TH ESTS This is to certify that the dissertation entitled A STUDY OF THE RELATIONSHIPS BETWEEN PERCEIVED BENEFITS FROM GRADUATION PROGRAMS AND GRADUATION PROGRAM COSTS presented by MICHAEL KING MARSHALL has been accepted towards fulfillment of the requirements for PH.D. degree in ADMINISTRATION 8 CURRICULUM Lough Major professor Date MSU is an Affirmative Action/Equal Opportunity Institution 0- 12771 Min...“ ' MN»... . 9‘2“: — (g, ' ’9" . fat .. i 21’ $7 "' t a») j 1 gig??? 59¢. "' 1 ._, I ° 43;. 15,". I i 5'. ' on 44.. . e m z 4., ., "35' yr {5 ..‘ "a w . , {it-u... 913 E ,. ., ‘V‘ _r: V . . -. I Lt?) - . “”“J’ . I , v.» ' v “#341.“ . )V1ESI_] RETURNING MATERIAL§2 Place in book drop to LJBRARJES remove this checkout from Ann-rm your record. FINES will be charged if book is returned after the date stamped below. E: ”a: g I r. p f I?“ :54" 1° . 3 r .1 J i j I upon use dist? A STUDY OF THE RELATIONSHIPS BETWEEN PERCEIVED BENEFITS FROM GRADUATION PROGRAMS AND GRADUATION PROGRAM COSTS BY Michael King Marshall A THESIS Submitted to Michigan State University in partial fulfillment of the requirements for the degree of DOCTOR OF PHILOSOPHY COLLEGE OF EDUCATION 1983 ABSTRACT A STUDY OF THE RELATIONSHIPS BETWEEN PERCEIVED BENEFITS FROM GRADUATION PROGRAMS AND GRADUATION PROGRAM COSTS BY Michael King Marshall This study was designed to test the relationships be- tween high school graduation program benefits and their production costs. The approach is from a "product" per- spective and relies on techniques drawn from Systems Ana- lysis, Marketing Research, Economics, and Finance. Schools are considered to be similar in many respects to factories and service-producing enterprises that are also comprised of workers, buildings, equipment and materials. The study assumed a multi-faceted educational product composed of further education benefits, job benefits, and personal benefits. Production costs were determined by using cost accounting methods. Sixty graduates from the 1979 graduating classes at each of seven Okanagan high schools were randomly selected as a survey sample to determine their perceived benefits from each course completed during their senior high school years. Three hundred and thirty-one usable responses were then costed on a course-by-course basis according to the Michael King Marshall categories of instructional personnel costs, materials costs, and overhead costs. Benefits and costs for each course and graduate were then aggregated. The four major hypotheses developed and tested were: I. Total Educational Benefits are positively related to senior high school program costs. II. Total Further Education Benefits are positively related to senior high school program costs. III. Total Job Benefits are positively related to senior high school program costs. IV. Total Personal Benefits are positively related to senior high school program costs. Tests of significance using Correlation Analysis and Analysis of Variance techniques showed that the educational product is composed of differing educational benefits and these are related in positive ways to production costs and specific cost categories. The study also established that different groups of consumers have varying cost-benefit relationships. The disaggregation approach employed in this study made it possible to link some of the educational benefit components to specific educational costs. ACKNOWLEDGEMENTS The writer would like to recognize several individuals who have contributed to this study. Most importantly, as chairman of the writer's doctoral committee, Dr. Herbert C. Rudman has been a consistent source of inspiration and important information. His support was generously provided at every stage of the study and was critical to the com- pletion of the project. Special acknowledgement must also be given to the other members of the writer's doctoral guidance committee whose suggestions and comments helped to improve the study: Dr. Cole Brembeck, Dr. Philip Cusick, and Dr. Stan Hecker have each added in important ways to the study. The writer acknowledges with thamqsthe support and encouragement given by Mr. Murli Pendharkar, superintendent of schools in the Central Okanagan School District. His cooperation and that of his staff including central office personnel, principals, and teachers was essential to the study. Special acknowledgement is also given to the College of Education staff associated with the University of British Columbia's Computing Center. Their technical advice con- cerning data processing and programming was also essential at various stages of the study. This study is dedicated to my wife Anne and children, Melanie, Tony, and David, without whose patience and under- standing this study could not have been undertaken and completed. ii CHAPTER I. II. III. IV. TABLE OF CONTENTS THE PROBLEM ......OOOOOOOOOOOOO Need ......I..... OOOOOOOOOOOO Purpose ................................ Hypotheses ............................. Theory ................................. Historical Measures of Educational Output ............................... Benefits as a Measure of Educational Output ............................... Measuring the Educational Product ...... Educational Cost ....................... Overview ............................... RELATED LITERATURE ...... ...... Product Identification ...... Product Measurement .................... PrOduct costing ......OOOOOOOOOOOOOOOOO. Cost-Benefit Analysis ....... smary ......OOOOOOOOOOOOOOO DESIGN OF THE STUDY ... ..... ... Sample ... ......... .... ...... Measures .................... Design ...................... Hypotheses .................. Analysis .................... Summary ..................... ANALYSIS OF RESULTS .. ....... .. Total Benefits and Costs .... Total costs 0.0.0..........OOOOOOOOOOOOO Total Instructional Personnel Costs .... Materials Costs and Overhead Costs ..... Further Education Benefits .. Total costs ......OOOOOOOIOOO Instructional Personnel Costs iii “3de ll 14 17 20 24 26 26 33 38 43 46 50 50 53 59 61 63 65 68 68 7O 73 76 79 80 84 TABLE OF CONTENTS--C0ntinued CHAPTER Page Materials Costs and Overhead Costs ....... 86 Job Benefits ............................. 88 Total Costs .............................. 88 Instructional Personnel Costs ............ 91 Materials Costs .......................... 92 Overhead Costs ........................... 93 Personal Benefits ........................ 93 Total Costs .............................. 94 Instructional Personnel Costs ............ 97 Materials Costs .......................... 99 Overhead Costs ........................... 100 Summary .................................. 101 V.. SUMMARY AND CONCLUSIONS ........... ......... 112 Summary .................................. 112 Conclusions .............................. 115 Total Education Benefits ................. 115 Further Education Benefits ............... 116 Job Benefits ............................. 116 Personal Benefits ........................ 117 Discussion ............................... 118 Implications for Future Research ......... 120 BIBLIOGRAPHY ......0.0.........0...............000 123 APPENDICES 0 ....... 0.....0........0...0...0.. ..... 130 iv LIST OF TABLES TABLE Page 3.1 Summary of 1979 Senior Grade Enrolments and Timetable Organization in School District #23 .000...00.0000.0000000.0.00.000000.000... 51 3.2 Summary of School Response Rate to the Graduate Benefit Survey ..................... 52 4.1 Means for Total Benefits and Total Costs .... 69 4.2 Summary of Relationships--Total Benefits and Total costs 0000.00.00.00.....0000000000.0... 72 4.3 Means for Total Benefits and Total Instruc- tional Personnel Costs ...................... 73 4.4 Summary of Relationships--Tota1 Benefits and Total Instructional Personnel Costs ..... 76 4.5 Means for Total Materials and Overhead Costs 78 4.6 Summary of Relationships--Total Benefits and the Variables Materails Costs and Overhead costs 0....00.0.0000.0...000......0000000000. 80 4.7 Means for Further Education Benefits and Total costs ......000........0...0000...0..00 82 4.8 Summary of Relationships--Further Education Benefits and Total Costs .................... 85 4.9 Summary of Relationships--Further Education Benefits and Instructional Personnel Costs .. 87 4.10 Means for Job Benefits and Total Costs ...... 89 4.11 Summary of Relationships--Job Benefits and Total Costs ................................. 91 4.12 Means for Personal Benefits and Total Costs . 95 4.13 Summary of Relationships—~Persona1 Benefits and Total Costs ............................. 97 LIST OF TABLES--Continued TABLE Page 4.14 Summary of Relationships--Persona1 Bene- fits and Instructional Personnel Costs .... 99 4.15 Summary of Component Benefits and Costs ... 104 4.16 Summary of Hypothesis 1 Tests ............. 106 4.17 Summary of Hypothesis 2 Tests ..... ........ 106 4.18 Summary of Hypothesis 3 Tests ...... . ...... 107 4.19 Summary of Hypothesis 4 Tests ..... ........ 107 4.20 General Summary of Hypotheses' Tests . ..... 109 4.21 Detailed Summary of Hypotheses' Tests ..... 110 vi LIST OF FIGURES FIGURE Page 1.1 Input-Output Model ........................ 10 1.2 Educational Cost-Benefit Model ............ 11 1.3 Educational Cost-Benefits Components Model 23 3.1 Location of School District #23 ........... 50 3.2 Graduation Program Components ............. 60 3.3 Graduate Subgroups Tested for Cost-Benefit Relationships ............................. 61 4.1 Summary of Total Benefits ................. 102 4.2 Summary of Total Costs .. ..... ...... ....... 103 vii LIST OF APPENDICES APPENDIX Page A Letter of Authorization Sent to Schools . 131 B First Survey Letter Sent to Graduates ... 133 C Reminder Note Sent to Graduates ......... 135 D Second Survey Letter Sent to Graduates .. 137 E Sample Completed Survey Form ............ 139 F Sample Data Recording Sheet ............. 141 G High School Course Codes ................ 143 H Course Cost Calculations ................ 145 I Sample Teacher Salary Worksheet for Courses at Kelowna Secondary School ..... 148 J School Support Costs Per Student ........ 150 K Textbook Catalogue Used for Pricing Texts 0000000..0..000.00.000.000000000000 152 L Text Costs for Prescribed and Authorized Courses Depreciated Over Four Years ...... 154 M Memo to School District Staff Outlining Non Instructional Cost Needs ............ 156 N Calculation of School Administration and counselling costs 0.000000000000000000000 159 0 Calculation of School Equipment Costs ... 162 P School Assessments 1979 and 1980 ........ 164 Q Custodial Costs and Facility Deprecia- tion for Subject Areas in Each School ... 166 viii LIST OF APPENDICES--Continued APPENDIX R Custodial Times and Spaces For All Schools in the Central Okanagan School District 00.0000000000000000...000000.00. Energy Sample Sample Sample Expenditures for Schools .00.0.000 Fortran Coding Sheet ............. School Cost Data Recording Sheet . Course Costs for Schools Page 168 170 172 174 176 CHAPTER I THE PROBLEM Need David Churchman in a paper presented to the American Educational Research Association made the statement that "educators object to thinking of people as 'products,‘ preferring to speak in terms of the 'full potential of the individual.”1 Today, as education searches for better and less costly ways to deliver its product, there is an increasing need to develop a more specific understanding of that product and the costs incurred in its production. Any implied dangers of dehumanizing education, while in- herent to some extent in adopting a product orientation, are probably outweighed by not utilizing available tech- niques to better understand education as a product. The school system with all of its complexities as a socio— technical system,2 is as Johns and Morphet point out similar lDavid Churchman, A Cost-Benefit Methodology for Sum- mative Evaluation, paper presented at the Annual Meeting of the American Educational Research Association (64th, Boston, April 7-11, 1980): P. 1. 2E.L. Trist, "On Socio-Technical Systems" in Warren G. Bennis et a1., The Planning of Change—-2nd Edition (New York: Holt, Rinehart, and Winston, 1969), PP. 268-82. 1 in many respects to a factory.3 According to them, the school system may be usefully conceptualized as a "processor" con- sisting of workers, buildings, equipment, and materials, with inputs of money and raw material in the form of students, and with output in the form of human capital that has been developed and improved by the educational services provided by the processor. It is important to consider that education is by definition4 both a product as well as a process. This con- ceptual distinction is not commonly made by most educators who as a result of their training and experience tend to be preoccupied with the process of developing the full pot- ential of each child. These are the same individuals who would be most inclined to totally reject any comparison of a school to a factory, even if such a comparison might bene- fit their clients. Some business techniques and perspec- tives can be applied to help identify and accommodate the very product needs that are served by so many process-cen- tered educators. In addition, an education product focus brings with it an implied cost dimension at a time when edu- cational costs are extremely high. During the past twenty years there have been develop- ments in several disciplines including Systems Analysis, 3Roe L. Johns and Edgar L. Morphet, The Economics and Financing of Education Third Edition (Englewood Cliffs: Prentice-Hall, 1975), p. 41. 4Henry Bosley Woolf, Ed. Webster's New Collegiate Dictionary (Springfield, Mass: G & C Merriam Co., 1976), p. 361. Marketing Research, Economics, and Finance that should have contributed to the understanding of educational products. An understanding of the potential benefits that come from viewing education as another service-producing industry would have necessitated a greater dependence on the knowledge accumulated in these related fields, and probably would have been accompanied by product improvements in educational services. The accountability movement that began in the late sixties with its focus on standards of achievement, educational outcomes, and financial responsibility has now created a situation where as Sciara and Jantz point out, "education must begin to borrow from the 'factory' model whether it wants to or not."5 Whatever else, the educational product is at the very least under close public and professional scrutiny. Thomp- son, addressing the Association for Institutional Research, states that educational institutions can no longer afford to ignore public concerns about what is taught, how much is learned, and who is enrolled.6 He advocates that quality must be defined in terms of the benefits and costs as per- ceived by consumers of educational products. Leon Lessinger 5Frank J. Sciara and Richard K. Jantz, Accountability in American Education (Boston: Allyn and Bacon, 1972), p. 3. 6Fred Thompson, "The Cost and Value of Marketing Analy- sis," Paper presented at the 18th Annual Association for Institutional Research Forum (Houston, May 21-25, 1978), p. l. uses the term Caveat Emptor to describe what he believes as the best attitude in a situation where the producer's interest has been confused with the user's needs.7 Education it seems, unlike industry, does not have to do what survival demands, Or at least it has not had to be nearly so competitive in the past, both in terms of funding as well as public support, for its secure monopoly position in the education market. It has never really had to adapt its product to the rigorous requirements of free competition.8 Service industries such as airlines, television networks, restaurants, and hotel chains just to mention a few, conduct extensive research on the services they produce. They recognize the value of product feedback in remaining compet- itive by adjusting their services to better fit the needs of their marketplace. Ultimately it is the consumer of a meal, television show, or film who will determine and internalize the value of that particular product relative to its cost. Most educators and school boards could generally agree that high school programs are to a large extent designed, developed, and offered to facilitate students' preparation for activities beyond graduation. This product of education 7Leon M. Lessinger, "Quality Control and Quality Assur- ance in Education," Journal of Education Finance (Spring, 1976), p. 514. 8Theodore Levitt, "Marketing Myopia" in Modern Market- ing Strategy (Cambridge: Harvard University Press, 1964), p. 48. could be perceived as investment in human capital.9 Benson differentiates this product from education as a consumption commodity where students consume education for enjoyment only. Education costs, according to Benson, can only be justified for investment products and not for the rather immediate consumption products. Education is a service industry having much in common with other service producing enterprises such as museums, theatres, private clubs, and amusement parks. While these may tend to focus on a consumption product rather than investment, they are similar to education in that they produce a service for a cost. However, unlike education they must be preoccupied with an emphasis on their product. In competitive industry the prime focus is on a market need and the product is designed to satisfy potential consumers. Only after the need-oriented product has been identified, are the means or processes of production determined, always with an essential consideration of production costs. Simply put, the product dictates the process. Education on the other hand has traditionally not focused on its product. Rather, it has grown naturally as an important social institution, remaining basically un- changed over the years as new programs and new materials have 9Charles B. Benson, Education Finance in the Coming Decade (Bloomington: Phi Delta Kappa, 1975), pp. 5-8. come and gone.10 The history of American public schooling does not give rise to confidence that the schools will change their processes quickly and adopt a new focus in educating masses of young people. Writing on the evolution of organizations, Kotler and Levy state that many organiza- tions in the course of evolving, lose sight of their original mandate, grow hard, and become self-serving.11 In American schools, the process dictates the product. If the public school system and more specifically the high school system is perceived as an educational producer for society, then several questions central to this study require answering. First of all, what is the educational product? What are those affective, skill, or cognitive learnings that can be related to an educational product?12 Once identified, how do these learnings as part of a product become measurable? And once it is possible to identify and quantify the educational product in whole or part, how does the product relate to specific costs of production? These are some of the obvious and substantive questions that are 10Robert G. Owens and Carl R. Steinhoff, Administering Change in Schools (Englewood Cliffs: Prentice-Hall, 1976), p. 2. 11P. Kotler and S.J. Levy, "Broadening the Concept of Marketing," Journal of Marketing, (January, 1969), p. 10. 12W. Georgiades, How Good Is Your School? (Reston: NAASP, 1978), p. vi. appropriate to ask in a product-oriented business of education. As an important service institution now under pressure, schools should begin an intensive examination of their product relative to its production costs. The underlying fabric for such an analysis can be based on product defini- tion in terms of specified output criteria, a means of pro- duct assessment or measurement, and production costing using a cost accounting approach. These elements, while commonly applied in goods' manufacturing and some service industries, have only seen limited use in education. It is hoped that this study will contribute substantially to understanding the educational product as it relates to its production costs. Purpose Education in North America is a giant service industry catering to the needs of society, individuals, and its own bureaucratic structure. In often little-understood ways, high schools graduate ill-defined products amidst increasing public outcry and increasing costs. This study centers on the product and cost dimensions of high school education. The main purpose is to study the relationships between those benefits that constitute the educational product and their production costs as determined using cost accounting methods. For the purpose of this study high school graduates are examined as members of subgroups according to their graduation program, post-high school activity, or the number of courses included in their program. This subgrouping has been included in an attempt to link specific cost relationships within each subgroup; relationships that would be averaged out and hidden within the sample as a whole. By adopting this product approach and using appropriate methodologies13 for identifying bene- fits and costs, this study is intended to test the relation- ships between program benefits and their production costs. Hypotheses The central hypothesis being tested in this study is that educational benefits are positively related to their production costs. The significance of the relationships will be tested within a range of p < .05 to p < .001 de- pending on the specific sub-hypothesis. Because Total Educational Benefits as a dependent measure is determined by summing benefits in the categories of Further Education, Job, and Personal Benefits, the central hypothesis stated above is broken into four research hypotheses: 13Greg Kearsley and Terry Compton, "Assessing Costs, Benefits, and Productivity in Training Systems," Training and Development Journal (January, 1981), p. 52. 1. Total Educational Benefits are positively related to senior high school program costs. 2. Total Further Education Benefits are positively related to senior high school program costs. 3. Total Job Benefits are positively related to senior high school program costs. 4. Total Personal Benefits are positively related to senior high school program costs. These hypotheses are tested within the overall sample and three major sub-groupings. Each graduate is classified according to the specific graduation program chosen, post- high school activity, and the number of electives chosen for graduation. Through an analysis of overall and sub- group results, it is hoped that distinct product-related benefits can be linked to production costs. Theory The fundamental question of identifying critical relationships and links between educational products and their production costs will be researched using-an input- process-output concept and model. This systems approach is advocated by Dyer,l4 Banghart and Trull,15 and Johns 14Henry S. Dyer, "Toward Objective Criteria of Pro- fessional Accountability in the Schools of New York City" in G.D. Borich and K.S. Fenton, The Appraisal of Teaching: Concepts and Process (Reading: Addison-wesley Publishing, 1977), p. 241. 