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J ."x "1 " r'r ' f".¢t"' ¢ 0 K". . aIW o . vol", Ht "a IIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIII Illlllllllllll‘lll‘lliJl’JllHIlHilllll I‘I‘JI l'l Will 3 1293 00562 15 This is to certify that the dissertation entitled A COMPARISON OF LEVELS OF SATISFACTION TO SELECTED DEMOGRAPHIC VARIABLES FOR STUDENTS AT HENRY FORD COMMUNITY COLLEGE presented by Gwendolyn D. Watts-Pringle has been accepted towards fulfillment of the requirements for Ph. 0. degree in Educational Administration M 5-1/4 MS U is an Affirmative Action/Equal Opportunity Institution 0- 12771 MSU LIBRARIES RETURNING MATERIALS: Place in book drop to remove this checkout from your record. FINES will be charged if book is returned after the date stamped below. A COMPARISON OF LEVELS OF SATISFACTION TO SELECTED DEMOGRAPHIC VARIABLES FOR STUDENTS AT HENRY FORD COMMUNITY COLLEGE By Gwendolyn D. Natts-Pringle A DISSERTATION Submitted to Michigan State University in partial fulfillment of the requirements for the degree of DOCTOR OF PHILOSOPHY Department of Educational Administration 1988 ABSTRACT A COMPARISON OF LEVELS OF SATISFACTION TO SELECTED DEMOGRAPHIC VARIABLES FOR STUDENTS AT HENRY FORD COMMUNITY COLLEGE By Gwendolyn D. Hatts-Pringle The purpose of this study was to identify selected demographic and academic characteristics of the student population at Henry Ford Community College and to identify further any differences among various groups and types of students in order to better understand the varying degrees of successes, problems, and attitudes that these students had encountered at the institution. The central question was: Is there a significant difference between technical students and liberal arts students? Ten hypotheses were tested to determine whether there were significant differences between technical and liberal arts students on 16 demographic attributes, reasons for attending a two-year college, quality of education, 18 college services, 11 aspects of the college, 5 recruitment activities, l5 student-focused activities, and 9 conditions dealing with the college. The survey instrument that was selected for data collection, the Student Opinion Survey, was developed by the American College Testing Program. The data were analyzed for each variable listed under each Gwendolyn D. Hatts-Pringle hypothesis. The mean for the technical-student group was calculated and compared to the mean for the liberal-arts-student group. Both chi-square and t-test were applied on certain hypotheses. The results of this study revealed that on six out of the ten hypotheses a statistically significant difference was found between liberal arts and technical students at Henry Ford Community College. The six areas in which the groups differed significantly were related to demographic attributes, reason for attending a two-year college, academic aspects of the college, recruitment activities, student-related activities, and conditions related to student interaction within the college environment. The four areas in which no statistically significant differences were found were for the variable quality of education at the college, 18 services offered at the college, 5 student-focused activities, and 4 conditions reviewed at the college. The data revealed that the overall level of student satisfac- tion needs to be further evaluated and improved. Copyright by GWENDOLYN D. NATTS-PRINGLE 1988 ACKNOWLEDGMENTS Dr. Kenneth Harding, the chairman of my committee, made a lasting contribution to the fulfillment of my educational goal and my academic growth and development. His support and encouragement will be with me forever. My deepest appreciation to Drs. Louis Hekhuis, Gloria Smith, and James Snoddy for their support and successful guidance. A very extra special thank-you to Dr. Stuart Bundy, President of Henry Ford Community College, Dr. Michael Meade, and Gerald Olszewski for the opportunity and support to conduct this research at the College. To my family and friends, who have always believed in me, I am very grateful. In particular, I am forever indebted to my mother, Lizzie, my father, Sam, and my sister, Gloria. To my daughter, Kenya, who has always been there for me, I pass on the fire of desire to achieve even higher goals and all my love for her understanding when the times were hard. To the men of Kappa Alpha Psi at 269 Erskine in Detroit, who provided me with a wonderful social outlet every Friday night during the writing stage of my dissertation, a very important thank-you. Last but not least, to my Creator, I sing a very special praise of thankfulness. TABLE OF CONTENTS LIST OF TABLES ....................... Chapter I. INTRODUCTION .................... Need for the Study ................ Importance of the Study .............. Purpose of the Study ............... Hypotheses .................... Theory ...................... Limitation of the Study .............. Procedures of the Study .............. Definitions of Terms ............... Overview ..................... II. REVIEW OF THE LITERATURE .............. Introduction ................... Related Dissertation Studies ........... Evaluation of Dissertation Studies ....... Current Journal Articles ............. III. DESIGN OF THE STUDY ................. Introduction ................... The Sample .................... Characteristics of Henry Ford Community College . . Instrumentation .................. Reliability and Validity ............. Hypotheses .................... Data Collection .................. Data Analysis ................... Summary ...................... vi -l 0010501-4 IV. ANALYSIS OF THE DATA ................ 39 Introduction ................... 39 Results of Data Analyses ............. 39 Results of Hypothesis Tests ............ 113 Summary ...................... 126 V. SUMMARY, CONCLUSIONS, AND RECOMMENDATIONS ..... l27 Summary ..................... 127 Conclusions and Recommendations ......... 128 Hypothesis l ................. 128 Hypothesis 2 ................. l33 Hypothesis 3 ................. 135 Hypothesis 4 ................. 135 Hypothesis 5 ................. l35 Hypothesis 6 ................. l36 Hypothesis 7 ................. l37 Hypothesis 8 ................. 138 Hypothesis 9 ................. l39 Hypothesis 10 ................. 139 Final Thoughts ................. l40 APPENDIX .......................... 143 BIBLIOGRAPHY ........................ 147 vii LIST OF TABLES Table Page 1. Comparison of Technical Students to Liberal Arts Students on the Variable Age ............ 40 2. Comparison of Technical Students to Liberal Arts Students on the Variable Ethnicity ......... 41 3. Comparison of Technical Students to Liberal Arts Students on the Variable Purpose for Entering Henry Ford Community College ............ 43 4. Comparison of Technical Students to Liberal Arts Students on the Variable Overall College Grade Point Average .................... 45 5. Comparison of Technical Students to Liberal Arts Students on the Variable Gender ........... 46 6. Comparison of Technical Students to Liberal Arts Students on the Variable Marital Status ....... 47 7. Comparison of Technical Students to Liberal Arts Students on the Variable Number of Dependent Children ...................... 48 8. Comparison of Technical Students to Liberal Arts Students on the Variable Hours Per Heek Currently Employed ...................... 49 9. Comparison of Technical Students to Liberal Arts Students on the Variable Enrollment Status at Henry Ford Community College ............... 50 10. Comparison of Technical Students to Liberal Arts Students on the Variable Number of Years Attended Henry Ford Community College ............ 51 ll. Comparison of Technical Students to Liberal Arts Students on the Variable Type of Class Most Frequently Attended ................. 52 viii 12. 13. 14. 15. 16. 17. 18. 19. 20. 21. 22. 23. 24. 25. Comparison of Technical Students to Liberal Arts Students on the Variable Status Prior to Attending Comparison of Technical Students to Liberal Arts Students on the Variable Distance of Residence From Henry Ford Community College ........... Comparison of Technical Students to Liberal Arts Students on the Variable Financial Aid Recipient Comparison of Technical Students to Liberal Arts Students on the Variable Current Area of Study Comparison of Technical Students to Liberal Arts Students on the Variable Occupational Choice Comparison of Technical Students to Liberal Arts Students on the Variable Rating of College at Time of Application .................. Comparison of Technical Students to Liberal Arts Students on the Variable Importance of Locale . . . . Comparison of Technical Students to Liberal Arts Students on the Variable Importance of Courses Comparison of Technical Students to Liberal Arts Students on the Variable Importance of Low Cost of Attending ............. , ...... Comparison of Technical Students to Liberal Arts Students on the Variable Importance of Could Nork While Attending .................. Comparison of Technical Students to Liberal Arts Students on the Variable Good Vocational-Academic Reputation .................... Comparison of Technical Students to Liberal Arts Students on the Variable Liked the Social Atmosphere .................... Comparison of Technical Students to Liberal Arts Students on the Variable Liked the Size of the College ...................... Comparison of Technical Students to Liberal Arts Students on the Variable Good Chance of Personal Success ...................... ix Page 54 55 56 58 60 62 63 64 65 66 67 68 69 70 26 27. 28. 29. 30. 31. 32. 33. 34. 35. 36. 37. 38. . Comparison of Technical Students to Liberal Arts Students on the Variable Availability of Scholarship or Financial Aid ............ Comparison of Technical Students to Liberal Arts Students on the Variable Advice of Relatives or Parents ....................... Comparison of Technical Students to Liberal Arts Students on the Variable Advice of High School Counselor ...................... Comparison of Technical Students to Liberal Arts Students on the Variable wanted to Be With Friends Comparison of Technical Students to Liberal Arts Students on the Variable If Starting Over would You Attend This College? .............. Comparison of Technical Students to Liberal Arts Students on the Variable Impression of Quality of Education ...................... Comparison of Technical Students to Liberal Arts Students on the Variable Academic Advising/Course Planning ...................... Comparison of Technical Students to Liberal Arts Students on the Variable Personal Counseling Services ...................... Comparison of Technical Students to Liberal Arts Students on the Variable Vocational Guidance/Career Planning ...................... Comparison of Technical Students to Liberal Arts Students on the Variable Job Placement Services . . . Comparison of Technical Students to Liberal Arts Students on the Variable Financial Aid Services . . . Comparison of Technical Students to Liberal Arts Students on the Variable Recreational Programs and Services .................... Comparison of Technical Students to Liberal Arts Students on the Variable Library/Learning Resources Center ....................... Page 72 73 75 75 76 77 77 78 78 79 80 80 39. 40. 41. 42. 43. 44. 45. 46. 47. 48. 49. 50. 51. Comparison of Technical Students to Liberal Arts Students on the Variable Resident Hall Programs and Services Comparison Students Comparison Students Services Comparison Students Comparison Students of Technical Students to Liberal Arts on the Variable Student Health Services of Technical Students to Liberal Arts on the Variable Student Employment of Technical Students to Liberal Arts on the Variable Cafeteria/Food Services of Technical Students to Liberal Arts on Activities the Variable College-Sponsored Social Comparison of Technical Students to Liberal Arts Students on Activities the Variable Cultural Programs and Comparison of Technical Students to Liberal Arts Students on the Variable College Orientation Program ....................... Comparison Students Comparison Students Services Comparison Students Comparison Students Comparison Students Grading System of Technical Students to Liberal Arts on the Variable Computer Services of Technical Students to Liberal Arts on the Variable Parking Facilities and of Technical Students to Liberal Arts on the Variable Veterans Services of Technical Students to Liberal Arts on the Variable Day-Care Services of Technical Students to Liberal Arts on the Variable Satisfaction Hith Testing/ Comparison of Technical Students to Liberal Arts Stgdents on the Variable Course Content in Your Ma or ........................ xi Page 81 81 82 83 83 84 84 85 85 86 86 87 88 52. 53. 54. 55. 56. 57. 58. 59. 60. 61. 62. 63. Comparison of Technical Students to Liberal Arts Students on the Variable Out-of—Class Availability of Instructors ................... Comparison of Technical Students to Liberal Arts Students on the Variable Attitude of Teaching Staff Toward Students ................ Comparison of Technical Students to Liberal Arts Students on the Variable Variety of Courses Offered ....................... Comparison of Technical Students to Liberal Arts Students on the Variable Class Size Relative to Type of Course ................... Comparison of Technical Students to Liberal Arts Students on the Variable Flexibility to Design Your Program .................... Comparison of Technical Students to Liberal Arts Students on the Variable Availability of Your Advisor ....................... Comparison of Technical Students to Liberal Arts Students on the Variable Value of Information From Advisor ....................... Comparison of Technical Students to Liberal Arts Students on the Variable Challenge Offered by Your Program ....................... Comparison of Technical Students to Liberal Arts Students on the Variable Preparation You Are Receiving for Occupation .............. Comparison of Technical Students to Liberal Arts Students on the Variable General Admissions Procedure ...................... Comparison of Technical Students to Liberal Arts Students on the Variable Accuracy of College Information Received ................ Comparison of Technical Students to Liberal Arts Students on the Variable Availability of Financial Aid Information ................... xii Page 89 90 90 91 91 92 93 93 94. 95 96 64. 65. 66. 67. 68. 69. 70. 71. 72. 73. 74. 75. 76. Comparison of Technical Students to Liberal Arts Students on the Variable Assistance Provided by College Staff ................... Comparison of Technical Students to Liberal Arts Students on the Variable Catalog/Admissions Publications ................... Comparison of Technical Students to Liberal Arts Students on the Variable Rules Governing Student Conduct ...................... Comparison of Technical Students to Liberal Arts Students on the Variable Student Voice in College Policies ..................... Comparison of Technical Students to Liberal Arts Students on the Variable Academic Probation and Suspension Policies ................ Comparison of Technical Students to Liberal Arts Students on the Variable Purposes Student Activity Fees Used ..................... Comparison of Technical Students to Liberal Arts Students on the Variable Student Government . . . . Comparison of Technical Students to Liberal Arts Students on the Variable Classroom Facilities . . . . Comparison of Technical Students to Liberal Arts Students on the Variable Industrial Arts/Shop Facilities .................... Comparison of Technical Students to Liberal Arts Students on the Variable Business-Training Facilities/Equipment ............... Comparison of Technical Students to Liberal Arts Students on the Variable Laboratory Facilities Comparison of Technical Students to Liberal Arts Students on the Variable Athletic Facilities Comparison of Technical Students to Liberal Arts Students on the Variable Study Areas ....... xiii Page 96 97 98 98 99 99 100 100 101 102 103 103 104 77. 78. 79. 80. 81. 82. 83. 84. 85. 86. 87. 88. 89. Comparison of Technical Students to Liberal Arts Students on the Variable Student Community Center/ Student Union ................... Comparison of Technical Students to Liberal Arts Students on the Variable College Bookstore . . . . Comparison of Technical Students to Liberal Arts Students on the Variable Availability of Adequate Housing ...................... Comparison of Technical Students to Liberal Arts Students on the Variable General Condition of Buildings ..................... Comparison of Technical Students to Liberal Arts Students on the Variable General Registration Procedures .................... Comparison of Technical Students to Liberal Arts Students on the Variable Availability of Courses at Times Hanted ................... Comparison of Technical Students to Liberal Arts Students on the Variable Academic Calendar for This College ................... Comparison of Technical Students to Liberal Arts Students on the Variable Billing and Fee Payment Procedures .................... Comparison of Technical Students to Liberal Arts Students on the Variable Concern for You as an Individual .................... Comparison of Technical Students to Liberal Arts Students on the Variable Attitude of College Nonteaching Staff ................. Comparison of Technical Students to Liberal Arts Students on the Variable Racial Harmony at This College ...................... Comparison of Technical Students to Liberal Arts Students on the Variable College Media ...... Comparison of Technical Students to Liberal Arts Students on the Variable This College in General xiv Page 105 105 106 107 107 108 108 109 110 110 111 112 112 CHAPTER I INTRODUCTION We need to strengthen our nation by investing in our youth. The future of any country which is dependent upon the will and wisdom of its citizens is damaged, and irreparably damaged, whenever any of its children are not educated to the full extent of their talents, from grade school to graduate school. --President John F. Kennedy State of the Union Message, 1963 Need for the Study The American community college has evolved over five generations. According to Deegan and Tillery (1985), the fifth generation is in the process of evolving into a comprehensive community college. They indicated that the problem with accomplishing the mission of the comprehensive community college is that "carrying it out with excellence suggests that all of the basic functions that constitute the comprehensive community college must be done well." In other words, transfer programs, vocational programs, and remedial programs must work in an effective manner in order for students to actualize their goals within the comprehensive community college. During the decade from the 19705 to the 19805, the community college has attracted many nontraditional learners. These learners have not always just come out of high school. Many are employed either full or part time, whereas still others are making major career changes. Thornton (1972) stated that “American higher education will face shifting trends in enrollments and increased urgency of its recognized tasks.“ Reynolds (1969) stated that ”the effect of unanticipated environmental developments on junior college trends is extensive." He suggested forther that "the tremendous growth in the number of potential students seeking admission to college influenced many students to turn to junior colleges as an economical supplementation for solving their problem." That observation suggests that community colleges evolved out of existing educational problems, and, in turn, community colleges have taken pressure off of other traditional educational institutions. However, the problem is becoming greater now that nontraditional students have begun to seek and gain entry into community colleges. ’ Many traditional educational institutions such as high schools and universities are expecting the community college to deal with all students seeking admission who cannot be effectively served by traditional means. North and Hanson (1976) conducted a study on the outcomes of vocational-technical transfer programs by examining the educational and vocational status of students five years after enrollment. They reported the following results: Overall student ”consumers” think that their community colleges and vocational-technical schools provide valuable training experiences which, one might surmise, have indeed influenced their future. This study shows that the vast majority of those employed in program-related occupations are satisfied with their current jobs and would go through their programs again. (pp. 28-30) North and Hanson’s study revealed that community college students in program-related occupations were satisfied with their educational training. However, this is only one study. Much more of the literature has spoken to the shortcomings of the community college. Lombardi (1978) suggested: Community college educators exhibit a mild form of schi20phrenia. On the one hand they strive to achieve higher status for their institution, as do educators in other segments. (hi the other hand, in assuming such functions as adult basic education, remediation, and adult education, they attract low aptitude and functional illiterates, thereby lowering the status of the institution by bringing it closer to the high school from which they have been attempting to create a wide chasm. Bowen calls the latter a "double selection process" through which "some congruity is achieved between the characters of institutions and the characteristics of their students." (p. 32) Community college educators with a schizophrenic attitude relative to their student populations and their institutions must be able to deal effectively with the schizophrenia and develop a new attitude toward teaching both high and low achievers because, as Koltai and Thurston (1971) indicated, ”as early as 1969, California Colleges (State of California) enrolled 88 percent of the first- time-in-college students; Florida, 65 percent; and Michigan, 50 percent." With these types of percentages of first-time-in-college students enrolling in community colleges, community college educators have a tremendous responsibility to present an atmosphere that will promote positive acceptance for all students. Not only do community college educators have to make serious efforts to serve the considerable diversity of students, but the community college administrative leadership must support research programs that will reveal information about the characteristics of the diverse student population. O’Banion and Thurston (1972) suggested: Junior college personnel workers have another peculiar responsibility. They must be concerned about the growth and development of students from many backgrounds and with various levels of ability and attainment. Yet junior colleges no less than their four-year counterparts must be concerned with academic excellence. Due to the heterogeneity of the student body, this must be excellence in terms of the individual and not according to a standard norm. Each student must be given assistance in developing to his peculiar set of abilities and background. (p. 9) Not only do community college educators need to look at the particular learning needs of individual students, but there is a grave need for instructors and administrators to be versed in the characteristics of the entire student population. Much too often, educational programs are designed to promote improved academic success within the student population without any prior assessment of the needs and characteristics of that student population. Visgoski (1971) indicated that: Educators generally agree that the community junior college cannot fulfill its responsibility without a clear and factual understanding of its students. This understanding, however, is not easily achieved. The diversity of programs offered in the junior colleges attracts students of' such vastly different characteristics that it is difficult to portray a composite picture of the junior college student. It is essential, however, that community college staff members attempt to identify the characteristics of junior college students and to consider the implications these characteristics have for instructors and student personnel staff. (pp. 183-84) The American College Testing Program has developed a Two-Year College Form of the Student Opinion Survey, which assists community college personnel with student characteristics relative to (a) background information, (b) impressions of the college, (c) level of satisfaction with college services and programs, and (d) level of satisfaction with the college environment. In view of the rapid changes that have taken place within community colleges, it is important for each community college to assess its student population in terms of how satisfied the students are with the college environment. It is the responsibility of both the teaching faculty and the administrators to be able to discover the important characteristics of their student population so that plans and programs can be developed in relation to those characteristics. A community college atmosphere structured to accommodate its students, according to the identified characteristits of its students, has a much better chance of satisfying the overall mission of the community college. Importance of the Study It is important to identify the variables that students identify as being important factors that promote a high level of satisfaction within the college environment. It is equally important that a measurement be completed to determine if there are varying levels of satisfaction among different groups of students, such as technical versus liberal arts, on a number of variables. The higher the level of student satisfaction, the more likely it is that the college staff will find a greater percentage of students returning to the college, as well as a greater number of students accepting recruitment overtures. Identifying the students’ levels of satisfaction with college services and the college environment provides information on whether or not the present programs are meeting the needs of the students. This information, if used effectively, could improve student recruitment and continuation at Henry Ford Community College. Purpose of thg_§tpdy Raines (1971) observed that "a knowledge of the student population is vital to any research program that is concerned with the educational progress of the students." The purpose of this study was to identify selected demographic and academic characteristics of the student population at Henry Ford Community College and to identify further any differences among various groups and types of students in order to better understand the varying degrees of successes, problems, and attitudes that these students have encountered at their institution. Hypotheses The following ten hypotheses, stated in the null form, were tested in this research: Hypothesis 1: There is no difference between demographic attributes of the technical students and demographic attributes of the liberal arts students on the following 16 attributes: age ethnic identity purpose for entering a two-year college grade-point average gender marital status number of dependent children hours employed per week 3'40 'ht‘D 0.0 6"” current enrollment status years attended college of study type of classes most frequently attended pre-entrance academic history proximity to campus financial aid status current area of study occupational choice U 0 3 a dag-u...