• TABLE OF CONTENTS
HIDE
 Title Page
 Dedication
 Acknowledgement
 Table of Contents
 List of Tables
 Abstract
 Introduction
 Review of the literature
 Design of the study
 Results
 Summary, discussion, and concl...
 Appendix
 Bibliography
 Biographical sketch














Group Title: relationship between disruptive behavior and socio-economic status, ethnicity, and sex of the student;
Title: The relationship between disruptive behavior and socio-economic status, ethnicity, and sex of the student;
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 Material Information
Title: The relationship between disruptive behavior and socio-economic status, ethnicity, and sex of the student; the size, location, and ethnicity of the school, in selected tri-ethnic junior high schools
Physical Description: xv, 150 leaves : ; 28 cm.
Language: English
Creator: Garrido, Armando Raul, 1932-
Publication Date: 1978
Copyright Date: 1978
 Subjects
Subject: Junior high school students -- Socioeconomic status -- Florida   ( lcsh )
Junior high school students -- Florida   ( lcsh )
Human behavior   ( lcsh )
School discipline -- Florida   ( lcsh )
Educational Administration and Supervision thesis Ph. D   ( lcsh )
Dissertations, Academic -- Educational Administration and Supervision -- UF   ( lcsh )
Genre: bibliography   ( marcgt )
non-fiction   ( marcgt )
 Notes
Thesis: Thesis--University of Florida.
Bibliography: Bibliography: leaves 140-149.
General Note: Typescript.
General Note: Vita.
Statement of Responsibility: by Armando R. Garrido.
 Record Information
Bibliographic ID: UF00098080
Volume ID: VID00001
Source Institution: University of Florida
Holding Location: University of Florida
Rights Management: All rights reserved by the source institution and holding location.
Resource Identifier: alephbibnum - 000084929
oclc - 05301865
notis - AAK0275

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Table of Contents
    Title Page
        Page i
        Page ii
    Dedication
        Page iii
    Acknowledgement
        Page iv
        Page v
    Table of Contents
        Page vi
        Page vii
    List of Tables
        Page viii
        Page ix
        Page x
        Page xi
    Abstract
        Page xii
        Page xiii
        Page xiv
        Page xv
    Introduction
        Page 1
        Page 2
        Page 3
        Page 4
        Page 5
        Page 6
        Page 7
        Page 8
        Page 9
    Review of the literature
        Page 10
        Page 11
        Page 12
        Page 13
        Page 14
        Page 15
        Page 16
        Page 17
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        Page 19
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        Page 35
        Page 36
        Page 37
        Page 38
        Page 39
        Page 40
        Page 41
    Design of the study
        Page 42
        Page 43
        Page 44
        Page 45
        Page 46
        Page 47
        Page 48
        Page 49
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        Page 55
        Page 56
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        Page 58
        Page 59
        Page 60
        Page 61
    Results
        Page 62
        Page 63
        Page 64
        Page 65
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    Summary, discussion, and conclusions
        Page 110
        Page 111
        Page 112
        Page 113
        Page 114
        Page 115
        Page 116
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    Appendix
        Page 135
        Page 136
        Page 137
        Page 138
        Page 139
    Bibliography
        Page 140
        Page 141
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        Page 143
        Page 144
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    Biographical sketch
        Page 150
        Page 151
        Page 152
Full Text













THE RELATIONSHIP BETWEEN DISRUPTIVE BEHAVIOR AND
SOCIO-ECONOMIC STATUS, ETHNICITY, AND SEX OF THE
STUDENT; THE SIZE, LOCATION, AND ETHNICITY OF THE
SCHOOL, IN SELECTED TRI-ETHNIC JUNIOR HIGH SCHOOLS












By

ARMANDO R. GARRIDO


A DISSERTATION PRESENTED TO THE GRADUATE COUNCIL OF
THE UNIVERSITY OF FLORIDA IN PARTIAL
FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF
DOCTOR OF PHILOSOPHY




UNIVERSITY OF FLORIDA


1978




























































Copyright by
Armando R. Garrido
1978
































To my parents

Armando and Blanca Garrido

with filial devotion
















ACKNOWLEDGMENTS


The writer wishes to express appreciation to

Dr. S. Kern Alexander for assuming the chairmanship of

his doctoral committee in the absence of Dr. Hines. Dr.

Alexander's scholarly criticism and assistance aided in

the completion of this project.

A sincere note of gratitude goes to Dr. Ralph B.

Kimbrough for his support, guidance, and assistance in

this research effort.

To Dr. Hal G. Lewis, for his willingness to be

on the committee during Dr. Hines' absence, the writer

offers a special note of thanks.

The writer wishes also to express his overwhelming

debt to Dr. Vynce A. Hines for his encouragement, con-

tinued help, and personal support. He provided inspira-

tion without which this research would never have been

completed.

To my children, Tellita, Armando, and Jacinto, who

did without a father for over two years, I extend a special

note of gratitude.

Last, but not least, the writer acknowledges his

concern for all the underprivileged children in whose

interest this work was undertaken and to whom he dedicates











whatever knowledge and enhancement of the educational

climate this project may bring forth.
















TABLE OF CONTENTS


ACKNOWLEDGMENTS . . . . . . .

LIST OF TABLES . . . . . . .

ABSTRACT . . . . . . . .


Page

. . iv

S. . viii

. . xii


CHAPTER


I INTRODUCTION ............ . 1
Nature of the Study . . . . 3
Statement of the Problem. . . . 4
Limitations of the Study. . . . 5
Definition of Terms . . . . 5
Sampling. . . . . . . . 6
Data Collection . . . . . 7
Significance. . . . . . . 8
Organization of the Study . . . 9

II REVIEW OF THE LITERATURE .. . .. 10
Literature on Disruption. . . ... 11
Literature on Socio-economic Status 24
Literature on Ethnicity . . .. 31
LLiterature on Sex . . . . .. 33
Literature on School Location . . 35
Literature on School Size . . .. 36
Literature on the School Principal. 37
Summary . ... . . . . . 40


III DESIGN OF THE STUDY. .
Hypotheses. .....
Procedures ....
Subjects . . ..
Instruments . . .
Methods . . ..
Statistical Analysis.
Summary . . . .

IV RESULTS . . . .
Section I . . .
Section II .
Section III .. . .
Section IV. . . .
Section V . . .
Summary . . . .
















TABLE OF CONTENTS (continued)

Page

CHAPTER

V SUMMARY, DISCUSSION, AND CONCLUSIONS. 110
Summary . . . . . . . . 110
Discussion. . . . . . . .. 124
Conclusions . . . . . . .. 131

APPENDIX . . . . . . . . . . .. 136

BIBLIOGRAPHY. .................... 140

BIOGRAPHICAL SKETCH . . . . . . . .. 150

















LIST OF TABLES


TABLE Page

1. ETHNICITY . . . . . . . .. .51

2. JUNIOR HIGH SCHOOL COMPLAINTS REPORTED
TO THE DADE COUNTY SCHOOLS SECURITY
ENFORCEMENT DEPARTMENT IN THE 1976/1977
SCHOOL YEAR . . . . . . .. .52

3. SCORES USED TO DETERMINE SOCIO-ECONOMIC
POSITION. . . . . . . . .. 58

4. RESULTS OF STEPWISE MULTIPLE REGRESSION
ANALYSIS AND RESULTS OF THE ANALYSIS OF
VARIANCE IN T HE MULTIPLE REGRESSION . . 64

5. DISRUPTIVE AND NON-DISRUPTIVE STUDENTS
OF DIFFERENT SOCIO-ECONOMIC POSITIONS . 66

6. DISRUPTIVE AND NON-DISRUPTIVE STUDENTS
OF DIFFERENT ETHNIC ORIGINS . . . .. 68

7. DISRUPTIVE AND NON-DISRUPTIVE STUDENTS
OF DIFFERENT SEXES. . . . . . .. 69

8. DISRUPTIVE AND NON-DISRUPTIVE STUDENTS
OF LOWER SOCIO-ECONOMIC POSITION BY
ETHNICITY . . . . . . . .. .70

9. DISRUPTIVE AND NON-DISRUPTIVE STUDENTS
OF MIDDLE SOCIO-ECONOMIC POSITION BY
ETHNICITY ..... . . . . . 71

10. DISRUPTIVE AND NON-DISRUPTIVE STUDENTS
OF UPPER SOCIO-ECONOMIC POSITION BY
ETHNICITY . . . . . . . . 72

11. DISRUPTIVE AND NON-DISRUPTIVE STUDENTS
OF LOWER SOCIO-ECONOMIC POSITION BY SEX 73

12. DISRUPTIVE AND NON-DISRUPTIVE STUDENTS
OF MIDDLE SOCIO-ECONOMIC POSITION BY SEX. 74


viii













TABLE Page

13. DISRUPTIVE AND NON-DISRUPTIVE STUDENTS
OF UPPER SOCIO-ECONOMIC POSITION BY
SEX . ... . . . . . . 75

14. DISRUPTIVE AND NON-DISRUPTIVE BLACK
STUDENTS BY SEX . . . . . .. 76

15. DISRUPTIVE AND NON-DISRUPTIVE WHITE
AMERICAN STUDENTS BY SEX . . . .. 77

16. DISRUPTIVE AND NON-DISRUPTIVE HISPANIC-
ORIGIN STUDENTS BY SEX . . . .. 78

17. DISRUPTIVE AND NON-DISRUPTIVE STUDENTS
IN SCHOOLS WITH PRINCIPALS OF DIFFERENT
ETHNIC ORIGINS . . . . . .. 80

18. DISRUPTIVE AND NON-DISRUPTIVE LOWER
SOCIO-ECONOMIC STUDENTS BY ETHNICITY
OF PRINCIPAL . . . . . . ... 80

19. DISRUPTIVE AND NON-DISRUPTIVE MIDDLE
SOCIO-ECONOMIC POSITION STUDENTS BY
ETHNICITY OF PRINCIPAL . . . .. 81

20. DISRUPTIVE AND NON-DISRUPTIVE UPPER
SOCIO-ECONOMIC POSITION STUDENTS BY
ETHNICITY OF PRINCIPAL . . . .. 83

21. DISRUPTIVE AND NON-DISRUPTIVE BLACK
STUDENTS BY ETHNICITY OF PRINCIPAL . 84

22. DISRUPTIVE AND NON-DISRUPTIVE WHITE
AMERICAN STUDENTS BY ETHNICITY OF
PRINCIPAL . . . . . . . .. 85

23. DISRUPTIVE AND NON-DISRUPTIVE HISPANIC-
ORIGIN STUDENTS BY ETHNICITY OF PRINCIPAL 86

24. DISRUPTIVE AND NON-DISRUPTIVE MALE
STUDENTS BY ETHNICITY OF PRINCIPAL . 87

25. DISRUPTIVE AND NON-DISRUPTIVE FEMALE
STUDENTS BY ETHNICITY OF PRINCIPAL . 87

26. DISRUPTIVE AND NON-DISRUPTIVE STUDENTS
IN SCHOOLS OF DIFFERENT SIZES . . .. 88













TABLE Page

27. DISRUPTIVE AND NON-DISRUPTIVE LOWER
SOCIO-ECONOMIC POSITION STUDENTS BY
SIZE OF SCHOOL . . . . . .. 89

28. DISRUPTIVE AND NON-DISRUPTIVE MIDDLE
SOCIO-ECONOMIC POSITION STUDENTS BY
SIZE OF SCHOOL . . . . . .. 90

29. DISRUPTIVE AND NON-DISRUPTIVE UPPER
SOCIO-ECONOMIC-POSITION STUDENTS BY
SIZE OF SCHOOL . . . . . .. 91

30. DISRUPTIVE AND NON-DISRUPTIVE BLACK
STUDENTS BY SIZE OF SCHOOL . . .. 92

31. DISRUPTIVE AND NON-DISRUPTIVE WHITE
AMERICAN STUDENTS BY SIZE OF SCHOOL . 93

32. DISRUPTIVE AND NON-DISRUPTIVE HISPANIC-
ORIGIN STUDENTS BY SIZE OF SCHOOL ... 94

33. DISRUPTIVE AND NON-DISRUPTIVE MALE
STUDENTS BY SIZE OF SCHOOL . . ... 95

34. DISRUPTIVE AND NON-DISRUPTIVE FEMALE
STUDENTS BY SIZE OF SCHOOL . . ... 96

35. DISRUPTIVE AND NON-DISRUPTIVE STUDENTS
IN URBAN AND SUBURBAN SCHOOLS . . .. 98

36. DISRUPTIVE AND NON-DISRUPTIVE LOWER
SOCIO-ECONOMIC-POSITION STUDENTS BY
SCHOOL LOCATION . . . . . 98

37. DISRUPTIVE AND NON-DISRUPTIVE MIDDLE
SOCIO-ECONOMIC POSITION STUDENTS BY
SCHOOL LOCATION . . . . . ... 99

38. DISRUPTIVE AND NON-DISRUPTIVE UPPER
SOCIO-ECONOMIC-POSITION STUDENTS BY
SCHOOL LOCATION . . ... . . .. 100

39. DISRUPTIVE AND NON-DISRUPTIVE BLACK
AMERICAN STUDENTS BY SCHOOL LOCATION .. 101

40. DISRUPTIVE AND NON-DISRUPTIVE WHITE
AMERICAN STUDENTS BY SCHOOL LOCATION 102












TABLE Page

41. DISRUPTIVE AND NON-DISRUPTIVE HISPANIC-
ORIGIN STUDENTS BY SCHOOL LOCATION 103

42. DISRUPTIVE AND NON-DISRUPTIVE MALE
STUDENTS BY SCHOOL LOCATION . . .. 104

43. DISRUPTIVE AND NON-DISRUPTIVE FEMALE
STUDENTS BY SCHOOL LOCATION . . .. 105

44. DISRUPTIVE AND NON-DISRUPTIVE STUDENTS
IN SEVENTH, EIGHTH, AND NINTH GRADES 106

45. COMPARISON OF DISRUPTIVE AND NON-
DISRUPTIVE EIGHTH GRADERS AND SEVENTH
AND NINTH GRADERS COMBINED . . 107

46. REJECTED NULL HYPOTHESES IN ORDER OF
SIGNIFICANCE . . . . . .. 123

47. BLACK-AMERICAN, WHITE AMERICAN, AND
HISPANIC-ORIGIN STUDENTS IDENTIFIED
AS DISRUPTIVE IN SCHOOLS WITH PRINCIPALS
OF DIFFERENT ETHNIC ORIGINS . . 129