10 16 As illustrated in Figure 1.1, it allows a and Morphet. clear distinction to be made between the more easily measurable input-output dimensions and the considerably more complex production processes. k % INPUTS ——4{ PROCESS ——_—..[OUTPUTS ] Figure 1.1 Input-Output Model Tanner suggests that the systems approach particularly lends itself to analysis of complex systems. Even the most complicated school system can be viewed as consisting of a conversion process by which certain inputs are transposed 17 or converted into outputs. As shown in Figure 1.2, this 15F.W. Banghart and A. Trull, Educational Planning (New York: Macmillan Company, 1973), pp. 112-3. 16Roe L. Johns and Edgar L. Morphet, The Economics and Financing of Education—-Third Edition (Englewood Cliffs: Prentice-Hall, 1975), p. 41. l7C.K. Tanner, Designs for Educational Planning, (Lexington: Health Lexington Books, 1971), p. 3. 11 study will test those relationships between educational costs as input and educational benefits as output. The processes whereby these inputs are transposed into outputs are totally disregarded for the purposes of this study. % EDUCATIONAL PROCESS EDUCATIONAL COSTS ‘ 'H BENEFITS Figure 1.2 Educational Cost-Benefit Model By only focusing on the input and output dimensions of this model, it is possible to test the theory that educational products are positively related to their production costs. As cost inputs for a Mercedes-Benz, a Metropolitan Opera production, or a gourmet meal for example would be reason- able predictors of the product, this study will search for similar cost predictors that bear on the educational product. Historical Measures of Educational Output The traditional measure of educational output has been achievement. According to Holtzman and Brown, it has been customarily defined operationally by citing a stan- dardized test of achievement, by grade—point averages, or 12 by teacher judgement.18 As a measure of short-term progress for a particular course or as a cumulative grade-point score for an educational program, achievement is undergoing an increasing amount of scrutiny. This disenchantment is reflected in a paper by Guba where he put forward the case that traditional achievement scores have failed educators and these should be replaced by a new means of assessment.19 At the classroom level Tanner argues that there is a vast gap between what a student learns in a given course and what the instructor thought he learned as measured by an achievement test.20 He views these commonly used achievement measures as having limited use for classroom teachers and guidance counsellors, but condemns their usage as long- range program effectiveness measures.21 In spite of the opposition lodged against the use of achievement grades or scores, they continue to be widely applied in situations ranging from the classroom to the international testing arena. Narrow and wide generalizations are made on these 18W. Holtzman and W. Brown, "Evaluating the Study Habits and Attitudes of High School Students," Journal of Educa- tional Psychology, LIX (1968), pp. 404-409. 19Egon G. Guba, The Failure of Educational Evaluation," in The Educational Technology Review Series #ll--Evaluation of Education (Englewood Cliffs: EducaEional Technology Publications, 1973), PP. 1-2. 20Tanner, op. cit., pp. 68-69. 21Ibid., p. 64. 13 scores. Writers such as Cassidy continue to draw conclu- sions regarding the performance of American students re- lative to their counterparts from previous decades and in other countries based on achievement scores.22 More recently, in response to growing concerns for "quality" and effectiveness, researchers are seeking to provide better ways of measuring educational outputs and outcomes. The first benefit analysis is traced back to an 1844 publication that dealt with the utility of public 23 Early education economists viewed benefits purely works. in monetary terms and their studies sought to link wage or salary income to the level of education attained. During the 1970's, educational benefits were increasingly con- sidered in a broader context. Carpenter and Rapp argue that any assessment of benefit should consider all major benefits including those that are not grossly quantifiable, such as enjoyment and appreciation that an education can bring to everyday life.24 This new dimension to educational benefits 22Jack Cassidy, "Forum: Is Anyone Out There Learning? Some Positive Ammunition," Teacher (August, 1980), p. 23. 23Scarvia B. Anderson and Samuel Bell, The Profession and Practice of Prggram Evaluation (San Francisco: Jossey- Bass Publishers, 1978), p. 25. 24Margaret E. Carpenter and Marjorie L. Rapp, "The Analysis of Effectiveness" in Sue A. Haggart, Ed., Program Budgeting for School District Planning (Englewood Cliffs: Educational Technology Publications, 1972), P. 151. l4 paralleled a general recognition that schools were now serving a range of concerns beyond the narrow academic goals once attributed to the institution.25 Curricula now reflect liberal education objectives focusing on the development of a whole person who understands and can function well in the world.26 27 All initiatives at measuring the "hard-to- measure" are drawn together in Ruth's proposed taxonomy of educational benefits.28 He categorizes several kinds of beneficiaries, in addition to distinguishing between various types and forms of benefit. Ruth's work and taxonomy in particular cast an enlightening perspective on the concept of an educational product. Benefits as a Measure of Educational Output Educational benefits are defined as "anything that promotes or enhances well-being of a group or individual and that is produced by an educational delivery system."29 25Marten Shipman, In School Evaluation (London: Heinemann Educational Books, 1979), p. 101. 26Iris Varner and Carson H. Varner, "Liberal Education and Marketability," Journal of Educational Thought (Dec- eluber’ 1980) I p. 220. 27Edward H. Loveland, Ed., "The Student, Evaluative Data, and Secondary Analysis," New Directions for Program Evaluation, 1980, p. vii. 28Lester R. Ruth, Jr., “A Proposed Taxonomy of Educa- tional Benefits," A paper presented to the Ninth Annual Conference Southeastern Association of Community College Researchers, San Antonio, Texas, July 23, 1980, pp. 12-13. 29 Ibid., p. 12. 15 This study is concerned with only one of three recipient categories, namely, the private consumer or school graduate. The two that are not part of this study are the general public and the educational system itself. Ruth's conceptual approach to educational benefits as multifaceted outcomes for the graduate recipient, with "products" identified in several categories, has the pot— ential to resolve many of the present difficulties encoun- tered in defining and measuring educational output. While the graduate can be considered as a unit of "human capital" by education economists, it may be shown to be more approp- riate for them to consider the graduate as a composite of many quite different "products." One of the keys to enhancing the understanding of educational productivity may be found in what economists and logicians refer to as the 30 Parts of the overall educational Fallacy of Composition. product may simply not equal a total product. Through a more disaggregated consideration of the educational product, with a specific focus on further education benefits, job benefits, and personal benefits, education can, according to Anderson and Bell, be promised something beyond the fairly simple economic functions and 30Paul A. Samuelson and Anthony Scott, Economics-- Fourth Canadian Edition (Toronto: McGraw-Hill Ryerson, 1975), p. 12. 16 relationships evaluators have tried to use in the past.31 Historically, education has been viewed as a single entity or product, when thought of as a product at all. Van Gigch and Hill recognize a more complex educational product; one that they believe would be difficult if not 32 impossible to define. Alluding to the complexity of the educational product, Benson makes the further point that the complete nature may not be revealed for many years.33 While still at a formative stage, the view of education as a complex, multi-dimensional product is becoming more prevalent and accepted than the traditionally narrow view of education as "human capital." Perceived benefits from education programs, analyzed in different categories such as further education or job benefits, could help to resolve some of the difficulties associated with defining and measuring educational output. Traditionally, earnings have been used by economists and educators as one of the most common measures of educational 31Scarvia B. Anderson and Samuel Bell, The Profession and Practice of Prggram Evaluation (San Francisco: Jossey- Bass Publishers, 1978), p. 24. 32J.P. Van Gigch and R.E. Hill, Using Systems Analysis to Implement Cost Effectiveness and Program Budgeting in Education (Englewood Cliffs: Educational Technology Publications, 1971), p. 41. 33Benson, op. cit., p. 55. 17 benefit. An example of this is Paul Taubman's study of educational benefits in terms of higher earnings and greater longevity.34 In a similar way, David Churchman addresses the difficulty of translating educational benefits into 35 Some educational benefits purely financial variables. may not easily lend themselves to conversion into monetary terms. Wick and Beggs see this stress on multiple output measures as being critical to an improved understanding of theeproduct and better decision-making as it affects the production function.36 Measuring the Educational Product A basic problem in evaluating the educational product has been the inexactitude of educational measurement.37 This has been further complicated when educators have tried to measure the product as a composite entity, rather than viewing the product in terms of several quite dissimilar components. Morris and Fitz-Gibbon argue that each program 34Paul Taubman, "Measuring Educational Benefits," A Paper presented at the Annual Meeting of the American Educational Research Association (San Francisco: April 8- 12, 1979), p. 22. 35Churchman, Op. cit., p. 2. 36John W. Wick and Donald L. Beggs, Evaluation For Decision—Making_in the Schools (Boston: Houghton-Mifflin, 1971), p. 15. 37Walter I. Garms et a1., School Finance (Englewood Cliffs: Prentice-Hall, 1978), p. 255. 18 being evaluated should be supported by evidence that the measure used is sensitive to the program's objectives.38 In a similar way, when considering several categories of educational benefit, the measures applied should be sensitive to the type of benefit. Carpenter and Rapp make the point that any assessment of program benefits should take into account all major benefits even if some are not grossly quantifiable.39 When all benefits are to be examined, Sturges40 concurs with a marketing approach and presents a case for having students, as "consumers," judge the quality of their education. He belives that they are the best source of information. Their perceptions of educa- tional benefits and relative ratings of each could constitute according to Tanner both a measure of program effectiveness as well as a valid output measure.41 He further holds that student judgement, coupled with achieved behavioral objec- tives, is a progressive step toward future assessment, and 38Lynn Lyons Morris and Carol Taylor Fitz-Gibbon, How to Measure Achievement (Beverly Hills: Sage Publications, 1978), p. 8. 39B. Carpenter and Marjorie L. Rapp, "The Analysis of Effectiveness" in Sue A. Haggart, Ed., Program Budgeting For School District Planning (Englewood Cliffs: Educational Technology Publications, 1972), p. 151. 40Jack Sturges, "How to Make the Most Out of Course Evaluation Forms," Paper presented at the Educational Inno- vations Exchange, Council on Social Work Education Annual Program Meeting (New Orleans, 1978), p. 3. 41Tanner, op. cit., pp. 68-69. 19 is more valuable than traditional measures of student achievement.42 His position is supported by Wick and Beggs who believe that the approach of surveying attitudes toward programs and converting this into hard output data offers 43 a means of identifying strong or weak programs. If the local decision-makers wish to develop an accountability management system,44 feedback from graduates can be obtained using the follow-up study. Herman points out that this opinion can prove to be both useful and easy to Obtain. There is evidence of continued growing interest in the use of follow-up studies for testing the adequacy of institu—- tional programs and practices.45 This study will make use of graduate opinion obtained through a follow-up instrument to measure the degree of benefits obtained from high school courses. 42Tanner, op. cit., p. 64. 43Wick and Beggs, op. cit., p. 15. 44Jerry J. Herman, School Administrator's Accountability Handbook (West Nyack, New York: Parker Publishing, 1979), p. 43. 45Using Student Follow-Up Surveys to Improve College Programs--A Staff Repgrt (Atlanta: Southern Regional Education Board, 1980), p. iii. 20 Educational Cost Having laid the theoretical framewOrk for determining educational benefits through the use of follow-up studies, there remains the area of educational costing that must be addressed. Costing in education is viewed as an extremely difficult business requiring technical skills that have not been a part of the traditional training of educational 46 evaluators. This point is emphasized by Borich who claims there are plenty of CPA'S who are quite incompetent at estimation of costs of educational products of a rather non-standard kind.47 Most of the difficulty arises from the aggregation of cost data, which according to several writers on this subject, render the cost information all 48,49 but useless for program analysis. Some new formats have been suggested that would display functional detail 50 by individual schools and facilitate accounting by areas 46W.I. Garms, et a1., op. cit., p. 248. 47G.D. Borich, Ed., Evaluating Educational Programs and Products (Englewood Cliffs: Educational Technology Publications, 1974), p. 13. 48R.A. Rossmiller and T.G. Geske, "Toward More Effec- tive Use of School Resources," Journal of Education Finance (Spring, 1976), PP. 494-495. 49Stephen J. Knezevich, Program Budgeting (Berkeley: McCutchan Publishing, 1973), p. 167. 50James W. Guthrie, School Site Budgeting Report to Oakland Public Schools (Oakland: Master Plan Citizen's Committee, 1973). 21 and activities.51 Simply stated, what education costing needs is more of a cost accounting approach. Cost accounting is the process of determining, report- ing, and interpreting the cost of manufactured products, or of rendering services, or of performing any funCtion or operation in an enterprise.52 Costing within this frame- work is extended to a point where the cost of labour, materials, and other expenses is determined for each unit and each type of product manufactured and for each type of service rendered. Education has almost universally used a general or financial accounting approach to summarize those operations and transactions involving public school funds. General accounting tends to emphasize over-all or aggregate figures; its limitation is that the financial and Operating statements presented to school boards and senior district administrators tend to be highly summarized and condensed. These statements are periodic and therefore relatively infrequent. They are statements rendered at regular intervals, but nevertheless they present data "after the fact." On the other hand, cost accounting can provide detailed and specific information to aid education decision-makers 51J.E. Mitchell et a1., MSEIP Documentation of Prpject Development and General Systems Design, Midwestern States Educational Information Project, (Des Moines: State of Iowa Department of Public Instruction, 1969). 52Robert H. Van Voorhis et a1., Using Accounting in Business (Belmont, CA: Wadsworth Publishing, 1962), p. 160. 22 in determining whether certain curricula or programs are too costly or less efficient than they should be. The goal Of cost accounting is to help management to operate its enterprise as efficiently as possible.53 In this study, cost is considered from a cost account- ing perspective. Where most manufacturing companies con- vert certain basic materials through the use of labour and the utilization of overhead costs into finished products, education is to a large extent more labour intensive. As such, the typical "cost elements" of materials, labour, and overhead can be appropriately designated as instructional materials, personnel, and overhead. No one cost system can be used without variation by all types and sizes of enter- prises, and there is likewise no universal method of classifying costs for all purposes.54 The cost information required by managers of an airline company, a golf and country club, a car assembly plant, and a school district could be well-accommodated by a cost accounting format. This chapter section began with a generic model de- picting educational inputs, processes, and outputs. Through adopting cost accounting methods, it is possible to classify educational costs as those that relate to 53Robert H. Van VOorhis et a1. Using Accounting in Business (Belmont, CA: Wadsworth Publishing, 1962), p. 162. 54Ibid., p. 166. 23 instructional personnel, instructional materials, or instructional overhead. These costs can then be studied to determine relationships with specific educational out- puts defined for purposes of this study as further education benefits, job benefits, and personal benefits. The under- lying theory being tested in this study is that for certain educational products such as academic or vocational gradua- tion from high school, different output benefits will be positively related to and effected by expenditures in specific cost categories. This can be illustrated by expanding the Educational Cost-Benefit Model to include the specific variables that are central to this study. This more detailed model is shown in Figure 1.3 INSTRUCTIONAL FURTHER EDUCA- PERSONNEL COSTS TION BENEFITS INSTRUCTIONAL JOB BENEFITS MATERIALS COSTS PROCESS INSTRUCTIONAL ~ PERSONAL OVERHEAD COSTS BENEFITS TOTAL INSTRUCT- TOTAL EDUCA- IONAL COSTS TION BENEFITS Figure 1.3 Educational Cost-Benefit Components Model 24 Overview This study recognizes a real and growing need to view education from a "product" perspective. In industry, the product has traditionally dictated the process; in American education, process has more commonly dictated the product. Schools and school systems with all their com- plexities as socio-technical systems are similar in many respects to factories. Even the most complicated school system can be thought of as consisting of a conversion process by which certain inputs are transposed or converted into outputs. Like other goods and services industries, schools are comprised of workers, buildings, equipment and materials with inputs of resources and outputs of products. This study centers on the product dimension of high school education. The main purpose of the study is to test the relation- ships between high school graduation program benefits con- stituting an important, measurable component of the high school "product" and their production costs. Develop- ments during the past twenty years in several disciplines including Systems Analysis, Marketing Research, Economics, and Finance now contribute to a better understanding of the educational product. While the high school graduate has been considered as a unit of "human capital" by education economists, this study employs some other business tech- niques in considering the graduate as a composite of many 25 quite different "products." Chapter II is organized in four sections; each review- ing literature pertinent to product identification, product measurement, product costing, and cost-benefit analysis, respectively. These areas provide the conceptual framework and techniques that are essential to understanding and developing this study. Chapter III contains the specific design for testing the relationships between educational benefihsand their associated production costs. The sample is comprised of three hundred and thirty-one graduates chosen randomly from the 1979 graduating classes in seven Okanagan schools. Each of the graduates responding will have their unique course program costed using cost accounting methods. In addition, their course benefits and actual grades will be obtained and aggregated for analysis. The design has been set up to facilitate testing various benefits for their individual or overall relationships with component costs of production. The central hypothesis is further elaborated into four general hypotheses and sub-hypotheses in this Chapter that is concluded with a section on Analysis. Chapter IV is concerned with the analysis of cost and benefit data obtained for each graduate and aggregated into overall and sub-group totals. The final chapter includes a a collation of all previous chapters, conclusions arising out of the study, discussion, and implications for future research. CHAPTER II RELATED LITERATURE The literature related to this study is drawn from four areas that contribute to a better understanding of the relationship between high school course or program benefits and their associated course or program costs. The four contributing areas pertinent to this study are product identification, product measurement, product costing, and cost-benefit analysis. The latter area to a large extent involves interaction between the first three. Product Identification Garms has stated that objectives held for schools are nowhere clear and simple, and that educators cannot agree on desirable educational outcomes.1 However, within the overall school curriculum, individual courses do have quite specific objectives delineated. Consequently, the school product is not surprisingly more ambiguous than the course product. According to Rodriguez and Davis, schools have assumed increasing responsibility for functions lGarms et a1., op. cit., p. 255. 26 27 formerly the domain of other social institutions.2 Con- currently, as the schools broadened their scope beyond the basic, traditional, course-centered curricula, the product took on an almost undefinable character. And as if aggre- gation of all the myriad outputs into one perceived product was not misleading enough, the whole matter is further com— plicated when the uniqueness of each student's program and experiences are taken into account. To speak of school products, or worse still system products, would be an even greater exageration or misrepresentation of the product concept. What the literature increasingly points toward is the importance of directing any product analysis as close as possible to the individual student level. The well-known work of Coleman et a1.,3 Jensen,4 and Jencks et a1.5 suggested that schools were relatively in— effective and had little influence on educational production. 