ARIES IHHNUHHINN/lWI!’IIII’HHH'INHHIf}!!! l! W “4595 ‘ 310696 9219 fifiT-‘WV MM - as 7.54 4' U; b'uM-i 503 This is to certify that the dissertation entitled A COMPARISON OF TWO METHODS OF MEASURING THE RELATEDNESS OF THE JOBS OF VOCATIONAL EDUCATION GRADUATES TO THEIR VOCATIONAL EDUCATION PROGRAMS presented by Harvey Ollis has been accepted towards fulfillment of the requirements for Ph. D. Education degree in 18% PM Major professor Date May 12, 1983 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. Wm. Jii‘ag'ifiatéfisf3;;l 1‘“ 2‘9?_ l I A COMPARISON OF TWO METHODS OF MEASURING THE RELATEDNESS OF THE JOBS OF VOCATIONAL EDUCATION GRADUATES TO THEIR VOCATIONAL EDUCATION PROGRAMS By Harvey Tito Ollis A DISSERTATION Submitted to Michigan State University in partial fulfillment of the requirements for the degree of DOCTOR OF PHILOSOPHY Department of Secondary Education and Curriculum 1983 ’5‘I- ’09-'— ABSTRACT A COMPARISON OF THO METHODS OF MEASURING THE RELATEDNESS OF THE JOBS 0F VOCATIONAL EDUCATION GRADUATES TO THEIR VOCATIONAL EDUCATION PROGRAMS by Harvey Tito Ollis Statement of the Problem The problem addressed in this study was to compare two different methods of measuring whether the jobs obtained by vocational graduates were related to their instructional program. One measure of job relatedness was graduate self-assessment. The other relatedness measure was based on matching job titles and instructional program titles using a cross-code index. Another aspect of the study was to identify the predictive nature (if any) of selected student and program characteristics on the two measures of job relatedness. Research Procedures The population of this study consisted of a sample of 1,336 program completers who responded to the 1980 Follow-Up Survey from six vocational education instructional programs. The sample data for all the variables were analyzed in multiple regression equations with student and program characteristics serving as independent variables and the job relatedness measures serving as dependent variables. The variability of the job relatedness measures explained by each of the independent variables was identified. The two measures of job relatedness were tested for independence and association using contingency table analysis and chi-square and phi statistics. Tests for independence and association between the job relatedness measures provided information on the natUre of the relationship, its significance and its strength. Major Findings of the Study The two measures of job relatedness did not produce comparable results. A majority (62.0 percent) of the respondents reported that their jobs were related to their instructional program. However, only twenty-five percent of the respondents were in related jobs based on job title-program title matching measure of job relatedness. ACKNOWLEDGEMENTS The researcher wishes to express his gratitude to the individuals who made this study possible. My appreciation is extended to the following: Dr. Robert Poland, major advisor, who provided me with guidance and direction and to committee members Dr. Harrison Gardner, Dr. Stanley Hecker, and Dr. Daniel Kruger. Dr. Bruce Grow and Dr. Carl Holoszyk, former colleagues at the Michigan Department of Education, who greatly supported this effort. Ms. Betty Johnson, Trig Johnson, David Lipstein and Trish Carrico, former colleagues at Program Resources, Inc., who encouraged this effort. Ms. Retha Arens who provided expert word-processing assistance in the typing and final preparation of the manuscript. CHAPTER I III TABLE OF CONTENTS PROBLEM ........................ . 1 Introduction ...................... 1 Statement of the Problem ..... . .......... 5 Need for the Study ................... 6 Outcomes of the Study .................. 8 Delimitations of the Study ............... 9 Limitations of the Study ................ 9 Definition of Terms ................... 10 REVIEW OF THE LITERATURE ................ 14 Vocational Education Follow-Up Studies ......... 15 Student Characteristics, Program Characteristics, and Outcome Measures ................... 19 Occupational and Educational Code Systems ........ 25 Occupational Coding of Job Titles ............ 31 Cross-Code Indexes Relating Occupations and Educational Programs ................. 38 RESEARCH PROCEDURES ................ . . .43 Instrumentation ................. . . . .44 Population ................ . ...... 46 Sample ......................... 47 Independent Variables ............... . . .52 Dependent Variables ............. . ..... 55 Research Questions .............. . . . . .61 Data Analysis . ......... . . . . . . . . . . . .62 IV FINDINGS ........... . ........ . . . .65 Frequency of Response .................. 65 Multiple Regression Analysis .............. 72 Measurement of Independence and Association ....... 76 V SUMMARY, CONCLUSIONS, AND RECOMMENDATIONS ....... 82 The Problem ...................... 82 Research Procedures .................. 82 Findings ........................ 83 Conclusions ...................... 87 Implications and Concluding Statements ......... 88 Recommendations .................... 89 APPENDICES Appendix A - 1980 Follow-Up Survey Of Former Students (VE-40 45-A) .................. 91 Appendix B - Standard Occupational Classification Codes and Titles ..................... Appendix C - 1980 Follow—Up Report "Placement Summary Of Completers By Program" (X0607) ......... 101 BIBLIOGRAPHY .......................... 109 iv Table Table Table Table Table Table Table Table Table Table Table Table Table Table Table 1 2 OS taco H O H H LIST OF TABLES Frequency of Selected Outcome Questions Found in a National Study of Vocational Follow-Up Instruments . . . .22 Sampling Plan Used by the Michigan Department of Education to Assign Occupational Codes .......... 49 Sample Vocational Programs and Their Program Areas . . . .51 1980 Survey Respondent Population and Sample ....... 52 Sex of the Respondents ................ . .66 Race of the Respondents .................. 67 Participation Status of the Respondents in Cooperative Education ................... 68 Instructional Program of the Respondents ......... 79 Student Self— Assessment of Job Relatedness Survey Item and Sample Respondents ................ 70 Comparison of Two Measures of Job Relatedness and Sample Responses ..................... 70 Multiple Regression Data for the Student Self-Assessment Measure of Job Relatedness ................ 73 Multiple Regression Data for the Job Title-Program Title Measure of Job Relatedness ................ 74 Number and Percent of Respondents by Job Related Categories as Measured by Student Self-Assessment and Job Title- Program Title Match .................... 77 Chi-Square and Phi Statistics for the Two Measures of Job Relatedness by Independent Variables ....... . .79 Ranking of Related Sub— —Groups by Strength of Association (Size of Phi Statistics) ........... . . . .81 Figure Figure Figure Figure Figure Figure Figure Figure Figure Figure CONT—I U" \l 10 LIST OF FIGURES Occupational Classification Systems . . . ........ 27 Educational Classification Systems . . . ...... . .29 Classification Systems Used in Major Occupational Demand and Supply Data Sources ......... . . . .32 Industry and Occupation Questions Used in the 1970 and 1980 Census of Population . . . . . ........ .34 Vocational Education Data System (VEDS) Follow- Up Report--Employment Status . . . . . . . . . . . . . . .36 Vocational Education Data System (VEDS) Follow-Up Report--Field of Employment . . . . ......... .37 1980 Follow-Up Survey of Former Students (VE-4045-A)-- Student Sex Item .................. . .53 1980 Follow- -Up Survey of Former Students (VE- 4045- A)-- Student Race Item . . . . . ..... . . . . . . .54 Related SOC Codes for Sample Instructional Programs . . .58 1980 Follow-up Survey of Former Students (VE-4045-A)-- Job Relatedness . . . ............ . . . . . .60 vi Chapter I PROBLEM Introduction Vocational education is a form of instruction designed to prepare its students to function in occupational roles by providing skills, attitudes, and knowledge that are relevant to occupational performance. Vocational education curricula, classroom equipment, supplies, and teacher certification all must be appropriate to the relevant occupation or groups of occupations. Taken together, these factors represent a clear occupational emphasis in vocational education. This emphasis in the process of vocational education extends to a strong interest in the employment experiences of former students. This study addressed the concept of "relatedness" of the occupational employment experiences of former vocational education students to their instructional program. The study explored several methods of measuring this relatedness of programs to occupations. By analyzing information on former students, this study joins the body of literature that focuses on vocational education outcomes. Historically, vocational education has had a special responsibility for the employment of its graduates. The occupational emphasis in the process of vocational education was reflected in the expectations held for the product of this process. "The acid test of vocational education is the extent to which its graduates are employed in occupations for which they are trained.“1 This judgment, by the Panel of Consultants on Vocational Education in 1962, clearly indi- cated the expectations held for occupationally related employment of former students. Even with this historical emphasis on the outcomes of vocational education programs, evaluation activities at the federal, state, and local levels had not focused on the employment experiences of former students. Prior to 1976, state evaluation activities concentrated mostly on the vocational program's operational processes, rather than experiences of program graduates.2 The mandate for outcome assessment was contained in the Educational Amendments of 1976, which stated in Section 112(b)(1) that: (B) each state shall evaluate, by using data collected . . . each program within the state which purports to impart entry level job skills according to the extent to which program completers and leavers (i) find employment in occupations related to their training, and (ii) are considered by their employers to be well trained and prepared for employment 1Panel of Consultants on Vocational Education, Education for a Changing World, (Washington, D.C.: U.S. Department of Health, Education and Welfare, 1962), p. 2. 2Esther Gottlieb Smith and Nancy L. Holt, “State Evaluation of Vocational Education Programs: A National Study of Evaluation Procedures and Practices“, Journal of Vocational Education Research, Winter, 1980, Vol. V, No. l, p. 18. 3Educational Amendments of 1976, (Washington, D.C.: U.S. Congress, 1976), Section II?(b)(I)(B). p. 2187. Darcy4 has noted that this legal mandate for outcome assessment coincided with growing public concern over tax burdens and a greater deveTOpment and sophistication in educational evaluation. Together these factors have resulted in greatly expanded evaluations of the outcome measures of vocational education programming. Wentling5 reported, in a recent national study, that local vocational evaluation activities have internalized the importance of outcome assessment, with “improving programs" being cited twice as frequently as "federal and state reporting requirements“ as the reason for evaluation. Wentling6 further noted that student follow-up surveys are the domi- nant outcome evaluation method used by local educational agencies. The impact of these developments has resulted in the following status of evaluating the outcomes of vocational education programs: 1. Mandate--Programs which purport to impart entry-level job skills are to be evaluated according to the extent to which program completers and leavers find employment in related occupations.7 4Robert L. Darcy, Vocational Education Outcomes: Perspective for Evaluation, (Columbus: The National Center for Research in Vocational Education, The Ohio State University, Research and Development Series No. 163, 1979), p. 32. 5Tim Wentling, and William E. Piland, "A Study of Local Education Practices in Vocational Education“, Journal of Vocational Education Research, Summer, 1981, Vol. VI, No. 3, pp 37-55, p. 41 5Ibid. p. 47. 7Federal Register, Vol. 42, No. 191, Oct. 3, 1977, pp. 538-44. «t, [I 2. Instrumentation--Student follow-up surveys are the method most frequently used by local educational agen- cies to evaluate the outcomes of instructional programs.8 Even with agreement in these areas, a problem had emerged--how to ascertain that a job is, indeed, related to a vocational program. The solution to this problem required a method of measuring the ”relatedness" of the former students' employment to their vocational program. In an Oklahoma Study, Morton9 observed that ". . .confusion still exists in correctly identifying graduates as working in an occu- pation for which trained. . .“ In a recent national study of voca- tional education outcomes, Darcy10 argued that placement in a training-related job was a questionable evaluation criterion because “relatedness" was an ambiguous concept. Rossman11 has defined relatedness as ". . .the extent to which there are perceived similarities between characteristics of the training program and the occupation in which the graduate is employed." This definition of relatedness seemed helpful and was the one used in this study. The definition indicated that relatedness 8Tim Wentling, op. cit. 9J. B. Morton et al. Parallel Follow-U , (Stillwater, Oklahoma: State Department of Vocation and Technica Education, 1977), p. 10. 10Robert L. Darcy, op. cit., p. 33. 11Marilyn Martin Rossman, "Measuring the Relatedness of Vocational Education Graduates' Preparation and Placement,“ Journal of Vocational Education Research, Summer 1978, Vol. III, No. 3, p. 2. involves “perceived similarities.“ The question then became--whose perceptions? And what are the criteria for measuring similarities? The purpose of this study was to compare two different methods of measuring the relatedness of occupational outcomes. Statement of the Problem This study was designed to address the problem of measuring job relatedness. Two different measures of job relatedness were tested for their comparability in selected secondary vocational education programs. The "1980 Michigan Follow-Up Survey of Former Students“ was used as the data collection instrument. The following job relatedness measures were analyzed in this study. 1. Student Self-Assessment of Relatedness--Student respon- ses identifying how much they use their vocational training on their present job was one measure of rela- tedness. 2. Job Title Matched to Program Title--Another measure of relatedness was the job title-program title match. This involved comparing the job title as reported by the stu- dent to the program title, using a cross-code index which identified the related occupations for each program. The following related research questions were analyzed in this study: 9:- 1. Do the student and program characteristics predict variation in the two measures of job relatedness? 