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(‘1... 1 tv . .l. .n. . . I‘.’ 9!: (1.1.x Ill/Ill!!! III/I’l/l/I/HI/ HI I l/Ill/I/l/ll/I/lll g 3210574 1222 LlBRARY Michigan State University This is to certify that the thesis entitled FACTORS INFLUENCING SECONDARY MICHIGAN AGRICULTURAL STUDENTS ABOUT NON-MEMBERSHIP IN THE FFA presented by JAMES CONNORS has been accepted towards fulfillment of the requirements for M. S. degree in Agricultural and Extension Education Major professor Date /fl27/?d / / 0-7639 MS U is an Affirmative Action/Equal Opportunity Institution 760 PLAOEJN RETURN BOX to remove this checkout from your record. TO AVOID FINES return on or before date due. ll DATE DUE DATE DUE DATE DUE EEP 1 4 19C); " r ,3 is :‘I '----t 1' . —=:I ”I: is E ”7:34 .L—____ ': , TT—— . if,“ § MR, 015 2002 1| LP if s fin gr— j cl MSU Is An Affirmatiye Action/Equal Opportunity Inuitution FACTORS INFLUENCING SECONDARY MICHIGAN AGRICULTURE STUDENTS ABOUT NONMEMBERSHIP IN THE FFA By James Connors A THESIS Submitted to Michigan State University in partiaI fulfiilment of the requirements for the degree of MASTER OF SCIENCE Department of AgricuItura] and Extension Education I 1990 ABSTRACT FACTORS INFLUENCING SECONDARY MICHIGAN AGRICULTURE STUDENTS ABOUT NONMEMBERSHIP IN THE FFA By James Connors Over the last century, the number of members of the National FFA Organization in Michigan has dropped dramatically. Non-FFA- member agricultural education students in Michigan were surveyed iri this study. For analysis purposes, they were grouped by gender, grade level, place of residence, and number of semesters of agricul— tural classes completed. Survey questions were asked to determine: whether the groups differed on four variables that might influence» FFA membership. These variables were financial constraints, time <:onstraints, peer pressure, and geographical factors. Descriptive statistics (frequencies, percentages, means, and standard deviations), t-tests, and ANOVAs were used in analyzing the data. Statistically significant differences were found between males and females, groups of students by place of residence, and groups of students by grade level in their reasons for not joining the FFA. To my wife, Rebecca, for her encouragement, support, and patience during my study. ACKNOWLEDGMENTS I would like to express my sincere appreciation and gratitude to Dr. Harrison Gardner, who served as my major professor. His help and guidance were essential to the completion of this master’s thesis. Profound thanks and appreciation are extended to Dr. Jack Elliot for serving as statistical consultant to my study. Thanks to Dr. Eddie Moore, chairperson, and Dr. George Ferns for serving on rny graduate committee. Appreciation is extended to Dr. Carroll Namhoff, Chairperson of the Department of Agricultural and Extensiori Education, for his guidance and support. Sincere thanks to Richard Karelse, Doug Spike, Pete Siler, Bill Bartow, Dr. Kirk Heinze, and Dr. Carroll Hamhoff for reviewing the: instrument. My profound appreciation is extended to the Michigan agricultural education teachers who helped administer the survey, and to the high school agricultural education students who completed the questionnaires. Sincere appreciation to a close personal friend, James Brousseau. His encouragement and advice were greatly appreciated during this study. Finally, sincere appreciation to LaDonna Duda, Nedra Burns, and nw'parents, George and Romaine Connors, for their love, concern, and encouragement during this study. iv TABLE OF CONTENTS Page LIST OF TABLES ........................ vii Chapter I. INTRODUCTION ..................... l Need for the Study ................. 2 Purpose and Objectives ............... 3 Research Hypotheses ................. 4 Open-Ended Questions ................ 4 Assumptions ..................... 5 Delimitations .................... 5 Methodology ..................... 6 Definition of Terms ................. 6 Overview ...................... 7 II. REVIEW OF RELATED LITERATURE ............. 8 FFA Membership ................... 8 Michigan Agricultural Education Students ...... 9 Perceptions of Administrators, Teachers, and Students Regarding the FFA ............ 10 Participation in the FFA .............. ll FFA Dues ...................... ll Images of Agriculture ................ l3 Summary ....................... 13 III. METHODOLOGY ...................... 15 Population ..................... 15 Sample Selection .................. 15 Development of the Interest Survey ......... 17 Data-Collection Procedures ............. 21 Data-Analysis Procedures .............. 22 Summary ....................... 23 IV. RESULTS OF THE DATA ANALYSES ............. 24 Description of the Sample .............. 26 Results of the Quantitative Data Analyses ...... 29 V Hypothesis l ................... 29 Hypothesis 2 ................... 39 Hypothesis 3 ................... 5l Hypothesis 4 ................... 62 Results of Qualitative Analyses ........... 72 Questionl .................... 72 Question 2 .................... 74 Question 3 .................... 76 Question 4 .................... 78 Question 5 .................... 80 Question 6 .................... 82 Question 7 .................... 84 Question 8 .................... 87 Summary ....................... 89 V. SUMMARY, FINDINGS, CONCLUSIONS, AND RECOMMENDATIONS . . 90 Summary ....................... 90 Findings ...................... 92 Conclusions ..................... 94 Recommendations ................... 95 Reflections ..................... 97 APPENDICES . A. NAMES OF JURY MEMBERS ................. 98 B. LETTER TO THE MEMBERS OF THE JURY AND SURVEY COMMENT SHEET ......................... 99 C. LETTER OF APPROVAL FROM MSU COMMITTEE ON RESEARCH INVOLVING HUMAN SUBJECTS ............... 102 D. LETTER OF TRANSMITTAL ................. 103 E. SURVEY INSTRUCTION SHEET AND SURVEY INSTRUMENT . . . . 104 F. THANK YOU/REMINDER LETTER TO RESPONDENTS ....... 111 G. SUPPLEMENTAL TABLES .................. 112 BIBLIOGRAPHY ......................... 128 vi Table NOlU'lk 10. ll. 12. l3. 14. LIST OF TABLES Michigan Association of FFA: Membership Statistics, 1977-1988 ...................... Distribution of Michigan Agricultural Education Programs in the Study, by FFA Region ........ Percentage of Sample Responding to the Survey Instrument ..................... Distribution of Respondents by Gender ......... Distribution of Respondents by Place of Residence . . . . Distribution of Respondents by Grade Level ...... Distribution of Respondents by Semesters of Agricul- tural Classes Completed ............... Male and Female Non-FFA Members’ Means and Standard Deviations Pertaining to Financial Variables . . . . l-Test Results for Male and Female Non-FFA Members Pertaining to Financial Variables .......... Male and Female Non-FFA Members’ Means and Standard Deviations Pertaining to Time Variables ....... l-Test Results for Male and Female Non-FFA Members Pertaining to Time Variables ............ Male and Female Non-FFA Members’ Means and Standard Deviations Pertaining to Peer Variables ....... l-Test Results for Male and Female Non-FFA Members Pertaining to Peer Variables ............ Male and Female Non-FFA Members’ Means and Standard Deviations Pertaining to Geographic Variables . . . . vii Page 17 26 27 27 29 32 33 35 37 28. 29. 30. 31. 32. 33. 34. 35. 36. 37. 38. 39. 40. Freshman, Sophomore, Junior, and Senior Non-FFA Members’ Means and Standard Deviations Pertaining to Time Variables ................... ANOVA Results for Freshman, Sophomore, Junior, and Senior Non-FFA Members Pertaining to Time Variables . . Freshman, Sophomore, Junior, and Senior Non-FFA Members’ Means and Standard Deviations Pertaining to Peer Variables ................... ANOVA Results for Freshman, Sophomore, Junior, and Senior Non-FFA Members Pertaining to Peer Variables . . Freshman, Sophomore, Junior, and Senior Non-FFA Members’ Means and Standard Deviations Pertaining to Geographic Variables ................ ANOVA Results for Freshman, Sophomore, Junior, and Senior Non-FFA Members Pertaining to Geographic Variables ...................... Tukey Test Results for Freshman, Sophomore, Junior, and Senior Non-FFA Members’ Differences in Means on Geographic Variables ............... Non-FFA Members’ Means and Standard Deviations Pertaining to Financial Variables, by Number of Semesters of Agricultural Education Class Completed . . ANOVA Results for Non-FFA Members Pertaining to Financial Variables, by Semesters Completed ..... Non-FFA Members’ Means and Standard Deviations Pertaining to Time Variables, by Number of Semesters of Agricultural Education Class Completed . . ANOVA Results for Non-FFA Members Pertaining to Time Variables, by Semesters Completed ....... Non-FFA Members’ Means and Standard Deviations Pertaining to Peer Variables, by Number of Semesters of Agricultural Education Class Completed . . ANOVA Results for Non-FFA Members Pertaining to Peer Variables, by Semesters Completed ....... ix Page 55 56 57 58 60 61 61 63 64 65 67 68 41. 42. 43. 44. 45. 46. 47. 48. 49. 50. 51. 52. 53. 54. 