FullText

Title

Author(s)

The computer literacy of Hong Kong teachers

Sou, Hon-poo, Howard.; 蘇漢波.

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Issued Date

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Rights

1986

http://hdl.handle.net/10722/51153

The author retains all proprietary rights, (such as patent rights) and the right to use in future works.

The Computer Literacy of Hong Kong Teachers

Dissertation presented in part fulfilment of the requirement of the degree of Master of Education
University of Hong Kong

August 1986

THE UNIVERSITY OF HONG KONG

LIBRARY

EDUCATION LIBRARY
Deposited by the Author

ii-

Abstract

Computers

can

used

be

in classrooms

elementary

of

secondary schools to enhance teaching in many subject

An

areas.

element in classroom computer is that teachers

essential

and

should

be well prepared in terms of competence and attitude but research in teachers computer literacy was not found in Hong Kong.

The

purpose

questions

of

this study was to study

following

the

Cl) What is Hong Kong teachers' self-reported computer

and which group of teachers will

literacy

consider

themselves

more computer literate ? (2) What is Hong Kong teachers

using computers

towards

3

administration positive in classroom teaching

and which

attitude

?

group

and

of teacher will

attitude school in

have

more

a

interested

(3) Are Hong Kong Teachers

in

attending computer courses and which type of computer courses, in of content and time of conducting,

term

will be the

favourable

courses to which group of teachers 7
It

expected

was

suggest

ways

towards

using

could

aid

to

that answers

improve

to

the computer

these

questions

literacy

and

could

attitude

computers in school of Hong Kong Teachers which tailoring computer

of this study were 464 teachers from 23

secondary

educational

administrators

in

courses for teachers.
Subjects
schools

education

in

Hong

Kong

and 112 lecturers from

in Hong Kong making a sample of 576

4

colleges

subjects.

items questionnaire was developed for data collection. iii A

of
64

The computer results of this study were :

literacy was

low

and

Kong

(1) Hong

with

teachers

those

teacherst

initial

training in computer and having chance to interact with computers had higher computer literacy scores.

positive

attitude

towards

had

(2) Hong Kong teacher

using computers

both

in

classroom

teaching and school administration. It was also found that chance to practicing examples of computer

appreciate

appropriate

application

and

level of computer literacy were important factors to

the positive attitude towards using computers in schools of

Hong

Kong teachers. (3) Majority of Hong Kong teachers were interested in They were interested in courses

attending computer courses.

which

could enable them to operate a computer effectively and to

have immediate applications.

According to the results

pattern of achieving competence in

computer as an end user and hence positive attitude towards using computers in school was mapped out.

providing

(1) computer accessibility,

It was also suggested
(2) initial

training

that

in

computers together with (3) practicing examples set up by quality softwares, were

essential factors to improve both the

teachers

competence in computer and their attitude towards using computers in schools. It was thus recommended that there was an urgent need for the

authorities

concerned

computer courses for teachers all teachers

and

in Hong

Kong

to

provide

(2) open computers in schools to

(3) develop quality softwares

classroom teaching and school administration

iv

(1)

both

for

the

Content
Page

I. Introduction
1.1 Summary
1.2 Computer Education
1.3 The development of computer education in Hong Kong
1.4 Statement of problem
1 . 5 Purpose of the study

1.6 Need for the study
1,7 Limitation of the study
II. Review of Literature
2.1
2.2
2.3
2.4
2.5

Summary
The development of computer in education
Computer education in teacher education
Defining computer literacy for teachers
Related research works

III Method
3.1 Introduction

32 Instrument
3.2.1 Introduction
3.2.2 School questionnaire
3.2.3 Teacher questionnaire
3.2.3.1 The design
3.2.3.2 Scaling method
3.2.3.3 Pilot study
3.3 Sampling
3 4 Procedure
3.5 Data analyses
3.5.1 Establishing the subscales
3.5.2 Descriptive statistics
3.5.3 Relations of subscales and independent variables
Lv Results and Interpretations
4.1 Introduction
4.2 Results of data collection
4_3 Establishing siibscales
4.3,l Introducation
43.2 Psychometric properties of attitude scales
4*3.3 Psychometric properties of self reported computer literacy scale
43*4 Backgrounds of subjects training in computer and their applicaíons of computers
4.4 Computer literacy scale
4.4,1 Introduction
44.2 Characteristics of the computer literacy subscales V

i i 2
4
7
8
8
9

10

10 il 12
14
16
21
21
22
22
22
23
23
24
26
29
32
33
33
39

40
41

41
42
45
45
45
49

54
57
57

Page

4.4.3 Relations of subjects' computer literacy and other independent variables
44.3.l Locating independent variables correlated with computer literacy subscales
4.4.3.2 School variables
4.4.3.3 Sex
4.4.3*4 Major subjects teach
4.4.3.5 Highest education
4.4.3.6 Teachers from different institution
4.4.3.7 Training in computers
4.4.38 Computer accessibility
4.4.3*9 Computer user
4.4.3.10 Reading in computer

63

4.4.31l Summary
4.5 Attitude towards using computers in school
4.5.1 Introduction
4.5.2 Characteristics of the subscales of attitude towards using computers in schools
4.5*3 Relations of attitude subscales and other independent variables
4.5.3.1 Locating independent variables correlated with the attitude subscales
4.5.3.2 School variables
4.5.3_3 Major subjects teach
4.5.3.4 Training in computer
4.5.3.5 Interaction with computers

63
69
72
73
76
77
78
81
83
84
86
87
87
88
90
90
93
95
97
99

4.5.36 Computer literacy
101
4.5.3.7 Summary
103
4.6 Interests in attending computer courses and
105
the most favourable courses of Hong Kong teachers
4.6.1 intersts in attending computer courses
105
4.6.2 Most favourable courses
105
V. Summary and discussion
5.1 Summary
5.2 Results of data collection
5.3 Summary of findings
5.4 Recommendation
5.5 Weaknesses of this study
5.6 Future research areas
Appendix A Mean scores of items in the
Computer Literacy scale
Appencis B Normal plots, detrended normal plots and stem-and-leaf plots of the computer literacy subscales
Appendix C Normal plots, detrended normal plots and stem-and-leaf plots of the attitude subscales. Appendix D Survey Questionnaires
Appendix E Code book of survey questionnaires
Appendix F Summary results on the frequencis of responses of each item in the teacher auestionnaire BibìliograpFìy

112
112
113
114
121
122
123

126

127

133
137
i4

l6 vi List of Tables

Table

2-1

3-1
3-2
3-3

3-4

4-1
4-2
4-3
4-4
4-5
4-6
4.-7
4--8

4-9
4-10
4-11

4-12

4-13

4-14
4-15
4-16

4-17
4-18

4-19

4-20

Description

Page

Relations between teachers' attitude towards
17
computer based instructions and their computer knowledge and selected demographic characteristics
School variables
22
Variables in teacher questionnaire
28
Sample schools stratiified by school age and sex of student
30
Sample schools stratified by school locations and school type
30
Number of questionnaires returned from schools
42
Number of questionnaires returned from C of E
43
Reliability analysis of attitude subscales
48
Results of the two factors model of the two subgroups of the computer literacy scale
51
Correlations of subscales of computer literacy
51
Reliability analysis of computer literacy subscales 52
Coding of computer literacy scale
57
Definitions of competence levels in computer literacy
58
Mean scores of computer litercy subscales
60
Number of computer courses attended by subjects 62
Number of subjects with knowledge in different programming languages
62
BoxM tests for Homogeneity of dipersion matrices for CPINF, CPSOC and CPCOM with different independent variables
66
Hotellingts T2 tests of subjects' computer literacy with different independent variables
67
Univariate F-tests of computer literacy
68
subscales with different independent variables
Mean Computer literacy scores of subjects in
69
different school types
Mean Computer literacy scores of subjects in schools have or have-not using computers in
70
administration
Mean Computer literacy scores of subjects in schools have or not have self-procred computers 70
Cross-tabs of subjects in sxhools have or not have self-procured computers with schools have
71
or have not using computers in administration
Cross-tabs of subjects in different school types with shcools have or have not using computers
71
in administration
Mean Computer literacy scores of subjects with
73
different sex

vii

Table
4-21
4-22
4-23
4-24

4-25

Description
Mean Computer literacy scores of subjects teaching different subjects
Mean Computer literacy scores of subjects with different highest education
Mean Computer literacy scores of subjects teach in different institutions
Mean Computer literacy scores of subjects attending different No. of computer courses in formal education
Mean Computer literacy scores of subjects

Page

74
76

77

79

attending different t\Io of courses with

4-26

4-27
4-28

4-29

4-30
4--31

4-32
4-33

4-34
4-35
4-36
4-37
4-38

4-39

4-40
4-41

4-42
4-43

computer applications
Mean Computer literacy scores of subjects attending different No. of in-service courses in computer
Mean Computer literacy scores of subjects with different computer accessibilities
Mean Computer literacy scores of subjects with different types of computer applications in daily work
Mean Computer literacy scores of subjects with different No. of computer books or perioficals read Definitions of levels in attitude towards using computers in schools
Mean scores of subjects attitude scales
Number of subjects believed that computers could be used in different areas in schools
BoxM tests for Homogeneity of dipersion matrices for dependent variables ATUCCT and ATUCSA
Hotelling's T2 tests of subjects ATUCCT and ATUCSA with different independent variables
Univariate F-tests of ATUCCT and ATUCSA
Mean scores of ATUCSA of subjects with different school variables
Mean attitude scores of subjects with different major subjects teach
Mean attitude scores of subjects attending different No. of computer courses in formal education Mean attitude scores of subjects attending different No. of courses with coputer appliations Mean attitude scores of subjects with different computer accessibilities
Mean attitude scores of subjects with different types of computer applications in daily work
Mean attitude scores of subjects with different levels of computer literacy
Frequencies of subjects interested in attending computer courses with different levels in subscales

viii

80

81
82

83

85

87
88
90

92

92
93
95
96

98

98

100
100

102

106

Table

4-44

4-45
4-46

4-47
4-48

4-49

A-1

Description

Page

Number of subjects in different ranks of interests in attending computer courses
107
for teachers
Number of subjects interested in attending computer courses with different levels of CPINF 109
Number of subjects interested in attending computer courses with different levels of CPSOC 110
Number of subjects interested in attending computer courses with different levels of CPCOM 110
Number of subjects interested in attending computer courses with different levels of ATUCCT 111
Number of subjects interested in attending computer courses with different levels of ATUCSA 111
Mean scores of items in Computer literacy scale 126

List of Figures

Figure
4-1

4-1

5-1

B-1
B-2
B-3
B-4
B-5
C-1
C-2
C-3

Description

Page

Distibution of item means of computer literacy scale
A hierachical relation of attitude towards using computers in schools, computer literacy and teachers' backgrounds
Model of improving teachers attitude towards using computers in school
Normal plot and detrended normal plot of CPINF
Normal plot and detrended normal plot of CPSOC
Normal plot and detrended normal plot of CPCOM
Stem-and-leaf plot of CPINF and CPSOC
Stem-and-leaf plot of CPCOM
Normal plot and detrended normal plot of ATUCCT
Normal plot and detrended normal plot of ATUCSA
Stem-and-leaf plot of ATUCCT and ATUCSA

59

104
119
128
129
130
131
132
134
135
136

CHAPTER I

INTRODUCTION

The more recent view of the computer in the classroom is not that the computer will reinforce current teaching methodologies, but that the computer will alter both content and method. The computer is viewed as a tool to expand and enhance thinking and problem-solving skills in all subject areas (Fiske,l983).
The computer is seen not as a device to deliver information to students, but as a device that allows the student to access. organize, manipulate, and communicate information (Sheingold, 1984).

1 . i Summary

Computer

is

now a major tool for

dissemination and upgrading of all technologies,

becoming and transfer,

codification,

rapidly

and is

an indispensible partner in virtually all technological

industrial

process. (Chen,

1986)

The

same

story

in

technologies is now happening in the classrooms of elementary and secondary school classrooms. opportunities offers

teaching

for

In classroom,

enhancing

the use of computers

elementary

secondary

and

in many subject areas - opportunities that

being

are

missed because many teachers at all levels do not know how to use computers in the classroom and are not prepared to

teach

about

their impact on our society. (Miner,l982)
In Hong Kong,

education

are

all the concerns on secondary school computer

focused on the subject "computer

studies'.

study is trying to explore a different area - the first of general

classroom

application of computers in

all

This

question subject areas

whether

:

attitude and

teachers are well prepared

our

in

terms

of

competence.

This chapter first explores the meaning of computer education and then reviews the Eong Kong situation of computer education

secondary

school and concludes with the statement of problem

in

of

this study.

1.2 Computer Education
According

to

computer educators (Deringer &

Engle & others ,1983;

Jay 1985;

Chen 1985),

Molnar

1982;

Computer education

can be roughly divided into 2 levels:

i. Education for computing
The

theories and applications of computers are taught

as

a general subject,

under

the

subject

title

'Computer Science" or "Computer Studies. ii. Computing for education
Computers
instrument

are used as equipments in studying and as an in delivering instructions to increase

the

productivities of teachers.

Luehrman (1972), and others in the early 7Os began to raise an important issue :

what is the appropriate use of computers in

education? Should computers help in teaching students ? Or should students be

(1981) put it,

just

be

the

taught how to program computers ?

Dwyer

Or as Tom

should the students be trained to be the pilot or passenger 7

That

is,

should

students

receive

comprehensive training in the use of computers so that they

know

how

to select and assemble appropriate hardwares and can program

the

computers to carry out desired tasks just like a pilot

how

to control a plane.

Or should the students only be

know taught through

the computers by CAl packages or obtain certain

through

standard software package just like a passenger who

reach

the

results

can

destination by a plane but he does not know how

to

operate it.

From

who extracted

work of Hunter (1982),

the

about

lOO

landmark studies about the developments of computer education
USA

from

1949

to

1979,

it

can be seen

that

in

trend

the

of

development was from Teaching students how to use computers " in extended to include 'Using computers in classrooms for

the 60's,

redesigned
CMI

computer

basis learning strategies such as

and also in the delivery of instructions
'Effective1y

integrating

'I

computers

developed

to

curriculum

to increase the teacher productivity

fact

In

computers used

in the

delivery

program

movies,

into

in the

'

the
80's.

instructions

of

Computers

also

etc,(Turner & Hammond,

tests,

keeping student

If the capabilities of

1975).

computers

can be

fully utilized

curriculum

of

subject areas and into

integrated

and

into

the

school

system,

administrators and teachers can save the time of

routine

all

the

and clerical works for works required decisions and such and

with

can be used in adminsitering and marking

school

70's

laboratary demonstractions etc.

instruction capabilities (Philip 1983) .

records,

and

overhead projectors,

combine the characteristics of blackboards, slide projectors,

fl the

CAl

as

planning

and development

of

creativities

curriculum,

teaching

strategies

system

school

and

and

etc.

hence

the

increase

productivities of them.
In

some

industries,

such

industries,

the

as

banking

airline

and

they are now developed to a state that none of

them

can survive without computers. In the school system, the same may soon happen:

expensive;

the

the

cost of computers is becoming less

potential applications of computers is

more and more obvious; a systematic

knowledge

and

less

becoming

all that needed are quality softwares and

plan for implementation

.

Following

this

trend,

of operating a computer will sooner or later becomes a

The same problem in developing

survival

skills of teachers.

computer

based system in other industries will also arise in the

school system,

that is,

in the developing stage,

a

all resources

used, time, money, space etc, will be much more than the existing system. The problem is whether we have a team of teachers who are able and willing to integrate computers technologies

into

the

classroom.

1.3 The development of computer education in Hong Kong
The
was
1980

subject t'Computer Studies

introduced

at Form 4 and Form 5

to the Hong Kong Secondary School

and was implemented in 1982.

Since 1982,

levels

Curricula

in

210 schools have

been equipped with computers (11 sets of micro-computer) so that the subject computer studies can be taught ín these

schools.

In

1986, another 93 schools will be provided with similiar machines.

According

to the Education Department,

all Government and Aided

Secondary Schools will then be provided with computers.

Since studies" computers and only

are only used for

the

subject

a small proportion of students

particular subject

"computer

choose

computers in schools become the

this

possession

of a small group of persons. This is a gross under-utilization of computer the

schools

in

keyboard during facilities.In fact as the class size of
Hong Kong is 40,

practice during the lesson. time and after school.

lunch

practically

are

demonstrations.

purpose

students cannot

of

during

idle

school

have

They have

secondary individual practice

their

Most computers in hours except

schools

for

some

This is a serious waste of resource. Is this the

developing

computer

education

in

Hong

Kong?

Is

computer

studies only a white elephant in the school curriculum?

If

what will

not,

come next?

fully utilize

How can we

the

existing facilities to benefit more students?

As

subject

the

students

with

"computer

of pilot.

more

but

is,

providing

computers,computer terminology, It is important that we have enough

computers and be benefited by

becoming

computer

terms,

in Dwyers (1981)

at

the

pilots,

important is that all our students should know how

interact with that aimed

a comprehensive knowledge of

education in Hong Kong is, training studies"

passengers.

such

To put it in a

to

experiences,

more

concrete

first leveL

education in Hong Kong is on the

However, the secretary of Education (Henderson, 1985), the formal
Director of Education (Haye, 1984) and professional bodies (HKCS,

HKASME, UKACE, 1985) have all pointed out that computer education in Hong

Prof.

Kong should be developed to include the

Chen

(1984)

second

also opines that for long term

5

level.

development,

computing

education

for

the majority of the in-service teachers

and

than

education is more important

for

computing.

In Hong Kong, pre-service trainees

teacher

computers

were

so

are

that

expensive

restricted to only a selected few. training formal

was

education

Some teachers may have formal this group through is

their

But most will have virtually no

A survey (Mon, Tung & Sin, 1984) revealed

knowledge of computer.

only

computer

when

era

an

others may have informal training

few

personal interests in computers.

that

in

but as mentioned earlier,

in computer,
A

small.

educated

education in computer.

some

receive

one-fifth of computer studies teachers

It will not be far from facts

to

assume that teachers of subjects other than computer studies have no training

formal

know how to operate

should

teachers

in computer at all.

It is

computers

own specialized subject(s) in

teaching his/her

effectively the in

classroom.

trainings should be provided for this later group to

Appropriate

era

them to function effectively as a teacher in the

enable

that

essential

of

information technologies.

Teacher training is a long term task. In view of the pace of

development have in

it is just not too late

close look into Hong Kong TeachersT

a

education

and

However,

as

different,

should

computer education,

be

needs

on

computer

to provide appropriate training course for the needs

of

each

individual

teacher

to

them.

may be

a monolithic approach which assumes that all teachers

given

unsatisfactory.

the

Since

same materials teacher's readiness,

certainly

be

both affective

and

will

cognitive,

a major factor determining the success or failure

is

of any new instructional materials in the

in-service

classroom,

and pre-service training programs in computers should be tailored to teachers

of different categories and to

self-initiating

as

well as disinterested teachers.

1.4 Statement of problem

The

purposes

computer exposures, in attending

computers

in

of

this

study

were

investigate

to

the

self report of computer literacy, interest

computer

courses,

and

attitude

towards

teaching and in school administration

trainers, teachers, and teacher trainees

using teacher of

The following questions

are asked in this study:

L

What

Hong Kong

is

Which

literacy?

teachers

group

of

self-reported teachers will

computer consider themselves more computer literate?
2.

What

computer
Which

Kong teachers' attitude

Hong

is

in

group

teaching and of in

school

teachers will have

towards

using

administration? a more

positive

attitude ?
3.

Are Hong Kong teachers interested in attending computer courses ? course in terms of

Which type of training courses,

contents and time of conducting,

will be

attractive to which categories of teachers ?

7

most

1,.5 Purpose of the study
It

reveal

was expected that the answers to these

Hong Kong

competence

on

Teachers

computers,

background of

would

questions

level

of

computers

in

training,

attitude towards using

schools and their interests on attending computer courses,

would be

of

help to educational

administrators

which

tailoring

in

computer courses for teachers of different categories.

1.6 weed for the Study
In Hong Kong,

computer

several survey

studies teachers (Moon,

effectiveness

of the subject

studies on the background
Tung and Sin,

1984)

,

on

Computer Studies" (Moon and

1984) and on the response of Principals,

Teachers,

of

the
Tung,

and clerical

staff to the implementation of miaor-computers in schools (Chung,

Tung and Moon,l985) have been conducted. However, studies attitude teachers'

towards

using computers in schools

on the

and on

teachers' level of competence in operating a computers could not be the

of

found in the literature.

Using computers in classroom across

whole spectrum of curriculum is gradually become the teachers' seminars

associations and

and workshops,

the

educational

focus

authority.

participants generally opined that

In

the

computer literacy level of Hong Kong teachers is low and there is an urgent need to provide in-service training. This study intends to confirm

these conjectures and to further explore

through a survey study.

this

area

1.7 Limitation of the study
The
from

the

study was limited to the analyses of the data collected selected secondary schools teachers and

Colleges of Education in Hong Kong.

lecturers

in

CHAPTER II

REVIEW OF THE LITERATURE

2.1 Summary

The purpose of this study was to study Hong Kong

background

of

training,

attitude

towards using

teachers

computers

in

schools,

self-reported

knowledge

and

interest

of attending computer training courses in order to

map

competence

of

computer

out the training needs in computers of Hong Kong teachers and

to

suggest an outline of course dessign. To fulfil this purpose, the trend of

reviewed

development of computers in education should first be to justify the needs.

teacher

education,

teacher

education

teachers

would

the

And as this

development

study

of computer

and the definition of computer

then

be

reviewed.