2. Are the two measures of job relatedness independent or related? If they are not independent, what is the strength of their relationship? Need for the Study The importance of the issues explored in this study is indicated in the priority of occupationally related outcomes for Michigan voca- tional education programs. The mission of vocational education in Michigan, as defined in the Annual and Long Range State Plan for Vocational Education in Michigan 1980 (hereafter cited as State Plan), was that . .persons of all ages in all Michigan communities will have ready access to high quality vocational and technical education which is realistic in the light of actual or anticipated opportunities for gainful employment and consistent with their needs, interests and abilities. One of the goals within this mission is that all local vocational-technical education programs will be planned, monitored, and evaluated in light of actual or anticipated employment oppor- tunities and with regard to the demand by students for programs 12The Annual and Lon Ran e State Plan for Vocational Education in Michigan: I980, (Lansing, Micfiigan: Vocational-Technical Edfication Service, Michigan Department of Education, 1980). p. 178. related to their abilities and occupational objectives. The definition of vocational instruction in the State Plan spe- cified instruction which was designed to prepare individuals for employment in a specific occupation or in a cluster of closely related occupations in an occupational field. Each of these statements indicated that Michigan vocational edu- cation programs had the purpose of preparing individuals for employment in related occupations. In considering the success of vocational education programs, the operational problem in Michigan, and nationally, was how to identify "relatedness." The Michigan Department of Education conducted an annual follow- up survey of secondary vocational graduates. According to the State_ 3133, data from a representative sample of local program completers and leavers was collected and analyzed to determine the extent to which they had found employment in occupations related to their training. Data from the Michigan follow-up surveys historically had been reported by programs with comparisons of the related and unrelated graduate outcomes using a student self-assessment measure of related- ness. The 1980 follow-up survey also contained the job titles and duties of former students which were subsequently assigned occupa- tional codes. This study used these occupational codes, with available program-job cross-code indexes, to produce a "job title- '\ program title matching" measure of relatedness. The conduct of this study involved comparing this measure of relatedness to the student self-assessment measure of relatedness. Outcomes of the Study The comparative assessment of job relatedness measures is rele- vant to the national discussions on program evaluation and to the need of state and local educators for information to use in program deve- lopment, monitoring and evaluation. In this regard, the present study was intended to provide the following outcomes: 1. The Michigan Department of Education would be provided information for use in the design of future follow-up surveys and reporting the results of those surveys. 2. The National Center for Education Statistics would be provided an assessment of the impact of using two dif- ferent measures of the job relatedness of vocational education outcomes. 3. Vocational education planners and researchers would be provided with an analysis of using alternative measures of relatedness in evaluating vocational program out- COMES. Delimitations of the Study The study sample was limited to those Michigan secondary vocational education students graduating in 1980 and responding to the follow-up surveys in 1981. The sample analyzed was further limited to students from six selected instructional programs: ' Agricultural Production, General Merchandise, Nurse Aide, Food Management, Steno/Secretarial, Auto Mechanics. The study was limited to the analysis of those student, program, and job characteristics that were identified on the follow-up survey. Other characteristics or other measures of these characteristics were not considered in the analysis. Limitations of the Study The survey respondents provided data on student, program, and outcome characteristics. The self-reported data was used in this study and limitations in the accuracy of this data affected this study. The occupational coding and vocational program-to- occupational code relationships were provided by Michigan state agencies. Limitations in the accuracy of this data affected this study. 10 Definition of Terms Cooperative Education--A program of vocational education for persons who are simultaneously employed (and receiving wages) and receiving instruction (both academic courses and related vocational instruction). These two experiences must be planned and supervised by the school and employers so that they contribute to the person's edu- cation and employability.13 Cross-Code Indexes--Documents that identify and display the rela- tionships between occupational and educational classification struc- tures. Cross-code indexes have been developed to relate education and training data to employment data for use in educational program planning, curriculum planning, and vocational guidance.14 Educational Code Structures--Taxonomies of instructional programs con- taining codes, titles, and definitions. These structures have been designed by federal agencies to help local and state educational agen- cies identify, classify, and prOperly report information about subject matter and curriculum activities.15 The most widely used educational classification structures include: 13Vocational Education Data System (VEDS) Technical Assistance Handbook (Washington, D.C.: National—Center for Education Statistics, U.S. Department of Health, Education and Welfare, 1978) p. 1. 14Vocational Pre aration and Occu ations, Volume I, Interim Edition, (Washington, D.C.: National Occupational Information Coordinating Committee, 1979), p. 3-5. 151bid. p. 37. ’I '—VI l i I i 11 1. U.S. Office of Education (USOE) Codes 2. Higher Education General Information Survey (HEGIS) Codes 3. Classification of Instructional Programs (CIP) Codes Instructional Programs--See Vocational Education Instructional Programs. Marketable Skills--Skills and knowledge acquired by a student that meet acceptable standards for employment in a particular field.16 Marketable skills are also known as salable skills. New Entrants--New entrants to the labor market are new participants in the labor force who are seeking employment for the first time. Many new entrants into the labor market are recent completers or leavers from training/education institutions and programs.17 0ccupation--A group of jobs, found at more than one establishment, having work activities that are identical or related in terms of com- binations of similar methodologies, materials, products, worker actions, and/or worker characteristics.18 < 16Carter V. Good, ed., Dictionar of Education, (New York: ’ McGraw-Hill, 3rd Edition, 1 ), p. . 170ccupational Information System Handbook, Volume I, Occgpational Information Development, (Washington, D.C.: NationET—Occupational Information Coordinating Committee, 1981), p. 3-17. 18Handbook for Analyzing Jobs, (Washington, D.C.: U.S. Department of Labor, Interim Revision, 1980), p. 4. 12 Occupational Code Structures--Taxonomies of occupations and groups of occupations containing codes, titles, and definitions. These struc- tures have been designed by federal agencies to collect and report data on employment and to assist in job placement activities. Examples of occupational code or classification structures include: 1. Dictionary of Occupational Titles (DOT) Codes 2. Standard Occupational Classification (SOC) Codes 3. Occupational Employment Statistics (OES) Codes Occupational Objective--The intended occupational outcome of training and other preparation as stated or implied by the individual student. The occupational objective is usually stated in terms of specific job titles. Program Completer--A person who has completed all the reguirements of a U.S. Office of Education program (11th grade or higher) which pre- pares persons to enter the job market with entry-level occupational skills.19 Relatedness--Measure of the extent to which there are perceived simi- larities between the characteristics of the training program and the occupation in which the graduate is employed.20 19Vocational Education Data System (VEDS) Tecppical Assistance Handbook, op. cit., p. 5. 20Marilyn Martin Rossman, op. cit., p. 2. 13 Vocational Education Instructional Programs--Organized educational programs which are directly related to preparing individuals for paid or unpaid employment, or for additional preparation for a career requiring other than a baccalaureate or advanced degree.21 Vocational Program Area--Groupings of Vocational Education Programs into major instructional areas. For secondary vocational education, the following program areas were used: 1. Agriculture (code 01) 2 Distribution (code 04) 3. Health (code 07) 4. Home Economics (code 09.02) 5. Office (code 14) 6. Trade and Industrial (code 17) Wages--Monetary compensation for a given unit of time or output, exclusive of premium payments for overtime or other extras.22 21Educational Amendments of 1976, (Washington, D.C.: U.S. Congress, P.L. - 82, 6 , Sec 5(1). 22Glossar of Current Industrial Relations and Wa e Terms, (Washington, D.C.: U.S. Department of Labor, Bulletin I438, May, 196 Chapter II REVIEW OF THE LITERATURE This study compared two methods of measuring the relatedness of the jobs of former vocational students to their vocational programs. One method used student self-assessment; the other method involved matching job titles and program titles using cross-code indexes. The conduct of this study, therefore, drew upon literature and research in several different areas including: 1. Vocational Education Follow-Up Studies 2. Student Characteristics, Program Characteristics and Outcome Measures 3. Occupational and Educational Code Systems 4. Occupational Coding of Job Titles 5. Cross-Code Indexes Relating Occupations and Educational Programs Of these five areas, “vocational education follow-up studies" is the broadest subject area, covering hundreds of research studies. The next four areas, in the order listed above, are progressively more specialized research areas. They are described in some detail in this chapter because of their importance to the job title-program title 14 15 measure of relatedness examined in this study. This chapter discusses some of the important literature in each of the above areas. Vocational Education Follow-Up Studies Darcy1 described vocational education follow-up studies as a type of analysis that seeks to identify the input, process, and out- come of vocational education. This concept was very important to the design of this study. Data on the vocational education input (the student), process (the program) and outcome (job-relatedness measure) were analyzed. Two outcome (job-relatedness) measures were compared in one research question. In the other research question, the impor- tance of selected student and program characteristics to these outcome measures was assessed. Outcome analysis is important to vocational education as a basic method of assessing program performance. Wentling and Lawson observed that "...inherent in all follow-up objectives is an emphasis on the primary objective of occupational education - the preparation of indi- viduals for a productive career.“2 The use of vocational follow-up analysis as a tool for program planning has been of growing national interest. The recent national 1Robert L. Darcy, Vocational Egpcation Outcomes: Pergpective for Evaluation, (Columbus: The National Center for Research in Vocational Education, The Ohio State University, Research and Development Series No. 163, 1979), p. 22. 2Tim L. Wentling and Tom E. Lawson, Evaluatin Occu ational Education and Trainin Pro rams, (Boston: Allyn and Bacon, Inc., 9 5). p. 27. if? 16 Vocational Education Study, commissioned by the National Institute of Education, reported that: The connection between program evaluation and more effective state and local program planning in the light of needed skills and present and future job oppor- tunities, on the one hand, and improvement in the quality of educational programs, on the other, had been registered in the legislation of 1963 and 1968. However, reports issued in the mid-19705 showed that the connection still was not being made. The 1976 vocational education legislation sought to relate labor market demand for occupational skills to program planning. The legislation specifically provided for ". . .(1) systematic eva- luations, (2) labor market-oriented planning, (3) improved occupa- tional information systems, and (4) the requirements for new data for accountability."4 The impact of the legislation on the literature concerning voca- tional follow-up had been dramatic. The 1982 edition of the Thesaurus of ERIC Descriptors5 contains over 670 citations on the topic of ''vocational follow-up," more than twice the number found only five years earlier. A national survey of vocational follow-up studies 313g Vocational Egpcation Study: Thp Final Report, (Washington D.C.: National Institute of Education, U.S. Department of Education, 1981), p. IV-Z. 41pm. 5Thesaurus of ERIC D§§criptors (Phoenix: Oryx Press, 1982, 9th Edition p. 6 . .‘iilllll'l conducted between 1970 and 1979 17 features:6 6Patrick A. O'Reilly and F. Marion Asche, Follow-Up Procedures: A National Review, (Blacksburg, VA: Virginia Polytechnic Institute Objectives--The most frequently cited purposes of the studies, in descending order, were (1) evaluation, (2) planning, and (3) compliance reporting. Academic Level--The academic level was evenly divided between secondary and postsecondary. Source of Information—-Students were the primary source of information. Students were used as the source of information eight times more frequently than employers, the next most frequent source of information. Completer Status--Most studies focused on students who had completed the instructional program. Employment Status--More than 80% of the studies described the employment status of the former students. Program Specific Data--Less than half of the studies reported the results by vocational program. Sampling Procedure--More than 70% of the studies sur- veyed the entire population of former students. and State University, 1979). p. 13. identified the following common a l "'1 18 8. Follow-up Period--Most of the studies were conducted within a year of graduation of the students. Most were not repeated for longitudinal analysis. The advent of the 1976 legislation brought about a standar- dization of follow-up activities with both student and employer sur- veys being required. In a 1981 national evaluation study, Wentling7 found that student follow-up surveys were the most frequently used local education evaluation activity. (Wentling's survey included over 200 local vocational administrators.) The preceding discussion implies that the process of conducting student follow-up studies had become the most common type of local evaluation activity. Uses of the resulting data have focused on program assessment and improvement. Wentling8 reported that the six most frequent uses of local evaluation activities were the following (in descending order of frequency): 1. Changing curricula Informing administrators 2 3. Supporting staff development 4 Supporting equipment requests 5 . Recruiting students 6. Discontinuing programs 7Tim Wentling and William E. Pillard, op. cit., p. 47. 