Abstract of Dissertation Presented to the Graduate Council
of the University of Florida in Partial Fulfillment
of the Requirements for the Degree of
Doctor of Philosophy

THE RELATIONSHIP BETWEEN DISRUPTIVE BEHAVIOR AND
SOCIO-ECONOMIC STATUS, ETHNICITY, AND SEX OF THE
STUDENT; THE SIZE, LOCATION, AND ETHNICITY OF THE
SCHOOL, IN SELECTED TRI-ETHNIC JUNIOR HIGH SCHOOLS

By

Armando R. Garrido

August, 1978

Chairman: Dr. S. Kern Alexander
Cochairman: Dr. Vynce A. Hines
Major Department: Educational Administration


The purpose of this study was to ascertain whether

there existed significant relationships between disruptive

behavior and the socio-economic status, ethnicity, and

sex of the student; and the location and size of the school.

A secondary purpose was to determine whether there was a

relationship between the ethnicity of the school principal

and the kinds of students who exhibited disruptive behavior.

The sample consisted of 1,080 students drawn from

12 junior high schools in Dade County with a total popula-

tion of 14,281 students. Half of the junior high schools

were located in urban Dade County, and the other half were

located in suburban Dade County. Two of the junior high

schools were of small size, 7 were of medium size, and 3

were of large size. Fifty percent (50%) of the principals

were white American, and the other 50% were non-white

American. Ninety students were selected from each school,











comprised of equal number of males and females from each

of the 3 ethnic groups.

During the spring of 1978, questionnaires were used

to obtain measures of socio-economic status, ethnicity, sex,

and disruptive behavior of the students in the sample.

Measures of the schools' characteristics--size, location,

and the ethnic origin of the principal--were also obtained.

Hollingshead's Two Factor Index of Social Position was used

in order to determine the socio-economic status of each

student in the sample. The questionnaires were completed

by the students under the supervision of a guidance coun-

selor. The assistant principal in charge of discipline for

each school reviewed them to ascertain that the information

about the students' school behavior was accurate. Of the

1,080 students selected, 123 were identified as disruptive.

Two statistical techniques were used to analyze the

data in this study. Multiple regression was used in testing

the first hypothesis, and chi square was used in testing

the rest.

Ten conclusions were drawn from the analysis of the

data in this study:

1. The proportion of disruptive lower socio-

economic status students was significantly higher than the

proportions of disruptive middle- and upper-class students.

Furthermore, this variable had the highest relationship

with the incidence of disruptive behavior.


xiii











2. The proportion of disruptive male students

was significantly higher than the proportion of disruptive

female students.

3. The ethnicity of the student was incidental to

the incidence of disruptive behavior when socio-economic

status was taken into consideration.

4. The proportion of disruptive lower-socio-

economic-status male students is significantly higher than

the proportions of disruptive middle- and upper-socio-

economic-status male students.

5. The proportions of disruptive black American

and Hispanic-origin male students are significantly higher

than the proportions of disruptive black American and

Hispanic-origin female students.

6. The proportion of disruptive lower-socio-

economic-status students in schools with white American

principals was significantly higher than the proportion

of disruptive lower-socio-economic-status students in

schools with non-white American principals.

7. The proportion of disruptive black American

students in schools with white American principals was

significantly higher than the proportion of disruptive

black American students in schools with non-white American

principals.

8. There was no significant difference in the

proportions of disruptive students of different ethnic

origins in schools with non-white American principals.

xiv











9. Schools with white American principals identi-

fied as disruptive a significantly higher proportion of

black American students and a significantly lower propor-

tion of white American students than schools with non-

white American principals.

10. The proportion of disruptive students in the

eighth grade was significantly lower than the proportions

of disruptive students in the seventh and ninth grade.
















CHAPTER I


INTRODUCTION


Disruptive behavior has always been an area of

great concern for educators, not only because society

expects that schools, as one of its institutions, will

play a major role in the socialization process of its

youth, but also because, for the learning process to take

place, it is necessary that the classroom environment be

conducive to education. The educational purposes of the

school are accomplished best in a climate where the duties

and responsibilities of the students and the rules and

regulations of the school are respected.

About a decade ago a major transformation in the

modes of behavior of our youth began to take place, to

the dismay of governmental authorities, parents, and

educators, significantly increasing the generation gap.

The emphasis on guaranteeing the constitutional rights

of students and minorities, the drastic changes brought

about by recent Supreme Court decisions upon the procedures

for controlling students' behavior, the Viet Nam War and

the anti-war demonstrations, the assassination of poli-

tical and civic leaders of the sixties, violence on

television, the increase in the divorce rate and in the

1












number of homes where both parents work, and the rapid

evolution of our youth culture have all been factors

which have produced a shattering impact upon student

behavior. In fact, although disruptive behavior is

not new to American schools, it has become more frequent

and has involved a greater number of students.

In Florida, the problem of disruptive behavior

in the schools has affected every school district and

has resulted in fiscal and human capital losses to the

state. Because of this, in 1973, The Governor's Task

Force on Disruptive Youth was created to conduct studies

throughout the state.

During the junior high grades, students experi-

ence a drastic change in the rate of physical growth

and for them reaching puberty has great physiological

and psychological implications. This period of time in

a student's life is considered the most difficult one

in all grades, K through 12 inclusive. Because of these

changes,it is in the junior high school where students

manifest the most behavioral problems.

Many hypotheses have been formulated on the

subject of disruptive youth in schools. Several of

them shall be examined in an attempt to arrive at some

qualified, enlightened answers. Hopefully, if factors

that cause disruptive behavior can be identified, then

measures may be taken to prevent its occurrence. It is












usually easier and preferable to take preventive measures

to solve a conflict of this nature than it is to try to

arrest the problem once it has erupted openly. Disruptive

behavior not only interrupts the learning process within

the classroom, but in the more serious cases may result

in the forceful removal of the student from the classroom.

It follows that his removal from the academic environment

necessarily has deleterious effects upon his learning

process. The more times the suspension occurs, the less

probable that the student eventually will catch up with

his/her school work. Expulsion is a more serious matter

because it denies the youth the opportunity of rehabilita-

tion, at least within his/her own environment.


Nature of the Study


This study was an associational study of various

student characteristics, some junior high school char-

acteristics, and student suspensions during the first

eight months of the 1977-78 school year. Twelve of the

forty-six junior high schools in Dade County participated

in the study. Each of the schools had a representative

population of white Americans, black Americans, and

Hispanic origin students. Three variables of the students--

ethnicity, socio-economic status, and sex, together with

three variables of the school--size, location, and ethnicity

of the principal, were analyzed with the frequency of student












suspensions and statistically tested. Hollinqshead's

Two Factor Index of Social Position was used to

determine the socio-economic status of the students.


Statement of the Problem


The primary purpose of this study was to

attempt to ascertain whether socio-economic status,

ethnicity, and sex of the student, and the location

and size of the school can be predictors of disruptive

behavior in tri-ethnic junior high schools, of white

American, black American, and Hispanic-origin

students.

A secondary purpose was to discover whether

there is a relationship between the ethnicity of the

school principal and the kinds of students who exhibit

disruptive behavior. More specifically, this research

sought answers to the following questions:

1. What is the difference in the number of

disruptive students of lower, middle, and high socio-

economic positions in junior high schools?

2. What is the difference in the number of

disruptive students of white American, black American,

and Hispanic-origin students in junior high schools?

3. Is there any difference in the incidence

of disruptive behavior between male and female students

in junior high schools?












4. Is there a difference in the number of

disruptive students in urban and suburban junior high

schools?

5. Is there any difference in the incidence

of disruptive behavior in small, medium, and large

size junior high schools?

6. Does the ethnic origin of the school principal

have any effect upon the kind of students who exhibit

disruptive behavior in junior high schools?


Limitations of the Study


Three limitations were recognized in this

study:

1. The results of this study have validity

only concerning disruptive behavior in tri-ethnic junior

high schools in Dade County, Florida.

2. The information contained in the question-

naires was accepted as accurate.

3. No consideration has been given to whether

teacher effectiveness is related to disruptive acts

occurring in the classroom.


Definition of Terms


A disruptive student was operationally defined

as any junior high school student who is removed from












the school environment for behavior reasons during the

first eight months of the 1977-78 school year.

A junior high school student was operationally

defined as any student in the seventh, eighth, or

ninth grades of a junior high school.

A Hispanic-origin student was operationally

defined as any student born in a Hispanic country or

of Hispanic descent.

An urban junior high school was operationally

defined as any junior high school in Dade County

within a six-mile radius from downtown Miami.

A small size junior high school was operationally

defined as one with a school population of less than

1000 students.

A medium size junior high school was operationally

defined as one with a school population of between 1000

and 1499 students.

A large size junior high school was operationally

defined as one with a school population of 1500 or more

students.


Sampling


A stratified random sample of equal numbers of

male and female students from each ethnic group (white

American, black American, and Hispanic-origin) was

drawn from a computer printout by ethnic origin of the













student population of each of the twelve junior high

schools selected. The sample of each of the twelve

junior high schools selected in this study contained:

15 male white American students

15 female white American students

15 male black American students

15 female black American students

15 male Hispanic-origin students

15 female Hispanic-origin students


Data Collection


A questionnaire was used to gather the data

needed for this study (see Appendix). It had the

student's name at the top. This questionnaire indicated

that the student's name should be detached from the

form before it was returned, because of a requirement

of the Dade County Schools Research Committee designed

to maintain the privacy rights of the students involved

in studies. The questionnaire provided the following

information.

1. grade

2. sex

3. ethnicity

4. occupation of the student's father

5. occupation of the student's mother

6. level of schooling completed by the student's

father.











7. level of schooling completed by the student's

mother

8. whether the student had been suspended

9. ethnicity of the school principal

10. name of the school.



Significance


In the ninth annual Gallup Poll of the public's

attitude toward the public schools, discipline (disruptive

behavior) was singled out as the major problem confronting

the public schools of the nation.

This study increased the existing body of knowledge

about the relationship of socio-economic status, ethnicity,

and sex of students, the ethnicity of the principal, the

size and location of the junior high school, and disruptive

student behavior. There had been some research done on

disruptive behavior previously, but little or none had been

done in a tri-ethnic setting. The findings of this study

have practical significance for educators who practice

their profession in urban and suburban, multi-ethnic

settings and in particular for those educators working in

Dade County, Florida. The results of this study will be

made available for sharing with any and all interested

educators.







9



Organization of the Study


This introductory chapter has included the state-

ment of the problem, the nature, limitations, and signifi-

cance of the study, as well as the method of sampling and

data collection. Chapter II will include the review of

the literature. The design of the study will be discussed

in Chapter III. Chapter IV will present the results of the

study, and the summary, discussion, and conclusions will

be presented in Chapter V.














CHAPTER II


REVIEW OF THE LITERATURE


The major concern of this study is the relationship

between disruptive behavior and socio-economic status,

ethnicity, and sex of the students; and the location,

size, and ethnicity of the principal of the school.

