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1984

Selected Educational Indicators for Monitoring the Primary-School System,

Edith G. Marshalleck Andrews University

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Marshaileck, Edith Geraldine

SELECTED EDUCATIONAL INDICATORS FOR MONITORING THE PRIMARY- SCHOOL SYSTEM, JAMAICA

Andrews University Ed.D. 1984

University Microfilms International 300 N. Zeeb Road, Ann Arbor. Ml 48106

Copyright 1984 by Marshaileck, Edith Geraldine All Rights Reserved

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School of Education

SELECTED EDUCATIONAL INDICATORS OR MONITORING

THE PRIMARY-SCHOOL SYSTEM, JAMAICA

A Dissertation

Presented in Partial Fulfillment

of the Requirements for the Degree

Doctor of Education

by

Edith Geraldine Marshaileck

July 1984

Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. SELECTED EDUCATIONAL INDICATORS FOR MONITORING

THE PRIMARY-SCHOOL SYSTEM, JAMAICA

A dissertation presented in partial fulfillment of the requirements for the degree Doctor of Education

by

Edith G. Marshaileck

APPROVAL BY THE COMMITTEE: //

Chairman: Robert J. Cruise of Education

Committ ^ F tjtc n e r 3/, n s - j Committee Me Bernard M. Lall Date Approved/'

Committee flllejnb^-: Mapon) J. Merchant

Guest Examiner fpbm School of Education: Wilfred W. Liske

External Examiner :YjCameron Lam be

Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. © Copyright by Edith Geraldine Marshaileck, 1984 All Rights Reserved

Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. ABSTRACT

SELECTED EDUCATIONAL INDICATORS FOR MONITORING

THE PRIMARY-SCHOOL SYSTEM, JAMAICA

by

Edith G. Marshaileck

Chairman: Robert J. Cruise, Ph.D.

Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. ABSTRACT OF GRADUATE STUDENT RESEARCH

Dissertation

Andrews University

School of Education

Title: SELECTED EDUCATIONAL INDICATORS FOR MONITORING THE PRIMARY-SCHOOL SYSTEM, JAMAICA

Name of researcher: Edith C. Marshaileck

Name and degree of faculty adviser: Robert J. Cruise, Ph.D.

Date completed: July 1984

Problem

Since the 1960s there has been increasing interest in the develop­

ment of social indicators, educational indicators being an important subset

of these. Studies in the U.S. and Europe have sought to (1) establish

a conceptual framework for educational indicators, and (2) identify indi­

cators useful for economic planning and monitoring the state of education.

The need for these indicators in developing countries has also been

identified.

The researcher sought by (1) a correlational/predictive study

and (2) an exploratory opinionnaire to validate a list of indicators for

monitoring primary education in Jamaica and guiding financial choices.

1

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Method

Utilizing scores from three batteries of the 1980 Common Entrance

Examination (CEE) to high schools and a profile of pupil personal and

school variables, canonical and discriminant analyses were applied to

data from a sample of 802 pupils drawn from a stratified sample of schools,

in three . The strata were urban, rural, and most

and least successful in securing high-school places based on CEE per­

formance. Opinionnaire responses were secured from 177 primary-school

teachers on a list of selected indicators.

Results

The canonical analyses identified several inputs as correlating

significantly with pupil achievement including: (1) percentage of trained

teachers over a three-year period; (2) sessions attended 1978/79; (3)

parent's socioeconomic status when introduced into the analyses; (4)

principal's administrative experience (negative relationship); (5) higher

grade at which CEE was taken; and (6-7) grade teacher's experience and

qualifications. The four highest rated indicators by the teachers were

overcrowding, trained teacher/pupil ratio, efficient principal and index

of malnutrition.

Socioeconomic status and higher grade levels in urban areas and

higher percentages of trained teachers in rural areas were chief among

the distinguishing variables identified by discriminant analyses.

Conclusions

The researcher proposed a number of indicators set in a systems/

economics/time perspective. These included: (1) percentage of male/

female pupils in the age cohort attending 90 percent of sessions shown

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teachers; (3) standardized test results; (4) primary-school completion

expectancy rate; and (5) enrollment projections. Other indicators were

discussed, e.g., overcrowding and teacher/pupil ratios. Recommenda­

tions were made.

Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. TABLE OF CONTENTS

ILLUSTRATIONS ...... vii LIST OF TA B LE S ...... v iii ACKNOWLEDGMENTS ...... xi

C h ap ter I. INTRODUCTION ...... 1

Social Indicators ...... 1 Educational Indicators ...... 3 Educational Indicators—Further N eeds ...... 4 Statement of the P ro b lem ...... 6 Purposes of the S tu d y ...... 6 Significance of the S tu d y ...... 7 H y p o th e s e s ...... 8 List of Indicators ...... 9 Definition of Term s ...... iG Eleven Plus (11+) Exam ination ...... 10 In d ic a t o r s ...... 10 Primary-School System ...... 12 Secondary-School System ...... 12 S y s te m s ...... 13 Triennial Examinations— Primary and All-Age Schools, Jamaica ...... 13 Delim itations ...... 14 Assumptions ...... 14 Organization of the S tu d y ...... 15

II. REVIEW OF RELATED LITERATURE ...... 16

Indicators—Other than Educational ...... 16 B a c k g r o u n d ...... 16 Economic In d icato rs ...... 17 Demographic Indicators ...... 19 Social In d icato rs ...... 20 Educational Indicators ...... 22 Studies Aimed at Identifying Indicators: Input/Output Educational Studies ...... 25 Outcome In d icato rs ...... 31 Criteria for Selection of In d icato rs ...... 31 Economic Considerations for Educational In d ic a to r s ...... 34 Educational Indicators: A Comprehensive W o r k ...... 40

iii

Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. Literature Related to the Variables under S t u d y ...... 49 Sex, Age, Achievement ...... 49 Numbers of Years in S chool ...... 52 T e a c h e r /Schools Differential Effects ...... 54 Educational Televisio n ...... 56 School Libraries ...... 58 Socioeconomic Status: Classification I n d e x ...... 58 Literature on Jamaican Education Relevant to the S tu d y ...... 59 The Common Entrance Exam ination ...... 59 Correlates of Achievement in a Common Entrance-Level Examination ...... 64 Smaller Studies ...... 71 Towards Indicators in the Jamaican Educational S y s te m ...... 73 Quantitative Inform ation ...... 73 Educational Television: Jam aica ...... 75 School Libraries: Jamaica ...... 76 S u m m a r y ...... 77

III. METHODOLOGY ...... 80

O v e r v ie w ...... 80 The Correlational/Predictive S tu d y ...... 80 Selection of Sample S ch o o ls ...... 81 Description of Sample S chools ...... 83 Sampling of P u p ils ...... 88 Data Cathering— Correlational Study ...... 91 Obtaining the Quantitative Indices: C rite rio n V a ria b le s 1 - 4 ...... 92 Obtaining the Quantitative Indices: P re d ic to r V a ria b le s 1 - 1 6 ...... 92 Qualitative D ata ...... 94 Categorization of the Predictor V a r i a b l e s ...... 95 Rationale for Selection of the V a r i a b l e s ...... 95 Environmental Factors to Be Considered ...... 96 Strength, Relevance, and Degree of Differen­ tiation of Certain Variables of the S tu d y ...... 96 The Exploratory S tu d y ...... 97 Hypotheses and Statistical Analyses U sed ...... 98 Hypotheses 1(a)-1 ( c ) ...... 100 Hypotheses 2(a) — 2 (d ) ...... 100 Hypothesis 3 ...... 101 Hypothesis 4 ...... 102 Hypothesis 5 ...... 102 Hypothesis 6 ...... 103 Hypothesis 7 ...... 103 Hypothesis 8 ...... 103

iv

Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. Analytical Methodology ...... 103 Pearson Product-Moment C o efficien t ...... 104 Analysis of V arian ce ...... 104 Canonical C orrelation ...... 105 Discriminant A nalysis ...... 106 Analysis of Teacher Responses by the Categorical Scalings M o d e l ...... 107 Data A nalysis ...... 108 The Family of Indicators ...... 108

IV. FINDINGS OF THE STUDY ...... 109

Results—Correlational/Predictive S t u d y ...... 109 Hypotheses 1 (a )-1 (c ) ...... 110 Hypotheses 2(a )-2 (d ) ...... 111 Hypothesis 3 ...... 115 Hypothesis 4 ...... 122 Hypothesis 5 ...... 124 Hypothesis 6 ...... 126 Hypothesis 7 ...... 127 Hypothesis 8 ...... 129 The Exploratory Study ...... 131 Results of the Opinionnaire ...... 133 Additional Indicators Provided by Teachers ...... 137 Factors Contributing to CEE Success as S u p p lie d by P r in c ip a ls ...... 138 Summary of the Findings ...... 138

V. SUMMARY. CONCLUSIONS, AND RECOMMENDATIONS ...... 142

S u m m a r y ...... 142 B a c k g r o u n d ...... 142 Methodology— Correlational Predictive A nalyses ...... 145 Survey Methodology ...... 147 F i n d i n g s ...... 147 Conclusions ...... 149 Im plications ...... 156 C o m m en ts ...... 157 Family of Indicators ...... 158 Indicator 1— A Context/Leading In d ic a to r ...... 159 Indicator 2— A Process/Contributing In d ic a to r ...... 160 Indicator 3— A Output/Lagging In d ic a to r ...... 161 Other Indicators ...... 162 Recommendations ...... 164

v

Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. APPENDIX A—Sample Pages from 1984 Economic In d ic a to rs ...... 169 APPENDIX B—Johnstone (1981) Selected F o r m u la s ...... 171 APPENDIX C—McGuire-White Social Class I n d e x ...... 180 APPENDIX D— Performance of All Schools in C E E ,T h re e P arishes 1979 183 APPENDIX E— Performance of All Schools in C E E .T h re e Parishes 1980 189 A P P E N D IX F— CEE A w ard s 1979 and 1980 as Percentage of Pupils Enrolled in Grades 4-6—Ten Best Performing Urban and Rural Schools ...... 195 APPENDIX C— Details of School Sample Drawn, Urban (Most and Fewest A w a r d s ) ...... 196 APPENDIX H— Details of School Sample Drawn, Rural (Most and Fewest A w a r d s ) ...... 1S8 APPENDIX I—Common Entrance Score Card ...... 200 APPENDIX J—Socioeconomic Status— Categories 1-3 201 APPENDIX K—Examination Class List ...... 204 APPENDIX L—Sample of Questionnaire with Accompanying L e tte r ...... 205 APPENDIX M—Additional Indicators as Suggested by Teachers ...... 210 APPENDIX N— Principals' Observations on Factors Influencing Performance in the Common Entrance Examination ...... 213

BIBLIOGRAPHY ...... 216

vi

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Figure 1. Educational Outputs and Examples ...... 35 2. A Framework for the Development of Indicators of Education Systems ...... 43 3. Schema for Indicators Developed by W rite r ...... 165 4. Lorenz Curves Measuring Inequality of Distri­ bution of Enrollments Across Grades at the First-Level— El Salvador and Nicaragua, 1965 ...... 172

vii

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1. Categories of Educational Indicators ...... 24 2. Major Studies of Teacher Quality and Class S iz e ...... 26 3. Major Studies of Teacher Quality and Class Size— Frequency Count of Input Variables' E ffe c ts ...... 29 4. Selected Outcome Indicators and Possible Approaches for Measurement of these Outcome Indicators ...... 32 5. Results of Educational Production Function Studies for Poor C o u n tries ...... 41 6. Summary of Education Variables Used in Selected Comparative Education Studies ...... 45 7. Summary of Core Educational Input Indicators ...... 46 8. Summary of Core Educational Process Indicators ...... 47 9. Summary of Core Educational Output Indicators ...... 50 10. Core Indicators System— Societal Congruence ...... 51 11. Mean Quotients in Moray House Battery (1959 - Total Sample Jamaica) ...... 51 12. Mean Quotients—Partial Sample—Moray House Battery 1959 - Jamaica (Primary School Entrants O n ly ) ...... 52 13. Social Class and Test Performance—Moray House Tests (Jamaica) 1959 ...... 63 14. The Significance of Differences Between the Means Obtained by Different Social Groups ...... 63 15. Regression Weights of Promising V a ria b le s ...... 68 16. ETV Utilization Survey— 1978/79 R esults ...... 76 17. Schools with Bookstocks, Summer 1979 ...... 77 18. Number of Schools in the Parishes of Kingston, St. Andrew, and St. Thomas Classified as Urban (City/Town) or Rural/Remote by Ministry of Education (1976) ...... 82 19. Ten Best Performing Urban Schools (Grades 1-6) ...... 84 20. Ten Best Performing Rural Schools (Grades 1 -6 ) ...... 86 21. Urban Schools with Fewest Awards (Grades 1 -6 ) ...... 87 22. Rural Schools with No Awards (Grades 1 -6 ) ...... 88 23. Distribution of the Four Types of Schools in the Stratified S am ple ...... 89 24. 1980 Common Entrance Exam ination ...... 90 25. Sixteen Indicators Presented for Rating to the Sample of T each ers ...... 99 26. Correlational Analysis for Forty Schools—Obtained Correlations ...... m 27. Correlational Analysis for Forty Schools—Means and Standard D eviations ...... 111

viii

Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. 28. Comparison of Quotients in Manley's Study— 1959 Data; Present Study— 1980 D ata ...... 112 29. Means of Ten Best Performing Urban Schools— Total B a tte ry of 1980 CEE S c o r e s ...... 113 30. Analysis of Variance on School Means of Total Battery of CEE Scores—Ten Best Performing Urban S chools ...... 113 31. Means of Ten Best Performing Urban Schools— Mathematics Test of 1980 CEE Scores ...... 114 32. Analysis of Variance on School Means of Mathe­ matics Test— Ten Best Performing Urban S chools ...... 114 33. Means of Ten Best Performing Urban Schools— English T e s t of 1980 CEE S c o r e s ...... 116 34. Analysis of Variance on School Means of English Test—Ten Best Performing Urban Schools ...... 116 35. Means of Ten Best Performing Urban Schools— Intelligence Test of 1980 CEE S cores ...... 117 36. Analysis of Variance on School Means of Intelli­ gence Test— Ten Best Performing Urban S c h o o ls...... 117 37. Matrix of Differences of Means (Rounded)—Ten Best Performing Urban Schools— Intelligence T e s t ...... 118 38. Canonical Correlation and Standardized Coefficients for Each Canonical Function of Intelligence, Mathematics, and English Test Scores with Thirteen Personal and School Input Variables (N = 8 0 2 } ...... 120 39. Canonical Correlation and Standardized Coefficients for Each Canonical Function of Intelligence, Mathematics and English Test Scores with Twelve Personal and School Input Variables (N = 8 0 2 ) ...... 123 40. Discriminant Functions—Upper 33 Percent Compared with Lower 33 Percent of Urban Students— Twelve Variables ...... 125 41. Discriminant Functions— Upper 33 Percent Compared with Lower 33 Percent of Urban Students— Thirteen Variables ...... 128 42. Discriminant Functions— Upper 25 Percent Compared with Lower 25 Percent of Rural Students-- Twelve Variaoles ...... 130 43. Discriminant Functions— Upper 25 Percent Compared with Low er 25 Percent of. R u ra l S tu d en ts— Thirteen Variables ...... 132 44. Rank Ordering of Indicators Based on Teacher R a tin g s ...... 134 45. O rd erin g o f S ixteen In d ic a to r s ...... 136 46. Additional Indicators Provided by T e a c h e rs ...... 137 47. Ranking of Findings for Six Statistical Tests and Teacher Survey Opinionnaire ...... 139 48. Summary Ranking of Personal and School Variables (Canonical Correlations) ...... 150

ix

Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. 49. Summary Ranking of Personal and School Variables— Urban (Discriminant Analysis) ...... 151 50. Summary Ranking of Personal and School Variables— Rural (Discriminant Analysis) ...... 152 51. Summary Rankings of Teachers' Opinions on Sixteen Variables ...... 153 52. Percentage Distribution of First-Level Students by Grade—El Salvador and Nicaragua, 1965 172 53. Farrell's Scalogram of Educational Structural Differentiation: 49 Nations, I960 177 54. McGuire-White Social Class Index— Occupations ...... 182 55. CEE A w ard s 1979 and 1980 as P ercentage o f Pupils Enrolled in Grades 4-6—Ten Best Performing Urban Schools ...... 195 56. CEE Awards 1979 and 1980 as Percentage of Pupils Enrolled in Grades 4-6—Ten Best Performing Rural Schools ...... 195 57. Details of School Sample Drawn, U rb an (Most Awards) . 196 58. Details of School Sample Drawn, Urban (Fewest Awards) 197 59. Details of School Sample Drawn, Rural (Most Awards) • 198 60. Details of School Sample Drawn, Rural (Fewest Awards) 199

x

Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. ACKNOWLEDGMENTS

The prolonged and intense effort involved in the production of this

dissertation means that more than usual thanks are due to a number of

persons who were instrumental in assisting me in bringing the project to

closure. My most grateful thanks are due (1) to the chairman of my committee.

Dr. Robert J. Cruise, whose optimism, inspiration, faith, and advice kept

me going over the long haul; (2) to the other members of my committee:

Drs. Futcher, Lall, and Merchant, and particularly Dr. Futcher who

assisted greatly in the statistical areas; (3) to Dr. Neville Ying, my local

(Jamaican) adviser; (4) to Dean G. H. Akers who so kindly made allowances

for my peculiar circumstances; (5) to Dr. Gertrude Jordan who unstintingly

provided material and moral support in numerous ways including long­

distance computer/library work and editing; (6) to the staff of the Andrews

University computer center and to Mr. Bill Cash who interestedly ran the

analyses; (7) to Ken Harris-Stubbs, Devon Galbraith, and Mrs. Bruce Jones

who assisted me with data gathering; (8) to Eleanor Pommells-Clark and

Suzy Wilk who typed the first draft and final paper, respectively; (9) to the

school principals and teachers who cooperated in supplying the data without

which the study would not have been possible; (10) to the Ministry of

Education and the Ministry of Finance and Planning, Jamaica, for a grant

towards the project and leave-of-absence to complete it, respectively; and

(11) to Dr. Rudolph Klimes who launched me on the doctoral program.

Special thanks are also due to my superiors and colleagues in the

xi

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I am indebted to my brother; Dr. L. M. Mullings, and sister, Mrs.

Edna Crarey, my friend, Cem Fitz-Henley, and others who encouraged and

generously assisted me financially.

My husband, Alton, and children, Sheryl and Hans, and my father,

patiently shared in the sacrifice of time which this study necessitated and

supported me fully to the end. May they share my joy.

Friends arose at the last minute to help and to them I am also very

g r a te fu l.

Finally, above all, I am deeply grateful for the Providential guidance

and assistance which have at all times attended me.

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INTRODUCTION

Social Indicators

Introduced in the mid 1960s, the term "social indicators" has

excited the interest of professionals and lay people who have

interested themselves in studying the evolution of the social system.

Labelled also "social accounts," "social report," "social book-keeping,"

"social intelligence," and "monitors of social change," these indicators

were intended to identify and quantify those societal variables which

significantly affect the quality of life.

Proponents of social indicators did not overlook the already

well-established economic and demographic indicators. In the

published discussions on the subject. Land (1971, p. 323) stated:

I propose that the term social indicators refer to social statistics that (1) are components in a social system model (including sociopsychological, economic, demographic, and ecological) or of some particular segment or process thereof, (2) can be collected and analyzed at various times and accumu­ lated into a time-series, and (3) can be aggregated or dis­ aggregated to levels appropriate to the specifications of the model. . . . The important point is that the criterion for classifying a social statistic as a social indicator is its informa­ tive value which derives from its empirically verified nexus in a conceptualization of a social process.

Public debate over the types and potential uses of social indi­

cators continued. By 1972, Sheldon and Land ( 1972) concluded that

the social indicators debate had

1

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. . . simmered down to more or less general recognition of three different types of indicators designed for different uses: (1) Problem-oriented or direct policy-oriented indicators which are intended for direct use in policy and program decisions. (2) Descriptive indicators intended primarily to describe the state of society and the changes taking place within it. (3) Analytic indicators that serve as components of explicit conceptual and causal models of the social systems or some particu­ lar segment thereof, (p. 139)

In addition, they offered as a point of departure the

following list of social indicators which located education among the sub­

systems contributing to the social and economic welfare of society (p. 146).

A. Socioeconomic Welfare

1. Population (composition, growth, and distribution)

2. Labor force and employment

3. I ncome

4. Knowledge and technology

5. Education

6. Health

7. Leisure

8. Public safety and legal justice

9. Housing

10. Transportation

11. Physical environment

12. Social mobility and stratification

B. Social Participation and Alienation

1. Family

2. Religion

3. Politics

4. Voluntary associations

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5. Alienation

C. Use of Time

D. Consumption Behavior

E. Aspiration, Satisfaction, Acceptance, Morale, etc.

Educational Indicators

Given (1) the ferment in the social sciences leading to field work

on social indicators, (2) the fact that education is an important sub­

system in the total societal system, and (3) the summons to accountabil­

ity within the field of education itself, it is not surprising that a call

for educational indicators was sounded. Relatively early Ferriss (1969),

under the auspices of the Russell Sage Foundation, published Indicators

of Trends in American Education, a book which brought together time-

series data indicating the changing characteristics of education—

organizationally, and as a characteristic of the population (Sheldon,

1975, p. 7). Since then there have appeared other reports on

the educational attainments of young people, e.g., in the National

Assessment of Educational Progress and in The Condition of Education

(1975) published by the National Center for Educational Statistics, U.S.

Department of Health. Education, and Welfare (Sheldon, 1975, p. 8).

Activity in the development of indicators has not been limited

to work emanating from Washington, D.C., i.e., the U.S. Department of

Health, Education, and Welfare. States have constantly monitored input

measures and more recently have become involved in the systematic

measurements of input /output relationships and inventories of various

sorts. Cost benefit approaches have not been neglected either. In many

states there is legislation. Accountability activities in a range of states

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and territories are annotated by Hawthorne (1974). Publications cited

include: (1) Pennsylvania, Department of Public Instruction—publica­

tions on Educational Quality Assessment (1968 onwards); (2) Florida,

Department of Education— Florida Statewide Assessment Programs (1971

onwards); (3) New York, State Education Department— Performance

Indicators in Education (1968 onwards); and (4) Oregon—'by Clemmer,

Fairbanks, Hall, Impara,and Nelson (1974) — Indicators and Statewide

Assessment.

Work on a cross-section of indicators was also underway over­

seas. Studies on cost effectiveness (Coombs 6 Hallak, 1972), returns

to education (Psacharpopoulos & Hinchliffe, 1973), and various

publications through the International Institute for Education Planning

in Paris have all set a framework for international and cross-

cultural studies. Nor were the developing countries omitted. Kiros,

Mushkin,and Billings (1975), in a joint effort between Georgetown

University and the University of Addis. Ababa, produced the study

Educational Outcome Measurements in Developing Countries.

Educational Indicators— Further Needs

There are overwhelming data sources in education, yet there

remain deficiencies in crucial areas in many countries. Among the major

needs listed are:

1. A new tabulation format for old items (B. Duncan, 1968).

2. More evidence on many vital aspects of the system such as

the amount of learning that takes place (Ferriss, 1969) .

3. Segmenting the data to provide indicators that are not only

descriptive but also problem or policy-oriented, perhaps even analytical.

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These indicators might be concerned not only with the objective,

quantitative outcomes of education but also with the subjective, qualita­

tive outcomes— the "well being" of education. They might be concerned

with inputs as well as outputs, costs, returns on investment, and social

benefits. The educational operation could perhaps be sectored; and

final and intermediate products identified. Learning-domain expectations

might be established and achievements measured. In addition, the

"knowledge by-product" might be taken into account as well as its

return effect on the educational system. Indicators in the social environ­

ment perceived as affecting education might also be included.

The question is not whether or not educational indicators should

be identified, but rather just what are the critical indicators and what

aspects of education are to be monitored. As Cooler ( 1975, p. 26)

questions: How does one arrive at a useful and valid mix of kinds of

educational indicators? What balance of qualitative and quantitative

indicators must be achieved? Further, how can indicators be "popular­

ized" while retaining an acceptable depth of analysis? W. Cohen (1975,

pp. 60-62), provocatively suggests that there might be an educational

indicator as useful as the health indicator— Infant Mortality Rate—

that would come out monthly, that may be disaggregated, that may

be used in setting goals, and that may be used in identifying

deficiencies as well as progress.

These are questions which stimulate thought in the search

for educational indicators. They provide a reference for the assess­

ment of the usefulness of proposed indicators.

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Statement of the Problem

As Kiros et al. (1975, p. 9) recognized, ministers of education

and finance,as well as other ministry officials in developing countries,

feel acutely the need for quantitative bases for evaluating how and

w 'ere they might best direct their educational systems to further educa­

tional goals and to stimulate national development. Together they face

the expensive and urgent task of human resource development against

the background of limited financial resources and other constraints—

human and societal.

Educators and administrators concerned with education and with

accountability in education feel the need for at least two types of

indicators:

1. Indicators of systems outputs which can be analyzed to see

how well the system is doing within itself and against external criteria.

2. Indicators of inputs of proven positive relationships with

achievement. These could be revalidated from time to time. Crucial

inputs may be reassessed. New inputs or inputs specific to time and

place may be identified.

Jamaican officials realize that Jamaica is no exception to these

problems. Both types of indicators are needed, particularly at the level

of primary education where the first extensive external assessment of

performance takes place at the Eleven Plus (11+) examination.

Purposes of Study

The primary purpose of the study was to identify and validate a

set of educational indicators for the primary-school system (grades 1-5)

in Jamaica. Subsidiary purposes were as follows:

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1. To secure from a selection of Jamaican primary teachers

ratings of a number of educational indicators submitted to them and of

others which they might suggest. (The list would include input, process,

and output indicators as well as systems accessibility and environmental

indicators. )

2. To examine the predictive validity of certain inputs of the

primary school system by observing their co-varying relationship with

certain measures of pupil performance. (Those which apparently contri­

bute most to achievement would be identified as significant input

indicators. )

3. To relate the two sets of input indicators which receive the

highest rankings in both investigations.

Significance of the Study

Indicators provide information on a system's performance. When

these are monitored over a period of time, they may be used to assess

progress towards goals, or they may reveal trends (including mainte­

nance of or fluctuations around a norm) and tendencies toward growth or

decline. In a system as important as the educational system, it is highly

desirable to have such a profile of indicators for monitoring performance.

The stability of the measures from which the indicators are derived

would have to be established. The indicators themselves may be changed

or modified as planning considerations demand. The indicators identified

in this study should provide a useful initial profile for the study of the

Jamaican primary-school system.

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H ypotheses

The study employed the survey technique to isolate a set of

highly rated educational indicators perceived to be essential in

effective educational management. It also employed a correlational/

predictive model to investigate the relationship between thirteen vari­

ables and three sets of achievement scores in order to posit the

predictive validity of certain inputs.

The following research statement and general hypotheses were

therefore put forward:

1. There is a significantly differentiated list of indicators, as

rated by educators and administrators, such that at least ten ranked

indicators are secured.

2. There is a significant canonical correlation between a linear

combination of predictor variables and a linear combination of criterion

v a ria b le s .

3. There is a linear combination of predictor variables which

significantly separates the following groups of 11+ candidates:

(a) The top 33 percent from the bottom 33 percent of those

sampled in urban schools.

(b) The top 25 percent from the bottom 25 percent of those

sampled in rural schools.

(c) Among the ten best performing urban schools, the pupils

of the school with the highest mean score from the pupils

of the school with the lowest mean score.

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List of Indicators

The list of indicators utilized in the study included the following:

1. Systems Utilization and Accessibility

(a) Ratio of enrollment to school-age population

(b) Degree of overcrowding by school

(c) Percentage of overcrowded schools

2. Systems Inputs

(a) Teacher/pupil ratio —trained teachers

(b) Teacher/pupil ratio—overall

(c) Number of library books per pupil

(d) Number of hours of educational television viewed

3. System s Process

(a) Percentage of teacher turnover

(b) Percentage of pupils attending 90 percent of school sessions

(c) Efficient principal

4. Environmental

(a) Index of malnutrition

(b) Percentage of unstable families

5. Systems Outputs

(a) Grade-by-grade average achievement in English

(b) Grade-by-grade average achievement in mathematics

(c) Percentage of students achieving below 50 percent in English and in mathematics

(d) Percentage of eligible age group obtaining passing mark in the Common Entrance Examinations

The rationale for the selection of these indicators for study is

presented in chapter 3.

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Definition of Terms

Eleven Plus (11+) Examination

The Eleven Plus (11+) Examination is a national examination for

entry into forty-six "academic" high schools. The examination is adminis­

tered to children between the ages of ten years nine months and twelve

years nine months, and comprises tests in mental ability, mathe­

matics, and language arts. In January 1980, 35, 697 pupils from primary

and all-age schools and 2, *109 from independent schools—a grand total of

38, 106 entrants— sat for the examination. Awards totalled 8, 853 comprising

twenty-nine scholarships, where all expenses are paid, and 8,824 free

places, where qualifying students receive free tuition and assistance with

other expenses based on the criterion of need. Of these free places

7,578 went to Primary and All-Age Schools (Jamaica, Ministry of

Education, 1980— Educational Statistics 1979-80).

In d icato rs

Indicators are measures of performance which function as

informers of a system's condition. These are usually presented as a set

of statistics whose variations signal change in the larger world from which

they are derived. In economics a "leading indicator" leads or precedes

major economic change, a "lagging indicator" reports on a major economic

change after the fact, a "co-incident indicator" coincides with economic

change (Warner 6 Dublin, 1965, p. 29). Demographic indicators, though

not publicized as regularly as economic indicators, are nevertheless

respected and monitored for the insights provided. The birth and death

rates and even more importantly the infant mortality and life expectancy

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rates are statistics that are observed and commented on in countries

all over the world.

Since social indicators and, more specifically, educational

indicators are the focus of this study it is useful to present some

definitional perspectives. Definitions of social indicators present a

dichotomy of functions. From the document Toward a Social Report,

published by the U.S. Department of Health, Education, and Welfare

(1969), the following statement is taken:

A social indicator . . . may be defined to be a statistic of direct normative interest which facilitates concise, comprehensive, and balanced judgment about the condition of major aspects of a society. It is in all cases a direct measure of welfare and is subject to the interpretation that if it changes in the "right" direction while other things remain equal, things have gotten better, or people are "better off." Thus statistics on the number of doctors or policemen could not be social indicators whereas figures on health or crime rates could b e . (p . 97)

Carlisle (1972) defined a social indicator as the operational

definition or part of the operational definition of any one of the

concepts central to the generation of an information system descriptive

of the social system (p. 25).

Two indicator functions are identifiable from the foregoing:

1. A statistic of normative interest.

2. A descriptor providing evidence on progress toward a goal,

or objective, or a measure of societal welfare.

In so far as utilization is concerned, it appears that the definition

of social indicators given by Sawhill (1969) is much to the point. They

are described as quantitative measures of [social] conditions designed

to guide choices at several levels of decision making (p. 473). In regard

to educational indicators. Cooler's ( 1975) definition seems comprehensive:

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A definition of educational indicators might be deduced from definitions of social indicators, as applied to education. More simply stated, educational indicators are statistics that enable interested publics to know the status of education at a particular moment in time with respect to some selected variables, to make comparisons in that status over time, and to project future status. Indicators are time-series statistics that permit a study of trends and changes in education (pp. 11-12).

Educational indicators are not, however, synonymous with

evaluation. As Mushkin and Billings (1975, p. 66) note: "Educational

indicators are not always interchangeable with criteria for evaluation

which often require: much greater specificity."

Primary^School System

The Primary-School System comprises grades 1-6 found in four

types of schools. The number of each type of school in 1980 is shown

in parentheses. The grand total was 792 schools.

1. Primary schools, grades 1-6, ages 6^-12 (229 total)

2. Primary schools with infant departments, K-6, ages 4-15 (54 to ta l)

3. All-age schools, grades 1-9, ages 6*-15 (465 total)

4. All-age schools with infant departments, K-9, ages 4-15 (44 total).

Six special schools for the handicapped, including one with both

normal and physically handicapped pupils, are included in the numbers

g iv e n .

Secondary-School System

The Secondary-School System comprises five types of schools (138

total). The number of each type of school in 1980 is shown in parentheses.

1. New Secondary (78 total)

2. Government-aided "academic" High Schools (46 total)

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3. Technical High Schools (7 total)

4. Comprehensive High Schools (5 total)

5. Vocational and Agricultural Schools (2 total) .

System s

"Systems are bounded regions in space-time, involving energy

interchange among their parts which are associated in functional relation­

ships and with their environments" (Miller, 1955, p. 514). They have a

number of interacting parts classified as subsystems which are inter­

related in function and structure but are focused to a primary goal.

Systems are therefore characterized by boundaries, subsystems,

environment relationships (whether open or closed), and tendencies to

entropy (degeneration), steady state, or negentropy. Feedback is

vital for the maintenance of the system's steady state (Immergart 5

Pilecki, 1973, chapter 2).

Triennial Examinations— Primary and All-Age Schools, Jamaica

The triennial examinations for Primary and All-Age schools are

so arranged that each school undergoes assessment once every three

years. The evaluation involves written examinations and review of other

aspects of school operations by a panel of examiners. The written

examinations are administered at the discretion of the panel and all grades,

or a selected number of them, may be involved. Special attention is

paid, however, to grades 3, 5, 7, and 9. The written tests are not

standardized but are designed to be of comparable difficulty at each level.

Instructional management and teacher/pupil interaction are also reviewed.

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Delimitations

The variables surrounding and involved in a systems operation

are multitudinous. The study confined its investigation mainly to

the school system and selected variables therein. The researcher's

knowledge of the Jamaican educational system and experience with its

operations influenced the initial selection of variables. Since the

opinion of other educators was also sought, the final selection was not

based on a sole opinion.

While it would seem that a study of educational indicators

should be more comprehensive in scope and should include education

(1) at secondary and tertiary levels, (2) in both formal and informal

systems, and (3) in both public and private institutions at primary level,

available resources for this study were too limited to permit this. The

study was, therefore, delimited to the public primary system comprising

grades 1-6. No attempt was made to study the private primary-school

system of preparatory schools or, for the most part, the extra-school

variables which might have a causal relationship with achievement in the

Common Entrance Exam ination.