Finally,

focused

on

education

in

literacy

for

literature

and

research on the relations of teachers attitude, computer literacy

levels demographic variables and background of training would be reviewed. The four major areas of literature reviews are

i. The development of computer in education ii. Computer education in teacher education iii. Defining computer literacy for teachers iv. Related research works

2.2 The development of Computer in Education

No

one

is in any doubt that the computer era has

arrived.

Due to the rapidly improving capabilities of computers, it is not just becoming a subject of study,

important

tools

schools.

events

instruction

elementary

in

into

an

secondary

and

mapped out by Hunter (1982) who extracted about 100

As

in

of

but also developing

development of computer

the

Tinsley

(1975)

British

computer

education

who reported the work of the society, in

school

and

US,

committee,

Computer Education has

two

major

components
Education

i.

for computing :

The studies of the

theory,

operation and application of computers,
Computing for education : Topics in subjects other than

ii.

computer

studies

are learnt through

exploration

and

simulation with computers,

This notion was shared by educators in US (Deringer & Molnar
1982 .

Engle

(Jay,

1985),

1975),

Moursund,

,

view

Bork

1975 )

was

of computers, a ecosystem in education.

development

it was not just a new

new brain,

,

in British

1975; Peless,

1984). Sawada (1985) took a more

that accompanying the

intelligence it ,

in developing countries (Estallela,

and in Hong Kong (Chan,

extreme

tool,

& Rogers 1983

and

of

artificial

technological

computing would become

an

Teachers must become effective catalysts

for student-directed learning.

It was also indicated that the task for developing

computer

education in the SO's was to integrate computer applications into other curricula in elementary and secondary schools, and into the

11

school administration,

(Camine,

to increase the productivity of teachers.

Shuman

1984;

Working party

1985;

Computer Society Schools Committee 1980;
Beck, 1980

)

States & Shostah, 1975.

The notion was supported by Researches which showed

.

Based

Computer

that

Britich

the

of

Education

positive

(CEE) had

achievement of elementary

effect

in

improving

the

students,

where the low-achieving group had the most significant

improvement (Bj&k,
And Others,

Loftrup & Nìlsson
Fise,

1985;

pre-schoolers

(average

secondary

1975;

school

Eangert, Rodert,

Johnson (1985) found that even

1985).

age

and

49 months) had

underpinning for computer involvement.

important

Projects in

cognitive

implementing

computers into the school curricula, either in the whole range of schools from kindergarten to grade 12 (Douglas & Bryant, just several schools (Green 1985) all

in

encouraging

Subject basis projects in teaching with computers, such

results.

mathematics

in

as

reported

1985 or

(Shepherd,

1985),

&

(Lesson

history

Jaworski,

(Nichol

1975)

1985),

geopraphy

,

chemistry

(Gerhold

1985), social studies (Cacha 1985), and even liberal art (Canson all 1985)

showed

that computer could be

an

useful

tool

of

instruction in the subjects.

2.3 Computer education in teacher education development The

of computer education leads to the

notion

that all teachers of the 80's should know how to use computers to enhance their specialized skills and to improve the

their teaching (Anderson 1980;

Engel

,

Moursund

,

Estenson,

& Rogers 1983 . )

12

,

1985

quality

Mansell,

which further leads to

of

1984;

the

world-wide

of lacking appropriately

problem

(Wearing,

Engel,

1975;

Moursund,

Education Association 1983;

discussed

that

&

trained

teachers

1983;

National

Rogers

Tung & Sin 1984).

Mon,

Agee (1985)

many courses designed to help teachers to

teach

with and about computers actually focused on user training. There is urgent need to design and

an

courses for teachers.

literacy

conduct

appropriate

Numerous reports on

training

projects in computer

courses for pre and in-service elementary and secondary

school teachers could be found in the literatures in recent years

& Shavelson,

Staoz,

1984,

Okey, 1984; Moore, 1984; Lioyd, Taylor, & West

1983;

(Anderson,

Wholeben, 1985)

objectives

course

to

of

computers,

and

the

of

implication of computers, a given role.
,

few the aspects

Watt (1982)

years

degree

capabilities

social

and

vocational

teacher's

course hours from

low

limitations

of

and

educational

to a matter of functioning effectively

However

as pointed out by Seidel (1982),

not all individuals or groups needed to

individual

with computers and which could be

dramatically in next decade if necessary.

13

learn

computer

way,

should be dynamic which varied according to involvement 1985.

from few

course,

about computers to the same degree or in the same literacy Garhart,

where the mode and duration of attendent

,

technical

and

&

Streibel,

and course contents varied greatly,

appreciation

within

1985.

expand

2.4 Defining computer literacy for teachers
In the above reviews,

clearly defined

.

the term Computer Literacy" was

not

It shared the semantic ambiguity of the other

literacies, such as language literacy, scientific literacy, etc..
(Anderson,

others

1980).

works

Wilkinson & Patterson (1983) after

concluded that there were 2 extremes in

computer literacy for teachers.

how

computers think. to

CAl

2.

reviewing

1.

Programming base

defining
- teaching

think as a tool of teaching children how

or CMI base - teachers and students needed

know how to operate a computer,

just like operating a

T.V.

to

only set and needed not know how to program it - left it to the experts.
A

by

survey

Lacina

(1984)

revealed

that

both

computer

coordinators (N=88) and program directors (N5l) shared the view that two competences were very important for teachers.
:

evaluate

to

i.

computer

and choose quality software

instructional tool in drill &

as

simulation and problem solving. evaluate hardware,

They are to ii.

,

practice,

tutorial,

However, the competences to i.

ii. program the computer and the knowledge of

the history of computer were just moderately important.
&

Peterson

applications,

the ii. knowledge

opined

teachers.

trends

that

i.

educational

computer

elementary programming technique.

from

computers

De Vault and Harvey (1985) examined
1960

to

1980 related

to

Hart

should be

programming and problem solving

literacy

in the in-service training course of computer

included for computers

computer terms & operations, ±1±. course-ware

evaluation technique iv.
(1986)

of

Pantiel

for

(1985) discussed that teachers ready

have

should

use

issues

instructional

and suggested that a teacher education program

uses

and of should

include

experience with

i.

professionals,

hands

iii.

examination of softwares,

children,

on

discussion

ii.

experiences,

extensive

iv.

y. curriculum development opportunity.

In a teacher training course at Western Oregon State following the

records,

entire

elements

were

curriculum packages,

y.

selection (Wright & Forcier, in Kansas city,

.

tutorials, iv.

iii.

and

In the report of a workshop it suggested that the

in 1982,

operate a computer and run a program,

based learning materials, to managed

requirements of computer literacy for all teachers were

minimum
i.

computer

i.

software evaluation

vii.

1983)

Missouri,

University,

video computer interface vi.the

as an exploratory tool,

computer

help

included,

drill and practice material,

ii.

among

3.

know the style of using a computer vi.know the

address major classes of objective,

related

information

and

evaluate computer

ii.

sources

Moursund &

resources (Engel,

of

Rogers

1983).

mention before,

As

it was impossible to have a

definition of computer literacy for teachers. above could literacy computer

initial

However, from the

at least map out the course for

pattern

of

an

non-computer-studies

i. knowledge of a computer system and its capabilities

teachers:

and

we

reviews,

'tprefect"

limitations,

that was the informative elements of

computer

literacy, ii. awareness of how computers could be used in schools and our society,

in

literacy,

system

was

and the and

iii.

of

computer

hand-on experience in operating a

computer

that was the social elements

the abilities to select appropriate communicative element

15

of

computer

softwares literacy, that

were

essential

of such a

elements

programming and y elements. .

while

knowledge

iv.

of

knowledge of hardwares were moderate important

pattern

This

course,

could also be regarded as

the

minimum

on the relations between attitude

towards

requirements of computer literacy for all teachers.

2.5 Related research works

Many

researches

computer

based

exposure,

computer

knowledge

and selected demographic characteristics of

teachers,

teacher

instructions,

trainee

literature.

and

computer

school administrators were

found

in

the

Table 2-1 summarizes the works of li authors in 1984

to 85 on such relations.

In addition to the relations in Table 2-1, used a four parts questionnaire, ii. computer exposures,

iii.

Bradford

i. demographic characteristics, computer literacy,

towards

utilizing micro-computers in public school

analyze

the

administrators that relationships
,

that

between these

attitude

iv.

setting,

variables

He

there was significant difference between the attitude

the

found

mean

board members and teachers,

and also

He also

revealed

respective computer literacy scores.

computer exposures scores were related positively

attitude

to

school

on

board members and teachers (N=203).

scores for administrators, for (1984)

and computer literacy.

Finally,

to

both

he discussed that the

overall low computer literacy and attitude scores along with

the

low computer exposures scores identified that there was an urgent

need

to

improve

both teacher computer literacy

and

attitude.

Table 2-1
Relations between
Teachers' Attitude toward Computer-based Instructions and
Their Computer knowledge and selected Demoqraphic Characteristics

Author

year

Subjects
.v
.-

:x

...

4'
Lf

u
8

:;

==

>

.

t:
.;:

-*

rI

, l -

r.

=t-

¿
-

1984

N=203

z1 --

-

-t

_;

,ç

X

administrators
& teachers

Valesky

1984

N=385

X

X

O

O

O

O

X

X

teachers

Coffey

1984

N=44 administrators X

O

O

O

Martin

1984

N=236

X

X

X

O

X

X

teachers

Fester

1985

N=26 teachers X

Earl

1984

N=348

X

teachers

Ruechert

1984

N=522

X

O

X

teachers

Dambrot

1985

N=941

X

X

col freshmen
Bitter

1985

N=240

X

teachers

Loyd&

1984

O

O

O

O

X

Gressard
Grasty

1985

N=318

O

Significant difference in attitude
X
O : Insignificant difference in attitude
:

17

O

-

-

:

:=

-s-,

E

t-.

E

.

,-

Bradford

i,

L

-

Luning (1985) ±n a simular study on teachers (N=226), which also asked the actual use of computers in classroom and use

teachers

self-reported

of

competence

computer

computer competence.

an

as

indicator

their

He then randomly interviewed 20 teachers to

investigate whether the self-reported level of competence was an good revealed use for actual level

indicator

of

of

competence.

Her

analysis

that there was positive relation between knowledge

computer in classroom and when knowledge was

and

increase,

opinion on the type of use was also increase. She also found that the self reported level of computer competence was a good overall indicator computer

of

competence but was

not

sufficient

a

indicator for further training.

In

assessing

instructions,
(1984) (N=236)

Valesky

in
,

attitude

the

addition

towards

to the results of

based

computer table Martín

1,

that non-users had interest to learn more.

found

(1984)(N=385),

found

that

mathematics

and

science

teachers had more positive attitude than other teachers; teachers of than

3-4 years of teaching experience have more positive teachers with less or more years of

teaching

attitude

experience;

one or more in-service training programme(s)

teachers

taken

computer

had more positive attitude.

However,

computer

in

course

work in higher

education did not affect their attitUde. Rueckert

(l984)(N=522),

reported

that 90% of the teacher recognized

the

importance of 03E, 80% showed support, and 60% were interested in computer attending

of business studies,

teachers

had

courses.

more

positive

attitudes

Grasty

(1985)(N=3l6)

found

that

foreign language and mathematics towards computers

than

other

teachers.

Chung, Tung and Moon (1985) conducted a survey on the

responses

of

implementation
(N=75x4)

principals,

teachers and clerical

staff

the

to

of micro-computers in Hong Kong secondary schools

They found that teachers who know how to operate micro-

.

computers

would have significant favourite towards using

computers

in schools.

evaluating the results of computer training courses

In teachers, Coffey (l984)(N=44),

revealed

that

used a pre and post test

attainment of computer resulted a the effect

more

for

design positive attitude,

however,

attitude.

He also found that female could attain more than male.

Feaster

(N=26) using the same strategy,

(1985)

could

increase

both

participants.

Thompson

(1985)

course

assessed

on attainment was

abilities

knowledge

the

found

computer rose

in

depended

found that

the

attitude

of

and

participants'

that

on

significantly

self

their

and

anxiety about computer decreased.

The

reviews

highlighted

that,

(a)

computer

exposure,

represented by the accessibilities to different computer systems and chance to be exposed to the latest development

the

computer

was

industry,

computer

teacher's

an very important factor to

competence

computers in schools,

and

attitude

of

enhance

towards

the a using

(b) one or two computer training course(s)

for teachers could improve both their level of competence on, and towards, attitude

using computers in schools,

in using

competence attitude towards

computer

training

computers had

using them in

positive

schools,

(c) the level of

correlation with

(d)the

advantage

courses for teachers was two folds

increase their capabilities,

ii.

:

i.

of

to

to increase their willingness,

in using computers in their teaching. study It was the purpose of this

to investigate whether these relations could be

Hong Kong.

20

found

in

Chapter III

METHOD

3.1 Introduction

When

conducting suitable technique(s) questions. one

In

a

for

the

study,

answering

the

researcher

examines

particular

research

order to choose the appropriate research

method,

must understand the nature of the research and the obstacles

to obtaining the knowledge to answer the questions.
The purpose of this study was to study the computer literacy and attitudes

teachers in order to justify the needs of, service was

Hong Kong

towards using computers in schools of

training courses in

and to

computer for teachers.

a descriptive survey type study.

in-

suggest,

This

study

In descriptive survey type

study, the researcher must satisfy himself in two questions, that are, a,

"Can

the instrument used to collect data

measure

attributes of the subjects that he wishes to measure ?", uIs the

sample

of

his study a

representative

sample

population where he wishes to draw his conclusions 7 two areas were the foci in the design of this study.

and of the
b.

the

Hence this

3.2 Instrument

Two survey questionnaires were developed to collect data for this study. They were
A. School questionnaire
B, Teacher questionnaire

qo J, qíorairre

3.2.2

The variable shorten these purpose of school questionnaire was to

which were

collect

common to a set of subjects

school

in order

to

the teacher questionnaire and to ensure the accuracy of

variables.

description

The

school

questionnaire had

items.

A

of the variables in it was given in Table 3-1 and

a

8

copy of the questionnaire was given in appendix D.

Table 3-1
School Variables

Variable

SCHTYP
SCHSEX
SCHAGE
SCHLOC

SCHCST
SCt-iCAD

SCHCOC
SCHCOM

Description

1 item measures the type of school
1 item measures the sex of students
1 item measures the age of school
1 item measures the location of school i item measures whether computer studies is in the school curriculum item measures whether the school has used
1
computers in some of its administrative work item measures whether the school has a computer
1
club item measures whether the school has computers i other than those for computer studies

22

3.2.3

Teacher questionnaire

3.2.3.1

çn

There were 3 sections in the teacher questionnaire. literature reviews,

towards

using

researchs reported that teachers

In

the

attitudes

computers in schools and their computer

literacy

level were related to certain demographic characteristic and also to their

trainings in computers as well as their

attending computer courses.

interests

in

In order to investigate whether such

dependence is also true in Hong Kong situation, the first section of the questionnaire,

demographic

characteristics

applications teaching, with 29 items,

in

and b.

was directed at

of subjects.

schools were on

two

Most of the

areas:

in school administration,

a.

in

gathering computer classroom

the second section,

with li items, was organized to gather teachers' attitude towards these two areas. The third section, with 24 items, was devoted to measure the self-reported computer literacy of subjects. Items in this section were based on the evaluation section of the computer literacy programme for teachers designed by the Further Education
Unit of the British Government (Lloyd,

considering teachers the

computer

different definition of computer

1984). By

literacy

cited in the literature review and by considering

target

studies

the

Taylor & West,

population of this study were majority

teachers,

softwares,

that

they were

consumer,

not

for that non-computerproducer

of

this section was aimed at measuring whether

subjects had,

23

a. basic understanding of what a computer is,

b. knowledge

some

of

computers

applications

and

their

implication,

c. knowledge of basic operation skills of computers.
In

items

particular,

were

set

to

measure

subjects

competence of computers in the following areas:
a. Informative elements,
b. Social elements,
c. Communicative elements.

3.2.2.2 Scaling Method

the co-operation of the subjects in

In a survey study,

returns

of

questionnaire

success

of

the

study.

is

a very important

To ensure a

questionnaire must be easy to complete. easier to

than

answer

open

higher

return

questions,

all

closed questions except the

subject

order to collect

In

subjects,

an

"Other(please

opinions

specify)'

to

rate,

the the As closed questions were

questionnaire were teach. factor

the

items

one of option was

in on this

major

enthusiastic

included

in

suitable items.

scaling

In

knowledge of the

4

items

of

section one

measuring

of programming language and the expected

computers

in school,

it was very difficult

to

the

applications

define

the

levels

of knowledge and the levels of expectation on an interval

scale.

However,

it was expected that when a subject

with a question such as

24

confronted

-Do you know BASIC? you -Do

or

that computers can be used

agree

drill

for

and

practice in your daily teaching?

he/she would have a discriminai tYes" or 1No' answer. deteministic model, or that was,

to the questions,

"No"

Hence

the subjects only responsed "Yeso

was chosen for scaling in

this

The discriminai process might be different for

areas.

That

individuals.

statements

response

for

is,

of BASIC,

those

subjects

knew

two

different

only

few

a

some might response 'Yes" while some might

By taking into account that this situation

"No".

a

only

happened in borderline cases which were not be the majority,

- a

subject who could write a useful program would not response

No'

to

stimulus - this method was considered as a

this

and

method to indicate the subjects' low end understanding

effective

In order to simplify and shorten the items, the

of the stimuli.

were

stimuli

simple

listed

and subjects were asked

circle

to

those

stimuli with a 'Yes" response. section In

the scaling of

two,

attitude

Under

Likert

items are monotonically related to underlying traits. assumption, this

scale

advantages

of

approximately construct was

That is,

assumed that the 2 traits measured were unidimensional. individual it

items,

a summative model using a

was chosen for scaling this five

attitude

the

items.

to

the

trait,

and (iii) it provides a reliable,

rough

is

easy

to

ordering

of

(ii)

people with regard to a particular attitude (Oppenheim,
141)

25

The

scores

model are (i) summation of item

linearly related

points

1968

P

as it was very difficult to find subjects who

In section 3,

were willing to be tested of their competence in computers, items of this section were self-reported competence in

method was

scaling

The

a four levels comparative

computer.

responses

self-

The competence

reported competence similar to the Likert scale.

of an item was divided into the following 4 levels:

a. Never heard/try

b. Have heard/tried
c. Know how but not comprehensive

d. Comprehensive know how were Subjects

understanding

of

disadvantage

asked the induced by

on

this

item.

different

that

interpretation

to

circle
This

have

may

the levels of competence.

scaling method was

method has

scaling

subjects

estimated

own

their

discussed

different

short

The in the

coming

Chapter

V.

However, this method has the advantages of Likert scale discussed above. The questionnaire thus constructed had 63 items.

3.2.2.3 Pilot Studies

After

lecturers

initial in contacts,

24 secondary school

teachers

Colleges of Education were selected for the

study to assess the quality of an item in sections 2 and 3.

or

pilot

They

were identified into the following three groups
a. Have comprehensive knowledge in computers
b. Have moderate knowledge in computers
c. Refuse to interact with computers

Questionnaire with serial number for

identification

purpose

was sent to each of the selected subjects with returned envelopes and covering letter asking their co-operation to

a

questionnaire questionnaire. week. to week and to suggest

one

in
All

24

return

improvement

the

to

the

questionnaires were returned within

one

Interviews were then set up with the subjects, either

face

or

through telephone, to determine

would be desired for the final version of the

what

face

modifications

questionnaire.

In

the interview, they were asked to comment on
a. The time needed to complete the questionnaire;

b. The clarity of the instructions and the items; and
c. General impression, readiness of the questionnaire.
Item

were

total

found

correlations and reliability of

each

subscale

to ensure that each item was a good measure

of

the

According to the suggestions gathered in the interviews

and

subscale.

the results of analyses, the format and wording of some items and

instructions were modified.

Particularly,

the following

major

amendments were made:
Item on "Viewdata" was poorly answered.

a.

by considering

the fact that subjects were in the teaching profession who might have less contact with the commercial world,

this item was replaced by Easy Pay System (EPS).
b.

An

anchor

items (item 35) was added to

the

attitude

towards using computers in school administration scale.

After amendment, the questionnaire had 64 items, The name of subscale together with their measuring items

variables

or

given

Table 3-2 and a copy of the questionnaire was

in

Appendix D.

