of pupils at the lowest - ed

DOCUMENT RESUME

24 AA 000 318

Survey and Analyses of Results from Title I Funding for Compensatory Education. Final Report.

General Electric Co., Washington, DC. TEMPO .Spons Agency -Office of Education (DHEW), Washington, DC . Bureau of Resear ch.

Report No -FR -67TMP -115Bureau No -BR -7 -0979Pub Date 1 Mar 68Contract -OEC -05 -67 -55Note-227p.EDRS Price MF -$100 I-IC -$1145Descriptors -Academic Performance, *Achievement Rating, Achievement Tests, Community Characteristics,

*Comparative Analysis, *Compensatory Education Programs, Data Analysis, Economically Disadvantaged,

Educational Finance, Educational:), Disadvantaged, Elementary Grades, Environmental Influences, *Federal Aid,

*Program Evaluation, Secondary Grades, Student Characteristics, SurveysIdentifiers -*ESEA Title I Programs

The aim of the study was to provide the Department of Health, Education, andWelfare with evidence as to the productivity of compensatory education (CE) programs

for disadvantaged children, particularly the effects of Title I of the Elementary and

Secondary Act of 1965 during its first year and a half. Data were coHected on pupilperformance and exposure to CE in 11 school districts (132 schools): in addition toachievement test scores for 1965-66 and 1966-67, information was gathered on thecharacteristics of the pupils, their schools, and their communities. Results indicated:(1)

a slight decline in average pupil achievement level in the sample schools. (2) a slightimprovement in achievement of pupils at the lowest achievement levels in their

respective grades; and (3) considerable variation in changes in achievement among

school districts. Preliminary results suggested that the amount of improvement was

related to level of Title I expenditures. The overall study provided evidence that morespecific studies were needed to properly evaluate the effects of Title I. Appendicescontain technical discussions as well as supporting material for the main text.(JAM)

-

.1::%>'

C.... t 'A pa.--1 j.....1

%.> f:: a_

..

,

U.S. DEPARTMENT OF HEALTH, EDUCATION 8 WELFARE

OFFICE OF EDUCATION

THIS DOCUMENT HAS BEEN REPRODUCED EXACTLY AS RECEIVED FROM THE

PERSON tlt ORGANIZATION ORIGINATING IT. POINTS OF VIEW OR OPINIONS

STATED DO NOT NECESSARILY REPRESENT OFFICIAL OFFICE OF EDUCATION

POSITION OR POLICY.

SURVEY AND ANALYSES OF RESULTS FROMTITLE I FUNDING FOR COMPENSATORY EDUCATION

FINAL REPORT

67TMP-115

1 March 1968

Submitted ToProject Officers

Department Health, Education and WelfareWashington, D.C. 20211

TEMPOGENERAL ELECTRIC COMPANY

WASHINGTON OPERATION

Copy

iii

ININIPPA Al.r'rK crm...c

This report summarizes the work done to date by General Electric,TEMPO on Contract No. HEW-05-67-55, A Survey and PreliminaryCost-Benefit Analysis in Elementary-Secondary Education, Phase I.The study, which began 21 April 1967, was conducted as a joint effortwith the Department of Health, Education and Welfare (DHEW) and

the Office of Education (OE). Although this report is submitted as afinal report on the above contract, it should be viewed as a progressreport on the overall study, and should be added to the body of infor-mation which was reported earlier.

Two interim progress reports preceded the present report:

67TMP-67 (submitted 27 June, revised 21 July 1967)

67TMP-89 (submitted 15 September 1967)

The June report describes data collection formats and discussesproblems in data collection. The proposed analytical approach ispresented in detail.

The September report summarizes the fourteen field trips con-ducted in the study and provides descriptive information on those com-pensatory education (CE) programs. The trip reports provide descrip-tions of the information and impressions obtained from sits to four-teen school districts.

The trip reports are reprinted as a separate appendix to this report.

SYNOPSIS OF WORK

The first several weeks of the study were devoted to designing ana-lytical approaches and planning a survey of CE programs in selectedschool districts. Models for testing the statistical significance of

observed changes in selected pupil performance measures were de-veloped and presented in 67TMP-67, the June progress report.

:

iv67TMP-115

Plans ,`.c obtain data on pupil performance and exposure to CE were

expanded to include information on the characteristics of the pupils,

their schools and their communities. The large variation in these

later variables was jiidged as important for explaining observed

changes in pupil performance between 1965-66 and 1966-67.

Following guidelines of the Office of Education (as contained in

their financial and pupil accounting handbooks), special forms weredesigned to obtain data in a standardized fashion to conserve the time

of school personnel. (The forms are displayed in 67TMP-67.)

The fourteen school districts included in the study were selected

by DHEW but were not intended to be representative of all school dis-

tricts pursuing compensatory education programs. Rather, for most

of the districts selected, there was reason to believe that successful

programs were in progress in at least some of the schools. One ob-

jective of the study wa i. to investigate the characteristics of programs

which held promise of favorable impact on the performance of de-

prived children.

The field trips were made by joint tearis of DHEW, OE and TEMPO

personnel and entailed 3-day to 2-week visits to each district. Un-

doubtedly more time would have been helpful in every case but the

need to visit many locations in order to expand the sample sizes of

schools and programs was considered more important. One negative

effect of the intense travel schedule was the inability to summarize

and analyze adequately the information and impressions after each

trip.

Problems encountered in collecting information provide insight

into the complexity of such a study and are, therefore, useful. back-

ground information. Briefiy stated, the more severe problems were:

amount of detailed information required for making per-

formance measures compatible is very great and the number

of special conversion factors that are required prevents

extensive use of automatic data processing;

achievement scores came from different tests and came

from tests which were administered at different points during

the school year among and within the sample districts;

much of the readily available data on CE were not in usable

form for study because they did not give Information for spe-

cific grades;

PREFACE

it was difficult to distinguish between CE and regular schoolprograms and between CE programs funded by federal andnon-federal agencies;

the large transfer of pupils into a sample school makes itdifficult to identify the amount of CE to which pupils havebeen exposed.

Achievement data received from the school were reviewed for ap-plicability in comparing 1965-66 with 1966-67 performance levels.Because of incompatibility and incompleteness of data, it was neces-sary to delete three of the fourteen school districts in the statisticalanalysis. The trip reports include information of fourteen school dis-tricts but the rest of the report is based on information from elevenschool districts.

SYNOPSIS OF THIS REPORT

This final report consists of four sections, and seven attached ap-pendices. An appendix of trip reports, prepared for use within DHEWand OE, has been bound separately to maintain the school-districtanonymity requested for this report.

Section 1 describes the original study objectives and the. technicalapproach used in analyzing sample data. It gives a brief summaryof the final selection of observations for statistical analysis.

Section 2 presents the results of an analysis which changes inachievement test scores and the association of ch,-_nges with the spe-cific state varirbles are examined. The variation in achievementtest scores among school districts is described and a summary ofthe procedures used in processing achievement data is presented.

Section 3 analyzes the correlation between changes in achievementand Title I expenditures measured at the district level. It also il-lustrates, for two sample school districts, procedures used and prob-lems inherent in determining the type and level of CE at the gradelevel in specific schools. It provides insight into variations in thetype, purpose, duration and intensity of CE programs, and in thetype of students involved in them, and the relationship of these pro-grams to regular education programs.

Section 4 presents observations, conclusions and recommendationsbased on the Phase I effort.

vi 67TMP-115

The attached appendices contain technical discussions as well as

supporting material for the discussions in the main text.

vii

SUMMARY

This report analyzes data from a sample of 132 schools whichreceived funds from Title I for compensatory education to aid educa-tionally disadvantagee. pupils. Most of the eleven school districts fromwhich the schools were drawn were selected because there was rea-son to believe tint successful compensatory education programs werein progress in at least some of the district schools. Conclusions arebased on a comparison of achievement scores in 1966-67, after pupilswere exposed to compensatory education from Title I funds, withachievement scores in 1965-66.

There appears to have been a slight decline in average pupil achieve-ment level in the sample schools. For the entire sample the averagegrade equivalence score in 1966-67 was approximately one-half monthlower than the corresponding grade equivalence score in 1965-66.The percentage of the pupils in the 1966-67 test results who also par-ticipated in programs funded by Title I is not known but is believedto be less than 50 percent.

On the other hand, there appez...._ a to have been a slight improve-ment in achievement of pupils who are at the lowest achievement levelsin their respective grades. The average grade equivalence score of

pupils at the lowest decile in the 1966-67 tests was -Tproximately one-fourth month higher than the average grade equivalence score of cor-responding pupils in the 1965-66 tests. Although the one-fourth monthchange is very small, it is statistically different from the observednegative changes in both the mean score and the score at the upperquartile.

There is considerable variation in changes in achievement amongschool districts. One district shows a statistically significant increasein the average score while two show significant declines. With re-spect to achievement at the lowest decile, none of the school districtsshows significant decrease, but two districts show significant increases.

viii 67TMP-115

The very preliminary results suggest that amount of improvementis related to level of Title I expenditures. The districts which showedthe largest improvement at the lowest decile are the districts whichhad the higher average Title 1 expenditures per pupil.

The two variables most closely related to changes in achievementare initial achievement level and percent Negro. Lower initialachievement levels in 1965-66 are associated with iarger gains be-tween 1965-66 and 1966-67. This suggests that the availability ofTitle I funds is probably helping pupils at the lowest achievementlevels the most. Schools which had 40 to 60 percent Negro pupilsshowed the poorest response to compensatory education programs.Schools with 0 to 20 percent Negro pupils showed the best response.

Examinations of schools in two districts reveal extremely widevariationo among schools and among grades within a school in ex-penditures for both regular school programs and compensatory edu-cation programs. in one of the districts there was a positive cor-relation between changes in achievement and total expenditures butin the other district no significant relationship could be detected.

The overall study provides considerable evidence that more spe-cific studies are needed to properly evaluate the effects from TitleI. In addition, more emphasis should be placed on getting participat-ing schools to keep systematic records on pupil, school, and programcharacteristics. The records from many schools are not adequatefor the types of analysis required for proper evaluation of compensa-tory education.

It is always possible that the positive changes which have been at-tributed to CE are due to sampling variation. However, a must berecognized that to judge statistical results as insignificant also in-volves risk. There can be a loss to society in failing to support aprogram that is actually successful but available data do not clearlyindicate the success. TEMPO relates the above conclusions and thedetailed discussions in the remainder of the report as an objectiveevaluation in light of available data. It must be kept in mind that TitleI funded programs were still relatively new at the time of 1966-67tests and it is not reasonable to expect large gains in achievement sosoon.

-

ix

TABLE OF CONTENTS

PREFACE iii

Synopsis of Work iii

Synopsis of _This Report v

SUMMARY

LIST OF ILLUSTRATIONS xi

LIST OF TABLES xii

SECTION

1 I NTRODUCTI ON 1

Study Objectives 1

Summary of Data Collected 2

Summary of Technical Approach 6

2 CHANGES IN ACHIEVEMENT TEST SCORESBETWEEN 1 965-66 AND 1 966-67 12

The Measurement of Achievement andInfluence of Title I 12

Processing Achievement Data 18

Results of Statistical Analysis 25

3 PRELIMINARY ANALYSIS IN IDENTIFICATION OFDISTINGUISHING FEATURES OF SUCCESSFULCE PROGRAMS 60

District Level Title I Expenditure perPupil-11 Districts 60

Purpose of Two Case Studies in Allocationof Program Resources to the Grade Level 62

Information Required 64

x 67TMP-115

Analysis of District 10 CE Programs

Analysis of District 13 CE Programs 93

Conclusions from the Case Studies 120

4 OBSERVATiONS, CONCLUSIONS, AND

RECOMMENDATIONS 122

General Observations 123

Conclus3ons 127

Recommendations 131

65

APPENDIX

A PRINTOUT OF THE DATA USED IN THE SURVEY 136

B DESCRIPTION OF VARIABLES 156

C STATISTICAL MODELS FOR ANALYSIS OF

ACHIEVEMENT DATA 160

Confidence Intervals for Observation by Grade 160 .

Rationale and Models for Multivariate Analyses 162

Results from Analysis of Variance andAnalysis of Covariance 168

Correction for Effect of Errors of Measurementon Observed Correlation Between Initial TestScores and Changes in Test Scores 169

Variance of Weighted Averages 172

D SPECIFICATIONS OF ACHIEVEMENT TEST DATA 174

E CORRECTIONS FOR DIFFERENCES IN PRE-POST

TESTING DATES 180

F USE OF STANDARD T-SCORES 187

G DETAILED INFORMATION FOR DISTRICT 10 190

209REFERENCES

xi

LIST OF ILLUSTRATIONS

FIGURE NO. TITLE PAGE

1 Definitions of types of data and types of conclusiom. 8

2 Measures of educationally disadvantaged and effect

of CE. 9

3 Trend in achievement level. 15



6 Distribution of achievement scores in a typical Title Ischool compared to that for the entire notion. 19

7 Example of data processing and summary ofstatistics on each grade for 1965-66 and 1966-67. 24

8 Changes in test scores in District 13 grouped by school. 37

9 Racial distribution, mobility and trends of attendance(percent) in sample schools. 69

0 Observed change of reading achievement for test periodSeptember 1965 to September 1966District 10. 88

11 Exposure to CE--selected schools.

xii 67TMP-115

LIST OF TABLES

TABLE NO. TITLE PAGE

1 Description of sample school districts includedin statistical analysis. 3

2 Characteristics of sample elementary schools inDistrict 4. 4

3 School and pupil samples sizes for eleven sampleschool districts. 5

4 Grade levels tested (1965-66 and 1966-67) withvarious achievement tests and subtests in elevensample school districts. 21

5 Sample r,f schools analyzed in Phase I . 22

6 Average change in reading achievement test scoresfor the total sample. 28

7 Frequency of changes in achievement test scoresin the mean and at the first decile. 30

8 Contrasts between changes in the mean and at thefirst decile by district. 31

9 Cha%-:s in mean and lowest deci le achievemen l. testscores by school district. 33

10 Results from analysis of covariance. 36

11 Summary of selected state and allocation variables bydistrict. 40

12 .::orrelations between selected variables, computed fromcombined data on all districts. 41

13 Correlations between selected variables, computed fromdata for District 13. 42

14 Estimated regression coefficients relating change inmean achievement to seleclild variables. 44

..........1110116.111M11,110111MMOM.........................----....-...........1.00.1.1011.11~11

TABLES

15 Estimated regression coefficients relaHng change inachievement at the first decile to selected variables. 46

1 6 Correlations between grade level and changes in

achievement scores. 47

17 Summary of achievement level 1 965-66 and changes inachievement between 1965-66 and.1966-67 by grade. 48

18 Average of changes in achievement scores, by percent

Negro in school. 51

1 9 Correlations between percent Negro in a school and

achievement scores. 52

20 Significance levels of differences in mean change

among groups based on percent Negro. 53

21 Correlations between change in percent Negro in aschool and achievement scores. 55

22 Average change in achievement test scores, by type

of change in racial composition. 56

23 Correlations between change in attendance rate and

changes in achievement scores. 58

24 Average Title I funds per pupil and changes in

achievement. 62

25 Sample selection criteria and compensatory education

programs District 10. 67

26 Attendance, mobility and racial distribution of sampleschools (percentages) in District 10. 68

27 Teacher aide assignments. 72

28 Expenditures for regular and compensatory educationprogramsSchool 1. 82

29 Summary of program expenditures of District 10. 83

3 0 Program expenditures by grades of School 1. 87

31 Expenditures Grade 2 (1 965-66) and achievement data

for Grade 3 (SeptemlAer 1966) of District 10. 90

32 Comparisons between grades with CE projects and grades

for which achievement data could be analyzed. 91

33 Title I project budgets in District 13. 94

xiv 67TMP-115

34 Scmp'e school characteristics, 1965-66. 96

35 Estimated CE resources for primary remedial readingSchool 3.

1 AA, 0"7,

36 CE activities serving sixth grade cohorts and levels of

detail of available information. 107

37 Summary of CE expenditures for sixth grade cohorts. 108

38 Demographic characteristics of the sixth grades of

Schools 5 and 7. 109

39 Regular classroom teacher expenditure for sixth grade

cohorts. 113

40 Expenditures,per pupil for sixth grade cohorts. 115

41 CE expenditures for sixth grade cohorts at Schools 5

and 7. 116

42 Regular classroom teacher expenditure for the fifthgrade cohorts at Schools 5 and 7. 119

43 Expenditures per pupil for fifth grade cohorts. 119

44 Analysis of covarianceDistrict 13 schools (usingchange in lowest quartile as a measure of change in

achievement). 164

45 Analysis of covarianceseven school districts (usingchange in mean reading score as a measure of change

in achievement). 165

46 Analysis of covariance seven school districts (usingchange in lowest decile as a measure of change in

achievement). 166

47 Ariclysis of covarianceseven school districts (usingchange in lowest quartile score as a measure of change in

achievement). 167

48 Analysis of variance among school districts (IA. 169

49 Relation between assumed reliability values ofestimates of mean test scores and "true" correlationbetween initial level and gain (when measured

correlation is -0.43). 171

50 Preparation of District 1 achievement test data. 176

TABLES

51 Preparation of District 3 achievement test data.

Preparation of District 4 achievement test data.

53 Preparation of District 13 achievement test data.

54 Bases for adjustment factors required by variationsin dates between administration of pre and post tesh. 182

55 Change from beginning of year to middle of year norms:

SAT paragraph meaning. 183

56 Change from middle of year to end of year norms:SAT paragraph meaning. 184

57 Change from beginning of year norms to middle ofyear: MAT Reading. 185

58 Change from eleventh grade to twelfth grade norms:

MAT Reading. 185

59 Adjusted average changes in districts where pre and

post test dates differed by three or more weeks. 186

60 Conversion of raw score on Advanced Battery, Form W,of SAT to grade score and national percentile (for testsgiven in sixth grades during May and June of academic

year). 188

61 Converting percentiles to Standard T scores. 189

XV

177

178

179

62 Expenditures for regular

63 Expenditures for regularprograms: School 3.


65 Expenditures for regularprcgrams: School 5.





and compensatory education








192

193

194

195

196

197

198

xvi

.1111111.1..1111.0.01,311111110.14

70 Expenditures for regular and compensatory education

67TMP-115

programs: School 10. 199

71 Program expenditures by grades: School 2. 200









STUDY OBJECTIVES

SECTION 1

sk rreeNni serIENKIIry MN., Ilia No I g

1

The study is aimed at providing the Department of Health, Educa-tion, and Welfare with evidence as to the productivity of compensa-tory education ICE) programs for disadvantaged children, The studyhas focused particularly on the effects of Title I of the Elementaryand Secondary Education Act of 1965 during its first year and a halfof operation. The specific objectives of the study were to answerthe following questions:

1. Has statistically significant enhancement of pupil perform-ance resulted to date from CE programs ?

2. What school, pupil, and environmental characteristics areassociated with enhanced pupil performance?

3. What are the distinguishing features of successful CE pro-grams ?

Initial study plans included the following measures of enhance-ment: achievement test scores, attendance rate, drop-out rate, and

frequency of disciplinary actions. The effect of CE was to be mea-sured by comparing results on each measure before and after expo-sure to CE. However, because of time constraints, it became neces-sary to restrict analysis to achievement test scores and attendance.

qi

Within a school district each grade level received the same testthroughout the district. For each grade, one sub-portion of the testwas selected as a measure of achievement. In most cases this wasthe reading sub-portion, but in some cases a suitable but related sub-portion was used. .

The objectives and measures of student performance used in thisstudy are short-range ones; they do not deal with duration of changes

nor was an attempt made to forecast the students' future performance

2 67TMP-115

and earning power or benefits to society. Although these longer--range objectives and associated measures would be more appropriateand revealing as to the productivity of CE programs, such an approachwould require a much longer and different kind of study. However,it is believed that the present approach, which deals with the immedi-ate and observable impacts of CE programs, is an essential firststep in any examination of longer-range impacts.

SUMMARY OF DATA COLLECTED

The Office of the Secretary, DHEW, and the Office of Educationselected school districts (see Table 1) from which to obtain datafor this study. Most of the districts selected were those for whichthere was reason to believe that successful CE programs were inprogress in at least some of the schools. In each of these districtsa sample of schools was selected so as to include high, medium, andlow rankings on each of tke following characteristics:

Student Attributes:

1, Educational deprivation

2. Economic deprivation

3. Mobility

4. Grade level.School Attributes:

1. Size of enrollment

2. Racial composition

3. Attendance rates.

CE Program Attributes:1. History of prior CE programs

2. Intensity of current CE programs.,

In each school district, schools eligible for ESEA Title I supportwere identified, pertinent characte%istics recorded, and a samplechosen so as to include the desired wide range of values for each ofthe above characteristics. For example, in a given district, severalschools were chosen with predominemtly Negro pupil populations butwith different degrees of economic and educational deprivation.

SECTION 1

Table 1. Description of sample school districts included instatistical analysis.°

3

School DistrictI TN./1)e of Local1 '

Education AgencyC74 eographic Region

1 City East North Central

2 County South Atlantic3 City West North Central4 City East North Central5 City East North Central6 County South Atlantic8 City East South Central

10 County West South Central

12 County South Atlantic13

_City Pacifi c

14 City Pacific

NOTE:a By agreement with MEW and the participating school districts, the school

districts will not be identified in the results of the study.

Within a given set of characteristics, selection was made withoutprior knowledge of the success of compensatory programs at any ofthe schools within a school district. Table 2 illustrates the spec-,trum of characteristics presented in one of the sample districts, Asimilar diversity of characteristics exists in other districts.

Field trips were made to fourteen school districts, but sufficientdata for analysis were available from only the eleven districts shownin Table 1. The number of sample schools in each district thatwere included in the statistical analyses are shown in Table 3.

The principal typos of data obtained for the fourteen school dis-tricts were: (1) achievement test scores, attendance records, andother available measures of pupil performance, (2) descriptions ofcompensatory education programs, (3) financial data describing ex-penditures for regular and CE programs, and (4) information onschool and pupil characteristics.

The additional data, over ar-c.; above those analyzed in this report,included some achievement te :;,,t. data on the 3 school districts not in-cluded in the statistical analyses and data for several prior years forseveral of the other school districts. Data already received include

4 67TMP-115

Table 2. Characteristics of sample elementary schools in District 4.

School

Stui4entPopulation

(Oct. 1966 ADM)

PercentNegro

(1966-67)

Sixth GradeMean

Reading

Achievement(percent; loc

Percent ofStudents

EconomicallyDisadvantagedd

Years of CEa._ ............

IoyJune 1967

4 1010 99 2 70 1-1/2

6c 1617 98 10 60 3+ib 1193 95 8 75 3+

9 411 38 1 85 1-1/2

2 561 15 15 75 7

10 758 94 29 35 1

5 295 24 26 75 1

11 882 19 36 50 1-1/2

7 1330 97 41 35 1

3 541 38 45 45 1

8 661 4 52 35 1

NOTES:c Intensive Teacher Aide Pmgram in addition to Title I Teacher Aides.b Special Remediation Program in addition to Title I Remediation Pragrams.

Percentile rank within District 4, 1964-66.lcd Family annual income s $2,000 (1960 census data).

over 2600 grade-years and more than 250,000 pupil test scores. Sub-

stantial but varying amounts of information have been accumulated on

other measures of pupil performance such as attendance and drop-

out records.

A considerable amount of information has been obtained on up to

37 different CE activities in each of these districts. Additional infor-

mation describes characteristics of specific schools and pupils par-.

ticipating in CE projects. Financial data have been received from

ten of the fourteen districts in varying degrees of detail. In the other

four districts, total Title I appropriations are available from OHEW

reports. Average expenditures of Title I funds per pupil in these dis-

tricts up to the time of the 1966-67 achievement test varied from $21

to $140 (see Table 11 in Section 2, column entitled "Effective Title I

Dollars per Pupil").*

*These averages are total district Title I expenditures divided by total

pupil population in all schools receiving Title I funds.

_

SECTION 1

Table 3. School and pupif samples sizes for eleven sample school districts.

5

School DistrictNumber of Schools in Sample

Total AverageDaily Membershipin Sample Schools

1966-1967Elementary Secondary

1 19 5 19,100

2 14 5- ,... 9,3003 15 7 15,600

4 11 8 24,3005 14 9,2006 2 0 700

8 9 7 14,600

10 10 0 4,60012 4 0 1,800

13 7 4 10,700

14 6 4 7,700 .

TOTAL 111 40 117,600

In addition to the basic data on test scores considerable informa-tion is available on the relationship among the following types of testrecords: standard T, national percentile, standard scores for varioustypes of tests, grade equival:nce and stanine scores. Information onthe frequency of each type of test and the frequency with which testsare changes from year to year is also available. Since achievementtests were administered at different times during the school year, adiscussion of the significance of the differing testing times in evaluat-ing year-to-year changes has been presented in Appendix E, alongwith a summary of the testing schedules.

Frequent differences of definitions were found among school records.For example, some districts considered an excused absence as "pre-sent" for attendance records, others did not. Some computed pupilmobility for the school year, others for the calendar year. Recordsof pupil "drop-outs" were based on different definitions. The oc-currence of ungraded schools required that an equivalent grade levelof pupils be determined for purpose of comparisons. Sometimes asa result of these differences in definition, approximations, based onsuch data as were available, were required in order to create a setof comparable data (e. g. , enrollment data had to be used in lieu ofADM*).

*Average daily membership.

----"migmerdeleXelbtic.-1

6 67TMP-115

Some CE projects were defined in terms of activities or objectivessuch as remedial I ,ading and English instruction for pupils from fami-

lies where English is not spoken; other CE programs were defined in

terms of resource inputs such as teacher assistants and dollars forschool equipment. The latter definition permits simple accounting,but does not permit easy identification of all the resources involved

in specific program objectives.

SUMMARY OF TECHNICAL APPROACH

In TEMPO's first interim report (67TMP- 7, 27 June 67) a detailed

discussion of the proposed technical approach was provided. In this

report, discussion will be limited to a summary of the interim re-port and a short discussion of subsequent changes and additions.

Data from th Q. eleven school districts were analyzed to provide

an estim ,tE ,.)4 the effectiveness of CE programs by comparing achieve-

ment scc- , 1966-67 (after schools had implemented CE programsfunded irom Zit le I) with achievement scores in 1965-66. In most

cases, there was little or no CE funded from Title I up to the time of

the 1965-66 tests.

An attempt was made to identify the student, school, and programcharacteristics that were most highly correlated with such changes

in effectiveness. This approach allowed for the possibility that stu-

dents from different socio-economic groups respond differently to the

various CE programs. For example, a certain program or activity

may be highly successful in one group but not in another group with

differesit socio-economic characteristics.

The "fixed guide" approach was used because of the availability ofachievement data from sample schools. In this approach distri-bution of pupil test scores for a spe;:lfic grade in a school in 1966-67

was compared to the distribution of test scores for correspondingpupils in the same gra("1 and school in 1965-66. The statistical ana-lysis included 314 specific grades (see Table 5, Section 2) representingapproximately 35,000 pupils in each year. This means that there were

314 basic observations, however, there is still a choice as to whichparameter(s) of the distribution should be used for measuring charse

in achievement. The analysis in this phase of work was limited to

the following four parameters: change in mean test score; change in

the test score at the first decile; change in the test score at the firstquartile; and change in the test score at the third quartile.

SECTION 1 7

In many schools there were several classes in each grade. Thescores from each class within a grade were combined so that all pu-pils in a grade constituted one observation. This seemed advisablehpr=uae thpre w=f: pn rptinble way to select clamses in each of aca-demic years 1965-66 and 1966-67 so that they would be comparableexcept for CE programs. This procedure does, however, lead toanother question in interpreting results.

The number of pupils in each of the 314 basic observations in eachof the years 1965-66 and 1966-67 varied from 16 to 598. This raisesthe question whether each of the 314 observations should be giventhe same weight in judging the magnitude and statistical significanceof average change in test scores between the two years. If longitudi-nal data (i.e., test scores for the same pupils in both years) had beenused, the obvious choice would be to weight each pupil equally. How-ever, in the "fixed grade" approach there is no unequivocal way tomatch individual pupils in 1965-66 with those in 1966-67. The choicewas made to present two types of statistics, namely,

1. Unweighted averages and standard deviations of the 314basic observations2. Weighted averages of the 314 observations based on num-ber of pupils in each observation.

The difference between the two averages can be easily discussed withthe aid of Figure 1.

The data available for statistical analysis in this study were in theform indicated in the lower right box in Figure 1. However, wheneach observation is weighted by the sample size, it is equivalent todata appropriate for the lower left box. The distinction between leftand right boxes is clear with respect to the average test score but itis not so clear with respect tc test scores at the first decile, firstquartile, and third quartile. The latter scores may represent thescore of only one pupil even though there are 598 pupils in the grade.In the case of decile and quartile scores, it is best to think of theweighted average as representing a simple average of scores of allpupils who ranked within an in:-.erval, say, 8 to 10 percentile in theirgrade in their school. The interval concept removes the problem ofa einglc score representing the decile or quartile score regardlessof grade size.

8

LONGITUDINAL

(e.g., comparisonof pupi 1 (s) score in4th grade in postyear with score ofsome pupil(s) in3rd grade in preyear)

FIXED GRADE

(e.g., comparisonof pupi 1(s) score in4th grade in postyear with score ofpupil(s, in 4thgrade in pre-year)

67TMP-115

PUPIL GRADE

I

314 314

;ElNI + N23 Ix2

X11 El [X2 X11

aveAX aveilX -17.Tato! pupits post and pre 314

PRE YEAR: N1 'X

1 '- POST YEAR: N2 ' X2

1

Figure 1. Definitions of types of data and types of conclusions.

The weighting process indicated by the equation in the lower leftbox of Figure 1 is not a simple average of pupils in an interval but

represents an average of single scores adjusted for the greater sta-bility (or confidence) in the measure (decile and quartile scores) for

grades with a larger number of pupils.

None of the conclusions presented in this report are based on lon-

gitudinal data as represented by the upper two boxes in Figure I.It is possible to use data from the lower boxes to make statementsappropriate for the upper boxes but it requires some added data or

assumptions.

Since data as to which pupils in sample schools received CE were

not available, all pupils for which test scores were available were in-cluded in the sample. Measures of average achievement indicated in

the upper part of Figure 2 are available but measures of potentialachievement level indicated in the lower part are not.

lf, for a given grade level, the gap between the two lines in the

upper part of Figure 2 is increasing each year, the simple compari-

son of pre and post years is a biased measure of the effect of CE;

that is, the average score for the pre year is nat a good estimate of

SECTION 1 9

AVERAGE PUPILENTIRE NATION

NI0-0.4°

CE IN ....4.0

<1th GRADE -40"

40,0e.

EDUCATIONALLY DISADVANTAGED

,

POTENTIAL LEVEL OFEDUCATIONALLYDISADVANTAGED

6 10 12

o)CE IN

StIl GRADE -- 4.do-,°14EDUCATI-ONALLY DISADVANTAGED

2 4 6 8 10 12

YEARS OF SCHOOLING

Figure 2. Measures of educationally disadvantaged and effect of CE,

10 67TMP-115

the broken line in the upper part of Figure 2. In an attempt tocompensate for this possible bias the analysis of pre and post testscores was extended to include analysis of the contrast betweenchanges in the lower decile and changes in the mean and quartiles.The later analysis is based on the assumption that a high percentageof pupils in the lower decile of their class received CE but a smallerpercentage of total pupils received significant amounts of CE. Thespecific statistical procedure for analyzing the contrast is given inSection 2.

The objective of the statistical analysis was to estimate the dif-ference between pupil scores when they had CE and what their scoreswould have been in the absence of CE (broken lines in Figure 2).However, data on scores on the same pupils without CE are not avail-able so most analyses were done by a straight comparison of 1965-66and 1966-67 test scores.

The technical approach called for analyzing each of the 314 obser-vations separately if statistically reliable results could be developed.This would avoid the problems inherent on averaging data from dif-ferent tests and averaging data across different grade levels. It soonbecame apparent that this approach was not appropriate and datawould have to be pooled. First, there is considerable variation intest scores between years that cannot be estimated from availabledata on the variation among pupils within a year. For example, thetest could be given under very good conditions one year and poor con-ditions the other year. Second, the sampling variation in test scoreswas so large that few of the observed differences in pre and postscores for individual observations were statistically significant.Therefore, the scores were all converted to Standard T-Scores so thatobservations could be pooled. The assumptions underlying the eval-uation of T-Scores for different grades and schools are given in Sec-tion 2. .

In summary, the basic approach in Phase I was, first, to deter-mine on a grade-by-grade basis whether significant enhancement hadoccurred and second, to identify whether, in the aggregate, the en-tire sample reflected significant enhancement. Regression analysisand analysis of covariance described in Section 2 were used to helpidentify student and school characteristics that are correlated withchanges in student performance.

SECTION 111

Statistical analysis is not sufficient for a complete evaluation ofthe compensatory education programs. Inconclusive results of sta-tistical tests on selected measures of effectiveness do not prove lackof progress. First, they may indicate that the clract.:.r4s14.-a anrnpl Ad

by the selected measures were not changed by the programs; changesmay have occurred in other characteristics that were not measured.Second, even if there may have been no short-term benefits, theremay be latent long-range benefits that are difficult to forecast oridentify after only one year of intensive nationwide compensatory ac-tivities. Third, the sampling variation in the relatively small sam-ples might be too great to detect actual changes in achievement.Even when statistically significant results are obtained, these mustbe evaluated in light of other relevant irlormation.

Limited attempt was made during the Phase I effort to collect sev-eral diverse types of information not amenable to formal statisticalanalysis but which might be useful in the overall evaluation of Title Iprograms. Some of this information is presented in trip reports inthe separate appendix and some is presented in the detailed analysisof two school districts in Section 3.

Nir

[

1

12

SECTION 2

CHANGES IN ACHIEVEMENT TEST SCORESRFTWFFN 1965-66 AND 1966-67

THE MEASUREMENT OF ACHIEVEMENTAND INFLUENCE OF TITLE I

67TMP-115

The primary measure of achievement used in this study is thescore on the reading sub-portion of various standardized achievementtests*. Obviously, this measure does not cover the entire range ofobjectives of compensatory education. However, reading is an es-pecially appropriate element in the evaluation of compensatory educa-tion for several reasons: there is some evidence that verbal behaviormay be more affected than other skills by cultural disadvantages(References 1 and 2), reading is a fundamental academic skill, andreading is part of all the major achievement tests used throughoutthe United States.

The study employs a "fixed-grade" approach in measuring theeffects of compensatory education programs on achievement. Thedistribution of achievement scores for children in a particular gradeand school for the year prior to compensatory education is comparedwith the distribution of achievement scores for children in that samegrade and school in the following year, when compensatory educationis implemented. An alternative method, the "longitudinal" approach,is to observe changes in scores of individual pupils in successivegrades (i. e., the change between an individualts score in his gradeprior to CE and his score in the succeeding grade after exposure toCE). The fixed-grade approach is based on results for two differentsets of individuals and its usefulness and validity are influenced byour ability to identify and cope with the additional factors introducedby comparing results for two different sets of pupils.

*There is one exception: in one district a composite score (i.e., anaverage score of several subtests of a test such as reading, vocabu-lary, spelling, language, arithmetic, etc.) was used because CEprograms were known to be oriented toward other academic skills.

SECTION 1 13

The longitudinal approach is attractive because it uses the sameset of individuals but it requires comparing results in two (ora-a-v.& a./ Att.J. V J. GAL I. 6 .11. CM& C it) .. t. A-1...

-I-) U 1., 1.11C comparison of achievement beforeand after compensatory education can involve large and possiblysystematic errors because pre and post scores for each pupil wouldbe based on different tests and evaluated against different norms.

In this specific study the choice of the fixed-grade approach wasdictated by greater availability of achievement data and becauseschool records do not link individual test scores with amount of ex-posure of the pupil to CE. Longitudinal data are very limited due tomobility of pupils, lack of records on individual pupils, and the gene-ral policy of not testing every grade every year.

Most of the analyses on Phase I were based on test data for twoyears, the 1965-66 and 1966-67 school years. Ideally, the "post"year (1966-67) would represent performance after exposure to TitleI programs and the "pre" year (1965-66) would represent performanceprior to exposure. However, some of the pre-year (1965-66) testswere conducted in the Spring of 1966 after Title I funding started. Itis assumed that pupils tested in the Spring of 1966 showed no enhance-ment attributable to Title I. This assumption seems justified becauseTitle I activities usually did not start until February 1966.and theactivities often took months to get under way. Also, a large portionof the total first year outlay was for equipment and construction (Ref-erence 3), which would take relatively long to have effect, comparedto reading programs, for example, which might give fairly rapidenhancement.

Another assumption in a simple comparison of pre and post yearsis that the major positive changes in achievement test scores aredue to benefits derived from Title I. The general descriptions re-ceived at the school districts support this assumption. Certainly formost schools sampled, the amount of special CE expenditures wasgreatly enhanced by Title I. Also, this CE was designed as an addi-tion to the on-going school program, not a substitute for it. As willbe seen later in this report, there is wide variation among gradeunits in both CE and regular program expenditures per pupil. Thisis a possible cause of large sampling variation in achievement testresults.

The most important uncertainty with respect to judging the effectsof CE on the basis of observed differences in scores in successive

14 67TMP-115

years is the possibility of trends in achievement which are independent

of CE. There are several reasons for expecting a downward trendin achievement of pupils at inner-city schools (which constitute mostof the sample) relative to the entire nation. First, there is an exitof middle and upper income whites to the suburbs (Reference 4).Second, there is an inflow of families from rural areas where theeducational level c.f. pupils is probably quite low. Third, riots andother forms of demands for racial and economic equality are disrup-tive forces that can hinder the educational process when these forcesare being exerted.