Assumptions

In undertaking this study, it was assumed that

1. The systems model represents— if even grossly—the

functional relationships of the primary education system.

2. The data utilized in the study are close approximations of

reality and reflect significant causal or co-varying phenomena.

3. The known but as yet unmeasured variable, pupil motiva­

tion, is normally distributed in the population of Jamaican primary-school

pup ils.

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4. There is no sine qua non variable external to the school

variab les .

Organization of the Study

Chapter 1 discusses the activities in the area of social indicators

which have preceded and contributed to calls for educational indicators.

It identifies the problems to be addressed, and presents the aims to be

pursued in this study. Important terms are defined. Delimitations as

well as major assumptions are outlined.

Chapter 2 presents a review of the related literature, including

literature on indicators drawn from the fields of economics and health.

Chapter 3 deals with the methodology for deriving the pre­

dictive/correlational relationships. The data used, the methods of

obtaining these, and the statistical analysis utilized are also outlined.

The method of securing and analyzing teacher opinion is also described.

Chapter 4 presents the results of the correlational studies

and the indicators identified in the survey of teachers and

principals.

Chapter 5 posits the family of indicators, draws conclusions,

and makes recommendations.

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REVIEW OF RELATED LITERATURE

Literature and research findings relevant to this study are

reviewed under the following headings:

1. Indicators—other than educational

2. Educational indicators

3. Literature related to the variables of the study

4. Literature on Jamaican education relevant to the study

Indicators— Other than Educational

B ackg ro u n d

Cross (1966a) points out that, in the long history of Western

civilization, progress is repeatedly associated with efforts to obtain new

kinds of information. The censuses of Jewish and Roman times are

examples of such demographic information.- During the Middle Ages the

Latin phrase ratio status— the predecessor of "statistics"—was used to

refer to the factual study of politics and government. The word

"statistic," coined in Germany, first appeared in English in 1770.

The U.S. Constitution, framed six years later, showed the

framers' consciousness of the importance of this factual information of

politics and government. Article 1, Section 2, provides for a decennial

census. In 1790, by order of Congress, the free, white male population

16

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was broken down into two categories, "16 years and over" and "16 years

and under." The nation was getting ready for business. By 1880

proposals for further breakdowns of the population were made, but these

were not implemented until twenty years later.

Article II, Section 3, of the Constitution provides that the

President "shall from time to time give the Congress information on the

state of the Union." The State of the Union message; the Budget

message—started under the Budget and Accounting Act of 1921; the

Economic Report— reference the Employment Act of 1946; the Manpower

Report—under the Manpower Development and Training Act of 1962; as

well as the Statistical Abstract together form the backbone of the

informational system on the "State of the Union" (Cross, 1966a, pp .xi,xiv).

Economic Indicators

The Economic Report, produced by the Council of Economic

Advisers, has received special attention, both developmentally and in

terms of publicity. It places order on a vast output of information.

The monthly Economic Indicators prepared by the Council is a care­

fully organized set of some forty-five tables with charts. It has become

the means by which people "in-the-know" keep their fingers on the

pulse of the economy (Gross, 1966a, p. xii). The forty-five areas of the

Report are subsumed under the following topics;

1. Total Output, Income, and Spending

2. Employment, Unemployment, and Wages

3. Production and Business Activity

4. Prices

5. Money, Credit, and Security Markets

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6. Federal Finance

7. International Statistics

Siderman (1966, p. 93) shows that up to 1964 the economic indicators in

State of the Union messages focused on:

1. Total activity and income statistics

2. Markets and production

3. Income (distribution)

4. Productive resources

5. "Sound" currency

6. Employment rates

7. Surpluses (Treasury)

8. Debts

Press, radio, and television utilize information from the "leading"

economic indicators regularly, and the Consumer Price Index is of

interest to the majority of citizens.

The indicators themselves are derived from a number of

sources—government departments (including the Treasury), public and

private corporations, and firms. The data from each economic area are

summarized and presented in analytic and interpretive tables, together

with graphs showing trends over a given period of time. The

analytic and interpretive tables are specific to and intended to be

appropriate to each area. Two sample pages from the Economic Indi­

cator, published in 1984,are provided in appendix A. They are

(1) The Table of Contents and (2) Changes in Consumer Prices

(table and chart).

These economic indices reflect the development of measurement

technology in areas such as the development of index numbers, adjust-

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ments for changing monetary values, and plotting of real as against

apparent growth rates. It should be noted that the indicators are

subject to error. Oskar Morgenstern (1963, pp. 242-252] has called

attention to inaccuracies in the economic time series that are in

greatest use in making judgments about the economy. The reasons

for these errors are not discussed in this paper.

Demographic Indicators

The census, decennial or otherwise, is a familiar feature of the

developed and developing societies. Population growth is of such

vital and universal concern that the United Nations has made it one

of its areas of interest.

A substantial body of literature exists on the subject of demo­

graphy, and although there are no monthly indicators, the public is

regularly made aware of vital statistics. Crude birth and death rates,

infant-mortality rates, incidence of deaths-by-disease categories, and

I if e-expectancy rates are all familiar and publicized statistics.

The statistical procedures used in deriving some of these

indicators are fairly simple; for example, the fertility rate showing

births per 1,000 women in the age group 15-45 or the crude death

rate showing deaths per 1,000 of population. Far more sophisticated

and often controversial statistical methods are employed in the deve­

lopment of life-expectancy tables and population-projection rates.

The interpretation of all of these indicators must be made against

the background of additional information. A simple example is a deceptively

low death rate due to a predominantly young population.

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Social Indicators

The development and use of social indicators have not shown as

long and fruitful a trend as is the case of the demographic and econo­

mic indicators. Lazarsfeld (1961) affirms that the idea that social

topics could be quantitatively analyzed arose in the seventeenth century.

Biderman (1966, p. 76) reported that over a century ago Herbert

Spencer advocated the use of statistics for societal analysis.

A movement toward the development of social indicators did not

eventuate in the United States until the 1960s. The development of the

space program and its likely impact on the lives of people provided

impetus for this movement.

The Organization for Economic Cooperation and Development

(OECD) produced a document. Indicators of Performance of Educational

Systems (1973), which observed that there are two opposite views

concerning the definition of social indicators. On the one hand is the

definition of measures of output or results, put forward in the U.S.

Department of Health, Education, and Welfare Document 1969— Toward a

Social Report. On the other hand, there is the in-depth social report­

ing view: i.e., the assessment of the condition of society vis-a-vis

its aspirations, goals, or problems (p. 23). This dichotomy in

definition is pointed out in chapter 1.

A great deal has been written in an effort to (1) provide

definitions (Carlisle, 1972; Land, 1971; U.S. Department of Health,

Education, and Welfare, 1969), (2) set conceptual foundations (Bauer,

1966; Biderman, 1966; Cross, 1966a; Moore & Sheldon, 1965), and (3)

present reflective and sometimes critical evaluations (Bell, 1969;

O. Duncan, 1969; Land, 1971; Olson, 1969; Sheldon 6 Freeman, 1970).

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Methodological work continued, as evidenced by the study by Andrews

and Withey (1976) which sought to measure Americans' perceptions of

well-being in order to see how these could be used to yield a series

of "social indicators."

In 1973 the U.S. Office of Management and Budget prepared

Social Indicators 1973, a book of statistics on eight major social areas—

health, public safety, education, employment, income, housing, leisure

and recreation, and population. It looked forward to subsequent edi­

tions. Two others appeared in 1976 and 1980. The 1980 edition

expands the list of social areas to include (1) transportation, (2) social

security and welfare, and (3) social participation. These indicators

were based on two main criteria: measurement of individual and

family well-being (rather than institutional well-being) and measure­

ment of outputs rather than inputs.

Concerning the question of indicators, Bauer (1966, p. 26)

observed that the statistical series collected by the U.S. Government

(or by anyone, for that matter) reflect those areas of concern that

have occupied the minds of the American people—though with some lag

in time. These interests, he claims, are reflected unevenly since the

probability of a given statistical series being developed is also

affected by:

1. The articulateness and power of the group whose interest

is involved

2. The susceptibility of the phenomenon to being measured

3. The extent to which the phenomenon is socially visible

4. The preferences and skills of agency personnel who gather

the statistics.

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Relatedly, Biderman (1966, p. 97) noted that a consensus of

the entire society, or of any given social group within it, concerning

the significance of a certain phenomenon, does not mean that this will

be reflected by available indices. Other factors determining the

availability of indicators are (1) measurement technology, (2) social

observability, and (3) data-agency perspective. Fear of political

misuse should not be overlooked. Indicators may be used either as

vindicators or indictors (Biderman, 1966, p. 78).

Educational Indicators

In the preface to the report on the proceedings of the 1975

Educational Testing Service (ETS) invitational conference on educa­

tional indicators, David Krathwohl declared that "educational indicators

is a topic whose time has come" (p. x i). He pointed out that, in

America, massive federal legislation often has great impact upon the

schools, but key statistics are seldom available to help legislators,

policy makers, and laymen understand in uncomplicated terms how

education is changing. The need for such measures has been rein­

forced by a mandate from Congress: the 1974 Educational Amendments

to the Elementary and Secondary Education Act require the Assistant

Secretary for Education to submit an annual report to Congress on

the condition of education in the United States. A response was there­

after made to this order in the publication of The Condition of Educa­

tion (1975; Golladay, 1976 ed.) published by the U.S. Department of Health,

Education, and Welfare. The 1976 document is divided into two sections:

1. "An Overview of Education" dealing with students and

schools, outcomes of schooling, and concerns of elementary and

secondary education.

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2. "A Closer Look at Selected Topics" such as post-secondary

education participation, relationships between education and work,

education personnel, and finance. International comparisons of educa­

tion in the United States and in other countries are also included.

Although not labeled educational indicators, it is substantially that, as

it presents a wealth of tables and graphs.

The ETS Conference (1975) also dealt with the broad

context and problems of defining social indicators, including educational

indicators. In defining educational indicators at the conference,

Dennis Gooler (1975) suggested a framework for a comprehensive system

of educational indicators. The system is categorized in table 1.

Considered overall, the proposed indicators could be categor­

ized according to potential use—i.e., (1) those of practical interest

and (2) those of academic interest. Indicators of cognitive and

affective outcomes, indicators as to aspirations, access, and concrete

ratios are of practical interest. Indicators of impact and of use of

resources such as cost to benefit/effectiveness ratios might be consi­

dered of interest primarily to the professionals.

Other topics dealt with at the 1975 conference included

"Measurement and Efficiency in Education" (Olson), "Quality of Life

as an Educational Outcome" (Withey), and "Measures of Educational

Outcomes in Developing Countries" (Mushkin S Billings).

Gooler (1975) raised three questions especially pertinent to

this investigation:

1. How can one identify cause-effect or at least correlational

relationships among indicators?

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2. How can one arrive at a useful and valid mix of kinds of

indicators?

3. What balance of qualitative and quantitative indicators

must be achieved (p. 26) ?

TA B LE 1

CATEGORIES OF EDUCATIONAL INDICATORS

Access

How many and what kinds of people participate in educational activities Retention rates in educational activities Catalog of existing/available educational activities or services

Aspirations

Description of needs and desires of various kinds of people Individual self-assessment of personal capabilities Description of institutional goals

Achievement

What people know, do, and feel What people have earned (degrees, diplomas, certificates) What is taught

Impact

Consequences of having schooling Impact of education on social /economic/cultural systems Consequences of not having schooling

Resources

Capital, personnel, and materials expenditures Quality of human resources Cost to benefit/effectiveness ratios Quality of educational climate Time

Source: Dennis D. Gooler, "The Development and Use of Educational Indicators." In Educational Indicators: Monitoring the State of Education. Princeton, N.J.: Educational Testing Service, 1975, p. 15 (ERIC Document Reproduction Service No. Ed 150 147).

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Studies Aimed at Identifying Indicators: Input/Output Educational Studies

In the United States, the landmark input/output study is the

Coleman Report (1966) which surveyed 645,000 pupils in more than

3,000 schools in grades 3, 6, 9, 12 in all regions of the United States.

The survey showed minor differences in school characteristics but

great differences in achievement across the different racial and ethnic

groups. The Report argued that when social background and attitudes

of students are held constant, per pupil expenditures, pupil/teacher

ratios, school facilities, and curricula show very little relation to

achievement (Jensen, 1974, p. 176).

Twenty-three studies of input/output performance before,

including, and since the Coleman Report (seven of which analyzed part of

the Coleman Report) are summarized in table 2. These are based on data

gathered from (1) selected grade levels in primary and secondary

U.S. schools, (2) kindergarten and elementary schools in Great

Britain (one study), and (3) U.S. college freshmen (one study).

Bargen and Walberg (1974), who supplied the summary, note that

nearly all studies show that per student expenditures for teachers, and

teacher experience or education are significantly associated with student

achievement as measured in most cases by student verbal or reading

achievement. These results were striking since verbal skills are

importantly "conditioned by . . . home environment and by heredity"

(p. 243). Average class size showed mixed results and should be

interpreted cautiously.

It is observed from the twenty-three studies listed that the

investigations centered around the following inputs:

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MAJOR STUDIES OF TEACHER QUALITY AND CLASS SIZE

Investigator Crades Sample Control Variables Significant Correlates with Student Achievement

Armor (1972) 6 U.S. schools SES*, background Teacher salary, verbal ability

Averch and Klesllng 9 U.S. schools and SES* Teacher salary, class size ( 1970) individuals

Benson ( 1965) 5 California schools SES (district) Teacher salary

Bowles ( 1969) 12 U.S. Negro Indi­ Background Teacher verbal ability, education; viduals class size

Bowles and Levin 12 U .S. individuals Background Teacher verbal ability, experience ( 1966)

Burkhead, Fox, and 12 Chicago and Atlanta Median family Income Teacher salary, experience; class Holland (1967) schools (census), lower-grade size nonsignificant achievement

Cohn (1968) 12 Iowa districts Prior achievement Teacher salary; class size non­ significant

Coleman et al. 3,6, 9, 12 U.S. individuals Background Teacher verbal ability; teacher ( 1966) experience, education and class size nonsignificant, but these findings are disputed

Goodman ( 1 959) 7, 11 New York Stale SES Teacher expei lence, observer rating individuals of ability to relate subject matter to student ability and interest. Instruc­ tion expenditures per student

Guthrie, Klelndorfer, 6 Michigan SES Teacher experience, attitude toward Levin, and Stout (1971) individuals teaching, school, and other teachers, verbal ability

Hanushek ( 1970) 3 California SES*, prior achieve­ Teacher experience and education individuals ment nonsignificant

verbal ability nonsignificant tion major in college ability, academic rather than educa­ salary - negative; class size - mixed observer rating class of size teacher nonsignificant quality; significant; only significant teacher experience when all included control In model variables significant; class size High school teacher salary; class size Teacher experience, tenure, verbal in in school; class site attendance at universitycollege; teacher rather verbal than ability non­ Teacher experience and education non­ Expenditures per student student; class size Teacher salary; expenditures per Teacher experience, accreditation; education, lack of teacher turnover Expenditures per student Teacher experience, education-mixed; Teacher experience, satisfaction, and Teacher experience, attitude, and

SES SES SES SES*, background SES (by census tracts) Teacher experience, verbal abilitySES, prior achieve­ment SES SES, student attitudes,grade aspirations, par­ SES, backgroundSES Teacher experience, education; SES, SES, background SES, SES, characteristics of home and community ents' attitudes

individuals individuals U .S. schools Individuals U .S. Individuals U.S. northern U .S. schools individuals Eastern city British districts individuals Boston districts districts districts Virginia 9, 9, 12 6 Eastern city 8 New York Statu 6 New York State 6,9, 12 6 Northern urban 6 10, 10, 12 Kinder- freshmen High garden, elementary School

Source: M. Bergen and H. J. Walberg, "School Performance." In Evaluating Educational Performance. Edited by Herbert Walberg. (Berkeley, Calif.: McCutchan Publishing Corporation, 1974), pp. 240-242. number of books In the home, appliances, and other factors thought to be related to student achievement. *SES *SES refers to status socioeconomic measured by parental or average community education and/or income. Background refers to (Central Advisory Rlblch 1968) ( Hanushek 1968) ( Klesllng (1970) Levin 1970) ( 6 Plowden — 1967) ( Raymond 1968) ( College Kalzman (1971) Klesllng (1969) Smith 1972) ( Thomas Thomas 1962) ( Council for Education) Mlchaelson Mlchaelson 1970) ( Melville ( 1956) Mollenkopf and

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1. T each ers

their education

their experience

their accreditation

their verbal ability

their observed and rated quality

their attitudes to teaching, to school, to other teachers

their salary

their tenure

their satisfaction

their lack of turn over

their ability to relate subject matter to student ability and interest

2. Class Size

3. Expenditures Per Pupil

The results of these studies, in terms of the times that the

aforementioned inputs were found significant/not significant or had

mixed results, are summarized in table 3.

The following points taken from the Mushkin and Billings

(1975) presentation at the ETS Conference are relevant at this point:

1. The findings of the James Coleman study—that the chief

determinants of educational achievements of children are the educational

level and socio-economic status of their families— might not be applicable

in every type of case. Combinations of school inputs seem responsible

for differences in some cases. For example, Schiefelbein's (1974)

Chilean study report showed textbooks to be significant; Blaschke's (1975)

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TABLE 3

MAJOR STUDIES OF TEACHER QUALITY AND CLASS SIZE— FREQUENCY COUNT OF INPUT VARIABLES' EFFECTS

V a ria b le Times Times Found Times Found M ixed Studied Significant not R esu lts Sig. or Neg.

Teacher variables

Education 9 6 2 1 Experience 14 9 4 1 Accreditation 1 1 0 0 Verbal ability 9 7 2 0 Observed quality 1 1 0 0 Attitudes to teaching, to other teachers 1 1 0 0 S alary 8 7 1 Neg. 0 T enure 1 1 0 0 Satisfaction 1 1 0 0 Lack of turn-over 1 1 0 0 A b ility to relate subject matter to student ability & in te re s t 1 1 0 0 Class size 11 6 4 1 Expenditures 4 4 0 0

Michigan study showed teacher behavior to be significant; the study by

the International Association for the Evaluation of Educational Achieve­

ment (IEA) Sweden (see Comber 5 Keeves, 1973; Platt, 1973; Purves,

1973; Thorndike, 1973) showed that there are differences in the extent

to which achievement in different subjects is influenced by family back­

ground, family having less to do with achievement in science and mathe­

matics than with achievement in vocabulary skills or literature.

2. Achievement measures have been found to vary with

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measures of self-concept and perception of locus of control (pp. 68-69).

Moats (1970) utilized an input-process-output model to

validate ten educational indicators (input and output indicators) taken

from the Pennsylvania Bureau of Educational Quality Assessment and

asked two questions: "Are the indicators statistically related to

quality education as defined and measured by some reliable method?"

and "How many and what are the factors which make up the domain

represented by the indicators?" After canonical analysis, the highest

weighted indicator variables emerged as (1) net total expenditure,

(2) percentage of graduating class receiving post high-school educa­

tion, and (3) dollars spent on curriculum materials. Factor analysis

produced four factors accounting for 71 percent of the variance.

These were: (1) staff expenditure, (2) orientation to broad and

continuing education, (3) staff working conditions, and (4) pupil

dropout rates.

Kuhns (1972) investigated the predictive relationships among

certain specified manipulative inputs and selected outputs as measured

by the Pennsylvania Department of Education, Bureau of Educational

Quality Assessment. Multiple-linear regression was used and three

input-output models were compared. The three models utilized

manipulative and non-manipulative inputs selectively. A number of

interesting findings resulted; among them:

1. The manipulative inputs generally were adequate

predictors of school outputs.

2. A major determinant of student performance on school-

output measures was non-school (non-manipulative) inputs such as

family socioeconomic status.

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Outcome Indicators

Kiros, Mushkin, and Billings (1975) undertook "an initial

effort" to bring together information about educational outcomes,

including types of measures, the role and use of measurements, and

national policy consequences of measurements in developing countries.

Table 4 provides their potential list of outcome indicators and possible

approaches for measuring these. The important point was made that

"output" was an analytical construct— that through some rationale a

developmental output or set of outputs had to be settled upon. Review

of table 4 shows their emphases to be on affective and qualitative

long-term outputs. These represent important outcomes for study in

developing countries but are mainly outside the scope of this study.

Criteria for Selection of In d ic a to r^

Clemmer, Fairbanks, Hall, Impara, and Nelson (1974, p. 3),

in their work on indicators for statewide assessment in Oregon, made

several worthwhile points on the selection of indicators. To be of

greatest use in assessment, the indicators should be:

1. Related to agreed-upon goals

2. Derived from reliable and valid data

3. Derived from data that will continue to be collected so

that comparisons over time may be made

4. Derived from data for which the measurement techniques

have stability over time.

Their classification of indicators was as follows:

1. Input indicators—conditions or variables over which the

school has some c o n tro l.

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TABLE 4

SELECTED OUTCOME INDICATORS AND POSSIBLE APPROACHES FOR MEASUREMENT OF THESE OUTCOME INDICATORS

Outcome Indicators Approaches for Measurement

"Personal Development" Indicators

1. Achievem ent cognitive tests self-reports unobtrusive (non-reactive) measures

2. Attitude towards work, professionalism self-report (interview, question­ naire employer reports

3. In itia tiv e observation (structured) self-report (interview) employer reports

4. Leadership self-report (questionnaire) unobtrusive (non-reactive) measures (electio n to o ffic e , prom otion) employer reports non-cognitive tests

5. Motivation self-report (interview, question­ naire

6. Rationality self-reports (non-cognitive tests, in te rv ie w )

7. Risk-taking, "seculariza­ self-reports (non-cognitive tests, tion," self-reliance interviews, questionnaires)

8. Tolerance self-report (non-cognitive tests) observation reports of associates

"Social Outcome" Indicators

1. Social m obility . self-reports (interviews, questionnaires) . unobtrusive measures (back­ ground, income)

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TABLE 4—Continued

Outcome Indicators Approaches for Measurement

2. Social integration . self-reports (questionnaire on inter-tribal marriage, associa­ tes, language spoken at home) . unobtrusive measures (migra­ tion, urbanization data)

3. Social participation . self-reports (questionnaire on membership in organizations, civic and community participa­ tion) . unobtrusive measures (member­ ship, contributions)

4. Health-level improvement . self-report (questionnaire on health practices, attitudes) . unobtrusive measures (infant mortality, incidence of certain diseases)

"Political Outcome" Indicators

1. N atio n al in teg ratio n . self-reports (questionnaire on attitudes, political participa­ tio n ) . unobtrusive measures (migra­ tion, urbanization)

2. Democratization . self-reports (questionnaire on attitudes towards justice, merit and reward, voting practice) . Unobtrusive measures (voting p a tte rn )

Source: F. Kiros, S. Mushkin, and B. Billings, Educational Outcome Measurement in Developing Countries. Washington, D.C.: Georgetown University, T975, pp. 93, 94 (ERIC Document Reproduction S ervice N o . Ed 120 25 3 ).

2. Context indicators—conditions or variables over which

the school has little or no control; for example, ability of student or

socio-economic status of students.

3. Performance indicators—measurable or observable

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behavior or variables used to determine program effectiveness or

efficiency (data may concern [a] student performance scores or

[b] a program variable such as instructional process or availability

of learning experience).

4. Societal indicators—measurable aspects of a social con­

dition affected to some degree by education; for example, (a) arrests

for delinquency, (b) employment rates for recent graduates (p. 3).

Clemmer and his associates (1974) have noted that the

criteria for the acceptance of an indicator may change depending on

desired use. They also produced a summary classification of outputs

and examples (see figure 1). Their secondary indicators may be

classified as longer-term outputs and, in this regard, would be

similar to those put forward by Kiros, Mushkin,and Billings (1975).

Economic Considerations for Educational Indicators

Noah (1971, pp. 199-207) points out that, in the common

situation where there are limited resources available to satisfy the

wants or needs of an individual or organization, there arises the

problem of a choice between alternative means of pursuing given ends.

In the business world, the businessman is forced by competition to

behave in an economizing and innovative way, though entrepreneurs

seek more than just maximum profits. A high rate of innovation is

consistent with the achievement of many of his objectives.

In education as in industry, the efficiency problem can be

raised. Knowing that we want to produce a given output, what is the

most economical way of doing the job?

Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. 35

Phase 1 . Primary Effects

P roduct In vestm en t Consumption

Q u a n tity Q uality 1 ncome Employmentj

Num ber o f A ttitu d e s Value Added, School drop­ s tu d e n ts . A ttrib u te s Earnings, outs. High School A ptitu d es A dded Unem ploy­ completion, Achievement e a rn in g s , m ent R ate, etc . (e.g., self­ e tc . e tc . esteem, creativity, I.Q . S A T scores)

Phase 2. Secondary Effects

In vestm en t Consumption j F eedback Feed b ack |

Economic Consumer information growth (e.g., Consumer efficiency years o f Medical care schooling, U 1>C of leisure time lifetim e Moral and citizenship earnings dif­ values, etc. ferentials)

Phase 3. Tertiary E ffects

Intergenerational Im pact

Educational Motivation of Children

Fig. i. Educational Outputs and Examples

Source: R. Clemmer, D. Fairbanks, M. Hall, J- Impara, C. Nelson, Indicators and Statewide Assessment, Salem, Oregon: Oregon State Department of Education, 1974, p. 14 (ERIC Document Reproduction Service No. Ed 091 869) .

Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. 36

Most decisions in education, as in other areas of adminis­

tration, are made in conditions of partial uncertainty and ignorance.

The major need is to organize information around the decision require­

ments, to limit the area of uncertainty, and to define its general

characteristics (Noah, 1971, p. 207). As a minimum the following

actions are required by boards of education:

1. To identify clearly the objectives of the educational

enterprise being financed (not in the usual shibboleths of "education

for life" or "educating each child to the extent of his capabilities11)*

2. To explore the full costs of the decisions taken,

recognizing the commitments to future costs.

3. To identify and explore alternative ways of achieving

stated objectives.

4. To estimate the full costs of each of these alternatives.

5. To associate measures of output (benefit, yield) with

each of these alternatives so that some meaningful ratios of expected

output per unit of input may be calculated.

6. To deliberately and, as a matter of constant concern,

regularly develop new alternative ways of achieving given objectives which

may be more satisfactory than conventional ones. (p. 207)

A board of education which does this is undertaking program

budgeting and forging a powerful tool for improvement of its decision­

making. And one could add that it is laying the foundation for

performance budgeting.

Kiros, Mushkin, and Billings (1975) commented at some length

on the economic outcomes of education, including macro- and micro-

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economic measures. In the introduction to their work it is noted that

education in the developing world is playing a major multipurpose

role— economic, social, and political— with diverse weights assigned to

these purposes in different nations. Later it is pointed out that

macroeconomic and microeconomic estimations of the contribution of

education at the various levels may be made, despite difficulties in

identifying and quantifying the variables involved. At macroeconomic

levels, estimations of the contribution of education to the total growth

in real national income may be made. At microeconomic levels, there

may be estimations of benefits through cost-benefit analyses, utilizing

internal rates of return, and net present discounted values for these

analyses. Costs, for example, would include the following:

1. Direct costs:

(a) Salaries of teachers and auxiliary staff

(b) Supplies provided by and for the school

(c) Rent for land usage

(d) Interest (debt service).

2. Indirect costs:

(a) Room and board if the student has to live away from home

(b) Additional clothing required for school

(c) Transportation to and from school

(d) Cost of personal supplies.

3. Opportunity costs:

(a) The value of the tax exemption enjoyed by non­ profit educational institutions

(b) The opportunity cost of the student's time (employ­ ment foregone) while in school, (pp. 121, 122)

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The benefits would include:

1. Private benefits:

(a) Increased earnings for the individual

(b) Consumption benefits for the individual

(c) Increased capacity of individuals to adjust to new circumstances, jobs, job opportunities.

2. Social benefits:

(a) Provision of manpower for economic growth

(b) Increased productivity for society

(c) Benefits to society of invention and innovation that are generated by increased levels of education

(d) Better citizenship (and hence lower crime costs)

(e) Intergenerational effects

(f) External effects on other individuals, family, employees, and employer

(g) Discovery and cultivation of talent by the educa­ tional system, (p. 124)

It was also pointed out that studies of social rates of return

to education performed for many developing countries showed that there

was a decline in the rate of return as the level of education increased.

Returning to the question of output measurement, Kiros et

al. ( 1975) point out that, when output data in educational programs and

projects are available, gaps in knowledge, skill, and attitudes in the

population can be identified. Deficiencies, especially those deemed

functional for the society, become the basis for issue definition and

analysis. Such analysis can inform policy officials about the size and

nature of the problem and set the stage for generation of policy and

project options. Determination of outputs of education, in a measurable

way, underlies improved management of resources.

Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. 39

Alexander and Simmons (1975) attempted to identify schooling

inputs which might be recommended to policy makers as having a

significant impact on schooling. They proposed an educational produc­

tion function (EPF) as an analytical tool for this purpose: despite

acknowledged limitations for economic analysis, it was felt that the

results could be used for analyses of the cost effectiveness of selected

educational inputs. The production function expresses the maximum

product from an input combination at the existing state of technical

knowledge. Its nature and underlying assumptions derive from the

theory of the firm which is extensively examined in microeconomic

literature. In order to maximize output subject to a budget constraint, .

it is necessary that the marginal product of the last dollar spent be

the same for all inputs. The prescription is to estimate the marginal

products of all inputs, determine their relative prices, and equate

the ratios of marginal product to price over all inputs. Given this,

output efficiency in the educational sector would be maximized (p. 1).

The Education Production Function is generally written

as (Alexander S Simmons, 1975, p. 2) :

Ait = 9 (Fi(t)' Si(t)' P i( t)' °i( t)' 'it' U) The i subscript refers to the i^ student; the t subscript in parenthesis (t) refers to an input that is cumulative to time t, w h ere

Ajt = a vector of educational outcomes for the i^ student at tim e t

F.f = a vector of individual and family background charac­ teristics cumulative to time t

S.,..= a vector of school inputs relevant to the i^ student cu m u la tiv e to t

P., .= a vector of peer or fellow student characteristics cumulative to t

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0 .,., = a vector of other external influences (the community, for example) relevant to the L. student cumula­ tiv e to t

I.. = a vector of initial or innate endowments of the i.. student at t

U = an error term

The use of the EPF would depend on two factors. These are:

(1) identification of those inputs which contribute to learning with

estimations of their relative contributions, and (2) financial inter­

ventions to test the outcome of attempting to maximize certain inputs.

Alexander and Simmons (1975) provided information on the

relative significance of various school inputs researched in developing

countries (see table 5) . It is interesting to note that most variables

showed differing results, among the countries studied.

Educational Indicators: A Comprehensive Work

Johnstone (1981) dealt extensively with the subject of educational

indicators. He considered the concept and classification of educational

indicators as well as statistical formulas for developing them, indicators

were discussed in terms of the systems model, whether they were

referenced as "normative," " criterion, " or "self-referenced"; whether

they were defined as pragmatic, theoretical, or empirical; and whether

they should be classified as representative, disaggregated, or composite

(which he favored) .

He provided a schema for educational indicators based on the

systems concept (see figure 2) . In this illustration the systems environ­

ment included the economic, social, and political systems. The education

systems itself included as input, " resources" and " preference for educa-

Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. TABLE 5

RESULTS OF EDUCATIONAL PRODUCTION FUNCTION STUDIES FOR POOR COUNTRIES

Variable, and its Relationship to Investigator(s) with Country Where the Study Was Done Student Performance

Expected Statistically Significant Non-Statisticaliy Significant, Variable Sign with Expected Sign or with Opposite Sign

Background Variables and Schooling Variables

SES has strong effect at primary and Beebout ( 1972) Malaysia Carnoy (S.F.) (1971) Puerto Rico lower secondary grades for all + Carnoy (R .F .) (1971) Puerto Rico Carnoy-Thias (197*1) Tunisia subjects Epstein (1971) St. Lucia

science* (1972_) '" ‘"-national S'bein-Farrell ( 1973) Chile Simmons-Askoy (1972) Tunisia SES has less effect in developing c .f. developed countries IEA reading (,972'> International S'bein-Farrell (?) ( 1973) Chile SES has diminishing effect through­ Beebout (English) ( 1972) Malaysia Beebout (1972) Malaysia out secondary cycle Carnoy (1971) Puerto Rico Carnoy-Thias (197*1) Tunisia

I eA science (1972- } '" ‘'•‘national Schooling variables have some effect ? Carnoy (1971) Puerto Rico at lower grades, but a stronger Carnoy-Thias (197*0 Tunisia effect in upper secondary grades IEA reading international IEA science Schooling variables have some effect on + IEA reading ( 1972-) International Simmons-Askoy ( 1972) Tunisia native language beyond primary grades

Individual Schooling Variables

Por-pupll expenditures on school + Beebout ( 1972) Malaysia facilities or teachers Levy (1971) International Thlas-Carnoy ( 1969) Kenya (grade 11) Average class size, or pupil: Beebout (1972) Malaysia teacher ratio Carnoy (1971) Puerto Rico I eA scfence ( ' 972-> International Levy (1971) international S'bein-Farrell ( 1973) Chile Thias-Carnoy ( 1969) Kenya (grade 11) Teacher certification and academic Carnoy (1971) Puerto Rico Levy (1971) International qualification at primary and lower S'bein-Farrell ( 1973) Chile secondary grades Thias-Carnoy (1969) Kenya (grade 11)

(-) Carnoy (1971) PuertoCarnoy-Thias Rico (1979) Tunisia Carnoy-Thias 1979) ( Tunisia Carnoy-Thias 1979) ( Tunisia Carnoy (1971) Puerto Rico Carnoy (1971) Puerto Rico Beebout 1972) ( Malaysia Beebout 1972) ( Malaysia Carnoy-Thias (1979) Tunisia Beebout (1972) Malaysia Thias-Carnoy (1969) Kenya (grade 7) S'bein-Farrell (1973) Chile

' re?dln9 ( 1972-) International (+) scferlce <,972'> '" ‘^national a IEA IEA science 1972-) ( International Beebout 972) ( 1 Malaysia Carnoy (1971) Puerto Rico !1 IEA science 1972-) ( International IEA science 1972-) ( International IEA science IEA IEA reading (1972-) International Carnoy (1971) Puerto Rico S'bein-Farrell 1973) ( Thias-Carnoy Chile 1969) ( Kenya (grade 7) Beebout 1972) ( Malaysia !pa IEA science 972-) ( J International Beebout 1972) ( Malaysia Carnoy-Thias (197

Source: L. Alexander and J. Simmons, The Determinants of School Achievement in 1975, pp. 57-59. (ERIC Document Reproduction Service No. Ed 28 1 991). Developing Countries: The Educational Production Function. Washington, D .C .: World Bank, secondary grades qualification at upper secondary grades Teacher certification and academic Teacher experience at secondary upper grades Homework and free reading Teacher experience at primary and Teacher contract (tenure) at upper Performance and attitudes of class­ Teacher sex - males at primary and Boarding at secondary grades Double sessions lower secondary grades Teacher motivation room room peer-group secondary grades Size Size of school enrollment at upper lower secondary grades; females at Textbook availability grades at primary at home upper secondary grades Grade repetition Availability and use of library

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system Political of society and Skills Utilization Future framework of Resources system Social system Economic with and Skills Output Education subdivision Resources Satisfaction XXXXXXXXXXXXXX X Xxxxxxxxxxxxxxxxx

and Process subdivision System of Inputs S tru ctu re Distribution Education System- for for Input Education subdivision Resources Preferences Education ;xxxxxxxxxxxxxxx xxxxxxxxxxxxxxxxx Fig. 2. A framework for the development of indicators of education systems. Source: J. Johnstone, Indicators of Education Systems. Paris: UNESCO, International Institute for of Past system society framework Social system Political system Economic Educational Planning, 1981, p. 26 (ERIC Document Reproduction Service No. Ed 212 091).

Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. 44

tion" ; as process, " system structure and distribution of inputs" ; and as

outputs, "[utilization of] resources and skills" and "satisfaction with

education."

In addition, Johnstone (1981) listed a number of indicators already

developed (many under the auspices of the United Nations' Education,

Scientific, and Cultural Organization— UNESCO), formulas for deriving

these, and his selection and categorization according to the systems

concept. The following summaries are considered of special interest and

informational value:

1. A summary of education—economy studies together with the

education variables used (see table 6). These variables include (a) per­

centage of Cross National Product and percentage of government budget

spent on education, (b) numbers of eligible population in education, and

(c) literacy rates and levels of education reached.

2. A summary of eight core " input" indicators (see table 7).

These include (a) enrollment ratios, (b) rates of change in the ratios,

(c) financial (expenditure) indicators, (d) access indicators, i.e., per­

centage of eligible group in education including accessibility to females,

(e) minimum attainment (grade 4), and (f) maximum second level attain­

ment.

3. A summary of eighteen "process" indicators (see table 8) .

These include (a) availability of student places (ratios of enrollment),

(b) availability of classes and schools at consecutive levels, (c) rates of

change for (a) and (b) above, (d) female involvement (students and

teachers), (e) orientation of second- and third-level studies, (f) expected

number of years and expected completed grades for an entrant.

Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. 45

TABLE 6

SUMMARY OF EDUCATION VARIABLES USED IN SELECTED COMPARATIVE EDUCATION STUDIES

Education—economy Education— socio-political studies studies

S tu d y Education variable S tu d y Education Variable

Edding (1 962) % of CNP on Jahoda(1961) Level of education education reached

S venn il son Enrollment ratio Fox and Miller Combined first-and et al. (1 962) (1965) second-level enrollment ratios

Bowman an d % of population Almond and Years of schooling Anderson in primary edu­ Verba (1963) (1963) cation % of population in post-primary education

Harbison and Combination of Myers (1964) second- and third-level enrollment ratios

M cC lelland Secondary school C u trig h t Combination of (1966) enrollment per ( 1963) literacy rates and 10,000 population higher education enrollments per 10, 000 population

Meyer (1971) Ratio of enroll­ Rummel Expenditure on edu ments at each (1 972) cation as a % of level government budget first-level pupil- teacher ratio first-level unad­ justed enrollment ratio second- and third- level students per 10,000 population

Source : J. Johnstone, Indicators of Education Systems. Paris: UNESCO, International Institute for Educational Planning, 1981, p. 11 (ERIC Document Reproduction Service No, Ed 212 091).

Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. ■ c CTl

Division Division Method of Gin) Glnl coefficient coefficient Combination

Variables 1. 1. Index numbers Unweighted 1. 1. Index numbers Unweighted 2. Standard scores average 1. Index numbers Unweighted 1. Index numbers Unweighted 2. Standard scores average 2. Standard scores average Conversion of 2. Standard scores average None None None None

INDICATORS

TA B LE 7 Variables Used in Calculation Total amount spent on education as a proportion of the variables nominated for input Indicator 1 and and number of teachers per 10,000 population variables listed for input indicator Percentage 3 of enrollments with in a nominated certain groups and characteristic percentage of total population specifically the total enrollment of girls in each region CNP CNP and the total publicproportion expenditure of the on total education government as a expenditureVariables measuring the rate of change in both of the Adjusted enrollment ratios for first- and second-levels Proportion of the total population of an age theoretically in in those groups same Proportion of the total population of an age theoretically who are enrolled In that grade or above (for two years) Variables measuring the rate of change in each of the enrolled in gradeor above 1 which Is corresponding to the last grade of the second-level and

SUMMARY OF CORE EDUCATIONAL INPUT

Source: J. Johnstone, Indicators of Education Systems. Paris: UNESCO, International Indicator Name In In the provision of education educational attainment Indicator involvement Equality of access of girls to education indicator changing human resource level educational attainment Change In the minimum Change in the maximum second- . 1. 1. Involvement of human resources 3. 3. Financial involvement 2. 2. Development emphasis on 5. 5. Equality of access a. a. Financial expansion 8 Institute for Educational Planning, 1981, p. 150. (ERIC Document Reproduction Service No. Ed 212 091).

Reproduced with permission of the copyright owner. Further reproduction prohibited without permission.

values Combination Method of Unw eighted Unweighted 2. Ratio of C average average average Index numbers Index numbers Unweighted Index numbers Unweighted Standard scores average Standard scores Standard scores . 1. 2. 1. Index numbers 1 2. 1. Index numbers Unweighted 2. Standard scores 2. 2. Standard scores average No C index No 1. C index

TABLE 8 Ratio of enrollments(each ratio at third-level separately for to males second-level and females) Ratio of enrollmentsRatio of enrollments at special at education second-level to first to first level level Ratio of enrollments at pre-school to first-level second- and third-levels Ratos of change for all variables listed for indicators 1-3 1. Ratio of numbersRatio of of classes numbers In of specialclasses educationat second-level to first-level to first-level Percentages of second-level studentsPercentages enrolled fieldsof In third-level general students enrolled In nominated second- and third-levels Percentages of enrollment who are female at the first-. Ratio of numbers of classesSimilar at variables third-level to those to above second-level except numbers of schools Ratio of numbers of classes at pre-school to first-level education and teacher training courses Percentages of teaching force who are female at the first-, are used Instead of numbers of classes SUMMARY OF CORE EDUCATIONAL PROCESS INDICATORS

classes

(4), Indicator Name Variables in Calculation Conversion student places at ( ( 5) and schools 6) ( level studies for students consecutive levels education schools at consecutive the provision of levels Development emphasis levels level studies expansion of system Female Involvement in Orientation of third- on i]uaritilalive classes at consecutive 1. Relative availability of 3. Relative availability of 7. 2. Relative availability of 8. Orientation of second- 9. 6. i(-

Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. 10. Expected number of Promotion and repetition rates for all grades In the first- No Special formula years of education level and/or second-level received by an entrant

11. Expected number of Promotion and repetition rates for all grades In the first- No Special formula grades of education level and/or second-level completed by an entrant

12. Availability of Percentage of teachers in various qualification categories No C index qualified teachers

13. Distribution of Percentages of qualified teachers In each area of a country No Clnl coefficient qualified teachers as well as percentages of total teaching force in each area

1

15. Regional educational 1. Promotion and repetition rates for each grade in each region No 1. Special formula flow differential 2. First and final grade enrollments and total enrollments for ♦ Stand ard the level analyzed Deviation 2. Ratio of Clnl Coefficients

16. Index of structural Variety of characteristics of institutions No Cuttman scale differentiation

17. Dependence on a Percentages of all expenditure on a system provided by the No C index single fund source national government of a country and by state or provincial governments

18. Education cost Unit cost for first-, second- and third-level over a given time Index numbers Laspeyres indlca tor period and enrollments at each level in a base year formula

Source: J. Johnstone, Indicators of Education Systems (Paris: International institute for Educational Planning, 1981, ERIC Document Reproduction Service, No. ED 212 091). 49

(g) availability and distribution of qualified teachers, (h) male/female

educational flow differential, (i) regional flow differential, (j) index to

categories of institutions, and (k) funding and cost indicators.

4. A summary of five "output" indicators (see table 9). These

include (a) achievement levels, (b) an academic production index, (c)

specialization of graduates, (d) proportion of entrants graduating, and

(e) satisfaction with educational performance.

5. A summary of five " educational system— societal congruence

indicators" (see table 10). These are (a) educational profile of the un­

employed, (b) availability of the mass media, and (c-e) rates of return on

the three levels of education.

A listing of the formulas referred to in tabies 7-10, as well as

others of interest are included in appendix B.

Literature Related to the Variables Under Study

In addition to the literature already cited, literature and

research findings relevant to the variables included in this study are

presented. Eight predictor variables are reviewed below:

Sex, Age, Achievement

Bernard (1972), in his book Psychology of Learning and

Teaching, states that boys as a group show greater variability than

girls in the range of intelligence. More boys than girls are defective

in intelligence but also more boys than girls are superior. On the

average, males demonstrate slight superiority over females in general

reasoning, arithmetic reasoning, ability to detect similarities, and

certain aspects of general information. They tend to excel over girls in

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TABLE 9

SUMMARY OF CORE EDUCATIONAL OUTPUT INDICATORS

Variables Used in Method of Indicator Name Conversion Calculation Combination

1. Achievement Scores on either individual No A ddition level items or on sub-tests

2. Academic Numbers of third-level 1. Index Weighted or production graduates obtaining numbers Unw eighted index various types of degrees 2. Standard average or scores Numbers of second-level graduates completing various types of education

3. Specializa­ Proportion of third-level No 1. C index tion of graduates in nominated 2. Ratio of graduates fields of study C indices

4. Proportion Promotion, repetition and No Special of entrants graduation rates for all formula who finally grades in the f ir s t - and/ graduate or second-level

5. Satisfaction Ratings on an ordinal scale No W eighted w ith the to indicate degrees of average or performance satisfaction or responses Laspeyres of education on a nominal scale to formula systems specific features, problems, etc. of the education system

Source: J. Johnstone, Indicators of Education Systems. Paris: UNESCO, International Institute for Educational Planning, 1981, p. 175. (ERIC Reproduction Service No. Ed 212 091).

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TABLE 10

CORE INDICATORS SYSTEM— SOCIETAL CONGRUENCE

M ethod o f Indicator Name Variables Used in Calculation Conversion Combination

1. Educational Percentage unemployment rates No G ini p ro file of for selected educational coefficient th e u n ­ attainment groups and per­ em ployed centage of 15-64 age group in each of these groups

2. Availability Rates per 1,000 population for 1. S ta n d a rd 1. Addition of the mass the availability of radios, scores 2. Multipli­ media television, daily newspapers 2. In d ex catio n and non-daily newspapers num bers

3. Rates of re tu rn fo r first-level Many estimates including V ario u s education income foregone, forecast earnings, etc. (See 4. Rates of Psacharopoulos (1975), re tu rn fo r Thias and Carnoy (1969), second-level for full details.) education

5. Rates of re tu rn for third- level education

Source: J. Johnstone, Indicators of Education Systems. Paris: UNESCO, International Institute for Educational Planning, 1981, p. 181. (ERIC Document Reproduction Service No. Ed 212 091).

Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. 52

speed, coordination of large body movements, perception, and me­

chanical aptitude. Girls tend to have slight superiority in memory,

language usage, manual dexterity, numerical computation, and

perceptual speed.

Bloom (1964, cited in Bernard, 1972, p. 155) found that at

least during the ages of seven to sixteen, there is little justification

for separate analysis of boys and girls on intelligence test data. It

should be noted that in the Common Entrance Examination the cut off

score for boys is lower than that for girls—perhaps supporting the

observation of greater variability in intelligence or achievement scores

of boys as a g ro u p .

Numbers of Years in School

Good, Biddle, and Brophy (1975, p. 64), in their review of

elementary-school studies, indicate that, based on two general reviews

by Rosenshine and Furst (1973) and Dunkin and Biddle (1974), several

studies have demonstrated that attendance at elementary school makes

a difference and/or that some elementary schools are more successful

than others.

At the most fundamental level several studies have compared

children who have stayed in school with children who have left school

early. The studies all show that school has considerable impact not

only on infusing knowledge but also in developing children's cognitive

abilities and problem-solving skills.

One such study was conducted in Prince Edward County,

Virginia. The county closed its public schools from 1959-1961 rather

than comply with a court order to integrate the schools. Some

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children in the county did not attend school during this period.

Comparisons of children who stayed in the county but did not attend

school with peers who went to private schools in the county or who

left the county to attend school elsewhere showed that children who

did not attend school failed to progress and in many cases seriously

regressed in their intellectual abilities (Green et al., 1966).

A second study yielding similar results was conducted by

Schmidt (1966). This research was done on a South African community

where education is not compulsory. Children who started school early

and stayed in school longer were compared with children who began

later or did not stay in school very long. Among other things, his

comparisons revealed a strong relationship between years of schooling

and intelligence test scores even with age held constant and socio­

economic status (SES) controlled statistically.

Good, Biddle, and Brophy (1975) go on to comment that all of

these studies no doubt involved a certain amount of selection bias,

because even where SES was controlled it is likely that children who

attended school came from families who placed a greater value on

education than families who did not. Thus, differences seen in these

studies reflect not only the effect of school but probably also differ­

ences in family values. Nevertheless, these and similar data leave

little doubt that schooling has important effects upon cognitive

development. Children with more schooling not only learn more facts,

they develop their thinking and problem-solving abilities more fully.

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Teacher/Schools Differential E ffects

Barak Rosenshine (1971, pp. 66-95), in How Teachers Make

a Difference, makes a general note on the lack of research on how

teachers make a difference. While the studies cited may show certain

relationships, further research would be necessary to show what

curriculum inputs and what aspects of teacher presentation make a

difference in pupil outcomes.

On the question of some schools being more effective than

others. Good, Biddle, and Brophy (1975, pp. 65, 66) cite an especially

interesting study done by Brookover, Gigliotti, Henderson, and

Schneider (1973). These investigators took into account the socio­

economic and racial composition of school populations by matching

schools within categories before making comparisons. Then the investi­

gators identified pairs of schools within each category that were similar

on every variable measured except student achievement. These data

demonstrated that schools can differ significantly from one another

even when student populations are carefully matched. Students,

teachers, and principals of twenty-four schools were asked to fill out

questionnaires. The responses were then analyzed and related to

measures of school success in providing student learning. These

results showed that the most important single negative factor was

the student's sense of futility. Students in schools that had the

worst records showed the strongest sense of futility. These students

were cynical and apathetic, feeling that very little of value went on

in their schools and that they had little to say about it. Other

important differences between successful and unsuccessful schools

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included teacher perceptions of future evaluations, teacher expecta­

tions of the students, and the teachers' reported willingness to push

students to achieve. In short, when teachers believed that students

could learn and worked to see that they did, students learned; when

teachers did not think the students could learn and did not work very

hard to see that they did, the students did not learn much.

These data are consistent with those from studies reviewed

by Good, Biddle, and Brophy (1975); a relationship between teacher

expectations and student achievement is shown. Whether the unit of

analysis is the individual teacher or the entire school, teacher

expectations and student learning tend to go together.

Good et al. (1975) also point out that several studies

indicate that curriculum materials provided to teachers tend to set

the pace for the class by fixing the expectations of both teachers

and students concerning what is appropriate for students to learn. A

number of studies was cited as well as the review of thirty-two

studies of innovative curricula covering elementary school through

college (Walker & Schaffarzink, 1974). The conclusion is that much

of what students learn is a function of teacher and student expecta­

tions and that these are determined in large part by the curriculum

used (p. 67).

It was also affirmed that some teaching methods are more

effective than others even when the curriculum is identical.

Studies of affective behavior of teachers are also provided. Several

studies have indicated the importance of certain aspects of teacher

personality—especially the affective or emotional aspects. Certain

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behaviors may produce different learning outcomes with students from

different racial or class backgrounds.

Good, Biddle,and Brophy (1975) conclude their review by

stating that, although a variety of elementary-school research has been

considered, the review has been illustrative rather than exhaustive.

Two main points were brought out:

1. Teachers differ significantly from one another both

statistically and practically in their relative impact on student-learning

and student-affective variables such as self-concept and attitudes

towards learning and school.

2. Much is already known and more is being discovered

every day about what kinds of teacher behaviors are appropriate or

inappropriate for particular kinds of students in particular situations.

Although a teacher is partially an artist with a unique individual approach, teaching is (or should be) only partially an art. As knowledge about effective teaching accumulates, teaching should increasingly become an applied science .... The skilled teacher will be an individual who has mastered a large body of principles and skills, and who is capable of diagnosing a situation correctly and deciding which of the many options available to him are appropriate to the situation. (p. 79)

Educational Television

The vast majority of research studies on the effectiveness of

educational television had established, by the late 1960s, that there

were no significant differences in measured performance between

students who were instructed via television and those who were taught

directly. A few studies showed differences in favor of television and

a few found differences in the opposite direction (Reid 5 McLennan,

1967). Gordon (1965) concluded that television in an educational setting

may be used for: (1) enrichment; (2) cooperative or team teaching.

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and (3) total teaching. Of 393 comparisons between instructional

television and live instruction, there was no significant difference in

65 percent of the cases studied. There was an apparent tendency for

televised instruction to provide more effective learning in the primary

grades. There was also variation in the effectiveness of television

teaching according to subject matter. For example, at the time of

the study, language skills and health and safety education showed a fair

amount of effectiveness. Mathematics, science, and social studies

showed outstanding success for the groups tested, while history,

humanities, and literature had the smallest measure of sucess. Tele­

vision students held their own in comparative tests of critical

thinking, problem-solving, and sundry other incidental virtues of

education (pp. 66, 84, 85, 87).

In addition, learning from televised classes, like all

learning, seems to be a correlate of the motivation of students—

a class with low motivation to learn will probably learn as little from

a live instructor as from instructional television (Cordon, 1965,

p . 8 6 ).

Carpenter (1963), cited by Cordon ( 1965), listed factors

based on research at that time, which seemed to affect positively,

student learning in instructional television courses of any kind. These

factors were:

1. The quality of sources and resources used.

2. The way in which materials are related and organized.

3. The surroundings on the television screen in which materials are selected and organized.

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4. The characteristics of the students in terms of aspira­ tion, motivation, abilities, previous training, and state of physical and mental health.

5. The nature of students' responses to the materials on television.

6. The rewards, penalties, or reinforcements which occur with or during televised instructions.

7. The evaluations and comparisons of achievement rates and performance levels to which students are subjected. (Cordon, 1965, pp. 87, 88).

School Libraries

Caver (1963) points out that the most authoritative

pronouncements on school libraries were issued by the American

Association of School Librarians. An arresting paragraph in this docu­

ment reads:

Whatever form the soul-searching regarding the education of youth may take, sooner or later it has to reckon with the adequacy of the library resources in the schools. In the educa­ tion of all youth from the slowest learner in kindergarden to the most intelligent senior in high school an abundance of printed and audio visual materials is essential. (American Library Asso­ ciation—ALA— 1960, Standards for School Library Programs, p. 3)

It was further stated that educators and librarians agree that even

under the best conditions public library service is not accessible

enough for all school children.

The advent of video and computers has introduced teachers to

even more flexible resources for teaching by audiovisual technology. These

resources are not, however, being utilized in Jamaican primary schools.

Socioeconomic Status: Classifi­ cation Index

A convenient socioeconomic measure is the McGuire White

(1955) Index I of socioeconomic status which provides categorizations

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based on three sources of data: (1) occupation of family head,

(2) source of family income, and (3) education of family head. A

weighting method for aggregating the variables is described and a

rating provided. These are included at appendix C.

Literature on Jamaican Education Relevant to the Study

The Common Entrance Examination

Vernon (1961), in his report to the Minister of Education on

Selection for Secondary Education in Jamaica,made a number of state­

ments and observations relevant to this study:

1. The majority of pupils obtaining free or grant places in

Kingston schools then had most of their education in primary schools but

also attended infant, private, or preparatory schools (p. 37).

2. Boys tended to start a little behind (girls) but appeared

to catch up after three years in secondary school (p. 37).

3. Age of entry seemed to have no clear effect. Probably

those aged 11$ did rather better in secondary school than those

under this age (p. 37).

4. Girls did better than boys on all three Moray House

tests, but especially in English. Compared with the United Kingdom

11+ children, Jamaican candidates were relatively more advanced in

mechanical but poorer in problem arithmetic, and somewhat weaker in

a test of non-verbal reasoning (p. 38).

5. In discussing intelligence and the intelligence tests,

Vernon (1961, p. 43) pointed to a distinction made by Hebb (1949)

between Intelligence A—defined as an innate quality of the central

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nervous system and brain—and Intelligence B— which is the result of

Intelligence A interacting with environment in the growing child. Such

an intelligence is similar to the conception of health— fundamentally

limited by genetic endowment but also dependent on environmental

conditions from conception onwards. Vernon (1961) considered that

the intelligence under reference is a middle-class European and

American invention—a kind of intelligence particularly well-adapted

to scientific analysis, control, and exploitation of the physical world,

for large-scale and long-term planning and the carrying out of

materialistic objectives (p. 45).

6. The intelligence tests utilized in the battery attempted

to measure skills which are somewhat less affected by schooling than

are such measures as English and arithmetic. Home and school environ­

ment would nevertheless affect the measures on these tests (p. 46) .

7. Studies of maturation have shown that western education

is apt to introduce children to reading, numbers, and grammatical

and mathematical operations before they are ready for them and that

much quicker progress is made when they are postponed for a year

or two; also that such children do completely catch up with those who

made an earlier start (p. 49).

8. In 1959 nearly twice as many girls as boys entered for

the examination. Because of a 10-point lower limit in total marks

arbitrarily set for boys, 853 boys as against 902 girls secured places

(p . 5 7 ).

9. In England the average intelligence and English

quotients for boys were a little lower than for girls, though they

often exceeded girls in arithmetic. Their test spread was also wider

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with relatively more very high and very low scores (p. 57).

Manley (1963), in his study Mental Ability in Jamaica,

analyzed the records of a random sample of 1,730 children from the 1959

entries for the Common Entrance Examination. These children were

given the Moray House Verbal Reasoning Test 43, Moray House

Arithmetic Test 19, and Moray House English Test 19. Manley

discussed the sociological and educational implications of the results

and examined some of the possible reasons for these. The means

of the test scores were all between 85-90 with standard deviation of

about 10. This compared with the means of the United Kingdom test

scores in the region of 100 with standard deviation of 15. The

Jamaican spread was a skewed distribution. Table 11 displays the

Jamaican results (Manley, 1963, p. 5).

TABLE 11

MEAN QUOTIENTS IN MORAY HOUSE BATTERY (1959 - TOTAL SAMPLE JAMAICA)

N o. o f Intelligence A rith m e tic E nglish Examinees Quotients Q uotients Quotients Total

Boys 657 87.1 89. 9 8 5.6 262.6 G irls 1, 073 87.5 89.1 86. 3 262.9 B oth sexes 1, 730 87. 3 89.4 86.1 262.8 S ta n d a rd d eviatio n 10.8 10.3 10. 5 25.4

The results were classified by parishes and then oy all rural areas as

against Kingston and suburbs. Rural areas, however, did include

rural towns. The results in respect to candidates from the primary

schools only (candidates from the high schools and private schools

excluded) are summarized in table 12 (Manley, 1963, p. 8).

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T A B L E 12

MEAN QUOTIENTS— PARTIAL SAMPLE—MORAY HOUSE BATTERY 1959 - JAMAICA (PRIMARY SCHOOL ENTRANTS ONLY)

No. o f Intelligence A rith m e tic E nglish Parish Examinees Q uotients Q uotients Quotients Total

All ru ra l areas 1178 84.2 87.1 82. 7 253.7

Kingston (and suburbs) 228 91.3 92.0 8 9 .6 272.9

Total p rim ary 1406 85.3 87.8 8 4 .0 257.1

Although children from rural parishes obtained a larger percentage of

free places than any other single group, they obtained far fewer than

their proportionate numbei— a disproportionate number going to high-

school pupils, nearly all of whom were taking the examination for the

second time. Again, girls from all types of schools showed a slight

margin of superiority in intelligence and English (pp. 9, 11).

Manley (1963) made special note of the fact that boys

appeared to be dropping out of the system. Whereas there were

twice as many girl candidates as boys in the Common Entrance

Exam of 1959, there were also fewer boy candidates in 1961 for the

Technical High Schools Entrance Examinations which are set at age

thirteen. He concluded that if these boys had not dropped out of the

educational system, they had failed to approach the secondary stage

(p . 12).

Based on crude categorizations of parents' occupations,

Manley (1963) found that children drawn from certain social classes

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showed a decided superiority (p. 18). Tables 13 and 14 illustrate

this finding (pp. 15. 16).

T A B L E 13

SOCIAL CLASS AND TEST PERFORMANCE—MORAY HOUSE TESTS (JAMAICA) 1959

Intelligence Arithmetic English Group Quotients Quotients Quotients Total

1. Professional and managerial 98.6 96.4 98.4 293.4 2. Teachers 9 2 .3 94.4 90.4 277.1 3. Clerical - 91.5 92.1 89.3 272.9 4. Skilled & semi-skilled 8 7 .5 90.3 84.4 262.2 5. Farm ers 8 2 .9 85.6 83.7 252.6 6. Unskilled 82.1 85. 7 82.4 250.2

T A B L E 14

THE SIGNIFICANCE OF DIFFERENCES BETWEEN THE MEANS OBTAINED BY DIFFERENT SOCIAL GROUPS

Intelligence Arithmetic English G roup Q uotients Quotients Quotients

1. Professional and Managerial and Teachers 6 .3 * 2. 0 8 .0 *

2. Teachers and Clerical 0.8 4.1 * 1.1

3. Clerical and Skilled and Semi-Skilled 4.0* 1 .8 * * 4 .9

4. Skilled and Semi-Skilled and Farmers 4 .6 * 4 .7 * 0 .7

5. Farmers and Unskilled Workers 0.8 0.1 1 .3

* p < .01 ** p < . 05

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An "elite" group from wealthy homes who attended prepara­

tory schools showed even greater superiority in performance. Their

overall mean score was 19.7 points above the mean of primary school

children classified under the professional/managerial group.

A sizeable proportion of children from the professional

managerial group appeared to attend rural primary schools. It was

pointed out that this was not as unusual as might be expected since

primary schools might have been the only ones available in those

areas and all social groups either used them or sent their children

away to boarding schools—an expensive alternative (p. 20).

Correlates of Achievement in a Common Entrance Level Examination

The landmark Jamaican study of factors influencing per­

formance of primary-school pupils in an examination of similar level to

the common entrance level was that of Reid (1964). Specially prepared

tests in English and arithmetic which produced normalized standard

scores with a mean of 100 and a standard deviation of 15 were the

criterion measures used. The averaged scores of each school were

treated as the unit. A test of mental ability devised by Vernon for use

with Jamaican children was also used. Each school, therefore, had a

criterion score made up of the averaged scores in English and arithmetic

combined, as well as an averaged score of mental ability, together with

a score or rating on each independent variable.

The independent variables were:

1. School Size—the average enrollment of children for the

entire school.

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2. Class Size— the number of children enrolled in the

class from which the sample was drawn, i.e., the highest in the

Junior department.

3. Attendance— the average number of sessions, i.e .,

half days for which the children attended in the whole of the

previous school year expressed as a percentage of the total number

of possible sessions.

4. Length of Schooling— the average number of years

pupils attended school up to the time of the sampling, inclusive of

infant or "basic" schooling.

5. Teacher Education or Professional Qualification— coded

according to the levels of education and grade responsibility.

6. Buildings rated on a five-point scale following assessment by

staff of the Building Section of the Ministry of Education.

7. Accommodation— the amount of teaching floor space available

per child for the entire school.

8. Equipment, Library, Radio, Piano—points given

according to the number of books, for example.

9. Family Pattern— the proportion of children sampled in

each school living with two (2) parents, one (1) parent, or guardian,

expressed as a percentage of the school sample.

10. Family Size—number of living children, siblings as well

as cousins and other kin residing with the family.

11. Parents'Reading Habits—rated according to whether

either parent was a member of a lending library, read the newspaper

daily or weekly, and according to the number of books in the home.

12. Parental Interest— number of visits to school, member-

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ship of PTA, attention to term test results, help with home work,

number of visits to school, concern for pupil getting a high-school

p lace.

13. Economic Level of the Community—parents classified

in occupational categories:

Unskilled laborers

Small farm ers

Semi-skilled workers

Skilled workers

C lerical and small p ro p rie to rs

Managerial and professional

14. Progressiveness of Community—whether the community

had certain community facilities such as a public library, electricity,

e tc .

Reid's (1964) analyses began with the Pearson product-

moment correlation of each independent variable with the criterion

achievement score. This was followed by factor analyses which, he

pointed out, contained an element of arbitrariness since, as Burt

(1940) held, the analyst must first have formulated a theory and then

arbitrarily chosen variables to be included in the research; factor

analysis, therefore, cannot of itself permit a determination of causal

influences. Reid's (1964) factor analyses yielded four factors, three

of which he considered significant:

1. A general intellectual factor, which was contributed to

by the intelligence of the child, early schooling, well-trained staff, a

progressive communal environment, and interested and educated

parents with not very low incomes.

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2. A physical and social environmental factor, represented

by good buildings, generous space, small classes, and, mainly, the

small two-parent family.

3. A school-environmental factor, to which size of enroll­

ment, teacher status, early start of schooling, and equipment

contributed.

Reid (1964) initially selected the following variables as the most

promising to include in his final analyses by means of multiple corre­

lation, i.e ., correlation of one criterion variable with a battery of

o th e rs :

1. Parental interest

2. Reading habits

3. Occupational level

4. Progressive community

5. School size

6. Years of schooling

7. Teacher status

8. Maternal family headship

9. Equipment

10. Buildings

11. Class size

Intelligence was omitted since it would have been difficult

to argue whether it should be treated as a cause of attainment or

as an effect of the contributory variables. Items 1 and 2 were combined

into a new variable termed "Parental Education." The ten finally selected

variables and their regression weights are listed in table 15 (Reid, 1964,

p. 1 3 5 ).

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T A B L E 15

REGRESSION WEIGHTS OF PROMISING VARIABLES

V a ria b le Regression Weights

Parental education .5395 School size .1868 Teacher status .1485 Years of schooling .1271 Occupational level .0710 Progressive community .0153 E quipm ent - .0004 Maternal headship - .0979 Buildings - .0055 Small class - .1488

Reid (1964) concluded that the most essential contributing

factor to school achievement was good home background, e.g ., the

education of the parents themselves and their interest in their

children's education. When this was taken into account, socioeconomic

level had very little further contribution to make to predictions, for

it was already covered by parental educational level. Years of school

and qualifications of staff did make a small independent contribution,

and the larger school with good equipment provided a definite advan­

tage. Other variables—progressive community (favorable) and

maternal headship of family (unfavorable)—were considered largely

covered by the previously listed variables so that any additional

contribution appeared insignificant (pp. 135, 136).

Reid's (1964) study looked at the gross effects of primary

schooling. Measurement and computational limitations apparently did

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not allow for profiling of the factors influencing individual pupil

achievement. The factor analyses depended on his (1964) inter­

pretation of the environment, which influenced his decisions

as to what factors to enter in the equation. His analysis was on gross

school rather than individual measures and the results focused on non­

school rather than school effects. The present study, while utilizing

six of the variables of this earlier study, focuses on school effects

and examines these, not on gross measurements of school means but

on individual pupil measures, a procedure made possible by advanced

computing machines.

Roach (1981), in a study of 418 boys and girls aged 10-12

chosen from five urban elementary schools in Jamaica, used mathema­

tics achievement as the dependent variable and sex, family size,

birth order, occupational level, father's presence, preference for

conceptual style, field dependence, reading achievement, and mental

ability as the independent variables. Step-wise regression analyses

yielded mental ability, reading achievement, and family size in that

order as the best predictors of achievement in mathematics.

In a wide-ranging review, Christopher Bagley (1979) in his

article "A Comparative Perspective on the Education of Black Children

in Britain "showed that

1. The educational standards reached by the Jamaican popu­

lation lagged behind those of other islands.

2. One reason for underachievement of Jamaican children

in English schools seemed to be the relatively low level of educational

achievement of their parents (this stood in contrast to the educational

achievement of parents [and their children] from other Caribbean areas).

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3. Jamaican class-room absenteeism was high among boys

and teachers interacted more favorably with and gave more

positive feedback to pupils who were of higher socioeconomic back­

ground, who were fair rather than black, and who were girls rather

than boys (Girling, 1974),

4. Well-motivated children whose parents could afford to

make the sacrifice benefitted from a parallel system of education—

private classes.

5. Authoritarianism and its linked style of teaching

involving rote learning seemed inimical to creativity and breadth of

enquiry. A number of studies from various cultures shows that the

method, on the whole, is not successful in training children in lasting

skills (Simmonds, 1976; Wilson, 1973).

6. Curriculum was not relevant to the needs and culture of

the mass of the population. The curriculum is a Europeanized one

which has ignored the linguistic culture of the masses. Dwyer (1971)

showed that the concept formations transmitted by Jamaican Creole are

severe impediments in taking tests such as the Moray House instru­

m ent.

At this point it seems useful to cite the results of a study

done by Ragbir (1977) in respect to motivation of high-school students.

Although not focused on primary-level pupils, there is some relevance

to this review. Studying academic-achievement motivation in three

types of male Jamaican high-school students, Ragbir (1977) compared

the three types based on certain combinations of high and low levels

of the variables: intelligence, academic achievement, and social class.