A review of the literature found no study in-

corporating these variables, but it yielded many studies

about disruptive behavior some of which incorporate one

or more of the variables.

The literature on disruptive behavior has been

varied. Studies have been conducted in such areas as pre-

vention and identification (Gloeckler et al., 1968; Mussman,

1968; Hegstrom and Hugh, 1969; Nelson, 1971), behavior

modification techniques (Edwards 1968; Casstevens, 1969;

Wodarski, 1970; Burrows, 1971; Starky, 1973), perceptions

(Mendell, 1968; Driscoll, 1970), activism (Erickson et al.,

1965; Trump and Hunt, 1969), school discipline (Kounin,

1970), mental retardation (Szurek and Berlin, 1968),

social class (Warner, 1949; Hollingshead, 1949; Davis,

1953; Conant, 1961), ethnicity and ethnic composition

(Blake, 1960; Smith, 1962; Gurin, 1966; West, 1966), emo-

tional disorders (Hewett et al., 1967; Braun and Lasher,

10











1970), juvenile delinquency (Block and Flynn, 1956;

Reckless and Dinitz, 1972), delinquency and self-concept

(Balester, 1956; Atchinson, 1953; Scarpitti, Murray,

Dinitz, and Reckless, 1960; Lively, Dinitz, and Reckless,

1962; Lefeber, 1965; Fitts and Hamner, 1969), and

autistic children (Eosch, 1970).


Literature on Disruption


The Ninth Annual Gallup Poll of the Public's

Attitudes Toward the Public Schools (1977) reported

the highest percentage yet recorded of parents of public

school students citing discipline as the number one

problem in the schools, with integration/segregation/

busing being in second place, and lack of proper financial

support in third.

A study of the experience of teachers with dis-

ruptive behavior in the Dade Public Schools (1976) reported

that the junior high school teachers spend a considerably

greater proportion of their time in dealing with disruptive

behavior than elementary and senior high school teachers,

with 12.2 percent being struck by students, 39.6 percent

being threatened by a student with physical harm, and

72.7 percent having their instructional process completely

disrupted.

Duke (1978) reported that administrators of

urban and non-urban high schools in California and New York











identified truancy, skipping, and lateness to class as

the three most pressing discipline problems. He also

indicated that most administrators found themselves not

enforcing school rules consistently.

In contrast, King-Stoops and Meir (1978) listed

fighting, lack of respect for selves, other students,

and teachers, and destruction of school materials and pro-

fanity among the 10 more important discipline problems

identified by teachers.

Student teachers, in a study conducted by Driscoll

(1970) identified failure to follow directions, making

noise in the halls, whispering, talking in class, and chew-

ing gum among the most frequent types of disruptive

behavior. Being under the influence of narcotics,

stealing, starting fires, and bomb threats were identi-

fied among the most serious offenses.

In a study on early identification of children

who are likely to display poor social adjustment, low

academic achievement, and/or delinquency, Feldhusen (1971)

found that classroom behavior traits, arithmetic achieve-

ment, child's parents' marital relationship, and maternal

discipline were predictors of late social adjustment.

Teacher ratings of social adjustment, I.Q., sex, parents'

educational level, and classroom behavior were found to be

predictors of academic achievement.










The purpose of a study conducted by Feldhusen,

Benning, and Thurston (1964) was to link elements of

students' backgrounds with school misbehavior. After

analyzing the home environment of students who exhibited

disruptive behavior in the classroom, some psycho-social

correlates of misbehavior were found:

1. The discipline of the father was either too

lax or too strict,and the supervision of the mother

was inadequate.

2. The parents were indifferent or hostile toward

the student, and the family lacked unity.

3. The parents were not close and found it

difficult to discuss the child's problems.

4. The parents disapproved of many things in

their child and were not happy with the community where

they lived.

5. Both parents believed they could not influence

the development of their child and resorted to angry

corporal punishment when disciplining their child.

6. The parents' leisure time activities did not

help the social development of the child; as a result

of this attitude they thought that other children were

bad influences upon their child.

In a more recent study, they also discovered that

boys prone to delinquency achieved less in mathematics

than the non-delinquency-prone boys, and the former were

ranked much lower in their graduating class than their

counterparts.











Kaga (1972) pointed out that twelve-year-olds

are presented by Western society with local phenomena

surrounding school, drugs, sexuality, authority, and family,

each of which generates uncertainty that the child must

resolve. Contemporary fifteen-year-olds are waging a war

against feelings of isolation and are rendered anti-social

as a paradoxical reaction to these feelings. Racial strife,

density of population, and even more important, lack of

values and central ideology, continue to loom as potential

catastrophes in the future and, of course, often result

in disruptive behavior.

S. R. St. J. Neill (1976) used etiological methods

previously applied mainly to young children (Blurton-Jones,

1972) with pre-adolescent boys in a playground situation.

These methods were well suited to the playground situation

because of the ease of observation without disturbance and

because of the range of behavior shown and its dominance in

such a situation over verbal communication. The older boys

presented a greater incidence of violent behavior and fight-

ing, suggesting that age may be a possible variable in the

prediction of disruptive patterns of behavior.

Miller (1974) reported that the average juvenile

delinquent has an I.Q. of 95 and is two to four years below

his potential by the time he has been in the public schools

for seven years.












Twelve principals from a midwest city system met

briefly with a number of professors and administrators

from the College of Education of the Ohio State University,

as reported by Cunningham (1969). The Dean of the College

of Education, in an objective report of his experience as

an inner city junior high school principal, observed the

phenomenon of the principal in relationship to disruptive

behavior in the school. There had been a faculty walk-out

previously due to school conditions. The students were

mostly black. Absenteeism prevailed. About one-fifth of

the entire student body was absent every day. The only

time students showed up was at lunch time in many cases.

Lunch was partly federally funded. Students came into

the school building in spite of guards, had their lunch,

and went out into the street again. Absenteeism among

the school's eighty-five teachers was quite prevalent

also. Fights broke out quite frequently. One teacher had

been shot ten days before the author arrived on the scene.

He had been held up on the street, adjacent to the school,

and shot with a pellet gun.

Duke (1976) examined the issue of who misbehaves

in the article by that title. In considering a wide

range of variables, it was found that students were apt

to show evidence of dirsuptive behavior if they had

instances of failure in elementary school. He also












stated that there is a positive indication that

disruptive behavior and intelligence are inversely

related, i.e., the more intelligence, the less the

likelihood of showing disruptive behavior and vice

versa. The final words of the article point out the

need for further research to wit: research concerning

itself with "real world" types of investigation rather

than more esoteric "unreal" types of research. The

author also points to the fact that researchers should

not be banned from the schools only because of the

sensitive nature of the schools's discipline.

Redl (1975) was saddened at the fact that

disruptive behavior results in suspension and

expulsion which, in turn, create hostility and result

in more disruptive behavior. Only when a child and

his environment are so badly matched that continuation

would present the possibility of life-long scars should

the child be removed from his learning environment.

Henning (1949) distributed questionnaires to

twenty-five high school principals and asked them about

the extent and seriousness of student misconduct. It

is significant to note that twenty-eight years ago the

most serious offenses were considered to be lying, petty

theivery, and getting together in halls and lavatories.

These examples of misconduct seem hardly worthy of

mention in today's more violent school environment.












We can contrast the above with the findings of

Cutts and Moseley (1957) who cited the most common

instances of misbehavior as the following: talking,

physical attack, unexcused absences, throwing things,

and physical activity. They also listed items as

diverse as chewing gum and immorality as examples of

disruptive behavior.

Studying the different perceptions of disruptive

behavior among secondary school teachers, counselors, and

deans, Mendell (1968) found that deans chose more severe

punishments for disruptive students than did secondary

school teachers and counselors. The older the teacher

the more severe disciplinary measures recommended. Male

educators chose greater penalties than female educators.

He also pointed out that educators chose more severe punish-

ment for male students than for female students.

The National Institute of Education (1977)

conducted a study to determine the frequency and serious-

ness of crime in elementary and secondary schools in

the United States.

The study was divided into three phases. In

Phase I more than 4,000 school principals were asked to

report, through a mail survey, the incidence of illegal

or disruptive activities in their schools. The parti-

cipating schools were chosen at random.












In Phase II, field representatives conducted

on-site surveys of a representative sample of 642

junior and senior high schools. Principals, teachers,

and students were surveyed. They also reported infor-

mation about themselves, their schools, and their

communities.

In Phase III, a more intensive study of ten

schools was conducted. These ten schools had been

identified as having a history of crime and violence

but had shown a dramatic improvement in a short time.

Some of the most important findings of the study

were, in summary, the following:

1. In school, risk of violence to teenagers is

greater than elsewhere.

2. The larger the community, the greater the

proportion of schools having a serious problem.

3. Higher levels of school crime are reported

in secondary schools than those in elementary schools.

4. The proportion of teachers attacked is smaller

in rural areas and in senior high schools than in large

cities and in junior high schools.

5. In secondary schools, personal violence and

vandalism are much more prevalent than in elementary

schools; on the other hand, in senior highs and junior highs

the incidence of property offenses is about the same, al-

though personal violence is most pronounced in junior highs.











6. The classrooms are the safest places for

students in school with high risks during the between-

class rushes in hallways and on stairs.

7. Taking all factors into consideration, there

is no apparent relationship between a school's racial/

ethnic composition and the risk of violence there.

8. More violence and vandalism are experienced

in larger schools and schools with larger classes.

9. Students' feelings of frustration can erupt

in violence if students do not feel that their courses

are relevant and that they have some control over school

events.

10. The most likely violent students are those who

give up on school.

11. A key factor in reducing violence seems to be

a consistent system for running a school were known rules

are firmly and fairly enforced.

12. A central conclusion is that the principal's

role appears to be a critical factor in that the principal's

leadership and initiation of a structure of order seem to

differentiate safe schools from unsafe ones.

13. As found, the principal's ability to initiate

a structure of order in the school is equally important

to his/her personal style of leadership, especially with

fair, firm, and most of all, consistent action on his/her

part.










A perusal of Dissertation Abstracts yielded some

studies on disruptive behavior. Burrows (1971) investigated

the effects of systematic changes in the levels of

teacher approval on students' disruptive behavior and

self-concepts. In one classroom the teacher eliminated

approval for three weeks. In another classroom the teacher

increased the approval level for six weeks. In classroom

No. 1 a functional relationship between levels of teacher

approval and student disruptive behavior was demonstrated.

In classroom No. 2 a decrease in teacher approval resulted

in no significant changes in disruptive behavior nor self-

concept. No associations were found between self-concept

changes and achievement, intelligence, socio-economic

status, or sex.

Hendrix (1970) stressed the need for able and

dedicated teachers who know the ghetto and its problems

and understand the psychological and social deficits of

these students. Studying the causes of why inner city

children do not achieve as well as others, he found,

"Discrimination and racism, family disorganization, poor

self-image, white colonial middle-class schools in Black

ghettos, and inadequate teachers are documented as some

of the most significant causes of this failure" (p. 283).

According to his findings, some of the most

important needs of inner city students are: "(a) positive

self-image, (b) expanded aspirational level, (c) success











experiences, (d) peer group encouragement of academic

success, (e) exposure to black culture, and (f) an under-

standing of the general culture" (p. 283).

In a study of how students' misbehavior was per-

ceived by teachers in the Michigan Public Schools,

Teitelbaum (1970) found that the teachers perceived the

most serious and most frequent disruptive behavior involved

students' relationships to other students, followed by

violations of school authority.

In a study designed to clarify the conditions that

determine teachers' behavior in their reaction to child

misbehavior, Victor (1970) reported that while his study

yielded no statistically significant findings, there were

a number of significant trends. Individuals who scored

higher in teacher direct attitudes participated more in

misbehavior. Furthermore, this difference was the result

of non-verbal behavior. The high conceptual level teacher

direct group gave more positive sanctions than any other

group and no differences were found between personality and

attitude, and the adaptability index.

Wodarski (1970), in a study to determine to what

extent behavior modification techniques, based on Skinner's

operant theory, were successful in helping to improve

non-studying and disruptive behaviors in ghetto schools,

found that the introduction of behavior modification








22

techniques resulted in high rates of studying behavior and

low rates of non-studying and disruptive behaviors.

The purpose of a study by Niewiadomski (1971) was

to determine student perceptions of school discipline prac-

tices, the seriousness of the information, and the fairness

and the effectiveness of disciplinary actions. He reported

that disciplinary practices in the school studied were

found to be moderate, with the use of drugs, destruction

of school property,and stealing the most serious dis-

cipline problems. Disciplinary actions were found to be

fair except in cases of disrespect to teachers, forging

passes, and stealing. The disciplinary actions were found

tobe effective except in cases of gambling, lying, and

stealing.