A second source of systematic year-to-year change in achievementlevels springs from the nature of achievement measures. In this

case the expected trend is in the direction of improvement in averageachievement level in successive years. Several test publishers*report that successive classes throughout the nation obtain higherscores on tests. It is not clear why this result occurs; it may bedue to increased spread of knowledge, or to teachers incorporatingtest content into their teaching.t In any event, this trend makestest norms progressively obsolete. When this occurs, and at what

rate, is not clear. However, from the publisher's SAT equivalencetablest this rate was estimated as approximating 0.5 Standard T-score units, per year. This is approximately a 0,05 increase ingrade equivalence score per year (1. e. , the upper line in the tophalf of Figure 2 is shifting upward). In analyses to date we havenot taken potential trend influences into account. However, someachievement data for earlier years were processed to gain some in-sight on how trend information might be utilized. All of the datawere from one district (8); they include five grade levels (4, 6, 7, 8and 11) and four different years. A representative sample of thesedata was plotted and appears below as Figures 3, 4, and 5. Thesefigures illustrate the difficulty in giving a precise interpretadon tosuch information. There are some cases (for example, the graphof the 1st decile in Figure 3) where the achievement level movesrather erratically, and the existence of a trend is not obvious. In

other cases (the graph of the 1st decile in Figure 4, for example)there is an apparent absence of any trend. A third situation is shownin Figure 5, where a trend is apparent in the lower decile and lowerquartile, and one is tempted to predict what the 1967 level would

have been in the absence of any CE by simple extrapolation.

*See, for example, References 5, p 53, and 6, pp 28-29.t See, for example, Reference 7, pp 152-155.

SECTION 2

DISTRICT 8SCHOOL 14GRADE 11

s............./......

50 0

.0.000,00,,4C-41

+ 1st DECILEo 1st QUARTILE

MEDIANO 3rd QUARTILEs 9th DECILEA MEAN

1964 1965 1966 1967 YEARS

Figure 3. Trend in achievement level.

15

16

701 DISTRICT 8SCHOOL 15GRADE 11

s'..,I-2 *D 50I ....T....42<0Z a

6-a

.''..°°°°°°"-----------z.....

2CIk..) +.(.)

20

10

0

67TMP-115

1st DECILE1st QUARTILEMEDIAN3rd QUARTILE9th DECILEMEAN

1964 1965 1966 1967

.......--sv,Figure 4. Trend in achievement level.

YEARS

DIS

TR

ICT 8

SC

HO

OL 9

GR

AD

E 4

+ ht DE

CIL

E

0 1st

QU

AR

TIL

E

ME

DIA

N

El

3rd

QU

AR

TIL

E

* 9th

DE

CIL

E

A ME

AN

1966

1967

Fig

ure 5. T

rend in ac

hiev

emen

t

leve

l.

YE

AR

S

17

18 67TMP-115

There are difficulties in interpreting changes in test scores insuccessive years in the fixed-grade approach when there is possibilityof a trend in achievement level in the sample schools. It may be nec-essary to utilize the kngitudinal method along with the fixed-grademethod in order to develop more precise estimates of tha effertive-ness of Title I programs.

PROCESSING ACHIEVEMENT DATA

There are two main aspects in obtaining comparable units for ob-served differences in test scores. One is comparability over a rangeof achievement levels. The other is comparability among differenttests and different test dates within an academic year.

The comparability over different achievement levels within a gradewas obtained by converting to the Standard T-score. The scale forthe Standard T- score has been constructed so that a change from 30to 35, for example, is comparable to a change from 60 to 65. Com-parable in this case means that the amount of effort in CE requiredto raise the achievement level 5 points is approximately the samein both cases. As a result, T-scores can be averaged and subjectedto statistical analysis, whereas percentile scores, for example, can-not (Reference 8, p 64). In some of the analyses, results for differentgrades were combined and in these cases it was assumed that dif-ferences in T-scorc:s are also comparable among grades. That is,the amount of effort in CE required to increase an achievement levelfrom say 30 to 35 in one grade is approximated the same as for asimilar movement in -tiler grades. The T- score is computed directlyfrom a percentile score (see Table 61 ). The second aspect of com-parability among different tests and test dates enters through the useof the publishers' norm tables for computing percentile scores (seeTable 60 as an example of this conversion). The assumptions usedin computing percentile scores were:

I. The reading, paragraph meaning, and composite subtestsmeasure the same pupil attribute

2. The pu- thers' norm populations for each test is similarwith respec. to the distribution of achievement levels

3. The publishers' norms provide proper adjustment for thetin. e of year at which the test is given.

The first assumption was necessary because each of the three sub-tests was used in one or more school districts, Since our primary

-

SECTION 2 19

interest was in analyzing differences between pre and post test scores,it was not necessary to assume that norm populations were equal inabsolute level, but only in the range and distribution over the range.

Each of these assumptions will be treated in more detail in the sub-sections below. One feature of the data deserves special notice.Since pupils in eligible Title I schools were selected for being cultur-ally and educationally deprived, their achievement test scores tendto be lower than those of the norm populations. Figure 6 illustratesthe distribution of achievement scores of a typical fourth grade in asample school in 1965-66. Eighty percent of the pupils in this gradereceived test scores below the mean score of the pupils in the normpopulation. Table 11, discussed later, shows the mean achievementlevel (based on 1965-66 tests) for the entire sample and for sampleobservations in each district.

The major characteristics of the data received were as follow.

Type of Test

Data analysis was limited to standardized achievement tests ad-ministered to entire grades of pupils in a school district for each of

-ram=20

PUPILS IN A 4th GRADE IN A&"*" TYPICAL SAMPLE SCHOOL

NATION

30 40 50 60

STANDARD T SCORE

Figure 6. Distribution of achievement scores in a typical Title I schoolcompared to that for the entire nation.

70 80

20 67TMP-115

2 years, 1965-66 and 1966-67. In the 11 school districts, 5 differenttests were used: Stanford Achievement Test (SAT), MetropolitanAchievement Tests (MAT), Iowa Tests of Basic Skills (ITBS), IowaTests. of Educational Development (ITED), and Sequ-ential r.I:ests ofEducational Progress (STEP). The variety of tests and subtests indifferent grades in the 11 school districts is shown in Table 4.

For any given test there was often variation in the forms used inthe pre and post years. Usually this variation was between two formswhich were constructed so as to provide equivalent measures ofachievement. However, in cases where different editions of a testwere used, raw scores were converted to a common scale, usingpublishers norms.

Time of Testing

There was considerable variation in the time of the year in whichtests were given among and even within school districts. This re-sulted in differences in amounts of CE to which pupils were exposedprior to the 1966-67 test. Such differences in exposure to CE cannoteasily be taken into account in a simple comparison of pre and posttest results but can be incorporated in the regression analysis. Asshown in Appendix B, a new variable was constructed to show whatis called "effective Title I dollars" per pupil. This was computedby adding the Title I funds spent in 1965-66 and the fraction of TitleI funds for 1966-67 spent up to the time of the 1966-67 achievementtests and dividing the sum by total number of pupils in Title I schoolsin each district. This new variable was included as one of the de-termining variables in regrecsion and analysis of covariance.

Differences in test dates between 1965-66 and 1966-67 requireduse of different norm tables for pre and post tests or adjustmentswithin a particular norm table. The occasions on which test datesin the twoyears differed by three or more weeks are shown in Appen-dix E, Table 54. The corrections required for these differencesare shown in Appendix E, Table 59. The data presented in AppendixA have been corrected for differences in test dates.

Specific Grades/Students Exposed to Title 1 Programs

Relatively few school systems keep records on the amount andtype of CE programs at specific schools. This means that it wasoften not possible to identify precisely which grades in a school

Tab

le 4

. Gra

de le

vels

test

ed (

1965

-66

and

1966

-67)

with

var

ious

ach

ieve

men

t tes

tsan

d su

btes

ts in

ele

ven

sam

ple

scho

ol d

istr

icts

.

Sch

ool

Dis

tric

t

Sta

nfor

dA

chie

vem

ent

Tes

ts:

.. rara

grap

hM

eani

ng

tM

erop

olita

nA

chie

vem

ent

Tes

ts:

Rea

ding

Iow

a T

ests

of B

asic

Ski

llsIo

wa

Tes

ts o

f Edu

c. D

evel

.S

eque

ntia

l

Rea

ding

Com

posi

teA

bilit

y to

Inte

rpre

tlit

erar

ym

ater

ials

Com

posi

teT

ests

of

Edu

c.N

ogre

ss:

Rea

ding

14,

5, 6

, 7, 8

22,

3, 4

, 5, 6

34,

6, 8

10, 1

2

44,

6, 8

10, 1

2

56

4

63,

6

82,

3, 4

, 5,

6, 7

, 8, 1

110

3, 4

, 5

123

131,

2, d

ocs,

811

5

143,

4, 6

, 8...

......

......

......

.....

NO

TE

:a

Inst

ance

3 in

whi

ch d

iffer

ent e

ditio

ns o

f the

test

wer

e us

ed in

yea

rs 1

965-

66 a

nd 1

966-

67.

(A m n 1 0 Z " n)

Tab

le 5

. Sam

ple

of s

choo

ls a

naly

zed

in P

hase

l .a

Sch

ool D

istr

ict

Num

ber

of S

choo

ls fo

r G

rade

Tot

al G

rade

sT

otal

Sch

ools

.) ..,A -t

eI

I

ajoi

.,8

I9

1

10,

11i _ .2

110

174

44

3921

210

1212

1210

5612

315

155

11

3821

411

115

2716

514

1428

14

62

24

2

89

99

99

34

355

16

1092

213

9

44

4

137

77

72

232

11

146

66

186

TO

TA

L7

2642

7947

787

200

11

314

132

.

NO

TE

:a

Thi

s do

es n

ot in

clud

e da

ta u

n ai

l sch

ools

liste

d in

Tab

le 3

.

SECTION 2 23

received Title I programs. Furthermore, it was not possible toidentify the specific students in a gr-,.de who received CE from TitleI programs. Consequently, it was decided to use test scores for anentire grade and to use all grades in Title I designated schools forwhich test data were available for both 1965-66 and 1966-67.

It was also decided to limit the sample to grades 1-12 in publicschools. The sample of schools by grade and district which wereanalyzed is shown in Table 5.

Form of Data

Data received from school districts were in the following forms:class listings of individual pupils, punched cards of individual pupils,computer tab runs by individuals, and computer printouts of fre-quency distributions. Test scores included one or more of the follow-irg: raw scores, standard scores (for specific type of test), grade(or grade equivalent) scores, percentile scores, and stanines.

All scores not in national percentile were converted to nationalpercentiles by using the appropriate conversion table provided byeach test publisher for each separate form of test. Percentile scoreswere then converted to Standard T- scores. The distribution ofStandard T-scores in the population is assumed to be normal with amean of 50 and a standard deviation of 10. This assumption was util-ized in converting national percent-Iles to Standard T- scores.* De-tails on the form of data obtained from certain school districts aregiven in Appendix D and an example of the detailed procedures forconverting scores from one particular test is given in Appendix F.

Test results for each grade in each school for 1965-66 and 1966-67have been summarized in terms of the nineteen statistics (see lowerpart of example of computer output in Figure 7). The central partof Figure 7, illustrates the conversion from raw scores to StandardT- scores. The summary statistics are all in terms of T-scores.The examples show 84 pupils in a grade; in the overall sample, thenumber of pupils in a grade ranged from 16 to 598.

*This is consistent with reasoning by the Office of Education presentedin Reference 8.

24 67TMP-115

GRADE 6, t'OST YEAR scHaat. XXXDATA IN RAW SCORES TO HUN THRU UNE- SHARI NG COMPUTER STAII STICAL PROGRAM

41.46.608105s 41* 46. 6(8* 88. 41, 46, 59* 8 5, 8 5, 59, 4 6. 4 1, 4 6. 41. 57. 8 5

39* 46* 57.83.80* 56* 46* 39, 38, 4 4. 7 6. 5 4. 7 1. 5 4. 4 4, 36, 33. 52* 4467*32* 33. 44, 51.. 66. 64, 49. 42. 30. 39. 33, 42, 42.49.47. 49* 47.64. 62.6251* 51.36.39* 47* 47* 46* 41.33.30* 42* 30.62.62.54r 30* 32* 36* 30.38.49* 52* 30, 57

RAW SCORES RANKED IN ASCENDING 3HDER:

39 30 30 30 30 30 30 32 32 33 3333 33 36 36 36 38 38 39 39 39 4141 41 41 41 41 42 42 42 42 44 4444 44 46 46 46 46 46 46 46 46 4747 47 47 49 49 49 49 51 51 51 5252 54 54 54 56 57 57 57 59 59 6060 62 62 62 62 64 64 66 67 71 7680 83 85 85 85 88 105

RAM SCORES CONVERTrD TO STANDARD 1-SCORES AND KANKEU:

26.7 26.7 26.7 26.7 26.7 26.7 26.7 29. 529.5 31.2 31.2 31.2 31.2 32.5 32.5 32.534.5 34.5 34.5 34.5 34.5 36.1 36.1 36.136.1 36.1 36.1 36.6 36.6 36.6 36.6 37.737.7 37.7 37.7 38.3 3863 38.3 38.3 38.338.3 38 Z. 38.3 39.2 39.2 39.2 39.2 411., 8

40.8 408 40.8 41.9 41.9 41.9 42 3 42 343.6 43.6 43.6 44.2 44.7 44.7 44.7 45.445.4 46.4 46.4 47.5 47.5 47.5 47.5 48.148.1 50.1 59. 5 52. 1 54. 4 56.4 57. 7 58.858.8 588 59. 5 64.8

SUMMARY STATISTICS IN STANDARD T-SCORES:

SMALLEST VARXATEm 26.7 NUMBER OF VARIATES* 84LOWER DECILE* 29.5 ARITHMETIC MEAN' 40.381

FIRST QUARTILE" 34.9 STANDARD DEVIATION. 8.52709MEDIAN* 38.3 VARIANCE. 72.7113

THIRD QUARTILE* 45.225 COEFF OF VAR [PC11. 21.117UPPER DSCILEm 53.25 STANDARD SKEWNESS' .623

LARGEST VARIATEm 64.8 STANDARD EXCESS' .181

TOTAL RANGES 38. 1

DECILE RANGEm 23. 75

SEMI-QUART RANGE* 5.1625BOILEYS SKEWNESS= .341PEARSON SKEWESSm 732

Figure 7. Example of data processing and summary of statisticson each grade for 1965-66 and 1966-67.

160.10.N.411.111......

SECTION 2 25

Volume of Data

It was desired that the study include a wide variety of student andenvirorwnental charnctevistics. This required that a wide variety ofschool and program conditions had to be included, and that the over-all sample had to be large so that there would be a sufficient numberof observations within each type of condition to draw firm conclusions.Also, .since school personnel suggested that only a small amount ofchange in achievement could be expected so soon after the initiationof Title I programs, our sample would have to be correspondinglylarge to detect aty differences.

The amount of achievement test data used in the statistical analy-sis is shown in Table 5. The statistics shown in Figure 7 are avail-able for each of the 314 grades shown in Table 5 for both pre andpost years.

There is great variation in the amount oz: data collected from thevarious school districts. This variation resulted from differencesin size of school district, variety in CE programs among schoolsand grade levels and difficulty in obtaining information.

There are fewer secondary than elementary schools. In largepart, this is a natural consequence of the larger enrollment of secon-dary schools. It means, of course, that more students are representedby sample units at the secondary level.

The more relevant summary statistics along with pertinent dis-trict, school and grade characteristics for each of 314 observationsin the sample have been retained in punched cards (see complete list-ing of data in Appendix A). Ps. list and description of variables analy-zed in Phase I are given pendix B.

RESULTS OF STATISTICAL .A1YSIS

The summary tables and discussions will be presented in sectionscorresponding to the objectives stated on page 1. To focus attentionon the study objectives most of the technical discussion on statisticalanalysis has been put in appendices. The most relevant mathematicsand assumptions underlying the various statistical analyses are pre-sented in the main text but more complete details are in appendices.Also, the basic data on each of the 314 observations appear in Ap-pendix A.

26 67TMP-115

General observations that have been developed from the overallproject but not necessarily from the statistical analysis are presentedin the first part of Section. 4.

Results from many of the statistical analyses are not reported herebecause they were not statistically significant. Because of the greatvolume of data it seemed best to describe each analysis that wascarried out, but include in tables only those results which proved tobe significant. The attempt to judge whether the observed change ineach of the 314 grades was significant produced inconclusive results.First, the only measure of standard error was the observed varia-tion among scores within the pre year and within the post year btathis is known to be a biased underestimate of the variance of the ob-served change between pre and post years.* Second, even with thebiased underestimate of the variance of the change in achievementthe percentage of the 314 observations that would be judged as sig-nificant was approximately what would be expected by chance. There-fore, the tables and discussion in the remainder of Section 2 arebased on average changes or frequency of positive changes in variousgroups (a group could be total sample, a specific school district, aspecific grade, etc.).

The results using change in attendance as a performance measureshow no significant improvement between 1965-66 and 1966-67. Themean change for the entire sample was + 0.12 percent but the standarderror of this estimate is 1. 60 which means that the estimate is notsignificant at the 50 percent level. Some of the individual districtsshowed a larger change but there are other explanations for the change.For example, the severe weather in New Orleans reduced the atten-dance in 1965-66 and it was natural to expect a positi-ye change aslarge as the 2.8 percent that was observed. Because of the statisti-cally insignificant results for change in attendance, most of the dis-cussion of change in performance in the remainder of this section isin terms of change in academic achievement.

*Analyses of sample data indicates that the variance of the differencebetween pre and post means is at least twice as large as the sum ofthe estimated variances of the pre and post means. This means thatthe information for one grade (i.e., one pre year and one post year)is 1 It sufficient for judging statistical significance.

-

SECTION 2

_

27

lias Statistically Significant Enhancement ofPupil Performance Resulted to Date from CE Nograms?

This question will be addressed in terms of the overall sample and

in terms of the sample of schools within each of eleven school districts.The term "enhancement," as used here, is the difference betweenachievement level after exposure to CE programs and the achieve-ment level which would have been expected in the absence of suchprograms. Enhancement cannot be measured directly from avail-able data. It is possible to measure the achievement level of pupilswho received CE but the achievement level of the same pupils in theabsence of CE can only be estimate.A. Therefore, conclusions on de-.gree of enhancement of specific pupils must be developed by inference.

The results of most statistical tests presented below were basedon observed differences in achievement scores between 1965-66 and1966-67 rather than estimated differences between achievement withand without exposure to CE. That is, no adjustment was made for apossible negative trend; this means that observed differences betweenthe two years understate differences between achievement with and

without CE.

OVERALL SAMPLE. There is no indication of general improve-ment in the entire student population in the 314 grade observations.There is, however, indication that the achievement of students in thelower part of the distribution in their respective grades was slightlyenhanced between 1965-66 and 1966-67. Table 6 shows both theweighted and unweighted average change at the first decile as signifi-cant at the 20 percent level. As described in the Section on technicalapproach (see page 8), the weighted average is essentially anaverage of all pupils whereas the unweighted average is an averageof one statistic for each of the 314 grades.

Although data on the application of CE to various levels in theachievement distribution are not available it is reasonable to expectthat CE and, especially, remedial programs were usually orientedtowards those students whom are the most seriously disadvantagedand, therefore, have the lowest achievement scores. This meansthat we should expect more favorable results at the first decile.The change at the first decile is 0.25 Standard T-Score units. Thisis not easily interpreted in terms of grade equivalence because itrepresents the average change in many different grade levels. We

know however that it is in the neighborhood of one-fourth month andis, therefore, quite small in importance. If, however, this small

Tab

le 6

. Ave

rage

cha

nge

in r

eadi

ng a

chie

vem

ent t

est s

core

sfo

r th

e to

ta;

sam

ple.

°

Ach

ieve

men

t Tes

t Sta

tistic

Unw

eigh

ted

Obs

erva

tions

bE

ach

Obs

erva

tion

bW

eigh

ted

by S

ampl

e S

ize

Ave

rage

Cha

nge

Sta

ndar

dE

rror

Sig

. Lev

el°

Ave

rage

Cha

nge

Sta

ndar

dE

rror

Sig

. Lev

el

Mea

n (3

)

Low

est

lieci

le (

D1)

Low

est Q

uart

ile (

Q1)

Upp

er Q

uart

ile (

Q3)

- 0.

29

+ 0

.25

- 0.

30

-0.

48

0.13

0.18

0.16

0.17

0.05

0:20

0.10

0.01

- 0.

40+

0.2

1

- 0.

42

- 0.

69

0.11

0.16

0.14

0.15

0.00

1

0.20

0.01

0.00

1

Not

es:

a In

uni

ts o

f Sta

ndar

d T

-sco

res

and

base

d on

obs

erve

d ch

ange

s in

314

sch

ool-g

rade

s in

11 d

istr

icts

.31

431

4b

Tne

unw

eigh

ted

aver

age

is c

ompu

ted

as31

4 X

i and

the

wei

ghte

d av

erag

eis

co

mpu

ted

asm

. X.

Ei=

1i=

1

314 E m

. whe

re m

. is

the

aver

age

num

ber

of p

upils

who

took

the

pre

and

post

test

and

X. i

s th

e ob

serv

ed

i=1

chan

ge in

the

spec

ified

sta

tistic

. App

endi

x C

dis

cuss

esth

e co

mpu

tatio

nal p

roce

dure

for

the

estim

ated

stan

dard

err

or.

c T

his

is th

e pr

obab

ility

that

the

obse

rved

sam

ple

resu

lt co

uld

have

happ

ened

by

chan

ce if

the

true

cha

nge

betw

een

1965

-66

and

1966

-67

was

inde

ed z

ero.

CO

711''

SECTION 2 29

positive value indicates a reversal of a negative trend it is of consi-derable importance. In judging the relevance of the g.0 percent sig-nificance level for the unweighted decile it is important to keep inmind that although it is not highly significant it surely does not sup-port the hypothesis that there was no change.

Table 6 also indicates a decrease in achievement in all but thelowest decile between 1965-66 and 1966-67. These results supporta second important conclusion namely that even with CE programspresent there is a negative trend in achievement level in schools to-wards which CE is oriented, reflecting the sociological and economicchanges that are taking place in the student population.

The positive change in the decile, while not very large, becomesmore significant when contrasted with the negative change in AX,AQ 1, and AQ3. The four statistics used (AX, 4D1, AQ1, AQ 3)* arenot independent as indicated by the correlation coefficients shownlater in Table 12. Also, except for the effects of CE one expectsall four statistics to move in the same direction since they all comefrom the same distribution. One can then ask the question, how un-usual is it to obtain the deviations actually observed if in fact therewere no differences between the true means of AD

1and AX? The

answer to this question is that the observed differences between AD].and AX would be highly unlikely by chance alone (less than 0.001probability).1

Thus, although the absolute change in the first decile (+0.25) wasnot highly significant, the difference between the positive change inthe decile and the negative change in the mean was significant at the0.001 level. Hence, this is an indication of a positive effect of CEprograms if one assumes that CE programs are usually concentratedon the lowest achievers in each grade.

The contrast between changes in the mean and changes at. the firstdecile can be studied further by analyzing the frequency dam in Tables7 and 8. For example, there are more positive than negative changes

*A indicates change in the statistic from 1965-66 to 1966-67 (postyear minus pre year); X, Di, Q1, Q3, refer respectively to achieve-ment at the mean, first decile, first quartile, and third quartile.thetermined by testing for differences between correlated meansusing the correlations found in Table 12.

Tab

le 7

. Fre

quen

cy o

f cha

nges

in a

chie

vem

ent t

est s

core

s in

the

mea

n an

d at

the

first

dec

i le.

Dis

tric

t

All

Dis

tric

ts

1 2 3 4 5 6 8 10 12 13 14

Tot

al G

rade

sin

Sam

ple

Incr

ease

s

314

145

3923

5618

3819

278

2811

43

5525

136

43

3221

188

Mea

n

Dec

reas

esI N

o C

hang

e

Firs

t Dec

ile

163

I6

15I

1

380

190

181

161

10

291

70

1I

o

101

91

Incr

ease

s

126 9

24 20 10 7 3 16 7 3 17 10

Dec

reas

esN

o C

hang

e

103

85

1020

2012

153

134

1011

10

11A

51

1I

0

11

6

4 2

SECT10.4 2 31

Table 8. Contrasts between changes in the mean and at the firstdeci le by distri ct.°

DistrictObservations withChange in Means

more favorable

1 22.5

2 14

3 16

4 11

5 15.5

6 0

8 20

10 7

12 1

13 14

14 8

TOTAL 129.

I

1

1

Observations withChange in Decile 1 TOTAL I Sig. Levelblmore favorable I

16.5 ov). ..4k)

42 56 0.001

22 38 I 0.40

16 27 0.40

125 28 c

t 4 0.005

35 55 0.05

6 13c

3 4 0.40

18 32 0.50

10 18c

185. 314. 0.01

NOTES:a Differences among districts in iratio of "observations favorable to the decile

to total observations" was not significant at the 5 percent level (x2 =17.56 < x2

05(10)= 18.3).

20'

b The x test was used to determine if the function of observations favorable tothe deci le in each district was significantly different from one-half.

c Greater than 0.50 percent.

at the first decile but the reverse is true for the mean. The numberof nbservations for which the change was measured as zero is impor-tant in evaluating the precision of the measuring instruments. Eighty-five or 27 percent of the 314 observations showed no change in thefirst decile while only 2 percent showed no change in the mean. Thetest scores are less precise in measuring low achievers within eachgrade and the publishers' conversion tables for computing nationalpercentile are also less precise at loyv achievement levels within eachgrade. This lower precision at the first decile is possibly one ofthe reasons why the averlge change for the entire sample is not highlysignificant.

1

.a,...:11..1010.111.111W+.:.-u.

32 67TMP-115

The tendency for the decile to increase relative to the other param-eters can be examined by counting the number of observations forwhich the decile showed a more favorable change than the mean.As shown in Table 8 there were considerably more observationsfavoring the decile than the mean. Based on 314 observations, thedifference in proportions is significant at the 1 percent level. Thedistricts which show this contrast between changes in the decile andmean most clearly and strongly are 2, 6, and 8, for each of which thedisproportion between changes in 1.--e mean and decile is statisticallysignificant.

This study did not include analysis of the nature of the CE pro-gram in each of the 11 districts. Therefore, no full description ofthe programs in districts 2, 6, and 8 is avaiiable to help explain theemphasis at the lower end of the achievement distribution. It mightbe noted, however, that the amount of Title * funds per pupil expendedby the time the post test date tends to be relatively low in two of thethree districts (see Table 11).

INDIVIDUAL SCHOOL DISTRICTS AND VARIATION AMONG DIS-TRICTS. The average change in the mean and at first decile for eachdistrict is shown in Table 9. Some of the statistically significantchanges are positive and some are negative.

Due to the large variation in results among observations withina school district only three individual districts show a significantchange in the mean and only one district shows a significant changeat the first decile. The lesser number of observations in each in-dividual district makes the test for statistical significance less power-ful than the eorresponding te, t for the entire sample. The expectedlarge variation within and among districts is one of the reasons whythis study was designed to include a large sample and to include ob-servatio is from several different school districts.

,

School District 13 shows significant positive changes in the meanand at the first decile. This district is analyzed in gr,:ater detailin Section 3. District 6 shows a greater positive change than District13 but there are only 4 observations in District 6 and the results arenot statistically significant. There is no obvious explanadon of thelarge negative changes in Districts 2 and 4.

Comparing the weighted and unweighted averages in Table 9 onecan see that weighting by sample size produced more favorable re-sults in some districtr_ and less favorable results in other districts.

...row., -. r.....00.-1 ,.e........... ....... ....--......--*

Tab

le 9

. Cha

nges

in m

ean

and

low

est d

ecile

ach

ieve

men

t tes

t sco

res

bysc

hool

dis

tric

t.

Num

ber

of G

rade

sO

bser

ved

12

3

3956

42

A. U

nwei

ghte

d O

bser

-va

tions

Ave

rage

Cha

nge

inM

ean

0.25

- 1.

350.

34-

1.03

Sta

ndar

d E

rror

0.31

0.38

0.39

0.27

Sig

. Lev

eP0.

500.

010.

400.

01

Ave

rage

Cha

nge

inLo

wes

t Dec

ile0.

050.

040.

220.

68S

tand

c-ci

Err

or0.

320.

480.

580.

72S

ig. L

evel

ab

bb

0.40

B. O

bser

vatio

ns W

eigh

-te

d by

No.

of

Pup

ils in

Gra

de

Ave

rage

Cha

nge

inM

ean

- 0.

07-

1.19

- 0.

210.

92S

tand

ard

Err

or0.

260.

370.

300.

2AS

ig. L

evel

°0.

010.

500.

01A

vera

ge C

hang

e in

Low

est D

ecile

- 0.

410.

130.

21-

0.19

Sta

ndar

d E

rror

0.32

0 47

0.45

0 58

Sic

. Lev

el°

0.30

6b

6

Sch

ool D

istr

ict

5 28 0.16

0 27

,I, 0.70

0.50

0.20

0.25

0.24

0.30

0.76

0.46

0.20

68

1012

1:3

14

5513

432

18

1.28

- 0.

37-

0.21

0.42

1.16

0.01

0.97

0.27

0.83

0.97

0.46

0.34

0.30

0.20

bb

0.05

4.20

0.26

0.55

1.78

1.32

0.95

1.82

0.37

1.00

2.02

0.69

0.64

0.10

0050

b0.

500.

050.

20

1.58

- 0.

650.

071.

010.

690.

040.

850.

230

067

0.86

0.41

0.36

0.20

0.01

0.30

0.10

5.23

0.36

0.45

3.17

0.97

0.88

1.81

0.30

01.

770.

530.

670.

050.

3068

50.

200.

100.

30

NO

TE

S:

a T

hepr

obab

ility

of o

bser

ving

an

aver

age

chan

ge a

s la

rge

or la

rger

than

the

one

show

n in

the

prec

edin

g ro

ww

hen

the

time

chan

ge is

zer

o is

equ

al to

the

prob

abili

ty s

how

n in

this

row

.b

Gre

ater

than

0.5

0 pe

rcen

t.

CA

)C

A)

34 67TMP-115

The significance level of the positive changes in District 13 is lessfor the weighted than for the unweighted. On the other hand, the sig-nificance level for the positive changes in District 6 was greater forthe weighted than for the unweighted. Except for testing a specifichypothesis TEMPO suggests that the weighted and unweighted aver-ages be viewed as supporting the same general conclusions on ef-fectiveness of CE.

Tests of significance using analysis of variance were performedto determine if there were significant differences in observed changesin achievement test scores among school districts. These analysesshowed that differences in changes in mean achievement were signifi-cant at the 1 percent level (see Table 40 ). However, differencesmeasured in terms of changes in achievement test scores at the firstdecile and first quartile were not statistically significant.

Analysis of covariance was used as a more discriminating testfor detecting significant differenccs among districts. In this tech-nique analysis of variance is performed after an adjustment is madefor differences caused by variation in specific state variables. Thereis considerable variation in state variables among districts (seeTable 11) which could cause changes in achievement. In other words,significant difference regardless of the cause or conditions is testedby analysis of variance, while significant differences from causesother than the specified covariates is tested by analysis of covariance(see discussion in Anpendix C ).

The analysis of covariance was extended to include a test for sig-nificant differences among schools within District 13. The resultshave important hearing on whether the effort in Phase II shculd con-centrate on obtaining information at the school or grade level.

The basic model for analysis of covariance was

Y = T. + a1

($) + a2

(L) + a3

(A) + a4(%N) + c

where

(1)

Y = measure of change in achievement (A 5, A D1, or A 01)

T. = the variation in changes in achievement level that is at-]. tributable to the ith group

SECTION 2 35

$ = average Title I CE program funds per student (for allstudents in Title I schools in the school district) expendedby the post test date,

L = mean achievement level at the beginning of Title I programs,

A = attendance rate in a school (1965-66)

rAN = percent of pupils who were Negro (1965-66)

c = an error component in the postulated relation.

There were seven districts and therefore seven groups in the analy-sis of covariance for testing significant differences amok.s districts.There were eleven schools and therefore eleven groups in the analy-sis for testing significant differences among schools within District13. The variable for Title I $ was dropped from model in the analy-sis of District 13 schools because Title I expenditures were not avail-able at the school level.

The results from analysis of covariance are shown in Table 10.The major conclusions are:

1. The variation in changes in the meat among districts aresignificant at the 1 percent level. As in the analysis of variance,the differences as measured at the first decile are not signifi-cant at the 5 percent level. It must be realized that samplingvariation at the first decile and first quartile are larger thanat the mean and therefore the F test based on these measuresis not as sensitive as the test based on the mean.2. The analysis of District 13 schools shows no significantdifferences among schools. This means that changes in tesi,scores between 1965-66 and 1966-67 are not associated withspecific scnools and, therefore, variation in results cannot beattributed to differences among schools.

The analysis of covariance for testing significant differencesamong schools within a district was limited to a test based on changein the lower quartile for schools in District 13. There seems littleneed to extend these analyses since other data also indicate no signifi-cant differences among schools.

Detailed results for analysis of covariance are presented in Ap-pendix C. The coefficients of the covariates presented in the detailedtables are analogous to regression coefficients. They provide another

Tab

le 1

0. R

esul

ts fr

om a

naly

sis

of c

ovar

ianc

e.

Diff

eren

ces

AM

ong

Sev

en S

choo

lD

istr

icts

°N

o. o

f Gra

deO

bser

vatio

nsF

S:a

tistic

s fo

r N

ull

Hyp

othe

sisb

Cha

nge

in m

ean

achi

evem

ent s

core

s24

0F

= 3

.85

>F

(1%

)=

2.9

0

Cha

nge

in lo

wer

dec

ileac

hiev

emen

tsc

ores

240

F =

1.7

1 <

F (

5%)

= 2

.14

.C

hang

e in

low

er q

uart

ileac

hiev

emen

tsc

ores

240

F =

2.6

0 >

F (

5%)

= 2

.14

Diff

eren

ces

.Am

ong

11 s

choo

ls in

Dis

tric

t13

1. C

hang

e in

low

er q

uart

ile a

chie

vem

ent

scor

es32

F =

1.4

2 <

F (

5%)

= 2

.38

NO

TE

S:

Onl

y sc

hool

dis

tric

ts 1

, 2, 4

, 8,

10, 1

3, a

nd 1

4 fo

r w

hich

data

on

the

stat

e va

riabl

es u

sed

wer

eav

ail-

able

wer

e in

clud

ed in

this

ana

lysi

s. D

ata

used

in a

naly

sis

of c

ovar

ianc

e iid

not

incl

ude

the

adju

st-

men

ts in

dica

ted

in T

able

59.

The

se a

djus

tmen

ts a

re s

mal

l and

wou

ld n

ot li

kely

cha

nge

the

re3u

lts in

this

tabl

e if

they

wer

e us

ed.

bT

he fi

rst v

alue

of F

is c

ompu

ted

from

sam

ple

data

and

the

seco

nd F

val

ue is

from

Sne

deco

r's F

tabl

e

with

deg

rees

of f

reed

om 6

and

230

for

the

first

thre

e te

sts

and

10 a

nd 1

9 fo

rth

e fo

urth

test

.

"1,1

tibt

_

SECTION 2 37

measure of the influence of specified variables on achievement re-sults. The results from analysis of covariance support the observa-tions from regression analysis that the mean achievement level atthe beginning of Title I programs is negatively correlated with changein achievement.

The basic unit of measurement of achievement in Phase I is thegrade within a specific scho91. The only lower level of aggregationthat could be used is the individual student. Results indicate thatmajor differences in changes of achievement are among grades withina school and not among schools. If the several grades within a schoolare grouped together, possible sources of differences in relationsbetween CE and enhanced achievement may be hidden by the averag-ing process.

Further insight into variation in observed changes in achievementcan be obtained from examination of Figure 8. This shows the changein achievement test scores, at the first decile and mean respectively,for the grades and schools that comprise the District 13 sample.For example, in school "1" the mean achievement score in the 6thgrade in 1966-67 was 2 Standard T-scores higher than the correspond-ing 6th grade score in 1965-66. The score at the first decile in 1966-67

1 2 3 4 5 6 7 8 9 10 11SCHOOL

.86

U J ...-6 *6.....

CI .1I

6 21,1II1

2

0Z 1 .2

5

(1.4.44'5

1Z i5e51 .-4u

.-6

.4

s 28

.1111

.5

1 2 3 4 5 6 "7 8 9 10 11SCHOOL

Figure 8. Changes in test scores in District 13 grouped by school.

38 671MP-115

was one standard T- score lower than the corresponding score in1965-66. These results are representative of the variation withinand among schools in most school districts. In almost every schoolthere are both positive and negative changes spread over a substantialrange of year-to-year variation. Similar situations exist for otherdistricts for both the change in mean and change at the first decile.This could be caused by sampling variation or it could be caused bydifferences in type and amount of CE.

What school, pupil, and environmental characteristics are associated

with enhanced pupil performance?

The first part of this section presents a brief summary of the dif-ferent analyses and presents tables of est. nated regression coef-ficients and simple correlation coefficients. The next part discussesthe statistical results relevant to each of several state variables.The last part of the section presents general conclusions concerningthe relationship among state variables and changes in achievement.