27

were

given

in

Table 3-2

Variables in Teachers Questionnaire

I tern

Variable

No

AGE
SEX
MARSTA

1
2
3

ThAThA

4

HIGEDU

5

MAJSUB

6

YRETEA
PERADM

7
8

CCAPP

9

CCFOR

10

CPINSC*

13-14

CPREAD*

15-16

CPACCE*

18-20

CPUSER*

21-23

ATUCCT*

30-34,39

ATUCSA*

35-38,40

CPINF*

41-52

cps*

53_57

CPCOM*

58-64

*

Description

1 itern rneasures the subjecVs age

1 item measures the subjects sex
1 item measures the marital and family status of the subject
1
item measures the teacher training of the subject 1 item measures the highest education of the subject 1 item measures the major subjects teach by the subject
1 item measures the years of teaching experience item 1 measures the percentage of administrative work in the subjects work load
1 item measure the number of courses attended by the subject in his/her formal education which required the application of computers.
1
item measure the number of computer course attended by the subjects in his/her formal education items measures the number of in-service
2
computer training course attended by the subject items measure the subject's reading on
2
computer items measure subject's accessibility to
3
computer systems
3 items measure whether the subject is a user or non-user in his/her daily work
6 items measure the subjects attitude towards using computers in classroom teaching
5 items measure the subject's attitude toward using computers in school administration
12 items measure the subjects competence in the informative elements of computer literacy items measure the subject's competence in
5
the social elements of computer literacy items measure the subject's competence in
7
elements of computer communicative the literacy

The justification of composite variables given in Chapter IV.

or

subscales

were

n

3.3

The

subjects of this

Government lecturers or

Aided

from

study was

464

teachers

secondary schools in Hong

the 4 colleges of education in

reasons of choosing this sample were

:

1987.

schools

(b)

Hong

with

4 and 6 years

Kong.

112

The

micro-computers

Graduate and non-graduate teachers

teachers

and

Kong

23

(1) All secondary schools

and colleges of education will be equipped with in from

of

secondary

of

teaching

experiences

respectively can applied to be appointed as lecturers in colleges of education.

This

two groups of teachers hence

have

similar

training background but we different working environment. interesting to see whether there is any difference in

It is

competence

in, and attitude towards, using computers due to this difference.
The

teachers

selected

might

or

might

not

be

teaching

computer related courses. In order to have a representative sample pool, the schools were stratified according to the following four school variables
a. Type of school

b. Age of school
c. Location of school
d. Sex of students

The distribution

of schools in the stratifying

given in Table 3-3 and Table 3-4.

29

plan were

Table 3-3
Sample Schools Stratified by
School Age and Sex of Students

Sex of student
Age

Boy

Girl

<10

0

0

5

5

10-20

2

1

5

8

>20

1

3

6

10

Total

3

4

15

23

Co-Ed

Total

Table 3-4
Sample Schools Stratified by
School location and School Type

School Type
Location

Government

Aided

Total

Urban

3

7

lO

Urban Estate

O

3

3

NT Estate

2

8

9

Total

5

18

23

In the table, there were some empty cells, the reasons were:
i.

All newly opened schools were co-educated schools

ii. All new Government schools were in NT.

30

In

the design of sampling strategy,

it was considered that

if a small number of questionnaires (10 for example) were sent to a large number of schools, the ultimate result might be only those

teacher with

some

knowledge in computers

would

complete

the

questionnaires and thus formed a seriously biased sample.

The small first

number

design of sampling strategy was of stratification

schools,

and

less

than

lO,

to

selected

according

a

the

to

asked all teachers in the sample schools

to

complete the questionnaires.
After

approaching the Principals of several from their experience,

all advised that,

schools,

not all their teachers

were enthusiastic in helping research work and as the of questionnaires were on volunatary basis, their help.

more work. completing

they could not force

colleagues to complete research questionnaires.

estimation,

They

they

To

their

half of their colleagues would be willing

to

also advised that a popular teaching staff would

be

about

effective

in

pushing his/her colleagues to help

According to the advices,

such

it was decided to send a agreed

number of questionnaires to larger number of schools.

31

in

3 4 Procedure
After approaching Principals of secondary schools to the stratified plan,

according

twenty-three schools agreed to help

in

administering the questionnaires to their staff. The distribution of schools were given in Tables 3-3 and 3-4 . The Principals also agreed to

of

of his/her staff

one

appointed

The

exercise,

number

appointed

teacher was contacted to

questionnaires

to

be sent

the

coordinate

to

according

agree to on

his/her

estimation which was approximately 60% of the number of staff their schools. and a

The questionnaires,

returned

packet,

returned

with

a

envelope.

The

coordinator with

a

were sent to the coordinator in a letter and

covering

in

each with a covering letters

envelope addressed to the

proposed deadline of return,

a

a

pre-addressed

coordinator then return

stamped

completed

the

questionnaires received after the deadline in a packet.
All

four

Colleges

of

Education agreed

to

help

in

the

research and tthe same strategy for school applied.

In the covering letter,

the investigator promised to send a

summary result of this study to those subjects interested.

32

na1 ses

3,5

3. 5.

1

One

of

important factor governing the

the

success

survey study is that the instrument can measure the

of

a

psychological

traits the investigator wishes to measure. In this study, several psychological traits,

represent by different subscales, were each

measured by a set of items.

measured

To ensure that each set of items had

the psychological trait they intended to

they

measure,

had to satisfy that,

a. all items in each set were measures of the same psychological ensure could be tested by factor analysis to

which

trait,

the unidimensionality of the subscale.

b. all

items

that the was,

total

reduce

deleting an item from the subscale would

reliability of the subscale,

item

subscale,

in each set were good measures of the

which could be tested by

correlation of each item

and

the

coefficient

Alpha of each subscale,

c. the

trait

subscale was measure of the desired psychological

which could only be justify on logical basis.

Due

to

the latest development in the technique

different

analysis,

of

factor

researchers may apply factor analysis quite

differently in their work to meet their own requirement. As proper use of factor analysis was a necessary element to the validity of this study the investigator wished to discuss how factor analysis was applied to this study in this section.
In

Factor Analysis,

correlation

the basic assumption is that,

matrix of 3 or more observed variables,

33

given

there is

a a restrictive, the falsifiable hypothesis that all the correlations in

matrix could be explained by the correlation of the observed

variables

with one or more unobserved variable(s),

called

the

common factor(s).

The mathematical model of Factor Analysis is:

y =f x +f x +....+f x +e jil i

j22

jmm

j=l...n j Where yj is the jth observed variable, j5 the pth common factor

X

p=l .

.

m

.

p is the residual of y, about its regression

e
J

on the factors (the unique factor)

is the regression weight of y

f

on x

ip p j
Using this model, each observed variables consists of 2 parts

a. the regression on the common factor or its generic part

(f x +f x +....+f x) j22 jil

jmm

residual about the regression or its specific

the

b.

part

(e j common

The

comon in

the

partialled out,
It

sense

that

is/are what the if the

common

variables factor(s) or

important

a little, is have

in

is/are

the residuals of the variables are uncorrelated.

not important whether the common factor(s)

is

lot,

factor(s)

that

explain(s)

What

of the variances of the variables. it explains

their

a is correlations

completely

to test a

hypothesis

(Mcdonalt 1985, p 30),

According

to

the above discussions,

specifying the number of common factors for a set of variables, we have to assert the followings
1.

To

test

that the set of variables are suitable

Analysis

34

for

Factor

a. The

variables must be related to each other that they share

common test factors.

the

identity

Bartletts test of sphericity is

used

to

is

an

This hypothesis should be rejected at

an

hypothesis matrix. that

the correlation

matrix

appropriate level of significant.
b. The other indicator for the existing of common factor(s) if the

partialled

out,

that,

variables equal linear

effects

of

other

the partial correlation between a pair

should be close to

zero

(which

to the correlation of residuals).

tested by

the

variables

Kaiser-Meyer-Olkin

is

are

of

approximately

This hypothesis is

measures

of

sampling

adequacy,

Where r

is the sample correlations íj is the partial correlations

and a ii KMO is expected to be close to unity.
c.

However, is if all the variables are highly correlated, there

redundancy

of information among the variables

and

the

factors will be very difficult to interpret (it may happen that a

variable with small factor loading on a factor

but

with

a

very high correlation with that

factors

for

the

that its variance is accounted by

another

variable

reason which has high correlation with it) .

variables

in

a

subscale which have

35

Hence,

multiple

if there

are

correlation

close to unity with other independent variables, some of the variables have

to

be

eliminated until

variable

each

contribute some thing of its own to the common factor(s).

In this study, items

selected

to

measure

in

each

subscale were constructed

the psychological trait of

the

or

respective

trait and factor analysis was use to confirm the simple structure of items.

factor
He

As noted by Mcdonald (1985),

exploratory approach

analysis is not a good statistical tool for this

of

purpose.

suggested that confirmatory approach should be used for

such

purpose. In his book on Factor Analysis, he wrote,

In the exploratory approach, it might be claimed, we do not behave consistently. We first fit the model with many parameters and no constraint due to simple structure. We then transform the result to an equally fitting approximation to simple structure that may be

very poor

and speak as though we

now have

fewer parameter. But either the low number in the simple structure are consistent with exact zeros in the population or they are not. If the are, we should estimate only they we do not in fact nonzeros. If they are not, have simple structure at all.
In the confirmatory treatment, we decide the nurTer of factors and the location of exact substantive grounds. The zeros on rational, parsimony need not be invoked at of notion all .......................................... that we can break
It should be clear, then, exploratory of tradition from the away to transfomation followed by analysis approximate simple structure, at least in the final stage of a piece of research .......

(Mcdonald, 1985, P 102)

Hence confirmatory approach of factor analysis was used to assess the unidimensionality

of subscales.

The hypothesis

analysis was assessed by the following two criteria

36

of

factor

d. For

a

sample

of

n varib1es,

under

the

restrictive

hypothesis that there is m common factors in the

from which

the sample is drawn,

liklihood ratio criterion (LRc) to measure

defined

as

,

a

function,

population called denoted by 7\

the

goodness of fit of

the

natural

the

logarithm of

the

is defined

hypothesis. 7, is the ratio

of

the

liklihood of the sample under the restrictive hypothesis the liklihood of the sample where there is no

to

restrictions

on the nature of the population from which it comes.Assuming

multivariate square, normal population, 7\is distributed like chi-

if the sample size is large enough,

with degree of

freedom given by
2

df = C(n-m)

- (n+m)]/2

The chi-square value of 7then can be compared with tabulated chi-square for the given degree of freedom.
The comparison is indeed a measure of the departure of correlation and

in

the

matrix of the residuals from an identity matrix

this sense,

measures misfit of the

model

to

the

sample data.

Since

the purpose of factor analysis is to keep account

the data as simple as possible, to the purpose of this test is

affirm the most restrictive hypothesis that is

Hence

if

the

hypothesis of m

of

factors

is

tenable.

rejected,

the

hypothesis with m+l, M+2. . . factors will be tested, until the

hypothesis is affirmed. However, it is clear that the number of factors

retained will depend on the

significant

level

chosen in this nested sequence of statistical decision.
It

is possible that the number of factors retained is

37

more

than to is,

the number of true factors.

It would be a worse error

retain and interpret factors that are tnot factors structure

that are random error masquerading as

in

the

error,

than

omit

to

detectable factors that are real.

that

real',

some

genuine not-very-- More precisely,it would

be rational to ignore a significant chi-square that seems to be requiring at least m+l factors, to supply little to the fit,
That is,

or to the meaning of

the chi-scíuare test,

maximum

of

liklihood

protection

against

if the (m+l)st factor is analysis. combined with the efficiency

estimation,

serve

primarily

as

over factoring in the relatively

a

small

sample.
e.

As

accounting

model,

for correlations is the

purpose

of

factor

smallness of the residuals is by definition the

the

measures of its success in doing so, The trouble with direct inspection of residual matrix as a basis for determining the

goodness

of

comforting

fit

of the model is of

course

the

lack

of

sense of objectively that comes from choosing

statistical

a

significant level and consistently applying it.

A rule of thumb in the decision is that
i. if

all the residuals are less than .1,

it is unlikely

to be able to fit a further common factor that would be well defined and interpretable, ii, if there are some large residuals,

examined

than they should be

to see whether they cluster,

constitution

of

additional factor

the

fitted if the chi-square is significant.

38

indicating that the

may be

Based testing on

the

the

above discussion,

goodness

the

decision

of fit of the factor model

rules

for

be

the

will

inspection of
1. Bartlett's test of sphericity.

The hypothesis of the

test

should be rejected at a chosen significant level.
2. KMO index. The index should be close to unity. correlations of each variable with all the

3. Multiple

other

independent variables. Items with multiple correlation close to unity should be eliminated.
4.

chi-square

of 7 .

rejected at a
5.Residuals

The

hypothesis of the test

should be

chosen level of significant.

of all variables.

The residuals should be

small

(<.1) or with a few large but scattering residuals.

3.5.2 Descriptive statistics

After

deviations

establishing

the

subscales,

the

means,

standard

and frequencies of subscales and other variables were

found and reported.

39

3.5.3 Relation of subscales and independent variables

In this study, a 5% (.05) significant level would be used to test all hypotheses.

There were two major areas of interests in this study. First was computer

the

literacy

of subjects

and

second

was

the

subjects' attitude towards using computers in school.
In the first areas, there were 3 subscales, CPINF, CPSOC and
CPCOM.

this three

As

information

were

correlated,

substantial

may be lost when correlations between variables

Hence

ignored.

subscales

MANOVA had to be used in examining the relations

of these 3 subscales to other independent variables.

MANOVA was an expensive statistical tool, independent and if ANOVA5

the MANOVA would not be significant.

taken were :

(a)

.

ANOVA of the subscales with

variables were found, (b). MANOVA

were

However, as

variable were not significant with any one

subscales,

are

found to have significant

of an of the

Hence the steps independent all

of independent variables which
ANOVA with more than one of

the

2

were

subscales test then

found.

HotellingTs T

the multivariate dependence of the

tests were used

independent

to

variables.

2
(c)

If

the

hypothesis

of Hotelling's

T

of

an

independent

the univariate F-tests of each subscales

variable was rejected,

on that independent variables were found to locate the source dependence. (d)

univariate

F-tests,

different

.

categories

For the those

subscale(s)

subscale

insignificant

scores were broken down by

of the independent

examine the pattern of dependence.

with

of

variable

to

further

Chapter IV

RESULTS and INTERPRETATIONS

4.1 Introduction

The computer purpose of this study was to study Hong Kong

literacy and their attitude towards using computers

schools

in

suggest

training

their

teachers'

order

to

justify the training needs

courses.

interests

in

Teachers training in

and

in

also

attending computer courses

computers

would

to

and

also

he

investigated.

Results

of

the study were reported in this

chapter had 5 sections. the questionnaires were reported.

establish subjects section their In section 4.2 results of

subscales

the to be

4.3.

to measure

sections 44,

administering

varies

attributes

were

subjects computer literacy

attitude towards using computers in schools and

relations

with

subjects'

in

in

and

reported.

Subjects'

other variables were reported

the

of

reported

relations with other independent variables were

Finally,

This

The statistical procedures to

used in subsequent analyses

In

chapter.

section

their
4.5.

interests in attending computer courses were

reported in section 4.6.

4.2 Results of Data Collection
865

questionnaires were sent to 23 secondary schools and

4

Colleges of Education. 592 completed questionnaires were received after two week.

were

The

The return rate of 68.4%.

of the 592 returns 15

either blank or partially completed and could not be

valid returned rate was 66.6% of the questionnaires sent

97,3% of the number returned.

Table 4-1
Number of Questionnaires Returned from Schools

01
02
03
04
05
06
07
08
09
10
11
12
13
14
J_5

16

17
18
19
20
21
22
23

Total

Sent

2

25
50
30
30
30
40
30
25
20
50
50
20
30
25
30
30
30
40
20
40
30 lO 710

or

The details of returns were given

in Table 4-1 and 4-2.

Code

used.

Returned

16
20
40
19
18
23
31
26
21
18
27
20
7

15
14
30
28
25
29
15

Percentage

Void

0
0
2
3

0
0
0

0
1
2
1
0
1
0
0
0
0
1

8

1
0
0

23
5

2
0

478

14

64%
80%
80%
63%
60%
77%
78%
87%
80%
90%
26%
40%
35%
50%
56%
100%
93%
83%
73%
75%
20%
77%
50%

67.3%

Table 4-2
Number of Questionnaires Returned from Colleges

Code

Sent

Returned

81
82
83
84

40
25
40
50

17
18

Total

155

114

Void

Percentage

42%
72%
80%
94%

1
0
0

32
47

1

73.5%

2

The return rates were surprisingly high.

By examining those

schools with exceptionally high return rate, it was found that in schools these

active teachers.

Principals exercise. by

had

For those school with very low return rate, the not appointed any

teacher

to

coordinate

the

They distributed the questionnaires to teachers either

themselves

Kong

the teachers coordinating this exercise were very

or just by tray,

This result suggests that

teachers

were

very passive in this

with

some

active member to motivate them,

However,

willing

to give hands.

unwilling activities, to

kind

It is also possible that

cooperate with

Principals

especially when the principle

in

of

Hong

activities.

they were

teachers

were

type

of

himself takes a

low

this

key (send the questionnaire by tray) but they are more willing to give hands to colleagues. It is suggested that in future research works, this

can be

strategies of administering questionnaires

considered.
Of

that

those schools with a low return rate,

only

it

possible

was

those with great interests in computers would

return

the questionnaires. These subjects would shift the results of the

43

to the high end.

study

That was,

the result of the study were

very encouraging while the actual situation was quite different.
In

this study,

situation

discussed

considering each the return rate was over 60% and hence above might

not

by

However,

the fact that less than half of the teachers in each

school responsed to this study,

with

those

apply.

the

it might happen that

some interests in computers would response

only this to

study which might also result in shifting the results of the study to the high end.

As the investigator did not have access to private schools, the sample of this study did not include private school teachers.

was

It

expected

difference

computer

in

schools

in

computers

that

private

school

literacy

and

might

have

towards

using

teachers

attitude

when compare with

government

and

aided

schools. Hence the conclusions of this study might not be applied to private school teachers.
In

terms

distributed

school

of

variables,

the

Out of the 474 returns from secondary schools,

were

from government schools and 343 from

were

135

aided

school.

121

There

(23%) returns from school without computer studies

their curriculum and 441 (77%) with.

using

sample were well

227 (40%) were from schools

computers in some administrative works and 349 (60%)

those not using.

in

348 (60%) from school had a computer clubs

from and 228 (40%) from schools did not had.
In terms of demographic variables, the sample had some bias.
Of

the 576 returns,

male;

424

graduates;

(74%)

254 (44%) were females while 322 (56%) were

were

graduates while

152

(26%)

were

non-

there were 8 categories of major subjects teach but

188 (33%) were mathematics and science teachers; of the subject was below 30.

only

that

those

questionnaire.

with

Hence

All these results seemed to suggest

interests cares the average age

in

returned

computers

were be taken in

interpreting

the the results

4.3 Establishing subscales

4,3.1 Introduction among Relationships

assessed

variables cannot be properly

until we have good measurements of the attributes (or

variables)

we are interested in. The purpose of this section was to establish meaningful which were good measurements

subscales

the

of

attributes (or variables) this study was interested in.
Subscales

and composite variables

in the

areas

following

were examined in this section rn attitudes towards using computers in school

- self-reported competence in computer literacy
- Backgrounds

of

subjects

training in

computer

and

their applications of computers in daily works

4,3.2

Psychometric properties

There were

11

of attitude scales

items (item 30 to item

40)

measuring

attitude towards using computers in schools. subjects1 45

the

Based on

the contents of the items,

this 11 items were divided into two

groups
30, 31, 32, 33, 34 & 39, which measured

- Item nurriler

subjects'

attitude

towards

using

computers

in

classroom

teaching (ATUCCT),
- Item number 35,

attitude

36,

37,

38 & 40,

which measured subjectsl

towards using computers in school

administration

(ATUCSA).

The following results were

was tested.

A two factors model

provided by the SPSS-X program:

i. Bartlett test o

spericity = 1412.7

P < .05

ii. KMO measure of sampling adequacy = .82165
.40537

iii. squared multiple correlation ranged form .13141 to

According

to the decision rules discussed in Chapter 3,

ii and iii suggested that this sample was an adequate sample

i,

for

applying the factor model.
Lisrel program on confirmatory factor analysis provided

the

following results iv. Chi-square test of 7\(liklihood criterion ratio) p < .05, suggested that the

'X43, N = 576) = 206.17,

model was not over-factorized.
V.

Goodness of fit index is .941; 17 (31%) of the residuals
>

.05

while

9 (16%) >

l

.

Five residuals >

.1

were

clustered along the row of item 36

The

results of Lisrel program suggested to set free item 36

and item 39. The contents of item 36 is,

"Computers can make it easier for me to prepare lessons and to set tests and examinationst'

This

item

could be interpreted either as attitude

computers

in

computers

classroom

to

prepare lessons.

towards

attitude

preparing

teaching

as

described

it

It also could be

using computers in school

lessons,

setting

tests

considered as administrative works.

and

towards

using

applying

interpreted

administration,

as as could be

examinations

Hence it was decided to set

free this item.

The content of item 39 is, n Using computers in my daily teaching will only waste my teaching time.'
It

was

description

would be

unlikely of that

this item could be

interpreted

school administrative work and hence

retained in the subscale of 'attitude

this

as

item

using

towards

computers in classroom teaching (ATUCCT)" only.
After set free item 36, the results of factor analysis were iv. Chi-square (42,

p < .05, suggested

N = 576) = 157.30

that the model was not over-factorized.
V,

of

fit

index is

residuals >

.05

while 6 (11%) > .1 and there

Goodness

.953;

clear cluster of residuals > .1.

12

of

(22%)

The results

are

the

no

suggested

that the two factors model was adeguate for this sample.

Table

4-3

correlations not displays

that

all

item-total

corrected

were greater than .25 and deletion of items

respective

increase the value of coefficient alpha of their

subscales

which suggested that all items were good

of the respective subscales and would be retained.

