with three grant programs and has since grown to seven, including the Student Support Services, McNair Scholars, Educational Opportunity Centers, Upward Bound, Upward Bound Math/Science, and Veterans Upward Bound grant programs.

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15 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 Education RURAL POSTSECONDARY INSTITUTION ATTRIBUTES AND THEIR RELATIONSHIP TO MINORITY STUDENT ENROLLMENT, GRADUATION, AND COMPLETION By Lindsay Lynch May 2014 Chair: Dale Campbell Co Chair: Pedro Villarreal III Major: Higher Education Administration This study evaluated the relationship between college and university attributes and success of their minority student populations in terms of enrollment, graduation, and completion. Data regarding institution status as a minority serving institution, support and services designed to target nontraditional and disadvantaged student populations, percentage of staff and faculty classified as a r acial or ethnic minority, and whether or not it has targeted supplemental funding were captured from the National Center for Education Statistics Integrated Postsecondary Data System (IPEDS) and United States Department of Education. Institutional data was sub divided into three geographic context categories: rural, suburban, and urban. A nalyses were used to establish a functional relationship between the independent variables and minority student rates of enrollment, graduation and completion within each geographic context category. Based upon the IPEDS academic outcomes definitions, graduation refers to the rate at which students earn posts econdary credentials within 150% of the standard time and completion refers the

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16 rate at which students earn those same credentials, regardless of their length of study or other variables ( www.ipeds.gov/glossary ). Together, these relationships were used to develop a model of successful strategies for providing the most effective support system for minority students attending a rural college.

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17 CHAPTER 1 INTRODUCTION Purpose of the Study Through a better understanding of institutional design constructs and how they correlate to patterns of increased minority student success, rural colleges and universities will be better positioned to implement effective interventions supportive of all stu dent demographics. For decades, colleges and universities have shaped their support programming by literature evidencing the need to address racial disadvantage as a primary factor in success disparity across student demographics. While a vast body of rese arch is available regarding the need to support student development of a healthy racial identity as a means of facilitating a higher degree of success in postsecondary education, this population also presents an overwhelmingly high percentage of students w ho also meet low income and first generation in college classifications. Disaggregating the impact of race and racial identity from the other indicators of disparity has not been clearly addressed in the literature, leaving higher education professionals t asked with providing separate interventions. Ironically, it is often institutions challenged to serve student populations with the largest concentration of these demographics that have the most limited resources available to support such disperse student i nterventions. Rural colleges and universities, especially those with open access and less restrictive admission policies, serve some of the most disadvantaged student populations in all of higher education. Quite often their minority student populations co me from severe poverty, generations of low educational attainment, and decades of socio economic oppression; however, students in the racial minority often indicate many of those same disadvantages. Administrators at those

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18 institutions must decide how best to allocate their precious resources in an effort to effectively support the largest cross section of students. Given the national trend to expand access to higher education, it is only reasonable to assume that higher education must be poised to serve a n increasingly non traditional student population. Increasing emphasis on ensuring equitable success equates to increased institutional pressure to implement strategies and interventions in support of those populations. This research effort investigate d th e relationship between commonly tracked institutional programs and institution wide success of minority student populations. Through analysis of support programs for disadvantaged students at rural colleges, this study will provide data regarding the chara cteristics that most highly correlate with improved minority student success. Purpose statement The purpose of this study is to evaluate the nature of the relationship between institution student support programs and the academic success of minority stud ents, controlling for institution geographic context. The independent variables include geographic context (rural, suburban, or urban), HBCU designation (Historically Black College or University), existence of support services and special programs, presenc e of minority faculty and staff, and targeted supplemental funding. The dependent variables are minority student retention rates, graduation rates (within 150% of the standard time) and completion rates (with no time limit) It is expected that these anal yses will generate correlational data regarding a model of interventions that best support minority student success at rural serving institutions. These data are also expected to provide the higher education community with greater insight as to those facto rs which most substantially impact success for this student demographic.

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19 Research Questions The purpose of this empirical study is to evaluate the relationship between institution geographic context and academic outcomes of minority college students. A tw o phase multivariate methodology will be utilized to compare institution level academic outcome data for minority students, disaggregated by institution geographic context Graduation (within 150% of the standard time) and completion rates (with no time li mit) will be evaluated for minority students enrolled in public institutions of higher education. Successful academic outcomes will be correlated to specific institution attributes, as well as the presence of institution identified special services and lea rner support programs. Analyses will be conducted to answer the following research questions: 1. To what extent do academic success outcomes (enrollment, graduation, and completion) of minority college students vary based upon institution geographic context ( rural, suburban, and urban)? 2. Which special services and learner support programs correlate to higher academic outcomes for minority students in rural institutions? 3. serve minority students in a rural geographic context? Statement of the Problem Serving close to 2.5 million students annually, rural colleges and universities are Center for E ducation Statistics, 2012). Often tasked with being more than merely providers of education, rural institutions play a central role in their communities. Cultural enrichment, lifelong learning, economic development, and cultivation of local resources repre sent just a handful of the hats they wear (Cohen & Brawer, 2008). Most

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20 importantly, perhaps, rural colleges and universities are valued for what they represent the promise of education and prosperity for those far removed from the long standing ivy clad For many decades education has been recognized as the great economic equalizer system has evolved from an enclave of elitist schools built on the European liberal arts model to a diverse network of institutions ranging from small, technical education centers to massive research intensive universities. The first major paradigm shift came with the land grant institutions of the late nineteenth century. They represented a new face for higher education expanded access and a focus on innovation and excellence in technical l growth and prosperity as an emerging industrial power (Mellow & Heelan, 2008). As American industries witnessed nearly exponential growth in technology, they demanded employees with more than a high school education. They needed a highly skilled workforc e, and education became the indirect economic catalyst for expanded access to higher education. Just as the types of institutions changed, so did the programs they offered and the students they served. Higher education was focused on accessibility, with th the era of the community college, with open admission two year institutions being constructed in cities and towns nationwide (Cohen & Brawer, 2008). Originally intended to focu s on the first two years of the liberal arts model, they expanded into comprehensive schools with transfer as only one of their many missions. Open access

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21 colleges would make the dream of higher education a reality for nontraditional students in a vast ran ge of communities, from urban to rural (Mellow & Heelan, 2008). In tandem, legislation was passed guaranteeing federal student financial aid funding and racial and gender equality within the campus culture. On the global stage, the exponential growth of Am erican higher education catapulted the country to a new level of international prestige and economic dominance (Mellow & Heelan, 2008). The United States had education at every level, from advanced research and innovation in the universities, to small scal e workforce training at the local community colleges and technical centers (Cohen & Brawer, 2008). It quickly became apparent that access alone was not the solution. As colleges were pushed to diversify their student bodies, it quickly became apparent tha t certain populations of students did not thrive in a traditional higher education culture. Predominantly white institutions were challenged to serve students of color. Low income and first generation in college students often arrived academically underpre pared and struggled to balance school with work and family obligations. Institutions were pushed to do more and did; however, the traditional baccalaureate model seemed amiss as colleges scrambled to split resources between student services, support progra ms, and academic departments. The rising cost of higher education and concerns over achievement gaps resulted in a national call for academic accountability which challenged colleges to do more with less (Guskin & Marcy, 2002). Rural colleges were already struggling to do more with less (Pennington et al). Closing the widening racial achievement gap in higher education has become a point of critical concern. Institutions, practitioners, policy groups, and even the federal

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22 government have supported research on interventions and best practices to improve success for these non traditional students. While there does exist a robust body of research regarding success of traditionally recognized disadvantaged student groups racial and ethnic minorities, low incom e, and first generation in college students. The literature is weak in regards to meeting needs of these students in the rural college environment. Rural colleges need contextually based effective practices for improving success of their disadvantaged stud ent groups. They are experiencing explosive enrollment changes while struggling to serve unique student populations, making best practice models of interventions for minority rural college students an issue of growing importance. Minority Students in a Ru ral College Context There is no single descriptor for rural colleges. They range in size from small community colleges to large universities. What they do have in common is a rural geographic context which equates to lower quality academic feeder systems, greater demands on the institution, and limited external resources (Budge, 2010; Laskey & Hetzel). They are also the most common entry point for rural students, and are often challenged to serve some of the most disadvantaged populations in higher educatio n (Laskey & Hetzel). Given the vague definition in the literature regarding what constitutes serving institution. Understanding rural communities and students is crucial to under standing rural serving colleges and universities, because the external cultural environment deeply impacts the internal culture of an educational institution (Gregory & Noblit, 1998). Rural students represent perhaps one of the least studied demographics i n higher education.

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23 While racial and economic achievement gaps dominated much of higher education research, challenges faced by rural students oft went unnoticed or were subsumed by other non traditional student classifications, such as low income and firs t generation in college descriptors. Rural students, and as a result, rural colleges, did not receive interest until data emerged showing unique retention, transfer, and graduation patterns that appeared to be specifically related to rurality (Downey, 1980 ; Ali & McWhirtier, 2006; Peters, 1990). Understanding the unique intersection of factors affecting rural students is crucial to understanding rural colleges and the rural community environments in which they exist. The longstanding assumption that struggl es faced by rural college students was attributable to poor academic preparation has been replaced by a deeper understanding of the complex social, academic, and familial factors that impact their development (Demi, Jensen, & Snyder, 2010; Schonert, Elliot t, & Bills,1991; Laskey & Hetzel, 2011). Regardless of race and economic status, rural college students present characteristic social and academic patterns. As products of quaint communities with small high schools, they thrive in highly engaging and inter active social and academic circles, often struggling to assimilate to the culture of a large university (Schonert, Elliott & Bills, 1991; Downey, 1980; Freeman, 2006). A comparison of withdrawal and transfer patterns of urban and rural students paints a te lling picture. While urban students who withdraw often stop attending entirely, rural students tend to transfer to smaller, more intimate institutions (Aylesworth & Bloom, 1976; Schonert, Elliott, & Bills, 1991; Guiffrida, 2008). Rural students attending l arge universities also report social and personal concerns as their most common reason for withdrawal (Peters, 1990).

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24 The familial background for rural students is often much more structured and autocratic, engendering stronger ties to home and the family unit (Demi, Jensen, & Snyder, 2010). While the strength of the family unit can be a benefit to students, it has been shown to be the source of conflict for rural students torn between family needs and educational aspirations. Rural students develop social ly with a strong sense of place and ties to their geographic roots (Guiffrida, 2008). Their tendency to place home and family above personal educational goals may be a result of limited early exposure to careers and opportunities, especially for women and minorities (Gibbs, 1989). Minority Student Success A wealth of research exists regarding factors relating to success of minority college students and institution level interventions demonstrated to improve minority student retention and graduation. Minority students have emphasized the need for a visibly d iverse and welcoming campus culture that provides a combination of academic, social, and emotional support (Museus, 2008; Price, Hyle, & Jordan, 2009; Loo & Rolison, 1986; Jenkins, 2007). Minority students report feelings of isolation and exclusion within predominantly white institutions. The presence of social and cultural organizations focused strongly on the needs of minority students have been recognized as crucial support mechanisms in helping students of color adjust to the college campus culture, bec ause they provide a culturally familiar home base (Museus, 2008). Minority college students do not thrive in a color blind campus environment, needing the campus culture to recognize that race relationships are important in the racial identity development process (Jenkins, 2007). They need a campus culture that embraces discourse and diversity, promoting communication and collaboration in a healthy environment.

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25 The presence of minority faculty and staff also play an important role in minority itudes toward the campus. A visibly diverse campus faculty and staff are important for two reasons. They not only improve student connections to and engagement with the campus culture, but they also send a strong message to students of color that the campu s supports diversity and is committed to the success of all students. Multiple studies have evidenced that low rates of persistence and success of minority college students are more directly related to sociocultural alienation than any other factor (Loo & Rolison, 1986; Jenkins, 2007; Orozco, Alvarez, & Gutkin, 2010). The combination of poor academic preparation, limited economic resources, and a unique set of psychosocial development factors position rural students as an at risk population in higher educat ion (Laskey & Hetzel, 2011; Schonert, Elliott, and & Bills, 1991; Peters, 1990). Rural Minority Students: The Intersection of Disadvantage Many of the factors negatively impacting minority college students align closely with problems faced by rural studen ts. For rural minority students, however, they compound to create a perfect storm. While rural students have a higher rate of poverty than their urban peers, the poorest demographic nationally are rural minorities, with rural black families reporting the m ost extreme poverty levels (United States Department of Agriculture, 2011; Lichter, Parisi, Grice, & Taquino, 2007). In addition to the micro social development common for rural youth, rural minority students must also overcome psychosocial development in communities steeped in hierarchies of race and class based discrimination (Farmer, Dadisman, Latendresse, Thompson, Irvin, & Zhang, 2006). In contrast to growing trends of integration and suburbanization experienced by urban minorities, rural minorities st ill remain largely segregated (Lichter,

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26 Parisi, et al.). Rural minority adolescents are also much more likely to be raised in single parent families and, if they pursue higher education, be first generation in college students (Harris & Zimmerman, 2003). T he environmental factors experienced by many rural minority students during crucial emotional and social development periods predicate them for internalizing a negative racial self identity (Evans, Forney, Guido, Patton, & Renn, 2010). The college environ ment, however, is not an escape from the negative, oppressive experiences at home. While rural institutions draw many of their students from their geographic regions, institutional elements such as athletics and specialized majors continue to draw diverse students together, forcing them to adjust to new experiences and relationships (Diver Stamnes & Lomascolo, 2006; Woldoff, Wiggins, & Washington, 2011). Rural minority college students report experiences of two fold discrimination feelings of isolation wi thin a predominantly white environment and alienation by their more urbanized minority peers (Woldoff, Wiggins, & Washington, 2011). Rural minority student alienation exists in higher education across institution type, from the student centered environment of a community college, to the academic rigor of a university setting. Given that rural students attend rural colleges at a much higher rate than urban or suburban institutions, it is necessary to develop an intervention model best suited for the environm ental constraints and internal culture of a rural institution. Deficiencies in Previous Literature The literature contains significant research regarding minority student populations; however, studies pertaining to rural students are significantly limited by comparison. A majority of the studies regarding rural students focus more on pre

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27 collegiate education and the impact of psychosocial development within the rural community context. While understanding these factors is crucial to developing support mech anisms for rural college students, information about the rural college itself is equally important; however, the division between institutional aspects and student development is very blurred within the literature. Little research is available regarding ru ral colleges as unique organizational entities. The limited scope of literature that is available refers almost exclusively to rural community colleges. While these studies provide a foundation of information, selective admission universities and four year colleges serve a different student demographic. Significance of the Study Serving the needs of minority students in an urban context can be markedly different than within a rural setting. While evidence of racial disadvantage exists across almost every d emographic sector in American society, racial stratification is magnified, for all intents and purposes, by other factors of disadvantage within the rural context. Developing a successful rural college model supportive of minority student success begins wi th first recognizing that publicly funded rural colleges exist in a different environmental context than their urban and suburban counterparts. While plenty of research has been conducted regarding methods for improving success of minority students, many of the proposed steps are extremely difficult for rural colleges. The literature is robust with recommendations to hire minority faculty and staff, however, in a rural predominantly white community this is not an easy task (Pennington, Williams, & Karvonem 2006). It is even more difficult when framed by the academic requisites needed, given the low degree attainment rates in rural communities. At times, securing adequate faculty to cover the breadth of courses listed in the catalog is

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28 challenging in its ow n right, much less meeting racially driven quotas. Recruiting minority faculty and staff to relocate to rural, predominantly white communities steeped in racial and ethnic segregation is equally challenging. White administrators are often not oblivious to the challenges faced by minority students on their campuses. Yet despite their recognition of the value added aspect an enhanced focus on diversity affords the campus community, they are often at a loss as to how such services should be implemented. Tackl ing diversity obstacles often means going beyond internal factors and overcoming external forces that shape the campus culture. Despite their professed awareness of obstacles faced by minority students and the need to promote a campus environment more cond ucive to broad based student success, they tend to be largely unaware of how the campus culture is truly perceived by their minority students (Diver Stamnes & Lomascolo, 2006). Dwindling minority enrollment rates, particularly among male students in rural serving institutions highlights the need to develop a paradigm of support services tailored to their needs; however, their low numbers place colleges in a difficult position to justify allocating precious resources without a proven rural college model. Hi storical Perspective Beginning with passage of the Morrill Act in 1862, American higher education has witnessed a trend towards expanded access over the last one hundred and fifty years. While initial steps focused on physical access and development of a m assive land grant university system, subsequent steps such as the Civil Rights Acts of 1964, Higher Education Act of 1965, and the Higher Education Opportunity Act of 2008 put into place a framework supportive of equitable racial, ethnic, socio economic an d cultural access to education. According to the American Association of University Professors, despite

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29 significant federal effort on this front, a comparison of enrollment statistics to the overall population indicates that minority students are actually years ago (Renner, 2003). While data do indicate that overall degree attainment rates for black and Native American populations should be proportional to their population demographics by 2030, this positive trend is primarily due to achievement of females, with males falling substantially behind (Longtime & Jones, 2011). Hispanic and Latino males are categorized by Saenz and Ponjuan (2011) as all but disappearing from American colleges and universities. Trend data indicate tha t by 2030, Hispanic student achievement will be at best two thirds of their population representation, positioning them to enter a long term cycle of underrepresentation in higher education. Long term underrepresentation holds potential for a self sustaini ng cycle of disparity that becomes increasingly difficult to dismantle (Longtime & Jones, 2011). Contribution to Higher Education Research and Practice qualitative (institutional type minority student postsecondary enrollment trends nationwide indicates that they demonstrate enrollment cluster patterns in racially based institutions, such as Historically Black Colleges and Univers ities (HBCUs) and Hispanic Serving Institutions (HSIs), and in institutions located adjacent to major metropolitan areas (Renner, 2003). Despite their low enrollment patterns at rural and suburban, predominantly white institutions (PWI), it is these instit utions that pose the greatest potential impact on achieving educational equality. The economic downturn of 2008 has launched a series of socio economic shifts that will serve to push academic equality in non metro institutions to the forefront of higher ed ucation research.

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30 The Brookings Institute reports that as of 2011, 57% of the U.S. black population resides in the South a 50 year high (2011). This population redistribution is being largely attributed to financial trends impacting the North and Northe astern industrial sectors. Financial constraints, massive lay offs, and loss of personal wealth resulted in a pseudo Brookings Institute, 2011). With its lower cost of living and opp ortunities for employment become ideal relocation options. Lifestyle, salary, and employment opportunity gaps between metropolitan and non metropolitan regions have all but closed for individuals with a Baccalaureate or higher degree (United States Department of Agriculture, 2011). Those same gaps, however, have widened for individuals at the bottom of the educational strata (United States Department of Agriculture, 2011). As minority families spread away from their former metropolitan centers, developing networks and infrastructure supportive of their education needs will become more pressing for suburban and rural colleges and universities. Organization of the Study The ana lyses of institutional support programs and their relationship to increased minority student success is organized into five chapters. Chapter two will provide a review of relevant literature, including current research on minority student populations, rura l minority student populations, and rural colleges and universities as a unique subset of higher education institutions. Chapter three will outline the research methodology employed in this study, which includes the regression equation, its variables, data collection, and analytic techniques. Chapter four will present findings from this research, including minority student population trend data for more than 1,800

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31 rural serving institutions of higher education. Chapter five will present implications for the shaping student support efforts in the rural serving institution context. Defin ition of Terms Data sets obtained for this research effort are secured through the Integrated Postsecondary Educational Data System (IPEDS). As stipulated in the Higher Education Act reauthorization, all institutions receiving federal financial aid funding will submit annual institution level data. The definitions listed below are based upon data parameters and definitions provided by IPEDS and utilized as universal definitions for all reporting institutions. 1. on of an educational degree program. For purposes of this study, degree completion generally refers to attainment of either a two year or four year degree. Institutions granting more ed in these analyses. 2. admission and has been notified of one of the following actions by the institution: admission, non admission, wait listing, or withdrawal. 3. Graduation refers to completion of the degree or credential within 150% of the standard time (i.e. a two year degree within four years; a four year degree within six years). 4. Completion refers to completing the degree or credential without regard to a defi ned timeframe. 5. Campus culture is the combination of various cultures on campus created jointly by all university person and accumulated in the long term practice of school running. It consists of three aspects, namely, material culture, institutional cult ure and spiritual culture. Campus material culture, commonly taken on in the form of environment and facility, is the general name of external form of materialization in the development of university. Institutional culture includes the system shared in com mon and the distinctive system, which mainly refers to rule and regulation system, management and operation rule and restriction mechanism. Spiritual

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32 culture refers to how campus person take part in cultural activities and what results are achieved, thus r eflecting the ideology, values, psychological quality and aesthetic consciousness, etc. It includes written culture, behavior culture and mental culture. Material culture is the external symbol of campus culture. Institutional culture guarantees the orderl y development of campus culture. Spiritual culture is the core and spirit of campus culture. 6. Degree of Urbanization indicates the population density and proximity of the Sub urban, and Urban indicators are based upon IPEDS classifications, which utilize 2004 U.S. Census Bureau designations. 7. Rural and Rural Geographic Context are classifications that designate an institution of higher education physically removed from metropol itan population centers. For purposes of this research, the category encompasses five IPEDS classifications as follows: Rural Remote indicates an institution located in a Census defined rural territory that is more than 25 miles from an urbanized area and is also more than 10 miles from an urban cluster; Rural Distant indicates an institution located within a Census defined rural territory that is more than 5 miles but less than or equal to 25 miles from an urbanized area, as well as rural territory that is more than 2.5 miles but less than or equal to 10 miles from an urban cluster; Rural Fringe indicates an institution located within a Census defined rural territory that is less than or equal to 5 miles from an urbanized area, as well as rural territory that is less than or equal to 2.5 miles from an urban cluster; Town Remote indicates an institution located within a territory inside an urban cluster that Is more than 35 miles from an urbanized area; and Town Distant indicates an institution located within a territory inside an urban cluster that is more than 10 miles and less than or equal to 35 miles from an urbanized area. 8. Suburban and Subu rban Geographic Context are classifications that designate an institution of higher education located within reasonable proximity to a metropolitan population center, yet distant enough to maintain a separate identity from the more densely populated region This category encompasses four IPEDS classifications as follows: Town Fringe indicates an institution located in a territory inside an urban cluster that is less than or equal to 10 miles from an urbanized area; Suburb Small indicates an institution loca ted within a territory outside a principal city and inside an urbanized area with population less than 100,000; Suburb Midsize indicates an institution located within a territory outside a principal city and inside an urbanized area with population less th an 250,000 and greater than or equal to 100,000; and Suburb Large indicates an institution located within a territory outside a principal city and inside an urbanized area with population of 250,000 or more. 9. Urban and Urban Geographic Context are classifi cations that designate an institution of higher education as being located within a recognized population center. This category encompasses three IPEDS classifications as follows: City

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33 Small indicates an institution located within a territory inside an urb anized area and inside a principal city with population less than 100,000; City Midsize indicates an institution located within a territory inside an urbanized area and inside a principal city with population less than 250,000 and greater than or equal to 1 000,000; and City Large indicates an institution located within a territory inside an urbanized area and inside a principal city with population of 250,000 or more. 10. Enrollee is a student who applied, was admitted, and subsequently enrolled. 11. First Gener ation in College (FGIC) denotes a student from a household in which no parent has earned a Baccalaureate or higher credential. For students whose parents do not reside in the same household, FGIC status is determined by the education level of the custodial parent. 12. First Time in College (FTIC) refers to a student enrolled in college for the first time. This includes both academic and professional track students, students granted early admission, enrollees in the summer term prior to their first fall semeste r, and students who enter with advanced standing or accrued credits via dual enrollment, Advanced Placement, and International Baccalaureate. 13. Historically Black College or University (HBCU) The Higher Education Act of 1965, as amended, defines a HBCU as: university that was established prior to 1964, whose principal mission was, and is, the education of black Americans, and that is accredited by a nationally recognized accrediting agency or association determined by the Secretary [of Education] to be a reliable authority as to the quality of training offered or is, according to such an agency or association, making reasonable progress toward s to the founding date ( www.ipeds.gov ). 14. Racial/Ethnic Minority designates students whose primary racial or ethnic identity is non white. For purposes of this study, this classification specifically includes Hispanic an d Latino, American Indian and Alaskan Native, Asian, Black/African American, Native Hawaiian or Other Pacific Islander, and students indicating two or more races. 15. Hispanic & Latino: A person of Cuban, Mexican, Puerto Rican, South or Central American, or o ther Spanish culture of origin, regardless of race. 16. American Indian & Alaskan Native: A person having origins in any of the original peoples of North and South America (including Central America) who maintains cultural identification through tribal affili ation or community. 17. Asian: A person having origins in any of the peoples of the Far East, Southeast Asia, or the Indian Subcontinent, including for example, Cambodia, China, India, Japan, Korea, Malaysia, Pakistan, the Philippine Islands, Thailand, and Vie tnam.