Morgan (1955) compared social background of

parents with their attitudes on matters of high school

discipline, punishment methods, and positive concepts of

discipline. He indicated that there seems to be little

difference in attitudes by social background factors

except in the categories of occupation, family income,

and education.

The greatest number of differences occur in the
application of methods of punishment to specific
offenses. The least number of differences occur in
connection with the positive concepts of discipline.
The variety of punishments endorsed seemed to increase
directly with the amount of education and the amount
of family income. Among the occupational groups, the
business and professional parents are most tolerant
toward today's youth and least inclined toward severe
measures. (p. 756)












In "An Analysis of Personality and Demographic

Factors Concerning Students Involved in Disciplinary

Problems," Bealer (1967) found that the variables of more

significance to discrimination were personal education

aspiration, peer parental relationships, rank in class,

and impulse expression for males, and involvement in

extracurricular activities, rank in class, and religious

attendance for females. If individuals' scores were low,

it was quite likely that they would be involved in dis-

ruptive behavior. The opposite resulted for individuals

with high scores.

Bloom (1964), studying the attitudes of mentally

retarded students, concluded that there were significant

differences in responsibility, emotional stability, self-

regard, and attitudes toward work that were attributable

to education alone. Life style was a significant pre-

dictor of attitudes towards frustration tolerance, schools,

and teachers. There were no significant differences among

ethnic groups.

Cummins (1964) investigated the effective and

cognitive characteristics of disruptive students. He

reported no difference in the cognitive characteristics

of disruptive and non-disruptive students. It was also

found that affective characteristics did not differ in

disciplinary and non-disciplinary students. lie concluded

that disciplinary and non-disciplinary students are












essentially similar in their affective and cognitive

characteristics.

Scurry (1976), studying the relationship among

black senior high school students and their percep-

tions of alienation and internal and external control,

indicated:

1. Disruptive high school students perceived them-
selves as more alienated than the non-disruptive
high-school students.
2. Disruptive high school students did not perceive
themselves anymore internal-external than the
non-disruptive high school students. (p. 3541)

Wilde (1976) sought to determine the efficacy

of punishing videotaped models as a tool to diminish the

incidence of disruptive behavior in two junior high

school classes. He concluded that modeled punishment

had no effect on the incidence of disruptive behavior

upon the experiment's subjects.


Literature on Socio-economic Status


Coleman (1966) found in his famous study, that

all schools are very similar in the way they affect

achievement when the socio-economic background of the

students is taken into consideration. He also observed

that socio-economic factors have great importance in

predicting academic achievement. Furthermore, he

reported that the family economic level has the highest

relation to achievement for all minority groups.













Minority students also are more affected by the quality

of the school they attend:

The average white student's achievement seems
to be less affected by the strength or weakness
of his school's facilities, curriculums, and teachers
than is the average minority pupil's. To put it
another way, the achievement of minority pupils
depends more on the schools they attend than does
the achievement of majority pupils. (p. 22)

Hollingshead (1949) noted that the higher rate

of failure among lower class students is the combined

result of the values of the lower class students and the

bias of the teachers who are more inclined to extend

extra help to middle and upper class students.

Hindelang (1971) considered age and sex as

variables in studying the versatility of delinquent

behavior, i.e., whether children engaging in delin-

quent behavior tend to perform a wide variety of acts

or whether they confine themselves to a very narrow range

of acts. He found that females tend to engage in a wider

variety of delinquent acts than males and that males tend

to engage with greater frequency than females in street-

gang-related delinquencies. His study was supportive

of the belief that socio-economics may play a part in

disruptive behavior, because street gangs tend to exist

in lower socio-economic neighborhoods.

Reissman (1953) addressed the problem of the

relationship between aspiration and socio-economic











status. A person's peer group has an effect on the

interchange between social situations and aspiration

levels.

McPartland and McDill (1975) of the Center for

Social Organization of Schools, Johns Hopkins Uni-

versity, pointed out that "a student's success and

status in school have a unique relationship with the

probability of serious offenses, over and above what

is accounted for by family background and academic

ability" (p. 10).

An article by Lufler (1978), reporting the results

of a two-year study conducted by the Center for Public

Representation in Madison, Wisconsin, pointed out that

teachers felt "discipline problems are an extension

of out-of-school problems" (p. 424). The study also

found that most of the disruptive students came from

single-parent homes, from low socio-economic status

homes and/or from families that move frequently. Data

analysis revealed that disruptive students tended to

receive lower grades and were less involved in school

activities.

Brookover et al. (1967) concluded that the

influence of self-concept on achievement was possibly

greater than that of mental ability. In previous












studies (1964 and 1965), he and others had found that

a student's overall ability self-concept is related to

his achievement in school. Cook (1970) found that

black, low socio-economic, disadvantaged students had

significantly lower self-concepts than those of their

white counterparts. Branch (1974) discovered that

disruptive students in middle schools had lower self-

concepts than those of non-disruptive students in the

same school environment.

Jencks (1972) pointed out that there are many

who believe that the school cannot improve the achieve-

ment of the disadvantaged students, that academic per-

formance is predetermined by the socio-economic status

of a student's parents.

In the study "Toward Equal Educational Opportunity"

(1972), conducted by the United States Senate Select

Committee on Equal Educational Opportunity, it was

observed that advantaged children and children from

deprived homes begin their education at different starting

lines:

A child's socioeconomic status, his parents'
educational level and occupational status, the
extent to which he and his family are the victims
of racial discrimination and all the other ele-
ments of his home environment determine in large
measure his performance in school and his success
or failure in life. (p. 5)

An article by Pearl (1965) observed that:

There appears to be a general consensus
that low income youth, when contrasted with











more affluent counterparts, are characterized
by the following: a poorer self-image, a greater
sense of powerlessness, a more fatalistic
attitude toward life, a lack of future orien-
tation, and a greater potential for impulsive
"acting out." (p. 89)

This statement is highly significant since it singles

out a variable, low income, as the most important factor

in developing the attitudes most often associated with

disruptive youth.

There is no doubt that all the variables are

somewhat interrelated. The question becomes how to

rank them in order of their importance as predictors of

disruptive behavior.

According to Sexton (1961) the failure rate

among elementary school children whose families earned

$3,000 or less per year was six times greater than

the failure rate among those families earning $9,000

per year. This disproportion in the figures cannot be

attributed adequately to mere chance. Some of the

students falling in the lowest income-level families

had children manifesting serious behavior problems--

failing in elementary school studies and engaging in

disruptive behavior--while no problem children were

found among the families within the highest income

bracket.

An article by Miller (1958) about the etiology

of delinquency suggested that adolescent members of











street corner groups in lower class communities,

commit delinquent acts in an attempt to adhere to the

forms of behavior and to the standards of value of

their community. The article further concluded that

"many lower class individuals feel that their lives

are subject to a set of forces over which they have

relatively little control" (p. 11) and therefore when

they are faced with alternatives of accomplishing similar

objectives, the non-law-abiding avenue offers greater

and faster return for a smaller investment of their

energy.

Schonfeld (1968) contended "socio-economic

affluence has been found to play an important prepara-

tory and determining role in how youth copes with his

adolescent crisis" (p. 492). Does this mean that

high income youths are definitely better adjusted than

their lower income counterparts? Not necessarily:

it means only that several factors come into play when

there is definite family affluence, which the low

income youth does not have. He added that these

factors include the extent to which each youth derives

consequences from unsocial or anti-social behavior,

i.e. in the case of a high-income family adolescent,

his likelihood of escaping repercussions from such












acts, since the family usually has the means to retain,

and does indeed retain, skilled lawyers, or possibly pay

damages, causing charges to be dropped through techni-

calities, is a possibility not available to lower-

income-family adolescents. On the other hand, the

lower-income-family youth almost inevitably has to

shoulder the responsibility for his actions.

Erickson (1973) considered the importance of

socio-economic status in his carefully worded article,

"Group Violations, Socioeconomic Status, and Official

Delinquency." The author makes a point of emphasizing

that almost all delinquent acts are those (1) stem-

ming from lower class children, (2) are a group

event predominantly. The first part of this hypoth-

esis exactly agrees with this researcher's view-

point. The article outlined the study conducted to

prove the validity of his hypothesis. Violations of

the law by lower class boys are more frequent than

violations by higher and middle class boys. This seems

to be a pattern that carries over into the adult world.

There is also evidence that lower socio-economic

children tend to accrue more arrests and convictions

than their higher socio-economic-status counterparts.

Erickson supported this tenet by actually quoting a

figure of 11% greater proportional share of arrests












for all offenses for low socio-economic-status children as

compared with 9% less than their proportional share for

middle-class-status children. Higher class children

unaccountably accounted for a slightly lower than their

proportional share of arrests (less than 2%).


Literature on Ethnicity


The Governor's Task Force on Disruptive Youth

(1973) studied the demographic aspects of disruptive

youth in order to be able to determine the significance

of demographic variables in relationship to disruptive

youth in the schools of the State of Florida. Academic

variables, race, and socio-economic variables were

grouped together as the most prevalent factors. The

study suggested that:

. if a pupil was male, black, had a low sixth
grade test score, a low grade point average, a low
verbal aptitude score and had not been referred
for psychological services, he was more likely to
become a disruptive student and be either expelled
or suspended from school. (p. 9)

Zirkel and Gable (1977) conducted a study to

examine the test-retest reliability and construct

validity of selected types of self-concept measures.

These were non-verbal, verbal, and pictorial scores and

observer ratings for black, Puerto Rican, and white

adolescents. Results of these measures showed black











students received a greater number of poor ratings and

evidenced poorer self-concepts.

Walberg et al. (1974) reported that while blacks

rated higher in offenses such as driving without a license,

skipping school, and beating up and threatening others,

the incidences of the offenses did not show significant

differences between blacks and whites. He also observed

that there is ethnic bias in the recording and disposition

of juvenile cases.

Higgins (1974) proposed that one focus of pre-

and in-service training should be the development of more

precise objectives for the work of desegregation. In

view of all the desegregation-generated hostility caused

by placing poor black students in middle-to-high class

neighborhood schools, the value of busing seems to be

offset by the increase in disruptive behavior.

Studying group disorders in the public schools,

Ritterband and Silberstein (1973) found that the

presence of black teachers slightly inhibited the occur-

rences of non-political disorders. They also observed

that:

Equally plausible is the notion that
disorder occurs when inexperienced teachers
(who tend to teach the non-white pupils) cannot
capture their pupils' interest and/or cannot
control then. ... .however, no matter what
the school characteristic, whether size
(presumably implying bureaucratization and
impersonality) [or other factor]. (p. 466)











Williams and Gold (1972) found that "white

girls are no more or less frequently or seriously delinquent

than black girls; and white boys, no more or less frequently

delinquent than black boys" (p. 215). They further pointed

out that whether a policeman chooses to ignore or not to

ignore delinquent behavior may be contingent on such factors

as the juvenile's sex, race, and social status. The same

factors affect the citizen making the complaint.

White (1968) examined the situation in which urban

high school students were observed on the basis of many

variables, including (1) father's race; (2) mother's race;

(3) father's and mother's occupational prestige; (4) father's

and mother's education; (5) grade in school; (6) grade point

average, (7) sex. The findings about race evidenced that

black students were more alienated than white youths; black

females evidenced more alienation than males.


Literature on Sex


Touliatos and Lindholm (1976) reported that being

a female student in regular classes was a predictor of

good behavior, being a male student from a high-social-

class home in regular classes was a predictor of not

having personality disorders. In contrast, being in

the higher grades and from a lower socio-economic-status

home in regular classes was a predictor of disruptive

behavior.











Howard (1978), in a study of factors on school

vandalism, concluded that the middle school or junior

high school student is the age group within which most

vandals have been found. He also pointed out that

vandalism is almost exclusively a male activity,and

there is a high correlation between delinquent stu-

dents and educational deficiency. The study further

indicated that many parents associate school discipline

with the school principal.

Poorman, Donnerstein, and Donnerstein (1976)

noted that males as opposed to females tend to engage in,

as well as provoke, higher levels of aggressive behavior.

Results of this study indicated that aggression between

females was relatively stable over age. In contrast,

aggression between males increased significantly. They

suggested that this increase is the result of this kind

of behavior being rewarded by peers and parents.

In a study designed to investigate the touch

interactions between junior high school students, Willis

and Reeves (1976) noted that females were observed to use

fists and other aggressive touches, something that had not

been observed in an earlier study. They concluded that

"the increased aggressive touch may be a reflection of the

increased aggression of young females that has been reported

in recent years" (p. 91).

Rice (1975) expounded on the effects of task-focused

and approval-focused discipline techniques. How is the











target of the discipline viewed by his observing peers?