47

would

measurements

a

Table 4-3
Reliability Analysis of
Subscales of Attitudes towards using Computers in Schools

Subscale

Item

Corrected
Item-total
Correlation

Alpha if
Item
Deleted

.79098

30
31
32
33
34
36
37

.49645
.60976
.57423
.59283
.56188
.39646
.41125

.76916
.74598
.75335
74962
.75570
.78893
78336

.60630

35
36
37
38
40

.26506
.28378
.44227
.49952
.37196

.60380
.60106
.51853
.48858
.54593

Coefficient
Alpha

ATUCCT

ATUCSA

The

above analysis suggested that there are two factors

in

the attitude measurement, i, (ATLJCCT)

,

and 39, ii. teaching

Attitude towards using computers in classroom

Attitude

which includes items 30 , 31

,

32

33

34

36

and

towards

using

administration (ATUCSA) ,

37, 38 and 40.

computers

in

school

which includes items 35

36,

ornetrjc proe

4.3.3

se1f-rported

f

level

comtencencomputer1teracy

There were subjects' 24

items (item 41 to item

self-reported

contents

of

the

competence in

64)

computer

measuring

the

literacy.

The

items suggest that they were measures

of

the

following three characteristics
a. Knowledge

of

the

literacy (CPINF) of

informative

elements

item 41 to item 52,

low end jargons on the

of

computer

which are

configurations,

items

capabilities

and limitations of computers,

b. Knowledge
(cPsOc)

of
- item

the social elements of
53

to

item

57,

computer

which

are

literacy items on

application of computer in daily life and their impacts,

C. Knowledge

of

the

communicative

elements

of

computer

literacy (CPCOM) - item 58 to item 64, which are items on

communicating with

computers

(operating,

programming

etc).

When a three factors model was tested on these 24 items,

it

was found that items are highly correlated (14 items with squared

multiple

correlations > .7) which resulted zero

determinant

of

correlation matrix

By

investigating

the

contents of

the

items,

seemed

it

reasonable to assume that computer jargons and computer operation had to be learnt parallelly.

with

we can not found a person

comprehensive knowledge in computer jargons but with little

knowledge clear That is,

that

in interacting with computer,

there were redundancy of

or vice verse.

information

It

among

was these items.

However,

awareness

of social elements of computers

computerization were not so closely linked to CPINF the linkage between CPINF and CPCOM.

cpsoc

and

CPSOC

and CPCOM as

Hence CPINF together with

together with CPCOM should

redundency of information.

and

have no

To test the assumption,

serious

the 24 items

were divided into two groups:

Group i - item

41 to item 57 (17 items) which consists

of the subscales CPINF and CPSOC.

Group 2 - item

53 to item 64 (12 items) which

consists

of the subscales CPSOC and CPCOM.
A

two

factor model was tested on each group

respectively.

The

results were reported in Table 4-4.

There

are no clear cluster of residuals >.1 in the residual

matrix of both group 1 and group 2
According to the same rational of 4.2.1,

suggested

the above

that there were 2 factors in each group.

results

Accordingly,

there were 3 factors in the self-reported competence of

computer

literacy scale. The correlations of this 3 subscales are reported in Table 4-5.

The correlations suggested that CPINF and CPCOM

were highly

correlated while CPSOC was not so highly correlated with

and CPCOM which

confirmed

the

assumption.

The

CPINF

reliability

analyses of these 3 subscales are found and reported in Table 4-6.

50

Table 4-4
Results of The Two Factors Model of The Two Subgroups of

Self-reported Competence in Computer Literacy Scale

Group 1
(item 41 to item 75)

Bartlett test of spericity Group 2
(item 53 to item 64)

82479

5655.1

(p < .05)

(< .05)

KMO measure of sampling adequacy

.96360

.90984

Squared muftipie correlation

Max

.74124

.78873

Min

.42191

.41648

Chi-square test of
(liklihood ratio criterion) 758.80
(118, N=576)
(p < .05)

Goodness of fit index Number of residuals >.05

787.24
(53, N=576)
(p < .05)

.852

.812

30 (19.6%)

26(33.3%)

6 (3.9%)

5 (6.4%)

>.1

Table 4-5
Correlations of subscales of Computer Literacy

CpsoC

CPINF

CPINF

1.00000

CpS

.73267

1.00000

CPCOM

.82475

.59799

51

CPCOM

1.0000

Table 4-6

Reliability Analysis of Subscales of Computer Literaçy

Subscale

Coefficient
Alpha

CPINF

.85041

CPCOM

Alpha if
Item
Deleted

52

.82710
.80237
.75542
.81124
.83712
.83539
.73583
.79397
.83798
.82071
.81220
.80156

9572O
.95790
.95922
.95779
.95695
.95699
.95988
.95841
.95692
.95742
.95766
.95804

53
54
55
56
57

.63068
.59872
.73980
.66209
.68106

.82791
.83700
.79862
.82001
.81427

58
59
60

.78253
.85243
.82630
.81303
.84781
.82263
.83836

.94415
.93825
.94048
.94175
.93862
.94085
.93944

41
42
43
44
45
46
47
48
49
50
51

96i25

CPSOC

Corrected
Item-total
Correlation

Item

.94859

61
62
63
64

Table 4-6 reveals that all corrected item total correlations

were

greater

than

.598 and deletion of item in

would not

increase the coefficient alpha

subscales.

The

measures

results

suggested

that

all

subscales

of

their

respective

all

items

were

good

of their respective subscales and hence all items would

be retained.

52

The factors analyses in above

suggested

there

that

the self-reported competence

of

existed

three

literacy

computer

scale. They are
a. Knowledge

of

literacy

the

elements

item 41 to item 52,

-

(cPINF)

subjectst

informative

the

knowledge on computer jargons and capabilities

configurations,

computer

of

which

measure

describing

for

limitations

of

computers, of b. Knowledge
(CPSOC)

the social elements of
53 to item 57,

- item

literacy

computer

which measure

subjects'

knowledge on application of computerization in daily life and their impacts,

c. Knowledge literacy subjects '

of

the

(cPCOM)

communicative

elements

- item 58 to item

knowledge

on

which

communicating with

(operating, programming etc).

53

64,

of

computer

measure computers 43.4 Backgrounds

of subjects

training in computer

and

their

applications of computers in daily work

There

are some items in the questionnaire asking

background

information

the subjects

these items were combined,

If

nature.

of

which

different

are

common

the composite

in

variables

would be a better indicator of the common nature. Since all these items ask

items

in

factual information and there are only two to each composite variable,

the justification

three these of

composite variables were only based on the nature of the contents and supported by correlations.

The items in a composite variable

should be correlated to indicate that they were measures of common nature.

some

However, the correlations should not be too close

to unity to ensure that there were no redundency of information.

a.

Item

13 is on the number of in-service training courses

attended by

computer

of workshops or seminars on computers

number

attended these the subjects and item 14 is

in

the last 2 years.

to

measure the subjects'

these two items frequencies of

these

two

items

was

significant but was not close to unity. items was a better indicator of the

.64387

attend

were

and hence

their interest in attending computer training courses.

correlation

the

subjects

the

As teachers general

activities on voluntary basis,

combined

on

in

The

which was

Combining these two

subjects'

frequencies

and interest in attending computer training courses.
b.

Item

15 is on the number of computer books the subjects had

at home and item 16 is on the number of computer periodicals

54

the subjects had read regularly.

The computer books at home

might be owned by other family members.

However,

as chance

of contact was a very important factor to deveLop

interest,

with for computer the books at home would provide a better

subjects

to

contact

them.

Hence

item

chance was 15

considered as a measure of the subjects reading in computer.

Combines

item with

this

periodicals

the item

( a)

c.

,

the

number

of

read by the subjects was a better indicator

of

the subjects reading in computer.

two items was

about

.37301,

which,

The correlation of

these

according to the rational of

supports the formation of composite variable.

Item

18 is on whether the subjects has a computer at

item

19 asks whether the subjects can or can not access the

computers access in

other computer systems.

to

measure

their schools and item 20 whether
These three

the subjects accessibility

them was

combined

a better

they

have

items

all

to computers and

indicator

accessibility to computer systems.

homer

the

of

hence

subjects

The correlations between

items 18 and 19 was .08099; between 18 and 20 was .12081 and

between were and 20 was .28543.

19

relatively

computers

in

low which

The first two

might due

to

correlations

the

schools were restricted to the use

fact

that

staff

of

get

teaching computer studies and teachers were not easy to access now

to other computer system.

it is

relatively easy to have a computers at home as cost

computers, all On the other hand,

especially those fake computers,

teachers

can effort to have one

55

at

of

is so low that

home.

Since

the

contents

these

of

accessibility composite to

items

3

computer,

all

measure

the

subjects

they were combined to

variable represented the subjects

form

a

accessibility

to computers.
d.

Item not 21 to item 23 is on whether the subjects have or

used

computers

keeping student records, the teaching,

in,

preparing

respectively.

have

notes,

They all

and

measured

subjects' applications of computers in school and hence

combined

were

as a measure

between

correlations

.47620

which

composite

this

characteristic.

items 21 and 22 was

21 and 23 was .31192

items

of

;

.33295;

between items 22 and

The

between
23

was

supported combining items 21 to 23 to form

variable measures the subjects

applications

a

of

computers in school.

The

analyses

above

defined

the

following

composite

variables:

a.

Frequency

attended by

of in-service training courses

subject (CPINSC) - combining items 13 and 14,
b.

Subjectts

reading

interest

in

computer

(CPREAD)

-

combining items 15 and 16,

c.

Subject's

accessibility to computer systems (CPACCE) -

combining items 18, 19 and 20.
d.

Subjectts

applications of computers in

his/her daily

work (CPUSER) - combining items 21, 22 and 23,

56

4.4 Computer Literacy

4.4.1 Introduction

Three subscales,

in

Section

literacy.

4.3.3

Their

CPINF, CPSOC and CPCOM,

to measure subjects'

characteristics

were established

knowledge

and

relations

in

computer to other

independent variables were studied in this section.
Table 4-7 presents the coding of computer literacy scale. To facilitate the interpretation of mean score, competence have been divided into 3 levels,

subjects' levels of

that is, low, medium

and high, and Table 4-8 presents these definitions.

Table 4-7
Coding of Computer Literacy Scale
(Item 41 to Item 64)

Code

Description

o

Subject has no knowledge of the item

1

Subject has superficial knowledge of the item

2

Subject has some knowledge of the item

3

Subject has comprehensive knowledge of the item

57

Definitions of Competence Lecels in Computer Literacy

Range

Level

Description

Low

O - i

Subjects have limit knowledge about computers.
Practically,
they do not have the capability to use computers in their daily work and cannot understand technical terms as a computer user.

Medium

i - 2

some knowledge Subjects have of computer. Practically, with the help of others, they can use computers in certain areas of their daily work and can understand lower end technical terms for computer users.

High

Subjects have comprehensive knowledge as a computer user.
Practically, they can function effectively as a computer user in their daily work.

2 - 3

definitions

These

have taken into accounts that

items

on

computer literacy scale are at the lower end of the definition of computer literacy, to function

that is,

items are on subjectsT capabilities

effectively as an end user,

not as a

producer

of

computer software.

4.42 Characteristics of CPINF. CPSOC and CPCOI'4

Figure 4-1 displays the distribution of means of each and also

of each subscales.

The details of means and

items

standard

deviations of each items and subscales are given in Appendix A.

Figure 4-1

Cr Litera

Scale

Communicative elements (CC9M)

Social elements (CPSOC)

Informative elements (CPINF)

®

c

_L

I

é

s

?

.

'9

'B

t

11

it

:4

f'Ç

-r

p

k

1-3

fE

1'

In Table 4-9 is noted that the grand mean score of subjects'
,

literacy lower scale

was (x=1,25).

This grand mean score was

end oE medium score which implied that,

on

at

average,

the the subjects had superficial knowledge of computer. If they wanted to use computers in their daily works, they would required extensive helps from

Probably

people with comprehensive

knowledge

in

computer.

they only knew how to push the buttons of a system with

user-friendly software.

Table 4-9
Mean Scores of

Teachers

Self-reported Competence in Computer Literacy

--

- -

Level

N

.. .

Percentage

Mean

SD
,,

Informative elements
High
Medium
Low
Total

135
185
256
576

234

2.62
1.56

32.1
44.4
100.0

.32
.29
.31
.92

.46

1.32

Social elements
High
Medium
Low
Total

71

180
325
576

12,3
31.3
56.4
100.0

2.61
1.59

26.7
22.2
51.0
100.0

2.71
1.54

.31
.27
.36
.84

.45

1.07

Communicative elements
High
Medium
Low
Total

154
128
294
576

Grand total

576

Table cpSoc 4-9

also displays that all

and CPCOM,

.49
1.25

100.0
].±!![[ . .].[ ..[ ][ .

.29
.28
.35

.

1.05

1.25
[ .

three

.87
! . :

.

] . ,][

subscales,

had low mean scores (x=i,32,

1.07

CPINF,

and

1.25

respectively) and high standard deviations (sd= .92, .94 and 1.05 respectively) subjects

(44.4%,

respectively)

suggested

Further breakdown showed that around 50% of the

.

56.4%

and 51.0% for CPINF,

CPSOC

were at the low level of the scores.

and

The results

that subjects' knowledge in computer was not

There were a large portion of subjects at the lower end soectrum uniform,

of

and a small portion of the subjects at the higher

of the spectrum.

CPCOM

the

end

cs had the lowest mean score (x=1.07) and there were only
12.3% (N=71) of the subjects at the high level of the score which half only

were

the value of CPINF
These

N=154).

(26.7%,

(23.4%,

and cPc0M

n=135)

might indicate either that subjects were

not interest in the social elements of computer literacy,

subjects

had

insufficient knowledge in computer

or that

aware

to

the

social implication of computers and computerization.
In Table 4-10 it is noted that 42.5% (N=245) of the subjects

attended

have

education

one
7.5%

and

two computer

to

(N=43)

courses

of them have

in

their

attended

courses.

Taking

into account the low mean

computer

literacy,

the

courses taken by these 42% of

should be some basic courses on computers such as to Computers's or "Elementary Programmingu etc.

taken

3

computer
This

or more courses would have to knowledge the About

to

two

that is,

training

other

subjects

Only those

have

training

training

in

user.

courses

those claimed that they had

course

had only

superficial

in computers and could not work independently.

subjects

training in computers was described as

half

of the subject had elementary trainings in

which enabled them to have first contact with computer.

Hence,

follows computers However,

only a very small portion of them had comprehensive training enable them to function effectively as a computer user.

61

in

"Introduction

comprehensive

can be applied to the

attended by the subjects, one scores

make them function effectively as a computer

conclusion

attended

more

or

3

computer

formal

to

Table 4-10

Number of Computer Courses Attended by Subjects

Nature

Number of course attended
(0/
\ Ic'

0

1-2

3-4

5-6

7 or more

Formal education
Computer

Require the
App. of
Computers

288
(50.0)
350

245
(42.5)

(608)

(300)

173

21
(3.6)
38
(6.6)

15

7

(26)
10
(1.7)

(1.2)
4
(.9)

Informal education

Computer

399
(69.3)
414
(71.9)

Workshops or
Seminars
(in last 2 Yrs)

150
(26.0)
125
(21.7)

15

(26)
19
(3.3)

5

7

(.9)
7

(L2)

Table 4-11
Number of Subjects

with Knowledge in Different Programming Languages
Learned in
Formal Ed.

Language
BASIC
FORTRAN
COBOL
PASCAL
RPG

-

Informal Ed

169
166

154
17

38
28
1

19

9

0

(1.2)
11
(1.9)

BASIC

As

is

general the language learned

in

elementary

courses while other programming language will only be learned

advanced

more

programming

courses,

language

subjects'

in

Table

pattern

4-11

of

supported

in

knowledge the on

inferred

training pattern of the subjects.
In Figure 4-1,

the two items at the far lower end are

item

56, on Artificial Intelligence, and item 47, on ASCII code. These terms two

will

only be met in formai or extensive

The

computers.

four

items

staring a computer system,

41 on CPU

will

results

be

58

Ail these terms

met in the first contact

further

item

of

on

item 52 on programming language, item

and item 59 on running a program.

experiences

These

on the higher end are

studies

supported the

with

or

computers.

inferred backgrounds

of

training of the subjects.

4.4.3 Relations

of

computer

subjects

literacy

other

and

independent variables

4.4.3.1

Locating

independent

variables

correlated with

the

cornputerliteracysubscales.

In the literature review,

found

that

researchs in other countries have

subjects' computer literacy related to variables

on

their background, training and interest etc. , in computers . It is

also

interest of this study to

the

investigate whether

these

relations could be found in Hong Kong.

The

S

school variables

SCHTYP,

63

SCHSEX,

SCHAGE,

SCHLOC,

SCHCST, SCHCD, SCFICOC and SCHCOM teacher variables,
YRETEA,
as

PERADI'1,

AGE,

which

MARSTA,

SEX,

TEATRA,

HIGEDU, MAJSUB,

CCAPP, CCFOR, CPINSC, CPREAD, CPACCE and CPUSER

defined in Table 3-2,

INST,

as defined in Table 3-.1 and 14

together with one

measured whether

induced

the subject was

a

variables,

lecturer

in

colleges of education or was a secondary school teacher, were be used as independent variables in the analyses.
CPSOC and CPCOM with the above independent

ANOVAs of CPINF,

found to be significant in at least one

variables

were

dependent

variables

SCUTYP,

for the following independent

the

of

variables

SCHLJOC, SCE-ICAD, SCHCOM, SEX, INST, HIGED, MAJSUB, CCAPP,

CCFOR, CPINSC, CPRE2D, CPACCE and CPUSER.

CPSOC and CPCOM

As CPINF,

are correlated, (see Table 4-5),

MANOVA5 were used to investigate the dependence.
In

MANOVA,

we

have to make sure that the

of

assumptions

MANOVA were met before it can be used to test the hypotheses.

The assumptions of MANOVA are
a.

The

dependent

variables

have

a

normal

multivariate

distribution, which can be tested by stem and leaf normal probability

plot and detrended normal

plot,

plot

of

each dependent variable which test the normality of each dependent variable.
b.

The

dependent

varibales

are correlated, which

can be

tested by Bartletts test of sphericity which test hypothesis that the population correlation matrix is

the an identity matrix.
c.

The

variance-covariance matrices in each categories

of

the independent varibale are equal

which can be tested

by Box's M test. If this test is significant, Cochrans C

and

Bartlett-Box

the

variance matrices in each categories are

F tests will be used to test

whether

equal

in

order to justify the use of MANOVA.

As (a) and (b) are tests on the population of the

they were

variables,

only reported once in this

dependent

section.

The

slight difference computer results of different analyses was

due

to

difference

the

in

adjustment used by

algorithm for

the

calculation (regression solution in this case).
The normal plot, detrended normal plot and the stem and leaf

plot of CPINF, CPSOC and CPCOM were given in Appendix B.
The normal plots of CPINF, CPSOC and CPOM all show that the the plot were approximately straight lines.

middle parts of detrended excluding the two tails,

normal plots also show that,

points

all

around

were clustered nicely

The

These

zero.

results

suggested that there were clusters of extreme scores at both ends of distributions while the middle part were

the

normal the distributions.

By examinthg the steam and leaf plots and

score in these 3 subscales

subjectsT

approximately

discussed

in

4.4.2,

these clusters of extreme scores were confirmed. Since the middle parts of

all

distribution,

care

was

the

were

distributions

approximately

normal

MANOVA5 were still used to test the hypotheses but in interpreting

taken

the

results,

especially on

extreme scores.

The gave a

Bartlett result test of sphericity with 3 degrees of

of 1094 . 4

( p< . 05 )

,

which

population matrix was not an identity matrix.

suggested

freedom that the

Table 4-12

Boxes

M

Tests for Homogeneity of Dispersion Matrices

for CPINF, CPSOC and CPCOM with Different Independent Variables

Box's M

F tests of

Box's M

Indep Var

11.8
18.78
1.51
1,14
37.66
7.34
5*79
115.39
103.36
47.87
68.51
56.53
63.75
123.25

SCHTYP

scHL
SCHCAD
SCHCOM
SEX

INST
HIGED
MAJStJB

CCFOR
CCAPP
CCINSC
COMUSER

COMACCE
CPREAD

* The

hypothesis

different was categories

F

(12,475451)
(12,143355)
(6,1567361)
(6,1106386)
(6,2068593)
(6,237410)
(6,507636)
(42,164345)
(24.3089)
(24,1296)
(30,2849)
(18,35984)
(18,404522)
(36,8626)

.97

.47].

L55

.100
.959
.980
.000*
.297
.452
.000*
.000*
.014*
.001*
.008*
.000*
.000*

.25
.19

6.24
1.21
.96

2.68
3.93
1.74
2.06
1.97
3.50
3.25

the variance and covariance

matrix with

of the independent variables were

equal

rejected at .05 level.

For

Box's

that

DF

M

those independent variables which could not satisfy the tests, they

could

not satisfy

the

Cochrans

C

and

as MANOVA5 were not used

Bartlett-Box F tests neither.

However,

as conclusions of this study,

MANOVAs were still be used in that

group of independent variables to examine the approximate pattern of dependence.

computer

The final conclusions were based on the subjects'

literacy scores broken down by different categories

the independent variables.

of

Hotelling's

T2 tests were used to test the hypotheses

in different categories of the independent variables, no difference in the subjects scores in each of CPINF,

that

there was
CPSOC

d

2

CPSOC. The results of Notelling's T

tests were given in Table 4-13.