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34 18. Native Hawaiian or Other Pacific Islander: A person having origins in any of the original peoples of Hawaii, Guam, Samoa, or other Pacific Islands. 19. Racial/Ethnic Majority Designates students whose primary racial identity is white. The term majority is utilized not as a numerical representation, but rather an indication of the dominant socio cultural group within the field of higher education.

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35 CHAPTER 2 A REVIEW OF THE LITERATURE Institutional Factors and Minority Student Success Developing a mode l that accurately describes the relationship between college factors and minority student academic success hinges on a number of variables that work together to create a complex institutional environment. While some of these variables represent commonly un derstood definitions used widely in literature regarding higher education, others, however, are less clearly defined. This literature review will begin with a review of key terms found in the literature, including a discussion of the environmental context of rurality and how it impacts the institutional environment. It will then include a review of recent research in student services, learner support, and targeted funding as institutional interventions used to enhance success of disadvantaged student popula tions. Rurality. that federal agencies and researchers can agree on is that rural is really a multidimensional quality that can be used to describe population concentration, geographic isolation, economic power, and access to resources. In a dynamic, globally connected so ciety, the delineation between rural and urban has become less defined. Rurality has evolved to represent more of a spectrum than distinct classifications. For purposes of this research effort, the twelve geographic classifications as defined by the U.S. C ensus will be broken down into three primary categories that best represent rural, suburban, and

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36 urban serving institutions. These geographic strata are based on physical location, as is the primary definition used throughout the literature. Psychosocial development. Psychosocial development encompasses the face as their lives progress, such as how to define themselves, their relationships with others, and what to do with the Psychosocial development theories are most commonly associated with cognitive the cognitive development of coll related moral development (Evans et al. 44). In addition to cognitive development theories, psychosocial development also encompasses learning style theory and iden tity development (Evans et al.). Identity development research is closely tied to research and support models for serving nontraditional student demographics. identity theories. E development which are shaped by the social and historical context experienced by the individual (Evans et al.). Since the initial theory proposed by Erikson, a number of other resear chers have built upon his foundation of identity development, particularly in respect to minority and female populations. Racial identity development. Research regarding racial identity development began to emerge in the mid Psychological Nigrescence which would later evolve into the Nigrescence lifespan

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37 approach developed by Cross and Fhagen Smith (Eva ns et al.). They proposed distinct patterns of black racial identity development, with particular emphasize on the identity development process as it is experienced by black adolescents who develop a negative self perception, or internalized racism, and ho w that manifests in young adulthood a crucial developmental period for college students. In addition to the work of Cross and Fhagen Smith, Rowe, Bennett, and Atkinson developed the White Racial Consciousness Model; Ferdman and Gallegos established a mod el of Latino Identity Development, Jean Kim proposed the Asian American Identity Development Model; and Horse developed a model for American Indian Identity Development (Evans et al.). Research evidencing a clear connection between patterns of racial ident ity development and student academic success has not emerged; however, the body of work in this field country of origin, and culture that can also shape identity (as cited in Evans et al. p. increased need for theoretical perspectives that address diverse student populations, closer scrutiny of nonwhite racial identity theories is also necessary to better understand the rapidly growing student populations that are increasingly becoming the majority in Minority Serving Institution In addition to Historically Black Colleges and U niversities (HBCUs), the United States Department of Education allows colleges and Serving Institutions (MSIs) to also qualify for additional support funding. According to the U.S. Department of Education, MSIs inclu de the following institutions: Hispanic serving institutions, Alaskan Native serving

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38 institution, Hawaiian native serving institutions, Tribal colleges, predominantly black institutions, Asian American and Native American/Pacific Islander serving instituti ons, and Native American non tribal institutions (USDOE, 2007). To fall into these categories, colleges and universities must meet criteria related to enrollment thresholds for identified minority groups or historical criteria, as is the case for HBCUs. Cu ltural Barrier Theory. Cultural Barrier Theory was first proposed by Leong et al. in 1995 (Ramos Sanchez & Atkinson, 2009). It posits that certain Latino/a cultural attributes preclude help seeking behavior and has been applied within higher education to a ccount for Hispanic and Latino/a student reluctance to participate in advising and other support services commonly offered on college campuses. It parallels the cultural which she used as a framework for understanding why black children, especially males, tend to purposefully shun education, in her landmark book Why are all of the Black Children Sitting Together in the Cafeteria? Cultural Barrier Theory is relevant to this disc ussion of institutional support efforts for minority students, because it provides a useful framework for understanding how minority student populations perceive the campus culture, and how those perceptions may vary across generations. Education in the C ontext of Rurality Rural colleges exist as a unique entity within the spectrum of higher education institutions. Yet despite their shared environmental context, they also represent a surprisingly diverse cadre of institutions from community colleges to tie r one research universities. The impact of rurality is often not realized in institutional typology, but rather in the role it will take within the local community, in its resources, flexibility it will have, and through the programs and services it can of fer.

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39 It is not uncommon for rural colleges to exist as the primary, if not sole provider of postsecondary and lifelong learning opportunities in their immediate area. Because of this they often embody a more interactive and robust role within their local communities. In their qualitative study of ten Kansas community colleges, Pennington et al. (2006) investigated challenges faced by rural colleges. Through a series of interviews, they determined that rural community colleges face challenges common through out higher education; however, those issues are exacerbated by rural environmental factors. Their lower budgets, higher community demands, and a higher rate of students needing enhanced support services place them at a disadvantage among their peer institu tions (Pennington et al, 2006). While there are examples of rural institutions that enroll high percentages of minority students due to the composition of their local community populations, many serve pri marily ethnic majority student populations. In their qualitative study of minority student perceptions of a rural university campus environment, Diver Stamnes and Lomascolo (2006) found that minority and majority students commonly perceived the campus cult ure differently. They evaluated student perceptions regarding diversity within curricula and feelings of social marginalization within the campus culture. They found that 74% of majority students found the curriculum to be diverse, while only 13% of minori ty students felt the same. 58% of majority students reported experiencing marginalization, while 86% of minority students reported isolation and marginalization within the campus culture. Diver Stamnes and Lomascolo (2006) determined that many of the major ity students they surveyed had little or no history of experience with

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40 discrimination and diversity measures. They also concluded that the rural college administrators they evaluated were generally oblivious to how their different sub populations interacte d with each other and the campus environment. Serving Students in the Rural Institution Understanding rural students and their development needs is a key factor in understanding the challenges faced by rural institutions. Research indicates that rural stu dents present a unique psychosocial developmental pattern. Through quantitative analysis of retention patterns of 115 students in the Conditional Acceptance Program, Laskey & Hetzel (2011) found that their distinct psychosocial development impacts how stud ents interact with the campus environment. Through their research, they determined that the demographic should be recognized as a unique subset of students and that the institutions serving rural students must be prepared to tailor their support programs a round those unique developmental needs. Additional studies have also produced a body of evidence that indicates the need for higher education to recognize the uniqueness of the rural student demographic. In her ethnographic study of rural high school and c ollege students, Maltzan (2006) concluded that rurality functions as a factor interviews, she determined that both high schools and colleges must be prepared to support these students through targeted services designed to overcome rural obstacles (Maltzan, 2006). While institutions must be prepared to meet their needs, the literature does indicate that as a group, rural students tend to self select colleges and universities t hat better match their needs. Using data captured through the National Longitudinal Survey of Youth, Gibbs (1989) determined that while youth did indeed attend college at slightly

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41 lower rates than their urban peers, both groups tended to graduate at compar able rates. A key difference he found one that is perhaps indicative of the different psychosocial needs of rural and urban students was in their ideal institution typology. Rural youth were more likely to attend rural colleges or institutions that off collegial environment (Gibbs, 1989). In short, they appeared to thrive in collegiate environments that mimicked cultural elements of the rural communities they called home. Guiffrida (2008) supports the work of Gibbs (1989) and ot her rural education researchers by proposing that social and cultural adjustment issues faced by rural students, position community colleges as their ideal starting point in higher education. Evidence of rural student psychosocial development is the key t o establishing a deeper understanding of their enrollment, graduation, and transfer patterns. Rural colloquially y represent highly interactive social enclaves. Youth transitioning through social and psychological development periods in such environments establish psychosocial behavioral norms. By the time they enter late adolescence and early adulthood, they have em braced highly involved social circles. First noted by Downey (1980), this psychosocial framework for understanding rural youth educational patterns, aspirations, and success for rural youth has been reinforced in a number of studies over the past thirty ye ars. While research indicates that the college going rate of rural students is slightly lower than their urban peers, overall the difference is not viewed by scholars as being statistically different; however, distinct differences have been noted in persi stence and transfer patterns. In an effort to evaluate institutional factors related to withdrawal of

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42 freshman university students from rural communities, Peters (1990) conducted a mixed methods study of 462 students at the University of Northern Colorado. Using institutional enrollment data and a student survey, Peters noted that rural students dropped out at a rate significantly higher than urban students. Through data reported via the survey, rural students indicated a substantially higher withdrawal rat e due to personal and social reasons (Peters, 1990). Coincidentally, rural and urban students reported nearly equivalent rates of withdrawal due to financial or academic reasons. Additional studies have both reinforced these findings and provided greater insight regarding types of rural students most at risk in the traditional higher education environment. In a study of cognitive and psychosocial factors impacting 124 freshman students at a Midwest university, Ting (1997) found that traditional academic in dicators of postsecondary success, such as grade point average and standardized test scores, were not accurate predictors of rural student success. In their five year study of rural Iowa youth, Schonert, Elliott, & Bills (1991) found similar results. It is often the most academically successful rural high school students that withdraw from college at the highest rates (Schonert, Elliott, & Bills, 1991; Ting, 1997). Laskey and Hetzel (2011) analyzed student level data for 115 students at a private Midwester school students were also the most socially extraverted, and that for the population studied, there existed an inverse relationship between extraversion and retention in higher education They concluded that grade point averages and test scores may not be the best predictors of rural student success. All three studies propose that this pattern is a result of the highly involved cultural community within rural high schools. The micro

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43 socia l school environment often places the academically promising students in multiple social roles, resulting in a highly engaging developmental period. It is the same core group of students involved in multiple circles throughout the school and often communit y spheres. Transitioning from an environment of high engagement to the often diffuse, low engagement atmosphere of higher education can leave this demographic feeling isolated and disconnected from the field of student persistence and completion, engagemen t with the campus community has a profound impact on student success (Tinto, 1993; Tinto & Russo, 1994; Tinto, 2012). Beyond the micro social academic communities and social circles commonly experiences by rural youth, family and community constructs have also been indicated as a factor impacting academic trajectory. In their study of postsecondary enrollment patterns of rural youth, Demi, Jensen, and Snyder (2010) noted that the strict family hierarchical structures commonly reported by rural youth made t he transition to higher education more difficult. Through analysis of student responses to the Rural Youth Education (RYE) longitudinal study, they found a pattern of self limited behavior justified by a need to remain geographically close to the nuclear f amily. While factors such as grade point average, financial status, and FGIC classification were noted as having an impact, they were mediated by the family context. Demi, Jensen, and Snyder (2010) determined that common attributes related to rural communi ties and their families places a stronger emphasis on intergenerational bonds and the role of families within community social circles. Rural youth expressed a high degree of hesitance related to separating from the family unit and deference to the desires of older generations. When

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44 forced to choose between educational aspirations and family aspirations, rural youth were inclined to go with the latter. The negative impact of psychosocial development factors is even more pronounced for rural minority youth. In their multimodal qualitative study regarding educational and professional conceptions of Black families in the rural Deep South, Farmer et al. (2006) identified that historical context of racially based discrimination enhanced by other factors such as low income and FGIC statuses, lack of career exposure, and limited community support mechanisms, served to severely skew black student attitudes regarding higher education. They noted collective socialization hin their community infrastructure a similar trend to patterns of educational aspiration documented in rural, white Appalachian communities (Farmer et al., 2006; Ali & McWhirtier, 2006). Most parents indicated they simply hoped their children would secur e employment and the ability to make a financial contribution to the family. Aspiring to leave the community often equated to abandoning the family and social circles. Pursuing advanced education and career options beyond their immediate communities was vi ewed as breaking generational bonds and shedding age old values structures. Through their research in the Mississippi Delta region, Farmer et al. (2006) determined that generations of de facto segregation combined with a lack of exposure to career options and role models, academic support programs, and connections to a diverse community only served to magnify the negative aspects of rural psychosocial development. In his research on improving minority student education success in rural Kentucky, Stern (2010 ) proposes

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45 emphasizing access to success. He presents a case study of Jefferson Community ities to build education pathways that positioned rural minority youth for success in higher education. While severely impoverished communities of the Mississippi Delta and Appalachian regions represent extreme examples, collective research on rural minor ity students presents evidence that even in comparison to lower success rates experienced by minority students throughout higher education, rural minority students are at a disadvantage. In an evaluation of differences in transfer rates for urban, suburban and rural student groups, Castenada (2010) found that while rural students transferred at a lower rate than other student groups, rural minority students achieved even lower success. She recommends targeted support services specifically designed to meet their unique needs. In addition to overcoming racially based social and identity development patterns, minority students also report strong feelings of isolation within the college campus environment. Corley, Goodjoin, and York (1991) conducted mixed meth ods research comparing the relative academic success of rural and urban black students attending South Carolina State College. Through quantitative analysis of group SAT scores and grade point averages, they determined that while urban minority students en tered with higher standardized test scores, they earned relatively lower grade point averages through both high school and college. Despite academically outperforming their urban peers, rural youth demonstrated difficulty assimilating to the social environ ment of a college campus. Rural minority youth in their study reported feelings of

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46 Woldoff, Wiggins, and Washington (2011) built upon the work of Corley, Goodjoin, and Y ork (1991) with a phenomenological study of rural black student experiences in the university environment. Through a series of focus groups and short surveys, they meaning mak ing, interpretations, and interactions within a rural, predominantly white university. They compared data collected from both rural and urban black students. While both groups reported feelings of isolation within the campus culture, rural black students r eported additional feelings of alienation from their urban peer group. They collectively reported an in group pecking order related to rurality, with a higher degree of Learner Support Programs in the Rura l Institution The negative impact that rural youth psychosocial development has on educational success is often exacerbated by lower quality educational preparation. While not all rural K 12 systems underperform in comparison to their urban peer groups, as a whole, they commonly have fewer resources to provide the same breadth of services and support mechanisms offered by larger, urban districts. Restricted access to educational opportunities for growth, advanced achievement, and exposure to diverse experie nces translates to a different academic pathway to higher education for rural youth. In some measures, rural youth outperform their urban counterparts. In a comparative study of rural and urban youth test scores and grade point averages, Corley, Goodjoin, and York (1991) attributed the higher grade point averages of rural youth as an academic survival tactic in the college admissions process. They propose that rural youth actually develop better academic work habits to counter their lower test

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47 scores and la ck of access to Advanced Placement and International Baccalaureate coursework. Despite developing a stronger academic skill set to manage college coursework, rural youth often enter the higher education environment less prepared for advanced discipline cou rses than urban and suburban student groups. Research regarding rural youth educational trends also indicates a strong pattern of academically self limiting behavior. Through analysis of survey responses of 338 rural Appalachian students on a Social Cogni tive Career Theory battery, Ali & McWhirtier (2006) determined that educational self efficacy served as the strongest predictor of rural youth postsecondary enrollment. They propose that lack of access to a breadth of vocational and professional options co mbined with restrictive family and social constructs results in a strong pattern of self limiting behavior. To break through these perceived barriers, colleges must communicate to rural youth that not only is higher education a viable option, but that educ ational aspirations need not preclude maintaining personal and familial ties. Through his analysis of National Center for Education Statistics (NCES) Beginning Postsecondary Students Longitudinal Study (BPS) on rural youth from 1996 2011, Freeman, Conley, and Brooks (2006) found that a strong pattern of self limiting behavior connected to a lack of exposure to career and educational options. The study found the strongest pattern in rural minority youth, which he attributed to a lack of diverse role models i n certain professional categories. Rural women and minorities potentially self limit simply because they lack personal connections and self actualization in many career fields. What Really Matters for Rural Minority Students Historically, literature regar ding minority student support programs is rife with recommendations to address minority status development of a negative racial identity,

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48 lack of engagement with the predominantly white campus community, and lack of diversity as a visible element with th e campus culture as the primary obstacle to student success. For example in their phenomenological study of academically successful black males, Hrabowski, Maton, and Greif (1998) found six common developmental experiences for black males in the top 2% o f national academic rankings. Participants universally reported development of positive race and gender identities as key factors in their success. Based upon their findings and the larger body of literature regarding facilitating success for black student s, the researchers proposed that providing programs which engage minority male students in experiences to overcome internalized racism as a much needed and valid initiative on college campuses. More recent studies have supported the need for a focus on de veloping minority inclusive campus environments. Orozco, Alvarez, and Gutkin (2010) conducted a qualitative study of 363 California community college students in an effort to evaluate the impact of academic advising on minority students. They concluded tha t minority students demonstrated stronger patters of engagement and connection to the college campus when they had access to advisors with shared racial, cultural, or ethnic attributes (Orozco, Alvarez, & Gutkin, 2010). Through analysis of transfer and ret ention data on 5,000 students in the Los Angeles Community College District, Chang (2005) found that older students were more likely to interact with the campus community and also more likely to complete their educational goals. Younger minority students d emonstrated a strong pattern of disconnection from the campus community, indicating

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49 the need for environmental attributes designed to build connections with them (Chang, 2005). In a study to evaluate the role of ethnic student organizations as vehicles fo r promoting an increased level of engagement in the campus community, Museus (2008) conducted a phenomenological study of twenty four students at a mid Atlantic university. Through student interviews, Museus (2008) concluded that ethnic student organizatio ns played an important role in the campus community by serving as a liaison for students in a period of cultural adjustment and acting as a vehicle for healthy expression and cultural validation. They can also build bridges between minority subpopulations within a campus culture. The case study of Heritage College in rural Washington serves as one such example. According to Ross (1999), Heritage College utilized its minority student organizations as a vehicle to bridge communication and camaraderie between campus factions and quell rising racial tensions. Regardless of their impact on the campus community, ethnic, and minority students organizations largely represent activities funded by students, not the institutions. To date, there has been little empiric al evidence that institutionally funded programs specifically targeting minority students with a focus on facilitating ethnic and cultural identity development and engagement with the campus are effective. This lack of clear evidence is primarily due to th e strong overlap between minority student populations with low income and FGIC student populations. In the quantitative study to identify institutions successfully serving minority students, Jenkins (2007) used ordinary least squares regression analysis to evaluate institutional factors and student success

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50 and through follow up data, determined that those model colleges had tailored support programs for their minority st udent populations. Jenkins (2007) concluded that perhaps the most significant impact was realized at an institution with a federally funded Student Support Services program, which focuses on intensive intervention and services for low income and first gene ration in college students. At this particular institution, the SSS student population. While the study is limited in that the researcher did not disaggregate the po pulation based upon socio economic status, FGIC classification, and race, it does evidence the need to support disadvantaged populations through specific, intentional, interventions and services (Jenkins, 2007). Those studies that have disaggregated low i ncome and FGIC variables from race and gender present evident that race and gender are not the most indicative variables in predicting student success. In their mixed methods quantitative study of factors related to completion of returning college students Square analysis and logistic regression to evaluate the impact of race, gender, academic preparation, and participation in a readmission support program. Their results indicated that race and gender were not significa nt predictors of student success; however, participation in the support program was significant. They concluded that the most significant factors were most likely variables not captured in the study, but that the comprehensive nature of the support program addressed those issues, leading to improved success. Research conducted by Nguyen, Hays, and Wetstein (2010) regarding persistence trends for 5,427 freshmen at San Joaquin Delta College supports earlier

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51 findings that race and gender may not be as signifi cant as previously thought. Using logistic regression, Nguyen, Hays, and Wetstein (2010), determined that when controlling for race, participation in an orientation course made the biggest impact on long term academic persistence. They proposed that the si gnificant number of minority students who are also low income and FGIC has resulted in trend data indicating that it is their minority status which serves as the primary obstacle to success. Additional studies have provided the educational community with greater insight regarding the impact of various programs targeting minority students. Wohlgemuth et al. (2006) used logistic regression to evaluate environmental factors impacting retention an d graduation of minority students at a major university. They found that despite a demographic was still performing well below white students. They found that minority stude nts typically arrived with substantially weaker academic preparation, which served as their most significant obstacle in higher education (Wohlgemuth et al., 2006). They postulate that purely focusing on racially grounded supports does not address the full spectrum of interventions needed by the demographic. Wohlgemuth et al. (2006) also conclude that academic skills should serve as the strongest predictor of success in higher education, and that any support program for disadvantaged students must address t he skills gap to be effective in promoting long term student success. Another key finding from their research is that the most critical point of minority student departure from higher education occurs between the first and second years, indicating that fac tors such as financial aid and advising have a strong impact on student persistence through that juncture (Wohlgemuth et al., 2006).