The following four types of analyses were carried out in an attemptto identify the relationships between state variables and changes inachievement:

a. Simple correlations between changes in achievement andstate variaLdes were computed from the combined data on alldistricts.b. Simple correlations between changes in achievement andstate variables were computed from data on eacn of the 11 dis-tricts.c. Analysis of variance was computed for A X, D1, and AQ1,using all 314 observations. The total group was partitionedaccording to contrasting levels of state variables to estimatethe effects of these factors as reflected by the three measures.

d. Multiple regression analyses were done using a number ofstate variables for which data were available.

The results from each of the above analyses are addressed in thediscussion on each of the state variables in the sub-sections below.That is, conclusions on the relationships between each state variableand changes in achievement are based on statistical results fromeach of the above analyses.

_ mimemp161ffkAgt,-

SECTION 2 39

Table 11 presents a summary of selected state and allocation var-iables by district. The simple correlation coefficients presented inTables 12 and 13 show the degree of association between two variables.These coefficients were computed under the assumption that any re-lationship between two variables that might exist is linear. Forexample, the coefficient of - 0.10 between percent Negro and changein the mean (see Table 12) reflects only a small degree of associa-tion between these two variables. It is possible that the numericalvalue of the estimated coefficient is low because the relationship be-tween the two variables is non-linear. It is also possible that it islow because other variables are correlated with both percent Negroand change in achievement.

Correlation coefficients computed from the combined data for alldistricts are shown in Table 12. Similar correlation coefficientswere computed from data within each of the 11 school districts. Only

one of these latter sets is presented in tabular form, namely, thosefor District 13 in Table 13. The correlations from the other 10 dis-tricts have been extracted and used to illustrate discussion of spe-cific variables below.

Analysis of variance is helpful in identifying variables that areassociated with changes in achievement in that it can be used for de-tecting significant diffe.eimces among specified sets of results. Itwas used, for example, to determine if the change in achievementfor schools with high percent Negro wer ntly different fromchanges in schools with low percent Negro (see Table 18). Analysisof variance does not require the assumption of a linear relationshipamong the two variables of inte-rest. It is also applicable for testingfor significant differences among groups that cannot be described innumerical terms. For example, it would not be meaningful to com-pute a correlation coefficient between change in achievement anddistrict but it is possible to use analysis of variance for testing dif-ferences among distri-.:ts (see Table 48 ). Thus, analysis of varianceis applicable in situations where simple correlation coefficients arenot applicable.

Multiple regression analysis is helpful for identifying the effect ofeach state variable on changes in achievement and it is helpful in re-ducing the sampling variation when testing for significant effect fromCE. This technique is especially helpful when the variable of interest(change in achievement in this case) has been affected by many differentvariables. In the model described in Equation 2 (see page 43),

Tab

le 1

1. S

umm

ary

of s

elec

ted

stat

e an

d al

loca

tion

varia

bles

by

dist

rict.

Dis

tric

tM

ean

Tes

t Sco

re19

65-6

6c1!

Tot

al T

itle

I Fun

ds__

_($

mill

list

hlT

itle

I $ 1

Tor

NO

1965

-671

5

Effe

ctiv

eT

itle

I $pe

r P

upi l

c

Mob

il ity

(per

cent

a )

Per

cent

Neg

ro19

65-6

60

Per

cent

Spa

nish

1965

-66a

Mea

nG

rade

AD

M°

1965

-66

1966

-67

138

.22.

61.

567

6248

61d

150

244

.43.

53.

332

2151

6412

124

345

.70.

70.

894

51d

dd

115

442

.712

.010

.210

0'6

449

586

51

542

.01.

91.

669

64d

600

80

643

.21.

21.

215

814

016

440

60

844

.01.

21.

256

5342

510

152

1035

.13.

64.

111

360

:792

178

1243

.50.

20.

730

010

519

750

77

1341

.02.

62.

217

213

760

4620

129

1440

.71.

51.

387

5533

560

80

All

Dis

tric

ts42

.431

.028

.11

8275

I47

567

120

NO

TE

S:

a A

vera

ge a

cros

s al

l obs

erva

tions

in e

ach

dist

rict.

Mob

ility

is c

ompu

ted

asnu

mbe

r of

pup

ils m

ovin

g in

to p

lus

num

ber

mov

ing

out o

f a s

choo

l, ex

pres

sed

as a

per

cent

of s

choo

l AD

M.

b D

olla

rspz

r pu

pil c

ompu

ted

by s

umm

ing

tota

l Titl

e I f

unds

for

both

yea

rs a

nd d

ivid

ing

by d

istr

ict A

DM

inT

itle

Isc

hool

s.c

Dol

lars

per

pup

il co

mpu

ted

as th

e su

m o

fthe

ave

rage

1965

-66

Titl

e !d

olla

rs p

er p

upil

plus

the

frac

tion

of th

eav

erag

e 19

66-6

7 T

itle

Ido

llars

per

pup

ilco

rres

pond

ing

to w

hen

the

post

yea

r te

st w

cs a

dmin

iste

red.

° D

ata

not a

vaila

ble.

Tab

le 1

2. C

orre

latio

ns b

etw

een

sele

cted

var

iabl

es, c

ompu

ted

from

com

bine

dda

ta o

n al

ldi

stric

ts.°

cn

rncl 1

Var

iabl

eD

istr

ict

47

89

1011

1213

1 2 3 4 5 6 7 8 9 10 11 12 13

Cha

nge

in M

ean

Cha

nge

in 1

st D

ecile

Cha

nge

in 1

st Q

uart

ileC

hang

e in

3rd

Qua

rtile

Mea

n P

re A

chie

vem

ent

Sco

reIn

dex

of M

obili

tyG

rade

Atte

ndan

ce R

ate

(196

5-66

)C

hang

e in

Atte

ndan

ceR

ate

Per

cent

Neg

ro (

1965

-66)

Cha

nge

in P

erce

nt N

egro

Pre

Tes

t Dat

eP

ost T

est D

ate

Titl

e I $

Per

Stu

dent

1.0

0.64

1.0

0.77

0.59

1.0

0.85

0.39

0.50

1.0

- 0.

43-

0.19

- 0.

32-

0.35

1.0

0.03

0.00

0.01

0.04

-0.1

41.

0

0.05

0.08

0.03

0.07

0.35

0.01

1.0

0.02

0.09

0.03

-0.0

3

- 0.

15-

0.15

- 0.

30

1.0

-0.1

0-

0.07

-0.1

4-0

.10

-0.3

0-

0.47

-0.1

6

0.22

1.0

- 0.

08-0

,05

- 0.

06-

0.08

0.00

- 0.

05

0.06

-0.0

60.

001.

0

0.23

0.03

0.10

0.28

-0.1

70.

03

0.14

-0.2

2-0

.13

0.06

1.0

0.16

0.00

0.09

0.20

-0.0

9-

0 .1

0

0.17

-0.2

0-0

.14

01,0

5

0095

1,0

0.30

0.13

0.19

0.31

-0.2

30.

03

0.25

-0.0

70.

130.

030.

390.

341.

0

NO

TE

:a

With

314

obs

erva

tions

an

abso

lute

valu

e of

0.1

5 fo

r th

e co

rrel

atio

n co

effic

ient

is s

igni

fican

t at t

he 1

per

cent

leve

l

and

0.11

is s

igni

fican

t at t

he 5

per

cent

leve

l. W

ith 2

40 o

bser

vatio

ns th

e co

rres

pond

ing

valu

es a

re 0

.16

and

0.12

.

ICor

rela

tions

with

var

iabl

es 7

, 8, 9

, mei

10

wer

eco

mpu

ted

from

240

obs

erva

tions

in th

e7

dist

ricts

for

whi

ch d

ata

wer

e av

aila

ble

onth

ese

varia

bles

.

Tab

le 1

3. C

orre

latio

ns b

etw

een

sele

cted

var

iabl

es,

com

pute

d fr

om d

ata

for

Dis

tric

t13

.a

Var

iabl

eD

istr

ict

.

12

34

56

78

910

1112

13-

1C

hang

e in

Mea

n1.

0 0.

660.72 0.92 -0.73

0.05

-0.19

0.03

0.09

-0.0

40.

400.

210.

21

2 C

hang

e in

1st

Dec

ile1.

00.

52 0

.46

-0.4

30.

09-0

.16

0.20

0.01

0.02

0.09

-0.0

3-0

.03

3 C

hang

e in

1st

Qua

rtile

1.0

0.53

-0.

61-0

.01

-0.0

20.

06-0

.17

- 0.

0101

5-0

.01

-0.0

14

Cha

nge

in 3

rd Q

uart

ile1.

0-0

.70

0.12

-0.2

5--

0.05

0.21

- 0.

080.

460.

290.29

5A

vera

ge A

chie

vem

ent

Leve

l1.

00.

080.

270.

05-0

.10

0.05

-0.5

7-0

.32

-0.3

26

Inde

x of

Mob

ility

1.0

-0.4

50.

38-n

.20

0.05

0.26

0.20

0.20

7 G

rade

Atte

ndan

ce R

ate

1.0

-0.27

-0.46

0.21

-0.1

8-0

.12

-0.1

28

Cha

nge

in A

ttend

ance

Rat

e1.

0-0

.13

0.19

0.06

0.04

0.04

9 P

erce

nt N

egro

1.0

0.28

-0:0

4-0

04-0

.04

10 C

hang

e in

Per

cent

Neg

ro1.

0-0

.01

0.00

0 00

11P

re T

est D

ate

1.0

0.94

0.94

12

Pos

t Tes

t Dat

e1.

01.

0

13 $

per

Stu

dent

1.0

NO

TE

:a

With

32

obse

rvat

ions

an

abso

lute

val

ue o

f 0.4

4 fo

rthe

corr

elat

ion

coef

ficie

nt iJ

sig

nfic

ant a

t the

1 p

erce

nt le

vel

and

an a

bsol

ute

valu

e of

0.3

4 is

sig

nific

ant a

tth

e 5

perc

ent l

evel

.

SECTION 2 43

there are five different variables that are postulated to be significantin explaining observed change in achievement.

The model for estimating regression equations using data fromseveral school districts was

where

Y

$

Y = a + al ($) + a2

(ivi) + a3

(%I1) + a4

(L) 4 a5

(A) 4- c ,0

= change in achievement level (WC or AD 1)

= average Title I CE program funds per student expended bythe post test date 27.0 2' all students in Title I schools in theschool district

L = achievement level at the beginning of Title I programs

M = mobility in and out of the school

%N= percent Negro in a school (1965-66)

A = attendance rate ia a school (1965-66)

E = an error component in the postulated relation.

Descriptions of the way each of these variables were measured aregiven in Appendix B. The regression equations were estimatedwithout the corrections indicated in Table 59.

If the determining variables in the regression equation are inde-pendent each estimated regression coefficient is an estimate of theeffect of a one unit change in the determining variable on the depen.:dent variable. For example, an estimate of a2 in the above equationwould be an estimate of the effect of a one percent increase in mo-bility rate on change in achievement. A regression coefficient ismore meaningful than a simple correlation because the latter oftenreflects spurious correlation caused by the fact that both variablesare related to a third variable. Although the determining variablesmight not be independent, the regression coefficient for each variableis another measure of the relationship between that variable and thedependent variable.

The estimated regression coefficients using change in the meanas dependent variable are shown in Table 14. The estimated coef-ficients using change in achievement at the first decile are shown in

44 67TMP-115

Table 14. Estimated regression coerneents relating change in mean achievement

to selected variables.°

DistrictConstant

Termhit-bill:-

Rate'FercentNegroc

Mean

Achieve-ment

Scorec

Attend-onceRatec

CE Fundingper Student

(Title I)

2R- I

Pool 0.73 - 0.003 - 0.018 - 0.387 0.175 0.0027 0,37(0.006) (0.004) (0.039) (0.048) (0.0040)

1 38.5 - 0.075 - 0.039 - 0,91 0.027 0.60(0.021) (0.009) (0.136 (0.064)

2 3.21 - 0.003 - 0.034 - 0.628 - 0.343 0,30(0.011) (0.011) (0,141) (0.250)

3 - 39.0 d 0.028 - 0.142 0.482 0.09

i (0.036) (0.132) (0.319)

4 24.0 2 0.004 - 0.306 - 0.136 0.39(0.009) (0.143) (0.118)

5 8.11 d - 0.003 - 0.193 d 0.10(0.007) (0.116)

.

6-12 19.3 d 0.014 - 0.443 d 0.529mbine (0.002) (0.271)

8 7.54 - 0.007 - 0.019 - 0.614 0.219 0.44(0.016) (0.009) (0.102) (0.118)

10 - 59.1 - 0.048 0.188 - 0.518 0.701 0.87(0.022) (0.050) (0.091) (0.182)

13 0.216 0.005 0.004 - 0.524 0.232 0.55(0.026) (0.015) (0.094) (0.771)

14 51.3 0.030 - 0.016 - 0.213 - 0.459 0.33(0.065) (0.018) (0.123) (0.504)

NOTES:a Standard error values are shown in parentheses beneath the respective esti-

mated regression coefficients.I) ti r00

1

a 11r means Districts 1, 2, 4, 8, 10, 13, and 14 taken together.° Data are for 1965-66.d Data not available.e Not included in final regression equation because F value in the final test

for significant reduction of residual variance was less than 0.005.

ACTION 2 45

Table 15. The R2 statistic in the last column is an estimate of theportion of the variation in the dependent variable that can be explainedby the determining variables included in the equation.

Each of tIle variables that might have affected changes in achieve-ment between 1965-66 and 1966-67 will be discussed in a separatesub-section. The results from each type of statistical analysis arenot applicable to discussion on each variable and, therefore, are notreferred to in each sub-section.

1

GRADE. There is reason to expect that grade level would be as-sociated with benefit from compensatory education. There may becritical periods during whtch compensation for educational depriva-tion is relatively easy, ani others when it is very aifficult. Thus,it may be that if educationally deprived children are given remedia-tion soon enough they may be able to overcome most if not all of theirdisadvantage. This concept is consistent with the opinion expressedin an earlier report on the first year of Title I (Reference 3, p 39).

In this study, the effect of grade level was examined by an analy-sis of variance, The analysis of variance showed no significant dif-ferences in average change among grade levels.

The simple correlations between changes in achievement andgrade level are shown in Table 16. Although most of the correla-tions are negative, the results are not statistically significant.

The average achievement level in 1965-66 and the average foreach measure of change in achievement between 1965-66 and 1966-67are shown in Table 17. This table also shows the relationship be-tween Standard T- score, national percentile, and grade equivalence.

For example, the average T- score for the 78 observations ongrade 6 was 42.6. This average corresponds te the 23rd nationalpercentile. A student obtaining a Standard T-score of 42.6 at themid-point in the 6th grade would have a grade equivalence score of5,3 compared to the national average of 6.5. A student with a scoreof 5.3 would be considered 1.2 years behind in achievement level.

The results in Table 17 show no apparent relationship betweengrade level and changes in achievement. They also show no apparentrelationship between amount of educational deprivation and gradelevel.

67TMP-115

Table 15. Estimated regression coefficients relating change in achievement at the

first decile to selected variables.°

DistrictConstant

Terms

MobilityRatec

PercentNegroc

I Mean'Achieve-i ment

nd-AtteCEonceStudentRate

EffectiveFunding

(Title I)

Pool 0.29 - 0.018 .- 0.020 - 0.330 0.210 0.0063 0.13(0.010) (0.007? (0.061) 10.074) (0.0063) '

1 4.62 - 0.031 - 0.021 - 0.175 0.156 0.16(0.028) (0.0;2) (0.186) (0.087)

2 1.29 - 0.020 - 0.034 - 0.662 0.212 0.22(0.019) (0.015) (0.189) (0.334)

3 - 77.1 d 0.043 e 0.826 0.09(0.052) (0.465)

4 41.7 - 0.038 - 0.061 1.24 0.183 0.25(0.050) (0.032) (0.466) (0.430)

5 3.51 d - 0.007 - 0.090 d 0.02(0.013) (0.226'i

6, 12 48.2 d 0.001 1.06d 0.47

combined (0.005) (0.607)

8 22.2 - 0.051 - 0.041 - 0.672 0.128 0.31

(0.025) (0.014) (0.158) (0.183)

10 - 45.5 0.113 0.156 - 0.170 0.477 0.45

(0.055) (0.123) (0.225) (0.447)

13 50.0 0.006 - 0.008 0.458 0.310 0.21

(0.052) (0.030) (0.187) (1.54)

14 106 - 0.120 0.009 - 0.037 1.07 0.17

1

(0.106) (0.030) (0.209) (0.823)

NOTES:a Standard error values are shown in parentheses beneath the respective esti-

mated regression coefficients.b "Pool" means Districts 1, 2, 4, 8, 10, 13 and 14 taken together.

c Data are for 1965-66 only.d Data not available.e Not included in final regression equation because F value in the final test for

significant reduction of residual variance was less than 0.005.

SECTION 2

Table 16. Correlations between grade level and changes inachievement scores.'

r

DistrictChange of Achievement

AIX,i

A D,i

AQ,1

AQ,a

Number '1

of Grades j

1 - 0.15 - 0.23 - 0.20 - 0.05 39

2 - 0.17 - 0.12 - 0.12 - 0.09 56

3 - 0.07 - 0.11 - 0.12 - 0.03 38

4 0.00 0.05 - 0.18 0.06 27

5 0.01 - 0. i2 - 0.16 0.02 28

6 0.55 0.06 0,77 0.93 4

8 - 0.16 0.10 - 0.14 - 0.18 55

10 - 0.28 - 0.09 - 0.28 - 0.14 13

12 - - - - -13 - 0.17 0.01 - 0.02 - 0.26 32

14 - 0.22 - 0.04 - 0.20 - 0.16 18

All Districts - 0.13 - 0.08 - 0.14 - 0.08 314

NOTE:° Correlations were computed under the assumption that the relation between

change in achievement and grade (if any) is a linear relation betweenchange in achievement and the familiar numerical identification of grades(i.e., grade 1, grade 2, etc.). Although some of the individual correla-tions are significant at the 5 percent level the percer.tage of the total thatare significant is approximately what would be expected by chance alone.

Tab

le 1

7. S

umm

ary

of a

chie

vem

ent l

evel

196

5-66

and

cha

nges

inac

hiev

emen

t bet

wee

n 19

65-6

6 an

d 19

66-6

7, b

y

grad

e.

Ave

rage

Ach

ieve

men

t Lev

el19

65-6

6A

vera

ge C

hang

eN

o. o

fO

bser

vatio

nsG

rade

Sta

ndar

dT

-sco

reN

atio

nal

Per

cent

ileG

rade

Equ

iv. °

A R

A D

1A

Q1

A Q

3

139

.1.

141.

3+

1.9

7+

2.2

7+

0.9

9+

3.01

7

21

44.0

282.

2-

0.33

- 0.

22+

0.2

4-

0.97

26

340

.918

2.6

+0.

16+

1.0

6+

0.08

-0.

3442

442

.723

3.5

4:Q

.06

+ 0

.53

+ 0

.28

-0.

0979

541

.620

4.3

- 1.

01-

0.56

- 1.

24-

1.07

47

642

.623

5.3

- 0.

54+

0.0

5-

0.75

l-

0.60

78

740

.718

5.8

- 0.

66-

0.04

- 0.

20-

1.26

7

842

.825

7.0

- 0.

40+

0,1

1-

0.38

- 0.

5320

1045

b+

0,5

00.

00.

00.

c1

11

.48.

846

.235

b-

1.23

- 0.

18-

1.40

-1.

426

1251

.255

b+

0.9

0+

1.3

00.

0+

1.3

01

NO

TE

S:

a G

rade

equ

ival

ence

was

com

pute

d fr

omta

bles

pro

vide

d by

the

MA

T a

nd 1

TB

S T

ests

and

is b

ased

on

mid

-yea

rev

alua

tion.

For

exa

mpl

e, th

e gr

ade

equi

vale

nce

of 1

.3 fo

r th

e fir

st g

rade

is0.

2 be

low

the

1.5

leve

l whi

chis

the

aver

age

for

mid

-yea

r fir

st g

rade

s in

the

natio

n.b

Rib

lishe

rs' c

onve

rsio

n ta

bles

for

com

putin

g gr

ade

equi

vale

nce

wer

e no

t ava

ilabl

e to

the

cont

ract

or.

I.

SECTION 2 e, 49

The possible effect of grade level was studied in the regressionanalysis by relating the error component (i. e., E in Equation 2) tograde level. This was done in an attempt to determine if the changesin achievement that could not be explained by the variables includedin the regression equation could be explained by differences in gradelevel. There was no evidence that changes in achievement were re.lated to grade level.

POVERTY. Oi ..e. of the criteria for inclusion in Title I is low in-come level of the pupils' families. Although allocation of Title I dol-lars to school districts was based on number of pupils from familieswith income below $2, 000 the criterion of low income within a schooldistrict and, therefore, qualification of the school for Title I fundsvaries throughout the country. Our classification of poverty for eachschool was the criterion used by each of the respective school dis-tricts.

Schools in the sample were classified as high, medium or lowpoverty relative to all Title I schools in that district. In view of thepurposes of Title I funds more money might be expected to be allo-...;ated to schools with the most poverty.

'The analysis of variance and the simple correlations betweenpoverty and changes in achievement do not show any reliable relation-ships between poverty level and changes in achievement test scores.

MOBILITY. High student mobility is a condition likely to dilutethe effects of Title I. It is unlikely that students who transfer toanother school will have the same type of CE program.

High mobility makes it difficult to relate Title I dollars withchanges in achievement because many of the students taking whatwe have called the "post test" might have been exposed to very littleof the CE programs in the school in which he is tested.

The results from sample data give inconclusive evidence on theeffects of mobility. The regression coefficients for this variableare generally negative but only some of them are statistically signi-ficant (see Tables 14 and 15).

The analyses of variance showed no significant differences inchanges in achievement between high and low mobility rates. Thecorrelation coefficients in Tables 12 and 13 do not show a negative

50 GTMP-115

relationship. Since the regression and correlation coefficients haveopposite signs there is reason to believe that mobility is directlyrelated to other variables which have a positive effect on chan&es inachievement. For example, it is possible that more Title 1 dollarswould be allocated to schools with high.mobility because they arelikely to have a high percentage of pupils from families with low in-come.

The effects of high mobility should be investigated further inPhase II. It will then be possible to use analysis of covariance whichis a more powerful analytical tool than used thus far since it makesadjustments for covariates.

PERCENT NEGRO. The relationship in change in achievement topercent Negro was examined in light of the topical interest in Negroeducational problems. The analysis below suggests a strong rela-tionship between percent Negro enrollment and changes in achieve-ment. Five levels of percent Negro were defined for analysis ofvariance: 0 to 19 percent, 20 to 39 percent, 40 to 59 percent, 60 to79 percent, and 80 to 100 percent.

The results in Table 18 show that the 0 to 19 percent group re-sponded best, while the 40 to 59 percent group responded the worst.The positive change for the 0 to 19 percent group is statisticallysignificant at the 10 pezeent level. The LieLaye change in the meanand first quartile for the 40 to 59 percent group are statistically sig-nificant at the five percent level.

The non-linear relationship between percent Negro and change inachievement indicated by the results in Table 18 explains why somany of the simple correlatioia coefficients shown in Table 19 aresmall. There does appear to be a significant linear relationshipbetween percent Negro and absolute achievement level but not a sig-nificant linear relationship between percent Negro and change inachievement.

The effect of these levels on changes in achievement (as measuredby A X, A D and A Q1 ) was studied in one-way analyses of varianceusing 277 observations and in a two-way analysis of variance using

SECTION 2

Table 18. Average of changes in achievement scores, by percentNegro in school .

5 1

Number of Cases

Change in Mean:

Mean change in b43Z

Standard errorSignificance level'

Change in First Quartiie:

Mean change in baiStandard errortalSignificance levelo

Change in First Decile:

Mean change in AD.,Standard error ADiSignificance levela

Percent Negro in school

0-- 1 9 20-39 40-59 60-79

56 34 45 35

0.5 - 0.4 0.9 - 0.40.29 0.45 0.41 0.360.10 0.40 0.05 0.30

0.9 - 0.02 1.4 - 0.50.40 0.50 0.39 0.460,05 b 0.01 0.30

1.1 - 0.1 0.3 - 0.00.38 0.68 0.54 0.480.01 b b b

I 80-100

108

- 0.20.210.40

0.30.240.30

0.40.30b

NOTES:a Probability of obtaining a value as large or larger than the sample mean by

chance if the expected change in achievement score between 1965-66 and1966-67 were zero.

b Greater than 0.50 percent.

80 observations.* The analysis of variance results are shown inTable 20. The results using the first decile are not statisticallysignificant but several of the results using the mean and first quar-tile are significant. The difference among the five groups arestatistically significant. The difference between the 0 to 19 percentgroup and the 40 to 59 percent and between the 0 to 19 percent groupand the 20 to 100 percent group are both statistically significant.

* Ideally, it would oe preferable to handle all of the factors simul-taneously in a multiplz factor analysis of variance. However, thiswas not feasible; there ere numerous cells with missing data, andthe resulting partial layout was not balanted.

52 67TMP-115

Table 19. Correlations between percent Negro in a school andachievement scores.°

I District No.ofObs.

InitialAchievement

LevelAMean AD1 AQ1 AQ3

1 39 -0.20 -0. 20 -0.21 -O. 20 -0. 12

bI

2 56 -0.46 -0.17 -0.04 -0.25 -0.21

4 27 -0.93 0.00 -0.04 -0.19 0.06

5 28 0.05 -0.08 -0.11 0,04 0.20

6 4 -0.89b 0.76 0.60 0.45 0. 07

8 55 -0.33b -0.13 -0.11 0.07 -0.15

10 13 -0.38 0.47 0.34 0.41 0.35

12 4 -0.64 0.49 0.77 0.68. -0.55

13 32 -0.10 O. 09 O. 01 -O. 17 0.21

14 18 -0.34 -0.14 -0.19 -0.5513 0.11

NOTES:aPercent Negro for District 3 were not available for 1965-66.

bSignificant to 5 percent level.

It is difficult to specify the i recise cause as towhy changes inachievement are related to per,..ent Negro. However, the relation-ship is strong enough tha+ the topic deserves further analysis whenmore data are available on the allocation of Title I funds for CE.

Thee, ",..,,considerable variation among school districts in percent

Negro students, therefore it might be thought that the above resultsreflect simply differences among districts. To control for the effectsof district, a two-way analysis of variance was performed using onlytwo levels of Negro composition and the eight districts which met

/

SECTION 2

Table 20. Significance levels of differences in mean changeamong groups based on percent Negro.°

Contrasted Groupsb AR AD

1AQ

1

1. All 5 Groups 5% 25% 0.5%

2. Group I and Groups 11-V (pooled) 10% 50% 5%

3. Group I and Group III 10% 50% 5%

4. Group I and Group II 50% c 50%

5. Group III and Group V c c

6. Groups 1-11 (pooled) and c c 50%

Groups III-V (pooled)

Notes:aPercent Negro in the pre-year was used for the grouping: Group "I,

0 to 19 perc:nt Negro; Group 11, 20 to 39 percent Negro; Group III40 to 59 percent Negro; Group IV, 60 to 79 percent Negro; Group V,80 to 100 percent Negro.

bBased on the S-Msthod of multiple comparisons (see Reference 15).cGreater than 50 percent.

the data requirements. Because we wished to test whether the ob-served difference among levels of percent Negro was maintainedwhen district was controlled, only the categories of percent Negrowhich differed the most were compared. For each district havingsuch data, the five observations with the lowest percent Negro wereselected in each of the contrasting categories of 0 to 19 percent Negyoang 40 to 59 percent Negro. In both changes in the mean and changesin the lower quartile the results are highly significant. That is, thetwo levels of percent Negro have significantly different means, re-inforcing the earlier results. The non-significant results for the"interaction" effect indicate the relationship between achievementand percent Negro is similar within each of the eight districts.

54 671MP-115

Change in Percent Negro

Just as school racial composition correlates with achievementtest score level (e. g., correlation of - 0.30 in Table 12), so changesin racial composition may be expected to correlate with changes inachievement level.

The correlations between change in percent Negro (post versuspre) and changes in achievement test level are shown in Table 21.Only a few of the correlations within particular districts are solarge as to be statistically reliable and these do nor present a con-sistent picture. To look more intensively into the variable of changein racial composition, a second type of examination was done. Therewere 53 school-grade observations from 26 schools for which thechange in percent Negro in the school was 5 percent or more. Ofthese, 41 increased in percent Negro and 12 decreased. The changesin mean and decile achievement test scores for these observationsare shown in Table 22. Relatively large changes in percent Negroin either direction are associated with less favorable changes inachievement scores.

PERCENT SPANISH. There are several school districts whichhave a sizeable proportion of students of Spanish extraction. Theanalysis did not reveal any significant relationships between percentSpanish and changes in achievement. However, the analysis is notdecisive. The statistical tests were based on a small sample andthere was little variation in the percentages of pupils from Spanishspeaking families within each of the school districts.

MEAN READING ACHIEVEMENT LEVEL AT THE BEGINNINGOF TITLE I PROGRAMS. Compensatory education is aimed primar-ily at students who have suffered from cultural disadvantages andcan, therefore, be expected to have relatively low achievement testscores. It might be expected that the emphasis of the CE programs(particularly remediation programs) would be toward students withlower achievement test scores rather than those with highest scores.Thus, the nature of the program would suggest that a negative cor-relation might exist between change in achievement level and originalachievement level. It appears that.this is the case. However, inter-pretation of the meaning of the correlation must be qualified by therealization that there is a built-in correlation due to statistical re-gression between original levels on a variable and changes in thatvariable from one time to another. That is, on any given measure-ment of a variable "errors of measuremeat" are reflected in extreme

c

-

SECTION 2

Table 21. Correlations between change in percent Negro in a school

and achievement scores.°

II District

-No.of

Obs.

InitialAchievement

Score

-A X

IA Di

1

AQ3

1

2

4

5

6

8

10

12

13

14

39

56

27

28

4

55

13

4

32

18

b-0.34

0.30b

0.34

-0.01

60.89

0.05

0.17

-0.27

0.05

-0.03

0.11

-0.05

-0.12

-0.31

-0.76

-0.07

-0.40

-0.03

-0.04

-0.05

-0.03

0.01

-0.02

-0.45b

-0.60

-0.03

-0.22

0.13

0.02

-0.43

0.13

-0.04

0.23

-0.28

-0.45

0.00

-0.44

0.20

-0.01

-0.38

0.04

-0.01

-0.42b

-0.20

-0.07

-0.16

-0.20

-0.50

-0.08

0.06

Notes:aPercent Negro for District 3 were not available for 1965-66.

bStatistically significant to the 5 percent level.

_

67TMP-115

Table 22. Average change in achievement test scores, by typeof change in racial composition.

Observations NAveragea Mean

JAverageA Decile

Large increase (5%) in percent Negro 41 -0.8 -0.4

Little change in percent Negro 219 -0.2 +0.5

Large decrease (25%) in percent Negro 12 -0.6 -1.2

TOTA L 272 -0.34 +0.31

scores and a portion of these will "regress" toward Ihe mean onlater testing (Reference 14, pp 321-324). This phenomenon is main-ly a problem in evaluating the correlation between LII.Z and the premean a. e., the mean for 1965-66h Errors in measurements of

D1, Qi and Q3 for 1965-66 would not likely be highly correlated with-in measurement of X in 1965-66 and, therefore, the spurious* corre-lation between changes in D1, Q1 and Q3 and the pre mean is likelyto be small.

The average initial reading achievement level was a highly sig-nificant variable in the regression analysis. The regression coef-ficients are negative in all twenty-two regression equations shownin Tables 14 and 15. This result is in line with the negative cor-relations shown in Tables 12 and 13. The regression coefficients onthe pre mean (r) in Table 15 are affected by the spurious correlationdiscussed above.* Regression coefficients and simple correlationcoefficients both indicate that this variable is more highly correlatedwith changes in achievement at the first decile than any other statevariable analyzed during Phase I (e.g., see row 2 in Tables 12 and13).

*It is not possible to develop a. precise estimate of the effect of thespurious correlation from data that are available. A technical dis-cussion of this problem is presented in the last part of Appendix C.

SECTION 2

..................

57

These results suggest that the relationship between initial readinglevel and expected changes from CE should be investigated furtherin Phase II. As with all statistical results, the researcher must becareful in drawing firm conclusions until he has analyzed possiblereasons for spurious correlations.

MEAN ATTENDANCE RATE IN SCHOOL PRIOR TO CE. Theschool attendance rate in 1965-66 has a small positive correlationwith AR, b D1, A6Q1 and 6 Q3 when computed from the combined data

for all school districts (see Table 12). However, the same corre-lation computed from data within each of the school districts shows

both negative and positive correlations (e.g., see correlation forDistrict 13 in Table 13). The regression coefficients are generallypositive but only a few are significantly different from zero.

A positive correlation between attendance rate and enhancementwould suggest that it might be well to orient CE programs towardsincreasing attendance. The returns per dollar of Title I might behigher than if all money is oriented towards academic skills. How-ever, the correlations observed in the Phase I analyses might betested in follow-on work before drawing any firm conclusion con-cerning attendance and CE programs.

Change in Attendance Rate

Attendance is another type of pupil performance often regardedas a possible criterion for educational programs. It is assumedto vary with children's motivation to learn and to be a prerequisiteto benefiting from school work.

To date within our study no control for other factors, such asweather or recording procedures which might affect attendance mea-sures has been used. Further, districts differ fairly vnarkedly indefinitions of attendance. Therefore, the present mea.ures should

be regarded as fairly crude, especially for inter-district calculations.

The correlations between change in attendance figures between

year s 1965-66 and 1966-67 and change in achievement statistic sduring these same years are shown in Table 23. Most of the corre-lations appear low and only two are statistically reliable to the 5percent level. There does not appear to be any clear relationshipbetween change in attendance rate and change in achievement testscores.

58

...1.*.,..........61.

67TMP-115

Table 23. Correlations between change in attendance mite and changesin achievement scores.

Districts A7 I A n1

I AQ.I

I AQJ

I Number I

1 0.21 0.34° - 0.04 0.17 39

2 0.05 0.06 -0.05 -0.01 56

3 -0.14 -0.26 -0.25 -0.06 38

4 0.06 -0.21 0.00 0.13 27

10 0.19 0.46 0.10 -0.01 13

13 0.03 0.20 0.06 -0.05 32

14 0.18 0.48° 0(.21 0.19 18

Note:

°Statistically reliable to the 5 percent level.

SIZE OF GRADE AND SIZE OF SCHOOL. The statistical evidenceshows no significant relation between change's in achievement andnumber of pupils in the grade or number of pupils in the school.There is little evidence to encourage further investigation of thisvariable in follow-on works.

SUMMARY OF ANALYSIS OF SPECIFIC STATE VARIABLES.This study presents statistical evidence to support a priori reasoningthat certain environmental conditions have an important effect onthe results of compensatory education. This suggests that CE pro-grams should be designed in light of environmental conditions. Timein Phase I did not permit analysis of possible trends in achievementat inner-city schools. Analysis of specific environmental variablessuch as grade, poverty and mobility would be more meaningful if thetrend factor could be studied at the same time.

In this sample statistically significant differences were associatedwith percent Negro and achievement level at the beginning of compen-satory education. The analysis did not reveal any significant asso-ciation between the other state variables and enhancement in achieve-ment.

SECTI ON 2 59

The differences in average changes between 1965-66 and 1966-67in the various districts were statistically significant. It is not pos-sible to say if these differences are due to trends, differences inpupil/school characteristics, or fliff-r-ncc,s in rE3 rIrrI"nrrIcz,

The percentage of the variation in changes in achievement that canbe explained bx the variables included in the regression model is verysmall. The It for the regression using change in the first decile asdependent variable and computed from data for seven districts is only0.13 (see Table 15). That is, 0.14 is the best estimate of the percentof the variation in 6 D1 that is explained by the five variablesmobility rate, percent Negro, initial achievement level, attendancerate, and "effective Title I dollars per student."

There are many state variables other than those studied here whichmay have a relationship to enhancement in achievement. Future ef-fort in this area would do well to consider these additional variablessuch as changes in proportions of classes given achievement tests,the form of achievement tests used, and the percent of minority grouppupils (combining Negro and Spanish-speaking) in a grade.

60

:

67TMP-115

SECTION 3

PRELIMINARY ANALYSIS IN IDENTIFICATION OFDISTINGUISHING FEATURES OF SUCCESSFUL CE PROGRAMS

The first phase of this study focused on changes in achievement

test scores between 1965-66 and 1966-67 and the relationship be-tween these changes and selected pupil-school-environmental char-acteristics. The more detailed questions concerning dist!.nguishing

features of successful CE programs were deferred. However, itwas possible to make two types of examinations of effects of CE

programs preparatory to later analyses. One of these was the in-clusion in the correlation and regression analyses of a variable in-dicating average Title I expenditures per pupil by district. The

second examination involved case studies of specific CE activitiesat particular grades in two districts undertaken as prototype studiesof estimating cost and analyzing results of CE programs. Results

of the exercise suggest how relationships between CE programs and..

enhanced pupil performance must be examined.