81bid., p. 44. «J 19 Student Characteristics, Program Characteristics, and Outcome Measures The discussion of vocational education follow-up studies at the beginning of this chapter suggested that such studies required an identification of the educational input (student), the treatment (program) and the outcome (job). For this study of vocational follow- up data, it was similarly necessary to assess key characteristics of the student, the program, and the job. Student Characteristics Educational programs are not factories that receive homogeneous inputs of raw materials and produce, through educational processes, a standardized product. The student "input“ to the system is variable. Educational reporting often specifies several different categories of student characteristics which may include racial/ethnic group, han- dicapping condition, and sex. The differential impact of these charac- teristics on vocational outcomes has been recognized. Somers9 noted that independent of program, student race and sex affect the pay-off of vocational education. This assumed impact required that the con- duct of this study include an assessment of different student charac- teristics vis-a-vis the measures of relatedness. Information on the race and sex of follow-up survey respondents were used for analysis. 9Gerald G. Somers, The Effectiveness of Vocational Education and Technical Progrgpp: A National Fol ow-Up Survey, (Washington D.C.: U.S. Department of Health, Eduction and Welfare, 1971). 20 Program Characteristics The "treatment" provided by vocational instruction varies by program not only in terms of content but also impact on student out- comes. The 1981 National Institute of Education study of vocational education reported that: Students in different occupational specialties (vocational programs) in secondary school were foung to differ on outcomes pertaining to gainful employment. 0 The importance of program-level variation in the relatedness of occu- pational outcomes was carefully assessed in this study. Another program characteristic that can be measured is the student's participation in a cooperative education program with local employers. Asche and Vogler11 have noted employers' preferences for students involved in this type of program. Outcome Measures The variety and importance of outcome measures available for stu- dent follow-up analysis was well summarized in Wulfsburg's 1981 report. Wulfsburg, the former Assistant Administrator of the National Center for Education Statistics, reported: 10The Vocational Education Study: The Final Report, (Washington D.C.: National Institute for Education, U.S. Department of Education, 1981), p. VII-17. 11F. Marion Asche and Daniel E. Vogler, "Employer Satisfaction with Secondary Vocational Education Graduates,“ Journal of Vocational Education Research, Fall 1980, Vol. V., No. 4, p. V 21 In order to answer the question, "What is being accomplished?“ by vocational education programs, one needs an appropriate measure or "yardstick". . . including the extent to which students find related employment, employer satisfaction with the former stu- dent, wages, and job satisfaction and progress of the former student. O'Reilly'sl3 national literature review contained a detailed assessment of the questions included in the follow-up studies. Table 1 presents the frequency of questions related to the outcome measures suggested by Wulfsburg in 56 student follow-up instruments analyzed by O'Reilly. 12Ralph Wulfsburg, A Statistical Overview of Vocational Education, (Washington D.C.: National Center for Education Statistics, U.S. Department of Education, 1980), p. 64. 13Patrick A. O'Reilly, op. cit., p. 47. J11: A 7 r 22 Table 1 -- Frequency of Selected Outcome Questions Found in a National Study of Vocational Follow-Up Instruments14 Percent Frequency Question/Data Element of Occurrence Relatedness of Job to Training 82% Program Salary/Wage-Present Job 64% Hours Working-Present Job 64% Job Satisfaction 23% Three recent state studies focused on methods of identifying the relatedness of the job to the training programs. In a Texas study, Reed15 found that ". . .program-to-occupation matching can be per- formed by analyzing and classifying the program according to three classifications. . J' of occupational outcomes. Vocational programs were placed in one of these three classifications depending on the pattern of occupational outcomes. 1. Class I - Occppation Specific--This type of program resulted in more than 75% of the students being employed in the same group of occupations. 14Ibid., p. 48. 15James Reed, Relating Follgy:Up Data to Career Education and Occu ational Information 5 stems (Corsicana, Texas: Navarro College, 98 ) p. 2. 23 N . Class II - Occppation Related--This type of program resulted in 50-75% of the students being employed in the same group of occupations. w . Class III - Occgpation General-—This type of program resulted in less than 50% of the students being employed in the same group of occupations. In a Minnesota study, Rossman16 compared four methods of measuring the relatedness of the employment of vocational graduates to their training. The methods included: 1. Graduate Self Report--A measurement system in which gra- duates use their judgment to rate the relatedness of their training to their employment. 2. Researcher Classification of Skills--A classification system in which a researcher uses reported job titles and duties to analyze the relationship of jobs obtained to the instructional program. 3. Prestige Level--A system in which a researcher rates job and program titles using a prestige scale reflecting socioeconomic status (professional is the highest rating, laborer is the lowest rating). 16Marilyn Martin Rossman, “Job Relatedness As a Criterion for Assessing Vocational Education Program Effectiveness," (Ph.D. Dissertation, Minnesota, University of Minnesota, 1977), p. 44-47. 24 & . Dictionary of Occppational Titles (DOT)--A system in which a researcher determines the relationship of programs to DOT worker trait groups. Rossman concluded that the Graduate Self Report was the most appropriate measure for evaluating vocational programs in her study, one of Minnesota post-secondary vocational graduates. In a recent South Carolina study, Ollis17 reported that the pro- cedure used to measure relatedness critically affected the level of relatedness found. The study contrasted the following measures of relatedness: 1. Graduate Self Report--Graduates used their judgment to assess the relatedness of their training to their employment. 2. Job Title-Program Title Match--Responding students reported their job title. The investigator assigned an occupational code to the title and assessed, using a cross-code index, the relationship of the program to occupation. Three independent code structures were used; the 9-digit Dictionary of Occupational Titles codes (12,000 titles), the 4-digit Standard Occupational Classification (SOC) codes (500 titles) and the 2-digit (SOC codes (26 titles). 17Harvey Ollis, Alternative Methods for Collectipg Follow-Up Information About Secondary Vocational Education Students, (Columbia, South Carolina: South Carolina Occupational Information Coordinating Committee, 1982). p, I-Z. w 4- 25 Ollis18 concluded that the level of detail in the occupational classification structure affects the measurement of relatedness. The study's findings of relatedness varied by measure from 54% for the 2-digit SOC codes, 48% for graduate self report, 33% 4-digit SOC codes, and 16% using the 9-digit Dictionary of Occupational Titles codes. Occupational and Educational Code Systems The problem that was addressed in this study involved relating vocational instructional programs to the titles of job obtained by former vocational students. The possible relationships between the instructional programs and the job titles could have been understood only within the context of classification systems used to codify occu- pations and educational programs. This section summarizes the rele- vant code systems. A variety of different code or classification systems were used to organize information about occupations and educational programs. Many of these classification systems were developed by federal agen- cies to carry out specific regulatory or administrative mandates. The classification systems were used to efficiently collect, process, aggregate, and/or report data about specific programs. Some of the 18Ibid., p. IV-7. 26 classification systems were agency-unique and applied to a specific program within an agency. As a result, the classification systems were each fundamentally different in structure, coverage, and func- tion. Some of the classification systems, such as the Dictionary of Occupational Titles (DOT) codes, are used by a wide variety of USET‘S.19 The essential features of these occupational and educational classifications systems can best be described using a series of figures presented in the _Qppppational Information System (OIS) Handbook published by the National Occupational Information Coordinating Committee.20 Figure 1 presents the features of seven major occupational classification systems. Further it describes the coverage of each system and lists the responsible federal agency and source publica- tion. Of special relevance to this study are the Dictionary of Occupational Titles (DOT) code and Standard Occgpational Classification (SOC) code systems. Figure 2 describes two major educational classification systems; the U.S. Office of Education code and the Higher Education General 19Occupational Information System Handbook, Vol. I (Washington, D.C.: National Occupational Information Coordinating Committee, 1981), p. 4.1.1. 20The author of this dissertation was the principal researcher in the development of the DIS Handbook. .5. 27 5.39.5.1: 35:35.5 .2532. Tu... 639:.ch . [11.53. a 3:; .25.. Hmarwu: um N.=::.uu.: 1...: .32... .25.. 1:2:u2. mm Nmmmm.uu.: 2...... its .m.._=_:.:..._:... .4... is... 19:15.... 2. .Eu .53-ii... 1:. 1:: .59.».m :3..au -...mm=_u n_:. m.:omau: .52.... as. 5.; Q... .m.:..u== unmmmm mam mu_.um:1:..md use... 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Occupational and educational classification systems are used by different federal, state and local agencies for various administrative and regulatory purposes. Data reported on these code systems is often included in manpower planning as representing either occupational supply or occupational demand. These two factors, defined below, are important to planning for vocational education and employment and training programs. Occupational Supply Occupational supply is defined as the sum of workers employed in an occupation plus the number of persons who are not employed but are available for and actively seeking employment in an occupation.21 In vocational education, the most important occupational supply con- sideration is not the number of persons employed, but rather the number of persons available and seeking employment, including voca- tional graduates. 21Occupational Information System Handbook, op. cit., p. 1-11. fl 31 Occupational Demand Occupational demand is defined as the number of persons who are employed in an occupation plus the number of new job openings occurring over time.22 In vocational education, the most important occupational demand consideration is the number of job openings that are or will be available. These openings represent potential employment opportunities for former vocational students. Figure 3 presents the major classification systems and data sour- ces that are used in occupational supply and occupational demand ana- lysis. Occupational Coding of Job Titles The assignment of occupational classification system codes to job titles is a complex and time-consuming process. Of relevance to this study were two large national data collection activities that have assigned occupational codes to job titles. These were the U.S. Census of Population and the Vocational Education Data System. The methods used to assign occupational codes in both systems are described in the next two sections. U.S. Census of Population Every ten years the Census of Population is taken. Information on every U.S. household is obtained, including the number of indivi- 221bid., p. 2-11. #— 32 Figure 3 -- Classification Systems Used in Major Occupational Demand and Supply Data Sources Occupational Demand Occupational Supply Data Source Classification System Data Source Classification 3V5t9m 1. 0E5 Program“ . Census-based matrix I. VEDS USOE Employmnt classifications . Estimates and CBS Survev-‘oased natrw -. HEGIS HEGIS Proyections classifications S. NCES survey USOE l 4. CETA HIS DOT or SOC ; 2. Employment . DOT . Service Job 3' SNAPS DOT I Orders 6. Vocational DOT 3 Rehabilitation l 3. Job Vacancies . SOC. DES Survey, or 1 DOT T. State Education Varies by State E Mm ! s.w1u DOT i 9. Job Corps - DOT ! 10. UI DOT 11.esmu M” l 12. Veterans MOS Key OES - Occupational Employment Statistics DOT - Dictiona;ry of Occupational Titles SOC - Standard Occupational Classification VEDS - Vocational Education Data System HEGIS - Higher Education General Information Survey CETA - Comprehensive Employment and Training Act MIS - Management Information System SNAPS - State and National Apprenticeship Programs WIN - Work Incentive Program UI - Unemployment Insurance ESARS - Employment Service Automated Reporting System USOE - U.S. Office of Education MOS - Military Occupational Specialty Source: Occu ational Information System Handbook, Vol. II Washington, D.C.: National Occupational Information Coordinating Committee l98l) p. 4.l-6. 33 duals residing 'hi the household, their sex, race, labor force par- ticipation, income, and geographic mobility. The 1970 and 1980 Censuses included questions on occupational status that were to be answered by a sample of the respondents (approximately one in five). Figure 4 presents a comparison of related questions contained in the two survey years. In both surveys, respondents were asked to identify the type of work done and important duties associated with the job. Completed census forms were collected by the Bureau of the Census and assigned an occupational code. In 1970, the code assignments were made using the Alphabetical Index of Industries and Occupations.23 This index provided an1 alphabetical listing of approximately 23,000 job titles groups within 441 separate occupational categories. Coders used the index and its occupational code designation for each respon- dent in the sample. The 1980 Census was occupationally coded in a similar manner using a revised 1980 index.24 The revised index contained a revised occupational code system based on the 1980 Standard Occupational Classification Manual.25 23Alphabetical Index of Industries and Occupations: 1970 Census of Population, (Washington D.C.: U.S., Bureau of the Census, Department of the Census, 1971). 