2L.J. Rodriguez and D.D. Davis, The Economics of Education (Lincoln: Professional Educators Publications, 1974), p. 84. 3J.S. Coleman et a1., Equality of Educational Oppor- tunity (Washington: Government Printing Office, 1966). 4A.R. Jensen, "How Much Can We Boost I.Q. and Scholastic Achievement?" Harvard Educational Review, Winter, 1969. 5C. Jencks et a1., Inegpality: A Reassessment of the Effects of Family and Schooling in America (New York: Basic Books, 1972). 28 Averch eg_gl.6 concludes that "the best information we have . . . is that schools do not now have a tremendous impact on the achievement that does occur." With some cumulative force, these studies repeatedly indicate that schools tot- ally or in part have no significant effect on the product. Consistently, the important factors that influence the educational outcomes are related to the student's background, such as family income and race. In addition to the previous studies which attempted to link output to aggregate inputs or school attributes mea- sured as central tendencies of schools, a fairly small set of studies shows positive effects on the school product when the level of aggregation is closer to the student. 7 Alexander and McDill and Alexander et al.8 found moderate to strong additive effects on the educational product as the result of track or stream factors, while Summers and 9,10 Wolfe found similar results from classroom resources. 6H.A. Averch et a1., How Effective is Schooling: A Critical Review and Synthesis of Research Findings (Santa Monica, CA: Rand, 1972), p. x. 7Karl L. Alexander and Edward L. McDill, "Selection and Allocation Within Schools: Some Causes and Consequen- ces of Curriculum Placement," American Sociological Review (1976), pp. 963-980. 8Karl L. Alexander et a1., "Curriculum Tracking and Educational Stratification: Some Further Evidence," American Sociological Review,(1978), pp. 47-66. 9A.A. Summers and B.L. Wolfe, ”Which School Resources Help Learning? Efficiency and Equity in Philadelphia Public 29 The earlier studies had used aggregated data and this was obscuring student specific growth. In discussing the Summers and Wolfe studies, Rossmiller and Geske attribute their success and important findings to the fact that Summers and Wolfe painstakingly tied data to specific students.ll Further support for the concept of identifying educa- tional products at a level near to or equivalent to that of the individual student is given by Barr and Dreeben.12 Also, Burnstein concludes that those school effects studies using the student gains or specific educational outputs as the unit of analysis are more likely to yield accurate estimates of the factors influencing individual student achievement.13 What is clearly emerging from the more recent school effects studies is the importance of directing the level of analysis at the consumer of the product, who Schools," Federal Reserve Bank of Philadelphia Business Review, February, 1975. loA.A. Summers and B.L. Wolfe, "Do Schools Make a Dif- ference?" American Economic Review, September, 1977. 11R.A. Rossmiller and T.G. Geske, "Toward More Effective Use of School Resources," Journal of Education Finance, (Spring, 1976): PP. 494-495. 12R. Barr and R. Dreeben, "Instruction in Classrooms" in Lee S. Shulman, (Ed.), Review in Research in Education--5 (Itasca, Ill.: Peacock, 1977). l3L. Burnstein, "The Role and Levels of Analysis in the Specification of Educational Effects," (Chicago: University of Chicago, 1978). 30 for the most part is the individual student. Aggregation in the earlier school effects studies has, as Bidwell and Kasardal4 argue, probably contaminated most of the findings. These studies purported to identify variables that affected individual student output as measured by achievement. However, these variables were not specifically attributed to each student, rather they were apportioned on the basis of overall school or school district data. The school effects literature has a fundamental implica- tion for this and future studies of educational outputs or products. Disaggregation of data is essential to identify and understand educational outputs as well as inputs. The initial and well-recognized studies on school effects indicated, using aggregated data, that schools had little or no influence on student attainment. More recent school effects studies, where input variables have been disaggregated and targeted to classrooms or curricular streams, are showing increasingly that schools have moderate to strong influences on achievement. This study has gone one step further by first of all disaggregating the product into three categories of benefit; second, further dis- aggregating curricular tracks or streams into their component subject areas and courses; and third, through a cost accounting approach, overall course-related costs 14Charles E. Bidwell and John D. Kasarda, "Concept- ualizing and Measuring the Effects of School and Schooling," American Journal of Education (August, 1980), p. 425. 31 will also be disaggregated. Educational product identification is dependent on the concept and techniques of disaggregation. When education as an industry is better able to identify its products and Itheir components, and then relate these to specific inputs, it will as Levin points out be better able to draw valid conclusions about the business of education.15 A very critical step has been taken toward identifying the product of education by Lester Ruth.l6 Ruth, by defining the term "educational benefits" and the categories of benefits in his taxonomy, hopes to assist in better evaluation of education programs and to stimulate research projects. He believes that emphasis in the Eighties will be on concerns for "quality" and effective- ness, and research must seek to provide better ways of measuring outputs and outcomes.17 Implied in his work is the essential premise that something must be defined or identified before it can be measured. His major categories are based on kinds of beneficiar-- ies, since what may benefit one individual or group may not 15H.M. Levin, "Cost-Effectiveness Evaluation of In- structional Technology: The Problems" in S.G. Tickton (Ed.), To Improve Learning: An Evaluation of Instructional Technology Vol. II (New York: Bowker, 1971), P. 20. 16Lester R. Ruth, op. Cit. l7Ibid., p. 15. 32 benefit, and could actually cost, another. The major divisions he proposes are: consumers, private; consumers, public; and producers, educational delivery system. By differentiating the beneficiaries, Ruth seems to articualte a solution to the concerns of Psacharopoulos,l8 Carpenter 19 20 who all state a need to and Rapp, and Johns andMorphet view a wider range of benefits than just those accruing to the graduate. The product of education is in reality a composite of many outputs, most of which benefit the student, but some benefits or parts of the overall product are directed to others. Under Ruth's Private Beneficiaries Category he lists Students/Graduates as the prime recipients, followed by Employees, Families of Students and Employees, and finally other organizations such as clubs and associations, He identifies the educational product from the high school graduate's perspective as being further divided into six major benefits including personal benefits, academic benefits, career benefits, cultural benefits, social bene- fits, and community-related benefits. These are broken down l8George Psacharopoulos, "Spending on Education in an Era of Economic Stress: An Optimists View," Journal of Education Finance (Fall, 1980), p. 163. 19Carpenter and Rapp, 9p. cit., p. 151. 20Johns and Morphet, op. cit., p. 104. 33 into long- and short-range as well as direct and indirect benefits. School effects studies that are increasingly pointing toward the value of disaggregating data, and the work of Ruth in clarifying the many different possible segments to the educational product, represent current and practical approaches to identifying the product of education. Product Measurement Chambers is one of many contemporary writers who under- score the difficulties associated with assessing and measur- 21 Traditionally, educational ing the outputs of education. achievement has been measured by standardized test scores and letter grades. When the output is aligned to a fairly clear-cut, well-defined objective within quite narrow cur- ricular parameters, a single measure such as the letter grade may be appropriate. However, as one moves from a precise objective to a broader, more encompassing one, there is a corresponding increase in the difficulty of assigning a single symbol to represent accomplishment of the objective. Where, as previously shown, the educational product is viewed as a multifaceted composite of many educational benefits, the use of letter grades and achieve- 21Jay G. Chambers, "The Development of a Cost of Education Index: Some Empirical Estimates and Policy Issues," Journal of Educational Finance (Winter, 1980), p. 263. 34 ment scores is not only an oversimplified approach, but also misleading to interpretation. When viewing a composite symbol, there is an inclination to assume the measure accurately describes some single characteristic in an overall sense, where in fact the grade or score may not accurately portray any part of some characteristic. The difficulty reflected by Anderson and Bell22 in the assignment of values to educational output, could be attributed to trying to cover several quite different educational outcomes with a single symbol. According to Tanner, the opinion of students is a valuable measure of program effectiveness, and a represen— tative sample of student opinion is considered a valid source of output measure.23 Furthermore, he adds that this judgement would be a progressrwastep toward future assessment, potentially more valuable than the traditional measures of student achievement, Most of the research done on student opinion as it pertains to specific courses, has been conducted at the college or university level. And while the findings cannot be unreservedly applied to the high school situation, it does give some credibility to the potential value of the student perceptions. Student opin- ion as a measure of course effectiveness is most commonly 22Anderson and Bell, op. cit., p. 24. 23Tanner, op. cit., pp. 64—69. 35 solicited through the "course evaluation form" or CEF. Sturges24 points out that the literature concerning course evaluation provides some information suggesting that data obtained from students about the quality of courses are as accurate and dependable as data obtained from other 25 report that if course evaluation sources. Costin et a1. forms are well-constructed, there is increasing evidence that students are capable of making fair and informed judgements. Additional evidence concerning the validity of student responses to CEF's is provided by Aleamoni and Yimer26 and Faia.27 McKee28 recognizes a paucity of studies that attempt to differentiate between the attitude a student holds toward a course and the student ratings of the course. 24Sturges, op. cit., p. 3. 25R. Costin et a1., "Student Ratings of College Teach- ing: Reliability, Validity, and Usefulness," Review of Educational Research (1971), pp. 511-533. 26L.M. Aleomoni and M. Yimer, "An Investigation of the Relationship Between Colleague Rating, Student Rating, Research Productivity, and Academic Rank in Rating Instruc- tional Effectiveness," Journal of Educational Psychology (1973), PP. 272-277. 27M.A. Faia, "How-And Why-To Cheat on Student Course Evaluations," Liberal Education (1976), pp. 133-119. 28Barbara C. McKee, "Student's Course-Oriented Atti— tude Change and Student Ratings of Instruction: A Canoni- cal Variate Analysis," Presented at the Annual Meeting of the American Educational Research Association (Boston: April 1980), p. 4. 36 McKee's own research indicates that students can and do make a distinction between a course and the instructor of a course.29 It is probably too early to make a definitive comment on the ultimate usefulness of student opinion. Kulik and Kulik believe that "student ratings may be irrele- vant and misleading, or they may be useful, convenient, reliable, and valid."30 Whatever else, the evidence seems to be growing in support of student opinion as a measure of the educational product. One area where high school graduate opinion has been widely sought, is in follow-up studies of vocation program graduates. In the United States, for school districts to continue receiving state and federal vocational education funds, they are required to conduct specific follow-up studies. Guidelines for these projects are delineated by the United States Office of Education, and those districts offering and funded for career education programs must comply to the follow-up requirements. This initiative has resulted in numerous studies being undertaken involving students who have graduated from vocational and technical schools. In a 29Barbara G. McKee, "The Influence of the Course Vs. the Instructor in Student Rating of Instruction: A Multiple Group Discriminant Analysis," Paper presented at the Annual Meeting of the American Educational Research Association (63rd, San Francisco, April 8-12, 1979), p. 50. 30LA. Kulik and C.C. Kulik, "Student Ratings of Instruction," Teaching of Psychology (December, 1974), p. 51. 37 few instances some studies were expanded to include grad— uates from other than vocational programs. Wasil31 has made extensive use of the follow-up model in education and is of the opinion that this vehicle is particularly valuable in providing course or program feedback. Follow-up information or indicators can serve as gauges or trouble signals to flag those courses or pro- 32 They can show where grams that are in need of review. and when to pursue in-depth analysis aimed at program im— provement. The literature revealed three studies that solicited student opinion using a follow-up survey to understand 33,34,35 their recent high school experience. The more 31Raymond A. Wasil, "Model for Implementation of School Follow—up System" in Follow-up Survey 1975 Graduates (Sedalia: State Fair Community College, 1974), p. 12. 32UsingStudent Follow-Up Surveys to Improve College Programs--A Staff Report (Atlanta: Southern Regional Education Board, 1980), P. iii. 33An Analysis of the Evaluation of High School Exper- iences in Reference to the Personal and Educational Character- istics of the Graduating Classes of 1973 and 1969 (Salinas: Salinas Union High School District, 1974). 34Phoenix Union High School System Follow-Up Study of 1972 Graduates (Phoenix: Phoenix Union High School District, 1974). 35Marie J. Abram, The Perceptions of 1978 and 1979 Graduates (Bowling Green: Professional Development Center Network, West Kentucky University, Spring/Summer, 1980). 38 recent Abram study was designed specifically to find indica- tors of how well the high schools were serving their clien- tele, the students, Student judgements were used to identify the areas of the course curriculum that were in greatest need according to the perceptions of the respondents. The educational product, traditionally measured by grades and standardized scores, is increasingly being subject to measurement by student opinion. Follow-up studies offer a practical and useful way to obtain ratings based on the perceptions of education's "consumers." Product Costing Early 20th Century efforts by some educators to apply an industrial approach and techniques to schools to make them more efficient, did recognize the cost factor as an essential element. From the beginning, education has adopted a general or financial accounting philosophy and format, with only a rather recent focus on the possibilities implicit in a cost accounting framework. In 1948, the generally recommended main headings for K to 12 expenditure accounts were:3 Administration (formerly "general control") Instruction Auxiliary Services 36Knezevich, op. cit., p. 149. 39 Operation of Plant Maintenance of Plant Fixed Charges Capital Outlay Debt Servicing By 1957, the Office of Education had revised these major expenditure account classifications to:37'38 Administration Instructional Salaries Other Instructional Expenditures Plant Operation Plant Maintenance Attendance Services Health Services Transportation Services Food Services Miscellaneous Services Community Services Summer Schools Adult Education 37P.L. Reason and A.L. White, Financial Accountingyfor Local and State School Systems, Standard Receipt and Expen- diture Accounts Bulletin 1957, United States Office of Education Handbook II (Washington: Government Printing Office, 1957). 38United States Department of Health, Education and Welfare, Office of Education, Statistics of State School Systems 1959-60 (Washington: Government Printing Office, 1963), PP. 57-73. 40 Community Colleges Fixed Charges Capital Outlay Interest TOTAL Benson lists these headings in the somewhat consolidated form that he was using in the early Sixties.39 Instructional Salaries Capital Outlay Operation of Plant School Services (cafeteria, health, attendance, etc.) Fixed Charges (teacher retirement, social security, etc.) Instructional Supplies and Services Administration Interest Maintenance of Plant Community Services (extension, summer school, etc.) TOTAL By the mid 1960's, interest in applying PPBS to educa- tion had started and it grew substantially in the late 1960's. With its stress on objectives or purposes to be fulfilled by the investment of public funds,40 there was an 39Charles S. Benson, The Economics of Public Education (New York: Houghton Mifflin Company, 1968), p. 14. 40Knezevich, op. cit., p. 156. 41 increased need for accounting information that could show expenditures aggregated around program elements and cate- gories. This need was reflected by Mitchel et al. in 1969 when they recommended accounting by area of responsibilities, subject area, activities, and object expenditures.41 The previous year, Lindeman had proposed a "three-dimensional accounting classification system" for public schools.42 According to Knezevich, the 1972 Office of Education's Revised Handbook also encouraged reporting by major functions, grade levels, organizations, and objects.43 He goes further in suggesting that while accounting by purpose demands designation by programs and expenditures clustered around functions, most current program accounting efforts in education fail to meet these tests.44 The literature on education accounting shows evidence of a trend toward the increased implementation of a cost accounting approach to supplement the traditional methods of financial or general accounting. The more systematic analy— 41J.E. Mitchell, et a1., MSEIP Documentation of Project Development and General Systems Design, Midwestern States Educational Information Project (Des Moines: State of Iowa Department of Public Instruction, 1969). 42E.L. Lindemann, A Three-Dimensional Proggam Account Classification System for Public Schools, Working Paper No. 6, (Los Angeles: UCLA Center for the Study of Evaluation and Instructional Programs, 1968). 43Knezevich, op. cit., p. 156. 44Charles S. Benson, Education Finance in the Coming Decade (Bloomington: Phi Delta Kappa, 1975), p. 59. 42 sis of resource allocations that PPBS in principle implies, has been associated with general improvement in budget docu- ments. Presently, one is increasingly likely to find instruc- tional budgets broken down to reveal expenditure by level of school program and by type of instruction offered. These expenditures are in greater detail and are directly assoc- iated with the distribution of resources to specific school functions.45 Tanner suggests that direct and indirect costs be apportioned to subject areas such as Language Arts, Science, Mathematics, Social Studies, and so on.46 He also elaborates additional cost categories such as administration, instruction, materials, maintenance, and others common to all educational institutions. Rossmiller and Geske show that disaggregated data concerning the various school inputs is virtually non- existent and state that "very few school systems are able to provide data on the cost of operation of individual schools, much less the fiscal inputs to various curricular programs 47 Other writers concerned with the prac— within schools." tical aspects of implementing PPBS recognize the paramount importance of a better financial accounting clasSification 45Tanner, op. cit. 461bid., p. 167. 47Rossmiller and Geske, op. cit., pp. 494-495. 43 system.48 The decision-maker needs information, and demands that it be organized in a particular way to facilitate selection of the most prudent course of action. This emphasis, incorporating the concept and techniques of cost accounting, is essential to a full understanding of the educational product. Cost-Benefit Analysis The final area examined in the literature is that which attempts to link the product of education to its production costs. Cost—benefit analysis and its modern off-shoots endeavours to identify and to measure the bene- fits and costs that would result from alternative courses of action.49 Man has always weighed the pros and cons, the advantages and disadvantages, of alternative actions. As indicated previously, cost-benefit analysis can be traced back to an article written in the middle 19th Century. However, with relatively recent improvements and refine- ments to techniques, it has only really come into its own in the past twenty years. Originally, the term and concept "benefit-cost analy- sis" was associated with and applied to natural resource projects, but its most popular use probably has been in 48Knezevich, op. cit., p. 148. 49Davis and Morrall, op. cit., p. 37. 44 national defense planning. In the late 1940's, the Rand Corporation used "costing" methods in determining for the United States Air Force, the best strategic bomber for development. During the 1950's, full-fledged cost-benefit analysis was used widely for the first time in water resource studies. In a 1959 report done by Kershaw and McKeon for the Rand Corporation, they suggest that it is not only desirable but also possible for school districts to compare the marginal benefits of one type of expenditure over another and to merge the benefit comparison with cost estimates to choose the budgetary option that gives the most return for the dollar spent.50 As a technique and methodology of evaluation, cost-benefit analysis has been used increas- ingly in the 1960's and 1970's to judge the effectiveness of educational programs.51 Anderson and Bell provide an overview of some contem- porary thinking on cost-benefit analysis and two of its off-shoots, namely cost—effectiveness and cost utility.52 According to them, the term cost-effectiveness is often not distinguished in the literature from cost-benefit, and 50Joseph A. Kershaw and Roland N. McKeon, Systems Analy- sis and Education (Santa Monica: The Rand Corporation, 1959), Ch. V. 51Davis and Morrall, op. cit., pp. 38-39. 