“ Hypothesis 2: There is no difference between response rates of liberal arts students and response rates of technical students concerning the following 13 reasons for attending a two-year college: convenience of location course offerings low cost ability for working while attending vocational or academic reputation social atmosphere size of college opportunity for personal success availability of scholarship or financial aid advice of parents or relative advice of high school professionals ability to be with friends rating of college at the time a druo-“3'SO "hm an 0"” Hypothesis 3: There is no difference between technical students’ responses and liberal arts students’ responses to the following questions: a. If you could start college over, would you choose to attend this college? b. What is your overall impression of the quality of edu- cation at this college? Hypothesis 4: There is no difference between levels of satis- faction of liberal arts students and levels of satisfaction of technical students with the following 18 services: academic advising personal counseling vocational guidance job placement financial aid recreational and intramural programs library/learning resources residence halls student health student employment cafeteria/food college-sponsored social activities cultural programs and activities a dfi'uo-‘oz'ta mm 0.0 0'” college orientation computer usage parking facilities veteran programs day care Hypothesis 5: There is no difference between levels of satis- faction of liberal arts students and levels of satisfaction of technical students with the following 11 academic aspects of the college: testing/grading course content in major area of study availability of instructors attitude of teaching staff variety of course offerings class size flexibility to design own program availability of advisor advisor input academic challenge of course of study preparation for chosen occupation 1.01303 ”Lu-04040 ‘hm 0.0 0"” Hypothesis 6: There is no difference between levels of satis- faction of liberal arts students and levels of satisfaction of technical students with the following five recruitment activi- ties: a. admission entry procedures b. information received before enrolling c. availability of financial aid information before enrolling d. staff assistance e college catalog/admissions information Hypothesis 7: There is no difference between levels of satis- faction of technical students and levels of satisfaction of liberal arts students with the following five student-focused activities: rules governing student conduct student government input on policies academic probation purposes for activity fees Hypothesis 8: There is no difference between levels of satis- faction of liberal arts students and levels of satisfaction of technical students with the following ten activities: a classrooms b. industrial arts/shop 3. business training equipment e (DQOO'N laboratory athletics study areas student center/union bookstore availability of adequate housing appearance of buildings and grounds Hypothesis 9: There is no difference between levels of satis- faction of liberal arts students and levels of satisfaction of technical students with the following four conditions: a. registration procedures b. availability of courses at convenient times c. academic calendar d. billing and fee-payment procedures Hypothesis 10: There is no difference between levels of satis- faction of liberal arts students and levels of satisfaction of technical students with the following five conditions: a concern for the individual b. attitude of nonteaching staff toward students 3. racial harmony ‘ e C—ac-I-a’ta -h college media general atmosphere M1 Educational institutions from early grades through higher education have demonstrated an increasing degree of interest in educational excellence and reform. If students are satisfied with their educational institutions, will they perform better? Does lack of satisfaction produce lower academic achievement? .Are dissatis- fied students going to continue to participate by continued enroll- ment, or will they drop out? How will an educational institution know if it is satisfying its clientele? Do educators need to know how to market such a valuable product as education? ’One author thought that it was about time to go to the consumers of education to get feedback. Soloman (1976) stated, Students have shown that they can contribute valuable insights to institutional problems. They can assist in the improvement of the curriculum; their judgments of teaching quality are IO usually valid; and they can participate in policy-making with restraint and dignity. (p. 115) The point that Soloman made clearly showed that students have something important to add to their educational institutions. Their participation must be present for any institution to be effective. There is a need to examine varying levels of satisfaction relative to selected demographic and academic variables for students at community colleges in order to evaluate the effectiveness of different college programs. One must go beyond just conducting a survey; one needs to evaluate the data and make recommendations that may have a positive effect on existing programs because of the results of those data. As a result of analyzing the data from the student opinion survey, one might find that liberal arts students may perceive significantly higher levels of satisfaction than technical students relative to class size, attitude of teaching staff, and so on. Or perhaps it might be found that the older returning students are experiencing a significantly lower level of satisfaction with library and learning resources. Collecting and analyzing student opinion information can serve as a starting point for investigating various problems at the educational institution. ijjtatipn of the Study This researcher identified specific characteristics of students I at Henry Ford Community College and how they differed among two student groups, technical versus liberal arts. Findings from this ll investigation are generalizable only to institutions having comparable size and student characteristics. Many researchers on the subject of retention have indicated that each college has to look at its own special characteristics in order to develop a system that meets its specific needs. However, the research data may be helpful in assisting community colleges to identify important variables that influence various academic directions for various types of students. Proc r f h The procedures of the study include method of data collection, population, sampling, instrumentation, and analysis of data. The method of data collection involved mailing 700 copies of the American College Testing Program Student Opinion Survey to degree candidates. Degree candidates were selected because they had been exposed to the various facets of the college for a maximum period of time and were considered to be in a better position to' evaluate their collegiate experience than were their underclass counterparts. The American College Testing Program developed a Student Opinion Survey (Two-Year College Form) so that two-year colleges might evaluate whether or not they are fulfilling their mission. This instrument was written up in The Ninth Mental Measurement Yeerppok (Mitchell, 1985). The following was indicated:' Available since 1979, the ESS is not one instrument, but, instead, a fairly extensive package of survey instruments and scoring services designed to assist educational institutions to gain a better understanding of their students and programs. The various components of the ESS are intended to be used 12 primarily to provide group-reported information to (and about) schools and colleges; they are not intended to provide information about individuals. As a result, in passing judgment on the ESS the psychometric criteria by which more traditional instruments are evaluated are not particularly important, and, in some cases, even inappropriate. (p. 37) The Student Opinion Survey (Two-Year College Form) was used to obtain responses from the target student population. The method of data analysis was that each variable listed under a hypothesis was analyzed. A mean for the technical-student population was calculated and compared to the mean of the liberal-arts-student population. A t-test was applied for any differences generated from the two-group comparison. The .05 level was the criterion for statistical significance. Definitions of Terms For the purposes of this study, the following terms are defined. Retention. The art of retaining students to continue enroll- ment in the same college. Continuedsenrollment. To enroll each semester without dropping out for short or long intervals. Student opinipn. A judgment or belief that is stronger than an impression but less firm than positive knowledge which is given by the students in attendance. Levels of satisfaction. The measuring of the differences in elevation of the state of being fulfilled and/or satisfied. 13 College environment. All the physical, social, and cultural factors and conditions influencing the growth and well-being of students within the college surroundings. Academic. Having to do with higher education; relating to liberal or classical studies, rather than vocational. Veeetional. Referring to a vocation or occupation that pertains to training in the development of skills required by different trades. Msion policy. The requirements for gaining entry into college. Full-time student. A student who has enrolled for at least the minimum number of credits to qualify for full-time status. Part-time student. A student who has enrolled fer less than the minimum number of credits to qualify for full-time status. Characteristics of the student pppulatipn. Showing the char- acter* or peculiar quality of the students within a particular college. QVQY‘V [EN The purpose of Chapter I was to provide an overview of the research study. In Chapter II, a review of pertinent literature is presented. The literature review includes current doctoral dissertation summaries and a review of journal articles dealing with community college issues. In Chapter III the design of the study is presented. Chapter IV reveals the results of the study. Finally, 14 Chapter V provides a summary and conclusions of the study, as well as recommendations for further research. CHAPTER II REVIEW OF THE LITERATURE Iptroductjpn This review of the literature is based on dissertation studies and current journal articles related to community college programs and policies. Many research studies as well as numerous journal articles have focused on student attrition rates at the community college level. These research studies and journal articles have suggested that certain external variables within the college environment when introduced will have an effect on remaining in school or dropping out of school. First, related dissertation studies that have addressed these external variables that influence enrollment trends are cited, followed by an evaluation of these studies and how they relate to the selected demographic variables and academic attributes of students at the community college level. Second, related journal articles are cited that have identified particular external variables that influence continuing in college, followed by an evaluation of these articles and how they relate to selected academic and demographic variables for students at Henry Ford Community College. 15 16 Related Qissertatjpn Stgdies Retention is not a new concept in educational institutions. Both teachers and administrators desire a favorable retention report because such a report would indicate that they are maintaining their enrollments. However, there is much alarm when enrollments drap. Pascarella (1985) made the point that Chickering (1969) "moves beyond a comprehensive literature review and proposes a general model of college impacts.” Pascarella went on to state that Chickering made the following observations: At least three major sources of variation in the socialization of college students need to be taken into account if one is to understand the effects of college: (1) the initial or pre- enrollment characteristics of students; (2) structural and organizational factors of the institution (e.g., enrollment, type of control, student faculty ratio, research emphasis); and (3) interactions between students and the primary agents of socialization on campus (i.e., faculty and students). (p. 640) Starting with the first of these three major sources, which is pre-enrollment characteristics of students, the pre-enrollment information may have an effect on persisters and learners. Kickels (1982) in her dissertation noted the following results: A personalized admissions program has the potential to offset possible enrollment declines in community college by encouraging students to persist in their academic aspirations. It is recommended that conmunity colleges consider such a recruitment and retention approach in their strategic marketing plans. (p. 8) ‘ Not only did Kickels support the idea that pre-enrollment characteristics of the student are an important issue; Powers (1982) in his dissertation revealed the following information: This descriptive study was the result of field observation, interviews and specific documentation of the evolution of procedural and policy changes occurring at Houston Community 17 College and relating to the following student retention strategies: (1) a review of retention-related institutional policy, (2) a renovated and expanded orientation procedure for new students, (3) a model scheduling process, (4) assessment of basic skills for new students, (5) a renovated registration process, and (6) implementation of a counseling advisement system. (p. 9) It is important to note that Powers observed the results of a renovated and expanded orientation procedure for new students and also observed the assessment of basic skills for new students. He further stated: The results of the study indicated that of the strategies implemented, the model scheduling process was the most effective. Although the attrition rates were reduced only slightly at each of the five campuses, the strategies were evaluated as being successful because of the qualifying fact that only new students were treated. (p. 10) Daily (1983) focused on a different population but provided conclusions similar to those of Chickering, Kickels, and Powers. Daily focused on problems related to retention and the reasons students dropped out of six historically black colleges. In this study, the researcher was concerned about the academic advisement and counseling given especially to freshman students. There seemed to be much support for providing new students with pre-enrollment information, which was intended to have a positive effect on the success of each student’s performance. Each one of these studies suggested that effective treatment administered to new students would have a positive effect on the retention rate. Daily supported this notion by revealing the following: The findings of the study reveal that three major dropout problems confronting the colleges under investigation were: (1) academic advisement and counseling; (2) social adjustment; and (3) stimulating activities. Although Black institutions 18 operated in some cases under adverse financial difficulties, retaining the freshman student through his/her academic program could be accomplished if: (1) colleges would first recognize and admit to the problems of retention and attrition; (2) they avail themselves of present research related to problems of retention and attrition; and (3) a sincere commitment to take action for the implementation of a corrective and preventive program was made. (p. 5) Although Daily focused on six historically black colleges and Kickels and Powers focused on community colleges, their research was concerned with the same issue--student retention strategies. With regard to structural and organizational factors of the institution, very little seems to be known about the interaction effect between the student body and the institution. Pascarella (1985) wrote: Little of the research on the influence of college . . . has been guided by the type of comprehensive, theoretical conceptualization of the Chickering or Tinto models. As a result, although we know that certain types of college experiences may be associated with certain specific outcomes, little is known about the ways in which the various sources of influence interact to lead to the outcomes observed. In short, we may have a good idea about what happens but still not have much understanding of how it happens. Structural characteris- tics of an institution, such as enrollment or the selectivity of the student body, may influence various types of student development, yet how is this influence manifest? Do structural characteristics directly influence development, or is their influence indirect through the nature of the student interac- tions which they foster within the institution’s various social and academic systems? (p. 641) Seale (1984) seemed to suggest that structural characteristics of the institution are indirectly influenced through the nature of the student’s interaction within the system. Seale conducted his research to test Tinto’s (1975) theoretical model of college persistence in a two-year community college setting. Beginning with selected background and situational variables, the model examines the 19 importance of different paths that students follow within the college environment in making their first retention/attrition decisions. (p. 4) Furthermore, Barnard (1983) took a different focal point. He identified, as one of the primary causes of dropping out, the lack of assistance in making a career decision. This research indicated structural and organizational methods that will assist students with the career decision-making process. Barnard was not alone in his suggestion that lack of career decision affects attrition levels. Campbell (1987) examined the different personal characteristics of college persisters compared to freshmen dropping out of college. He found that: The persisters were more likely to have decided on a career or academic field of interest prior to enrollment than were the drop-outs. Seventy-five percent of the persisters had either a career or academic field of interest decided upon prior to enrollment, compared to seventy percent of the drop-outs. (p. 6) Barnard recommended the following after completing his research: The career development class be continued and sections of the class offering be increased; replicate the study using the part-time student status only to measure whether there is significant difference within the groups as it relates to the variables tested; replicate the study in another city which has the ethnicity mix to measure the effect of the career class. (D. 7) Wallace (1980) also evaluated a career program at a community college. She wrote that: The purpose of this study was to evaluate a community college career program which was specifically developed to deal with both attrition and career-oriented education. The main feature of this experimental program (The Coastal-Environmental Studies Program-CESP) was a great increase in the faculty and administrator’s contact and involvement with the students. (p. 0) 20 Wallace’s research was similar to the present study because student opinions were analyzed that were concerned with academic variables, faculty, and services provided. There is much evidence to support the existence of interactions between the students and faculty within the institution and how this interaction affects attrition. Wallace’s research supported the idea that the interaction between students and faculty is an important issue, which corroborates the idea that it would be feasible to look at demographic variables of academic programs, faculty, and services to discover their influence on students’ levels of satisfaction. Wallace stated: The findings indicated that when student-faculty and student- administrator relationships are increased and made more mean- ingful, students will continue their career program training. These findings are suggestive rather than conclusive. We did not attempt to determine if all types of student-faculty and student-administrator relationships are equally influential. Student-faculty and student-administrative involvement may be important at the community college level but its importance at the four-year college is not known. (p. 11) Wallace suggested that increased student-faculty and student- administrator relationships would effect an increase in the number of students who continue in their career programs. However, Fong (1983) conducted a similar study in which she examined the interaction of faculty attitude, student grades, and the implica- tions of student attrition. She concluded: The findings of this study do not support those in the literature. That is, community college teachers’ attitude scores in this study were not found to be positively related to their students’ mean grades or negatively related to their students’ mean dropout rate. In most cases the direction of those of the correlations was opposite to the direction of those in previous findings. (p. 6) 21 Fong revealed further information about her investigation: The major findings of this investigation suggested that instructor attitudes, as measured by the Minnesota Teacher Attitude Inventory (MTAI), are not related to or are negatively related to the grades of the students of those instructors; or positively related to the dropout rate of the students of those instructors. Nor are attitude scores significantly related to other instructor characteristics and background variables. If the results of this study are confirmed in the future, a more conclusive statement can be made about the relevance or non- relevance of instructor attitudes to teaching behavior. (pp. 6- 7) Fong’s research revealed a different perspective on college teachers’ attitudes and students’ grade point averages, but as she indicated, additional studies need to be conducted on this matter. On the other hand, Neumann’s (1985) research differed in that student persisters were more likely to develop close informal personal, relationships with one or more of their community college faculty. Neumann appeared to have included all three of the constructs in Chickering’s (1969) model. For example, Neumann revealed that: Comprehensive background information was collected for each student including their family histories, individual characteristics, prior educational experiences and their attitudes, opinions and impressions of these experiences. Special attention was given to exploring their high school and college experiences. Through the use of open-ended questions I probed deeply into students’ community college experiences, asking them to describe their relationships with friends, family, classmates, faculty, advisors and staff at their community college. (p. 3) Neumann concluded with the notion that the persisters appeared to have become more integrated into the social system than leavers did. 22 Evaluation of Dissertatipn Stpdies There were many references to persisters and leavers in the review of dissertation studies. The present study focused more on the persisters, i.e., those students who completed their studies at the community college. All of the previous research studies except for Fong’s (1983) indicated that the structural environment and the interaction with teacher, classes, and other students influenced whether or not a student remained in school. These studies suggested that there are external variables such as faculty support, career classes, pre-enrollment information, and so on, that, when introduced, will have an effect on remaining in school or dropping out of school. Pascarella’s (1985) mention in his article of Chickering’s (1969) proposal that there is a general model of college effects is relevant to this study. Chickering addressed an important question of how to go about understanding the effects of college. The studies cited appear to have tested parts of the model or the entire model and concluded that pre-enrollment status, institutional factors, and socialization are important, relevant issues when dealing with college influence. These studies in most cases gave equal consideration to both persisters and leavers.