24Alphabetical Index of Industries and Occupations: 1980 Census of Population, (Washington D.C.: U.S., Bureau of the Census, Department of the Census, 1980). 25Standard Occupational Classification (SOC) Manual, (Washington D.C.: U.S., Executive Office of the President, Office of Management and Budget, 1980). 34 Figure 4 -- Industry and Occupation Questions Used in the 1970 and 1980 Census of Population L370 Census 3343. Wammpem humi.1len7.llbebdneeu~euep&.deunh In one a me be weed :be new boat. I] (‘1': («In U no job a tau-en bu weed. (m mien-ene- [er lat yet a 5mm: mete mo. 3. loan" I. Fortunate-ed! 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Irmmeeuweuymm Anne Forces. mt "AF”mweumfl. {Name of runway. m mam. or cm W! i ummumammwu i i mewaummmm ‘ ffcm.-Hmu.wmm~mm I: no mice Meme-alum 4 l c. lsmm—(meemi I l Manufacturing - I Resonance «m m Z Other - ermine. commune! sememnem. Zilmumounn 7 amkmuwwfiweemiemm? ' (for ear-vole.- Repealed m. m w. sum of ' ; aver r W W) ’ , b.mmMW'emmmuW{ nope i W --- .......... - ...... ..- -- - .......... _ Ff’o'r' 2:333}..- .55;va ESE-475515; 37a}; BEIHETQW ’ —_—q or! elm Mum; e . m min 3" “um (Fill 0‘" m") I30.Wumiem—(Ffllmearelel 5 mumm.umu L . Emoteyeeofomatecomoeny.msmees.or .. mm. for wages. salary. or ems. . . C .5 unomauai. for ween. salary. or cm ' Federal M W ................ 3 ; Fm m emotoyee . . . - | State mam m .................. c 1 Stan m emotoyee , . . a . , : teal mam! W (my. many. an). .. C I 1 Local mm (mm (my, canny. em). ‘ Self-mm In on bum I Safari-tom an own We. Wmuefletm— mumamrum- l One m not wed .......... c I Own m not incorporated 5 One w Wed ............. a I 0*“ poem am i wunhegggngzntuuwemueumruun c : Wammeggggggpnunwruamunaflwm - 3 l I Source: Occupational Information System Handbook, Vol. I (Washington. D.C.: National Occupational InfOrmation Coordinating.Camnittee 1981) p. 2.l.l. 0-4 35 In both 1970 and 1980, groups (n: the Bureau of Census coders, read the reported job title and duties and assign the most closely related census occupational category. Given the size of the census data collection, even the one-in-five sample represents the largest occupational coding of job titles undertaken in this country. Vocational Education Data System Following the passage of the 1976 federal legislation (1976 Education Amendments), the reporting requirements for state educa- tional agencies were standardized by the Vocational Education Data System (VEDS) program developed by the National Center for Education Statistics (NCES). One component of VEDS is the completer/leaver follow-up report that provided information on vocational program completers, including:26 1. Employment Status--The employment status (e.g., employed in a field related to training, pursuing additional education) of program completers is to be provided by individual six-digit Instructional Program codes. Figure 5 provides a sample format of this report. 2. Field of Employment--Another type of data to be provided in the VEDS follow-up report was the type of job held by the program completers. Figure 6 provides a sample 26Vocational Education Data System (VEDS) Technical Assistance Handbook (Washington D.C.: National Center for Education Statistics, U.S. Department of Education, 1979) section 2404-5, p. 4. 36 .a-eoem eowuuam Amam_ .eoepmusem to newsptaaao .m.: .mumumwumum comumusum to» cmucmu chowumz ”.u.o .coumcwcmmzv xoonvcm: mucmumwmm< Pmuwccomh Amom>v Emuwxw mama comamozcm pmcowpmuo> ”muczom _ I.m.gmm.m. -mm all. 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As can be seen on the sample, the “occupational field of current employment" is to be identified using the two-digit Standard Occupational Classification codes. States completing the VEDS reports were to iden- tify the appropriate two-digit code by collecting job titles of the program completers on the follow-up sum- mary and then, using the Standard Occupational Classification Manual, assigning the appropriate code. The NCES had not provided a methodology for making such code assignments.27 Cross-Code Indexes Relatingggccupations and Educational Programs The growing interest in the employment status of vocational edu- cation students has stimulated the development of resource materials detailing the occupations related to specific vocational training programs. This section describes four major references that have been developed for this purpose. Vocational Education and Occupations The Vocational Education and Occupations28 (VEO) was developed in response to the Vocational Education Amendments of 1968. This 271mm, p. 10. 28Vocational Education and Occupations (Washington D.C.: U.S., Department of Labor, Manpower Administration) 1969. 39 publication was designed to link vocational-technical education programs and occupations, and provide a means for evaluating, com- paring, and improving the results of occupational education. The publication had several uses for vocational education. It could be used to design curriculum content and to plan education facilities in relation to labor market needs in various occupations. It was useful for summarizing information (Ml occupational manpower resources and requirements. The VEO also could assist in guidance counseling youth and adults in making appropriate career and vocational choices. It was designed to make possible more realistic matching of the numbers of training program graduates with the labor market needs for gra- duates. The document related the six-digit U.S. Office of Education (USOE) codes to nine-digit Dictionary of Occupational Titles (DOT) codes. The data was presented in tables in sequence by DOT codes within USOE codes as well as a separate cross-reference in sequence by DOT codes. Although additional cross-code indexes (described below) had been developed that cover other occupational and educational classification systems, the importance of the USOE-DOT cross-reference in the VEO should not be overlooked. As a recent national study noted, Despite the use of USOE program codes for vocational education, students are actually being prepared and trained fOr [MIT occupations, and program planners and instructors must therefore rely heavily on the DOT to describe the occupations for which the students are being prepared. 29National Research Council, Work, Jobs, and Occupations: A Critical Review of the "Dictionary of Occupational Titles," (Washington D.C.: National Academy Press, 1980), p. 75. 40 Matching Occupational Classifications to Vocational Education Program Codes The Matching Occupational Classifications to Vocational Education Program Codes3O built on the earlier VEO by adding the Occupational Employment Statistics (OES) code. This classification system is used by the Bureau of Labor Statistics (BLS) in producing occupational pro- jections for the states and nation. The report was designed to bridge the Bureau of Labor Statistics OES system and the USOE system used to classify instructional programs. The report noted the limitations inherent in such a cross-code index, stating: Unfortunately, the classification systems as they are presently constructed do not permit a clear-cut matching of categories on a one-to-one basis. Perhaps the fun- damental barrier to a perfect matching of manpower pro- jections and instructional programs is that the various classification systems were developed for different pur- poses. The vocational education instruction codes were created primarily to facilitate educational planning, to standardize terminology. and to simplify reporting of educational statistics. On the other hand, the occupa- tional classification schemes incorporated ‘hi manpower projections were designed primarily to enumerate jobs which require extensive formal or specialized training or in which large numbers of pe0ple are employed. However, the conversion table presented in this report should enable in ovative planners to solve many of these matching problems. 3OMatching Occupational Classifications to Vocational Education Progrmn Codes, (Washington D.C.: U.S. Bureau of Labor Statistics, Department of Labor, 1975). 311bid., p. 1. 41 Vocational Preparation and Occupations Vocational Preparation and Occupations32 (VPO) is a comprehen- sive technical reference document that brings together the information on the interrelationships of occupational and educational classifica- tion systems. It covers the classification systems used for federal and state reporting of vocational education, Comprehensive Employment and Training Act (CETA), vocational rehabilitation, employment ser- vice, and apprenticeship programs. The specific classification systems presented in VPO include: 1. U.S. Office of Education (USOE) 2. Dictionary of Occupational Titles (DOT) 3. Standard Occupational Classification (SOC) 4. Occupational Employment Statistics (OES) Program The Vocational Preparation and Occupations (VPO) describes each classification system and lists its codes and titles. The VPO appen- dix contains a crosswalk of USOE codes to other classification codes. The VPO is intended to assist administrators and planners of edu- cation and training programs to compare and use information obtained under various classification systems in order to report occupational supply and demand information. The inclusion of the Standard Occupational Classification (SOC) 32Vocational Preparation and Occupations: Educational and Occupational Code Crosswalk (Washington D.C.: National Occupational Information Coordinating Committee, 1980). 42 codes in the VP0 is an important addition to relating occupations to training programs. The SOC codes provide a mechanism for cross- referencing and aggregating occupation-related data. The SOC covers all occupations in which work is performed for pay or profit.33 Michigan Interim OE-DOT Crosswalk The Michigan Interim OE-DOT Crosswalk34 represents a state adap- tation of the earlier VPO document. A group of Michigan vocational educators and labor market analysts reviewed the occupations related to vocational education programs and revised the VP0 crosswalk to reflect the Michigan labor market.35 References were also added, as appropriate, included the titles in the Michigan Occupational Information System. The preceding four documents represent the historical development in the area of relating code systems for occupations and vocational education programs. This study used the Michigan cross-code index (Interim OE-DOT Crosswalk) to match programs to related job titles. 33Standard Occupational Classification Manual, op. cit., p. 7. 34Michigan Interim OE-DOT Crosswalk (Lansing, Michigan: Michigan Occupational Information Coordinating Committee, 1980). 35The author of this dissertation initiated and directed the deve- lopment of the Michigan Interim OE-DOT Crosswalk in his capacity as the Director of the Michigan Occupational Information Coordinating Committee. Chapter III RESEARCH PROCEDURES The Inain purpose of this study' was to compare two different measures of the relatedness of the jobs of former students to their vocational education programs. These measures were graduate self- assessment of relatedness and matching of the titles of the job out- come and the vocational education program. This study analyzed these measures of relatedness for a group of former Michigan secondary voca- tional education students. The study also assessed the impact of selected student and program characteristics on these relatedness measures . It was the intent of the investigator that the results of this study would assist vocational education data analysts in their future work. Prior ix: the 1976 Educational Amendments, analysts suffered from limitations in educational outcome and manpower data bases.1 The accountability reporting required by the Vocational Education Data System (VEDS)--resulting from the 1976 Educational Amendments--had changed that situation. The VEDS data system, including the program completer follow-up component, greatly' expanded 'available data on occupational preparation programs. The problem then facing analysts became how to extract the meaning and implications from the volumes of 1The Vocational Education Study: The Final Report, (Washington D.C.: National Institute for Education, U.S. Department of Education, 1981) P. VII 17. 43 44 data available. It was for this reason that the investigator designed this study to use the existing VEDS follow—up information rather than collect new data. This chapter describes the procedures that were followed in this study, and the following elements are discussed: instrumentation, population, sample, independent variables, dependent variables, research questions, and data analysis. Instrumentation The study analyzed data collected by the Michigan Department of Education as a: part of that agency's evaluation responsibilities in administering federal funds. The data collection instrument used was the 1980 "Follow-Up Survey of Former Students" (Form number VE-4045-A), developed by the Nfichigan Department of Education. The instrument was distributed by local educational agencies to 1980 gra- duates in the early spring of 1981, as the eighth annual follow-up survey of former students conducted in Michigan. A c0py of the 1980 "Follow-Up Survey of Former Students" and the accompanying "Instructions for Conducting the 1980 Follow-Up Survey " are included as Appendix A of this study. The purpose and mandate for the 1980 survey' were described by the Michigan Department. of Education as follows:2 zInstructions for Conducting the 1980 Follow-Up Survey. (Lansing, Michigan: Vocational-Technical Education Services, Michigan Department of Education, 1981), p. 1. 45 The purpose of the 1980 Follow-Up Survey is to gather information needed to help peOple make decision about vocational education programs. Program fiscal agents (local districts) that receive Federal or State funds for conducting (vocational education) programs are required to report ‘follow-up data about program completers and leavers, including information needed for the State to do the follow-up with the employers of a sample of former students. In turn, we in the State office are required to report the results of the surveys to the National Center for Education Statistics for inclusion 'hi reports to the U.S. Department of Education and Congress. The 1980 "Follow-Up Survey of Former Students“ contains 14 questions, most of which include a list of optional answers from which the students are to choose the answer that best represents the student's situation six months after graduation. The tOpics covered in the survey are noted below. 