52Anderson and Bell, op. cit., pp. 24-25. 45 usually is simply subsumed under the umbrella of the latter. Cost-effectiveness allows the "benefit" to be expressed in terms of its actual physical or psychological outcome rather than its monetary value; on the other hand, cost-benefit analysis usually assigns monetary values to both the benefits and costs. Quade defines cost-effectiveness as a "comparison of alternate courses of action in terms of their costs and their effectiveness in attaining some specific objective."53 Goldstein states that two of the major distinguishing points of cost-effectiveness analysis over cost-benefit analysis are: first, the goals and objectives must be explicitly articulated; and second, all degrees of quality of informa- 54 Thus tion on "benefits" are allowed in the analysis. the analyst does not have to compress all the "benefits" into a single number expressed in dollars, but effectiveness is considered in terms of possibly several dimensions and non-ordinal measures can be used in these dimensions. Conceptually, cost-benefit analysis employing a systems approach to education offers a practical means of evaluating the educational product. Defined objectives can be evaluated using cost-benefit analysis to determine if 53Edward S. Quade, Cost Effectiveness Analysis (Wash- ington: Praeger, 1967), pp. 1-2. 54Harvey Goldstein, Cost-Benefit and Cost-Effective- ness Analysis (Washington: The National Training and Development Service, February 1981), P. 4. 46 they are efficiently or effectively met. This product information can then be fed back and the original objectives or program reviewed, in turn perhaps initiating appropriate modifications to either the objectives or the educational delivery system. While cost-benefit analysis has been fairly widely used in the former sense relating to objectives, Cafferella points out a specific need to expand research on the impact of this analysis on instructional technology.55 Summagy To test the relationships between educational benefits and their production costs requires the clearest possible understanding of what the product or benefit is, how it can be measured, how it can be costed, and how these three considerations are drawn together traditionally through cost-benefit analysis. Consequently, Chapter III focuses on these four areas and includes a review of recent trends documented in the literature. First of all, what is the educational product? The literature Shows that objectives held for schools are nowhere Clear and simple, and that educators cannot agree on desirable educational outcomes. Further, as schools have broadened their scope beyond the basic, traditional, 55E.P. Cafferella, "How Little Do We Know About the Cost-Effectiveness of Instructional Technology?" Educational Technology (January, 1975), pp. 57-58. 47 course-centered curricula, the product has taken on an almost undefinable character. Given the complexity and vagueness of the product, and the fact that most of the well-recognized school effects studies of the Sixties and early Seventies were contaminated by using aggregated data, the literature increasingly points toward the importance of directing any product analysis as close as possible to the individual student level. A small but important set of studies clarify the school product when the level of aggregation is closer to the student or consumer. What is clearly emerging from the more recent school effects studies is the importance of directing the level of analysis at the consumer of the product, who for the most part is the individual student. With analysis of the educational product placed at this level, Lester Ruth's seminal work on defining a taxonomy of educational benefits affords a legitimate base for defining the educational product at a consumer level. He identifies the educational product from the high school graduate's perspective as being divided into categories of direct and indirect benefits. Once identified, how can the product be measured? The literature underscores difficulties associated with assess- ing and measuring the outputs of education. When output is aligned to a fairly clear-cut, well-defined objective within quite narrow curricular parameters, a single measure such as a letter grade may be appropriate. However, the literature 48 cautions against the use of letter grades and achievement scores as an oversimplified approach to a multi-faceted educational product. Examining this more complex product at the student or school graduate level is being accom- plished more and more through the use of follow-up studies and student opinion. The literature shows that these methods offer a practical and useful way to obtain ratings based on the perceptions of education's "consumers." For costing the educational product, the literature on education accounting shows evidence of a trend toward the increased implementation of a cost accounting approach to supplement the traditional methods of financial or general accounting. From the early 20th Century efforts by some educators to apply an industrial approach and techniques to schools, education adopted a general or non- specific accounting philosophy and format. The current literature reveals that one is increasingly likely to find instructional budgets broken down to reveal expenditures in greater detail and directly associated with the dis- tribution of resources to specific school functions. This new emphasis incorporating the concept and techniques of cost accounting is essential to a full understanding of the educational product. The final area examined in the literature is that which attempts to link the product of education with its production costs. Cost—benefit or cost-effectiveness 49 analysis requires that goals and objectives are explicitly articulated, that outcomes be measured, and that pro- duction costs assessed. Conceptually, a cost-benefit analy- sis employing a systems approach to education offers a practical means of evaluating high school education and understanding its various products. CHAPTER III DESIGN OF THE STUDY Sample The sample for this study consisted of three hundred and thirty-one graduates from the 1979 graduation class in School District #23 (Central Okanagan), British Columbia. These graduates were selected randomly from each of the seven high schools that enrolled graduating students in 1979. The district, located in the interior of B.C. and shown in Figure 3xl, contains urban and rural schools. ‘2 -.-~- * ms. .3 map“. _ 1.1 , , ..- $5~rq~ , 3‘3"" ‘39,“. ‘4', . f ._ 1‘ fift‘umanu 1w. (“h (I . .41-“? ~uiuwpga._n- , - 11:. “fl 1. x f .‘pw' .. -4 a.“ v _._. pg...“ Figure 3.1 Location of School District #23 50 51 Serving a population of approximately sixty thousand, Central Okanagan School District's schools are represen— tative of those found throughout the province. Table 3.1 provides school data on enrolments and timetable organiza— tion, illustrating the diversity of size and structure in the schools from.which the sample was drawn. Table 3.1: Summary of 1979 Senior Grade Enrolments and Timetable Organization in School District #23 Secondary School Senior Enrolment Periods Timetable Gr 11 Gr 12 Per Day George Elliot 119 110 6 Quarter George Pringle 118 99 5 Yearly KLO 140 136 6 Semester Kelowna 482 506 6 Semester Mount Boucherie 138 158 5 Yearly Okanagan Mission 117 94 6 Semester Rutland Senior 177 252 5 Trimester Originally, sixty graduates' names were selected ran- domly from each of the seven high school's graduating class of 1979. Mail surveys were sent to these individuals, soliciting their perceived benefits from specified graduation courses and asking them to rate these benefits, using a six- point Likert scale, in three distinct categories. Grad- uates were also asked to indicate their present activity as work, school, and/or other. The initial mail survey was in all cases followed-up by two additional letters if a 52 response was not forthcoming. Table 3.2 summarizes the response from each school's graduates. Table 3.2. Summary of School Response Rate to the Graduate Benefit Survey Secondary School Responses Percent George Elliot 49 82 George Pringle 49 82 KLO 51 85 Kelowna 51 85 Mount Boucherie 43 72 Okanagan Mission 38 63 Rutland Senior 50 83 TOTAL 331 79 School profiles of the 331 graduate respondents indicate that in terms of ability characteristics, average achieve- ment, and choice of graduation program, differences are minimal. The average number of courses completed for gradu- ation is somewhat more variable between schools, reflecting differences between school's timetable organization. Sex was almost balanced in the sample with 166 males graduates and 165 female graduates responding to the benefit survey. In summary, the graduates whose perceptions on educa- tional benefits form the basis for "product" evaluation in this study, appear to be representative of the population of high school graduates in British Columbia. 53 Measures Educational benefits are defined according to Ruth as "those things that promote or enhance well-being of a group or individual and that are produced by an educational delivery system."1 This study is limited to those benefits derived specifically from courses taken in Grade 11 or Grade 12 and counted for graduation from high school. Using Ruth's Taxonomy as a basis, three categories of bene- fits were identified for the purposes of this study,2 namely, Further Education Benefits, Job Benefits, and Personal Bene- fits. Graduates were instructed to indicate by checking the degree of benefit obtained from each course completed in Grade 11 and 12. The survey form listed each graduate's specific course program to facilitate their response and help remind them of all graduation courses. The three categories of benefit employed a six point Likert Scale3 allowing responses from "No" to "Great.“ Graduate benefits were then aggregated for both the Core as well as the Flexible components of each student's program. In British Columbia, students must graduate on either an lRuth, op. cit., p. 12. 21bid., p. 17. 3J.W. Wick, Educational Measurement (Columbus: Charles E. Merrill, 1973), P. 267. 54 Academic, Combined, or VOcational program. By aggregating course benefits for the flexible or elective portion of each program, it was possible to obtain a product measure in terms of benefits. For each graduate it was a relatively straightforward process to determine benefit scores for their unique elective program. Course costs are determined using a cost accounting approach to categorize and allocate course-specific expen- ditures. The traditional education finance or general accounting format used by the British Columbia Ministry of Education and School Boards in the Province, does not lend itself to specific course or program costing. However, many of the costs subsumed under old headings can be reassigned under Course Account Headings. The course headings adopted for this study are: Instructional PERSONNEL Instructional MATERIALS Instructional OVERHEAD These are further broken down to include: PERSONNEL Instructional Salary Fixed Charges Aides Allocation, percent of administration Allocation, percent of Co-ordinator MATERIALS Texts Miscellaneous Supplies 55 OVERHEAD Facilities Proerate Equipment Pro-rate Facility Operation Facility Maintenance Most high school teachers in School District #23 are assigned seven courses or seven classes per school year. This study assumes that the teacher's salary will be divided or apportioned to each class on an equal basis. For example, if a teacher earns twenty-one thousand dollars per year and carries the regular class load, this would work out to three thousand dollars per course. The study further assumes that the course cost for "Instructional Salary" will be deter- mined by dividing the teacher's salary for a particular course by the class enrolment.4 For example, if the class size was twenty-five, using the previous illustration of three thousand dollars per course, the instructional cost per student would be one hundred and twenty-five dollars. On the other hand, if the class was a small senior elective with only ten class members, the cost for each student would rise to three hundred dollars for instruction. Aides are available in some schools for some subject areas such as Science, English and Home Economics. Where applicable, these were added to the Instructional Personnel costs. 4Ministry of Education Form "K," Province of British Columbia (1979). 56 School administration costs, including the counselling component, were apportioned on a percentage basis to each course. Some subject areas such as Physical Education and French have District Coordinators to help the classroom teachers. Where these were employed, their salaries were pro-rated and partially assigned as additional course costs. The final entry under Personnel Costs was made for Fixed Charges that included such items as Teachers' Pen- sions and Medical/Dental Benefits paid on behalf of these District employees. The Materials Account Heading for each course included all prescribed textbooks and a portion of the authorized textbooks and materials used in the course. These were given a four year life for depreciation purposes. The Materials heading also covered any miscellaneous supplies that.were required for the course. For example, supplies for Chemistry and Art as well as food for Home Economics were included in this category. Overhead Costs included all of the costs of production other than direct personnel or direct materials costs. This study depreciated building facilities and equipment on a course-specific basis. For instance, the classrooms, laboratories, or other teaching areas were valued and depreciated according to their useable lives, and this depreciation was charged to the courses requiring the 57 specific facility. Costs for course equipment were assigned in a similar manner. Various sources were used in accumu- lating depreciation cost data; these included insurance valuations, taxation valuations, replacement estimates, and actual purchase costs. Facility Operation and Maintenance costs were also pro-rated for each course. These figures were readily obtained from the School District records. Educational achievement in this study is determined for each graduate by reviewing the Permanent Record Cards5 (PR-1) on file in the School District Central Office and assigning Grade Points for each course completed. These Cards only show letter grades by course and do not contain any information on cumulative standings. During the Senior years of high school in British Columbia, students in 1979 were required to complete a minimum of twelve courses including English 11 (En 11), English 12 (En 12), Social Studies 11 (SS 11) and Physical Education 11 (PE 11). These would almost always be taken in the Grade 11 and Grade 12 years and several students would choose as many as fifteen or sixteen courses. Apart from the four required courses, students could also choose the program concen- tration of courses with an emphasis on the Academic Area, Vocational Area, or Combined Studies Area. The latter simply 5Ministry of Educapion Permanent Record Form, Province of British Columbia (1979). 58 representing a combination of Academic and VOcational courses. The following equivalencies are used to convert British Columbia Final Course Grades to Grade Points: A = 5.0 B = 4.0 C+ = 3.0 D = 2.0 P = 1.0 F = 0.0 School graduates were also asked to respond to a question on their post-high school activities. By indicat- ing whether they have been working or in school, part- or full-time since graduation, it is possible to categorize six major post-high school activities. These are: School Full-Time S School Full-Time, Work Part-Time SW School Full-Time, Work Full-Time SW School Part-Time, Work Full-Time SW Work FulleTime W Other 0 The follow-up survey form was designed to encourage graduates to make written comments pertaining to their high school courses. 59 Design The design of this study is essentially predictive, employing an input-output model to test cost-benefit relationships. Correlation statistics and analysis of variance techniques are used to examine and test the relationships between education costs and program benefits. Total Education Benefits, Further Education Benefits, Job Benefits, and Personal Benefits are all treated as dependent Variables. Total Costs, Instructional Personnel Costs, Materials Costs, and Overhead Costs are used in this study as independent variables. Graduate programs consist of two parts: the core courses are compulsory for all students and constitute between one quarter to a maximum of one third of the total program; the elective courses form the largest part of any graduate's program. This study is primarily concerned with testing the cost-benefit relationships in the elective program. This is also the portion of the graduation program that determines whether a student is classified as academic, vocational, or combined. These core and elective components are shown in Figure 3.2. A second approach to considering the high school pro- duct is to focus on the actual post-high school activity of each graduate. Here, the educational product is defined by the reality of the graduate's personal situation two years 60 FOUR CORE COURSES + + 4— ACADEMIC COMBINED VOCATIONAL ELECTIVES ELECTIVES ELECTIVES ACADEMIC COMBINED VOCATIONAL GRADUATION GRADUATION GRADUATION Figure 3.2 Graduation Program Components after graduation. Depending on whether a graduate is attend- ing school or working, full- or part-time, or in fact doing something else, these activities by their functional nature are used to classify graduates. These activity groups are examined for cost-benefit relationships. A final subgrouping that is built into the research design is determined by the number of courses selected in the graduation program. To some extent at least, the number of courses comprising a vocational, combined, or academic program can be used to categorize products as a minimal or extended graduation. These subgroups are examined for relationships between benefits and their associated costs of production. To summarize this section on design, Figure 3.3 illus- trates the three main groups with their respective subgroups that will be tested for relationships between benefits and program costs. 61 GRADUATES [I ‘1 GRADUATION POST-HIGH NUMBER OF PROGRAM SCHOOL COURSES ACTIVITY A C V S Sw SW sW W Other 8 9 10 ll 12 Figure 3.3 Graduate Subgroups Tested For Cost-Benefit Relationships Hypotheses General Hypothesis l.--Total Educational Benefits are positively related to senior high school program costs. Operational H1 The variable, Total significantly related to Costs. Operational Hl.l The variable, Total significantly related to Personnel Costs. Operational Hl.2 The variable, Total significantly related to Costs. Operational Hl.3 The variable, Total significantly related to Costs. Benefits will the variable, Benefits will the variable, Benefits will the variable, Benefits will the variable, be positively and Total Educational be positively and Total Instructional be positively and Total Materials be positively and Total Overhead 62 General Hypothesis 2.--Total Further Education Benefits areypositively related to senior high school program costs. Operational H2 The variable, Further Education Benefits will be posi— tively and significantly related to the variable, Total Educational Costs. Operational H2.l The variable, Further Education Benefits will be posi- tively and significantly related to the variable, Total Instructional Personnel Costs. Operational H2.2 The variable, Further Education Benefits will be posi- tively and significantly related to the variable, Total Materials Costs. Operational H2.3 The variable, Further Education Benefits will be posi- tively and significantly related to the variable, Total Overhead Costs. General Hypotheses 3.--Tota1 Job Benefits are positively related to senior high school program costs. Operational H3 The variable, Job Benefits will be positively and significantly related to the variable, Total Educational Costs. Operational H3.1 The variable, Job Benefits will be positively and significantly related to the variable, Total Instructional Personnel Costs. Operational H3.2 The variable, Job Benefits will be positively and significantly related to the variable, Total Materials Costs. 63 Operational H3.3 The variable, Job Benefits will be positively and significantly related to the variable, Total Overhead Costs. General Hypothesis 4.