- However, the present project gave exclusive consideration to persisters and evaluated the level of satisfaction with the college environment in reference to their selected field of study. Many might argue that leavers are an important population. However, this researcher believed that investigating a population of 23 successful students might provide new insights into old problems. By evaluating persisters’ behaviors and perceptions concerning college effect, common attributes of students who had success at the community college might emerge. Current Journal Artieles Attention is now given to current journal articles related to retention within the community college. Jones (1986) articulated his point of view as related to creating the necessary environment for retention. He indicated: Successful retention programs seem to have a number of commonalities, not so much in the services and activities, but in the method of operation and the attitudes of those who provide the services. One of the significant contributors to success is the personal contact between campus employees and students. Experience indicates that helping the high-risk student establish a linkage with the college through either a personal relationship with a staff member, involvement in campus organization, or a campus-based work assignment appears to be the single-most-effective means of reducing attrition. (p. 17) Jones placed major importance on the attitude of the service providers as well as personal relationships with staff members. In this particular research, there were questions regarding attitudes of service deliverers as well as the services. Jones also made a strong case for the idea that each college must develop its own retention program. He stated: Successful strategies to reduce attrition can be developed; however, no cookbook formula works for all institutions. Each college must first identify its own needs and problems and then develop its own unique plan to reduce student attrition. (p. 15) 24 Not only are community colleges concerned with strategies for retention; one author in particular viewed evaluation of occupational program as important because it has the potential to affect enrollment. Long (1986-87) suggested that there was a real need to evaluate occupational programs on a regular basis: Declining enrollments, changing technology, budget constraints, and concern for quality are a few of the reasons for evaluating occupational programs on a regular basis. Administrators must evaluate programs (as distinct. from faculty performance appraisals) in order to make rational and defensible decisions about staffing, budgeting, expansion, improvement, retrench- ment, or phaseout. The process of program evaluation, however, takes many different forms, depending on custom, structure, mission, grievance, collective-bargaining agreements, and other factors. (p. 48) Long’s statement is relevant to the present research in that it was concerned with evaluating programs within the college. The present writer investigated concerns of both liberal arts majors and occupational/vocational majors. Long’s favorable statement concern- ing evaluations lent support to this research in light of the fact that the present study, consistent with his observation, was an evaluation of programs, students, services, and so on. Palmer’s (1986) view is also relevant to this research effort. He conducted a review of the literature to examine the diverse characteristics of two-year college vocational students. Palmer suggested: ”While the average vocational student has a lower academic and socioeconomic profile than the average transfer student, the averages conceal a wide variance in the characteristics of vocational students." 25 Palmer suggested that liberal arts students were more like technical students than technical students were like each other. He further stated: "Finally, the overlapping characteristics of vocational and transfer students could be explained in part by the fact that some so-called terminal vocational programs actually serve as transfer curricula.” The ability to delineate vocational/technical students from liberal arts students is getting increasingly difficult because of articulation agreements whereby students are allowed to transfer by agreement, which now include some technical/vocational students. This is a question about which the present research may provide additional information. .Are technical students like liberal arts students with regard, to particular academic and demographic variables? This research was not specifically designed to answer the question of whether there is a significant difference among technical (vocational) students. Rather, the researcher hypothesized that technical students are not different from liberal arts students. I As a result of reviewing the related journal articles, there seems to be a large body of literature that has addressed the issue of minority student retention. Many writers have expressed the need for increased retention among minority groups; in particular, retention of black students is a major issue» In 1988 alone, the Jppppel of College Student Development contained six feature articles on blacks in 0.5. higher' education. Brown and Brown (1988), McCauley (1988), Carroll (1988), Mallinckrodt (1988), 26 Tomlinson and Cope (1988), and Williams and Leonard (1988) are just a few of the recent contributors to the literature on this topic. Dugan and Tillery (1987) listed seven priorities for action. Among these priorities, they suggested that "there is a need for a major national study' of’ student services programs in community colleges.” They further suggested: We need to know how student services programs are changing. How are these programs responding to shifting student needs and patterns of attendance? What roles are the new technologies playing in both the management and the programs (especially counseling and academic advising) of student services? Have these programs become more integrated with or more isolated from academic programs in the past decade? (p.39) The preceding statement reaffirms the direction of the present research. It was the writer’s intention to evaluate student services and other functions of a particular community college. Evaluation of Cprrent Joprpal Artieles The current journal articles appeared to suggest a need for community colleges to evaluate current services and programs and to develop their own special models of retention specific to their particular institutions. These models of retention that need to be created should include both terminal and transfer programs. Palmer’s (1986) suggestion that technical students were a diverse group within the group itself revealed a need to evaluate his assumption. The results of the present study should provide some additional insight into particular characteristics of technical as well as liberal arts students. 27 Sum Most of the dissertation studies suggested that the structural environment of the college and the interaction with teachers, classes, and other students influenced whether or not a student remained in school. Chickering’s (1969) model of college effect suggested that pre-enrollment status, institutional factors, and socialization on campus are important issues that need to be taken into consideration. The dissertation studies that followed Chickering’s model of college effect tested various parts of his model and supported his theory. The journal articles revealed a need for community colleges to evaluate their current services and programs and to develop their own special models of retention specific to their particular institutions. The present research comparing demographic data and other academic variables of students at Henry Ford Community College was given support by Chickering’s model, the cited dissertation studies, and the journal articles included in this review of literature. CHAPTER III DESIGN OF THE STUDY Intrpdpetipn Traditional education has emphasized liberal arts as the essential component of education. Although there is still merit to the importance of a liberal arts background, a new field has emerged. This new field is technological education. With the advent of technology in the market place has come the need for knowledge of technological concepts and materials. High schools as well as colleges are exposing students to both a technical education and a liberal arts education. This researcher compared responses of technical students to those of liberal arts students concerning levels of satisfaction related to matriculation at a local community college. The responses were analyzed to determine whether there were any real differences in responses between these two groups. A comparison of their responses on demographic variables as well as responses to satisfaction with college services, programs, and college environment may reveal useful insights into any differences between the two groups in terms of how they view college services, programs, and the college environment. , 28 29 This study was accomplished with students at Henry Ford Community College who had applied for graduation. Degree candidates were selected for participation because they had been exposed to the various facets of this college for a maximum period of time and would, therefore, be in a better position to evaluate the college experience than would their underclass counterparts. The sample was developed from a mailing of 700 surveys, 331 of which were returned. The students participated voluntarily, and their anonymity was assured because no identification information was solicited from individuals and results were reported in group form. The Sample The total sample included 331 students. However, eight surveys were discarded because they were incomplete. Of the 323 respondents who returned usable questionnaires, 181 were female degree candidates and 142 were male candidates. There were 86 technical males, 56 liberal arts males, 102 technical females, and 79 liberal arts females. The age range of the subjects was as follows: 117 were 18 to 21 years old, 129 were 22 to 29 years of age, and 77 were 30 and over. The racial ethnic composition of the sample included 6.2% black, 0.6% Indian, 85.7% white, 0.9% Mexican-Chicano, 1.2% Oriental-Asian, 0.6% other Hispanic, and 3.4% other; 1.2% preferred not to respond. There were 188 students in the technical group and 135 in the liberal arts group. 30 Qharaeteristics of Henry Ford Community College On September 2, 1952, the name Dearborn Junior College was changed to Henry Ford Community College. The college has grown in enrollment and in the number of courses and services offered until its student body is now approximately 15,000 full- and part-time students and its curriculum lists more than 900 courses (Hep;y_£ppg Cpmmunity gellege Catalog, 1987-89). The purpose of Henry Ford Community College is to provide liberal arts and preprofessional work for students who desire to transfer to higher educational institutions. Henry Ford Community College also provides one- and two-year career programs for students preparing for employment at the semi-professional level. The age range of students attending Henry Ford Community College is from 19 to 61 years of age. The ethnic make-up of the college includes African-Americans, American-Indians, Caucasian- Americans, Mexican-Americans, Asian Pacific, and Puerto Ricans. However, Caucasian-Americans comprise the greatest percentage of the college population. The college is committed to serving the needs of metropolitan Detroit area residents and has an open-door admissions policy, which means that anyone with a high school diploma, GED, or equivalent will be admitted. Some programs have additional requirements. The college has a very special relationship with the Ford Motor Company. In 1956, the Ford Motor Company gave the Dearborn Board of Education 75 acres of land on the former Henry Ford estate for use by the community college. 31 In the Henry Ford Community College Programs of Study guide (n.d.), the following is stated: Henry Ford Community College also is recognized nationally as a leader in forging training partnerships with business and industry. As home to the UAW-Ford National Development and Training Center, HFCC works with both management and labor to prepare workers for jobs in high technology. lnstrpmentation The survey instrument that was selected for data collection was developed by the American College Testing Program. The instrument is published as the Student Opinion Survey (Two-Year College Form). According to American College Testing Evaluation/Survey Services (1985), "the purpose of the Student Opinion Survey is to explore perceptions of enrolled students regarding the programs, services, and environment of the institution. The 8-3/4" x 11,” four-page instrument requires approximately 20 minutes to complete" (p. 12). Section one of the survey deals with background information. Such items request age; sex; purpose; grade point average; marital, work, and enrollment status; financial need; living location; area of study; and occupational choice. It is important for an institution to be aware of characteristics of the student population. For example, it is important to know the age parameters of the student p0pu1ation in order to target particular programs toward adult learners if a large population of adult learners is identified. In general, the background information in section one 32 has the potential to reveal the varied background information that contributes to the profile of the student population. Section two is designed to investigate students’ impressions of the college. Areas that are evaluated are course offerings, vocational and academic reputations, social atmosphere, size of the college, personal success, and overall impressions of the quality of the college. This section is designed to reveal whether the students are satisfied with course offerings, as well as how effectively both the vocational and academic programs are fulfilling their mission. Section three examines college services. This segment is intended to reveal how effectively the student body is being served and whether improved or additional services need to be added. Section four evaluates the college environment in terms of six aspects. The first subsection investigates academic attributes, including testing and grading systems, course content, quality of instructions, out-of-class availability of instructors, teacher attitude, class size, flexibility of program, and preparation for an occupation. ‘The second subsection investigates admissions. This portion of the survey evaluates the level of satisfaction with general admission entry procedures, accuracy of information before enrolling, availability of financial information before enrolling, assistance when entering, the college catalog, and admissions publication. The third subsection of the survey investigates institutional rules, policies, academic probation, suspension, purposes of activity fees, and personal safety and security. The 33 fourth subsection evaluates facilities. The areas evaluated are classrooms, industrial arts/shop facilities, study areas, student center, college bookstore, and housing. The fifth subsection is devoted to registration. The areas examined are registration, times and availability of courses, academic calendars, billing fees, and payment. The sixth subsection requests general information. Section five allows for the institution to ask 30 locally designed questions if it elects to do so. This researcher did not exercise that option. Section six requests that the student provide suggestions concerning programs and services at the institution. Reliebilitysend Veliditv The Student Opinion Survey is a nationally standardized instrument that is published by the American College Testing Program. Its most recent validation copyright is 1985. The Pearson product-moment correlation coefficients obtained test-retest correlations of .92 and .95. The validity of the Student Opinion Survey "depends primarily on literature review, consultation with content experts, pilot testing of the instruments, and American College Testing’s experience in instrument design and construction.” There were 15,000 cases in the pilot test of the instruments. Response patterns were analyzed within and between to sort out items that were confusing to students. Care was taken to explore inter- item relationships. 34 Hypotheses The following ten hypotheses, stated in the null form, were tested in this study: Hypothesis 1: There is in) difference between demographic attributes of the technical students and demographic attributes of the liberal arts students on the following 16 attributes: age ethnic identity purpose for entering a two-year college grade-point average gender marital status number of dependent children hours employed per week current enrollment status years attended college of study type of classes most frequently attended pre-entrance academic history proximity to campus financial aid status current area of study occupational choice '0 O 3 a dX'GJo-ha'ta «no 0.0 U'DJ Hypothesis 2: There is no difference between response rates of liberal arts students and response rates of technical students concerning the following 13 reasons for attending a two-year college: convenience of location course offerings low cost ability for working while attending vocational or academic reputation social atmosphere size of college opportunity for personal success availability of scholarship or financial aid advice of parents or relative advice of high school professionals ability to be with friends rating of college at the time Hypothesis 3: There is no difference between technical students’ responses and liberal arts students’ responses to the following questions: a. If you could start college over, would you choose to attend this college? b. What is your overall impression of the quality of edu- cation at this college? a .axg..d.:-ca 4,0 0.0 6'9 35 Hypothesis 4: There is no difference between levels of satis- faction of liberal arts students and levels of satisfaction of technical students with the following 18 services: 'SD'U O 5 a HRH-dorm $0 an U'N academic advising personal counseling vocational guidance job placement financial aid recreational and intramural programs library/learning resources residence halls student health student employment cafeteria/food college-sponsored social activities cultural programs and activities college orientation computer usage parking facilities veteran programs day care Hypothesis 5: There is no difference between levels of satis- faction of liberal arts students and levels of satisfaction of technical students with the following 11 academic aspects of the college: X't—a.-I-CD&D “hit an CTN testing/grading course content in major area of study availability of instructors attitude of teaching staff variety of course offerings class size flexibility to design own program availability of advisor advisor input academic challenge of course of study preparation for chosen occupation Hypothesis 6: There is no difference between levels of satis- faction of liberal arts students and levels of satisfaction of technical students with the following five recruitment activi- ties: (DO. 00'” admission entry procedures information received before enrolling availability of financial aid information before enrolling staff assistance college catalog/admissions information 36 Hypothesis 7: There is no difference between levels of satis- faction of technical students and levels of satisfaction of liberal arts students with the following five student-focused activities: rules governing student conduct student government input on policies academic probation purposes for activity fees 00.00"” Hyppthesis 8: There is no difference between levels of satis- faction of liberal arts students and levels of satisfaction of technical students with the following ten activities: classrooms industrial arts/shop business training equipment laboratory athletics study areas student center/union bookstore availability of adequate housing appearance of buildings and grounds Hyppthesis 9: There is no difference between levels of satis- faction of liberal arts students and levels of satisfaction of technical students with the following four conditions: a. registration procedures b. availability of courses at convenient times c. academic calendar d. billing and fee-payment procedures Hyppthesis 10: There is no difference between levels of satis- faction of liberal arts students and levels of satisfaction of technical students with the following five conditions: concern for the individual attitude of nonteaching staff toward students racial harmony college media general atmosphere (...-uS'CO 430 0.0 0'!” GQOU'N QetesCollection All 700 degree candidates were mailed a copy of the survey. The students were urged to give the survey their prompt attention and to return the survey at one of three drop-off locations around the campus. Three hundred twenty-three usable surveys were 37 returned. Some students did not answer all of the questions, which changed the total number of respondents for certain questions. ,Each table gives the number responding to each question. Data Analysis The data were analyzed for each variable listed under each hypothesis. A mean for the technical-student group was calculated and compared to the mean for the liberal-arts-student group. Data for Hypothesis 1 were calculated in crosstab form, and a chi-square test was used to analyze the nominal data. Data for Hypothesis 2 were calculated both in crosstabs and breakdowns, and a chi-square test was applied to analyze group means provided as ordinal data. A t-test was applied for Hypotheses 3 through 10. In Tables 5, 9, and 14, a Yates correction factor was employed because Yates (cited in Hays, 1981) believed that a correction device needs to be applied to a chi-square table when there are only two rows and two columns in the table. This correction factor was applied only when there were just two rows and two columns in the table. 5.2mm The purpose of this study was to compare the demographic and academic variables of degree candidates at Henry Ford Community College in terms of their satisfaction with services and programs. Ten null hypotheses were developed, involving demographic attributes, reasons for attending, services, academic aspects, 38 recruitment activities, and conditions of the college. Both chi- square and t-test were applied in testing the hypotheses. The Student Opinion Survey was the instrument used to collect the data. CHAPTER IV ANALYSIS OF THE DATA mm The data were analyzed for each variable listed under each hypothesis. A mean for the technical-student group was calculated and compared to the mean for the liberal-arts-student group. Data for Hypothesis 1 were calculated in crosstab form, and a chi-square test was used to analyze the nominal data. Data for Hypothesis 2 were calculated both in crosstabs and breakdowns, and a chi-square test was applied to analyze group means provided as ordinal data. A t-test was applied for Hypotheses 3 through 10. Results pf Data Analyses Table 1 contains data for technical students compared to liberal arts students on the variable age. These data show that 3.2% of the technical students compared to 3.8% of the liberal students were 19 years of age, 10.1% of the technical students compared to 25.2% of the liberal arts students were 20 years old, 16.5% of the technical students compared to 16.3% of the liberal arts students were 21 years old, 9.4% of the technical students compared to 7.4% of the liberal arts students were 22 years of age, 16% of the technical students compared to 15.6% of the liberal arts students were 23 to 25 years old, 20.7% of the technical students 39 40 compared to 8.9% of the liberal arts students were 26 to 29 years old, 19.1% of the technical students compared to 12.6% of the liberal arts students were 30 to 39 years old, and 5.3% of the technical students compared to 10.4% of the liberal arts students were 40 to 60 years of age. Table l.--Comparison of technical students to liberal arts students on the variable age. Student Group Total Age (in Years) Technical Liberal Arts No. % No. % No. % l9 ' 6 3.2 4 3.0 10 3.1 20 19 10.1 34 25.2 53 16.4 21 31 16.5 22 16.3 53 16.4 22 17 9.0 10 7.4 27 8.4 23-25 30 16.0 21 15.6 51 15.8 26-29 39 20.7 12 8.9 51 15.8 30-39 36 19.1 17 12.6 53 16.4 40-61 10 5.3 14 10.4 24 7.4 No response 1 .7 1 .3 Total 188 99.9 135 100.1 323 100.0 Note: Totals do not equal 100.0% due to rounding. Chi-square - 24.30659 Significance - .0020 The level of significance was .0020 when the chi-square test was applied to the differences between the two groups. This level 010 meet the criterion for statistical significance. Of the technical students, 39.8% were between 26 and 39 years of age, whereas only 21.5% of the liberal arts students were between 26 and 39 years old. 41 Table 2 reports data for technical students compared to liberal arts students on the variable ethnicity. The data show that 3.7% of the technical students compared to 9.7% of the liberal arts students were Afro-American, .5% of the technical students compared to .7% of the liberal arts students were American Indian, 88.2% of the technical students compared to 82.1% of the liberal arts students were Caucasian-American, 1.1% of the technical students compared to .7% of the liberal arts students were Mexican-American, 1.6% of the technical students compared to .7% of the liberal arts students were Asian Pacific, 0% of the technical students compared to 1.5% of the liberal arts students were Puerto Rican, and 3.7% of the technical students compared to 3.0% of the liberal arts students were of other ethnic backgrounds. Table 2.--Comparison of technical students to liberal arts students on the variable ethnicity. Student Group Total Ethnicity Technical Liberal Arts No. % No. % No. % Afro-American 7 3.7 13 9.7 20 6.2 American Indian 1 .5 1 .7 2 .6 Caucasian-American 165 88.2 110 82.1 275 85.7 Mexican-American 2 1.1 l .7 3 .9 Asian Pacific 3 1.6 l .7 4 1.2 Puerto Rican 0 .0 2 1.5 2 .6 Other 7 3.7 4 3.0 11 3.4 No response 2 1.1 2 1.5 4 1.2 Total 187 99.9 134 99.9 321 99.8 Note: Totals do not equal 100.0% due to rounding. Chi-square - 8.43056 Significance . .2962 42 The level of significance was .2962 when the chi-square test was applied to the differences between the two groups. This level 010 NOT meet the criterion for statistical significance. Therefore, there was no statistically significant difference between the technical and liberal arts students on the ethnicity variable in this study. However, it is important to note that only 12.9% of the total sample were other than Caucasian-American, whereas 85.1% were Caucasian-American. Table 3 shows data for technical students compared to liberal arts students on the variable purpose for entering Henry Ford Community College. The data show that .5% of the technical students compared to 3.0% of the liberal arts students had had no definite purpose for entering Henry Ford Community College, .5%» of the technical students compared to 1.5% of the liberal arts students had entered for self-improvement, 1.1% of the technical students compared to 5.9% of the liberal arts students had entered as a job requirement, and 1.1% of the technical students compared to 3.0% of the liberal arts students had entered in order to transfer to a two- year college. In addition, 15.4% of the technical students compared to 35.6% of the liberal arts students had entered to transfer to a four year college, 10.6% of the technical students compared to 1.5% of the liberal arts students had entered to complete vocational- technical training, 70.7% of the technical students compared to 46.7% of the liberal students had entered the community college to obtain an associate degree, and none of the technical students 43 compared to 3.0% of the liberal arts students had entered for other purposes. Table 3.