55. Non—FFA Members’ Means and Standard Deviations Pertaining to Geographic Variables, by Number of Semesters of Agricultural Education Class Completed ...................... ANOVA Results for Non-FFA Members Pertaining to Geographic Variables, by Semesters Completed . . . . Extracurricular Activities of Non-FFA—Member Agricultural Education Students ........... Important Factors That Influenced Non-FFA-Member Agricultural Education Students’ Decision Not to Join the FFA ................... Non-FFA-Member Agricultural Education Students’ Feelings Toward FFA Members ............. Factors That Would Have Influenced Non-FFA-Member Agricultural Education Students to Join the FFA . . . . Non-FFA-Member Agricultural Education Students’ Definitions of the Term "Agriculture" ........ Non-FFA-Member Agricultural Education Students’ Reasons for Enrolling in Agriculture Classes . . . . Non-FFA-Member Agricultural Education Students’ Opinions on How to Cover Costs of FFA Membership Non-FFA-Member Agricultural Education Students’ Agricultural Experiences .............. Frequencies for Time Variable Statement: I’m Too Busy Working After School to Participate in FFA Activities ................... Frequencies for Geographic Variable Statement: I Live Too Far From School To Come to FFA Activities Frequencies for Peer Variable Statement: I Would Be leased By My Friends If I Joined the FFA ...... Frequencies for Financial Variable Statement: I Can’t Afford to Purchase an FFA Jacket ....... Frequencies for Geographic Variable Statement: I Do Not Have Access to a Car ............. Page 63 71 74 76 77 79 82 84 86 89 112 112 114 Frequencies for Peer Variable Statement: None of My Friends Are Members ............... 114 Frequencies for Financial Variable Statement: Dues Are Too Expensive .................. 115 Frequencies for Time Variable Statement: I’m Too Busy With Homework and Studying ........... 115 Frequencies for Peer Variable Statement: My Friends Would Think Less of Me ............... 116 Frequencies for Financial Variable Statement: I Can’t Afford Any Chapter Trips ........... 116 Frequencies for Time Variable Statement: Band Takes Too Much of My Time ................. 117 Frequencies for Time Variable Statement: I Participate in Sports ................ 117 Frequencies for Geographic Variable Statement: I Do Not Have a Driver’s License ............. 118 Frequencies for Peer Variable Statementz' Popular Students Do Not Join the FFA ............ 118 Frequencies for Time Variable Statement: I’m Getting Ready for College .................. 119 Frequencies for Geographic Variable Statement: My Family Is Not Involved in Agriculture ........ 119 Frequencies for Peer Variable Statement: The FFA Is for Non-College-Bound Students ........... 120 Frequencies for Financial Variable Statement: I Do Not Have a Job Related to Agriculture ........ 120 Frequencies for Geographic Variable Statement: I Live in Town .................... 121 Frequencies for Peer Variable Statement: Students Who Join the FFA Get Bad Grades ........... 121 Frequencies for Financial Variable Statement: I Like to Spend My Money on Other Activities ..... 122 xi Frequencies for Time Variable Statement: I’m Too Busy With Other School Clubs ............ 122 Frequencies for Peer Variable Statement: 1 Would Feel Funny Wearing the FFA Jacket .......... 123 Frequencies for Financial Statement: I’m Saving My Money for College ................ 123 Frequencies for Time Variable Statement: My Parents Are Too Busy to Take Me to FFA Activities ...... 124 Frequencies for Geographic Variable Statement: I Can’t Get a Ride to FFA Activities ......... 124 Frequencies for Peer Variable Statement: Agriculture Is Not a Popular Area ................ 125 Frequencies for Geographic Variable Statement: I Do Not Live on a Farm ................ 125 Frequencies for Time Variable Statement: Hobbies Keep Me Too Busy to Join the FFA .......... 126 Frequencies for Geographic Variable Statement: My Parents Won’t Let Me Travel ............. 126 Frequencies for Financial Variable Statement: I’m Saving Money to Buy a Car .............. 127 xii CHAPTER I INTRODUCTION Within the last 14 years there has been a significant decline in the number of students enrolled in agricultural education classes in secondary schools in the United States. Along with this drop in enrollment has been a drastic decline in the number of students who have become members of the National Future Farmers of America Organization (FFA). In 1976, FFA membership peaked at 509,735 (Harris, 1986). The National Future farmer; Magazine (1988-89) showed that, in 1988, national FFA membership stood at 404,900. This represented a drop of 104,835 members or a decline of 21% since the peak membership year of 1976. The FFA membership figures in Michigan have reflected a similar trend. The Michigan Association of FFA had 10,493 members in 1977. That number declined to 5,427 members in 1988, a reduction of 48%. (Michigan FFA membership figures are listed in Table 1.) These 5,427 FFA members made up only 63% of the 8,497 students enrolled in agricultural programs in Michigan during the 1988-89 school year. There are a number of possible causes for the decline in FFA membership. During this period of membership decline, the number of students in America’s secondary schools has also decreased. In addition, the number of vocational/technical center programs has skyrocketed, giving students more vocational programs from which to choose. Table 1 Michigan Association of FFA: Membership Statistics, 1977-1988 Year Membership Percent Decline 1977 10,493 1978 10,118 4 1979 9,344 8 1980 8,625 8 1981 8,532 1 1982 7,900 7 1983 7,672 3 1984 7,068 8 1985 6,809 4 1986 6,128 10 1987 5,715 7 1988 5,427 5 Need for the Stgdy In the past, agricultural education students were encouraged to join the FFA because it was part of the classroom instruction. Instruction in FFA was considered to be an intracurricular part of agricultural education. Students in agricultural classes received classroom and laboratory instruction and were eligible to participate in activities and to receive awards. However, these benefits did not seem to entice all students to becoming members. Students who decided against joining usually had a variety of reasons. These ranged from not being interested, to being interested but limited by time and/or travel constraints. In this study, the writer attempted to determine whether the factors selected did or did not influence a student’s decision about whether to join the FFA. In an effort to improve the activities that local FFA chapters offer to students, it was important to understand why some students decided not to take part in FFA programs. Once these factors are identified, changes can be initiated to improve the activities the FFA offers and to recruit more agricultural education students to become members of the FFA organization. Pur o n b'ec 'v Many students who enroll in agricultural classes have no interest in joining and participating in local FFA activities. The researcher believes that these students are missing a valuable portion of the agricultural education program from which they could benefit. Thus, the purpose of this study was to determine why selected agricultural education students decided not to join the FFA and to discover whether differences existed between various groups of students concerning why they did not join the FFA. Specific objectives included: 1. Determine whether students’ financial situation played a part in their decision not to join the FFA chapter. 2. Determine whether other extracurricular activities inter- fered with FFA membership. 3. Determine whether students’ peers influenced their decision not to join the FFA. 4. Determine whether students’ place of residence influenced their decision not to join the FFA. 8W The following hypotheses, stated in the null form, were chosen for the study because they appeared to concern common reasons why students choose not to join the FFA. Hypethesie 1: There are no statistically significant differ- ences between males and females enrolled in secondary agricul- tural classes in their decisions not to join the FFA, based on the following areas of concern: (a) financial constraints, (b) time constraints, (c) peer pressure, and (d) geographical reasons. Hypothesie 2: There are no statistically significant differ- ences between secondary agricultural students who live in a town, on a rural farm, or in a nonfarm rural areas in their decisions not to join the FFA, based on the following areas of concern: (a) financial constraints, (b) time constraints, (c) peer pressure, and (d) geographical reasons. Hypotheeie 3: There are no statistically significant differ- ences between freshman, sophomore, junior, and senior students who are enrolled in secondary agricultural classes in their decisions not to join the FFA, based on the following areas of concern: (a) financial constraints, (b) time constraints, (c) peer pressure, and (d) geographical reasons. Hyeetheeje 4: There are no statistically significant differ- ences between students who have completed various semesters of agricultural classes in their decisions not to join the FFA, based on the following areas of concern: (a) financial con- straints, (6) time constraints, (c) peer pressure, and (d) geographical reasons. Qpen-Enged Questjens The following eight open-ended questions were included irI the non-FFA-member survey. These questions sought the students’ opinions on several subjects related to this study. The questions either related directly to one of the four objectives or pertained to the entire study in general. 