Two variables were studied--sex and type of desist

(command). The scores of the personality-trait of the

student were studied as well as the personality-trait

rating of the teacher, the confidence in the rating

of the child and of the teacher. The students who

hastened to the task-focused desists differed signifi-

cantly in their responses on the measures from those who

heard the approval-focused desists. Neither the sex of

the rater nor the sex of the rate and type of desist

interaction was significant (p 10). This seems to bear

upon the question, raised earlier, regarding the possi-

bility of sex as a significant predictor of disruptive

behavior.


Literature on School Location


In the Teacher Opinion Poll of the National

Education Association (1974), 5.4% of the sampled urban

secondary school personnel reported they had experienced

on-the-job physical assaults, while only 2.0% of the

sample's rural and suburban personnel said they had

similar experiences.

Koch (1975) found that the rate of teacher

assault and personal property damage has increased

dramatically in urban school districts.










Cloward and Ohlin (1960) considered delinquent

behavior primarily centered upon lower class, urban,

male adolescents. It is interesting to note the very

real and pronounced difference existing between the

incidence of disruptive behavior in lower class urban

and lower class rural adolescents. The answers may be

that the rural environment does not pose a threat of

hostility to the low-income-family youth because he

will not be likely to be confronted with and defeated

by middle or upper class children in social, academic,

and other achievement areas, but will be instead con-

fronted with children of like backgrounds and similar

likelihood of success levels.


Literature on School Size


Kelly (1978) suggested that observed physical

conflict between students will increase as relative

school population density increases. He further contended:

The presence of such . student populations
and a variety of recent professional and public
observations concerning school violence, absen-
teeism, and the decline of achievement standards
suggests that some correspondence between these
factors may indeed exist. . The current
literature indicates that student conflict and
corollary suspensions are far more prevalent in
large urban secondary schools than in suburban or
rural schools. . In its report on causes of
student conflict in California's schools, the California
State Department of Education cited school overcrowding
as a major causal factor, noting that in schools
where overcrowding is severe, the students report it
is tiring to go to classes which are too large, to
stand in lines to eat in the cafeteria or use the












restrooms and to line up to get a locker. The
attendant noise and fatigue (alone) provide a
climate for unrest. (pp. 152 & 156)

Baron (1975) studying the correspondence of

human overcrowding in living space to specific social

pathologies, reported public schools reflecting more

consistently adverse patterns of overcrowding.

The size and enrollment of the school has

been associated with discipline problems, violence,

and vandalism. Kingston and Gentry (1977) noted that

students in large high schools found it difficult to

identify with their schools and seldom participated

in school activities. The authors observed that this

may be the cause of disciplinary problems. In another

study, DeBuzna (1974) reported that the rate of

vandalism increased as the number of students enrolled

in the school increased.

The studies of The Teachers Task Force (1974)

indicated a negative relationship between school over-

crowding and academic achievement, while a study

conducted by Davis (1972) found that students in medium

to large size high schools (2,000-4,000) evidenced

lower grades than students in small size high schools.


Literature on the School Principal


Goldman (1961) indicated that teachers in schools

with high rates of vandalism described their principal











as weak and casual, while their counterparts in schools

with low rates of vandalism characterized the principal

as strong and democratic.

An article by Love (1977) contended that, in

integrated schools, the failure to diagnose problems

with accuracy originates in the inability of school

administrators to view themselves in a new perspective.

They cannot understand why their policies and teaching

methodologies, effective in the past, no longer work,

and they refuse to change because of an ideological

barrier made up of concepts of differences; i.e.,

1. differences in their minds that translate

into deficits for minority students

2. holding low expectations for the academic

performance of minority children

3. using inappropriate materials

4. poor interpersonal relationships between

teachers and minority students

5. biased counseling practices of teachers and

principals as well as counselors

6. failure to relate to minority students as

individuals

7. bias in the administration of discipline.

Love indicated what evidence to look for in order

to ascertain if these behavior patterns existed in any












particular school. According to the article, illustrations

of biased administration of discipline are:

1. To assume when there are behavior problems

that minority students started it or know something about

it.

2. To punish a student who is not involved in

disruptive behavior for not telling all he knows

3. Ignoring white students' misbehavior while

disciplining minority students for any rule infraction

4. Using white cultural norms and values in the

administration of discipline

5. Low rate of suspension and expulsion for

white students in contrast to high rate for their minority

counterparts, with a longer period of suspension for the

latter

6. Higher rate of disciplinary action for minority

pupils as a result of subjective decisions by teachers

and administrators.

Shuttlesworth and Evans (1974) stressed that "the

principal must always keep foremost in his mind that he

is the principal of all the students regardless of race, color,

or creed" (p. 50). To illustrate what can happen if the

principal fails to follow this, they pointed out that in

one high school of about 2,000 students, 80% white and 20%

black:

. several white teachers sent far more black
students than white students to the principal's
office for disciplinary reasons. When the black












students felt that the white principal was
defending what they considered "racism" (which
the principal might or might not have been doing),
they began to polarize, using as a slogan: "We'd
better start sticking together!" Polarization
first began among those blacks who had been sent to
the office, and rapidly spread to include almost all
other black students. No race riot broke out, but
hostility was strong and rumors of rioting lasted
for weeks. (p. 50)

In implementing a group therapy program to help disruptive

students, Webster (1974) stressed the importance of

obtaining the support of the school principal for this

type of intervention to be accepted by the school in

general, its effectiveness and success.


Summary


This chapter has reviewed selected literature on

disruptive behavior; ethnicity, socio-economic status,

and sex as student variables, and location, size, and

the principal as school variables. Some of the research

literature reviewed in this chapter established the basis

for this present study.

Significant findings pertinent to this study

have been included in this chapter, i.e., relevant to

the student socio-economic status (Hollingshead, 1949;

Reissman, 1953; Coleman, 1966; Jencks, 1972; McPartland

and McDill, 1975), ethnicity (The Governor's Task Force

on Disruptive Youth, 1973: Walberg et al., 1974; Zirkel and

Gable, 1977), sex (Rice, 1975; Touliatos and Lindholm, 1976;








41



Howard, 1978). Further relevant findings, related to

school location were included, i.e. (The Teacher

Opinion Poll of the National Education Association,

1974; Koch, 1975), size (Baron, 1975; Kelly, 1978), and the

principal (Shuttlesworth and Evans, 1974; Love, 1977).

Furthermore, most of the reported research serves as

background from which perspectives can be established

in evaluating this study.
















CHAPTER III


DESIGN OF THE STUDY


This study used a comparative survey method to

investigate the relationship between disruptive andnon-

disruptive students in tri-ethnic junior high schools.

Three variables of student characteristics, socio-economic

class, ethnicity, and sex were tested in order to determine

whether they were predictors of disruptive behavior in tri-

ethnic junior high schools. Also three variables of

school characteristics, size, location, and ethnicity

of the principal, were tested in order to determine whether

they were factors in the incidence of disruptive behavior in

tri-ethnic junior high schools. The students variables were

tested by intergroup and intragroup comparison techniques

in order to determine whether disruptive junior high school

students can be predicted by any of the variables inde-

pendently or in any combination of the three. The school

variables were tested to determine whether the variables, as

a single unit, were predictive of disruptive behavior in the

junior high school. In addition, the previously mentioned

student variables were tested as to whether each together

with each of the school variables was predictive of

disruptive behavior in tri-ethnic junior high schools.

42












Hypotheses


Three variables concerning characteristics of

junior high school students were identified. This

study analyzed the interactions of these variables with

each of the three variables concerning characteristics

of tri-ethnic junior high schools.

The student variables were socio-economic

status, ethnicity, and sex. The school variables were:

size, location, and ethnic origin of the principal.

The dependent variable in this study was disruptive

behavior.

In order to test the interactions of the student

and school variables, the following null hypotheses

were formulated

H --There is no significant difference between

the socio-economic position, the ethnicity, and the sex

of the student, the location, the size, and the ethnic

origin of the principal of the school, and the frequency

of disruptive students.

H2--There is no significant difference between

the proportion of disruptive and non-disruptive students

of different socio-economic positions.

H3--There is no significant difference between the

expected and observed proportions of disruptive and non-

disruptive students of different ethnic origins.












H --There is no significant difference between

the expected and the observed proportions of disruptive

and non-disruptive students of different sexes.

H5--There is no significant difference between

the expected and the observed proportions of disruptive

and non-disruptive students of lower socio-economic

position and different ethnic origins.

H --There is no significant difference between

the expected and the observed proportions of disruptive

and non-disruptive students of middle-socio-economic

position and different ethnic origins.

H7--There is no significant difference between

the expected and the observed proportions of disruptive

and non-disruptive students of upper socio-economic

position and different ethnic origins.

H --There is no significant difference between

the expected and the observed proportions of disruptive

and non-disruptive students, male and female, of lower

socio-economic position.

H9--There is no significant difference between the

expected and the observed proportions of disruptive and

non-disruptive students, male and female, of middle

socio-economic position.

110--There is no significant difference between

the expected and the observed proportions of disruptive

and non-disruptive students, male and female, of upper

socio-economic position.











H11--There is no significant difference between

the expected and the observed proportions of disruptive

and non-disruptive black American students of different

sexes.

H 2--There is no significant difference between

the expected and the observed proportions of disruptive

and non-disruptive white American students of different

sexes.

H --There is no significant difference between

the expected and the observed proportions of disruptive

and non-disruptive Hispanic-origin students of different

sexes.

H 4--There is no significant difference between

the expected and the observed proportions of disruptive

and non-disruptive students in schools with principals

of different ethnic origins.

H15--There is no significant difference between

the expected and the observed proportions of disruptive

and non-disruptive students of lower socio-economic posi-

tion in schools with principals of different ethnic

origins.

H 6--There is no significant difference between

the expected and the observed proportions of disruptive

and non-disruptive students of middle socio-economic

position in schools with principals of different ethnic

origins.












l17--There is no significant difference between

the expected and the observed proportions of disruptive

and non-disruptive students of upper socio-economic

position in schools with principals of different ethnic

origins.

IIH--There is no significant difference between

the expected and the observed proportions of disruptive

and non-disruptive black American students in schools

with principals of different ethnic origins.

H 9--There is no significant difference between

the expected and the observed proportions of disruptive

and non-disruptive white American students in schools

with principals of different ethnic origins.

H20--There is no significant difference between

the expected and the observed proportions of disruptive

and non-disruptive Hispanic-origin students in schools

with principals of different ethnic origins.

H2,--There is no significant difference between

the expected and the observed proportions of disruptive

and non-disruptive male students in schools with

principals of different ethnic origins.

H22--There is no significant difference between

the expected and the observed proportions of disruptive

and non-disruptive female students in schools with

principals of different ethnic origins.

H23--There is no significant difference between

the expected and the observed proportions of disruptive









and non-disruptive students in schools of different

sizes.

H24--There is no significant difference between

the expected and the observed proportions of disruptive

and non-disruptive students of lower socio-economic

position in schools of different sizes.

H25--There is no significant difference between

the expected and the observed proportions of disruptive

and non-disruptive students of middle socio-economic

position in schools of different sizes.

H26--There is no significant difference between

the expected and the observed proportions of disruptive

and non-disruptive students of higher socio-economic

position in schools of different sizes.

H27--There is no significant difference between

the expected and the observed proportions of disruptive

and non-disruptive black American students in schools of

different sizes.

H28--There is no significant difference between

the expected and the observed proportions of disruptive

and non-disruptive white American students in schools of

different sizes.

H29--There is no significant difference between

the expected and the observed proportions of disruptive

and non-disruptive Hispanic-origin students in schools of

different sizes.











H 30--There is no significant difference between

the expected and the observed proportions of disruptive

and non-disruptive male students in schools oe different

sizes.

H 31--There is no significant difference between

the expected and the observed proportions of disruptive

and non-disruptive female students in schools of

different sizes.

H32--There is no significant difference between

the expected and the observed proportions of disruptive

and non-disruptive students in urban and suburban schools.

H33--There is no significant difference between

the expected and the observed proportions of disruptive

and non-disruptive students of lower socio-economic

position in urban and suburban schools.

H34--There is no significant difference between

the expected and the observed proportions of disruptive

and non-disruptive students of middle socio-economic

position in urban and suburban schools.

H35--There is no significant difference between

the expected and the observed proportions of disruptive

and non-disruptive students of upper socio-economic

position in urban and suburban schools.

S36--There is no significant difference between

the expected and the observed proportions of disruptive

and non-disruptive black American students in urban and

suburban schools.














H37--There is no significant difference between

the expected and the observed proportions of disruptive

and non-disruptive white American students in urban

and suburban schools.