--Comparison of technical students to liberal arts students on the variable purpose for entering Henry Ford Community College. Student Group Total Purpose for Entering Technical Liberal Arts No. % No. % No. % No purpose 1 .5 4 3.0 5 1.5 Self-improvement l .5 2 1.5 3 .9 Job requirement 2 1.1 8 5.9 10 3.1 Transfer to 2-year college 2 1.1 4 3.0 6 1.9 Transfer to 4-year college 29 15.4 48 35.6 77 23.8 Complete voc.-tech. 20 10.6 2 1.5 22 6.8 Obtain assoc. degree 133 70.7 63 46.7 196 60.7 Other 0 .0 4 3.0 4 1.2 Total 188 99.9 135 100.2 323 99.9 Note: Totals do not equal 100.0% due to rounding. Chi-square = 47.39509 Significance - .000 The level of significance was .000 when the chi-square test was applied to the differences between the two groups. This level 010 meet the criterion for statistical significance. Therefore, there was a statistically significant difference between technical and liberal arts students with regard to their purpose for entering Henry Ford Community College. There were 35.6% of the liberal arts who responded that their reason for entering was to transfer to a four-year school, compared to only 15.4% of the technical students reporting this purpose. However, 70.7% of the technical students 44 compared to 46.7% of the liberal arts students responded that their purpose for entering was to obtain an associate degree. Therefore, a greater percentage of technical than liberal arts students had entered Henry Ford Community for the purpose of obtaining an associate degree. Table 4 reports data for technical students compared to liberal arts students on the variable overall college grade point average (GPA). The data show that 20.2% of the technical students compared to 16.4% of the liberal arts students had an overall college GPA of 3.5 to 4.0, 29.8% of the technical students compared to 28.4% of the liberal arts students had an overall GPA of 3.0 to 3.49, 34.0% of the technical students compared to 3.6% of the liberal arts students had an overall GPA of 2.5 to 2.99, 16.0% of the technical students compared to 22.4% of the liberal arts students had an overall GPA of 2.0 to 2.49, none of the technical students compared to 1.5% of the liberal arts students had an overall GPA of 1.5 to 1.99, and none of the technical students compared to .7% of the liberal arts students did not indicate their GPA. The level of significance was .2290 when the chi-square test was applied to the differences between the two groups. This level 010 NOT meet the criterion for statistical significance. Therefore, there was no statistically significant difference between the technical students and the liberal arts students on the variable overall college GPA. 45 Table 4.--Comparison of technical students to liberal arts students on the variable overall college grade point average. Student Group Total Grade Point Average Technical Liberal Arts No. % No. % No. % 3. 5- 4. 0 38 20.2 22 16 4 60 18.6 3. 0- 3. 49 56 29.8 38 28.4 94 29.2 2. 5- 2. 99 64 34.0 41 30.6 105 32.5 2. 0- 2. 49 30 16.0 30 22.4 60 18.6‘ 1. 5- 1. 99 0 .0 2 1 5 2 .6 Not established 0 .0 1 7 l .3 Total 188 100.0 134 100.0 322 99.8 Note: Total does not equal 100.0% due to rounding. Chi-square = 6.88943 Significance = .2290 Table 5 reports data for technical students compared to liberal arts students on the variable gender. The data show that 45.7% of the technical students compared to 41.5% of the liberal arts students were males; 54.5% of the technical students compared to 58.9% of the liberal arts students who were females. The level of significance was .5172 when the chi-square test was applied to the differences between the two groups. This level DID NOT meet the criterion for statistical significance. Therefore, there was no statistically significant difference between the technical and liberal arts students on the variable gender. 46 Table 5.--Comparison of technical students to liberal arts students on the variable gender. Student Group Total Gender Technical Liberal Arts No. % No. % No. % Male 86 45.7 56 41.5 142 44.0 Female 102 54.3 79 58.5 181 56.0 Total 188 100.0 135 100.0 323 100.0 Chi-square . .041956 Significance - .5172 (Yates correction) .57969 .4464 Table 6 reports data for technical students compared to liberal arts students on the variable marital status. The data show that 64.4% of the technical students compared to 77.8% of the liberal arts students were unmarried. Also, 35.1% of the technical students compared to 21.5% of the liberal arts students were married, none of the technical students compared to .7% of the liberal arts students were separated, and .5% of the technical students compared to none of the liberal arts students did not respond to this item. The level of significance was .0281 when the chi-square test was applied to the differences between the two groups. This level DID meet the criterion for statistical significance. Therefore, there was a statistically significant difference between the technical and liberal arts students on the variable marital status. This difference suggests that a greater percentage of technical than liberal arts students were married. It can be postulated that being 47 married requires that one have more financial and emotional responsibilities, which might influence the selection of a technical field of study because one can complete an associate degree within a two-year period and gain job-entry skills. In contrast, liberal arts students are more apt to complete a four-year program. Table 6.--Comparison of technical students to liberal arts students on the variable marital status. Student Group Total Marital Status Technical Liberal Arts No. % No. % No. % Unmarried 121 64.4 105 77.8 226 70.0 Married 66 35.1 29 21.5 95 29.4 Separated 0 .0 l .7 l .3 No response l .5 0 .0 1 .3 Total 188 100.0 135 100.0 323 100.0 Chi-square - 9.09146 Significance = .0281 Table 7 reports data for technical students compared to liberal arts students on the variable number of dependent children. The data show that 73.8% of the technical students compared to 79.9% of the liberal arts students had no children, 11.2% of the technical students compared to 8.2% of the liberal arts students had one dependent child, 8.0% of the technical students compared to 6.0% of the liberal arts students had two dependent children, 5.3% of the technical students compared to 3.7% of the liberal arts students had 48 three dependent children, and 1.6% of the technical students compared to 2.2% of the liberal arts students had four or more dependent children. Table 7.--Comparison of technical students to liberal arts students on the variable number of dependent children. Student Group Total Number of Dependent Technical Liberal Arts Children No. % No. % No. % None 138 73.8 107 79.9 245 76 3 l 21 11.2 11 8.2 32 10 O 2 15 8.0 8 6.0 23 7 2 3 10 5.3 5 3.7 15 4 7 4 3 1.6 3 2.2 6 l 9 Total 187 99.9 134 100.0 321 100 l Note: Totals do not equal 100.0% due to rounding. Chi-square - 2.15245 Significance - .7077 The level of significance was .7077 when the chi-square test was applied to the differences between the two groups. This level DID NOT meet the criterion for a statistically significant difference between the technical and liberal arts students on the variable number of dependent children. Table 8 reports data for technical students compared to liberal arts students on the variable hours per week currently employed. The data show that 29.4% of the technical students compared to 24.8% of the liberal arts students worked zero hours per week or only 49 occasional jobs. Also, 7.5% of the technical students compared to 6.8% of the liberal arts students worked 1 to 10 hours per week, 19.8% of the technical students compared to 14.3% of the liberal arts students worked 11 to 20 hours per week, 14.4% of the technical students compared to 17.3% of the liberal arts students worked 21 to 30 hours per week, 19.8% of the technical students compared to 19.5% of the liberal arts students worked 31 to 40 hours per week, and 9.1% of the technical students compared to 17.3% of the liberal arts students worked more than 40 hours per week. Table 8.--Comparison of technical students to liberal arts students on the variable hours per week currently employed. Student Group Total Hours Per Week Technical Liberal Arts Currently Employed No. % No. % No. % 0 to occasional 55 29.4 33 24.8 88 27.5 1-10 14 7.5 9 6.8 23 7.2 11-20 37 19.8 19 14.3 56 17.5 21-30 27 14.4 23 17.3 50 15.6 31-40 37 19.8 26 19.5 63 19.7 Over 40 17 9.1 23 17.3 40 12.5 Total 187 100.0 133 100.0 320 100.0 Chi-square - 6.58842 Significance - .2531 The level of significance was .2531 when the chi-square test was applied to the differences between the two groups. This level 010 NOT meet the criterion for statistical significance. Therefore, 50 there was no statistically significant difference between the technical and liberal arts students concerning the variable hours per week currently employed. Table 9 contains data for technical students compared to liberal arts students on the variable enrollment status at Henry Ford Community College. The data show that 53.8% of the technical students compared to 43.1%. of the liberal arts students were enrolled full time; 46.2% of the technical students compared to 56.9% of the liberal arts students were enrolled part time. Table 9.--Comparison of technical students to liberal arts students on the variable enrollment status at Henry Ford Community .College. Student Group Total Enrollment Status Technical Liberal Arts No. % No. % No. % Full time 99 53.8 56 43.1 155 49.4 Part time 85 46.2 74 56.9 159 50.6 Total 184 100.0 130 100.0 314 100.0 Chi-square . 3.09110 Significance - .0787 (Yates correction) 3.50714 .0611 The level of significance was .0787 when the chi-square test was applied to the differences between the two groups. This level DID NOT meet the criterion for statistical significance. Therefore, there was no statistically significant difference between the 51 technical and liberal arts students concerning the variable enrollment status at Henry Ford Community College. Table 10 shows data for technical students compared to liberal arts students on the variable number of years attended Henry Ford Community College. The data show that .5% of the technical students compared to 1.5% of the liberal arts students had attended Henry Ford Community College for one year, 22.9% of the technical students compared to 24.6% of the liberal arts students had attended for two years, 37.8% of the technical students compared to 41.0% of the liberal arts students had attended for three years, and 38.8% of the technical students compared to 32.8% of the liberal arts students had attended for four years. Table 10.--Comparison of technical students to liberal arts students on the variable number of years attended Henry Ford Community College. Student Group Total Number of Years Technical Liberal Arts Attended No. % No. % No. % 1 year 1 .5 2 1.5 3 .9 2 years 43 22.9 33 24.6 76 23.6 3 years 71 37.8 55 41.0 126 39.1 4 years 73 38.8 44 32.8 117 36.3 Total 188 100.0 134 99.9 322 99.9 Note: Totals do not equal 100.0% due to rounding. Chi-square = 1.86547 Significance = .6008 52 The level of significance was .6008 when the chi-square test was applied to the differences between the two groups. This level 010 NOT meet the criterion for statistical significance. Therefore, there was no statistically significant difference between technical and liberal students on the variable number of years attended Henry Ford Community College. Table 11 reports data for technical students compared to liberal arts students on the variable type of class most frequently attended. The data show that 75.3% of the technical students compared to 69.4% of the liberal arts students selected day classes as the type most frequently attended, 23.7% of the technical students compared to 29.9% of the liberal arts students selected evening classes, and 1.1% of the technical students compared to .7% of the liberal arts students chose other than day or evening classes. Table ll.--Comparison of technical students to liberal arts students on the variable type of class most frequently attended. Student Group Total Type of Class Technical Liberal Arts No. % No. %. No. % Day 140 75.3 93 69.4 233 72.8 Evening 44 23.7 40 29.9 84 26.3 Other 2 1.1 l .7 3 .9 Total 186 100.1 134 100.0 320 100.0 Note: Total does not equal 100.0% due to rounding. Chi-square - 1.59666 Significance - .4501 53 The level of significance was .4501 when the chi-square test was applied to the differences between the two groups. This level 010 NOT meet the criterion for statistical significance. Therefore, there was no statistically significant difference between technical and liberal arts students on the variable type of class most frequently attended. Table 12 reports data for technical students compared to liberal arts students on the variable status prior to attending. The data show that 38.8% of the technical students compared to 54.1% of the liberal arts students had entered directly from high school, 35.6% of the technical students compared to 20.7% of the liberal arts students had worked for a period of time before attending, 1.1% of the technical students compared to 3.3% of the liberal arts students had transferred from another two-year college, 10.6% of the technical students compared to 8.1% of the liberal arts students had transferred from a four-year college, and 1.6% of the technical students compared to .7% of the liberal arts students had completed military service before attending. The level of significance was .0281 when the chi-square test was applied to the differences between the two groups. This level 010 meet the criterion for statistical significance. Therefore, there was a statistically significant difference between technical and liberal arts students on the variable status prior to attending. A greater percentage of technical students had had work experience before attending Henry Ford Community College, whereas a greater 54 number of liberal arts students had entered directly from high school. Prior work experience might have been the impetus for selecting a technical field of study. Table 12.--Comparison of technical students to liberal arts students on the variable status prior to attending. Student Group Total Status Prior to Technical Liberal Arts Attending No. % No. % No. % Directly from high school 73 38.8 73 54.1 146 45.2 Entered after working 67 35.6 28 20.7 95 29.4 Transferred from two- year college 2 1.1 4 3.0 6 1.9 Transferred from four- year college 20 10.6 11 8.1 31 9.6 Entered after military 3 1.6 l .7 4 1.2 Other 23 12.2 18 13.3 41 12.7 Total 188 99.9 135 99.9 323 100.0 Note: Totals do not equal 100.0% due to rounding. Chi-square - 12.54091 Significance = .0281 Table 13 reports data for technical students compared to liberal arts students on the variable distance of residence from Henry Ford ConInunity College. The data show that 2.7% of the technical students compared to 1.5% of the liberal arts students .lived less than 1 mile from the college, 42.2% of both the technical and liberal arts students lived l to 5 miles from the college, 28.9% of the technical students compared to 38.5% of the liberal arts students lived 6 to 10 miles from the college, 19.8%. of the 55 technical students compared to 14.1% of the liberal arts students lived 11 to 20 miles from the college, 6.4% of the technical students compared to 3.0% of the liberal arts students lived 21 to 40 miles from the college, and no technical students compared to .7% of the liberal arts students lived more than 40 miles from the college. Table 13.--Comparison of technical students to liberal arts students on the variable distance of residence from Henry Ford Community College. Student Group Total Distance From the Technical Liberal Arts Community College No. % No. % No. % Less than 1 mile 5 2 7 2 1.5 7 2.2 1- 5 miles 79 42.2 57 42.2 136 42.2 6-10 miles 54 28.9 52 38.5 106 32.9 11-20 miles 37 19.8 19 14.1 56 17.4 21-40 miles 12 6.4 4 3.0 16 5.0 Over 40 miles 0 0 l .7 1 .3 Total 187 100.0 135 100.0 322 100.0 Chi-square - 7.46516 Significance a .1883 The level of significance was .1883 when the chi-square test was applied to the differences between the two groups. This level DID NOT meet the criterion for statistical significance. Therefore, there was no statistically significant difference between technical 56 and liberal arts students on the variable distance of residence from Henry Ford Community College. Table 14 reports data for technical students compared to liberal arts students on the variable financial aid recipient. The data show that 29.6% of the technical students compared to 29.3% of the liberal arts students were financial aid recipients; 70.4% of the technical students compared to 70.7%. of the liberal arts students did not receive financial aid. Table l4.--Comparison of technical students to liberal arts students on the variable financial aid recipient. Student Group Total Financial Aid Technical Liberal Arts Recipient No. % No. % No. % Yes 55 29.6 39 29.3 94 29.5 No 131 70.4 94 70.7 225 70.5 Total 186 100.0 133 100.0 319 100.0 Chi-square . 0.00000 Significance - 1.0000 (Yates correction) 0.0027 .9620 The level of significance was 1.0000 when the chi-square test was applied to the differences between the two groups. This level DID NOT meet the criterion for statistical significance. Therefore, there was no statistically significant difference between technical and liberal arts students on the variable financial aid recipient. 57 Table 15 reports data for technical students compared to liberal arts students on the variable current area of study. The data show that 3.7% of the technical students compared to no liberal arts students were studying architecture, 2.1% of the technical students compared to no liberal arts students were in biological sciences, no technical students compared to 60.0% of the liberal arts students were studying business and comerce, no technical students compared to 7.4% of the liberal arts students were in communications, 30.9% of the technical students compared to no liberal arts students were studying computer and information sciences, no technical students compared to 2.2% of the liberal arts students were in education, and 6.9% of the technical students compared to no liberal arts students were studying engineering. In addition, no technical students compared to 8.1% of the liberal arts students were studying fine and applied arts, no technical students compared to .7% of the liberal arts students were studying foreign languages, 34.0% of the technical students compared to no liberal arts students were studying health professions, no technical students compared to .7% of the liberal arts students were studying the letters (humanities, general), 2.1% of the technical students compared to no liberal arts students were studying mathematics, no technical students compared to 6.7% of the liberal arts students were in community service, no technical students compared to 5.9% of the liberal arts students were in social science, 20..2% of the technical students compared to no liberal arts students were studying trade, industrial and technical, and no technical students 58 compared to 8.1% of the liberal arts students were in general studies. Table 15.--Comparison of technical students to liberal arts students on the variable current area of study. Student Group Total Current Area of Technical Liberal Arts Study No. % No. % No. % Architecture 7 3.7 0 .0 7 2.2 Biological science 4 2.1 0 .0 4 1.2 Business & commerce 0 O 81 60.0 81 25.1 Communications 0 .0 10 7.4 10 3.1 Computer & info. sciences 58 30.9 0 .0 58 18.0 Education 0 .0 3 2.2 3 .9 Engineering 13 6.9 O .0 13 4.0 Fine & applied arts 0 .0 11 8.1 11 3.4 Foreign languages 0 .0 l .7 l .3 Health professions 64 34.0 0 .0 64 19.8 Letters 0 .0 1 .7 1 .3 Mathematics 4 2.1 0 .0 4 1.2 Community service 0 .1 9 6.7 9 2.8 Social science 0 .1 8 5.9 8 2.5 Trade, indust., technical 38 20.2 0 .0 38 11.8 General studies 0 .0 11 8.1 11 3.4 Total 188 99.9 135 99.8 323 100.0 Note: Total does not equal 100.0% due to rounding. Chi-square - 323.0003 Significance - .0000 The level of significance was .0000 when the chi-square test was applied to the differences between the two groups. This level DID meet the criterion for statistical significance. Therefore, there was a statistically significant difference between technical 59 and liberal arts students on the variable current area of study. The difference suggests that the technical students’ current area of study was different from the liberal arts students’ current area of study. The difference may be based on the fact that technical students are more concerned with gaining skills and abilities required for their chosen fields. Table 16 reports data for technical students compared to liberal arts students on the variable occupational choice. The data show that 4.3% of the technical students compared to 7.7% of the liberal arts students were undecided about their occupational choice, 3.3% of the technical students compared to .8% of the liberal arts students selected architecture, .5% of the technical students compared to 1.5% of the liberal arts students chose biological science, 1.1% of the technical students compared to 51.5% of the liberal arts students selected business and commerce, no technical students compared to 7.7% of the liberal arts students selected communications, 30.4% of the technical students compared to 3.1% of the liberal arts students chose computer and information sciences, no technical students compared to 3.8% of the liberal arts students selected education, 9.8% of the technical students compared to no liberal arts students selected engineering, no technical students compared to 6.2% of the liberal arts students selected fine and applied arts, and 32.1% of the technical students compared to 4.6% of the liberal arts students chose the health professions. In addition, .5% of the technical students compared to no liberal arts students selected the letters as their occupational choice, .5% of 60 the technical students compared to .8% of the liberal arts students selected mathematics, no technical students compared to 5.4% of the liberal arts students chose community services, no technical students compared to 5.4% of the liberal arts students selected social sciences, 17.4% of the technical students compared to .8% of the liberal arts students selected trade, industrial, and technical, and no technical students compared to .8%. of the liberal arts students selected general studies as their occupational choice. Table 16.--Comparison of technical students to liberal arts students on the variable occupational choice. Student Group Total Occupational Choice Technical Liberal Arts No. % No. % No. % Undecided 8 4.3 '10 7.7 18 5.7 Architecture 6 3.3 l .8 7 2.2 Biological science 1 .5 2 1.5 3 1.0 Business & commerce 2 1.1 67 51.5 69 22.0 Communications 0 .0 10 7.7 10 3.2 Computer & info. sciences 56 30.4 4 3.1 60 19.1 Education 0 .0 5 3.8 5 1.6 Engineering 18 9.8 0 .0 18 5.7 Fine & applied arts 0 .0 8 6.2 8 2.5 Health professions 59 32.1 6 4.6 65 20.7 Letters 1 .5 l .8 2 .6 Mathematics 1 .5 1 .8 2 .6 Community services 0 .0 7 5.4 7 2.2 Social sciences 0 .0 7 5.4 7 2.2 Trade, indust., technical 32 17.4 1 .8 33 10.5 General studies 0 .0 l .8 1 .3 Total 184 99.9 130 100.0 314 99.8 Note: Totals do not equal 100.0% due to rounding. Chi-square - 237.49965 Significance - .0000 61 The level of significance was .0000 when the chi-square test was applied to the differences between the two groups. This level DID meet the criterion for statistical significance. Therefore, there was a statistically significant difference between technical and liberal arts students on the variable occupational choice. The difference revealed that the technical students’ occupational choice was different from the liberal arts students’ occupational choice. The difference may be based on the fact that technical students are more concerned with gaining the skills and abilities required for their chosen fields. Table 17 reports data for technical students compared to liberal arts students on the variable rating of college at time of application. The data show that 81.3% of the technical students compared to 74.8% of the liberal arts students rated Henry Ford Community College as their first choice at the time of application, 16.0% of the technical students compared to 20.7% of the liberal arts students rated the college as their second choice, 1.6% of the technical students compared to 4.4% of the liberal arts students rated it as their third choice, and 1.1% of the technical students compared to no liberal arts students rated the college as their fourth choice at the time of application. D The level of significance was .1657 when the chi-square test was applied to the differences between the two groups. This level DID NOT meet the criterion for statistical significance. Therefore, there was no statistically significant difference between technical 62 and liberal arts students on the variable rating of college at time of application. Table 17.-—Comparison of technical students to liberal arts students on the variable rating of college at time of application. Student Group Total Rating of College Technical Liberal Arts No. % No. % No. % lst choice 152 81.3 101 74.8 253 78.6 2nd choice 30 16.0 28 20.7 58 18.0 3rd choice 3 1.6 6 4.4 9 2.8 4th choice 2 1.1 0 .0 2 .6 Total 187 100.0 135 99.9 322 100.0 Note: Total does not equal 100.0% due to rounding. Chi-square - 5.08469 Significance - .1657 Table 18 reports data for technical students compared to liberal arts students on the variable importance of locale. The data show that 58.3% of the technical students compared to 62.9% of the liberal arts students selected importance of locale as a major reason, 29.4% of the technical students compared to 27.3% of the liberal arts students selected importance of locale as a minor reason, and 12.2% of the technical students compared to 9.8% of the liberal arts students selected importance of locale as not a reason. The level of significance was .6806 when the chi-square test was applied to the differences between the two groups. This level DID NOT meet the criterion for statistical significance. Therefore, 63 there was no statistically significant difference between technical and liberal arts students on the variable importance of locale. Table 18.