DISTRICT LEVEL TITLE I EXPENDITURE PER PUPIL-11 DISTRICTS

To obtain at least a crude measure of the overall level of perpupil expenditure for CE, Title I expenditure figures for each dis-trict as a whole were used. For this level of expenditure to be ap-propriate to the achievement test results, the amount of the Title Iexpenditures in 1966-67 proportionate to the length of the academic

year elapsing before the post test was assigned. The measure of

Title I dollars per student was based on (1) total Title 1 dollars ex-pended within the district for 1965-66 and 1966-67, and (2) totalnumber of pupils in. district schools receiving Title I funds. Ef-

fective Title I dollars per student for each sample observation wascomputed as the sum of average dollars per pupil in 1965-66 plus a

portion of the average dollars per pUpil in 1966-67. The portion

used for 1966-67 was the fraction of the academic year that hadelapsed up to the time of the 1966-67 test for each specific grade

unit.

SECTION 3 61

At the level of specific school districts there seems to be a con-gruence between changes in achievement test score and effectiveTitle I dollars per pupil (see Table 24). The three districts withthe highest level of Title I funding have the largest gains in achieve-ment a"..: the first decile.

The correlation coefficients in Table 12 reveal an apparent rela-tionship between gain in achievement and effective Title I expendi-tures. The correlations between "effective Title I dollars" and eachof the four measures of changes in achievement are significant atthe 5 percent le-vel.

These positive findings must be qualified, however, by threeconsiderations. (1) The correlations for the lower quartile andlowest decile i. re lower than for the mean and upper quartile. (2)Observations within a district are not fully independent, since fora given grade level in a district all tests were administered at thesame time, and the same amount of Title I expenditures will apply.Since it is known that changes in achievement scores differ signi-ficantly among districts, much of the observed relationship may bedue simply to difference among districts.* (3) The regression co-efficients for the mean and the lowest decile after correction formobility rate, percent Negro, attendance rate and mean initial a-chievement level are small relative to their standard errors. Thissuggests that the apparent relationship between district level TitleI expenditures and achievement change might be accounted for byother variables which are correlated with amount of Title I dollars.

Correlations between district level Title I expenditures and achieve-ment changes within a district (e. g. , see Table 13) have quite limitedmeaning because the only source of difference in amounts of Title Iexpenditures is difference in testing data among grddes. It is not sur-prising that these correlations were not statistically significant.

In all, this crude attempt to determine the overall relation betweenkvel of Title I funding and achievement change produced evidence sug-gestive of a positive relationship; but this evidence is based on highlyaggregated data and cannot be regarded as highly reliable. Analysesof more detailed data within particular districts are presented below.

* For this reason it is hard to establish the degrees of freedom ap-propriate for testing the statistical significance of the correlationsbetween achievement test changes and Title I funding,

62

-

Table 24. Average Title I funds per pupil and changes

in achievement.

67TMP-115

District°

_

Change in Di Change in 7 EffectiveTitle I $ per pupil

6 4.20 1.28 140

12 1.78 0.43 135

13 1.32 1. 12 137

14 0.95 0. 14 55

10 0.55 -0.21 60

8 0.26 -0.38 53

3 0.22 0.36 51

1 0.05 0. 13 62

2 0.04 -1.35 20

4 -0.68 -1. 03 64

5 -0.70 -1. 16 64

Note:

°Districts arranged by order of magnitude on observed changes in D1 .

PURPOSE OF TWO CASE STUDIES IN ALLOCATION OF

PROGRAM RESOURCES TO THE GRADE LEVEL

One of the main objectives of this study is to determine relation-

ships between changes in pupil performance and characteristics of

compensatory education (CE) programs, including resource expendi-

tures and pupil exposures. In order to develop reliable estimates of

the contribution of CE to enhanced achievement, it is necessary to

measure or estimate resource expenditures at the same level at

which pupil performance measurements (e.g., achievement and at-

tendance) are made. Pupil performance measurements are available

for grades, but CE program descriptions and financial data were

found mostly at the district level. When these kinds of information

are recorded at school and district levels of aggregation, the effects

of CE upon pupils are obscured because of the small percentage of

SECT1 ON 363

students receiving GE and because of the large variation in CE re-

sources among grades within the schools. Therefore, it is neces-sary to estimate the distribution of program resources from school

districts to schools and grades and to identify the several types of

CE programs implemented for selected grades in sample schools.

*ago...

Wide disparities exist among the sample school districts in the

amount, degree of detail, and level of aggregation of data. It was

obvious that substantial effort would be required to extract, sum-marize, standardize, and process the information, and assign values

to the variables that will be utilized in the regression analyses to be

performed during Phase II. Two of the sample school districts wereselected to determine the feasibility of assigning CE resources to

grades. This analysis should yield a better understanding of varia-

tions in types of CE programs, duration of exposure of pupils, and

specific amounts of CE resources expended in these two districts.More importantly, the analysis should provide guidance as to the

preferred method for assigning these resources to the grade level

for all sample school districts during Phase II of this study.

'Different approaches were tested in the two districts selected.These differences in method reflect substantial differences in the

data obtained. One approach, used in District 10, employed the CE

program information that is readily available at the district level

and from this attempted to identify the type of programs authorizedby school and grade and to distribute CE resources to schools and

grades within the district based on these authorizations. The second

approach, used in District 13, started at the grade level within a

school and attempted to identify the specific programs that were im-

plemented and to estimate the resource requirements to perform

these activities.

Each approach required that reasonably complete data be already

accumulated or that c.dditional data be easily obtainable by phone or

mail. A brief inventory was made of the principal types of data ob-

tained from the several school districts. Each set was evaluated and

ranked according to relative completeness of pupil performance data,

including achievement test scores and attendance records, the variety

of compensatory education programs represented, and the quantity

and quality of financial data on hand.

The first approach assumes that programs are carried out in

reasonably good agreement with the original proposal or projectdescription and that there is little variation of program character-

istics among recipient schools except as indicated in the program

64671MP-115

plan. The second approach attempts to catalog , le distribution of

program resources which actually occurred at the grade level ina school. It avoids the assumption of little variation of programsamong schools and, therefore, requires more detailed informationabout participation, staffing, costs and changes of program- in aschool in order to distinguish the CE increment from the regularschool program.

Although the second approach is the more time consuming of the

two, its use was desirable in one of the pilot analyses because ofobserved departures of programs from original proposals amongmany of the sample school districts. In many instances, this de-parture from a prescribed program resulted from an inability duringthe first year of Title I to hire staff personnel in the middle of theschecq year or to obtain equipment on short notice. The co- 'aict of

a give_ program during the following year, was more likely to be

in accord with the budget and plan of the school district.

INFORMATION REQUIRED

Regardless of the approach employed, the objective was to obtain

very detailed knowledge of programs, schools and pupils. Frag-ments of information must be assembled from many sources todevelop and verify each estimate. The types of inforrnition desiredinclude:

1. Program Descriptions objectives, activities, personnelassigned, materials and supplies used, pupils (by schools

and grades), time and duration of program, pupil participa-tion and exposure.

2. School/Pupil Characteristics ethnic composition, economic

status, relative academic level, staff composition and turn-over, special classes.

3. Attendance Records by school and grade: average daily at-.

tendance, average dailymembership, gains, losses, per ent

attendance and absence, unusual factors or events influencing

attendance.

4. Financial Records district budget and expenditure reports,expenditures by school and project for regular and special

programs, expenditures by time periods, sources of funds.

SECTION 3

5. Evlluation Reports objectives, activities, staff and pupilparticipation, project expenditures by time periods, staffand pupil performance, measurement devices and theircharacteristics.

ANALYSIS OF DISTRICT 10 CE PROGRAMS

65

This section describes the process and the wide range of infor-mation employed in allocating program expenditures to the gradelevel for District 10 sample schools. Detailed program and expen-diture data are included.

Description of the Anaiysis

This has been an effort to pursue an approach which employs pro-gram information from school district plans, reports, and records asthe basis for determining the incidence and intensity of CE activitiesand for estimating resource expenditure for individual grades in sampleschools. District10 was selected for this experimental effort becauseit was one of the few visited which records expenditures by school andbecause it was one of the few visited which records expenditures byschool and because relatively detaild program information had beenobtained. The initial step was to assemble description information oneach CE project in the set of sample schools. This involqed search ofmany documents of program descriptions, Title I applications, schooldistrict budgets, expenditure reports, and evaluation reports.

Next, descriptive and quantitative summaries were prepared foreach project including objectives, principal activities, and resourcestImployed. Where appropriate the descriptions indicate (1) the num-

schools in the district and in the sample which had each pro-jet,. (2) the number an.d grade levels of pupil participants, (3) totaland per pupil expenditulres, and (4') hours of pupil exposure.

Finally, when the grade levels served by each project had beenidentified, reported expenditures were allocated to appropriate gradesby project and time period for each sample school.

The following sections describe the sample schools, some of theircharacteristics, and the bases for their selection; present the CEprogram descriptions; and summarize the results of this exercise.

66 67TMP-115

Sample Schools and Their Characteristics

Table 25 lists the characteristics used as criteria for selectionof the ten sample .:lemeritary schools and indicates the CE programsfor each school in 1966-67.* When selecting the sample from ap-proximately 55 schools eligible for Title I programs, an attempt wasmade to choose a sample which would possess a wide range of school

characteristics. In addition to these criteria, schools were chosento represent the mix of CE programs of the district. Eligible schoolsranged in enrollment from 150 to over 2500 pupils and the sampleschools chosen cover a large part of that range.

A high proportion of eligible schools had all-Negro pupil popula-

tions; however, some schools were selected which had the largestproportions of non-Negro pupils among the eligible schools. Theselection was based on data compiled in the winter of 1965-66 to

establish the initial eligibility of schools. The sample of ten schoolsincluded three which had substantial proportions of nen-Negro pupils.Since that time, substantial change of pupil populations has occurred,and in 1966-67, only one of these schools reported having any non-

Negro pupils.

About 16 percent of District 10 pupils were from low-incomefamilies; in eligible schools this percentage ranged up to 55 percent.tSample schools had from 22 to 49 percent of economically deprivedpupils. School personnel point out that high mobility the move-ment of a pupil from one school to another is a frequent character-istic of schools with substanti-1._ proportions of pupils from poorereconomic circumstances. Indices of mobility were computed forthe sample schools and are shown in Table 26 with attendance andracial concentration percentages. Considerable variation of pupilmobility exists, fr i.n year to year and from school to school, but

no distinct pattern is indicated.

* The selection criteria do not agree with similar information insubsequent talles due to different reporting periods.

tAs computed for the 1965-66 Title I application, based on annual

family income of less than $2,000.

1

I

)

SECTION 3

Table 25. Sample selection criteria and compensatory educationprogramsDistrict 10.

r---;:...I.........:_......,........................

67

1")a)

a.

r^mpensnteiry Frificntinn Program

...in

._ 1

00 0

2 2. C) .17. c >2 b a

0o 0

o t E ...vi 4. V iLiRA0

a) < o c c V) -0 .tY 4)0 C.) e E ti 0 x 0 20) I.13 > 0 ID UU g 2 ._

v,> .c 0

.... an = ...... VIC 0i.. ... 'V

C En ti 2 CL "5) 2' 1 t 0u .3 12 c E C 0 2 0 0

10 ...I CL. E X

8O a.

c -.g I.=

1 186 27.3 79

2 570 35.5 100

3 1561 35.2 100

4 265 31.8 100

5 1618 25.3 100

6 272 37.0 88

7 29:3 22.2 54

8 776 22.0 100

9 506 32.1 100

10 545 49.1 100

X X

x

x

Figure 9 permits comparisons to be made among racial con-centration, mobility and attendance. These comparisons do notindicate obvious relationships among these characteristics. Neithermobility nor attendance appears associated with racial distribution.An inverse relationship between pupil mobility and attendance mightbe anticipated but these data do not support that expectation.

68 67TMP-115

Table 26. Attendance, mobility and racial distribution ofsample schools (percentages) in District 10.

63-4

Attendance

64-5 65-6 66-7 63-4

Mobi li tya

64-5 65-6 66-7 63-4

Negro Pupils

64-5 65-6 66-7

95 92 89 92 32 35 37 28 20 41 69 100

2 89 92 89 91 29 41 18 62 100 100 100 100

3 89 89 86 90 14 29 34 47 100 100 100 100

4 85 87 87 91 23 28 28 35 100 100 100 100

5 91 92 84 92 39 13 54 25 100 100 100 100

6 83 87 87 88 64 43 26 74 29 52 74 100

7 90 98 90 92 47 53 35 47 7 23 90 44

8 88 90 85 93 43 13 22 17 100 100 100 100

9 87 87 89 91 16 32 21 22 100 100 100 100

10 83 87 85 86 33 29 25 30 100 100 100 100

Note:

a (Gains + Losses) + ADM.L

Improved attendance is an objective of many CE programs. Thefollowing attendance data were obtained by school and grade forfour consecutive years ending with the 1966-67 term: initial re-gistration, gains, losses, end-of-year membership, average dailymembership, average daily attendance, average daily absences,percent attendance, and percent absences. Attendance rates weresummarized and examined to detect any systematic change thatwould be helpful in analyzing the effects of CE programs. Table26 showed average annual attendance rates for the sample schools.

SECTION 3 69

SCHOOL

1

2

100

-

50 ...ea, ..4

0

100

50-

o .

.../.0

ee /*V

6

7

100

50 i

0

50

0

4. a.anfowaleel,

/.. .. f./

co Me 0 460.11b

3

100

so-

8

1M150

moomp=mNIMIND.. i.e."' 4 ......

....,",,,.../..

o

100 IN&

al .. ay..am, ...4 9

50 50

4 00° ,IP ella . 00

0 0

5

100

50

0

01111

411.4P GO.dP Sib *.

.%/% %./ qk

%. .%,

II I t64 65 66 67

Ig.....' ... 411.4ra ....

146.

dr,..0 -I1111 44b

... Imenur

Nombo alo as al op 6.4.

/09. ft.0111

10

KEY (%):

----ATTENDANCENEGRO

50

0

I. 494..0". a... .6.11111

es go404.

,..*lab 'tame.

1 I 4

64 65 66

MOBILITY

Figure 9. Racial distribution, mobility and trends ofattendance (percent) in sample schools.-

70 67TMP-115

A mixed pattern of increases and decreases in attendance ratesis apparent. Eight schools recorded decreased attendance for the1965-66 school years. All ten sample schools reported increasedattendance during the 1966-67 term. This is the only year of the

period in which all of the sample schools recoided imprnved at-tendance rates. To avoid a hasty conclusion that this improvementresulted from CE programs, a more probable cause was soughtand found. Extensive storm damage was sustained in this schooldistrict early in the 1965-66 school year and widespread disruptionof school activities was experienced during a period of weeks. Theimproved attendance of the following year more probably reflectsthe resumption of normal attendance. Additional analysis of attend-ance data has been reported in Section 2.

Monthly summaries of attendance data were not available at thecentral school office but probably could have been obtained from in-dividual schools at the expense of additional time. If monthly datahad been obtained, rather than average annual data, it might havebeen possible to omit the storm period from consideration and makea more sensitive appraisal of the impact of CE programs, and otherfactors, upon pupil attendance.

Program Descriptions

Sample schools had from one to four CE projects in 1966-67.

One project, Quality Instruction, was supported by school districtfunds, eight projects were funded under Title I, ESEA, and two pre-school projects were funded under the Economic Opportunity Act(EOA). The two EOA projects are listed for information only. Both

were pre-kindergarten projects; no allocation effort was requiredand very little project description information was available. Inaddition, there was a district-wide surmner CE program, calledReading-Enrichment-Recreation (RER), which is not listed in Table25 because pupil participants were not identified by schools.

PROJECT: QUALITY INSTRUCTION. Purpose: To improve thequality of instruction in selected schools which are experiencingsubstantial change of pupil population due to racial integration.

SECTION 3 71

Description: When the proportion of Negro pupils in a schoolexceeds one-third, the school may be selected for this project.More intensive services are allocated to the school which may in-.clude administrative or clinical personnel, classroom or specialistteachers, guidance counselors or teaching materials and supplies.This project is funded by the school district. Three of the sampleschools received small increments of support from this project in1966-67. It was reported that schools with this project seldom areeligible for Title I projects.

PROJECT: TEACHER AIDES. Purpose: To relieve teachers ofnon-professional and routine tasks in order to provide increasedopportunity for creative teaching, planning, individualized instruc-tion, and pupil counseling; to enable use of a greater variety andquality of instructional materials; to provide increased attention tothe needs of disadvantaged children.

Description: In 1965-66, 352 teacher aides were assigned to asmany classes in 53 schools, 1 per class with average class size of30 plus, in kindergarten and grade 1, including 17 "3-1" schools.*Each aide was employed 4-1/2 hours per day for ten weeks. In 1966-67, 379 aides were assigned to classes in kindergarten, grade 1, andgrade 2, in 54 schools, as follows: 345 part-time aides (4-1/2 hoursdaily, with 3 hours in classroom) were provided in 255 first grade,83 second grade, arid 6 combination first-second grade classrooms;full-time aides (6 hours with 5-3/4 hours in classroom) were as-signed to 31 kindergartens; 3 aides were also assigned to upperelementary grades as an experiment. During this year, the aidesparticipated for 27 weeks; all were high school graduates and overhalf had some college education. In 1965-66, the aides were sup-plemented by $350 of supplies and equipment per classroom in grades1 and 2, e.g., tape recorders, film strips, picture sets. In 1966-67, $300 of equipment and supplies were provided each of the 84second grade classrooms added to the aide project that year. Theaides enabled teachers to devote more time to instruction; also theyworked with children individually and in groups, especially in thearea of language development (which was part of their in-servicetraining).

*Schools having the Intensive Instructional Improvement project,see page 77.

,.

72

Table 27 summarizes Teacher

67TMP-115

Aide assignments in the sampleschools during the two program periods.

Table 27. Teacher aide assignments.

SAMPLE

SCHOOL

rDAIIP..7..-......

MARCH-jUNE 1966

K 1 2 Ca K

1966-67

1 2 Ca

1 1 2 2

2 1 3 1 3

3 2 10 1 11 2

4 1 1 1 2 1

5 3 7 3 7 7

6 1 3 1 3

7 1 2 2

8 1 4 1 4 4

9 1 2 1 1 2 2

10 1 3 3

Note:

°Combination of grades 1 and 2.

1965-66 l 966-67

Total Schools Served: 53

_53

Sample Schools Served: all 10 all 10

Total Pupils Served: 10,560* 11,461

Total Expenditure: $488,4721. $911,833

Expenditure Per Pupil Served: (10 wks) $44 (27 wks) $80

Hours /Pupil Exposure 225 K:8001-2:600

Estimate: number of aides x 30 pupils/classt Estimated from salary and equipment costs, plus estimatedadministrative overhead.

SECTION 3 73

PROJECT: ADJUSTMENT TEACHING. Purpose: To meet the varyingand special needs of grade 3 underachieving students from low-incomeareas.

Description: Adjustment teachers provided individualized tutoringto small groups of 8 to 10 pupils in any needed subject area. Eachchild in the project participated 40 minutes per day. Underachievingchildren were selected on basis of test scores, cumulative records,and teacher observations. This project was initiated in the fall of1966 and was reported to have continued for 20 weeks.

1966-67


Sample Schools Served (School 7): 1

Total Pupils Served: 430*

Total Expenditure: $60,000t

Expenditure Per Pupil Served: $139

Hours /Pupil Exposure: 67

PROJECT: REDUCTION OF CLASS SIZE. Purpose: To Iftelp makepossible individualized instruction by reducing the size of classes.

Description: Class size was reduced in grade 1 of twelve schoolsthrough the use of portable classrooms. In 1965-66, expenditureof $847,477 was made to obtain 17 portable classrooms. In the fol-lowing year, 15 additional teachers were employed to use them.

* Estimated: 9 pupils x 6 hours/day X 8 schools

Estimated: 8 teachers at $7,500 (average salary and benefits)

7467TMP-115

Total Schools Served:

Sample Schools Served (Schti-,1

Total Pupils Served:

Total Expenditure:Expenditure Per Pupil Served:

Hours/Pupil Exposure:

1):

1966-67

12

1

720*

$257, 248t

$357

450**

PROJECT: CLINICAL READING. Purpose: To improve writing,reading, spelling, work habits, and powers of concentration in

grades 3 through 6.

Description,: Clinical Reading Centers were established by the

school district, before ESEA programs, in elementary and secondary

schools. Title I funds permitted expansion of this project. In 1965-

66, 10 after-day centers were established, serving 15 pupils each

for one hour each day. In 1966-67, 8 after-day centers were cone.

tinued and additional day centers were established, two full- and

two half-day centers. In the day centers, groups of 32-35 pupils

receive 45-60 minutes/day of instruction instead of another class

activity which would be missed least. The day program servedpupils in grades 3 - 6, for 28 weeks (1966-67) at 5 hours/week. The

after day programs served grades 4 and 5, 'for 24 weeks (1966-67)

at 5 hours/week; class size was reduced to 8 - 10 pupils in 1966-67.

The following summary describes the incremental portion of the

program, made possible by Title I support. The Center in thesample school was funded by the school district but is representa-tive of other centers which were funded by ESEA.

*4t

.11=1,

Estimate:Estimate:

c ons tructionclas s room.

** Estimate:classes).

12 schools x 30 pupils x 2 classes/day.

15 teachers x $7, 500 average salary plus 1/10 ofcosts (based on estimated 10 year life of a portable

30 weeks x 5 days/week x 3 hours/day (two hal-.-day

SECTION 3

1965-66

75

1966-67

Total Schools Served: 10 12

Sample Schools Served (School 2): 1 1

Total Pupils Served: after-day* 151 81day 89

Total Expenditure:* $49, 555 $107, 379

Expenditure Per Pupil:* $328 $631

Hours /Pupil Exposure:* 75 50

PROJECT: LANGUAGE ARTS TEACHING CONSULTANTS. Purpose:To provide imaginative approaches to meeting individual needs ofunderachieving pupils, in all phases of listening, speaking, reading,and writing.

Description: Two language arts teaching consultants worked intwo schools with small groups of children who were achieving belowgrade level, in grades 1 through 6. The project encompassed allphases of listening, speaking, reading and writing, using innovativeapproaches and materials not used in the regular classroom. Groupsconsisted of about 8 children from each grade level, with meetingsdaily during class hours, plus one hour after school for specialtutoring and recreational reading. The project also included fieldtrips; a.,-litory and visual examinations; and 'parent involvement.

r4.

These data are recorded here as reported by the project super-visor even though the basis for computation may differ from otherprojects described in this section.

76

1965-66

67TMP-115

1966-67

Total Schools Served: 2 2

Sample Schools Sel7ved (St.hr,rd A): 1 1

Total Pupils Served: 120 88

Total Expenditure: $15,900 $32,741

Expenditures per Pupi' d $133 $372*

Hours /Pupil Exposure: 50t 300t

PROJECT: CENTRALIZED LIBRARIES. Purpose: To enable schoollibraries to serve both school and community. They are designedto be accessible to the neighborhood after school hours and duringthe summer, as well as to provide varied instructional and enrich-ment materials as part of the school program.

De.. .- ;ion: The project was initiated in 1965-66 and continued

du: Ing trim following year. It involved the assignment of librariansto elementary schools for the first time. Libraries have been, orare being, developed in 15 schools employing portable buildings, re-novations, new construction, and limited service to two schools

without librarians or furniture,. Five libraries began providing ser-

vices in January 1967; the remainder are in the process of develop-ment. A center was established to process books for six of these

libraries.

* Per pupil expenditure for those directly participatir; a figureof $77.59 was given which "inclr-3.es all children in grades onethrough six in the two schools involved in the pro,iect because it is

felt that all were a.fected directly or indirectly by the project."

tIn 1965-66, project started in one school 6 weeks before close

of school year; in other schools, 4 weeks before close. Estimatesassume 1 hour during school day and 1 hour after school, daily

for 5 and 30 weeks respectively, allowing for holidays and absences.

_

SECTION 3 77

1965-66 1966-67

Total Schools Served:

Sample Schools Served:

Total Expenditul-e:*

5

(Ce.1-setrd ) 7

$460,584 $441,092

PROJECT: INTENSIVE INSTRUCTIONAL IMPROVEMENT. Purpose:To concentrate services in 17 elementary schools in low-incomeareas where pupils consistently have tested low in readiness andachievement, among the most educationally disadvantaged in thesystem.

Description: This project was in operation for about 21 weeks ofthe 1966-67 school year, starting in January 1967. Services in-cluded the areas of administration, instruction, health, and socialwork. Adjustment teachers aided selected third grade pupils andconsultants participated "to intensify and vitalize learning experi-ences. " Teachers aides were assigned to grades K, 1 and 2. After-school tutoring was available, especially in reading; selected pupilsparticipated thrice weekly for an hour in groups of 4 to 10. A totalof 1961 pupils received up to 50 hours of tutoring.

Each school in this project had physical education, art and musicprograms. Instructional materials, designed for disadvantagedpupils, were provided $100 per classroom in grades 3 through 6

plus $1 per child in the tutoring class. Administrative assistants insix of the largest schools, with enrollments exceeding 1300, enabledthe principals to devote more time to improving instruction. Oneperson devoted half-time each to the duties of administrative as-sistant and adjustment teacher. Social and attendance workers visitedpupil homes; counseling was available for parents and referral tocommunity social and welfare agencies. Extensive medical and den-tal examinations were made; funds for correcting defects were ob-

tained from community service agencies.

Teachers and principals determined and requested specific kindsof help from consultants, identified problem areas, and recommended

These are only part of the total cost of the project, to be completedin the future. Adequate information on costs of developing, stocking,and operating of these libraries is not available.

78 671MP-115

instructional materials. There were 5 primary and 4 upper elemen-tary consultants, a ratio of one consultant for 50 teachers. Teacherswere given released time to "pursue professional tasks independently."

Additional staff included:

14 adjustment teachers for 3rd grade6 administrative assistants/adjustment teachers

10 consultants2 music consultants, grades 4, 5, 64 itin( rant art teachers, grades 4, 5, 6

18 physical education teachers6 health staff (4 nurses, dental hygienist, health coordinator)

15 social services (8 visiting teachers, 6 attendance workers,1 coordinator)

1 director

76 Total

1966-67


Sample Schools Served (Schools 5, 8 and 9) 3

Total Pupils Served: 16, 500

Total Expenditure: $685, 014*

Expense Per Pupil Served: $41.50

Hours/Pupil Exposure: 630t

PROJECT: ENGLISH AS A SECOND LANGUAGE. Purpose: Toteach English to children with other native languages, who often hearno English spoken at home, and to provide a better understandingof regular classroom activities.

Description: Teachers worked with small groups, using audio-visual-lingual techniques. The project started in the summer of1966, continued during the regular school year 1966-67, and wasconducted during the summer of 1967 as an integral part of the

' Does not include funds spent in 3-I schools under other Title Iprojects e.g., teacher aides were in the teacher aide project budget.t

Estimated on basis of 21 weeks X 5 days per week X 6 hours perday (assuming no absences or holidays).

SECTION 3 79

Reading-Enrichment-Recreation (RER) project, discussed below.In the summer sessions, each child participated 2 hours a day for 6weeks. In the 1966-67 school year, participation was generally 1hour a day, although some variation according to individual needswas allowed.

Summer1966 1966-67

Summer1967

Total Schools Served: n/a 9 n/aSample Schools Served: n/a

(School 7)1 (avg. 35

pupils /class )n/a

Total Pupils Served: 303 320 365

Total Expenditure: $51,182 $65,981 ,Exp. Per Pupil Served: $169 $206 ,Hours /Pupil Exposure 60 150 60

PROJECT: SUMMER READING-ENRICHMENT-RECREATION (RER).Purpose: To provide special educational, cultural, and recreationalservices to educationally deprived children in grades 2 through 12(grade 1 not included in 1966). Specific objectives, as expressed for1967, were to improve classroom performance in reading beyondusual expectations; to improve children's verbal functioning; to im-prove artistic awareness and self-expression; to improve the chil-dren's self-image; to increase their expectations of success in school;to improve the health of the children through physical fitness.

Description: An RER center was located in each of the 54 Title Ischools. The six-week project in the summer of 1966 consisted ofmorning sessions (3-1/2 hours including breaks) with one hour de-voted to each of reading and language skills, cultural enricirnent, andphysical education, and a 2 hour afternoon recreational program whichwas open to any child, regardless of whether enrolled in the morningclasses. Pupil-teacher ratios in the classes were as follows: remedialand language arts, 10:1; cultural enrichment, 15:1 (20:1 in 1967);physical education, with trained instructor, 25:1; (in practice, in phy-sical education, trained instructors were not always available andclass size sometimes exceeded 30). Total elementary instructionalstaff in 1967 was 447 teachers and 11 consultants for an overall ratio

*Part of overall RER budget.

80 67TMP-115

of about 18:1. Each child went on 3 field trips, cultural enrichmentfield trips, with this experience being worked into the content of thereading program. The project provided innovative instructional ma-terials and equipment, delayed in 1966. The 1965-66 evaluationstates, "...techniques, materials and activities which duplicatedthose used during the regular school year were least successful inproducing the desired behaviors." Experience with art, music anddrama (including pupil participation) were provided. The afternoonrecreation program concentrated on group sports and games. Se-condary students with knowledge of playing an instrument took partin instrumental music program three afternoons a week. Lightsnacks were served to elementary pupils during morning breaks.

The summer program, 1967, was similar to that in 1966 exceptthat (1) grade 1 pupils could also participate; t2) the session lastedfor 6-1/2 weeks, plus 1 week of pre-service training for staff; (3)the elementary cultural enrichment portion of the program wasfocused more specifically on language arts; (4) the secondary RERprogram was changed more radically so that emphasis in the academicpart of the program "shifted more or less exclusively to the languagearts; especially reading, although music also continued to be a strongfeature, including jazz performances." A wide selection of readingmaterials was made available (although again delayed), e.g., paper-back books for secondary pupils. Substantial attrition of these bookswas anticipated, even sought. One supervisor believed that disap-pearing books would indicate greater pupil interest in reading. Someteaching equipment was employed, such as tape recorders.

The supervised recreation portion of the project was continuedwithout substantial change and employed the equipment that had beenpurchased for the program of the preceding summer. In 1967, itwas extended beyond the end of the academic program (to August 18).The English as Second Language project was included in the summer1967 activities.

SECTION 3 81

Summer 1966 Summer 1967

Total Schools Served:* 54 54

Sample Schools Served: all 10 all 10

Total Pupils Served: 9,000 9,939tTotal Expenditure: $2,534,189** $1,302,213

Expenditure Per Pupil Served: $282 $131

Hours/Pupil Exposure* 90 90

Expenditures, by School and Program

This school system was one of the few visited that records expendi-tuxes for individual schools. Expenditure data were furnished by ac-counting categories, for the regular school programs of 1964-65,1965-66, and 1966-67 and for the compensatory education projects of1965-66 and 1966-67. Table 28 is a sample of the type of informationobtained. Tables 62 through 70 in Appendix G contain information forthe other 9 schools. Table 29 summarizes total expenditures, byschool and year, for the regular and CE programs. The prinicipalimpact of this information is that it reveals considerable variationsof p tr-pupil expenditure, even for what is described as the same mixof programs. For the regular program of 1964-65, the largest per-pupil expenditure was more than double that of the smallest. Similar

Elementary and secondary schools combined.

t Of the 9,939 enrollment, about 72 percent enrolled in the centerwhere they regularly attend classes; 19 percent enrolled in anothercenter; 7.7 percent were children attending parochial schools; 1.2percent were children attending other private schools. About 1,800were secondary level pupilsfor these, there was a high attritionrate; perhaps 50 percent left the program before its end. The bestmaintenance of attendance at secondary level was at grades 7 and 8.

*

Including about $860,000 for playground or sports equipment.

Three hours/day for 6 weeks (not including afternoon or extendedrecr eation pr Og rams ).

..?"-

r1 7

,, -.

7'7

,.."

1,tr

,

Tab

le 2

8.E

xpen

ditu

res

for

regu

lar

and

com

pens

ator

yed

ucat

ion

prog

ram

sSch

ool 1

.

Dis

tric

t 10

Sch

ool 0

1R

egul

ar S

choo

l Pro

gram

sC

ompe

nsat

ory

Edu

catio

n P

rogr

ams

Exp

endi

ture

Cat

egor

ies

Tea

cher

Aid

esA

djus

tmen

t Tea

chin

gR

educ

ed C

lass

Siz

eP

roje

ctQ

ualit

y

64-6

565

-66

66-6

765

-66

66-6

765

-66

66-6

7

##

#$

#$

#$

#$

#$

)

Prin

cipa

ls, C

onsu

ltant

s, S

uper

viso

rs1

8647

190

061

1147

430

Tea

cher

s6

3126

86

3329

18

5506

23

2481

229

9332

28

Libr

ary,

Aud

io-v

isua

l&

TV

Per

sonn

el18

Sec

reta

rial-C

leric

al1

3536

136

231

4070

Tot

al S

alar

ies

4345

145

920

7060

625

2929

9332

28

Tea

chin

g S

uppl

ies

& O

ther

Exp

ense

s25

135

638

864

731

718

85

Tot

al In

stru

ctio

nal E

xpen

ses

4370

246

276

7099

431

7633

1051

13

Hea

lth S

ervi

ces

Pup

il T

rans

port

atio

n

Pla

nt O

pera

tion

& M

aint

enan

ce79

7776

4310

726

27

Fix

ed C

harg

es10

913

114

3

Foo

d S

ervi

ces

Stu

dent

/Com

mun

ity A

ctiv

ities

Tot

al S

uppo

rt E

xpen

ses

7977

7643

1072

610

913

117

0

Tea

chin

g E

quip

men

t13

551

913

920

9

Tot

al E

xpen

ses

5167

953

919

8185

538

0435

8054

92

----

-.~4

i001

."""

*401

"0"4

1°,1

44

th

Tab

le 2

9. S

umm

ary

of p

rogr

am e

xpen

ditu

res

of D

istr

ict

10.0

Sam

ple

Sch

ool

1964

-65

Reg

ular

Bud

get

Tot

alE

xp. $

$/P

upil

151

679

407

211

2599

215

329

1951

200

460

938

256

529

2636

178

668

356

289

784

713

332

816

1981

218

913

7535

237

1095

944

180

1965

-66

Reg

ular

Bud

get

IC

E B

udge

t

Tot

al$/

Pup

ill

Tot

alE

xp. $

Exp

. $$frupil

1966

-67

Reg

ular

Bud

get

CE

Bud

get

Tot

alE

xp. $

$/P

upil

5391

928

338

0420

1133

8819

923

427

41

3043

9020

722

437

15

6723

126

928

0611

3103

8123

611

690

9

6842

025

610

528

39

9071

030

812

965

44

1404

9219

258

658

1350

3526

648

3110

1034

3019

548

549

8185

5

1428

95

3926

95

8159

6

3928

71

9308

4

1164

98

1868

01

1838

56

1344

73

437

264

305

334

253

288

361

294

412

273

Tot

alE

xp. $

$/P

upil

9072

48

3594

666

3226

625

4136

120

3668

324

2163

167

1885

658

1938

131

1078

924

4864

10

Not

es:

°Exp

endi

ture

s of

the

sum

mer

pro

ject

(R

ER

) w

ere

not r

epor

ted

by s

choo

ls a

nd a

re n

ot in

clud

ed.

bP

er p

upil

expe

nditu

res

are

base

d on

AD

M fr

om th

e ye

ar e

nd a

ttend

ance

rep

ort.

CA 73 e 0 z 03

1

. fr

84 671MP-115

but lesser disparities are shown for the subsequeat years. Forschools with the same CE projects, per-pupil expenditures alsovary in the same way. For example, while schools 4 and 10 eachhad the same CE project in 1966..67, the per-pupil expenditures inthe former were double those of the latter. This variation is notdue to different numbers of teachers or other resources added.Schools 5, 8 and 9 had the same two CE projects in 1966-67, yetthe largest per pupil expenditure was about 25 percent greater thanthe smallest. Similar differences are shown for 1965-66.

These differences raise some important questions. The reli-ability of estimates of CE program cost by grade and school basedon district level program information depend on the degree of stand-ardization of programs among pupils served. If equal amounts ofa resource are added by a project for each school but numbers ofpupils differ, it is not really meaningful to assume that the resultsof the project will be similar among schools.

Moreover, even with a similar per-pupil allocation, resources mayactually be employed in different ways. The statistics show variationsof per-pupil expenditures between schools; they do not show variationsof the employment of resources within a school or class. Consider aproject in which a reading teacher instructs five pupils of a class. Herimpact on the five pupils is not altered by the large or small number ofpupils who constitute the remainder of the class. At the same time,allocation of the costs of teacher and materials to the whole class doesnot reflect the real impact or cost per pupil of the project. If alloca-tion is made on the basis of the five pupils served directly, no recog-nition is given to the widely claimed "spillover effects." Allocationto the grade level may involve unknown amounts of error in estimatesof exposure to project activities.

Not only are there substantial variations of per-pupil expendituresbetween schools which have the same mix of projects but these "build"on very substantial differences of the regular budget per-pupil ex-penditures. Other variations are shown by school, from year to year,not all of which are increases, as public information records to bethe rule for schools in general. Half of the sample schools had spentless per pupil in 1965-66 than in the preceding year.

There are at least three factors which account for much, perhapsall, of these differences of per-pupil expenditures. Frequent andconsiderable variation of school registration or ADM is indicated byend-of-year pupil accounting data obtained for this study. School

-

...................OW,TWIN **011111ft,e,loy,....... ........1*10.9M.04.0.1.0.1* .................*44....11*./........