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Certain motivational influences were identified which distinguished

between middle-class high-ability high achievers, and middle-class

high-ability low achievers. It was found that a group of working-

class high-ability high achievers showed a middle-class type of

academic-achievement motivation on par with their middle-class high-

ability counterparts. Further, this group of working-class high

achievers showed the middle-class type of academic-achievement

motivation to a greater degree than middle-class high-ability low

achievers. He concluded that,since it has been widely found that the

working-class student performs at a lower level than his middle-class

counterpart of equal intelligence, links between motivation and

achievement could be established.

Smaller Studies

It is relevant and worthwhile at this point to cite the results

of certain smaller studies done by Bachelor of Education students at

the University of the West Indies.

On Attendance/Absenteeism. Clunie (1983), in a study of 110

grade-6 pupils in Primary and All-age schools , found that peak periods

for absenteeism were Fridays followed by Thursdays and the end of

each school term, particularly the Christmas term. Parental attitudes,

parents' low socioeconomic status, teachers' attitudes towards students

and work, streaming (mainstreaming), the program of activities, and

physical conditions of the school were factors contributing to

absenteeism.

Erskine (1979), in a study of 186 grade-8 students from the

All-age schools in rural and urban Jamaica found, among other things.

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that over the period of All-age school exposure, from ages 6^-15

(approximately eight years) many working-class children attended

school for less than 4-5 years. Students of higher socioeconomic status

had significantly less absenteeism than students from lower socioeconomic

status. Absenteeism was greater in the mornings than in the afternoons,

and, during the week, Friday was the peak day, followed by Thursday.

Low nutritional levels and lack of parental interest were also contribu­

ting factors.

On Teachers. Monteith ( 1978), utilizing a sample of twenty

schools and 119 teachers, found that distribution of trained teachers

and teacher retention were more favorably weighted towards urban

than rural and deep rural areas. Retention rates were higher among

older rather than younger teachers, and a significant relationship

existed between teacher retention and certain community and school

factors. Fenton (1979), on a sample of 100 teachers from primary and

preparatory schools in Jamaica, compared with 50 primary-school

teachers in Montserrat found, among other things, that

1. The strongest single influence in the schools was felt

to be the principal.

2. Jamaican primary-school teachers perceived themselves

as performing under very difficult and constraining circumstances

as opposed to preparatory-school teachers who did not thus perceive

themselves.

On St. Thomas, a Parish in the Present Study. Kean (1974)

studied a sample of seven schools on factors influencing school out­

comes. He found them underproducing in terms of percentage of

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pupils in the relative age cohort presented at the Common Entrance

Examination.

Towards Indicators in the Jamaican Educational System

Johanson (1969) proposed an improved information system for

the Ministry of Education in Jamaica. His systems approach implied

considering the problem as a whole. The project produced three

principal results:

1. A criterion model for analysis.

2. A model of a total information system for education,

prescribing units of information grouped into three general areas—

pupils, personnel, and property.

3. A first step toward achieving the total system for

Jamaica, the design of a detailed system of pupil accounting. This

would entail (a) registering all children at age six, (b) numerating

pupils currently enrolled, (c) registering all independent schools,

(d) establishing de facto school zones, (e) revising procedures for

enrollment and admission, and (f) keeping track of all movements by

pupils between schools. Johanson's (1969) study focused on the

organizational (and to some extent— the management) aspects of the

education system.

Quantitative Information

Other relevant literature on Jamaica related mainly to

quantitative information and utilized in this study include:

1. The Annual Report of the Ministry of Education.

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2. Education Statistics (1979/80).

3. The Directory of Educational Institutions, 1976-77.

All are published by the Ministry of Education, Jamaica. The Annual

Report 1975-76 announced that in addition to the administration of the

usual examination, a national test in reading was administered in 256

of the 775 primary schools. The booklet. Education Statistics,

published annually since 1975/76 (except for 1978/79), contains the

fo llo w in g :

1. "Summary of Educational Statistics," showing data on

numbers of educational institutions, by type, together with enrollments

(male/female), and numbers of teachers categorized as trained and

pretrained.

2. "Plant Statistics," showing numbers of institutions by

type and by parish, capacity, enrollment, and the statistic percentage

excess enrollment.

3. "Teacher Statistics," showing teachers in various categories

(i.e. by grade), by type of educational institution, by sex, and by

parish. Teacher-pupil ratios in the various levels of institutions are

also provided.

4. "Student Statistics," showing data on enrollments in the

public institutions at the various levels,by age, by grade, by sex, and

by parish. Data on numbers of repeaters, newcomers, and those

promoted are given. Data on enrollments in private primary and secon­

dary institutions, in the teacher training institutions, and in the

University of West Indies are also provided.

5. "Examination Statistics," showing results of

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(a) the Common Entrance Examination to secondary level

institutions ("High" Schools and "Technical" high schools);

(b) final examinations of the Teacher Training

institutions;

(c) degrees awarded at the University of the West

Indies;

Data at (a) and (c) above are categorized by sex.

6. "Financial Statistics," showing

(a) size of the education budgets—capital and

recurrent—for the year of interest as compared with pro­

visions for other Ministries and the Departments not

attached to Ministries;

(b) the functional classification of the Government's

b u d g et;

(c) a program allocation of the Ministry of Education's

budget for the year of interest and for the preceding two

years;

(d) a three-year overview of the changes in the levels

of allocations to the various programs within the Ministry of

E d u catio n .

Educational Television: Jamaica

It is noteworthy that this media form was not in the schools

in 1964, the year of Reid's study. Introduced in 1965 the success of

Educational Television (ETV), in terms of utilization, has been less than

outstanding. Ministry of Education 1978-80 reports concluded that,

although the programs were well received, there were major problems

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contributing to the under-utilization of ETV in the schools. These

centred around:

1. Too few sets in schools (ninety-four schools were, at

the time, requesting sets).

2. Poor maintenance of sets.

These factors contributed to scheduling problems. Table

16 shows the results of a relevant survey.

T A B L E 16

ETV UTILIZATION SURVEY— 1978/79 RESULTS

No. of No. N o. of N o. o f Schools School Schools O w ning Sets D e fe c tiv e Without T y p e Responding Sets Owned Sets Electricity Other

P rim ary 74 41 58 37 6 2 A ll-A g e 139 45 52 35 23 3 Secondary 14 13 30 20 0 0 and High

T o tal 227 99 140 92 29 5

Source: Jamaica, Ministry of Education, "Education Broad­ casting Service ETV Reports, 1978-80." (Mimeographed).

School L ib ra rie s : Jamaica

The "Schools Library Service Annual Report (1979-80)" lists

several relevant points. First is that the majority of older primary

schools were still without suitable library accommodation. Next, new

schools with library accommodation were given generous bookstocks.

Third, some older schools were provided library rooms through the

efforts of the Parent/Teachers' Associations. One such library room

was opened at the St. Richard's Primary School in 1979. Fourth, keen

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interest was shown by some principals and teachers in getting their

libraries to function despite drawbacks. Data on book stocks supplied

to primary schools of all categories taken together are shown in table 17.

T A B L E 17

SCHOOLS WITH BOOKSTOCKS, SUMMER 1979

Number of Books Received

U p to 500 500 to O ver Total Number of 1000 1000 Schools Served , by Parish

Parish Number of Schools Serviced

K ingston 23 11 9 43 S t. A n d rew 47 18 12 77

S t. Thomas 25 10 2 37

Total 95 39 23 157

Source: Jamaica, "Schools Library Service Report for Period April 1979 to March 1980," Kingston, Jamaica. (Mimeographed).

Sum m ary

This literature review provides an historical and descriptive

overview of economic, demographic, and social indicators. The dis­

cussion on educational indicators located these as one segment of the

social indicators which could be partitioned according to the elements

of the systems model. They could be classified as:

1. Context indicators

2. Input indicators

3. Process indicators

4. Output indicators.

In terms of the management of the formal education system.

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some of these indicators, particularly context indicators such as socio­

economic status, are not directly "manipulative." The "manipulative"

indicators are the "inputs" and "processes" of the school system.

Focus was placed on the question of whether there could be a single

significant composite indicator, and whether indicator variables should

be utilized in economic analyses.

This chapter has reviewed literature on the influence of

school as well as home effects on the educational product. It has

established (1) that schooling is a necessary input; (2) that there are

differentiated effects of schooling depending on teacher training,

ability, experience, remuneration, and motivation, and their interaction

with pupils; (3) that curricula, media, equipment, and adequacy

of accommodation are important manipulative variables also; (4) that

pupil motivation, whether engendered by the home or the school, is

of critical importance; (5) that where motivation is not fostered by

the home, it may be encouraged by the school; and (6) that there are

physical and developmental variables associated with sex and age to

be borne in mind. As measured by research the impact of these variables

may differ in significance from country to country and from time to time.

In so far as the Jamaican educational universe is concerned,

it has been shown that the conditions generated by poverty and the

cumulative effects of poor schooling militate against high achievement in

the primary-school population, since the important home effects are thus

adversely affected. The school effects in primary education could also

be regarded as deficient in certain areas. Intelligence of the Jamaican

child must therefore be understood as innate ability fundamentally

determined by genetic endowment but moderated by environmental

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factors from conception onwards (Vernon, 1961).

In so far as a statistical information system for Jamaica is

concerned, there has been a proposal for an information system—a

model of a total information system and the design of a system of

pupil accounting. It is also shown that the Ministry of Education

compiles considerable data and a certain number of statistics on the

educational system. The present study searches for a limited number

of indicators, statistics of normative interest, descriptors proven by

research, where necessary, to be capable of providing early evidence

of progress towards or regression from primary-education objectives.

Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. CHAPTER III

METHODOLOCY

Overview

This was, first, a correlational/predictive study which inves­

tigated the extent to which variations in certain primary-schools,

inputs and pupil personal variables corresponded with variations in

the achievement scores of a sample of Jamaican primary-school pupils

in the 1980 Common Entrance Examination.

Second, it was an exploratory field study aimed at securing

the perceptions of a sample of primary-school teachers regarding sig­

nificant indicators of educational performance in the primary-school

system in Jamaica.

Third, drawing on the findings of these two studies and on

the relevant literature, the study proposes a set of indicators for

monitoring the primary-school system in Jamaica.

The Correlational/Predictive Study

The correlational study aimed at identifying from among

selected primary-school inputs and pupil personal variables those

which covaried with or seemed predictive of achievement in the Age

Eleven Plus (11+) Common Entrance Examination to high schools in

three parishes in eastern Jamaica. It studied the behavior of these

variables in schools and children in urban area as opposed to schools

80

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and children in the rural areas of the parishes, utilizing for greater

differentiation a stratified sample of the ten best and of the ten least

performing schools in both areas.

As a p re lim in a ry , u tiliz in g the resu lts o f the Common Entrance

Examination of January 1980, a correlational analysis was done to deter­

mine the extent to which scores on the English and mathematics tests

covaried with the scores on the test of mental ability. The means and

standard deviations were secured and compared with the findings of

Manley's 1963 study done on 1959 data. The means of the ten best per­

forming urban schools were also compared.

Next, utilizing the results of the three batteries of the Common

Entrance Examination of January 1980 as the dependent variables, and

a selection of thirteen school input and pupil personal variables as inde­

pendent variables, identification was made of those independent variables

correlating most highly with the three sets of test scores.

Investigation also was made by discriminant analysis of the vari­

ables which separated the top 33 from the bottom 33 percent of the urban

sample and the top 25 from the bottom 25 percent of the rural sample based

on individual total scores. These were the percentages which by observa­

tion of the histograms and initial analyses best differentiated the groups.

Selection of Sample Schools

The Common Entrance Examination is taken each year by pupils

from public primary and private preparatory schools who are not less than

ten years nine months of age or more than thirteen years of age on the

first day of September that year. In January 1980, a total of 38, 106 pupils

islandwide sat the examination with 35,697 ( 12,718 boys and 22,979 girls)

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sitting from the public schools and 2,409 from private independent schools.

The sample of schools was taken from three eastern parishes of

Jamaica—Kingston, St. Andrew, and St. Thomas. Using a classification

of " rural” and ” urban” schools developed in the Ministry of Education,

Jamaica, in 1976,it was observed that, among the three parishes, there

was an acceptable ratio of urban to rural schools. Data in table 18 bear

out this fact, showing eighty urban and seventy rural schools (including

two special schools) in the three parishes.

TABLE 18

NUMBER OF SCHOOLS IN THE PARISHES OF KINGSTON, ST. ANDREW, AND ST. THOMAS CLASSIFIED AS URBAN (CITY/TOWN) OR RURAL/REMOTE BY MINISTRY OF EDUCATION (1976)

Number of Rural/ Parish Numcbe/- ° f U rban Total Schools Remote Schools

Kingston 27 1 28

St. Andrew 48 31 79

St. Thomas 5 38 43

Total 80 70 150

As school factors contributing to pupil achievement were a

prime focus of study, it was decided to stratify the schools sampled

based on "measure of success” in the Common Entrance Examination.

Success was not measured in terms of numbers of candidates awarded

high-school places, since it was established that a few schools screened

candidates while others did not. Rather, success was measured by the

percentages of awardees to numbers of students in the grades from which

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candidates would be drawn, i.e ., grades four to six in the 1979/80

school year-

Utilizing this measure, success was observed not only on

performance in the 1980 Common Entrance Examination but also in the

Common Entrance Examination of 1979. Appendices D and E show the

performance of all schools in the three parishes entering pupils in

the Common Entrance Examinations of January 1979 and 1980.

Based on this measure, therefore, an initial selection was made of a

total of forty schools—ten urban and ten rural schools with the highest

percentage of awards to number of students in the relevant grades and

ten each of the urban and rural schools with fewest or no awards.

Comparison of the schools in appendix F shows that the best

performing schools in urban areas differed considerably from the best

performing schools in rural areas in 1980 (15 percent-34 percent awards

to students in grades 4-6 in urban areas as against 5 percent-10 percent

in rural areas).

The selection of schools with the fewest awards was made from

urban area schools by random selection from schools obtaininq 5 per­

cent awards and below. In the case of rural areas, a random selection

was made from schools obtaining zero awards. A description of the

schools follows.

Description of Sample Schools

The ten best performing urban schools. The ten best schools

together with their grades 1-6 enrollments for 1979/80 are shown in

table 19. The group includes seven very large schools—Dunrobin,

Mico, New Providence (the largest, with 2,383 pupils in two shifts).

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TABLE 19

TEN BEST PERFORMING URBAN SCHOOLS (Grades 1-6)

Schools Enrollments 1979/80

Parish of Kingston

Alpha II - Jessie Rippol Primary 598

St. Aloysius Primary 1,406

St. George's Girls All-Age & Infant 759

Parish of St. Andrew

Dunrobin Primary 1,778

Hope Valley Experimental Primary & infant 522

Mico Practising All-Age 917

New Providence Primary 2, 383

Pembroke Hall Primary 1, 495

St. Richard's Primary 1,081

Tarrant Primary 1, 507

Pembroke Hall, St. Aloysius, St. Richard's, and Tarrant. There are

three medium-sized schools—Alpha II - Jessie Rippol, Hope Valley

Experimental, and St. George's Girls'.

These schools may be classified as magnet schools to a greater

or lesser degree, being renowned for their successes in the Common Entrance

Examination. Some, like St. George's, have a long history in this regard.

Alpha II (orJessie Rippol, a school named in honor of a nun), St. Aloysius,

and St. Richard's are Roman Catholic schools known for their discipline.

Mico Practising, an All-age school taking pupils up to age 15, is

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attached to the Mico Teachers' College. Hope Valley Experimental is

classified as a Special school as it maintains special relationship with the

U n iversity of West Indies' Polio Rehabilitation C entre, admitting

physically handicapped as well as normal children. Mico, St. Aloysius

and St. George's are downtown schools. Dunrobin and St. Richard's

are located in uptown middle class areas. All these schools draw

children from all socioeconomic levels in a varying mix of numbers. Alpha

II was omitted from analyses involving canonical correlation and discri­

minant analysis due to difficulties in securing pupil data from the school.

The ten best performing rural schools. The ten best rural

schools together with their grades 1-6 enrollments for 1979/80 are listed

in table 20. There are four relatively large schools. Lawrence Tavern,

the largest school, is followed by Duckenfield, Lyssons, and Trinity-

ville. The other six schools are relatively small. Most of these

schools are located in very rural areas. At Red Hills and Lawrence

Tavern, there is some degree or urbanization. Lyssons is located close

to the town of .

Ten urban schools—fewest awards. The ten urban schools

with fewest awards together with their enrollments are listed in table 21.

Two schools— Dupont and Seaward—are very large. Next in

descending order of enrollment size are St. Peter Claver, Tavares

Gardens, Allman Town, Mountain View, and Balcombe Drive. The last

three— Mannings Hill, Gordon Town, and Boys' Town are small schools.

The political violence in Kingston during the 1979/80 period affected all

schools and Boys' Town very significantly. This school had registered

enrollments of 280 in both 1976/77 and 1977/78.

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TABLE 20

TEN BEST PERFORMING RURAL SCHOOLS (Grades 1-6)

Schools Enrollments 1979/80

Parish of St. Andrew

Dallas All-Age 375

Lawrence Tavern Primary 1,080

Red Hills All-Age 404

Parish of St. Thomas

Dalvey Primary 247

Duckenfield Primary 742

Golden Grove Primary & Infant 330

Johns Town All-Age 142

Lyssons All-Age 677

Middleton Primary 310

Trinityville Primary 661

All these schools are located in low-income-earning areas of the

city, with Mountain View being perhaps on the upper end of the scale.

Gordon Town and Mannings Hill are located on the outskirts of the city.

Ten rural schools--fewest awards. The rural schools with no

awards selected for the study together with their enrollments are shown

in table 22. All of these are relatively small schools. Three or four

are very remote. After repeated unsuccessful attempts to secure

pupil data from Mt. Felix it was decided to omit this school from the

analyses involving canonical correlation and discriminant analysis.

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TABLE 21

URBAN SCHOOLS WITH FEWEST AWARDS (Grades 1-6)

Schools Enrollments 1979/80

Parish of Kinqston

Allman Town Primary 800

Boys Town All-Age 79

Parish of St. Andrew

Balcombe Drive All-Age 514

Dupont Primary & Infant 1,184

Gordon Town All-Age 256

Mannings Hill All-Age 261

Mountain View Primary 761

St. Peter Claver Primary 942

Seaward All-Age 1, 570

Tavares Gardens All-Age 940

Summary. The sample of the fo rty schools chosen included

schools from each of the four types in the primary education system.

There were sixteen primary schools, three primary schools with Infant

Departments, twenty All-Age schools, and one All-Age school

with an Infant Department. In addition, three schools operating double

shifts were included. These represented the response of the education

system to enrollment pressures. Table 23 shows the distribution

of these types of schools among the performance groupings of the

sample as well as the overall distribution for the three parishes.

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TABLE 22

RURAL SCHOOLS WITH NO AWARDS (Grades 1-6)

Schools Enrollments 1979/80

Parish of St. Andrew

Bowden Hill All-Age 111

Grove Primary 168

Halls Delight All-Age 234

Mt. James All-Age 297

Westphalia All-Age 104

Parish of St. Thomas

Bethesda All-Age 240

Hayfield All-Age 70

Mt. Felix All-Age 89

T hornto n All-Age 159

Whitehorses A ll-A ge 316

The next section discusses the determination of samole size

and the number of subjects for each of the two studies. The method of

securing the subjects is described as well as the statistical parameters

for the sample and the tests.

Sampling of Pupils

Table 24 shows that of the 150 urban and rural schools in the

population, 146 put forward 14,072 candidates in the Common Entrance

Examination of 1 980, gaining 3,177 awards. Overall, urban areas secured

23 percent awards over entries while rural schools secured 15 percent

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TABLE 23

DISTRIBUTION OF THE FOUR TYPES OF SCHOOLS IN THE STRATIFIED SAMPLE

Performance Primary Primary All-Age All-Age Grouping /Awards with Infant with Infant

U rb an Most 7 1 1 1

Urban Fewest 3 1 6 -

Rural Most 5 1 4 -

Rural Fewest 1 - 9 -

Sample Total 16 3 20 1

Total School Types in the Three Parishes 1979/80 59* 8* 69 14

* Includes special schools

awards over entries. Four schools put forward no candidates.

For certain analyses both urban and rural areas were treated

as populations. Utilizing the tables for determining sample size from a

given population developed by Krejcie and Morgan ( 1970), a sample of

302 would have been adequate for a signifiance level of a = .05 level

in respect of the rural areas. A sample of 319 cards with achievement

scores was drawn and complete data were secured in 2 85 cases. The

urban population of entrants was 12,673 from which— using the sample

table mentioned above—a sample of 373 would have been adequate. A

sample of 729 cards with achievement scores was actually drawn and

complete data secured on 517 cases. Appendices C and H present

details by stratum and by school of the sample drawn. An overall total

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TABLE 24

1980 COMMON ENTRANCE EXAMINATION (Entries and Awards from Urban and Rural Schools)

No. of No. of No. of Category Schools Entries Awards

Urban schools 79 12,673 2, 968

Rural Schools 67 1,399 209

Total 146 14,072 3,177

of 802 cases was achieved for the multivariate analyses, i.e ., canonical co­

relation, and discriminant analysis.

For the total of nineteen variables originally projected, 190-285

cases (with a ratio of ten-fifteen subjects for every variable) would have

been necessary for the stability of the correlation matrices. (See Kendall,

1975, p. 11 for a recommended ratio of ten to one— 10:1.) For the sixteen

variables finally utilized, a total of between 160-240 cases was the actual

requirement. Obtaining 285 complete cases for the rural areas and 517

for the urban areas—a grand total of 802— ensured the soundness of the

multivariate analyses.

The minimum effect size set for the Pearson r product-moment

correlation test was ± .30. This is considered to be of medium effect.

The test for the null hypotheses was set at ci= .05. With these two

parameters and a sample of 1,048 subjects the power of the test was .99.

For the Analysis of Variance test, the level for the null

hypothesis was set at a = .05. The power achieved on the test which

involved 466 subjects was .99. Power is defined as the probability of

rejecting the null hypothesis when it is in fact false (Welkowitz, Ewen,

6 Cohen, 1962, chapter 4).

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The sample was drawn by random selection of score cards of

entrants. A table of random numbers as well as manual random selection

was used, as cards were filed in two ways. Award cards were filed

under forty-six high schools and four comprehensive schools. Non­

award cards were batched under the schools from which the pupils entered.

Data Gathering— Correlational Study

The following data were secured from the Common Entrance score

cards of 1980 :

1. Mental A bility test scores

2. Mathematics test scores

3. English test scores

4. Sex

5. Age

6. Parent's occupation

7. Num ber of years in school (in most cases)

8. W hether there was previous school experience in P rep arato ry

or Basic schools.

A sample card is included in appendix I. Where data item number 7,

number of years in school, was not secured from the cards, it was

necessary to seek it directly from the schools.

The schools were approached by letter and followed by visits for

the following data items:

9. Number of sessions attended for the 1 978/79 school year, the

year preceding the term in which the candidates sat the

examination.

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10. Grade from which the individual pupil sat the Common

Entrance in January 1980.

11. Qualifications of the teacher of the particular grade in

1980.

12. Years of experience as teacher.

13. Whether use was made of Schools'Library Service and

whether the school had a lib ra ry .

14. Whether use was made of television in the Common

Entrance classes.

15. Qualifications of the principal.

16. Years of experience as principal.

The following information was obtained from the Ministry of

Education :

17. Pupil/teacher ratios for the school years 1977/78 - 1979/80.

18. Percentage of trained teachers at the school 1977/78 - 1979/80.

19. Classroom accomodation.

Obtaining the Quantitative Indices: Criterion Variables 1-4

The test scores were all numbers which together formed the

total scores. The total score was used in differentiating the groups for

the discriminant analyses.

Obtaining the Quantitative Indices: Predictor Variables 1-16

Variables 1 and 2. Sex was coded one (1) for male and two (2)

for female. Age presented no difficulty.

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Variable 3. Parent's occupation presented difficulty. For

example, occupations quoted on the cards such as " housewife" and

11 farmer," being general rather than specific, meant that a range of

incomes and education could be involved. After several fruitless

attempts to secure Jamaican guidelines to categorizations, the re­

searcher decided to classify occupations in broad bands related to

the 1955 McCuire-White Social Class index (see appendix C) and the

occupational categories of the Annual Jamaica Labour Force Survey.

These bands were coded:

1. 10— Lowest paid categories—primary education only,

assumed.

2. 20--A broad band covering assumed secondary-level

education and lower-middle and middle-middle incomes.

3. 30— Professionals and upper-middle, lower upper-class

incomes.

The list of occupations together with their coding is given in

appendix J. Nonspecific occupations were placed in category 20.

Variables 4 and 5. Number of years in school presented no

difficulty, neither did number of years in Preparatory, Infant, or

Basic School.

Variables 6 and 7. Number of sessions as well as grade from

which the Common Entrance was sat presented no difficulty.

Variable 8. Teacher's qualification was coded as follows:

Code 1 = Pre-trained

Code 2 = Teacher in the In-Service Teacher Education Thrust (ISTET) program

Code 3 = Trained Teacher or Intern

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Code 4 = Trained teacher with Vocational Training

Code 5 = Trained teacher with Management Training

Code 6 = Teacher with the Certificate in Education

Code 7 = Teacher with a First Degree

Variable 9. Number of years in teaching presented no coding

difficulty.

Variables 10 and 11. Use of Library and Television was each

coded one (1) for No, two (2) for Yes.

Variable 12. Pupil-teacher ratios for grades 1-6 were secured

for three years and averaged; the average was used.

Variable 13. Percentage of trained teachers was secured,

averaged over three years,and the average was used.

Variables 14 and 15. Principal1 s qualification was coded as for

teacher's qualification: principal's years of service as principal

presented no coding difficulty.

Variable 16. Degree of overcrowding was coded on the following

basis: data on classroom size collected by the Ministry of Education in

1978 were used to derive the desirable enrollment level based on 10

square feet per pupil (cf. 9 square feet per pupil in Reid's (1964)

study). The actual enrollment was divided by this number and the

resulting quotient was the number used. Modifications were made in a

few cases where these were obviously needed.

Qualitative Data

Finally, the collection of data from the schools included a request

for the principal's comments on the factors which negatively or positively

influenced performance in the Common Entrance Examination.

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Categorization of the Predictor Variables

The predictor variables may be divided into pupil variables and

school variables.

The pupil variables were:

1. Sex

2. Age

3. Parent1 s occupation

4. Preparatory school experience

5. Number of years at the particular school

5 . Number of sessions attended

7. Grade from which the Common Entrance was sat.

The school variables were:

1. The grade teacher's qualification

2. The grade teacher1 s experience

3. Use of lib rary

4. Use of television

5. Teacher/pupil ratio for the school, 1977-80

6. Percentage trained teachers, 1977-80

7. Principal1 s qualification

8. Number of years as principal

9. Degree of overcrowding

Rationale for Selection of the Variables

Chapter 2 presented literature on the variables utilized in the

study. It is useful to restate that the variables examined were school

factors directly manipulable by those responsible for the provision of

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education. No attem pt was made to p ro file, measure, and correlate

variables pertaining to the students' homes and communities. In respect

to school variables, it was not possible, though desirable, to measure

certain other variables identified in the literature as having a bearing on

pupil achievement. These included pupil motivation and supply of text

books.

Environmental Factors to Be Considered

Mention should be made of the very unstable environment

existing in urban Kingston and St. Andrew, and to a lesser extent

throughout Jamaica in 1979-80. Political violence, with regular outbreaks

of gunfire in low income areas, led to reduced enrollments in many

schools and must have had its effects on pupil performance.

Strength, Relevance, and Degree of Differentiation of Certain Variables of the Study

Data collection proved to be very difficult. Numerous visits had

to be made to certain schools. Some records had been misplaced or were

lost, due in one case to a break-in of the principal's office. In the

larger schools, teachers were not passing in registers to the principal's

office at the end of the school year as required. Smaller and rural

schools presented less difficulty in this matter. Principals pointed out

that records were easier to maintain when the Ministry of Education had

required them to prepare annual Class Lists. A sample list is shown in

appendix K. This class list summarized a good deal of the required

data which otherwise could only be obtained by reference to the

Attendance Registers and other registers in the school.

Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. 97

Finally, as mentioned earlier, complete pupil and school data

were possible on only thirty-eight schools. The hypotheses requiring

complete data were therefore tested on thirty-eight schools and a

total 802 pupils.

Number of years in preparatory school also presented uncertain­

ties. It appeared that these data were not consistently entered on the

c a rd s .

Information on Library and Television was not sufficiently

differentiated for the schools. Measures were not secured for the

number of books per pupil or numbers of books, other than readers,

which pupils were required to read. Data on hours of television

exposure were not secured, so these data became dichotomous—whether

or not TV was used with the Common Entrance class. It was decided,

therefore, to omit these from the analyses. Comment is, however,

offered on the variables in view of their perceived importance to and

potential for the learning process. The data would be useful in the

final conclusions and recommendations.

Mention should be made of the extra coaching which CEE pupils

customarily receive within and outside their schools. School principals

were questioned about this. After school and holiday classes were held

in most schools for a fee. Two schools had separate day-time classes.

The Exploratory Study

The population for this area of the study comprised originally

approximately 700-750 teachers drawn from the forty schools sampled.

Principals felt that those teachers (approximately 300) working in the

Common Entrance grades were the ones who would be most qualified to

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respond. Opinionnaires were circulated to 300 teachers and question­

naires were received from 177 teachers. This response gave the sample

validity at a significance level of a = .0 5 .

The letter (sample in appendix L) sought the teachers'

ratings of a total of sixteen indicator items broken down into thirty-one

responses specifying (1) school level, (2) parish level, (3) islandwide

level. These were to be rated on a continuum of 1-5, 1 beinq most

important. Table 25 classifies and lists these sixteen indicator items.

In addition, teachers were asked to add any indicators which

they considered to be important and rate these indicators also on a

continuum of 1-5, 1 being most important. More than one attempt had to

be made to secure return of the questionnaires. It became apparent

that returns were best received when the researcher circulated the

questionnaire and waited for the completed responses. Stamped self-

addressed envelopes did not help very much, though small tokens such

as book marks did help.

Hypotheses and Statistical Analyses Used

Fourteen hypotheses were originally proposed but thirteen were

finally tested. Three hypotheses—hypotheses 1(a)-1(c)—were tested

utilizing the Pearson product-moment correlation test; foui hypotheses

2(a)-2(d)—by the analyses of variance test; two, by canonical correla­

tion and four, by the discriminant analysis tests. The fourteenth test

involving discriminant analysis became unnecessary, when no significant

difference was found among the school means of the total test battery of

the 1980 CEE for the ten best performing urban schools.

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TABLE 25

SIXTEEN INDICATORS PRESENTED FOR RATING TO THE SAMPLE OF TEACHERS

Indicators Subsets

Systems Accessibility 1. Ratio of enrollment to school-age population

2. Degree of overcrowding by school

3. Percentage of overcrowded schools

Systems Inputs 4. Teacher/pupil ratio by trained teachers

5. Overall teacher/pupil ratio

6. No. of library books per pupil

7. No. of hours of educational tele­ vision

Systems Process 8. Percentage of teacher turnover

9. Percentage of pupils attending 90 percent of school sessions

10. Efficient principal

Environmental 11. Index of malnutrition

12. Percentage of unstable families

Systems Outputs 13. Crade-by-grade average achieve­ ment in English

14. Crade-by-grade average achieve­ ment in mathematics

15. Percentage of students achieving below 50 percent in English and in mathematics

16. Percentage of students passing Common Entrance Examination

Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. 100

The hypotheses stated in the null form are as follows:

Hypotheses 1(a)-1(c)

Hypothesis 1(a) reads: There is not a significant correlation

between the scores of the intelligence and the English tests of the

1980 CEE, fo r th e total sample o f 1,048 p u p ils .

Hypothesis 1(b) reads: There is not a significant correlation

between the scores of the intelligence and the mathematics tests of

the 1980 CEE,for the total sample of 1,048 pupils.

Hypothesis 1(c) reads: There is not a significant correlation

between the scores of the English and mathematics tests of the 1980 CEE,

for the total sample of 1,048 pupils.

The significance levels for the above three hypotheses are

Y = ± . 30 and a = .05.

Hypotheses 2(a)-2(d)

Hypothesis 2(a) reads: There is not a significant difference

among the school means of the total scores of the 1980 CEE test battery,

for the ten best performing urban schools. The statistical test is

analysis of variance and the significance level a = .05.

Hypothesis 2(b) reads: There is not a significant difference

among the school means of the mathematics test scores of the 1980 CEE,

for the ten best performing urban schools. The statistical test is analysis

of variance and the significance level a= .05.

Hypothesis 2(c) reads: There is not a significant difference

among the school means of the English test scores of the 1980 CEE, for

the ten best performing urban schools. The statistical test is analysis of

variance and the significance level a = .05.

Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. 101

Hypothesis 2(d) reads: There is not a significant difference

among the school means of the intelligence test scores of the 1980 CEE,

for the ten best performing urban schools. The statistical test is analysis

of variance and the significance level is cl = .05.

Hypothesis 3

There is not a statistically significant canonical correlation

between the linear combination of thirteen predictor variables—that is,

thirteen pupils' personal and school variables—and the linear combina­

tion of the criterion variables of intelligence, arithmetic, and English

scores of the Common Entrance Examination 1980. The thirteen

predictor variables were:

1. Pupil1 s sex

2. Pupil1 s age

3. Parent1 s occupation expressed as an index of socioeconomic status

4. Number of years at the particular school

5. Number of sessions attended in 1978/79

6. Crade from which the 1980 Common Entrance Examination was sat

7. Qualifications of the grade teacher

8. Length of service of the grade teacher

9. Overall teacher/pupil ratio of the school, averaged over the three-year period— 1977/78 to 1979/80

10. The average percentage of trained teachers at the school — 1977/78 to 1979/80

11. Principal's qualifications

12. Principal's years of service as principal

13. Degree of overcrowding

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Hypothesis 4

There is not a statistically significant canonical correlation

between the linear combination of twelve predictor variables— that is

twelve students' personal and school variables—and the linear

combination of the criterion variables of intelligence, arithmetic, and

English scores of the Common Entrance Examinations of 1980. The

predictor variables are those listed in Hypothesis 3 with the exclusion

of parent's occupation which is expressed as an index of socio­

economic status. The significance level is a = .05.