--Comparison of technical students to liberal arts students on the variable importance of locale. Student Group Total Importance of Locale Technical Liberal Arts No. % No. % No. % Major reason 105 58.3 83 62.9 188 60.3 Minor reason 53 29.4 36 27.3 89 28.5 Not a reason 22 12.2 13 9.8 35 11.2 Total 180 99.9 132 100.0 312 100.0 Note: Total does not equal 100.0% due to rounding. Chi-square = 0.76954 Significance . .6806 Table 19 reports data for technical students compared to liberal arts students on the variable importance of courses. The data show that 79.1% of the technical students compared to 55.5% of the liberal arts students selected importance of courses as a major reason, 13.7% of the technical students compared to 35.9% of the liberal arts students selected importance of courses as a minor reason, and 7.1% of the technical students compared to 8.6% of the liberal arts students selected importance of courses as not a T835011. 64 Table 19.--Comparison of technical students to liberal arts students on the variable importance of courses. Student Group Total Importance of Courses Technical Liberal Arts No. % No. % No. % Major reason 144 79.1 71 55.5 215 69.4 Minor reason 25 13.7 46 35.9 71 22.9 Not a reason 13 7.1 11 8.6 24 7.7 Total 182 99.9 128 100.0 310 100.0 Note: Total does not equal 100.0% due to rounding. Chi-square - 22.43839 Significance - .0000 The level of significance was .0000 when the chi-square test was applied to the differences between the two groups. This level DID meet the criterion for statistical significance. Therefore, there was a statistically significant difference between technical and liberal arts students on the variable importance of courses. The difference suggests that technical students were more concerned with obtaining their required courses than were liberal arts students. This may be due to the limited selection of courses that technical students can select, whereas liberal arts students have more options for fulfilling their requirements. Table 20 contains data for technical students compared to liberal arts students on the variable importance of low cost of attending. The data show that 53.8% of the technical students compared to 46.1% of the liberal arts students selected importance 65 of low cost of attending as a major reason, 27.5% of the technical students compared to 28.9% of the liberal arts students selected it as a minor reason, and 18.7% of the technical students compared to 25.0% of the liberal arts students selected it as not a T685011 . Table 20.--Comparison of technical students to liberal arts students on the variable importance of low cost of attending. Student Group Total Importance of Low Technical Liberal Arts Cost of Attending * No. % No. % . No. % Major reason 98 53.8 59 46.1 157 50.6 Minor reason 50 27.5 37 28.9 87 28.1 Not a reason 34 18.7 32 25.0 66 21.3 Total 182 100.0 128 100.0 310 100.0 Chi-square - 2.35608 Significance - .3079 The level of significance was .3079 when the chi-square test was applied to the differences between the two groups. This level 010 NOT meet the criterion for statistical significance. Therefore, there was no statistically significant difference between technical and liberal arts students on the variable importance of low cost of attending. Table 21 reports data for technical students compared to liberal arts students on the variable importance of could work while attending. The data show that 43.8% of the technical students 66 compared to 50.4% of the liberal arts students selected importance of could work while attending as a major reason, 20.2% of the technical students compared to 19.7% of the liberal arts students selected it as a minor reason, and 36.0% of the technical students compared to 29.9% of the liberal arts students selected it as not a reason . Table 21.--Comparison of technical students to liberal arts students on the variable importance of could work while attending. Student Group Total Importance of Could Technical Liberal Arts Work While Attending No. % No. % No. % Major reason 78 43.8 664 50.4 142 46.6 Minor reason 36 20.2 25 19.7 61 20.0 Not a reason 64 36.0 38 29.9 102 33.4 Total 178 100.0 127 100.0 305 100.0 Chi-square = 1.50556 Significance - .4711 The level of significance was .4711 when the chi-square test was applied to the differences between the two groups. This level DID NOT meet the criterion for statistical significance. Therefore, there was no statistically significant difference between technical and liberal arts students on the variable importance of could work while attending. 67 Table 22 reports data for technical students compared to liberal arts students on the variable good vocational-academic reputation. The data show that 63.2% of the technical students compared to 62.2% of the liberal arts students selected good vocational-academic reputation as a major reason, 26.4% of the technical students compared to 22.8% of the liberal arts students selected it as a minor reason, and 10.4% of the technical students compared to 15.0% of the liberal arts students selected it as not a reason. Table 22.-~Comparison of technical students to liberal arts students on the variable good vocational-academic reputation. Student Group Total Good Vocational- Technical Liberal Arts Academic Reputation No. % No. % No. % Major reason 115 63.2 79 62.2 194 62.8 Minor reason 48 26.4 29 22.8 77 24.9 Not a reason 19 10.4 19 15.0 38 12.3 Total 182 100.0 127 100.0 309 100.0 Chi-square - 1.63074 Significance - .4425 The level of significance was .4425 when the chi-square test was applied to the differences between the two groups. This level DID NOT meet the criterion for statistical significance. Therefore, there was no statistically significant difference between technical 68 and liberal arts students on the variable good vocational-academic reputation. Table 23 reports data for technical students compared to liberal arts students on the variable liked the social atmosphere. The data show that 6.7% of the technical students compared to 11.1% of the liberal arts students selected liked the social atmosphere as a major reason, 21.2% of the technical students compared to 23.8% of the liberal arts students selected it as a minor reason, and 72.1% of the technical students compared to 65.1% of the liberal arts students selected it as not a reason. Table 23.--Comparison of technical students to liberal arts students on the variable liked the social atmosphere. Student Group Total Liked the Social Technical Liberal Arts Atmosphere No. % No. % No. % Major reason 12 ‘6.7 14 11.1 26 8.5 Minor reason 38 21.2 30 23.8 68 22.3 Not a reason 129 72.1 82 65.1 211 69.2 Total 179 100.0 126 100.0 305 100.0 Chi-square - 2.42769 Significance - .2971 The level of significance was .2971 when the chi-square test was applied to the differences between the two groups. This level DID NOT meet the criterion for statistical significance. Therefore, there was no statistically significant difference 69 between technical and liberal arts students on the variable liked the social atmosphere. Table 24 reports data for technical students compared to liberal arts students on the variable liked the size of the college. The data show that 9.6% of the technical students compared to 14.2% of the liberal arts students selected liked the size of the college as a major reason, 27.5% of the technical students compared to 38.6% of the liberal arts students selected it as a minor reason, and 62.9% of the technical students compared to 47.2% of the liberal arts students selected it as not a reason. Table 24.--Comparison of technical students to liberal arts students on the variable liked the size of the college. Student Group Total Liked the Size Technical Liberal Arts of the College No. % No. % No. % Major reason 17 9.6 18 14.2 35 11.5 Minor reason 49 27.5 49 38.6 98 32.1 Not a reason 112 62.9 60 47.2 172 56.4 Total 178 100.0 127 100.0 305 100.0 Chi-square = 7.42936 Significance . .0244 The level of significance was .0244 when the chi-square test was applied to the differences between the two groups. This level DID meet the criterion for statistical significance. Therefore, 70 there was a statistically significant difference between technical and liberal arts students on the variable liked the size of the college. The difference suggests that liberal arts students viewed the size of Henry Ford Community College as a reason for attending, whereas technical students in general viewed size as not a critical reason for attending the college. Table 25 reports data for technical students compared to liberal arts students on the variable good chance of personal success. The data show that 29.4% of the technical students compared to 24.2% of the liberal arts students selected good chance of personal success as a major reason, 35.6% of the technical students compared to 34.4% of the liberal arts students selected it as a minor reason, and 35.0% of the technical students compared to 41.4% of the liberal arts students selected it as not a reason. Table 25.--Comparison of technical students to liberal arts students on the variable good chance of personal success. Student Group Total Good Chance of Technical Liberal Arts Personal Success No. % No. % No. % Major reason 53 29.4 31 24.2 84 27.3 Minor reason 64 35.6 44 34.4 108 35.1 Not a reason 63 35.0 53 41.4 116 37.7 Total 180 100.0 128 100.0 308 100.1 Note: Total does not equal 100.0% due to rounding. Chi-square - 1.59389 Significance - .4507 71 The level of significance was .4507 when the chi-square test was applied to the differences between the two groups. This level DID NOT meet the criterion for statistical significance. Therefore, there was no statistically significant difference between technical and liberal arts students on the variable good chance of personal success. Table 26 contains data for technical students compared to lib- eral arts students on the variable availability of scholarship or financial aid. The data show that 12.8% of the technical students compared to 17.2% of the liberal arts students selected availability of scholarship or financial aid as a major reason, 12.8% of the technical students compared to 14.8% of the liberal arts students selected it as a minor reason, and 74.3% of the technical students compared to 68.0% of the liberal arts students said. it was not a reason. Table 26.--Comparison of technical students to liberal arts students on the variable availability of scholarship or financial aid. Student Group Total Availability of Technical 'Liberal Arts Financial Aid No. % No. % No. % Major reason 23 12.8 22 17.2 45 14.7 Minor reason 23 12.8 19 14.8 42 13.7 Not a reason 133 74.3 87 68.0 220 71.7 Total 179 99.9 128 100.0 307 100.1 Note: Totals do not equal 100.0% due to rounding. Chi-square - 1.59301 Significance - .4509 72 The level of significance was .4509 when the chi-square test was applied to the differences between the two groups. This level 010 NOT meet the criterion for statistical significance. Therefore, there was no statistically significant difference between technical and liberal arts students on the variable availability of scholar- ship or financial aid. I Table 27 reports data for technical students compared to liberal arts students on the variable advice of relatives or parents. The data show that 8.5% of the technical students compared to 8.0% of the liberal arts students selected advice of relatives or parents as a major reason, 18.2% of the technical students compared to 23.2% of the liberal arts students said such advice was a minor reason, and 73.3% of the technical students compared to 68.8% of the liberal arts students said this was not a reason. Table 27.--Comparison of technical students to liberal arts students on the variable advice of relatives or parents. Student Group Total Advice of Parents Technical Liberal Arts or Relatives No. % No. % No. % Major reason 15 8.5 10 8.0 25 8.3 Minor reason 32 18.2 29 23.2 61 20.3 Not a reason 129 73.3 86 68.8 215 71.4 Total 176 100.0 125 100.0 301 100.0 Chi-square - 1.13905 Significance - .5658 73 The level of significance was .5658 when the chi-square test was applied to the differences between the two groups. This level DID NOT meet the criterion for statistical significance. Therefore, there was no statistically significant difference between technical and liberal arts students on the variable advice of relatives or parents. Table 28 cmntains data for technical students compared to liberal arts students on the variable advice of high school counselor. 'The data show 'that 7.3%. of the technical students compared to 8.7% of the liberal arts students selected advice of high school counselor as a major reason, 8.4% of the technical students compared to 20.5% of the liberal arts students selected such advice as a minor reason, and 84.4% of the technical students compared to 70.9% of the liberal arts students said advice of high school counselor was not a reason. Table 28.--Comparison of technical students to liberal arts students on the variable advice of high school counselor. Student Group Total Advice of High Technical Liberal Arts School Counselor No. % No. % No. % . Major reason 13 7.3 11 8.7 24 7.8 Minor reason 15 8.4 26 20.5 41 13.4 Not a reason 151 84.4 90 70.9 241 78.0 Total 179 100.1 127 100.1 306 99.2 Note: Totals do not equal 100.0% due to rounding. Chi-square . 10.01021 Significance - .0067 74 The level of significance was .0067 when the chi-square test was applied to the differences between the two groups. This level DID meet the criterion for statistical significance. Therefore, there was a statistically significant difference between technical and liberal arts students on the variable advice of high school counselor. The difference suggests that liberal arts students responded that advice of the high school counselor was a minor reason for attending Henry Ford Community College, whereas a greater percentage of technical students responded that advice of the high school counselor was not a reason for attending. Table 29 reports data for technical students compared to liberal arts students on the variable wanted to be with friends. The data show that .6% of the technical students compared to 3.1% of the liberal arts students selected wanted to be with friends as a major reason, 11.8% of the technical students compared to 9.3% of the liberal arts students selected it as a minor reason, and 87.6% of the technical students compared to 87.6% of the liberal arts students said it was not a reason. The level of significance was .1833 when the chi-square test was applied to the differences between the two groups. This level DID NOT meet the criterion for statistical significance. Therefore, there was no statistically significant difference between technical and liberal arts students on the variable wanted to be with friends. 75 Table 29.--Comparison of technical students to liberal arts students on the variable wanted to be with friends. Student Group Total Wanted to Be Technical Liberal Arts With Friends No. % No. % No. % Major reason 1 .6 4 3.1 5 1.6 Minor reason 21 11.8 12 9.3 33 10.7 Not a reason 156 87.6 113 87.6 269 87.6 Total 178 100.0 129 100.0 307 99.9 Note: Total does not equal 100.0% due to rounding. Chi-square . 3.39376 Significance - .1833 Table 30 reports on the variable If starting over would you attend this college? The data show that on a scale of 1 to 5 the mean of technical students’ responses was 2.1170 compared to a mean of 2.0222 for liberal arts students. When the t-test was applied to the difference between mean scores, a probability of .414 was generated. This level DID NOT satisfy the criterion for statistical significance. Table 30.--Comparison of technical students to liberal arts students on the variable If starting over would you attend this college? No. of Standard t-Test Group Students Mean Deviation Probability Technical 188 2.1170 1.078 Liberal arts 135 2.0222 0.950 -414 76 Table 31 reports on the variable impression of quality of education. The data show that on a scale of l to 5 the mean of technical students’ responses was 1.8449 compared to a mean of 1.7852 for liberal arts students. When the t-test was applied to the difference between mean scores, a probability of .451 was generated. This level DID NOT satisfy the criterion for statistical significance. Table 31.--Comparison of technical students to liberal arts students on the variable impression of quality of education. No. of Standard t—Test Group Students Mean Deviation Probability Technical 187 1.8449 0.705 45] Liberal arts 135 1.7852 0.695 ° Table 32 reports on the variable academic advising/course planning. The data show that on a scale of 1 to 5 the mean of technical students’ responses was 2.6750 compared to a mean of 2.5283 for liberal arts students. When the t-test was applied to the: difference between mean scores, a probability of .350 was generated. This level DID NOT satisfy the criterion for statistical significance. 77 Table 32.--Comparison of technical students to liberal arts students on the variable academic advising/course planning. No. of Standard t-Test Group Students Hean Deviation Probability Technical 120 2.6750 1.196 350 Liberal arts 106 2.5283 1.148 ' Table 33 reports on the variable personal counseling services. The data show that on a scale of 1 to 5 the mean of technical students’ responses was 2.5102 compared to a mean of 2.5610 for liberal arts students. When the t-test was applied to the difference between mean scores, a probability of .853 was generated. This level DID NOT satisfy the criterion for statistical significance. Table 33.--Comparison of technical students to liberal arts students on the variable personal counseling services. No. of Standard t-Test Group Students Mean Deviation Probability Technical 49 2.5102 1.210 Liberal arts 41 2.5610 1.379 -353 Table 34 reports on the variable vocational guidance/career planning services. The data show that on a scale of l to 5 the mean of technical students’ responses was 2.3878 compared to a mean of 2.500 for liberal arts students. When the t-test was applied to the 78 difference between mean scores, a probability of .598 was generated. This level DID NOT satisfy the criterion for statistical significance. Table 34.--Comparison of technical students to liberal arts students on the variable vocational guidance/career planning. No. of Standard t-Test Group Students Mean Deviation Probability Technical 49 2.3878 1.115 598 Liberal arts 52 2.5000 1.019 ' Table 35 reports on the variable job placement services. The data show that on a scale of l to 5 the mean of technical stUdents’ responses was 2.4310 compared to a mean of 2.1842 for liberal arts students. When the t-test was applied to the difference between mean scores, a probability of .264 was generated. This level DID NOT satisfy the criterion for statistical significance. Table 35.--Comparison of technical students to liberal arts students on the variable job placement services. No. of Standard t-Test Group Students Mean Deviation Probability Technical 58 2.4310 1.061 Liberal arts 38 2.1342 1.036 254 79 Table 36 reports on the variable financial aid services. The data show that on a scale of 1 to 5 the mean of technical students’ responses was 2.3478 compared to a mean of 2.2453 for liberal arts students. When the t-test was applied to the difference between mean scores, a probability of .652 was generated. This level DID NOT satisfy the criterion for statistical significance. Table 36.--Comparison of technical students to liberal arts students on the variable financial aid services. No. of Standard t-Test Group Students Mean Deviation Probability Technical 69 2.3478 1.281 65 Liberal arts 53 2.2453 1.191 - 2 Table 37 reports on the variable recreational programs and services. The data show that on a scale of 1 to 5 the mean of technical students’ responses was 2.0870 compared to a mean of 2.000 for liberal arts students. When the t-test was applied to the difference between mean scores, a probability of .688 was generated. This level DID NOT satisfy the criterion for statistical significance. 80 Table 37.--Comparison of technical students to liberal arts students on the variable recreational programs and services. No. of Standard t-Test Group Students Mean Deviation Probability Technical ' 23 2.0370 0.668 688 Liberal arts 29 2.0000 0.845 ° Table 38 reports on the variable library/learning resources center. The data show that on a scale of 1 to 5 the mean of technical students’ responses was 1.7353 compared to a mean of 1.5840 for liberal arts students. When the t-test was applied to the difference between mean scores, a probability of .073 was generated. This level DID NOT satisfy the criterion for statistical significance. Table 38.—-Comparison of technical students to liberal arts students on the variable library/learning resources center. No. of Standard t-Test Group Students Mean Deviation Probability Technical 170 1.7353 0.758 Liberal arts 125 1.5340 0.650 ~°73 Table 39 reports on the variable resident hall programs and services. The data show that on a scale of 1 to 5 the mean of technical students’ responses was 2.8750 compared to a mean of 2.3333 for liberal arts students. When the t-test was applied to 81 the difference between mean scores, a probability of .069 was generated. This level 010 NOT satisfy the criterion for statistical significance. Table 39.--Comparison of technical students to liberal arts students on the variable resident hall programs and services. No. of Standard t-Test Group Students Mean Deviation Probability Technical 8 2.8750 0.354 069 Liberal arts 9 2.3333 0.707 ° Table 40 reports on the variable student health services. The data show that on a scale of l to 5 the mean of technical students’ responses was 2.4444 compared to a mean of 2.6667 for liberal arts students. When the t-test was applied to the difference between mean scores, a probability of .590 was generated. This level DID NOT satisfy the criterion for statistical significance. Table 40.--Comparison of technical students to liberal arts students on the variable student health services. No. of Standard t-Test Group Students Mean Deviation Probability Technical 9 2.4444 0.882 Liberal arts 6 2 6667 0.516 ~59° 82 Table 41 reports on the variable student employment services. The data show that on a scale of 1 to 5 the mean of technical students’ responses was 2.1739 compared to a mean of 2.1250 for liberal arts students. When the t-test was applied to the difference between mean scores, a probability of .872 was generated. This level DID NOT satisfy the criterion for statistical significance. Table 41.--Comparison of technical students to liberal arts students on the variable student employment services. No. of Standard t-Test Group Students Mean Deviation Probability Technical 23 2.1739 0.984 7 Liberal arts 24 2 1250 1.076 -3 2 Table 42 reports on the variable cafeteria/food services. The data show that on a scale of l to 5 the mean of technical students’ responses was 2.6226 compared to a mean of 2.4958 for liberal arts students. When the t-test was applied to the difference between mean scores, a probability of .268 was generated. This level DID NOT satisfy the criterion for statistical significance. Table 43 reports on the variable college-sponsored social activities. The data show that on a scale of 1 to 5 the mean of technical students’ responses was 2.1389 compared to a mean of 2.1591 for liberal arts students. When the t-test was applied to the difference between mean scores, a probability of .895 was 83 generated. This level 010 NOT satisfy the criterion for statistical significance. Table 42.--Comparison of technical students to liberal arts students on the variable cafeteria/food services. No. of Standard t-Test Group Students Mean Deviation Probability Technical 159 2.6226 1.017 268 Liberal arts 119 2.4958 0.832 ' Table 43.--Comparison of technical students to liberal arts students on the variable college-sponsored social activities. No. of Standard t-Test Group Students Mean Deviation Probability Technical 36 2.1389 0.639 Liberal arts 44 2.1591 0.713 .395 Table 44 reports on the variable cultural programs and activities. The data show that on a scale of l to 5 the mean of technical students’ responses was 1.9333 compared to a mean of 1.9020 for liberal arts students. When the t-test was applied to the difference between mean scores, a probability of .833 was generated. This level DID NOT satisfy the criterion for statistical significance. 84 Table 44.--Comparison of technical students to liberal arts students on the variable cultural programs and activities. No. of Standard t-Test Group Students Mean Deviation Probability Technical 45 1.9333 0.654 0 833 Liberal arts 51 1.9020 0.781 ' Table 45 reports on the variable college orientation program. The data show that on a scale of 1 to 5 the mean of technical students’ responses was 2.3214 compared to a mean of 2.4500 for liberal arts students. When the t-test was applied to the difference between mean scores, a probability of .328 was generated. This level 010 NOT satisfy the criterion for statistical significance. Table 45.-~Comparison of technical students to liberal arts students on the variable college orientation program. No. of Standard t-Test Group Students Mean Deviation Probability Technical 84 2.3214 0.779 28 Liberal arts 30 2.4500 0.399 -3 Table 46 reports on the variable computer services. data show that on a scale of l to 5 the mean of technical students’ responses was 2.3776 compared to a mean of 2.3158 for liberal arts students. When the t-test was applied to the difference between mean scores, a 85 probability of .734 was generated. This level DID NOT satisfy the criterion for statistical significance. Table 46.--Comparison of technical students to liberal arts students on the variable computer services. No. of Standard t-Test Group Students Mean Deviation Probability Technical 98 2.3776 1.070 734 Liberal arts 57 2.3158 1.121 ' Table 47 reports on the variable parking facilities and services. The data show that on a scale of l to 5 the mean of technical students’ responses was 3.0389 compared to a mean of 2.9254 for liberal arts students. When the t-test was applied to the difference between mean scores, a probability of .439 was generated. This level 010 NOT satisfy the criterion for statistical significance. Table 47.