SECTION 385

administrators plan budgets based on anticipated school enrollmentfor the coming year. They cannot control the number of pupils whochange schools. Rarely do they change the boundaries of school ser-vice areas to offset enrollment fluctuations; they do not wish to causefrequent disturbances of pupii-schooi- community relationships.School area boundaries are changed when the physical capacity of aschool is exceeded as may be caused by growth of pupil populations.Another factor is the trend of increased salaries in recent .fears.The larger regular budgets of all sample schools in 1966-67 werecaused, at least in part, by salary increases which averaged $1, 500

per year for teachers. Finally, teacher seniority and salaries ac-count for another element of variation.

Such variations of expenditures will complicate any attempt tocompare programs on a cost-benefit basis, i. e., to seek the cost cfobtaining a unit of increased pupil performance via alternative CEapproaches. Salary differences among teachers, changes of salaryscales, and changes of expenditures for materials or equipment aresubject to control of school administrators and can be taken into ac-

count. Fluctuations of pupil enrollment are not controllable and area source of error or reduced precision in evaluating the benefitsand costs of educational activities.

Allocation, by School and Grade

When the school district accounting system permits summarizingexpenditures by school and program, the methods for allocating these

expenditures to grades are relatively simple. The difficult part ofthe process is that of determining which program activities were di-rected at each of the several grades of a school. This task involvedsearching through many documents in order to assemble a reasonablycomplete list of assignment of programs to grades. Frequent dis-crepancies and disparities were found. For example, expendituresreported in different sources often were in conflict; some were esti-mates for which the basis was not always clear, others were partialor total expenditures but for different time periods.

After compiling and checking the information on hand, preliminarydrafts of project descriptions were prepared. Unresolved questionswere referred to district and project administrators who were veryhelpful in providing additional information and explanations. When

the information was considered reasonably complete, the projectdescriptions were written. From this search was obtained the grade

86 67TMP-115

level assignment of the several projects. The final step was thearithmetical exercise of distributing stated expenditures at the schoollevel to the grades served. Except when project information indicatedotherwise, expenditures were allocated to grades in proportion to thenumbers of pupils in that grade for each year.

Table 30 is an example of the results of this exercise and containsestimates of regular and CE program expenditures, by school, grade,and year.* Information for the other 9 schools in contained is Tables71 through 79. These allocations must be regarded as estimates, atleast until verified by school district administrators. Caution mustbe exercised when comparing these estimates with changes of pupilperformance. The time periods during which these estimated funds

were expended do not necessarily coincide with that of the pre- andpost-test measurements. Some refinements or reallocations may be

appropriate before undertaking more sophisticated analysis, such asregression studies. This may require assuming specific rates of ex-penditure of resources month by month rather than a constant rate ofexpenditure through the school year. The following discussicn isbased on the constant-rate assumption.

Effects of CE Programs on Achievement

Analysis of achievement test scores has been reported in Section 2.Only a brief recapitulation is made here in order to complete thiscase study. Figure 10 summarizes changes of first deciles and meansof reading test scores of grades in sample schools for which the a-chievement test data were suitable for statistical analysis. For ex-ample, consider the changes recorded for grades 3 and 4 of School 1.

* These estimates, on a per-pupil basis, do not agree with the per-pupil estimates of project descriptions above. They were computed

on different bases and from different data. These estimates arebased on reported expenditures and were computed from the totalnumber of pupils in a class. The estimates of the project descrip-tions wer, made chiefly from budgetary cost information and attemptto indicate expenditures for pupils who participated directly in aproject.

Totals are reported expenditures; columns may not add to thetotals due to rounding.

SECTION 3

Table 30. Program expenditures by grades of School

87

1965-66 I Regular

Programs

$

Teacher AidesAdjustmentTeachers,Reduced ClassSize

$

Total CEPrograms

$Grade ADM

K 29 7411 994 994

1 57 14565 1953 1953

2 25 6388 857 857

3 24 6133

4 26 6644

5 21 5367

6 7 1789

Sp. 22 5622

Totals 211 53919 3804 3804

1966-67 Regular

Progrcms

$

Teacher Aides,AdjustmentTeachers,Reduced ClassSize

$

ProjectQuality

$

Total CEPrograms

$Grade AD M

K 30 13567 1085 910 1995

1 35 15828 1266 1062 2328

2 34 15376 1229 1031 2260

3 19 8592 577 577

4 18 8140 546 546

5 20 9045 607 607

6 14 6331 425 425

Sp. 11 4974 334 1 334

Totals 181 81855 3580 5492 9072

Note:aPer-pupil expenditures for regular and CE projects of the ten sample schools are

given in Table 28.

88

-64

3.3

5

1---3

3

6

I.

1 2 3 4 5 6 7 8 9 10

SCHOOL

3

3

3 4 GRADE

5

34 5

3

3

67TMP-115

3

3

3

-.5 4

1 2 3 4 5 6 7 8 9 10

SCHOOL

Figure 10. Observed change of reading achievement for test period

September 1965 to September 1966District 10.

24

21

18

15

12

9

SCHOOL 1GRADES 3-6

6

3

65-66 66-67

SCHOOL 6GRADES 3-6

SCHOOL 2GRADES 3-6

65-66 66-67 65-66 66-67

TFT DATE E=1 REGULAR PROGRAMS CE READING

Figure 11. Exposure to CEselected schools.

t1.0 CE OTHER

SECTION 3 89

The score of the third grade pupil at the first decile was 5 unitsgreater on the post-test while the score of a classmate at the meandid not increase. Scores of fourth grade pupils at the first decileand mean were lower on the post-test than when tested one yearearlier. This figure records about equal incidence of negative andpositive changes of these measures. No consistent pattern of changeis shown, by school or grade. These measures, and others reportedin Section 2, yield no indications of significant change of readingachievement.

No relationships were found between change of pupil test scoresand type of CE programs or level of expenditure. Table 31 givesthe relevant data for grade 3 in nine schools. The change in themean and at the first decile were not more favorable in those caseswhere per pupil expenditures on CE were the highest. This absenceof the desired results is not unexpected; the following paragraphspresent some of the reasons.

First, achievement test scores analyzed did not match well withthe grades which had CE projects. Test data were not obtained forsome grades. In particular, all sample schools had the TeacherAide project in grades K through 2 but test results were not obtained.Some of the test data re cived could not be made suitable'for statisticalprocessing. For example, either pre- or post-test scores were notavailable for some grades. Table 32 compares the grades for whichpre- and post-test scores were used to measure changes with thegrade levels which participateA in CE activities.

Next, not all of the CE projects could be expected to have impactupon reading performance. Only one of the ten projects was orienteddirectly toward improving reading achievement and it served limitednumbers of pupils. Two projects focused upon English language artsof which reading is an essential part. Two other projects includedreading content; one was started after the post-test date, the otherwas a summer program for which pupil particfpants from the sampleschools cannot be identified. The remaining five projects providedadditional personnel, materials, or equipment for use in other in-structional activities. Table 32 sl_ows that only three of the sampleschools (2, 6, 7) had reading-oriented CE projects in 1965-66.

Figure 11 demonstrates the exposure of pupils to CE activitiesin three sample schools. The relative magnitudes of regular andCE expenditures are shown on the vertical axis.

Tab

le 3

1.E

xpen

ditu

res

Gra

de 2

(19

65-6

6) a

nd a

chie

vem

ent d

ata

for

Gra

de 3

(S

epte

mbe

r 19

66)

of D

istr

ict 1

0.

Sch

oola

Reg

ular

Pro

gram

Tot

alC

EA

DM

Exp

endi

ture

s/pu

pi I

Pre

&D

1A

Q1

AQ

3C

EC

E +

Reg

.7

818

545

2108

101

2120

434

.5-1

.46.

0F

.i.o

-5.2

410

360

921

4321

262

31.4

4.8

5.7

3.8

2.5

163

8485

725

3429

036

.00.

14.

81.

5-2

.0

920

729

2106

8525

269

31.1

3.0

2.0

5.0

1.0

712

763

2481

4654

331

36.6

1.0

0.6

3.0

-1.7

1013

715

1704

7622

203

25.5

4.0

0.0

6.0

3.3

213

924

2433

7632

215

34.2

-0.9

-2.0

-2.0

-1.0

551

120

6337

218

2926

432

.5-1

.7-2

.0-3

.0-3

.0

614

375

2954

5851

298

33.2

-3.0

-5.2

-4.0

-1.0

346

085

6559

245

2719

4N

otav

aila

ble

Ave

rage

of a

bove

20,7

9828

4697

3225

332

.80.

61.

11.

0-0

.7

Not

e:aS

choo

lsar

rang

ed b

y or

der

of m

agni

tude

on

obse

rved

cha

nges

in D

i.

SECTION 3

Table32. Comparisons between grades with CE projects and grades forwhich achievement data could be analyzed.

91

eftrAINre. ir-eNn WILIIPLi ArLIICVMS.ACAITVIVAUC.) n...i . vvniLn m..n1LvLovu.1,41

TEST DATA WERE ANALYZED

r`CI A MCC 1A/L11/"LI LIMN..-m.1....1 vvill....11 I ir-,..,

CE PROJECTS

ji Pre (9/65) Post (9/66) 65-66

-MO

1 66-67

3,4 3,4 K-2 K-2

3,4 3,4 K-2, 1-6, K-2, 1-6

3-6° 3-6°

- - K-2, 1-6 K-2, 1-6

4 3 3 K-2 K-2

5 3,5 3,5 K-2 K-2, 3-6°

6 3 3 K-2, 1-6° K-2, 1-6,

3 3 K-2, 1-6° K-2, 1-6,

1-6°

8 3 3 K-2 K-2, 3-6°

9 3 3 K-2 K-2, 3-6°

10 3,5 3,5 K-2 K-2

Note:

°Projects which had at least some reading emphasis.

School 1 illustrates the situation of minimum pupil exposure,about one month, in a CE project which added limited amounts ofpersonnel, materials or equipment to the school program. A pupilin School 6 who was in a 3rd grade in 1965-66 and progressed tothe 4th grade for the following year might have received 5 or 6

months of exposure in a language arts activity. In this school,the CE expenditures were greater in absolute and relative terms.A similar pupil in School 2 could have received about the samelength of exposure in a project with definite reading orientation.Per-pupil expenditures for CE projects were greater in School 6

than in other schools of the sample (see Table 28).

Finally, because achievement tests were given in the fall(September 1965 and September 1966), only a limited amount ofexposure to CE activities could be represented by the test data.

92 67TMP-115

For projects initiated soon after Title I funds were made available in1966, pupils could have received as much as five months of exposureprior to the post test. If they participated in the summer reading pro-ject also, a maximum of 7 months exposure c.)uld be obtained. Sinceno project was a full-time activity, it is improbable that more than afew pupils received as much as 7 months of part-time exposure to CEactivities.

Summary of District 10 Case Study

This case study required about eight man-weeks of effort after thedata had been obtained. A return trip of about one week would be re-quired to verify the expenditure estimates. Similar studies of otherschool districts probably would require greater effort and time.

Several observations can be made about this study of CE programsof one school district:

1. No obvious relationships were found among pupil mobility, theproportions of Negro pupils in the sample schools, and at-tendance rates.

2. It was not possible to determine if CE projects had any impacton pupil attendance rates. More detailed data would be requiredto eliminate the impacts of other factors.

3. Half of the ten CE programs of this school district added modestincrements of personnel, materials, or equipment to the activi-ties of a school. It will be very difficult to discover the impactof these resources on pupil performance, as measured by testsof reading achievement.

4. Change of reading achievement may be very difficult to measureat the grade level. Only one CE project had a primary and di-rect focus on reading achievement, four others had varyingdegrees of reading orientation. Only a fraction of pupils in agrade, probably less than 25 percent, received direct impactof these projects.

5. Considerable variation of per-pupil expenditures was noted.In some cases, the variation of the pe- apil expenditure of theregular school program from year tc ar exceeded the CEincrement for either year.

6. No significant change of reading achievement was found and norelationships were discovered between change of reading testscores and type of CE activity or level of expenditure. Therewas little reason to expect substantial change in view of Vie un-limited amounts of pupil exposure represented by the pre-posttest period.

7-

SECTION 3 93

7. When detailed project information and expenditures dataare known by project and school, the allocation processis not particularly difficult. If either type of informationis lacking, it may be impossible to obtain reasonablyaccurate estimates. Without such accuracy, the probabilityof gaining meaningful results from cost-benefit compari-sons is extremely limited.

ANALYSIS OF DISTRICT 13 CE PROGRAMS

This section summarizes CE activities of District 13, describesthe selection of sample schools, presents the method used to esti-mate CE resources at the grade level, describes the characteristicsof CE projects, summarizes CE project expenditures for two gradesin each of two schools, and compares these expenditures with changesin achievement test scores.

Background of District CE Activities

Compensatory education in School District 13 consists primarilyof the comprehensive program funded under Title I, ESEA supple-mented by other federal, state, and local CE activities. For the1965-66 school year, 26 activities were organized into foiir projects:Pre-kindergarten, Remedial and Corrective Basic Skills Develop-ment, Cultural Enrichment, and S.....pportive Auxiliary Services.*Twenty-three public elementary schools and nine public secondary,continuation or adjustment schools with total enrollment of 25, 500students were included, plus four elementary parochial schools andone secondary parochial school, totaling about 2, 000 students. Thepublic schools served census tracts in which 7 percent to 22 percentof the families reported incomes under $2, 000 in 1959. In the fol-lowing year, one public elementary school and one public secondaryschool were added. Title I funding of the pre-kindergarten projectwas terminated. Budgets for these projects are shown in Table 33.

Title I projects and funds were approved early in 1966. Imple-mentation was delayed by non-availability of staff or equipment andby construction or procurement lags. Deviations from original plans

4.4"r The district reported 37 CE activities. These were summarizedto 26 for this study.

94

Table 33. Title 1 project budgets in District 13.°

67TMP-115

1

Project1

1965-66 1966-67

Pre-kindergarten $ 243,000 0

Remedial & Corrective Skills 1,075,000 911,000

Cultural Enrichment 486,000 79,000

Auxiliary & Supportive Ser. 668,000 994,000

Overhead & Fixed Charges 130,000 227,000

TOTALS $2,602,000 $2,211,000

Note:a Data were obtained from District CE plans of December 1965 and

July 1966, and from the 1966-67 Title I budget status report ofJune 1967.

were sometimes required, but expenditures for 1965-66 were re-ported as reasonably close to the budget amounts. In 1966-67 areduced budget was approved and commitment of financial supportwas not received until after the beginning of that school year. Thiscaused some disruption to the current program including some re-ductions to meet the lower budget level.

In addition to the Title I projects, this district has pursued otherCE activities with federal, state, and local support. In 1963-64and 1964-65, a pilot project was conducted in five schools, and pro-vided a wide range of activities at a funding level of $50,000 per year.A second State CE program, initiated in 1966-67, provided a three-part effort to reduce elementary school pupil-teacher ratios, buildfacilities at nine elementary schools, and provide a demonstrationreading program in one junior high school. In 1964-65 a counselingproject, supported by National Defense Education Act and local funds,was operated in several secondary schools, and provided servicesapparently similar to the Title I program.

41

SECTION 395

Sample Schools and Their Characteristics

Data on the following school and pupil characteristics wereexamined: percent eligible pupils, percent Negro pupils, percentSpanish speaking pupils, school enrollment, numbers of instruction-al personnel, and pupil mobility. Insofar as possible, schools wereselected to represent a wide range of these characteristics in orderto determine whether relationships exist between the outcomes of CEactivities and characttrisitics of the recipient pupil population. Thesecharacteristics are summarized in Table 34.

Seven elementary and four secondary schools were selected. Theseschools had enrollments from 423 to 1,918 pupils and employed from17 to 86 teachers. School populations consisted of from 11 to 91 per-cent Negro pupils and from 7 to 84 percent Spanish speaking pupils.From 8 to 19 percent of the pupils in these schools were from familieswith income under $2, 000 per year. Pupil mobility* in the sampleschools ranged from 16 to 79 percent.

bescriptions of CE Activities

This district has pursued a wide range of CE activities, some pre-ceding and others in addition to those made possible by Title I, ESEA.To estimate the allocation of resources to grades requires knowledgeof the several CE activities of the district; but their large numberprecludes detailed discussion of each one. The following paragraphspresent brief descriptions of District 13's CE activities. Thirty-sevenactivities, identified by the district, have been summarized to twenty-six activities for this study. In the process of summarizing, someactivities were combined and others, which did not serve pupils inelementary and secondary 1.des, were excluded, e.g., pre-schooland adult education acti-

Remedial and Corrective Basic Skills Activities

PRIMARY REMEDIAL READING. To provide remedial reading as-sistance to children of average or better ability but who are underachievers. This program has been provided for grades 2 and 3 for

*Defined as: (total students entering or withdrawing from a school

during the 2nd through the 9th month of the school year) (averageschool enrollment during the school year).

Tab

le 3

4.S

ampl

e sc

hool

cha

ract

eris

tics,

196

5-66

.

Sch

ool

Cha

ract

eris

tics

Sch

ool N

umbe

r

I2

34

51

67

89

1011

Enr

ollm

ent

825

601

546

851

423

830

821

1085

1603

1360

1918

Inst

ruct

iona

lP

erso

nnel

2420

1732

1529

3252

7862

86

Pup

il M

obili

ty (

%)

7977

6156

3978

5638

4632

16

Neg

ro P

upils

(%

)8

2456

8011

4491

7059

6923

Spa

nish

Spe

akin

gP

upils

(%

)14

2111

1284

407

1432

1623

Per

cent

of P

upils

from

fam

ilies

with

inco

me

unde

r $2

000/

yrin

195

9

810

1212

1819

1910

1510

9

.I

, ,,,

SECTION 3 97

several years with district funds; Title 1 support permitted expansionof this program to provide additional teacher specialists for eligiblepublic and parochial schools and to include pupils in grades 1 and 4.

READING ADJUSTMENT CLASSES. To help students in grades 7and 8 who have average or better intelligence but whose readingachievement is at least 2 years retarded. Reading problems werediagnosed and pupils placed in groups of 8 under 2 teachers withspecial training or experience. Teacher aides and additional equip-ment were provided. Title I fun.Ls supported this project in 3 schools.

REMEDIAL READING. Similar to the above project, to meet needsof pupils in grades 7 to 12 with lesser reading retardation, in groupsof 15 to 18 pupils. Already a distr'ct-supported project, ESEA fundsprovided additional classes in 6 schools.

ENGLISH AS A SECOND LANGUAGE. To help non-English speakingpupils to develop fundamental English language skills and to preparethem for regular school programs. An aural-lingual approach wasused at beginning, intermediate, and advanced instructional levels.A class of 18 pupils was provided with ._' teacher aide or assistant,tutors, materials, and equipment. Some portable classrooms wereobtained. This is an expansion of an existing project.

CLASSES FOR EDUCATIONALLY HANDICAPPED PUPILS. A re-mediation project to provide more attention to problems of academic-ally handicapped pupils of average or graater ability but retarded inbasic skills. Small groups of pupils (15-20) in elementary gradeswere assigned to a teacher on a full-day schedule. A resource teach-er, materials, in-service training and portable classrooms wereprovided. Title I funds enlarged an existing activity.

Cultural Enrichment Activities

CULTURAL ENRICHMENT. A number of activities were providedto motivate and stimulate elementary and secondary pupils of dis-advantaged areas, inclueing: art and music classes, enrichedsummer session and Saturday classes for talented pupils, assemblyprograms and cultural exchange, study trips, oral communicationsskills festival, equipment for remedial use and cultural enrichmentin business education, and equipment for instruction in home manage-ment and personal development.

98 67TMP-115

LIBRARY SERVICES. ESKA. funds were used to expand a modestdistrict program-to_provide and equip libraries in elementary schoolsand secondary target area schools and to provide personnel forgreater library availa.bility.

CLASSES FOR MORE ABLE PUPILS. More able pupils in grades3-6 were grouped into an enriched and accelerated program in fourcenters. A resource teacher, field trips, visiting teachers, specialequipment, and in-service training wr:re provided.

Auxiliary and Supportive Services Activities

HEALTH SERVICES. Speech and hearing teachers were hired to in-crease speech and hearing therapy in Title I schools. Additionalnurses and a clerk were added to increase nursing time provided atTitle I schools.

COUNSELING PROJECTS. Five program activities provided addi-tional professional or clerical personnel and materials to intensifycounseling toward solving academic, mental, or social problems ofpupils and parents.

AUXILIARY TEACHER SERVICES. After a pilot project, additionalteachers were appointed to assist classroom teachers by: substitutingfor the regular teacher to permit small group instruction; lessonplanning; providing remedial reading instruction to individual pupilsor small groups; serving in the library; confering with parents; andassisting in school/parent/community activities.

TEACHER ASSISTANTS, AIDES, AND CLERKS. Assistants, aides,and clerks were provided in selected secondary and elementary tar-get schools to relieve teachers of non-instructional classroom dutiesor clerical work and to permit more individualized instruction.

KINDERGARTEN AIDES. After a successful pilot project, parenthelpers were employed as teacher aides to alleviate some of theproblems of overcrowded classes in project schools. They helpedto prepare instructional materials, to improve the classroom environ-ment, and to supervise classroom and playground activities.

SECTION 3

EXTENDED TIME AND TRAINING ACTIVITIES. Three programactivities provided for orientation and in-service ft-a...fling of new

teachers and for continuing professional advancement through con-

ferences, courses, and workshops.

99

ADMINISTRATIVE SERVICES. Target schools have more office

referrals by teachers and administrative transactions. Vice prin-cipals were appointed in target area elementary schools to strengthenadministration and permit the principal to devote more attention to

curriculum development.

CENTRAL OFFICE ACTIVITIES AND FACILITIES. Two projects

were defined to provide for centralized district office services and

facilities. One described capital outlay for remodeling, construction,

or relocation of portable classrooms employed in projects describedabove. The other provided funds for administrative and support ser-vices of central offices which were necessary for the management,coordination, and evaluation of the overall CE program.

Other CE Activities

1963-64 PILOT PROJECT. A pilot project was initiated in 1963-64

in three elementary and two junior high schools to improve communi-cation skills and motivation, to aid pupils in understanding theirabilities, to strengthen teacher understanding of pupils' problems,to improve school relations with parents, and to provide pre-schoolexperiences.

STATE CE PROJECT. In 1966-67, a state-district supported pro-ject was pursued in nine elementary and one secondary school to

reduce pupil-teacher ratios and to obtain portable classrooms. Ademonstration reading program was initiated in one junior high school.

NDEA COUNSELING PROJECT. During 1964-65 and 1965-66, acounseling project was supported in several secondary schools byNDEA funds to raise educational and vocational aspirations, to in-crease home-school contacts, and to motivate pupils to remainschool. Activities included extended individual and group guidance

sessions with pupils and a parent participation program.

Description of the Analysis

The approach pursued in this case study was designed in accord.-

ance with the type and volume of available program information and

100 67TMP-115

expenditure data. As defined at the district level, many CE "activi-ties" actually were resource inputs to a CE project. It was necessary,therefore, to examine several sources of information such as projectplans, activity descriptions, budget documents, and evaluation reports,in order to arrive at an operational description of a project at theschool and grade ley&

Financial re...ords did not distinguish expenditures by schools.Special accounting for Title I funds employed resource categories(e.g remedial reading teachers, teaching equipment) and schooladministrative divisions: elementary, secondary, student services,curriculum services, post high school, and overhead. The CE pro-.jects were subdivided by the district according to types of servicesprovidea: pre-kindergarten, remedial and corrective development,cultural enrichment, and auxiliary and supportive services. It was thennecessary to define the CE activities pursued in a grade, to cumulatea catalog of resource inputs from several sources, and to estimatetheir costs. Use of district-wide cost factors was required, such e saverage teacher salaries and per-pupil expenditures for instructionalmaterials or equipment. School and district personnel reports werea primary source of resource data.

A data form was designed on which to record information soughtfor subsequent regression analyses. This form permitted aggrega-tion of info,mation at three levels: all eligible schools, a particularschool, and a selected grade. The following time periods were usedas needed; the school years ending June 1965, 1966, and 1967; sum-mer sessions 1965 and 1966. In addition, since Title I began in themiddle of school year 1965-66, a separate time period, Spring 1966,was used for ar:tivities which occurred only in the latter half of thatschool year. The 26 CE activities identified in this study were thencategorized into ten types of projects to pe7mit comparisons on abasis more consistent with projects of other districts. They were:

1. Remedial reading and language arts

2. Other specific instri..ctional projects (e.g., math, science)3. Administrative changes, such as team teaching or modular \

scheduling

4. Vocation-related projects5. Staffing increments not related io specific instructional

pro:acts

SECTION 3

6. Non-instructional equipment and supplies

7. Staff development

8. Health and guidance services

9. Community-parent services10. Cultural enrichment.

Finally, characteristics of staff, students and activity costs wereincluded as follows:

1. Number of equivalent full-time teachers, by period2. Number of direct pupil beneficiaries

3. Ave7age size of participating ?upil group

4. Average hours/week per participant5. Weeks of project exposure per pupil

6. Instructional salaries7. Other expenditures.

101

A brief description was prepared for each of the 26 CE acti.itiesand the data form was completed for each grade in the sample schools.An attempt was made to provide the required quantitative informationat the lowest organizational level for which program information wasavailable. When possible, these quantitative descriptions were basedupon specific information at the grade level. When grade level datawere lacking, school or district level information was used to allocateexpenditures to grades, employing the following assumptions:

1. The number of children in a grade was defined as the total ofpupils listed in active enrollment reports of that grade pluspupils in ungraded classes allocated to that grade by progr..1mcoordinators.

2. Allocated staff positions were considered filled.3. Services described at the school level were applied on a per

pupil basis, as appropriate.4. Budgeted amounts were used to estimate expenditures.5. Information provided in CE program descriptions was accepted

as describing the CE activities.

1

102

The allocation process revealed that many uncertainties still ex-isted on the part of the authors with respect to information concerningservices received, despite the fact that this district was chosen forhaving relatively complete records.

Illustration: Primary Remedial Reading

This illustration demonstrates the methods for estimating CE re-sources at the grade level for a specific activity. The particular casereflects the general observation that the actual application of CE re-sources varies widely among schools and grades in terms of absoluteamounts of CE activities undertaken. Further, considerable varia-tion also exists within a grade through time.

For a number of years prior to Title I, District 13 has conducteda remedial reading program for second and third grade "underachievers"of average or better ability. This program provides specially trained.remedial reading teachers in all elementary schools. These teachersare assigned on a half-day, nine-week basis through the 36 week schoolyear. They work with groups of 10 children for one period each day.These sessions are in addition to regular classroom work in reading.In theory, a child participates in the program for nine weeks, returnsto his regular schedule for nine weeks, and then, if necessary, re-ceives nine more weeks of remedial help.

With the addition of Title I funds, six remedial reading teacherswere added to intensify existing services to eligible public and pa-rochial schools. From February to June, 1966, this supplementalprogram was divided into three six-week sessions, serving grades1-4. Pupil participants were selected by staff members of theschools. During the 1966-67 school year, a state-funded programprovided additional teachers for this remedial reading program.These teachers were not assigned to target area schools, but toother scIlools in the dist-ict. To perform the required calculations,the following steps were taken and assumptions made:

1. Estimates of instructional staff were derived from districtrosters of Primary Remedial Reading teachers. Each'eacher is assigned to a school on a half-day (three periodsor less) basis. Normally the school year is divided intofour nine-week periods of instruction. Thus, it was assumedthat staff were added in increments of one-eighth (one-fourthyear x one-half day) of a Full-Time Equivalent (FTE) teacher.

SECTION 3 103

How , the 18-week first semester of Title I was dividedinto 3 equal parts, which yields a FTE factor of one-twelfth(one-sixth year x one-half day).

2. Salary extimates were based on average regular teachersalary in 1965-66, $8,100.

3. Salary costs were apportioned on the basis of the number ofpupil participants in a grade.

4. Other costs of the program were considered insignificant, asreported by the program director.

5. Pupil participation by grade and school was obtained fromreIN-Irts made by the teachers.

Table 35 contains the results of the above calculations for this CEactivity in one sample school. It illustrates the amount and variationsof CE resources among grades and time periods. Similar tabulations,not shown here, of grade level expenditures for other activities andschools indicate that similar variations cften occur. One reason forthese observed variations is the fact that, although some activitiesmay apply equally to all eligible pupils, others apply only to certainpupils, grades or schools. Some activities contin-ted at the samelevel with the initiation of Title I support; others expanded.

These variations were compounded by changes in the numbers ofregular classroom teachers and in pupil enrollment. Examples ofthese variations are included in the following detailed studies of theCE activities and achievement changes of selecteu fifth and sixth gradecohorts of pupils.

Case Study of Sixth Grade Cohorts

Until the grade level descriptions are more fully verified, it ispremature to examine in depth the relationship between CE inputs andpupil performance. However, it is possible to illustrate the types ofcomparisons that could be made by the following case study. In thestudy, summaries of CE expenditures were made for fifth and sixthgrades in each of two schools where a sharp contrast in achievementtest results was noted. The cha.:ges of mean achievement were asfollows (1966-67 scores minus 1965-66 scores in Standard T units):'

The Reading subtest of the Stanford Achievement Test was used forthe sixth grade and the Paragraph Meaning subtest o: the SequentialTest of Educational Progress for thefifth grade.

104

-

67TMP-115

Table 35. Estimated CE resources for primary remedial readingSchool 3.

TimePeriod' Grade

Ful 1 -Ti me

EquivalentTeachers

PupilParticipants

Estimated

I Expenditurec

1 0 0 0

1964-65 2 0.2 21 $1300

3 0.1 10 700

4 0 0 0

1 0 0 0

1965-66d 2 0.2 19 1300

3 0.1 12 700

4 0 0 0

1 0.1 20 500

1965-66 2 0 0 0

Title I peri od 3 0 0 0

4 0.0 10 200

1 0.1 21 700

1966-67 2 0.2 31 2000

3 0.3 30 2000

4 0.1 10 700

Notes:

°Project not pursued during summer peliodsbThe activity was designed for groups of 10 pupils to receive 5 hours/day ot re-

medial instruction for 2 alternate quarters/period,. During the Title 1 portion of

1965-66 three 3-week classes weie added, and in 1966-67 there was consider-

able irregularity in schedulingc Based on a constant average teacher salary. Other costs were considered

negligible.d Listed here are activities which extended throughout the academic year.

eListed here are activities restricted to the special time periods established when

Title 1 began in the spring of 1966.

SECTION 3

IN Mean AchievementSchools Grades

5 6

5 -1. 1 +1 . 2

7 -3. 4 +5. 7

Difference +2. 3 -4. 5(School 5 m'-zus School 7)

105

There are three observations which should be made wit!, respectto this table:

1. At the sixth grade level, School 7 showed a considerable gaincompared to School S.

2. At the fifth grade level, both schools showed a decline inachievement, with School 7 showing a greater decline thanSchool 5. The difference between the declines experiencedby School 5 and School 7, however, is quite small.

3. Between the fifth and sixth grades a reversal of the relation-ship between School 5 and School 7 occurred. While at thefifth grade level, the difference between the schools is notlarge, the absolute total of the differences for both.gradesis substantial. However, it should be noted that the com-parisons for 5th and 6th grades are not independent. Theearlier fifth grade class in the 5th grade comparison is thelater 6th class in the sixth grade comparison. Thus, anunusual early fifth grade class could, by itself, have accountedfor the change in the direction of the relationship between the-

fifth and sixth grade classes. This lack of independence,while it affects the reliability of conclusions reached on thiscase study, nevertheless illustrates how CE expenditurescan be compared with achievement test results. Other com-parisons, such as the absolute magnitude of the changes, arenot appropriate due to different test dates, test intervals, ortest forms.

In developing estimates of resource inputs, the grades were viewed

as cohorts, i. e., groups of pupils which receive a sequence of ex-perience through time. The ideal cohort would have stable member-ship throu6 time, but these groups did have changes of membership.For these comparisons, the 6th grade cohort refers to classes which

move from grade to grade and were in the 6th grade when tested inrespective years. Therefore, when considering a sixth grade cohort,

106 67TMP-115

the services received when this group was in the fifth grade must alsobe borne in mind.

Differences of CE services provided to the two cohorts were ex-amined in the grade tested and in earlier years. The types of com-pensatory education activities provided to the sixth grade cohorts atSchools 5 and 7 are shown in Table 36. There were many activitiesserving both groups of sixth graders. However, for many of thesethere is no basis for differentiating between the experiences at thedifferent schools; information was district wide and therefore pre-*sumably applied equally in the two schools.

For this illustration, it was assumed that the types of compensa-tory education most likely to be related to reading achievement testscores are: (1) Remedial Reading and Language Arts, (2) Other Spe-cific Instructional Programs, and (3) Staff Increments. Consequently,the analysis was restricted to these three types of CE activities; thespecific activities of these types which were considered in this analysisapp_ar in Table 37. The procedures used in combining expendituresare given below, and include the various assumptions which had to bemade.

The following procedures were used in summing expenditures for6th grade cohorts. The expenditures discussed are summarized inTable 37.

1. To make descriptions at the level of the district or the schoolapplicable to particular grades it was necessary to allocatesuch services on a per pupil basis. Table 38 shows demo-graphic characteristics of the successive 6th grades at Schools5 and 7. For the purpose of comparing services in the ele-mentary schools of different size, vve assume no differencein per pupil level of service unless there is contrary evidence.

2. It is assumed that the CE services which occurred in the yearpreceding the achievement tests are those which have impactupon the achievement test scores. For the sixth grade thetwo sets of achievement test compared are those administered

ert

Whether services were designed to be equal for all pupils or equalfor all schools would make a difference. It was assumed that serviceswere provided on a per pupil basis.

Tab

le 3

6. C

E a

ctiv

ities

ser

ving

six

th g

rade

coho

rts

and

leve

ls o

f det

ail o

f ava

ilabl

ein

form

atio

n.

CE

Act

ivity

Per

iod

of S

ervi

ces

Pro

vide

dLe

vel o

f Det

ail

Sch

ool 5

64-6

5 65

-66

66-6

7

Sch

ool 7

64-6

5 65

-66

66-6

7

Eng

lish

as S

econ

d La

ngua

geE

duca

tiona

lly H

andi

capp

edR

eadi

ng C

linic

Aud

io-V

isua

l Equ

ipm

ent

Impr

ovin

g In

stru

ctio

n in

R&

CS

kills

aF

acili

ties

for

Rem

edia

tion

Cla

sses

for

Mor

e A

ble

Libr

ary

Ser

vice

sC

ultu

ral E

nric

hmen

tC

entr

al C

E S

ervi

ces

& O

verh

ead

a

Inte

nsifi

ed V

isiti

ng T

each

er S

ervi

ceG

uida

nce

Clin

ic°

Add

ition

al N

ursi

ng S

ervi

ces

Aux

iliar

y T

each

er S

ervi

ces

Ele

men

tary

Sch

ool A

dmin

istr

atio

n S

ervi

ces

Tea

cher

Ass

ista

nts

& A

ides

Res

ourc

e H

elp

to N

ew T

each

ersa

Add

ition

al C

leric

al A

ssis

tant

sIn

-Ser

vice

Edu

catio

n°C

urric

ulum

Dev

elop

men

t°S

tate

P/T

Red

uctio

n P

roje

ct

xx

xx x

xx

xx

x xx

xx

xx

xx

xx

xx

xx

xx

xx

xx

xx

xx

xx

x x

xx

x xx

xx

xx

xx

x xx

xx

xx

xx

xx

xx

xx

xx

xx

xx

xx

xx

xx

x x

Sch

ool

Gra

deG

rade

Sch

ool

Sch

ool

Sch

ool

Gra

deS

choo

lS

choo

lD

istr

ict

Sch

ool

Dis

tric

tS

choo

lS

choo

lS

choo

lS

choo

lD

istr

ict

Sch

ool

Dis

tric

tD

istr

ict

Gra

de

Not

e:a

Exp

endi

ture

s fo

r th

ese

activ

ities

wer

e as

sum

ed to

be e

quiv

alen

t bet

wee

n si

xth

grad

e co

hort

s of

1966

-67.

.1IM

P

108 67TMP-115

Table 37. Summary of CE expenditures for sixth grade cohorts.

1

School 5, Sixth Grade School 7, Sixth Grade

e-F A,tivitiPc 1965-66 1966-67 1965-66 1966-67

English as a Second 4)et 1 CAAI JUV $1500

Language

Readi ng Clinic $1200

Educational ly Handicapped 1600 $8100 8100

Classes for More Able 2400

Auxiliary Teacher Service 300 200

Elementary SchoolAdministration Service a

Teacher Assistants and Aides 200 200

Additional Clerical Assistance 200 100

TOTALS $1500 $3800 $8100 $12200

Estimated Number of PupilsReceiving Service 54 54 68 61

Expenditure Per Pupil $28 $71 $119 $200

Difference BetweenSuccessive Cohorts $43 $81

Note:

° Negligible .

SECTION 3

Table 38. Demographic characteristics of the sixth gradesof Schools 5 and 7.

Characteristic

1965-66 1966-67

School 5 School 7 School 5 I School 7

Number of regular & adjustmentsixth graders (February) 46 62 45 58

Sixth grade pupils as percent oftotal enrollment 12% 8% 11% 8%

Sample size for achievementtests (January 1966 andOctober 1966) 34 62 42 62

Percent of sixth graders tested 74% 100% 93% 107%

[Number of classroom teachers 1 1-1/2 1 1-1/2

in January 1966 and in October 1966. For the first test, thetime interval for which to establish the level of serc:rice isfrom January 1965 to January 1966. This period includes noTitle I expenditures. For the second test, the time of serviceis from October 1965 to October 1966. This period is thesimpler to examine since it is approximately equal to academicyear 1965-66 and the summer of 1966.* This includes the"first year" of Title I. Thus, the analysis consists of a com-parison of the January 1966 scores of the cohort which was inthe 6th grade in the 1965-66 school year with the October 1966scores of the cohort which was in the 6th grade during the1966-67 school yc;ar. Since each cohort was assumed to havebeen supported by CE programs during the year preceding thetest, programs initiated after January 1966 were not consideredas having affected the earlier cohort for purposes of the com-parison, even though they were in fact applied to that cohortlater in the school year.