1. N01014:. What kind of extracurricular activities do you participate in after school? What was the most important factor that influenced your decision to not join the FFA? How do you and your fellow students feel about the agricul- tural education students who join the FFA and participate in chapter activities? What would have influenced you to join the FFA? Define agriculture. Why did you enroll in agricultural education class(es)? In your opinion, what is the best way to help cover the costs associated with FFA membership? What kind of experiences or background do you have in agri- culture? Aseemptions In conducting this study, the writer assumed that: 1. Agricultural teachers who were randomly selected adminis- tered the survey only to non-FFA members who were enrolled in an agricultural class. 2. Non-FFA members completing the survey were able honestly to perceive their reasons why they did not join the FFA. Delimitetjegs Only those non-FFA-member agricultural students who lived in Michigan were included in the study sample. The sample was further delimited to non-FFA-member agricultural students who enrolled in agricultural classes during the 1988-89 academic year. 'The study findings pertain only to the 441 non-FFA-member agricultural education students who responded to the survey instrument. Methodologx ~ A Likert-type opinion scale was used to obtain the data from non-FFA-member agricultural students. ‘The survey also included eight open-ended questions that pertained to the study. The survey responses were analyzed using descriptive statistics, frequencies, percentages, means, and standard deviations. T-tests and analyses of variance were used to determine whether statistically significant differences existed between groups of students. Qualitative research methods were used to categorize responses to the eight research questions. Qefinitien ef Terms The following terms are defined in the context in which they are used in this thesis. i r l u n . Any student who had been enrolled in an agricultural class at a vocational center or a comprehensive high school. EEA. The National FFA Organization is a national youth organi- zation for students studying for careers in agriculture. In 1988, the name of the organization was officially changed from the Future Farmers of America to the National FFA Organization by constitu- tional amendment. MM. Any student who had enrolled in an agricul- tural class but had not joined the local FFA chapter. 1eeet1ene1;1eehniee1_(yee;teeh1_eenten. An educational facil- ity operated by an intermediate school district in Michigan. This facility is sometimes called a career center or a skills center. mm” The need for the study, purposes and objectives, research hypotheses and questions, assumptions and limitations, methodology, and definitions of terms were discussed in Chapter 1. Chapter II is a review of literature related to the study. Topics of concern are FFA membership; Michigan agricultural students; perceptions of administrators, teachers, and students about FFA activities; participation in FFA; FFA dues; and images “of agriculture. The methodology used in the study is explained in Chapter III. Included are a description of the population, sample selection, development of the interest survey, and data-collection and data-analysis procedures. Chapter IV contains the results of the data analyses performed in this study. A summary of the study, conclusions, and recommendations are included in Chapter V. CHAPTER II REVIEW OF RELATED LITERATURE This chapter contains a review of literature related to several topics of concern in the study. Subjects include FFA membership; Michigan agriculture students; perceptions of administrators, teachers, and students about the FFA; participation in the FFA; FFA dues; and images of agriculture. FFA Membership The problem of declining FFA membership has been examined for the past several years. Many articles have been written about the causes of this decline in membership. Recently, the National FFA Organization reacted to the decreasing membership by passing sweeping constitutional revisions at its 1988 national convention. A number of studies have touched on the issue of declining FFA membership. Bail (1958) conducted one of the earliest studies related to FFA membership; his study was entitled ”Attitude of Teachers and Students to the Role of the Future Farmers of America Organization in Vocational Agriculture." Bail found that 66% of the students he surveyed in West Virginia strongly agreed or agreed that enrollment in vocational agriculture classes should automatically include membership in the FFA. n ri ult r n In 1968, Selland (1969) conducted a study that directly concerned FFA membership in Michigan. He studied both members and nonmembers of the FFA to determine whether any significant differences existed between the two groups. Selland found that "a greater percentage of members had been enrolled in vocational agriculture in the ninth and tenth grades than had non-members" (p. 110). This would indicate that students who are enrolled in agricultural education as freshmen or sophomores are more likely to join the FFA. Further, Selland found that a larger percentage of members than nonmembers resided on farms. This may have been because, in 1968, the FFA was not yet involved in agribusiness, leadership, and agriscience areas of agriculture. Selland also investigated whether there was a difference between members and nonmembers with regard to problems in attending FFA meetings. He found that "a high percentage of both members and non-members indicated that such factors as transportation, work responsibilities during the time of meetings, and conflict of meeting time with other clubs were not problems in their being able to attend FFA meetings" (p. 114). However, there was a significant difference between members and nonmembers in how they responded to the question. Selland concluded that residence was not a factor affecting membership in the FFA, that participation in other activities did not affect membership in the FFA, and that lack of transportation to activities was not a problem affecting membership. However, the 10 fact that an agricultural education student’s friends did not belong to the FFA influenced nonmembers’ decisions not to join the organization. It is interesting that, in 1968, Selland recommended further investigation into the possibility of changing the name of the Future Farmers of America to attract more members into the organization. P ti ns Admini tr r h d tu nts Re rdin h FFA Parker (1974) studied the perceptions of urban administrators, teachers, and students in agriculture concerning the activities of the FFA. Regarding the statement that ”members of the FFA in this school are looked at as ’smart’ and ’good kids,’" Parker found that "in all the groups more respondents disagreed than agreed with the statement" (p. 62). Students were asked to list the major reasons why they did not join the FFA. "Of the listed reasons the one that accounted for the largest percentage of respondents (35 percent) was that the organization did not sound interesting" (p. 67). Parker reported that "the five reasons reported most frequently [for not joining the FFA] were: didn’t have time for meetings, too many other activities, didn’t pay my dues, didn’t know enough about it, and just didn’t want to” (p. 68). The sixth most frequently indicated reason for not joining the FFA was lack of transportation. Only 6% of the students Parker surveyed said the reason they did not join the FFA was that "it costs too much" (p. 68). Parker also asked students to respond to the statement, ”Members of the FFA in 11 this school get better grades than do members of other organizations" (p. 123). He found that '44 percent of the students disagreed, and 44 percent indicated no opinion on the issue" (p. 124). Par i t In his study of the factors affecting participation in the FFA, Carter (1983) found that "more than half of the members surveyed indicated that different backgrounds of members had no effect on participation" (p. 7). He also discovered that students’ membership in other groups did not affect their participation in activities of the local FFA chapter. Although this study did not deal with membership in the FFA, it did show that students’ backgrounds and participation 'hi other activities did not influence their participation in the organization. FFA Dues In his 1982 survey of 251 agriculture teachers, supervisors, and teacher educators, Lee found that 85% (211) of the respondents thought students should pay the FFA dues, whereas only 9% (22) said they thought the FFA chapter should pay students’ dues. A majority of the respondents agreed with the statement, ”FFA membership should be required of all students enrolled in secondary vocational- technical agriculture classes" (p. 23). Cooper and Nelson (1983) investigated the effect of FFA dues on whether students joined the FFA chapter. The data showed that 34% of non-FFA members said they would have been willing to pay up to $4 12 in FFA dues, and 84% would have been willing to pay a maximum of $10 in dues. A larger proportion of FFA nonmembers than members said they would have been willing to pay more than $10 in dues. The researchers concluded that ”only 6% of the non-FFA members indicated the cost of belonging to FFA prevented them from joining" (p. 20). Hence, 94% of the nonmembers responding reported that the expense associated with