--Comparison of technical students to liberal arts students on the variable parking facilities and services. N0. of Standard t-Test Group Students Mean Deviation Probability Technical 180 3.0389 1.283 Liberal arts 134 2.9254 1.234 ~439 86 Table 48 reports on the variable veterans services. The data show that on a scale of l to 5 the mean of technical students’ responses was 2.4545 compared to a mean of 2.3333 for liberal arts students. When the t—test was applied to the difference between mean scores, a probability of .753 was generated. This level 010 NOT satisfy the criterion for statistical significance. Table 48.-~Comparison of technical students to liberal arts students on the variable veterans services. No. of Standard t-Test Group Students Mean Deviation Probability Technical 11 2.4545 1.036 753 Liberal arts 12 2.3333 0.778 ' Table 49 reports on the variable day-care services. The data show that on a scale of l to 5 the mean of technical students’ responses was 2.7500 compared to a mean of 2.6250 for liberal arts students. When the t-test was applied to the difference between mean scores, a probability of .742 was generated. This level DID NOT satisfy the criterion for statistical significance. Table 49.--C0mparison of technical students to liberal arts students on the variable day-care services. No. of Standard t-Test Group Students Mean Deviation Probability Technical 12 2.7500 0.866 Liberal arts 3 2.6250 0.744 ~74? 87 Table 50 reports on the variable satisfaction with testing/ grading system. The data show that on a scale of l to 6 the mean of technical students’ responses was 3.1915 compared to a mean of 3.0148 for liberal arts students. When the t-test was applied to the difference between mean scores, a probability of .049 was generated. This level DID satisfy the criterion for statistical significance. 'Therefore, it can be inferred that there *was a statistically significant difference between technical and liberal arts students on the variable satisfaction with the testing/grading system. The data suggested that technical students were more satisfied with the testing and grading system at Henry Ford Community College than were liberal arts students. Table 50.--Comparison of technical students to liberal arts students on the variable satisfaction with testing/grading system. No. of Standard t-Test Group Students Mean Deviation Probability Technical 188 3.1915 0.061 Liberal arts 135 3.0143 0.062 -°49 Table 51 reports on the variable course content in your major. The data show that on a scale of 1 to 6 the mean of technical students’ responses was 2.8602 compared to a mean of 2.8815 for liberal arts students. When the t-test was applied to the difference between mean scores, a probability of .816 was generated. 88 This level DID NOT satisfy the criterion for statistical significance. Table 51.--Comparison of technical students to liberal arts students on the variable course content in your major. No. of Standard t-Test Group Students Mean Deviation Probability Technical 186 2.8602 0.820 816 Liberal arts 135 2.8815 0.792 ° Table 52 reports on the variable out-of—class availability of instructors. The data show that on a scale of l to 6 the mean of technical students’ responses was 3.1264 compared to a mean of 3.2248 for liberal arts students. When the t-test was applied to the difference between mean scores, a probability of .329 was generated. This level 010 NOT satisfy the criterion for statistical significance. Table 52.--Comparison of technical students to liberal arts students on the variable out-of-class availability of instructors. No. of Standard t-Test Group Students Mean Deviation Probability' Technical 182 3.1264 0.898 Liberal arts 129 3.2243 0.341 ~329 89 Table 53 reports on the variable attitude of teaching staff toward students. The data show that on a scale of l to 6 the mean of technical students’ responses was 3.0160 compared to a mean of 3.0296 for liberal arts students. When the t-test was applied to the» difference between mean scores, a probability of .898 was generated. This level DID NOT satisfy the criterion for statistical significance. Table 53.--Comparison of technical students to liberal arts students on the variable attitude of teaching staff toward students. No. of Standard t-Test Group Students Mean Deviation Probability Technical 187 3.0160 0.964 Liberal arts 135 3.0296 0.339 '398 Table 54 reports on the variable variety of courses offered. The data show that on a scale of 1 to 6 the mean of technical students’ responses was 2.7487 compared to a mean of 2.7239 for liberal arts students. When the t-test was applied to the difference between mean scores, a probability of .772 was generated. This level DID NOT satisfy the criterion for statistical significance. 90 Table 54.--Comparison of technical students to liberal arts students on the variable variety of courses offered. No. of Standard t-Test Group Students Mean Deviation Probability Technical 187 2.7487 0.730 772 Liberal arts 134 2.7239 0.789 ° Table 55 reports on the variable class size relative to type of course. The data show that on a scale of 1 to 6 the mean of technical students’ responses was 2.7273 compared to a mean of 2.7185 for liberal arts students. When the t-test was applied to the difference between mean scores, a probability of .906 was generated. This level DID NOT satisfy the criterion for statistical significance. Table 55.--Comparison of technical students to liberal arts students on the variable class size relative to type of course. No. of Standard t-Test Group Students Mean Deviation Probability Technical 187 2.7273 0.635 906 Liberal arts 135 2.7185 0.676 ' Table 56 reports on the variable flexibility to design your program. The data show that on a scale of 1 to 6 the mean of technical students’ responses was 3.1029 compared to a mean of 91 2.9385 for liberal arts students. When the t-test was applied to the difference between mean scores, a probability of .119 was generated. This level 010 NOT satisfy the criterion for statistical significance. Table 56.--C0mparison of technical students to liberal arts students on the variable flexibility to design your program. No. of Standard t-Test Group Students Mean Deviation Probability Technical 175 3.1029 0.904 119 Liberal arts 130 2.9385 0.913 ° Table 57 reports on the variable availability of your advisor. The data show that on a scale of 1 to 6 the mean of technical students’ responses was 3.2128 compared to a mean of 3.3125 for liberal arts students. When the t-test was applied to the difference between mean scores, a probability of .371 was generated. This level 010 NOT satisfy the criterion for statistical significance. Table 57.--Comparison of technical students to liberal arts students on the variable availability of your advisor. No. of Standard t-Test Group Students Mean Deviation Probability Technical 141 3.2128 0.782 Liberal arts 112 3.3125 0.987 '37] 92 Table 58 reports on the variable value of information from advisor. The data show that on a scale of 1 to 6 the mean of technical students’ responses was 3.3310 compared to a mean of 3.2613 for liberal arts students. When the t-test was applied to the difference between mean scores, a probability of .581 was generated. This level DID NOT satisfy the criterion for statistical significance. Table 58.--Comparison of technical students to liberal arts students on the variable value of information from advisor. No. of Standard t-Test Group Students Mean Deviation Probability Technical 142 3.3310 0.928 581 Liberal arts 111 3.2613 1.076 ' Table 59 reports on the variable challenge offered by your program. The data show that on a scale of 1 to 6 the mean of technical students’ responses was 2.7935 compared to a mean of 2.8346 for liberal arts students. When the t-test was applied to the idifference' between mean scores, a probability of .622 was generated. This level 010 NOT satisfy the criterion for statistical significance. 93 Table 59.--Comparison of technical students to liberal arts students on the variable challenge offered by your program. No. of . Standard t-Test Group Students Mean Deviation Probability Technical 184 2.7935 0.732 622 Liberal arts 133 2.8346 0.730 ' Table 60 reports on the variable preparation you are receiving for occupation. The data show that on a scale of l to 6 the mean of technical students’ responses was 2.9149 compared to a mean of 3.0313 for liberal arts students. When the t-test was applied to the difference between mean scores, a probability of .214 was generated. This level DID NOT satisfy the criterion for statistical significance. Table 60.--Comparison of technical students to liberal arts students on the variable preparation you are receiving for occu- pation. No. of Standard t-Test Group Students Mean Deviation Probability Technical 188 2.9149 0.823 214 Liberal arts 128 3.0313 0.803 ' Table 61 reports on the variable general admissions procedure. The data show that on a scale of l to 6 the mean of technical students’ responses was 3.3656 compared to a mean of 3.2045 for liberal arts students. When the t-test was applied to the 94 difference between mean scores, a probability of .144 was generated. This level DID NOT satisfy the criterion for statistical significance. Table 61.-~Comparison of technical students to liberal arts students on the variable general admissions procedure. No. of Standard t-Test Group Students Mean Deviation Probability Technical 186 3.3656 0.979 ‘44 Liberal arts 132 3.2045 0.947 ° Table 62 reports on the ‘variable accuracy of college information received before enrolling. The data show that on a scale of 1 to 6 the mean of technical students’ responses was 3.3462 compared to a mean of 3.0709 for liberal arts students. When the t- test was applied to the difference between mean scores, a probability of .006 was generated. This level 010 satisfy the criterion for statistical significance. Therefore, it can be inferred that there was a statistically significant difference between technical and liberal arts students (”1 the variable- accuracy of college information. The data revealed that technical students were more satisfied with the college information received than were liberal arts students. This finding suggests that Henry Ford Community College may'want to conduct further investigation dealing with the accuracy of college information that liberal arts 95 students receive. Liberal arts students tend to transfer to four- year colleges, which requires that they take particular types of courses at the community college level. During their contact with the college before enrolling, liberal arts students were less satisfied than technical students. with the accuracy of college information they received before enrolling. Table 62.--Comparison of technical students to liberal arts students on the variable accuracy of college information received. No. of Standard t-Test Group Students Mean Deviation Probability Technical 182 3.3462 0.908 006 Liberal arts 127 3.0709 0.789 ° Table 63 reports on the variable availability of financial aid information. The data show that on a scale of 1 to 6 the mean of technical students’ responses Twas 3.6691 compared to a. mean of 3.3548 for liberal arts students. When the t-test was applied to the difference between mean scores, a probability of .022 was generated. This level 010 satisfy the criterion for statistical significance. Therefore, it can be inferred that there was a statistically significant difference between technical and liberal arts students on the variable availability of financial aid information. The data suggest that technical students were more 96 satisfied than liberal arts students with the availability of financial aid information. Table 63.--Comparison of technical students to liberal arts students on the variable availability of financial aid information. No. of Standard t-Test Group Students Mean Deviation Probability Technical 136 3.6691 1.096 022 Liberal arts 93 3.3548 0.868 ° Table 64 reports on the variable assistance provided by college staff. The data show that on a scale of 1 to 6 the mean of technical students’ responses 'was 3.4835 compared to a. mean of 3.4083 for liberal arts students. When the t-test was applied to the difference between mean scores, a probability of .513 was generated. This level DID NOT satisfy the criterion for statistical significance. Table 64.--Comparison of technical students to liberal arts students on the variable assistance provided by college staff. No. of Standard t-Test Group Students Mean Deviation Probability Technical 182 3.4835 0.973 Liberal arts 120 3.4033 0.933 .513 97 Table 65 reports on the variable catalog/admissions publications. The data show that on a scale of 1 to 6 the mean of technical students’ responses was 3.0919 compared to a mean of 2.9407 for liberal arts students. When the t-test was applied to the difference between mean scores, a probability of .100 was generated. This level DID NOT satisfy the criterion for statistical significance. Table 65.--Comparison of technical students to liberal arts students on the variable catalog/admissions publications. No. of Standard t-Test Group Students Mean Deviation Probability Technical 185 3.0919 0.826 100 Liberal arts 135 2.9407 0.790 ° Table 66 reports on the variable rules governing student conduct. The data show that on a scale of 1 to 6 the mean of technical students’ responses was 3.0914 compared to a mean of 2.9688 for liberal arts students. When the t-test was applied to the~ difference between mean scores, a probability of .164 was generated. This level DID NOT satisfy the criterion for statistical significance. 98 Table 66.--Comparison of technical students to liberal arts students on the variable rules governing student conduct. No. of Standard t-Test Group Students Mean Deviation Probability Technical 175 3.0914 0.768 164 Liberal arts 128 2.9688 0.742 ' Table 67 ‘reports on the variable student voice in college policies. The data show that on a scale of l to 6 the mean of technical students’ responses was 3.7391 compared to a mean of 3.6632 for liberal arts students. Nhen the t-test was applied to the difference between mean scores, a probability of .486 was generated. This level DID NOT satisfy the criterion for statistical significance. Table 67.--Comparison of technical students to liberal arts students on the variable student voice in college policies. No. of Standard t-Test Group Students Mean Deviation Probability Technical 138 3.7391 0.786 48 Liberal arts 95 3.6632 0.858 - 5 Table 68 reports on the variable academic probation and suspension policies. The data show that on a scale of l to 6 the mean of technical students’ responses was 3.6000 compared to a mean of 3.4762 for liberal arts students. When the t-test was applied to 99 the difference between mean scores, a probability of .275 was generated. This level DID NOT satisfy the criterion for statistical significance. Table 68.--Comparison of technical students to liberal arts students on the variable academic probation and suspension policies. - No. of Standard t-Test Group Students Mean Deviation Probability Technical 125 3.6000 0.852 75 Liberal arts 84 3.4762 0.719 '2 Table 69 reports on the variable purposes student activity fees used. The data show that on a scale of l to 6 the mean of technical students’ responses was 3.7550 compared to a mean of 3.7822 for liberal arts students. Nhen the t-test was applied to the difference between mean scores, a probability of .813 was generated. This level DID NOT satisfy the criterion for statistical significance. Table 69.--Comparison of technical students to liberal arts students on the variable purposes student activity fees used. No. of Standard t-Test Group Students Mean Deviation Probability Technical 151 3.7550 Liberal arts 101 3.7822 -313 100 Table 70 reports on the variable student government. The data show that on a scale of l to 6 the mean of technical students’ responses was 3.6695 compared to a mean of 3.5854 for liberal arts students. When the t-test was applied to the difference between mean scores, a probability of .411 was generated. This level DID NOT satisfy the criterion for statistical significance. Table 70.--Comparison of technical students to liberal arts students on the variable student government. No. of Standard t-Test Group Students Mean Deviation Probability Technical 118 3.6695 0.654 4]] Liberal arts 82 3.5854 ’ 0.785 ' Table 71 reports on the variable classroom facilities. The data show that on a scale of l to 6 the mean of technical students’ responses was 3.0160 compared to a mean of 2.9254 for liberal arts students. Nhen the t-test was applied to the difference between mean scores, a probability of .262 was generated. This level DID NOT satisfy the criterion for statistical significance. Table 7l.--Comparison of technical students to liberal arts students- on the variable classroom facilities. No. of Standard t-Test Group Students Mean Deviation Probability Technical 187 3.0160 0.714 Liberal arts 134 2.9254 0.711 ~25? lOl Table 72 ‘reports, on the variable industrial arts/shop facilities. The data show that on a scale of l to 6 the mean of technical students’ responses was 3.0127 compared to a mean of 3.4571 for liberal arts students. when the t-test was applied to the difference between mean scores, a probability of .010 was generated. This level 010 satisfy the criterion for statistical significance. Therefore, it can be inferred that there was a statistically significant difference between technical and liberal arts students on the variable industrial arts/shop facilities. The data revealed that technical students were less satisfied with the industrial arts/shop facilities than were the liberal arts students. This difference might be as a result of the fact that technical students’ courses required attending shop facilities more than liberal arts students because technical students must acquire certain skills and abilities before completing a technical program. Table 72.--Comparison of technical students to liberal arts students on the variable industrial arts/shop facilities. No. of Standard t-Test Group Students Mean Deviation Probability Technical 79 3.0127 0.870 1 Liberal arts 35 3.4571 0.741 -° ° Table 73 reports on the variable business-training facilities/ equipment. The data show that on a scale of 1 t0 6 the mean of 102 technical students’ responses was 3.5614 compared to a mean of 3.0808 for liberal arts students. when the t-test was applied to the. difference between mean scores, a probability of .000 was generated. This level DID satisfy the criterion for statistical significance. 'Therefore, it can be inferred that there *was a statistically significant difference between technical and liberal arts students on the variable business-training facilities/equip- ment. The data revealed that liberal arts students were less satisfied with business-training facilities/equipment than were their technical classmates. Because the business major is included in the liberal arts group, it would appear that liberal arts students were more aware of the business-training facilities and equipment and were more aware of the condition of the business- training facilities and equipment, and this may have accounted for the difference between the two groups. Table 73.--Comparison of technical students to liberal arts students on the variable business-training facilities/equipment. No. of Standard t-Test Group Students Mean Deviation Probability Technical 114 3.5614 1.081 Liberal arts 99 3.0808 0.841 .000 Table 74 reports on the variable laboratory facilities. The data show that on a scale of l to 6 the mean of technical students’ responses was 2.9396 compared to a mean of 2.9101 for liberal arts 103 students. Hhen the t-test was applied to the difference between mean scores, a probability of .743 was generated. This level DID NOT satisfy the criterion for statistical significance. Table 74.--Comparison of technical students to liberal arts students on the variable laboratory facilities. No. of Standard t-Test Group Students Mean Deviation Probability Technical 149 2.9396 0.628 743 Liberal arts 89 2.9101 0.733 ' Table 75 reports on the variable athletic facilities. The data show that on a scale of l to 6 the mean of technical students’ responses was 3.0808 compared to a mean of 3.0127 for liberal arts students. When the t-test was applied to the difference between mean scores, a probability of .542 was generated. This level DID NOT satisfy the criterion for statistical significance. Table 75.--Comparison of technical students to liberal arts students on the variable athletic facilities. No. of Standard t-Test Group Students Mean Deviation Probability Technical 99 3.0808 0.765 Liberal arts 79 3.0127 0.707 '542 104 Table 76 reports on the variable study areas. The data show that on a scale of 1 to 6 the mean of technical students’ responses was 3.1257 compared to a mean of 3.1094 for liberal arts students. When the t-test was applied to the difference between mean scores, a probability of .876 was generated. This level DID NOT satisfy the criterion for statistical significance. Table 76.-~Comparison of technical students to liberal arts students on the variable study areas. No. of Standard t-Test Group Students Mean Deviation Probability Technical 183 3.1257 0.826 87 Liberal arts 128 3.1094 1.006 ° 6 Table 77 reports on the variable student conInunity center/ student union. The data show that on a scale 0f 1 to 6 the mean of technical students’ responses was 3.2901 compared to a mean of 3.3246 for liberal arts students. When the t-test was applied to the~ difference between mean scores, a probability of .723 was generated. This level DID NOT satisfy the criterion for statistical significance. 105 Table 77.--Comparison of technical students to liberal arts students on the variable student community center/student union. No. of Standard t-Test Group Students Mean Deviation Probability Technical 162 3.2901 0.753 723 Liberal arts 114 3.3246 0.847 ° Table 78 reports on the variable college bookstore. The data show that on a scale of l to 6 the mean of technical students’ responses was 2.8830 compared to a mean of 2.8209 for liberal arts students. Nhen the t-test was applied to the difference between mean scores, a probability of .464 was generated. This level DID NOT satisfy the criterion for statistical significance. Table 78.--Comparison of technical students to liberal arts students on the variable college bookstore. No. of Standard t-Test Group Students Mean Deviation Probability Technical 188 2.8830 0.692 Liberal arts 134 2.8209 0.321 -454 Table 79 reports on the variable availability' of adequate housing. The data show that on a scale of l to 6 the mean of technical students’ responses was 3.8462 compared to a mean of 3.3571 for liberal arts students. Nhen the t-test was applied to the difference between mean scores, a probability of .052 was 106 generated. This level .010 satisfy the criterion for statistical significance. Therefore, it can be inferred that there was a statistically significant difference between technical and liberal arts students on the variable availability of adequate housing. The data suggest that technical students were more satisfied with the availability of adequate housing than were liberal arts students. Table 79.-~Comparison of technical students to liberal arts students on the variable availability of adequate housing. No. of Standard t-Test Group Students Mean Deviation Probability Technical 26 3.8462 0.732 052 Liberal arts 14 3.3571 0.745 ' Table 80 reports on the variable general condition of buildings. The data show that on a scale of 1 to 6 the mean of technical students’ responses was 2.7273 compared to a mean of 2.6567 for liberal arts students. When the t-test was applied to the difference between mean scores, a probability of .292 was generated. This level DID NOT satisfy the criterion for statistical. significance. 107 Table 80.--Comparison of technical students to liberal arts students on the variable general condition of buildings. No. of Standard t-Test Group Students Mean Deviation Probability Technical 187 2.7273 0.582 292 Liberal arts 134 2.6567 0.602 ° Table 81 reports on the variable general registration procedures. The data show that on a scale of l to 6 the mean of technical students’ responses was 3.3138 compared to a mean of 3.1481 for liberal arts students. When the t-test was applied to the difference between mean scores, a probability of .132 was generated. This level DID NOT satisfy the criterion for statistical significance. Table 81.--Comparison of technical students to liberal arts students on the variable general registration procedures. No. of Standard t-Test Group Students Mean Deviation Probability Technical 188 3.3138 0.932 1 Liberal arts 135 3.1431 1.026 ° 32 Table 82 reports on the variable availability of courses at times wanted. The data show that on a scale of l to 6 the mean of technical students’ responses was 3.6043 compared to a mean of 3.4361 for liberal arts students. When the t-test was applied to 108 the difference between mean scores, a probability of .197 was generated. This level DID NOT satisfy the criterion for statistical significance. Table 82.-~Comparison of technical students to liberal arts students on the variable availability of courses at times wanted. No. of Standard t-Test Group Students Mean Deviation Probability Technical 187 3.6043 1.175 ‘97 Liberal arts 133 3.4361 1.103 ° Table 83 reports on the variable academic calendar for this college. The data show that on a scale of 1 to 6 the mean of technical students’ responses was 4.2849 compared to a mean of 4.0373 for liberal arts students. When the t-test was applied to the difference between mean scores, a probability of .107 was generated. This level DID NOT satisfy the criterion for statistical significance. Table 83.--Comparison of technical students to liberal arts students on the variable academic calendar for this college. No. of Standard t-Test Group Students Mean Deviation .Probability Technical 186 4.2849 1.319 Liberal arts 134 4.0373 1.395 ~l°7 109 Table 84 reports on the variable billing and fee payment procedures. The data show that on a scale of 1 to 6 the mean of technical students’ responses was 3.8032 compared to a mean of 3.6288 for liberal arts students. When the t-test was applied to the difference between mean scores, a probability' of .176 was generated. This level DID NOT satisfy the criterion for statistical significance. Table 84.