H38--There is no significant difference between

the expected and the observed proportions of disruptive

and non-disruptive Hispanic origin students in urban

and suburban schools.

H39--There is no significant difference between

the expected and the observed proportions of disruptive

and non-disruptive male students in urban and suburban

schools.

H 40--There is no significant difference between

the expected and the observed proportions of disruptive

and non-disruptive female students in urban and suburban

schools.

H41--There is no significant difference between

the expected and the observed proportions of disruptive

and non-disruptive students in different grades.


Procedures


Measures of socio-economic status, ethnicity,

sex, and disruptive behavior of the students were

obtained from information provided by selected tri-ethnic












junior high schools. The group of identified disruptive

junior high school students was compared to the group

of identified non-disruptive junior high school students

on the three variables of socio-economic position,

ethnicity, and sex. Measures of three variables of the

school characteristics, size, location, and the ethnic

origin of the principal were also obtained. The rela-

tionship between the six independent variables and the

dependent variable was statistically tested. In

addition, combinations of the six independent variables

were statistically tested, as well as within group

measures of all the independent variables. The subjects,

the instruments, the method, and the statistical analyses

utilized in this study will follow.


Subjects


There are 46 junior high schools in Dade County

with over 61,000 students, with approximately equal

numbers of males and females. Of these 46 junior high

schools, 26 have a tri-ethnic student population in which

each ethnic group has a representation of at least 6%

of the total school population. The ethnic composition

of the junior high school population is listed in Table

No. 1.

Permission was obtained from the Dade County

Schools Research Committee to conduct the study in selected












TABLE 1

ETHNICITY


Ethnicity Students Percentage


White Americans 24,199 39.30

Black Americans 15,879 25.79

Hispanic Origin 21,226 34.48

Other Minorities 265 0.43
Total 61,569 100.00


tri-ethnic junior high schools. Subjects were drawn

from 12 junior high schools in Dade County with a total

enrollment of 14,281 students. Half of the junior high

schools were located in urban Dade County and the other

half in suburban Dade County.

Of the 12 junior high schools selected for this

study, 2 were of small size, 7 were of medium size, and

3 were of large size. Fifty percent (50%) of the

junior high school principals were white American and the

other 50% were non-white Americans.

A stratified random sample of 30 black American,

30 white American, and 30 Hispanic-origin students was

selected from each of the 12 junior high schools. Half

of the students in each ethnic group were male and the

other half female. There was a total of 1,080 subjects












in this study. This represented approximately 1.75% of

the total junior high population and 7.6% of the enrollment

of the selected junior high schools in this study. Of the

students selected in the sample, 270 were in the 7th grade,

407 were in the 8th grade, 396 in the 9th grade, and 7

failed to indicate the grade. Only 120 were in the

upper socio-economic position, with 468 in the middle,

and 492 in the lower socio-economic positions. School

authorities identified 123 students as disruptive and

950 as non-disruptive. Most of them (630) attended

medium size schools, with 270 in large schools, and 180

in small schools.

TABLE 2

JUNIOR HIGH SCHOOL COMPLAINTS REPORTED TO THE DADE COUNTY
SCHOOLS SECURITY ENFORCEMENT DEPARTMENT
IN THE 1976/1977 SCHOOL YEAR


Offense No of Complaints

Rape 1
Robbery 82
Assault 660
Theft 636
Arson 41
Vandalism 488
Possessing a weapon 48
Sex offense 22
Marijuana 91
Disorderly conduct 269
Total 2,338












School No. 1 (for the purposes of this study

the schools will be identified, 1, 2, 3 . 12),

large in size, with a white principal, located in suburban

Dade County, had an enrollment of 1,520 7th, 8th, and

9th grade students. The ethnic composition of the school

population was 20% black American, 72% white Ameri-

can, 7% Hispanic-origin, and 1% others. Approximately

13% of the students were determined to be economically

disadvantaged.

School No. 2, small in size, with a non-white

principal, located in urban Dade County, had an enroll-

ment of 758 7th, 8th, and 9th grade students. The

ethnic composition of the school population was 45%

black American, 17% white American, and 37% Hispanic

origin. Approximately 71% of the students were determined

to be economically disadvantaged.

School No. 3, medium in size, with a white

principal, located in suburban Dade County, had an

enrollment of 1,431 7th, 8th, and 9th grade students.

The ethnic composition of the school population was 42%

black American, 17% white American, and 42% Hispanic

origin. Approximately 60% of the students were determined

to be economically disadvantaged.

School No. 4, small in size, with a non-white

principal, located in urban Dade County, had an enroll-

ment of 497 7th grade students. The ethnic composition











of the school population was 32% black American, 46% white

American, and 22% Hispanic origin. Approximately 32% of

the students were determined to be economically dis-

advantaged.

School No. 5, large in size, with a white

principal, located in urban Dade County, had an enroll-

ment of 1,570 7th, 8th, and 9th grade students. The

ethnic composition of the school population was 26%

black American, 6% white American, and 68% Hispanic origin.

Approximately 69% of the students were determined to be

economically disadvantaged.

School No. 6, large in size, with a white

principal, located in suburban Dade County, had an

enrollment of 1,644 7th, 8th, and 9th grade students.

The ethnic composition of the school population was

20% black American, 7% white American, and 73% Hispanic

origin. Approximately 48% of the students were determined

to be economically disadvantaged.

School No. 7, medium in size, with a non-white

principal, located in urban Dade County, had an

enrollment of 1,204 7th, 8th, and 9th grade students.

The ethnic composition of the school population was 65%

black American, 16% white American, and 19% Hispanic

origin. Approximately 64% of the students were deter-

mined to be economically disadvantaged.










School No. 8, medium in size, with a white

principal, located in urban Dade County, had an

enrollment of 1,291 7th, 8th, and 9th grade students.

The ethnic composition of the school population was

51% black American, 29% white American, 19% Hispanic

origin, and 1% other. Approximately 54% of the students

were determined to be economically disadvantaged.

School No. 9, medium in size, with a non-white

principal, located in suburban Dade County, had an

enrollment of 1,380 7th, 8th, and 9th grade students.

The ethnic composition of the school population was

16% black American, 73% white American, 10% Hispanic

origin, and 1% other. Approximately 23% of the students

were determined to be economically disadvantaged.

School No. 10, medium in size, with a white

principal, located in urban Dade County, had an enroll-

ment of 1,277 8th and 9th grade students. The ethnic

composition of the school population was 40% black

American, 37% white American, and 23% Hispanic origin.

Approximately 23% of the students were determined to be

economically disadvantaged.

School No. 11, medium in size, with a non-white

principal, located in suburban Dade County, had an enrollment

of 1,316 7th, 8th, and 9th grade students. The ethnic compo-

sition of the school population was 37% black American, 46%

white American, and 17% Hispanic origin. Approximately 34%

of the students were determined to be economically disadvantaged.












School No. 12, medium in size, with a non-white

principal, located in suburban Dade County, had an enroll-

ment of 1,408 7th, 8th, and 9th grade students. The

ethnic composition of the school population was 44%

black American, 31% white American, 24% Hispanic origin,

and 1% other. Approximately 57% of the students were

determined to be economically disadvantaged.

There were 12,956 students suspended from Dade

County junior high schools during the first three

quinmesters of the 1977/78 school year. Eight hundred

forty-three (843) of them were enrolled in the 12 junior

high schools that participated in this study.


Instruments


In Chapter I, the questionnaire used to gather the

data needed for this study was discussed. However, the

information needed to determine the socio-economic

position of the subjects had to be processed. The Two

Factor Index of Social Position (Hollingshead, 1957) was

used to compute an index of socio-economic class. The

index was developed by Hollingshead to "meet the need for

an objective, easily applicable procedure to estimate the

position individuals occupy in the status structure of

our society" (p. 235).

The two factors used in the index were the

occupation and the educational level of the head of the












household. The occupations are ranked in seven

categories.

. (1) executives and proprietors of large
concerns and major professionals; (2) managers and
proprietors of medium concerns and minor
professionals; (3) administrative personnel of large
concerns, owners of small independent businesses, and
semiprofessionals; (4) owners of little businesses,
clerical and sales workers, and technicians; (5)
skilled workers; (6) semiskilled workers; and
(7) unskilled workers. (p. 235)

This scale is based on the premise that society gives

distinct values to different occupations because they

reflect the skill and power of individuals. The educa-

tional scale is divided into seven levels:

S(1) graduate professional training (persons
who completed a recognized course which led
to the receipt of a graduate degree); (2) standard
college or university graduation (individuals who
had completed a four-year college or university
course leading to a recognized college degree);
(3) partial college training (individuals who had
completed at least one year but not a full college
course); (4) high-school graduation (all secondary-
school graduates, whether from a private preparatory
school, public high school, trade school, or
parochial high school); (5) partial high school
(individuals who had completed the tenth or eleventh
grades but not the high school course); (6) junior
high school (individuals who had completed the
seventh, eighth, or ninth grades); (7) less than
seven years of school (individuals who had completed
less than seven grades irrespective of the amount
of education received. (p. 236)

This scale is based on the premise that people with similar

education tend to have similar attitudes, tastes, and

behavior patterns.

In order to calculate the index of social posi-

tion, the value for occupation is multiplied by a factor












weight of seven. The value for education is multiplied

by a factor weight of four, and both products are

added. The scores range from a low of 11 to a high

of 77. In this study the scores were divided into three

levels.

TABLE 3

SCORES USED TO DETERMINE
SOCIO-ECONOMIC POSITION


Socio-Economic Position Total Score


Lower 11-22

Middle 23-51

Upper 52-77



The questionnaire used in this study provided

information on the occupation and the education of

both parents. If information for both parents was

given, it was assumed that the father was the head of

the household. When the only information given in the

questionnaire was "unemployed" and no additional informa-

tion could be obtained, the student was assumed to be of

lower socio-economic status.


Methods


During the spring of 1978 permission to conduct

this study was requested from 14 junior high school












principals. Only one refused to give his authorization;

hence, because of the research design, it was also

necessary to eliminate a second school that had been

paired with it.

Questionnaires with the names of the students

selected for the study already written upon them were

delivered to the 12 junior high schools that had accepted

the invitation to participate in the study. A conference

was held with the assistant principal for guidance of

each school in order to ensure good cooperation and

better understanding of the study. It was requested that

the assistant principal randomly replace any subject no

longer in the school. The replacement would be chosen

with the same demographic characteristics.

The questionnaires were completed by the students

under the supervision of a guidance counselor. The

assistant principal in charge of discipline reviewed the

questionnaires once they had been completed by the

students in order to ascertain that Item No. 8 (Was the

student suspended? ) had been answered accurately.

Before being returned by the schools, the students'

names were detached from the questionnaires, because of

a requirement of the Dade County Schools Research

Committee designed to maintain the privacy rights of the

students. Furthermore, after receiving the questionnaires,

the names of the schools were also detached, in order to












comply with the request to maintain the names of the

schools which participated in this study in anonymity

and these were placed in envelopes labeled:


1 2 3 4 5 6 7

Principal Non/W Non/W Non/W W W W W

Size M S M L M M L

Location U U S U S U S


When all questionnaires were returned, the data

were coded and keypunched.


Statistical Analysis


Hypothesis 1 was tested in order to determine if

several student and school independent variables were

predictors of disruptive behavior. Multiple regression

was used in the statistical analysis. Kerlinger (1964)

pointed out:

Multiple regression is close to the heart of
scientific investigation. It is also fundamental
in statistics and inference, and is tightly tied
to basic and powerful mathematical methods. From the
researcher'spoint of view, moreover, it is useful
and practical: it does its analytic job successfully
and efficiently. (p. 630)

Discussing this statistical technique as an inferential

tool, Nie et al. (1975) wrote:

Through multiple regression techniques the
researcher could obtain a prediction equation
that indicates how scores on the independent
variables could be weighted and summed to obtain
the best prediction of the dependent variable. (p. 321)












Because of the nominal-scale nature of the six

independent variables and the dichotomous nominal-

scale nature of the dependent variable, "dummy"

variables had to be used.

Hypotheses 2 through 41 were formulated to

test intergroup and intragroup relationships. Chi

square was used in the statistical analysis because it

is a test of statistical significance that helps to

determine if there is a systematic relationship between

two variables.


Summary


The focus of this chapter was the design of

this study. The hypotheses were formulated, the pro-

cedures were explained, the subjects as well as the

instruments were described, and the methods used in the

statistical analysis were outlined. The methods of

sampling and data collection were previously discussed

in Chapter I. An analysis of the results is discussed

in Chapter IV.