FFA membership had not prevented them from joining. Casey (1987) studied the possibility of an alternative membership structure for the National FFA Organization. He indicated that the FFA was an integral part of vocational agriculture and that charging dues for integral activities was inappropriate. Casey recommended that "the FFA should remain integral to vocational agriculture and that no fees should be assessed students which could create barriers to their participation in leadership development activities of the organization" (p. 1962A). Kellogg (1987) surveyed state supervisors, teacher educators, agriculture teachers, and FFA sponsors regarding their perceptions of the name Future Farmers of America. He found that 51.6% of the respondents thought the name had not contributed to declining enrollments in vocational agriculture programs, whereas 24.0% believed the name had contributed to declines. Kellogg also found that a majority of ornamental horticulture teachers, agricultural resource teachers, and all production agriculture teachers either agreed or strongly agreed that the name deterred appropriate 13 students from enrolling in vocational agriculture. The respondents strongly supported the retention of the letters FFA as the name of the organization. Based on the recomendations of Kellogg’s study and the support of the FFA board of directors, the organization officially changed its name to the National FFA Organization in 1988. Images ef Agriegltgre Although Mallory and Sommer’s (1986) study did not pertain specifically to FFA membership, it showed some possible reasons for membership decline. The researchers found that "students were unaware of the wide range of opportunities in agriculture careers, and that they only equated agriculture with farming" (p. 15). This lack of knowledge about career opportunities in agriculture could be directly related to the decline in FFA membership. The low farm profits and increased numbers of farm foreclosures that were prevalent in the early 19805 have given students a negative perception of agriculture in general. Summ r Several studies have been undertaken to compare FFA members’ and nonmembers’ perceptions of the FFA and FFA membership. Researchers have concluded that financial difficulties did not play a part in students’ decisions to decline FFA membership. Residence location and lack of transportation to activities were also ruled out as possible factors in declining FFA membership. However, if 14 students’ friends were not members of the FFA, they themselves were less likely to join the organization. Parker (1974) found that the five reasons students most often cited for not joining the FFA were not enough time, too many other activities, having to pay dues, not knowing enough about it, and just not wanting to join. Lee (1982) concluded that the amount of dues FFA members must pay did not cause a large number of students to forego FFA membership. More than half of the respondents in Kellogg’s (1987) study thought the name Future Farmers of America had not contributed to the decline in enrollments in vocational agriculture classes. Mallory and Sommer (1986) found that students had a narrow view of the field of agriculture and most of the time equated it with farming. CHAPTER III METHODOLOGY The methodology used in conducting the study is explained in this chapter. The population is described, the sample-selection process is explained, and development and pilot testing of the interest survey are discussed. Finally, the data-collection and data-analysis procedures used in the study are described. Poeulation The target population for this study was all students enrolled in agricultural education classes who were not members of the Michigan FFA Association. During the 1988-89 school year, 8,597 students were enrolled in agricultural education in Michigan; approximately 5,427 were members of the FFA. This means that there were 3,170 non-FFA-member agricultural education students in the state during the 1988-89 school year. These 3,170 students were the target population for the study. Semple Selection Because surveying the entire target population was not economically feasible, the researcher chose to survey all non-FFA- member agriculture students in a sample of the agricultural education programs in Michigan. Best (1981) stated, "The idea 15 16 sample is large enough to serve as an adequate representation of the population . . . and small enough to be selected economically” (p. 13). Stratified random sampling was done by school instead of individually. Borg and Gall defined simple random sampling as "all the individuals in the defined population having an equal and independent chance of being selected as a member of the sample" (p. 182). The experimentally accessible population was all non-FFA- member agricultural students in 75% of the Michigan agriculture programs that had FFA chapters during the 1988-89 school year. The agricultural education programs were chosen from the 1988-89 Michigan Agrieglture and Natural Resouree Edueetors Direetoty. The Direetory listed 117 school districts that offered agricultural education classes and had chartered FFA chapters. The researcher wrote the name of each of these districts on a slip of paper, placed all 117 names in a box, and randomly chose 88 names in order to select 75% of the FFA chapters in Michigan. According to Smith (1975), "simple random selection may be accomplished by placing all of the names or listings of the population in a container, mixing the slips thoroughly, and drawing one at a time until the desired sample size is selected" (p. 33). Non-FFA-member agricultural students from these 88 randomly selected school districts became the sample for the study. This random selection provided a good diversity of schools from throughout Michigan. The number of schools chosen from each FFA region and the percentage of the total sample are shown in Table 2. 17 Table 2 Distribution of Michigan Agricultural Education Programs in the Study, by FFA Region Number of Schools Percentage FFA Region Selected of Total 1 14 15.9 2 12 13.6 3 9 10.2 4 11 12.5 5 8 9.1 6 10 11.4 7 13 14.8 8 11 12.5 Total 88 100.0 v 1 m n f h nt e S rv The survey that the researcher developed was primarily a Likert-type questionnaire. Best (1981) wrote, ”The first step in constructing a Likert-type scale consists of collecting a number of statements about a subject. It is important that they express definite favorableness or unfavorableness to a particular point of view" (p. 181). According to Borg and Gall (1984), "Likert scales are probably the most common types of attitude scales constructed" (p. 423). Sax (1989) noted that "a Likert scale typically employs five choices expressing different degrees of agreement or disagreement" (p. 491). A scale value is assigned to each of the five responses (Best, 1981). The five categories used in this study were 5 Strongly Agree, 4 . Agree, 3 - Undecided, 2 :- Disagree, and l 18 Strongly Disagree. For this survey, the researcher added a sixth category, Not Applicable, to the Likert scale. This response option was added so that students who did not have any association with the content of the question could indicate that the statement was not applicable to their situation. This category was not assigned a value, so it did not cause any discrepancies in the data analysis. The instrument also included several open-ended questions. Tuckman (1972) stated, "The unstructured response, perhaps more commonly called the open-ended question, allows the subject to give his own response in whatever form he chooses" (p. 177). These questions pertained to the four objectives of the study, as well as to topics of general interest in the study, and allowed respondents to express their opinions in their own words. Tuckman also commented that "the unstructured response mode is a response form over which the researcher attempts to exert little control other than by virtue of the questions he asks and the amount of space he provides" (p. 177). The survey instrument was reviewed and field tested for clarity, validity, and reliability. The following procedures were used: (a) selection of an expert panel, (b) pilot testing of the instrument, and (c) reliability testing of the instrument using Cronbach’s alpha coefficient. The survey was evaluated for content validity by a panel of agricultural education experts. The purpose of the evaluation was to improve the quality of the instrument. The panel of experts 19 included representatives from the State Department of Education, Vocational and Technical Education Service; Michigan State University, Department of Agricultural and Extension Education; the Michigan Association of Teachers of Vocational Agriculture; and the National Vocational Agriculture Teachers Association (see Appendix A). Panel members were sent a cover letter, a copy of the survey instrument, and a page on which to write their comments about the instrument and suggestions for improving it (see Appendix B). The researcher gave the panel members one week to review the instrument and then contacted them individually to obtain their comments and suggestions. After the instrument was improved, using the jury’s suggestions, it was prepared for pilot testing. According to Tuckman (1972), a pilot test "uses a group of respondents who are part of the intended test population but will not