--Comparison of technical students to liberal arts students on the variable billing and fee payment procedures. _ N0. of Standard t-Test Group Students Mean Deviation Probability Technical 188 3.8032 1.151 17 Liberal arts 132 3.6288 1.103 - 5 Table 85 reports on the variable concern for you as an individual. The data show that on a scale of l to 6 the mean of technical students’ responses was 3.6559 compared to a mean of 3.5349 for liberal arts students. When the t-test was applied to the difference between mean scores, a probability' of .260 was generated. This level DID NOT satisfy the criterion for statistical significance. 110 Table 85.--Comparison of technical students to liberal arts students on the variable concern for you as an individual. No. of Standard t-Test Group Students Mean Deviation Probability Technical 186 3.6559 0.959 260 Liberal arts 129 3.5349 0.902 ° Table 86 reports on the variable attitude of college nonteaching staff. The data show that on a scale of l to 6 the mean of technical students’ responses was 3.5600 compared to a mean of 3.4250 for liberal arts students. When the t-test was applied to the difference between mean scores, a probability of .215 was generated. This level DID NOT satisfy the criterion for statistical significance. Table 86.-~Comparison of technical students to liberal arts students on the variable attitude of college nonteaching staff. No. of Standard t—Test Group Students Mean Deviation Probability Technical 175 3.5600 0.944 1 Liberal arts 120 3.4250 0.876 -2 5 Table 87 reports on the variable racial harmony at this college. The data show that on a scale of l to 6 the mean of technical students’ responses was 3.3029 compared to a mean of 3.3333 for liberal arts students. When the t-test was applied to 111 the difference between mean scores, a probability of .748 was generated. This level DID NOT satisfy the criterion for statistical significance. Table 87.--Comparison of technical students to liberal arts students on the variable racial harmony at this college. No. of Standard t-Test Group Students . Mean Deviation Probability Technical 175 3.3029 0.739 748 Liberal arts 126 3.3333 0.903 ' Table 88 reports on the variable college media. The data show that on a scale of l to 6 the mean of technical students’ responses was 3.3101 compared to a mean of 3.1217 for liberal arts students. When the t-test was applied to the difference between mean scores, a probability of .040 was generated. This level DID satisfy the criterion for statistical significance. Therefore, it can be inferred that there was a statistically significant difference between technical and liberal arts students on the variable college media. The data suggest that technical students were more satisfied with college media (college newspapers, campus radio, and so on) than were liberal arts students. It would appear that liberal arts students were required to interact more with college media than were technical students due to the nature of their college program. 112 Table 88.--Comparison of technical students to liberal arts students on the variable college media. No. of Standard ‘ t-Test Group Students Mean Deviation Probability Technical 158 3.3101 0.739 040 Liberal arts 115 3.1217 0.751 ' Table 89 reports on the variable this college in general. The data show that on a scale of l to 6 the mean of technical students’ responses was 2.8989 compared to a mean of 2.7704 for liberal arts students. When the t-test was applied to the difference between mean scores, a probability of .119 was generated. This level DID NOT satisfy the criterion for statistical significance. Table 89.--Comparison of technical students to liberal arts students on the variable this college in general. No. of Standard t-Test Group Students Mean Deviation Probability Technical 188 2.8989 0.728 Liberal arts 135 2.7704 0.732 -119 113 Results gf Hypothesis Tests Hypothesis 1: 'There is no difference between demographic attributes of the technical students and demographic attributes of the liberal arts students on the following 16 attributes: Hypothesis Hypothesis Attributes Agggptgd Rejected 3. age x b. ethnic identity x c. purpose for entering a two-year college x d. grade-point average x e. gender x f. marital status x 9. number of dependent children x h. hours employed per week x i. current enrollment status x j. years attended college of study x k. type of classes most frequently attended x l. pre-entrance academic history x m. proximity to campus x n. financial aid status x 0. current area of study x p. occupational choice x Based on the 16 attributes of Hypothesis 1, the research showed that ten attributes revealed no statistically significant difference between technical and liberal arts students. These attributes were ethnic identity, grade-point average, gender, number of dependent children, hours employed per week, current enrollment status, years attended college of study, type of classes most frequently attended, proximity to campus, and financial aid status. However, there was a statistically significant difference between groups on six of the attributes where the null hypothesis was rejected. These attributes were age, purpose for entering two-year college, marital status, pre-entrance academic history, current area of study, and occupational choice. 114 Turning to the six attributes that showed a significant difference between technical and liberal arts students indicates that the technical students had a greater percentage of the population between 26 and 39 years of age. In other words, the technical students had 39.4% as compared to 21.5% of the liberal arts students who were between the ages of 26 and 39. 'The technical students had a larger population of older students. The second attribute that revealed a significant difference was purpose for entering Henry Ford Community College. The data revealed that 70.7% of the technical students compared to 46.7% of the liberal arts students had entered Henry Ford Community College for the purpose of obtaining an associate degree. It would appear that from evaluating the characteristics of the technical-student population and the nature of the skills and abilities that this program requires, one would find more technical students entering for the purpose of obtaining associate degrees because the technical program is geared toward completion of a two-year degree with the skills to enter the job market. On the other hand, the data indicated that 35.4% of the liberal arts students compared to 15.4% of the technical students entered for the purpose of transferring to a four-year college. Because of the nature of the liberal arts program, it may be important to point out that liberal arts students enter more for the purpose of transferring than for obtaining an associate degree. 115 The third attribute on which there was a significant difference between groups was marital status. The data revealed that 77.8% of the liberal arts students compared to 64.4% of the technical students were unmarried, and 35.1% of the technical students compared to 21.5% of the liberal arts students were married. These percentages suggest that technical students are more likely to be married than liberal arts students. Marital status may influence the selection of a technical program due to the nature of the program, which is geared to provide the student with job-entry skills. Conversely, with liberal arts students the data revealed that students are less likely to be married and their purpose for entering is more likely to be the interest in transferring to a four-year school. The fourth attribute, pre-entrance academic history, revealed a significant difference between technical and liberal arts students. That is, 38.8% of the technical students compared to 54.1% of the liberal arts students entered directly from high school; 35.6% of the technical students compared to 20.7% of the liberal arts students entered after working. The data suggest that technical students are more likely than liberal arts students to have entered college after working. Liberal arts students are more likely to have entered Henry Ford Community College directly out of high school. The fifth attribute on which there was a significant difference between groups was current area of study. Sixty percent of the liberal arts students compared to none of the technical students 116 indicated their current area of study was business/commerce; 30.9% of the technical students compared to none of the liberal arts students indicated computer science was their current area of study. The difference in courses required by the technical and liberal arts programs accounts for the students’ current areas of study. The sixth attribute on which technical and liberal arts students differed significantly was occupational choice. Specifically, 30.4% of the technical students compared to 3.1% of the liberal arts students indicated computer science was their occupational choice; 51.5% of the liberal arts students compared to 1.1% of the technical students said business/comerce was their choice of occupation. Occupational choice interacts with current area of study because the latter usually influences the former. These two attributes revealed a significant difference between the two groups because of the different skills or courses that each group is required to acquire. Therefore, the null hypothesis was rejected because of the variables age, purpose for entering two-year college, marital status, pre-entrance history, current area of study, and occupational choice being subsumed under Hypothesis 1. Hypothesis 2: There is no difference between response rates of liberal arts students and response rates of technical students ggnférenzing the following 13 reasons for attending a two-year Hypothesis Hypothesis ea 5 39.32030 B..i.s:c_e_ee a. convenience of location x b. course offerings x c. low cost x 117 d. ability for working while attending x e. vocational or academic reputation x f. social atmosphere x 9. size of college x h. opportunity for personal success x i. availability of scholarship or financial aid x j. advice of parents or relative x k. advice of high school professionals x l. ability to be with friends x m. rating of college at the time x Based on the 13 reasons for choosing to attend Henry Ford Community College, the data revealed that there were ten reasons on which Hypothesis 2 was accepted. The ten reasons on which there were no significant differences between technical and liberal arts students were convenience of location, low cost, ability for working while attending, vocational or academic reputation, social atmosphere, opportunity for personal success, availability of scholarships or financial aid, advice of parents or relative, ability to be with friends, and rating of college at the time. However, there were three reasons on which significant differences were found between technical and liberal arts students. These three reasons were course offering, size of college, and advice of high school professionals. Focusing on these three reasons, 79.1% of the technical students compared to 55.5% of the liberal arts students selected importance of courses that students wanted as a major reason for selecting Henry Ford Community College.- The data suggest that it is more important for technical students than for liberal arts students to obtain the courses they want. The technical students are more confined to particular courses because 118 of the need to acquire adequate technical skills in a limited time. On the other hand, liberal arts students have the option to select more than one specific class to satisfy academic requirements. The second reason for selecting Henry Ford Community College on which the two groups differed significantly was size of college. Specifically, 38.6% of the liberal arts students compared to 27.5% of the technical students chose "liked the size of the college" as a reason for attending the college. The data suggest that a greater percentage of liberal arts students than technical students were concerned with the size of the college. The third reason for selecting Henry Ford Community College on which a significant difference was noted between groups was advice of high school counselor. That is, 15.7% of the technical students compared to 29.2% of the liberal arts students mentioned this reason for attending the college. The data indicated that a greater percentage of liberal arts than technical students selected "advice of high school counselor" as a reason for attending Henry Ford Community College. Therefore, the null hypothesis was rejected due to the variables course offerings, size of college, and advice of high school professionals being subsumed under Hypothesis 2. Hypothesis 3: There is no difference between technical students’ responses and liberal arts students’ responses to the following questions: Hypothesis Hypothesis mm a. If you could start college over, would you choose to attend this college? x b. What is your overall impression of the quality of education at this college? x 119 Based on the two items relative to Hypothesis 3, the research data showed no significant differences between technical and liberal arts students. Therefore, the null hypothesis was accepted. Hypothesis 4: There is no difference between levels of satisfaction of liberal arts students and levels of satisfaction of technical students with the following 18 services: Hypothesis Hypothesis t Serviees Rejected academic advising personal counseling vocational guidance job placement financial aid recreational and intramural programs library/learning resources residence halls student health student employment cafeteria/food college—sponsored social activities cultural programs and activities college orientation computer usage parking facilities veteran programs day care 1DUODB-‘X’U-d-3'CO-hmnnc'm XXXXXXXXXXXXXXXXXX Based on the 18 services listed in Hypothesis 4, the data revealed no significant differences between technical and liberal arts students regarding these services. Therefore, Hypothesis 4 was accepted. 120 Hypothesis 5: There is no difference between levels of satisfaction of liberal arts students and levels of satisfaction of technical students with the following 11 academic aspects of the college: Hypothesis Hypothesis Academic Aspects Accepted Rejected testing/grading x course content in major area of study availability of instructors attitude of teaching staff variety of course offerings class size flexibility to design own program availability of advisor advisor input academic challenge of course of study preparation for chosen occupation Ngu—a-(QLO-thnO’D-t XXXXXXXXXX Based on the 11 academic attributes of the college, there was one aspect that resulted in a significant difference between groups. This aspect was testing and grading. The data revealed that technical students were more satisfied than liberal arts students with the testing and grading system at Henry Ford Community College. The other academic attributes did not reveal any significant differences. The attributes on which no significant differences were revealed were course content in major area of study, availability of instructors, attitude of teaching staff, variety of course offerings, class size, flexibility of advisor, availability of advisor, advisor input, academic challenge of course of study, and preparation for chosen occupation. Therefore, the null hypothesis was rejected due to the variable testing and grading being subsumed under Hypothesis 5. 121 Hypotheeis 6: There is no difference between levels of satisfaction of liberal arts students and levels of satisfaction of technical students with the following five recruitment activities: Hypothesis Hypothesis Recruitment Activities Aeeepteg Rejeeted a. admission entry procedures x b. information received before enrolling x c. availability of financial aid informa- tion before enrolling x d. staff assistance x e. college catalog/admissions information x Based on the fjve recruitment activities subsumed under Hypothesis 6, the research showed that three activities showed no significant differences between groups. These activities were admission entry procedures, staff assistance, and college catalog/ admissions information. On the other hand, there were two recruitment activities on which the research revealed significant differences. These activities were information received before enrolling and availability of financial aid information before enrolling. In the two above recruitment areas the null hypothesis was rejected. Concerning availability of financial aid information before enrolling, the mean for technical students was 3.6691 compared to a mean of 3.3548 for liberal arts students. These data show that technical students were more satisfied with the availability of financial aid information. The «data suggest that liberal arts students may have a greater need for such information. The data also suggest that a greater percentage of liberal arts students come to the college directly from high school, compared to a larger 122 percentage of technical students who tend to work before coming to the community college. The other recruitment activity that revealed a significant difference between groups was information received before enrolling. The mean for technical students was 3.3462 compared to a mean of 3.0709 for liberal arts students. Therefore, the data suggest that technical students are more satisfied than liberal arts students. with the college information received. Therefore, the null hypothesis was rejected due to the variables information received before enrolling and availability of financial aid information before enrolling being subsumed under Hypothesis 6. Hypothesis 7: There is no difference between levels of satisfaction of technical students and levels of satisfaction of liberal arts students with the following five student-focused activities: Hypothesis Hypothesis Activities Accepted Bejeeted rules governing student conduct student government input on policies academic probation purposes for activity fees (DQOU'ID XXXXX Based on the five students-focused activities subsumed under Hypothesis 7, the research revealed that no significant differences were found between the two groups on these activities. The five activities were rules governing student conduct, student government, input on policies, academic probation, and purposes for activity fees. Therefore, the null hypothesis was accepted. 123 Hypothesis 8: There is no difference between levels of satisfaction of liberal arts students and levels of satisfaction of technical students with the following ten activities: Hypothesis Hypothesis Activities Aeeepted Bejeeted a. classrooms x , b. industrial arts/shop x c. business training equipment x d. laboratory x e. athletics x f. study areas x 9. student center/union x h. bookstore x i. availability of adequate housing x j. appearance of buildings and grounds x Based on ‘the ten activities of' Hypothesis» 8, the research revealed that there was no significant difference between groups on eight activities. Those activities were classrooms, equipment, laboratory, athletics, study areas, student center/union, bookstore, availability of adequate housing, and appearance of buildings of grounds. The two activities on which there were significant differences were industrial arts/shop and business training equipment. The mean of technical students’ responses was 3.0127 compared to a mean of 3.4571 for liberal arts students on industrial arts/shop facilities. Therefore, the data suggest that technical students are less satisfied with the industrial arts/shop facilities than are liberal arts students. This difference might be a result of the fact that technical students’ courses require their using shop facilities more than liberal arts students due to the skills and abilities that technical students acquire before completing a technical program. 124 On the other hand, the research revealed that liberal arts students were significantly less satisfied than technical students with the business-training facilities and equipment. The data showed that the mean for technical students’ responses was 3.5614 compared to a mean of 3.0808 for liberal arts students. Therefore, the data suggest that because the business major is included in the liberal arts area, liberal arts students are more aware of the conditions of the business-training facilities and equipment than are technical students, and this may have accounted for the difference between the two groups. This speculation is further supported in that technical students, who are more involved in and aware of the technical arts/shop facilities and are in a better position to evaluate this area, were less satisfied than liberal arts students with the industrial arts/shop facilities. Therefore, the null hypothesis was rejected due to the variables industrial arts/shop and business training equipment being subsumed under Hypothesis 8. Hypothesis 9: There is no difference between levels of satisfaction of liberal arts students and levels of satisfaction of technical students with the following four conditions: Hypothesis Hypothesis Conditipps AQEQDLQQ Bejeeted - registration procedures x 0'93 availability of courses at convenient times x c. academic calendar x d. billing and fee-payment procedures x 125 Based on the four conditions of Hypothesis 9, the data indicated that no significant differences were found between groups on any of the conditions. These conditions were registration procedures, availability of courses at convenient times, academic calendar, and billing and fee payment procedures. Therefore, the null hypothesis was accepted. Hypothesi; 19: There is no difference between levels of satis- faction of liberal arts students and levels of satisfaction of technical students with the following five conditions: Hypothesis Hypothesis Conditions Accepted Bejeepeg a. concern for the individual x b. attitude of nonteaching staff toward students x c. racial harmony x d. college media x e. general atmosphere x Based on the five conditions of Hypothesis 10, the results suggest that there were four conditions on which no statistically significant differences were found between groups. These conditions were concern for the individual, attitude of nonteaching staff toward students, racial harmony, and general atmosphere. A statistically significant difference was found between technical and liberal arts students on the variable college media. The mean of technical students’ responses was 3.3101 compared to a mean of 3.1217 for liberal arts students. Therefore, the data suggest that technical students are more satisfied with college media (college newspapers, campus radio, and so on) than are liberal arts students. It would appear that liberal arts students are 126 required to interact with college media more than are technical students due to the nature of their college programs. Therefore, the null hypothesis was rejected due to the variable college media being subsumed under Hypothesis 10. 50333:! This chapter contained the results of the data analyses conducted for this study. Chapter V includes a summary of the study and conclusions and recommendations based on the research findings. CHAPTER V SUMMARY, CONCLUSIONS, AND RECOMMENDATIONS Sumac! Community colleges throughout the United States are being called on to educate as well as train massive numbers of individuals seeking new job skills, transfer courses, professional improvement, career guidance, academic advice, counseling, motivation, excellence in teaching, and personal and social involvement within the community college structure. These demands are increasing in an era of' new technologies. It is the responsibility of educational institutions such as community colleges, which must be able to address the characteristics of their student populations, institutional goals, and programs, to reveal whether or not the students and the institution are focusing on the same objective. Increased awareness of the student population’s concerns has the potential to influence students’ continuing to enroll at a particular college. Promotional strategies are now being employed at educational institutions because prospective students are potential consumers of a product called education. In the 1980s, colleges have begun aggressively to seek out students. Recruitment is no longer done by word of mouth. It is organized and planned. The plan is to 127 128 demonstrate that the institutions have a highly marketable, quality product. As we move into the 19905, more educational institutions will begin to guarantee their students’ satisfaction with the results of ‘their' education. For’ example, Henry Ford Community College is one of the first community colleges to offer a written guarantee of job skills to graduates of associate degree programs in occupational studies and course—credit transferability to liberal arts students.' Henry Ford Community College has become more accountable to its students, who are the consumers of education. One must first identify the demographic background of the educational consumers. Then the services, programs, impressions, and environment of the college can be evaluated. Conclusions and Recommendations In the following pages, each of the ten hypotheses is restated, followed by the conclusions regarding that hypothesis and pertinent recommendations for further research. Hypothesis 1 There is no difference between demographic attributes of the technical students and demographic attributes of the liberal arts students on the attributes of age, ethnic identity, purpose for entering a two-year college, grade-point average, gender, marital status, number of dependent children, hours employed per week, current enrollment status, years attended college of study, type of classes most frequently attended, pre-entrance academic history, proximity to campus, financial aid status, current area of study, and occupational choice. Conclusions. The data revealed that the null hypothesis was rejected due to the attributes of age, purpose for entering a two- year college, marital status, pre-entrance history, current area of 129 study, and occupational choice being subsumed under Hypothesis 1. Based on these findings, the researcher concluded that there was a statistically significant difference between technical and liberal arts students on the attributes of age, purpose for entering a two- year college, marital status, pre-entrance history, current area of study, and occupational choice. Turning to the first of the six attributes, it was concluded that there was a significant difference between technical and liberal arts students in terms of age. Significantly more technical students than liberal arts students were between the ages of 26 and 39. Concerning the second attribute, purpose for entering a two- year college, significantly more technical than liberal arts students entered Henry Ford Community College for the purpose of obtaining an associate degree. 