CHAPTER IV


RESULTS


The major purpose of the present study was to

ascertain if there was a relationship among certain

student characteristics, certain school characteristics,

and disruptive behavior. Three independent variables of

student characteristics and three independent variables

of school characteristics were combined to formulate

39 null hypotheses. Because the information was avail-

able, a fourth independent variable of student character-

istics, school grade, was used by itself in formulating

one null hypothesis and in combination with the other

independent variables for a total of 41 null hypotheses.

Two statistical techniques were used to analyze

the data in this study. The forward (stepwise) inclusion

approach of multiple linear regression was used in testing

the first hypothesis for predictability. Chi square was

used to test the rest of the hypotheses for relationship.

The findings of this study are grouped into six

sections. Section I presents the findings of testing

hypothesis one, which tries to determine whether any of the

independent variables or any combination of them are

predictors of disruptive behavior. Section II presents

62












the results of testing the independent variables of

socio-economic position, ethnicity, and sex of the

students formulated in hypotheses 2, 3, 4, 5, 6, 7, 8,

9, 10, 11, 12, and 13. Section III presents the results

of testing the independent variable of the ethnicity of

the principal and its relationship with students'

variables formulated in hypotheses 14, 15, 16, 17, 18,

19, 20, 21, and 22. Section IV presents the results

of testing the independent variable of the size of the

school and its relationship with student variables

formulated in hypotheses 23, 24, 25, 26, 27, 28, 29,

30, and 31. Section V presents the results of testing

the independent variable of the location of the school

and its relationship with student variables formulated on

hypotheses 32, 33, 34, 35, 36, 37, 38, 39, and 40.

Section VI presents the results of testing the independent

variable of the students' grade placement.

Section I


HI, There is no significant difference between
the socio-economic position, the ethnicity, the grade,
and the sex of the student; the location, the size,
and the ethnic origin of the principal of the
school and the frequency of disruptive students.

Multiple regression was run to determine whether the independent

variables were predictors of disruptive behavior. The equa-

tion used in this statistical technique was:


Y = C + BX1 + B2X2 + . . + BX
11 22-Zl\











The best predictors obtained in the regression

analysis were (1) socio-economic position--lower; (2) sex--

male; (3) ethnicity--non-Hispanic; (4) grade--non-eighth

grader.

The values obtained in the regression analysis

produced the following equation:

Y = 0.02788 + .18075X1 + .8506X2

.6398X3 .4653X4

where Y is the predicted dependent variable, X1 lower socio-

economic position, X2 male, H3 Hispanic origin, and X4

eighth grade.

The results of the analysis of variance in each

step of the multiple regression showed the variables

listed in Table 4 significant at the 0.01 level.


TABLE 4

RESULTS OF STEPWISE MULTIPLE REGRESSION ANALYSIS AND
RESULTS OF THE ANALYSIS OF VARIANCE IN THE
MULTIPLE REGRESSION


Standard
Variable B Beta Error B

Lower socio-economic
position .18075 .28336 0.01872

Male .8506 .13388 0.01840

Hispanic -.6398 -.09495 0.01976

Grade 8 -.4653 -.07098 0.01900











TABLE 4 (continued)



Variable Degrees of Freedom F

1. Lower socio-
economic position 1 84.1045

2. Male sex 2 54.49337

3. Hispanic ethnic
origin 3 39.89209

4. Eighth grade 4 31.55811



Since the null hypothesis encompassed all the

independent variables, it is not rejected. However, it

can be said that the student with most probability of

being suspended is of lower socio-economic position, male,

not of Hispanic origin nor in the eighth grade.


Section II


Chi square was used to test the statistical

significance of the rest of the hypotheses in this study.

It determines whether a relationship exists between two

variables. The following formula was used in this

statistical technique:

f 2
f f
X2 o e

f
e













where f is the observed frequency in each cell and f is
o e
the expected frequency.

The hypotheses in this section test the rela-

tionship between disruptive behavior and the socio-

economic status, ethnicity, and sex of the student.

iH2, There is no significant difference between
the expected and the observed proportions of
disruptive and non-disruptive students of different
socio-economic positions.


TABLE 5

DISRUPTIVE AND NON-DISRUPTIVE STUDENTS OF
DIFFERENT SOCIO-ECONOMIC POSITIONS



Row
Lower Middle Upper Total


Non- Count 390 448 119 957
Disruptive Row Pct. 40.8 46.8 12.4 88.6
Col. Pct. 79.3 95.7 99.2
Tot. Pct. 36.1 41.5 11.0


Disruptive Count 102 20 1 123
Row Pct. 82.9 16.3 0.8 11.4
Col. Pct. 20.7 4.3 0.8
Tot. Pct. 9.4 1.9 0.1


Total Column 492
Total Column Pct. 45.6


468
43.3


120 1080
11.1 100.0


Chi square was run to


determine any


statistical relationship


between disruptive behavior and students' socio-economic

position. The obtained chi square of 79.28 with 2 degrees

of freedom had a probability of less than 0.0001. Therefore,











the null hypothesis is rejected. In order to determine

which of the proportions of lower, middle, and upper

socio-economic position was statistically significant,

the z test formula for significance of difference

between proportions (Glass and Stanley 1970, p. 325) was

used.

P P2

jf( + f f + f 2 (
nnI + n 2)


The proportions of disruptive and non-disruptive

students of middle and upper socio-economic position ob-

tained a z value of 1.88, not high enough to be

significant at the .05 level.

There was a statistically significant difference

at the 0.01 level between the proportion of disruptive

students of lower socio-economic position and the pro-

portions of disruptive students of middle and upper

socio-economic positions.

H There is no significant difference between
the expected and the observed proportions of
disruptive and non-disruptive students of different
ethnic origins.

Chi square was run to determine any statistical

relationship between the incidence of disruptive behavior

and the ethnicity of the students. The obtained chi

square of 13.59 with 2 degrees of freedom had a probability

of .0011. Therefore, the null hypothesis is rejected. The













TABLE 6

DISRUPTIVE AND NON-DISRUPTIVE STUDENTS OF
DIFFERENT ETHNIC ORIGINS


Row
Black Hispanic White Total


Non- Count 301 326 330 957
Disruptive Row Pct. 31.5 34.1 34.5 88.6
Col. Pct. 83.6 90.6 91.7
Tot. Pct. 27.9 30.2 30.6


Disruptive Count 59 34 30 123
Row Pct. 48.0 27.6 24.4 11.4
Col. Pct. 16.4 9.4 8.3
Tot. Pct. 5.5 3.1 2.8


Total Column 360 360 360 1080
Total Column Pct. 33.3 33.3 33.3 100.0



proportions of disruptive and non-disruptive students of

white American and Hispanic ethnic origins obtained a z

value of 0.516 which is not statistically significant.

There was a statistically significant difference at the

0.01 level between the proportion of disruptive and non-

disruptive black American and white American students and

the proportions of black American and Hispanic-origin

students.

H., There is no significant difference between
the expected and the observed proportions of disruptive
and non-disruptive students of different sex.

Chi square was run to determine any statistical

relationship between disruptive and non-disruptive












TABLE 7

DISRUPTIVE AND NON-DISRUPTIVE
DIFFERENT SEXES


STUDENTS OF


Row
Male Female Total

Non- Count 453 504 957
Disruptive Row Pet. 47.3 52.7 88.6
Col. Pet. 83.9 93.3
Total Pet. 41.9 46.7


Disruptive Count 87 36 123
Row Pet. 70.7 29.3 11.4
Col. Pct. 16.1 6.7
Total Pet. 8.1 3.3


Total Column 540 540 1080
Total Column Pet. 50.0 50.0 100.0




students of different sex. The obtained chi square of

22.94 with 1 degree of freedom had a probability of

less than 0.0001. Of the students identified as dis-

ruptive 87 were male and 36 female. Therefore, the null

hypothesis is rejected.

H1, There is no significant difference between
the expected and the observed proportions of dis-
ruptive and non-disruptive students of lower socio-
economic position and different ethnic origins.

Chi square was run to determine any statistical

relationship between disruptive and non-disruptive

students of lower socio-economic position and different












TABLE 8

DISRUPTIVE AND NON-DISRUPTIVE STUDENTS OF LOWER
SOCIO-ECONOMIC POSITION BY ETHNICITY



Row
Black Hispanic White Total


Non- Count 150 178 62 390
Disruptive Row Pct. 38.5 45.6 15.9 79.3
Col. Pct. 73.9 85.6 76.5
Tot. Pct. 30.5 36.2 12.6


Disruptive Count 53 30 19 102
Row Pct. 52.0 29.4 18.6 20.7
Col. Pct. 26.1 14.4 23.5
Tot. Pct. 10.8 6.1 3.9


Total Column 203 208 81 492
Total Colunn Pct. 41.3 42.3 16.5 100.0



ethnic origins. The obtained chi square of8.97 with 2

degrees of freedom had a probability of 0.0113. Therefore,

the null hypothesis is rejected. The proportions of black

American and white American disruptive and non-disruptive

students obtained a z value of 0.46, which is not

statistically significant. There was a statistically

significant difference at the 0.01 level between the

proportions of disruptive and non-disruptive black American

students and the proportions of disruptive and non-

disruptive Hispanic-origin students. A high z value of 1.85

was obtained between the proportion of disruptive and












non-disruptive white American students and disruptive and

non-disruptive Hispanic-origin students, but it failed

to reach the value of 1.96 needed to be significant at

the 0.05 level.

H,6 There is no significant difference between
the expected and the observed proportions of
disruptive and non-disruptive students of middle
socio-economic position and different ethnic
origins.


TABLE 9

DISRUPTIVE AND NON-DISRUPTIVE STUDENTS OF MIDDLE
SOCIO-ECONOMIC POSITION BY ETHNICITY




Row
Black Hispanic White Total


Non- Count 125 121 202 448
Disruptive Row Pct. 27.9 27.0 45.1 95.7
Col. Pct. 96.2 96.8 94.8
Tot. Pct. 26.7 25.9 43.2


Disruptive Count 5 4 11 20
Row Pct. 25.0 20.0 55.0 4.3
Col. Pct. 3.8 3.2 5.2
Tot. Pct. 1.1 0.9 2.4


Total Column 130 125 213 468
Total Column Pct. 27.8 26.7 45.5 100.0



Chi square was run to determine any statistical

relationship between disruptive and non-disruptive

students of middle socio-economic position and different

ethnic origins. The obtained chi square of 0.82 with 2












degrees of freedom had a probability of 0.662. Hence,

the null hypothesis is not rejected.

H7,' There is no significant difference between
the expected and the observed proportions of
disruptive and non-disruptive students of upper
socio-economic position and different ethnic origins.


TABLE 10

DISRUPTIVE AND NON-DISRUPTIVE STUDENTS OF UPPER
SOCIO-ECONOMIC POSITION BY ETHNICITY



Row
Black Hispanic White Total


Non- Count 26 27 66 119
Disruptive Row Pct. 21.8 22.7 55.5 99.2
Col. Pct. 96.3 100.0 100.0
Tot. Pct. 21.7 22.5 55.0


Disruptive Count 1 0 0 1
Row Pct. 100.0 0.0 0.0 0.8
Col. Pct. 3.7 0.0 0.0
Tot. Pct. 0.8 0.0 0.0


Total Column 27
Total Column Pct. 22.5


27
22.5


66 120
55.0 100.0


Chi square was run to determine any statistical

relationship between disruptive and non-disruptive

students of upper socio-economic position and different

ethnic origins. The obtained chi square of 3.47 with 2

degrees of freedom had a probability of 0.176. Therefore,

the null hypothesis is not rejected. Only one student












in this socio-economic status was identified as

disruptive, which represents 0.8% of the total number

of students in this group. Since one of the require-

ments of chi square, that the expected value of any

cell never be less than 5, is not met, a z test was conducted

with the following not statistically significant results:

Black Americans and white Americans z = 1.57

Black Americans and Hispanic-origin students

z = 1.008

H There is no significant difference between
the expected and the observed proportions of
disruptive and non-disruptive students, male and
female, of lower socio-economic position.


TABLE 11

DISRUPTIVE AND NON-DISRUPTIVE STUDENTS OF LOWER
SOCIO-ECONOMIC POSITION BY SEX



Row
Male Female Total


Non- Count 182 208 390
Disruptive Row Pct. 46.7 53.3 79.3
Col. Pct. 71.4 87.8
Tot. Pct. 37.0 42.3


Disruptive Count 73 29 102
Row Pct. 71.6 28.4 20.7
Col. Pct. 28.6 12.2
Tot. Pct. 14.8 5.9


Total Column 255 237 492
Total Column Pct. 51.8 48.2 100.0












Chi square was run to determine any statistical

relationship between disruptive and non-disruptive

students of lower socio--economic status and different

sexes. The obtained chi square of 19.1 with 1 degree of

freedom had a probability of less than 0.0001. Hence,

the null hypothesis is rejected. Only 12.2% of the

female student sample in this socio-economic position

was identified as disruptive in contrast to 28.6% of the

male student sample.