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52 The case of New Mexico State University (NMSU) Grants Campus adds to the literature regarding effectively improving mino rity student academic success without specifically addressing race as an obstacle. NMSU Grants is a prime example of the significantly disadvantaged student populations that many rural community colleges are s only double MSI, with substantial Native American and Hispanic student populations and its district falls within the bottom 10% of socio economic strata nationally (Blanchard, Casados, & Sheski, 2009). Its high proportion of racial and ethnic minority st udents facilitated a naturally diverse campus community, yet those students substantially underperformed in comparison to white peers. Instead of focusing on traditional minority student interventions, NMSU Grants made the decision to support its students in ways meaningful to their unique needs (Blanchard, Casados, & Sheski, 2009). They evaluated how and why students were not completing academic programs or transferring, and determined that financial factors had the strongest impact. Students were only com pleting what they needed to meet employment goals. They transformed academic programs to create more realistic pathways, providing options for vocational and short track programs as well as on site Bachelor of Applied Science degrees (Blanchard, Casados, & Sheski, 2009). In total, they redefined success by creating multiple academic options that would allow students In an effort to build a better foundation of knowledge surrou nding how minority student populations interact with the college campus environment, Ramos Sanchez and Atkinson (2009) conducted a quantitative study of 262 Mexican American community college students in California. They compared student responses to surve ys designed

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53 to assess cultural values and help seeking behavior patterns across generations. Students in the older generation expressed a closer association with traditional Mexican cultural values, which the researchers classified as enculturated individu als, while the younger generation, which more closely associated with dominant American culture, was classified as acculturated (Ramos Sanchez & Atkinson, 2009). Using hierarchical regression analyses, the researchers evaluated differences in attitudes tow ards help seeking behaviors between the two generations. In contrast to Cultural Barrier Theory, which validates lower incidence of help seeking behavior and general engagement with the campus community among certain ethnic minority groups as a conflict wi th their engrained cultural norms, participants with stronger ties to Mexican cultural values actually had more positive reactions to engagement with the campus community (Ramos Sanchez & Atkinson, 2009). The younger generation of Mexican American students indicated they were less likely to engage in help seeking behavior than the and correlations between variables, the researchers determined that another variable unr elated to cultural or ethnic affiliation was negatively impacting the manner in which Mexican American students interacted with the college community (Ramos Sanchez & Atkinson, 2009). The larger body of research on minority students indicates that they do indeed experience a higher rate of success in the unique environment of an HBCU or HSI (Renner, 2003). When coupled with data gathered by Muses (2008) and Orozco, Alvarez, and Gutkin (2010), the literature indicates that there certainly is a value added component for campus environment which truly embraces an ethnically and culturally

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54 diverse community. However, the work of Jenkins (2007); Wohlgemuth et al. (2006); Blanchard, Casados and Sheski (2009); and Ramos Sanchez and Atkinson (2009), indicate that a gap exists between the scholarship and practice. Most likely previous research has simply been limited or skewed by the significant overlap between variables. That is, an overwhelming majority of the minority student population is also classified as low income or FGIC and quite often, both. Figure 2 1. Intersection of disadvantage experienced by r ur al minority s tudents Given the body of work regard ing the benefit of supporting college students in development of a healthy racial identity as an attribute beneficial throughout academic and life pursuits, educators would be remiss to disregard it moving forward in the design of support programs, however substantial evidence has emerged that those interventions alone are not enough. Minority students, especially those attending rural serving institutions, must have access to more robust programs designed to support them in overcoming their most substanti al obstacles. Low income students FGIC Students Minority Students Intersection of Disadvantage

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55 Theoretical Framework Given the complex nature of institutions, multiple theoretical frameworks will be applied to make sense of institutional trend data evaluated in this study. framework to guide this study. Through application of ecology systems theory, the institution is a function of its subsystems. The subsystem through which students interact with the institution is shaped by their reflection of self; therefore, theories of identity developme nt will also be applied as guiding principles in understanding how student groups interact with, interpret, and apply the institutional environment. heory. equation of developmental ecology a s follows: Development is a function of the interaction of the person and the environment (Evans, Forney, Guido, Patton, & Renn, 2010). Bronfenbrenner proposed that development occurs as a result of the interaction between process, person, context, and tim e (Evans et al.). At the heart of the model is interaction with the environment (Evans et al.). Notable scholars in the field of higher education student affairs equate B process people which facilitate interaction with th e immediate environment. This includes college faculty and staff with whom the student interacts, as well as student organization which the student interacts with the envir well known part of the model and the cornerstone of the ecological system. Ecological

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56 context, which is comprised of micro meso exo and macrosystems, has emerged as the most important element of his theor y in relation to the field of college student development, most particularly regarding how the student interacts with multiple layers of the college environment. It is an assumption of the model that elements represented by the system evolve over time. For purposes of this study, the student will represent the microsystem and the institution will represent the mesosystem.

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57 Figure 2 2. Conceptual model of how the ecological system framework describes the interaction between a college student and support programs within the campus environment. Micro System Student Support Program Student Affairs Activitie s Academic s Macro System Society Exo System Family & Community Meso System College Campus

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58 frame to interpret the relationship between psychosocial development, college environment, and community and family structures that shape the college experiences of rural minority students. The Micro System: Rural, Minority Psychosocial Development. Maltzan (2006) found a negative relationship between rurality and academic success. Psychosocial development in the micro social environment of rural communities and schools does not adequately prepare students for the less involved, more independent culture common in postsecondary education (Gibbs, 1989; Maltzan, 2006). In addition to growing up in the highly involved, micro social rural commun ity environment, rural, minority students must overcome a milieu of additional developmental obstacles. They often come from communities with entrenched patterns of race and class based discrimination (Farmer et al. 2006). The literature indicates signific ant, long term implications for racial identity development within such an oppressive and negative environmental context. Cross and Fhagen Smith identified three distinct patterns of racial identity development with pattern B representing individuals who develop in the absence of a healthy black racial identity (Evans et al.). This lack of positive racial identity often manifests in low race salience and eventual internalized racism (Evans et al.). Preadolescence and adolescence are crucial developmental s ectors for individuals in this pattern, because it is at this juncture that a negative racial self concept will either be challenged or reinforced. While their research specifically focused on black racial identity development, later research on other

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59 mino rity student populations supports similar patterns of challenge versus reinforcement (Evans et al.). Rural minority students are also more likely to come from the poorest social strata, be raised in single parent homes, and be the first in their families to attend college (USDA, 2011; Lichter, Parisi, Grice, & Taquino, 2007; Harris & Zimmerman, 2003). Thi s combination of developmental and environmental factors shape their self perception, academic trajectory, professional aspirations, and interactions with peers and college faculty and staff. In short, the micro system determines how the student will int eract with the meso system (campus environment). College administrators must first understand the unique rural, minority student micro system before they can develop an effective meso system. The Meso System: The Rural College Campus. Rural colleges are f requently challenged to do more with less. They typically have fewer resources available, yet must serve the most disadvantaged student populations (Budge, 2010; Laskey & Hetzel, 2011). According to Pennington et al. (2006) they tend to have lower budgets, more community demands, and a higher percentage of students in need of special services. Rural college administrators must determine the most effective allocation of resources to promote broad based rural student success. Application of the ecological sys tems equation frames interaction of both the micro system (student) and the exo system (community and family) contexts with the meso system (campus community and culture). Campus based supports must balance unique rural student development patterns. To som e extent, rural colleges and universities naturally do this, as evidenced by rural student enrollment and transfer patterns published by Peters (1990). However,

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60 more effective service patterns must still be established to support rural minority students, a s they remain the most at risk demographic across institution geographic context (Harris & Zimmerman, 2003). The Exo System: Rural Communities and Families. According to Gregory and Noblit (1998), the external community profoundly shapes the internal cultu re of a college or university. Therefore, understanding the nature of rural communities is a crucial factor in understanding rural colleges and universities. Rural communities place a strong emphasis on intergenerational bonds and family involvement in the community (Demi, Jensen, & Snyder, 2010). The families themselves often function within a strict, authoritarian hierarchy, which promotes a strong expectation to place family responsibilities above personal academic and career aspirations (Gibbs, 1989; De mi, Jensen, & Snyder, 2010). There are also strong patterns of collective socialization and 2006; Demi, Jensen, & Snyder, 2010). Across all academic variables, the f amily/community unit has been identified as the mediating factor in predicting rural student academic success (Demi, Jensen, & Snyder, 2010). This study builds upon the previous literature regarding the campus meso system by evaluating the impact of the f ollowing new variables: placement services, employment services, campus based day care, evening and weekend courses, and distance education options. These variables combined with the traditional variables of academic /career counseling and remedial services

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61 Figure 2 3. Application of the ecological systems framework to the factors impacting rural minority student success in the college/university environment. Macro System: Society Exo System: Rural Community and Families Typically highly structured, autocratic, and involved enclaves that commonly establish unique definitions of success; psycho social development in this environment may involve de facto racial and class based segregation; May promote self limiting behavior through lack of exposure to diverse role models, experiences, professions, and educational options. Meso System: Rural Campus Culture Micro System: Rural Minority Student The rural minority student is most likely low income, FGIC, a nd academically under prepared This student is also likely to have developed a negative racial identity. Student is also accustomed to a highly involved micro social context, with patterns of frequent interaction with fellow students, family, and comm unity. Student Activities Academics Student Services Admissions Financial Aid Registration Advising & Counseling Ideal Student Support Program A program that most effectively supports rural, minority students has yet to be identified, hence the purpose of this study.

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62 CHAPTER 3 METHODOLOGY The purpose of this empirical study is to evaluate the relationship between institution geographic context and academic outcomes of minority college students. A two phase multivariate methodology will be utilized to compare institution level academic outco me data for minority students, disaggregated by institution geographic context. Student graduation (within 150% of standard time) and completion (with no time limit) will be evaluated for minority students enrolled in public institutions of higher educatio n. Successful academic outcomes will be correlated to specific institution attributes, as well as the presence of institution identified special services and learner support programs. Analyses will be conducted to answer the following research questions: 1. T o what extent do academic success outcomes (student graduation and completion) of minority college students vary based upon institution geographic context (rural, urban, and suburban)? 2. Which special services and learner support programs correlate to higher academic outcomes for minority students in rural institutions? 3. serve minority students in a rural geographic context? The presented research questions were answered throu gh regression analyses of institution level data collected by the Integrated Postsecondary Educational Data System (IPEDS) and U.S. Department of Education Of fice of Postsecondary Education. Results of these analyses are intended to provide practitioners w ith a best practices model for improving minority student academic success in rural colleges and universities. Crucial data for developing this model include how indicators of academic success for minority students vary in relationship to the degree of rur ality for the

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63 support programs are effective in the rural institution environment; and key institution attributes contributing to the implementation of those progr ams and services. As part of the process to answer the proposed research questions, three hypotheses were also proposed. Hypotheses While substantial research exists regarding factors impacting minority students, and proven interventions to i ncrease their s uccess in higher education, there is limited literature evaluating successful methods to support these students specifically within the rural college context. Some of the most highly promoted approaches to improving minority student success, such as hiring minority faculty and staff, targeted support programs, and a substantial minority student organization presence within the campus community, may not be feasible on the rural college campus (Pennington et al 2006). Hiring diverse faculty is often difficu lt in rural communities, which generally have lower rates of degree attainment and offer limited appeal in the recruitment process. The smaller overall enrollment in rural colleges yields smaller minority student populations, making it harder for minority students to make connections with each other (Woldoff, Wiggins, & Washington, 2011). Recent research on rural colleges has identified characteristic trends justifying further investigation of effective interventions in their specific environmental context Rural institutions, most specially community and technical colleges, have been recognized as serving unique student sub populations (Gillet Karam, 1995). The micro social development and strong familial ties of rural students have been proven to negative ly impact their success (Aylesworth & Bloom, 1976; Downey, 1980; Peters,

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64 1990; and Schonert, Elliott, & Bills, 1991). The academic and social environment typical of rural high schools often yields graduates unprepared or underprepared for the increased aca demic rigor and less socially interactive collegiate environment (Schonert, Elliott, and Bills, 1991; Maltzan, 2006). Based upon factors impacting rural, minority students presented in the literature, t he following null hypotheses were presented: Hypothesi s 1: There are no differences in graduation and completion for minority students enrolled in rural, suburban, and urban institutions. Hypothesis 2: There is no difference in the impact of institutional characteristics, services, and learner support progra ms on graduation and completion of minority students enrolled in rural, suburban, and urban institutions. Hypothesis 3: There is no significant correlation between institution attributes and minority student success. Data Sources This study utilize d secondary institution level data available through the Integrated Postsecondary Education Data System (IPEDS) and U.S. Department of Education Office of Postsecondary Education. The sample is comprised of publicly funded institutions within the thirty Carn Assoc: S Doc/ED: Single doctorate (education) S Doc/Other: Single (Carnegie Foundation for the Advancement of Teaching, n.d.). Institutions falling into the five type s of Carnegie Clas sifications indicating dominance in doctoral programs, research, and professional degrees were excluded from the sample. In accordance with the Higher Education Act of 1965, all institutions of higher education participating in the federal student financi al aid programs must submit annual data pertaining to student enrollment, indicators of academic success, institutional characteristics, and financial aid (National Center for Education Statistics, 2012) IPEDS serves as the primary data collection tool fo r the National Center for Education

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65 Statistics. Analyses conducted for this study u tilized IPEDS ad hoc reporting tools and data sets for 2010 and 2011. Additional comparative data from the National Survey of Student Engagement (NSSE), the Career and T echnical Education Statistics (CTES), and the NCES Beginning Postsecondary Students and Baccalaureate and Beyond tables w as also utilized. This study seeks to develop a model of effective higher education practices for serving minority students in a r ural geographic context. The intent is not to provide empirical evidence of the impact of interventions at the student level, but rather a framework for which institution attributes correlate with higher levels of minority student success in the rural coll ege context. This study utilized secondary data pertaining to institution characteristics, performance, and aggregate outcomes for sub sets of their student populations. While these outcome data alone may not generate sufficient policy implications, the st evidence to support further, student level research. Dependent Variables Based upon the definition of academic success presented earlier, the following dependent variables w ere identified. 1. overall institution minority student enrollment percentage 2. overall institution minority student graduation rate 3. overall institution minority student completion headcount 4. black student enrollment percentage 5. black student graduation rate 6. black student completion headcount 7. Hispanic student enrollment percentage 8. Hispanic student graduation rate 9. Hispanic student completion headcount Minority enrollment is defined as the percentage of total enrollment comprised of the following racial/ethnic groupings: Am erican Indian/Alaskan Native, Asian/Native

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66 Hawaiian/Pacific Islander, Black non Hispanic, and Hispanic. White non Hispanic student enrollment was included in the denominator as part of the overall institution enrollment. Black student enrollment percentage and Hispanic student enrollment percentage are defined as those students self identifying in those two demographic classifications divided by overall institution enrollment. Graduation rate is defined as the total number of graduates completing within 150 % of the standard time divided by the adjusted cohort. The standard times for degree completion as defined by IPEDS are four years for a two year degree and six years for a four year degree (National Center for Education Statistics, 2012). Completion headc ount is defined as the number of students meeting requirements for completion of an educational credential, regardless of the amount of time to completion (National Center for Education Statistics, 2012). Table 3 1. Summary table of dependent variables De pendent Variables Data Source Variable Type Scale Range Minority Student Enrollment Percentage IPEDS Interval 0 100 Minority Student Graduation Rate IPEDS Interval 0 100 Minority Student Completion Headcount IPEDS Interval 0 100 Black Student Enrollment Percentage IPEDS Interval 0 100 Black Student Graduation Rate IPEDS Interval 0 100 Black Student Completion Headcount IPEDS Interval 0 100 Hispanic Student Enrollment Percentage IPEDS Interval 0 100 Hispanic Student Graduation Rate IPEDS Interval 0 100 Hispanic Student Completion Headcount IPEDS Interval 0 100 Independent Variables for Preliminary Analyses Independent variab les w ere comprised of a series of institutional characteristics. Data w as grouped by geographic context, with separate regression models developed for urban, suburban, and rural institutions. The independent variables within each m odel were as follows: HBCU designation, support services and special programs, minority faculty and staff, and targeted supplemental funding.

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67 Geographic Context This study evaluate d the relationship between institution geographic context and success of minority student populations in an effort to determine successful practices for supporting minority students in the rural college environment. As part of the annual IPEDS data collection process, institutions report their degree of urbanization by selecti ng one of twelve descriptors, including city (large, midsize, and small), suburb (large, midsize, and small), town (fringe, distant, and remote), and rural (fringe, distant, and remote). For purposes of this study, the three sub sets within each category w ere combined into three groupings. The three city categories w e re combined to form the he three town categories w ere s naturally align, as suburb categories refer to locations inside or immediately adjacent to an urbanized area and town categories refer to areas inside an urbanized cluster (National Center for Education Statistics, 2012) The three rural categories w ere and the surrounding areas with a population of 100,000 or more, suburban will designate urban clusters of 100,000 or more (not one municipality of 100,000 or more) and surrounding areas within thirty five miles, and urban will designate areas more than ten miles from a cluster or with a population of 50,000 or less (National Center for Educa tion Statistics, 2012) Separate regressions w ere established within e ach grouping. This separatio n was intended to generate correlational data regarding which interventions have the

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68 strongest relationship to improved minority student outcomes in that p articular geographic context. HBCU Tribal, and HSI Designation Institutions designated as a Historically Black College or University (HBCU) and Alaskan native or tribal colleges report th ese descriptor s as part of their institutional characteristics in IPEDS. Hispanic Serving Institution (HSI) designation is a calculated variable based upon the percentage of students classified as Hispanic. Literature indicates that minority students experience significantly higher success rates in the HBCU environment, even students presenting attributes typically associated with lower performance in higher education, such as lower high school G.P.A. and test scores, first time in college status, and low socio economic status (Rodgers & Summers, 2008) HBCU HSI, and tri bal institutions are also eligible for additional sources of federal funding, potentially providing them with a better network of resources to support at risk students. These designation s will be included as independent variable s given that minority stu dents attending HBCU HSI, and tribal institutions should experience significantly higher successful academic outcomes. HBCU HSI, and tribal institution status will be treated dichotomous binary variable s Support Services and Special Programs According to Pennington, Williams, and Karvonem (2006), rural institutions are more likely to serve a higher population of students that fall into multiple non traditional student classifications. The breadth of literature about improving success of nontraditional s tudents in higher education promotes creative, alternative support mechanisms. Rural college students are more likely to be FGIC, low SES, and challenged to balance work and family demands with the rigor of postsecondary

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69 academics. During the IPEDS data su bmission process, institutions are asked to indicate the presence of specific support services and special programs that exist on their campuses. The following variables from that IPEDS table has been identified as most relevant to the success of students in rural colleges, given that they address problems faced by this demographic in the literature: coop (work study) programs, distance learning programs, programs offered entirely via distance learning media, weekend/evening college, remedial services, acad emic/career counseling, employment services for students, placement services for completers, and on campus day care. Each of these attributes will be treated as a dichotomous binary variable. Minority Faculty and Staff The presence of minority faculty and staff has long been recognized as a key factor in success of minority college students. An ethnically diverse faculty helps students of color make connections to the college, increasing their engagement with the campus community (Guifridda & Douthit, 2010) Rural institutions are overwhelmingly predominantly white institutions (PWIs) that generally face challenges with hiring minority faculty. The IPEDS Human Resources table tracks full time and part time faculty (including tenure track status) and staff by gender, race, and ethnicity. Targeted Supplemental Funding In response to recognition that minority groups were performing at a significant disadvantage in higher education, a number of major federal funding streams have been designated to target programs and interventions specifically for those student groups. Often these funds are made available through national grant competitions; however, some are guaranteed supplements for certain institution types, such as tribal and Alaskan native colleges.

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70 Federal TRIO funding includes Student Support Services and MacNair grants to provide targeted support for low income, FGIC students. These grants can amount to over $400,000 annually (U.S. Department of Education Office of Postsecondary Education, 2012) T itle V funding for Hispanic Serving Institutions provides colleges with Table 3 2. Independent variables. Independent Variables Value MINORITY INSTITUTION HBCU HSI Alaskan, Native Hawaiian, or Tribal College 0 = No*, 1 = Yes 0 = No*, 1 = Yes 0 = No*, 1 = Yes SUPPORT SERVICES & SPECIAL PROGRAMS Distance Learning Programs 0 = Not Available*, 1 = Available Weekend/Evening College 0 = Not Available*, 1 = Available Remedial Services 0 = Not Available*, 1 = Available Academic/Career Counseling 0 = Not Available*, 1 = Available Employment Services for Students 0 = Not Available*, 1 = Available Placement Services for Completers 0 = Not Available*, 1 = Available On Campus Day Care 0 = Not Available*, 1 = Available MINORITY FACULTY & STAFF Continuous (Range, TBD) TARGETED FUNDING TRIO Funding 0 = No*, 1 = Yes Title V Funding 0 = No*, 1 = Yes Title III Funding 0 = No*, 1 = Yes *Denotes reference group Hispanic enrollment of 25% or more with the opportunity to compete for grants that range from $450,000 775,000. Funds are intended to provide institutions with the necessary resources to develop and implement programs to improve success of their Hispanic s tudents (U.S. Department of Education Office of Postsecondary Education, 2012) Title III funding provides an annual automatic allocation for tribal and Alaskan native colleges. Funds are designated for projects that strengthen the institution, but the colleges have autonomy to determine how funds will be spent (U.S. Department of Education Office of Instituti onal Service, 2012) Data on institution supplemental funding

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71 will be obtained from the U.S. Department of Education and added to the institution characteristics table as dichotomous variables. The geographic context variable is treated as a categorical va riable and used to split the population of institutions ( N = 1,861) into three sub groups. The population includes 561 urban institutions (30.10%), 750 suburban institutions (40.30%), and 550 rural institutions (29.60%). The variable for minority serving i nstitution has three sub serving institution status (HBCU, HSI, or Tribal College) as the reference group. Support services and special programs include coop/work study opportunities, distance le arning options, the ability to enroll entirely online, weekend and evening course options, remedial services, academic and career counseling, employment services, placement services, and the existence of on campus day care. All nine variables in this vecto with lack of that support service or program serving as the reference group. The overall faculty and staff considered to be classified as a racial o r ethnic minority. The numerator consists of all racial and ethnic minority faculty and staff members. The are included in this variable, given that both interact with the student body and both contribute to the overall campus climate. Targeted funding represents the existence of three special funding streams with substantial potential impact on non traditional student populations. The vector for targeted funding in cludes TRIO, Title III, and Title V with lack of funding as the reference category.