1. Attending School (question 1) A. Use of vocational training (question 2) B. Type of school (question 3) 2. Working A. Hours per week employment (question 4) B Use of vocational training (question 5) C. Job satisfaction (question 6) D Wages (question 7) E. Job title and duties (question 8) F. Employer information (question 9) 3. Not working 46 A. Looking for job (question 10) B. In military service (question 11) C. Homemaker (question 12) 4. Student demographics A. Sex (question 13) B. Racial/ethnic group (question 14) The survey also contained several questions that were to be answered by school personnel rather than students. The two school questions important to this study identified the vocational education instructional code of the program the student completed and the student's participation, or non-participation, in a cooperative educa- tion program. P0pulation The population for this study consisted of the 1980 graduates of Michigan secondary schools who had completed vocational education occupational preparation programs and were employed in March, 1981. All 1980 vocational education graduates were sent a: mail survey, entitled "Follow-Up Survey of Former Students," in March of 1981. The survey (form VE 4045-A) was developed by the Michigan Department of Education and was described in the preceding section. A total of 47,768 former vocational students were surveyed in the 1980 survey. A total of 33,618 surveys were completed and returned for a response rate of 70.38%. Of the students responding, 20,484 indicated they 47 were employed full-time or part-time. The population of this study was therefore 20,484.3 Sample Two levels of sampling were used in the conduct of this study. The first level of sampling involved selecting the population subgroup that had occupational codes assigned to the graduate jobs. The second level of sampling involved selecting a subgroup of vocational educa- tion instructional programs for analysis. Both sampling methods are described below. Occupational Coding Sample The purpose of this study was to compare two different measures of the relatedness of job outcomes of former students of vocational education programs. One measure (self-assessment of former students) was recorded on the 1980 survey for every survey in the population. The second measure expressed the relationship between the vocational program and the job title reported on the survey. It was obtained by first assigning occupational codes to the reported job title and then "matching" this code to the instructional program by the use of a cross-code index. Not all (M: the completed surveys with job titles were assigned occupational codes. The Michigan Department of Education, as a part of its coordination of the 1980 survey, assigned 3Placement Summary of Completers by Program, (Lansing, Michigan: Vocational-Technical Education Services, Michigan Department of Education, Report X0607, 1981), p. 7. 48 occupational codes to a sample of the returned surveys. Table 2 iden- tifies the sampling plan used. The sampling plan was inversely related to the size of the program, with a small share (1/19th) of the largest program occupationally coded and all (1/1) of the smallest programs coded. Vocational Program Sample The second level of sampling involved the selection of a group of vocational instructional programs for analysis. Program-level analy- sis has been common in Michigan vocational education; the Annual State Plan for Vocational Education in Michigan and the analysis reports (M: the follow-up survey feature program-level data presen- tation. The appropriateness of this approach was supported by two recent national studies. In 1981, Wood and Haney reported that employment 'Hi jobs related to training varies considerably from one vocational education program area to another, with the highest propor- tion of job-to-training matches in trade and industry programs and in business programs.4 ‘The 1981 National Institute of Education study of vocational education, mandated by the 1976 Educational Amendments, reported that: Students in different occupational specialties (vocational programs) in secondary school were found to 4E. Woods and H. Haney, Does Vocational Education Make a Difference? A Review of Previous Research and Re-Analysis of National Longitudinal Data Sets (Cambridge, Massachusetts: The Huron Institute, I981), p. 4.5. 49 Table 2 -- Sampling Plan Used by the Michigan Department of Educa- tion to Assign Occupational Codes Vocational Programs Job Titles Occupationally Category Coded Code Title 1 1/19 O4.0800* General Merchandise 2 1/10 17.0302* Auto Mechanics 3 1/9 14.0700* Steno/Secretarial 14.0901 Clerk-Typist 14.9700 ClericaL Lab 14.9800 Steno/Clerical Lab 4 1/6 17.1000 Construction & Maint. In-School 17.1098 Construction & Maint. On-Site 5 1/4 01.0100* Agricultural Production 07.0303* Nurse Aide 09.0203* Food Management 17.2302 Machine Shop 17.2306 Welding & Cutting 6 1/3 01.0300 Agriculture Mechanics 01.0301 Ag Power and Machinery 01.0500 Ornamental Horticulture 01.0502 Floriculture 01.0503 Greenhouse Operation & Mgt 01.0504 Landscaping 07.9802 Health Occupations Cluster 09.0201 Child Care & Guidance Serv. 14.0102 Bookkeepers 14.0104 Machine Operators 14.0105 Tellers 14.0200 Business Data Processing 14.0201 Computer Operations 17.0301 Body and Fender 17.1300 Drafting Occupations 17.1398 Architectural Drafting Table 2—-Continued 50 Vocational Programs Job Titles Occupationally Category Coded Code Title 6 1/3 17.1500 Electronics Occupations (Cont'd) 17.1501 Communications 17.1502 Industrial Electronics 17.1503 Radio and Television 17.1598 Radio and TV Broadcasting 17.1900 Graphic Arts Occupations 17.1903 Lith. Photo Platemaking 17.2602 Cosmetology 17.3100 Small Engine Repair 7 1/2 01.0600 Agricultural Resources 07.0101 Dental Assistant 07.0904 Medical Office Assistant 07.9801 Ward Clerk/Ward Secretary 14.0203 Programmers 17.0100 Air Conditioning 17.0700 Commercial Art Occ. 17.1100 Custodial Services 17.1400 Electrical Occupations 17.1401 Industrial Electrician 8 1/1 All Remaining Programs 51 differ on outcomes pertaining to gainful employment.5 The six vocational programs selected for analysis in this study were the largest programs--in terms of enrollment--in each of the vocational education program areas They were selected based on their size, so that a large segment of vocational programming could be effi- ciently analyzed and tested for relatedness measures. Table 3 presents the six vocational programs selected for inclu- sion in this study and the program areas associated with each. Table 3-- Sample Vocational Programs and Their Program Areas Sample Vocational Programs Program Areas Code Title Code Title 01.0100 Agricultural Prod. 01. Agriculture 04.0800 General Merchandise 04. Distribution 07.0303 Nurse Aide 07. Health 09.0203 Food Management 09.02 Home Economics- Occupational Preparation 14.0700 Steno/Secretarial 14. Office 17.0302 Auto Mechanics 17. Trades and Industry The population and sample of these six vocational programs for the 5The Vocational Education Study: The Final Report, op. cit., p. VII-17. 52 1980 survey are presented in Table 4. The population of the six programs included 8,343 of the 20,483 survey' respondents for all programs, a 40.73% coverage. The sample reflected more than 16 per- cent of the population in the six programs. Table 4 -- 1980 Survey Respondent P0pulation and Sample Vocational Program 1980 Survey Respondents Percent Sample of Code Title Population Sample Population 01.0100 Agricultural Prod. 495 136 27.47% 04.0800 General Merchandise 3,434 261 7.60% 07.0303 Nurse Aide 553 185 33.45% 09.0203 Food Management 727 261 35.90% 14.0700 Steno/Secretarial 1,031 175 16.97% 17.0302 Auto Mechanics __2;193 ___318_ 15.12% Total 8,343 1,336 16.01% Independent Variables This study compared two different measures of the relatedness of the jobs in: former vocational education students. Four independent variables covering student and program characteristics were analyzed in this study to help describe and explain any differences between 53 these measures. This section describes the data sources used in this study for these independent variables. Sex of Student The sex of the student was a self-reported variable on the Follow-up Survey. The survey item for the sex of the student is shown in Figure 7. Figure 7 -- 1980 Follow-Up Survey of Former Students (VE-4045-A) Student Sex Item What is your sex? [::] Male :1 Female Race of Student The race of the student was a self-reported variable on the Follow-Up Survey. The survey item for the race of the student is illustrated in Figure 8. 54 Figure 8 -- 1980 Follow-Up Survey of Former Students (VE-4045-A) Student Race Item American Indian or Alaskan Native Please identify yourself as a member of one of the groups of pe0ple listed below. (Check ONLY ONE) Asian or Pacific Islander Black, not of Hispanic Origin Hispanic DUDE] D White, not of Hispanic Origin Cooperative Education Cooperative education is a program Option involving both in- school and (N1 the job learning experiences. Students who had par- ticipated in such a program were identified by school staff after the student returned the completed survey. The staff identified the cooperative education status by checking a yes or no category, as appropriate. Vocational Program The vocational education instructional program that the student completed was recorded by school staff after the student returned the completed survey. The appr0priate six-digit U.S. Office of Education code was used to designate the specific instructional program. Table 3 identified the instructional programs analyzed in this study. 55 Dependent Variables Two dependent variables were analyzed in this study. These variables were the two different outcome measures of job relatedness. Described below are the sources used for these variables. Job Relatedness Measured by Job Title Matched to Program Title Identifying this measure of job relatedness involved completing two procedures, occupational coding and cross-code matching. Given the importance of this factor to the first research question, these procedures are described below in some detail. The first procedure involved assigning an occupational code for each reported job title. As described in the "Occupational Coding of Job Titles“ section of Chapter II in this study, the Vocational Education Data System required the identification of former student jobs by the codes contained in the Standard Occupational Classification (SOC) Manual. Michigan Department of Education staff assigned four-digit SOC codes to the survey records using a procedure6 developed by the National Occupational Information Coordinating Committee (NOICC). The procedure contained the following steps: 1. Step 1--Review the title and job duties reported on the 6“Training Materials for SOC Coding of Occupational Information in the VEDS Follow Up 0f Completers and Leavers", (Washington D.C.: National Occupational Information Coordinating Committee, 1980). 56 returned survey. 2. Step 2--Look-up the reported title in the SOC Index for possible SOC titles. 3. Step 3--Read the description and job titles for each relevant SOC code found in the Index. 4. Step 4--Select and record the SOC code that best matches the reported title and duties. This procedure was repeated for each of the 1,336 returned responses included in the sample (see Table 4). The accuracy of the SOC coding was not tested in this study. The coding procedure was assumed reasonable and the coding staff competent.7 The second procedure involved using a "cross-code index" to iden- tify if the four-digit SOC code was related to the instructional program. The procedure used to determine the relatedness of the occu- pational coding was established by the investigator, using a cross- code methodology that he tested in the state of South Carolina.8 The 7The author of this dissertation was responsible for training the coders on the use of the SOC in his capacity as the Director of the Michigan Occupational Information Coordinating Committee. 8Harvey Ollis, Alternative Methods for Collecting Follow-Up Information About Secondary Vocational Education Students (Columbia, 5. Carolina: South Carolina Occupational Information Coordinating Committee, 1982) p. I-2. 57 Michigan Interim OE-DOT Crosswalk9 described in this study, Chapter II, was used as the cross-code index. Figure 9 presents the six voca- tional instruction programs from that document. The last column in Figure 9 is the "SOC Code." The identification of the job relatedness involved matching the four-digit SOC codes in this column with the four-digit SOC code assigned to the reported job title. If the SOC code of the reported job title matched any of the listed SOC codes, the job was considered “related.“ If it did not match, it was con- sidered "not related.“ An example of this can be seen for Auto Mechanics (USOE program code 17.0302) on the second page of Figure 9. If the reported job title were coded 6711 (Automobile Mechanics), 7281 (Automobile Mechanic Helper), or 6792 (Automobile Tester), then it was coded as related; otherwise not related. To assist readers to better understand the related SOC, the SOC title of each related occupation's SOC code is presented in Appendix B. Job Relatedness Measured By Student Assessment The second relatedness measure was simpler to assess; this was a self-reported variable on the Follow-Up Survey. The survey item is listed in Figure 10. 9Michigan Interim OE-DOT Crosswalk, (Lansing, Michigan: Michigan Occupational Information Coordinating Committee, 1980). 58 Figure 9-- Related SOC Codes for Sample Insructional Programs NICNIoAN INIPPIN 0t-001 CPossuALx oc1 1. i900 usoe PPDPPAN 01. 010000 APPIcuLIDPAL PPDPUCTIDN SUBdECT NAIItP AND LtAPNIND tthPIthes NNIcN APP couccPNtD NI1N 1N5 PPINCIPLts AND PPDCtSSts INvoLvep IN IN! PLANNINo PELArep 10 AND THE tc0NDNIc use or PACILIIIts. LAND. NAIEP NACNINth. CNtNICALs. FINANCE AND LAADP iN 1N5 PPDDOcIIDN 0P PLANI AND ANINAL PPoouc15 iN PPACIICP. ACIIVIIIts INCLUDE CLASSPOON INSIPOCIIDN AND LADDPAIDPv EXPEPIthts. IN AND our DP SCHOOL. INCLUDINo PAPNs. 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O O O O O n M1ch1gan Occupat10na1 InformatIDn CoordinatIng oom- mittee,1980) 60 Figure 10 -- 1980 Follow-Up Survey of Former Vocational Students (VE-4045-A) Job Relatedness On your present job, how much do you I::] A lot use the vocational training you received in your high school or area vocational [::] Some education center? ]:[ Hardly Any E] None The researcher re-coded the responses into dichotomous categories for comparison with the job title-program title measure of related- ness. Responses “a lot" and "some" were considered to indicate rela- tedness and responses "hardly any” and "none" were considered to indicate non-relatedness. This is the same procedure used by Michigan Department of Education staff in the administrative reports of the follow-up stu- dies. Appendix C presents the Michigan Department of Education ”Placement Summary of Completers By Program“ (Report X0607, 10/29/81). This report identifies the number of employed respondents (part—time and full-time) who were in jobs "related" or "unrelated" to their program. The criteria used in this report was the same as the dicho- tomous, self-assessment categories described 'hi the preceding paragraph. 61 Research Questions The purpose of this study was to compare two different measures of the relatedness of occupational outcomes of vocational program gra- duates. A comparison was made of the response pattern of the following items: 1. Student Self-Assessment of Relatedness--Student respon- ses detailing how much they used their vocational training on their present job provided one measure of relatedness. 