Hypothesis 5

There is no linear combination of input variables which

significantly separates the top 33 percent from the bottom 33 percent

of pupils sampled in the urban schools. The statistical test is discrimi­

nant analysis and the significance level is a = .05.

Twelve input variables are utilized. These are:

1 . Pupil's age

» 2. Pupil's sex

3. Number of years at the particular school

4. Number of sessions attended in 1978/79

5. Crade from which the 1980 Common Entrance Examination was sat

6. Qualification of the grade teacher

7. Length of service of the grade teacher

8. Overall teacher/pupil ratio of the school averaged over the three-year period 1977/78 - 1979/80

9. The average percentage of trained teachers at the school 1977/78 - 1979/80

10. Principal's qualifications

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11. Years of experience as principal

12. Degree of overcrowding

Hypothesis 6

There is no linear combination of input variables which

significantly separates the top 33 percent from the bottom 33 percent of

the pupils sampled in urban schools. Thirteen variables are used, i.e .,

the variables in Hypothesis 5, with socioeconomic status added. The

statistical test is discriminant analysis and the significance level is

a = .0 5 .

Hypothesis 7

There is no linear combination of input variables which

significantly separates the top 25 percent from the bottom 25 percent of

pupils sampled from the rural schools. The twelve input variables are

those listed for Hypothesis 5. The statistical test is discriminant

analysis and the significance level is ct = .05.

Hypothesis 8

There is no linear combination of input variables which

significantly separates the top 25 percent from the bottom 25 percent of

pupils sampled from the rural schools. Thirteen input variables are

used, that is, those variables listed in Hypothesis 5, with socio­

economic status added. The statistical test is discriminant analysis and

the significance level is a = .05.

Analytical Methodology

The statistical methods used were the most appropriate for

examining the relationships of the variables under study. These were:

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1. Pearson Product-Moment Correlation Coefficient

2. Analysis of Variance

3. Canonical Correlation

4. Discriminant Analysis

5. Categorical Scaling

Pearson Product-Moment Coefficient

The Pearson product-moment correlation technique produces a

single descriptor statistic which quantitatively describes the degree to

which change in the values of one variable parallels a degree of change

in the other, indicating also whether the companion change is in a

similar (positive) or opposite (negative) direction, or whether there is

no significant co-variance. This method was used to determine the

covarying relationships among the scores of the three batteries of the

Common Entrance Test.

Analysis of Variance

The analysis-of-variance technique provides a statistical answer

to the question of whether there is a significant difference in the

measures on the dependent variable when two or more groups are

involved. In the case of two groups, the t-statistic is usually used.

The analysis-of-variance technique is commonly employed when three or

more groups are involved and has its greatest usefulness when two or

more independent variables are studied (Runyon & Haber, 1977, p. 288).

Utilizing the F-ratio, this technique determines whether the variance

between the groups is more significant than the variance within groups.

It answers the question of whether or not there is an indication of an

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overall effect of the experimental treatments before specific hypotheses

are investigated.

In this study, analysis of variance was used to determine

whether there were significant differences in school means of the ten

best performing urban schools on the three batteries of the test and

the total test scores of the 1980 Common Entrance Examination.

Canonical Correlation

Canonical correlation is described as the generalization of

multiple-regression analysis to any number of dependent variables.

Canonical correlation utilizes K independent or predictor variables and

M dependent or criterion variables.

Through the least squares analysis two linear composites are formed, one for the independent (predictor) variables X and one for the dependent (criterion) variables Y. The correlation between these two composites is the canonical correlation Rc. The square of the canonical correlation R^ is an estimate of the variance shared by the two composites. The canonical coefficient is the maximum corre­ lation possible between the two sets of variables. (Kerlinqer & P ed h azu r, 1973, p p . 3*11-342)

In illustrating its application, the above cited authors state that

more than one source of common variance can be identified and analyzed.

The first and largest source of variance is extracted first, then the next

largest source of variance left in the data is identified. The respective

coefficients are the indices of the relationship (pp. 344-345).

The appropriateness of the canonical correlational technique

to this analysis may best be appreciated by reference to the critique

of the Coleman R eport by Elazar j . Pedhazur (1982) . He points out

that multiple-regression analysis, the methodology used in the Coleman

study, is more validly applied to experimental rather than non-

experimental research. In experimental research the independent

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variables are manipulated and the dependent variables observed; there­

fore causal assumptions may more validly be made. In non-experimental

research such as the Coleman study, correlation, even though substan­

tial, does not establish direct relationships because it is difficult:

1. to untangle the effects of each variable

2. to know whether variables are serving as proxies for the

true variables (p. 175).

The incremental partitioning of variance of multiple regression

rests on a crucial question: In what order are the variables entered

into the equation? Pedhazur (1982) suggests that because one inde­

pendent variable precedes another independent variable in time, this

fact is not sufficient justification for regarding it as causal and thus

entering it first.

In commenting on the statistical methodology applicable to non-

experimental (or experimental) multi-dimensional research, Pedhazur

( 1 982) suggests that studying it piecemeal does not hold promise of

understanding it. Multi-variable phenomena require analytic methods

commensurate with them (p. 686). The development of the computer

allows for the utilization of procedures such as canonical analysis, as

developed by Hotelling in 1 936 (Pedhazur, 1982, p. 720). This

technique tests the correlations of two sets of variables simultaneously

rather than sequentially. Canonical correlation was therefore consid­

ered most appropriate to this study.

Discriminant Analysis

Having established through canonical correlation that there

was a significant combination of predictor variables covarying with the

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criterion variables, discriminant analysis was used to isolate those vari­

ables which separated the top segment of pupils from the bottom

segment in urban and in rural areas. The discriminant analysis

technique, developed by R. A. Fisher in 1936 (Pedhazur, 1982), enables

the weighting of individual scores so as to lead to maximum discrimination

between the groups and identification of the dimensions along which the

groups differ (see Pedhazur, 1982, pp. 692-717).

Analysis of Teacher Responses by the Categorical Scalings Model

The categorical scaling model was appropriate for this situation

where stimuli were presented to teachers for ranking on a continuum of

importance—that is, 1-5, with 1 being most important. Torgerson (1955,

p. 207) identifies three modes for eliciting judgments:

1. Replication over trials within a single subject.

2. Replication over individuals—each stimulus being judged

once by each subject.

3. Mixed models involving replication over both individuals and

trials, each stimulus being judged several times by each subject.

The second method was the one utilized in this study.

Torgerson ( 1955) also notes that a great number of analytical

procedures dealing specifically with categorical judgments have been

devised (p. 214).

Categorical scaling commences with a matrix showing the frequency

with which each stimulus is rated in each category. From this matrix

cumulative frequencies and proportions are derived. These are converted

into normal deviates (z scores) . A matrix of intercorrelations among

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these deviates is subjected to matrix algebra procedures, the first

eigenvector giving positions of the stimuli on an arbitrary interval scale.

In the analysis, the scale was modified by addition of a constant so that

the lowest scale value was zero.

Data Analysis

All data collected were recorded on the xerox sigma 6 computer

at Andrews University, Berrien Springs, Michigan and carefully rechecked.

Analyses utilized the packaged BMDP statistical programs.

The Family of Indicators

The survey identified ratings of the indicators presented to the

teachers of the schools which were sampled. Other indicators were

suggested by them as well. The opinions of principals on factors

contributing to success in the Common Entrance Examination were also

secured. The correlational studies as well as the discriminant analyses

were performed to identify input variables of greatest importance. The

significant variables identified were gauged against the findings of the

literature review of chapter 2. The family of indicators was formulated

against this theoretical and empirical background.

Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. CHAPTER IV

FINDINGS OF THE STUDY

This chapter presents the results of analyses of data gathered

in a correlational study of pupil performance in the Common Entrance

Examination (CEE) of 1980. The aim of this investigation, the first and

major segment of a two-part study, was to examine the extent to which

certain school and personal variables were predictive of or co-varied

with test scores of the Common Entrance Examination of January 1980.

The second segment involved the collection and analysis of data on an

opinionnaire circulated to a sample of teachers in the schools selected

for the first part of the study.

Results— Correlational/Predictive S tu d y

Thirteen hypotheses were tested on the data gathered for the

correlational/predictive segment of this study. Hypotheses 1(a)-1(c)

tested the degree of correlation among the scores for all entrants on the

three batteries of the 1980 Common Entrance Examination. The Pearson

product-moment correlational technique was utilized for these hypotheses.

Hypotheses 2(a)-2(d) established by analysis of variance whether there

was a significant difference among the school means of the ten best

performing urban schools. Hypotheses 3 and 4 established by canonical

analysis whether there was a linear combination of input variables which

109

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significantly correlated with the scores on the three batteries of the 1980

CEE for all entrants. Hypotheses 5-8 utilized discriminant analysis to

isolate those factors which most significantly separated the top 33 percent

from the bottom 33 percent of urban entrants, and the top 25 percent

from the bottom 25 percent of rural entrants. Individual total CEE scores

were used in distinguishing the groups. The respective percentages

were selected on the basis of breaks appearing in the histograms of the

two sets of scores (urban and rural) and preliminary analyses of these.

Hypotheses 1(a)-1(c)

Hypothesis 1(a) reads: There is not a significant correlation

between the scores of the intelligence and the English tests of the

1980 CEE, for the total sample of 1,048 pupils.

Hypothesis 1(b) reads: There is not a significant correlation

between the scores of the intelligence and the mathematics tests, of the

1980 CEE for the total sample of 1,048 pupils.

Hypothesis 1(c) reads: There is not a significant correlation

between the scores of the English and the mathematics tests of the 1980

CEE, for the total sample of 1, 048 pupils.

The significance tests for the above three hypotheses were

Y = ± . 30 and a= .05. Table 26 displays the obtained correlations all

above '(= +.30 and significant at p < .001 level. The three hypotheses

were therefore rejected. The highest correlation was between the

English and intelligence scores (.85). There was a slightly lower

correlation between the intelligence and mathematics scores (.82) and

the lowest correlation was between English and mathematics (.78).

Table 27 shows the means and standard deviations. When compared with

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TABLE 26

CORRELATIONAL ANALYSIS FOR FORTY SCHOOLS-- OBTAINED CORRELATIONS

Intelligence Mathematics English

Intelligence 1.00 .82 .85

Mathematics .82 1.00 .78

English .85 .78 1.00

p < .001

T A B L E 27

CORRELATIONAL ANALYSIS FOR FORTY SCHOOLS— MEANS AND STANDARD DEVIATIONS

Variable Cases Mean Standard Deviation

Intelligence 1048 102.89 18.06

Mathematics 1048 86.63 21.00

English 1048 87.23 18.97

the analyses done by Manley (1963) on 1959 data, it is observed that the

arithmetic quotient shows little change (less by 1.2 points rounded).

The English and more so the intelligence scores have risen (greater by

3.2 and 17.6 points rounded, respectively). See table 28.

Hypotheses 2(a)-2(d)

Hypothesis 2(a) reads: There is not a significant difference among

the school means of the total scores of the 1980 CEE test battery, for the ten

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TABLE 28

COMPARISON OF QUOTIENTS IN MANLEY'S STUDY— 1959 DATA; PRESENT STUDY — 1980 DATA

No. of Mean Data Year Cases Mathematics Intelligence English (arithmetic)

1 959 1406* 85. 3 87.8 ( Prim ary Schools only) ro ro o 00 00 00 1 980 1048 102.89 86.63 CO

* On a total sample of 1730 which included Preparatory Schools, all means were said to be between 85 and 90 with standard deviations about 10 (Manley, 1963, p. 6).

best performing urban schools. The significance level was a= .05. Table

29 shows the means on the total test scores for the ten best performing

urban schools. Table 30 shows the analysis of variance for the test of the

hypothesis. A significant F probability was not achieved (p = .58). The

h yp o th esis was th e re fo re re ta in e d .

Hypothesis 2(b) reads: There is not a significant difference among

the school means of the mathematics test scores of the 1980 CEE, for the

ten best performing urban schools. The significance level was a = .05.

Table 31 shows the means on the mathematics scores for the ten best

performing urban schools. Table 32 shows the analysis of variance for the

test of the hypothesis. A significant F probability at the level set was not

achieved (p =.07). The hypothesis was therefore retained.

Hypothesis 2(c) reads: There is not a significant difference among

the school means of the English test scores of the 1980 CEE, for the ten

best performing urban schools. Table 33 shows the means on the English

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TABLE 29

MEANS OF TEN BEST PERFORMING URBAN SCHOOLS— TOTAL BATTERY OF 1980 CEE SCORES

Croup Name Count Mean S tandard No. Total Deviation

01 St. Richard1 s 44 300.71 49. 84

02 Dun robin 53 300.04 54. 16

03 Pembroke Hall 47 300.85 53.01

04 St. George1 s Girls 44 293.71 4 8.82

05 Alpha II 42 298.10 49. 71

06 T a rra n t 45 295.07 4 4.28

07 St. Aloysius 44 308.21 47. 75

08 Hope Valley 35 291.71 45.71

09 New Providence 67 299.05 50.49

10 Mico 45 281.87 6 1 .3 2

Total 466 297.18 50.82

T A B LE 30

ANALYSIS OF VARIANCE ON SCHOOL MEANS OF TOTAL BATTERY OF CEE SCORES—TEN BEST PERFORMING URBAN SCHOOLS

Source d f SS MS F P

Between Croups 9 19546.09 2171.79 .8 4 .58 W ithin Croups 456 1181422.00 2590.84

Total 465 1200968.

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TABLE 31

MEANS OF TEN BEST PERFORMING URBAN SCHOOLS— MATHEMATICS TEST OF 1980 CEE SCORES

Group Name Count Mean Standard No. Deviation

01 St. Richard's 44 9 2 .2 3 21.28

02 Dunrobin 53 91.81 19. 90

03 Pembroke Hall 47 9 8 .1 7 21.66

04 St. George's Girls 44 8 9 .4 5 19.79

05 Alpha II 42 101.71 19.42

06 T arran t 45 95. 29 18.23

07 St. Aloysius 44 9 0 .3 4 19.88

08 Hope Valley 35 9 2 .7 4 19.86

09 New Providence 67 95.04 21.33

10 Mico 45 88.44 22.61

Total 466 9 3 .5 7 20.65

T A B L E 32

ANALYSIS OF VARIANCE ON SCHOOL MEANS OF MATHEMATICS TEST — TEN BEST PERFORMING URBAN SCHOOLS

S ource d f SSMS F P

Between Groups 9 671 2 .7 745.86 1.776 .0705 Within Groups 456 191493.6 419.94

T otal 465 198206.3

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scores for the ten best performing urban schools. Table 34 shows the

analysis of variance for the test of the hypothesis. A significant F

probability was not achieved (p = .35). The hypothesis was therefore

re ta in e d .

Hypothesis 2(d) reads: There is not a significant difference

among the school means of the intelligence test scores of the 1980 CEE,

for the ten best performing urban schools. Table 35 shows the means

on the intelligence scores and table 36 the analysis of variance for the

test of the hypothesis. This was significant with an F probability of

p = .0003. The hypothesis was therefore rejected.

Because of the significant F ratio the Newman Keuis test

(Winer, 1962, pp. 77-89 ) was used to compare the means for each pair of

schools. Table 37 presents this comparison. The schools are ordered

according to size of the mean. Any entry in the table shows the difference

between the mean of the school at the column head and the mean of the

school at the row head. For example, 3.54 = 105. 52 - 101. 98. An

asterisk indicates a significant difference at the ct= .05 level.

It was proposed to isolate by discriminant analysis those factors

which separated the students in the school with the highest mean on total

scores from the school with the lowest mean. As no significant difference

among the school means on the total CEE test scores was found this

analysis was abandoned.

Hypothesis 3

The third hypothesis centered around whether out of thirteen

predictor variables there was a combination of variables covarying

significantly with achievement scores on the intelligence, mathematics.

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TABLE 33

MEANS OF TEN BEST PERFORMING URBAN SCHOOLS— ENGLISH TEST OF 1980 CEE SCORES

C ro u p Name C ount Mean S tan d ard No. Deviation

01 St. Richard's 44 97.11 18.51

02 Dun rob in 53 96.77 20. 55

03 Pembroke Hall 47 95. 51 18.15

04 St. George's Girls 44 94. 59 18.56

05 Alpha II 42 91.33 18.22

06 T a rra n t 45 93.62 15.78

07 St. Aloysius 44 99.36 18.41

08 Hope Valley 35 91.86 16.33

09 New Providence 67 93.28 17.77

10 Mico 45 89.84 21 .49

Total 466 94.38 18.52

T A B L E 34

ANALYSIS OF VARIANCE ON SCHOOL MEANS OF ENGLISH TEST —TEN BEST PERFORMING URBAN SCHOOLS

Source d f SS MS F P

Between Groups 9 3432.1 381.34 1.11 .35 W ithin Groups 456 156027.7 342.16

Total 465 159459.8

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TABLE 35

MEANS OF TEN BEST PERFORMING URBAN SCHOOLS— INTELLIGENCE TEST OF 1980 CEE SCORES

Croup Name Count Mean Standard No. Deviation

01 St. Richard1 s 44 111.36 13.85

02 Dun robin 53 111.45 18.30

03 Pembroke Hall 47 107.19 16.18

04 St. George1 s Cirls 44 109.89 15.22

05 Alpha II 42 105.52 15.72

06 T a rra n t 45 106.16 12. 96

07 St. Aloysius 44 118.25 12.43

08 Hope Valley 35 107.11 13.67

09 New Providence 67 110.70 14.94

10 Mico 45 101.98 21.45

Total 466 109.09 16.14

T A B L E 36

ANALYSIS OF VARIANCE ON SCHOOL MEANS OF INTELLIGENCE TEST —TEN BEST PERFORMING URBAN SCHOOLS

Source d f SS MS F P

Between Groups 9 7920.4 880.05 3.55 .0003 Within Groups 456 113142.1 248.12

Total 465 121062.5

Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. 118 - 6.80* 7.55* 8.36* 12.09* 16.27* 12.73* - .09 6.89* .75 9.97* 5.93* 1.56 5.29* 9.39* 11.19* 9.26* 11.06* - 5.89* 5.20* 1.97 9.25* - .66 5. 18* 5. 8.72* 9.38* 3.59 3.51 9.17* 9. 9. 59* 7.91* 3.73" 2.78 2.70

.08 - 1.03 . 95 . 1.59 1.67 9.37* 5.13* 5.21* Hope Hope Pembroke St.Ceorge's New St. St. T A B L E 37 - .69 3. 59*3. 9.18* SCHOOLS— INTELLIGENCE TEST -- - Mico Mico Alpha II Tarrant Valley Hall Clrls Providence Richard's Dunrobln Aloysius 105. 52 105. 101.98 106.16 111.15 118.25 111.36 110.70 107.19 B9 109. - .81 107.11 - Means Means 101.98 105.52 16 106. 1 107.1 107.19 109.89 110.70 36 . 1 11 111.<15 118.25 Newman Keuls a posteriori test MATRIX OF DIFFERENCES OF MEANS (ROUNDED)—TEN BEST PERFORMING URBAN * = means which are significantly different based on the Means p < .05 Dunrobln St. Aloysius St. Richard's New New Providence Tarrant Hope Hope Valley Pembroke Hall St. George's Clrls Alpha II Mico

Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. 119

and English tests of the CEE 1980. The predictor variables were:

1. Sex

2 . Age

3. Parent's occupation expressed as an index of socioeconomic status

*». Number of years at the particular school

5. Number of sessions attended 1978/79

6. Crade from which the Common Entrance was sat in 1980

7. The grade teacher's qualifications

8. The grade teacher's years of experience

9. Overall average teacher-pupil ratio for the school for the three years 1977/78 - 1979/80

10. Three-year average of the percentage of trained teachers at the school 1977/78 - 1979/80

11. The principal's qualifications

12. The principal's years of experience as principal

1 3. The factor of overcrowding

The null hypothesis reads: There is not a statistically significant

canonical correlation between the linear combination of thirteen predictor

variables—that is, thirteen pupil personal and school variables—and the

linear combination of the criterion variables of the intelligence, mathe­

matics, and English scores of the 1980 Common Entrance Examination.

The null hypothesis was rejected at a = .05 level. The results

of the analysis are shown in table 38 and discussed below.

First Canonical Function— Hypothesis 3. Since ±.30 was to be

taken as the acceptable level of correlation, the linear combination on the

first canonical function is primarily discussed. The first function showed

a significant canonical correlation coefficient of .575 at a probability level

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TABLE 38

CANONICAL CORRELATION AND STANDARDIZED COEFFICIENTS FOR EACH CANONICAL FUNCTION OF INTELLIGENCE, MATHEMATICS, AND ENCLISH TEST SCORES WITH THIRTEEN PERSONAL AND SCHOOL INPUT VARIABLES (N = 802)

Function 1 2 3

Canonical Correlation .575 .217 .157 C h i-S q u are 375.16 58.04 19.75 Degrees of Freedom 39 24 11 Probability < .000005 < .00012 < .04892 Test Scores (Set 1) Rank Rank Rank

Intelligence .391 2 -1.701 2 -1 .2 8 4 2 Mathematics .122 3 1.708 1 - .6 8 9 3 English .541 1 .139 3 1 .8 7 9 1 Personal + School Input Variables (Set II)

Sex .103 11 - .1 7 7 8 .539 2 Age .027 13 -.2 4 1 6 -.2 2 6 6 Parent's Socioeconomic Status (SES) . 346 3 .373 3 .243 4 Years at School .046 12 .497 2 .125 9 Sessions Attended 78/79 . 352 2 -.1 0 9 10 -.7 3 3 1 Crade CEE Sat 1980 . 334 5 .068 13 .1 1 5 10 Teacher's Qualifications . 221 7 . 234 7 . 228 5 Teach. Years Experience .248 6 .090 11 -.1 0 7 11 Avg. Teach./Pupil Ratio, 77-80 .115 9 .265 5 .1 5 5 7 Avg. Percentage Trained Teach., 77-80 .371 1 -.1 5 2 9 .154 8 Principal1 s Qualifications .1 38 8 -.3 2 7 4 .074 12 Principal's Years Experience - .3 4 5 4 .605 1 - .3 4 3 3 Overcrowding - .1 1 2 10 .078 12 -.0 1 8 13

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of p < .000005 and explained 33 percent of the variance between the two

sets of variables. The important criterion variables are English (.541)

and intelligence (.391) correlating with the predictor variables of

(1) percentage of trained teachers (.371), (2) number of school sessions

attended (.352), (3) higher socioeconomic status (.346), (4) principal's

administrative experience (-.345), (5) grade level in 1979/80 (.334), (6)

number of years the grade teacher taught (.248), and (7) teacher

qualification (.221). This suggests that the pupils who performed

highest on the intelligence and English tests were:

1. from higher socioeconomic status (.346)

2. had higher rates of attendance (.352)

3. were at higher grade levels— in the 1979/80 school year (.334),

and attended schools with:

1. higher proportion of trained teachers (.371)

2. principal with less administrative experience (-. 345)

3. more experienced grade teacher (.248)

4. more qualified grade teacher (.221).

Second Canonical Function— Hypothesis 3. The second function

had a canonical correlation coefficient of .217. Mathematics (1.708) and

intelligence (-1.701) from the first variable set ranked first and second.

The variables which were significantly linearly related to mathematics and

intelligence were (1) the principal's number of years service as principal

(.605), (2) number of years the pupil spent at the school (.497), ( 3)

higher socioeconomic status (. 373), (4) principal's qualifications (-.327),

(5) averaged teacher/pupil ratio (.265), (6) age (-.241), and (7) teacher's

qualifications (.234). This suggests in a weaker correlation that pupils who

did well on the arithmethic but not as well on the intelligence tests were

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younger pupils, from higher socioeconomic levels, who had a longer exposure

to school, under more experienced but less qualified principals who had better

trained teachers, but who were not in schools with necessarily low pupil/

teacher ratios. The explained variance is so small, however (5 percent), that

much emphasis should not be placed on these findings.

Third Canonical Function. The third canonical function is

significant with probability < .05. However, as only 2 percent of the

variance was explained, further discussion is not merited.

Hypothesis 4

Since certain limitations were perceived in the categorizations

on the socioeconomic variable, the researcher decided to examine the

relationships between the criterion and predictor variables with socio­

economic status excluded from the predictor variables.

The null hypothesis reads: There is not a statistically significant

canonical correlation between the linear combination of twelve predictor

variables—that is twelve students' personal and school variables—

and the linear combination of the criterion variables of intelligence,

mathematics, and English scores of the 1980 Common Entrance Examinations.

The null hypothesis was rejected at a = .05 level. The results

of the analysis are shown in table 39.

First Canonical Function—Hypothesis 4. The results show two,

rather than three, significant canonical functions (see table 39). The

first function shows a significant canonical correlation coefficient of . 543,

signficant at a probability p < .000005 with 29 percent of the variance

explained. The significant criterion variables are intelligence (. 522)

and English (.485) with predictor variables in the following order:

(1) averaged percentage of trained teachers (.417), (2) number of

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TABLE 39

CANONICAL CORRELATION AND STANDARDIZED COEFFICIENTS FOR EACH CANONICAL FUNCTION OF INTELLIGENCE, MATHEMATICS AND ENCLISH TEST SCORES WITH TWELVE PERSONAL AND SCHOOL INPUT VARIABLES (N = 802)

Function 1 2 3

Canonical Correlation . 543 .202 .1 50 Chi Square 327.49 51.08 18.03 Degrees of Freedom 36 22 .10 Probability <.000005 <.00042 < .05438

Test Scores (Set 1) Rank Rank N.S. Intelligence .522 1 -1 .4 1 7 2 -1 .5 5 5 Mathematics .039 3 1.808 1 -.366 E nglish .485 2 -.1 7 6 3 1.891

Personal + School In p u t V ariab les (S e t ID Sex .127 9 -.226 7 .542 Age .025 11 -.2 3 1 6 -.3 0 4 Y e a rs at School .009 12 .482 2 .234 Sessions Attended 78/79 .408 2 .073 11.5 - .7 0 4 G rad e CEE Sat 79/80 .383 4 .144 8 . 217 Teacher's Qualifications .216 6 .236 5 .314 Teach. Years Experience .257 5 .143 9 -.0 5 7 Avg. Teach./Pupil Ratio, 79- 80 .157 8 .325 3 .291 Avg. Percentage Trained Teachers, 77-80 .417 1 -.100 10 .195 Principal's Qualifications .209 7 -.2 7 0 4 .072 Principal's Years Experience - .4 0 4 3 .603 1 -.2 7 2 Overcrowding -.1 1 6 10 .073 11.5 -.0 0 8

Not Significant

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sessions attended in 1978/79 (.408), (3) principal's experience in

administration (-.404), (4) higher grade in 1979/80 (.383), (5) number of

years experience of the grade teacher (. 257), and (6) grade teacher's

qualifications (.216).

These findings correspond with the findings of hypothesis 3

which included socioeconomic status among the predictor variables.

Second Canonical Function— Hypothesis 4. The second function

shows a canonical correlation coefficient of .202 and is significant at

P< -0004 level. The highest correlations on the first set of variables are

mathematics (1.808) and intelligence (-1.417). The highest weightings on

the second set are (1) principal's years of experience as principal (.603),

(2) number of years pupil spent at the school (.482), (3) average teacher/

pupil ratio (.325), (4) principal's qualifications (-.270), (5) teacher's

qualifications (.236), and (6) age (-.231). The explained variance was

only 4 percent; hence, further emphasis will not be placed on these findings.

The third function was not significant at a= .05 level and is

therefore not discussed.

Hypothesis 5

Stated in the null form, hypothesis 5 reads: There is not a linear

combination of input variables which significantly separates the top 33

percent from the bottom 33 percent of pupils sampled in urban schools

based on the individual totals of the 1980 CEE scores.

The twelve input variables of hypothesis 4 were utilized in this

analysis. Table 40 displays the results of the analysis. The approximate

Chi Square was 126.5466, the degrees of freedom 12, and probability level

p < .00005. The hypothesis was rejected. The group means on the

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TABLE 40

DISCRIMINANT FUNCT IONS— UPPER 33 PERCENT COMPARED WITH LOWER 33 PERCENT OF URBAN STUDENTS— TWELVE VARIABLES

Discriminant Variable No. Name Weights Rank

1 Sex 1.0161 11

2 Age .5757 12

3 Years at school 2.0535 10

4 Sessions attended 1978/79 4.2258 9

5 Grade CEE sat 1979/80 7.5358 1

6 Teacher's qualifications 5.6805 4

7 Teacher’s experience 5.5157 5

8 Teacher/pupil ratios 5.7581 3

9 Percentage of trained teachers 4.6942 6

10 Principal's qualifications 4.6018 7

11 Principal's years of experience -6. 5189 2

12 Overcrowding -4.3689 8

Croups Means (D.F.)* Chi Square (approximate) : 126.5466

Upper 11 .295 Degrees of freedom : 12 Lower 10*272 P = < .00005

* D .F . = Discriminant Function

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discriminant function were 11.295 for the upper 33 percent and 10.272

for the lower 33 percent of entrants.

The standardized weights enable comparison to be made between

the relative importance of the variables in separating th' groups.

Examination of the table shows that the two rr. jst outstanding

factors separating the groups were (1) the higher grade levels attained

(7.5358) and (2) principals with fewer years of administrative experience

(-6.5189) . The other factors in descending order of importance were

(3) higher teacher/pupil ratios (5.7581), (4) better qualified teachers

(5.6805), (5) grade teachers with greater experience (5.5157), (6)

percentage of trained teachers (4.6942), (7) principal's qualifications

(4.6018), (8) overcrowding, a negative factor (-4.3689), and (9)

attendance 1978/79 (4.2258). That is, the upper 33 percent of students

in urban areas differed from the lower 33 percent in that they took the

examinations at higher grade levels, attended school more regular!-/,

had more qualified principals who were younger rather than older in

administrative experience. In their schools the teacher/pupil ratios were

higher but teachers were more qualified and experienced. The school

historically had a higher percentage of trained teachers and were less

c ro w d e d .

Hypothesis 6

Stated in the null form, hypothesis 6 reads: There is no linear

combination of input variables which significantly separates the top 33

percent from the bottom 33 percent of pupils sampled in urban schools

based on the individual totals of the 1980 CEE scores.

Hypothesis 6 examined the differentiation when socioeconomic

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status was added to the twelve predictor variables. Table 41 shows the

variables together with the standard discriminant functions and ranking.

The Chi Square is 155.2898, with 13 degrees of freedom and probability

p < .00005. The hypothesis was rejected. The group means were 11.868

for the upper 33 percent and 10.564 for the lower 33 percent of urban

entrants. Examination of the results shows that a cluster of variables

similar to those identified in the earlier analysis differentiated the

groups. Higher socioeconomic status (7.7222), higher grade level

attained when the pupils sat the Common Entrance Examination in 1980

(6.3814), and principals with less experience in administration (-6.3587)

were the chief factors separating the two groups. Next in descending

order of importance were (1) teacher/pupil ratio (5.5071), (2) grade

teachers' experience (5.5052), (3) grade teachers' qualifications

(5.4806), (4) overcrowded schools (-5.0513), (5) principal's qualifications

(4.5139) and (6) sessions attended 1978/79 (3.8607). That is,with the

socioeconomic variable introduced, the upper 33 percent of students in

urban areas differed from the lower 33 percent in that they came from

higher socioeconomic levels, took the examination at higher grade levels,

and attended school more regularly. Their principals were qualified but

were younger rather than older in administrative experience. The teacher/

pupil ratio tended to be higher but the grade teachers were qualified and

experienced and there was less overcrowding.

Hypothesis 7

Hypothesis 7 tested the degree of differentiation between the

upper and lower 25 percent of pupils sampled in the rural areas.

Hypothesis 7 states: There is no linear combination of input variables

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TABLE 41

DISCRIMINANT FUNCTIONS— UPPER 33 PERCENT COMPARED WITH LOWER 33 PERCENT OF URBAN STUDENTS THIRTEEN VARIABLES

S tan d ard Discriminant Rank Variable No. Name W eights

1 Sex 1.3205 12

2 Age 1.0102 13

3 Parent's socioeconomic statu s 7.7222 1

4 Y ears in school 2.7320 11

5 Sessions attended 78-79 3.8607 9

6 Crade CEE sat 1979/80 6.3814 2

7 Teacher's qualifications 5.4806 6

8 Teacher's experience 5.5052 5

9 Teacher/pupil ratio 5. 5071 4

10 Percentage o f train ed teachers 2.9147 10

11 Principal's qualifications 4. 5139 8

12 Principal's years of experience -6.3587 3

13 Overcrowding -5 .0 5 1 3 7

Groups Means (D .F.) * Chi Square: 1 55.2898

Upper 11.868 Degrees of freedom: 13

Lower 10.564 p = < .00005

*D.F. = Discriminant Function

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which significantly separates the top 25 percent from the bottom 25

percent of pupils sampled from rural areas based on the individual totals

of the 1980 CEE scores.

The twelve input variables are those given for hypothesis 4.

Table 42 shows the variables, together with standard discriminant

functions and rankings.

The approximate Chi Square is 31.8618 with 12 degrees of freedom

and probability p< .00005. The hypothesis was rejected. The group

means were 9.108 for the upper 25 percent and 7.921 for the lower 25

percent of urban entrants. The percentage selected (25 percent) gave

better differentiation between the groups than the 33 percent for urban

groups. The most important variable was (1) percentage of trained

teachers (8.2524), followed by (2) principals with less administrative

experience (-5.1115), (3) higher grade levels attained when the pupils

sat the Common Entrance Examination in 1979/80 (4.7123), (4) number of

sessions attended in 1978/79 (4.4307), (5) overall lower teacher/pupil

ratios (-3.7651), and (6) principal's qualifications (3.0646).

Overcrowding did not emerge as a significant factor separating the groups.

This implies that the upper 25 percent of students in rural areas differed

from the lower 25 percent in that they took the examinations at higher

grade levels, attended school regularly, their principals were generally

qualified but were younger rather than older in administrative experience.

Their schools had higher percentages of trained teachers and lower teacher/

pupil ratios.