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72 Analytic Methods Preliminary analyses consisted of both basic statistical analyses proces ses and advanced multivariate analyses. Data will be divided into three primary comparison groups: rural, suburban, and urban institutions. Initial data analyses will be comprised of basic descriptive statistics and t tests for the population and each grou ping, one way analysis of variance (ANOVA) to measure variation within and between groups, and if between group variation is determined, a series of three post hoc tests with a Bonferroni Adjustment will be conducted to determine the nature of the variatio n. Chi Square Tests of Independence will be performed to determine if there is a relationship between geographic context and the existence of the list of support services. Analyses will be conducted to measure the relationships between these variables and each of the three geographic contexts. The Chi Square Tests of Independence will be utilized in addition to the multivariate approach, because it will allow the researcher to assess those relationships using nominal variables. Regression was used as the m ultivariate analyses methodology. Multiple regressions were utilized to evaluate the relationship of MSI status, special services and support programs and targeted supplemental funding on minority student enrollment, graduation (within 150% of the standar d time) and completion (with no time limit) Rural Colleges Suburban Colleges

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73 Urban Colleges Figure 3 1. Regression functions by geographic context The same set of three equations was replicated for minority enrollment, graduation, and completion at both suburban and urban institutions, resulting in a total of nine individual regression functions. Independent variables w ere blocked into five groups of rela ted factors: MSI status, Learner Support and Special Services, Minority Faculty and Staff, Targeted Funding, and Geographic Context represent the vector of coefficients in each of their respective variable blocks. Multiple regres sions were used to evaluate the relationship of MSI status, support and services, presence of minority faculty, targeted supplemental funding, and geographic context on minority student enrollment, graduation, and completion rates. In an effort to provi de the most meaningful data in development of an effective intervention model for rural minority students, the researcher also evaluate d linear regressions of each dependent variable on each primary independent variable individuall y as well as examine d th e regressions between the independent variables (McDonald, 2008) Rationale for analytic me thodology. For advanced multivariate analyses, the researcher u sed multiple regression analyses. This methodology w as selected because it allows the researcher to understand the functional relationships between multiple independent variables and each of the dependent variables. Multiple regression is recognized as a common social science analytic process in evaluating the impact of multiple, dichotomous, independent variables, treating each of the independent

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74 variables as an outcome predictor (Rossi, Lipsey, & Freeman, 2004) This approach has been chosen over other multivariate methodologies, because it is expected to produce the best data regarding functional relationships between the institutional attribute variables and minority student success. While mult iple regression can serve as a predictive tool (McDonald, 2008) that is not the intended use for this study. Multiple regression can also be useful as a form of selection modeling (selection bias control) (Mendoza, Villarreal, & Gunderson, 2014) ; however, because student level data is not tracked in these data sources, it w as not used in that manner. This study include s numerous dichotomous binary variables. The researcher is aware that u se of multiple dichotomous binary variables can potentially violate linear regression assumptions of normality and homoscedasticity (Pampel, 2000) ; and that utilizing linear regression with samples that violate the assumption of homoscedasticity has the potential to yield incorrect standard errors and tests of significance, increasing the likelihood of the researcher making a Type I error (Pampel, 2000) When dichotomous categorical dependent variables a re predicted by a l inear function of categorical and continuous variables, logistic regression is considered to be the appropriate quantitative methodology (McDonald, 2008 ; Long, 1997 ) Generally, logistic regression analysis is commonly utilized in quantitative research reg arding student persistent, retention, and graduation b ecause it generates predictive relationships between variables; h owever, it is not the appropriate methodological choice for this individual students, as cases. Therefore, the researcher has chosen multiple least squares

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75 regression, as it provides the most robust analytic approach appropriate for the types of included variables. Delimitations The population of institutions for this study will be limited to publicly funded but does not have a dominant doctoral or professional degree focus. Non public institutions are afforded a different degree of financial liberties than their publicly funded counterparts. They also have internal and external factors which impact the organization and its culture. In order to generate useful trend data, institutions will be limited by s public. Institutions with substantial research functions as is indicated by a dominant focus in the doctorate and professional degree fields are expected to have a different combination of resources and financial support at their disposal, which served a s the determining factor in limiting the institutions by degree offering and mission. The independent variables identified for use in the regression analyses are primarily limited to secondary data available through IPEDS. The researcher recognizes that additional variables not tracked by IPEDS are also relevant to the regression equation; however, the robust sample size and scope of institutions used for analyses will generate meaningful results and trend data sufficient to establish a foundation for fur ther research This study seeks to explore the potential relationship between institutional geographic context and minority student success rates. It is recognized in the literature that rural colleges may serve some unique student sub populations, and be cause of this, have a greater potential need for additional resources. The quasi experimental

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76 design of this study presents the possibility of garnering results subject to selection effect, however, selection modeling w as not utilized to c ontrol for th is. The researcher recognize s that there are factors impacting student choice of postsecondary institution, such as geographic location, cost of attendance, major programs of study, institutional prestige, selectivity of admissions processes, and pre collegiate exposure to and engagem ent with the college. Statistical controls for selection effect are not appropriate in the context of this study. Initial data analyses will be used to evaluate institution level data. Factors impacting student selection of postsecondary institution would need to be evaluated using student level data; and therefore would not fit with this approach. Data for this study are captured from IPEDS and the U.S. DOE, and neither database tracks student level data. A large sample for the study w as utilized to mi tiga te the impact of selection bias (Dooley 2001 ). IPEDS makes data available on all institutions receiving federal funding. This study will use data submitted on publicly funded colleges and universities ( N = 1,861 ). Analyses will compare publicly funded rural institutions ( n = 550 ) with non rural urban and suburban institutions ( n = 1,311 ). Potential Limitations of This Study IPEDS cohort data for graduation and completion involve students attending college during the economic crisis of 2008 2010. The research er recognizes that this external variable could positively or negative ly skew data resulting in a large r cohort effect than would normally be expected.

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77 CHAPTER 4 DATA ANALYSIS AND RESULTS This study evaluates the relationship between institution attributes and the academic success of minority students while controlling for institution geographic context. The independent variables include geographic context (rural, suburban, or urban), MSI s tatus (HBCU, HSI, or Tribal College), existence of support services and special programs, presence of minority faculty and staff, and targeted supplemental funding. The dependent variables are minority student enrollment, graduation rates, and completion r ates. These analyses were used to generate correlational data regarding a model of interventions that best support minority student success at rural serving institutions. This chapter begins with a discussion of the data, including preliminary and advance d multivariate analyses, followed by a discussion of the results. Preliminary analyses includes basic descriptive statistics and t tests, one way analysis of variance (ANOVA) to measure variation within and between groups, and Chi Square Tests of Independe nce to evaluate the relationship between geographic context and the existence of support services. Preliminary Analyses Preliminary analyses of the variables, including basic descriptive statistics, ANOVA, and Chi Square Tests of Independence are presented as a foundation for interpreting the more advanced regression analyses. The preliminary analyses section begins with a discussion of the frequency distribution of institutions by geographic context (urban, suburban, and rural), distribution of MSI colleg es and universities, and distribution of student enrollment. That is followed by a discussion of the descriptive

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78 analyses of the independent variables, ANOVA, and Chi Square Tests of Independence. Descriptive Statistics of Population A total of 1,861 inst itutions, representing a total student headcount of 16,831,099, were included in this study. Of those institutions, suburban institutions comprised the largest percentage of the population at 40.30% ( n =750), while rural institutions represented the smalles t group at 29.60% ( n =550). Suburban institutions comprised the remaining 30.10% ( n =561). The Integrated Postsecondary Education Data System (IPEDS) was used to evaluate the frequency of HBCU and tribal colleges among the population. Of those, 2.5% ( n =50) were classified as an HBCU ( Table 4 1). The fifty HBCU institutions included twenty nine urban institutions (58% of the overall HBCU population). With only 26% ( n =13) listed as suburban and 16% ( n =8) as rural, the HBCU institutions in this study fall m ost heavily within the urban geographic context. Table 4 1. Frequency of HBCU i nstitutions Institutions Frequency Percent Geographic Group Percent of Population Urban 29 5.3 1.5 Suburban 13 1.7 0.7 Rural 8 1.4 0.4 Total 50 2.6 Frequency data regarding the distribution of tribal colleges within this population was also investigated Among the 1,861 institutions in the population 1.30% ( n =25) is classified as a tribal college. Of those, 84.00% ( n =13) were rural colleges and 16.00% ( n =4) were sub urban colleges. No urban tribal colleges were included in the population.

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79 Table 4 2. Frequency of tribal colleges Frequency data regarding the distribution of Hispanic Serving Institutions was also investigated. The majority of HSIs were located in urban areas. Of the HSI population, 50.43% ( n =117) were classified as urban, 36.21% ( n =84) were classified as suburban, and 13.36% ( n =31) were classified as rural. Table 4 3. Frequency of HSIs Institutions Frequency Percent Geographic Group Percent of Population Urban 117 21.3 6.3 Suburban 84 11.2 4.5 Rural 31 5.5 1.6 Total 232 12.4 Distribution of Student Enrollment by Racial Groups Rural Institutions The distribution of student enrollment by racial groups was evaluated for each geographic group. The 550 rural institutions represented a total enrollment of 2,575,589 students, with an average institu tion headcount of 4,682.89. Minority students represented 37.15% ( n =956,733) of the total rural college student population. The average rural institution minority student enrollment was 28.27% ( n = 1,530). Rural tribal colleges, HBCU institutions, and Hispa nic Serving Institutions indicated the highest concentration of minority student enrollment. Of the 21 rural tribal colleges, 14 reported minority enrollment of 90.00% or higher. Institutions Frequency Percent Geographic Group Percent of Population Urban 0 0.0 0.0 Suburban 4 1.6 .5 Rural 21 1.4 1.1 Total 25 1.6

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80 Table 4 4. Rural college e nrollment distribution by racial grouping Racial Grouping Headcount Mean Headcount Percent of Total Population American Indian/Alaskan Native 55,909 101.65 2.17% Asian 69,077 125.59 2.68% Black 357,887 650.70 13.89% Hispanic 268,117 487.49 10.41% Native Hawaiian/Pacific Islander 7,813 14.21 0.29% Two or More Races 43,648 79.36 1.69% Unknown 134,394 244.35 5.22% White 1,618,856 2,943.37 62.85% Total Enrollment 2,575,589 4,682.89 100.00% Haskell Indian Nations University in Lawrence, Kansas, had the highest percentage of minority student enrollment (100%). Even Bay Mills Community College, which reported the lowest overall minority student enrollment (61.00%) of the rural tribal colleges, was still home to a significant minority student population. On average, the 21 tribal colleges hosted student populations with a minority enrollment rate of 88.15%. While those student populations were substantially comprised of Native American and Alaska n Native students, they did report serving students from a range of racial groups. Table 4 5. Rural minority serving institution enrollment distribution Institution Type Number Total Enrollment Mean Enrollment Mean Minority Enrollment Mean Percent Minori ty Enrollment Rural Tribal Colleges 21 17,047 811.76 734.95 88.15% Rural HBCUs 8 31,333 3,916.63 3,288.87 80.91% Rural HSIs 31 262,465 8,466.61 4,689.61 56.58% The rural institution population included eight HBCU institutions. Of those eight colleges and universities, Central State University located in Wilberforce, Ohio, reported the highest overall minority student enrollment (97.00%). Bluefield State College, located in Bluefield, West Virginia is the only rural HBCU to report low minority student

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81 83.76% white student enrollment indicates the current campus culture and st udent body composition are more representative of a predominantly white institution. On average, the rural HBCUs have larger student enrollment ( = 3,91 7 ) and are more racially diverse. There were thirty one HSIs included in the rural institution populatio n. Of those institutions, Texas A & M International University reported the highest concentration of minority students (94.00%) and the highest concentration of Hispanic students (92.00%). Clovis Community College in Clovis, New Mexico, reported the lowest concentration of minority students within the HSI classification (36.00%) with a total Hispanic population of 25.18%. Suburban Institutions The 750 suburban institutions represented a total enrollment of 6,032,310 students, with an average institution he adcount of 8,043.08.The total suburban college student population is 41.23% minority ( n = 2,487,136). On average, the suburban institution student populations were 28.42% minority ( n =2,716). Table 4 6. Suburban college enrollment distribution by racial grou ping Racial Grouping Headcount Mean Headcount Percent of Total Population American Indian/Alaskan Native 56,896 75.86 0.94% Asian 266,459 355.28 4.42% Black 771,353 1,028.47 12.79% Hispanic 793,160 1,057.55 13.15% Native Hawaiian/Pacific Islander 24,924 33.23 0.41% Two or More Races 124,423 165.90 2.06% Unknown 347,003 462.67 5.75% White 3,545,174 4,726.90 58.77% Total Enrollment 6,032,310 8,043.08

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82 The suburban college sub group ( n =750) included the lowest number of both tribal colleges and HBCUs, but the largest number of HSIs of the three geographic contexts. Of the four suburban tribal colleges, Southwestern Indian Polytechnic Institute in Albuquerque, New Mexico, reported the hi ghest overall percentage of minority student enrollment at 100.00%. In stark contrast, Fond du lac Tribal and Community College in Cloquet, Minnesota, while technically meeting the definition of a tribal college, reported a minority student enrollment rate of only 21.00%. The suburban sub group included thirteen HBCUs. Denmark Technical College in Denmark, South Carolina, reported the largest minority student enrollment at 96%. In contrast, West Virginia State University in Dunbar, West Virginia, reported a mere 16% minority student enrollment. Table 4 7. Suburban minority serving institution enrollment distribution Institution Type N Total Enrollment Mean Enrollment Mean Minority Enrollment Mean Percent Minority Enrollment Suburban Tribal Colleges 4 4,487 1,121.75 524.75 73.77% Suburban HBCUs 13 56,174 4,321.08 3,480.23 78.53% Suburban HSIs 84 1,092,708 13,008.43 7,867.25 60.19% HSIs comprised the largest family of minority serving institutions in the suburban sub group. Of the eighty six suburban HSIs, San Diego State University Imperial Valley Campus reported the highest minority enrollment at 86.3%. South Plains College in Leve lland, Texas reported the lowest overall minority enrollment at 32.00%. Urban Institutions The urban college sub group ( n =561) represented a total enrollment of 10,825,683 with an average institution headcount of 16,994.79. The total urban college

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83 student population is 48.78% minority ( n =5,280,364). On average, the urban institution student populations were 39.52% minority ( n =6,808). Table 4 8. Urban institution enrollment distribution Racial Grouping Headcount Mean Headcount Percent of Total Population American Indian/Alaskan Native 58,815 104.84 0.68% Asian 533,398 950.80 6.89% Black 1,279,620 2,280.96 13.73% Hispanic 1,517,109 2,704.29 16.44% Native Hawaiian/Pacific Islander 25,702 45.81 0.29% Two or More Races 163,339 7,093.80 2.03% Unknown 468,414 291.16 5.17% White 3,979,624 834.96 51.22% Total Enrollment 8,223,200 14,658.11 The urban sub group included no tribal colleges, but it did encompass the largest concentration of both HBCU ( n =28) and HSI colleges ( n =119). It also included the only double MSI institutions with two HBCU institutions Amarillo College and East Valley Institute of Technology also reporting a large enough Hispanic student enrollment to meet HSI status. Table 4 9. Urban college minorit y serving institution enrollment distribution Institution Type N Total Enrollment Mean Enrollment Mean Minority Enrollment Mean Percent Minority Enrollment Urban HBCUs 29 276,722 9,542.14 6,275.86 72.50% Urban HSIs 117 2,478,724 21,185.68 14,006.61 66.06% Graduation Rates Graduation is defined as completion of the degree or credential within 150% of the standard time. 94 .00 % of the colleges and universities (n=1,753) reported graduation data. Overall, suburban institutions reported the largest aggregate graduation rate at 40.71%, urban institutions reported the lowest at 31.70%. Composite minority graduation rates lagged behind overall graduation rates and non minorit y

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84 graduation rates in suburban and rural institutions. Rural institutions reported the lowest overall minority student graduation rate at 26.57%. Black students represented the demographic with the lowest graduation rate across all three geographic context s. In contrast, institutions across all three contexts reported graduation rates for Asian students to be equivalent to or slightly higher than non minority students. Table 4 10. Distribution of graduation rates by racial groupings across geographic conte xt Geographic Region White Students Black Students Hispanic Students Asian Students Total Minority Urban 31.89% 21.72% 27.02% 32.72% 31.00% Suburban 36.33% 19.37% 30.54% 35.23% 27.88% Rural 32.60% 20.86% 27.67% 32.67% 26.57% Completion Data 99.78% ( n =1,857) of the institutions reported completion data. In contrast to the enrollment and graduation dat a which was presented as percentages, completion data is calculated in headcount. This difference is due to the fact that completion is not time limited, and therefore, not calculated using a cohort format Students are counted as completers when all graduation requirements are met and the credential is conferred, regardless of the length of time. In comparison, the graduation statistic refers to the perce ntage of that group completing the degree requirements within an allotted timeframe. White students comprised the majority of completers across all geographic contexts. Hispanic students accounted for the smallest percentage of the minority completers ( Table 4 11). Table 4 11. Mean completers by racial category for each geographic context Geographic Region Total Comp White Comp Black Comp Hispanic Comp Asian Comp Minority Comp Urban 1,848 1,05 6 22 9 5 11 7 38 6 Suburban 940 630 94 3 3 6 15 4 Rural 523 37 1 6 3 1 10 89

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85 Support Services and Special Programs All of the support services and special programs were present in the rural colleges sub group. The service with the largest representation was Academic and Career Counseling, which was reported by 97.70% ( n =543) of the rural colleges. On Campus Day Care was the most infrequently reported service, with only 35.80% ( n =199) of the colleges indicating they offered that program for students. In comparison to the suburban and urban colleges, r ural colleges reported a lower frequency for each support service, with the exception of remedial services. 93.90% ( n =522) of the rural colleges indicated that they offered remedial services, as compared to 89.10% ( n =668) of suburban colleges and 85.40% ( n = 479) of urban colleges Table 4 12. Frequency of support services and special programs in rural colleges Independent Variables Frequency Percent of Rural Colleges Distance Learning Programs 411 74.70% Weekend/Evening College 235 42.70% Remedial Services 517 94.00% Academic/Career Counseling 537 97.60% Employment Services for Students 449 81.60% Placement Services for Completers 449 81.60% On Campus Day Care 193 35.10% Suburban colleges also reported all of the support services. The most frequently reported services was Academic and Career Counseling at 98.50% ( n =739), while the least frequently reported services was On Campus Day Care at 40.10% ( n =301). Table 4 13. Frequency of support services and special programs in suburban colleges In dependent Variables Frequency Percent of Suburban Colleges Distance Learning Programs 587 78.30% Weekend/Evening College 330 44.00% Remedial Services 668 89.10% Academic/Career Counseling 739 98.50% Employment Services for Students 637 84.90% Placement Services for Completers 606 80.80% On Campus Day Care 301 40.10%

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86 In a pattern similar to rural and suburban colleges, urban colleges as reported all support services, with Academic and Career Counseling having the highest frequency at 99.30% ( n =557). Urban colleges were the only sub group to report the option of Weekend and Evening College as their most infrequent service at 54.70% ( n =307). Urban colleges also reported the highest rate of On Campus Day Care at 57.80%. Table 4 14. Frequency of support services and special programs in urban colleges Independent Variables Frequency Percent of Urban Colleges Distance Learning Programs 492 87.70% Weekend/Evening College 307 54.70% Remedial Services 479 85.40% Academic/Career Counseling 557 99.30% Employment Services for Students 507 90.40% Placement Services for Completers 483 86.10% On Campus Day Care 324 57.80% Minority Faculty and Staff Of the 1,861 institutions at total of 1,484 reported faculty data for 2011. Urban colleges reported the highest average percentage of minority faculty at 25.78% ( n =44,708). Rural colleges reported the lowest mean percent of minority faculty at 11.49% ( n =6,157). Suburban colleges reported and mean percent of minority faculty at 17.01% ( n =20,766) Table 4 15. Distribution of faculty by geographic region Geographic Region Total Faculty Minority Faculty Percent Minority Faculty Mean Percent Minority Faculty Urban 169,781 44,708 26.32% 25.78% Suburban 110,047 20,766 18.87% 17.01% Rural 36,560 6,157 16.84% 11.49% Targeted Funding 796 grant programs were funded among the 1,861 institutions included in the sample. Grant programs fell most heavily within the rural group of institutions; however,

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87 given that they are designed to target at risk populations and high need institutions, thi s distribution is as expected. Table 4 16. Targeted funding by geographic context Geographic Context Title III Funding Title V Funding TRIO Student Support Services Total Awards Percent of Group Urban 19 14 172 205 36.54% Suburban 23 32 250 305 40.67% Rural 33 49 204 286 52.00% Analysis of Variance (ANOVA) Analysis of Variance (ANOVA) was used to determine if a relationship exists between geographic context and graduation rates. The ANOVA models were specifically used to evaluate whether or not variation in overall graduation rate and minority student gradua tion rate were statistically significant across the three geographic contexts. Overall Graduation Rate The first ANOVA model evaluated the relationship between overall institution graduation rate and geographic context (urban, suburban, and rural). Analys is of index score variation between the three geographic context groups suggested that the relationship between institution geographic context and overall graduation rate is statistically significant ( F =23.108; p Table 4 1 7 One way ANOVA of mean differences in graduation rate by geographic context Sum of Squares df Mean Square F Sig Between Groups 26093.352 2 13046.676 23.108 .000*** Within Groups 1001029.850 1773 564.597 Total 1027123.202 1775 *** p

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88 In order to determine the nature of the relationship between geographic context and overall graduation rate, a series of post hoc comparisons were conducted. A Bonferroni Adjustment was used to keep the family wise error rate at .05. All three between grou p comparisons were evaluated: urban and suburban, urban and rural, and suburban and rural. Table 4 1 8 Post hoc tests using Bonferroni Adjustment for mean differences in graduation rate by geographic context *** p Through the series of pairwise comparisons, significant differences in mean graduation rate were found to exist between both urban and rural and suburban and rural institutions. Results of the ANOVA indicate that rural institutions have a significantly low found between urban and suburban institutions. Minority Graduation Rate The second ANOVA mode l evaluated the relationship between minority student graduation rate and geographic context (urban, suburban, and rural). Analysis of index score variation between the three geographic context groups suggested that the relationship between institution geo graphic context and overall graduation rate is statistically significant ( F =35.976; p (I) Geo_Context (J) Geo_Context Mean Difference (I J) Std. Error Sig. U rban Suburban 1.694 1.355 .635 Rural 7.314 1.465 .000 *** Suburban U rban 1.694 1.355 .635 Rural 9.008 1.367 .000 *** Rural U rban 7.314 1.465 .000 *** Suburban 9.008 1.367 .000 ***

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89 Table 4 1 9 One way ANOVA of mean differences in minority student graduation rate by geographic context Sum of Squares df Mean Square F Sig Between Groups 24935.186 2 12467.593 35.976 .000*** Within Groups 561069.805 1619 346.553 Total 586004.991 1621 *** p In order to determine the nature of the relationship between geographic context and minority graduation rate, a second series of post hoc comparisons were conducted. Table 4 20 Post hoc tests using Bonferroni Adjustment for mean differences in graduation rate by geographic context *** p The same Bonferroni Adjustment was used to keep the family wise error rate at .05. All three between group comparisons were evaluated: urban and suburban, urban and rural, and suburban and rural. Through the series of pairwise comparisons, significant differences in mean graduation rate were found to exist between both the suburban and urban and suburban and rural institutions. Results of the ANOVA indicate that suburban institutions have a significantly higher minority graduation rate than both urban institutions (9.359, p and rural institutions (5.789, p ifference in minority student graduation rate was found between rural and urban institutions. (I) Geo_Context (J) Geo_Context Mean Difference (I J) Std. Error Sig. U rban Suburban 9.359 1.145 .000 *** Rural 3.570 1.232 .011 Suburban U rban 9.359 1.145 .000 *** Rural 5.789 1.092 .000 *** Rural U rban 3.570 1.232 .011 Suburban 5.789 1.092 .000 ***

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90 Minority Completers The fourth ANOVA model evaluated the relationship between minority student completion numbers and geographic context (urban, suburban, and ru ral). Analysis of index score variation between the three geographic context groups suggested that the relationship between institution geographic context and minority student completion numbers is statistically significant ( F =136.534; p Table 4 2 1 One way ANOVA of mean differences in minority completers by geographic context Sum of Squares df Mean Square F Sig. Between Groups 27623240.762 2 13811620.381 136.534 .000 *** Within Groups 187953221.696 1858 101158.892 Total 215576462.458 1860 *** p In order to determine the nature of the relationship between geographic context and minority completion numbers, a fourth series of post hoc comparisons were conducted. The same Bonferroni Adjustment was used to keep the family wise error rate at .05. All three between group comparisons were evaluated: urban and suburban, urban and rural, and suburban and rural. Table 4 2 2 Post hoc tests usin g Bonferroni Adjustment for mean differences in completers by geographic context (I) Geo_Context (J) Geo_ Context Mean Difference (I J) Std. Error Sig. 95% Confidence Interval Lower Bound Upper Bound Rural Suburban 64.60861 17.85508 .001 ** 107.3920 21.8252 Urban 296.32642 19.08518 .000 *** 342.0574 250.5955 Suburban Rural 64.60861 17.85508 .001 ** 21.8252 107.3920 Urban 231.71781 17.75380 .000 *** 274.2586 189.1770 Urban Rural 296.32642 19.08518 .000 *** 250.5955 342.0574 Suburban 231.71781 17.75380 .000 *** 189.1770 274.2586 *. The mean difference is significant at the 0.05 level. ** p p