Table 4-13
2

i' s T Tests of Subjects' Computer Literacy with Different Independent Variables
F tests of Hotelling's T
2

Indep Var

Hotelling's T

SCHTYP
SCHLOC
SCHCAD
SCHCOM
SEX
INST
HIGED
MAJSUB
CCFOR
CCAPP
CCINSC
COMUSER
COMACCE
CPREAD

DF

.0462
.0219
.0223
.0202
.1478
.0196
.0158
.3611
.6624
.3549
.4354
.3966
.4250

1144)
(6, 1144)
(3, 572)
(3, 572)
(3, 572)
(3, 572)
(3, 572)
(21, 1688)
(12, 1703)
(12, 1703)
(21.1694)
(9, 1706)
(9, 1706)
(21, 1694)
(6,

1.2395

F
4.39
2.08
4.25
3.86
28.18
3.74
3.01
9.67
31.33
16.79
11.71
25.06
26.87
33.33

p
.000*
.053
.006*
.009*
.000*
.011*
.030*
.000*
.000*
.000*
.000*
.000*
.000*
.000*

* p<.05

Those

índependent

variables with significant F tests

of

2

Hotelling's T

in Table 4-13,

their univariate F tests for

each

of the dependent variables would be examined to locate the source of difference. The results were reported in Table 4-14.

67

thDifferentIndendentves
Indep Var
SCHTYP
SCHCAD
SCHCOM
SEX
INST
HIGED
NAJSUB
CCFOR
CCAPP
CCINSC
COMUSER
COMACCE
CPREAD

DF
(2,573)
(1,574)
(1,574)
(1,574)
(1,574)
(1,574)
(7,566)
(4,571)
(4,573_)

(7,568)
(3,572)
(3,572)
(7,568)

CPINF
8.78*
7,73*

754*
70.84*
3,89*

537*
23.74*
88.46*
46.43*
29.66*
48.65*

5313*
74.20*

CPSOC
10.74*
9.38*
10.37*
44.85*
8.78*
7.61*
12,78*
38.94*
24.66*
26.06*
32.93*
36.73*
35.63*

CPCOM
4.67*

1034*
773*
79.24*
.54

6.38*
22.51*
64.33*
41.21*
22.03*
70.57*
76.47*
86.71*

* p<.05

If univariate F-test was found significant in a cell, scores of the subscales were broken down by different categories of the

corresponding

independent

variables.

discussed in the following sections,

Their

relations

were

4.43.2 School Variables

Table 4-13 and 4-14 suggest that,

literacy

all subscales of computer

had significant difference for different categories

of

the school variables SCHTYP, SCHCAD and SCHCOM. Tables 4-15 to 4-

17 further display that in CPINF, CPSOC and CPCOM school a. Government

teachers had significant lower scores then their

counter

parts in aided schools and colleges of education, b. teachers of

schools

using

significant

computer

in

some

administrative works

had

higher scores then teachers in schools not using; c

teachers of schools which had computers other than those provided for computer studies had significant higher scores then teachers of schools which did not have.

Table 4-15

Mean Computer Literacy Scores of Subjects in Different School Types

Type

MEAN

N

SD

Informative elements (CPINF)

Government
Aided
C of E*

1.02
1.37
1.47

121
343
112

.91
.92
.84

Social elements (CPSOC)

Government
Aided
C of E*

.79

121
343
112

1.10
1.28

.80
.83
.82

Communicative elements (CPCOM)

Government
Aided
C of E*

121
343
112

* C of E : Colleges of Education

.99

1.32
1.31

1.05
1.05
1.04

Table 4-16

i_n Schools Have or Have-not Using Computers in Administration

N

Using

MEAN

SD

Informative elements (CPINF)

No
Yes

L19

227
349

1.40

.94
.89

Social elements (CPSOc)

No
Yes

227
349

.94

1.16

.84
.82

Communicative elements (CPCOM)

No
Yes

1.07
1.36

227
349

1.05
1.04

Table 4-17
Mean Computer Literacy Scores of Subjects in Schools Have or Not-have Self-procure Computers

Self-procure

MEAN

N

SD

Informative elements (CPINF)

No
Yes

1.18
1.39

201
375

.91
.91

Social elements (CPS)
No
Yes

.92

201
375

1.15

.81
.84

Communicative elements (CPCOM)

No
Yes

1.08
1.33

201
375

70

1.04
1.05

Table 4-18
Cross-tabs of Subjects in

Se 1ocureCoputers with
Schools Have or I-lave-flot using Computers in Administration

Have self-procure Computers

Using Computers in Administration

No

No

Yes

183

18

44

331

Yes

Cross-tabs of Subjects in Different School Types with Schools Have or Have-not Using Computers in Administration

Using Computers in Administration

Type

Yes

No

Government

121

Aided

62

28.1

112

College of Education

It is also noted in Tables 4-18 and 4-19 that schools having

self-procure computers were also schools using computers in of the

schools

sampling

school

the

have used computers in administrative works. is the assumption of this survey,

scores of CPINF,
3

administrative works and non of

the

some

government
As

random

difference

in

CPSOC and CPOM for different categories in the

school variables

could all be attributed to the difference in

7oa

Cross-tabs of Subjects in
Schools Have or Not-have Self-procure Computers with

Schools Have or Have-not us ng Computers in Adjnistrjon

Have self-procure Computers

Using Computers in Administration

No

No

Yes

183

18

44

331

Yes

Table 4-19
Cross-tabs of Subjects in Different School Types with Schools Have or Have-not Using Computers in Administration

Using Computers in Administration

Type

No
Government

121

Aided

62

Yes

281
112

College of Education

It is also noted in Tables 4-18 and 4-19 that schools having

self-procure computers were also schools using computers in of the

schools

sampling

school

administrative works and non

of

the

have used computers in administrative works. is the assumption of this survey,

scores of CPINF,

the

some

government
As

random

difference

in

CPSOC and CPCOM for different categories in the

71

u

variable,

the

use

of

computers

in

some

of

the

school

administrative work",
It is the present practice of most school that computers for

computer

studies

teaching

the subject.

of

some

are

opened to

However,

staff

other

such as records

keeping

data preparation in order to prepare data to be

interacting with

if not all, will have hand on computers. encourage

to use computers in administrative work, efficient of

expected

not just for

but

administration,

for

also

As staff are forced

some contacts with computer in this situation, that major

should be

Hence schools

increasing computer literacy of their staff.

have

and

captured by

These experience may be the

to their computer literacy.

the

in

experience in

attribute

increasing

those

all their staff have to know the basic concept

computers and some,

to

than

for schools using computers

the administrative work,

marks processing, of not

it will achieve better effect then

just

is

it

opening

the access of computers in schools to all teachers.

4.4.3,3 Sex

In Table lower scores

4-20, it is noted that female subjects in CPINF and CPCOM

cpSoc than male subjects female awareness

they have is interest

similar

but

the

constrained by the understanding of

explanation

is

in

score

This may be explained by the fact that in social

levels

of

have less interest in machine than male while

awareness,

This

and slightly lower

had much

supported by the fact that

72

the

there

machine. is no

significant difference in attitude scores of female and male (see
Section 4.5).

Table 4-20

Mean Computer Literacy Scores of Subjc't

Sex

N

MEAN

SD

Informative elements (CPINF)

Female
Male

254
322

.98

.75
.95

1.59

Social elements (CPSOC)

Female
Male

254
322

.82

.70
.88

1.27

Communicative elements (CPCOM)

Female
Male

254
322

.83

.81

1.57

1.11

4.4.3.4 Major Subjects Teach

In Table mathematics and

methodologies technical teachers

4-21, it

had

and of science

is noted that in all teachers and

lecturer

highest scores while teachers

commercial

subjects

had

medium

As

results

could be

74%

(N=425)

of the subjects

inferred by the

73

were

subjectst

teaching

in of economics,

and

scores

language and other social subjects had

scores.

subscales,

three

the

lowest

graduates,

training

in

the the Table 4-21

Mean Computer Literacy ScorefSi
Teachrng Dierent Subiects
Subject

N

MEAN

SD

Informative elements (CPINF)

Ch or Ch H

CorA
G or H
Eng
E or EPA
T or Corn

TM
M or S

70
49
63
93
38
37
36

.63
.89

.65
.73
.78
.80
.90
.81
.77
.88

1.15
1.01
1.25
1.34
1.72
1.83

188

Social elements (CPSOC)

Ch or Ch H

CorA
GorH
Eng
E or EPA
T or Corn

TM
M or S

70
49
63
93
38
37
36

.57
.65
.72
.68
.74
.88
.79
.93

.62
.61
.91
.95

1.11
1.01
1.54
1.39

188

Communicative elements (CPCOM)

Ch or Ch H

CorA
G or
Eng
E or
T or
TM
M or

H
EPA
Com
S

70
49
63
93
38
37
36

.55
.82

.66
.86

1.16

1.00

.64

.79
.96
.91

1.05
1.19
1,78
1.73

188

1.00
1.07

Note : Ch or Ch H - Chinese or Chinese History
C or A - Cultural or Art Subjects
G or H - Geography or History
English - Wnglish
E or EPA - Economics or EPA
T or Corn - Technical or Commercial Subjects
TM - Teaching Methodologies
M or S - Mathematics or Science Subjects

74

universiteS. In the universities, mathematics and science students

use

to

have

of economics,

students

computers

use other in

course works

their

technical and commercial subjects

in some of their course works while

and

will

students

of

subjects general will not be requested to apply computers

their

learning implys computers in completing

studies. is that

In

colleges of

education,

in the curriculum of teaching lecturers in this subject

knowledge in computers.

75

computer

aided

methodologies which

must

have

appropriate

443.5 E-Jighest Education

Table 4-22 displays that graduate subjects had higher scores than due

non-graduate subjects in all 3 subscales to majority

the

fact that non-graduate teachers in

trained

universities

This result may

.

in

Hong Kong

locally and computers have been
60s

or

even earlier

while

are

introduced

they

to

have been

introduced to the colleges of education in Hong Kong only in the
80s. Besides, universities have a large varieties of computers and students have better access to computer facilities while colleges of education

in Hong Kong have only

some

micro-computers

students can only access the computers as time-tabled.

Table 4-22
Mean Computer Literacy Scores of Subjects with Different Highest Education

Education

N

MEAN

SD

Informative elements (CPINF)

Non- Graduate
Graduate

152
424

1.17
1.37

.85
.93

Social elements (CPSOC)

Non- Graduate
Graduate

152
424

.91

1.13

.79
.85

Communicative elements (CPCOM)

Non- Graduate
Graduate

152
424

1,06
1.31

.95

1.08

and

4.4.3.6 Teachers from Different Institutions

had

Tables

4--23 displays that lectuers in colleges of education

higher

scores

in

difference

significant

CPINF and in CPSOC

while

there was

scores of CPCOM than

their

no

counter

parts in secondary schools. According to Table 4-19, all colleges

education

of

only

while

had used computers in

some

51% (N-237) of the subjects were from schools

computers in some administrative works.
4.4.3.2

using

The inference in Section

thus can be applied here. However, as in each college of

education

in

Hong Kong,

only a team of

responsible for actual processing of data, not administrative works

several

members

was

other lecturers would

have better chance in accessing computers than their counter

parts in secondary schools which may explained the

insignificant

difference in CPCOM.

Table 4-23
Mean Computer Literacy Scores of Subjects
Teach in Different Institutions

Institution

MEAN

N

SD

Informative elements (CPINF)

Sec Sch

464

1.28

.93

C of E

112

1.47

.84

Social elements (CPSOC)

Sec Sch

464

1.02

.83

C of E

112

L28

.82

hA

4.43.7 Training in Computer

Tables 4-24 to 4-26 display that in all the 3 subscales,

there were large gaps between the scores of subjects who had not attended any courses in computers and subjects who had

one to two courses. in computer

Without

attended

This results suggests that initial

was very important to subjects

such 'starting courses",

their self-learning in Computers.

'starting course,

subjects

training

computer

literacy.

subjects had no ways to
However,

start

after attending such

computer literacy was significantly

improved.

From subscales, the

same

there

tables,

were

it

also noted

that

in

large difference between the

the

all

scores

of

subjects attending one to two course and subjects attending three to four courses. for subjects

attending

more

attending

one

computer while

However, the difference was attending courses.

three

to

four

This results may

with

and

suggest

those attending three to four courses

questionnaire were on the lower end of

subjects

course

subjects

that

those of to two courses had only superficial knowledge

comprehensive knowledge as a computer user. this not so significant

had

more

However, as items in computer literacy,

more advanced studies in computers could not

reflected by their computer literacy scores.

be

Table 4-24
Mean Computer Literacy Scores of Subjects
Attending Different No. of Computer Courses in Formal Education

No of Courses

N

MEAN

SD

Informative elements (CPINF) o 1 - 2

3*4
5-6
7 or more

288
245
21
15
7

.81

1.68
2.61
2.72
2.71

.74
.74
.46
.29
.69

Social elements (CPSOC) o 1 - 2

3-4
5-6
7 or more

288
245
21
15
7

.76

1.26
1.95
2.13
2.60

.71
.76
.88
.92
.66

Communicative elements (CPCOM) o 1 - 2

3-4
5-6
7 or more

288
245
21
15
7

.73

1.58
2.65
2.82
2.78

.87
.95
.57
.17
.44

Table 4-25

Attending Different No. of Courses with Computer Applications

No of Courses

N

MEAN

SD

Informative elements (CPINF)

i - 2

350
173

3-4
5-6

38
10

o

7 or more

5

.98

1.71
2.29
2.38
2.13

.80
.78
.84
.67
.92

Social elements (CPS)
O

1 - 2

3-4
5 - 6
7 or more

350
173
38
10
5

.83

1.35
1.72
2.02
1.52

.71
.83
.96

1.06
1.09

Communicative elements (CPCOM)

1 - 2

350
173

3-4
5-6

38
10

o

7 or more

5

.88

1,65
2.31
2.63
2.20

.93
.94
.91
.48

1.26

Table 4--26

LA
.

No of Courses

OfIn-service Courses i.nComptmuter

MEAN

i'j

sr

Informative elements (CPINF)
353
184

o
]_ - 2

3-4
5-6

1.00
1.65
2.54
2.44
2.96

24
9
6

7 or more

.83
.73
.48
.70
.10

Social elements (CPSOC)
353
184
24

o

1 - 2

3-4
5-6

9

7 or more

6

.81

1,33
2.09
2.13
2.8

.71
.78
.73
.82
.49

Communicative elements (CPCOM)
353
184

o

i - 2

3-4
5-6

24
9
6

7 or more

.94

1.00

1.53
2.59
2.55
3,00

.89
.56
.47
.00

4.4.3.8 Computer Accessibility

In Table 4-27, subjects with

there were huge gaps between the scores

and without access to computer facilities in

of all the three subscales. This result suggested that accessibility was an important factor in the subjects

computer

literacy.

There

were also large gaps between the scores of subjects with one, two

and

three

types of access (at home,

in school and

others)

to

computer facilities. In computer industry, explosure to different

types

of

participants'

suggest order that

computer

is

professional

an

very

important

knowledge.

This

factor

of

result

seems

to

facilities

in

given access to different computer

to exposure the subjects to different computer system was

also an important factor of the subjects' computer literacy.

Table 4-27
Computer LiteracScoresofSujj with Different Computer Accessihilities

Types

MEAN

N

SD

Informative elements (CPINF)

2

137
191
176

3

72

o
1

7l

1.25
1.54
2.11

.69
.81
.89
.84

Social elements (CPSOC) o i
2
3

137
191
176
72

.57
1.04
1.26
1.65

.60
.77
.84
.86

Communicative elements (CPCOM) o 1
2
3

it's

137
191
176
72

.50

1.10
1.54
2.34

.71
.92

1,03
.77

4.43.9 Computer User

Table

In

4-28, computer users

and

non-users

had

difference in the scores of CPfl'F and CPCOM while the

in cs was smaller. were more computers scores

difference

The results suggest that CPINF and

important

factors

in making

the

subjects

in their daily works while CPSOC was a less
It

factor.

in

large

CPCOM to use

important

could either be interpreted as subjects with the subscales would tend to apply computers

higher in more

areas of their daily work, or subjects with the tendency to apply

computers

in

their

daily work would learn more and

hence

higher scores in computer literacy subscales.

Table 4-28
Mean Computer Literacy Scores of Subjects

! th

Differ entTypesof ComputerApplications in Daily Work

No of Type

MEAN

N

SD

Informative elements (CPINF) o i
2
3

405
95
51
25

1.07
1.62
2.23
1.32

.80
.93
.70
.92

Social elements (CPSOC) o i
2
3

405

.88

95
51
25

1.36
1.67
1.92

.73
.99
.83
.70

Communicative elements (CPCOM) o 1
2
3

405
95
51
25

.91

176
2.36
2.49

.91
.99
.73
.75

had

44.3,1O Reading in Computer

Table 4-29,

In in it is noted that there was large difference

the scores of subjects with and without readings in

computer

and

there was a monolithic increasing of the subjects scores

all

three subscales against the number of books

read.

As

the

interest

in

computer

was

literacy.

number computers, an

of reading could

or

reflect

it suggests that subjects

important factor of

the

in

periodicals

the

subjects'

interest

subjects '

on

computer

Mean Computer Literacy Scores of Sublects with Different No. of Computer Books or Periodicals Read

No of Reading

N

MEAN

SD

Informative elements (CPINF) o 1 - 2

3-4
5-6
7-8
- 10
11 - 12
13 or more
9

261
121
49
34
76

25
8
2

.72

1.38
1.58
2.05
2.18
2.57
2.64
2.83

.61
.68
.82
.78
.66
.66
.74
.24

Social elements (CPSOC) o 1 - 2

3-4
5-6
7-8
9 - 10

il - 12
13 or more

261
121
49
34
76
25
8
2

.66

1.08
1.18
1,60
1.63
2.13
2.20
3.00

.62
.72
.82
.78
.80
.74
.88
.88

Communicative elements (cPCOM) o i - 2

3-4
5-6
7-8
9

- 10

lì - 12
13 or more

261
121
49
34
76
25
8
2

.54

1.26
1,64
2.17
2.31
2.72
2.68
2.86

.65
.74
.93
.82
.87
.62
.85
.20

4. 4. 3. 11

Section 4.4.3,

In

subjects

computer literacy was found to

depend on the following variables : SCHTYP, SCHCAD, scHcoM, INST,
HIGEDU,

SEX,

MAJSUB,

Also,

CPUSER,

variables :

it

CCAPP,

was

found

CCFOR, CPINSC, CPREAD, CPACCE and not to depend

on

the

following

SCHSEX, SCHAGE, SCHLOC, SCHCST, SCHCOC, AGE, MARSTA,

YRETEA and PERAD.

was

It

computer
SCHCOM,

the difference

subjects

in

literacy due to the difference in the variables SCHTYP,

SCHCAD and INST could be attributed to the deference

while

SCHCAD

could

also discussed that,

the difference due to SCHCAD,

HIGEDU

ín

and MAJSUE

be attributed to whether there was a computerized working

environment. subjects' computer

Also

CPUSER and CPACCE

could be attributed to the

chance to contact computers and to be exposed to system. computerized

This

working

factor

together with the

environment

more

factor

of

could be grouped under

heading 'Interaction with computers".

On the other hand,

a

the

CCAPP,

CCFOR and CPINSC could generate an important factor, the "Initial

training

in

computer'

,

which would determine

the

subjects'

computer literacy.

These

two factors,

training in computer, in machine,

interaction with computers and

together with an inborn factor,

represent by the sex difference,

factors to a teachers' competence in computers. presented graphically in Figure 4-2.

initial

interests

were the important
The relation was

4.5 Attitude towards using Computers In school

4.5.1 Tntroduction

Two

subscales,

ATUCCT

and

ATUCSA,

were

4.32 to measure the subjectst attitudes

Section

established towards in

using

computers in school.
Items in the attitude measures were scaled by Likert scales.

five options of the Likert scales,

The

neutral,
2,

1

the

disagree and strongly disagree,

strongly

agree,

agree,

were coded by 5, 4,

3,

respectively and the scores of each subscale were found as

scores

of all items in each

subscale.

Subjects'

attitude

towards using computers in school have been divided into 3 level,

that is highly positive,

positive and negative. Table 4-30 gives

the definitions.

Table 4-30
Definitions of Levels in Attitudes towards
Using Computers in Schools

Description

Level

Range

Highly
Positive

4-5

Subjects have an average of agree to strongly agree to all items in the scales. They are probably the initiater for using computers in schools Positive

2.5-4

Subjects have an average of slightly disagree to agree to all items in the scales. They probably will not take the initiation to use computers in schools but certainly will not object such applications. Sometimes, they themselves will become the users if there are initiaters. Negative

l-2.5

attitude have a clear negative
Subject
They will towards using computers in school. in computers of the applications object school activities.

4.5.2

Characteristics of the subscales of attitude towards using computers in school.

Table 4-31

Mean scores of subjects attitude scales

N

Level

Percentage

Mean

SD

ATUCCT
Figh1y
Positìve
Positive
Negative
Total

44

8

4.31

.23

470
62
576

81
II
100

3.33
2.10
3.28

.39
.33
.61

159

28

4.43

.24

411
6

71
1

576

100

3.56
1.97
3.79

.35
.53
.54

lOO

3.49

.49

ATtJCSA

Highly
Positive
Positive
Negative
Total

Grand total

The reported 576

mean

scores

each subscales were calculated

of

in Table 4-32.

