THE EFFECTS of EARLY, REGULAR, and LATE REGISTRATION on STUDENT SUCCESS in COMMUNITY COLLEGES by MARGARET ANN STREET, B.S., M.A

THE EFFECTS of EARLY, REGULAR, and LATE REGISTRATION on STUDENT SUCCESS in COMMUNITY COLLEGES by MARGARET ANN STREET, B.S., M.A

THE EFFECTS OF EARLY, REGULAR, AND LATE REGISTRATION ON STUDENT SUCCESS IN COMMUNITY COLLEGES by MARGARET ANN STREET, B.S., M.A. A DISSERTATION IN HIGHER EDUCATION Submitted to the Graduate Faculty of Texas Tech University in Partial FulfiUment of the Requirements for the Degree of DOCTOR OF EDUCATION Approved Accepted August, 2000 Copyright 2000, Margaret Ann Street ACKNOWLEDGMENTS I am deeply grateful to the members of my committee, especially my co- chairmen. Dr. Albert Smith patiently provided guidance and encouragement throughout the project. Dr. Arturo Olivarez provided much needed assistance with the statistical analysis. To my friends and colleagues at the college, go many thanks. Your "nagging" encouragement was much needed and appreciated. Special thanks are extended to Tracy Hilliard for the help using SPSS, and to Chuck Everett for the assistance with data collection. I owe everything to my parents. Their love of learning has inspired me throughout my life. Without their support and encouragement, I could never have reached this milestone in my own education. u TABLE OF CONTENTS ACKNOWLEDGMENTS ii ABSTRACT vi LIST OF TABLES viii LIST OF FIGURES x CHAPTER L INTRODUCTION 1 Conceptual Framework 3 Problem 4 Purpose 5 Research Questions and Hypotheses 5 Need for the Study 7 Delimitations 10 Limitations 10 Assumptions 11 Definition of Terms 11 Organization of the Dissertation 13 IL REVIEW OF LITERATURE 15 Introduction 15 Models for Predicting Student Success and Retention 15 The Input-Environment Outcomes Model 17 m Summary of I-E-O Model 20 Student Success and Retention Variables 21 Input and Environmental Variables 22 Outcome Variables 27 Summary of Variables Used in the Study 28 Registration 29 Policies and Practices 29 Late Registration 31 Problems Associated with Late Registration 32 Studies Concerning Early, Regular, and Late Registrants 33 Summary 40 IIL METHODOLOGY 41 Introduction 41 General Research Design 41 Description of Variables 42 Sample 43 Collection of Data 45 Analysis of Data 45 Sunmnary 48 IV. FINDINGS 49 Introduction 49 Sample 50 iv Differences Between New Student Registration Groups 54 Differences Between Returning Student Registration Groups 58 Summary of Major Findings 64 V. SUMMARY, MAJOR FINDINGS, DISCUSSION, RECOMMENDATIONS, AND CONCLUSIONS 66 Summary 66 Major Findings 68 Discussion 70 Discussion of Academic Dependent Variables 70 Discussion of Retention Dependent Variables 74 Recommendations for Future Policy and Practice 77 Recommendations for Further Research 79 Conclusions 81 REFERENCES 83 APPENDICES A. REQUEST FOR STUDENT DATA 88 B. CODING OF DATA 91 C. PARTIAL LIST OF DATA 93 ABSTRACT Student success is a critical issue in higher education. Using the input- environment outcomes assessment model of Astin (1993), the main problem of this study was to determine whether or not early, regular, and late registration students differed from each other in terms of their academic success. This study had three purposes. The first purpose was to determine the differences between students enrolling during the three phases of registration (early, regular, and late) in a two-year college. A second purpose was to suggest late registration policy and practices that might improve student success. The third purpose was to make research recommendations for further study in the area of late registration. Registration time, academic records, and demographic information were collected from a stratified random sample of students at one community college in the fall of 1998. Students were grouped according to type (new and returning) and registration time (early, regular, and late). The sample consisted of 86 new students (55 regular and 31 late registrants) and 165 returning students (55 from each phase of registration). Analysis of covariance and chi-square tests were used to analyze the data. The major findings were as follows. For both new and returning students, late registrants were shown to be much less likely to persist to the spring semester than were early (returning students only) or regular registrants. VI Of the new students, 80% of regular and 35% of late registrants were retained to the next semester. For returning students, 80% of early, 64% of regular, and 42% of late registrants were retained. Differences in withdrawal rates were also significant for both new and returning students. New students who registered on time (regular) withdrew from 10% of their course hours while those who registered late withdrew from 21%. For returning students, early registrants withdrew from 5% of their course hours, regular registrants withdrew from 4%, and late registrants withdrew from 13%. Returning