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91 Pearson Chi Square Test of Independence A Pearson Chi Square Test of Independence was utilized to evaluate the potential relationship between geographic context and the seven institutional support services. The Pearson Chi Square test allows for comparison of categorical variables. Table 4 2 3 Chi Square analysis of geographic context and support services *p p p Significant differences in the existence of support services were found across the three geographic contexts. Rural institutions demonstrated a significantly lower rate of distance learning programs, weekend and evening courses, and remedial services. Urba n institutions demonstrated a significantly lower rate of employment services, placement services, and on campus day care. Suburban institutions demonstrated a significantly higher rate of all support services with the exception of on campus day care. Rura l institutions had a significantly higher rate of on campus day care services. Linear Regression Regression served as the multivariate analyses methodology. Multiple regressions were interpreted to evaluate the relationship of MSI status, special services and support programs and targeted supplemental funding on minority student enrollment, graduation (within 150% of standard time) and completion (with no time limits) The same set of three equations will be replicated for minority enrollment, Value df Sig. Distance Learning Programs 34.989 4 .000*** Weekend/Evening College 22.793 4 .000*** Remedial Services 23.610 4 .000*** Academic/Career Counseling 8.799 4 .066 Employment Services for Students 20.702 4 .000*** Placement Services for Completers 9.570 4 .048* On Campus Day Care 68.191 4 .000***

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92 graduation, and completion at both suburban and urban institutions, resulting in a total of nine individual regression functions as follows: Rural College Regression Functions Suburban College Regression Functions Urban College Regression Functions Figure 4 1. Regression functions Independent variables were blocked into four groups of related factors: MSI status, Learner Support and Special Services, Minority Faculty and Staff, and Targeted Funding represent the vector of coefficients in each of their respective variable blocks. Multiple regressions will be used to e valuate the relationship of MSI status, support and services, presence of minority faculty, and targeted supplemental funding for minority student enrollment, graduation, and completion rates within each geographic context. In an effort to provide the most meaningful data in development of an effective intervention model for rural minority students, the researcher will also evaluate linear regressions of each dependent variable on each primary independent variable individuall y (minority enrollment, minority graduation rate, minority completion numbers ), as well as examine the regressions between the independent variables (McDonald, 2008)

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93 Results of Linear Regression Functions Linear regressions for each variable block were evaluated to determine their appropriateness for inclusion in the multivariate model. All for blocks of predictor variables were found to have a significant relationship. The strongest relationship presented was for campus services with an R Square value of .389, indicating that it accounted for 38.9% of the variance in the model. When evaluating the relationship between the four blocks of predictor variables and student graduation without controlling for geo graphic context, MSI status (HBCU, HSI, and tribal colleges), the presence of placement services for graduates, and targeted supplemental funding (SSS, Title III, and Title V) were all found to be significant predictors of higher overall graduation rates. The percentage of minority faculty was found to have a negative relationship to overall institution graduation rates, indicating that with each percentage point increase in minority faculty, the graduation rate decreases. The presence of distance education weekend and evening courses, remedial services, employment services, and child day care all presented significant negative relationships, indicating that institutions offering those services had lower graduation rates. HSI status was also found to correl ate to higher graduation rates for black and Hispanic student populations as was the presence of placement services for graduates. In contrast to the negative relationship found between the percentage of minority faculty and overall graduation rates, a sig nificant, positive relationship was found between the percentage of minority faculty and Hispanic student graduation rates. While the percentage of minority faculty did not present a relationship to black student graduation patterns, a significant relation ship was found between the percentage of black faculty

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94 and black student graduation rates. All three targeted funding programs were found to have a significant, positive relationship to black student graduation rates, while only the SSS grant program and T itle V funding presented a relationship to increased rates of Hispanic student graduation. Appendix B presents a summary table of the predictor variables and their relationship to graduation rates. Multiple Linear Regression Functions by Geographic Contex t Multiple linear regression functions were established for each of the following independent variables: student enrollment percentages (overall minority, black, and Hispanic), graduation rates (overall minority, black, and Hispanic), and completion headc ount (overall minority, black, and Hispanic). Rural Colleges Minority student enrollment, graduation, and completion patterns in rural institutions. Within the rural institutions, the regression function for minority student enrollment indicates that at a p value of p serving institution status (HBCU, tribal, and Hispanic Serving Institution) and the presence of minority faculty are significant predictors of minority student enrollment. Of the fourteen predictor variables, three were found to have a p v alue of less than .001 ( Table 4 24 ). All three MSI classifications as well as the presence of minority faculty were indicated as having a significant relationship to minority student enrollment. Minority serving institution status was found t o have an overall negative relationship to minority student enrollment. Specifically, rural tribal institutions had minority student enrollment lower than peer institutions ( = .318, p ), and HSIs had lower enrollment ( = .203, p ). In contra st, the percentage of minority faculty

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95 Table 4 24. Rural institution variables regressed for minority student enrollment p was found to have a significant positive relationship. As the percentage of minority faculty increased, overall minority student enrollment increased ( = .574, p ). Table 4 25 Results of regression function for minority enrollment in rural institutions Model Unstandardized Coefficients Standardized Coefficients t Sig. Std. Error H bcu .077 .064 .040 1.195 .232 T ribal .318 .043 .262 7.311 .000 *** HSI_Status .205 .036 .203 5.631 .000 *** Undergrad_Distance .028 .018 .052 1.525 .128 Weekend_Eve .001 .014 .002 .065 .948 Remedial .046 .031 .047 1.470 .142 Academic_Career .025 .049 .016 .502 .616 Emplyment_Svc .005 .019 .008 .252 .801 Placement_Svc .010 .019 .016 .519 .604 Day_Care .024 .014 .049 1.681 .093 Percent_Min_Faculty .848 .061 .574 13.849 .000 *** SSS_Grant .019 .015 .038 1.278 .202 Title_III_Grant .007 .035 .006 .205 .838 Title_V_Grant .060 .052 .041 1.164 .245 (Constant) 1.197 .230 5.195 .000 *** *** p Model R R Square Adjusted R Square Std. Error of the Estimate Change Statistics R Square Change F Change df 1 df 2 Sig. F Change MSI .675 .456 .453 .17266 .456 151.698 3 544 .000 *** Services .681 .464 .454 .17249 .008 1.155 7 537 .327 Faculty .778 .605 .597 .14822 .141 191.263 1 536 .000 *** Funding .779 .607 .597 .14818 .002 1.109 3 533 .345

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96 The variable blocks for MSI status, campus services, and percent of minority faculty were all found to have a significant relationship to rural minority student graduation ( Table 4 26 ). Table 4 26 Rural institution variables regressed for minority studen t graduation Model R R Square Adjusted R Square Std. Error of the Estimate Change Statistics R Square Change F Change df 1 df 2 Sig. F Change MSI .210 .044 .037 13.709 .044 6.431 3 419 .000 *** Services .327 .107 .085 13.365 .063 4.125 7 412 .000 *** Faculty .359 .129 .105 13.214 .022 10.457 1 411 .001 ** Funding .370 .137 .107 13.203 .008 1.233 3 408 .297 p Table 4 27 Results of regression function for minority graduation at rural institutions Model Unstandardized Coefficients Standardized Coefficients t Sig. Std. Error (Constant) 53.247 24.788 2.148 .032 ** H bcu 5.549 5.880 .054 .944 .346 T ribal 6.311 4.293 .094 1.470 .142 HSI_Status .073 3.568 .001 .020 .984 Undergrad_Distance .612 2.316 .014 .264 .792 Weekend_Eve 2.347 1.327 .084 1.769 .078 Remedial 20.690 4.788 .202 4.321 .000 *** Academic_Career 7.648 13.738 .027 .557 .578 Emplyment_Svc 3.719 2.173 .086 1.712 .088 Placement_Svc 2.488 2.000 .065 1.244 .214 Day_Care 1.423 1.378 .050 1.032 .303 Percent_Min_Faculty 20.349 5.876 .237 3.463 .001 ** SSS_Grant .066 1.374 .002 .048 .962 Title_III_Grant 4.571 3.241 .066 1.410 .159 Title_V_Grant 6.260 4.765 .080 1.314 .190 p When evaluated individually, none of the predictor variables correlated to a significant positive relationship to rural minority student graduation rates. The presence

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97 of remedial services ( = .202, p ) and the percentage of minority faculty ( = .237, p ) presented a significant negative relationship to rural minority graduation rates. This indicates that institutions offering remedial services are more likely to have lower minority graduation rates. The negative relationship presented fo r minority faculty indicates that as the percent of minority faculty increases, the rural minority student graduation rate dec reases. The same three variable blocks were found to be significant to rural minority completions (T able 4 28 ). Table 4 28 Rural institutions variables regressed for minority student completion Model R R Square Adjusted R Square Std. Error of the Estimate Change Statistics R Square Change F Change df1 df2 Sig. F Change MSI .220 .048 .043 150.64142 .048 9.227 3 544 .000 *** Services .343 .118 .101 146.01197 .069 6.006 7 537 .000 *** Faculty .413 .170 .153 141.71228 .053 34.081 1 536 .000 *** Funding .420 .176 .155 141.58496 .006 1.321 3 533 .267 p While there were no variables indicating a positive relationship to increased levels of minority graduates, five variables were found to have a significant relationship with minority completers. Tribal institutions had a significant, positive relationship ( =.167, .01). Undergraduate distance education ( =.112, .05), weekend and evening course options ( =.084, .05), and placement services for graduates ( =.096, .05) were all found to have a significant relationship to higher numbers of minority completers in rural institutions. The percentage of minority faculty present had the strongest relationship to increased minority completers ( =.356, .001).

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98 Table 4 29 Results of regression function for minority completers in rural institutions Model Unstandardized Coefficients Standardized Coefficients t Sig. Std. Error (Constant) 444.741 220.179 2.020 .044 H bcu 46.596 61.507 .036 .758 .449 T ribal 133.720 41.528 .167 3.220 .001 ** HSI_Status 29.755 34.798 .045 .855 .393 Undergrad_Distance 39.746 17.469 .112 2.275 .023 Weekend_Eve 26.122 13.126 .084 1.990 .047 Remedial 27.459 29.683 .042 .925 .355 Academic_Career 2.930 46.978 .003 .062 .950 Emplyment_Svc .907 18.076 .002 .050 .960 Placement_Svc 38.141 17.890 .096 2.132 .033 ** Day_Care 5.614 13.627 .017 .412 .681 Percent_Min_Faculty 347.483 58.515 .356 5.938 .000 *** SSS_Grant 6.127 14.245 .018 .430 .667 Title_III_Grant 28.716 33.754 .034 .851 .395 Title_V_Grant 88.260 49.338 .091 1.789 .074 p There is a distinct difference in the relationship these variables present between graduation and completion. These findings indicate that they do promote higher levels of student success, just not within the traditional graduation timeframes. Black stude nt enrollment, graduation, and completion patterns in rural institutions. The regression function for black student enrollment indicates that at a p value of p serving institution status, presence of minority faculty, and some support services with blac k student enrollment rates ( Table 4 30 ). Analysis of the enrollment predictors indicated five variables with a significant relationship to enrollment patterns. Rural black student enrollment increas ed with flexible course scheduling and percentage of minority faculty ( Table 4 31 ). Rural

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99 Table 4 30 Rural institution variables regressed for black student enrollment ***p black student enrollment increased with each percentage point increase in minority faculty ( =.342, .001), if the institution offered weekend or evening courses ( =.155, p ), and if distance education options were available ( =.099, p .05) ( Table 4 31 ). In terms of preference for MSI colleges and universities, rural black Table 4 31 : Results of regression function for rural institution Black student enrollment Model Unstandardized Coefficients Standardized Coefficients T Sig. Std. Error (Constant) 4466.246 1892.804 2.360 .019 hbcu 627.547 528.754 .056 1.187 .236 tribal 1606.789 357.005 .229 4.501 .000 *** HSI_Status 700.908 299.150 .120 2.343 .019 Undergrad_Distance 305.291 150.171 .099 2.033 .043 Weekend_Eve 422.602 112.842 .155 3.745 .000 *** Remedial 191.632 255.178 .034 .751 .453 Academic_Career 303.610 403.852 .034 .752 .453 Emplyment_Svc 41.131 155.390 .012 .265 .791 Placement_Svc 201.103 153.790 .058 1.308 .192 Day_Care 45.376 117.145 .016 .387 .699 Percent_Min_Faculty 2921.823 503.035 .342 5.808 .000 *** SSS_Grant 110.343 122.461 .038 .901 .368 Title_III_Grant 169.656 290.169 .023 .585 .559 Title_V_Grant 452.485 424.142 .053 1.067 .287 p **p ***p Model R R Square Adjusted R Square Std. Error of the Estimate Change Statistics R Square Change F Change df1 df2 Sig. F Change MSI .251 .063 .058 1308.119 .063 12.222 3 544 .000 *** Services .390 .152 .137 1252.305 .089 8.082 7 537 .000 *** Faculty .450 .202 .186 1216.084 .050 33.466 1 536 .000 *** Funding .453 .205 .184 1217.158 .003 .685 3 533 .562

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100 students were more likely to enroll in a tribal institution ( =.229, p ) and to attend an HSI ( =.120, p .05 ) Table 4 32 Rural institution variables regressed for black student graduation Model R R Square Adjusted R Square Std. Error of the Estimate Change Statistics R Square Change F Change df 1 df 2 Sig. F Change MSI .105 .011 .003 21.653 .011 1.438 3 388 .231 Services .460 .211 .190 19.515 .200 13.814 7 381 .000 *** Faculty .464 .216 .193 19.486 .004 2.134 1 380 .145 Funding .475 .226 .197 19.436 .010 1.646 3 377 .178 p **p ***p Rural black student enrollment increased with each percentage point increase in minority faculty ( =.342, .001), if the institution offered weekend or evening courses ( =.155, p ), and if distance education options were available ( =.099, p .05) ( Table 4 32). In terms of preference for MSI colleges and universities, rural black students were more likely to enroll in a tribal institution ( =.22 9, p ) and to attend an HSI ( =.120, p .05 ) Services offered by rural institutions were found to have a significant relationship to black s tudent graduat ion patterns ( Table 4 33). Of the five campus services found to be significant to black student graduation patterns, only placement services for completers was indicated to have a positive relationship ( =.128, p .01 ) Undergraduate distance education ( = .263, p .001), weekend and evening classes ( = .140, p .01 ) remedial services ( = 134, p .01 ) and academic and career counseling ( = .182, p .01 ) were all found to have a negative relationship to rural black student enrollment. These findings indicate that when evaluated in comparison to the other variables in the equation, the presenc e of flexible course scheduling options,

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101 remedial services, and academic and career counseling correlate to lower black student graduation rates. Table 4 33 Results of regression function for black student graduation in rural institutions Model Unstandardized Coefficients Standardized Coefficients t Sig. Std. Error (Constant) 178.738 38.149 4.685 .000 *** Hbcu 13.723 8.929 .090 1.537 .125 Tribal 8.157 10.696 .042 .763 .446 HSI_Status 3.121 5.288 .036 .590 .555 Undergrad_Distance 23.318 4.351 .263 5.359 .000 *** Weekend_Eve 6.059 2.023 .140 2.995 .003 ** Remedial 20.468 7.122 .134 2.874 .004 ** Academic_Career 78.348 21.818 .182 3.591 .000 *** Emplyment_Svc 4.390 3.521 .063 1.247 .213 Placement_Svc 7.695 2.928 .128 2.628 .009 ** Day_Care 1.260 2.097 .029 .601 .548 Percent_Min_Faculty 14.570 9.412 .098 1.548 .122 SSS_Grant 3.607 2.070 .082 1.743 .082 Title_III_Grant 5.858 4.662 .058 1.256 .210 Title_V_Grant 1.300 7.158 .011 .182 .856 p **p ***p While only campus services were found to be significant to rural black student graduation, MSI status, services, and the percentage of minority faculty were found to be significant for the number of rural black student completers ( Table 4 34 ). Table 4 3 4 Rural institution variables regressed for black student completion Model R R Square Adjusted R Square Std. Error of the Estimate Change Statistics R Square Change F Change df 1 df 2 Sig. F Change MSI .272 .074 .069 135.729 .074 14.462 3 544 .000 *** Services .362 .131 .115 132.341 .057 5.030 7 537 .000 *** Faculty .410 .169 .151 129.563 .038 24.271 1 536 .000 *** Funding .415 .172 .150 129.664 .003 .724 3 533 .538 p **p ***p

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102 Six of the fourteen predictor variables were indicated to have a significant relationship to black student completers in rural institutions. For the MSI status block, HBCUs were found to have a negative relationship ( = .101, p .05 ) while tribal institutions were found to have a positive relationship ( =.18 4, p .001 ) This indicates that black students attending a tribal institution are more likely to complete their degree than those attending an HBCU. Three of the campus services demonstrated a significant positive relationship. Rural institutions offering undergraduate distance education options ( = .100 p .05 ) weekend and evening course options (* = .101 p .05 ) and placement services for completers ( =.101, p .05 ) had significantly higher numbers of black completers. The most significant positive relationship was found for Table 4 35 Results of regression function for black completers in rural institutions Model Unstandardized Coefficients Standardized Coefficients t Sig. Std. Error (Constant) 290.990 201.640 1.443 .150 Hbcu 118.085 56.328 .101 2.096 .037 tribal 134.563 38.032 .184 3.538 .000 *** HSI_Status 57.771 31.868 .095 1.813 .070 Undergrad_Distance 32.332 15.998 .100 2.021 .044 Weekend_Eve 28.823 12.021 .101 2.398 .017 Remedial 14.872 27.184 .025 .547 .585 Academic_Career .407 43.022 .000 .009 .992 Emplyment_Svc 7.952 16.554 .022 .480 .631 Placement_Svc 36.628 16.383 .101 2.236 .026 Day_Care 17.362 12.479 .059 1.391 .165 Percent_Min_Faculty 266.009 53.588 .299 4.964 .000 *** SSS_Grant 7.166 13.046 .024 .549 .583 Title_III_Grant 23.367 30.912 .030 .756 .450 Title_V_Grant 54.535 45.184 .061 1.207 .228 p **p ***p

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103 the percentage of minority faculty ( =.299, p .001 ) This indicates that the strongest predictor of rural black student completion is the percentage of minority faculty. Hispanic student enrollment, graduation, and completion patterns in rural institutions. The regression function for rural Hispanic student enrollment indicated that at a p value of p serving institution status and percent of minority faculty were significant predictors ( Table 4 36 ). Analysis of rural Hispanic student enrollment indicated five variables with a significant relationship to enrollment patterns. The strongest predictor was presence of minority faculty. Rural Hispanic student enrollment increased with each percentage increase in minority faculty ( =.178, p .001). Surprisingly, rural Hispanic student Table 4 36 Rural institution variables regressed for Hispanic student enrollment Model R R Square Adjusted R Square Std. Error of the Estimate Change Statistics R Square Change F Change df 1 df 2 Sig. F Change MSI .623 .389 .386 4397.343 .389 156.755 2 493 .000 *** Services .631 .399 .388 4392.750 .010 1.147 7 486 .332 Faculty .644 .415 .403 4336.705 .016 13.643 1 485 .000 *** Funding .659 .435 .419 4276.561 .020 5.579 3 482 .001 ** ** p p enrollment patterns indicated a positive relationship to HBCU institutions ( =.130, p .01), yet a negative relationship was found for HSIs ( = .521, p .001), which indicates that rural Hispanic students are more likely to enroll at an HBCU than at an HSI. In the targeted funding block, presence of a Student Support Services grant ( = .106, p .01) and presence of a Title III grant ( = .083, p .05) were found to have a negative relationship to Hispanic student enrollment in rural institutions. This res ult

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104 indicates that the presence of either one of those grant programs correlates to lower Hispanic student enrollment. Table 4 37 Results of regression function for rural institution Hispanic student enrollment Model Unstandardized Coefficients Standardized Coefficients t Sig. Std. Error (Constant) 16157.635 3452.933 4.679 .000 *** hbcu 3148.246 993.760 .130 3.168 .002 ** HSI_Status 7100.566 613.852 .521 11.567 .000 *** Undergrad_Distance 451.261 848.067 .023 .532 .595 Weekend_Eve 662.889 405.404 .060 1.635 .103 Remedial 499.496 595.901 .032 .838 .402 Academic_Career 1147.621 1788.291 .028 .642 .521 Emplyment_Svc 84.480 888.985 .004 .095 .924 Placement_Svc 913.098 646.792 .057 1.412 .159 Day_Care 193.766 412.435 .017 .470 .639 Percent_Min_Faculty 5290.285 1264.833 .178 4.183 .000 *** SSS_Grant 1207.157 404.035 .106 2.988 .003 ** Title_III_Grant 1868.618 783.277 .083 2.386 .017 Title_V_Grant 1199.751 814.506 .063 1.473 .141 Of the four variables blocks, only campus services were indicated to have a significant relationship to Hispanic student graduation rates in rural institutions ( Table 4 38 ). Table 4 38 Rural institution variables regressed for Hispanic student graduation Model R R Square Adjusted R Square Std. Error of the Estimate Change Statistics R Square Change F Change df1 df2 Sig. F Change MSI .095 .009 .001 26.478 .009 1.162 3 382 .324 Services .411 .169 .149 24.440 .160 12.064 6 376 .000 *** Faculty .417 .174 .152 24.403 .005 2.132 1 375 .145 Funding .418 .174 .146 24.491 .001 .100 3 372 .960

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105 No predictor variables were found to positively correlate to Hispanic student graduation in rural institutions. Undergraduate distance education options ( = .301, p .001) and remedial services ( = .134, p .01) were both were found to have a negative relationship. These findings indicate that when evaluated with all of the other variables distance education options and remedial services resulted in lower Hispanic student graduation rates. Table 4 39 Results of regression function for Hispanic student graduation rates in rural institutions Model Unstandardized Coefficients Standardized Coefficients t Sig. Std. Error (Constant) 57.654 51.766 1.114 .266 Hbcu 9.299 11.623 .047 .800 .424 Tribal 20.308 18.218 .055 1.115 .266 HSI_Status .089 6.660 .001 .013 .989 Undergrad_Distance 32.976 5.701 .301 5.784 .000*** Weekend_Eve 2.990 2.576 .057 1.161 .246 Remedial 24.945 8.991 .134 2.774 .006** Emplyment_Svc .460 4.460 .005 .103 .918 Placement_Svc 6.041 3.750 .080 1.611 .108 Day_Care 4.669 2.659 .087 1.756 .080 Percent_Min_Faculty 17.445 11.763 .094 1.483 .139 SSS_Grant .928 2.641 .017 .351 .726 Title_III_Grant 2.388 6.013 .019 .397 .692 Title_V_Grant .879 8.864 .006 .099 .921 The only variable block indicating a significant relationship to Hispanic completers in rural institutions was the percentage of minority faculty ( Table 4 40 ). In addition to the significant relationship presented for the percentage of minority faculty Minority Serving Institution status was also a significant predictor of Hispanic student completers. HBCU status resulted in an increase in Hispanic student completions ( =.111, p .05) as did tribal classification ( =.127, p .05).