0n the other hand, significantly more liberal arts than technical students entered Henry Ford Community College for the purpose of taking the necessary courses for transferring to a four-year college or university. Concerning the third attribute, marital status, technical students were found to be more likely to be married than were liberal arts students. ' On the fourth attribute, pre-entrance academic history, technical students were more likely than liberal arts students to have entered Henry Ford Community College after working. Liberal 130 arts students were more likely to have entered the college directly out of high school. 0n the fifth attribute, current area of study, significantly more technical students than liberal arts students were studying computer science. The current area of study of significantly more liberal arts than technical students was business/commerce. For' the sixth attribute, occupational choice, significantly more technical students than liberal arts students indicated computer science as their chosen field. (M1 the other hand, significantly more liberal arts students than technical students mentioned business/commerce as their occupational choice. In conclusion, technical students at Henry Ford Community College appeared to have a larger population of older students between the ages of 26 and 39 who more than likely were married and had worked before attending Henry Ford Community College with the purpose of obtaining an associate degree with a major in computer science. The liberal arts students had a larger population of younger students between the ages of 19 and 25 who were unmarried and attended Henry Ford Community College directly out of high school with a major in business/commerce. Recpmmendations. l. Focusing on the variable age, it is recommended that Henry Ford Community College staff consider this attribute in their instructional method. It has been suggested in the literature that the learning process of more mature (older) returning adults may be different from that of younger adults. Henry Ford Community College 131 staff should evaluate the college’s services and programs in light of the different age groups, which may have different learning styles. In addition, further research may need to be conducted, looking at the variable age and what role it plays in the college environment. 2. A continued effort needs to be made to inform technical students of the requirements of obtaining an associate degree at Henry Ford Community College. In addition, there needs to be a continued effort to inform liberal arts students of the requirements to transfer to four-year colleges. 0n the issue of two-year versus four-year colleges, further research might be useful to evaluate the satisfaction levels of two-year-college graduates with those of four-year-college graduates. 3. Henry Ford Community College staff should insure that mar- ried students are provided with social-cultural programs that include spouses and children. In other words, in light of the large proportion of technical students who are married, there should be a double goal of‘ providing programs that meet the needs of both married and unmarried students at the college. Educational institu- tions at all levels have been geared toward the unmarried student. However, with a large population of older returning students, the data revealed that there was a statistically significant difference between technical and liberal arts students on the variable marital status. Further research may be needed to explore the marital status of students and its effect on attending college. 132 4. Henry Ford Community College staff should take into consid- eration that a large number of technical students have worked before coming to the college. This work experience may place technical students at a learning level at which they can relate work experiences to their' current classroom setting. However, many liberal arts students have had no work experience and may need to be introduced to the world of work by way of college work-study and on-campus jobs, as well as other work-placement sources. Further research may be helpful if it can be determined whether work experi- ence has a negative or positive influence on college completion. 5. With regard to the current area of study, it is recommended that staff of Henry Ford Community College be aware that there is a large population of technical students whose current area of study is computer science and that there is a large population of liberal arts students whose area of study is business/commerce. It is further suggested that, when offering computer science and business/ commerce classes, the college ensure that there are enough sections for these students. Not only does this need to be done or continue to be done for computer science and business/commerce classes, but student demand for courses and supply of these courses need to be evaluated on a continuous basis. 6. Staff members of Henry Ford Community College need to be aware that a large population of technical students have computer science as an occupational choice, and a large population of liberal arts students have chosen business/commerce. To that end, college staff should develop and refine occupational placement 133 opportunities, when possible, which will provide employment opportunities in the area of the student’s occupational choice. Hypothesis 2 There is no difference between response rates of liberal arts students and response rates of technical students concerning the following reasons for attending a two-year college: convenience of location, course offerings, low cost, ability for working while attending, vocational or academic reputation, social atmosphere, size of college, opportunity for personal success, availability of scholarship or financial aid, advice of parents or relative, advice of high school professionals, ability to be with friends, and rating of college at the time. Conclusions. This null hypothesis was rejected due to statistically significant differences between technical and liberal arts students on the attributes of course offerings, size of college, and advice of high school professionals being subsumed under Hypothesis 2. The data on course offerings suggested that it was more important for technical than liberal arts students to obtain the courses they wanted. The second reason for selecting Henry Ford Community College was size of college. It was concluded that a larger percentage of liberal arts than technical students attended Henry Ford Community College because of its size. The third reason for attending revealed that a greater percentage of liberal arts than technical students attended because of the advice of their high school counselors. In conclusion, technical students at Henry Ford Community College attended this college because it offered the desired courses. Howeverx a ‘lower percentage cited size of’ college and 134 advice of the high school counselor as a reason for attending than did liberal arts students. Liberal arts students were less likely than technical students to attend Henry Ford Community College for the courses it offered. However, liberal arts students were more likely than technical students to attend the college because of its size and the advice of their high school counselors. Recommendatipns. 1. Currently, technical students are given the opportunity to enroll in their classes earlier than liberal arts students because of their program requirements. A greater number of technical than liberal arts students indicated that the course offerings were a major reason for attending Henry Ford Community College. Technical students were more concerned about course offerings than liberal arts students. Therefore, it is this researcher’s opinion that the college should continue to enroll technical students early. 2. The college should maintain and improve its relationships with high school counselors because a small percentage of both liberal arts and technical students students were attending Henry Ford Community College because of advice from their high school counselors. It might be beneficial to make high school counselors more aware of the technical programs that are available to students at Henry Ford Community College. 3. Henry Ford Community College staff should be aware that many liberal arts students attend the college because of its size. 135 Hypothesig 3 There is no difference between technical students’ responses and liberal arts students’ responses to the following ques- tions: If you could start college over, would you choose to attend this college? What is your overall impression of the quality of education at this college? Cpnclgsions. The data revealed that the null hypothesis was accepted because there *was no statistically significant between technical and liberal arts students on the items subsumed under Hypothesis 3. Hypothesis 4 There is no difference between levels of satisfaction of liberal arts students and levels of satisfaction of technical students with the following services: academic advising, personal counseling, vocational guidance, job placement, financial aid, recreational and intramural programs, library/ learning resources, residence halls, student health, student employment, cafeteria/food, college-sponsored social activi- ties, cultural programs and activities, college orientation, computer usage, parking facilities, veteran programs, and day care. Conclusions. The data supported the null hypothesis because there was no statistically significant difference between technical and liberal arts students on any of the 18 services. Hypothesis 5 There is no difference between levels of satisfaction of. liberal arts students and levels of satisfaction of technical students with the following academic aspects of the college: testing/grading, course content in major area of study, availa- bility of instructors, attitude of teaching staff, variety of course offerings, class size, flexibility to design own program, availability of advisor, advisor input, academic chal- lenge of course of study, and preparation for chosen occupa- tion. 136 Conclusions. The null hypothesis was rejected due to the academic aspect of testing/grading being subsumed under Hypothesis 5. The data revealed that technical students were more satisfied with the testing and grading system at Henry Ford Community College than were liberal arts students. Recommendation. Further* evaluation should be made of the testing and grading of liberal arts students to discover why they were less satisfied with these practices than were technical students. H ot sis 6 There is no difference between levels of satisfaction of liberal arts students and levels of satisfaction of technical students with the following recruitment activities: admission entry procedures, information received before enrolling, avail- ability of financial aid information before enrolling, staff assistance, and college catalog/admissions information. Conclusions. The data provided evidence to reject the null hypothesis due to two recruitment activities: information received before enrolling and availability of financial aid information before enrolling. These data showed that technical students were more satisfied than liberal arts students with the availability of financial aid information. The data further suggested that liberal arts students may have a greater need than technical students for financial aid information. In addition, the data revealed that a greater percentage of liberal arts students came to the college directly from high school, in comparison to technical students, who tended to work before coming to the community college. Perhaps the fact that liberal arts students had not worked before attending may 137 explain why they were less satisfied with the availability of financial aid information. The data also suggested that technical students were more satisfied with the information received before enrolling at Henry Ford Community College. Recpmmendetipne. 1. Henry Ford Community College staff may want to conduct further investigation dealing with the accuracy of college information that liberal arts students receive. 'This is an important issue because liberal arts students tend to transfer to four-year colleges, which require particular types of courses. It should be noted that liberal arts students in this study were less satisfied than technical students with college information they received before enrollment. The college should evaluate the accuracy of information provided before enrollment, which is an admissions function. 2. Henry Ford Community College staff should investigate whether there is a greater need for financial aid information on the part of liberal arts students than technical students. Hypothesis 7 There is no difference between levels of satisfaction of technical students and levels of satisfaction of liberal arts students with the following student-focused activities: rules governing student conduct, student government, input on policies, academic probation, and purposes for activity fees. Conclgsippe. The data revealed that the null hypothesis was accepted because there was no statistically significant difference 138 between technical and liberal arts students concerning the student- focused activities subsumed under Hypothesis 7. H!22Lh§§i§.§ There is no difference between levels of satisfaction of liberal arts students and levels of satisfaction of technical students with the following activities: classrooms, industrial arts/shop, business training equipment, laboratory, athletics, study areas, student center/union, bookstore, availability of adequate housing, and appearance of buildings and grounds. Conclusions. The research data showed that the null hypothesis could be rejected due to the activities of industrial arts/shop and business training equipment being subsumed under Hypothesis 8. Technical students were less satisfied than liberal arts students with the industrial arts/shop facilities. On the other hand, liberal arts students were less satisfied than technical students with business training equipment. It appears that students who had direct experience with industrial arts/shop facilities and business training equipment were less satisfied with these areas than students who did not have direct experience. Recommendatipns. 1. Henry Ford Community College staff should investigate low levels of satisfaction of technical students with the industrial arts/shop facilities. 2. Henry Ford Community College staff should investigate low levels of satisfaction of liberal arts students with business training equipment. l39 Hypothesis 9 There is no difference between levels of satisfaction of liberal arts students and levels of satisfaction of technical students with the following conditions: registration proce- dures, availability of courses at convenient times, academic calendar, and billing and fee-payment procedures. Conclpsions. The data showed that the null hypothesis could be accepted because there was no statistically significant difference between technical and liberal arts students concerning the items subsumed under Hypothesis 9. Hypothesis 10 There is no difference between levels of satisfaction of liberal arts students and levels of satisfaction of technical students with the following conditions: concern for the indi- vidual, attitude of nonteaching staff toward students, racial harmony, college media, and general atmosphere. n l s' n . The data revealed that the null hypothesis could be rejected due to the condition of college media, which was subsumed under Hypothesis 10. The data suggested that technical students were more satisfied than liberal arts students with college media (such as college newspapers and campus radio). It appears that, due to their involvement with the college media, liberal arts students gained more insight into this area than did technical students. Reeommendation. Henry Ford Community College staff should evaluate college media (for example, college newspapers and campus radio) in terms of the involvement and participation of liberal arts students. 140 Finally, the data revealed that on six out of the ten hypotheses significant differences were found between technical and liberal arts students concerning particular variables. Finel Thouqhts Henry Ford Community College rings with the excitement of celebration for its fiftieth anniversary. It has grown into a comprehensive community college, with even greater challenges anticipated during the next 50 years. During the ending years of the 19805, it is time to make plans for even greater academic success and educational excellence, more community involvement, and increased partnerships with business and industry. All of these areas promote student involvement and success, which are essential for a comprehensive community college. It will not be acceptable or profitable, however, to sponsor programs without some research and evaluation. The mission of the comprehensive community college will, by necessity, be one of evaluation, planning, research, and assessment. As a result of this research endeavor, it is recommended that Henry Ford Community College further investigate the levels of satisfaction of the entire student body because the target population in this study was degree candidates. In addition, the "level" of satisfaction, although favorable, might not be as high as it should be. Is being satisfied enough? Does the college need to evaluate ways to make the total population more satisfied? It is assumed that students who graduate from the college with degrees are 141 going to be more satisfied with the institution than those who have not completed the degree. This particular study revealed that there is a need for this research project to be evaluated very carefully to identify trends in the target group which may also be present in the total group. There appears to be a strong case for continuing to conduct research projects on the characteristics of the student population to further assess changes that might occur in the student body from one year to the next. As a result of this research project, the following observations and recommendations are directed especially toward the faculty and staff at Henry Ford Community College: 1. Henry Ford Community College should consider the variable of age in their instructional methods and make a continued effort to inform technical and liberal arts students about program requirements. It should be known that a greater percentage of technical students are married than liberal arts students. A large number of technical students have worked before coming to school. Technical students have a greater percentage of students in the computer science area of study, and liberal arts students have a greater percentage of students in the business/commerce area of study. 2. The college should continue to enroll technical students early. The relationship with high school counselors should be maintained and improved upon. In regard to liberal arts students, many attend the college due to its size. 142 3. The college needs to be aware that there were no signifi- cant differences in the 18 service areas, but it is important to note that both groups were neutral in regard to their level of satisfaction. This is an area that needs further investigation. Other areas worthy of examination are testing and grading, accuracy of college information liberal arts students receive before enrolling, and need for financial-aid information for liberal arts students. 4. Technical students are less satisfied with the industrial arts/shop facilities than are liberal arts students, and liberal arts students are less satisfied with business training equipment than are technical students. College media (such as college newspapers and campus radio) is another area that needs further investigation. In conclusion, it must be stressed that in order to understand the true characteristics of the student population, which changes from year to year, there must be some form of continuous updating in the research and evaluation area. As a first step in this direction, an executive summary of this research project will be provided to Henry Ford Community College. APPENDIX 143 .29. ._< .2596... 9.5;. 33:60 52:06; a... .... .5: . O 3 . :25 2 n _ I u: . 2...: c. E): C Star. :6» . - ES. .2232}; C .... .13! 3 u 39.—w- 130400 7...} ... R . . 3 wt» ’ . .. <>0 whiilOBt< I» O .....1 i .. C .... e 9:: -211... on}; :35... m ® 8.00..- ..o 3.. E.» ..< 3.3. ...... 3 . 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Simply ignore the extra ovals. ll no additional ques- 17 tions are included. leave this section blank. ©©©®©®®©G®®® 16 ©~©©©®®®©®®®® 15 ®©®®®®©©®®®9 14 ®®®®®®©©®®®© 13 ©®®©®®®©CD®®© 12 ®®©©©©©®®®®® 11 SECTION VIE-ADDITIONAL ouesrlous ®©©©®®®©®®®® 10 ©©®©®®®©®®® 9 SECTION VI—COMMENTS AND SUGGESTIONS ®®®©®®©©®®®© ©®©©®©©®®®®® ©®®®®®®®®®®Q ©©®Gi®©®®®®®é§ ©®®©®®®©®®®® ©©®®®©©®®®®3 ®©®®®©®®®®®® ©®®©®®©~D®®®® u on additional set at multiple-choice questions is included with this term. please use this section to record your responses. Twelve ovals are provided tor each question. but low It you wish to make any comments or suggestions concerning this college. please use the lines provided below. ©®®®~D©©®®®®® L DO NOT WRITE BELOW MS LINE. BIBLIOGRAPHY BIBLIOGRAPHY American College Testing Evaluation/Survey Services. Ueer’e guide. 3rd ed. Iowa City: Author, l985. Barnard, Leahbeth Hitchcock. ”Evaluation of the Efficacy of a Career Development Class on the Retention of Undeclared Students at Arapahoe Community College.” Ph.D. dissertation, University of Northern Colorado, 1983. Bergquist, Sidney R. ew Web ter’ Dicti n r h n i Language. Chicago: Consolidated Book Publishers, 1976. Brown, Oliver J., and Brown, Lester B. ”College and University Minority Recruitment: Barriers, Recruitment Principles, and Design Guidelines." Journal of College Student Development 29 (January 1988). Campbell, Cal. "Predicting Which Freshmen Hill Drop 0ut--A Measure of College Persistence.” Pendleton, S.C.: ACCTion Consortium, 1987. Carroll, Juollie. ”Freshman Retention and Attrition Factors at a Predominantly Black Urban Community College.” geurnel ef College Student Qevelepment 29 (January l988). Cope, Nancy R., and Tomlinson, Saundra M. "Characteristics of Black Students Seeking Help at a University Counseling Center." Journal of College Student Development 29 (January l988). Deegan, William L., and Tillery, Dale. Renewing the American Community College. San Francisco: Jossey-Bass, 1985. “Toward a Fifth Generation of Community Colleges: Seven Priorities for Action.” gommunity, Technieal, end Jgnjer Cellege Journgl (April/May 1987): 39. Fong, Bernardine Chuck. ”Community College Instructors’ Attitudes and Their Relationship to Student Attrition." Ph.D. disserta- tion, Stanford University, 1983. Hays, Hilliam L. Statistics. New York: Holt, Rinehart, and Winston, l98l. 147 148 Henry Ford Community College. atalo 98 - . Dearborn, Mich.: Author, 1987. ram u . Dearborn, Mich.: Author, n.d. Jones, Steven. ”No Magic Required: Reducing Freshman Attrition at Community College.” Qemmunity College Review 14,2 (1986): 17. . "Retention Activities That Work.” Aggijeg Center EBAC Neg; (1982). Kickels, Mary Kay. "The Relationship Between Participation in a Personalized Admissions Program and the Recruitment and Retention of Community College Students.” Ph.D. dissertation, Northern Illinois University, 1982. Koltai, L., and Thurston, A. "The Community Colleges." In American Junier tollegee. 8th ed. Edited by E. S. Gleazer, Jr., and J. F. Cooke. Washington, D.C.: American Council on Education, 1971. Lombardi, John. ommu it du ation: hr C l e S a . Los Angeles: ERIC Clearinghouse for Junior Colleges, University of California, Los Angeles, 1978. Long, James P. ”Evaluating Occupational Programs." tommugity College_ngieu 14,3 (1986-1987): 43. Mallinckrodt, Brent. ”Student Retention, Social Support, and Dropout Intention: Comparison of Black and White Students." Jourgel ef tollege Student Qevelogment 29,1 (1988). McCauley, Diana Pollard. "Effects of Specific Factors on Blacks’ Persistence at a Predominantly White University." Jegrgel ef lle e S uden Dev lo men 29,1 (1988). Mitchell, James V. The Ninth Mentel Measurement Yearboek. Lincoln, Neb.: Buros Institute of Mental Measurements, 1985. Neumann, William F. I'Persistence in the Community College: The Student Perspective (Attrition, Drop-Out).” Ph.D. dissertation, Syracuse University, 1985. North and Handson. “Evaluating Vocational Programs." Jeurnal ef the Amerieeg Assocjetieg of Community end ggnjer tollegee 43,3 (1976): 28-30. 149 O’Banion, Terry, and Thurston, Alice. ”Student Development Programs in the Community Junior College.” In The Crueial Bple pf Stupent Eerepnne! §erviee§ in the Dgnio: College, p. 9. Edited by Leland L. Medsker. Englewood Cliffs, N.J.: Prentice-Hall, 1972. Palmer, Jim. ”What Do We Know About Community College Vocational Students? An ERIC Review." Community Cpllege Reyiew 14,1 (1986). Pascarella, Ernest T. ”Students’ Affective Development Within the College Environment." Dpurnal pf Higher Edgeetjpn 56,6 (1985). Raines, Max. ”Characteristics of Junior College Students." In Eerepeetive on the Community-Junior College. Edited by William Dgilvie and Max Raines. New York: Appleton-Century-Crofts, 97 . Reynolds, James W. h m r hensiv unior 11 e ur i l m. New York: McCutchan, 1969. Seale, Robert. "A Structural Mode1 for Explaining Retention and Attrition in a Community College." Ph.D. dissertation, University of Houston, 1984. Solomon, Roger B. A Different Drummer: The_CCC_Cpllege. Atlanta, Ga.: Life-Long Learning, 1976. Thornton, James W., Jr. The Community Junior College. New York: John Wiley and Sons, 1972. Wallace, Elaine. "The Effect of Student Faculty and Student Adminis- trations’ Relationship on Attrition--A Comparison of Two Science Career Programs at Wayne County Community College." Ph.D. dis- sertation, The University of Michigan, 1980. Williams, Thelma M., and Leonard, Mary M. "Graduating Black Under- graduates: The Step Beyond Retention." ourna f 1 Student Development 29,1 (1988). Wisgoski, Alfred. "Characteristics of Junior College Students: Implications for Faculty and Student Personnel Specialists.” In Eerspectivee on the Cpmmunity-Junjor Cpllegfi. pp. 183-84. Edited by William Ogilvie and Max Raines. New York: Appleton- Century-Crofts, 1971. "liliilii'iillilliis