-eTota1 Personal Benefits are positively related to senior high school program costs. Operational H4 The variable, Personal Benefits will be positively and significantly related to the variable, Total Educational Costs. Operational H4.l The variable, Personal Benefits will be positively and significantly related to the variable, Total Instructional Personnel Costs. Operational H4.2 The variable, Personal Benefits will be positively and significantly related to the variable, Total Materials Costs. Operational H4.3 The variable, Personal Benefits will be positively and significantly related to the variable, Total Overhead Costs. Analysis The purpose, design, and analysis of this study focus on testing for positive and significant relationships between senior high school program benefits and their pro- duction costs. Each graduate's perceived benefits, as reported on the graduate benefit survey, were totalled overall and under the headings of Further Education Benefits, 64 Job Benefits, and Personal Benefits. Costs were deter- mined using a cost accounting method and were categorized under Total Costs, Instructional Personnel Costs, Materials Costs, and Overhead Costs. These eight variables were analyzed for cost-benefit relationships using the Pearson product-moment correlation coefficient to test for relation- ships between cost and benefit variables and also using an analysis of variance to specifically test the effects of cost variables on the four benefit variables. Both the correlation analysis and the analysis of variance were carried out on the complete sample of 331 graduates as well as three sub-groupings of the sample according to graduation program completed, post-high school activity, and the number of courses taken for graduation. The Pearson correlation coefficient r is used to test the relationships between benefit and cost variables using a one-tailed t-test with N-2 degrees of freedom at a significance level less than .05. The assumptions for this model are essentially that scores are randomly sampled from normal populations with equal variances and the samples are independent. The analysis of variance was used to assess any signifi- cant effects of the cost variables, Total Cost, Instruc- tional Personnel Costs, Materials Costs, and Overhead Costs on the dependent variables. Each of the cost variables were quartiled into categories ranging from low cost to 65 high cost.. According to values for cost variables, grad— uates were assigned to one of the four categories thereby enabling cost effects of the independent variable to be tested against the dependent variable, benefits. This one- way, fixed effects analysis of variance model assumed that the distribution of the dependent variable was normal and that population variances in the samples were equal. An advantage in employing the analysis of variance model is that reasonable departures from the assumptions of normality and homogeneity may occur without seriously affecting the validity of the inferences drawn from the data. Summagy This study was designed to test the relationships between educational benefits and their specific production costs. A sample of three hundred and thirty-one graduates from the 1979 graduating class in British Columbia's Central Okanagan School District responded to a graduate benefit survey. These were drawn randomly from the seven senior high schools and represent a good cross-section of the district school p0pulation. The graduates were asked to indicate for each course completed during their senior high school years what their perceived benefits were. Their responses could be checked off in three categories, Further Education Benefits, Job Benefits, and Personal Benefits. Each of these also allowed 66 the graduate to express the degree of benefit on a six- point Likert Scale ranging from "No Benefit" to "Great Benefit." For the purpose of this study, totals were calculated for the three categories of benefit and these were then summed to give a grand total, referred to in the study as the variable, Total Benefits. For each graduate respondent, course costs were determined using cost accounting methods. These costs were classified as instructional personnel, materials, and overhead. These costs were then aggregated by course to arrive at total costs in each of the three categories, and these were also combined into a total-program cost. This study is only concerned with that portion of the graduate's program termed elective. While graduates in British Columbia high school require four core subjects, the elective group of courses are actually those that are student-specific and determine their unique program. The term Total Benefits and Total Costs have been calculated by subtracting both the core benefits as well as the core costs from the complete graduate program. The four general hypotheses and their many operational hypotheses were tested using Pearson correlation analysis and analysis of variance employing significance levels of .05. The correlation analysis tested for significant and positive relationships between cost and benefit variables; the analysis of variance tested the effects of cost variables 67 on the dependent benefit variables. The analyses were employed with the total sample of graduates and three sub-groups determined according to the graduation program, post-high school activity, and number of courses completed for graduation. CHAPTER IV ANALYSIS OF RESULTS Total Benefits and Costs Total benefits and total costs were examined for the overall sample of three hundred and thirty-one graduates. In addition, total benefits and costs were determined for three groupings of the sample according to graduation program, post-high school activity, and number of elective graduation courses. The overall and group values are shown in Table 4.1. Academic program benefits were the greatest, 96.7, and the total production costs highest at $2,592. Vocational graduates reported the least total benefits, 79.7, while their costs, $2,423., were slightly more than the Combined program graduate whose costs were $2,404. and benefits, 86.6. An analysis of post-high school activity indicates that graduates who are neither working nor going to school reported the lowest benefits, 77.6, and had the lowest program production costs, $2,293. These low scores contrast with those of graduates attending school full-time, whose costs were $2,627. and benefits, 95.5. These represent 68 69 Table 4.1. Means for Total Benefits and Total Costs Groups Total Benefits Total Costs Mean SD Mean SD Overall Sample (n=33l) 89.0 26.4 $2,487 $365 Graduation Program Academic (n=138) 96.7 25.3 2,592 292 Combined (n=106) 86.6 25.8 2,404 357 Vocational (n=87) 79.7 25.5 2,423 436 Post-High School Activity School Full-Time (n=57) 59.5 2.30 2,627 297 School Full-Time and Work Part-Time (n=34) 95.5 20.1 2,492 321 School and Work (n=75) 91.5 25.6 2,554 364 Full-Time Work and Part-Time School (n=20) 100.1 26.6 2,553 437 Work Full-Time (n=ll8) 83.2 26.8 2,410 367 Other (n=27) 77.6 31.9 2,293 351 Number of Graduation Electives 8 Courses (n=57) 71.5 23.5 2,120 315 9 Courses (n=61) 81.0 23.0 2,314 278 10 Courses (n=79) 88.7 25.1 2,545 276 11 Courses (n=104) 97.4 23.5 2,667 306 12 Courses (n=27) 112.4 26.2 2,841 252 percentage differences of 15 and 25, respectively. group of graduates with the highest benefits were those working full-time and attending school part-time. large group of graduates who were working full-time had a relatively low benefit score of 83.2 and program costs of $2,410. The The 70 As expected, both program benefits as well as program costs increased as the number of graduation electives went up from eight to twelve. The range of benefits was from 71.5 to 112.4 and costs went from $2,120. to $2,841. The maximum means represented increases of fifty-seven and thirty-four percent, respectively, for benefits and costs. Total Costs In testing the hypothesis that the variable, Total Benefits will be positively and significantly related to the variable, Total Educational Costs, it was determined by correlation analysis and analysis of variance that such a significant relationship does exist. The Pearson product- moment correlation coefficient for these two variables was r = .2975, p < .001; analysis of variance performed on the dependent variable, Total Benefits, identified a Total Cost effect, F(3,327) = 9.344, p < .001. Clearly, graduates who had higher perceived total benefits also were the ones who had the higher program production costs, while those whose benefits were the least had the lowest total program costs. A more detailed analysis of the correlational relationship between these variables shows that 85.3 percent of the variance of total benefits attributable to total costs is accounted for by instructional costs. Materials costs and overhead costs are responsible for 6.0 and 8.7 percent, 71 respectively. Correlation analysis applied to the three graduation programs showed that significant benefit and cost relation- ships existed for all: Academic, r = .2679, p < .001; Combined, r = .2842, p < .01; and Vocational, r = .2256, p < .05. Only three of the six post—high school activity groups showed significant relationships between total bene- fits and total costs. Graduates who were attending school full-time and working part-time, attending school and working equally, or working full-time had total benefit-cost relationships of r = .4313, p < .01; r = .3263, p < .01; and r = .2955, p < .001, respectively. The final grouping, by number of graduation electives, had positive and signifi- cant relationships between total benefits and total costs for those graduates who completed either eight or ten elec— tive courses. The former sub-group of fifty-seven graduates had relationships with r = .3274 and p < .01. For those with ten courses, r = .1856 and p < .05. While all hypo- theses were directional and therefore tested with one-tail, it was interesting to note that a significant, but negative relationship existed for graduates who had completed eleven electives at r = -.1646, p < .05. Analysis of variance performed on the dependent vari- able, Total Benefits, for each of the sub-groupings of graduation program, post-high school activity, and number of elective graduation courses found significant total 72 cost effects for the Academic program, F(3,l34) = 3.957, p = .010; graudates attending school full-time and working part-time, F(3,30) = 3.001, p = .046; graduates working full-time, F(3,ll4) = 4.816, p = .003; graduates who completed eight elective courses, F(3,53) = 2.913, p = .043; and graduates who completed ten elective courses, F(3,75) = 3.419, p = .022. For the variables Total Benefits and Total Cost, the significant relationships are summarized in Table 4.2. Table 4.2. Summary of Relationships, Total Benefits and Total Costs Groups Level of Significance Correlational Anova Overall Sample (n=331) p < .001 p < .001 Graduation Program Academic (n=138) p < .001 p = .010 Combined (n=106) p < .01 Vocational (n=87) p < .05 Post-High School Activity School Full-Time (n=57) School Full—Time and Work Part-Time (n=34) p < .01 p = .046 School and Work (n=75) p < .01 Full-Time Work and Part-Time School (n=20) Work Full-Time (n=118) p < .001 p = .003 Other (n=27) Number of Graduation Electives 8 Courses (n=57) p < .01 p = .043 9 Courses (n=61) 10 Courses (n=79) p < .05 p = .022 11 Courses (n=104) 12 Courses (n=27) Total Instructional Personnel Costs 73 Approximately eighty percent of total educational costs are instructional pesonnel costs. This section of the analysis is concerned with identifying and testing for posflive and significant relationships between the variables Total Benefits and Total Instructional Personnel Costs. The means for these variables are given in Table 4.3. Table 4.3. Means for Total Benefits and Total Instructional Personnel Costs Total Benefits Total Instruction Groups Personnel Costs Mean SD Mean ’ SD Overall Sample (n=331) 89.0 26.4 $1,975 $286 Graduation Program Academic (n=138) 96.7 25.3 2,103 233 Combined (n=106) 86.6 25.8 1,917 277 Vocational (n=87) 79.7 25.5 1,841 290 Post-High School Activity School Full-Time (n=57) 95.5 23.0 2,136 236 School Full-Time and Work Part-Time (n=34) 95.5 20.1 2,043 265 School and Work (n=75) 91.5 25.6 2,033 296 Full-Time Work and Part-Time School (n=20) 100.1 26.6 2,026 287 Work Full-Time (n=118) 83.2 26.8 1,871 252 Other (n=27) 77.6 31.9 1,799 272 Number of Graduation Electives 8 Courses (n=57) 71.5 23.5 1,644 193 9 Courses (n=61) 81.0 23.0 1,853 217 10 Courses (n=79) 88.7 25.1 2,025 214 11 Courses (n=104) 97.4 23.5 2,117 217 12 Courses (n=26) 112.4 26.2 2,287 244 74 The highest cost program far expenditures on instruction was the Academic program at $2,103. and the lowest was Voca- tional at $1,841. The Combined graduation program at $1,917. was between the other two graduation options. Those gra- duates who were attending school two years after high school had the most expensive instructional costs, $2,136. This amount decreased proprtionately as the degree of work increased. For a graduate working full-time, instructional costs were $1,871. The lowest instructional personnel costs were for the group of graduates who were neither working nor attending school. Based on post-high school activity, the percentage difference between the lowest instructional costs and the highest was nineteen percent. Depending on the number of courses elected for graduation, the instruc- tional costs ranged from a low of $1,644. to a high of $2,287. There was a direct relationship between elected courses and instructional costs. An analysis of the relationships between total benefits and total instructional costs, using Pearson correlation coefficients, indicated that several were significant at a level of p < .05. First of all, for the overall sample of graduates, r = .3242, p < .001. Total benefits for graduates of all three program options were significantly related to their program production costs for instruction: Academic, r = .2125, p < .01; Combined, r = .3017, p < .001; and Vocational, r = .2336, p < .05. Two relationships between 75 total benefits and instructional costs were identified for graduates who were working and attending school equally, as well as those who are working full-time two years after graduation. These were the only post-high school activity groups whose cost-beneift relationships were significant at or beyond the .05 level. Their respective coefficients were r = .3138, p < .01 and r = .3442, p < .001. Analysis of the groups of graduates who elected from eight to twelve courses showed that significant relationships could be identified for those who took eight and ten courses for their graduation programs. The eight course graduates had r = .3888, p < .01 and ten course graduates had r = .2012, p < .05. Analysis of variance performed on the dependent var- iable, Total Beneifts, for sub-groupings of graduate programs and number of graduation electives identifed only two significant Instructional Personnel Costs effects. These were for the Academic program, F(3,134) = 2.792, p < .05 and for graduates who completed eight elective courses, F(3,53) = 3.211, p < .05. For the variables, Total Benefits and Total Instruc- tional Personnel Costs, the significant relationships are summarized in Table 4.4. Table 4.4 Summary of Relationships, Total Benefits and Total Instructional Personnel Costs Groups Level of Significance Correlational Anova Overall Sample (n=331) p < .001 - Graduation Program Academic (n=138) p < .01 p < .05 Combined (n=106) p < .001 VOcational (n=87) p < .05 Post-High School Activity School Full-Time (n=57) - School Full-Time and Work Part-Time (n=34) - School and Work (n=75) p < .01 Full-Time Work and Part-Time School (n=20) - Work Full-Time (n=118) Other (n=27) p < .001 Number of Graduation Elec—v tives 8 Courses (n=57) p < .01 p < .05 9 Courses (n=61) 10 Courses (n=79) p < .05 11 Courses (n=104) 12 Courses (n=26) Materials Costs and Overhead Costs The variables, Materials Costs and Overhead Costs account for about eight and twelve percent of total pro- duction costs, respectively. This section is concerned with the analysis of these variables and possible positive relationships with the variable, Total Benefits. The means 77 for the component cost variables are presented in Table 4.5. As could be expected, the vocational program costs for materials and overhead at $252. and $330. are higher than the respective costs for either academic or combined program graduates. Academic graduates had the least expensive materials costs and Combined program graduates had the lowest overhead costs. The Vocational program graduates' standard deviations :flor both materials costs as well as overhead costs were notably higher than any other sub- group, and are indicative of a wide range of costs associated with specific vocational programs. An analysis of the post-high school activity groups show that those graduates who working two years after graduation appear to have had higher materials and overhead costs. Lower costs seem to be associated with either attending school or being involved in some activity other than school or work. Generally, materials and overhead costs increased with the number of courses elected for graduation. The slight dip in average costs for those graduates who chose nine courses might be attributed to the mix of academic and vocational courses chosen by this subgroup. Analysis of the relationships between the variable, Total Benefits, and the variables, Materials Costs and Overhead Costs, identified five that were significant beyond the p = .05 level. Pearson correlation coefficients were obtained on the dependent variable, Total Benefits, for 78 Table 4.5. Means for Total Materials and Overhead Costs Total Materials Total Overhead Gr°ups Costs Costs Mean SD Mean SD Overall Sample (n=331) $217 $88 $296 $95 Graduation Program Academic (n=138) 198 59 291 68 Combined (n=106) 212 75 275 80 Vocational (n=87) 252 123 335 134 Post-High School Activity School Full-Time (n=57) 201 69 289 64 School Full-Time and Work Part-Time (n=34) 173 44 276 75 School and Work (n=75) 220 80 301 88 Full-Time Work and Part-Time School (n=20) 227 90 300 119 Work Full-Time (n=118) 235 105 304 115 Other (n=27) 209 76 286 80 Number of Graduation Electives 8 Courses (n=57) 205 94 271 115 9 Courses (n=61) 194 82 266 85 10 Courses (n=79) 222 95 298 82 11 Courses (n=104) 229 83 321 100 12 Courses (n=26) 232 75 322 58 the sub-groupings of graduate programs and number of courses elected for graduation. The correlation analysis did not identify a significant relationship between Materials costs and Total Benefits for the overall sample, however, two of the sample sub-groups did register significant relation- ships. These sub-groups were Academic program graduates, 79 r = .1812, p < .05, and graduates attending school full- time, r = .2268, p < .05. An analysis of variance per- formed on the dependent variable, Total Benefits, iden- tified a materials cost effect, F(3,102) = 2.885, p = .043, for the combined program graduate. For overhead costs, the two relationships with Total Benefits that were identified by correlation analysis were for the over- all sample, r = .1002, p < .05, and the academic program graduates, r = .2607, p < .001. Significant relationships between tbtal benefits and the variables, Materials Costs and Overhead Costs are summarized in Table 4.6. Further Education Benefits The variable, Further Education Benefits, was deter- mined by aggregating graduates' responses in this category for all elective graduation courses. Graduates were asked to indicate on a six-point Likert scale the extent to which they received benefits related to further studies at college, university, trade school, or other post-high school situation. The second major section in this chapter will identify those positive and significant relationships existing between the variable, Further Education Benefits and senior high school program costs. 80 Table 4.6. Summary of Relationships, Total Benefits and the Variables Materials Costs and Overhead Costs Level of Significance Groups Materials Costs Overhead Costs Corr. Anova Corr. Anova Overall Sample (n=331) - p<:.05 - Graduation Program Academic (n=138) p < .05 p < .001 Combined (n=106) p=.043 Vocational (n=87) Post-High School Activity School Full-Time (n=57) p<:.05 - - School Full-Time and Work Part-Time (n=34) - - School and‘Work (n=75) - ' Full-Time Work and Part-Time School (n=20) - ' Work Full-Time (n=118) - ' Other (n=27) - ‘ Number of Graduation Electives 8 Courses (n=57) 9 Courses (n=61) 10 Courses (n=79) 11 Courses (n=104) 12 Courses (n=26) Total Costs The Total Cost variable was determined by adding three component costs, and this variable was studied for positive and significant relationships with the variable Further Education Benefits. Applying Pearson product-moment correla- 81 tion analysis to these two variables resulted in an r = .2888, p < .001 for the overall sample of three hundred and thirty-one graduates. Analysis of variance carried out on the dependent variable, Further Education Benefits, identified a total cost effect, F(3,134), p = .005. Further education benefits are related to total elective program costs; those graduates who have the highest level of further education benefits are also the graduates whose total costs are the greatest. Total costs and further education benefits are pre- sented in Table 4.7 for the overall sample and three group- ings of the graduate respondents. Not surprisingly, there is a dramatic decline in further education benefits from the academic program to the vocational program and also from the school oriented post-high school activity to the more work-centered activity. In contrast, Table 4.7 shows a marked increase in further education benefits as the number of graduation electives goes up from eight to twelve. The percentage difference between further education benefits as reported by academic and vocational graduates is seventy-one percent, while the total costs are only seven percent more for the academic program graduates. The low level of these benefits for vocational graduates is not surprising as relatively few would pro- bably continue with their schooling. This was also apparent for the sub—groups of graduates who were attending school 82 Table 4.7. Means for Further Education Benefits and Total Costs Groups Further Education Total Costs Benefits Mean SD Mean SD Overall Sample (n=331) 26.6 13.2 $2,487 $365 Graduation Program Academic (n=138) 32.8 11.6 2,592 292 Combined (n=106) 24.5 12.4 2,404 357 Vocational (n=87) 19.2 12.1 2,423 436 Post-High School Activity School Full-Time (n=57) 34.3 9.8 2,627 297 School Full-Time and Work Part-Time (n=34) 31.1 7.8 2,492 321 School and Work (n=75) 29.8 12.0 2,554 364 Full-Time Work and Part-Time School (n=20) 31.2 12.5 2,553 437 Work Full—Time (n=118) 20.3 13.3 2,410 367 Other (n=27) 19.6 13.3 2,293 351 Number of Graduation Electives 8 Courses (n=57) 17.0 11.2 2,120 315 9 Courses (n=61) 24.7 11.8 2,314 278 10 Courses (n=79) 25.9 11.8 2,545 276 11 Courses (n=104) 30.4 12.0 2,667 306 12 Courses (n=26) 39.3 13.8 2,841 252 full-time and those graduates who were working full-time, as reported for post-high school activity. The former indicated further education benefits at a level sixty—nine percent above the latter group, while their total costs were just nine percent more. For students electing a full course load, there were almost two and a half times as many further 83 education benefits than those taking a minimum eight electives. The equivalent increase in costs was only thirty- four percent. Understandably, these benefits are clearly related to graduation programs and post-high school activity. A correlation analysis of the three graduation programs showed‘that for both academic graduates and combined grad- uates, significant and positive relationships existed between the variable, Further Education Benefits, and total cost. The coefficients for Academic and Combined graduates were, r - .2452, p < .01 and r = .2542, p < .005, respectively. Applying analysis of variance to the dependent variable, Further Education Benefits, determined that a Total Cost effect existed for the Academic graduate subgrouping, F(3,134) = 4.492, p = .005. Analysis of the six sub-groups of post-high school activities found three significant Pearson correlation coefficients between further education benefits and total costs. Those graduates who were attending school full-time and working part-time, attending school or working equally, and working full-time had positive and significant relation- ships between this