2. Job Title Matched to Program Title--Another measure of relatedness matched the job title, as reported by the student, to the program title, using a cross-code index which identified the related occupations for each program. One research question asked whether any of the student or program characteristics helped predict the two neasures of job relatedness. This questions was analyzed using the following data from the 1980 "Follow-Up Survey of Former Students": 1. Student characteristics A. Sex B. Race 2. Program characteristics A. COOperative education B. Instructional program 62 The second research question tested the relationship between the relatedness measures. This research question was tested by conducting contingency table analysis of independence and relationship. The two research questions analyzed in this study are listed below: 1. Do the student and program characteristics predict variation in the two measures of job relatedness? 2. Are the two measures of job relatedness independent or related? If they are not independent, what is the strength of their relationship? Data Analysis Data Analysis Techniques In the first research «question, the relationship between the dependent variables of job relatedness and the independent variables of student, program and job characteristics was tested with a multiple regression statistic. The primary advantage of the multiple regression method is that it allows simultaneous analysis of ‘the effects of a large number of variables on a given outcome.10 The multiple regression analysis was used to identify the portion of the 10Sampit, Chatterjee and Bertram Price, Regression Analysis by Example (New York: John Wiley and Sons, 1977), p. I. 63 variation in the dependent variables that could be explained by the variation in independent variables. The second research question had to do with measurement of inde- pendence or relatedness between the two dependent variables. The chi- square test, used in contingency tables, provides an appropriate test of the independence of two sample distributions.11 Chi-square sta- tistics comparing the two job relatedness measures were developed for all of the respondents and ‘for sub-groups by student and program characteristics. By itself, chi-square can be used to identify the independence or relatedness of two variables. It does not identify the strength of a relationship.12 Several measures of the strength of the association between the two variables are available.13 The second research question involved comparing the two sub-categories (related, not related) of each of the two measures of job relatedness in a 2 x 2 contingency table. For a 2 x 2 table, the phi statistic was a suitable measure of the association or strength of the relationship.14 11William Hays, Statistics for the Social Sciences (New York: Holt, Rinehart and Winston, Inc., 1973). p. 718. 12Norman H. Nie, et. al., Statistical Package for the Social Sciences, second edition, (New York: McGraw-Hill Book Co., 1975), p. 224. 138.5. Everitt, The Analysis of Contingency Tables (London: Chapman and Hall, 1977), p. 56. 14Norman H. Nie, op. cit. 64 The chi-square and phi statistics were employed to test for a relationship between the two independent variables and the strength, if any, of their association. Data Analysis Operation The data from the sample survey responses was received by the investigator from the Michigan Department of Education in computer card format. After the investigator added the rating of relatedness for the occupational code to each card, the data were ready for analy- sis, comparing the two measures of job relatedness. The Statistical Package for the Social Sciences (SPSS) was used to analyze the data. SPSS Version 8.0 was used at the computer center at Michigan State University. The specific subprograms used were FREQUENCIES, MULTIPLE REGRESSION, and CROSSTABS which provided both descriptive and statistical results. Chapter IV FINDINGS This chapter presents the data gathered on former students of six selected vocational education instructional programs. These students graduated or left school in 1980 and responded to a follow-up survey distributed by their local educational agency in the winter of 1981. This chapter presents data analyses of the independent variables, which included the student characteristics (sex and race) and the program characteristics (cooperative education and instructional program), along with the dependent variables that measured job rela- tedness (self-assessment and job title-program title match). The data is presented in the following three sections: the frequency' of responses for each of the independent and dependent variables, multiple regression analysis predicting the importance of the indepen- dent variables to the dependent measures of job relatedness, and measurement of the independence and association between the measures of job relatedness. Frequency of Response Sex of the Respondents The sample consisted of 1,336 program completers who responded to the 1980 Michigan Follow-Up Survey. A slight majority of the respon- 65 66 dents were female (52.2%). ‘Table 5 presents the sex profile of the respondents. Table 5 -- Sex of the Respondents (n=1,336) Number of Percent (%) Sex Category Respondents of Total Male 639 47.8 Female 697 52.2 TOTAL 1,336 100.0 Race of the Respondents Five racial categories were represented in the sample. However, the number of respondents in all categories except white and black was very small. Almost ninety-three percent of all sample respondents were identified as white. Approximately five percent of the survey population were identified as black. Table 6 presents the racial pro- file of the sample. 67 Table 6 -- Race of the Respondents (n=1,336) Number of Percent (%) Racial Category Respondents of Total Indian 16 1.2 Asian 5 0.4 Black 64 4.8 Hispanic 7 0.5 White 1,239 92.7 Not Identified ___5 i4 TOTAL 1,336 100.0 Cooperative Education Cooperative education was a dichotomous variable, with respon- dents either participants or non-participants. Almost two-thirds of the respondents (64.4%) did not participate in a c00perative educa- tion progrmn. Table 7 presents the profile of the sample for this variable. 68 Table 7 -- Participation Status of the Respondents Cooperative Education (n=1,336) Cooperative Education Number of Percent (%) Participation Category Respondents of Total Yes 425 31.8 No 860 64.4 Not Identified 51 3.8 TOTAL 1,336 100.0 Instructional Program This study covered six large vocational education instructional programs. 'The sample included all the respondents in these six instructional programs who had been assigned occupational codes, as described in Chapter III. Auto Mechanics, Food Management and General Merchandise were the instructional programs having the largest number of respondents, while Agricultural Production had the fewest. The response pattern by instructional programs is presented in Table 8. 69 Table 8 -- Instructional Program of the Respondents (n=1,336) Number of Percent (%) Program Code and Title Respondents of Total 01.0100 Agricultural Production 136 10.2 04.0800 General Merchandise 261 19.5 07.0303 Nurse Aide 185 13.9 09.0203 Food Management 261 19.5 14.0700 Steno/Secretarial 175 13.1 17.0302 Auto Mechanics __;;u; _j§1§§ TOTAL 1,336 100.0 This measure of job relatedness was based on the students' assessment. you use the vocational training you received?" quently cited choices were: percent) and "Some" (24.6 percent). Job Relatedness--Student Self Assessment this item. Respondents were asked "On your present job, how much do The three most fre- “A Lot“ (34.7 percent), and "None" (24.9 Table 9 presents the responses to self- 70 Table 9 -- Student Self-Assessment of Job Relatedness Survey Item and Sample Responses (n=1,336) Job Relatedness Number of Percent (%) Survey Item Respondents of Total A Lot 467 35.0 Some 328 24.6 Hardly Any 154 11.5 None 333 24.9 Not Identified ___;gg __1L51 TOTAL 1,336 100.0 Job Relatedness-~Job Title Matched to Program Title The second measure of job relatedness in this study was the cross-code matching of the instructional program and the respondent job title. Based on the cross-code index. procedure described in Chapter III, three-quarters (75%) of all respondents were identified as having jobs that were not related to their training. The response pattern of this outcome measure is contained on' the right side of Table 10, along with other data. This survey item was recoded, as a dichotomous variable, for direct comparison with the cross-code index job relatedness measure. The recoding involved assigning responses "A Lot" and "Some" as 71 related and "Hardly Any“ and “None“ as unrelated. This same procedure has been used by the NHchigan Department of Education in reporting follow-up results. (See Appendix C). ‘The recoded self-assessment measure is presented on the left side of Table 10. There is a major difference between the two measures of job rela- tedness shown on Table 10. Based on the self-assessment measure, more than 60 percent of all respondents identified their job as being related to their instructional program. For the same sample, only 25 percent of the jobs were related based on the job title-program title measure of relatedness. The significance and association of the rela- tionship between these factors is described in the sections following Table 10. Table 10 -- Comparison of Two Measures of Job Relatedness and Sample Responses (n=1,336) Self-Assessment Job Title - Program Title Related Status Respondents Percent Respondents Percent Related 795 62.0 334 25.0 Not Related 487 38.0 1,002 75.0 TOTAL 1,282* 100.0 1,336 100.0 * Note: 54 respondents did not answer this question 72 Multiple Regression Analysis Multiple regression is a statistical technique through which one can analyze the relationships between a dependent variable and a set of independent variables.1 In this study, a forced multiple regression analysis was performed. In this approach, the independent variables were entered into the regression equation one at a time. The variable that explained the greatest amount of the variance in the dependent variable was entered first, followed by the next most impor- tant independent variable. This provided a listing of the independent variables ranked in order of their predictive value in explaining the variation of the dependent variable. In this study, multiple regression analyses were performed with the student and program characteristics data as the independent variables. Separate regression equations were run with each of the job relatedness measures (self-assessment and job title-program title match) as the dependent variables. Tables 11 and 12 present the data from the regression analyses. lNorman H. Nie, op. cit., p. 321. 73 Table 11 -- Multiple Regression Data for the Student Self-Assessment Measure of Job Relatedness (n=1,009) F to Enter Independent Variable or Remove Significance R Square Cooperative Education 18.8290 .0000* .0188 Sex 11.8606 .001* .0370 Race 4.1852 .041* .0408 Instructional Program .1940 .660 .0410 * significant at the .05 level Table 11 lists the independent variables affecting variation in the self-assessment measure of job relatedness. The independent variables are listed in the order in which they explain or can predict the variance in the self-assessment measure. The second column of Table 11 presents the “F to Enter or Remove.“ The "F“ is a statisti- cal test of relationship, which, in conjunction with the next column (“Significance"), identifies the relationship between the independent variable and the dependent variable. The last column of Table 11 (“R Square”), identifies the percent of the variation explained by all of the independent variables listed to that row on the table. Based on the data in Table 11, cooperative education, sex, and race were all significantly related with self-assessment (at the .05 level). Instructional program was not statistically related. The combined predictive value of the first three independent variables, as 74 presented in the "R Square" column, explained 4.08 percent of the variation in the self-assessment measure of job relatedness. Table 12 -- Multiple Regression Data for the Job Title-Program Title Measure of Job Relatedness (n=1,009) F to Enter Independent Variable or Remove Significance R Square Instructional Program 33.6513 .000* .0318 Cooperative Education 3.0375 .082 .0424 Sex 2.9000 .089 .0430 Race 1.8638 .172 .0432 * significant at the .05 level Table 12 presents the multiple regression data for the job title- program title measure of job relatedness. The independent variables, in the order of their contribution, included: instructional program, c00perative education, sex and race. Only the instructional program was significantly related. 'The instructional program explained 3.18 percent of the variation in the job title-program title measure of job relatedness. As shown by these tables, the sequence of the independent variables, which reflects their contribution to explaining variation in the dependent variable, was different for the two measures of rela- tedness. The student self-assessment of job relatedness was best pre- 75 dicted by cooperative education, followed by sex, race, and instructional program. The sequence of the prediction variables for the job title—program title measure of relatedness was instructional program followed by cooperative education, sex and race. The instructional program was the only significantly related variable (at the p < .05 level) for the job title-program title measure of job relatedness, whereas the other three independent variables were significantly related for the student self-assessment measure . The final column on Tables 11 and 12 is “R Square," which iden- tifies the portion of the variation in the dependent variable (job relatedness) that could be predicted or explained by the independent variables presented up to that row on the table. On Table 11 three independent variables were significantly related to the self- assessment measure of job relatedness. The "R Square“ for these three variables combined indicated that less than 5% (.0408) of the variation in this job relatedness could be explained by them. Table 12 presented the "R Square" for the independent variables to the job title-program title measure of job relatedness. Only one independent variable, instructional program, was significantly related on Table 12. Its "R Square" was .0318--less than 4%. The overall findings of the multiple regression analysis indicated that several of the student and program characteristics were signifi- 76 cantly related to the dependent variables. However, none of these characteristics, individually or in combination, explained as much as 5% of the variation in the job related measures, leaving more than 95% unexplained. Measurement of Independence and Association A contingency table was used to measure the independence or rela- tedness of the two dependent variables. Table 13 presents the number and percent of "related" and "not related" responses for both the self-assessment. measure (left side of 'table) and the job title - program title match measure (top of table). As noted previously, a majority (62%) (H: the self-assessment ratings were related, compared to only 25 percent related for the other measure. For some “cells" in Table 13, the responses are very consistent--for example, of the 487 respondents identified as not related using self assessment all but 19 were also not related based on code matching. Also, of the 321 rated as related (title matching), all but 19 were related (self-assessment). 