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106 Table 4 40 Rural in stitution variables regressed for Hispanic completers Model R R Square Adjusted R Square Std. Error of the Estimate Change Statistics R Square Change F Change df 1 df 2 Sig. F Change MSI .075 .006 .000 5.154 .006 1.015 3 544 .386 Services .150 .022 .004 5.143 .017 1.324 7 537 .236 Faculty .190 .036 .016 5.112 .014 7.570 1 536 .006 ** Funding .198 .039 .014 5.118 .003 .562 3 533 .640 Table 4 41 Results of regression function for Hispanic completers in rural institutions Model Unstandardized Coefficients Standardized Coefficients t Sig. Std. Error (Constant) 20.552 7.960 2.582 .010 Hbcu 4.749 2.223 .111 2.136 .033 Tribal 3.413 1.501 .127 2.273 .023 HSI_Status .582 1.258 .026 .463 .644 Undergrad_Distance .306 .631 .026 .484 .628 Weekend_Eve .738 .475 .071 1.554 .121 Remedial .411 1.073 .019 .383 .702 Academic_Career .217 1.698 .006 .128 .898 Emplyment_Svc .170 .653 .013 .259 .795 Placement_Svc .215 .647 .016 .332 .740 Day_Care .427 .493 .040 .866 .387 Percent_Min_Faculty 5.978 2.115 .183 2.826 .005 ** SSS_Grant .217 .515 .020 .421 .674 Title_III_Grant .459 1.220 .016 .376 .707 Title_V_Grant 1.973 1.784 .060 1.106 .269 For rural institutions, the percentage of minority faculty present was found to correlate to higher enrollment, graduation, and completion for all minority populations evaluated. For rural black students, flexible course options, such as distance education and evening and weekend courses, were significant predictors of higher enrollment. Rural black students were also more likely to enroll in a tribal college or HSI than in a

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107 HBCU or PWI college or university. In contrast Hispanic students were more likely to enroll in an HBCU than in the other MSI institutions or a PWI. No campus services were found to correlate to higher Hispanic student enrollment patterns in rural institutions. Several variables were found to correlate to improved rural minority student success. Only one variable was found to have a positive relationship to graduation. Rural institutions offering placement services for graduates had significantly higher rates of black student graduation. In contrast, several variables were found to have a significant relationship to minority student completion. Placement services for graduates, tribal college status, and evening and weekend courses were all significant predictors of both overall minority completion as well as black student completion. Ins titutions offering remedial services for graduates were more likely to have higher overall minority graduation rates; however, that relationship was not found for black and Hispanic student completion patterns. No campus services correlated to higher Hispa nic student completion; however, Hispanic students were found to be more likely to complete their degree HBCUs and tribal colleges than at other institution typologies. Appendix A presents a summary of each variable with a significant, positive relationshi p to minority student enrollment, graduation, and completion for each geographic context. Suburban Colleges Minority student enrollment, graduation, and completion patterns in sub urban institutions The regression function for minority student enrollment in suburban institutions indicated that the variable blocks for MSI status and presence of minority faculty were significant predictors ( Table 4 42 ). Analysis of the fourteen individual predicto r variables resulted in five predictors with a significant relationship to suburban minority student enrollment patterns

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108 Table 4 42 Suburban institution variables regressed for minority student enrollment Model R R Square Adjusted R Square Std. Error of the Estimate Change Statistics R Square Change F Change df1 df2 Sig. F Change MSI .648 .420 .417 .16412 .420 140.462 3 583 .000 *** Services .657 .432 .422 .16337 .012 1.760 7 576 .093 Faculty .813 .661 .654 .12634 .229 388.132 1 575 .000 *** Funding .813 .661 .653 .12658 .000 .272 3 572 .846 p ( Table 4. 43 ). The percentage of minority faculty presented the strongest positive relationship ( = .591, p options were also found to have a significant relationship to minority enrollment patterns ( = .078, p ( = .096, p HSIs ( = .322, p Table 4 43 Results of regression function for minority enrollment in suburban institutions Model Unstandardized Coefficients Standardized Coefficients t Sig. Std. Error (Constant) 1.123 .205 5.488 .000 *** Hbcu .140 .041 .096 3.385 .001 ** Tribal .119 .083 .040 1.437 .151 HSI_Status .215 .022 .322 9.806 .000 *** Undergrad_Distance .023 .024 .025 .955 .340 Weekend_Eve .034 .011 .078 3.129 .002 ** Remedial .029 .020 .036 1.447 .148 Academic_Career .100 .099 .027 1.006 .315 Emplyment_Svc .048 .024 .057 2.017 .044 Placement_Svc .016 .016 .028 1.024 .306 Day_Care .007 .011 .016 .621 .535 Percent_Min_Faculty .820 .042 .591 19.478 .000 *** SSS_Grant .005 .011 .012 .489 .625 Title_III_Grant .017 .027 .015 .605 .545 Title_V_Grant .012 .029 .013 .419 .675 p

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109 services ( = .057, p institutions were more likely to have lower minority enrollment percentages than other institution types, and that employment services correlated to lower minority enrollment. The variable block fo r campus services was the only vector with a significant relationship to minority student graduation rates within the s uburban geographic context ( Table 4 44 ). Table 4 44 Suburban institution variables regressed for minority student graduation rates Model R R Square Adjusted R Square Std. Error of the Estimate Change Statistics R Square Change F Change df 1 df 2 Sig. F Change MSI .149 .022 .017 19.145 .022 4.334 3 570 .005 ** Services .434 .189 .174 17.548 .166 16.504 7 563 .000 *** Faculty .436 .190 .174 17.547 .002 1.060 1 562 .304 Funding .440 .194 .173 17.557 .003 .778 3 559 .506 p The strongest positive relationship was found for institutions offering placement services for completers ( = 8.011, p the MSI status block, Hispanic Serving Institutions were correlated to higher minority student graduation rates ( = .108, p = .14.077, p institutions offering weekend and evening course options ( = 5.271, p = 20.121, p = 9.437, p significant negative relationship to suburban minority graduation rates. These findings indicate that suburban institutions offe ring those services had lower minority student graduation rates.

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110 Table 4 45 Results of regression function for minority graduation rates in suburban institutions Model Unstandardized Coefficients Standardized Coefficients t Sig. Std. Error (Constant) 49.844 28.473 1.751 .081 Hbcu 6.052 5.782 .047 1.047 .296 Tribal 11.063 11.530 .041 .959 .338 HSI_Status 6.452 3.074 .108 2.099 .036 Undergrad_Distance 14.077 3.490 .162 4.034 .000 *** Weekend_Eve 5.271 1.507 .137 3.497 .001 ** Remedial 20.121 3.021 .259 6.660 .000 *** Academic_Career .251 13.758 .001 .018 .985 Emplyment_Svc 9.437 3.430 .120 2.751 .006 ** Placement_Svc 8.011 2.221 .154 3.607 .000 *** Day_Care 2.481 1.538 .064 1.613 .107 Percent_Min_Faculty 6.006 5.926 .048 1.013 .311 SSS_Grant 1.241 1.508 .032 .822 .411 Title_III_Grant .805 3.804 .008 .212 .832 Title_V_Grant 5.329 4.095 .062 1.301 .194 p Table 4 46 Suburban institution variables regressed for minority completers Model R R Square Adjusted R Square Std. Error of the Estimate Change Statistics R Square Change F Change df 1 df 2 Sig. F Change MSI .165 .027 .022 300.49031 .027 5.424 3 583 .001 ** Services .280 .079 .063 294.21588 .051 4.590 7 576 .000 *** Faculty .374 .140 .123 284.55784 .061 40.763 1 575 .000 *** Funding .381 .145 .124 284.36083 .006 1.266 3 572 .285 p The regression function for minority completers at suburban institutions indicated that the variable blocks for MSI status, campus services, and presence of minority faculty w ere significant predictors ( Table 4 46 ). Of the fourteen predictor variables, six were found to have a significant relationship to the number of minority completers at suburban institutions The percent

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111 of minority faculty had the strongest positive relationship ( = .309 p and evening course options ( = .119 p = .089 p Table 4 47 Results of regression function for minority completers at suburban institutions Model Unstandardized Coefficients Standardized Coefficients T Sig. Std. Error (Constant) 765.093 451.066 1.696 .090 Hbcu 3.316 94.992 .002 .035 .972 Tribal 283.102 187.625 .066 1.509 .132 HSI_Status 78.447 121.064 .034 .648 .517 Undergrad_Distance 12.758 53.133 .010 .240 .810 Weekend_Eve 72.282 24.221 .119 2.984 .003 ** Remedial 167.243 45.346 .147 3.688 .000 *** Academic_Career 120.236 222.688 .023 .540 .589 Emplyment_Svc 64.794 53.913 .054 1.202 .230 Placement_Svc 25.254 35.385 .031 .714 .476 Day_Care 53.864 24.994 .089 2.155 .032 Percent_Min_Faculty 606.510 97.573 .309 6.216 .000 *** SSS_Grant 7.295 24.329 .012 .300 .764 Title_III_Grant 4.298 61.589 .003 .070 .944 Title_V_Grant 123.058 63.432 .091 1.940 .053 *p **p ***p services identified as having a significant impact on suburban minority completers. MSI status and targeted funding were not found to be significant predictors of suburban minority student completion. Remedial services presented a negative relationship to suburban minority student completion ( = .147 p 0 1) Given that remedial services are generally offered by open access institutions that accept students academically underprepared for higher education, this finding is not unexpected. It can be attributed to the lower probability of long term success for those student demographics. Bla ck student enrollment, graduation, and completion patterns in sub urban institutions The regression function for suburban black student enrollment indicated

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112 that MSI status, campus services, and the presence of minority faculty are significant factors in p redicti ng black student enrollment ( Table 4 48 ). Table 4 48 Suburban institution variables regressed for black student enrollment **p ***p Table 4 49 Results of regression function for black student enrollment in suburban institutions Model Unstandardized Coefficients Standardized Coefficients t Sig. B Std. Error Beta (Constant) 6844.663 3623.181 1.889 .059 Hbcu 459.237 734.341 .029 .625 .532 Tribal 2168.264 1468.549 .065 1.476 .140 HSI_Status 324.816 387.782 .044 .838 .403 Undergrad_Distance 884.846 419.071 .088 2.111 .035 Weekend_Eve 860.830 190.750 .182 4.513 .000 *** Remedial 149.238 357.687 .017 .417 .677 Academic_Career 1231.582 1755.943 .030 .701 .483 Emplyment_Svc 93.201 424.688 .010 .219 .826 Placement_Svc 141.780 279.092 .023 .508 .612 Day_Care 338.941 195.236 .071 1.736 .083 Percent_Min_Faculty 3686.471 745.540 .241 4.945 .000 *** SSS_Grant 55.900 191.639 .012 .292 .771 Title_III_Grant 16.784 485.603 .001 .035 .972 Title_V_Grant 1188.398 520.300 .112 2.284 .023 *p **p ***p Four variables were found to have a significant relationship to suburban black student enrollment patterns. In similar fashion to urban black student enrollment, the presence of minority faculty had the strongest relationship to suburban black student Model R R Square Adjusted R Square Std. Error of the Estimate Change Statistics R Square Change F Change df 1 df 2 Sig. F Change MSI .167 .028 .023 2342.558 .028 5.581 3 583 .001 ** Services .280 .079 .063 2294.598 .051 4.518 7 576 .000 *** Faculty .344 .118 .101 2246.397 .040 25.984 1 575 .000 *** Funding .356 .127 .105 2241.722 .008 1.800 3 572 .146

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113 enrollment ( = .241, p distance education ( = .088, p = .182, p the targeted funding block, only the presence of a Title V grant had a significant relationship to suburban black student enrollment ( = .112, p Table 4 50 Suburban institution variables regressed for black student graduation Model R R Square Adjusted R Square Std. Error of the Estimate Change Statistics R Square Change F Change df 1 df 2 Sig. F Change MSI .263 .069 .053 31.554 .069 4.351 2 117 .015 Services .457 .209 .152 29.865 .140 3.268 6 111 .005 ** Faculty .469 .220 .156 29.798 .011 1.504 1 110 .223 Funding .470 .221 .133 30.193 .001 .046 3 107 .987 *p **p ***p Table 4 51 Results of regression function for black student graduation rates at suburban institutions Model Unstandardized Coefficients Standardized Coefficients t Sig. B Std. Error Beta (Constant) 255.513 86.430 2.956 .004 ** T ribal 106.433 33.444 .300 3.182 .002 ** HSI_Status 1.641 9.115 .022 .180 .857 Undergrad_Distance 39.563 14.680 .306 2.695 .008 ** Weekend_Eve 3.915 6.406 .059 .611 .542 Remedial 15.251 15.404 .103 .990 .324 Emplyment_Svc 15.167 12.191 .141 1.244 .216 Placement_Svc 10.493 7.626 .134 1.376 .172 Day_Care 6.872 6.556 .105 1.048 .297 Percent_Min_Faculty 21.360 17.235 .117 1.239 .218 SSS_Grant .336 6.046 .005 .056 .956 Title_III_Grant 7.757 22.121 .031 .351 .727 Title_V_Grant 1.621 11.786 .014 .138 .891 *p **p ***p

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114 The regression function for black student graduation at suburban institutions indicated that MSI status and services were significant predictors (Table 4 50 ). Two predictor variables were found to have a significant relationship to black student graduation rates in suburban institutions; however, both were negatively related. Tribal institutions correlated to a lower graduation rate ( = .300, p undergraduate distance education options ( = .306, p Two predictor variables were found to have a significant relationship to black student graduation rates in suburban institutions; however, both were negatively related. Tribal institutions corre lated to a lower graduation rate ( = .300, p undergraduate distance education options ( = .306, p The regression function for black completers at suburban institutions indicated that the variable blocks for MSI status, campus servic es, and the percentage of minority were all significant (Table 4 52 ). The percentage of minority faculty was indicated to Table 4 52 Suburban Institution variables regressed for black completers Mod el R R Square Adjusted R Square Std. Error of the Estimate Change Statistics R Square Change F Change df 1 df 2 Sig. F Change MSI .262 .069 .064 203.159 .069 14.354 3 582 .000 *** Services .328 .107 .092 200.132 .038 3.535 7 575 .001 ** Faculty .373 .139 .122 196.732 .032 21.043 1 574 .000 *** Funding .378 .143 .122 196.813 .004 .842 3 571 .471 *p **p ***p have the most significant relationship to the number of black completers ( = .214, p = .144, p education ( = .088, p

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115 A negative relationship was found for HBCUs ( = .163, p services ( = .086, p fourteen predictor variables, suburban HBCUs and institutions offering remedial services had fewer black student complete their degrees. Table 4 53 Results of regression function for black completers at suburban institutions Model Unstandardized Coefficients Standardized Coefficients T Sig. Std. Error (Constant) 150.392 318.130 .473 .637 Hbcu 232.680 64.472 .163 3.609 .000 *** Tribal 139.771 128.933 .048 1.084 .279 HSI_Status 38.104 34.054 .059 1.119 .264 Undergrad_Distance 77.757 36.793 .088 2.113 .035 Weekend_Eve 60.312 16.762 .144 3.598 .000 *** Remedial 67.475 31.404 .086 2.149 .032 Academic_Career 111.548 154.164 .031 .724 .470 Emplyment_Svc 20.839 37.286 .025 .559 .576 Placement_Svc 7.169 24.505 .013 .293 .770 Day_Care 11.192 17.157 .027 .652 .514 Percent_Min_Faculty 290.224 65.457 .214 4.434 .000 *** SSS_Grant 12.215 16.837 .029 .725 .468 Title_III_Grant 6.152 42.634 .006 .144 .885 Title_V_Grant 61.794 45.680 .066 1.353 .177 *p **p ***p Hispanic student enrollment, graduation, and completion patterns in suburban institutions. The variable blocks for MSI status, campus services, and the percentage of minority faculty were all significant indicators of Hispanic student enrollme nt for suburban institutions ( Table 4 54 ). Five of the fourteen individual predictors were found to be significant (Table 4.54 ). Within the MSI block, HBCUs were found to correlate to higher Hispanic student enrollment ( = .116 p us had a negative relationship ( = .538

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116 p an HSI than in other types of institutions. Two campus services, weekend and evening Table 4 54 Suburban institution vari ables regressed for Hispanic student enrollment Model R R Square Adjusted R Square Std. Error of the Estimate Change Statistics R Square Change F Change df1 df2 Sig. F Change 1 .604 b .365 .361 2199.150 .365 111.496 3 583 .000 *** 2 .635 c .403 .392 2145.189 .038 5.243 7 576 .000 *** 3 .654 d .428 .417 2101.114 .025 25.419 1 575 .000 *** 4 .657 e .431 .418 2100.130 .004 1.180 3 572 .317 *p **p ***p Table 4 55 Results of regression function for Hispanic student enrollment in suburban institutions Model Unstandardized Coefficients Standardized Coefficients T Sig. Std. Error (Constant) 2294.226 3394.333 .676 .499 Hbcu 2167.198 687.958 .116 3.150 .002 ** Tribal 2132.530 1375.792 .055 1.550 .122 HSI_Status 4592.169 363.289 .538 12.641 .000 *** Undergrad_Distance 305.465 392.602 .026 .778 .437 Weekend_Eve 597.277 178.702 .109 3.342 .001 ** Remedial 72.019 335.095 .007 .215 .830 Academic_Career 30.542 1645.034 .001 .019 .985 Emplyment_Svc 216.763 397.864 .020 .545 .586 Placement_Svc 76.003 261.464 .010 .291 .771 Day_Care 754.412 182.904 .137 4.125 .000 *** Percent_Min_Faculty 3422.088 698.450 .192 4.900 .000 *** SSS_Grant 63.538 179.534 .011 .354 .724 Title_III_Grant 5.106 454.932 .000 .011 .991 Title_V_Grant 888.650 487.437 .072 1.823 .069 *p **p ***p classes ( = .109 p = .137 p significant positive relationship to suburban Hispanic student enrollment. Interestingly,

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117 this was the only demographic for which child day care would be a positive predictor of enrollment. Hispanic student enrollment was also found to increase with the percentage of minority faculty ( = .192 p The regression function for suburban minority student graduation indicated that MSI status and campus servic es were significant factors (Table 4 56 ). Table 4 56 Suburban institution variables regressed for Hispanic student graduation Model R R Square Adjusted R Square Std. Error of the Estimate Change Statistics R Square Change F Change df 1 df 2 Sig. F Change MSI .209 .044 .039 16.768 .044 8.689 3 569 .000 *** Services .502 .252 .238 14.928 .208 22.279 7 562 .000 *** Faculty .506 .256 .241 14.897 .004 3.308 1 561 .069 Funding .512 .262 .244 14.874 .006 1.588 3 558 .191 *p **p ***p Hispanic Serving Institutions ( = .145 p completers ( = .171 p = .091 p significant relationship with suburban minority student graduation. Four services were found to have a negative relationship, specifically, undergraduate distance education ( = .170 p = .193 p services ( = .280 p 001), and employment services for students ( = .104 p When blocked, the only vector with a significant impact on suburban Hispanic completion was the perc entage of minority faculty (Table 4 57 ). However, the more in depth analysis of individual pr edictor variables indicated that a number of campus services presented a significant positive relationship to the number of minority

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118 Table 4 57 Results of the regression function for Hispanic student graduation in suburban institutions Model Unstandardized Coefficients Standardized Coefficients T Sig. Std. Error (Constant) 9.843 30.149 .326 .744 Hbcu 8.776 4.904 .076 1.790 .074 Tribal 22.941 10.812 .079 2.122 .034 HSI_Status 7.650 2.605 .145 2.937 .003 ** Undergrad_Distance 13.229 3.005 .170 4.402 .000 *** Weekend_Eve 6.612 1.281 .193 5.161 .000 *** Remedial 19.257 2.562 .280 7.516 .000 *** Academic_Career 3.244 15.026 .008 .216 .829 Emplyment_Svc 7.300 2.933 .104 2.489 .013 Placement_Svc 7.884 1.891 .171 4.170 .000 *** Day_Care 3.106 1.308 .091 2.374 .018 Percent_Min_Faculty 9.220 5.061 .083 1.822 .069 SSS_Grant 1.195 1.278 .035 .935 .350 Title_III_Grant 4.509 3.224 .052 1.399 .162 Title_V_Grant 4.893 3.470 .065 1.410 .159 *p **p ***p Table 4 58 Suburban institution variables regressed for Hispanic completers Model R R Square Adjusted R Square Std. Error of the Estimate Change Statistics R Square Change F Change df 1 df 2 Sig. F Change MSI .037 .001 .004 22.303 .001 .261 3 582 .854 Services .151 .023 .006 22.194 .022 1.813 7 575 .082 Faculty .317 .100 .083 21.315 .077 49.439 1 574 .000 *** Funding .319 .102 .080 21.354 .001 .301 3 571 .825 *p **p ***p When blocked, the only vector with a significant impact on suburban Hispanic completion was the percentage of minority faculty ( Table 4 58 ). However, the more in depth analysis of individual predictor variables indicated that a number of campus services presented a significant positive relationship to the number of minority

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119 Table 4 59 Results of regression function for Hispanic completers at suburban institutions Model Unstandardized Coefficients Standardized Coefficients t Sig. Std. Error (Constant) 124.369 34.516 3.603 .000 *** Hbcu 30.011 6.995 .199 4.290 .000 *** Tribal 20.560 13.989 .066 1.470 .142 HSI_Status 9.666 3.695 .140 2.616 .009 ** Undergrad_Distance 5.267 3.992 .056 1.319 .188 Weekend_Eve 2.841 1.819 .064 1.562 .119 Remedial .657 3.407 .008 .193 .847 Academic_Career 9.698 16.726 .025 .580 .562 Emplyment_Svc 3.630 4.045 .042 .897 .370 Placement_Svc 6.456 2.659 .109 2.428 .015 Day_Care 1.344 1.861 .030 .722 .471 Percent_Min_Faculty 49.851 7.102 .347 7.019 .000 *** SSS_Grant 1.718 1.827 .038 .940 .347 Title_III_Grant .442 4.626 .004 .095 .924 Title_V_Grant .414 4.956 .004 .083 .934 *p **p ***p completers ( Table 4 59 ). Just as there were a limited number of variables with a positive significant relationship to suburban Hispanic student graduation, only three predictors were found to be significant in regards to suburban Hispanic completers (Table 4 59 ). Within the MSI s tatus block, HBCUs were found to have a significant relationship to the number of Hispanic suburban completers ( = .199 p found to have a significant positive relationship ( = .140 p were found to have a positive relationship. Placement services was found to have a negative relationship ( = .109 p to have the most significant relationship ( = .347 p

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120 Urban Colleges Urban College Minority Student Enrollment, Graduation, and Completion Patterns The results of the regression function for minority student enrollment in urban Table 4 6 0 Urban institution variables regressed for minority student enrollment Model R R Square Adjusted R Square Std. Error of the Estimate Change Statistics R Square Change F Change df 1 df 2 Sig. F Change MSI .647 .418 .416 .18687 .418 177.092 2 493 .000 *** Services .657 .431 .421 .18607 .013 1.609 7 486 .131 Faculty .883 .779 .775 .11598 .348 765.954 1 485 .000 *** Funding .884 .781 .775 .11591 .002 1.173 3 482 .319 **p ***p institutions indicates that at a p value of p faculty were significant predictors of enrollment (Table 4 60 ). Of the thirteen predictor variables, two were found to have a significant relationship to minority student enrollment patterns. A negative relationship was found for HSI status, which indicated that minority student enrollment was lower ( = .278, p ) at a HSI coll ege or university. A positive relationship was found for the percentage of minority faculty, indicating that with each percentage increase in minority faculty ( = .730, p ), urban minority student enrollment increased. No services or targeted funding programs were indicated as having a significant relationship to urban minority student enrollment. The regression function for minority student graduation rate at urban institutions indicated that MSI status was a significant predictor ( Table 4 62 ).