T For convenience, this assumption is made for all but the regularclassroom teachers' salary, which is calculated more precisely.

110 67TMP-115

3. Although English as a Second Language at School 5 was notfunded by Title I.in grade 6, this 7...:tivity was expanded byTitle I elsewhere in the district and is included in the analysis.The rate of expenditure was the same at School 5 for the pastseveral years. The service for the sixth grade cohort wasestimated as approximately 15 percent of the service given tothe school.* Even though average teachers' salary changedover years, a constant 1965-66 salary level was used for eachyear to prevent variz.tion due to cost of the service rather thanquality or amount (Referenc- 9).

4. For the Educationally Handicapped and Adjustment classes atSchool 5, there was no service prior to January 1966. Thus,there were no expenditures for the earlier cohort. For thelater sixth grade cohort, there was no service at the sixthgrae level in 1966-67. There was, however, service to thatsame group during the last half of the preceding school year,when that cohort was in the fifth grade. This service con-sisted of a class of 18 pupils drawn from the fourth throughsixth grades. More exact information about participation wasnot obtained. Therefore, one-third share of the expenditurefor this service was assigned to the later 6th grade cohort.At School 7, the same level of service existed for the fifthgrades in 1964-65 and 1965-66. Therefore each cohort re-ceived the same amount of service.

5. In School 7, Classes for the More Able were begun in Febru-ary 1966. Therefore, this service was not considered teapply to the earlier sixth grade cohort; the service for thelater sixth grade cohort was that received during the Title Iperiod of 1965-66 by the fifth grade. School 5 did not havethis service.

More pIccise estimates of the amount of service to the later andearlier cohorts would be the proportion of the total school which wasin the fifth grade in 1965-66 and the average of the fifth grade in1965-66 and the sixth grade in 1965-66. These estimates, based onFebruary enrollment figures, would be 14 percent and 13 percentrespectively. Because it is not known whether special classes orkindergarten classes were eligible for this program, an approximatefigure constant for all cohorts, was used in the present illustrativecalculations

SECTION 3 111

6. The Auxiliary Teachers Service, which began in February1966, was considered to apply only to the later sixth gradecohort of each school. Each school had a half-time auxiliaryteacher. The share of the cost which applies t^ th- Ath gradecohorts would be about 12 percent for School 5 and 8 percentfor School 7, based upon the percentage which the 6th gradeconstitutes of the school.

7. For Teacher Assistants and Aides who were assigned on 7,

per-school basis, the appropriate percentages that each sixthgrade was of the total school were applied to obtain arralloca-tion for the sixth grade cohorts. For School 7, informationabout teacher assistants in 1965-66 had not been receive(1, bythe time this analysis was performed so that the assumptionthat there were no services in that time .period is questionable.The services from teacher assistants and from aides wereadded together.

8. For Additional Clerical Assistants, the same proportions wereused to allocate service to the sixth grades. The difference inlevel of service favoring School 5 results because School 5 isa smaller school and it was assumed that there was more perpupil benefit for a given level of service at the smaller school.

9. The state project fo reduce pupil-teacher ratio began in 1966-67, and did not directly provide a sixth grade teacher.'

10. The amount for Elementary School Administrative Serviceswas negligible for the 1966-67 sixth grade cohort at School 7,the only school to which it applied.

The primary interest with respect to the expenditures of CE fundsis the change in expenditures per pupil through time. Based on the

*One teacher at Schooi 7 was actually paid from state compensatory

education funds. Since the project concerned was aimed at reducingpupil-teacher ratio in a range of grades, the particular grade assign-ment is incidental, for accounting purposes. It is more reasonableto regard the proportion of all teachers supported by CE funds as thelevel of CE services. This would amount to 20 percent in School 7and 10 percent in School 5 in 1966-67. To simplify the presentation,this CE project is included in Regular Classroom Teacher Services.

112 67TMD-115

above a4sumptions9 the amounts expended in the schools in the yearprior to the achievement tests were computed and are shown in Table37. To determine the expenditures per pupil, it was necessary todetermine the appropriate number of pupils serviced; this was per-formed as follows. For the earlier cohort, the average of (1) enrol-lment in the regular, Educationally Handicapped (EH) nid Adj,ictm,.nt5th grade classes in 1964-65 and (2) enrollment in regular, EH, andAdjustment sixth grades in 1965-66 was used. For the later cohort,enrollment in regulars EH and Adjustment fifth grade classes in1965-66 was accepted. The number of pupils serviced is shown inTable 39, and the cost per pupil for each cohort is shown in Table 37.The.level of CE services, as represented by expenditures per pupil,rose almost twice as much for the 6th grade cohort of School 7 be-tween 1965-66 and 1966-67 ($81 per pupil) as it did for the samecohort at School 5 ($43 per pupil).

Any comparison cf services to pupils provided by different schoolswould be incomplete if it were resti.cted to CE programs and failedto consider possible differences in regular classroom instructionfurnished by those schools. In order to provide for the support fur-nished by regular classroom teachers, it was necessary to cost theirservices for the relevant time period, i. e., the year preceding thetwo achievement tests. Since this service represented a.larger sumof money than was involved in the CE program, the approximationsof the support period used for the CE programs were considered toogross, and a more precise period was employed. In order to coincidewith the support periods for January 1966 and October 1966 test dates,the time periods used were:

Earlier cohorts:

Later cohorts:

The number of teachers

1/2 fifth grade 1964-65 academic year + 1/2sixth grade 1965-66 academic year8/9 fifth grade 1965-66 academic year + 1/9sixth grade 1966-67 academic year

at each grade level each year was:

School 5 School 71964-65 1965-66 1966-67 1964-65 1965-66 1966-67

Grade 5 1-1/2* 1-1/2 1-1/2 2 2 2-1/2

Grade 6 1 1 1 1.-1/2 1-1/2 1-1/2

* Fractional teachers arise when pupils from two grades are assignedto a teacher.

Tab

le 3

9.R

egul

ar c

lass

room

teac

her

expe

nditu

re fo

r si

xth

grad

e co

hort

s.

Sch

ool 5

.S

choo

l 7

Six

th G

rade

in 1

965-

66S

ixth

Gra

dein

195

6-67

Six

th G

rade

in 1

965-

66 in

Tea

cher

sal

ary

per

coho

rtin

yea

r pr

eced

ing

achi

vem

ent

test

s

Est

imat

ed n

umbe

r of

pup

ils in

coho

rt w

hen

rece

ivin

g se

rvic

e

Tea

cher

sal

ary

per

pupi

l

$10,

100

(24

+ 3

0)

$187

$11,

650

54

$216

$14,

150

(32

+ 3

6)

$208

Diff

eren

ce b

etw

een

succ

essi

veye

ars

(196

6-67

1965

-66)

$29

$50

Diff

eren

ce b

etw

een

scho

ols

$21

Not

e:a

Six

th G

rade

1966

-67

$15,

744

61

$258

^,11

1

For

196

6-67

, the

enr

ollm

ent o

f the

six

th g

rade

coh

ort i

s: fi

fth g

rade

reg

ular

and

adj

ustm

ent p

upils

in F

ebru

ary

1966

.F

or 1

965-

66, t

he e

nrol

lmen

t of t

he s

ixth

gra

de c

ohor

t is:

1/2

(si

xth

grad

ere

gula

r an

d ad

just

men

t pup

ils in

Oct

ober

196

5) p

lus

1/2

(fift

h gr

ade

regu

lar

and

adju

stm

ent p

upils

in M

arch

196

5). T

he g

rade

dis

trib

utio

n of

Adj

ustm

ent c

lass

es p

rovi

ded

by E

xcep

tiona

l Chi

ldS

ervi

ces

Offi

ce w

as g

ener

ally

acc

epte

d, a

nd a

pplie

d to

the

enro

llmen

t fou

nd in

the

Rep

orts

of

Act

ive

Enr

ollm

ent.

CZ

114 67TMP-115

Thc cos,. of teacher services was priced at the average elementaryschool teacher salary in 1965-66, $8, 100,

The calculations of teacher service for the 6th grade cohortswere:

School 5 in 1965-66 1/2 x 12100 + 1/2 x 8100 = $10, 100

School 7 in 1965-66 1/2 x 16200 + 1/2 x 12100 = $14, 150

School 5 in 1966-.67 8/9 x 12100 + 1/9 x 8100 = $11, 650

School 7 in 1966-67 8/9 x 16200 + 1/9 x 12100 = $15,744

The increasing amount of service for the later cohort is due to thegreater amount of time spent at the 5-"a grade level, which has agreater amount of teacher service.

The calculations of expenditures per pupil are shown in Table 39.The greater increase in regular classroom expenditures pei pupilfor School 7 is due to the decrease in the number of pupils in the

cohort.

Table 40 summarizes the expenditures per pupil for CE and class-room teacher salary. In both amounts of expenditures per pupil andincreases over the preceding year, School 7 pupils are faring muchbetter than those in School 5. These results are particularly interest-ing because they are consistent with achievement results describedearlier in this section.

Case Study of Fifth Grade Cohorts

A similar analysis was made for grade 5 of the same schools. Inthis comparison, a different time interval for the CE service for theearlier cohorts is involved since testing occurred in October in suc-cessive years. Thus, the appropriate support period for the earliercohorts extends from October 1964 to October 1965, and that for thelater cohorts from October 1965 to October 1966. As for the sixthgrade comparisons, these time intervals were considered to includethe academic year and summer of 1964-65 and 1965-66, respectively.

Differences in CE expenditures between fifth and sixth grade cohortsoccurred for only one activity. For the Educationally Handicapped (EH)

SECTION 3

Table 40. Expenditures per pupil for sixth grade cohorts.

115

School 5 School 7

1965-66Cohort

1966-67Cohort

1965-66Cohort

1966-67Cohort

CE Activities

Regular ClassroomTeacher Salary

TOTAL

$ 28

$187

$ 71

$216

$119

$208

$200

$258

$215 $287 $327 $458

Difference BetweenSuccessive Cohorts

$72 $131

activity, the level of service to the fourth grade in School 7 was lessthan that received by the 5th grade.* (See Table 41. )

To convert the amount expended for a cohort to a per pupil levelof service, the enrollment of regular, EH, and Adjustment classesat the fourth grade level of the preceding year was taken as the sizeof the cohort receiving service.

The level of CE service increased at each school for successivecohorts. As was true for the sixth grade, the increase for the fifthgrade cohort was greater at School 7 than School 5. The difference,however, is only about a third as great as it was for the sixth grade.

*There is also a shift in level of service between 1965-66 and 1966-

67. Taking into account about 1/9 of a year (for the service in 1966-

67) at half the level of expenditure would result in increase of about$450 to the 1965-66 total at School 7. Similarly, for the sixth grademaking this alteration in time intervals would result in a subtractionof the level of service to the 1966-67 sixth grade cohort at School 7of $450. In neither case does this correction alter results appreci-ably.

116 67TMP-115

Table 41. CE expenditures for sixth grade cohorts at Schools 5 and 7.

CE Activities

School 5, Fiith Grade School 7, Fifth Grade

1965-66Cohort

1966-67Cohort

1965-66Cohort

1966-67Cohort

English as a SecondLanguage $1,500 $1,500

Reading Clinic $1,200

Educationally Handicapped 1,600 $4,000 4,000

Classes for More Able 2,400

Auxiliary reacherService 300 200

Elem. School Admin.Service a

Teacher Assistants andAides 200 200

Add. Clerical Assistance 200 100

TOTALS $1,500 $3,800 $4,000 $8,100

Est. No. pupi ls in cohortwhen receiv'Jng services 58 68 69 79

Expenditure per pupil $26 $56 $58 $103

Difference between suc-cessive cohorts $30 $45

Difference between schools $15

Note:

°Negligible.

SECTION 3

As in the case of the sixth grade cohorts, the costing of regularclassroom teachers was based on the ov.-3 year supporting periodprior to the date of the achievement tesi. Since achievement testswere given in October, the support perio..1 consisted of eight monthsof the preceding school year and only one month (September) of theschool year in which the test occurred. The time periods used were:

Earlier cohort: 8/9 fourth grade services in the 1964-65academic year + 1/9 of fifth grade servicesin the 1965-66 academic year.

Later cohort: 8/9 fourth grade services in the 1965-66academic year + 1/9 of fifth grade servicesin the 1966-67 academic year.

Levels of teacher service varied, in number of teachers assignedper grade level, as follows:

School 5 School 7

1964-65 1965-66 1966-67 1964-65 1965-66 1966-67

Grade 4 1 1-1/2 1-1/2 2 2 3

Grade 5 1-1/2 1-1/2 1-1/2 2 Z

Using the average teacher salary oi $8, 100, regular teacher servicefor the four fifth grade schools was as follows:

School 5 in 1965-66 8/9 X 8100 + 1/9 x 12100 = $8,544

School 7 in 1965-66 8/9 x 16200 + 1/9 x 16200 = $16,200

School 5 in 1966-67 8/9 X 12100 + 1/9 x 12100 = $12,100

School 7 in 19(6-67 8/9 X 16200 + 1/9 X 20200 = $16,644

* One teacher at School 7 was actually paid from state compensatoryeducation funds. Since the project concerned was aimed at reducingpupil-teacher ratio in a range of grades, the particular grade assign-ment is incidental, for accounting purposes. It is more reasonableto regard the proportion of all teachers supported by CE funds as thelevel of CE services. This would amount to 20 percent in School 7and 10 percent in School 5 in 1966-67. To simplify the presentation,this CE project is included in Regular Classroom Teacher Services.

118 67TMP-115

There is an increasing amount of service at each school, but when

the increases in pupil enrollment lre considered there is a sharpcontrast in changes in expenditures per pupil: School 5 rises andSchool 7 drops. (See Table 42. )

When the change in expenditures per pupil for regular classroomteachers is combined with the change from compensatory education,

School 5 is seen to have an increase in expenditures per pupil of $61,

while School 7 has an increase of $21. (See 'I. ,e 43. ) This contrastin favor of the fifth grade cohort at School 5 is also consistent with

the achievement test results.

Summary of District 13 Case Study

This case study concerned itself with two sets of cohortscohortsin the fifth grade in both the 1965-66 and 1966-67 school years andcohorts in the sixth grade in the same two school years. Two schools

were included in the analysis. For each tet of cohorts, a comparison

was made between changes in achievement test scores over the twa

years and changes in the amounts of selected resources per pupil ex-

pended on the two cohorts. The expenditures used included estimatesof both funds expended explicitly for selected GE projects and thosefor regular classroom instruction for the year immediately precedingthe test date, since it was assumed that the test scores should reflect

the services provided during that period.

The case study results showed that

1. For the sixth grade collorts, increases in expenditures perpupil at School 7 were greater than at Scnool 5. Similarly,increases in achievement test scores at School 7 were greaterthan at School 5.

2. For the fifth grade cohorts, the relationships between School 5

and 7 are reversed. Achievement changes now tend to favor

School 5, although the differe .ce is small. Similarly, the in-crease in expenditures per p-L.,3i1 was greater at School 5 than

it -was at School 7.

3. Although the difference between the changes in achievementscores Lir the fifth grade cohort at School 5 and School 7 wassmall, it represents a substantial reversal of the relationshipwhich existed between the two schools for the sixth grade co-horts. It should be borne in mind, however, that the two cohorts

were not independent, and thus this reversal might well have

been the result of the unusual performance of the cohort common

to both gm:des.

SECTION 3

Table 42. Regular classroom teacher expenditure for the fifth gradecohorts at Schook 5 and 7.

119

R

School 5 School 7

1965-66 1966-67Cohort Cohort

1965-66Cohort

1 966-67Cohort

Teacher salary per cohortin year preceding achieve-ment tests

Est. no. of pupils in cohortwhen receiving service

Teacher salary per punii

$8,544 $12,100

58 68

147 178

$16,200

69

235

$16,644

79

211

1

Difference between successiveyears (1966-67 1965-66)

Difference between schools

+$31

$55

-$24

Table 43. Expenditures per pupil rur fifth grade cohorts.

School 5 School 7

1965-66Cohort

1966-67Cohort

1965-66Cohort

1966-67Cohort

CE Activities $ 26 $ 56 $ 58 $ 103

Regular ClassroomTeacher Salary 147 178 235 211

TOTAL $ 173 $ 234 293 $ 314

Difference between successive $61 $21

cohortsI

120 67TMP-115

Approximately 12 man-weeks of effort was required to pursue thiscase study. This effort is probably representati-, of thec\time andmanpower required to develop CE resource descriptions for schooldistricts for which expenditures are not reported by school and grade.In the case study just described, the number and nature of the assump-tions required to allocate resources by grade and project were suchthat additional analysis and verification is certainly required. To dothis would require revisiting District 13 for a period of at least oneweek.

CONCLUSIONS FROM THE CASE STUDIES

Compensatory education programs of two school districts havebeen examined in detail in order to determine the feasibility of identi-fying problems in and defining the effort required for d.:tscribing CEprogram activities and estimating the expenditures of resources atgrade level, so that they might be compared with measures of pupilperformance.

Different anafytical approaches were required because of differ-ences in data obtained from school districts. In one case, districtlevel CE project information was combined with expenditure data byschool and project to make estimates of project expenditures by grade.In the other, such info-mation was not available by schools, and spe-cific detailed information had to be obtained for each kind of activityat the school and grade level. In each case study, wide variations of

s'ervices were found among schools and grades. TI- need for ex-tensive information projects and activities was confirmed. In eachanalysis, the a,isumptions and interpretations were such that the esti-mates derived should be used with caution until verified to the extentpossible by personnel in the school districts.

To illustrate the use of these resource estimates, selected com-parisons were made with measures of pupil performance. In onedistrict, no relationship was found between changes in eipendituresfor regular or CE project activities and achievern.;nt test changes.In the other district, an apparent relationship was found betweenchanges in educational services and achievement scores for a smallnumber of grades and schools.

No firm conclusions should be drawn about the relationships of CEservices and performance measures from these limited examinations.The variations of services received among grade units and of achieve-ment measures suggest that it will be necessary to seek resource-

SECTI ON 3 121

performance relationships at the grade level. Further, the complex-ity of data on CE programs and expenditures and the difficulty inobtaining the required information indicate that such analyses willrequire much effort in data gathering anu analysis.

The year-to-year variation in regular school program expendituresper pupil was found to be greater than the amount of expenditures forCE. This suggests that both types of expenditures should be con-sidered in the evaluation of the contribution of Title I funds towardsenhancement of achievement.

129 67TMP-115

SECTION 4

OBSERVATIONS, CONCLUSIONS, AND RECOMMENDATIONS

The primary objective of this study is to provide answers to the

following questions:

1. Has significant enhancement of pupil performance resultedto date from CE programs?

7 What schools, pupil and environmental characteristics areassociated with enhanced pupil performance?

3. What are the distinguishing features of successful CEprograms?

Section 2 describes the analysis performed to answer questionsi and 2. Section 3 describes the work accomplished in the firststep for developing answers to question 3.

The knowledge gained and experience encountered during thestudy have made it possible to make certain observations which arerelevant in evaluation of programs to improve education. Theseobservations are made in the first part of this section. In the secondpart, specific conclusions with regard to the basic objectives of this

study are presented. Only partial answers can be given at this timeto the first two questions, and except for analysis of level of expend-itui es, the third question has not yet been addressed. Although con-clusions from Phase I are tentative, they provide some insights intothe ultimate answers to the above questions. Furth...r, they provideguidance concerning fruitful directions that future research mighttake.

Finally, the last part of this section contains recommendations,based on the Phase I effort; which it is hoped will prove helpful toDHEW and other interested organizations.

SECTION 4 123

GENERAL OBSERVATIONS

The following observations were developed during field trips anddiscussions with officials concerned with Title I programs. Thelarge number of field .trips provided an opportunity to learn aboutthe students who are the prime target for CE, the school programs,and the views of local school officials.

Pupils Affected by Compensatory Education Programs

It was observed that although some CE programs are designedto benefit all pupils in Title I schools, many compensatory educa-tion programs are directed towards the most severely disadvant-aged pupils within each school and grade. This observation isillustrated by CE project descriptions in Section 3 and appears tobe supported by the statistical analyses of changes in achievement .

This concentration of dE service., raises a fundamental questionabout the stated objectives of Tit lc I, ESEA. Within the targetschools selected in the sample, a large percentage of pupils in eachschool are "educationally deprived." It appears that "educationallydeprived" pupils who do not happen to rank at lower achievementlevels in their respective schools are not receiving the same amountsof CE services as pupils who rankat the lower levels. This mightmean that, within the stated objectives of Title I, many programsare not yielding maximum possible benefits.

If the performance of the lowest achievers increases in propor-tion to the CE program funds provided for these students, the con-centration of funds at the lower end of the distribution might be de-fensible. If, however, diminishing returns occur (i.e. , if achieve-ment gains decline for constant increases in CE program resources),then the policy of concentrating the CE program funds on these low-est achievers may be an inefficient way to spend such funds.

It was not possible in Phase I to study the possibility of diminish-ing returns because of the very limited data on expenditures perpupil. An effort that would include obtaining regular program ex-penditures as well as expenditures for specific types of CE wouldlikely provide a range of expenditures per pupil that would be a basisfor determining the level at which diminishing returns begin.

o Wow.. wwWw. Yo..whorw owryywewhohaw.....,Aw

124

Pupil MobilityOfficials in many of the sample school districts report that a

high rate of pupil mobility exists in the inner city schools. This hasbeen verified to a large extent by the statistics accumulated to datein this study. Where this problem is found to be serious, it niay benecessary to take explicit account of it either in HEW programs orindependently by the recipient states.

Possible problems created by this high mobility rate are easy tovisualize. If a severely disadvantaged child changes schools duringthe school year, it is quite likely that the CE resources expended toupgrade him will not have been utilized in an efficient manner, underpresent administrative procedures. Schools attended during the yearmay have different types of programs, different criteria as to pupilswho are Pligible for help, and different diagnoses of particularstudent problems.

Evaluation of CE at the Local Level

All of the school districts visited have designated personnel re-sponsible for evaluating.th.e effectiveness of educational programsin their districts. Some of these positions are relatively new, per-haps the direct result of OE or State interest in evaluation, or ESEArequirements. This should be viewed as a very beneficial impactof ESEA upon future educational programs.

Schools, however, are primarily concerned with the day-to-dayeducation of their students; they are only secondailly concerned,if at all, with the conduct of rigorous educational research. Yet,if effective CE programs are to be identified and if ineffective pro-grams are to be eliminated, some research sophistication must beintroduced. Studies must be designed from the beginning, to allowconclusions to be drawn without the need for the massive datamanipulation required in this study. Care must be taken to statevery specific objectives of an educational program and, whetheror not it is a CE program, studies should be performed as experi-ments in which variables and conditions are carefully controlled.Considerable effort is required to improve data reporting and re-cording, so as to make definitive analyses possible. The typeso-1 assumptions and interpretations required to obtain the basicdata of this study are inefficient and so complex that they mayeasily yield inaccurate information.

SECTION 4

-

125

Difference among School Records

The degree to which school districts observe recommended guide-lines for records keeping was observed to vary widely. Frequ,mtdifferences of definitions were found, causing additional diffi:..titieq

in obtaining data for comparisons of pupil performance and compari-sons of expenditure levels for CE programs among the school dis-:.ricts visited. For example, some districts considered an excused

absence as "present" for attendance records, others did not. Somecomputed pupil mobility for the school year, others for the calendaryear. Records of pupil "drop-outs" employed different categories.The occurrence of ungraded schools required extra care to identifythe imputed grade level of pupils, especially for the purpose ofanalyzing achievement test scores. Differences in definitions and

forms of records require considerable extra effort in evaluation of

programs such as Title I. As in this study, data can be adjusted tobe comparable but it is probable that they adjustments reduce pre-cision of the statistical measures. Sometimes the desired data arenot available and approximations had to be accepted, e.g., the sub-

stitution of enrollment for ADM data.

Definitions of and Cost Accounting for CE Programs

Many of the school districts visited defined some of their CE

projects in terms which complicate or hamper efforts to evaluate

the true cost of the project. Some projects were defined in terms

of activities or objectives, others as resource inputs. For example

several "projects" were defined in terms of resources such as

teacher aides, community counselors, resource teachers, and in-

structional materials centers. These "project" definitions permit

simple accounting of funds but complicate identification of the full

measure of resources employed.

Financial records are seldom kept by school or project, andavailable budget and expenditure records vary in form and level of

detail. The treatment of resource inputs as separate projects tends

to hamper evaluation by fragmenting the district CE program, by

adding unnecessary complexity, and by obscuring a portion of re-

sources allocated to a project. Much effort is required to "redefine"CE projects in such a way as to clarify the appropriate measure of

performance (1. e., the objective) and to identify all of the input

resources.

126 67TMP-115

Relating Title I Expenditures per Pupil to Changes in Achievement

Although achievement test data are kept by school and grade,expenditures of Title I funds cannot be easily correlated with theachievement test results. Many school districts have test scoresfor individual pupils identified by name of pupil and the school inwhich he was enrolled but they do not have means to identify theamount of CE the individual pupils received. In some cases thetest scores are in the form of frequency functions identified only byschool in which pupils were enrolled. In this case, even if CEcould be identified for specific pupils it could not be correlatedwith achievement test scores.

Since most types of CE programs are usually oriented to only asmall percentage of the entire pupil population in Title I designatedschools the records currently being kept do not permit easy andprecise evaluation of the effectiveness of CE programs.

If schools receiving CE funds (1) would provide descriptions ofpresent and past CE projects and (2) provide a code along with eachpupil test score identifying CE programs in which the pupil hadparticipated the school district would have a wealth of information.Most schools would have less than 10 CE projects in the entireschool and a simple code could be used to identify the CE programson the test record.

Year-to-Year Variation in Test'Scores

There is a large year-to-year variation in mean test score forspecific grades within a school. The variation is much larger thanwhat would be expected from analyses of variation among pupilscores within a grade in a specific year.

In the entire sample the standard deviation of the difference inmean scores between two years was approximately twice as grea.::as would be expected bas0 on the standard deviation of test scoreswithin each year. This means that there is a large year-to-yearvariation in test ,,cores caused by such factors as quality of instruc-tion and conditions under which test is given. In essence, the dif.ference in test scores for the same grade in a schc31 in two differ.ent years appears to depend as much on differences in testing andquality of instruction as it does on differences in pupils.

SECTION 4 127

One of the causes of difference between 1965-66 and 1966-67 wasCE but this cannot, of course, account for both negative and positivechanges. The sample statistics used in this study suggest that onthe average CE accounts for only a small part of the variation be-tween the two years.

CONCLUSIONS

There are a number of conclusions that may be drawn from thestudy thus far. However, it is necessary to recognize that theseare tentative conclusions and subject to some degree of uncertaintybecause average change in achievement scores were found to besmall and sampling variation was large. Since Title I, ESEA, hadbeen in effect for a maximum of 1-1/2 years in the schools includedin the study, it was expectea that whatever benefits had accruedfrom Title I would probably be small. Moreover, the actual periodof CE exposure between 1965-66 and 1966-67 achievement tests formost students in this sample was less than one year. In addition,it was expected that sampling variation would be relatively large,due to uncontrolled factors that could cause significant differencesin test results.

Conclusions from the analyses in Section 2 are based upon resultswhichalthough statistically meaningful within the restrictive con-text necessarily createdinvolve rather small numerical values.The average change in test scores measured in grade equivalencewas less than 1 month. Hence it is possible that clanges in achieve-ment levels which seem to indicate a positive effect from Title Icould be attributable to sampling variation arising from uncontrolledenvironmental factors. On the other hand, a general downwardtrend in achievement at inner-city schools, if it exists, could under-state the amount of enhanceir At produced by CE programs.

Thus, to make an analogy with physical science the problem wasone of "detecting a weak signal in the presence of noise. " When thestatistical laws governing the noise are not completely known it isnot possible to give very precise estimates of the amount of signal.To continue with the analogy, the problem is compounded by thefact that the instruments being used to measure the signal (i.e.,standardized tests, in this case) are known to be imperfect in calibra-tion.

1

,

128 67TMP-115

The analyses described in previous Sections and the conclusionssummarized below represents the best estimate of the situation basedon the data that could be accumulated fnr thi s Q tidy. The fnl 1 (wringconclusions are useful not only as substantive findings, but as indi-cators of areas where further work would provide additional con-firmation of findings.

1. Compensatory Education programs seem to have enhanced theachievement of the students in the lowest part of their classes.*Although the performance of these students actually increasedby only a modest amount between 1965-66 and 1966-67, thereis reason to believe (see number 4 below) that they would havedone considerably worse in the absence of CE programs.(See pages 27-30.)

2. The most favorable changes between 1965-66 and 1966-67 werein those school districts which had the largest average expend-itures of Title I funds per pupil. Statistical analyses shows apositive correlation between change in test scores and amountof Title i expenditures. (See Tables 12 and 24. )

3. There appears to be a decline in mean pupil achievement levelsin the Title I schools. This conclusion was based on averagestaken over 314 school-grades in 11 different school districts.(See page 27 and Table 6.)

4. The year-to-year variation in mean achievement scores is sogreat that it was necessary to base conclusions on averagechange for several schools and several grades. This makesit difficult to interpret the importance of changes in scores.The most frequently observed change for individual grades wasapproximately two months expressed in grade equivalence.(See Appendix A and Figure 8. ) At the first decile positivechanges were more frequent than negative, but for the meanthe reverse was true. The average change at the first decilewas an increase in the neighborhood of one-fourth month ingrade equivalence .and for the mean the average change wasa decrrase in the neighborhood of one-half month in gradeequivalence. (See Tabies 6 and 7.)

*Enhancement is defined as a higher achievement level than would

have existed if there had been no CE programs. See Section 2,page 27.

SECTION 4129

5. Year-to-year changes in regular program expenditures for spe-cific grades in a school often exceeds the funds available fromTitle I. This makes it important to compare changes in achieve-ment with eXpenditures from both regular and CE programs.(See, for example, Table 29 and Figure 11.)

6. The changes in attendance between the two years were not signifi-

cant. There appears to have been several factors contributingto changes in attendance but these causes were unrelated to CEprograms. (See page 26. )

7. Changes in achievement between 1965-66 and 1966-67 were re-lated to the proportion of Negro students in a school. Thoseschools having less than 20 percent Negro student population didsignificantly better than the schools having a higher proportionof Negroes. Moreover, this relationship was similar in allschool districts. The schools in the 40-60% Negro range (1965-66)

showed the most negative change between 1965-66 and 1966-67.(See page 50 and Table 18.)Although changes in achievement were related to percent Negropupils there is no apparent relationship between changes inachievement and changes in percent Negro. (See page 54. )

8. The degree of enhancement seems to be related to the initialachievement levels of a grade school (i.e., prior to dEP); thatis, the greatest improvement came from the school grades withlowest mean achievement in 1965-66. The observation does nottake into account variations in the level of funding for CE pro-grams, thus, the . -lationship might be due to the poorer schoolshaving the highest intensity programs. (See pages 54 and 56. )

9. The eleven school districts did not change uniformly in meanachievement level between 1965-66 and 1966-67. One districtshowed some significam improvement and two districts showed

significant declines. Observed changes in each of the otherdistricts were not significantly different from zero. (See page 32

and Table 9.)

10. No strong relationships were observed between changes inachievement and poverty level, mobility, percent Spanish speak-

ing population, or size of school (ADM). However, it was diffi-cult to obtain adequate measures of poverty and mobility becauseof varying definitions employed by the several school districts.The validity of standardized achievement tests is uncertain when

the tests are given to pupils whose native language is not Englishand this abscures analysis of the relationship between percentSpanish and changes in achievement. (See page 54.)

130 67TMP-115

11. Despite the lack of significance in the mobility and attendanceregression coefficients, the consistency of their signs suggestsan area for further study. With only a few exceptions, themobility coefficients were negative (i.e., indicating a possibleinverse relationship between mobility and achievement changes)and the attendance coefficients were positive (i.e., indicatinga possible direct relationship between attendance and achieve-ment changes). (See Tables 14 and 15. )

12. Responses to CE were not uniform among grades within aschool. Most schools had some grades in which achievementincreased between 1965-66 and 1966-67 and some grades whichdeclined. This suggests that subsequent analyses should obtainand analyze data by grade level rather than using statistics onaverages for the entire school. (See pages 37-38 and 86-89.)

13. No consistent relationship was found between grade level andchanges in achievement prior to and after exposure to CE.Negative and positive changes occurred at both lower and high-er grade levels. (See Tables 16 a._ 17. ) Also, the residualsfrom the regression equations were not related to grade level.That is, the variation in achievement that cannot be explainedby the variables in the regression equations is not related tograde level.(See page 45. )

14. From examinations of CE activities at the grade level in districts10 and 13 wide variations among and within schools and gradelevels were found in expenditures per pupil (both CE programsand regular classroom instruction) and in types of CE activities.Determination, by activity, of CE services provided at the gracelevel was found to be feasible but time consuming due to the com-plexity of programs and the nature of school district records andaccounts. (See pages 120 and 121.)

15. In District 10 sample schools no relationships were discoveredbetween change-of reading test scores and type of CE activityor level of expenditure. There was little reason to expect sub-stantial change in view of the small amounts of pupil exposureto CE prior to the post test. (See Table 31 and Figure 11. ) InDistrict 13 a positive relationship was observed between changein achievement scores and educational expenditures in twogrades in two schools. (See pages 103 and 105, and 118.)

SECTI ON 4 131

The number of pupils in each of the 314 grades observed in this .

study varied from 16 to 598. Since one expects the mean score of a,large class to have less sampling variation than the mean score for asmall class two different types of averages were computed. One wasa simple average of the observed changes and the other was a weightedaverage based on the number of pupils in each grade. In general theweighted averages tend to confirm the conclusions that can be drawnfrom the simple averages. The confidence level for conclusions onthe negative change in the mean and quartiles is, however, somewhathigher in the case of weighted averages.

There appears to have been many causes of the changes in achieve-ment scores in sample schools between 1965-66 and 1966-67. Thefive state and CE program variables included in the regression equa-tions appear to explain only about 25 percent of the variation in changesin achievement. Since the only available measure of funding for CEwas very crude it is possible that better data on CE program variableswill explain considerably more of the year-to-year variation. On theother hand, there were many negative changes between 1965-66 and1966-67 that are undoubtedly caused by other than CE program vari-ables.

It is very difficult to determine the results that should be expectedat this time from the first two years of Title I. However, judgementson expected results must be made in order to make decisions on futureTitle I expenditures.

A: aough it can be costly to continue programs that yield smallreturns it can also be costly to not encourage programs that areyielding returns. It can also be costly to not experiment with pro-grams a sufficiently long time to obtain a firm evaluation.

The conclusions in this report are presented as an objective an-alysis cf available data. They do not present strong evidence ofsubstantial enhancement but they surely do not support the hypothesisof no positive effect on enhancement. The tentative conclusion fromthis study is that Title I funding has increased the amount of CE fordisadvantaged pupils and that the achievement level of pupils whohave been exposed to this increased CE has been enhanced.

RECOMMENDATI ON S

The first and second recommendations are concerned with re-search projects th,:t will give more definitive answers to the threequestions posed at the beginning of this research effort. The third

132 67TMP-115

is concerned with long-term efforts to improve evaluation of educa-tional programs. The fourth is concerned with data reporting schemesfor recipients of Title I funds.

Further Analysis of Study Objectives

It must be kept in mind that the three questions posed at the be-ginning of this study do not cover all relevant questions concerningTitle I. For instance they do not include questions on the cost-benefit ratio of CE programs, rate of increase in achievement asexpenditures are increased, or the relationship between achieve-ment in reading and the overall value of education to the individual.These are important questions, but they were beyond the scope ofthe present overall study and will not be considered in these recom-mendations.

Among the 314 observations in the sample there are several thatindicate there might have been substantial increase in achievementfrom CE. However, before selecting or rejecting observations onsome criterion of success, the following factors should be considered:first, the relation between the measure of success and the focus ofthe specific CE programs; second changes in funding of programsnot funded from Title I but which coincided with Title I; third, theportion of the pupils in each observed grade that were the primetarget of the CE program; fourth, the period of exposure to CE inrelation to the time achievement tests were given. It is iecommend-ed that follow-on research efforts, oriented towards identifying dis-tinguishing features of successful CE, be designed to collect data onall four of the above aspects.

On the question of whether significant enhanceme;:t has resultedto date from CEP there are two major aspects that require furtherstudy. Further studies should be oriented toward determining ifthere is a significant downward trend in achievement levels in schoolstypical of those now receiving Title I funding. Second, data on thesample schools must be analyzed to determine which pupils in theseschool3 actually received CE. Case studies of two school districts,presented in Section 3, reveal many instances in which CE projectswere oriented to only a very small percentage of pupils in a school.

On the question of what school, pupil and environmental factorsare associated with enhanced pupil performance, further studiesshould focus on collecting and analyzing information on the specificpupils receiving CE. The Phase I study collected considerable in-formation on schools, some information on individual grades, and.

SECTION 4 133

practically no information on specific pupils. For example, informa-tion on the mobility rate for the entire school might be a poor estimateof the mobility of the most disadvantaged pupils.