77 Table 13 -- Number and Percent of Respondents by Job Related Categories as Measured by Student Self-Assessment and Job Title—Program Title Match Job Title - Program Title Match Student Total Self-Assessment Related Not Related Category N % N % N % Related 302 23.6 493 38.5 795 62.0 Not Related 19 1.5 468 36.5 487 38.0 TOTALS 321 25.0 961 75.0 1282 100.0 Chi-Square = 185.13; Significant at the .05 level; Missing Data = 54 The major discrepancy between the two job relatedness measures was found elsewhere on Table 13; specifically, of the 795 related respondents (self-assessment) only 302 were considered related (title matching). Also, more than half (493 of 961) of those coded not related (title matching) were related (self-assessment). The meaning of differing response patterns between these two measures of job relatedness was analyzed in tests measuring statisti- cal independence (chi-square) and association (phi). Independence is described first. 78 Measurement of Independence The chi-square is a test of statistical significance. The signi- ficance of the chi-square statistic is a function of the number of columns and rows in the contingency table. The chi-square test sta- tistic listed at the bottom of Table 13 was significant at the .05 level. This meant that the two measures of job relatedness were not independent, but, rather, were significantly related. A separate chi-square assessment of the independence of the two relatedness measures was conducted for each of the sub-groups (e.g., male, female) within each of the independent variables (e.g., sex). A total (fi’ fifteen contingency tables were produced, each having the same ‘format as “Table 13, but covering only' a selected sub-group. The statistical tests (Hi these contingency tables are presented on Table 14. In this table, the independent variables are listed in the first column, the number of cases are listed in the second column and the chi-square statistic in the third column. There are fifteen sub-groups on Table 14. For the independent variable “race," three of the five sub-groups were too small for ana- lysis. Of the twelve other sub-groups, all but one had a chiesquare statistic that was significant at the .05 level. As noted earlier, the chi-square statistic for the entire sample indicated a significant relationship between the dependent variables. In testing the same relationship for the sub-groups of student and program characteristic, all but one of these sub—groups demonstrated a (significant rela- tionship. 79 Table 14 -- Chi-Square and Phi Statistics for the Two Measures of Job Relatedness by Independent Variables (n=1282) Number of Phi Independent Variable Cases Chi-Square Statistic All Respondents 1,282 185.13* .3819 Student Characteristics Sex Male 610 77.91* .3615 Female 672 100.21* .3897 Race Indian 13 ** *** Asian 5 ** *** Black 62 10.95* .4578 Hispanic 6 ** *** White 1,191 167.14* .3766 Program Characteristics Cooperative Education Participant 404 38.85* .3163 Non-Participant 832 126.60* .3930 Instructional Program Agriculture Production 133 11.88* .3179 General Merchandise 248 18.87* .2854 Nurse Aide 177 70.66* .6437 Food Management 247 75.19* .5602 Steno/Secretarial 168 2.57 *** Auto Mechanics 309 24.90* .2957 * Significant at the .05 level ** Cell size too small to test *** Not applicable, since chi-square was not significant 80 Measurement of Association Having found evidence of relatedness between the dependent variables, a phi statistic test was conducted to assess the strength of that relationship. Phi ranges from 0 (weakest relationship) to 1 (strongest relationship). The fourth column on Table 14 presents the phi statistic for the respondents by related sub-group and total. Overall, phi was .3819 for all respondents. This suggests a moderate level of association between the dependent variables. Looking at the characteristic sub-groups, females evidenced a stronger relationship between the variables than males. Blacks, the only non- white racial sub-group ‘with significant responses, had a stronger relationship between the two variables than did whites. The two job relatedness measures were more strongly associated for respondents who did not participate in cooperative education than for those who did. Assessing the results by instructional program reveals that respondents in Nurse Aide and Food Management programs had very strong association between the two variables while Steno/Secretarial had the lowest association of any large sub-group. Table 15 lists the related sub-groups and total respondents ranked by the strength of their association (size of the phi statistic). Instructional programs had the greatest. range ‘hi the strength of their association, with the two highest and lowest rated sub-groups being from this variable. Blacks, females and cooperative 81 education non-participants were three other sub-groups with above average associations. Table 15 -- Independent Variables (From Table 14) Ranked by the Strength of Association (Size of Phi Statistic) Independent Variable Sub—Group Number Phi Nurse Aide 177 .6437 Food Management 247 .5602 Black 62 .4578 C00perative Education Non-Participants 832 .3930 Female 672 .3897 Total (All Respondents) 1,282 .3819 White 1,191 .3766 Male 610 .3615 Agricultural Production 133 .3179 Cooperative Education Participants 404 .3163 Auto Mechanics 309 .2957 General Merchandise 248 .2854 This chapter has described the frequency of responses by variable, multiple regression analyses, and the independence and asso- ciation between the two measures of job relatedness. Chapter V SUMMARY, CONCLUSIONS, AND RECOMMENDATIONS Historically, vocational education has had a special respon- sibility for the employment of its graduates because these programs purport to impart entry-level job skills. Since the 1976 Educational Amendments, and its increased emphasis on the outcomes of former stu- dents, vocational education had been evaluated on the extent to which its graduates find employment in related occupations. The Problem The problem addressed in this study was to compare two different methods of measuring whether the jobs obtained by vocational graduates were related to their instructional program. One measure of job rela- tedness was graduate self-assessment. The other relatedness measure was based on matching job titles and instructional program titles using a cross-code index. Another aspect of the study was to identify the predictive nature (if any) of selected student and program characteristics on the two measures of job relatedness. Research Procedures The population of this study consisted of a sample of 1,336 program completers who responded to the 1980 Follow-Up Survey from six 82 83 vocational education instructional programs. The Statistical Package for the Social Sciences (SPSS) was used to analyze the sample data. Descriptive statistics were prepared for each of the student and program characteristics (independent variables) and the job related- ness measures (dependent variables). The sample data for all the variables were analyzed in multiple regression equations with student and program characteristics serving as independent variables and the job relatedness measure serving as dependent variables. The variability of the job relatedness measures explained by each of the independent variables was identified. The two measures of job relatedness were tested for independence and association using contingency table analysis and chi-square and phi statistics. Tests for independence and association between the job relatedness measures were made for the entire sample and for fif- teen sub-groups of student and program characteristics. These tests provided information on the nature of the relationship, its signifi- cance and its strength. Findings Description of the Sample The study used a sample of 1,336 program completers who responded to the 1980 Michigan Follow-Up Survey. The sample was limited to respondents who had reported they were employed (full or part-time) 84 and had provided the title of their job. These job titles were assigned occupational codes by Michigan Department of Education staff. The sample was limited to respondents in six large instructional programs. The student, program, and employment characteristics of the survey respondents were as follows: A majority or (52.2%) of the respondents were female. Most (92.7%) (H: the respondents were white. Blacks were the next largest group (4.8 %), followed by American Indians (1.2 %) A majority (64.4%) of the respondents were non-participants in cooperative education programs. The respondents represented six instructional programs. The individual programs ranged from 10.2 percent to 23.8 percent of the sample. The instructional programs (and their relative share of the sample) were as follows: Auto Mechanics (23.8%), General Merchandise (19.5%), Food Management (19.5%), Nurse Aide (13.8%), Steno/Secretarial (13.1%), and Agricultural Production (10.2%) A majority (62.0%) of the respondents reported their jobs were related to their instructional program. This was the self—assessment measure of job relatedness. 85 6. Three-quarters (75.0%) of the respondents were in jobs that were not related to their instructional program based on the job title-program title measure of job relatedness. Research Questions The sample data was analyzed using multiple regression analyses and statistical tests of independence and association. The findings for the study research questions for sample respondents from the 1980 Michigan Follow-Up Survey were as follows: 1. [M3 the student and progrwn characteristics predict variation in the two measures of job relatedness? The instructional program was the only student or program characteristic (independent variable) that was significantly related (at the .05 level) to the job title- program title matching measure of job relatedness. For the other measure of job relatedness (self-assessment), c00perative education participation, respondent sex, and respondent race were all significantly related (at the .05 level). Neither of these groups of significantly related inde- pendent variables explained as much as 5 percent of the variation within either of the two measures of job related- 86 ness. This means that more than 95% of the measures of job relatedness could not be explained or predicted by the stu- dent or program characteristics; thus, they were of very limited predictive value. Are the two uneasures of ,job relatedness independent. or related? If they are not independent, what is the strength of the relationship? For all respondents, the two measures of job related- ness were significantly related (at the .05 level). Sub- groups of student and program characteristics were analyzed. For eleven out of the twelve largest sub-groups, the two measures of job relatedness were significantly related (at the .05 level). A moderate (phi = .3819) measure of association was found for all respondents. This reflects the strength of the relationship described in the preceding paragraph. Student and program sub-groups varied considerablyv with Nurse Aide (.6437), Food Management (.5602) and black respondents (.4578) evidencing much stronger than average measures of association. Sub-groups from General Merchandise (.2854), Auto Mechanics (.2957), Cooperative Education Participants (.3163), and Agricultural Production (.3179) had *weaker 87 than average measures of association between the two measures of job relatedness. Conclusions This study found that the two neasures of job relatedness were significantly related to different student and program charac- teristics. The self-assessment measure was significantly related to cooperative education, sex and race. The job title-program title measure was significantly related to the instructional program. The overall findings of the multiple regression analysis indicated that although several of the student and program characteristics were related to the job relatedness measure, they predicted less than 5% of the variation in the dependent variable, leaving over 95% of the job relatedness unexplained. The two measures of job relatedness did not produce similar ratings for the same group of respondents. Overall, more than sixty percent of the self-assessment respondents indicated that their job was related to their training. The job title-program title matching produced a related result in only twenty-five percent of the cases. The two measures of job relatedness were found not to be indepen- dent, but rather, significantly related. The strength of the asso- ciation between the measures was moderate. When the two measures were compared for sub-groups of student and 88 program characteristics, they were found to be significantly related in eleven of the twelve sub-groups. The strength of the relationship varied between sub-groups, with instructional program sub-groups having the greatest variation. Implications and Concluding Statements The present research has done little to clarify the ambiguous con- cept of job relatedness. The two measures of job relatedness produced widely divergent results from the same sample data. If a related job is equated to program success, the success rate for the study sample was either 62% or 25%, depending on the measure used. The two measures of job relatedness were found, however, not to be independent, but rather significantly related with a moderate strength of association. These measures were significantly related for most of the student and program characteristic sub-groups, but with varying degrees of association. The instructional programs were the charac- teristics with the greatest range in the strength of the association. The program and student characteristics were found to explain little (less than 5%) of the variation in either measure of job rela- tedness. This was true even though each of the three characteristics were significantly related to one relatedness measure (self-assessment) and the fourth characteristic was significantly related to the other measure of relatedness (job title-program title match). 89 The two measures of job relatedness are not simply theoretical approaches--they have been used in administrative reporting and eva- luation. The Michigan Department of Education reported "related" job outcomes based on follow-up respondent self-assessment. The Vocational Education Data System follow-up form (see Figure 5, Chapter III), encouraged the use of job tfitlejprogram title matching. Job title-program title matching were also used by the Michigan Department of Education to establish State “Added Cost" funding priorities. Although related job outcomes represents only one criterion for eva- luation, it is an important one and administrative uses of this factor should be based on a consistent measure. It is recommended that additional research be done on the measure- ment (H: the relationship between vocational education instructional programs and the employment outcomes of former students. Student and program characteristics should be assessed, including a wider range of instructional programs and a larger student sample than covered by this study. This would allow for the identification of variables that better predict successful vocational education outcomes. Recommendations As a result of this study, the following recommendations are made: 1. That further research can be conducted on assessing the relatedness of job outcomes to vocational programming, including the role of student and program characteristics on these outcomes. 