In order of facilitate

between subscales and levels,

the

and

comparison

all mean scores were averaged over

the number of items in that category.
In

ATUCcT

Table

ATUCSA

and

respectively)

4-32,

,

of

it is noted that the mean scores

were

greater

which suggested that,

than

3

(3.28

on average,

and

both
3.79

subjects were

not against using computers in both classroom teaching and school administration. (x=3.79)

It

is also noted that the mean score of

was much higher than the mean score of ATUCCT

ATUCSA
(x=3.28)

which

suggested that subjects were general favourite the use

computers

The

in school administration than in

fact that,

classroom

in the 'highly nositivet level,

of

teaching.

there were

44

subjects in ATUCCT while there were 159 subjects in ATUCSA,

and

-in the "negative

and

level,

there were 62 subjects in ATUCCT,

only 6 subjects in ATUCSA, result also supported the conclusion.

may due to the fact that some schools have used computers

in some of their administrative work and hence teachers in school This

these

could had practical experience on what computers could do

in school administration and for teachers in school not yet using

computers

in

application had used.

administration,

they

could aware

this

area

through their peer group or by visiting school

On the other hand,

there were practically no

of

that

schools

using computers in classroom teaching, and teachers had no way to

experience
The

how computers could be applied in classroom teaching.

results

computers

of

Table 4-32 where more

could be

used

in

school

subjects

believed

administration

classroom teaching further supported this inference.

than

that in Table 4-32

Number

of

Subjects

be

_u ters could be

jsciools

Area

%*

N

Classroom teaching
Enrichment of lessons
Drill and practice
Simulation of experiments
Remedial lesson for less able students

344
335
216
144

60

58
38
25

School Administration
Keeping student records
Processing student reports
Producing statistical information of students
Processing test and examination papers

538
500

93
87

489
400

85
69

Note :* Percentage of the total returns (N=576)

4,5.3

Relations of the attitude subscales and other

independent

variables

4.5.3.1

Locating

independent

variables

correlated with

the

attitude subs cales.

ANOVA using ATUCCT

and ATUCSA

as dependent variables

with

the same set of independent variables as in Section 4.4.3.1. were

significant

either

in

ATUCCT or in ATUCSA

following independent variables :

or

both,

for

the

SCHTYP, SCUCAD, SCHCOM, INST,

MAJSUB, YREEXP, CCFOR, CCAPP, COMACC, COMUSER, READ, CPINF, CPS and CPCOM.

As ATUCCT and ATUCSA were correlated (r=. 56) to used

MANOVAs were

,

test whether there was significant differences

scores of ATUCCP and AT[JCSA

in

the

between different categories in each

of the independent variables.

According

to

the discussion in Section 4.4.3.1 the

detrended

plots,

normal

plots and the stem and leaf

ATIJCCT and ATTUCSA were given in Appendix C.

and ATTUCSA, and all

plots

of

For both the ATUCCT

the normal plots were approximately a straight line

points

around

nicely

normal

in the detrended normal zero. These

results

plots were

suggested

clustered

that

the

two

distributions of scores were approximately normal distributions.

The gave Bartlett result a

test of sphericity with i degree
129.11

of

(p<.05),

which

of

suggested

freedom that the

population matrix was not an identity matrix.
Table 4-33 displays that the all the Boxrs M tests were

significant there (p>.O5)

which

suggested that the

was no significant difference in the

matrices

of

different categories in each

hypotheses

variance

not that covariance

independent

variable

significant

for

were not rejected.
2

Hotellings T

tests were found not

independent variables INST,

YREEXP,

the other independent variables,

the

and READ in Table 4-34. For

univariate F tests were used to

locate the sources of difference and were reported in Table 4-35.

91

Table 4-33

Box's M tests for Homogeneity of Dispersion Matrices for the Dependent Variables ATUCCT and ATUCSA

F-tests of Box'M

Indep Var

Box's M

SCHTYP
SCHCAD
SCHCOM
INST
YREEXP
MAJSUB
CCFOR
CCAPP
COMUSER

9.30
5.09
3.21

COMACC

READ
CPINF
cpsoc
CPCOM

.56

3,11
30.49
8.80
9,61
9.57
7.53
16,05
3,37
4.76
2,46

DF
(6,1095126)
(3,11590354)
(3,4730068)
(3,565375)
(3,74044556)
(21.275882)
(12,4538)
(12,1863)
(9,57469)
(9,767837)
(18,12015)
(6,2767527)
(6,365158)
(6,1967573)

F

p

1.54
1.69
1,07

.160
.167
.363
.906
.377
.092
.761
.714
.401
.587
.626
.763
.579
.874

.19

1.03
1.43
.69
.74

1.04
.83
.86
.56
.79
.41

Table 4-34
2

Hotelling's T

tests of ATUCCT and ATUCSA

with different independent variables

tests for Fiotelling's T2
-

2

Indep Var

Hotelling's T

SCHTYP
SCHCAD

.0448
.0135
.0131
.007
.1198
0064
.0396
.0375
.0282
.0365
.040
.051
.018
.031

SCHCOM

INST
MAJSUB
YREEXP
CCFOR
CCAPP
COMtJSER

COMACC
READ
CPINF cpsoc CPCOM

* p<.05

DF
(4,1142)
(2,573)
(2,573)
(2,573)
(14,1128)
(8,1138)
(8,1138)
(8,1138)
(6,1140)
(6,1140)
(14,1132)
(4,1142)
(4,1142)
(4,1142)

F

P

6,39
3.86
3.75
2.06
4.83
1.84
2.82
2.66
2.68
3.47
1.60
7.34
2.55
4.36

.000*
.022*
.024*
.129
.000*
.160
.004*
.007*
.014*
.002*
.072
.000*
.038*
.002*

Table 4-35

Dependent Variables

DF

Iridep Var

SCHTYP
SCHCAD

(2,573)

SCHCOM

(1,574)
(7,566)
(4,571)
(4,571)
(3,572)
(3,572)
(2,573)
(2,573)
(2,573)

(1574)

MAJSUB
CCFOR
CCAPP

COMUSER
COMACC
CPINF cpsoc CPCOM

1.71
.18

10.17*
7.02*

.70

734*
341*

8.02*
4,77*

1.66
2.51*

433*

373*
43j*

3.60*
4.24*
11.57*

8.32*

505*
545*

.94

6.69*

* p<.05

If

attitude

univarjate F-test was scores categories

of

found significant

in

o-E the subscales were broken down by

the

corresponding

independent

a

cell,

different

variables.

Their

relations were discussed in the following sections.

4.5.3.2 School variables
2

In

Table 4-34,

tests were
SCHTYP,

it is noted that in MONAVA,

significant

for

the

three

Hotellings T

independent

variables

SCHCAD and SCHCOM while in Table 4-35, it is noted that

all three sets of univariate F-tests were only significant for the

subscale ATUCSA
In

schools

and were all insignificant for ATEJCCT.

Table 4-36,it is found that,

had

lowest

scores;

(b)

(a) teachers of government teachers in

schools

using

computers in administrative work had higher scores when compared

93

teachers

with work; (c)

in schools not using computers in

athinistrative

teachers in school which had self-procured

computers

other than those provided for computer studies had higher

scores

when compared with teachers in school which did not have.

As the

pattern of scores were similar to the scores of CPINF, for the same set of independent variables

CPCOM of 4.43,2 could be

Section

difference

of

all be attributed to the

the inference that here,

scores due to difference in

could

SCHCOM

applied

cpsoc and

SCHTYP,

variable

was,

the

SCHCAD

and

using

SCHCAD,

computers in some of the school administrative work.

The results

suggest that school using computers in some of the administrative

using on attitude

could significantly improve the subjects

work

the

which

computers in school administrative work but had no

effect

classroom

teaching

supported the inference that setting examples of

computer

attitude towards using computers in

applications

suggests

also

literacy

and

attitude towards that area.

The

an important factor to computer

was

also could improve the subjects result towards

schools

that

had

their

improved

administration by using computers in some of their administrative

works

as

their

computerisation

members

had

awared

the

advantage

and hence showed more positive attitude

using computers in school administrative work.

YJ

of

towards

Table 4-36

MeanScores

in

chop

Sch aol Variables

Category

MEAN

Type of school
Government
Aided
C of E'

121
343
112

3.60
3.86
3,77

.60
.50
.55

Using computers in school administration
No
Yes

227
349

3.71
3.83

.57
.51

3.70
3.83

.57
.52

Self-procured computers

No

201
375

Yes

*c of E - Colleges of Education

4.4.3.3jjpr Sublects teach in schools

Table had 4-37

highest

display that teachers of English and

scores

in ATUCCT

while

teachers

of

Economics
Geography,

These

English

and

results

may due to the fact that among all the subjects in

Hong

English is the only subject that

some

Kong

secondary

meaningful

had highest

Economics

schools,

scores

in

Computer Aided Learning packages are

Economics

is

the

that

subject

ATUCSA.

available

and

information

commercial

such as Viewdata etc. can be directly apply to the

technologies, subject. These

subjects

to

reasons

caused

might

teachers

agree the statements that using

95

of

these

two

in

the

computers

teaching

of

their

own subject could improve the

their

teaching.

could

not infer any cause why teachers of these

For the the results of ATUCSA,

qualities

the

researcher

three

subjects

had higher scores.

Table 4-37

Mean Attitude Scores of Subjects with Different Major Subjects Teach

Subject

N

MEAN

SD

Classroom teaching (AT[JCCT)

Ch or Ch H
C or A
G or F-J

Eng
E or EPA
T or Corn

TM
M or S

70
49
63
93
38
37
36
188

2,88
3.08
3.20
3.45
3.46
3.24
3.37
3,37

.65
.60
.61
.60
.42
.57
.60
.58

School Administration (ATtJCSA)

Ch or Ch H
C or A
G or H
Eng
E or EPA
T or Corn

TM
M or S

70
49
63
93
38
37
36

188

3.56
3.75
3.88
3.87
3.95
3.69
3.69
3,81

Note : Ch or Ch H - Chìnese or Chinese History
C or A - Cultural or Art Subjects
G or H - Geography or History
English - Wriglish
E or EPA - Econornics or EPA
T or Corn - Technical or Commercial Subjects
TM - Teaching MethodolOgïeS
M or S - Mathematics or Science Subjects

.57
.47
.56
.53
.41
*47
.65
.53

of

4.53.4 Training in computer
2

Table

4-34

indicates that ìn MONIVA,

significant

were

Table

In

CCAPP,

for the two independent

significant

4-35,

for

CCAPP,

Hotellings T variables univariate

tests

CCFO

and

F-tests

were

for both the subscales ATUCCT and ATUCSA

while

for

CCFOR, univariate F-test was only significant for ATUCCT.

Tables

4-38

had

first

three

were

for and of

the

fifth

The results were also displayed in Figure 4-2. These

may

suggested that subjects'

in

classroom

increased

computers,

attitudes

teaching and in

school

towards

using

administration

as their knowledge in computers was

increased.

knowledge

of

they began to aware the difficulties in building

an

when

However,

subjects' scores increased

categories and decreased for the fourth

categories.

computers

display that all the three sets

same patterns:

scores

results

and 4-39,

they

have

a

more

comprehensive

error free and effective computer system and also the risks to be in using a non-professional system,

taken some which made them have

reservation to agree the attitude statements.

account

Taking

the small nuthber in the number of subjects in these

categories and that items in CPINF,

into two CPSOC and CPCOM were at the

lower end of computer literacy, the knowledge of subjects in this two categories probably could not be reflecled in their scores in

CPINF, CPSOC

and CPCOM.

Table 4-38

Mean Attitude Scores
Attending Different No. of Computer Courses in Formal Education

No. of course

N

MEAN

SD

Classroom teaching (ATUCCT)
0

1 - 2

3-4
5-6

288
245
21
15

7 or more

7

3.18
3.37
3.58
3.22
3.10

.62
.58
.64
.75
.62

Table 4-39
Mean Attitude Scores of Subiects

Attending Different No. of Courses with Computer Applications

No, of course

MEAN

N

SD

Classroom teaching (ATUCCT)

o

1 - 2

3-4
5-6
7 or more

350
173
38
10
5

3.22
3.33
3.57
3.46
2.83

.63
.58
.52
.61
.64

School Administration (ATUCSA)

1 - 2

350
173

3-4
5-6

Jo

o

7 or more

38
5

3.74
3.84
3.99
3.84
3,84

.54
.54
.53
.49
.26

4_5.3.5 Interaction with computers
2

In Tables 4-34 and 4-35,

COMUSER,

both

for

significant

independent

tests of MANOVA were

variables

COMACC

and

and univariate F-tests of them were significant for both

the subscales ATUCSA
In

the

Hotellings T

Table

and ATUCcT.

4-40,

it is noted that all the mean scores

were

greater than 3, the neutral value, and there was great difference

between

the

scores

of

subjects with

and without

access

to

computers. However the difference in scores between subjects with one type and with more than one type of access to computers

These

small.

results

access to computers,

suggest that no matter with

was

or without

no subjects were against using computers in

schools. For those with access to computers, they could aware the

capabilities

and

advantage

of

computers and hence

had more

positive attitudes towards using computers in schools.
In Table 4-41 it is also noted that all the mean scores were

greater both than 3 and there was monolithic increasing in scores

ATUCCT

and ATUCSA when the types of

were increased.

computer

of applications,

advantages

application

The results suggest that both computer users and

non-users were not against using computers in schools. types in

they could aware more

With more

capabilities

and

of computers and hence had more positive attitudes in

both ATUCCT and ATUCSA.

Table 4-40
Subiçj:

with Different Computer Accessibilities

No of Types

N

MEAN

SD

Classroom teaching (ATUCcT)

312

137
191
176

o i 2
3

3.30
3.33
3.40

72

.63
.55
.66
.57

School Administration (ATUCSA)

137
191
176

o i 2
3

3.65
3.83
3.85
3.76

72

.55
.52
.53
.55

Table 4-41

Mean Attitude Scores of Subiect

withDifferent Type sof Co mputerApplications in Daily Work

No of Types

MEAN

N

SD

Classroom teaching (ATUCCr) o i
2
3

3.25
3.25
3.37
3.63

405
95
51
25

.62
.64
.51
.55

School Administration (ATUCSA) o i
2
3

3.75
3.85
3.85
4.10

405
95
51
25

100

.52
.58
.51
.59

4.5.3.6 Computer Literacy
2

In Table 4-34, Hotellings T

tests of MANOVA were significant

for the independent variables CPINF, CPSOC and CPCOM.
35,

In Table 4-

the univariate F-tests of the independent variables CPINF and

CPCOM were significant for both the subscales ATUCSA

while for the independent variable CPSOC,

and ATUT

univariate F-test was

only significant for the subscale ATUCCT.

Table the 4-42 displays that there was monolithic increasing of

subjects

attitudes

computer literacy. computer for

increasing

levels

of

subjects

The results suggest that increasing subjects'

knowledge would lead them to higher level of

consensus

to the statements that there were advantages in using computers in schools. By

considering the high mean scores of ATUCSA for

independent test CPSOC

may had variables CPSOC,

the insignificant of univariate F-

due to the fact that subjects of different a general consensus about

computer in school administrative work,

attitudes

due

processing

system

to

the as the

the

advantage

in

section

4.4.3.7

reflected here. The reason was discussed in Chapter V.

101

of

in

using

However, the drawback of

comprehensive understanding

discussed

levels

of

was

data not Table 4-42
Mean Attitude Scores of Subjects

with Different Levels of Computer Literacy

Level

N

MEAN

SD

Informative elements (CPINF)
Classroom teaching (ATUCCT)

Low
Medium
High

256
185
135

3.15
3.32
3.45

63
.59
.57

School Administration (ATUCSA)

Low
Medium
High

256
185
135

3.69
3.86
3.87

.55
.51
.52

Social elements (CPS)
Classroom teaching (ATUCCT)

Low
Medium
High

3,22
3,30
3.47

325
180
71

.63
,57
.60

School Administration (ATUCSA)

Low
Medium
High

3.20
3.31
3.40

294
128
154

.63
.59
.58

Communicative elements (CPCOM)
Classroom teaching (AT[JCCT)

Low
Medium
High

3,20
3.31
3.40

294
128
154

.63
.59
.58

School Administration (ATUCSA)

Low
Medium
High

3.71
3.66
3.88

256
185
135

102

.52
.53
.55

4.5.3.7 Summary
Inì

MAJSUB,

this section,
CCFOR,

CCAPP,

ATUCCT was found to

subjectst

CPUSER,

CPACCE,

depend

on

CPINF, CPSOC and CPCOM

while their ATUCSA was found to depend on SCHTYP, SCHCAD, SCHCOM,
ÜB,

CCAPP ,

ATUCSA were

scHc,

CPUSER

independent

CPACCE CP1NF and CPCOM . Both NI'UCCT and of SCHSEX,

SCHAGE,

SCFiLOC,

SCHCST,

AGE, MARSTA, HIGEDU, YRETEA, PERADM, CPINSC and

SCHCOM,

CPREAD.
It

was

also

towards

using

SCHTYP

SCHCAD

,

examples

of

discussed

computers
,

SCI-ICOM

that the

appropriate

in

and MAJSUB could all be

attributed

to

The

softwares

CCAPP, CPUSER, CPACCE, CPINF,

could be grouped under the heading of competence
It

could be concluded that good examples

and

factors

to

competence were

influence Hong Kong teachers schools. attitude

difference

computer applications set up by quality

cpSoc and CPCOM computers. in

the

in schools due to

while the difference due to CCFOR,

in

difference

the

two

important

attitude towards using computers in

relations of dependence was showed graphically

Figure 4-2.

103

in

Positive Attitude
Towards using computers in schools

Computer literacy

Quality
Softwares

H
Q
Interaction wi th

Initial training computers

Computerized
Working Environment

SCHAD
I

sc:ÑAD

I

SCE-ITYP

HII3ED

I-'

SCEICOM

Access to computer MÏJSUB

CPUtER

CCARCISC

CPAEJSE

I

INST

Figure 4-2
A Hierachical Relations of Attitude towards Using Computers in School
Computer Literacy and Teachers' Backgrounds

4_ 6

Interests
......

.

..._

--

in
...

attending
.

..

. ......._

.

.

computor

courses

.
.

_._._

.

.._.

..

.

and

- .

.

.

the

most

.

_._._..

.

.

.

favourable courses of Hong Kong Teachers.

4 . 6 . i Interestsin attending computer course

Out of the 576 returns, that they were

435 (76%) of the subjects indicated

interested in attending

computer

courses

for

teachers

which suggested that irrespective of their low computer

literacy

scores,

literacy

in

subjects awared of the importance of

their

computer

teaching career and were willing

have

to

trainings to upgrade their computer literacy.

Table subjects 4-43 displays that in all subscales,

the

nuthber

interested in attending computer courses increased with

increasing

levels,

which

suggested

that

computer

subjects'

literacy levels and attitudes towards using computers in

were

of

factors

governing

the

subjects

interests

in

schools

attending

computer courses.

Most favourable courses

4.6.2

T\io indicators were used to indicate subjects the types

They were,

of computer courses.

i.

preference in the number

of

subjects showed that they were interested in that type of courses and ii,

the rank subjects assigned to that type of courses.

order to facilitate comparison,

were

averaged

over

the rank orders

at eacn

the number of subjects interested

course.

105

In

course in that

Table 4-43

Frequencies of Subjects Interested in Attending compute r Courses

with Different Levels in Subscales

Interest

Levels of subscales
High

Medium

Low

151

171

34

85
256

(CPINF)

Yes
No

Total

113
22
135

185

(CSOc)
Yes

63

146

No

8

34

71

180

226
99
325

106
22
128

200
94
294

357
113
470

36
26
62

299
112
411

3

Total

[E.joI]
Yes
No

Total

129
25
154

( ATJXJCT)

Yes

42

No

2

Total

44
( ATItJCSA)

Yes

133

No

26

Total

159

3

6

Table 4.-44

wn

Thes

.lnAttenthngDifferen t Computercourse

*_____ .

-

.

.
.

.

.

.

.

.
:

.

.

.

*

Course

Mean**
H & D
CA
BCO
ASSP
UESP
EP
AP

115
165
324
341
323
287
239
147

sp

:

.

.

Ranks

3.65
4.84
7.07
6.65

629
58O
4.92
3.57

i

2

15
26
191
91
69
25
25

3

5

6

7

8

18
23

17
27

31

9

3

1

5
8

1
2
4

3

8

7

8

11

22
47

20
47
62
75

24
15

17

132

2

4

97
77
24
10

75
46
11

35
38
68
39
24

11
12
33
23
56
29

11
21
22

21
22

6

1
4
7

27

Note: H & D - History and development of computing
CA - Computer awareness
BCO .- Basic skills of computer operations
ASSP - Application of standard software packages
CJESP -. Use of educational software package
EP .- Elementary programming
AP - Advance programming sp - Social impacts of computerization
*

Nu[flbr of subjects indicated that they were interested in this type of course.

** Average of rank orders over the interested in that course.

Table

in terms of number

4_44 displays that,

showing interest,

number

of

of

subjects

the types of courses could be grouped under

categories
a. most favourable courses
-basic skills of computer operation,

-application of

-use of

subjects

standard

educational

software packages,

software packages,

107

3

b. medium favourable courses

-elementary

programming

ogami,

-advanced

c. less favourable courses
-history and development of computing,

-computer awareness,
-social impacts of computerization. terms of rank ordering,

In

observed.