Further analysis should concentrate on two aspects of the question,namely, what characteristics are associated with local school dis-tricts' allocation of CE funds and what characteristics are associatedwith success per dollar of expenditure.

Longitudinal Studies

This study did not utilize the method of measuring the progressof individual students during exposure to specific CE programs, i. e.,the longitudinal approach. Such a procedure has great merit if timeand data are available. TEMPO recommends that DHEW initiate aproject that would apply the longitudinal approach to the problem ofevaluation of CEP. It could attempt to utilize existing data but prob-ably would need to obtain further information covering longer timeperiods. Because of the comprehensive data collection and analysistask required, this study should focus on a few CE groups ratherthan a large-scale population group.

Non-Profit Educational Research and Evaluation Organization

All of the school districts have created positions for researchpersonnel for evaluation of special programs. However, in general,it has been exceedingly difficult for these groups to attract the typeof analytical talent necessary to design the necessary informationsystems, to perform the analytical work and to recommend improvedteaching methods based on such analyses. One reason for this re-cruiting difficulty is the growing demand for such analysts through-out industry and government. It is unlikely that this demand will bemet satisfactorily for many years. A supplement (and possibly analternative) to individual evaluation groups in each of the school .

districts throughout the country is needed. No attempt will be madeto review the proposals that have been made to deal with this educ-ational evaluation problem. Instead, this report will simply addone more proposal to the growing list of alternatives.

It is the view of this contractor that a non-profit EducationalResearch and Evaluation Organization is needed and would be at-tractive to the kinds of analysts required. Because of the desire on

---.................ele,"8118,0"..........

134 67TMP-115

the part of the school districts to preserve their independence, di-rect control and total financial support by the U.S. Department ofHealth, Education and Welfare might be 1.-..ndesirable. Although DHEW,should take the lead in helping to e 't ablish such an institution, it aughtbe best for the states and school districts to support it financially.General research into innovative teaching meth.ods and evaluationcould be made available to all member jurisdictions and states ordistricts could request help in testing new techniques or in eval-uating various local programs,. This institution could also help mem-ber jurisdictions in the design of information fyysterns and thereby en-courage the development of some degree of standardization among thejurisdictions without involving DHEW. The Board of Directors shouldconsist of representatives from States, Local School Districts, Un-iversities, Industry and DHEW.

Other arrangements are feasible and might be at least as pro-ductive as the one suggested here. For example, an existing organ-izaton (such as the Educational Testing Service) might be encour-aged to assume the role of such an organization. Another alternativemight be to expand the program being developed by Ralph Tyler(the Program for the National Assessment of Educational Progress Y:to include these evaluation functions, but this might not be feasiblepolitically. Still another possibility might be to encourage the Re-search and Development Centers to take on the job.

The Research and Development Center at the University of Calif-ornia at Los Angeles already has focused upon the study of the theory,methods, and operation of activities to evaluate instructional pro-grams.

All these approaches would try to centralize the scarce talent ina single location. If some decentralization is deemed desirable, itmight be well to consider the Regional E..,ucational Laboratories.The 20 RELs already have established relations with, and are fam-iliar with, problems of the schools in their regions, and the sort ofevaluation program needed might be easier to establish through theRELs than through another agency. It is not sufficient to establishthe evaluation function; it is also necessary that appropriate data beaccumulated on a recurring basis and that evaluation results, stem-ing from these data, be incorporated into the processes of planningand managing programs, schools, and school districts. One of the

*Reference 10, pp 378-:380

. IUM MUM

SECTION 4 135

important tasks that the research organization could perform is tospecify data requirements for educational research and to developa comprehensive data bank with contributions from all participatingschool organizations. DHEW is urged to take the lead in encoragingthe States and Distr:.cts to emphasize evaluation of their programsand to establish some centralized mechanism to get evaluations done.Evaluations a r e essential if the dollars allocated to education are tobe employed effectively.

Data Collection Formats for Title I Recipients

The most severe problem encountered in this study was the lackof accurate and relevant data on CE programs and pupil-school-environmental characteristics. These data are not consistentlyand systematically recorded by the school districts. Such was thecase despite the several guidelines already provided by OE. Unlesssomething is done to remedy fhis situation, timely, accurate andmeaningful evaluation will remain difficult.

It is important to make proper arrangements so that data routinelycollected by local school districts can be utilized, thereby circum-venting the need for designing experimental progra. ';o evaluateFederally funded projects. While it is recognized that requests byFederal Government agencies, for uniform procedures raise pol-itical and practical difficulties the requirement for consistent anduniform records is considered worthy of further attention.

136

APPENDIX A

PRINTOUT OF THE DATA USED IN THE SURVEY

67TMP-115

This appendix contains a prin:out of the data used in this surveyfor the regression, co-variance, and stratification analyses. Onlygrades which had achievement test results for both 1965-66 and1966-67 were used as observations. To meet this criterion, it wasnecessary to discard many observations when a post-pre year matchcould not be made.

A total of 314 observations are shown covering 132 schools in 11district. Eleven of the 12 grades are covered there were no ob-servations for the 9th grade in any district. Grades 10 and 12 con-tain only one observation each.

An example with a brief explanation of each datum or yariable isshown on page 137.

The data are listed in ascending district, school and grade orderstarting on page 138.

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Title

1 ADM

4*<-

/ Distnct

Pre

Totoi

Title 1

District

S Post

0/ Total

Title 1

School

ADM

00.

School

Mob.

%°s,,

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Post

v % Span

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% Span

Spk Post

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ADM

Pre Grade

ADM

Post Mean

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e

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Date

Pose

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156 67TMP-115

APPENDIX B

DESCRIPTION OF VARIABLES

Because school districts vary in their administrative proceduresand classifications, identical forms of information for all districtscould not be obtained. There was, therefore, some variation inthe types of material included under any particular definition. Forexample, total Title I funds may be based upon budgeted amounts orexpenditures; mobility may be calculated during just the academicyear or for a calendar year; etc. The definitions which follow rep-resent the kinds of information we desired to obtain, and the figuresused in thisreport should be interpreted as approximations whichmay vary somewhat among districts.

Variables Description

District Title I ADM

. District Total Title I $1965-66

District Total Title I $/966-67

Grade

The average daily membei4hip of allschools (public and parochial) in thedistrict receiving Title I funds.Usually this figure was obtained fromapplication forms for Title I.

Expenditures (or budget) for Title Ifrom February through August 1966.

Expenditures (or budget) for Title Ifrom September 1966 through May 1967.

The school system classification ofgrade used for interpreting achieve-ment results. Some non-graded classeswith their appropriate grade levels wereincluded but most special classes formentally retarded were excluded.

APPENDIX B

Variables

% Negro 1965-66% Negro 1966-67

% Spanish Speaking1965-66

% Spanish Speaking1966-67

Mean Achievement TestScore - pre

Description

157

The percentage of the students in aschool identified as Negro in the dis-tricts' racial census. In cases whereno formal census was done, estimatesby district personnel were used.

District census estimats of the per-cent of the school population whichcomes from families where the primarylanguage in the home is Spanish and forwhich it is reasonable to assume thatschool performance is hampered by aninadequate knowledge of English.

The Mean Standard T score in thereading subtest or composite achieve-ment test by a specific grade at aparticular school in academic year1965-66.

Mean Achievement Test As above for academic year. 1966-67.Score - post

Change in Mean Achieve- Mean Achievement Test Score postment Test Score minus Mean Achievement Test score

pre.

Change in 1st decile, 1st As above, for the respective points inquartile, and 3rdquartile

Sample Size 1965-66Sample Size 1966-67

the achievement test score distributions.

The number of pupils in a grade at agiven school for whom achievement testdata were obtained in 1965-66 (pre) and1966-67 (post).

Attendance Rate (ADA/ Average Daily Attendance (pupil daysADM) attended divided by number of days

school is in session) divided by ADM.

Change in Attendance Attendance rate in 1966-67 minus at-Rate tendance rate in 1965-66.

158

Variables

Test Date

School ADM; GradeADM

School Mobility

Poverty Index

Average Title I dollarsper Pupil

Weighted Averages

Description

67IMP-115

Month and year achievement tests wereadministered to a given grade.

The Average Daily Membership (1965-66); as defined by the Office of Educa-tion (Reference 11); aggregate daysmembership divided by number of daysschool is in session. In some casesenrollment figures were substituted.

The sum of (a) total number of studentsentering the school after formal open-ing of the school years, and (b) totalnumber of students leaving the schoolduring the school year, the sum thendivided by the school ADM. (If infor-mation required for this definition wasnot available, substitute measureswere used.)

A ranking of Low (1), Medium (2), orHigh (3) to indicate how each schoolcompares to other Title I schools ina school district. (High means greatestdegree of poverty. )

District total Title I dollars 1965-66 plusK times (District Total Title I dollars1966-67) divided by District Title I ADM,where K is the fraction of the 1966-67academic year that elapsed by the 1966-67 test date for that grade.

The observed values of changes in themeans (AX), the 1st deciles (ADO, andthe quartiles (Li(2) are weighted by theaverage number of pupils in the pre andpost year.

APPENDIX B 159

nweightedaverage =

E .1 + m2)in

i=1 (m1

+m2

).1

i=1

[change in achievement]i

where m1

and m2 are the number of

pupils in 1965-66 and 1966-67 respec-tively (in the ith observation). Thesum of the weights add to one.

160 67TMP-115

APPENDIX C

STATISTICAL MODELS FOR ANALYSIS OF ACHIEVEMENT DATA

CONFIDENCE INTERVALS FOR OBSERVATION BY GRADE

The confidence intervals for A mean are based on the fact thatregardless of the form of the underlying distribution, the distribu-tion of the sample mean is approximately normal for large samples._ _Let X

0and X

1be the sample means in two successive years (Pre

and Post) for a particular grade and school, computed from samplesof sizes n

0and n

1,respectively. Let AX = 4^,X1 - Xo . Then, as-

-suming independence of X1 and R

0(they represent two different groups

of individuals) liX will be normally distributed with mean Sand vari-

ance a2/n0

+ a 2 /n1 = (72 (1/n0

+ 1/n1) where 6 is the true difference2in the means, and a is the (assumed) common variance. (The as-

sumption of common variances seems reasonable after observingthe small variation of the sample variances, as shown in the rawdata. Then, a 90 percent confidence interval for the true difference

6 is equal to LTC ± 1.65 s (1/n0

+ 1/n1)1/2, where s is the pooled

estimate of a, given by

s

[

2(n

0- 1) s 02 + (n

1- 1) s

1

n0

+ n1 - 2(1)

2where s and s 12 are the pre and post sample variances, respectively.0

The pooled sample sizes are never less than 30, and usually muchlarger.

\

APPENDIX C

-

161

Approximate confidence intervals for A 1 s t decile (adj.) and LI1st quartile (Lq 1) are computed from the Chebyshev inequality, andby estimating the standard deviations of the first decile and firstquartile from the equations by

ard

Sd = (1. 7094)s/n1/ 2

1

S = (1. 36 26)Sin1/2ql

respectively.* Thus, proceeding as with the b mean above,Ad

1= Ld

11- bd

10(the Post-Pre difference) has a true mean d

and variance

2

d2 2a = (1.7094) a (1/no + 1/n

1)

1

Writing Chebyshev's inequality in the form

_ d I > 1/.. a ]

(2)

(3)

(4)

and choosing X so that 1/A2 = O. 1 (i. e., X = 07, the approxi-mate 90 percent confidence interval for IS d1 is

ad1

± vro (1.7094) s (1/n0 + 1/n1

)1/ 2

, (5)

where s is the pooled estimate given by (1) above. The confidenceinterval for ,Aq

1is identical except for the constant 1.36 26 in place

of 1.7094:

± Vili (1.3626) s (1/n0 +1/n1)1/2

*See Reference 1 2, p. 243, for the origin of the two numerical

constants.

(6)

'4k

16267TMP-115

RATIONALE AND MODELS FOR MULTIVARIATE ANALYSES

Multiple regression and analysis of covariance were the two multi-variate analyses used in Phase I. They are important tools in analy-

sis of non-experimental data. They are expecially helpful when there

are large differences in so-called environmental conditions amongsample observations. These techniques not only help to identify theeffect of specific environmental conditions on the variable of primeinterest but they help to reduce sampling variation and, thereby,make tests for statistical significance more discriminating.

The regression mo-lel used in Phase I, namely

Y = a0

+ al ($) + az (M) + a3

(%N) + a4

(L) + a5

(A) + E (7)

has major limitations because of the different levels of aggregationon data for the different variables. The dependent variable (Y) wasmeasured at the grade level and was defined as change in meanachievement score or change in reading more at the lowest decile,lowest quartile, or highest quartile. The Title I dollars per student

were computed from average dollars per student for an entire schooldistrict. The mobility rate (M) and percent Negro (%N) were comput-ed for the entire school. The initial achievement level (L) is theaverage score for a specified grade in the 1965-66 test. The attend-ance rate (A) was computed for the entire school.

For the variables which were measured at the school or districtlevel the observations by grade are, obviously, not independent.This violates one of the assumptions in regression analysis and itmeans that less confidence can be placed on the estimated regressioncoefficients. For example the coefficient on the $ variable in Tables14 and 15 was, in essence, computed from seven observations, and

not 240 as indicated by the number of grade observations. With only

seven observations it is very likely that this variable is acting as aproxy variable and the estimated coefficient represents the effects ofvariables other than level of Title I expenditures.

When the model s estimated from data within a specific schooldistrict the dollars valiable ($) was dropped. The mobility and at-tendance rate variables also had to be dropped in some cases becausedata were not available.

'1

APPENDIX C

In analysis of covariance the variables M and A had to be deletedfrom the model in Equation 7 for the test of significant differencesamong schools in District 13. These variables are measured only atthe school level. This means that there would be no variation withinschools and it would not be possible to estimate the reqiiirerl statisticsin analysis of covariance for testing significant differences amongschools (see Table 44).

In analysis of covariance, the concepts of analysis of variance andregression are combined to provide a more discriminating analysisthan is afforded by either of the two component parts. The F testin analysis of covariance is designed to determine if there is a signi-ficant difference in the adjusted means of the depenctent variable amongspecified groups. The adjusted mean is calculated from the equation

adj (Y.) = Y. - E a. X. ,J J

where Y. is the observed mean for the ith group, a. are estimatedregression coefficients, and X. are the variables thak are known tocontribute to the variation in Y3 (see list of covariates in Tables 44through 47).

In essence, the observed variation in the dependent variable amongspecified groups is divided into the three components: (1) variationdue to the -:ovariates (X.), (2) variation due to factors associatedwith each group, and (3) variation due to the unknown randomcomponent. The F value in the F test is based on the ratio of thesum of the second and third components, to the third component.That is,

F =V2 + V3

V3

and the value of F in Table 44, for example, was calculated as

F = 1.416 = 4. 573. 23

In the example of Table 44, the F value is not significant at the5 percent confidence level and we cannot reject the null hypothesisthat the "school effect" contributes no significant influence on the

(10)

164 67TMP-115

Table 44. Analysis of covarianceaDistrict 13 schools (using change inlowest quartile as a measure of change in achievement).

ISource DF YY Sum-Squares Sum-Squares DF

(Due) (About)Mean-Square I

AmongSchools 10 65.5

ErrorWithin 21 132.4 71.0 61.4 19

(Total) 31 197.9 90.8 107.1 29

Difference for testing adjusted treatmentmeans 45.7 10

........--

3.23

4.57

Null Hypothesis. No difference among schools after adjusting:

F = 1.416 < F (5%) = 3.43

Note:a F or discussion of the use of covariance, see pages 34 and 163.

Table of Coefficients for Covariates:

VariableAmong Schools

CoefficientError (Within

Coefficient Std. Error T-Value

L -0.409 -0.495 0.107 -4.65

$ -0.006 -0.025 0.012 -2.11

Note:L is mean achievement level in 1965-66 and $ is effective Title I dollars perstudent (see definitions in Appendix B).

APPENDIX C 165

Table 45. Analysis of covarianceaseven school districts (using change inmean reading score as a measure of change in achievement).

e xi..I Source L.m,

1 1 Sum:,-Squares Sum-Squares DF(Due) (About)

Mean Square

AmongDistricts 6 169.8

Error(Within) 233 1214.3 350.7 863.6 230

(Total) 239 1384.2 434.0 950.3 236

Difference for testing adjusted treatmentsmeans 86.6 6

3.76

14.4

Null Hypothesis. No difference among districts after adjusting:

F = 3.85 > F (1%) = 2.90

Note:a

F or discussion of the use of covariance, see pages 34 and 163.

.


Variable Among SchoolsCoefficient

'IL

A

$

Error (Within)

Coefficient St. Error T-Value

-0.170 -0.431 0.045 -9.52

0.158 0.078 0.062 1.25

0.013 -0.004 0.113 -0.34

Note:L is mean achievement level in 1965-66, A is attendance rate, and $ iseffective Title I dollars per student (see definitions in Appendix B).

i

166671MP-115

Table 46. Analysis of covarianceseven school districts (using changein lowest deci le as a measure of change in achievement).

cnurce DF YY Sum-Squares Sum-Squares DF

(Due) (About)Mean-Square


Error(Within) 233 2366,9 253.6 2113.3 230

(Total) 239 2445.8 238.1 2207.6 236

Difference for testing adjusted treatment

means 94.4 6

9.19

15.7


F = 1.71 < F (5%) = 2.14

Note:a F or discussion of the use of covariance, see pages 34 and 163.


Variable Among SchoolsCoefficient Coefficient

Error (Within)

St. Error T-Value

L -0.136 -0.371 0.071 -5.25

A 0.240 0.098 0.097 1.01

$ 0.001 -0.019 0.018 -1.07

Note:I. is mean achievement level in 1965-66, A is attendance rate, and $ is

effective Title I dollars per student (see definitions in Appendix 8).

APFENDIX C 167

Table 47. Analysis of covarianceaseven school dktrkts (using change inlowest quartile score as a measure of change in achievement).

I Source DF YY Sum-Squares Sum-Squares DF(Nap) (Akvit)

Mean-Square


Error(Within) 233 1790.3 329.1 1461.2 230

(Total) 239 1895.3 334.9 1560.4 236

Difference for testing adjusted treatmentmeans 99.2 6

6.35

16.53


F = 2.60 > F (5%) = 2.14

Note:aF or discussion of the use of covariance, see pages 34 and 163.

Table of Coefficients for Covariates:,.......

Variable Among Schools Error (Within)Coefficient

Coefficient St. Error T-Value

L -0.149 -0.418 0.059 -6.31

A 0.164 0.050 0.081 2.54

$ 0.009 -0.019 0.015 0.36

Nate:L is mean achievement level in 1965-66, A is attendance rate, and $ iseffective T:tie dollars per student (see definitions in Appendix 8).

t.... ...................

168 671MP-115

dependent variable. By school effect we mean the net influence of allvariables associated with school. The associated variables includesuch things as type of Title I program, school facilities, and qualityof instruction.

In the analysis of covariance for the 11 schools in District 13, theamount of Title I dollars was not used for specifying different groupsbecause the only information on expenditures was for the entire schooldistrict.

In the analysis of covariance for the seven school districts it wouldhave been possible to specify different groups on the basis of expendi-tures. However, it seemed best to specify this as one of the variablesin the regression equation (i.e., one of the X. covariates in equation7 above) since numerical values for observadon on this variable arereadily available. For variables such as type of Title I programwhich cannot be easily expressed in numerical form, specification ofgroups based on type of program and the use of analysis of covarianceis an alternate to regression analysis.

The F values for Tables 44 through 47 are discussed in Section 2.It is advisable to consider more research in analysis of covariancein Phase II since time permitted only a few analyses in Phase I.

RESULTS FROM ANALYSIS OF VARIANCE AND ANALYSIS OF COVARIANCE

The summary of results from analysis of covariance were pre-sented in Table 10 in the main text. Tables 44 through 47 give fur-ther details.

Table 48 shows the results from analysis of variance among schooldistricts. The results from both the analysis of variance and analysisof covariance show a significant difference among school districts.

APPENDIX C

Table 48. Analysis of variance among school districts (LiX).

169

Sum of Squares DF Mean Square F Ratio

AmongDistricts 185 . 04 10 18.50 3.77

WithinDistricts 1508.35 307 4.91

Total 1693.39 317

F = 3.77 > F (1%) = 2.37 indicating there Li a significant differencein average change in the mean among school districts.

CORRECTION FOR EFFECT OF ERRORS OF MEASUREMENT

ON OBSERVED CORRELATION BETWEEN INITIAL TESTSCORES AND CHANGES IN TEST SCORES

Errors of measurement produce a negative correlatinn betweeninitial achievement level and change in achievement as measured,even if there is no true correlation. Similarly, any true correlationthere may be, will be obscured in the analysis of observed data.

Let the observed initial value, x, represent the sum of the truevalue,x*, and an error of measurement' el .

x = x*+ e .1

Similarly, let the measured final value, z, represent the sum of thetrue initial value, a true gain, g, and an error of measurement e 2.

z = x*+ g + e2 .

The observed difference between the two, y = z - x, becomes:

y = g + e2

- el .

(12)

(13)

The reason for the apparent negative correlation between x and y,even if x* and g are uncorrelated, is the presence of "+e 1" in theexpression for x and "- el" in the expression for y.

170 67TMP-115

Peters and Van Voorhis (Reference 13, p. 460) state that themagnitude of the correlation due simply to unreliability of measure-ment is

r = -x, y 1,11/2 (1-rx) , (14)

where rx is the reliability of the instrument used in measuring xand z. This means that if there is no reliability to the instrument,a correlation of -0.7 will be found between initial level and obs.arvedgain, and that as reliability increases the correlation due to mea-surement error alone will drop.

Thomson (Reference 14, pp 321-324) provided the followingformula to correct for errors of measurement:

=rx,,.%g

ar + x (1-r )xy a x

Y

1

aY

r [cr 2 a 2 (1-r ) - cr 2 (1-rxx y x z

where, using the terminology in (11) through (13) above,

2ae

1rx = 1.0 -2

ax

2ae

2r = 1.0 -z 2

az

(15)

(16)

(17)

The Thomson formula requires estimates of the reliability of themeasuring instrument and measures of the variance of initial value,(x) final value (z) and gain (y). At the present state of our studythere is no measure of the reliability of the test instrume.it for mea-suring achievement of school-grade units. In spite of the lack of suchestimates, it was desired to see how the measured fairly high negativecorrelation between initial mean achievement !evel and change in the

\

APPENDIX C 171

mean (i.e., -0.43 for the total of 314 observations) would be alteredwhen corrected for errors of measurement of various orders. Forthese calculations, it was assumed that el and e 2

are not correlatedwith each other or with x=:' cr g.

Usine Thomson's formula the "true" correlation between initialmean achievement level and geir -?.s calculated for various assumedlevels of reliability of test ins .:- f for grade-level observations(see Table 49).

Calculations using reliability values of 0.85 or less yielded valuesgreater than 1. 00 or imaginary numbers, suggesting that such anassumption was incompatible with the observed values of variancesor the assumption that x*, g, el, and e 2

are uncorrelated. For re-liability between 0. 9 and 1.0 the correlation between the true gain andtrus! initiall.wel differs only slightly from the -0.43 coefficientbetween the observed measures. It appears that the observed fairlyhigh negative correlations between initial level and gain in meanachievement scores cannot be attributed to an artifact of test un-reliability, but should be accepted as indicating a true negative re-lationship.

-foible 49. Relation between assumed relic; ility values of estimates ofmean test scores and "true" correlation between initiallevel and gain (when measured correlation is -0.43).

Assumed Reliability ofPre and Post Tests

1. 00

0. 98

0.95

0. 90

0.85

"True" Correlation BetweenInitial Achievement Level and Gain

-0.43

-0.42

-0.41

-0.40

Assumption not consistent withobserved values of variances

172

VARIANCE OF WEIGHTED AVERAGES

The formula for the variance of aservation is given equal weight is

V =[x. - x- ]

2

3.

n - 12

67TMP-11:

simple average where each ob-

1

The estimated variance for a weighted average such as

is given by the formula

nV = E [bij2 a 2(xi)

i=1

(18)

(19)

. (20)

In this study the x. is a parameter of a distribution of1m. pupils.

3.

The variance a 2(x.) can be3.

a21

a2m.

1

where m. is the number1

servations on the :A sets7-is only necessary to estirr

,

represented as

scores from

(21)

of pupils and a 2 is a constant for all ob-of pupils. The b. and m. are known and it.ate a2 in orderlto use tormula (20).

We know that each value oi

2m. [x.-- x ]

1 1

is an estimate of a 2. Therefore the best estimate of al is

(22)

i

1--.-AmnerMNIVILANNIIIIIIIINIIMAu..."

APPENDIX C 173

2m.

i=1

where n is the number of observations of sets of pupils.

(23)

The standard errors reported for weighted averages in Tables 6and 9 were computed by substituting the value of (V from Equation23 into Equation 21 and substituting the values from Equation 21 intoEquation 20.

671MP-115

APPENDIX D

SPECIFICATIONS OF ACHIEVEMENT TEST DATA

The following tables describe,. for four school districts (1, 3, 4and 13), the form of the achievement test data obtained and the s.:epsnecessary to convert them into national percentile scores. Thesources used for conversion were usually norms or equivalencetables provided by the publishers of the particular tests. In each con-version process the last step was conversion of percentile scores in-to Standard T scores (see Appendix F). Corresponding informationfor the remaining cities is available but has not been included.

The following is a list of abbreviations and terms used in Tables50 through 53:

Type of Test:

ITBS Iowa Tests of Basic Skills

ITED Iowa Tests of Educational Development

MAT Metropolitan Achievement Tests

SAT Stanford Achievement Test

STEP Sequential Tests of Educational Progress

Reading A subtest of the MAT, ITBS, and STEP

Para. Mng. Paragraph Meaning subtest of the SAT

Composite A summary score for several subtests used o.ithe ITED and ITBS

Ability to interpret literary materials A subtest of the ITED

APPENDIX D ,75

Forms and Batteries of Tests:

Pri. Primary battery

Int, Intermediate battery

Adv. Advanced battery

Numbers and letters refer to specific forms.

Types of Scores

Converted scores A statistically derived score used on theSTEP in order to make scores from dif-ferent forms of the STEP comparable.

Grade score, Grade Equivalence or GE Scores reflectingthe grade placement of pupils for whomthe given score is the average or norm.

Percentile score A score or rank indicating the percentageof pupils in the standardization group atthe given grade placement having scoresless than the given score.

Raw score The number of correct answers in a test.

Standard scores A raw score used on the ITED which wasconstructed to have a median of 15 andstandard deviation of 10. With the passageof time, this standard no longer appliesuniformly.

Standard T-score A score representing the placement of theindividual in a norm population cf normallydistributed scores around a mean of 50and standard deviation of 10.

Tab

le 5

0.P

repa

ratio

n of

Dis

tric

t1

achi

evem

ent t

est d

ata.

Gra

deT

est &

Sub

test

For

m U

sed

Mon

th T

este

dF

orm

of D

ata

Con

vers

ion

Pro

cess

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r to

Obt

aini

ngS

tand

ard

T-S

core

s

Pre

Pos

eP

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ost P

reP

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p 1

Ste

p 2

Pro

duct

Sou

rce

Pro

duct

Sou

rce

4S

AT

Int.

Int.

Late

Apr

i 1 2

4G

rade

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de %

i le

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r-en

d

Par

agra

ph1-

XI-

X M

ay-M

ay 5

Sco

res

Sco

res

Sco

res

Nor

ms

Mea

ning

5S

AT

Int.

Int.

Late

Mar

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rade

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de %

i le

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r-en

d%

i le

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-yea

r

Par

agra

phII-

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W M

ay6-

17S

core

sS

core

sS

core

sN

oran

Sco

res

Nor

ms

Mea

ning

(Pre

)(P

ost)

6S

AT

!nt.

Int.

Feb

.Ja

n.G

rade

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Gra

deG

rade

%ile

Mi d

-yea

r

Par

agra

ph11

-XII

-YS

core

sS

core

sS

core

sS

core

Sco

res

Nor

ms

Mea

ning

(Pos

t)T

able

7S

AT

Adv

. Adv

. Lat

eA

pril

14 G

rade

Raw

Gra

deG

rade

%i l

eY

ear-

end

Par

agra

phW

XM

ay-M

ay 5

Sco

res

Sco

res

Sco

res

Sco

reS

core

sN

orm

s

Mea

ning

(Pos

t)T

able

8S

AT

Adv

. Adv

. Lat

eD

ec.

Gra

de°

Raw

Gra

deG

rade

%i l

eB

egin

ning

Par

agra

phW

XM

ay5-

17S

core

sS

core

sS

core

sS

core

Sco

res

& Y

ear-

end

Mea

ning

(Pos

t)T

able

Nor

ms

Not

e:

aln

1966

-67

Col

lege

Pre

para

tory

cla

sses

wer

e no

t tes

ted.

To

mak

e gr

oups

com

para

ble,

stud

ents

in th

ese

clas

ses

in 1

965-

66

wer

e el

imin

ated

from

:;*

eigh

th g

rade

data

.

Tab

le 5

1.P

repa

ratio

n of

Dis

tric

t 3 a

chie

vem

ent t

est d

ata.

Gra

des

Con

vers

ion

Pro

cess

Prio

r to

Tes

t &F

orm

Use

dM

onth

Tes

ted

For

m o

f Dat

aS

tand

ard

T-S

core

sS

ubte

stP

r.,

Pos

tP

reP

ost

Pre

Pos

tP

rodu

ctS

ourc

e

4, 6

, 8IT

BS

34

Jan.

Jan.

Gra

de%

Ile19

65-6

6M

i d-y

ear

Com

posi

teeq

uiv.

scor

esda

ta to

tabl

es o

fst

ate

nat'l

.na

t'l. °

Idle

nat'l

. GE

norm

sano

rms

norm

s&

%ile

nor

ms

10, 1

2IT

ED

Y-4

X-4

Sep

t.S

ept.

%i I

e%

i le

none

nor

eC

ompo

site

scor

essc

ores

nat'1

.na

t'l.

norm

sno

rms

Not

e:a

Gra

de e

quiv

alen

t sco

res

wer

e lis

ted

in s

corin

g in

terv

als;

mid

poin

ts o

f the

sco

ring

:nte

rval

s w

ere

used

.

Tab

le 5

2.P

repa

ratio

n of

Dis

tric

t 4 a

chie

vem

ent t

est

data

.

Gra

des

Tes

t &F

orm

Use

dM

onth

Tes

ted

Sub

test

Pre

Pos

tP

reP

ost

For

m o

f Dat

aC

onve

rsio

n P

roce

ss P

rior

toO

btai

ning

Sta

ndar

d 1-

Sco

res

Pro

duct

Sou

rce

4B, 6

8,IT

BS

44

Rea

ding

Oct

.O

ct.

Gra

de e

quiv

a-N

atio

nal

Nat

iona

l nor

ms,

%i l

e sc

ores

begi

nnin

g of

year

10B

,S

TE

P?

?O

ct.

Oct

.C

onve

rted

Nat

iona

lN

atio

nal n

orm

s,

128

Rea

ding

scor

es%

i le

scor

esbe

ginn

ing

ofye

ar°

Not

e:

°Mid

poin

ts o

f per

cent

ile in

terv

als

wer

e us

ed.

1Y11

1111

- 03

Oik

iat4

Tab

le 5

3. P

repa

ratio

n of

Dis

tric

t 13

achi

evem

ent t

est d

ata.

Gra

deT

est &

Sub

iest

For

m U

sed

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Pos

t

Mon

th T

este

dP

reP

ost

For

m o

f Dat

a

Con

vers

ion

Pro

cess

Prio

r to

Obt

aini

n S

tand

ard

T-S

core

sS

tep

1S

tep

2S

tep

3P

rodu

ctS

ourc

eP

rodu

ctS

ourc

eP

rodu

ctS

ourc

e

1S

AT

Pri.

Pri.

May

May

Raw

Sco

res

Gra

deS

ubte

stN

otio

nal

May

-P

arag

raph

I -W

I -W

Sco

res

Con

vers

ion

%i l

e S

core

sJu

ne

Mea

ning

Tab

leN

orm

s

2S

AT

Pri.

Pri.

May

May

Raw

Sco

res

Gra

deS

ubte

stN

atio

nal

May

-P

arag

raph

II -W

II -W

Sco

res

Con

vers

ion

%ite

Sco

res

June

Mea

ning

Tab

leN

orm

s

5S

TE

P

Rea

ding

4A4A

Oct

.O

ct.

Num

ber

ofco

rrec

tan

swer

s

Con

vert

edS

core

sS

ubte

stC

onve

rsio

nT

able

Nat

iona

l%

ile S

core

sF

all N

orm

s

6S

AT

Int.

Int.

Jan.

Oct

.R

aw S

core

sG

rade

Sub

test

1964

Edi

tion

Edi

tion-

Nat

iona

lJa

n-A

pril

Par

agra

phM

eani

ngK

MII-

WS

core

sC

onve

rsio

nT

able

grad

e sc

ore

equi

v. fo

req

uiv.

bT

able

s%

ileS

core

s&

Sep

t. -

Dec

.F

orm

KN

orm

sc(I

nt. I

I)

8S

AT

Adv

.A

dv.

Oct

.-O

ct.

Raw

Sco

res

Gra

d.S

ubte

stA

s ab

ove

Edi

th.s

n-N

atio

nal

Sep

t. -D

ec.

Par

agra

phM

eani

ngJM

WN

ov.

Sco

res

Con

vers

ion

Tab

lefo

r F

orm

Jeq

uiv.

,T

able

s°%

ileS

core

sN

orm

s(A

dv. W

)

11IT

ED

--"A

bilit

y to

inte

rpre

tlit

erar

ym

ater

ials

"

X45

X45

Oct

.O

ct.

Sta

ndar

dS

core

sN

atio

nal

°Ail.

Sco

res

Beg

inni

ng o

fye

ar m

rms

Not

es:

aM

idpo

ints

of p

erce

ntiie

inte

rval

s w

ere

used

.b

Sin

ce d

iffer

ent m

onth

s w

ere

invo

lved

, diff

eren

t nor

m ta

b!es

had

to b

eus

ed.

cFor

ms

KM

and

JM

are

195

3 ed

ition

test

s an

d F

orm

W a

196

4 ed

ition

: equ

ival

ence

bet

wee

n th

e tw

o ed

ition

s re

quire

d us

e of

spe

cial

tabl

es.

.4

fillemal1010114.01.1104.mve.--......

180 67TMP-115

APPENDIX E

CORRECTIONS FOR DIFFERENCES IN PRE-POSTTCCTI Mr n ATCCI I.4 I Isv ...7 v.-% I a...,

In a ntber of instances, achievement tests were administeredat somewhat different times in the pre and post years. These differ-ences generate systematic errors in observations of change in achieve-ment. Achievement test publishers provide norms for only a fewdiP'erent times of year; for example, the Stanford Achievement Test(SAT) has beginning-of-year norms (for September through December),middle-of-year norms (January through April), and end-of-year norms(May and June). These norms are usually obtained by interpolatingbetween the results from pupils in different grades, rather than act-ually determining separate norms for various times of year. No dis-tinction is made between tests administered at different times withinthe interval covered by the norming period. This is consistent withthe recognized crudeness of achievement test scores for individuals.Indeed, publishers carefully point out that the scores for.individualsare quite imprecise. However, for group comparisons which accum-ulate errors from individual scores, more precision is needed. Asan example, if pre-year testing is done in January and post-yeartesting in April, the same norms (middle-of-year) would be used toscore both sets of results. However, the post year results wouldthen contain a positive bias and the pre-year results a negative bias.To determine the extent of errors introduced by differences in timeof year, all cases where there were three or more weeks discrepancybetween pre and post testing dates were examined. These instancesand the factors required for correction are shown in Table 54. Theamount of correction needed was obtained by applying the appropriate"change per month" (Shown in the last column of Tables 55 through 58and calculated by interpola;ing in the appropriate norm tables) to thediscrepancy in test dates 'shown in the "Time Difference" columnsin Table 54). For example, the first entry in Table 54 shows a cor-rection factor of +0. 5. Notice that the SAT In. I was given at the endof the year to this fourth grad,!. The amount of change per monthwas calculated for both the fortieth and the twentieth percentile levels.These two points in the distribution were used to represent the rel-atively low scores in our sample and to diminish the effect of rounding

APPENDIX E 181

errors. Table 56 shows the appropriate "change per month" as 0. 5at the fortieth percentile and 0.8 at the twentieth percentile; aver-aging these two numbers gives 0. 65. From Table 54, the discrepancyin testing dates was three weeks or, approxin.ately, 0.75 month.Therefor..., the c^rr...ctirsn recrir.,1 is to. 66) x (0. 751 . n. c =c chewmin the last column of the first line in Table 54.

Tables 57 arid 58 are similar to Tables 55 and 56 but apply to theMAT Reading Test.

Table 59 shows average changes in achievement level before andafter adjustment for differences in the pre-post testing dates for thefour districts with differences of three or more weeks in test dates.

The adjustment produced noticeable change in the values for Dis-tricts 1 and 12, where the proportion of observations adjusted washigh. In District 1, all cases were adjusted; in, District 12, 25 per-cent of the cases were adjusted. The adjusting of scores is a likelysource of error. As is shown in Table 59, adjustments for the 50observations affected make the change more negative. However, thisdecrease is fairly small compared to the standard errors of thestatistics.

,

Tab

le 5

4. B

ases

for

adju

stm

ent f

acto

rs r

equi

red

by v

aria

tions

in d

ates

bet

wee

n ad

min

istr

atio

nof

pre

and

pos

t tes

ts.