be part of the sample" (p. 196). Borg and Gall (1979) also indicated that a researcher should pretest a questionnaire with a sample of individuals similar to those one wishes to use in the research before conducting the actual survey. The researcher selected two schools in Marlette and Brown City, Michigan, in which to pilot test the survey instrument. These schools were chosen because they had not been selected to participate in the final survey. Non-FFA-member' agricultural education students from the two schools were given the same survey at two different times. One way to estimate reliability is to determine the correlation between scores on the same test administered twice to the same group (Sax, 20 1989). The type of reliability indicated by this procedure is called stability. The instrument was administered to the students at the two schools on a Friday; it was administered again approximately 10 days later. Sax (1989) said that "over short periods of time chance effects are reduced and predictive validity coefficients are increased” (p. 214). The results were analyzed to determine whether the instrument was reliable. The reliability of the instrument was tested using the Statistical Package for the Social Sciences (SPSS) computer program (SPSS, 1987). The SPSS/PC+ version was used. Reliability coefficients were determined for the four objectives tested. The coefficients for questions pertaining to each of the four objectives were relatively low: Objective 1, financial factors - .56; Objective 2, time constraint factors .. .76; Objective 3, peer factors . .76; and Objective 4, geographical factors - .69. Concerning low reliability coefficients, Ary (1979) stated, "The test—retest coefficient also assumes that there is no practice effect. . . . These practice effects from the first test will not likely be the same across all students, thus lowering the reliability estimate" (p. 212). Three of the four objectives had acceptable alpha levels. However, Objective 1 had a relatively low alpha level. To correct this, the researcher decided to discard one of the variables that pertained to that particular objective. The researcher discarded the variable, wages, because it had a very low correlation 21 coefficient and the alpha level increased considerably when it was removed. When the wages variable was removed, the correlation coefficient for Objective 1 rose to .63. Pertaining to final reliability coefficients, Asher (1976) wrote, ”For early stages for basic research purposes, where only the statement. is needed ‘that variables are related, low reliability correlations are acceptable" (p. 93). He went on to state that ”Nunnally . . . declared that for basic research, reliability of .50 to .60 will suffice" (p. 93). The researcher next forwarded the questionnaire and a statement regarding the purpose of the research to the chairperson of the University Committee on Research Involving Human Subjects (UCRIHS) at. Michigan State University to obtain approval to conduct the study. Such consent was necessary because the study involved human subjects and, in particular, minors. The committee granted approval to conduct the survey (see Appendix C). Data-tellection Preeeggres The researcher co-authored a transmittal letter with Richard Karelse, State Supervisor for Agriculture, Vocational and Technical Education Service, Michigan Department of Education (see Appendix D). That letter, along with an instruction sheet, 12 copies of the survey instrument (see Appendix E), and a return envelope, were mailed to the 88 schools that had been selected for the study. Best (1981) stated, ”In mailed questionnaire studies, since the percentage of responses may be as low as 20 to 30 percent, a large 22 initial sample mailing is indicated" (p. 14). Mailing labels for the schools selected to participate were obtained from the Department of Agricultural and Extension Education, Michigan State Universityu The agricultural education teachers were asked to administer the survey to all non-FFA-member agricultural education students in their classes and to return the completed surveys to the researcher within 10 days. At the end of a week, a thank-you/ reminder letter was sent to all schools from which completed surveys had not been received (see Appendix F). The final response rate was 61% (54) of the schools surveyed. Deta-Analysis Precedgree The data were analyzed using the SPSS/PC+ version of the Statistical Package for the Social Sciences, (SPSS, 1987) in the Department of Agricultural and Extension Education. The results of these analyses are presented in Chapter IV. Ary, Jacobs, and Razavieh (1979) stated, "The most commonly used levels of significance in the field of education are the .05 and .01 levels" (p. 144). A .05 level of significance with an accompanying 95% confidence level was used in assessing the results of this study. Three statistical methods were used to analyze the data. Responses to the Likert-scale items were analyzed using descriptive statistics, such as frequencies, percentages, means, and standard deviations. T-tests and analysis of variance (ANOVA) were used to examine differences between and among groups of students with regard to gender, grade level, geographic residence, and number of 23 semesters of agricultural class completed. Responses to the open- ended survey question were analyzed using qualitative research methods. Summarx A survey that included 31 Likert-type items, along with eight open-ended questions, was used to obtain the subjects’ views concerning FFA membership. The content validity of the instrument was checked by a panel of agricultural education experts. The panel’s suggestions for improving the instrument were accepted, and the survey was revised. The instrument was pilot tested in two school districts that were not part of the sample for the final survey. The pilot test indicated that the survey was reliable and ready for dissemination to sample schools. Surveys were sent to 88 schools that had agricultural education classes. ‘The agricultural education teachers were asked to administer the survey to all non- FFA-member agricultural education students. Completed surveys were received from 61% (54) of the schools surveyed. The results were analyzed using descriptive statistics, t-test, ANOVA, and qualitative methods. Results of the data analyses are presented in Chapter IV. CHAPTER IV RESULTS OF THE DATA ANALYSES The purpose of this study was to identify possible reasons why certain agricultural education students in Michigan chose to decline membership in the National FFA Organization. The objectives of the study were to determine whether students’ financial situation played a part in their decision not to join the FFA chapter, to determine whether other extracurricular activities interfered with FFA membership, to determine whether students’ peers influenced their decision not to join the FFA, and to determine whether students’ place of residence influenced their decision not to join the FFA. The data analysis was based on students’ responses to a questionnaire containing 31 Likert-type questions and eight open- ended questions. The open-ended questions included in the survey were designed to elicit respondents’ opinions on the following topics: 1. What kind of extracurricular activities do you participate in after school? 2. What was the most important factor that influenced your decision to not join the FFA? 3. How do you and your fellow students feel about the agricul- tural education students who join the FFA and participate in chapter activities? 4. What would have influenced you to join the FFA? 24 25 5. Define agriculture. 6. Why did you enroll in agricultural education class(es)? 7. In your opinion, what is the best way to help cover the costs associated with FFA membership? 8. What kind of experiences or background do you have in agri- culture? Three statistical methods were used to analyze the survey response data. Responses to the Likert-type items were analyzed using descriptive statistics such as frequencies, percentages, means, and standard deviations. T-tests and analyses of variance (ANOVA) were used to determine whether statistically significant differences existed between group means. Finally, responses to the open-ended survey questions were analyzed using qualitative research methods. Eighty-eight schools were chosen for inclusion in the study; of that number, 54 responded, for a 67% response rate. Four hundred forty-one individual student surveys were returned. Of the 54 schools from which responses were received, nine (16.6%) indicated that all students enrolled in agriculture classes were members of the FFA. A summary of the response statistics is presented in Table 3. The results of ‘the study are presented in three sections. Characteristics of the students who completed the survey instrument are discussed first. These characteristics include gender, place of residence, grade level, and semesters of agriculture classes completed. Next, results of the analyses of quantitative data used in testing the hypotheses are presented. In the third section, 26 results of the qualitative analyses of responses to the open-ended questions are discussed. Table 3 Percentage of Sample Responding to the Survey Instrument Number Percent Schools returning 45 51 completed surveys Schools indicating 100% FFA membership 9 10 Total 54 61 Description of