category of benefits and total costs. Their coefficients were; r = .3758, p < .05; r = .2766, p < .01; and, r = .2881, p < .001, respectively. An analysis of variance on the variable, Further Education Benefits, for the group of graduates who were working full-time, found a 84 Total Cost effect, F(3,114) = 3.899, p = .011. The final group that was analyzed for relationships between total costs and further education benefits con- sisted of graduates who had opted for differing numbers of elective courses. Significant relationships were identified for those graduates taking eight and twelve courses. Pearson coefficients for these two sub—groups were, r = .3231, p < .01, and r = .3364, p < .05, respectively, between the variables, Further Education Benefits and Total Costs. A Total Cost effect was also determined using an analysis of variance on the dependent variable, Further Education Benefits, for those graduating with eight electives, F(3,53) = 3.176, p = .031. Table 4.8 summarizes the significant relationships between the variables, Further Education Benefits and Total Costs. Instructional Personnel Costs For the overall sample of three hundred and thirty- one graduates, correlation analysis identified a positive and strong relationship between the variables, Instructional Personnel Costs and Further Education Benefits, r = .3794, p < .001. Testing for similar relationships across the graduation programs, it was determined that: Academic r = .2139, p < .01; Combined, r = .3240, p < .001; and, ‘Vocational, r = .2262, p < .035. An analysis of variance 85 Table 4.8. Summary of Relationships, Further Education Benefits and Total Costs Groups Level of Significance Correlational Anova Overall Sample (n=331) p < .001 p==.005 Graduation Program Academic (n=138) p < .01 p==.005 Combined (n=106) p < .005 Vocational (n=87) Post-High School Activity School Full-Time (n=57) School Full-Time and Work Part-Time (n=34) p < .05 School and‘Work (n=75) p < .01 Full-Time Work and Part-Time Work (n=20) Work Full-Time (n=118) p < .001 p==.011 Number of Graduation Electives 8 Courses (n=57) p < .01 p= .031 9 Courses (n=61) 10 Courses (n=79) 11 Courses (n=104) 12 Courses (n=26) p < .05 was performed on the dependent variable, Further Education Benefits, and identified an Instructional Personnel Cost effect for both the Academic Program graduates, F(3,134) = 3.673, p = .014 as well as the Combined Program graduates, F(3,102) = 4.523, p = .005. Analysis of the post-high school activity sub—groups, 'using Pearson correlation coefficients identified three 86 significant and positive relationships between instruc— tional costs and further education benefits. The groups with significant relationships were: graduates attending school full-time and working part-time, r = .3607, p < .05; graduates attending school and working equally, .3078, p < .005; and, graduates working full-time, r r .3669, p < .001. Applying analysis of variance and correlational analy- sis to groups of graduates with varying numbers of gradua- tion electives, identified four significant relationships. Those graduates who completed only eight electives showed relationships between their instructional costs and their further education benefits, using Pearson coefficients, r = .4103, p < .001 and analysis of variance, F(3,53) = 3.227, p = .030. For graduates who completed ten courses, the equivalent significance indicators were, r = .3070, p < .005, and F(3,75) = 2.830, p = .044. The relationships between instructional costs and further education benefits are summarized in Table 4.9. Materials CoSts and Overhead Costs The variables, Materials and Overhead Costs were tested against further education benefits and only three positive and significant relationships were identified. For Academic graduates, materials costs and overhead costs were both related to further education benefits using Pearson correla- 87 Table 4.9. Summary of Relationships, Further Education Benefits and Instructional Personnel Costs Groups Level of Significance Correlational Anova Overall Sample (n=331) p < .001 -- Graduation Program Academic (n=138) p < .01 p = .014 Combined (n=106) p < .001 p = .005 Vocational p < .05 Post-High School Activity School Full-Time (n=57) -- School Full-Time and Work -- Part-Time (n=34) p < .05 School and Work (n=75) p < .005 -- Full-Time Work and Part-Time School (n=20) Work Full-Time (n=118) p < .001 -- Other (n=27) -_ Number of Graduation Electives 8 Courses (n=57) p < .001 p = .030 9 Courses (n=61) 10 Courses (n=79) p < .005 p = .044 11 Courses (n=104) 12 Courses (n=26) tion analysis. The respective values were, r = .1681, p < .05 and r = .1704, p < .05. The other relationship, also determined using correlation analysis, was for those graduates who were attending school full-time and working part-time. For this subgroup, overhead costs were related to further education benefits, r = .3131, p < .05. 88 Job Benefits The variable, Job Benefits was determined from grad- uate responses in this separate category. Graduates were asked to rate those benefits related to earning money by working part-time or full-time. Each course was listed and graduates had the opportunity to indicate on a six- point Likert scale the extent to which they benefitted. This category was added to obtain total job benefits. The third major section in this chapter will identify those positive and significant relationships existing between the variable, Job Benefits and senior high school program costs. Total Costs Both correlation analysis using Pearson coefficients as well as analysis of variance was performed on the variables, Total Cost and Job Benefits for the overall sample and sub-groups of graduate programs, post-high school activity, and number of courses elected for graduation. Total job benefits and total costs are given in Table 4.10. Unlike further education benefits, it can be observed from Table 4.10 that job benefits across the many sub-groups of the sample do not differ extremely. As expected, voca- tional graduates and those graduates working full-time, even if attending school part-time, are those with the highest job benefits. It is also not surprising that the 89 Table 4.10. Means for Job Benefits and Total Costs Groups Job Benefits Total Costs Mean SD Mean SD Overall Sample (n=331) 23.8 10.4 $2,487 $365 Graduation Program Academic (n=138) 23.1 10.4 2,592 292 Combined (n=106) 24.2 10.0 2,404 357 Vocational (n=87) 24.4 10.8 2,423 436 Post-High School Activity School Full-Time (n=57) 20.8 10.7 2,627 297 School Full-Time and Work Part-Time (n=34) 21.8 . 2,492 321 School and Work (n=75) 22.8 . 2,554 364 Full-Time Work and Part-Time Work (n=20) 30.0 10.0 2,553 437 Work Full-Time (n=ll8 25.8 10.3 2,410 367 Other (n=27) 22.1 12.9 2,293 351 Number of Graduation Electives 8 Courses (n=57) 22.1 10.3 2,120 315 9 Courses (n=61) 22.7 9.3 2,314 278 10 Courses (n=79) 25.0 11.2 2,545 276 11 Courses (n=104) 24.3 10.3 2,667 306 12 Courses (n=26) 23.8 11.1 2,841 252 groups with the lowest job benefits are those where the graduates are attending school full-time. In general, there appears to be little relationship between the number of courses elected for graduation and job benefits. A correlation analysis between the variable, Job Bene- fits and total costs found a positive and significant re- 90 lationship for the overall sample, r = 1221, p < .05. A study of the possible relationships between job benefits and total costs for the three graduation programs, identi- fied the only significance within the vocational program graduates. A Pearson coefficient for this sub-group was r = .2566, p < .01. For the post-high school activity group, those graduates who were working full-time were the only sub-group where significant relationships between total costs and job benefits could be identified. An analysis of variance performed on the dependent variable, Job Benefits, found of total costs effect for the working graduates, F(3,114) = 4.092, p = .008. The Pearson coefficient for the same group was r = .2273, p < .01. Analysis of graduates electing eight to twelve courses, identified two sub-groups with significant relationships between job benefits and total costs. Correlation co- efficients for those graduates taking eight and ten elec- tive courses were, respectively, r = .3169, p < .01 and r = .2463, p < .05. For this latter sub-group, an analysis of variance showed a total cost effect on the variable, Job Benefits, F(3,75) = 4.690, p = .005. The significant relationships between job benefits and total costs are summarized in Table 4.11. 91 Table 4.11. Summary of Relationships, Job Benefits and Total Costs Groups Level of Significance Correlational Anova Overall Sample (n=331) p < .05 Graduation Program Academic (n=138) Combined (n=106) Vocational (n=87) p < .01 Post-High School Activity School Full-Time (n=57) School Full-Time and Work Part-Time (n=34) School and Work (n=75) Full-Time Work and Part-Time School (n=20) Work Full-Time (n=118) p < .01 Number of Graduation Electives 8 Courses (n=57) p < .01 9 CourSes (n=61) 10 Courses (n=79) p < .05 11 Courses (n=104) 12 Courses (n=26) .008 .005 Instructional Personnel Costs Relationships between the variables, Job Benefits and Instructional Personnel Costs were not found to be signifi- cant for the overall sample of graduate respondents. Analysis of variance performed on the variable, Job Benefits for the three graduation programs, also was unable to identify 92 any effects that could be linked to instructional costs. A correlation analysis did find a positive and significant relationship between instructional costs and job benefits for graduates of the vocational programs, r = .2186, p < .05. A similar relationship existed for the one hun- dred and eighteen graduates who were working full-time, r = .2308, p < 01. For those graduates who chose only eight courses, r = .3467, p < .005. The final relationship determined by an analysis of variance on job benefits, did identify an instructional personnel costs effect for those graduates who had taken ten elective graduation courses, F(3,75) = 4.728, p = .050. Materials Costs The variable, Materials Costs was related to job benefits for the overall sample. This relationship was determined using correlation analysis where, r = .1171, p < .05. However, applying Pearson correlational analysis and analysis of variance techniques to the three graduate program uncovered no significant relationship between job benefits and materials costs. For those graduates who were attending school full-time two years after leaving school or who chose nine elective graduation courses, significant relationships were identified between job benefits and materials costs. These were determined by correlation analysis r = .3249, p < .01 and analysis of variance per- 93 formed on the dependent variable, Job Benefits that found a materials costs effect, F(3,57) = 2.766, p = .050. Overhead Costs Overhead costs were found to be significantly and positively related, using correlation analysis, to the variable, Job Benefits for the overall sample of three hundred and thirty-one graduates. These costs were also linked to job benefits for vocational program graduates. Both relationships were determined by Pearson coefficients, respectively, r = .1498, p < .005 and r = .2352, p = .05. Virtually no relationships could be identified for any of the post-high school activity groups. For graduates elect- ing ten or eleven courses in their senior years, the var- iables Job Benefits and Overhead Costs appeared to be related. For the ten course graduates, r = .2209, p < .05, and for those taking eleven courses, F(3,100) = 5.711, p = .001. Personal Benefits The variable, Personal Benefits was determined by adding up graduate responses that rated those benefits of a personal nature. This category of benefits was defined by outcomes that made the graduate feel happier, more interesting, wiser, or more informed. The responses were aggregated for all elective courses, and the total represented 94 those personal benefits of interest in this analysis. The fourth major section in this chapter will identify the positive and significant relationships between the var- iable, Personal Benefits and senior high school program costs. Total Costs Total costs, determined by combining instructional costs, materials costs and overhead costs, were tested against the variable, Personal Benefits to identify any significant relationships. Correlation analysis between these two variables resulted in an r = .2473, p < .001 for the overall sample. Applying an analysis of variance on the dependent variable, Personal Benefits identified a total cost effect, F(3,327) = 6.607, p < .001, for the total sample of graduates who responded to the benefit survey. Clearly, for the variable, Total Costs and personal benefits, a significant relationship does exist. Personal benefits, unlike job benefits, tend to decline as graduate programs move from an academic to a vocational focus. However, these benefits appear to be consistently higher than any other category of benefits. It is interest- ing to note that personal benefits also drop off evenly as post-high school activity takes on a greater work emphasis and less school based activity. Finally, Table 4.12 shows that as the number of graduation electives increase, there 95 Table 4.12. Means for Personal Benefits and Total Costs Groups Personal Benefits Total Costs Mean SD Mean SD Overall Sample (n=331) 38.6 11.2 $2,487 $365 Graduation Program Academic (n=138) 40.8 11.0 2,592 292 Combined (n=106) 37.9 11.3 2,404 357 VOcational (n=87) 36.0 10.8 2,423 436 Post-High School Activity School Full-Time (n=57) 40.4 10.0 2,627 297 School Full-Time and Work Part-Time (n=34) 42.6 11.2 2,492 321 School and Work (n=75) 38.9 10.8 2,554 364 Full-Time Work and Part-Time School (n=20) 38.9 11.8 2,553 437 Work Full-Time (n=118) 37.1 11.6 2,410 367 Other (n=27) 35.9 11.3 2,293 351 Number of Graduation Electives 8 Courses 32.4 8.5 2,120 315 9 Courses 33.7 10.1 2,314 278 10 Courses 37.8 10.6 2,545 276 11 Courses 42.7 10.1 2,667 306 12 Courses 49.4 10.6 2,841 252 is a corresponding increase in the personal benefits derived from the graduation electives. For those graduates who were on an academic program, both analysis or variance and correlation analysis uncovered significant relationships between personal benefits and total program costs. Respectively, these were F(3,134) = 4.282, p = .006 and r = .3099, p < .001. Combined program 96 graduates were also found to show positive and significant relationships between personal benefits and total costs, r = .2640, p < .006. No such relationships were found to be significant for the group of eighty-seven graduates on the vocational program. Among those graduates who were attending school full- time and working part-time, the variables Total Costs and Personal Benefits were related. Analysis of variance was performed on the variable, Personal Benefits, and a Total Cost effect was identified for this group of graduates, F(3,30) = 4.396, p = .011. A Pearson correlation analysis on the same variables resulted in an r = .5084, . p < .001. The only two other subgroups in this category to register significant relationships were those graduates who worked and attended school equally, r = .3071, p < .005, and the small group of twenty—seven graduates who neither attended school nor worked since graduating from high school, F(3,23) = 3.628, p = .028. No relationships were identified for those sub-groups based on the number of electives chosen for graduates. This was actually the situation for all component costs as well; no relationships were identified between personal benefits and either instructional costs, materials costs, or overhead costs according to the number of graduation electives. Personal benefits' relationships with total costs are 97 summarized in Table 4.13. Table 4.13. Summary of Relationships, Personal Benefits and Total Costs Level of Significance Groups Correlational Anova Overall Sample (n=331) p < .001 p < .001 Graduation Program Academic (n=138) p < .001 p < .006 Combined (n=106) p < .005 Vocational (n=87) Post-High School Activity School Full-Time (n=57) School Full-Time and Work Part-Time (n=34) p < .001 p < .011 School and Work (n=75) p < .005 Full-Time Work and Part—Time School (n=20) Work Full-Time (n=118) Other (n=27) p < .028 Number of Graduation Electives 8 Courses (n=57) 9 Courses (n=61) 10 Courses (n=79) 11 Courses (n=104) 12 Courses (n=26) Instructional Personnel Costs A correlation analysis of the variable, Instructional Personnel Costs and personal benefits for the overall sample disclosed that a significant relationship did exist, 98 r = .2514, p < .001. Three positive and significant re- lationships were found between costs and benefits for academic and combined program graduates. An analysis of variance performed on personal benefits identified an instructional cost effect for academic graduates, F(3,134) = 2.870, p = .039. A Pearson correlation for the academic graduates was r = .2623, p < .001. The third relationship was for combined program graduates, determined by correlation analysis to be r = .2381, p < .01. For the post-high school activity sub-groups, positive and significant relationships were identified for all except those attending school full-time and those in the small group of twenty who attended school part-time and worked full-time. The significant relationships were between personal benefits and instructional costs for: full-time students working part-time, r = .4900, p < .005; gradu- ates attending school and working equally, r = .2689, p < .01; graduates working full-time, r = .1696, p < .05; and, those graduates who were neither working nor attending school, r = .3563, p < .05. The relationships between the variables, Personal Benefits and Instructional Personnel Costs are summarized in Table 4.14. 99 Table 4.14. Summary of Relationships, Personal Benefits and Instructional Personnel Costs Groups Level of Significance Correlational Anova Overall Sample (n=331) p < .001 -- Graduation Program Academic (n=138) p < .001 = .039 Combined (n=106) p < .01 Vocational (n=87) Post-High School Activity School Full-Time (n=57) -- School Full-Time and Work Part-Time (n=34) p < .005 -- School and Work (n=75) p < .01 Full-Time Work and Part-Time School (n=20) -- Work Full-Time (n=118) p < .05 Other (n=27) p < .05 Number of Graduation Electives 8 Courses (n=57) 9 Courses (n=61) 10 Courses (n=79) 11 Courses (n=104) 12 Courses (n=26) Materials Costs Materials costs were related to personal benefits according to a Pearson correlation analysis, r = .1182, p < .05. The only graduate program for which significant relationships were found was the combined program. An ana— lysis of variance performed on personal benefits generated 100 evidence of a materials cost effect, F(3,102) = 3.3470, p = .019. The Pearson correlation for the same variables in this group of graduates was r = .2425, p < .01. For the sub-groups of graduates who were working and attending school equally and who were working full-time, relation- ships were identified between personal benefits and mater- ials costs. These were r = .2357, p < .05, and r = .1561, p < .05, respectively. Overhead Costs For the overall group of graduates who responded to the benefit survey, no relationships were determined between personal benefits and overhead costs. Three relationships were identified for the graduation program sub-groups. Academic graduates showed a positive and significant relationship between personal benefits and overhead costs, r = 3315, p < .001. For this same sub-group, an analysis of variance on the variable, Personal Benefits showed an overhead costs effect of F(3,134) = 4.169, p = .007. A similar effect was also identified for the combined program graduates, F(3,102) = 2.689, p = .050. The only other significant relationship for any of the sub-groups was found for those graduates who attended school full- time and worked part-time, r = 4130, p < .01. 101 Summary This chapter has applied general statistical analysis and Pearson product-moment correlation analysis to all benefit and cost variables included in the study. Also, analysis of variance was employed in examining total cost effects on the variables, Total Benefits, Further Educa- tion Benefits, Job Benefits, and Personal Benefits for the overall sample. An analysis of variance was also per- formed on Graduation Program and Number of Graduation Electives sub-groups, testing for program cost effects. These analyses were directed toward the central hypothesis, that: Educational benefits are positively related to educational costs. The following four research hypotheses were tested, in order: 1. Total Educational Benefits are positively related to senior high school program costs. 2. Total Further Education Benefits are positively related to senior high school program costs. 3. Total Job Benefits are positively related to senior high school program costs. 4. Total Personal Benefits are positively related to senior high school program costs. A general statistical analysis determined that benefits derived from graduation courses differed, and these are summarized in Figure 4.1. 102 Production costs were also calculated and are illustrated in Figure 4.2. From these summary graphs it is possible to obtain a clear appreciation of the relative differences in magnitude between the total cost and total benefit components. 100 90 80 70 60 50 40 30 20 10 PROGRAM BENEFITS IN RATING POINTS For instance, while the ['1 89.0 F 38.6 H 26.6 F 23.8 Total Further Job Personal Benefits Education Benefits Benefits Benefits Figure 4.1 Summary of Total Benefits 103 2600 4 F1 2488 2400 r 2200 - 2 00 - 1975 0 ‘1 1800 r 1600 L 1400 - 1200 - 1000 ' 800 600 ~ 400 ’ 200 . [1217 [1 Total Instructional Materials Overhead Costs Personnel Costs Costs Costs 296 Figure 4.2 Summary of Total Costs benefits for the overall sample do differ, with personal benefits at 38.6 and job benefits at 23.8, these are not nearly so divergent as the production costs, where mater- ials account for only $217 and instruction, $1,975. 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These differences are relatively consistent within the sub- groups and seem indicative of "producfl'differences. Grad- uation programs, post-high school activity, and the number of graduation electives in particular, clearly show that there are differences in magnitude and substance that must be considered in an analysis of the high school "product." The first section of this chapter was concerned with testing for positive and significant relationships between the variable, Total Benefits and educational costs. Those determined to be significant beyond the .05 level are summarized in Table 4.16. It can be observed from this table that for both total costs, as well as for component total costs, several significant relationships were identi- fied with the variable, Total Benefits. The second section in this chapter involved analyzing those relationships be- tween the variable, Further Education Benefits and high school program costs. These have been summarized in Table 4.17. The third and fourth sections of this chapter were concerned with the variables, Job Benefits and Personal Benefits, respectively. The results of hypotheses testing relative to these two variables and the cost vari- ables are presented in Tables 4.18 and 4.19. 