Dis

tric

tG

rade

Tes

t (S

ubte

st)

Dat

e of

Tes

tin

Aca

d. Y

r.65

-66

66-6

7T

ime

Diff

eren

cea

Sco

reb

Diff

eren

ceA

djus

tmen

tF

acto

rc

14

SA

T (

PM

) In

t ILa

teA

pr. 2

43

wee

ks-0

.5+

0.5

May

May

5

15

SA

T (

PM

) In

t I, I

ILa

teM

arch

3 w

eeks

+0.

4-0

.4M

ay6-

17

16

SA

T (

PM

) In

t II

Feb

.Ja

n.1

mon

th-0

.8+

0.8

17

SA

T (

PM

) A

dv.

Late

Apr

. 24

3 w

eeks

-0.2

+0.

2M

ayM

ay 5

18

SA

T (

PM

) A

dv.

Late

Dec

.1-

1/2

mon

ths

+0.

8-0

.8M

ay5-

17

811

MA

T (

Rdg

) H

.S.

Jan

7M

ay 1

54

mon

rhsd

+0.

9-0

.9

12e

3M

AT

(R

dg)

Sep

t.O

ct. 5

3 w

eeks

+1.

6-1

.6P

ri II

15

136

SA

T (

PM

) In

t I, I

IJa

n.O

ct.

1 m

onth

+0.

4-0

.4

Not

es:

.

aD

iffer

ence

is in

ref

eren

ce to

mid

dle

of n

orm

per

iod.

bA

mou

nt o

f Sta

ndar

d T

-sco

re d

iffer

ence

favo

ring

post

test

.c C

orre

ctio

n to

be

appl

ied

to o

bser

vatio

ns (

post

min

us p

re).

dT

hese

dat

a w

ere

base

d on

a s

ingl

e no

rm fo

r th

e 2

test

ings

, rat

her

than

diff

eren

t tim

e of

yea

r no

rms.

eO

nly

one

scho

ol (

Sch

ool 2

) ha

d a

3-w

eek

diffe

renc

e.

Tab

le 5

5. C

hang

e fr

om b

egin

ning

of y

ear

tom

iddl

e of

yea

r no

rms:

SA

T p

arag

raph

mea

ning

.

Gra

deB

atte

ry

Per

cent

i le

Sco

re L

evel

Beg

inni

ngof

Yea

r

Equ

ival

ent

Beg

inni

ng-

of-Y

ear

Gra

de S

core

Equ

ival

ent

Mid

Yea

rP

erce

ntile

Sco

reP

erce

ntile

Sco

reb

Cha

nge

Per

Mon

thS

tand

ard

T S

core

Cha

nge

Per

Mon

th

5In

t I40

4728

30.

8

2039

122

0.8

6In

t 11

4056

292.

80.

8

2047

141.

50.

6

8A

dv.

4075

322

0.5

2062

161

0.4

Not

es:

aAll

are

1964

edi

tion.

bB

ased

on

the

4-m

onth

per

iod

betw

een

mid

-poi

nts

of th

e tw

o no

rm p

erio

ds.

Tab

le 5

6. C

hang

e fr

omm

iddl

e of

yea

r to

end

of y

ear

norm

s:S

AT

par

agra

ph m

eani

ng.

Gra

deB

atte

ry

Per

cent

ileS

core

Lev

elB

egin

ning

of Y

ear

Equ

ival

ent

Mid

-Yea

rG

rade

Sco

re

Equ

ival

ent

End

of Y

ear

Per

cent

ile S

core

Per

cent

ile S

core

Cha

nge

Per

Mon

thb

Sta

ndar

d T

Sco

reC

hang

e F

er M

onth

4In

t I40

4234

20.

5

2034

142

0.8

5In

t II

4052

361.

30.

4

2042

151.

70.

7

6In

t II

4062

380.

70.

2

2050

180.

70.

31

7A

dv.

4070

380.

70.

2

2058

180.

70.

3

8A

dv.

4079

380.

70.

2

2065

180.

70.

3

,

Nor

es:

aA

ll ar

e 19

64 e

ditio

n si

nce

the

6th

grad

e sc

ores

from

the

1953

edi

tion

wer

eco

nver

ted

into

196

4 ed

it4,n

equi

vale

nts.

bB

ased

on

the

3-m

onth

per

iod

betw

een

mid

poin

ts o

f the

two

norm

perio

ds.

t.

Tab

le 5

7. C

hang

e fr

om b

egin

ning

of

year

nor

ms

to m

iddl

e of

yea

r: M

AT

Rea

ding

a.

Gra

deB

atte

ry°

Per

cent

i le

Sco

re L

evel

Beg

inni

ng o

fY

ear

Equ

ival

ent

Equ

ival

ent

Beg

inni

ng-

of-Y

ear

"Sta

ndar

d" S

core

Mid

Yea

rP

erce

nti l

eS

core

Per

cent

ile S

core

Cha

nge

Per

Mon

thb

Sta

ndar

d T

-Sco

reC

hang

e P

er M

onth

31

Prim

ary

II40 20

34 29

13.3

4.4

Not

es:

aThe

calc

ulat

ib

Bas

ed o

n th

e

7.1

4.2

1.8

1.5

ons

for

the

Prim

ary

II ba

ttery

wer

e ba

sed

upon

the

seco

nd g

rade

leve

l.

3-3/

4 m

onth

per

iod

betw

een

mid

poin

ts o

f the

norm

inte

rval

s.

Tab

le 5

8. C

hang

e fr

om e

leve

nth

grad

eto

twel

fth g

rade

nor

ms:

MA

T R

eadi

ng°.

.011

1110

1111

110=

1111

11

Gra

deB

atte

ry

Per

cent

ileS

core

Lev

elM

id-Y

ear

11th

Gra

deE

quiv

alen

t"S

tinda

rd"

Sco

re

I Equ

ival

ent

%ile

Sco

reM

id-Y

ear

12th

Gra

deP

erce

ntile

Sco

reC

hang

e P

er M

onth

Sta

ndar

d T

-Sco

reC

hang

e P

er M

onth

11H

igh

Sch

ool

4052

310.

90.

2620

42.

150.

50.

20--

--...

......

.,N

ote:

aB

ased

on

"age

-con

trol

led

sam

ples

" te

sted

ann

ually

.T

he y

ear

inte

rval

bet

wee

n te

sts

is c

onsi

dere

dto

con

sist

of

ten

acad

emic

mon

ths.

18667TMP-115

Table 59. Adjusted average changes in districts where pre and

post test dates differed by three or more weeks.

I

1

I.

1

DISTRICT

8 1 '12 13I

Number of Cases 39 55 4 32

Adjusted Cases 39 3 1 7

[Average Change in Mean

Unadjusted 0.27 -0.33 0.83 1.25

Adjusted 0,24 -0.38 0.43 1.16

Standard Error (unadj. ) 0.30 0.27 1.07 0.48

Significance Level (unadj.) 0.35 0.22 0.45 0.01

Average Change in Lowest Decile

Unadjusted 0.08 0.31 2.18 1.40

Adjusted 0.05 0.26 1.78 1.31

Standard Error (unadj. ) 0.28 0.38 2.42 0.71

Significance Level (unadj.) 0.50 0.42 0.42 0.05

187

APPENDIX F

USE OF STANDARD T-SCORES

The Standard T-score was selected for the following reasons: theunits of standard T-scores are nearly equal throughout the range ofachievement levels for a given grade level; results from differenttests can be converted to T-Scores via tables provided by the Testpublisher; test scores from different grades can be converted to thesame T-score levels; test scores obtained at different times of theyear can be converted to the same T-score units. None of the othermeasures has all of these qualities.

It is realized that test scores when converted to the Standard T-score have the above qualities only to a degree. The T-score isobtained by converting the raw score for a specific test to a nationalpercentile rank and then converting the percentile rank to the Stand-ard T-score. For example, a raw score of 11 on the test illustratedin Table 60 is equivalent to a "national" percentile rank of 8. Asshown in Table 61 a national percentile of 8 is equivalent to a stand-ard T-score of 36.0. One source of incompatibility among resultsfrom different tests is the fact that publishers use different popula-tions for developing the conversion table to be used for transformingraw score to "national" percentile. That is, it is really a conversionto a percentile rank for the test population and not the entire nation.

It has been assumed that none of these factors has a serious effecton conclusions in this study, because of the following reasons: (1)there is no attempt to make comparisons of absolute scores since thedifferences from Pre to Post are the important observations; (2) thesame rules were used in the conversion for both Pre and Post years,e.g., interpolation or extrapolation between values in conversion tables.

Tables 60 and 61 provide the reader with examples of the relation-ship between national percentile, Standard T-score, and grade equiva-lence. Any of the statistics on Standard T-scores provided in the sum-mary tables of this report can be interpreted in terms of nationalpercentiles by using Table 61. Table 60 provides a conversion fromnational percentiles to grade equivalence but for only the sixth gradein the latter part of the academic year.

V i

.................

188 67TMP-115

Table 60. Conversion of raw score on Advanced Battery, Form VI, of SATto grade score and national percentile (for tests given in sixthgrades during May & June of academic year) .

No.Right

1

2

3

4

567e9

10

11

12

13

14

15

16

17

18

19

2021

22

232425

2627282930

GradeScoreb

Below 20II

21

232527293235384042'444648505253545658606263646566687072

National i No. r... y1

1/4.71U(s

Percenti lec Right I Score'

5dow 1It

II

II

II

11

II

2

4

68

1011

12

14

16

2021

222428323436384244485254

31 74

32 7633 7834 8035 82..

36 8437 86

38 9039 9440 9941 102

42 104

43 105

44 106

45 10746 108

47 11048 112

49 113

50 114

51 116

52 118

53 12054 121

55 123

56 124

57 126

58 12759 129

60 129+

,..at;onal.......1Percentilec

5862687074767881

838589909"/:

9293949596969798989999999999999999

Notes:

°All data are from publisher's tables accompanying test booklets.

bGrade score is 10 times grade equivalent score. For example, a grade equiva-

lent of 6.0 is a grade score of 60.

cThis national percentile rank is valid only for tests given to the 6th grade inMay or June of the academic year.

APPENDIX F

Table 61. Convernng percentiles to Standard T scores.°

i 89

%b Tc %b Tc %b c

T %b Tc

1 - 26.7 26 - 43.6 51 - 50.3 76 - 57.1n nn r n-f Art et.4 - L7.J L/ - 40.7 52 - 50.5 77 - 5-7.43 - 31.2 28 - 44.2 53 - 50.7 78 - 57.74 - 32.5 29 - 44.5 54 - 51.0 79 - 58.15 - 33.5 30 - 44.7 55 - 51.3 80 - 58.46 - 34.5 31 - 45.0 56 - 51.5 81 - 58.87 - 35.2 32 - 45.4 57 - 51.8 82 - 59.28 - 36.0 33 - 45.6 58 - 52.0 83 - 59.59 - 36.6 34 - 45.9 59 - 52.3 84 - 59.9

10 - 37.2 35 - 46.2 60 - 52.5 85 - 60.411 - 37.7 3.5 - 46.4 61 - 52.8 86 - 60812 - 38.3 37 - 46.7 62 - 53.0 87 - 61.313 - 38.7 38 - 47.0 63 - 53.3 88 - 61.714 - 39.2 39 - 47.2 64 - 53.6 89 - 62.315 - 39.6 40 - 47.5 65 - 53.8 90 - 62.816 - 40.1 41 - 47.7 66 - 54.1 91 - 63.417 - 40.5 42 - 48.0 67 - 54.4 92 - 64.018 - 40.8 43 - 48.3 68 - 54.7 93 -; 64.819 41.2 44 - 48.5 69 - 55.0 94 - 65.620 - 41.6 45 - 48.7 70 - 55.3 95 - 66.521 - 41.9 46 - 49.0 71 - 55.5 96 - 67.522 - 42.3 47 - 49.3 72 - 55.8 97 - 68.823 - 42.6 48 - 49.5 73 - 56.1 90 - 70.324 - 42.9 49 - 49.7 74 - 56.4 99 - 70.525 - 43.3 50 - 50.0 75 - 56.7

Notes:a

Reference 8, p 66.bNet;onal

percentile.

ICEquivalent Standard T-Score.

19067TMP-115

APPENDIX G

DETAILED INFORMATION FOR DISTRICT 10

Tables 62 through 70 provide expenditure information for each of

the 10 schools in District 10. Discussion of these tables and the cor-responding Table for School 1 is in Section 3.

Tables 71 through 79 provide expenditure data by grade and type ofCE program. Discussion of these tables and the corresponding Tablefor School 1 is in Section 3.

Tab

le 6

2.E

xpen

ditu

res

for

regu

lar

and

com

pens

ator

y ed

ucat

ion

prog

ram

s: S

choo

l 2.

Dis

tric

t 10

Sch

ool 0

2R

egul

ar S

choo

l Pro

gram

sC

ompe

nsat

ory

Edu

catio

n P

rogr

ams

Exp

endi

ture

Cat

egor

ies

Tea

cher

Aid

esA

djus

tmen

t Tea

chin

gR

educ

ed C

lass

Siz

eC

entr

aliz

edLi

brar

y

64-6

565

-66

66-6

765

-66

66-6

765

-65

6-67

.

fil$

#$

#$

#$

ri$

#$

#$

Prin

cipa

ls, C

onsu

ltcnt

s, S

upeM

sors

186

891

9362

112

i65

20

Tea

cher

s15

8209

115

8438

915

1077

745

3196

347

3617

4469

10

Libr

ary,

Aud

io-v

isua

l & T

V P

erso

nnel

48

Sec

retw

ial-C

leric

al1

3024

133

601

4070

Tot

al S

alar

ies

9380

497

111

1240

0932

6447

3617

4469

10

Tea

chin

g S

uppl

ies

& O

ther

Exp

ense

s10

2411

4210

6296

714

3827

96

Tot

al In

stru

ctio

nal E

xper

res

9482

898

253

1250

7142

3147

3631

8297

06

Hea

lth S

ervi

ces

Pup

il T

rans

port

atio

n

Pla

nt O

pera

tion

& M

aint

enan

ce17

771

1513

517

490

5335

3

Fix

ed C

harg

es12

620

610

948

4

Foo

d S

ervi

ces

S?u

dent

/Com

mun

ity A

ctiv

ities

Tot

al S

uppo

rt E

xpen

ses

1777

115

135

1749

012

625

910

983

7

Tea

chin

g E

quE

pmen

t33

411

221

4241

217

Tot

al E

xpen

ses

1125

9911

3388

1428

9554

79I4

995

7532

1076

0

Tab

le 6

;.'E

xpen

ditu

res

for

regu

lar

and

com

pens

ator

y,,.

-.1u

catio

n pr

ogra

ms:

Sch

ool 3

.

Dis

tric

t 10

Sch

ool 0

3R

egul

ar S

choo

l Pro

gram

sC

ompe

nsat

ory

Edu

catio

n P

rogr

ams

Exp

endi

ture

Cat

egor

ies

.

Tea

cher

Adj

ustm

ent

Red

uced

Aid

esT

each

ing

Cla

ss S

ize

IC

entr

aliz

ed L

ibra

ry

64-6

565

-66

66-6

765

-66

66-6

765

-66

66-6

7

#$

#$

#$

#$

#$

#$

#$

Prin

cipa

ls, C

ons.

, !ta

nts,

Sup

ervi

sors

110

214

193

911

1343

36

Tea

cher

s42

2358

3942

2502

2444

3250

1913

9579

1320

306

1744

6810

Libr

ary,

Aud

io-v

isua

l & T

V P

erso

nnel

150

Sec

reta

rial-C

leric

al2

8098

282

952

9200

Tot

al S

alar

ies

2541

5126

7910

3476

5297

3520

306

1744

6810

Tea

chin

g S

uppl

ies

& O

ther

Exp

ense

s29

8829

8927

2623

9115

4428

20

Tot

al In

stru

ctio

nal E

xpen

ses

2571

39(

2708

9935

0378

1212

620

306

3288

9630

Hea

lth S

ervi

ces

Pup

il T

rans

port

atio

nP

lant

Ope

ratio

n &

t4 a

inte

nanc

e34

812

3349

141

559

353

615

Fix

ed C

harg

es10

947

7

Foo

d S

ervi

ces

Stu

dent

/Com

mun

ity A

ctiv

ities

Tot

al S

uppo

rt E

xpen

ses

3481

233

491

4155

935

310

910

92

Tea

chin

g E

quip

men

t75

819

4645

76

Tot

al E

xpen

ses

2919

5130

4390

3926

9514

464

2154

479

7310

722

Tab

le 6

4. E

xpen

ditu

res

for

regu

lar

and

com

pens

ator

y ed

ucat

ion

prog

ram

s:S

choo

l 4.

Dis

tric

t 10

Sch

ool 0

4R

egul

ar S

choo

l Pro

gram

sC

ompe

nsat

ory

Edu

catio

n P

rogr

ams

.T

each

er A

ides

Exp

endi

ture

Cat

egor

ies

Adj

ustm

ent T

e-ic

hing

Red

uced

Cla

ss S

ize

64-6

565

-66

66-6

765

-66

66-6

765

-66

66-6

7

$I/

$#

$I/

$al

$$

Prin

cipa

ls, C

onsu

ltant

s, S

uper

viso

rs1

7724

183

841

1117

430

Tea

cher

s7

4003

17

4251

88

5562

13

1578

346

58

Libr

ary,

Aud

io-v

isua

l & i'

V P

erso

nnel

83

Sec

reta

rial-C

leric

al1

3536

136

231

140

7016

9146

58

Tot

al S

alar

ies

5129

154

5251

7086

516

9146

58

Tea

chin

g S

uppl

ies

& O

ther

Exp

ense

s49

745

147

359

2

Tot

al in

stru

ctio

nal E

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ses

5178

854

976

71^3

822

8346

58

Hea

lth S

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ces

Pup

il T

rans

port

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n

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nt O

pera

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& M

aint

enan

ce91

5012

255

1024

4

Fix

ed C

harg

es67

203

Foo

d S

ervi

ces

Stu

dent

/Com

mun

ity A

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ities

Tot

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uppo

rt E

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ses

9150

1225

510

244

6720

3

Tea

chin

g E

quip

men

t14

456

Tot

al E

xpen

ses

6093

867

231

8159

628

0648

61

1"T

Tab

le 6

5. E

xpen

ditu

res

for

regu

lar

and

com

pens

ator

yed

ucat

ion

prog

ram

s: S

choo

l 5.

Dis

tric

t 10

Sch

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5R

egul

ar S

choo

l Pro

gram

sC

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Edu

catio

n P

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Exp

endi

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ustm

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each

ing

Red

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ize

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Prin

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; 255

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446

75

Libr

ary,

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815

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reta

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leric

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7431

278

642

9090

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2514

6434

9162

7891

2712

457

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Tea

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s31

5528

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2415

9569

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4068

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8237

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2926

3631

0381

3928

7111

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3039

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89

Tab

le 6

6. E

xpen

ditu

res

for

regu

lar

and

com

pens

ator

y ed

ucat

ion

prog

ram

s: S

choo

l 6.

Dis

tric

t 10

Sch

ool 0

6R

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ar S

choo

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sC

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Edu

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Exp

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64-6

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65-6

666

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#$

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$

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cipa

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7120

183

911

1117

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cher

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4761

49

4615

19

6244

44

2556

464

91

Libr

ary,

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io-v

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l & T

V P

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nnel

47

Sec

reta

rial-C

leric

al1

3280

136

221

4070

Tot

al S

alar

ies

5801

458

164

7768

826

3364

91

Tea

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ense

s41

510

2764

370

616

740

0

Tot

al In

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5842

959

191

7833

133

3966

5840

0

Hea

lth S

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Foo

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9926

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334

6

Tea

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t39

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836

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Tot

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6835

668

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9308

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3473

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Tab

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7.E

xpen

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for

regu

lar

and

com

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s: S

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Dis

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Sch

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Prin

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7160

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9826

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80

Libr

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Aud

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l & T

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Sec

reta

rial-C

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al1

4049

136

231

2539

906

375

Tot

al S

alar

ies

6717

577

643

1008

6821

4524

9880

7512

315

Tea

chin

g S

uppl

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Exp

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s51

651

064

539

714

2220

3

Tot

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stru

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ses

6769

178

153

1015

1325

4239

2082

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315

Hea

lth S

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Pup

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n70

5

Pla

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021

1255

714

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45

Fix

ed C

harg

es89

109

139

964

Foo

d S

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290

Stu

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1702

112

557

1487

989

109

544

969

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chin

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325

285

951

8

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8471

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710

1164

9832

8442

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Tab

le 6

8. E

xpen

ditu

res

for

regu

lar

and

com

pens

ator

y ed

ucat

ion

prog

ram

s: S

choo

l 8.

Dis

tric

t 10

Sch

ool 0

8R

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ar S

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gram

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Edu

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n P

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Exp

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cher

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stru

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nal

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ent

64-6

565

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66-6

765

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66-6

765

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66-6

7

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##

$

Prin

cipa

ls, C

onsu

ltant

s, S

uper

viso

rs1

8996

184

401

1132

720

785

Tea

cher

s20

9775

721

1081

5222

1462

855

3858

914

021

2565

Libr

-y, A

udio

-vis

ual &

TV

Per

sonn

el63

Sec

reta

rial-C

leric

al1

4049

129

681

4600

Tot

al S

alar

ies

1108

0211

9561

1622

1239

4114

021

3350

Tea

chin

g S

uppl

ies

& O

ther

Exp

ense

s14

9512

5314

8273

839

8

Tot

al In

stru

ctio

nal E

xpen

ses

1122

9712

0814

1636

9446

7914

419

3350

Hea

lth S

ervi

ces

Pup

il T

rans

port

atio

n

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nt O

pera

tion

& M

aint

enan

ce49

683

1967

822

766

Fix

ed C

harg

es17

661

120

3

P

Foo

d S

ervi

ces

1

Stu

dent

/Com

mun

ity A

ctiv

ities

Tot

al S

uppo

rt E

xpen

ses

4968

319

678

2276

617

661

120

3

Tea

chin

g E

quip

men

t34

110

1079

8

Tot

al E

xpen

ses

1619

8114

0492

1868

0158

6515

828

3553

....-

..-

Iia

Tab

le 6

9.E

xpen

ditu

res

for

regu

lar

and

com

pens

ator

y ed

ucat

ion

prog

ram

s: S

choo

l 9.

Dis

tric

t 10

Sch

ool 0

9R

egul

ar S

choo

l Pro

gram

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ompe

nsat

ory

Edu

catio

n P

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ams

Exp

endi

ture

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ies

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cher

Aid

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lass

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e

Inte

nsiv

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stru

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nal

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ent

64-6

565

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66-6

765

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66-6

765

-66

66-6

7

#$

#$

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$$

Prin

cipa

ls, C

onsu

ltant

s, S

uper

viso

rs1

8996

193

701

1193

720

312

Tea

cher

s16

1027

0416

1052

8218

1489

314

3230

578

5315

65

Libr

ary,

Aud

io-v

isua

l & T

V P

erso

nnel

51

Sec

reta

rial-C

laric

al1

4049

141

481

4600

Tot

al S

alar

ies

1157

4911

8800

1654

6833

0178

5318

77

Tea

chin

g S

uppl

ies

& O

ther

Exp

ense

s12

3410

6799

868

719

9

Tot

al In

stru

ctio

nal E

xpen

ses

1169

8311

9867

1664

6639

8880

5218

77

Hea

lth S

ervi

ces

Pup

il T

rans

port

atio

n

Pla

nt O

pera

tion

& M

aint

enan

ce20

552

1543

817

380

Fix

ed C

harg

es13

634

312

0

Foo

d S

ervi

ces

Stu

dent

/Com

mun

ity A

ctiv

ities

To$

al S

uppo

rt E

xpen

ses

2055

215

438

1738

013

634

312

0

Tea

chin

g E

quiP

men

t10

707

397

Tot

al E

xpen

ses

1375

3513

5305

1838

5648

3187

9219

97

Tab

le 7

0.E

xpen

ditu

res

for

regu

lar

and

com

pens

ator

y ed

ucat

ion

prog

ram

s: S

choo

l 10.

Dis

tric

t 10

Sch

ool 1

0R

egul

ar S

choo

l Vro

gram

sC

ompe

nsat

ory

Edu

catio

n P

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ams

Exp

endi

ture

Cat

egor

ies

Tea

cher

Aid

esA

djus

tmen

t Tea

chin

gR

educ

ed C

lass

Siz

e

64-6

565

-66

66-6

765

-66

66-6

765

-66

66-6

7

#$

#$

#$

#$

igs

#$

$

Prin

cipa

ls, C

onsu

ltant

s, S

uper

viso

rs1

8996

196

701

1103

720

Tea

cher

s14

7360

614

7976

314

1048

104

3258

346

61

Libr

ary,

Aud

io-v

isua

l & T

V P

erso

mte

l39

Sec

reta

rial-C

leric

al1

3757

141

481

5069

Tot

al S

alar

ies

8735

993

581

1209

1639

3746

61

Tea

chin

g S

uppl

ies

& O

ther

Exp

ense

s93

696

211

0962

0

Tot

al In

stru

ctio

nal E

xpen

ses

8829

594

543

1220

2539

3746

61

Hea

lth S

ervi

ces

Pup

il T

rans

port

atio

n

Pla

nt O

pera

tion

& M

aint

enan

ce86

4988

8712

089

Fix

ed C

harg

es13

820

3

Foo

d S

ervi

ces

Stu

dent

/Com

mun

ity A

ctiv

ities

Tot

al S

uppo

rt E

xpen

ses

8649

8887

1208

913

820

3

Tea

chin

g E

quip

men

t35

977

9

Tot

al E

xpen

ses

9594

410

3430

1344

7348

5448

64.

.

200

Table 71. Program expenditures by grades: School 2.

67TMP-115

1965-66RegularPrograms

Teacher Aides,AdjustmentTeachers,

Reduced ClassSize

CentralLibrary

ClinicalReading

I Total CEPrograms

Grade ADM $ $ $ $

K 56 1025 8 1112 681 1793

1 144 26377 2858 1752 461 0

2 V 76 13922 15 08 925 2433

3 68 12456 827 2604 3431

4 65 11907 791 2604 3395

5 80 14654 973 2604 3577

6 58 10624 706 2604 331 0

Sp. 72 13189 876 876

Totals 619 109781 5478 7 5": 10416 23425

I 1966-67RegularPrognams

$

Teacher AidesAdjustmentTeachers,

Reduced ClassSize

$

.

CentralLibrary

$

ClinicalReading

Total CEPrograms

$Grade ADM

K 64 16936 1137 1275 2412

1 110 29108 1955 2192 4147

2 1 07 28313 1902 2132 4034

3 60 15877 1195 5048 7243

4 62 16406 1235 5048 6283

5 63 16670 1256 5048 6304

6 59 15613 1176 5048 6224

Sp. 15 3970 299 299

Totals 540 1428 93 4994 1 0760 20192 36946

APPENDIX G


201


Teacher Aides,Adjustment

Teachers'Reduced Class

Size

CentralLibrary

Total CEPrograms

Grade ADM $ $ $ $

K 116 21825 2534 572 3106

1 3 01 56617 6574 1483 8057

2 245 46085 5352 1207 6559

3 210 39510 1035 1035

4 198 37257 976 976

5 1 69 31778 832 832

6 163 30652 803 803

Sp. 216 40636 1064 1064

Totals 1618 3 04360 14460 7972 22432

1966-67Regular

Teacher Aides,AdjustmentTeachers'

Reduced ClassSize

CentralLibrary

Total CEProgramsProg rams

Grade ADM $ $ $ $

K "42 39623 4990 1082 6072

1 227 63342 7976 1729 9705

2 244 68093 8575 1859 10434

3 177 49401 1349 1349

4 192 53603 1464. 1464

5 146 40762 1113 1113

6 137 38248 1044 1044

Sp. 142 39629 1082 1082

I Totals 1407 392701 21541 1 0722 32263

202


67TMP-115

1965-661 Teacher Aides

AdjustmentRegular Teachers,Programs I

!Reduced Class

Total CEPrograms

l

1

I Size

Grade ADM $ $ $

K 40 9638 857 857

1, 48 11566 1028 1 028

2 43 1 0362 92i 921

3 29 6988

4 21 5060

5 21 5060

6 28 6747

Sp. 49 11808

Totals 279 67229 2806 2806



Reduced ClassSize

Total CEPrograms

Grade ADM $ $ I$

K 43 14206 1620 1620

1 41 13545 1545 1545

2 45 I 14867 1696 1696

3 35 11562

4 26 8592

5 28 9253

6 19 6275

Sp. 10 3305

I Totals 247 81605 4861 4861

APPENDIX G


203

1965-66RegularP rog ra rns


Reduced ClassSize

Total CEProarams

Grade ADM $ $ $

K 135 31659 2 716 2716

1 228 53448 4587 45 87

2 218 5112 0 4386 4386

3 2 01 47116

4 1 96 45936

5 193 45254

6 139 32590

Sp. 14 3290

Totals 1324 310413. 11 689 11689'


Teacher Aides'AdjustmentTeachers'

Reduced ClassSize

IntensiveIns.ructionalImprovement

Total CEPrograms

,

Grade ADM $ $ $ $

163 41841 7285 7285

1 279 71660 12469 12469

2 238 61131 1 0637 10637

3 224 57506 1700 1700

4 214 54963 1634 1634

5 198 5 0838 1511 151 1

6 198 5 0838 I 1511 151 1

Sp. 16 4125 I122 122

Totals 1530 3 92902 303 91 6488 36879 I

204


67TMP-115


leacher Aides,Adjustment

Teachers,Reduced Class

Size

Language ArtsTeacher

ConsultantsTotal CEPrograms

Grade ADM $ $ $

K 33 8183 798 798

1 80 19835 1934 2140 4074

2 58 14375 1402 1552 2954

3 36 9822 963 963

4 38 9421 1016 1016

5 22 5453 588 588

6 5 1238 134 134

Sp. 4 992

Totals 276 68419 4134 6393 10527

1966-67Regular

Programs


Reduced ClasseJI ze

ProjectQuality

Language ArtsTotal CEPrograms

IGrade ADM $ $ $ $

K 47 12464 1778 102 1880

1 81 21481 3065 176 4242 7483

2 65 17239 2459 1.41 3405 6005

,.i 65 17239 141 3405 3546

4 48 12734 105 2514 2619

5 0

6 0

Sp. 45 11933 98 98

Totals 351 93090 7302 763 13566 21631

APPENDIX G


205



i Teachers'Reduced Class

Size

English as aSecond

LanguageTotal CEPrograms

Grade ADM $ $ $ $

K 33 9153 803 977 1780

1 56 15539 1362 1658 3020

2 46 12763 1119 1362 2481

3 59 16364 1746 1746

4 27 7493 800 800

5 29 8046 859 859

6 23 6377 681 681

Sp. 54 14976 1598 1598

Totals 1 327 90711 3284 9681 112965

1966-67Regular

Pr°grams

Teacher Aides'Adjustment


Size

English as aSecond

LanguageProjectQuality

Total CEPrograms

Grade ADM $ $ $ $ $

K 29 10660 839 1263 71 2173

1 67 24628 1938 2918 163 5019

2 52 19106 1504 2264 127 3895

3 50 18372 2177 122 2299

4 45 16543 1960 110 2070

5 27 9926 1173 62 1235

6 25 9192 1089 61 1150

Sp. 22 8C85 958 54 1012

Totals 317 116512 4281 13802 770 18853

206




,Teachers,Reauced Class

Size

$

=

1

Total CEPrograms

$Grade ADM $

K 60 11015 1252 1252

1 120 22043 25 04 2504

2 101 18545 2108 21 08

3 102 18728

4 118 21664

5 115 21116

6 89 10339

Sp. 6 0 11015

Totals 765 134465 5864 5864



Reduced ClassSize

IntensiveInstructionalImprovement

Total CEPrograms

Grade ADM $ $ $

K 71 18493 3 999 3 999

1 102 26582 5 745 5 745

2 108 28132 6083 6083

3 84 21893 684 684

4 86 22397 701 701

5 98 25536 798 798

6 97 25274 790 790

Sp. 71 18493 578 578

Totals 71 7 186800 15827 3551 1 9378

APPENDIX G


207



T - 1...s..,..Ivacimi,Reduced Class

Size

Total CEPrograms

Grade ADM $ $ $

K 37 9025 916 916

1 73 17793 1808 1808

2 85 20729 2106 2106

3 69 16818

4 73 17793

5 75 18280

6 84 20485

Sp. 59 14383

Totals 555 135306f

4830 4830

1966-.67Regular

Programs



Size

IntensiveInstructionalImprovement

JTotal CEPrograms

Grade ADM $ $ $

K 39 15977 2103 2103

1 69 28259 3721 3721

2 55 22522 2966 2966

3 75 30704 524 524

4 55 22522 384 384

5 70 28663 489 489

6 62 25391 433 433

Sp. 24 9818 168 168

Totals 449 183856 8792 19981

10788

208


67TMP-115

1965-66Regular

Prru,rnme-,u -



Size

Total CE0-e oogrOnis

Grade ADM $$

K 54 9743 1125 1125

1 103 18586 2146 2146

2 76 13715 1583 1583

3 83 14977

4 80 14439

5 70 12639

6 50 9029

Sp. 57 10291

Totals 574 103419 4854 4854

1966-67Regular

Programs


Reduced ClassSize

Total CEPrograms

Grade ADM $ $

K 41 11430 982 982

1 88 24541 2109 2109

2 74 20642 1773 1:773

3 59 16459

4 83 23143

5 69 19243

6 55 15343

Sp. 13 3631

Totals 483 134432 4864 4864

REFERENCES

1. Grotberg, Edith H. , Learning Disabilities and Remediation inDisadvantaged Children, Rev. Educ. Res. , vol 35 (1965).

2. Raph, Jane B. , Language Development in Socially DisadvantagedChildren, Rev. Educ. Res. , vol 35 (1965).

3. U. S. Office of Education, The States Report: The First Year ofTitle I, Summary Report, U. S. Government Printing Office,Washington, D. C.

4. United States Commission on Civil Rights, Racial Isolation in thePublic Schools U. S. Government Printing Office, Washington,D. C.

5. Manual for Administrators, Supervisors and Counselors: IowaTests cif Basic Skills, Houghton, Mifflin Co. , Boston, Mass. ,1964.

6. Technical Supplement, Stanford Achievement Test, Harcourt,Brace and World, Inc. , New York, New York, 1966.

7. Holt, J. , How Children Fail, Dill, New York, New York, 1964.

8. U. S. Office of Education, Guide of Evaluation of Title I Projects,U. S. Government Printing Office, Washington, D. C. , October1966.

9. Wasserman, William, Education Price and Quantity Indexes,Syracuse University Press, Syracuse, New Yo:rk, 1963.

10. Higgins, M. J. , and J. C. Merwin, Assessing the Progress ofEducation: A Second Report, Phi Delta Kappan, vol 48 (1967).

11. U. S. Office of Education, Pupil Accounting for Local and StateSchool Sy.?tems, U. S. Government Printing Office, Washington,D. C. , 1964.

12. Kendall, M. G. , and A. Stuart, The Advanced Theory of Statistics,vol I, Hafner, New York, New York, 1963.

21067TMP-115

13. Peters, C. C. , and W. R. Van Voorhis, Statistical Proceduresand Their Mathematical Bases, McGraw Hill, 1940.

14. Thomson, G. H. , A Formula to Correct for the Effect of Errorsof Measurement on the Correlation of Initial Values withGains, Journal of Experimental Psychology, vol 7 (1925)

15. Scheffe, Analysis of Variance, Wiley, 1959.

UNCLASSIFIEDSecurity Classification

DOCUMENT CONTROL DATA - R&D(Security classification of title. body of abstract and indexing annotation must be entered sewn Ike overall mien S. classified)

1. ORIGINATIN 0 ACTIVITY (Corporate autho;)

General Electric, TEMPOWashington Operation

2.. REPORT SECURITY C LAssIFICATION

Unclas sified -26. OROuP

3. REPORT TITLE

SURVEY AND ANALYSES OF RESULTS FROM rITLE I FUNDING FOR

COMPENSATORY EDUCATION4. DESCRIPTIVE NOTES (Type et tepee end inlusive data.)

1. AUTH0R(3) (Last no Wet now. WNW)

S. REPORT DATE

I March 196870. TOTAL. NO. OF PASmS

225

........71A No. or

15

S.. CONTRAcy OR 4IRANT NO.

HEW-05-67-55IL PROJECT NO.

4.

d. .

SAL ORIOINATOWS REPORT NUMSERM

67TMP-115

SAL 27:411111111PORY NO(S) (Any sift' woolen OW any be ottelened

10. A VA IL AMLITY/LiMITATION NOTICES

Distribution only through Project Officers, Department of Health, Education, andWelfare.

Is. SUPPLEMENTARY NOTES 12. SPONSOR

Department Health, Education and WelfarWashington, D.C. 20211

13. AMSTRACT

This report analyzes data from a sample of 132 schools which received fundsfrom Title I for compensatory education to aid educationally disadvantaged pupils.Mose of the eleven school districts from which the schools were drawn wereselected because there was reason to believe that successful compensatory educa-tion programs were in progress in at least some of the district schools. Conclu-sions are based on a comparison of achievement scores in 1966-67, after pupilswere exposed to compensatory education from Title funds, with achivementscores in 1965-66.

_

UNCLASSIFIEDSecurity Classification

,..

of pupils at the lowest - ed

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