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121 Table 4 61 Results of regression function for minority student enrollment in urban institutions Model Unstandardized Coefficients Standardized Coefficients t Sig. Std. Error MSI Hbcu .027 .027 .026 1.019 .309 HSI_Status .165 .017 .278 9.908 .000 *** Services Undergrad_Distance .015 .023 .017 .640 .523 Weekend_Eve .012 .011 .026 1.136 .256 Remedial .002 .016 .003 .110 .913 Academic_Career .024 .048 .013 .492 .623 Emplyment_Svc .009 .024 .011 .393 .695 Placement_Svc .011 .018 .016 .624 .533 Day_Care .008 .011 .015 .673 .501 Minority Faculty Percent_Min_Faculty .945 .034 .730 27.556 .000 *** Targeted Funding SSS_Grant .004 .011 .009 .408 .683 Title_III_Grant .008 .021 .009 .400 .689 Title_V_Grant .039 .022 .047 1.789 .074 (Constant) .593 .094 6.340 .000 *** ***p Table 4 62 Urban institution variables regressed for minority student graduation rate Model R R Square Adjusted R Square Std. Error of the Estimate Change Statistics R Square Change F Change df 1 df 2 Sig. F Change MSI .145 .021 .017 14.592 .021 4.907 2 455 .008 ** Services .408 .167 .152 13.553 .146 13.077 6 449 .000 *** Faculty .409 .168 .151 13.561 .001 .420 1 448 .517 Funding .419 .175 .153 13.543 .008 1.405 3 445 .241 **p ***p

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122 Table 4 6 3 Results of regression function for minority student graduation rates in urban institutions Model Unstandardized Coefficients Standardized Coefficients t Sig. Std. Error (Constant) 18.853 11.513 1.638 .102 Hbcu 5.517 3.215 .088 1.716 .087 HSI_Status 4.866 1.993 .138 2.442 .015 Undergrad_Distance 4.812 3.775 .056 1.275 .203 Weekend_Eve 6.465 1.318 .216 4.905 .000 *** Remedial 13.359 2.197 .268 6.081 .000 *** Emplyment_Svc 1.497 3.702 .019 .404 .686 Placement_Svc 5.010 2.194 .104 2.284 .023 Day_Care 1.382 1.370 .045 1.009 .313 Percent_Min_Faculty 1.887 4.157 .024 .454 .650 SSS_Grant .387 1.304 .013 .297 .767 Title_III_Grant 3.568 2.494 .063 1.431 .153 Title_V_Grant 3.643 2.644 .074 1.378 .169 *p **p ***p Analysis of the individual predictors indicates that at a p value of p colleges and universities and institutions offering placement services for completers had a slightly higher graduation rate for m inority students ( Table 4 63 ). Institutions offering weekend and evening course options ( = .216, p ) and remedial services ( = .268, p ) had slightly lower graduation rates for minority students. Table 4 64 Urban institution variables regressed for minority completers **p ***p 0 1 Model R R Square Adjusted R Square Std. Error of the Estimate Change Statistics R Square Change F Change df 1 df 2 Sig. F Change MSI .146 .021 .017 467.97097 .021 5.368 2 493 .005 ** Services .281 .079 .062 457.26946 .058 4.335 7 486 .000 *** Faculty .352 .124 .106 446.37949 .045 25.002 1 485 .000 *** Funding .369 .136 .113 444.63148 .012 2.274 3 482 .079

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123 The regression function for urban minority completers indicated that MSI status, campus services, and the presence of minority faculty all presented a significant relationship to the number of minority completers ( Table 4 64 ). Of the thirteen predictor variables, six had significant relationships to minority student completion. The strongest predictor of minority student completion was the percentage of minority faculty at the institution ( = .279, p ). Table 4 65 Results of reg ression function for minority completers at urban institutions Model Unstandardized Coefficients Standardized Coefficients t Sig. Std. Error (Constant) 507.588 358.999 1.414 .158 Hbcu 10.114 103.321 .005 .098 .922 HSI_Status 24.835 63.822 .022 .389 .697 Undergrad_Distance 242.649 88.173 .145 2.752 .006 ** Weekend_Eve 16.029 42.150 .017 .380 .704 Remedial 169.138 61.956 .130 2.730 .007 ** Academic_Career 244.638 185.928 .070 1.316 .189 Emplyment_Svc 37.167 92.427 .022 .402 .688 Placement_Svc 180.424 67.247 .133 2.683 .008 ** Day_Care 87.577 42.881 .093 2.042 .042 Percent_Min_Faculty 697.269 131.504 .279 5.302 .000 *** SSS_Grant 64.051 42.007 .067 1.525 .128 Title_III_Grant 172.229 81.437 .091 2.115 .035 Title_V_Grant 11.592 84.684 .007 .137 .891 *p **p ***p Three campus services correlated to higher levels of minority student completion, including distance education options ( = .145, p completers ( = .133, p 1 ), and child day care ( = .093, p presented a negative relationship. Remedial services ( = .130, p 1 ) and Title III grant funding ( = .091 p

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124 Black student enrollment, graduation, and completion patterns in urban institutions. The regression function for urban black student enrollment indicated that all four variable blocks were significant predictors. At a p value of .001, MSI status, minor ity faculty, and targeted funding programs were found to be significant (Table 4 6 6 ). Table 4 6 6 Urban institution variables regressed for black student enrollment Model R R Square Adjusted R Square Std. Error of the Estimate Change Statistics R Square Change F Change df 1 df 2 Sig. F Change MSI .203 .041 .037 3246.100 .041 10.550 2 493 .000 *** Services .281 .079 .062 3203.616 .038 2.880 7 486 .006 ** Faculty .401 .161 .143 3061.915 .081 47.024 1 485 .000 *** Funding .450 .203 .181 2993.191 .042 8.509 3 482 .000 *** **p ***p Analysis of the individual variables indicates that of the thirteen predictors, five were found to be significant. With each percentage point increase in the presence of minority faculty, black student enrollment increased ( = .382, p ). Black student enrollment increased ( = .119, p 1 ) at institutions offering weekend and evening courses at those providing placement services for completers ( = .100, p 1 ). Targeted funding was found to a have a slight ly negative impact on black student enrollment. The presence of a Student Support Services grant ( = .173, p the presence of a Title III grant resulted in a decrease ( = .121, p 1 ) in black student enrollment. Although Student Support Services grant projects are focused on helping disadvantaged students succeed, they are not designed as recruitment programs. While they may serve as valuable tools in helping students stay enrolled and

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125 Table 4 67 Results of regression fu nction for black student enrollment in urban institutions Model Unstandardized Coefficients Standardized Coefficients t Sig. Std. Error (Constant) 3597.389 2416.729 1.489 .137 Hbcu 189.310 695.539 .013 .272 .786 HSI_Status 760.914 429.639 .095 1.771 .077 Undergrad_Distance 871.943 593.567 .074 1.469 .142 Weekend_Eve 772.751 283.745 .119 2.723 .007 ** Remedial 215.518 417.075 .024 .517 .606 Academic_Career 1920.802 1251.636 .078 1.535 .126 Emplyment_Svc 312.164 622.206 .026 .502 .616 Placement_Svc 945.919 452.693 .100 2.090 .037 Day_Care 160.374 288.666 .024 .556 .579 Percent_Min_Faculty 6690.641 885.265 .382 7.558 .000 *** SSS_Grant 1164.788 282.787 .173 4.119 .000 *** Title_III_Grant 1603.751 548.220 .121 2.925 .004 ** Title_V_Grant 132.455 570.078 .012 .232 .816 *p **p ***p Table 4 68 Urban institution variables regressed for black student graduation rates Model R R Square Adjusted R Square Std. Error of the Estimate Change Statistics R Square Change F Change df 1 df 2 Sig. F Change MSI .171 .029 .025 17.416 .029 6.841 2 457 .001 ** Services .292 .085 .069 17.017 .056 4.611 6 451 .000 *** Faculty .295 .087 .069 17.019 .002 .884 1 450 .348 Funding .312 .097 .073 16.982 .010 1.662 3 447 .175 *p **p ***p achieve higher levels of success, the findings of this study indicate they are not programs successful in recruiting black students to urban institutions. The regression function for urban black student graduation rate indicated a significant relationship between MSI status and graduation patterns ( Table 4 68 ).

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126 Table 4 69 Results of regression for black student graduation rates at urban institutions Model Unstandardized Coefficients Standardized Coefficients t Sig. Std. Error (Constant) 3.560 13.964 .255 .799 Hbcu 3.055 4.030 .041 .758 .449 HSI_Status 6.375 2.494 .152 2.556 .011 Undergrad_Distance 2.439 4.178 .028 .584 .560 Weekend_Eve 6.126 1.647 .172 3.720 .000 *** Remedial 7.183 2.637 .126 2.724 .007 ** Emplyment_Svc 3.699 4.010 .046 .922 .357 Placement_Svc 2.490 2.696 .045 .923 .356 Day_Care 2.535 1.713 .069 1.480 .140 Percent_Min_Faculty 3.738 5.196 .041 .719 .472 SSS_Grant 2.786 1.627 .078 1.712 .088 Title_III_Grant 4.531 3.121 .066 1.452 .147 Title_V_Grant .045 3.258 .001 .014 .989 *p **p ***p Analysis of the thirteen individual predictors indicates that three variables had a significant relationship to urban black student graduation patterns. Black students attending a Hispanic Serving Institution graduated at a higher rate than their peers at other institutions types ( = .152, p evening course options ( = .172, p ) and remedial services ( = .126, p had a slightly lower black student graduation rate. The regression function for black completers at urban institutions indicates that the variable blocks for MSI status, campus services, and percentage of minority faculty all have a signific ant relationship ( Table 4 70 ). Analysis of the thirteen predictor variables indicates that the strongest predictor of black student completion was the percentage of minority faculty present at the ins titution ( = .329, p

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127 demonstrated a significant relationship; however, only Hispanic Serving Institutions were found to have a positive relationship ( = .144, p based Table 4 70 Urban institution variables regressed for black completers Model R R Square Adjusted R Square Std. Error of the Estimate Change Statistics R Square Change F Change df 1 df 2 Sig. F Change MSI .302 .091 .088 307.297 .091 24.724 2 492 .000 *** Services .357 .128 .113 302.937 .036 3.377 6 486 .003 ** Faculty .439 .193 .178 291.672 .065 39.265 1 485 .000 *** Funding .449 .202 .182 291.034 .008 1.710 3 482 .164 **p ***p Table 4 71 Results of regression function for black completers at urban institutions Model Unstandardized Coefficients Standardized Coefficients T Sig. Std. Error (Constant) 376.731 231.333 1.629 .104 Hbcu 175.787 67.629 .126 2.599 .010 HSI_Status 112.620 41.775 .144 2.696 .007 ** Undergrad_Distance 143.148 57.714 .111 2.480 .013 Weekend_Eve 53.069 27.589 .082 1.924 .055 Remedial 71.097 40.553 .075 1.753 .080 Emplyment_Svc 26.666 60.498 .020 .441 .660 Placement_Svc 126.808 44.016 .128 2.881 .004 ** Day_Care 14.366 28.068 .022 .512 .609 Percent_Min_Faculty 558.970 86.076 .329 6.494 .000 *** SSS_Grant 37.168 27.496 .057 1.352 .177 Title_III_Grant 85.230 53.305 .066 1.599 .110 Title_V_Grant 49.838 55.430 .045 .899 .369 *p **p ***p services were indicated to have a positive correlation with higher numbers of black completers. Undergraduate distance education options ( = .111, p placement services for completers ( = .128, p relationships. Surprisingly, HBCU institut ions were found to have a significant negative

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128 relationship ( = .126, p graduated at a lower that at other institution typologies. Hispanic student enrollment, graduation, and completion patterns i n urban institutions The function for urban Hispanic student enrollment indicated that three of the blocks were significant predictors of enrollment ( Table 4 7 2 ). Tab le 4 72 Urban institution variables regressed for Hispanic student enrollment Model R R Square Adjusted R Square Std. Error of the Estimate Change Statistics R Square Change F Change df 1 df 2 Sig. F Change MSI .623 b .389 .386 4397.343 .389 156.755 2 493 .000 *** Services .631 c .399 .388 4392.750 .010 1.147 7 486 .332 Faculty .644 d .415 .403 4336.705 .016 13.643 1 485 .000 *** Funding .659 e .435 .419 4276.561 .020 5.579 3 482 .001 ** Table 4 73 Results of regression function for urban Hispanic student enrollment Model Unstandardized Coefficients Standardized Coefficients t Sig. Std. Error (Constant) 16157.635 3452.933 4.679 .000 *** Hbcu 3148.246 993.760 .130 3.168 .002 ** HSI_Status 7100.566 613.852 .521 11.567 .000 *** Undergrad_Distance 451.261 848.067 .023 .532 .595 Weekend_Eve 662.889 405.404 .060 1.635 .103 Remedial 499.496 595.901 .032 .838 .402 Academic_Career 1147.621 1788.291 .028 .642 .521 Emplyment_Svc 84.480 888.985 .004 .095 .924 Placement_Svc 913.098 646.792 .057 1.412 .159 Day_Care 193.766 412.435 .017 .470 .639 Percent_Min_Faculty 5290.285 1264.833 .178 4.183 .000 *** SSS_Grant 1207.157 404.035 .106 2.988 .003 ** Title_III_Grant 1868.618 783.277 .083 2.386 .017 Title_V_Grant 1199.751 814.506 .063 1.473 .141 p

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129 Analysis of the thirteen predictor variables indicates that HBCU institutions and institutions with a higher percentage of minority faculty reported higher levels of Hispanic student enrollment. A significant negative relationship was fo und for HSI status ( = .521, p Student Support Services grant funding ( = .106, p Title III grant funding ( = .083, p Table 4 97 ), which indicates that Hispanic students enrolled at institutions with these programs at a lowe r rate. The regression function for urban Hispanic student graduation indicated that only the variable block for campus services had a significant relationship (Table 4 74 ). Table 4 74 Urban institution variables regressed for Hispanic student graduati on Model R R Square Adjusted R Square Std. Error of the Estimate Change Statistics R Square Change F Change df 1 df 2 Sig. F Change MSI .095 .009 .001 26.478 .009 1.162 3 382 .324 Services .411 .169 .149 24.440 .160 12.064 6 376 .000 *** Faculty .417 .174 .152 24.403 .005 2.132 1 375 .145 Funding .418 .174 .146 24.491 .001 .100 3 372 .960 No variables were found to have a significant, positive relationship with urban Hispanic student graduation rates. Two campus services, however, were found to have a significant negative relationship with urban Hispanic graduation rates. These findings in dicate that those services correlate to lower Hispanic student graduation rates. Institutions offering distance education options ( = .301, p services ( = 2.774, p d oes not indicate that those services result in lower rates. Given the time parameters

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13 0 Table 4 75 Results of regression function for Hispanic student graduation rate at urban institutions Model Unstandardized Coefficients Standardized Coefficients t Sig. Std. Error (Constant) 57.654 51.766 1.114 .266 Hbcu 9.299 11.623 .047 .800 .424 Tribal 20.308 18.218 .055 1.115 .266 HSI_Status .089 6.660 .001 .013 .989 Undergrad_Distance 32.976 5.701 .301 5.784 .000 *** Weekend_Eve 2.990 2.576 .057 1.161 .246 Remedial 24.945 8.991 .134 2.774 .006 ** Emplyment_Svc .460 4.460 .005 .103 .918 Placement_Svc 6.041 3.750 .080 1.611 .108 Day_Care 4.669 2.659 .087 1.756 .080 Percent_Min_Faculty 17.445 11.763 .094 1.483 .139 SSS_Grant .928 2.641 .017 .351 .726 Title_III_Grant 2.388 6.013 .019 .397 .692 Title_V_Grant .879 8.864 .006 .099 .921 p associated with the definition of graduation, these results can be interpreted to indicate that urban Hispanic students who either need remedial courses or who access their courses via distance education take more than the standard time to complete. The regression function for urban Hispanic completers indicated that a significant relationship existed with MSI status, c ampus services, and funding ( Table 4 76 ). While there were no variables correlating to a significantly higher urban Hispanic student grad uation rate, two variables did significantly correlate to a higher number of urban Hispanic completers. HBCU institutions correlated to a higher number of Hispanic completers ( = .145, p = .127, p 01). A negative relationship was found for institutions offering evening and weekend courses ( = .119, p

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131 Table 4 76 Urban institution variables regressed for Hispanic completers Model R R Square Adjusted R Square Std. Error of the Estimate Change Statistics R Square Change F Change df 1 df 2 Sig. F Change MSI .115 .013 .009 11.847 .013 3.269 2 492 .039 Services .244 .059 .044 11.637 .046 3.984 6 486 .001 ** Faculty .252 .063 .046 11.624 .004 2.049 1 485 .153 Funding .306 .093 .071 11.471 .030 5.344 3 482 .001 ** p program ( = .114, p completers decreased at urban institutions offering evening and weekend course options and those with a Student Support Services grant program in place. Table 4 77 Results of regression f unction for Hispanic completers at urban institutions Model Unstandardized Coefficients Standardized Coefficients t Sig. B Std. Error Beta (Constant) 6.580 9.118 .722 .471 Hbcu 7.465 2.666 .145 2.801 .005 ** HSI_Status 1.855 1.647 .064 1.127 .260 Undergrad_Distance 2.787 2.275 .058 1.225 .221 Weekend_Eve 2.847 1.087 .119 2.618 .009 ** Remedial .120 1.598 .003 .075 .940 Emplyment_Svc 3.599 2.385 .074 1.509 .132 Placement_Svc 1.193 1.735 .033 .688 .492 Day_Care 3.097 1.106 .127 2.799 .005 ** Percent_Min_Faculty 6.290 3.393 .100 1.854 .064 SSS_Grant 3.490 1.084 .144 3.221 .001 ** Title_III_Grant 3.813 2.101 .080 1.815 .070 Title_V_Grant 3.432 2.185 .085 1.571 .117 p Summary of Data Analysis The data analyses provided in this chapter are intended to evaluate the relationship between common institutional attributes and minority student enrollment,

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132 graduation, and completion across the three geographic contexts. The desc riptive statistics indicate that significant differences in minority student graduation rate s exist across the three geographic context classifications. Rural institutions have a significantly lower minority student graduation rate than their urban and sub urban peer institutions. The multiple regression analysis functions indicated that the greatest impact of the variables measured was on minority student enrollment and completion, not on graduation. This trend was evidenced across all three geographic con texts. E nrollment The strongest factor impacting minority student enrollment patterns was the presence of minority faculty at the institution. Flexible course scheduling options, specifically evening and weekend courses and distance education options were the most significant campus services. Minority Serving Institution status presented an interesting relationship to enrollment. Tribal institutions and HSIs had a significant impact on rural minority student enrollment patterns. Surprisingly, HBCUs did not have a significant impact on black student enrollment patterns; however, they did have a significant relationship to Hispanic student enrollment patterns. That relationship was evidenced across all three geographic contexts. Graduation Only two variables really presented a strong relationship to minority student graduation patterns. Hispanic Serving Institutions presented a strong relationship to urban and suburban minority student graduation rates. Placement services for completers was also indicated as a significant factor in minority graduation patterns. Campus based child care services were indicated as a significant factor impacting

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133 graduation rates for suburban Hispanic students only. None of the targeted funding programs were found to be significant factors related to minority student graduation patterns. Completion The percentage of minority faculty presented the strongest relationship to minority student completion numbers. Options for more flexible course offerings, such as weekend and evening course options and distance education were significant variables in mino rity completion patterns. HBCUs, while not significant in regards to minority student graduation, were a significant factor in completion numbers across geographic groupings. Tribal institutions presented a strong relationship to completion patterns for al l three rural minority classifications. None of the variables in the targeted funding block were found to be significant factors in minority completion. The same variables found to be significant in minority enrollment patterns were also significant in mi nority completion patterns. This is possibly due to the process for calculating graduation and completion statistics. Graduation includes a time frame for completing the credential, whereas completion does not. Those factors attracting minority students to the institution appear to coincide with completion of the degree or credential at a slower pace than is encompassed by the graduation measure.