106 v 4>oz¢ uomuum uooo a mvuocoo « no. v a sewunnmuuoo vacuuuwcmum c wagesoo x «auoz x x aumou coonuo>o x mumoo mandamus: «X CX X X X X cX «X X mumOU Ho:20muom ocs Hmc0auosuumcn .x «x x x x ax ax mumoo Home? muquocmm COuuoosom umzuusm NH Ad ad a a O 3 m3 3m 3m m 00> EGO o4 mo>fiuooam Edumoum >uw>wuo< zoazlumom Emumoum :oHunsonuo Haauo>o 1| . :‘II-Idl l' li“!d‘lll.,l|‘,. Jfilufl‘: Ifilqulg' lllqili'll. Iii .l‘. ‘ mummy N mammnuomhz mo xunaasm .ha.v mafia? x x mumou ommzum>o x a x mumoo mamfiumumz X cX X X X X X cX mumOU. amazemuom 0cm guacauoauumcu «x «x «x x «x x x 4x .x mumoo Hauoe muauocmm Hmooe Na x AA ca a a o 3 a: :m 3m m 00> soo 04 mo>wuomum Emumoum auw>auo< :muzluuom Emumoum scaamsomuo Hamum>o ‘Illl‘nIiI-T 1 ‘4: .... I5. lFII‘ i- Inlllull. I Illlll. ... 110‘ 1|I M....,(.1Il1|.l.‘l mumma A mammnuoa>= uo >un5§zm .oa.v manna .mc. v a <>oza uommum umoo o monocmc . .mo. v m :ofiumamuuoo acnOHuwcmum a mmuocoo x "xmmfl x «x «x mumoo cmozuozo x x «x x mumoo mdnwuousz x x x x x «x x mumoo amazemuom tsp do:0wuosuam:H «x x .x x «x «x mumoo Huuoa muwuocmm Hosanuom NH Ad ad a m o 3 a: 3m 3m m 00> 300 ca mm>auomam EuHaOHQ xua>wuo< gmfizuuaom Edumoum :Oquosomuo Hamuo>o 1... I 1! IIIILIIIII‘I. 0.1.5-!!! II II‘ '1' (ii-In a‘l : A 1. 1:..- all \ .III I- ..1..I|u.‘lnl.l...l mumoa v mammnuomaz no mumassm .ma.v manna x x x mumoo omonum>o «x x x mumoo maadumunz .x x x x . mumou AmocOmumm ocm «occauosuumca «x x «x x . x mumou Hobos oudumcom non NH AH ca m a O 3 m3 3m 3m m 00> 300 04 mo>quomum Emumoum sua>quo< zmaznuuom Enumoum cofiuusomuo Hanum>o 1 1 In: ' mumma m mumocuomaz no husasam .ma.v manna 108 The final tables in this chapter summarize those hypotheses tested involving all cost and benefit variables considered in this study. Two hundred and forty hypo- theses were tested using Pearson correlation analysis, while one hundred and forty-four analyses of variance were performed on dependent benefit variables in an attempt to identify cost effects. Table 4.20 is a summary of significant cost-benefit relationships for the overall sample and three subgroupings. Table 4.21 presents the same information in a more detailed format. From these tables it is possible to observe that some benefits and costs' relationships tend to be more related for certain subgroupings of the sample. For instance, no significant relationships were identified for the small group of graduates who worked full-time and attended school part- time. This was also true for those graduates who had elected 11 or 12 courses for their graduation. Compared to these, several subgroups displayed consistently frequent relationships between costs and benefits. This can be seen for groups such as the academic graduates, combined graduates, graduates working and attending school equally, graduates working full-time, and those graduates who had elected either 8 or 10 graduation courses. It is also possible to recognize some trends or patterns of relationships for specific sub-groups. For example, one would expect job benefits to show more re- lationships for Vocational program graduates or those grad- 109 mummzuomaz goonmmnuwm mo. v m mfimwnuomaz udoooquom~m Edumoum Emumoum ceauoaoouo Hamuo>o mumoo aua>auo< smaniumom “It In" . 4!!!! H1 I... l 1.2-Ill «ll-1.-.! . Int-1.“. £75 . )z'flb. .lzvi Ill mum09..momozu0Q>= mo aunasdm Amumcoo .o~.v manna 110 mo. v & ocunooon mommzuoax: mouocmo x “ouoz on CA S mafinmcoaumamm H8009 Hacum>o munoo omocum>o mumoo mauwuoumz mumoo Amocomuom pom Hm:0wuosuumcn mumoo Acuoe announsm m x x mumoo noozuo>o v x x x x mumou mamfiuwumz e x x x mumoo Hm::0muom can AccoHuoouumsu w x x x x x x mumou Hobos muquocom Anaemumm A H ...4 OOO O OOO O MOI-0 O MOO O HOO N. de 0) OOO O ”HO 4‘ NON F MOO m MNH 0‘ (OWN A FINN r-i mm O OHO H O ONH ('1 pm O O N M .... M O M m N M M v m x x . x mumoo onosum>o m x x x mumou mdmfiumun: v x x x x mumoo . Amccomumm tom Hoseauosuumcm m x x x x x mumoo Hobos muwuocom non mumoo omoguo>o mumoo manwuoumx x mumou Hmccomumm pom macaquosuumCH n x x x x x x x mumoo Hmuoa muwumcmm cauumooom Hosanna H XXX x mumoo nmozum>a mumou manwuoumz aumou fiascomuum pct Hucoduosuumcm x auuoo Houoa muaumcom dance 0': OMN X X X X X X XXX X NH HM OH O O o 3 M: 3“ 3m m 00> ECU 0‘ Mama-0H0 mm>mu00HmIEdumoum aum>wuo<.mmd=numom Enumoum :Oauasomuo Humuo>o I'lu- 1“ kiln! mamas .uomocuoasa no auaassm nonamuma .H~.. magma 111 uates working full-time, and this confirmed by the results shown in Table 4.21. One would also anticipate fewer relationships between job benefits and costs for Academic program graduates, and this also was observed in the data. From both the actual number of relationships as well as the patterns between sub-groups, it would appear that educational benefits are positively related to educational costs within the parameters of this study. CHAPTER V SUMMARY AND CONCLUSIONS Summary This study has been designed to test the relation- ships between high school graduation program benefits and their production costs. The approach is from a "product" perspective and relies on techniques drawn from Systems Analysis, Marketing Research, Economics, and Finance. Schools are considered to be similar in many respects to factories and service-producing enterprises that are also comprised of workers, buildings, equipment and materials. The study assumes a multi-faceted composition of the com— plex educational product, and tests for positive relation- ships between benefit components of the product and pro- duction costs as determined by cost accounting methods. The current literature in four areas was examined. First, objectives held for schools are nowhere clear and educators do not agree on desirable outcomes. As such, identifying the school product is not simple but does seem to point in the general direction of defining the educa- tional product at a consumer level. Lester Ruth's taxonomy 112 113 of educational benefits affords a means for identifying the product in this study. A second focus in the litera- ture centered on how the educational product could be measured. Traditional letter grades and achievement scores, while appropriate measures for certain specific objectives, were not deemed as appropriate as follow-up studies and graduate opinion for obtaining a measure of the product consumed during the senior high school years. A third area of interest in this study related to the costing of the educational product. The literature re- vealed a trend toward the increased implementation of a cost accounting approach to supplement the traditional methods of financial or general accounting. More and more, one is likely to find instructional budgets broken down to show expenditures in greater detail and directly assoc- iated with the distribution of resources to specific school functions. The final area examined in the literature is cost-benefit or cost-effectiveness analysis. Contem- porary thinking of the respective components as well as their interrelationships provided essential background for studying how cost is specifically related to various benefits in this study. For the purpose of the study, sixty graduates from the 1979 graduating classes at each of seven Okanagan high schools were randomly selected as a survey sample to determine their perceived benefits from each course com- 114 pleted during their senior high school years. Three hundred and thirty-one usable responses were then costed on a course-by-course basis according to a number of cost factors unique to their program courses. The study and survey instrument were designed to focus on further education benefits, job benefits, and personal benefits. Graduates rated their perceived benefits for each course completed and this was done using a six-point Likert scale for each of the three benefit categories. Course costs, determined on a cost accounting basis, were similarly classified into the three categories of instructional personnel costs, materials costs, and overhead costs. Costs and benefits for each course were then aggregated into totals for each graduate. The overall sample of three hundred and thirty-one graduates was reclassified into three sub-groupings according to graduation program, post- high school activity, and the number of courses elected for graduation. The central hypothesis, that educational benefits are positively related to educational costs, was tested for all benefit and cost variables. The Pearson product- moment correlation coefficient was employed in testing for significance at the .05 level between two hundred and forty cost and benefit variables. Analysis of variance was performed on one hundred and forty-four benefit variables in testing for significant cost effects beyond the .05 level. 115 The four research hypotheses examined in these tests were: 1. Total Educational Benefits are positively related to senior high school program costs. 2. Total Further Education Benefits are positively related to senior high school program costs. 3. Total Job Benefits are positively related to senior high school program costs. 4. Total Personal Benefits are positively related to senior high school program costs. Conclusions Total Education Benefits Total education benefits were positively and signifi- cantly related to total costs for the overall sample, for graduates on all three high school programs, and for approximately half of the sub-groups according to post- high school activity or graduation electives. Many other positive and significant relationships were identified between total benefits and component cost variables, particularly instructional personnel costs. From the overall and graduation program results, one can conclude that those graduates with the most perceived benefits had the most expensive programs. Total benefits were also significantly related to instructional costs, and it must be concluded that this component cost is to a large extent 116 indicative of total benefits. Materials and overhead costs are relatively minor determinants for total bene- fits. Further Education Benefits Further education benefits, comprising thirty per- cent of total benefits, were notably related to the instructional personnel costs. These benefits were posi- tively and significantly related for nine of the fifteen graduate groupings considered in the study. They were somewhat less related for the total costs; the vocational graduates who reported low benefits in this category were one of the groups not significantly related. Again, materials costs and overhead costs did not appear to have more than a minor impact on further education benefits. From these records, it is reasonable to conclude that most graduates, excluding those on the Vocational program, derive further education benefits in proportion to their total costs and in particular to their instructional COS tS . Job Benefits Job benefits accounted for twenty-seven percent of the total benefits and had fewer significant relationships than any other benefit category. It was not surprising that these benefits were highest for Vocational program 117 graduates and those graduates working full-time. It was also observed that these two groups were the ones that had the significant cost-benefit relationships. These job benefits were also highest for graduates who had selected 10 elective courses for their graduation and job benefits actually dropped off as the number of courses increased. This pattern was not evidenced for either further education benefits or personal benefits. For the group of graduates attending school full-time two years after graduation, their job benefits were significantly related with materials and overhead costs. Overall job benefits were also signifi- cantly related to both materials as well as overhead costs. An examination of the job benefits relationships point toward the conclusion that these benefits, while reflecting cost-benefit links for some sub-groups, are generally more related for vocational program graduates and those working full-time. There is also a stronger association with materials and overhead costs. Personal Benefits Personal benefits constituted the largest portion of total benefits, making up about forty-three percent of the total. These benefits were related to total costs for the overall sample and to most cost categories for Academic and Combined program graduates. Virtually no relation- ships were identified for the Vocational program graduates. 118 Similarly, no significant relationships were found for any of the sub-groups according to number of graduation elec- tives. For those graduates who were working and attending school full or part-time, significant relationships were identified between personal benefits and costs. There were also the two groups who had the highest personal benefits. One can conclude that personal benefits for some groups of graduates are linked to their program costs, including instructional, materials, and overhead costs. There are other groups who show no relationship between these benefits and program costs. Discussion Even the most complicated school system can be viewed as a conversion process by which certain inputs are con- verted into outputs. This study has examined educational benefits and their production costs, and then tested for significant and positive relationships between costs as input and benefits as output. The actual processes of converting cost inputs into benefit outputs has not been a concern of this study. Using Lester Ruth's Taxonomy of Educational Benefits as a basis for three benefit categories, the study esta- blished that clearly these benefits varied in degree from one graduate to another. Subgroupings of graduates accord- ing to the type of graduation program, post-high school 119 activity, and the number of courses elected for graduation, revealed that in terms of total and categorical benefits, graduation "products" varied greatly. The application of cost accounting techniques to costing out each graduate's program made it possible to classify specific costs into the categories of instructional personnel costs, materials costs, and overhead costs. It was not surprising to find that instructional personnel costs were consistently in the eighty percent of total costs range; however, the relative consistency of mater- ials and overhead costs across all graduation programs was not expected. For individual graduates, particularly those on a heavily vocational-oriented program, course costs would vary considerably. To some extent these unique graduate situations were averaged—out in determining totals, but it is likely that these costs were important in the analysis of benefit relationships. The benefits obtained from the graduate survey were treated as dependent variables, while program costs were tested for relationships or effects on the benefit variables. Statistical analysis identified many positive and significant relationships between benefit and cost variables. A marketing approach was applied in this study and graduates were grouped as "consumers" into graduation programs, post-high school activity groups, or groups based on the number of electives in a graduation program. By 120 examining these different groups' results and relation- ships, it was possible to tie some specific responses and patterns to them. The disaggregated approach designed into this study, while requiring much effort to identify individual course costs and benefits, has facilitated the isolation of group results and relationships. The data base was in fact built-up, rather than being obtained by averaging, and probably lends itself to more valid and accurate conclusions. The early studies, involving aggregation of data at a level far above the graduate, would have difficulty offering the same substantive base for analyzing data, effects, or relationships. Implications for Future Research This study has shown that the educational product is composed of differing educational benefits and these are related in some positive ways to production costs and specific cost categories. It has also established that different groups of consumers have varying cost-benefit relationships. The disaggregation techniques applied in this study have essentially enabled some of the educa- tional benefit parts to be linked to some of the educational cost parts. Future research can reach further into the Taxonomy of educational benefits proposed by Lester Ruth and applied 121 in this study. Specifically, the categories of Further Education Benefits, Job Benefits, and Personal Benefits can be broken even more into sub-benefits that can in turn be tested against other more detailed factors. For instance, individual courses or subject areas across cer- tain predetermined groups could be tested for positive relationships with costs which have also been categorized using cost accounting techniques. This study has indicated that the variable, Job Benefits is not related to any of the cost components for either Academic or Combined program graduates. Economic conditions today and job preparation programs would both encourage the pursuit of further research on the topic of job benefits as well as demand that such a consideration include the associated cost factors. It can be concluded from this study that high schools are graduating quite distinct products with very unique combinations of courses and some other school experiences not considered in this investigation. Certainly, future studies could focus on a particular group of graduates and determine what input, including costs, is most important to the production of their benefits. Another area worth investigating is, assessment of the long-term benefits from high school courses. This study surveyed graduates two years after high school and in many cases the individuals are still changing their life 122 patterns, to such an extent that present perceived bene- fits may not endure over a longer term. A longitudinal study of graduates would add a new dimension to under- standing benefits and how they relate to cost and other inputs. Perhaps in summary, the greatest implication for future research arising out of this study is the unlimited potential for understanding the educational product by adopting a product-centered, production approach with all the best interests of the consumers in mind. BIBLIOGRAPHY Abram, Marie J. The Perceptions of 1978 and 1979 Graduates. Bowling Green: Professional Development Center Net- work, West Kentucky University, Spring/Summer 1980. Aleomoni, L.M., and Yimer, M. "An Investigation of the Relationship Between Colleague Rating, Student Rating, Research Productivity, and Academic Rank in Rating Instructional Effectiveness." Journal of Educational Psychology. 1973. pp. 274-77. Alexander, Karl L., and McDill, Edward L. "Selection and Allocation Within Schools: Some Causes and Conseq- uences of Curriculum Placement." 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APPENDICES 130 APPENDIX A LETTER OF AUTHORIZATION SENT TO SCHOOLS 131 scnoot DISTRICT NO. 23 (CENTRAL OKANAGAN) 01311001330011 SECONDARY SCHOOL PRINCIPALS . flan H. G. Pendharkar Superintendent of Schools 81-03-30 b-------w-‘- - _ .f .....n assesses PROJECT - cannon-:5 1979 cu. m, n This is to inform you that I have authorized Mr. H. Marshall to conduct a doctoral research project that will involve over four hundred 1979 Graduates from School District 423. While the primary purpose of the study will he to fulfil Mr. Marshall's PhD requirements. it is also quite likely some of the information generated will be of interest to School Principals and Counsellors. A random sample of 1979 Graduates will be contacted regarding their perceived benefits from specific courses and subject areas. These benefits will then be statistically considered relative to actual achievements, present activities, course costs. school program taken, and other variables. The data gathering will involve survey instruments, personal interviews, students record cards (PR), and District financial records. - This study should not place any extra demands on your school, however, should Mr. Marshall require some assistance or information from you relative to your 1979 Graduating Class, I would ask that cooperation be given wherever possible. 1:32 APPENDIX B FIRST SURVEY LETTER SENT TO GRADUATES 133 {103.6 0‘. 3011004 iausagés Telephone (504) 860 8888 ‘ ' School Oasmcl No. 23 Telex 048.5103 (Central Okanagan) OFFICE OF THE SUPERINTENDENT 0F SCHOOLS'. 1940 Haynes Road 14. G. Pendharksr ' KELOWHA, B C., Canada Superintendent of Schools V1X 5"? File No. 05-1 A4211 27, 1981 Dear As a 1979 Graduate you are important to me! To complete requirements for my Ph.D. in Education. I an undertaking a research study involving selected high school graduates from School District 023. I also hope the information you provide and the thesis itself may assist the School District in reviewing its programs and course offerings. Your name has been chosen as part or the survey sample; not all your former classmates are being asked to participate. Your response is particularly needed to make this project worthwhile. Since graduating almost two years ago, you have now had the opportunity to use some of the knowledge and skills learned from your high school coerses in work. college, and other personal settings. I am interested in knowing which courses you think have been of most benefit to you in the past two years and the type of benefit involved. Space has also been provided for additional comments you wish to make regarding your courses. Please take the few minutes required to complete this survey. To assist you, i have listed your Grade ll and Grade 12 courses on the survey form. After completing, return the fern as soon as possible in the post-paid envelope to the Office of the Superintendent of Schools. Your cooperation in this survey will be very such appreciated. Sincerely. ' - Authorized by: e ’I' ' $4.21... L... . ga—l—"7 5' Marshall H. G. Pendharkar . Supervisor of Instruction Superintendent of Schools HH/ed 134 APPENDIX C REMINDER NOTE SENT TO GRADUATES 135 81-05-11 Dear Graxate: Help!!! I am looking for missing qxestionnaires! If yox've retxrned yoxrs. yox've already helped and don't need to read the rest of this note. - \ My message may be a little ‘Qé- hard to read becexse the "u? is missing on my type- writer. My sxrvey is like the typewriter -- a little .... hard to comp e a - .