the Sample The 441 sample members were male and female agricultural students from 45 high school agriculture programs in Michigan. None had joined the FFA. ID: the following paragraphs, the respondents are described according to gender, place of residence, grade in school, and semesters of agriculture classes completed. The gender of respondents is shown in Table 4. Of the 441 students in the sample, 289 (65.5%) were males and 152 (35.5%) were females. The respondents’ places of residence are shown in Table 5. Whereas only 154 (35.3%) of the students lived in town, another 202 (46.3%) lived in a rural area but not on a farm. Thus, 356 (81.6%) students had nonfarm places of residence. Just 80 students (18.3%) 27 lived on farms. These figures make it hard to justify a full- production agricultural program to school superintendents. Table 4 Distribution of Respondents by Gender Gender Number Percent Male 289 65.5 Female 152 35.5 Total 441 100.0 Table 5 Distribution of Respondents by Place of Residence Place of Residence Number Percent Town 154 35.3 Rural farm 80 18.3 Rural nonfarm 202 46.3 Total 436 100.0 The various grade levels of the non-FFA-member agricultural education students who responded to the survey are shown in Table 6. One hundred forty-three (32.4%) of the respondents were in the ninth grade, and 147 (33.3%) were in the tenth grade. These figures indicate that more non-FFA members were freshmen and sophomores than 28 were juniors and seniors. Only 94 (21.3%) of the respondents were in their junior year, and 57 (12.9%) were in their senior year of high school. It would be beneficial if all freshmen and sophomores could be recruited into the FFA because they would have several years of school left in which to participate in chapter activities. Table 6 Distribution of Respondents by Grade Level Grade Level Number Percent Freshman 143 32.4 Sophomore 147 33.3 Junior 94 21.3 Senior 57 12.9 Total 441 100.0 The number of semesters of agricultural classes that the sample members had completed is shown in Table 7. One hundred twenty-six (29.5%) of the respondents had completed only one semester of agricultural classes, whereas 183 (42.9%) had completed two semesters. Forty-two (9.8%) students had completed three semesters, 51 (11.9%) had completed four semesters, 5 (1.2%) had completed five semesters, and 20 (4.7%) had completed six semesters of agricultural classes. The data indicated that students tended to take a full year of agricultural classes. 29 Table 7 Distribution of Respondents by Semesters of Agricultural Classes Completed Semesters Completed Number Percent One 126 29.5 Two 183 42.9 Three 42 9.8 Four 51 11.9 Five 5 1.2 Six 20 4.7 Total 427 100.0 R ul h uan ' at'v Hypothesie I There are no statistically significant differences between males and females enrolled in secondary agricultural classes in their decisions not to join the FFA, based on the following areas of concern: (a) financial constraints, (b) time constraints, (c) peer pressure, and (d) geographical reasons. Hypothesis 1 sought to determine whether male and female non- FFA members differed on the possible reasons for their decision not to join the FFA. The survey instrument contained 31 Likert-type questions concerning reasons the respondents had not joined the organization. In analyzing respondents’ mean scores on these items, the means were interpreted as follows: Range of the Meen Less than 2.5 2.5 to 3.4 3.5 or more n r t ion of Re Disagree Undecided Agree nse 30 Male and female students’ mean scores for each financial variable are presented in Table 8. Students tended to disagree with the statements pertaining to not being able to afford an FFA jacket or chapter trips. Males tended to think that FFA dues were too expensive, whereas females were undecided about that statement. Both male and female students agreed with the statement that they preferred to spend their money on other activities than to use it for activities related to the FFA. Males agreed with the statement that they were saving money to buy a car, whereas females tended to be undecided on that statement. Conversely, females agreed with the statement that they did not have a job related to agriculture, whereas males were undecided on that statement. Both males and females were undecided on whether they were saving their money for college. The frequencies and percentages of responses for each of the financial variables are presented in the supplementary tables in Appendix G. An average mean value for the financial variables was calculated for each respondent group using the SPSS computer program. The means were then analyzed using a t-test, to determine whether a statistically significant difference existed between the two groups on the financial variables. The group means, t-value, degrees of freedom, and two-tailed probability are shown in Table 9. The t-test showed that there was a statistically significant difference between males’ and females’ means on the financial variable questions. The test produced a two-tailed probability of 31 .023, which was significant at the .05 alpha level. Therefore, Null Hypothesis 1 was rejected. Table 8 Male and Female Non-FFA Members’ Means and Standard Deviations Pertaining to Financial Variables Males Females Total Variable Mean SD Mean SD Mean SO I can’t afford to purchase an 2.35 1.24 2.07 1.10 2.25 1.20 FFA jacket. The dues are too expensive. 2.59 1.27 2.19 1.06 2.45 1.21 I can’t afford chapter trips. 2.46 1.19 2.22 0.99 2.37 1.12 I don’t have a job related to 3.12 1.45 3.51 1.39 3.24 1.44 agriculture. I like to spend my money on 4.00 1.19 3.57 1.28 3.85 1.23 other activities. I’m saving money for college. 2.86 1.30 2.89 1.31 2.87 1.30 I’m saving money to buy a car. 3.61 1.33 3.15 1.35 3.44 1.35 32 Table 9 I-Test Results for Male and Female Non-FFA Members Pertaining to Financial Variables Two-Tailed Group Mean I-Value 4: Probability Vzmgles 2:73 2°29 235 ~023* *Significant at alpha < .05. Male and female students also responded to eight Likert-type questions pertaining to time variables. These variables concerned whether certain other activities took up too much time for students to participate in the FFA. The specific frequencies and percentages of responses for each variable can be found, in Appendix G. The means for males and females on the eight financial variables are shown in Table 10. Both males and females disagreed with the statement that band took up too much of their time. This was probably because very few band members had time in their class schedules to enroll in agricultural education, which is usually an elective class. Only 40 of the 441 students agreed or strongly agreed with the statement. Males and females differed on the statement pertaining to whether hobbies took up too much time. Males had a mean score of 3.50, which was categorized as agreement with the statement. Females had a mean score of 3.34, which was categorized as being undecided. Although these means fell into different categories, 33 they were very close to one another. Overall, 236 (54%) students agreed or strongly agreed with the statement concerning hobbies. Table 10 Male and Female Non-FFA Members’ Means and Standard Deviations Pertaining to Time Variables Males Females Total Variable Mean SQ Mean SD Mean SO I am too busy working after 3.33 1.26 3.06 1.28 3.24 1.27 school. I am too busy with homework. 2.85 1.39 2.95 1.29 2.89 1.35 Band takes up too much of my time. 2.04 1.24 1.98 1.15 2.02 1.20 I participate in sports. 3.17 1.45 2.76 1.45 3.04 1.46 I am getting ready for college. 2.90 1.39 2.93 1.36 2.91 1.38 I am too busy with other school clubs. 2.39 1.18 2.53 1.26 2.44 1.21 My parents are too busy to take me 2.70 1.32 2.65 1.29 2.69 1.31 to activities. I have hobbies that keep me too busy 3.50 1.33 3.34 1.26 3.45 1.31 to join. In general, students were undecided on the statement that they participated in sports. However, in analyzing the frequencies, it 34 was seen that 149 (34%) students either agreed or strongly agreed with the statement, whereas 154 (35%) students either disagreed or strongly disagreed with the statement. Thus, the number of students who participated in sports almost equaled the number of nonparticipants. On all of the other statements, both males and females tended to be undecided. The means for males and females were analyzed using a tftest for differences between means. As shown in Table 11, males had an average mean on the time variables of 2.72, whereas females had an average~ mean of 2.60. The t:test showed that there was no statistically significant. difference between males’ and females’ means on the time variables. Table 11 I-Test Results for Male and Female Non-FFA Members Pertaining to Time Variables Two-Tailed Group Mean I-Value gt Probability Males 2.72 Females 2.60 1-18 195 .239 Another possible cause for students’ not joining the FFA was the pressure they felt from other non-FFA members. Eight statements on the questionnaire referred to different aspects of peer pressure that students might encounter. The data for males and females pertaining to peer variables are presented in Table 12. 35 Table 12 Male and Female Non-FFA Members’ Means and Standard Deviations Pertaining to Peer Variables Males Females Total Variable Mean SD Mean SD Mean SO I would be teased by my friends. 