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134 CHAPTER 5 DISCUSSION AND CONCLUSION munity colleges, serve some of the most disadvantaged students in higher education. Education has long been viewed as the pathway out of poverty the great social equalizer. The increased push for access and rising tide of interest in accountability has l eft institutions that serve large numbers of nontraditional students struggling to keep up with external pressures. Findings from this study demonstrate that when evaluating the impact and focus for support services designed to impact rural minority studen ts, the emphasis should be placed on completion (with no time limits) as opposed to graduation (within 150% of the standard time) This research builds upon the existing body of literature regarding minority student success in higher education, by providi ng insight into not only those institution attributes that do correlate with achievement, but also how achievement for this student demographic should possibly be measured. The study specifically addressed three questions. The first was to what extent min ority student academic success outcomes, such as graduation (within 150% of the standard time) and completion (with no time limits) vary based upon institution geographic context. The proposed hypothesis was that no differences in minority student academi c success exist between the three geographic contexts. Second, this study sought to determine which of seven special services and learner support programs correlated to higher academic outcomes for minority students in rural serving institutions. It was pr oposed that no services would specifically correlate to increased minority student success in rural colleges and universities. Finally, this study

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135 investigated which institutional attributes, such as MSI status, percentage of minority faculty, and presence of targeted supplemental funding, correlated with higher minority student achievement in rural serving institutions. The hypothesis was that no institutional attributes correlated to enhanced minority student achievement in a rural context. Minority Stud ent Success across Geographic Contexts To what extent do academic success outcomes (graduation and completion) of minority college students vary based upon institution geographic context (rural, urban, and suburban)? Graduation The findings of this study c onflict with the proposed hypothesis that no differences exist in minority student achievement across the three geographic contexts. The results indicate that suburban institution graduation rates (completion of a degree or credential within 150% of the st andard time) outpace rural and urban institutions. These findings were held constant for both overall graduation rate and minority student graduation rate. Specifically, analysis of overall graduation rate alone indicated that rural institutions are signif icantly lower than urban and suburban institutions. While suburban institutions did indicate the highest overall graduation rate, it was not indicated to be significantly higher than urban institutions. In comparison to the findings for overall graduatio n rate, evaluation of minority student graduation rates indicated that suburban institutions had a significantly higher rate than both urban and rural institutions. No significant difference was found between urban and rural institutions. These results inf er that the combination of variables present in the suburban institution context (student population, institution attributes, support

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136 services, and funding programs) provide the best probability of degree completion within 150% of the standard time frame ( a two year degree within four years and a four year degree within six years). Completion The hypothesis that no differences in academic outcomes would exist across the three geographic contexts was not supported by analysis of completion data (earning the degree or credential without regard to time limits) either. Results indicate that urban institutions present a significantly higher number of completers than both suburban and rural institutions. This finding held constant for both overall co mpleters and minority completers. While urban institution s presented the most significant difference in completers, suburban institutions were also found to have a significantly higher number of completers than rural institutions. Analysis of the minority student completion data indicated similar findings to the overall completion data. The only difference was presented in the comparison of suburban and rural student completion data. The difference in institution typology for minority completion data was n ot as strong as that presented for the overall completion comparison. These findings indicate that while suburban institutions present the best combination of variables to support degree completion within 150% of the standard time, urban institutions prese nt the best combination of factors to support degree completion without regard to a timeframe. Regardless of timeframe, rural institutions present the lowest probability of student graduation and completion. Analyses of student academic outcome data acros s the three geographic contexts presents findings in support of the existing literature that rural students

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137 underperform (Pennington et al., 2006; Maltzan, 2006; Laskey & Hetzel, 2011; Ting, 1997; Schonert, Elliott, & Bills, 1991). Impact of Special Servi ces and Learner Support Programs in a Rural Context Which special services and learner support programs correlate to higher academic outcomes for minority students in rural institutions? Flexible Course Offerings: Distance Education and Weekend/Evening Co urses Results conflict with the proposed hypothesis that no services would correlate to higher minority student academic outcomes in rural institutions. Findings indicate that undergraduate distance education options and weekend and evening courses options both correlate with significantly higher rates of minority enrollment in rural institutions, as well as significantly higher minority student completion numbers across all three geographic contexts. Specifically, further analyses by racially grouping prov ided a more in depth view of the impact of both of the course scheduling options. Distance education and weekend and evening courses were found to positively correlate to increased levels of rural black student enrollment and completion. Distance educatio n has substantially increased access to higher education. While it may encompass a wide variety of forms, at its heart, it breaks down the traditional geographic obstacles to education often faced by rural students. In addition to the 74.70% (n=411) of rur al institutions in this study who reported offering undergraduate distance education options ( Tables 4 12, 4 13, and 4 14), students residing in their service areas also have the option to access courses and degree programs at a wealth of other institution s nationwide. Weekend and evening courses basically expand access to traditional higher education to a wider sector of society. While students who attend evening and weekend

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138 courses may not be purely part time students, they are generally students who can not attend a traditional Monday Friday daytime schedule, indicating they have extenuating commitments outside of education. Just as with distance education, evening and weekend students most likely have many different profiles. The strong relationship pres ented between alternative course delivery formats and enrollment and completion, but not graduation, most likely correlates to the nontraditional nature of the typical students choosing to complete their education using these options. Given the background in the literature regarding the unique psychosocial development of rural minority students, and the additional variables impacting their choice of educational program, it is logical to conclude that flexibility in course delivery would be a key factor in t heir academic success. Placement Services for Completers Results of this study also indicate that placement services for completers have a strong correlation to increased success of rural minority students. This relationship was not only found for rural minority students, but also for urban and suburban students as well. It was the only campus service with a positive relationship to both graduation and completion. This connection speaks to the unique psychosocial development and environmental context that shapes the educational experience for many rural, minority students. A distinct education to workforce connection has emerged as a key variable in improving graduation and completion numbers for this demographic. According to Neault and Pickerell (2008), the literature is lacking in research to support expanded access and funding for career services, internships, and placement programs within higher education. While there are no cases present in the literature evidencing the use of placement services, including internships and cooperative

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139 agreements, as a direct strategy to improve the overall success of a college wide student demographic, there are examples where those approaches have significantly impacted a specific program of study or division. aunched a three part program to address its waning enrollment trends (Koch & Kayworth, 2009). The program engaged in a series of activities designed to specifically focus on student recruitment, retention, and placement to support both short term and long term gains in student enrollment. Within the area of graduate placement, department staff strategically focused on both job coaching for students, as well as relationship building with potential employers (Koch & Kayworth, 2009). These activities were targ eted for a degree program with very positive job market and employment potential; however, the administration and faculty realized that students were not making those connections on their own. They were struggling to recruit new students and current studen ts were not persisting at desired levels. As a result, the program experienced a 293% increase in enrollment (Koch & Kayworth, 2009). Another example is the Northern Michigan University Freshman Fellowship Program, which implemented the use of research pla cement experiences as a strategy to improve student recruitment and retention (Wozniak, 2011). Evaluation of the NMU student cohorts from 2006 2010 revealed that while the program did not have a significant impact on student recruitment, it did have a posi tive, significant impact on student retention and graduation (Wozniak, 2011). These programs serve as examples of the impact placement programs have on student completion.

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140 The presence of programs that build an education to work connection is perhaps even more important for rural students than for their suburban and urban peers (Hutchins & Akos, 2013). In their comparison of school to work programs across geographic context, Hutchins and Akos (2013) found that while rural institutions are more likely to ha ve vocational internship and placement programs available, rural students are less likely to be able to access placement programs for academically oriented programs of study. Given the lack of career exposure, geographic limitations, and higher probability of being low income and FGIC, school to work programs are even more crucial for rural students (Hutchins & Akos, 2013). Beyond the impact placement services have on rural student perceptions of education and the connection to their long term goals, there is also evidence that these programs fundamentally impact the student learning process. In her qualitative analyses of student perceptions of experiential learning, Cooper (2013) found that participating in gave participants a strong scaffold on which to build from the foundation knowledge imparted in the classroom and enabled (p. 297). Placement programs have also been evidenced to have a directly pos itive impact on the institution. In his study of comparable university programs, Weible (2010) found that the presence of internship and placement programs resulted in an increase in the number of graduates starting their own businesses, stronger community connections, improved institutional reputation, and enhanced student recruitment. Connection b etween Campus Services and Academic Success This study suggests that three key campus services distance education options, weekend and evening course schedule s, and placement services for

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141 completers strongly correlate to higher levels of rural minority student success. Results place these three services above a wealth of other supports commonly offered by colleges and universities, including remedial educatio n, academic and career counseling, employment services, and even campus based child care. This is not to imply that the other services and support efforts should be discontinued, but rather which services should be added to achieve the highest levels of mi nority student success in a rural context. The existing literature on rural and minority students provides a valuable foundation for interpreting these findings. Laskey & Hetzel (2011) proposed that the unique psychosocial development of rural students sh apes how those students interact with and interpret the campus environment, and therefore, rural institutions must provide tailored programming (Castenada, 2010; Corley, Goodjoin, & York, 1991). In order to really understand why specific campus services ha ve the greatest impact on rural, minority students, college and university administrators should go beyond traditional indicators of academic success, such as grade point average, courses, and test scores, and instead, look at rural family and social const ructs. Studies have evidenced that rural youth present a strong pattern of self limiting behavior driven by a need to remain geographically close to their nuclear family (Demi, Jensen, & Snyder, 2010). They have also been found to have a strong deference to the perceptions and desires of the older generations in their familial and social circles (Demi, Jensen, & Snyder, 2010). Studies have found the for rural youth, leaving the community, or even aspiring to do so, is often viewed as abandoning the family and breaking those generational bonds that are held in such high esteem within the rural

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142 community structure (Farmer et al., 2006; Ali & McWhirtier, 2006; Freeman, Conley, & Brooks, 2006). Flexible course delivery options, such as distance education and we ekend and evening courses provide options for rural students struggling to balance their strong family and community bonds with pursuit of an education career. Distance education makes education accessible without the need to break geographic ties. Weekend and evening course schedules give students attempting to balance a commitment to family needs with their education. valuable in interpreting the correlation between student success and placement services. Studies have indicated that it is common within poor, rural communities which often have different definitions of success (Ali & McWhirtier, 2006; Farmer et al., 2006). Whereas higher education often equates to a measure of success in suburban and urban communities, poor, rural families often push employment and a financial contribution to the family as the ultimate goals (Ali & McWhirtier, 2006; Farmer et al., 2006). Stern (2010) proposed that the key factor in developing a in the low income, rural regions is by emphasizing success. The findings from this study support those previous works. There exists a definitive relationship between placement services for completers and academic outcomes (graduati on and completion) for rural minority students. By offering a campus based service which directly connects earning a degree or credential and placement in employment, colleges and universities are possibly able to help rural minority students synthesize th eir familial and social pressures with educational opportunity.

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143 Impact of Institutional Attributes in a Rural Context MSI status, the presence of minority faculty, flexible course scheduling options (evening and weekend courses and distance education opti ons), and placement services for graduates were evidenced to have a significant relationship to higher levels of minority student enrollment and completion. The results of this study conflict with the proposed hypothesis that no institution attributes wou ld correlate to higher minority student academic outcomes (graduation and completion) in rural institutions. Findings indicate that there is a strong relationship between the presence of minority faculty and minority student enrollment and completion acros s all three geographic contexts. Additionally, MSI status was also found to positively correlate to increased levels of minority student enrollment and completion. Targeted funding was not found to have a positive relationship to any of the minority studen t academic outcomes evaluated. None of the institution attributes were found to positively correlate to increased graduation rates for rural minority students. Results of this study largely support the existing body of literature regarding minority studen t success in higher education. Minority students thrive in a minority inclusive campus environment (Hrabowski, Maton, & Greif, 1998; Chang, 2005; Museus, 2008; Orozco, Alvarez, & Gutkin, 2010). MSI status, in particular being a HBCU or tribal college, was found to have a significant positive relationship to rural minority student enrollment and completion In addition to MSI status, as the percentage of minority faculty increased, so did the minority enrollment percentage and the number of minority complet ers. In contrast, as the percent of minority faculty increased, the minority student graduation rate declined. This contrast follows the same pattern as

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144 evidenced for the other variables presenting a strong relationship to rural minority enrollment and com pletion. Implications for Practice While models of success for serving low income, FGIC students have received substantial attention in the literature, the impact of geographic context often goes unmentioned; yet, geographic context bears a strong connect ion to both the culture of the institution and the nature of the students it is most likely to serve. In contrast with much of the current literature which presents research on the impact of programs and services on various categories of disadvantaged stu dents, this study presents three key recommendations for serving those disadvantaged students within the environmental developmental ecology (Evans et al.), development is a function of the interaction of the person and the environment recommendations regarding the relationship of rural minority students and the environmental factors they commonly interact with in the college campus environment. First, colleges and universities serving rural, minority students can work to offer flexible course scheduling options geographical ties and a connection with the nuclear family. Whi le this study specifically evaluated undergraduate distance education and evening and weekend courses, there are certainly other options which colleges and universities may want to explore. Most likely, the more options available, the more probable it will be that these students will enroll and complete their programs of study. It is advisable that t his flexibility go beyond the mere physical course scheduling and permeate the culture of the institution. By recognizing the conflict many of these students mu st navigate to synthesize their

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145 educational plans with familial and social perceptions, the institutions are more likely to help students bridge those issues and complete their program of study. Second, rural serving institutions can explore building str ong connection s between their educational programs and the local job market. Results of this study evidence a strong link between rural minority student graduation and completion with placement services for completers. In fact, placement services was the o nly campus service included in this study with a positive correlation to minority student graduation rates, which builds a strong case for expanding the prevalence of placement services. Building a solid connection between the educational programs and dir ect employment is evidenced to help students better navigate those pressures to enter the job market and contribute to the family unit. The literature evidences a strong connection between the rural community job market context and success of rural student s. While a strong connection between the job market and education options is being recommended, that recommendation must be contextualized within the limitations that the rural job market may present. By building strong connections with the local job marke t and specifically targeting promising employment sectors within their local geographic region, this approach may also quell fears of human capital loss and severing family ties which have been documented in the literature as a growing concern for rural co mmunities. Third, rural colleges and universities must work to really foster inclusive campus environments that promote an expectation of excellence from their minority student populations. For example, in their study of ethnic student alienation at a pre dominantly white university, Loo and Rolison (1986) found that when minority students observed a

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146 lack of services and activities specifically tailored to them, they equated it to lack of support. Feelings of sociocultural alienation outpaced other factors in leading to lower minority student persistence (Loo & Rolison, 1986). They found that through campus based efforts such as residential learning communities, strong student support services, minority faculty, academic supports, and efforts to counteract n egative racial identity, those feelings of alienation could be overcome even in a predominantly white university environment (Loo & Rolison, 1986). It is important to note, however, that the pathway to fostering a minority inclusive campus environment should be expected to vary from one institution to another, given the interaction between the students, the campus, and the larger community. As administrators take steps to create a more minority inclusive campus environment, it will be important for them to contextualize those efforts and evaluate their impact within the larger context of the institution and surrounding community. While this study specifically validated the relationship between minority student outcomes and the presence of minority facul ty, it also recognized that the literature presents a strong case as to the obstacles rural colleges often face in recruiting and retaining minority faculty. If developing a diverse faculty is identified as a key factor in promoting rural minority student success, then there is a strong case to equip rural college administrators with more tools to make that happen. Possibilities include flexibility in salary and benefits packages that meet market rates, making positions at rural colleges more attractive to faculty at urban institutions. In addition to more competitive salary structures, rural college administrators may need the ability to negotiate more freely with candidates. Rural college may also want to consider other

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147 avenues that can be attractors to fa culty, such as dual career hiring initiatives. A key factor in the faculty recruitment processes may also be the investment by those institutions in seeking out racially and ethnically diverse faculty through connections to universities. The evidence supp orting diversity within the faculty can certainly be extended to other campus attributes that would provide a comparable support for the students. The presence of minority faculty, particularly in relationship to rural minority students, provides those stu dents with access to role models and mentors that they may not be readily able to access through other avenues in their communities. The literature has documented that one of the key factors impacting nontraditional rural student populations is the lack of access to diversity, most specifically in respect to role models. Given that rural institutions may not have the same ability to recruit and hire minority faculty as their suburban and urban peer institutions do, it is critical that they explore other ave nues. Minority student organizations have been found to be valuable assets in both facilitating the transition to college life for minority students and supporting their own cultural validation process (Museus, 2008). Rural colleges should also explore m entoring initiatives as another avenue to help their minority student population foster relationships with role models. In cases where the number of minority faculty and staff are not sufficient to really connect with their minority student population, com munity mentoring projects can be a valuable tool to help at risk students build connections with role models. Examples of such projects are at Santa Fe College in Gainesville, Florida (J. Sasser, personal communication, August, 2010) an d the BOSS Male Mentoring Program at Roanoke

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148 Chowan Community College in Ahoskie, North Carolina (Ruffin Barnes, W., Elam, M., & Kwasikpui, T., 2014) Figure 5 1. A new model for supporting rural minority students Administrators at rural colleges and universities must take steps to actively foster a minority inclusive campus culture. All of the recommended additions to the campus meso system indicated in Figure 5 1 are only po ssible through administrator action. Student Services Mentoring Tailored Advising Student Activities Racial/Ethnic Student Organizations Academics Remedial Services Education Work Connection Placement Services Coops & Internships Education to Work Connection Flexible Course Formats Weekend/Eve Courses Distance Education Options New Rural College Meso System Supportive of Minority Student s

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149 While increasing the numbers of minority faculty and staff may not always be feasible as is evidenced in the literature, the other recommended changes are possible through strategic planning, budgeting, and reallocation of resources. Policy Recommendations Assessment and Accountability. Higher education, and community colleges in public understanding about the function and operation s of public colleges and universities while affirming the significance of the great variety of approaches and (Voluntary System of Accountability Program, 2011). As evidenced by the findings of this study, traditional mea sures of higher education institutional effectiveness, such as basic enrollment, retention, and graduation rates, may not be the most effective means of measuring institutions that serve large populations of nontraditional students. For those who enter hig her education academically under prepared, or who are FGIC, low income, or socially or racially dis engaged from the campus community, degree completion within the traditional time parameters may not be achievable. The Voluntary Framework of Accountabilit y (VFA) metrics proposed by the American Association of Community Colleges (AACC) pushes a new approach to measuring community colleges. The VFA position is that when looking to assess community colleges, graduation rates really provide very little informa tion (American Association of Community Colleges, 2012). The AACC proposes three spheres of assessment: Student Progress and Outcomes; Workforce Economic, and Community Development; and Student Learning Outcomes (AACC, 2012). The AACC approach to assessing student success uses a cohort tracking approach that includes both two year

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150 and six year measures of student progress towards completion of a degree, certificate, or other credential, which allows a much more generous time period for non traditional and d isadvantaged students to finish their educational plans (AACC, 2012). The Voluntary System of Accountability (VSA) sponsored by the Association of Public and Land Grant Universities and the American Association of State Colleges and Universities offers co lleges and universities an alternative to the federal graduation rate in measuring undergraduate student success and progress (Voluntary System of Accountability, 2013). In the VSA model, participating institutions report cohort progress at four year, five year, and six year marks for enrollment, graduation, transfer and income, FGIC, veterans, and other special populations (VSA, 2013). W hile the VSA clearly proposes a more robust and holistic approach to assessing student success, those traditional degree completion timeframes still form the foundation of its model. As colleges and universities diversify their student populations to inclu de more low income, FGIC, and minority students, it may become more appropriate for those institutions to embrace an assessment model more similar to that proposed by the AACC. Funding. There is precedent within the current approach to higher education fu nding programs to allocate targeted funding streams for special institution classifications that have been identified as disadvantaged. The Title III Strengthening Institutions program allocates a percentage of its annual funds for tribal and Alaskan nativ e serving institutions. Title V funding is solely dedicated to special projects and initiatives at Hispanic serving institutions. Additionally, HBCU and HSI status are

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151 frequently targeted as priority institutions throughout other Department of Education fu nding programs. Given their significant difference in student success outcomes, particularly with minority student groups, rural institutions also present a case for receiving targeted funding designed to strengthen their ability to serve students. Anothe r point of potential concern for rural colleges is the move towards state funding models that include a performance component. For example, Florida is currently evaluating implementation of a funding platform that will include a portion of institution fund ing based upon achievement of student performance measures. The Florida model does not equate performances based on peer institution status, but rather a statewide benchmark which pits vastly different institutions against one another in a competition for funding. Based upon the findings of this study, there is evidence to validate geographic context as a factor in determining institution groupings. Suggestions for Further Research This study presents preliminary findings that will hopefully spur a wealth of future research on institution attributes that best support minority students as well as differences in student success across geographic context. There are a number of specific areas in which the current literature regarding minority student success ca n be expanded. This study utilized aggregate, institution level data regarding factors that correlate to minority student success; however, before an effective model of minority student support can truly be established, I recommend further research, both qualitative and quantitative, that pairs student level success data with the identified campus based services and support programs. The theoretical framework for this study views the campus environment as an interaction of many ecological layers, making it impossible

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152 to simplistically view the impact of one layer without considering the greater institution and community environment. Gaining more holistic knowledge of how students interact with those factors in their respective micro meso and exo systems will generate a replicable model. In similar fashion, I also recommend further qualitative and quantitative research regarding the factors that create a minority inclusive rural campus environment. PWI rural campuses are the entry point for countless rura l, minority students. Evidence of effective campus based interventions to create a more diverse and minority student friendly campus culture will better position those institutions to serve a broader student demographic. Because this study used institutio n level student success data based upon racial demographic groupings, low income and FGIC students were not disaggregated. The literature provides ample evidence as to the disadvantages those student populations face in higher education, as well as the sub stantial overlap between the low income, FGIC, and minority student classifications. Therefore, I recommend further research that disaggregates those special populations especially with regard to low income status, within the minority student demographics in an effort to gain greater insight as the best interventions and campus based support programs. In addition to understanding trends within the different sub classifications of students, given the strong body of evidence in the literature regarding the u nique rural student psychosocial development and strong connection with the nuclear family unit, further research is needed regarding successful approaches to fostering family support and involvement with the educational process. Conclusion As higher education moves forward with efforts to meet the looming national agenda to rapidly increase the number of graduates at all postsecondary levels, valid

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153 approaches for enrolling and retaining nontraditional students will become increasingly more i mportant. These results generate a body of evidence that can be used to develop a greater understanding of both the factors that support rural, minority students and how colleges can best structure their services and programs to help these students succeed This study builds upon the previous body of research regarding student success by recommending a new model of campus services for supporting rural minority students. This new model recommends rural colleges offer an academic platform that embraces flexib le course formats, builds a strong education to work connection, and promotes student activities and student services that embrace diversity.

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154 APPENDIX A SUMMARY OF FACTORS WITH POSITIVE RELATIONSHIP TO MINORITY STUDENT SUCCESS Dependent Variables HBCU Tribal HSI Undergrad Distance Ed Wknd/Eve Classes Remedial Academic Counseling Employment Services Placement Services Day Care Minority Faculty SSS Grant Title III Grant Title V Grant Enrollment Urban Minority X Urban Black X X X Urban Hispanic X X Suburb Minority X X Suburb Black X X X X Suburb Hispanic X X X X Rural Minority X X X X X Rural Black X X X X X Rural Hispanic X X X Graduation Urban Minority X X Urban Black X Urban Hispanic Suburb Minority X X Suburb Black Suburb Hispanic X X X Rural Minority Rural Black X Rural Hispanic Completion Urban Minority X X X X Urban Black X X X X Urban Hispanic X X Suburb Minority X X X Suburb Black X X X Suburb Hispanic X X X Rural Minority X X X X X Rural Black X X X X X X Rural Hispanic X X X

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155 APPENDIX B SUMMARY OF FACTORS RELATED TO HIGHER GRADUATION RATES Variable Overall Graduation Black Graduation Rate Hispanic Graduation Rate MSI Status Tribal College HBCU HSI Status Campus Services Distance Education Weekend & Evening Courses Remedial Services Academic & Career Counseling Employment Services Placement Services for Graduates On Campus Day Care Faculty Percent of Minority Faculty Funding SSS Grant Title III Grant Title V Grant

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156 REFERENCE LIST Ali, S.R. & postsecondary aspirations: Applying social cognitive career theory. Journal of Career Development, 33 (2), 87 109. American Association of Community Colleges. (2012). VFA Measures Snap shot Retrieved January 10, 2014 from: http://vfa.aacc.nche.edu/Documents/VFAMeasuresSnapshot.pdf Aylesworth, L. S., & Bloom, B. L. (1976). College experience and problems of rural and small town students. Journal of College Student Personnel, 17 236 242. Barbatis, P. (2010, Spring). Underprepared, ethnically diverse community college students: Factors contributing to p ersistence. Journal of Developmental Education, 33 (3), 14 24. College Students. Journal of College Student Retention: Research, Theory & Practice 8 (2), 199 214. Blan chard, R., Casados, F., & Sheski, H. (2009). All Things to All People: Challenges and Innovations in a Rural Community College. Journal of Continuing Higher Education 57 (1), 22 28. Budge, K. (2010). Why Shouldn't Rural Kids Have It All? Place conscious Leadership in an Era of Extralocal Reform Policy. Education Policy Analysis Archives. Carnegie Foundation for the Advancement of Teaching. (n.d.). The Carnegie Classification of Institutions of Higher Education Retrieved January 20, 2014 from: http://classifications.carnegiefoundation.org/ Casteneda, C. (2010). Transfer rates among students from rural, suburban, and urban community colleges: What we know, don't know, and need to know. Commu nity Colelge Journal of Research and Practice 26 439 449. Chang, J. C. (2005, November). Faculty student interaction at the community college: A focus on students of color. Research in Higher Education, 46 (7), 769 802. Cohen, A. M., & Brawer, F. B. (2 008). The American Community College. San Francisco, CA: Jossey Bass. Corley, E. R., Goodjoin, R., & York, S. (1991). Differences in grades and SAT scores among minority college students from urban and rural environments. High School Journal 173 177.

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162 BIOGRAPHICAL SKETCH Lindsay Lynch earned a Bachelor of Arts degree from the University of Florida in May, 1999. She rec eived a Master of Education in c urriculum and i nstruction from the University of Florida in December, 2009. Throughout her graduate studies at the University of Florida, Lynch was employed at South Florida State College. She graduated with a doctorate in higher edu cation administration from the University of Florida Institute of Higher Education in May, 2014. She is Director of Grants D evelopment at Sout h Florida State College.