90 That the National Institute of Education, the National Center for Research in Vocational Education, and the U.S. Department of Education conduct research studies to opera- tionally define appr0priate measures of job relatedness. That the Michigan Department. of Education operationally define the concept of "related employment" in the State Plan and consistently use this definition for administra- tive purposes. That the Michigan Department of Education add a prominant explanation on the (jobi placement reports describing ‘the source of the relatedness data (student self-assessment). That the Michigan Department of Education Vocational-Technical Education Service conduct a study of available follow-up data to analyze the pattern of job relatedness in the nine years of state follow-up surveys in Michigan. That vocational education research personnel in Michigan, including the Michigan Department of Education staff and university-based investigators, conduct further research on alternate measures of job relatedness and the predictive power of student and program characteristics to explain variation in these job relatedness measures. APPENDIX A 1980 FOLLOW-UP SURVEY OF FORMER STUDENTS (VE-4O 45-A) vs «a In: Michigan Department or Education FOLLOW-UP SURVEY OF FORMER STUDENTS We are writing you, as a former high school student. to ask your help in improving some of the courses you took in school. By answering a few questions about what you are doing now and giving us your opinions, you can help us plan to make the courses better for students in the future. The courses we are writing you about are those that you took in "vocational education" in order to get ready for a job after high school. The courses you took might have been in auto mechanics. office work. marketing and selling, agricultural production, welding and cutting, data processing, child care, small engine repair, electronics, food management, cosmetology, or one of many others possible. ‘ Please take a few minutes to answer the questions and mail back your answers and opinions. We’re counting on your help. Pleueamwerthequstiomhypfltingm'Y'indlebox Thank YOU MY much- next to the m or You CHOICE or by filling in the blast. 1. Are you now attending a school or college, or enrolled in a training program. or working as an apprentice? (Check ONLY ONE.) Yes uE] No ism SCHOOL DISTRICT [ABEL 2. In your major area of study (or training), how “E A lot much do you use the vocational training you a Some received in your high school or area vocational E] Hardly any eduation center? E None (Check ONLY ONE.) 3.0Ieckthetypeofschoolorprogramyouare now attending. (Check ONLY ONE.) High school 1-yeer college wetland-technical program ‘1 39393399 i i a i i 3 92 4. If vou are working for pav. about how manv r“ . HOURS PER WEEK do vou work? Write the "mmmw "am I ' r 80 ‘0 number or hours per week in the box. 1:: ‘g‘m‘fim'm — 1' l— ll you are working for pay. please go to Ques- tion 5 below. -. .9 -o -0- °' 5. On your present job. how much do you use the 29E A lot vocational training you received in your high 9 Some school or area vocational education center? 51 Hfld'Y any (Check ONLY ONE.) E None 6. Overall. how satisfied are you with your present 2' 8 WHY satisfied job? (3 Somewhat satisfied (Check ONLY ONE.) E Not very satisfied E Not at all satisfied 7. On my present job i am paid about a 5 per hour. 8. Pleueiiilinthenameottheconwywhereyouwork Company's Street Address City State Zip Code fine fill in the name of your lob —Pl'ease list the three most important things you do on your you as LEW-E 5mm ' l. )1 2. 3. Will. name at your job superwsor 9. The high school job training that you and other former students received usually gets good ratings when we ask supervisors. We M p a, b may need to ask your supervusor about the M in, training you received in high school. Is that OK with you? Yes a 3 Please fill in your supervisor's work phone number (- cw) 10. ll. 12. 13. 14. Are vou looking tor a 100? «Check ONLY ONE.) Yes 1:27 No _ 22 Are vou in the military servuce? lCheck ONLY ONE.) Yes an: No :3 Are vou a homemaker? (Check ONLY ONE.) Yes 39m No a What is your sex? um Male [3 Female Please identify yourself as a member of one of the groups of people listed below. (Check ONLY ONE.) n E American Indian or Alaskan Native 93 [2] Asian or Pacific Islander w”"". E Black. not of Hispanic Origin {3 Hispanic ‘~ E White. not of Hispanic Origin , _. Pie-e p to Qedoe is. (SCHOOL USE ONLY) 1. Yes at] C am or Log NO a a 2. Yes «[3 No “B 3. Co-op Yes «35] No eE] 4.Yes em H 0E OfLEPeEfl Drona ”0 El 5.Yes em H "a orLEPsim orDsiE No new . oenm.lm 7. Psalm NameoiProgram .lfanAREACENTERor can COG SWDT'M‘pm'M' [1].“? report respondent's m u m identification. 9. Telephone um Mail rem 15. COMMENTS Please make anv comments and/or suggestions vou believe are needed to improve some oi the courses you took or servuces you received while in high school. Also. add any general comments or sugges- tions vou have about vour school experience. 94 PART 5 COMMENTS Pleaaemalteanycomments and/or suggestions you believeareneeded to improvesomeot' thecourses you tookorservices you received while in high school. Also. add any general comments or suggestions you have about your school experience. (SCHOOL USE ONLY) 7 l— ‘l l— —l Information obtained by _l l_ .J 1.A. ,3 E) g 53 telephone. E El E] e 1s m " El El [21 E) E] B. .n E] - E If an AREA CENTER, report cero coo: respondent’shorne C.O.E. Code r_._______ district identification. ELL Li I] NameofProgram '3 1' PSN T-_-__ D. 3 Q 95 THE 1980 VOCATIONAL EDUCAIION FOLLOW-UP SURVEY* Introduction The purpose of the 1980 Follow-Up Survey is to gather information needed to help people make decisions about vocational education programs. Program fiscal agents (local districts) that receive Federal or State funds for conducting programs are required to report follow-up data about program completers and leavers. including information needed for the State to do the followbup with the employers of a sample of former students. In turn, we in the State office are required to report the results of the surveys to the National Center for Education Statistics for inclusion in reports to the 0.8. Department of Education and Congress. The follow-up of completers and leavers of 1980 continues the series of annual surveys begun in 1973. This year, as in all previous years, we have considered recommendations from an Ad Hoc Follow-up Advisory Committee,** professionals in local districts. and technical advisers in making changes in both the survey form and process. This year, we have made four changes in the study: 1. You, as representative of a local program fiscal agency, will need to survey ALL completers and ALL leavers of reimbursed wage-earning programs that your agency reported last July on Form VE-430l, "Secondary Vocational Enrollment and Termination Report for School Year Ending June 30, 1980". (Please remember that you are not required to survey completers and leavers of Consumer and Homemaking programs. those with the OE Code 09.011. You may follow them up as part of the optional non-vocational student survey. 2. We will base your survey response rates on the number of completers and leavers your school reported on Form VE—4301 last July. That means we will calculate the rate. for each Program Serial Number (PSN) on the VE-430l. by dividing the number of your completers and leavers who respond to the survey by the number reported on the VE-430l. 3. You will need to report whether a former student fits one or more of the definitions of handicapped. disadvantaged. or limited English proficiency and, if so, whether the student received reimbursed services as part of an approved state special needs project . * See Appendix A for definition of terms. ** See Appendix I for members of the committee. 96 4. A total of seven questions for the former Students has been removed from the questionnaire. U0 Students will be asked to supply their supervisor's name and phone number on the student follow-up form to aid in completing the employer follow-up. If a student omits this information and the LEA can supply it, please do so. While we have no choice about following up completers and leavers of reimbursed programs. you have the option. as in previous years. of also surveying non-vocational graduates. I22.2§Z.2£2 added cost funds 33 cover 5g; expense 2; surveving £hg_former VOCATIONAL student. In conducting the survey, we recommend that you make administrators, counselors. teachers, placement coordinators, students. and the community aware that: I. You are conducting the survey: and 2. The school and community can benefit from using the results. And, finally, please remember that fiscal agencies. net "home schools," are responsible for actually collecting data from completers and leavers of their programs. That means. in no case, should a school follow-up a former vocational student who was not counted on its Form VE-ABOI. In summary. the data gathered from the followbup survey provides educators at the Federal, State, and Local levels with the information needed to make decisions about students' needs and what schools can do to address those needs. Services 3; Support 3; Your Survey We provide a Survey Support Center during the entire time of the survey to assist you in conducting a successful survey and to handle some of the mechanics for us. During the survey, the Center will: 1. Supply additional needed materials: 2. Answer questions related to the survey: and 3. Offer suggestions for solving problems you may have in conducting your survey. - In addition, we provide a statewide series of workshops in the Fall for local staffs who will actually be conducting the survey and the instructions and suggestions on the following pages. They are: l. A suggested schedule for conducting the survey: 2. A definition of terms (Appendix A): 3. A sample cover letter to mail with questionnaires (Appendix B): A worksheet for coding survey forms and keeping control of the survey as you conduct it (Appendix C): ‘\ -7- b 97 Tentative instructions for selecting a sample of former students whose employers will be followed up, including a tentative form for listing them (Appendix D); improve response (Appendix E); ‘l the first mailing (Appendix F); Some recommendations for publicizing the survey to help to A sample cover letter to mail to those who do nOt respond to 8. An explanation of the information needed in the "school use" part of the questionnaire (Appendix G); 9. A sample of the transmittal sheet used to send the questionnaire and some additional information to the Survey Support Center (Appendix H); and l0. the membership of the Ad Hoc Advisory Committee (Appendix I). Suggested Schedule The chart below depicts the steps you can use in planning and conduct- ing the student and employer follow-up. An explanation of each step appears on succeeding pages. Dates 1980 1981 Roy. Feb. 1 Mar. Apr. 4§51473ept. . I I Attend Inservice 4 - Zl . Program I s ' 3 , l ) Gather mailing and :l --- 27 f ‘ "school use" in- } ' ¢° I formation: ' ' 4°; 3 a“, a 36 “student name ’ “a be 5°“ a" ' --address and/or ' a,» ‘ ~§ ‘° 35" i phone number 05:3 °fiwfii ' «0.2. Code as“ 1“ ‘ ..psx é’oo‘.vfirxpofin1 --Program name Q56 $999 9° 0565 --Graduate ‘00 5° 5, ‘0" ep‘ «Completer or V,o $0" p‘f i i lesver ' c9°ée85 ' -3andicapped. LEP, d‘ ' 5 disadvantaged -Participation in special needs project: if so. handicapped. L2? or disadvantaged ‘x 0 ice ll. 12. 13. 14. ISI Write and dupli- ! cate cover letter: Address envelopes; or get mailing ‘ labels Create coding list Choose potential employer sample - Code question- naires Run P.R. campaign _- _ ..--.‘._._. nail surveys or begin phone calls? Complete returned forms or phoned information Followbup non- respondents by phone or mail Complete informa- tion from those responding to second/third contact (same as step 10) 1 flail forms and employer log i sheets to CEPD ‘ Specialist CEl’D Specialist sends material to Center LEAs receive results 1980 Nov. 98 Feb. 27 27. Dates 1981 Xar. 2 - 13 16 - 26 Apr. 16 ---- 30 3O l -- 30 ......v‘., . flay 15 . ._.‘.__.._.. Sept. 18 ‘.\ ———.——.4...——._. APPENDIX B SOC CODES AND TITLES APPENDIX B SOC CODES AND TITLES Listed below are 39 Standard Occupational Classification (SOC) codes and titles. instructional programs included in this study. presented on Figure 9. The codes and titles are related to the six The SOC codes were Instructional Program SOC Code SOC Title Agricultural Production 1440 Purchasing Agents and Buyers 5512 General Farmers 5611 Supervisors; Farm Workers 5612 General Farm Workers 6720 Garage and Service Station Related Occupations General Merchandise 1240 Purchasing Managers 1390 Officials and Administrators; NEC* 1633 Electrical and Electronic Engineers 4011 Wholesale and Retail Trade Supervisors 4148 Salespersons; Furniture and Home Furnishings 4154 Salespersons; Cosmetics, Toiletries and Allied Products 4159 Salespersons; NEC* 4162 Sales Clerks 4320 Buyers; Wholesale and Retail Trade 4350 Demonstrators, Models, and Sales Promoters 4360 Shoppers 4390 Sales Occupations, NEC* 4642 Interviewing Clerks 4683 Cashiers 4732 Messengers 4749 Material Recordings, Scheduling and Distributing Clerks, NEC* 4783 Investigators and Adjusters, Except Insurance 4786 Collectors 99 1'00 SOC CODES AND TITLES Instructional Program SOC Code SOC Title Nurse Aide 5236 Nursing Aides, Orderlies, and Attendants Food Management 4744 Stock and Inventory Clerks 5021 Supervisors; Food and Beverage Preparation and Service Occupations 5213 Waiters and Waitresses 5214 Cooks, Except Short Order 5215 Short-order Cooks , 5217 Kitchen Workers, Food Preparation 5218 Waiters'lWaitresses' Assistants 5219 Misc. Food and Beverage Preparation Occupations 7272 Bakers Steno/Secretarial 1490 Management Related Occupations, NEC* 4612 Secretaries 4613 Stenographers Auto Mechanics 6711 Automobile Mechanics 6792 Helpers; Vehicle and Mobile Equipment Mechanics and Repairers 7281 Precision Inspectors, Testers, and Graders * NEC--Not Elsewhere Classified APPENDIX C 1980 FOLLOW-UP REPORT "PLACEMENT SUMMARY OF COMPLETERS BY PROGRAM" (X0607) 101 - I. .m. «a lulu .-..wlnminl u .adelua; clwlmunlo. ddflJHIJIIaudnuauuj—ujggll Nnmimlm magnalno. . on: . n... . n .. o. . o . on . : oono.oo . _. . . no.3 . no.3 . no. . no. . no. . no.3 . on... .. no.oo . nnJo . .. $22.3 92.25.33 . ....n-.,m,$..ml..n--|... ...llel -vol-iho - .. n . n . o . o. . 1 .. 83.... m o. z a." ..m mouth nommm m-nlo...llulno. u no. u ImolI. . no.8? no.on . «to. . 5.5.2.3 ooou no ,. oo.o . nu.“ . o . n .o n..— . . «all! . o .- :. 5| -m no.3 finnquw «no? u no. ll. 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