Hypothesis 8

Hypothesis 8 in the null form reads: There is no linear combination

of input variables which significantly separates the top 25 percent from the

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TABLE 42

DISCRIMINANT FUNCTIONS— UPPER 25 PERCENT COMPARED WITH LOWER 25 PERCENT OF RURAL STUDENTS TWELVE VARIABLES

S tan d ard Discriminant Variable No. Name R ank W eights

1 Sex . 5106 11

2 Age -.3 4 6 6 12

3 Y ears in school -.9 4 7 2 10

4 Sessions attended 1978/79 4.4307 4

5 C rad e CEE sat 1979/80 4. 7123 3

6 Teacher's qualifications 1.4171 8

7 Teacher's experience 2.0023 7

3 Teacher/pupil ratio -3. 7651 5

9 Percentage of trained teachers 8.2524 1

10 Principal's qualifications 3.0646 6

11 Principal's years experience -5.1115 2

12 Overcrowding .9773 9

Groups Means (D.F.)* Chi Square (approximate): 81.8618

Upper 25% 9.108 Degrees of freedom: 12

Lower 25% 7.921 p = < .00005

*D .F. = Discriminant Function

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bottom 25 percent of pupils sampled in rural schools based on the indivi­

dual totals of the 1980 CEE scores.

The thirteen input variables used were those of hypothesis 3, i.e.,

with socioeconomic status added. The results are presented in table 43.

The approximate Chi Square was 87.2743 with 13 degrees of free­

dom and probability p< .00005. The hypothesis was rejected. The group

means on the discriminant function were 9.893 for the upper 25 percent

and 8.639 for the lower 25 percent of entrants. Examination of the results

shows that with the socioeconomic variable introduced in the rural areas the

most differentiating factor was still (1) percentage of trained teachers

(8.6974), followed by (2) principals with less administrative experience

(-5.2244), (3) higher grades attained when pupils sat the Common Entrance

Examination in 1979/80 (4.4863), (4) lower teacher/pupil ratios (-4.4706),

and (5) number of sessions attended (4.2511). Socioeconomic status did

not emerge as a strong factor contrary to expectation. This implies that

the upper 25 percent of students in the rural areas differed from the

lower 25 percent in that they attended school regularly, and longer,

were in schools with higher percentages of trained teachers over the

years, their principals yvere qualified but younger rather than older in

administrative experience, and the teacher/pupil ratio was lower.

The Exploratory Study

The exploratory segment of the study obtained the opinions of

177 teachers on sixteen categories of indicators subcategorized under

school, parish, and Island. This resulted in a total of 31 stimulus

statements being presented to the teachers for rating on a continuum

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TABLE 43

DISCRIM INANT FUNCTIONS— UPPER 25 PERCENT COMPARED WITH LOWER 25 PERCENT OF RURAL STUDENTS THIRTEEN VARIABLES

Standard Discriminant Rank Variable No. Name Weights

1 Sex .3674 12

2 Age -.0916 13

3 Parent's socioeconomic status 2.3687 7

4 Years in school -.9828 11

5 Sessions attended 1978/79 4.2511 5

6 Grade CEE sat 1979/80 4.4863 3

7 Teacher's qualification 1.7821 9

8 Teacher* s years experience 2.2957 8

9 Teacher/pupil ratio - a . 4706 4

10 Percentage of trained teachers 8.6974 1

11 Principal's qualifications 2.9918 6

12 Principal's years of experience -5.2244 2

13 Overcrowding 1.1031 10

Croups Means (D.F.) * Chi Square (approximate): 87.2743

Upper 9.893 Degrees of freedom: 13

Lower 8.639 p = < .00005

*D.F. = Disciminant Function

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of 1-5, 1 being most important. The data gathered were submitted to the

Andrews University computer center. Analysis was made by the categor­

ical scaling method involving conversions to an arbitrary interval scale

and rank ordering of the derived values.

Results of the Opinionnaire

Table <14 presents the rank ordered list. The ordering of the

sixteen categories of variables when parish and Island levels are brought

together is shown in table 45.

Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. .8430 .7310 .7680 .7850 .8070 .6200 . 7190 .6630 . . 3290 . 5040 .4480 .1600 .2060 .1210 . . 0000 Values O rd ered

Indicators TABLE 44 RANK ORDERINC OF INDICATORS BASED ON TEACHER RATINGS Percentage of overcrowded schools (for the Island) Percentage overcrowdedTeacher/pupil schools (by Percentage ratio--trained parish) of unstable teachers families (by (by parish) school) Index of malnutrition (by parish) Ratio enrollment to school age population (by parish) Degree of overcrowding (by school) Overall teacher/pupilGrade-by-grade ratio (by average parish) achievement in mathematics (by school) Percentage of pupils attending of 90% school sessions by term Teacher/pupil ratio--trained teachers (by school) Grade-by-grade average achievement in English (by school) or year (by school) Efficient principal (by school) 9 2 5 Overall teacher/pupil ratio (by school) 7 1 8 3 46 Index of malnutrition (by district) 15 11 10 12 13 14 Rank O rd er

Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. 16 Percentage of Pupils attending 90% of school sessions by term or year (for the Island) .8530

17 Percentage of pupils attending 901 of school sessions by term or yearly (by parish) .8590

18 Ratio enrollment to school-age population (for the Island) . 9010 19 Percentage of teacher turn-over annually (by school) . 9130 20 Percentage of students achieving below 50% in English and mathematics (by school) . 9283 21 Crade-by-grade average achievement in mathematics (for the 1 stand) 1.0076 22 Percentage of unstable families (by parish) 1.0201 23 Percentage of teacher turn-over annually (for the Island) 1.0865 214 Crade-by-grade average achievement in English (by parish) 1.0759 25 Percentage of eligible age group obtaining passing mark in Common Entrance Examinations (not necessarily awards) 1.0802 (by school) 26 Grade-by-grade average achievement in mathematics (by parish) 1.0997 27 Grade-by-grade average achievement in English (for the Island) 1.1502 28 Number of library books per pupil (by school) 1.1505 29 Percentage of teacher turn-over annually (by parish) 1.2535 30 Percentage of eligible age group obtaining passing mark in Common Entrance Examinations (not necessarily awards) 1.2761 (by parish) 31 Number of hours of educational T .V . viewed (by school) 1.8387 136

15 . . 22 23 . 29 . 20 . . . 21 . 12 . 19 . 25 . . 30 28 . . . 11 . 26 . . 31 ...... Name Name by Teachers Indicator Rank Accorded for the Is la n d for the Is la n d by school by school by school by school by school by parish by p a ris h by p a ris h by p a ris h by school by p a ris h for the I s l a n d in in mathematics Percentage students achieving Percentage unstable families Percentage teacher turn-over Percentaqe overcrowded schools Percentage eligible group obtaining pass mark In CEE (not necessarily Number of library books per pupil Crade-by-grade achievement Number of hours of E T V below below 50 percent In English and mathematics awards) annually

9. 15. 16. 10. 19. 11. 12. Order of Importance

TABLE 1*5 9 1 7 3 8 9 17 29 27 by Teachers Rank Accorded ...... 18 ...... 2 . . . . 13 5 ...... 10 ...... 16 ...... 6 ORDERING OF SIXTEEN INDICATORS ...... Name Indicator ...... overcrowding for the I s l a n d by s c h o o l by p a r is h by p a r is h by s c h o o l by s c h o o l by s c h o o l by p a r i s h by p a r is h by s c h o o l by district by s c h o o l for the I s l a n d by p a r i s for h the I s l a n d by p a r i s h 90 90 percent of school sessions 13. teachers Index of malnutrition Teacher/pupll ratlos--tralned Degree of Ratio enrollment to school-age Percentage pupils attending In English Crade-by-grade achievement by term or year population Overall teacher/pupil ratio

, 1 . 1 2. 7. 8. 5. 9 3. Efficient principal 6. Order of Importance

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Additional Indicators Provided by Teachers

Teachers provided a total of eighty-nine additional items. The

details of this material are in appendix M. Table 46 provides the

categories assigned the items and the tallies.

TA B L E 46

ADDITIONAL INDICATORS PROVIDED BY TEACHERS

In d icato rs T a lly

1. Teachers and staff 18 2. School working conditions 16 3. P aren ts and home 13 4. Pupil behaviors 12 5. C u rric u lu m 7 6. D iscip lin e 6 7. Diet and nutrition 5 8. Ministry of Education inputs 3 9. Pa rent/Teachers Association 2 10. O th e rs 7

Total 89

The above included items not listed anywhere in the study.

These were:

1. Teacher/teacher, teacher/pupil interaction

2. Communication with parents

3. Teachers'salaries

4. Teacher efficiency, interest in pupils, and training

5. Public-relations training

6. Discipline

7. Textbooks related to Jamaica

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8. A national syllabus

9. Health facilities for schools

10. School security

11. Ministry of Education supervision

12. School Boards of quality

13. School tra n s p o rta tio n

14. School/community relationships

15. Parent/Teachers Association, and

16. No p o litic s in school.

Factors Contributing to CEE Success as Supplied by Principals

Principals identified, mainly through interview, a number of factors

contributing positively or negatively to Common Entrance Examination

success (see appendix N). These generally paralleled factors supplied by

the teachers, focusing on home and environmental conditions, organized

and disciplined class work, good attendance, adequate books, pupil

motivation, native intelligence, and, from one rural school, distance to

be travelled in order to get to school.

Summary of the Findings

This was a two-part study, part one being a correlational/

predictive study and part two an opinionnaire survey. In part one ten

of the thirteen hypotheses tested were rejected. Three were retained.

Table 47 brings together the findings of both parts of this

study by displaying the rankings of the variables within their respective

analyses. This enables comparison of the rankings across analyses and

highlights the following:

Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. 139 Survey 9 7 5 3 8 4 6 13 11 Rural Thirteen Variables

3 7 1 1 2*9 2* 10 6 11 12 12 10 1 - 9 4 6 8 3 7* 8 13 11 10 Discriminant Analyses 1 2 5 5 3 4 5 9 7 - 2* 11 12 Urban Twelve Variables Urban Variables Thirteen Variables Twelve Rural

5 6 4 7 8 - 12 10 7 3 5 4 1 1 6 2 2 8 4* 3* 13 11 12 11 9 12 TABLE 47 1 0*1 10* 8* Thirteen Variables Twelve Variables Canonical Correlation

RANKING RANKING OF FINDINGS FOR SIX STATISTICAL TESTS AND TEACHER SURVEY OPINIONNAIRE (3 year-average) 7. Teacher's qualifications 2. Age 3. SES--Parent's socioeconomic status 1. Sex 5. Sessions attended 978/79 1 9. Teacher/pupil ratio (3 year average) 9 8. Teacher's experience 6 4. Years in school 6. Grade CEE sat 1979/80 V ariab le 11. Principal's qualification 10. Percentage of trained teacher 12. Principal's years of experience 13. Overcrowding

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7 9 8 2 3 4 6 11 12 14 10 13 15 16

teachers 50 50 percent--English and mathematics passmark in CEE school sessions 19. Enrollment to school age population 14. Teacher/pupil ratio--trained 18. English achievement 25. Percentage pupils achieving 26. Library 27. T . V . 20. Mathematics achievement21. Percentage overcrowded22. Unstable schools family 23. Teacher turn-over24. Percentage pupils achieving below 15. Efficient principal * = Negative Correlation 16. Malnutrition 17. Percentage attending 90 percent of

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1. Ratio or percentage of trained teacher occupied the highest

rank on both canonical analyses and on the two rural discriminant

analyses. This factor was also important to the teachers, being ranked

second. It occupied a lower ranking on both urban discriminant analyses.

2. Socioeconomic status had a high ranking in urban areas when

this was introduced into the analysis. It was ranked first in the

discriminant analysis of the two urban groups.

3. Number of sessions attended was ranked highly on both

canonical analyses (second on both) and in the discriminant analyses on

the two rural groups.

4. Taking the examination when in higher grades in school had

a clear advantage in all analyses.

5. The grade teacher's experience, followed closely by his/her

better qualification, was also important.

6. Principal's years of administrative experience correlated

negatively with achievement in the analyses.

7. Overcrowding was negatively related in four analyses.

8. Overcrowding was perceived by the teachers to be the most

important factor affecting performance. This was followed by five factors,

in descending rank: the trained teacher/pupil ratio, an efficient

principal factor, a malnutrition assessment factor, an overall teacher/pupil

ratio factor, and an attendance factor.

Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. C H A P TE R V

SUMMARY, CONCLUSIONS, AND RECOMMENDATIONS

Summary

B ackground

The main purpose of this study was to postulate a single or a

set of indicators which would provide timely and significant statistical

information for planning and monitoring primary education in Jamaica.

This was to be accomplished through relating the research findings in

the field to the findings of (1) a correlational study of Jamaican

primary schools inputs and outputs, and (2) a survey of teacher

opinions on significant factors contributing to educational achievement.

Chapter 2 reviewed the literature to provide a contextual

framework. Indicators were defined as measures of a system1 s

performance, statistics of normative interest signalling change in

variables of interest, registering progress towards or retrogression

from a goal. The systems model was suggested by some authors as a

basis for the classification of educational indicators. Accordingly there

could be "context," "input," "process," and "output" indicators.

Another categorization listed " Access," "Aspiration," "Achievement,"

"Impact," and "Resources" indicators. A third categorization proposed

"Personal Development," "Social Outcomes," and "Political Outcomes"

indicators. Indicators were looked at in terms of " primary" or present

1U2

Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. effects, " secondary" or long-term effects, and " tertiary" or inter-

generational effects, indicators were discussed in the context of

economic analysis. Reference was made to the "leading," "co-incident,

and "lagging" economic indicators. Indicators were said to be

"manipulative" and " non-manipulative." Finally, it was questioned

whether there could be a single educational indicator as informational

as the demographic indicator. Infant Mortality Rate.

Actual work on the development of educational indicators in the

U.S. and abroad was reviewed. The most extensive work was that of

Johnstone (1981) who surveyed inter- and intra-national indicators

put forward by various professionals and United Nations' Education,

Scientific, and Cultural Organization (UNESCO). Johnstone (1981)

himself recommended a profile of indicators categorized according to

the systems model, together with statistical formulas.

Literature on the variables used in the study was also

reviewed. Summaries of research findings on school input/output

relationships in the United States and overseas countries were provided

Socioeconomic status was, in most cases, positively correlated with

achievement. In some developing countries, however, it had less effect

Bargen and Walberg (1974), in a summary of twenty-three studies on

United States and British subjects, found that teacher variables were,

in the main, significantly correlated with school achievement. A

summary of overseas research provided by Alexander and Simmons

(1975) showed variable effects for most of the individual schooling

variables such as per pupil expenditures, class size, teacher certifica­

tion, tenure, experience, and sex. Text book availability, availability

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and use of library, homework and free reading were also significantly

related to achievement in the studies done on these variables.

Literature on the primary-school system in Jamaica was reviewed.

The commentary offered by Vernon (1961) on the Common Entrance

Examination (CEE) selection for secondary education in Jamaica

provided information on the sex differential in performance, the effect

of maturation, what the tests were supposed to measure and how

Jamaican children performed in comparison to English children.

Manley's (1963) study on the results of the 1959 Common

Entrance Examination—the entrance examination to the academic high

schools in Jamaica—pointed out the differential effects of socioeconomic

status and the sex differential in terms of examination performance and

participation. The apparent lower participation of boys in the education

system was underscored.

Reid (1964), in a comprehensive study, examined the relation­

ship of a profile of home, community, and school inputs with primary-

school attainment. His aim was to measure the interaction of these

factors on the criterion of attainment. The most essential contributing

factor to school achievement was good home background, the education

of the parents themselves,and their interest in their children's education.

Years of schooling and qualifications of staff did make a smaller inde­

pendent contribution.

Other Jamaican studies reviewed showed that underachievement

of Jamaican children in English schools was related to the parents' low

educational achievement (Bagley, 1979). Motivation was, however,

important (Ragbir, 1977). The pattern of absenteeism, the deficiencies

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of educational television, the level of provision of library books,and

the annual data and statistical information published by the Ministry of

Education were also reviewed.

Methodology— Correlational Predictive Analyses

The methodology for the correlational predictive study involved

a stratified sample of forty urban and rural schools. These were

stratified on a dimension of performance in the 1980 Common Entrance

Examination. Ten each of urban and rural schools showing high

percentages of CEE awards to the relative age cohort in the relevant

grades (grades 4-6) were selected. Ten each of urban and rural schools

showing fewest or no awards were also selected. Data were secured in

three ways: they were (1) taken directly from the CEE score cards, (2)

secured from school principals, and (3) secured from the Ministry of

Education.

Difficulties in securing data from the schools resulted in two

schools having to be omitted from six of the thirteen hypotheses. The first

seven hypotheses were therefore tested on forty schools and 1,048 sub­

jects,and the last six, consisting of canonical correlation and

discriminant analyses,were tested on thirty-eight schools and 802 sub­

jects. Of the completed cases 285 were from rural and 517 were from

urban areas.

Sixteen predictor variables were originally selected for analy­

sis. These were later reduced to thirteen through the elimination of

the variables (1) "Library," (2) "Educational Television," and (3) pre­

paratory school experience. Sufficiently differentiated data were not

secured on the first two; reliability of the last was questioned.

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The indexing of socioeconomic status from parent's occupation

listed on the CEE cards presented assessment difficulties. Accordingly

the last six hypotheses were tested with this variable included in three

analyses and excluded from three. The thirteen variables finally used

were :

1. Pupil1 s sex

2. Pupil1 s age

3. Parent1 s socioeconomic status

4. Number of years in the particular school

5. Number of sessions attended in 1978/79, the year prior to the 1980 CEE

6. Grade from which the 1980 CEE was sat

7. Crade teacher1 s qualifications

8. Crade teacher's years of experience

9. Averaged pupil /teacher ratios for three school years— 1977/78 - 1979/80

10. Percentage of trained teachers averaged over the three years— 1 977/78 - 1979/80

11. Principal's qualifications

12. Number of years administrative experience of principal

13. Degree of overcrowding at the school.

The data secured gave a fair coverage of the pupil's personal

variables, including his attendance rate and cumulative experience in

the particular school. School variables were also well represented,

for the year of interest and historically for three years previously .

The aims of the analyses were:

1. To examine the intercorrelations of the three test batteries

of the Common Entrance Examination. This would establish whether

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the tests showed low correlations among themselves.

2. To ascertain whether there was a significant difference in

test performance among the ten best performing urban schools.

3. To ascertain whether by utilizing the test scores of all entrants

there was a significant linear combination of school and personal inputs

correlating with a linear combination of the scores of the three batteries.

4. To ascertain what factors significantly separated: (a) the

first of the ten best performing schools from the last, should a signifi­

cant difference among the school means on the overall scores be found;

(b) the top 33 percent from the bottom 33 percent of urban entrants; and

(c) the top 25 percent from the bottom 25 percent of rural entrants.

A Pearson product-moment correlation coefficient of ±.30, and

probability p < .05 were the statistical parameters set.

Survey Methodology

The second part of the study, the sampling of teachers'

opinions,was accomplished through random circulation of a questionnaire

to teachers mainly in the CEE grades in the schools sampled. Ratings

on a continuum of 1-5, 1 being most important, were requested on sixteen

indicator items, disaggregated into thirty-one responses related to

school, parish, and Island as appropriate. The responses from 177

teachers were tallied. Categorical scaling was then used to place the

items along an arbitrary interval scale. These were then ranked.

F indings

Thirteen hypotheses were tested under eight headings. Hypotheses

under seven headings were rejected and retained under one.

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Hypotheses 1(a)-1(c) tested the degree of correlation among the

three batteries of the 1980 CEE. Significantly high correlations among

the test scores of 1,048 entrants from forty schools were found.

English and intelligence tests were the most highly correlated (.85),

followed second by intelligence and mathematics (.82), and last by

English and mathematics (.78).

Hypotheses 2(a)-2(d) tested the significance of the difference

between the school means of the ten best performing urban schools on

the total CEE test, and on the three individual tests of the 1980 CEE

battery. This hypothesis was retained in respect to (1) total scores,

(2) scores on the English, and (3) scores on the mathematics tests, there

being no significant differences in the school means on these tests. There

was, however, significant differentiation on the intelligence test. The

table of means was examined utilizing the Newman Keuls a-posteriori test.

St. Aloysius, in particular, and four other schools were shown to

have achieved significantly different means from other schools.

The reasons for this finding merits further investigation which will not

be undertaken in this study. As no significant difference was found

among the means of the total CEE battery for these schools, no discri­

minant analysis was performed to isolate the factors separating them.

Hypotheses 3 and 4 established by canonical analysis that there

was a significant linear combination of predictor variables covarying

with the criterion scores of the three test batteries of the 1980 CEE in

respect to 802 entrants. Hypothesis 3 utilized thirteen input variables;

hypothesis 4 utilized twelve variables, the variable socioeconomic status

being excluded.

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Hypotheses 5 and 6 utilized discriminant analysis to identify

those variables which separated the top 33 percent from the bottom 33

percent of urban entrants. Hypothesis 5 utilized twelve variables;

hypothesis 6 utilized thirteen variables, socioeconomic status being the

added variable. Individual total CEE scores separated the groups.

Hypotheses 7 and 8 utilized discriminant analysis to isolate

variables significantly separating the top 25 percent from the bottom

25 percent of rural entrants. Hypothesis 7 utilized twelve variables;

hypothesis 8 utilized thirteen variables, with socioeconomic status being

the added variable.

The findings of the study are summarized in tables 48-50. The

canonical analyses and the discriminant analyses were all significant

and identified factors associated with school success. The tables list

the variables in order of the weights they showed in the analyses.

Essentially the same pattern of school inputs correlated with success

with or without socioeconomic status included. Socioeconomic status

had a high weighting in the urban discriminant analysis. The co­

varying variables were different in respect of urban and rural areas

when top and bottom percentages of entrants were contrasted. The

ranking of the sixteen major indicators based on ratings by the

teachers is shown in table 51.

Conclusions

Both canonical analyses show the correlates of high performance

in 1980 CEE to be:

1. Higher percentage of trained teachers

2. Greater number of sessions attended

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TABLE 48

SUMMARY RANKING OF PERSONAL AND SCHOOL VARIABLES (Canonical Correlations)

Thirteen Variables Twelve Variables Rank Item Standardized Item Standardized C o efflcen t Coefficient

1 Percentage of trained teachers (.3 7 1 ) (.417)

2 Sessions attended 78/79 (.352) (.408)

3 Parent's socioeconomic status (. 346) Not included

4 Principal's years of experience -( .345) -(.4 0 4 )

5 C ra d e CEE sat 1 980 (.3 3 4 ) (.383)

6 Teacher's years of exp erien ce (. 248) (.257)

7 Teacher's qualifications ( .221) (.216)

8 Principal's qualifications (.1 3 8 ) (.2 0 9 )

9 Teacher/pupil ratio (.1 1 5 ) (.157)

10 Overcrowding - ( .1 1 2 ) Sex (.1 2 7 )

11 Sex (.103) Over­ -(.1 1 6 ) cro w d in g

12 Y ears in school (.0 4 6 ) Age (.025)

13 Age (.027) Y ears in (.0 0 9 ) school

KEY: Broken line ( ------) separates most important variables

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TA B LE 49

SUMMARY RANKINC OF PERSONAL AND SCHOOL VARIABLES—URBAN (Discriminant Analysis)

Rank Thirteen Variables Twelve Variables Discriminant Discriminant 1 tern IUm Function Function

1 Parent1 s socioeconomic status (7.72) Not included

2 Crade CEE sat 79/80 (6.38) (7 .5 4 )

3 Principal's years of experience -(6.36) -(6.52)

4 Teacher/pupil ratio (5 .5 1 ) (5 .7 6 )

5 Teacher's experience (5.50) T eacher's (5 .6 8 ) qualifications

6 Teacher's qualifications (5 .4 8 ) T e a c h e r's (5 .5 2 ) exp erien ce

7 Overcrowding -( 5.05) P ercentage (4 .6 9 ) tra in e d teachers

8 Principal's qualifications (4. 51) (4 .6 0 )

9 Sessions attended 78/79 (3 .8 6 ) O v e r­ - ( 4 .3 7 ) crow ding

10 Percentage of trained Sessions (4 .2 3 ) teachers (2 .9 1 ) atten d ed

11 Y ears in school (2.73) (2.05)

12 Sex (1 .3 2 ) (1 .0 2 )

13 Age (1 .0 1 ) ( -58)

KEY: Broken line ( -----) separates most important variab les

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TABLE 50

SUMMARY RANKINC OF PERSONAL AND SCHOOL VARIABLES—RURAL (Discriminant Analysis)

Thirteen Variables Twelve Variables Rank Item Discriminant Item Discriminant Function Function

1 Percentage of trained teachers (8 .7 0 ) (8 .2 5 )

2 Principal's years of e x p e rie n c e - ( 5 .2 2 ) - ( 5 .1 1 )

3 Crade CEE sat 79/80 (4.49) (4.71)

4 Teacher/pupil ratio -( 4 .4 7 ) Sessions (4 .4 3 ) attended

5 Sessions attended 78/79 (4.25) T each er/ - ( 3 .7 7 ) pupil ratio

6 Principal's qualifications (2.99) (3 .0 6 )

7 Parent's socioeconomic status (2 .3 7 ) Not included

8 Teacher's experience (2.30) (2 .0 0 )

9 Teacher* s qualifications (1.78) (1.42)

10 Overcrowding (1 .1 0 ) ( .9 8 )

11 Years in school - ( .9 8 ) - ( .95)

12 Sex ( .37) ( -51)

13 Age - ( .0 9 ) - ( .35)

KEY : Broken line ( ----- ) separates most important variables

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TABLE 51

SUMMARY RANKINGS OF TEACHERS' OPINIONS ON SIXTEEN VARIABLES

1 Degree of overcrowding (school)

2 Teacher/pupil ratios (trained teachers)

3 Efficient principal

4 Index of malnutrition

5 Overall teacher/pupil ratio

6 Percentage pupils attending 90 percent of school sessions

7 Crade-by-grade achievement in English

8 Ratio enrollment to school age population

9 Crade-by-grade achievement in mathematics

10 Percentage overcrowded schools

11 Percentage unstable families

12 Percentage teacher turn-over

13 Percentage students achieving below 50 percent in English and mathematics

14 Percentage eligible group obtaining pass mark in CEE (not necessarily awards)

15 Number of library books per pupil

16 Number of hours of ETV

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3. Socioeconomic status (if included)

4. Principals with less administrative experience

5. Higher grade level attained

6. Teacher1 s years of experience

7. Teacher's qualifications

8. Principal1 s qualifications.

The factors which separated urban high performers from low

performers were:

1. Higher socioeconomic status of parent (if included)

2. Sitting the CEE at higher grade levels

3. Schools where principals had fewer years of administrative experience

4. Schools with relatively higher teacher/pupil ratios

5-6. Teachers with higher qualifications and more years of experience

7-8. Less crowded schools and principals with higher qualifications

9-10. More sessions attended and higher percentage of trained teach ers.

For rural areas, the factors separating high performers from low

performers were:

1. Higher percentages of trained teachers

2. Principals with fewer years of administrative experience

3. Sitting the CEE when in a higher grade

4-5. More sessions attended and lower teacher/pupil ratios

6. Principals with better qualifications

7. Socioeconomic status (if included)

8. Grade teachers with higher qualifications and more years of experience.

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The teachers' survey produced the following high factors:

1. Degree of overcrowding

2. Teacher/pupil ratio— (trained teachers)

3. Efficient principal

4. index of malnutrition

5. Overall teacher/pupil ratio

6. Regular attendance

7. Achievement in English

8. Ratio enrollment to age cohort

9. Achievement in mathematics

10. Unstable family life .

Teachers added eighty-nine items as important indicators. These

were placed in ten categories. The four most important were:

1. Teachers and staff

2. School working conditions

3. Parents and home

4. Pupil behaviors.

Finally, the main factors mentioned by principals as important

contributing factors, negatively and positively, to performance in the

Common Entrance Examination were:

1. The home dimension— stable families with adequate supervision

and parental help

2. Attendance

3. Books

4. Pupil motivation and intelligence.

It should be noted that the top ten indicators rated by the teachers

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included five which emerged as important in the various segments of the

correlational analyses. These were:

1. The principal and his efficiency, cf. principal's qualifications

and years of service from the correlational study

2. The trained teacher input

3. The teacher/pupil ratio input

4. Regular attendance

5. Degree of overcrowding.

The other five highly rated indicators as presented to them but not

included in the correlational study as input/output variables were:

1. Degree of malnutrition

2. Achievement in English

3. Ratio enrollment to school-age population

4. Achievement in mathematics

5. Unstable families.

Implications

Certain findings in this study appear surprising and bear

closer study.

1. Overcrowding had a low weighting in rural areas. This may

reflect the fact that there are fewer overcrowded schools in rural areas.

That it does not emerge more heavily weighted in urban areas is also

surprising.

2. Principal's administrative experience (negative) may be a

function of distribution in the sample rather than a contributing factor.

3. High teacher/pupil ratios (positive) led to the question of

whether the effects are as negative as is generally supposed or whether

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these negative effects are mitigated by other inputs.

4. Socioeconomic status did not emerge as important in rural

areas. This is doubtessly because there was less differentiation

along this variable in rural areas. In urban areas, where there was

greater differentiation, the weight of this variable was more clearly

seen .

Comments

In spite of the possible intervening variables the findings of

this research point to the following implications:

1. A different composite of factors are contributing to school

success in rural areas from those in urban areas. Higher percentage of

trained teachers, longer and better school attendance, lower teacher/

pupil ratios are rural differentiating inputs. In fact, where socioeconomic

status is more homogeneous schooling inputs may make a more marked

difference than where there is greater differentiation in socioeconomic

status. It must be pointed out, however, that rural success may be

relatively lower overall than urban success. When socioeconomic status is

introduced into the urban analyses, it becomes a major factor influencing

school success. Nevertheless, even in overcrowded urban schools with

high teacher/pupil ratios, some children with longer and regular school

experience, and under better qualified and more experienced teachers,

were performing better. Officials responsible for financing education

should begin to look at these input variables in order to maximize their

use and observe the effect on pupil performance.

Although the sample of teachers was limited in number, their

rating of indicators is interesting. Mention has already been made of

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the three factors considered by them to be most important: (1) degree

of overcrowding, (2) trained teacher/pupil ratios, and (3) efficient

principal. The factor which ranked next in importance to these is one

which is more palpable to them than to non-school personnel, i.e., the

factor malnutrition. This was ranked above achievement and

above percentage of school-age population enrolled in school. The

implication is that this factor needs direct assessment. Other ratings

of indicators by the teachers are, by and large, what would be

expected. Noteworthy, however, are factors which earned the lowest

ratings, and, by virtue of this, are outstanding. These were (1)

percentage of children achieving pass marks in the CEE examination,

(2) use of the library, and (3) hours of educational television. This

might imply low perception of the importance of these factors on the part

of these teachers. The CEE is regarded, in many quarters, as a

"necessary evil." Its virtues, in terms of being a standardized test, are

not appreciated. The exam is perceived (1) as excluding children from

an elitist type of education which is viewed as desirable, and (2) as

producing negative self-concept in the children who fail the exam.

School library and educational television services received low

ratings. This may imply that these two resources are not perceived as

important educational inputs. Teachers' and the Ministry of Education's

supplies (books, etc.) are perhaps regarded as more important inputs.

Family of Indicators

What then may one put forward as the family of indicators or

the critical indicator? The researcher submits that these must be

determined not only by the conclusions of this research and previous

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findings as cited in the literature, but also by the present activities in

and needs of the Jamaican educational system. These include:

1. High absenteeism whether through irregular attendance or

major periods of absence during the school year

2. The steps being taken by the Ministry of Education to

address the problem through enforcement of the Compulsory Education

Clauses of the Education Act 1965

3. The fact that more girls than boys in the age cohort may be

participating in the educational system. More girls (22,979) than boys

(12,718) took the CEE in 1980 (Education Statistics 1979/80).

It is recommended that indicators for the Jamaican primary

system be categorized on a systems/economics/time dimension into:

1. Context indicators/leading indicators

2. Input/coincident indicators

3. Process/contributing indicators

4. Output/lagging indicators.

Indicator 1—A Context/Leading In d icato r

The first and most critical indicator therefore should be the

ratio of the age cohort attending school for a stated percentage of

sessions each term or year broken down by gender (male; female).

This is seen as a critical indicator. If pupils are not in school

they cannot be exposed to the effects of schooling; the longer the

pupil stays in formal education, the more likely it is that he/she will

leave school literate and numerate. This was borne out by the findings

of this research.

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It must be underscored that this statistic is distinctly different

from the average attendance statistic currently being used. The

average attendance statistic masks the attendance record of the indivi­

dual pupil. A prerequisite to the development of this statistic is know­

ledge of the schools catchment area— each school board managing a

pupil account. It is also different from the male/female flows put

forward by Johnstone (1981):

This indicator could be expressed as f(n) + m(n) = n ; TOT) + tTTn T fT

where f = female, m = male, n = numbers attending (say 90 percent) of

the sessions, N = the number in the age cohort of the school catchment

a re a .

The need for and importance of this indicator cannot be over­

stressed. It would clearly point up when, where, and in what categories,

grade-wise or sex-wise pupils were not participating in the education

system. Disaggregation would be possible and diagnostic and remedial

action could be undertaken on a timely basis. If other school conditions

are propitious, watching this indicator would forecast how well pupils

will perform over the period of primary school experience.

Indicator 2—A Process/Contributing In d ic a to r

The researcher submits that the second critical indicator should

be along the teaching dimension. The findings of this research suggest

that the percentage of trained teachers and the teachers' length of

experience combined have definite co-varying relationships with achieve­

ment. Teacher concerns figured strongly in teachers' responses both

to the survey questionnaire and on independent items. This finding also

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suggests that the CEE test requirements are being understood better by

experienced teachers. These grade teachers are known to give extra

lessons to CEE pupils, and it must be admitted that the trained, experi­

enced teacher contributes significantly to the CEE successes. Therefore,

if standards or objectives are set and enforced for the whole primary

system, teachers could be encouraged to produce as they do against the

CEE criteria. Two questions arise: First, could this "experience" skill

be taught? Second, could there be a statistic combining both factors to

provide a quick measure of expectation from the system? It is suggested

that this formula could be the ratio of trained teachers with x years of

experience over the number of pupils, by area of interest.