It

the similar pattern

was also observed that,

could be

among the three tyoes

of

courses in the "most favourable courses" group, "basic skills

of

computer

operations"

was ranked an exceptional

high

priority.

There was 191 subjects ranked it as first priority and it had the

highest the These results suggested that

average rank order (7.07).

subjects were interested in courses which could lead to

direct

application of computers.

lacked

of the capabilities to

However,

many of

them

the

still

operate a computer effectively as

an user, and hence ranked "basic skills of computer operations as

the first

priority.

Further breakdown levels attitude scales (Tables 4-48 & 49) showed similar

of

patterns, in of the numbers of subjects in different

which suggested that attitude towards using

computers

in

attending

schools

did

not affected subjects' interests

courses.
However,

literacy subscales, for

the

the

(Tables
CPINF,

breakdown by different
4-45

levels

to 4-47) showed that in

CPSOC and CPCOM,

of

all

computer

the

three

the most favourable courses

"High" level subjects were (i) application of

standard

software

packages and (ii) use of educational software

packages

while for the 'Low" level subjects, their most favourable courses

were shifted to (i)

elementary

basic skills of computer operation and

programming.

These

(ii)

results may suggest that when

a

subject had been equipped with the knowledge to become a computer users, he/she had kept up their knowledge with the development of

computer

industries and

awared that programming was

no

longer

the most imrtant element of computer applications. However, for those without any interaction with computers, what they wished to learned in the first place was how to operate a computer.

Table 4-45

Number of Subjects interested in Attending Computer cours

with Different Levels of CPNE
Levels

Course

C&D
CA
BCO
ASSP
UESP
EP
AP
SP

High
N=135

Medium

34
45
60
96

38
55

'J=l85

107
133
120
108
89
50

101
58
83
46

Low
N=256
43
65
157
112
102
121
67
_5_1

Note : According to the course names of Table 4-44

Iø

Table 4-46

Number of Subjects Interested in Attending Computer Courses
Differe

-

Course

C&D
CA
BCO
ASSP
UESP
EP
AP
SP

Levels

High
N=71

Medium
N=180

16
20
29
55
54
31
50
26

45
60

103
125
124
97
79
56

Low
N=325
54
85
192
161
145
159
110
65

Note : According to the course names of Table 4-44

Number of Subjects Interested in Attending Computer Courses with Different Levels of CPCOM

Course

Levels

High
N=154

C&D
CA
BCO
ASSP

37
46
60
110

tJESP

116

EP
AP
SP

Medium
N=128
27
42
83
89
82
73
60
31

71
96

55

Low
N=294
51
77
181
142
125
143
83
61

Note : According to the course names of Table 4-44

110

Table 4-48

Number of Subjects Interested in Attending Computer Courses with Different Levels of ATUCCT

Course

Levels

High
N=44

C&D

Medium
N=470

10
16
29

CA
BCO
ASSP
UESP

31
32

27
25
15

EP
AP
SP

Note

:

Low
N=62

99

6

133
265
285
266
235
196
123

16
30
25
25
25
18
9

According to the course names of Table 4-44

Table 4-49

Number of Subjects Interested in Attending Computer Courses with Different Levels of ATUCSA
Levels

Course

Medium
N=41l

High
N=l59

C&D
CA
BCO
ASSP
UESP
EP
AP
SP

84
119
222
229
219
196
161
106

30
45
99
109
101
89
76
40

Note : According to the course names of Table 4-44

ill

Low
N=6

1
1
3
3
3
2
2

1

Chapter V
Summary and DiSCUSSIOn

5.1

Computers

can be

used

secondary schools to he

in classrooms

of

elementary

teaching in many subject areas

.

These

opportunities are being missed because many teachers do not

how

to

concerns

use computers in the classroom.

In Hong Kong,

on secondary school computer education are

and

all

know the focused on

the subject s'computer studies". Research on the computer literacy of Hong

Kong teachers was not found in the literature

and

the

area of using computers in classroom teaching is still in the era of informal

development by interested

teachers.

essential

An

element in developing classroom computers is that teachers should

be well purpose the

prepared

in terms of

competence

attitude.

and

literacy,

of this study was to investigate the computer

attitudes

towards

order

using computers in schools in

develop ways of improving,

and also the interest

to

attending

in

computer courses as well as the most favourable course

The

,

of Hong

Kong teachers in order to provide information for decision makers in tailoring

computer

courses for

112

teachers.

Throughout

this

study, 5% significant level was assumed which implied that if the was sample

a

random sample of secondary

school

lecturers of colleges of education in Hong Kong,

teachers

and

by taking a

5%

risk of drawing wrong conclusion, we could extend the conclusions to all

secondary school teachers and lecturers in

colleges

of

education. The findings of this study were
( 1)

.

Hong Kong Teachers ' computer literacy was low. The 3 major

factors

related to teachers

training

on

basic

computer competence were

operation skills

of

computers,

i.

ii.

chance to interact with computers and ii. ithorn interests in machine.

Hong

(2)

Kong Teachers had positive attitude

computers in school.

Basic knowledge in

towards

using

computer and the

chance to be exposed to meaningful applications of computer were the 2 factors influencing the attitude of teachers.

Hong

(3)

Kong Teachers were interested in attending

computer

courses for teachers. They were most interested in courses and which could enable the to interact with the computers which had directly applications in their daily works.

5,2 Results of data collection

A

64

items survey questionnaire was developed

to

collect

data for this study. 865 questionnaireS were sent to 23 secondary

schools

secondary

from

and 4 colleges of education in Hong Kong .572 (474 schools returns were

and

received.

112 from colleges

The

of

education)

returned rate was

113

66.6%.

valid

Due

to

resources,

of

limitation

school teachers

this study did riot

included primary

By taking into consideration that the return of

questionnaire was on a voluntary basis, it might happen that only those with interests in computer would return the questionnaires.

5,3offindin
Three subscales,

measure

CpINF cs and CPCOM were established to

the informative elements,

communicative

and

the social elements

computer

of the subjects' self-reported

elements

the

literacy respectively.

it was found that teachers' average computer

In this study,

literacy was

at a very low level in

exceptionally low mean score in CPSOC.

around

were

25%

of

the súbjects in

that not more than 25%

suggested

effectively

all

the

In CPINF and CPCOM, there level "high"

the

taking

By

into consideration that only those interested in computers

lower.

In

CPSOC,

only

the actual percentage

"high"

12% of the subjects were in the

aware the social impacts of lower end computerization.

of

would

might be still

level which implied that about that percentage of teachers

the

which

of the teachers could function

as a computer users in their daily work.

return the questionnaires ,

with

subscales,

could

A look at

50% frequencies of responses revealed that there were around

the

subjects

indicated that they never

Assisted Instruction and Easy Pay System.

heard of

Computer

This was a very danger-r

behind situation as this group of teachers would be left far

114

the

of our society,

development especially boys,

As many secondary school

might easily learn this type of knowledge from

other teachers or their parents, to students,

they would find very

difficult

communicate with these students which might jeopardize
In

career.

lecturers

computer

terms of competence, in colleges

literacy.

their

secondary school teachers

of education were not well

and

prepared

There is an urgent need to provide

in

computer

course to bring this group of teachers to enable them to function

effectively as computer users.

The computer using

study

also found that,

a.

male

literate than female teachers;

b.

science

teachers

teachers were less computer literate;

more

mathematics and

c.

computer

teachers;

or more computer course(s),

literate

than

those

not

were

graduate teachers were
e.

no matter

education or in in-service training programme,

formal

computer

social and art subjects

d.

more computer literate than non-graduate one more

and lecturers of teaching methodologies

computer literate while languages,

attending

were

teachers of schools

computers in some administrative work were

literate than teachers in schools not using.

most

teachers

attending

teachers

in

their

were more

any course;

f.

teachers had more types of access to computers were more computer literate; g. computer users were more computer literate than nonh. reading in computers was a major indicator of computer

users;

literacy.

From teachers mathematics sorne these results,

could or be

The more computer literate

described

as

majority

male,

science teachers of schools using

administrative work,

Hong

Kong

graduate,

computers

in

who had attended more than 2 computer

115

courses and had access to more than one computer system. They had used computers in their daily work and read books or journals

in

computers.

was

It

also

was

experience

the

an

finding

in-service literacy programme, of this

that hand

study

important factors of computer

one or two course(s)

attending

of

,

literacy

and

no matter in formal education or

could significantly improve the

teachers.

on

Why just attending one

computer

computer

course

could significantly improve the computer literacy of the subjects

was

a very interesting question.

experience the By sharing

the

with several computer studies teachers,

explanation

gone

through the initial stage,

access to computer system,

knowledge
Figure

With this learning model,

the schools to all teachers, the However, when one

interest,

and with

Their relations were given

computer literacy of teachers were,

with

with

to

one could easily improve his/her own

through self-learning.

4.3.

we agreed on

that computer was a subject very difficult

start without some essential initial training. has self-learning

a,

in the the ways to upgrade

opening the computers in

and b. providing an training course

essential knowledge to enable all teachers

to

start

their self learning.

Two measure classroom

subscales the ,

ATUCCT

subjects'

teaching,

and ATUCSA

attitudes

and

in

respectively.

116

towards school were

established

to

computers

in

using

administrative

work,

In this study, it was found that only 8% (N=44) and 1% (N=6) of subjects

the

On

respectively.

using

towards

had negative attitudes in average, computers

classroom teaching.

ATUCCT

and

subjects had more positive in school

administration

ATUCSA attitude than

It could be concluded that majority of

in

Hong

Kong teachers had positive attitudes towards using computers both in the classroom teaching and in school administration. With some practicing examples in Hong Kong,

existing

more teachers agreed

that computers could be used in some school administrative as keeping student records,

such

the

processing student reports and

statistical information of students etc.

producing

efficiency not examples,

of school so many teachers agreed to the

practicing that statements

teaching.

in

reject the idea of using computers

not

did

improve

to

Without

administration.

computers could be used to enhance classroom they works

However,

classroom

teaching.

study

The computers ATUCSA

in

than

also some found that a.

teachers

administrative work were

teachers

of

school

not using;

school

of

using

more

positive

in

b.

teachers

of

Economics and English had highest scores in ATUCCT while teachers of Geography, English and Economics had highest scores in ATUCSA;
C.

teachers

who had attended one or more computer

only,

their formal education were more positive in ATUCCT

teachers who

than

teachers

computers

attended one or more

courses

those

who had not attended any

such

in

while

required

the

ATUCCT

and

courses;

d.

in computers were more positive in both

application
A'IUCSA

had

courses

who had access to computer systems and who had used in their daily work were more positive in both

117

ATUCCT

and

ATUCSA than those without access to computer system

user;

non-

e. teachers with higher scores in the informative elements

(CPINF)

and communicative elements (CPCOM) of computer

literacy

were more positive in both ATUCCT and ATUCSA, while teachers with higher scores in the social element (CPs0c) of computer

literacy

were more positive only in ATUCCT, than those with lower scores.

From

the

above

results,

Hong

Kong

teachers

with

positive

attitude towards using computers in classroom

(ATUCCr)

could

teachers

who

courses

be described as majority English

had

required

education,

attended one or more

courses,

their

subscales of computer literacy.

more

positive

administrative

works

or

formal

had used

and had higher scores in all the

three

Economics

computer

had access to one or more computer systems,

attitude

teaching

and Economics

the application of computers in

computers in their daily works,

more

towards

Hong Kong teachers with

using

computers

could be described as

school

majority English,

and Geography teachers of schools using

some of their administrative works,

in

computers

in

who had attended one or more

courses required the application of computers in the course work,

had access to one or more computer system

,

had used computers in

daily works and had higher scores in the informative (CPINF )

and

communicative (CPCOM) elements of computer literacy.
It

could

then

be inferred that

practicing

examples

and

competence in computer literacy were the two important factors to

improve

a subject's attitude towards using computers in

schools

while the second factor further depended on the accessibility and

initial

training

of computers.

Their relations were given

in

Figure 43 and

a model to improve teachers

attitudes

towards

using computers in schools could be represented graphically as in
Figure 5-l.

Figure 5-1

fIa2yinTeachers Attitude
Towards Using Computers in School

Attitude towards using computers in school

I

I

Practicing examples Computer literacy Initial training in computer

Computer
Accessibility

76%

(N=435)

interested

the

subjects

of content,

that

indicated

in attending computer courses for

terms

In

of

they were

teachers.

the most favourable courses

of

more

Computer literate teachers were application of standard

software

and of less

computer

packages

and use of educational software,

literate

teachers were basic skills of computer

operation

and

elementary programming.
In

terms

of conduction time,

most

teacher

(24%,

N=139)

preferred the courses to be conducted during long school holidays

while

running the courses immediately after school hour

119

(5

- 7

p.m. )

(22%.

Nl25) and on Saturday morning (20%,

second and third
In

terms

N=114) got the

best supoert from teachers.

of

course

time,

35% (N=203)

indicated that the courses should take

of

the

teachers

one to two hours per week

while 32% (N=184) indicated that they could effort to spend three to four hours per week.

More than four hours per week got

very

indicated that majority

Kong

few support.

The

above

results

of

Hong

teachers were eager to attend computer courses which could enable

them to operate a computer effectively. some initial

knowledge of computers,

For those teachers they were also

with

eager

to

learn how to apply computers in their teaching and in their daily work. It could be concluded that in terms of entering behaviour to

computer

self-motivated

Course designer

according to their readiness, and Hong Kong teachers were

courses for teachers,

previous

knowledge,

needed only design the

already course that were their learning abilities

of teachers with different

competence in computer

120

levels

of

5.4 Recommendation

F-long Kong teachers were found to be low in computer literacy

positive

but

in

attitude

towards

using

computers

classroom teaching and in school administrative work.

self-motivated hence, both

in

They were

to attend computer courses for teachers.

there

is an urgent need to design computer

courses

for Hong Kong secondary school teachers and lecturers in colleges

of education to meet their needs. The courses should have 2 major types .

The first type should be courses aimed at enabling

without

basic

skills of computer operation to become

end user of computers. at The second

introducing quality

structured

to take not more than 4 hours

offered either during long holidays,

both

aimed

in classroom

to those teachers who could

operate a computer effectively as end users.

be

effective

type should be courses

software packages,

teaching and in general application,

those

Each course per should
Courses

week.

immediately after school or

on Saturday mornings could get equal support.

Accessibility

to

computer

was an important

to

factor

a

subjects computer literacy, hence computers in schools should be

opened to to all teachers to provide opportunities for the teachers

enhance their computer literacy and to encourage them to

use

computers in their teaching.

Good

examples represented by quality software packages is a their major factor to motivate teachers' interest and to improve

attitudes towards computer applications. However, lack of quality

softwares

packages

administration

in both

classroom

teaching

is now a major problem in Hong Kong.

121

and

school

Hong

Kong

her own culture background and education

has

C1SC where

at

developod

purpose

demonstration
Some

purpose .

concerned

software

users,

teachers

are

not

the

World may

but will not be suitable

by themselves.

softwares

of

system,

Kong

F-long

However,

producer,

teachers

softwares

be

good

for try practicing

to develop

as school teachers are

softwares developed by

far below the standard set

for

just

school

down by professional

bodies, such as British Computer Society. Using such Thalf-baked't

softwares may give beginners a wrong idea about the advantages of

computer applications.

Hence it is also an urgent need to set up

a comprehensive plan to develop quality softwares. A new question on Who should take up this responsibilities P " then emerges and

waiting for answer.

5.6 Weaknesses of this study

The

design

end

lower

hence

and

literacy.

This

investigation

low

items were on the end low

questionnaire

end

of

into the at

Hong Kong teacherst computer literacy was

that

account

of questionnaire for this study had taken

computer the constrained

of attitude (towards using computers

in

schools) its change

at the higher end of computer literacy where some of

effect

was found in investigating number of courses attended by

the subjects. still led as there

However, irrespective of the low end items,

which a huge cluster of scores at the low end of the scale

to violation of assumptions in statistical analysis
MANOVA.

such

The results and conclusions of this study were

122

only

for

valid and the variation of computer literacy at the

could not extend to i.nclude the whole spectruj

literacy.

Also,

as

several analyses,

the

lower of end

computer

assumptions of MANOVA were not met

in

the interpretation of results had to take into

account of such short coming.
Lunìng (1985),found that self-reported competence was a good indicator of

sufficient

subjects

indicator

computer

competence

but

was

not

for further training which suggested

a

that

subjects might over estimate their own computer literacy levels, but the relation between

competence was linear. the questionnaire was based on this result.

contents

validity thus of

computer

The design of computer literacy scale

literacy was not tested. the the actual and self-reported

Subjects

computer

They just claimed their competence

the 24 items on knowledge

of

in

in

computers.

The

of the results and conclusion on computer literacy

was

based

on the validity of applying the results

of Luning

finding to Hong Kong.

5.6 Future Research Areas

With

regard to the research questions raised in this study,

further research cari be pursued in a number of areas.

In

order to implement the recommendation of this

structured essential. are

loosely

computer

literacy

In Hong Kong

curriculum

for

teachers

a is all the computer courses for

teachers

comprehensive

computer

structured and there is no

literacy curriculum

for

study,

teachers.

123

Kwok

(1985)

used Delphi

technique to develop a computer literacy curriculum for Hong Kong secondary school.

Similiar

study

is

needed

develop

to

a

curriculum for Hang Kong teachers.
Due to limitation of resources,

primary

school teachers. teachers school

computing

can we 1owever,

this study has not included

There is no reason to exclude

from computer literacy programme

enhance

can

not

teaching in

primary

equate primary school

as

primary classroom schools

as

teachers

well.

to

non-

graduate teachers in secondary school on the basis that they have similiar training. The different working environment of secondary and primary

attitudes

courses

schools

will

make

their

computer

competence,

towards computers and interests in attending

quite different.

computer

This study can be extended to

primary

school teachers.
This study revealed that Hong Kong secondary school teachers

colleges

and

towards

using

of education lecturers all had positive computers in schools and majority

of

interested in attending computer training courses. causes of these results were not investigated. found they

advantages

What

them were

However,

the

Have the teachers

that they can not effectively communicate with students if

are

there

attitudes

not

of

computer literate

?

classroom computing ?

Or,

Or,

have

they

the

aware

have they found

that

is an urgent needs to use computers in their daily work

is the motivation of teachers

interest is

an

?

interesting

question for future research.
Finally, in survey questionnaire, it is almost impossible to test the subjects' competence in computer.

Their competence can

only be reflected by self-reported scales. However, education and

124

culture

background will be an important factor in affecting

the

validity of the information measured by self-reported scale. That ìs ,

reflect that who

person that area

consider ignorance. considers that ignorance in certain

he/she does not have the chance to be

area

just

trained

in

will generai give true information while person who the same

Further

as

a shame will try

research

to

hide

his/her

to find out the relation

reported and tested competence of computer of Hong Kong

will also be an interesting question.

125

of

own self- teachers

Appendix A

NeaflscoresofItemsint he

2irL±teracy Scale

Table A-1
Literacy Scale

No

Content

MEAN

SD

41

CPU
Magentic disc unit
Network
Operating system
Byte
Program file, Data file
ASCII code
Lockword/password
RAN
Database
Compilers
Programming language

1.61
1.44
1.24
1,31
1.36
1.56

1.10
1.08

42
43
44
45
46
47
48
49

50
51
52

53
54
55
56
57

58
59
60
61
62
63
64

Note :

.99
.99

1.01

1,20
1.07
1.14
1.23
1.19
1.05
1.04

1. 71

.99

Informative elements (CPINF)

1.32

.92

CAl/CAL
EPS
Computer crime
Artificial Intelligence
Threat to privacy

1.02
1.29

1.09
1.11
1.05

.75

.98

1.30

1.06

Social elements

1.07

.84

.86

1.26
1.28
1. 22

.99

Switch on a computer and check
1,80
that it is ready for use
Select, load and run
1 . 56 a program
1.20
Write a simple program
Identify and correct errors
1.11
in a program
1. 00
Copy computer file
.98
Set up a computer system
1.06
Try out software packages

1.12
1.24
1.25
1.22

Communicative elements

1.25

1.05

All items

1.25

.87

1.20
1.22
1.20

self-reported were coded according to the
Items
competence of the subjects computer literacy with a minimum vale of O and a maximum value of 3.

126

Appendix

B

Normal P3ots, IDetrended Normal Plots

and
Stem-and--leaf Plots

Computer Literacy Subscales

¿. &tbscale on Informative elements (CPINF)

b. Subscale on Social elements (CPSOC)
C, Subscale on Communicative elements (CPCOM)

127

Normal Plot and Detrended Normal Plot of
The Subscale on Informative Elements (CPINF) of Computer Literacy

U'MAL

L(

-4-"---+----4---+ -.---*---;

i

:

i

:

i

:

4

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:

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V

?fi

:

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+

A
T

:

I

:

:

_)7

4.

:ì

:

:

FI:

:

:

¿Gdr

AE;

:

D

AHCA

:

F*
-1

4
:

F

:

P

-

ri

CPMAL PLOT

ETREtDED

CVA

:

4

L.*

1.

7'

4

+

:4

:

I

-2

:

+
1

:'4

I
;

;

-i

:

-41
-.

I
I

54

I

:

.

:

-+----4----+.---+-----+-

:

-

Ir i .