2.52 1.41 2.37 1.25 2.47 1.36 None of my close friends are 2.99 1.37 3.11 1.46 3.03 1.40 members. My friends would think less of me. 2.38 1.26 2.00 1.01 2.25 1.19 Popular students don’t join the 2.52 1.41 2.32 1.24 2.45 1.36 FFA. The FFA is for non-college- 2.12 1.16 1.89 .97 2.04 1.10 bound students. Students who join get bad grades. 2.23 1.13 1.94 .92 2.13 1.07 I would feel funny wearing the 3.31 1.36 2.86 1.34 3.16 1.37 FFA jacket. Agriculture is not a popular area. 2.63 1.31 2.70 1.28 2.65 1.30 The data show that students did not consider peer pressure to be an influence on their decision not to join the FFA. Both males and females disagreed with the statement that they would be teased if they joined the FFA. They also disagreed with the statements 36 that the FFA was for non-college-bound students and that members of the FFA got bad grades. The means indicated that both males and females were undecided on the statement that they would feel funny wearing the FFA jacket. However, 177 (40%) respondents agreed with the statement, whereas 153 (35%) disagreed. It is interesting that 211 (48%) respondents disagreed with the statement that agriculture is not a popular area; one-fourth of the respondents (109) agreed that agriculture is not a popular area. An average mean for the peer variables was calculated for each respondent group using the SPSS computer program. These average means were then analyzed using a t-test to determine whether a statistically significant difference existed between the two groups. No statistically significant difference was found between males’ and females’ means on the peer pressure variables. The results of the L-test are shown in Table 13. Table 13 l—Test Results for Male and Female Non-FFA Members Pertaining to Peer Variables Two-Tailed Group Mean I-Value g: Probability Males 2.53 Females 2.43 ~90 316 .371 The students also responded to eight statements pertaining to geographic variables. The items concerned whether the students’ 37 place of residence had an effect on their decision not to join the FFA. The means and standard deviations for male and female students pertaining to the geographic variables are shown in Table 14. Table 14 Male and Female Non-FFA Members’ Means and Standard Deviations Pertaining to Geographic Variables Males Females Total Variable Mean 50 Mean §Q Mean §Q I live too far from school. 2.51 1.18 2.53 1.24 2.51 1.20 I don’t have access to a car. 2.57 1.41 2.92 1.43 2.68 1.42 I don’t have a driver’s license. 2.82 1.49 3.07 1.42 2.91 1.47 My family is not involved in 3.11 1.41 3.16 1.39 3.13 1.40 agriculture. I live in town. 2.66 1.53 2.81 1.46 2.71 1.51 I can’t get a ride to activities. 2.35 1.19 2.49 1.22 2.40 1.20 I don’t live on a farm. 3.54 1.37 3.65 1.28 3.57 1.34 My parents won’t let me travel. 2.07 1.16 2.02 1.01 2.05 1.11 Both males and females disagreed with the statement that they could not get a ride to the FFA activities. However, according to 38 the frequencies, 251 (57%) of’ the respondents either agreed or strongly agreed with the statement. Students also disagreed with the statement that their parent or guardian would not let them travel to FFA activities. In addition, 175 (40%) students agreed and 162 (37%) disagreed with the statement that they did not have a driver’s license. In general, respondents agreed with the statement that they did not live on a farm. This is probably because 356 (81%) of the students did not live on a farm. On all other variables, the students were equally divided in their responses, which produced means that were in the middle of the scale. The means were analyzed using a L-test for significant differences between males and females pertaining to the geographic variables. Table 15 contains the group means, t-value, degrees of freedom, and two-tailed probability. No statistically significant difference was found in males’ and females’ means for the geographic variables. Table 15 I-Test Results for Male and Female Non-FFA Members Pertaining to Geographic Variables Two-Tailed Group Mean l-Value d: Probability Males 2.66 Females 2.72 '°59 255 .492 39 In summary, males and females did not differ significantly on variables related to time, peer pressure, or geographical factors. The t-test did show that there was a statistically significant difference between males and females concerning the financial variables. Because of this significant difference, Null Hypothesis 1 was rejected. mum's; There are no statistically significant differences between secondary agricultural students who live in a town, on a rural farm, or in a nonfarm rural areas in their decisions not to join the FFA, based on the following areas of concern: (a) financial constraints, (b) time constraints, (c) peer pressure, and (d) geographical reasons. Hypothesis 2 concerned whether students who lived in different geographic areas would respond differently to the four groups of variables pertaining to FFA membership. 0n the questionnaire, students were asked to identify their place of residence: town, rural farm, or rural nonfarm. Table 16 shows the data for town, rural farm, and rural nonfarm students pertaining to the financial variables. Students who lived in town tended to agree with the statement that they did not have a job related to agriculture. However, rural nonfarm and rural farm students tended to be undecided about the question. The frequencies showed that 205 (47%) respondents agreed with the statement, whereas 138 (31%) disagreed. 40 Table 16 Town, Rural Farm, and Rural Nonfarm Non-FFA Members’ Means and Standard Deviations Pertaining to Financial Variables Rural Town Rural Farm Nonfarm Total Variable Mean SD Mean SD Mean SD Mean SD I can’t afford to purchase an 2.19 1.20 2.16 1.23 2.34 1.19 2.25 1.20 FFA jacket. The dues are too expensive. 2.50 1.28 2.46 1.21 2.41 1.18 2.45 1.21 I can’t afford chapter trips. 2.44 1.19 2.05 1.01 2.46 1.11 2.37 1.12 I do not have a job related 3.51 1.37 2.53 1.41 3.32 1.42 3.23 1.43 to agriculture. I like to spend my money on 3.93 1.19 3.49 1.41 3.99 1.15 3.87 1.23 other activities. I’m saving money for college. 2.85 1.32 2.79 1.28 2.93 1.30 2.87 1.30 I’m saving money to buy a car. 3.54 1.33 3.24 1.41 3.47 1.36 3.45 1.35 Students who lived in town or in a rural area but not on a farm agreed with the statement that they liked to spend their money on other' activities. Rural farm students , although categorized as being undecided, were very close to agreeing with the statement. Students who resided in town said they agreed with the statement 41 that they were saving their money to purchase a car. Rural farm and rural nonfarm students tended to be undecided on this statement. A mean was calculated for each place-of-residence group on the financial variables. These means were then used in the ANOVA test to determine whether statistically significant differences existed between groups. Table 17 shows the sum of squares, degrees of freedom, mean square, E-value, and significance of E calculated by ANOVA. Table 17 ANOVA Results for Town, Rural Farm, and Rural Nonfarm Non-FFA Members Pertaining to Financial Variables Analysis of Variance Sum of Mean Signif. Group Mean Variance g: Squares Square E of E Town 2.91 Between 2 4.174 2.087 groups 3.836 .023* Rural 2.62 Hithin 280 152.325 .544 farm groups Rural 2.94 Total 282 156.498 .555 nonfarm *Significant at alpha < .05. A statistically significant difference was found between the means of town, rural farm, and rural nonfarm students pertaining to the financial variables. To identify which groups differed significantly from the others, a Tukey test was performed on the 42 data. The Tukey test determined that the rural farm students differed significantly from those who lived in town or in a rural area but not on a farm (see Table 18). Because significant differences were found, Null Hypothesis 2 was rejected. Table 18 Tukey Test Results for Town, Rural Farm, and Rural Nonfarm Non-FFA Members’ Differences in Means on Financial Variables Group Mean Town Rural Farm Rural Nonfarm Town 2.91 * Rural farm 2.62 Rural nonfarm 2.94 * *Denotes pairs of groups significantly different at alpha < .05. The means of town, rural farm, and rural nonfarm students were also analyzed with regard to the time variables. The means and standard deviations for students grouped by place of residence are shown in Table 19. On most variables, the students tended to be undecided. However, all three respondent groups disagreed with the statement that band took up too much of their time for them to be in the FFA. Students who lived in town and in a rural area, but not on a farm, tended to agree with the statement that hobbies took up too much of their time for them to be in the FFA. Rural farm students were undecided on this statement. 