~ becaxee year are Yox are only one gredxate, bxt one gradxate can really make a difference stt as only one key has made a disaster oxt of this message! Hoxld yox p1ease' mail yoxr completed qxestionnaire today. THANKS 136 APPENDIX D SECOND SURVEY LETTER SENT TO GRADUATES 137 Board cl School IruSlees Telephone (50‘) 860-8888 School Disarscl No. 23 Telex 048 SlOJ (Central Okanagan) OFFICE OF THE SUPERINTENDENT 0F SCHOOLS 1940 Haynes Road 14. G. Pendharkar KELOWNA. BC . Canada Superintendent of Schools le 5117 File No. 05-1 Dear ' In case you did not receive my earlier letter. this second copy of the questionnaire is being sent. Your opinions are particularly important to me in completing this research study for my Ph.D. in Education. Your response actually represents several members of the 1979 Graduating class and I would like to include your opinions in my study. Please help by mailing your completed questionnaire tOdC’e . I have enclosed for your convenience a post-paid envelope addressed to the Office of the Superintendent of Schools. Thank you for your help. Sincerely. Authorised by: 4-!‘1 ‘" k. H. Marshall n. G. Pendharkar Supervisor of Instruction Superintendent of Schools rel/ed 138 APPENDIX E SAMPLE COMPLETED SURVEY FORM 139 GMAT? I979— A TO! [N- U! STUDY fi*— .- sonnet. DISTRICT an (CENTRAL mustang rum: or rm: rououmr. acnvxnrs have no mzm rnmnu tuvoevso sxnl since cmrxom more l/l new mm mm or'calsrs mm acrrvxmzn. 1» SCHOOL. rust-rm: scrum. nut-rm; [SJ/ mourns roll a Joe D In some. ran-rm: C] venues. ran-71m: {3“- amen: HIIK‘I! or YOU! MIG" SCIICDI. COURSES HAW. PT" 0" W‘ST was!" 1'0 you 5!” anATIa‘. am "I WHAT HAYS? "195?. CONS 10!! m 0" l0)! “MD! 1. ‘NO GRADE 12 COWS!!! COWLEY“. m INDICATE m Tilt SI! POINT SCALES THE DELZRI‘E or IFREI IT DEIIW'O. roe wsrm. A CWISI PAY WW5 GREAT BENEFIT UNIT! ”DUR‘IIICI EDUCATION“, "0 I‘I'NIZI'IT I08 'EHPIDYNITW'. AND “(3) I'LHM'IT were 'HJ’SOHAL'. ANTI"?! CWPSI'. HAY "Mil? N.) PHlITIT TM “'0'!le FWJCATIM'. “PM? BTIIEI‘IT TOR 'EHHDYHCNT". AND ((‘NSIHRMHJ: H) M'NH'IT UNDER 'PERSONAL'. I! All IIUIRIISTED ll WING THE TYPE AND DEGREE (l' BENEFIT DERIVED in ”GI m mm. 8037!?! 81K! GMT!“ fUIlTNCI WAT] ON WIDYNDIT 'Ilm If III“ N'- ” m. I? ’III A! “mes. 'IMI" f“ C ‘r '0‘. (R. J, (Ml.- suvlra canvas is “I. II is a. mam m-v' no use '2'. ”$3.. 7” .-. sum 0 O m m “I m ‘ ”I'D. ‘ 3:39"!"' I; I I 11:13:11: C." T 0" . ‘ - .I ‘- -“--- nr.l.l$li ll vuutlsu 12 551M. smarts ii minim. sauce-non 11 ...—- .0 .- .- ‘3. 0"! ‘3 “m “ [{w\ H “>75...“ ("$.13 A! l H "~v.:- '4: w \‘ {is H .s. .10»; w 44m IS soLcu-c bu! low P 603,? [ll-4mg! flaw 15.8.T,[5vmo.bq:4‘ . mam: you me COMPLETIMS rut wtsr'lomaxat amp/144414.’ “44"“me "22‘4"” ...... ‘" " ‘ "‘ ......” .1- ALL? m am 453%“— 44 «WW mm. 4....» LagflL— ”(151% W” ..- 1.71.9“ 1% {Wig “W :4'J44.z41/ 441.; «Ag If) / 4114/ 411/11 1 [4 l..i{£ZLiQLW_M ’ 0". ' , l a ' ...J OLAUAI u. a.“ 44/12; . , z 4 , “x L .M 14 lb; lay/m- L £5.11 w , , J“, who“ may .1194» “(tel/vol 4241 m fins/m]. eta/ploy“! 140 APPENDIX F SAMPLE DATA RECORDING SHEET 141 I l C‘ A I 'v‘ (.f. I: (J‘n' ' - \ code, name. L Pecans» ABlLl‘tY 12./Q... Afieumauce. sr/Ti VII/n.1,. L... 5'11__ ”V1.1. on... Call 6 Cos‘ls '3'. G EE£F$T {1 10599.3 Met Oval“ 4c Q 5 4- G ,l ISL Cl 12 00‘ f 5 4 G 3 6'37 H n 00:: j: 0r ’56 \72. In H.101 P, l l 4]] no 3m 3"567 g 43:," 15c. 32. m m E 4 3 C." en |% 14 \al C‘ G c 4 cm 'H M 30\ '3 G G G rm l?. 15 Son [1 C: G C. m 12 \3 -505 .1 3 ’5 6 a“! :9. 3‘1 am A 3 3 6 23°: 20 33 qoa F 3 5 6 303 'm 31 6“ A 6 G G The 55' 45 701 2?: 74' asSq 305 NM“, out (um we} “a ”‘6' .39 wflm.» 4:34.31 ‘7 142 meJJbe APPENDIX G HIGH SCHOOL COURSE CODES 143 ENGLISH EN 11 ll 12 HR 11 LIT 12 SOCIAL§ SS 11 GEOO 12 HIST 12 EC 11 1A2 11 CIV 12 001 002 003 004 101 111 121 151 141 191 PHYSICAL EDUCATION IE 11 CR 12 PE 12 glrnzrlrgcs ALG 11 ALO 12 CON MA 11 TR BA 11 GEOH 12 SCIEKCE BI 11 PI 12 Ch 11 CH 12 IH 11 PH 12 E SC 11 GILL 12 FOR 11 AG 11 A0 12 201 211 291 301 302 511 312 30} 401 402 411 412 421 422 451 452 491 441 442 ECRLIGH LANGUAGE FR 11 FR 12 D GER 11 GER 11 GER 12 D S? 11 SP 11 SP 12 INDUSTRIAL EDUCATION DRAFT 11 DRAFT 12 DRAFT 11/12 00H 11 C0! 12 MIL 11 MIL 12 TLAST 11 MI 11 H! 12 EL! 11 ELX 12 TECH 11 TECH 12 AERO 11 AERO 12 AE 11 AI 12 HOME Economics TD 11 TD 12 TX 11 TX 12 HOT 11 HIS 12 CC 12 501 $02 50} 504 505 506 507 508 601 one 603 611 612 621 622 625 631 632 641 642 64) m 691 692 693 694 701 702 711 712 721 751 741 LIFE II THE 70.791 ]J44 BUSINESS EDUCATION For. TI 11 TI 11 Par. 2! 12 SH 11 SH 12 BI 11 8K 12 08 11 Ol 12 HK 11 OP 11 0? 12 00 12 ACCT 12 ACCT 11 DH 12 DC 12 DH 12 ART!HUSIC[2RAHA ART 11 ART 12 DP 11 DP 12 AD 11 IA 11 AD 12 OR COHH 11 ACT 11 ACT 12 ST CR 11 TH 11 DA 11 BA 12 H0 11 H0 12 IS 11 IS 12 CHO 11 CHO 12 GUITAR 11 TILE STUDIES 1' ones 11 once 12 801 802 805 811 .812 821 822 851 832 841 851 852 861 871 872 901 902 903 904 905 906 907 908 911 912 915 914 921 922 925 924 925 926 927 928 991 992 951 932 APPENDIX H COURSE COST CALCULATIONS 145 Course Cost Calculations Total Costs: Instructional Personnel Costs Materials Costs Overhead Costs Instructional Personnel Costs 1.1 Instruction--Teacher's Salary ll? Scale and Experience Class Size 1.2 Fixed Charges--.05 x Instruction 1.3 Administrative Costs Per Student 7 1.4 CounsellingiCosts Per Student 7 1.5 Clerical Costs Per Student 7 Materials Costs 2.1 Texts Costs of Texts Per Course (depreciation 4 four years) 2.2 Course Materials—-Actual Per Course Overhead Costs 3.1 Facilities--Per sq. ft. cost calculated for each area of the school X (X) (actual room area) (.02) (7) (Class size) 3.2 Equipment-—Using standard course equipment lists and costs with 20 year depreciation (X) (.05) (7) (Class sire) 146 3.3 Operation——Heat, light, power, water, sewer (special area) (school costs) (total school aran—(7) (class size) 3.4 Custodial-—Total district c—1 Budget $2,325,600 District hours Hours per school (special area) (school cust cost) (school area) (7)'(class size) 147 APPENDIX I SAMPLE TEACHER SALARY WORKSHEET FOR COURSES AT KELOWNA SECONDARY SCHOOL 148 ac HoourJédcm mfimflm "L SALARY WORKSHEET 149 5.9‘Q3‘Sl)’: B .... to t .LMLM! 13.2133 SAMSEJL. ' -(Agu ._ 30 i/7 s-‘S 3%)26 l3“) saga * as ‘/7 c-a\ "725 .‘53" ' GthIZ at so :/7 =5 —\'1 25%?) 134- Hu » «V4 4/7 s-s 3076! '33 NANA ~ 2.: «V7 s-m zs'na ‘43 Etna .. \0 V7 548 25%?) '37) ER: ‘2 "P 25 '/‘7 5'8 25"‘3. I41 7‘“ u, M 3a 1/7 5~8 33377 104 9E“ - \0/3 3/7 5 -. r7373 ca Am!) «» 3| 1/7 5—4 ”7.8') l35 Gan/.2 o- 22 u/7 5 -4 “331 new . mm“ H» too/4 4/7 5-2'3 35913 :41 Gina ~ 32. ([7 s-c. 3|633 97 31‘?- 30 ‘/7 5-6 2.533 )03 A! \2. <~ \5’ u]? 5‘-\7 aswa 948' nmz . “I3 an s-r; 25am 3:? a“ '- 24, \/'7 . S-\7 25““3 '55 BK \) 4 aq ‘/7 547 95WW3 '33 31.2. J :35 V7 5...? gsqqg Mr‘l as u ~ \22/4- 4/7 5-5 9076) ‘7 Gt :2 < m \/7 5-4, V188" 203 8:50! . r7 ‘/7 5-4 N38“! m7 LII «>- 27 ‘/7 5-4 ”33“ log HK n T 53/2 3]; 5-5 2.533 H7 '4‘“ ~~ 30 1/7 s—c 21633 I03 me u -* 93/3 ° 3/7 5—6 2|633 H2- 95“ ‘ ‘C \/7 s-o 164m MG 5”“ " 3“ '/7 s-o "mm '10 ‘12": H t 65/2 1]? S-S 20%| “I em *~ 55/a 2/7 sm asm m: ‘3‘“ ‘” ‘2- '/7 547 35MB 3°“ "2“ q) 535/3 3/7 5-3 no.7 ‘H 0w“ 1» Ella 9/7 5-\+, gsqq's '23" ...-‘3” " 9° ‘/7 542 359% we 2’“ ‘a b “74/3 3/7 s. ‘2 25%;) '2' 09“ ‘L qs/a a]? 542 aswqa KI :13.sz 237/2. :17 s-s, [3.7“ .35 APPENDIX J SCHOOL SUPPORT COSTS PER STUDENT 150 School GE Area (FTZ) 64525 Enrolment 593 Admin $ 119 Counsel $ 45 Sec $ 74 Costs In Dollars Per Student GP 67909 612 95 60 74 KLO 73623 681 84 99 74 KSS 185310 1602 69 84 74 Inst .05 Inst 1/7 (Admin Coun Sec) 151 MB 69139 651 83 88 74 OKM 61745 606 87 71 74 72002 534 79 94 74 APPENDIX K TEXTBOOK CATALOGUE USED FOR PRICING TEXTS 152 ...- ...-— “...-“..-.-- —-—.- MINISTRY OF EDUCAIION. SCIENCE AND 'IIZCIINOIJOOY 95% TEXTBOOK_ CATALOGUE; THIS BOOKLET IS A PRICE LIST ONLY AND IS NOT TO BE USED AS AN ORDER FORM. PLEASE RAISE ORDERS IN SAME SEQUENCE AS CATALOGUE LIS I‘ING. AND QUOTE CATALOGUE NUMIIERS. ‘ PUBLICATION SERVICES BRANCH VIctorIa, B.C. m» I. I. “Wm. him. to the On" “at fluent“ "and; hrIdudOomol Dwain“ I'D I L.,“..- __-_.___._ 153 APPENDIX L TEXT COSTS FOR PRESCRIBED AND AUTHORIZED COURSES DEPRECIATED OVER FOUR YEARS 154 En 11 En 12 55 11 PE 11 P. Ty 11 Sh 11A Sh 113 Sh 12 M! 11 GB 11 GB 12 BR 11 BR 12 Acct 12 OO 12 OP 12 DH 12 W: 11 (J) Wt 11 (CH) fit 11 (DH) Lit 12 Man 11 rd 11 Pd 12A rd 120 T: 11' Tx 12A 1: 120 CC 12 His 12 Dr! 11/12 H§1 11/12 H: 11/12 Con 11/12 llsctx 11/12‘ TEXT--POUR YEAR DEPRECIATION Prescribed Text 64.59 6.70 1.24 4.41 7.60 0.45 0.45 5.55 1.54 0.90 3.62 4.77 1.70 3.53 0.30 1.05 6.36 3.52 1.00 5.14 1.73 3.00 3.76 3.95 2.39 3.23 3.67 3.75 3.66 2.01 6.54 155 Supplementary First Class 6 3.25 2.77 15.06 2.20 .47 3.29 4.76 10.36 0.30 2.24 3.90 9.59 11.52 0.22 5.13 3.79 7.05 3.00 0.75 APPENDIX M MEMO TO SCHOOL DISTRICT STAFF OUTLINING NON INSTRUCTIONAL COST NEEDS 156 The following cost needs should be placed in perspective. Educational costing is a difficult business, particularly when it becomes specific, and this prdbably accounts for the fact that very little "course" costing has been attempted. With this in mind and also knowing my Doctoral Committee is understanding as I attempt some original work, my own ex- pectations for very precise and readily available data are limited accordingly. This said, and fairly confident that I have a good handle on Instructional Salaries (typically 50% of course costs), let me elaborate my needs. For Fiscal 1979: Schools: GE, GP, KLO, KSS, MB, OKM, & RS l. Capital--As of December 31, 1979 1.1 Site--Assessed Values by School 1.2 Buildingse-Assessed (insurance?) value by school and by school area if possible 7 i.e. KLO gym, KSS Auto Shop, OKM HEC,’ RS art, etc. 1.3 Equipment--Assessed value by school and by school area if possible i.e. MB shops, GP commerce, etc. 2. Other Instructional--January l, 1979 to December 31, 1979 2.1 Aides--Salaries by school and subject area. 2.2 Supplies--B—3 by school and area 2.3 Secretarial Salaries-~By school 2.4 Texts-~By school 3. Plant Operation--By school 4. Plant Maintenance--By school 5. Administration--District staff 1979 6. School Services 6.1 Transportation—-By school 157 7. Fixed Charges—~Fringe Benefits (pension, dental, etc.) per teacher 8. Debt Retirement——By school Note: Some of the above categories may not be most approp- riate for British Columbia Educational Costing. I am certainly open to suggestions that would improve the costing format. 158 APPENDIX N CALCULATION OF SCHOOL ADMINISTRATION AND COUNSELLING COSTS 159 ADMINISTRATION COSTS Admin Hours[Total Hours (Pay Category)[¥ears Experience) Admin Costs/Time: GE GP KLO KSS OKM RS Coun. Hour§[Total 21/24 35/40 14/48 48/48 26/48 18/25 33/48 42/75 Cat/Yrs (6/18) (5/14) (6/24) (5/30) (6/19) (6/18) (6/14) (6/28) Class 33 + 34 + 37 + 94 + 37. U! 33 + 29 + 15/24 30/40 14/48 26/48 (5/23) + 15/24 (5/22) (6/15) (5/28) + 48/48 (6/15) + 26/48 (6/21) + + 15/25 (6/12) 30/48 35/75 (6/16) (6/26) COUNSELLING COSTS Hours (Pay Category/Years Experience) Counselling Costs/Time: GE GP KLO KSS OKM 18/24 15/40 (6/2) 10/48 (5/6) + 12/24 4/8 (4/13) + 25/40 (6/18) + 15/40 (4/0) + 10/40 (6/24) + 12/48 (5/28) + 6/48 (4/5) + 6/48 (6/7) + 18/48 (6/31) + 24/48 (4/3) + 70/48 (S/max) + 24/48 (6/12) + 27/48 (6/7) + 14/48 (6/17) + 16/48 (5/15) 10/48 (6/15) + 10/48 (6/21) + 10/48 (6/19 + 24/48 (5/6) + 24/48 (5/5) + 12/48 (6/6) + 12/25 (6/12) 6/25 (5/18) + 6/25 (6/12) + 12/25 (6/4) + 12/25 (6/2) + 8.5/25 (6/12) 30/48 (6/14) + 30/48 (5/13) + 18/48 (5/8) 25/75 (6/28) + 15/75 (6/26) + 60/75 (6/3) + 52/75 (5/13) 160 Admin Costs "K" Forms: GE 34085.25 + 20720.63 + 5844.25 + 6498.25 + 3590.75 = 70,739 GP 31863.88 + 26104.5 = 57,968 KLO 18168 + 12476.29 + 8766.38 + 7181.5 + 10772.25 = 57364.42 KSS 25993 + 46679.75 + 37950 = 110,622.75 MB 37918.32 + 15930 = 53848.32 OKM 37702.88 + 14925 = 52627.88 RS 29492.03 + 12915 = 42407.03 Counselling Costs: GE 16224.75 + 10216.5 = 26,441.25 GP 8470.13 + 17953.75 + 5508.38 + 5055.25 = 36,987.51 KLO 5984.58 + 6498.25 + 2284.88 + 3118.25 + 1072.25 + 8421.5 + 17328.67 + 12814.37 = 67,222.75 KSS 17953.75 + 10816.5 + 10380.5 + 6000.25 + 37906.46 + 14363 + 14032.13 + 14363 + 8664.33 = 134,479.92 MB 6238.32 + 6894.24 + 10613.28 + 9706.08 + 23555.32 = 57007.24 OKM 17953.75 + 16245.63 + 8766.38 = 42965.76 RS 9575.33 + 5745.2 + 16932.8 + 18021.81 = 50275.14 161 APPENDIX 0 CALCULATION OF SCHOOL EQUIPMENT COSTS 162 Coors. Blue Book 01/02 Jul 02 Jul 79 Sq. Ft. Eqqu— Fqulp- Equip- ment ment mvnt 11754.05) EN 704 2,610 1,070 13 MA 784 2,610 1,070 13 SS 704 6:363 ‘zggg 11 Lang 704 2,610 1,870 ‘6 Art 1000 21,460 15,329 109 Music 1344 9,700 6.929 49 Band 1344 19,500 13,929 99 Drama 1344 14,950 10,679 76 Bus Ed. 096 40,030 29,070 200 5° 3‘ 11 12”} 27,500 19,641 140 7° 31 12 1232 3 70 Ch 11 1232 72 Ch 12 1232} 20,300 20,271 145 73 Ph 11 1232 21,191 15,136 100 54 Ph 12 1232 5,764 4,117 29 03 as“ 12”} 0,030 5,736 “I 201 G 12 1232 41 flEch 1400 17,495 12,496 09 TX 1400 20,397 14,569 104 Comb 1400 36,993 26,424 (109) PB 1915 34,420 24,591 00 IE Wd 3024 49,941 35,672 255 n+1 2160 02,020 50,506 410 F1! 2160 59.590 42,564 304 PM/Hotto 2520 06,027 61,440 439 Dr! 1000 15,670 11,199 00 Bus Ed 096 40.030 29,170 200 Cafet- 3024 131,660 94,043 671 eria 163 696 ¢_. + 4 classes 902 2.. + 4 classes 1014 2. + 4 classes 370 7564- 9 4 classes 504 206 4—on1y 12's APPENDIX P SCHOOL ASSESSMENTS 1979 AND 1980 164 ooo.mn«.n can.an hvn.hu vna.v ooh.-v mvv.o~v.n mu .5 ~an.o~ oom.-h.n onu.un «mn.n~ ohm.- nah.mmu nnw.noo.~ 1x0 .0 oon.mao.v va~.a Hon.nm~ uao.vu~.m n! .n ann.n~ ooa.n-.h now.hu oom.ou nen.oou nno.oon.u vom.omm.h mm: .v oo~.vnn.n h~o.n~ coo.nu nvo.~n ono.~ao uam.ono.n Qua .n cow.vow.n ~n«.nn vso.ou oum.d~ nmo.oon ano.noa.n no .N coo.mou.n nvo.u mnn.o« nvv.n ~qa.vnn vua.vom.n nu .« ooaa .on sat onh.nv ~wo.ma hnv.m o.n« o~m.oav ama.onn.n a: .n anv.~n onu.- ona.on onu.vn ~.o mov.mam nom.on~.n Ito .0 mnn.o~ o.w whv.nvn osv.u~h.n I! .n ow~.m~ ovw.o~ ano.aa asa..o~ m.v~ oov.m~o.« nuc.ah«.aa «mu .v onn.o~ hno.on h~H.on «.hn noo.ooo hum.voo.v 04: .n vn~.ov «um.oa noo.n« ..nu omn.nnh oo~.~nw.v no .u ooa.a aom.~a «an.» «.ou aon.n~o pha.~oo.n no .« «sue? ucsuo unaucsh I» mouxosan ucso Hum unsanwaum noduoauuacou noon .o~ as:u.¢s~u> uses-onus.- 165 APPENDIX Q CUSTODIAL COSTS AND FACILITY DEPRECIATION FOR SUBJECT AREAS IN EACH SCHOOL 166 n... 53 an a: «an 8n a: 0: n3 n: 93 62 so .... as an h: an nun «nu 8n av" 03 and «3 mod nun 00 3 as we and Zn can can 53 van vow mum and 3m one h: as .- ca 34 «on new «em «on nan om.— rnu cod can «an no on man we «nu «an can 3N ban «on son «an a: 2k «nn n2 3 on! . cu n3 «an awn an one con man boa o3 vow n3 m3 an an 3 ca av.— non «a «R nnv own van a: nun God a: 03 e. U 6313938 >u430su 2.3 ooo.n~n.~ 70 i _ 62.36 3.2 .22 62.... can; emu; «no; .738 moofi 033 312304. New.” nmwd can; van.” 02 03.02 36 on In a ovm.~ 2.03 Man; can; 600‘ Hem." ~ma.~”m¢m.« 2."; m8.~ ovm.~ mom; baa QQQJA. no.0 .3 wow :80 can; «mu; n3.~ . nnm.~ v38 can.” HSJHZEH as.“ on»; 3n.“ «no.» on“ $043 no.1 av 30 I! . now; 033 p.36 53." v-.v £04 03432.; ~34 2.5; cow; moo; ~3 anoinm 3.3 ona acorn and ”av; new; 303 308 ON; ~ao.~ com; «2; on; can; 5:; «our. «ma Etna." :4 ..v «no a 0:; verin 30.... «3.... new; ochJ one; .2..« non.” 3o; 0:; 03.." 93 93.00 n1. «.3 «no 8 ova; 2n.n 3o.~ can; :0; ~0m.~ nomimsvoé 03.“ 52.4 oz”..— ovoJ ova 8~.3 «En 00 new. 8 4 .. 1 wood 94.3 on: co: nuOn 32.. 8: «n3 com Munro wood v2. used-5m has :8 use! uusun 3:4)..— uusnn usual ‘00: u an an I... ones: and I09- «sIuOI «to 080 32. 0:8 as. an. ...—9!: 04135 «gm cuss ca 25 use?!» new coin-Usual. huqfiusm was 3.8 «succuld 167 APPENDIX R CUSTODIAL TIMES AND SPACES FOR ALL SCHOOLS IN THE CENTRAL OKANAGAN SCHOOL DISTRICT 168 REPORT OF SCHOOLS CHECKED No. School Square Preaent 13.000 15.000 16.500 Chiei‘s Feet Houre Sq. Ft. Sq. Ft. Sq. it. Time Added 01 Mount Boucherie Secondary 79.139 46 49 42 30 44 02 George Elllot Secondary 64.525 40 40 34 31 36 03 George Pringle Secondary 61.909 44.5 42 36 33 110 04 Kelowna Alternate Secondary 5.200 -- -- -- -- -- 05 Kelowna Secondary 165.310 120 114 99 90 112 O6 E.L.O. Junior Secondary 13.632 40 45 39 36 42 01 Dr. Knox Junior Secondary 61.090 39 3E 33 30 36 OS Okanagan Hlealon Secondary 50.667 44 36 31 26 34 09 Rutland Junior Secondary 66.256 40 42 36 33 110 10 Rutland Senlor Secondary 72.002 56 44 36 35 40 11 Sprlnqvalley Junior Secondary 64.737 42 45 35 31 36 12 A.S. Hatheeon Elementary 31.600 l6 l9 17 15 16 13 Hollywood Road Secondary 50.014 32 31 27 24 32 14 Bankhead Elementary 31.600 16 19 11 15 16 15 Belqo Elementary 20.810 ll 16 15 14 16 16 -- -- -- -- -- -- ~- 16 -- -- -- -- -— -- -- 19 Caeoreo Elementary 12.344 6 I 7 3 6 20 Central Elementary and Demar 36.764 24 23 20 16 24 21 Bellevue Creek Elementary 21.530 12 13 11 10 12 22 Deflart Elementary -- -- -- -- -- -- 23 Davle Road Elementary 7.012 -- -- —— -- 3 24 Dorothea walker Elementary 33.000 16 20 ll 16 16 26 Eaet Kelowna Elementary 9.500 -- -- -- 4 -- 21 Elllaon Elementary 9.150 -- 5 4 5 26 Ellleon Primary 6.208 -- 3 l 3 30 Glenmore Elementary 34.921 24 21 19 11 19 32 Glenn Avenue Elementary 16.696 6 lo 9 6 10 33 Glenroaa Elementary 30.400 24 19 10 15 16 34 Gordon Elementary 6.794 -- 7 2.5 2 -- 35 Black Hountaln Elementary 29.220 20 16 16 14 16 36 -- -- -- -- -- -- -- 37 nudeon Road Elementary 26.420 16 16 14 13 16 30 Lakevleu Elementary 29,175 24 16 16 14 16 40 Hartln Elementary 16.609 9 ll 10 9 11 169 APPENDIX S ENERGY EXPENDITURES FOR SCHOOLS 170 hour . 9°: . H. HAKShall .M..G:¢ves .................... eeeeeeeeeeeeeeeee MEMORANDUM Subiict ..................... . .... ENERGY EXI‘FJ‘XD [TUBES . . _‘ Place: Administration 0: flee... Due:9§flu§‘Y.23A.1?ag, .......... The energy costs (September 1978 - June 1979) for the selected schools are as follows: Mount Boucherie George Elliot George Pringle Kelowna Secondary E.L.o. Secondary Power Pucl (gas) Water Power Fuel (gas) Water Power Fuel (gas) Sewage Water Power Fuel (gas) Sewer water Power Fuel (gas) Sewage water Okanagan Mission Secondary Power Fuel (gas) water Rutland Senior Secondary Power Fuel (gas) Water 171 529.264 12.955 466 $12,075 10.197 608 516.413 12.737 1.853 655 516.366 31.048 6.065 884 512.873 11.823 3.529 680 510.992 10.773 2.031 511.496 14.691 420 APPENDIX T SAMPLING FORTRAN CODING SHEET 172 .w v m P; N . .m 6.0.»... . «mm 90 9d 9. .P v 70.0 m in m. m H m 'Ufie' 0. "(F1 6' 79 “WW“ r er" W” {—01 173 APPENDIX U SAMPLE SCHOOL COST DATA RECORDING SHEET 174 .. -6 3' -6 -9 '3 6- -6 -3 .. -- 9- 8- -- 0- -0 6- -6 -0 -- .9 6- "n“ u: «a -- -- -- -- -- .. -- -- -- -- -- .. -- .n .3 ... .. .. -- -- a” -- 3.. cu o~ can ou ca and n- on -- u. n- u- an o~ and ma on no” on on and u- ou a- an. o~ o~ SSH on on and n- c- u- u- u- .. cu on sea an o« no“ on ou “a“ u- o« a- pan .a on _ .uu o~ .H man u. -n -- u- u- u- an .a uan .. u. u- u. o- a- on .H and vuo : a _ n- cu .H I an" u~ a» nan .. u- .. nu ma can an GA and n- .1 u- o~ on mad nu. on ea or“ a. nu _ nvu no on ~o~ an SE ..a «a a” no” an ea «a» on ca "a” on ea emu an» an _ «A one .6 ea o¢~ «a . on ~o~ an en 6.“ «~ .~ ~w~ an cu «pa on ca «ma ou ea one an. n a” _ and -u u- -- u- I -- u- -- n- u- u- a u- u- u- u- u- -u -- on a and «no a- a~ _ and u- c- u- u- u- -u u- u- u- u- n. u- no -- u. an -u una -u co .. nag . an .6“ an a on” v. a nun .. u- u- an a gag a“ a o- .u m and -n a .. «am mu m and an a Sad o. n mh~ an . a Spa .n n no” «N n u~d u~ a on” u- n -- Ada u- on pou .. no -u n- -o u- a" .. noa an n. ova u- u- .1 a- u- u- u- nu .. .6. «a am can bu nu V on“ u- -u -- u- -u u- u- o. -- "a cu «an .. u- u- -u a- nu sou an n. e and -u u- u- u- u- n- u- u- -- -- -- a- .a c- -- u- n- -u can n” Sn nan ow nu cu“ an nu mn~ -- -- us nu an 6.” cu .H a.“ u- -o u- u. nu .. no. n on n on p." on n nnu .n n n- u- o- -- on n no“ o~ .H a." u- nu .. u- n u- no. pm on God an on so“ an ca nna .a on can «a nu and «a o« “an pa on and an on on“ no. .a ”MS a“ .S ~63 ad a" and .N _ on vo~ .« .a mag SN .a no" he an -- an .« ana an. o x a o _ x . u o w x a o u x _ H o _, a H o x u o r a e-uaou .euoocum wou eueou eeusou adolem 1375 APPENDIX V SAMPLE COURSE COSTS FOR SCHOOLS 176 Sample School Cost Data Recording Sheet: School: 455 (44 Couraoa) Subject No. 10 Claaa(esl Faclllty bhvnluuu1t '0‘ 6"“ -310 “LP COCt/Studont 1 S2124y c21. Art. 52122140 40 11 511 15 1.11 .47 10.14 5.40 1.14 117 154.45 En 12 451 14 1.15 .44 10.40 5.71 1.20 141 140.05 55 11 414 14 1.74 .54 12.44 4.74 1.42 111 144.55 74 11 505 14 7.51 1.11 24.55 17.51 2.44 104 141.20 ca 12 44 2 5.2 1.42 11.14 14.41 1.45 125 147.45 410 11 251 5 1.12 .47 10.74 5.51 1.24 125 141.25 410 12 222 101.4 1.14 .47 10.42 5.41 1.14 141 100.05 0.4. 12 44 142 1.74 .57 12.54 4.40 1.41 171 217,15 7: n. 11 9) 14142 'J.74 .56 12.41 6.72 1.41 160 200.00 .4 11 211 144 4.55 4.04 15.00 4.16 1.71 136 174.40 01 12 104 1.5 4.24 5.01 24.54 11.24 2.17 144 225.40 00 11 207 11101144 5.25 5.57 72.14 5.50 2.00 154 117.00 :0 12 141 112 4.45 7.15 22.54 4.71 1.41 114 145.10 70 11 111 111214 5.24 5.77 22.15 5.14 1.57 115 177.55 p“ 13 14 3 7.21 11.11 11.54 12.54 2.72 155 214.75 45: 11 45 2 4.05 4.25 21.57 10.51 2.10 . 112 170.40 0401 12 21 1 4.51 4.54 25.24 11.70 2.44 141 140.05 40 11 21 1 4.52 .42 21.10 11.70 2.44 177 217.45 40 12 141 1 5.74 .91 11.54 17.54 1.45 245 110.25 2: 11 110 1.212 1.25 1.74 12.14 4.01 1.24 110 147.50 74 12 57 2 1.05 1.41 11.10 5.45 1.15 125 141.25 04: 11 27 1 1.22 1.70 11.51 5.75 1.22 105 142.25 4 04: 11 17 5.12 . 7.70 14.55 5.20 1.51 147 207.15 Ger 12 14 4.21 1.25 21.02 11.17 2.15 201 245.15 Sp 11 22 1 1.55 2.05 14.44 7.11 1.45 154 155.40 59 12 12 1 7.25 1.41 24.44 11.04 2.74 244 112.10 0 50 11 20 1 4.15 2.10 14.11 7.42 1.44 171 211.55 0144 12 51 112 2.47 .51 5.51 5.15 1.04 124 142.20 0400 12 74 112411110111 1.15 .50 11.11 4.02 1.24 151 152.45 111 12 12 1 7.25 1.04 24.11 11.04 2.74 142 751.10 014 12 10 1 4.70 1.10 24.52 15.44 1.24 410 442.50 Law 11 157 2.1 2.77 .41 5.21 4.54 1.05 125 141.25 40 11 24 1 1.41 .54 12.00 4.52 1.17 155 154.75 a: 11 11 111 5.41 .44 14.44 10.05 2.12 217 251.45 04444 11 50 2 4.44 1.20 17.42 4.45 1.45 145 144.45 0441: 12 02 2 5.11 1.41 20.71 5.54 2.01 177 217.45 Cat 11 100 114 15.45 12.75 44.71 10.17 4.14 145 224.25 044 12 74 1.1 20.47 11.12 72.12 21.74 4.47 155 214.75 H41 11 115 214 12.15 21.04 55.52 21.71 4.54 200 242.00 411 124 24 1 10.04 17.41 45.14 17.54 1.77 155 104.75 4 15 1 14.07 27.47 74.70 24.71 4.01 244 252.40 a: 11 110 5 12.77 15.55 40.14 22.44 4.40 115 171.75 a: 12 14 2 14.75 21.11 45.51 24.47 5.54 154 155.40 414 11 100 4 5.44 12.14 42.44 17.24 1.47 115 172.55 Ela 124 11 1 21.51 27.44 54.54 15.14 4.21 115 142.15 4 12 1 20.04 25.11 44.44 15.51 7.54 245 115.45 rv 11 14 1 7.05 4.54 11.17 12.44 2.44 100 144.45 104: lhflfl 24 2 20.07 11.15 44.44 15.52 7.54 701 245.15 4: 11/12 11 2 17.01 24.40 40.51 10.44 4.40 172 212.40 70 11 250 12 4.55 1.15 24.14 12.51 2.41 174 174.40 " ‘2: 154 : 20.20 14.45 52.04 71.15 4.54 112 170.40 ’ cc 12 121 4 -7.41 .41 24.71 11.41 2.44 141 222.05 404 11 15 1 4.21 .44 24.44 14.70 1.05 155 214.75 75 12 44 211 5.47 .45 14.44 10.20 2.14 141 201.05 1Q7'7 L "11111111111111111111111“