This could be a secondary statistic to pupil/teacher ratios (now

being collected) or percentage of trained teachers in schools. Further

research would be necessary to ascertain what should be the base number

of years or whether the relationship is curvilinear. Teaching style could

also be studied.

Indicator 3— A Output/Lagging In d ic a to r

The third critical indicator must be an output/outcome indicator

which measures the success of the system. This should be an assessment

system which quantitatively describes success grade-by-grade or at certain

predetermined critical levels in the system— say grades H and 6.

To some extent this is accomplished by the Common Entrance

Examination and a three-year assessment of all primary schools. This

study has pointed to the fact that quotients on the mathematics and

English test of the Common Entrance Examination may not be demonstrably

different after twenty-one years of similar test administration. If this

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is taking place among the select group offered for the CEE, what must

then be happening to the larger group? Standardized tests should be

introduced. The CEE results could also be monitored on this basis.

Other Indicators

There are other indicators suggested by this research but on

which definitive conclusions have not yet been reached.

Overcrowding— a contributing indicator. This was mostly

negatively related to achievement, though not as highly as might have

been expected. It was the foremost concern of the teachers in the

opinionnaire. The findings of this study may have been influenced by

the fact that mostly "brighter" pupils were sitting the Common Entrance

Examination, and that overcrowding was most adversely affecting "duller"

pupils who would not have been measured at all. That overcrowding

received a ranking of No. 1 of the thirty-one opinionnaire statements

shows that it is a nettlesome problem to teachers.

It may also be that the effects of overcrowding are not as

significant as the teachers feel them to be. Further study of this problem

should be made. Statistics for this indicator exist and only need to be

aggregated for monitoring as a contributing indicator.

Teacher/pupil ratio—a contributing indicator. In urban areas

higher ratios did not seem to affect achievement; in rural areas it did.

Further research is necessary to see whether after-school classes, given

by teachers in the system or individuals outside of it, are mitigating the

adverse effect of high teacher/pupil ratios in the schools. Establishment

of a definite relationship is necessary as this is a "process" — "contributing"

indicator of prime importance in the educational system.

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An index of malnutrition—an input indicator. This was of fourth

major concern to the teachers. A ratio based on assessed levels of

student malnutrition could be developed. Research establishing the

relationships between malnutrition and achievement could also be under­

taken, although the connection seems obvious. Its extent should be

m easured.

Principal's effectiveness—a process indicator. The negative

relationship of administrative experience of the principal needs further

investigation. Does this imply that, at a specific point in time there were

better educated principals with fewer years of service whose output in

terms of pupil achievement was better? An efficient principal was the

third indicator on the teachers' list. However, the findings of the study

may be a function of distribution in a small sample.

School inputs as input indicators. Research on the contribution

of media and textbooks is also needed before determination can be made

as to measures of effectiveness for these inputs. Should it be per unit

expenditures, or numbers of units, or combinations of units as inputs?

These are questions to be answered.

Enrollment projections. Usefulness of enrollment projections for

forecasting purposes was briefly mentioned in the literature review. The

need for these projections for planning purposes is obvious. They

are recommended for inclusion in the family of indicators. Graphical

representations would be useful for presentation. Attention is invited

to earlier work by the researcher on statistical methods for forecasting

enrollment at micro levels in Hanover, Jamaica (Marshalleck, 1976).

Expenditures per pupil. Mention was made in the review of

literature of the covarying relationship between per pupil expenditures

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and achievement. It has been brought out in the research that

expenditures may be more meaningfuBy looked at when they are made

against inputs which maximize outputs. Projections of total available

sums against presently efficient levels should provide some useful

bench marks. Further work to refine indicator measures is indicated.

Primary-school life-expectancy rates. This indicator arises

from the literature but also rests on the findings that higher grade

levels correlate with higher CEE scores. The indicator would be built

on trend analyses of primary-school completion rates. It would be

a critical indicator in manpower and human resource development planning.

Schema for indicators. Finally, figure 3 presents a schema

for the recommended and potential indicators. This figure summarizes

the discussions above.

Recommendations

Recommendations flowing from the research:

1. Replication of this study should be made periodically. With

the information gained from restudy of these school inputs, as well as

those listed in 2-7 below it would be possible for the Ministries of

Finance and Education to allocate resources more effectively.

2. Further study should be given to profiling the effective

principal in terms of levels of training, years of experience, as well as

other measures of effectiveness.

3. Further study should be given to teacher/pupil ratios to

determine desirable levels and to determine the relationship in "pure"

situations—i.e ., situations where no extra tutoring is provided. Co­

varying relationships should be examined in randomly selected and

ability streamed classes.

I r Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. 165

education

CONTEXT

--Interest In Children's --Income Parents'-Education - Socioeconomic Factors Socioeconomic LEADING INDICATORS 3- 3- OUTPUT and at Prescribed Levels Tests--Means Variances--Distributions LAGGING INDICATORS " " Other Standardized " " Numbers Achieving Literacy " " Numbers Entering Next Level " Common " Entrance Common Measures

"/Nos. Trained "/Pupil Ratios "Experience 2. 2. PROCESS Index of Overcrowding Media Books Books and Teaching Materials Principals- -Effectiveness Teachers' "Qualifications COINCIDENT CONTRIBUTING INDICATORS

education to Next Level 1. 1. INPUT CONTEXT CONTEXT CONTEXT --Income --Interest In Children's 0 Numbers Graduating Attending 901 Sessions Cohort Male and Female Entrants Principals Books Books and Teaching Materials Accomodation Media ’ ’ Percentage Pupils in Age LEADING INDICATORS LEADING INDICATORS Fig. 3. Schema for Indicators developed by writer LEADING INDICATORS " " Estimations of New Socioeconomic FactorsSocioeconomic „ Numbor9 Completing Ftarents'--Educatlon x grades

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4. The Ministry of Education should develop means of distribu­

ting the effects of the skilled teacher to areas of the system deficient

in this effect. Rural areas are usually most affected since qualified

teachers more often locate in urban areas. Periodic tutoring and super­

vision by master teachers and periodic extended teaching visits by

teams of master teachers are two possible solutions.

5. The Ministry of Education should undertake a cost benefit

analysis of Educational Television. It should be investigated whether

the medium could be used to help reduce the increasing costs of

teachers' salaries.

6. The Ministries of Health and Education should cooperate in

establishing regular school health examinations. Levels for under­

nourishment and malnutrition should be established and data gathered

(a) to examine the correlation between these conditions and achieve­

ment, and (b) to develop indices.

7. Study of the contribution of other educational inputs to

achievement should be made, e.g., (a) provision of textbooks in

differing combinations and numbers, (b) provision of school meals

(breakfast and/or lunch), (c) provision of uniforms, and (d) any other

input felt to be highly correlated with achievement. A random sample of

typical schools should be used in these studies.

8. The Ministry of Education should develop plans for annual

standardized achievement assessments grade-by-grade, across the school

system. If even on a sampling basis, the out-turns should be studied for

changes in averages, variances,and distribution.

Recommendations for administrative action:

Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. 167

1. The "teacher dimension" stood out in the responses from

teachers. The Ministry of Education should address these concerns as

best as possible. Despite financial constraints, efforts should be made

to come to terms with those concerns which are uppermost in the minds

of teachers. Detailed study may be required on this item.

2. The Ministry of Education should review its requirements for

school record keeping to make these as economical as possible in terms

of items, forms to be filled out, books kept,and returns to be made to

headquarters. Principals complained of the number of "statistics" to be

developed for the Ministry of Education and that no additional assistance

was provided them. The class list should be reviewed by the Ministry of

Education for reintroduction if considered advisable. On the other hand,

there is need for certain schools to preserve registers more carefully

and to send reliable returns promptly. The reliability of these data is

necessary for deriving valid measurements for educational studies and

international statistics.

3. Based on the findings of Reid's (1964) study and others

showing similar results, the Ministry of Education should mount programs

aimed at sensitizing parents to their responsibilities for their children's

education as well as their own continuing growth, however late it may

seem to them.

4. The Ministry of Education should not only use educational

indicators for planning purposes but should publicize them appropriately.

This could help to stimulate interest throughout the society on the

condition of primary education, a critical input in the country's program

of human resource development.

Eight years of education (over ages 6j-15) might be the

Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. 168

educational heritage for a major proportion of Jamaica's school age

population; it may be all that the public purse can afford for them

for some time to come. The outputs from this level of the system must

therefore be maximized in terms of curricular outputs and standards

reached. Primary education (grades 1-6, ages 6^-12) is a vital

segment of this and all other levels of education. There can hardly

be, therefore, an area more needful of early indicators of progress

toward goals or retrogression from them than the primary education

system .

Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. A P P E N D IX A

SAMPLE PACES FROM 198*1 ECONOMIC INDICATORS

C o n te n ts TOTAL OUTPUT, INCOME, AND SPENDING ^ Gross National Product...... 1 Gross National Product in 1972 D ollars ...... 2 Im plicit Price Deflators for Gross National Product ...... 2 Changes in G NP. Personal Consumption Expenditure*, and Related Price Measures ...... - ...... ) Nonftnancial Corporate Business—O utput. Costs, and Profits ...... 5 National Income ...... * Personal Consumption Expenditures ...... 4 Sources of Personal Income ..... 3 Disposition o f Personal Incom e ...... 6 Farm Income ...... - ...... Corporate Proflts ...... 8 Gross Private Domestic Investm ent ...... - ...... 9 Expenditures for New Plant and Equipment—Nonfarm Business ...... 10 EMPLOYMENT, UNEMPLOYMENT. AND WAGES Status o f the Labor Force ...... n Selected Unemployment Rates ...... - ...... 12 Selected Measures o f Unemployment and UnemploymentInsurance Programs ...... 13 Nonagricultural Employment ...... t4 Average W eekly Hours and H ourly Eamtngs— Private Nonagricultural Industries ...... - ...... 13 Average W eekly Earnings— Private Nonagricultural Industries ...... 13 Productivity and Related Data, Business Sector ...... 16 PRODUCTION AND BUSINESS ACTIVITY Industrial Production and Capacity U tilization ...... 17 Industrial Production—M ajor M arket Groups and SelectedManufactures ...... IS New Construction - ...... 19 New Private Housing and Vacancy Rates ...... 19 Business Sales and Inventories— Manufacturing and Trade ...... ~...... 20 Manufacturers* Shipments. Inventories, and O rders ...... - ...... - ...... 2\ PRICES Producer Prices ...... 22 Consumer Pnces— 23 Changes in Producer Prices for Finished Goods ...... 24 Changes in Consumer Pnces ...... 24 Prices Received and Paid by Farmers ...... 23 MONEY. CREDIT. AND SECURITY MARKETS Money Siock, Liquid Assets, and Debt Measures ...... -...... ~ ...... 26 Components o f Money Stock and Liquid Assets ...... — 27 Consumer Installment Credit ...... 2" Bank Loans and Investments, and Reserves ...... 28 Sources and Uses o f Funds. Nonfarm Nonftnancial Corporate Business ...... - ...... 29 Current Assets and Liabilities o f Nonfinancial Corporations ...... 29 Interest Rates and Bond Yields...... 30 Common Srock Prices and Y ields...... 5 1 FEDERAL FINANCE Federal Receipts, Outlays, and Debt ...... „ ...... 32 Federal Budget Receipts by Source and Outlays by Function ...... - ...... 33 Federal Sector, National Income Accounts Basis ...... - ...... - ...... 34 INTERNATIONAL STATISTICS Industrial Production and Consumer Prices— M ajor Industrial Countries ______—...... 33 U.S. Merchandise Exports and Im ports ...... 33 U.S. International Transactions ...... — ...... 36

I General Note { Detail to ebese cables may not add to totals because o f rounding, i Unless otherwise noted, all dollar figures are in current dollars.

169

Reproduced with permission of the copyright owner. Further reproduction prohibited without permission 170

CONSUMER PRICES In April, the consumer price index for afl urban consumers rose 0~5 percent seasonally adjusted and not seasonally adjusted. The index was 4.3 percent above its level in April 1983.

M OO . 1 f * 7 - 100 (KATtO SCALE) MCCX. 1 9 *7 -1 0 0 (XAnO SCALE) no

300 300

290 290

260

240

220 230

200 200

180

160

140 ^ 1976 1977 1979 1980

Ml «on r««| W u K I « **•» « « ** C* l*SOi (OW<» 9 t M in

(1967 ■ 100, ncrpt u M id ; eeethly dati eeesoeeBy adjtuttd, except u M id ] r Trias porta boo All Shelter items Appar­ lets ah Hoar- MirnTt- FWI M«Ccal Eaer- Prno4 F«o4 el urf food. ium i 1 •wa­ aaace a td New Motor nr* O* ' Total • Sem­ •placp T iu l 1 eneffr. TouJ en' rn ’ ud •dwr can bsd1 amd CtMU > (Ml 1 reprnn ihdtrr SSA SSA KM r "I RtL im p.*...... 100.0 18.7 37.6 21.3 7.0 14.0 0.5 H2 S3 21.8 3.5 5.9 6.1 ! 11.9 47.9 1976...... 170.5 180.8 174.6 179.0 199.6 182.7 147.6 165.5 135.7 177.9 184.7 189.3 159.9 1977...... 192.2 186.5 191.1 214.7 202.2 154.2 177.2 142.9 188.2 202.4 207.3 169.5 197M...... 211.4 202.8 210.4 ...... 233.0 216.0 159.6 185.5 153.8 196.3 219.4 i 220.4 179.1 1979 ...... , 217.4 234.5 227.6 239.7 256.4 239.3 166.6 212.0 IC6.0 265.6 239.7 2759 191.5 1980...... 246.8 254.6 263.3 281.7 ...... 285.7 278.6 178.4 249.7 179.3 369.1 265.9 361.1 208.3 I 9 * t ...... 272.4 274.6 293.5 314.7 ...... — 4...... 314.4 319.2 186.9 280.0 190.2 410.9 294.5 , 410.0 228.1 1982...... 289.1 265.7 314.7 337.0 ...... 334.1 350.8 191.8 291.5 197.6 389.4 328.7 416.1 245.6 1983...... 291.7 323.1 344.8 103.0 102.5 346.3 370.3 196.5 298.4 202.6 376.4 357.3 419.3 258.4 1983; Apr...... 295.5 291.5 320.3 341.4 101.7 101.7 343.6 366.6 194.7 293.7 201.4 368.7 353.1 413.3 255.7 ifa r ... 297 ! 292.1 321.1 342.3 102.2 102.0 344.3 368.4 195.7 296.4 201.1 379.8 354.8 420.5 256.3 June ..., 298.1 291.5 3219 343.3 102.5 102.2 345.1 369.3 196.3 2973 201.3 381.0 356.5 421.6 257.1 J u lr. ... 299.3 291.2 323.2 345.1 103.1 102.7 346.1 370.7 197.3 298.7 201.7 382.5 358.5 423.2 258.4 Auc- — 3003 291.7 324.1 346.3 103.6 103.0 347.9 371.9 197.9 300.8 203.3 383.7 360.3 424.6 259.7 Sept. .... 301.9 292.3 325.3 348.0 104.2 103.5 346.6 372.9 198.2 .702.8 204.9 383.7 361.7 425.1 260.9 O ct.. ... 302.6 293.5 326.0 349.3 104.6 103.9 351.1 372.2 198.2 304.4 205.5 383.2 362.9 424.2 262.2 s v . .... 303.1 294.1 327.4 350.7 105.0 104.3 353.4 374.4 198.5 305.5 205.3 381.6 364.7 424.5 263.5 Dec.. ... 303.5 295.4 328.1 351.8 105.3 104.5 354.7 373.8 198.5 306.1 205.7 379.8 366.0 423.3 264.2 19*4: Jan...... 305.2 300.2 329.6 353.0 105.7 104.9 356.7 378.2 199.0 306.7 205.6 375.9 368.6 421.7 265.8 Feb.. ..., 306.6 302.2 331.1 353.8 106.0 105.1 353.5 384.8 !9«.5 306.6 206.4 370.5 371.5 422.7 266.7 Mar . ..., 307.3 301.8 331.2 355.3 106.5 105.6 355.3 380.9 198.6 309.4 207.4 374.0 3735 I 421.8 267.H Apr...... ; 308.9 301.7 3338 357 6 107.4 106.2 356.3 383.9 1985 311.2 207.6 375.4 375.3 424.7 269.1

* ItrM n ivw M ■* i N u n .—JC5A data m M w iw m B t * rw^wWf it*;, im : tt? N tiw h r «4 wrWa rtHrr Im i «it br ««|» * W Im J m i t r m >nn«c «f t f v l m d p « U I * Fv4 «d. —•I ud MrtW pr. p« ifipil) , . Malar *4, ra d u l. Dili WfMMnc IW w w pm i i rratai tm t hr iM M tw nbf ««• w M d If ik tn im i m t «wtfr im u fillr m l fiprri

23

Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. APPENDIX B

JOHNSTONE (1981) SELECTED FORMULAS

Gini Coefficient

This statistic may best be described by reference to the attached

diagram of the Lorenz curve. The coefficient ratios the area between

the curve and the line of equality, to the total area under the line of

equality. The formula is:

n G = I (pi - 1qi - piqi - 1) i=1

where pi = the cumulative proportion of the characteristic whose equality

is being investigated, and qi= the cumulative proportion of the variable

which is acting as the criterion for the measurement.

The values for the two curves in the diagram are:

El S alvad o r G = 0.31

Nicaragua G = 0.41

Source: Johnstone (1981, pp. 93-94; 280-284).

171

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60 100

Cumulative percentage of students enrolled

Fig. 4. Lorenz curves measuring inequality of distribution of enrollments across grades at the first-level— El Salvador and Nicaragua, 1965 (Johnston, 1981, p. 93).

T A B L E 52

PERCENTAGE DISTRIBUTION OF FIRST-LEVEL STUDENTS BY GRADE— EL SALVADOR AND NICARAGUA, 1965

G rade El Salvador Nicaragua

1 37 45 2 20 20 3 15 14 4 12 10 5 n 6 6 7 5

Source: UNESCO Statistical Yearbook, 1974, p. 192.

The interpretation really implied by figure 4 is that, for El Salvador, 37 percent of the first-level enrollments receive 17 percent of the education offered at that level (i.e ., first grade), 57 percent of the total enrollment receives 33 percent of the total education offered (i.e ., first and second grades) and so on.

Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. 173

T h e C Index

1. Calculates percentages of students in each educational band.

2. Substitutes values into the equation below.

The frequently used measure of concentration is that known as

the Herfindahl-Hirschman index. It is very simply defined as:

k 2 C = z P i i=1

where Pi = proportion of total observations in the ith category, and

k = total number of categories.

If one category contains all observations, the C measure of

concentration takes the value of 1.0. If all k categories in a defined scale

have an equal proportion of the total amount— so no point of concentration

exists—the C measure takes the value 1/k. When there are many

categories, C is approximately 0.0 therefore.

3. The resulting value is interpretable in terms of whether there

is a concentration of students in one band or whether enrollments are

fairly evenly distributed across all bands. A high C value does not,

however, show where the concentration exists. Reference would have to

be made to th e basic d is trib u tio n s .

Source: Johnstone (1981, pp. 97, 154).

Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. 174

Expected Number of Years of Education to Be Received by an E n tra n t

Expected number of years 1 ______P I2 ______of education to be = (1 - r ^ ) + (1 - r-j-j) (1 - rjj) received by entrant P 23

+ (1 -r n )(l - r 22) (1 - r 33) + . .

(Equation 3.15)

The formula continues to develop as in the model evolving above.

For six grades, the last term to be summed would be:

______PI 2 P23 P34 P45 P56 ______(1 - r n )(1 - r 22)(1 - r 33)(1 - r^M l - r 55)(1 - r g6)

Substituting into Equation 3.15 can be time-consuming. When

moderately sophisticated computing facilities are available, it is more

efficient to use elementary matrix algebra.

Note: This is based on the Continuation Coefficient expressed as:

continuation = proportion of students promoted from grade i coefficient ______to g ra d e j______proportion of students not repeating grade i

= Pii 1 - r-. ii

Source: Johnstone (1981, pp. 109-110).

Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. 175

Expected Number of Grades of Education Completed by an E n tra n t

The formula for the number of grades expected to be completed

by a grade 1 entrant is:

number of grades pi2 + P 12 P23 expected to be = (1 - r n ) (1 - r n h l - r 22) completed by an e n tra n t P I 2 P23 P34______(1 - rn ) (l - r22) [ 1 - r23)

(Equation 3.17)

Source: Johnstone (1981, p. 112)

P ro p o rtio n o f E n tran ts Who F in a lly G rad u ate

The formula for the calculation of values is:

proportion of entrants who g rad u ate = P I 2 P23 P3U Pg

1 " r 11 1 " r 22 1 " r 33 1 - r gg

(Equation 3.19)

where the symbols are as for formula 3.19 and 'g' is the last grade in the

le v e l.

Source: Johnstone (1981, p. 113).

Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. 176

The Guttman Scale

The Guttman Scale Analysis involves two stages:

1. It identifies whether the set of nominated system charac­

teristics forms a hierarchy.

2. It orders the systems into the identified hierarchy.

An example is provided by Farrell ( 1969) in the attached

d ia g ra m .

Source: Johnstone (1981, pp. 134-136).

Laspeyres Formula for Education

Cost index for levels 1 - 3 is expressed as follows:

3

Cl = I E.. C.„ ib . it i=1

E -u-C *. ib ib i=1

where Cl = education cost index in year t; = enrollment at level i in

the base year b; and C.^ = per student cost for level i in year t.

When the pupil costs do not change from those operating in the

base year, or they change at the different levels by amounts proportional

to the base year enrollments at each level, the index number which is

calculated is 100. The weakness is that when there is a fall in demand

the Laspeyres formula will overstate price increases.

Source: Johnstone (1981, p. 105).

Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. erdcdwt priso o h cprgt we. ute erdcin rhbtd ihu permission. without prohibited reproduction Further owner. copyright the of permission with Reproduced

FARRELL'S SCALOGRAM OF EDUCATIONAL STRUCTURAL DIFFERENTIATION: 49 NATIONS, 1960 oiia Republic Dominican R. .5 C. uig ny tm wt * miuu Data Ambiguous * with items only using . .R C .95; = . .R C 0 ecn i mdl aeoy .92 = category model in percent 80 hn (Taiwan) China ad Arabia Saudi Philippines Afghanistan ot Korea South l Salvador El ot Rica Costa Venezuela Nicaragua Gua tema 1 a Indonesia Colombia Pakistan Ethiopia Thailand Paraguay Cambodia Honduras Morocco Tunisia olivia B Lebanon Uruguay Eucador beria ib L Mexico Ceylon Malaya razil B Guinea Jordan Panama Chile Nepal Syria Ghana Lybia Egypt Sudan Yemen aiti H Burma India Peru Laos Iraq Iran

I 1 II li (A V) *5■5 S § 177 11 = -3 ■= - 5 i- c c 01 U U V _ . KXXXXXXXOX o o o X « w w t w ? « I w I \ I § § »• o o ■ 3 5 > 3 > 3 -5 -3 ?■ ! • ~ ~ ~ ? • ! • • • 2 2 2 2 2 J | 2 - * • • d u

u £ 1 £ & * * & i w • - • • • C. Z J . C . C o. a — m a = 5 B> e 5 -= Is 5 1 xI a x I I - • £ w •

2 * 2 ■ *

_ _ H 1 3 / 3 i/l * * 5 a -

I ? i 5 i 2

Source: Farrell ( 1969, p. 309), illustrated in J. Johnstone. Indicators of Education Systems. Paris: UNESCO, International Institute for Educational Planning, 1981, p. 135. (ERIC Document Reproduction Service No. Ed 212 091). 178

Selected Indicator Formulas from UNESCO (1~974T

1. Equality of Acess

I = (a .b ) ru ra l (a.b) urban

where a = first grade enrollment ratio for new enrollments, and b = first

level education completion rate.

UNESCO (1974) points out that it is (theoretically) possible that

rural education might be more freely attended than urban education, in

which case the value for this indicator might exceed 1. Should such an

occasion arise, UNESCO suggests inverting the value. Values less than

0.5 form a "red zone" requiring remedial action (Johnstone, 1981, p. 144).

2. Minimum Educational Attainment: regarded as being four

years of first level education.

where N^ = the proportion of the total population of an age theoretically

corresponding to grade 4 of first-level which is enrolled in grade 4 or

above in year t, and z = a dummy variable to ensure the value for I is

between 0.0 and 1.0. "There seems to be reasonable consensus that four'

grades of primary education represents the true requisite for achieving

basic literacy" (Johnstone, 1981, p. 146).

3. Availability of Qualified Teachers: measures availability of

trained nationals as against expatriates in school system.

I = ( Ul (1 - s ^)) . ( u 2 (1 - s2))

where Uj = proportion of teachers with qualifications corresponding to

standard requirements or higher for ith level of education, and s. =

proportion of teaching force at the ith level who are expatriates.

Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. 179

Weakness: indicator makes assumptions that distributions of

qualifications of nationals and expatriates are identical. Johnstone (1981,

p. 158) suggests modifications—a division of the teacher qualification

spectrum into unqualified, semiqualified,and qualified.

4. Educational Flow Differential: measures differences in flow

patterns between males and females.

(a.b.c.d) females (a.b.c.d) males

where a = first-time first grade enrollment ratio; b = first level education

completion rate; c = transfer rate from first to second level; and d =

second level education completion rate.

To ensure a value between 0.0 and 1.0 UNESCO (1974) suggests

that when the value for males is smaller than that for females the inverse

of the value calculated should be used. Weaknesses include (1) confusion

in cross-national interpretations and ( 2) examination of gross flows only

(Johnstone, 1981, p. 160).

5. Educational Profile of the Unemployed: indicator showing

congruence between the education system and the labor force.

I = R.

" 1 where R j = unemployment rate of the population aged 15-64 with

education level i, and R^ = national average of unemployment rate of

population 15-64.

The dummy variable z ensures that the value for I lies between

0.0 and 1.0 by reducing all values for 1 above 1.0 to the maximum value.

Johnstone (1981, p. 160) shows that the indicator is limited in scope as well

as being insensitive to differential unemployment rates at various educational

le v e ls .

Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. APPENDIX C

MCGUIRE-WHITE SOCIAL CLASS INDEX

The McGuire-White Index of Socioeconomic Status is divided

into three areas—occupation of family head, source of the family

income, and education of the family head. The first rating, the

rating of occupation, is presented in table 54 . If the respondent

reports the family head is president of a corporation, the occupation

is g iv e n a ra tin g o f " 1"; if the respondent reports the family head

to be a high-school teacher, the occupation is given a rating of " 2";

if the respondent reports the family head to be a truck driver, the

occupation is given a rating of " 6," etc .

Whatever the respondent checks as being the primary source

of income is simply recorded as that number. For example, if the

respondent checks profits and royalties on the questionnaire, the

score o f " 3" is re c o rd e d .

The same is true for education. If the respondent indicates

the family head completed graduate work, a score of " 1" is recorded.

To calculate the total socioeconomic score for each subject,

the rating for occupation is multiplied by 5; the rating for source of

income is multiplied by 4; the rating for education is multiplied by

3—then the three scores are added together for total score. The total

score is checked against the listed five categories to see which level

180

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the respondent is in. For example, if the total score is 15, it would

fall in the upper-class category and the respondent would receive a

socioeconomic code of "1."

Category Socioeconomic Level Score

(1) Upper Class 12-22 (2) Upper Middle 23-37 (3) Lower Middle 38-51 (4) Upper Lower 52-66 (5) Lower Lower 67-84

Questionnaire items

1. What is the occupation of the head of your family of orienta­ tion household (teacher, minister, etc)? ______.

2. what is the primary source of the family income? ______1. Inherited savings and investments ______2. Earned wealth, transferable investment ______3. Profits, royalties, fees ______4. Salary, Commissions (regular, monthly, or yearly) ______5. Hourly wages, weekly checks ______6. Odd jobs, seasonal work, private charity ______7. Public relief or charity

3. What is the highest educational attainment of the principal earner of the family income? ______1. Completed graduate work for a profession ______2. Graduated from a 4 year college ______3. Attended college or university for two or more years ______4. Graduated from high school ______5. Attended high school, completed grade 9, but did not graduate ______6. Completed grade 8, but did not attend beyond grade 9 ______7. Less than grade 8

Reproduced with permission of the copyright owner. Further reproduction prohibited without permission.

Farm People landowner who do not leased property who their property. Land o perators supervise who properties £ have an activel i f e . urban farms who "hire out" supervise directly Farm owners w ith "h ired supervises "squatters-nesters" helpi" operators of foreman! owners of Small landowner,of rented operator hiring property "hands" lished farmsubs'ce laborers farmers. Gentlemen farmer or Sharecroppers! estab­ Tenants on good farms Migrant workers

t a i l o r , RR Policeman P o lice conduct. barber, prac.nurse, brake- C aptain, to r h elp er T axi £ trk qas s tn . a t . watchmaker d rlv e rs i w a ite r, w a itre s s , Domestic h e lp , bus boy, scrub men, men, e t a l. women, women, Ja n i­

Blue Collar Service Small contr. trician, RR engineer et al skilled trades who who works at or vises super­ his job Foreman! mstr carpenter, elec­ skilled wrks. repairm oni med. Apprentice to

i

TABLE 54 exec. sec. status of orqan. insurance, real estate, salesmen stock edit, writer auto salesman RR RR or t e l . tants to skilled tradei CPSi CPSi e d itoof r newspaper, Accountant! Bank c le rk , magazine! Semi-skilled factory and postal clerk, agt. or supv. Heavy la b o r, odd-job skilled mem workers production workersi assis­warehousemen, watchmen mine or m ill hands, un­ , grocery £ £ beauty

executives, (Stenographer, bookkeeper! (Dime s to re c le rk s u t i l i t y turing agents small branches salesman of supervisors! ticket in agent, dept sales stores, people et al President, et al bank, public some some manufac­ Top of corporation, Manager o f Asst, office £ known mchdse. or buyers £ dept. mgrs. or clerks! telephone operators, et al.

or MCGUIRE-WHITE SOCIAL CLASS INDEX--OCCUPAT IONS* ses valued $100,000 at from $10,000 $100,000 from $5,000 ProprietorsLarge busines­ Businessmen White Collar to $50,000 Dusiness value equity value to $10,000 from $2,000 $2,000 Business or Business or Business or to $5,000 equity value more depending on community at less than equity value at $50,000 to equity value

"Reputed Lawbreakers" teacher, libra­ ineer, school professor supt. teacher, tered regis­ nurse, e t a l r ia n , and others physician, eng­ with 4-yeardeqree out 4-yr deqree minister with­ High school table represent revisions made after interviewing in communities and are types to guide other ratings. *For an original table, consult Warner's revised scale (12, pp. 140-141). Modifications in the present 1. Lawyer, judge 3. Grade school 2. Rate Professionals 7. 4 .” " 5. 6. Business or

Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. A P P E N D IX D

PERFORMANCE OF ALL SCHOOLS IN CEE

THREE PARISHES 1979

List of Schools in Kingston, St. Andrew, and St. Thomas Showing (1) Enrollments (Grades 4-6), September, 1978, (2) CEE Entries, (3) Common Entrance Awards, and (4) Awards as Ratios o t bnroiimeht (Grades 4-b), January, 1979

Column 4 over Schools Enrollment Entries Awards Column 2

Parish of Kingston

Prim ary

1. All Saints' 94 22 3 .03 2. Allman Town 209 118 25 .12 3. A lpha 465 356 133 .29 4. Chetolah Park 396 141 61 -15 5. Clan Clarthy 358 156 32 .0 9

6. 751 220 43 -06 7. Franklyn Town 372 225 42 .11

8 . North Street Congregational 115 80 24 .21 9. Ormsby Hall 140 45 6 -04 10. Rollington Town 379 270 50 .13 11. St. Alban's 254 122 22 -09 12. St. Andrew 319 168 21 .07 13. St. Anne's 289 75 17 -06 14. St. Aloysius 386 234 82 -21

183

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Column 4 over Schools Enrollment Entries Awards Colum 2

Parish of Kingston

Primary & Infant 15. Holy Family 282 88 24 -09

All Age 16. All Saints' 314 104 14 -04 17. Boys Town 113 ! - .00 18. Central Branch 394 205 31 .08 19. Elletson 637 161 16 .03 20. Norman Cardens 443 155 25 .06 21 . 110 11 - .00 22. St. Michael's 311 61 13 .04

23. Wesley 97 6 - .00 24. Windward Road 748 163 83 .11

All Age & Infant 25. Calabar 570 214 44 .08 26. St. George's Girls 270 225 77 .29 27. 74 13 4 .05

'arish of St. Andrew

Primary 1. August Town 151) 43 1 - .00 126) 2. Balmagie 668 176 40 .06 3. Duhaney Park 435) 649 149 .16 498) 4. Dun robin 478 428 152 .32 5. George Headley 206 107 14 .07 6. Greenwich 373 184 27 .07

7. Grove 97 11 - .00 8. Half-Way-Tree 385 277 41 .11 9. Hope Valley 169 70 34 .20 10. Iris Gelley 123 27 1 -01 11. Jones Town 454) 287 52 .06 385)

Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. 185

Column 4 o ver Schools Enrollment E n trie s Awards Column 2

Parish of St. Andrew Primary - cont'd 12. Lawrence Tavern 417 170 46 .11 13. Maxfield Park 350) 323 29 .05 615 265) 14. Mona Heights 394 191 95 .24 15. Mountain View 332 199 17 .05

16. New Providence 448) 465 108 .12 913 465) 17. Pembroke Hall 485 329 139 .29 18. Rousseau 424 176 91 .21 19. St. Martin de Porres 140 46 3 .02 20. St. Patrick's 714 273 63 .09 21. St. Peter Claver 338 178 8 .02 22. St. Jude1 s 479 321 69 .14 23. Tarrant 520 237 123 .24 24. T rench Town 343 57 9 .03