students also differed significantly in their semester grade point average (GPA) and their successful completion rate based on their time of registration. Early registrants earned a fall semester GPA of 3.48 and successfully completed 96% of their course hours. Regular registrants earned a GPA of 3.33 and successfully completed 91 % of their course hours. Late registrants earned a GPA of 2.69 and successfully completed 74% of their course hours. Policy and practice recommendations were made based on these findings. The researcher concluded that the practice of late registration is a deterrent to both academic success and retention of students. vu LIST OF TABLES 1. Description of Variables 46 2. Comparison of New Student Samples and Population Selected Demographic Characteristics 52 3. Comparison of Returning Student Samples and Population Selected Demographic Characteristics 53 4. Results of ANCOVA for New Students Withdrawal Rates by Registration Time with Age and Term Hours 55 5. Frequency Table Showing Persistence of Regular and Late Registration New Students 55 6. Results of ANCOVA for New Students Term GPAs by Registration Time with Age and Term Hours b7 7. Results of ANCOVA for New Students Successful Completion Rates by Registration Time with Age and Term Hours 57 8. Results of ANCOVA for Returning Students Semester GPAs by Registration Time with Cumulative GPA and Term Hours 60 9. Results of ANCOVA for Returning Students Successful Completion Rates by Registration Time with Cumulative GPA and Term Hours 60 10. Results of ANCOVA for Returning Students Withdrawal Rates by Registration Time with Age and Term Hours 62 11. Frequency Table Showing Persistence of Early, Regular, and Late Registering Returning Students 63 12. Significant Variables Found by Testing the Hypotheses 65 13. Comparison of New Student Dependent Variables by Registration Time 69 14. Comparison of New Student Dependent Variables by Registration Time 69 vm 15. Coded Values for Categorical Variables 92 16. Partial List of New Student Data 94 17. Partial List of Returning Student Data 95 IX LIST OF FIGURES 1. Astin's I-E-O Assessment Model 4 2. The I-E-O Model 17 CHAPTER I INTRODUCTION Student success is a major concern of higher education institutions for a variety of reasons. According to the Commission on Colleges (1995) of the Southern Association of Colleges and Schools, "effectiveness in all educational programs, delivery systems, and support structures should be the primary goal of every institution" (p. 21). Student pass rates are often a component of assessments of institutional effectiveness (Alfred, Kreider, & McClenney, 1994). Faculty and program evaluations also make use of student pass rates. Another growing concern is the stronger push for accountability for community colleges (Parnell, 1990). "A fiscally conservative political climate at local, state, and federal levels has left many conmiunity colleges without adequate funds. It has also left the institutions under the gun to be far more accountable for the money they spend'' (Schmidt, 1998, p. A37). The impetus for performance-based funding seems to be grow^ing. ''Right now, 11 states tie some appropriations to measures of public institutions' performance, and 15 more are likely to follow suit within the next five years, according to state officials and policy analysts" (Carnevale, Johnson, & Edwards, 1998, p. B6). Retention rates are widely used as an indicator of institutional performance (Wyman, 1997). Graduation rate is still another performance indicator used by South Carolina's 1996 law which created a performance-based system for financing public education (Schmidt, 1997). Therefore, student success in terms of pass rates takes on critical accreditation, accountability, and financial importance for many institutions of higher education. Community colleges typically do not require college entrance exams. Students who earned a general equivalency diploma (GED) are admitted equally with high school graduates (Undergraduate admissions..., 1980). Individuals may also be admitted to many two-year colleges without a GED or high school diploma if they have demonstrated "reasonable potential for success" (Commission on Colleges, 1995, p. 23). This open door policy leads to a diverse student body that is, in general, less prepared to complete college level courses (Warren, 1985). For these reasons, it is vital that any policy that may impede student success be examined and revised if necessary. There is a general feeling among community college faculty, counselors, and administrators that students who register late do not do as well in their classes and tend not to complete their coursework (Roueche & Roueche, 1994a; Sova, 1986). If this is indeed true, then the late registration policies of institutions of higher education need to be reevaluated. There are two rationales

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