H9, There is no significant difference between
the expected and the observed proportions of
disruptive and non-disruptive students, male and
female, of middle socio-economic position.


TABLE 12

DISRUPTIVE AND NON-DISRUPTIVE STUDENTS OF MIDDLE
SOCIO-ECONOMIC POSITION BY SEX



Row
Male Female Total


Non- Count 215 233 448
Disruptive Row Pct. 48.0 52.0 95.7
Col. Pct. 94.3 97.1
Tot. Pct. 45.9 49.8


Disruptive Count 13 7 20
Row Pct. 65.0 35.0 4.3
Col. Pct. 5.7 2.9
Tot. Pet. 2.8 1.5


Total Column 228 240 468
Total Column Pct. 48.7 51.3 100.0












Chi square was run to determine any statistical

relationship between disruptive and non-disruptive

students of middle socio-economic position and different

sexes. The obtained chi square of 1.59 with 1 degree

of freedom had a probability of 0.208. Hence, the null

hypothesis is not rejected.

H ,' There is no significant difference
betwe n the expected and the observed proportions
of disruptive and non-disruptive students, male
and female, of upper socio-economic position.


TABLE 13

DISRUPTIVE AND NON-DISRUPTIVE STUDENTS OF UPPER
SOCIO-ECONOMIC POSITION BY SEX



Row
Male Female Total


Non- Count 56 63 119
Disruptive Row Pct. 47.1 52.9 99.2
Col. Pct. 98.2 100.0
Tot. Pct. 46.7 52.5


Disruptive Count 1 0 1
Row Pct. 100.0 0.0 0.8
Col. Pct. 1.8 0.0
Tot. Pct. 0.8 0.0


Total Column 57 63 120
Total Column Pct. 47.5 52.5 100.0



Chi square was run to determine any statistical

relationship between disruptive and non-disruptive students












of upper socio-economic position and different sexes.

The obtained chi square of 0.003 with 1 degree of

freedom had a probability of 0.96. Therefore, the null

hypothesis is not rejected. As was stated before, only

1 student was identified as disruptive in this socio-

economic position. Since the chi square requirement,

that the expected value of any cell never be less than

5, is not met, a z test was conducted. The value of 1.08

was not statistically significant.

H 1, There is no significant difference between
the expected and the observed proportions of
disruptive and non-disruptive black American students
of different sexes.


TABLE 14

DISRUPTIVE AND NON-DISRUPTIVE
BY SEX


BLACK STUDENTS


Row
Male Female Total


Non- Count 137 164 301
Disruptive Row Pct. 45.5 54.5 83.6
Col. Pct. 76.1 91.1
Tot. Pct. 38.1 45.6


Disruptive Count 43 16 59
Row Pct. 72.9 27.1 16.4
Col. Pct. 23.9 8.9
Tot. Pct. 11.9 4.4


Total Column 180 180 360
Total Column Pct. 50.0 50.0 100.0












Chi square was run to determine any statistical

relationship between disruptive and non-disruptive black

American students of different sexes. The obtained chi

square of 13.7 with 1 degree of freedom had a probability

of 0.0002. Therefore, the null hypothesis is rejected.

Only 5.5% of the black American female students were

identified as disruptive in contrast to 11.9% of the

black American male students.

HI2, There is no significant difference between
the expected and the observed proportions of
disruptive and non-disruptive white American students
of different sexes.


TABLE 15

DISRUPTIVE AND NON-DISRUPTIVE WHITE
BY SEX


AMERICAN STUDENTS


Row
Male Female Total


Non- Count 160 170 330
Disruptive Row Pct. 48.5 51.5 91.7
Col. Pct. 88.9 94.4
Tot. Pct. 44.4 47.2


Disruptive Count 20 10 30
Row Pct. 66.7 33.3 8.3
Col. Pet. 11.1 5.6
Tot. Pct. 5.6 2.8


Total Column 180 180 360
Total Column Pct. 50.0 50.0 100.0












Chi square was run to determine any statistical

relationship between disruptive and non-disruptive

white American students of different sexes. The obtained

chi square of 2.945 with 1 degree of freedom had a

probability of 0.0861. Although 11.9% of the

males, in contrast to 4.4% of the females in this

group were identified as disruptive, the null hypothesis

is not rejected.

H 3' There is no significant difference
between the expected and the observed proportions
of disruptive and non-disruptive Hispanic-origin
students of different sexes.


TABLE 16

DISRUPTIVE AND NON-DISRUPTIVE HISPANIC-ORIGIN STUDENTS
BY SEX



Row
Male Female Total


Non- Count 156 170 326
Disruptive Row Pct. 47.9 52.1 90.6
Col. Pct. 86.7 94.4
Tot. Pct. 43.3 47.2


Disruptive Count 24 10 34
Row Pct. 70.6 29.4 9.4
Col. Pct. 13.3 5.6
Tot. Pet. 6.7 2.8


Total Column
Total Column Pct.


180
50.0


180 360
50.0 100.0












Chi square was run to determine any statistical

relationship between disruptive and non-disruptive

Hispanic-origin students of different sexes. The obtained

chi square of 5.49 with 1 degree of freedom had a

probability of 0.0191. Therefore, the null hypothesis

is rejected. Only 10 female Hispanic-origin students

were identified as disruptive in contrast to 24 males

in this group.


Section III


Hypothesis 14 tests the incidence of disruptive

behavior in schools with principals of different ethnic

origins. The rest of the hypotheses in this section

test this school variable with each of the student

variables.

,14' There is no significant difference
between the expected and the observed proportions
of disruptive and non-disruptive students in
schools with principals of different ethnic origins.

Chi square was run to determine any statistical

relationship between the incidence of disruptive behavior

in schools with principals of different ethnic origins.

The obtained chi square of 0.147 with 1 degree of

freedom had a probability of 0.7016. Hence, the null

hypothesis is not rejected.

I15, There is no significant difference between
the expected and the observed proportions of dis-
ruptive and non-disruptive students of lower socio-
economic position in schools with principals of
different ethnic origins.












TABLE 17

DISRUPTIVE AND NON-DISRUPTIVE STUDENTS IN SCHOOLS
WITH PRINCIPALS OF DIFFERENT ETHNIC ORIGINS



White Row
American Other Total


Non- Count 476 481 957
Disruptive Row Pct. 49.7 50.3 88.6
Col. Pct. 88.1 89.1
Tot. Pct. 44.1 44.5


Disruptive Count 64 59 123
Row Pct. 52.0 48.0 11.4
Col. Pct. 11.9 10.9
Tot. Pct. 5.9 5.5


Total Column 540 540 1080
Total Column Pct. 50.0 50.0 100.0



TABLE 18

DISRUPTIVE AND NON-DISRUPTIVE LOWER SOCIO-ECONOIIIC
STUDENTS BY ETHNICITY OF PRINCIPAL



White Row
American Other Total


Non-
Disruptive




Disruptive


Count
Row Pct.
Col. Pet.
Tot. Pct.


Count
Row Pct.
Col. Pct.
Tot. Pct.


Total Column
Total Column Pct.


175
44.9
75.1
35.6


58
56.9
24.9
11.8


233
47.4


215
55.1
83.0
43.7


44
43.1
17.0
8.9


390
79.3


102
20.7


259 492
52.6 100.0













Chi square was run to determine any statistical

relationship between disruptive and non-disruptive

lower socio-economic position students in schools with

principals of different ethnic origins. The obtained

chi square of 4.195 with 1 degree of freedom had a

probability of 0.0406. Hence, the null hypothesis is

rejected. Of the students identified as disruptive in

this socio-economic position, 24.9% of the sample

attended schools with white principals and 17% of the

sample attended schools with principals of other ethnic

origins.

HI6, There is no significant difference between
the expected and the observed proportions of
disruptive and non-disruptive students of middle
socio-economic position in schools with principals
of different ethnic origins.


TABLE 19

DISRUPTIVE AND NON-DISRUPTIVE MIDDLE SOCIO-ECONOMIC
POSITION STUDENTS BY ETHNICITY OF PRINCIPAL



White Row
American Other Total


Non- Count 237 211 448
Disruptive Row Pct. 52.9 47.1 95.7
Col. Pct. 97.5 93.8
Tot. Pct. 50.6 45.1


Disruptive Count 6 14 20
Row Pct. 30.0 70.0 4.3
Col. Pct. 2.5 6.2
Tot. Pct. 1.3 3.0


Total Column
Total Column Pct.


243
51.9


225 468
48.1 100.0












Chi square was run to determine any statistical

relationship between disruptive and non-disruptive

middle socio-economic position students in schools with

principals of different ethnic origins. The obtained

chi square of 3.157 with 1 degree of freedom had a

probability of 0.0756. Of the middle socio-economic

status students attending schools with non-white American

principals, 6.2% were identified as disruptive in

contrast to 2.5% of the students in this group attending

schools with white American principals. Hence, the

null hypothesis is not rejected.

HI7, There is no significant difference between
the expected and the observed proportions of
disruptive and non-disruptive students of upper
socio-economic position in schools with principals
of different ethnic origins.

Chi square was run to determine any statistical

relationship between disruptive and non-disruptive

upper socio-economic position students in schools with

principals of different ethnic origins. Since, as

previously pointed out,only one student was identified

as disruptive in this socio-economic position, the

obtained chi square of 0.0045 with 1 degree of freedom

had a probability of 0.9465, and the null hypothesis is

not rejected. A z test was made because the expected

value of each cell was not 5 or above. The z of 1.082

was not statistically significant.












TABLE 20

DISRUPTIVE AND NON-DISRUPTIVE UPPER SOCIO-ECONOMIC
POSITION STUDENTS BY ETHNICITY OF PRINCIPAL




White Row
American Other Total


Non- Count 64 55 119
Disruptive Row Pct. 53.8 46.2 99.2
Col. Pct. 100.0 98.2
Tot. Pct. 53.3 45.8


Disruptive Count 0 1 1
Row Pct. 0.0 100.0 0.8
Col. Pct. 0.0 1.8
Tot. Pct. 0.0 0.8


Total Column 64 56 120
Total Column Pct. 53.3 46.7 100.0



H18, There is no significant difference between
the expected and the observed proportions of
disruptive and non-disruptive black American students
in schools with principals of different ethnic
origins.

Chi square was run to determine any statistical

relationship between disruptive and non-disruptive black

American students in schools with principals of different

ethnic origins. The obtained chi square of 3.97 with 1

degree of freedom had a probability of 0.0462. Therefore,

the null hypothesis is rejected. While 37 black American

students were identified as disruptive in schools with












TABLE 21

DISRUPTIVE AND NON-DISRUPTIVE BLACK STUDENTS
BY ETHNICITY OF PRINCIPAL


White Row
American Other Total


Non- Count 143 153 301
Disruptive Row Pct. 47.5 52.5 83.6
Col. Pct. 79.4 87.8
Tot. Pct. 39.7 43.9


Disruptive Count 37 22 59
Row Pct. 62.7 37.3 16.4
Col. Pct. 20.6 12.2
Tot. Pct. 10.3 6.1


Total Column 180 180 360
Total Column Pct. 50.0 50.0 100.0




white American principals, only 22 were identified in

schools with non-white-American principals.

H19, There is no significant difference between
the expected and the observed proportions of
disruptive and non-disruptive white American
students in schools with principals of different
ethnic origins.

Chi square was run to determine any statistical

relationship between disruptive and non-disruptive

white American students in schools with principals of

different ethnic origins. The obtained chi square of 8.18

with 1 degree of freedom had a probability of 0.0042.












TABLE 22

DISRUPTIVE AND NON-DISRUPTIVE WHITE AMERICAN STUDENTS
BY ETHNICITY OF PRINCIPAL



White Row
American Other Total


Non- Count 173 157 330
Disruptive Row Pct. 52.4 47.6 91.7
Col. Pct. 96.1 87.2
Tot. Pct. 48.1 43.6


Disruptive Count 7 23 30
Row Pct. 23.3 76.7 8.3
Col. Pct. 3.9 12.8
Tot. Pct. 1.9 6.4


Total Column 180 180 360
Total Column Pct. 50.0 50.0 100.0



Hence, the null hypothesis is rejected. Schools with

non-white American principals identified 23 white

American students as disruptive while schools with white

American principals identified only 7.

H20' There is no significant difference between
the expected and observed proportions of non-
disruptive Hispanic-origin students in schools with
principals of different ethnic origins.

Chi square was run to determine any statistical

relationship between disruptive and non-disruptive

Hispanic-origin students in schools with principals of

different ethnic origins. The obtained chi square of

0.812 with 1 degree of freedom had a probability of




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