Primary & Infant 25. Dupont 278 163 7 .03 26. Unity Primary 233 46 2 .01

All Age 27. Allman Hill 221 36 10 .05 28. Balcombe Drive 339 85 1 5 .04 29. Bito 14 3 - .00 30. Bloxburgh 31 2 1 .03 31. Bowden Hill 39 -- .00 32. Brandon Hill 91 4 - .00 33. Cavaliers 147 10 2 .01 34.Clifton 67 12 - .00 35. Cockburn Cardens 411 65 8 .02 36. Constant Spring 525 150 41 .08 37. Constitution Hill 86 14 2 .02

Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. 186

Colum n 4 o v e r Schools Enrollment Entries Awards Column 2

Parish of St. Andrew All Age - cont* d

38. Content Cap 63 19 - .00 39. Craighton 66 19 4 .06 40. Dallas 132 25 7 .05 41. Drews Avenue 395 178 27 .07 42. Essex Hall 117 13 - .00 43. Friendship Brook 59 8 - .00 44. Cordon Town 168 20 1 .01 69 18 .03 45. Greenwich Town 260) 562 302)562 46. Halls Delight 115 4 1 .01 47. Harbour View 565 391 106 .19 48. Hugh Sherlock 176 19 4 .02 49. King Weston 61 8 1 .02 50. Mannings Hill 121 6 - .00 51. Maverley 616 180 44 .07 52. Melrose 292 217 43 .15 53. Mico Practising 398 272 73 .18 54. Mt. Fletcher 170 17 2 .01 55. Mt. James 107 8 - .00 56. New Day 472 233 83 . 1 8 57. Padmore 58 4 - .00 58. Red Hills 166 18 6 .04 59. Rock Hall 266 76 17 .06 60. Seaward 467 195 44 .09 61. Somerset 58 11 - - 62. St. Richard's 339 239 115 . 34 63. St. Theresa's 121 5 1 .01 64. St. Benedict's 307 138 29 .09 65. Swallowfield 600 170 65 .11 66. Tavares Cardens 450 95 16 .04 67. Tower Hill 47 10 - .00

Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. 187

Column 4 over Schools Enrollment Entries Awards Column

Parish of St. Andrew All Aqe - cont1 d 68. Westphalia 41 6 - .00 69. Whitfield 636 146 23 .04 70. Woodford 91 11 - .00

All Age & Infant 71 . Colden Valley 96 16 - .00 72. Jack1 s Hill 64 8 - .00 73. John Mills 652 266 55 .08 74. New Carden 50 - - .00 75. Shortwood Practising 245 224 42 .17 76. St. Francis 332 222 46 .14 77. Stony Hill 382 76 9 .02

Parish of St. Thomas

Primary 1. 57 6 1 .02 2. Dalvey 86 21 1 .01 3. Duckenfield 299 79 33 .11 4. Font Hill 78 16 7 .09 5. Hillside 44 2 - .00 6. Lystra 98 6 2 .02 7. Middleton 157 32 13 .08 8. Mt. Vernon 40 4 - .00 9. Prospect 36 10 2 .06 10. Seaforth 412 50 13 .03 - * Cp. in^ Carden 76 19 3 .04 12. T rinityville 252 45 9 .04 13. White Hall 173 16 - .00 14. Winchester 45 7 - .00 15. 303 107 40 .13

Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. 188

Column 4 o v e r Schools Enrollment Entries Awards Column 2

Irish of St. Thomas

Primary £ Infant 16. Amity Hall 36 10 1 .0 3 17. Colden Grove 141 25 13 .0 9 18. Grants Pen 161 33 4 .02

All Age 19. Aelous Valley 157 34 10 .06 20. 121 15 1 .01

21. Arcadia 100 10 - .00 22. Bath 288 37 10 .03 23. Bethesda 95 19 1 .01 24. 210 24 1 .00 25. Easington 129 18 3 .02 26. Hayfield 47 8 - .00 27. Johns Town 64 12 - .00

28. Johnson Mt. 47 2 - .00 29. Lyssons 324 120 43 .13 30. Minto 90 21 1 .01 31. Morant Bay 670 188 70 .10

32. Mt. Felix 29 2 - .00

33. Old Pera 37 7 - .00 34. Penlyne Castle 55 9 1 .02 35. 230 18 11 .05 36. Richmond Gap 48 14 2 .04

37. Rowlandsfield 35 8 - .00

38. Thornton 94 12 - -00 39. White Horses 168 15 - -00 40. Wilmington 74 11 1 .01 41. Woburn Lawn 127 17 - -00

All Age S Infant 42. Cedar Valley 192 30 5 -03 43. Pear Tree River 72 7 5 .07

Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. A P P E N D IX E

PERFORMANCE OF ALL SCHOOLS IN CEE

THREE PARISHES 1980

List of Schools in Kingston, St. Andrew, and St. Thomas Showing (1) Enrollments (Grades 4-6), September, 1979, (2) CEE Entries, (3) Common Entrance Awards, and (4) Awards as Ratios of Enrollment [OraggTTR 6),'----- January, 1980

Column 4 over Schools Enrollment Entries Awards Column _ 2

Parish of Kingston

Primary *

1. All Saints' 80 22 - 00 2. Allman Town 353 126 13 04 3. Alpha 594 215 45 08 4. Chetolah Park 566 1 58 55 10 5. Clan Clarty 408 158 30 07 6. Denham Town 798 217 41 05 7. Franklyn Town 378 167 28 07 8. North Street Congregational 177 57 15 08 9. Ormsby Hall 165 45 6 04 10. Rollington Town 487 241 59 12 11. St. Alban's 328 123 18 05 12. St. Andrew 354 149 18 05 13. St. Anne's 394 97 24 06 14. St. Aloysius 496 237 76 15 15. Alpha II 210 192 74 35

* School classifications changed during 1979/80.

189

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Column 4 o v e r Schools Enrollment Entries Awards Column 2

Parish of Kingston

Primary S Infant 16. Holy Family 407 90 25 .06

All A ge

17. A ll Saints 297 101 15 .05

18. Boys Town 43 4 1 .02

19. Central Branch 392 180 40 .10 20. Elletson 465 122 7 .02 21. Norman Cardens 437 154 21 .05 22. Rennock Lodge 104 11 - .00 23. St. Michael 1 s 508 98 7 .01 24. Windward Road 625 173 77 .12

All Age & Infant

25. C alabar 609 204 57 .0 9

26. St. George's Girls 298 197 62 .21 27. P o rt Royal 70 19 2 .03

arish of St. Andrew

P rim ary

1. August Town 235 38 5 .02 2. Balmagie 610 167 45 .07 3. Duhaney Park 481) 674 134 .16 361) 4. Dunrobin 599 420 137 .23 5. Excelsior 35 29 10 .2 9 6. G eorge Headley 260 193 33 .1 3 7. Greenwich 377 158 36 .10

8 . G rove 73 11 - .00 9. H a lf-W a y -T re e 385 268 53 .14 10. Hope Valley Experimental 185 109 35 .19 11. Iris Gelley 120 30 2 .02

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Column 4 o v e r Schools Enrollment Entries Awards Column 2

Parish of St. Andrew Primary - cont 1 d 12. Jones Town 740 281 56 .08 13. Lawrence Tavern 422 116 19 .05 14. Lister Mair Cilbey 1 1 15. Maxfield Park 547 262 53 .10 16. Mona Heights 452 204 56 .12 17. Mountain View 317 166 16 .05 18. New Providence 432 343 112 .26 19. Pembroke Hall 420 327 126 .30

20. Rosseau 616 171 83 .13 21. St. Martin de Porres 177 40 11 .06

22. St. Patrick's 558 285 56 .10 23. St. Peter Claver 334 198 11 .03 24. S t. Ju d e's 470 343 89 .1 9 25. T a r r a n t 468 225 85 .18 26. Trench Town 292 53 20 .07 27. D up o n t 332 181 7 .0 2

Primary & Infant 28. U n ity 205 60 5 .02

All A ge 29. Allman Hill 220 57 6 .03 30. Balcombe Drive 306 64 16 .05

31. B ito 12 5 - .00

32. B lo xb u rg h 32 1 - .00 33. Bowden Hill 48 5 - .00

34. Brandon Hill 87 12 - .00 35. C a v a lie rs 127 10 1 .01 36. Cockburn Gardens 593 73 15 .31 37. Constant Spring 498 183 21 .0 4

38. Constitution Hill 72 8 - .00

39. Content Cap 65 17 - .00

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Column 4 o v e r Schools Enrollment Entries Awards Column 2

Parish of St. Andrew All Age - cont1 d 40. Craighton 61 18 1 .02 41. Dallas 168 20 9 .05 42. Drews Avenue 373 197 26 .07 43. Essex Hall 97 16 3 .03 44. Friendship Brook 66 9 - .00 45. Cordon Town 1 54 11 2 .01 46. Greenwich Town 485 67 6 .01 47. Halls Delight 95 10 - .00 48. Harbour View 565 383 73 .13 49. Hugh Sherlock 100 20 - .00 50. King Weston 67 20 2 .03 51. Mannings Hill 111 16 - .00 52. Maverley 586 156 32 . 05 53. Melrose 542 207 49 .09 54. Mico Practising 379 267 71 .19 55. Mt. Fletcher 1 98 18 2 .01 56. Mt. James 116 8 - .00 57. New Day 649 257 65 .10 58. Padmore 53 6 1 .02 59. Red Hills 173 30 10 .06 60. Rock Hall 369 79 13 .04 61. Seaward 766 171 38 .05 62. Somerset 58 16 1 .02 63. St. Richard's 359 224 122 .34 64. St. Theresa's 117 8 1 .01 65. St. Benedict's 308 95 12 .04 66. Swallowfield 557 212 54 .10 67. Tavares Cardens 362 111 7 .02 68. Westphalia 32 4 - .00 69. Whitfield 528 123 14 .03

70. Woodford 102 15 - .00

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Column 4 o v e r Schools Enrollment Entries Awards Column 2

Parish of St. Andrew

All Age S Infant 71. Golden Valley 91 8 1 .01 72. Jacks Hill 59 6 1 .02 73. John Mills 719 310 46 .06 74. Shortwood Practising 304 233 44 .14

75. St. Francis 265 225 35 .13 76. Stony Hill 452 56 12 .03

Parish of St. Thomas

Primary

1. Barking Lodge 53 8 - .00 2. Dalvey 90 18 5 .06 3. Duckenfield 275 78 26 .09 4. Font Hill 69 23 - .00 5. Hillside 35 4 - .00 6. Lystra 55 5 - .00 7. Middleton 139 45 7 .05

8. Mt. Vernon 32 2 - .00 9. Prospect 64 13 2 .03 10. Seaforth 326 55 12 .04

11. Spring Garden 60 18 1 .02 12. Trinity ville 230 43 11 .05 13. Whitehall 175 20 1 .02 14. Winchester 49 7 - .00 15. Yallahs 462 129 4£ .11

Primary & Infant

16. Amity Hall 30 13 - .00 17. Golden Grove 153 36 15 .10 18. Crant's Pen 136 26 5 .04

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Column 4 over Schools Enrollm ent E n trie s Aw ards Column 2

Parish of St. Thomas

All Age

19. Aelous Valley 142 18 1 .01 20. Airy Castle 98 23 4 .0 4 21. A rc a d ia 76 7 1 .01 22. B ath 265 46 5 .02 23. B ethesda 73 8 - .00

24. B u ll B ay 148 21 8 .05 25. E asington 112 24 3 .0 3

26. H a y fie ld 41 6 - .00 27. Johns Town 62 10 4 .06 28. Johnson Mt. 31 6 - .00 29. Lyssons 287 127 27 .0 9

30. M into 76 12 - .00 31 . Morant Bay 623 163 50 .0 8

32. Mt. Felix 37 6 - .00 33. O ld Pera 37 4 - .00 34. Penlyne Castle 57 9 1 .02 35. Port Morant 287 16 6 .02

36. Richmond Cap 55 16 - .00 37. Rowlandsfield 79 7 - .00 38. Thornton 81 25 - .00

39. White Horses 110 10 - .00

40. W ilm ington 49 11 - .00 41 . W oburn Lawn 125 15 1 .01 42. C e d a r Valley 175 43 4 .02

43. Pear Tree River 47 8 3 .06

Notes 1. Schools not submitting entrants were: Clifton, New Carden, Tower Hill, and Wesley. 2. Additional entries not included above = 16.

Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. A P P E N D IX F

T A B L E 55

CEE AWARDS 1979 AND 1980 AS PERCENTAGE OF PUPILS ENROLLED IN GRADES 4-6—TEN BEST PERFORMING URBAN SCHOOLS

Percentages School 1979 1980

St. Richard's Primary 34 34 Dunrobin Primary 32 23 Pembroke Hall Primary 29 30 St. George's Girls All-Age 6 In fa n t 29 21 A lpha II 15 Tarrant Primary 24 18 St. Aloysius Primary 21 15 Hope Valley Primary 6 Infant 20 19 New Providence Primary 12 26 Mico Practicing All-Age 18 19 * A djusted

T A B L E 56

CEE AWARDS 1979 AND 1980 AS PERCENTAGE OF PUPILS ENROLLED IN GRADES 4-6—TEN BEST PERFORMING RURAL SCHOOLS

Percentages School 1979 1980

Dallas All-Age 5 5 Lawrence Tavern Primary 11 5 Red Hills All-Age 4 6 Dalvey Primary 1 6 Duckenfield Primary 11 9 Golden Grove Primary 6 In fan t 9 10 Johns Town All-Age 0 6 Lyssons All-Age 13 9 Middleton Primary 8 5 Trinity ville Primary 4 5

Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. APPENDIX C

TABLE 57

DETAILS OF SCHOOL SAMPLE DRAWN, URBAN (MOST AWARDS)

Urban Schools Selected for Analysis with the Total Number of Students (1) Enrolled in Grades 4-6 in 1979/80, (2) Entered in the Common Entrance Examination, 1980, (3) Securing Awards, and and (4) Selected for Sample

School Enrollment Entries Awards Sample

St. Richard's 359 224 122 44

Dunrobin 599 420 137 53

Pembroke Hall 420 327 126 47

St. George's Girls 298 197 62 44

Alpha II 210 192 74 42

Tarrant 468 225 85 45

St. Aloysius 496 237 76 44

Hope Valley 185 109 35 35

New Providence 432 343 112 67

Mico Practising 379 26 7 71 45

Total 3, 846 2,541 900 466

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T A B L E 58

DETAILS OF SCHOOL SAMPLE DRAWN, URBAN (FEWEST AWARDS)

Urban Schools Selected for Analysis with (1) Nos, Enrolled C rad es 4 -6 in 1979/80 (2 ) Nos. of E n trie s in Common Entrance Examinations, 1980, (3) Nos. of Awards and (4) Sample Selected

School Enrollment Entries Awards Sample

Cordon Town 154 11 2 8

Allman Town 353 126 13 45

Dupont 332 181 7 31

B o y 1 s Town 43 4 1 4

Tavares Garden 362 111 7 26

B a (combe D rive 306 64 16 30

St. Peter Claver 334 198 11 33

M anning 1 s Hill 111 16 - 8

M ountain View 317 166 16 35

Seaward 766 171 38 38

Total 3, 078 1,048 111 263

Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. APPENDIX H

TABLE 59

DETAILS OF SCHOOL SAMPLE DRAWN, RURAL (MOST AWARDS)

Rural Schools Selected for Analysis with (1) Nos. Enrolled Crades 4-6 in 1 979/80, (2) Nos. of Entries in Common Entrance Examination, 1980, (3) Nos. of Awards and (4) Sample Selected

School Enrollment Entries Awards Sample

Duckenfield 275 78 26 37

Golden Grove 153 36 1 5 17

Lyssons 287 127 27 58

Johns Town 62 10 4 5

Red Hills 173 30 10 14

Lawrence Tavern 422 116 19 55

Dallas 168 20 9 9

Middleton 139 45 7 20

Dalvey 90 18 5 7

T rinityville 230 43 11 21

Total 1,999 523 133 243

Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. 199

T A B L E 60

DETAILS OF SCHOOL SAMPLE DRAWN, RURAL (FEWEST AWARDS)

Rural School Selected for Analysis with (1) Nos. Enrolled Crades 4-6 in 1979/80, (2) Nos. of Entries in Common Entrance Examination, 1980, (3) Nos. of Awards and (4) Sample Selected

School Enrollment E ntries Aw ards Sample

H a y fie ld 41 6 - 5

B ethesda 73 8 - 7

G rove 73 11 - 9

Halls Delight 95 10 - 8

M t. James 116 8 - 6

T h o rn to n 81 25 - 19

M t. F e lix 37 6 - 5

Bowden Hill 48 5 - 4

W estphalia 32 4 - 5

White Horses 110 10 - 8

Total 706 93 - 76

Reproduced with permission of the copyright owner. Further reproduction prohibited without permission.

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F o rm H o . 2a S in in f a n t 4 ( ( (See overleaf) rjvio ur Pervious Scxoou P r im a r y (b) Either i» now in Pnmary School or » u in Pnoury School up to La*1 Term (End ofSummer Tens), («) He* aurnJcJ Primary School for at ka il two yc*n; end M u k School Preferred . Schooli Picfcrred . Schooli I. School Code No, 1 0 2. CANDIDATE'S SUltNAME6, AND CHKiSlUN NAME AND NAM ADDRESS OF I.’ PARENT/Gl'ARDIAN (TO Jik COMl'LElED DY ‘ PRIMARY SCHOOL CAM)u5aTES) U . RtAiOM FOR FlPTT PfJIlXlN C l I l l PRIFCAINCB 9. TO DE COMPLETED UY OTHER CANDIDATES 12. 12. NAME OF NEAREST EXAMINATION CENT.IE « A P 2b J2b P u n

Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. A P P E N D IX J

SOCIOECONOMIC STATUS—CATEGORY 1 LOWEST INCOMES—PRIMARY EDUCATION ONLY

1. B arm aid 28. Laundress 2. Bar Tender 29. Messenger 3. Caretaker 30. Maid 4. Casual Worker 31. Meter Reader 5. Char Woman 32. Meter Repairman 6. C h e f 33. Mosquito Eradication Worker 7. C lean er 34. Office Assistant 8 . Clinic Attendant 35. Office Attendant 9. Cook 36. Office Helper 10. D ay's W orker 37. Office Maid 11. Delivery Man 38. Pants Renovator 12. Domestic Worker 39. Peddler 13. Female Attendant 40. P orter 14. Fisherman 41. Pump Operator 15. Fish V e n d o r 42. Self-Employed 16. G u ard 43. Shop Assistant 17. H elp er 44. Sprayman,Ministry of Health 18. Higgler 45. Surveyor Help 19. Hospital Attendant 46. Time Keeper 20. Hospital Cook 47. Unemployed 21. Hospital Helper 48. Unskilled Laborer 22. Hospital Orderly 49. Upholsterer 50. Vendor 23. Household Helper 24. Impact Worker 51. Waitress 25. Janitor 52. Ward Assistant 26. Lab Attendant 53. Ward Maid 27. Laborer 54. Watchman

SOCIOECONOMIC STATUS—CATEGORY 2 LOWER MIDDLE AND MIDDLE-MIDDLE INCOMES—SECONDARY EDUCATION LEVELS

1. A rtis t 5. Basic School Teacher 2. Assistant Nurse 6. Beautician 3. Assistant Security Officer 7. B inder 4. B a ker 8 . Brakeman, Jamaica Railway Corporation

201

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9. Bus Conductress 47. Motor Mechanic 10. B us D riv e r 48. Needle Worker 11. B u tc h e r 49. Nurses Aide 12. Cabinet Maker 50. Office Clerk 13. Canteen Operator 51. Operator 14. C a rp e n te r 52. Painter 15. C a s h ie r 53. Plumber 16. Chauffeur 54. Police Constable 17. Clerical Officer 55. Police Corporal 18. C le rk 56. Policeman 19. Confectioner 57. Postal Clerk 20. Counter Clerk 58. Postal Employee 21. Craft Worker 59. Postman 22. D e c o ra to r 60. Printer 23. Dressmaker/Seamstress 61. Psychiatric Aide 24. D r iv e r 62. Restaurant Operator 25. Electrician 63. Sales Clerk 26. F a b ric a to r 64. Salesman 27. Factory Worker 65. Saleswoman 28. F a rm e r 66. Security Guard 29. Field Assistant—Mosquito Control 67. Service Manager 30. Firem an 68 . Shoe Maker 31. Fruit Inspector 69. Shop Keeper 32. G ro c e r 70. Store Clerk 33. Headman 71. Store Employee 34. Headman (Kingston and St. Andrew 72. Student Corporation) 73. Student Typist 35. Hom eguard 74. Supervisor/Corporation Workers 36. Housekeeper 75. Tally Clerk 37. Housewife 76. Taxi Operator 38. Hotel Worker 77. Technician 39. IBM Key Punch Operator 78. Telegraph Clerk 40. Insurance Clerk 79.- T e le g ra p h O perator 41. Jamaica Public Service Worker 80. Telephone Operator 42. L an d la d y 81. Telephone Technician 43. Line Supervisor (Agricultural 82. Trailer Driver Marketing Corporation) 83. Transport Operator 44. Machine Operator 84. Truck Operator 45. Mason 85. T y p is t 46. Mechanic 86 . W elder

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SOCIOECONOMIC STATUS—CATEGORY 3 UPPER-MIDDLE AND LOWER UPPER CLASS INCOMES—WELL TRAINED PERSONNEL

1. A ccountant 28. Machine Shop Engineer 2. Advertising Agent 29. Manageress 3. Agricultural Officer 30. Medical Representative 4. Assistant Service Manager 31. Minister of Religion 5. Bank Clerk 32. Nurse 6. B u ild e r 33. Planter 7. Businessman 34. Price Investigator 8 . Civil Servant 35. Public Health Inspector 9. Contractor 36. Rehabilitation Officer 10. Correctional Officer 37. R e g is tra r 11. Crop Control Officer 38. Salesman 12. Detective 39. Sales Manager 13. Dress D esigner 40. Sales Representative 14. Druggist 41. Sales Supervisor 15. Elevator Engineer 42. S ecretary 16. Field Officer - JAMAL 43. Sergeant of Police 17. F lo ris t 44. Service Manager 18. Foster Parent Home Supervisor 45. State Registered Nurse 19. G arm ent M an u factu rer 46. Stenographer 20. Internal Auditor 47. Stenotype— writer 21. JAMAL Area Officer 48. Statistician Ministry of Labour 22. Jeweller 49. Supervisor 23. Lab Technician 50. Supervisor JTC 24. Lecturer 51. Supervisor Telephone Operator 25. Librarian 52. Teacher 26. Life Underwriter 53. Travel Consultant 27. Lithographer 54. Verbatim Reporter

JAMAL = Jamaica Movement for the Advancement of Literacy JTC = Jamaica Telephone Company

Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. erdcd ih emsin fte oyih onr Frhrrpouto poiie ihu permission. without prohibited reproduction Further owner. copyright the of permission with Reproduced

EXAMINATION CLASS LIST ( Illustration) eieH oj g ja jo a -euimexH s| e epueis u p je p ;e tse| o ja u a6v 6 a ui sjeaA uo Date

jg jsen jjig q p e X of u j aea aje jo -ug m OLD SJB3A |OOL|DS 0 uoi;euiuiex

Buipjoooe } Admission 10 V S S oe v u a aouep u uoissiiupv in a SUOISS9S NAMES This First

UOI* School School

1 3

J N C m in C APPENDIX L

SAMPLE OF QUESTIONNAIRE WITH

ACCOMPANYING LETTER

Dear Teacher:

You have often thought, no doubt, of the many areas of educa­ tional operations in our island which either describe the health of our educational systems or are directly related to good or poor academic performance. These would be critical factors or indicators to be watched and possibly controlled. The question arises as to which are important indicators and w hether there is agreem ent in research and among educators on these.

I am currently doing a doctoral dissertation on just such a problem, trying to isolate a set of indicators of the inputs into primary education which relate to performance. This is being done, first by study of the Common Entrance results of 1 980, alongside certain school and pupil variables. Next, I wish to secure the opinions of teachers as to what they consider to be significant factors in primary education, both in terms of causal and descriptive factors/indicators.

Would you kindly assist me in this study by completing the attached form? First, please rate the importance of the indicators in the attached list on a five point scale from 1-5 graduated as follows:

1. = Extrem ely important 2. = Very important 3. = O f medium importance 4. = of less than medium importance 5. = O f little importance

Next, please add in the space provided, any important indicators which I may have omitted, and similarly rate these.

Your input is critical to this study so please oblige by returning this form at your earliest. A stamped self-addressed envelope is enclosed.

This study had the approval of the Ministry of Education, as proof of which it has been countersigned by the Assistant Chief Education Officer (Primary Education' .

205

Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. 206

I look forward to an early response.

Yours gratefully.

Jean Marshalleck c/o Ministry of Finance 6 Planning 30 National Heroes Circle, Kingston 4

Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. 207

RATINC OF PERFORMANCE INDICATORS

Primary School System in Jamaica

PLEASE PROVIDE YOUR RATINC OF THE FOLLOWING MEASURES OF EDUCATIONAL PERFORMANCE BY ASSIGNING A NUMBER AS GIVEN IN THE SCALE BELOW

e.g. Extremely Very Medium Less than Little =1 =2 =3 Medium=4 =5 High Performance in Common Entrance Examination 2

INDICATORS IMPORTANCE - RATING SCALE

Extremely Very Medium Less than Little =1 =2 =3 Medium=4 =5

Ratio Enrollment to School Age Population a) By Parish b) For the Island

2 . Degree of Over­ crowding by School

Percentage Over­ crowded Schools a) By Parish 4 b) For the Island 5

Teacher/Pupil Ratio-T rained Teachers a) By School 6 b) By Parish 7

5. Teacher/Pupil Ratio Overall a) By School b) By Parish

Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. 208

INDICATORS IMPORTANCE - RATINC SCALE

Extremely Very Medium Less than Little =1 =2 =3 Medium=4 =5

6. Percentage Teacher T u rn -O v e r Annually a) By School 10 b) By Parish 11 c) For the Island 12

7. Percentage Pupils Attending 90% of School Sessions Termly or Yearly a) By School 13 b) By Parish 14 c) For the Island 15

8. C rade by Crade Average Achieve­ ment in English a) By School 16 b) By Parish 17 c) For the Island 18

9. C rade by Crade Average Achieve­ ment in Mathe­ matics a) By School 19 b) By Parish 20 c) For the Island 21

10. Percentage of Students achiev­ ing Below 50% in English and Mathematics a) By School 22

11. Percentage Eli­ gible Age Croup Obtaining Passing M ark in Common Entrance Exami­ nations (not neces­ sarily awards) a) By School 23 b) By Parish 24

Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. 209

INDICATORS IMPORTANCE - RATINC SCALE

Extrem ely V ery Medium Less than Little =1 =2 =3 Medium =4 =5

12. Na of L ib rary Books Per Pupil a) By School 25

1 3. No. of Hours of Educational T.V. Viewed a) By School 26

14. index o f Mal­ n u tritio n a) By D istrict 27 b) By Parish 28

15. Percentage Un­ stable Families a) By School 29 b) By Parish 30

16. Efficient Principal a) By School 31

17. Others (Please add any other indicators you consider impor­ tant and rate them similarly.) 32

18. 33

19. 34

20. 35

Kindly return to: Mrs. Jean Marshalleck c/o Ministry of Finance and Planning 30 National Heroes Circle, Kingston 4

Please give your name and address if you wish a copy of the results of this study.

Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. A P P E N D IX M

ADDITIONAL INDICATORS AS SUCCESTED

BY TEACHERS

Teachers and Staff

1. Efficient staff and good staff relationship 2 . Efficient staff 3. Efficient teacher by school 4. Teachers' interest 5. Teachers' salary 6 . Teacher/pupil relationship 7. Refresher courses for all teachers 8 . Degree of backwardness among teachers 9. Teachers' salary vs. pupils' performance 10. Teacher/parent communication 11. Teachers' personal interest in children 12. Trained teacher of Grade 6 13. Give all Common Entrance teachers insight of examinations, not some 14. Teacher/parent relationship 15. Teacher/teacher relationship 16. Pupil relationship set 17. Staff relationship 18. Attitude of teachers towards pupils

School Working Conditions

1. W orking conditions 2. School equipment 3. Availability of textbooks 4. Proper sanitary conveniences 5. Furniture 6 . Security of building 7. Size of buildings and accomodation by school 8 . Environment school and home 9. Health facilities by school 10. Health and Medical Care 11. How poor classroom equipment affects learning 12. Proper security of school, community facility and properties 13. Books 14. Pleasant learning situations

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15. Protection of school property 16. Working conditions

Parents and Home

1. Father image should be strong and positive 2. Parental supervision/homework 3. Educational facilities at home 4. Nutrients of pregnant mothers 5. (Q and literacy of parents in aiding children 6. Parents' attitude to pupils 7. Low or no income 8. Most effort spent on other children who are at other schools 9. Parental guidance 10. Family help and guidance 11. Home supervision and discipline 12. Parents' attitude 13. Environment at school and home

Pupil Behaviors

1. Pupil/pupil relationship 2. Pupils' interest 3. Pupils' and parents' interest 4. Children should learn to select priorities study before recreation (Games, T .V .) 5. Number of mentally handicapped pupils who need special treatment by school 6. Children's interest 7. Security of child up to age 6 y e ars 8. T .V . programs viewed after school hours 9. Social functions attended after school hours 10. Pupils' attitude to work 11. Pupils attending church and not roaming the streets 12. Pupils should attend selected shows

Curriculum /Achievement

1. Availability of textbooks and resource materials 2. Guidance services 3. Emphasis on practical work later easily applied to life 4. Printed textbooks relevant to Jamaica 5. National syllabus for all primary schools 6. Relevance of curriculum to communities 7. Level of reading

D iscipline

1. Discipline regarding independent study 2. Amount of play period 3. B eh avio r 4. Discipline

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5. indiscipline in schools 6. Home supervision and discipline

Diet and Nutrition

1. Number of free lunches per pupil by school 2. Consistent school feeding program 3. Feeding 4. Diet 5. Nutrition

Ministry of Education Inputs

1. Supervisors by (1) constituency, and (2) district 2. Efficient Ministry staff for Island 3. Public relations training by parish/by Island

Parent/Teachers Associations

1. P.T.A. involvement 2. Place of P.T.A. in school life

O th er

1. Cooperation 2 . Distance from home to school 3. Clothing 4. Take politics out of schools 5. School Boards—quality of members 6 . School transportation 7. Community school relationship

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PRINCIPALS' OBSERVATIONS ON FACTORS INFLUENCING PERFORMANCE IN THE COMMON ENTRANCE EXAMINATION

Urban Schools—Most Awards

St. Richard's Economic factors; unhappy or unstable parental/guardian relationships; parental and teacher pressures.

Dunrobin Consistent work; teacher and children; motivation of pupils; regular attendance.

Pembroke Hall Regular attendance; supply of learning materials; pupil's interest and attitude; parent's interest and attitude.

St. George's Innate intelligence; stable home; loss of parent detrimental, socioeconomic back­ ground; home with books.

Alpha II Not supplied.

T a rra n t Not supplied.

St. Aloysius Not supplied.

Hope V alley Economic background; parents' interest in child's progress; home environment; availability of reading material; ability to help p u p ils, etc.

New Providence Not supplied.

Mico Practising Two parent family.

Urban Schools—Fewest Awards

Gordon Town Intelligence; good school adjustm ent; extra lessons; irregular attendance; loss of books.

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Urban Schools—Fewest Awards - cont'd

Boy1 s Town Not supplied.

Tavares Cardens Pupils fail to purchase text books. Physical conditions at home impede " Home W ork." Some pupils do not have even tables to sit around. Parents not capable of helping children with the "Prep" work.

Balcombe Drive Irregular attendance; depressing environ­ mental factors.

St. Peter Claver Most of the students are late developers.

Manning's Hill Not supplied.

Mountain View Unstable environment; lack of personal books; poor attendance; interference by unemployed youths of the community.

Seaward One big factor is that many students are anxious to do well so as to be able to get out of their depressed community and go to other schools. Teachers responsible for preparing students are very keen. Hard w ork.

Dupont Cood home background; proper food and parental guidance.

Rural Schools—Most Awards

Duckenfield Not supplied.

Golden Grove Regular attendance; regular speed tests; manipulation of tables; good use of library facilities.

Lyssons Attendance; home influence; parents who can help; having text books; children who read a lot; ability grouping; do given assignments and corrections regularly.

Rural Schools—Fewest Awards

Halls Delight - Irregularity of attendance; lack of teaching facilities; lack of exposure.

Mt. James - Adequate text books; good teaching skills; a rounded curriculum, especially at Grades

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Rural Schools- -Fewest Awards - cont1 d

5 and 6 levels; use of library books for information and enjoyment; correct usages in oral expression followed by written expression.

Thornton Not supplied.

Mount Felix Not supplied.

Bowden Hill Comprehension skills (poor); computation (fair); some pupils had to travel long distances over hilly terrain to school; others attended poorly; all these pupils got no help with their studies at home.

Westphalia Regular checks with past papers at the Ministry of Education.

White Horses Not supplied.

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Personal Data: Name: Edith Geraldine Marshalleck Date of Birth: June 16, 1930 Place of Birth: , Westmoreland, Jamaica

Degrees Awarded: 1956 B.A. (Ceneral) University of London (University College of the West Indies, Mona, Jamaica) 1957 Diploma of Ed. University College of the West Indies, (Distinction, Mona, Jamaica in Teaching) 1972 Higher Diploma University of the West Indies, Mona, Jamaica of Education 1976 M.A. Education Andrews University, Berrien Springs, Michigan 1984 E d .D . Andrews University, Berrien Springs, Michigan Educational Administration

Positions Held: 1957-58 Acting Principal, Bahamas Academy, Nassau, Bahamas 1958-61 Clerk to the Privy Council, Governor's Secretary's Office, Jamaica 1961-66 Administrative positions. Ministry of Finance and Planning and Ministry of Agriculture, Jamaica 1978-80 Projects Coordinator and Acting Director, Construction and Maintenance Division, Ministry of Education, Jamaica 1981-82 Director, Budget Division, Ministry of Finance and Planning, Jamaica 1982- Deputy Financial Secretary, Ministry of Finance and Planning, Jamaica

Board Membership: 1972-73 Jamaica Movement for the Advancement of Literacy 1981- Project Analysis and Monitoring Company, Jamaica

Professional Membership: 1975 Charter Member Phi Delta Kappa, Andrews University chapter, Berrien Springs, Michigan

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