43 The frequencies indicated that 236 (54%) of the respondents agreed with this statement. Table 19 Town, Rural Farm, and Rural Nonfarm Non-FFA Members’ Means and Standard Deviations Pertaining to Time Variables Rural Town Rural Farm Nonfarm Total Variable Mean SD Mean SD Mean §Q Mean SD I am too busy working after .24 1.28 3.28 1.33 3.22 1.24 3.24 1.27 school. I am too busy with homework. .93 1.37 2.67 1.34 2.95 1.34 2.89 1.35 Band takes up too much of .04 1.23 1.80 1.03 2.08 1.25 2.01 1.21 my time. I participate in sports. .04 1.50 2.94 1.54 3.06 1.41 3.04 1.46 I am getting ready for .79 1.43 3.06 1.43 2.95 1.31 2.91 1.38 college. I am too busy with other .58 1.27 2.46 1.13 2.30 1.18 2.43 1.21 school clubs. My parents are too busy to .60 1.32 2.50 1.21 2.82 1.34 2.68 1.31 take me to activities. I have hobbies that keep me .52 1.30 3.06 1.40 3.55 1.26 3.45 1.31 too busy to join. 44 About equal numbers of students agreed and disagreed with the statement that they were getting ready for college and thus could not join the FFA. A large number of respondents (220 or 50%) disagreed with the statement that they were too busy with other clubs to participate in the FFA. This generated an average mean for the group that was in the disagreeing category. ANOVA was used to determine whether statistically significant differences existed between groups. Table 20 shows the results of that test. No statistically significant difference was found between groups based on residence. Table 20 ANOVA Results for Town, Rural Farm, and Rural Nonfarm Non-FFA Members Pertaining to Time Variables Analysis of Variance Sum of Mean Signif. Group Mean Variance g: Squares Square E of 5 Town 2.70 Between 2 .555 .277 groups .563 .570 Rural 2.56 Hithin 194 95.459 .492 farm groups Rural 2.70 Total 196 96.014 .490 nonfarm The means of town, rural farm, and rural nonfarm students were also analyzed with regard to the peer variables. The survey instrument included eight variables related to pressure that non-FFA 45 members might have perceived from other students. comparison are presented in Table 21. Table 21 The data for this Town, Rural Farm, and Rural Nonfarm Non-FFA Members’ Means and Standard Deviations Pertaining to Peer Variables Rural Town Rural Farm Nonfarm Total Variable Mean SD Mean SD Mean SD Mean SD I would be teased by my 2.57 1.39 2.11 1.17 2.56 1.38 2.48 1.36 friends. None of my close friends 3.18 1.40 2.72 1.41 3.06 1.39 3.04 1.40 are members. My friends would think 2.23 1.16 1.94 .98 2.38 1.26 2.24 1.19 less of me. The FFA is for non-college- 2.03 1.11 1.89 1.01 2.10 1.11 2.03 1.09 bound students. Students who join get 2.20 1.13 1.90 .84 2.16 1.09 2.12 1.07 bad grades. I would feel funny wearing 3.23 1.33 3.01 1.45 3.17 1.36 3.16 1.37 the jacket. Agriculture isn’t a 2.85 1.35 2.16 1.04 2.68 1.30 2.65 1.30 popular area. 46 The data pertaining to peer variables were interesting because they showed that most students did not think peer pressure played a part in their decision not to join the FFA. The means indicated that rural farm students disagreed with the statement that their friends would have thought less of them if they joined the FFA. Town and rural nonfarm students were undecided (”1 this statement. The frequencies showed that 236 (54%) of the respondents disagreed with the statement. Students also disagreed with the statements that the FFA was for non-college-bound students and that FFA members got bad grades. All groups of' students disagreed with the statement that their friends would have thought less of them if they had joined the FFA. Rural farm students were the only group to disagree with the statement that agriculture is not a popular area. This might have been because the rural farm students had a background in agriculture and understood what the field of agriculture entailed. Students who lived in town or in a rural area but not on a farm were undecided on the statement. The means for town, rural farm, and rural nonfarm students were analyzed using ANOVA. The group means, degrees of freedom, sum of squares, mean squares, E-value, and significance of E are shown in Table 22. No statistically significant difference was found in the means of students who lived in a town, on a rural farm, or in a rural area but not on a farm pertaining to the peer variables. 47 Table 22 ANOVA Results for Town, Rural Farm, and Rural Nonfarm Non-FFA Members Pertaining to Peer Variables Analysis of Variance Sum of Mean Signif. Group Mean Variance df Squares Square E of E Town 2.51 Between 2 2.492 1.246 groups 1.660 .192 Rural 2.31 Within 313 234.990 .751 farm groups Rural 2.55 Total 315 237.482 .754 nonfarm Eight statements on the survey pertained to geographic variables that may have influenced students’decision not to join the FFA. The data for town, rural farm, and rural nonfarm students on the geographic variables are presented in Table 23. Town and rural farm students tended to disagree with the statement that they lived too far from school to come to FFA activities. Rural nonfarm students were undecided on this statement. Rural farm students disagreed with the statement that they did not have access to a car to come to FFA activities. Town and rural nonfarm students were undecided on whether they had access to a car. The frequencies showed that 218 (49%) respondents disagreed with the statement that they did not have access to a car. 48 Table 23 Town, Rural Farm, and Rural Nonfarm Non-FFA Members’ Means and Standard Deviations Pertaining to Geographic Variables Rural Town Rural Farm Nonfarm Total Variable Mean SD Mean SD Mean SD Mean SD I live too far from school. 2.26 1.13 2.47 1.16 2.73 1.24 2.51 1.20 I don’t have access to a car. 2.64 1.41 2.47 1.40 2.81 1.45 2.69 1.42 I don’t have a driver’s 2.86 1.40 2.65 1.50 3.03 1.52 2.90 1.48 license. My family is not involved in 3.46 1.37 2.16 1.30 3.27 1.29 3.13 1.40 agriculture. I live in town. 3.95 1.22 1.65 .96 1.77 .82 2.72 1.51 I can’t get a ride to 2.41 1.21 2.26 1.13 2.44 1.22 2.39 1.20 activities. I don’t live on a farm. 3.97 1.15 2.19 1.24 3.84 1.16 3.58 1.34 My parents won’t let me 2.06 1.15 1.84 .88 2.14 1.16 2.05 1.11 travel. Rural farm students disagreed with the statements that their families were not involved in agriculture and that they did not live on a farm. Students who lived in town, or in a rural area but not on a farm, agreed with the statement that they did not live on a farm. 49 ANOVA was used to determine whether there were statistically significant differences between the means of town, rural farm, and rural nonfarm students on the geographic variables. The group means, degrees of freedom, sum of squares, mean square, E-value, and significance of E are shown in Table 24. A statistically significant difference was found between groups concerning the geographic variables. The E-value calculated by the ANOVA was extremely high compared to other such values that were found to be significant. Table 24 ANOVA Results for Town, Rural Farm, and Rural Nonfarm Non-FFA Members Pertaining to Geographic Variables Analysis of Variance Sum of Mean Signif. Group Mean Variance g: Squares Square E of E Town 2.93 Between 2 19.194 9.597 groups 22.425 .000* Rural 2.14 Hithin 253 108.274 .428 farm groups Rural 2.66 Total 255 127.468 .500 nonfarm *Significant at alpha < .05. Because the ANOVA indicated a significant difference between group means, the data were further analyzed to determine which 50 groups actually differed significantly. This analysis was completed by performing a Tukey test on the data. The Tukey test showed that, on the geographic variables, rural farm students differed signifi— cantly from town students and from rural nonfarm students (see Table 25). Table 25 Tukey Test Results for Town, Rural Farm, and Rural Nonfarm Non-FFA Members’ Differences in Means on Geographic Variables Group Mean Town Rural Farm Rural Nonfarm Town 2.93 * * Rural farm 2.14 Rural nonfarm 2.66 * *Denotes pairs of groups significantly different at alpha < .05. The reason the E-value was extremely high and a significant difference was present may have been the result of a multicollinearity effect. This effect is observed when two of the variables being analyzed are very close in definition. This is evidenced by the fact that the geographic variables were tested by students’ place of residence. In summary, the ANOVA showed that town, rural farm, and rural nonfarm students did not differ significantly in the way they responded to the time or peer variables. The ANOVA did show that these groups of students differed significantly ("1 the geographic 51 variables. But, as stated earlier, this was probably due to a multicollinearity effect that was present in the survey instrument. The town, rural farm, and rural nonfarm students did differ significantly on the financial variables. Therefore, Null Hypothesis 2 was rejected. W There are no statistically significant differences between freshman, sophomore, junior, and senior students who are enrolled in secondary agricultural classes in their decisions not to join the FFA, based on the following areas of concern: (a) financial constraints, (b) time constraints, (c) peer pressure, and (d) geographical reasons. Hypothesis 3 concerned whether students in various grade levels (freshman, sophomore, junior, senior) would respond differently to the four groups of variables pertaining to FFA membership. The four variables were financial, time constraints, peer pressure, and geographic. Concerning financial reasons that might have prevented them from joining the FFA, students in all grade levels disagreed with the statements that they could not afford to purchase an FFA jacket and that they could not afford to go on any chapter trips. Freshmen and sophomores tended to disagree with the statement that dues were too expensive, whereas juniors and seniors were undecided (Hi this statement. The frequencies showed that 233 (53%) respondents dis- agreed with this statement. Students in all grade levels agreed with the statement that they liked to spend their money on other activities rather than on the FFA. 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