2

274

1EJJI:FHC7

:

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2_

+

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ôrE:

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4
4
25

r[P4
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:'41

+

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:

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Figure B-2
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Figure B-4
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Informative Elements (CPINF) and Social Elements (CPS0C)

I. Informative elements (CPINF)

s

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u

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132

Appendix

C

Normal Plots, Detrended Normal Plots and Stem-and-leaf Plots

Subscales of Attitude towards Using Computers in School

a. Subscale on Attiude towards Using Computers in

Classroom Teaching

(ATUCcT)

b, Subscale on Attitude towards Using Computers in
School Administration (ATUCSA)

133

Figure C-1

Normal Plot and Detrended Normal Plot of The Subscale on
Attitude towards Using Computers in Classroom Teaching (ATUCCT)

rLCT

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Figure C-2

Normal Plot and Detrended Normal Plot of The Subscale on
Attitude towards tisinq Computers in School Administration (ATUCSA)

LT

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+

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Figure C-3
Stem-and-leaf Plots of The Subscales on
Attitude towards Using Computers in Classroom Teaching (ATrUCCr) and
Attitude towards Using Computers in School Administration (AThCSA)

I. Attitude towards Using Computers in Classroom Teaching
( ATUCCr)
'j

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136

Q

1C'

+5
O+4

Survey Questionnaires

a. School Questionnaire

b. Teacher Questionnaire

137

P 138

139 - 146

School Background Questionnaire

Name of school:

i, Type of school

1. Government
2. Aided
3. Colleges of Education

2. Sex of students

1. Boys
2. Girls
3. Co-educated

3, Age of school

1. less than 10 years
2. lO to 20 years
3. more than 20 years

1. Urban area
2. Urban estate
3. N.T. estate

5. Is computer studies in the school curriculum? o. No
1. Yes

6. Is the school using computers in some school administrative work?

o. No
1. Yes

7, Is there a computer club in the school?

o. No
1. Yes

8. Except computers provided by the
Education Department for the subject computer studies, does the school own some other computers?

o. No
1. Yes

138

28 April, 1986.

Dear Sir/Madam,

Computer studies will
Aided secondary schools education center will computer in subjects interest of many teach teachers' seminar.

soon be a subject in all Government and in Hong Kong and a well equipped computer be opened in the near future. Using other than computer studies is now the rs and is tried out and discussed in many

am a student in the Department of Education,
University of
Kong and currently conducting a study to collate Hong Kong teachers' opinions on using computer in teaching all subjects in the secondary schools.
I

E-long

have been identified as a specialist in the subject you am soliciting your expertise to make this study teach. I
The amount of time required for answering this possible, questionnaire is approximately 15 minutes.
You

Please return this questionnaire in the envelope attached. You need not enter any identification of yourself or your school as no person will be identified in this study. However, if you wish to have a copy of the summary result of the study, please
I guarantee that it will complete the address label below. he immediately be seperated from the questionnaire and that all information in the questionnaire will be identified.

Thank you very much for your cooperation and I look forward working with you in this project.

to

Sincerely,

Address label
(Complete only if you want copy of the summary result)
I

I Name

I would like to have a copy of the summary result of your study.

I

I Address
I
I
I
I

O.No l,Yes 139

a

Items i to 29 are items on demograhic characteristics interests in attending computer courses. Circle on questionnaire the response which is most appropriate to your and the you

(except items 11,12,25,28 and 29 where special instructions are given in the iteme)
(Circle the most appropriate response)
Less than 21
1. 21 - 25

1. Age:

o.

2. 26 - 30
3. 31 - 35
4. 36 - 40
5

41 -

o.

Female

0.
1.
2.
3.
4.

Secondary
Post secondary
Bachelor
Master
Others (please specify)

a.
1.
2.
3.
4.
5
6.

Nil
1 or less
2 - 3
4 - 5
6 - B s - 12
13 - 18
19 or more

45

6. over 45
2. Sex

3. Marital Status

1. l4ale
o. Single
1. Harried without child
2. Married with chìld(ren)
o. Colleges of Ed
1. Cert.Ed./Dip.Ed.
2. Other (please specify)

:

4. Teacher training

5* Highest Education

:

(Other than teacher training)

6. What major subject(s) are you teaching at present? Please specify

7. Years of teaching experience

:

'7,

8. Percentage of administrative work.

o. ot
1. 1 - 10%
2.
3.
4.

9. Hnber of courses you have taken in schools, colleges and universities which require the applications of
Computers in course work.
140

o.
1.
2.
3.
4*

11 - 25%
26 - 50% over 50%

None
1 - 2
3 - 4
5 - 6
7 or more

100 Number of computer courses attended in schools, colleges and universities.

11

Circle those programming language you have learnt in schools, colleges and universities.

O. None
1. 1 - 2
2. 3 - 4
3. 5 - 6
4. 7 or more
0. None
1. BASIC
2
FORTRAN
3. COBOL
4. PASCAL
5. RPG
6. Others (please specify) i0 ii.

12. Circle those prograimiting language

you have learnt on your own (rather than in formal education such as in schools, collegess and univaristies).

O. None
1. BASIC
2. FORTRAN
COBOL
4. PASCAL
5. RPG
6. Others (please specify)
:3

1.

11.

1.3. How many training courses on computer have you attended.(courses which are organised by Education Department,

Teachers' Associations, or by Computer
Manufacturers).

0. None
1. 1. - 2
2. 3 - 4

3. 5 - 6
4

7 or more

14. How many workshops or seminars on computers you have attended in the last 2 years.

O.
1.
2.
3.
4.

None
1 - 2
4
3
5 - 6
7 or more

15. -How many books on computer do you have at home?

O. Hone
1. 1 - 2
2. 3 - 4
3. 5 - 6
4. 7 or more

16. how many coputer periodicals
(magazines, journals) do you read

monthly on a regular basis?

'

1.

Hone
3.

2

2. 3 - 4
3. 5 - 6

4. 7 or more
No
1. Yes

17. Are you a teacher of Computer Studies?

0

18, Do your have a computer at home ?

O. No
1. Yes

141

e11u() 4

20. Can you have access to co*pnters other than thoee mention tn queetion8 18 & 19?

O

No

1. Yes

(e.g. couters in the unt,ersities or co*puter ovned by TOUE friends)

21. Exc1ding Couter Studies, do you use coaput*rs in teaching other aubects? uee coiputers in preparing notes, test and examine papers?

o

so

L Yes

22. Do yo

O
1

23. Do you use computers in keeping student records? O. 110

24. Are you interested in attending coesputer courses for teachers ?

O. Ho
1 Yes

25

Ho
Yes

1. Yes

Rank order only those courses ot interest to you; the most preferred course a rank ot 1, the next moat pzefezred course a rank o 2 etc. Leave blank those of no interest to you.
Priority

a.
b.
C.
d.
e.
f.
g.
h.
i.

26.

History and developsent of coeçuting
Computer awareness
Basic skills of coaputer operations
App'ication of standard software packages such as word processing, electronic worksheet etc.
Use at Educational software package such as CA! and ex9erimental ei*ulations, etc.
Elementary programming
Advanced programming
Social impacts of computerization
Oihere (Please specify)

-

If courses are organised outside normal øchøol hours, which of the following times will be most convenient to you?
7 p.m. on school days
Immediately after school, 5
In the evsnings, 7 - 9 p.m. on school days
On Saturdays mornings
During lonq school holidays, for examples, Easter holidays, Christmas holiday3 Or Summer holidays etc..
e. Others (Please specify)

a.
b.
C,
d.

27.

2L.

HOW many hours per week are you willing to spend in attending coaputer coutBe(s)?

1.

O

1 - 2
3. 3 - 4
4. 4 - 6
5 more than 6
2.

Circle the area(a) where you believe that co*puters may be used in teach Ing.

29.

Circle

th

area(s) where you believe that

computere

may

help in achool administration.
a.
b.
C,
d. e, Keeping student records
Processing student reports
Pro4thacing statistical inEormations of students
Procaa5ing test and examination papers
Others (please specify)

Questions 30 to 40 are statemants asking your opinions in the use of coers in claesrooffi teaching and in school administration.
Circle the option which best reflect your opinion to each of the foliwoing statements,

BA if
A it
N if
D if
SD if

you you you you you

STRONGLY AGREE with the etatment
AGEE with the statment are NEUTRALE about the statment
D1SAREE with the statment with the statment
STRONGLY DI8AØ

4.
4.
b.

4.
4.
.

-

.

(circ1

30.

I

bieve the ue of

5ubecr8

h1ps ieso 31.

In ce used :

cciputers in studies

SA A

N

D

SD

SA A

N

D

SD

tun cortuter

thtr

:

7OtIt choice)

tuderc& to bettei rndrstand

'

.

f

the

ject j teach couputers can be tc take care a the nees of each

indivit1 students
32.

cornputer5 in my teaching can help
'-!
less
"tudents ta better understand the l..

SA A N

D

SD

Using provide students

SA

Using

;.

33.

teaching

can able learning

A

N

D

SD

ielp me to present most of active and tore a in SA A

N

D

SD

in school administration

SA A

N

D

SD

to and SA A

N

D

SD

coaputers are used ta keep student recozds the eflectiveness and efficiency of teaching will be improved by making available statistical information such an and standard deviation of as the the comparisions of students test performance with different classes and

SA A

N

D

SD

A

N

D

SD

SA A N

D

SD

SA A

D

SD

in my opportunities

ore

or

to ha. more in-depth according to thì: interests.
34.

Comp:::. my inter
35.

36.

,;

Using is just a

Computers c: make it easier for prepare examines.

37,

i

.tion

lson3 an

me

tests

If

with previous yeti r
38.

to set

etc..

Using coputars in school administration significantly reduce paper work and vil]. hence increase the efficiency of running

SA

a school.
39.

Using computers in my daily teaching will only waste ay teaching time.

40.

out
School admjnstration can be ca,ried equally well with or without cmputers.
144

N

Items 41 to 57 are terminologies, topics about computers the applications o co*puters. and
Rate your degree o nderstafldiflg of the8e items on a scale o j. to 4,

1, if you have never heard of it before,

2, if you have heard of it but are not sure what it je,
3,

if you know what it is but are not eure the details its function,

of

4, if you know what it is and you know the details of its fuctions. n .4'

1

:o

L!

.'..-s

(circle your choice)

.

.. i 41.

Central

42.

43.

Processing

Unit (CPU)

i

2

3

4

Magnetic Disc Unit

i

2

3

4

Network

i

2

3

4

44.

Operating 8ytem (OS)

i.

2

3

4

45.

Byte

1

2

3

4

46

Progre* file, Data tile

i

2

3

4

47.

ASCII Code
(American Standards Code for
Information Interchange)

i

2

3

4

48.

Lockword/passward

2

3

4

49*

RAM (Random Access Memory)

2

3

4

50.

Database

2

3

4

51.

Compilers

i

2

3

4

52.

Proqzaming Language

-

2

3

4

53.

CAl/CAL

i

2

3

4

54.

Easy Pay System CEPS)

2

3

4

55.

Computer crime

2

3

4

56,

Artifilca]. Intelligence
The threat to individualst privacy

i

2

3

4

2.

2

3

4

51.

1.

(Computer Assisted ¡nstructjon/tearning)

due to computer1zatiOfl.

145

58 to 64 are procedures of operating a computer system a computer related job
Rate your degree of in carrying out the specified task on a scale of i to confidence Ite

or:

tfOLfl

4,

o
.

o

=
.

4

4

-

(circle your choice)

:i

!

58.

Switch on a micro-computer system or the tevminal of a computer systeri and check whether or not it is ready for use.

i

2

3

4

59.

Select, backing load and run a ptogram from example, for storage devices,

i

2

3

4

disc, tape, etc..
60.

Write

a simple program to do a specified task and run the program

1

2

3

4

61.

Recognise any error(s) in a program, next correct the program, and then rerun the revised program.

i

2

3

4

62,

Copy a computer file from one device to fro* one disc to another another; e.g., disc or from a disc to a tape, etc..

i

2

3

4

63.

Connect up the components of a microcomputer St$tCflt (monitor, disc drive, printer,atc.), to the central processing units. i

2

3

4

64,

Try out software packages the manual,

to

i

2

3

4

according

146

Appendix E

Code Book of The Questionnaires for The Study on

The Computer Literacy of Hong Kong Teachers

Pnrt 1 - School Questionnaire

P359

Part 2 - Teacher Questionnaire

P160 - 168

147

! !

Quest i on

g

VariabLe

location

Responses

Punch

--

01-23
81-84

No

School Code

1-2

Type of school

3

Sex of students

S4

S5

56

S7

SB

59

4

Aqe of school

5

Locion of school

6

Computer studies in the school curriculum 7

School using computers in ddnnnistrative work

8

Computer club in school 9

Govern
Aided
C of E

1
2

Boys
Girls
Co-Ed

1

< 10 yrs
10-20 yrs
> 20 yrs

Not used

Ji.

i43

2
3

i
2
3

Urban area
Urban estate
NT estate

i

No

o
1

Yes

School has computers 10 other than standard equipments 3

2

3

No
Yes

o

No
Yes

o

No
Yes

o i i

i

Skip

Part 2 - Teacher questionnaire

Quest ion

Variable

location

Responses

No
-

i

Serial number

12-14

Not used

15

Aqe

16

Punch

001-999

Skip less than 21
21-25
26-30

û

31-35
36-40
41-45 over 45

3

1
2
4

5
6

2

Sex

17

Female
Male

o
1

3

Marital status

18

Single
Married W/O child
Married with child

O
1
2

4

Teacher training

19

CofE
Cert Ed/Dip Ed
Other
No response

5

G

7

digest Education

Major subject(s) teach Years of teaching experience 20

21

22

O
1
2
9

Secondary
Post Secondary
Bachelor
Master
Other
No response

O

Chinese/C Hist
Cultral & Arts
Georg/Hist
English
Economics/EPA
Tech/Commercial
Teaching methods
Maths & Science

1
2

Nil

O i iorless
2-3
4-5
6-8
9-12
13-18
19 or more

i
2
3

4
9

3

4
5
6
7
8

2
3

4
5
6
7

Question
No
8

9

Variable

location

Percentage of administrative work

23

Number of courses taken which require the application of computers 24

Responses

0

1-10%
11-25%
26-50% over 50%
0

1-2
3-4
5-6

7ormore

10

11

Not used

25

Number of computer courses attended in formal Ed.

26

Punch

0
J-

2
3
4
0
1
2
3
4

Skip
0

0

1-2
3-4
5-6

1

7ormore

4

2
3

Knowledge oE programming languages learnt in formal education
27

BASIC

No
Yes

28

FORThAN

No

O i Yes

O
1

COBOL

29

No
Yes

O
1

PASCAL

30

No
Yes

O
1

RPG

31

No
Yes

O
1

Others

32

No
Yes

i

33

Not Used

150

O

Skip

Question
No
12

13

14

15

i6

Varib1e

location

18

Punch

knowledge of programming languages learnt in informal education
BASIC

34

No
Yes

o i FORTRAN

35

No
Yes

o i COBOL

36

No
Yes

o

i

PASCAL

37

No
Yes

o i RPC

38

No
Yes

O

No
Yes

O i Others

39

Not Used

40

Training courses on computers attended 41

Workshops or seminars attended in the last 2 years

Number of computer books at home

Numberof

42

Teacher of computer studies

45

Have a computer at home

46

0
1
2
3

7ormore

4

0

0 i 2
3

7ormore

4

0

0
1
2

l-2
3-4
5-6

44

15i

0

i-2
3-4
5-6

43

i

Skip

l-2
3-4
5-6

periodicals on computers read regularly 17

Responses

3

7ormore

4

0

0

l-2
3-4
5-6

i

7ormore

4

No
Yes

O

No
Yes

O

2
3

i

i

Question
No

Variable

location

Responses

Punch

19

Can used computers in school

47

No
Yes

O i 20

Can use other computers 48

No

O i 21

22

23

24

25

Yes

Use computers in
49
teaching other subjects

No

Use computers in
50
preparing notes etc.

No

Use Computers in keeping records

5i

No

Interest in attending computer courses 52

Not used

53

Computer awareness

55

Basic computer operation 56

Using standard softwares 57

Using educationai softwares 58

Elementary programming 59

Advanced programming 60

Sociai impacts of computeriZations 61

Others

62

Yes

O i No
Yes

O i Skip
(the

O

i-9

No
Yes

i-9

No
Yes

i-9

No
Yes

i-9

No
Yes

i-9

No

O

O

O

O

O

Yes

i-9

No
Yes

i-9

No
Yes

63

courses

No
Yes

No
Yes

Not used

O i Yes

Rank ordering interested computer number indicates the priority)
History of computing 54

O i Yes

O

O

i-9
O

i-9

Skip

26

Most convenient time for conducting computer courses

64

5-7 pm
7-9 pm
Saturdays
long holidays others i
2
3
4
5

27

Number of hours per week willing to spend in attending computer courses 65

0

i
2
3
4
5

28

29

l-2
3-4
5-6 more than 6

Areas where computers may be used in teaching

Enrichment of lessons 66

No
Yes

O i Drill and practice

67

No
Yes

i

O

Simulation of experiments 68

No
Yes

O i Remedial lessons

69

No
Yes

O

i

Teaching concepts

70

No
Yes

O i Others

71

No
Yes

O i Not used

72

Skip

Areas where computers may be used in school administration Keeping student records 73

No
Yes

O i Processing student reports 74

No
Yes

O

No

O

Yes

i

75
Producing statist. informations of students

i

Processing tests & examin papers

76

No
Yes

O i Others

77

No
Yes

O

Not used

78

153

i

Skip

Question
No

Variable

looet±on

Responses

Punch

30

Attitude scale item i

79

Strongly agree
Agree
Neutral
Disagree
Strongly disagree

i
2
3
4
5

3?

Attitude scale item 2

80

Strongly agree
Agree
Neutral
Disagree
Strongly disagree

i
2
3

4
5

32

Attitude scale item 3

81

Strongly agree
Agree
Neutral
Disagree
Strongly disagree

i
2
3
4
5

33

Attitude scale item 4

82

Strongly agree
Agree
Neutral
Disagree
Strongly disagree

i
2
3
4
5

34

Attitude scaie item 5

83

Strongly agree
Agree
Neutral
Disagree
Strongly disagree

i
2
3
4
5

35

Attitude scaie item 6

84

Strongly agree
Agree
Neutrai
Disagree
Strongly disagree

i
2
3
4

Strongly agree
Agree
Neutral
Disagree
Strongly disagree

i

Strongly agree
Agree
Neutral
Disagree
Strongly disagree

i
2

36

37

Attitude scale item 7

Attitude scale item 8

85

86

154

5

2
3

4

5

3

4
5

estion

Variable

38

Attitude scale item 9

87

Strongly agree
Agree
Neutral
Disagree
Strongly disagree

i
2
3
4
5

39

Attitude scale item 10

88

Strongly agree
Agree
Neutral
Disagree
Strongly disagree

i

40

Attitude scale item location

89

ii

Responses

Strongly agree
Agree
Neutral
Disagree
Strongly disagree

Punch

2
3

4
5
i
2
3

4
5

Not used

90

4]

Self-reported computer literacy scale item i

91

Never heard
1
Not sure what it is 2
Not sure its function3
Know its fuction
4

42

Self-reported computer literacy scale item 2

92

Never heard i Not sure what it is 2
Not sure its function3
Know its Luction
4

43

Self-reported computer literacy scale item 3

93

Never heard i Not sure what it is 2
Not sure its function3
Know its fuction
4

44

Self-reported computer literacy scale item 4

94

Never heard
1
Not sure what it is 2
Not sure its functton3
Know its fuction
4

45

Self-reported computer literacy scale item 5

95

Never heard
1
Not sure what it is 2
Not sure its function3
4
Know its Luction

46

Self-reported computer literacy scale item 6

96

1
Never heard
Not sure what it is 2
Not sure its function3

Skip

Know its fution

4

Questi on

Variable

location

Responses

Punch

No
47

Self-reported computer literacy scale item 7

97

Never heard
1
Not sure what it is 2
Not sure its function3
Know its fuction
4

48

Self-reported computer literacy scale item 8

98

Never heard
1
Not sure what it is 2
Not sure its function3
Know its fuction
4

49

Self-reported computer literacy scale item 9

99

Never heard
1
Not sure what it is 2
Not sure its function3
Know its fuction
4

Self-reported computer literacy scale item 10

100

Never heard
1
Not sure what it is 2
Not sure its function3
4
Know its fuction

51

Self-reported computer literacy scale item il

101

1
Never heard
Not sure what it is 2
Not sure its function3
4
Know its fuction

52

Self-reported computer literacy scale item 12

102

1
Never heard
Not sure what it is 2
Not sure its function3
4
Know its fuction

53

Self-reported computer literacy scale item L3

103

1
Never heard
Not sure what it is 2
Not sure its function3
4
Know its fuction

54

Self-reported computer literacy scale item J4

104

1
Never heard
Not sure what it is 2
Not sure its function3
4
Know its fuction

55

Self-reported computer literacy scale item 15

105

i
Never heard
Not sure what it is 2
Not sure its function3
4
Know its fuction

56

Self-reported computer literacy scale item 16

106

i
Never heard
Not sure what it is 2
Not sure its function3
4
Know its fuction

156

Qucst ion

Variable

location

No
Self-reported
computer literacy scale item 17

107

108

Responses

Never heard i Not sure what it is 2
Not sure its function3
Know its fuction
4
Skip

Self-reported computer literacy scale item 18

109

Never heard i Not sure what it is 2
Not sure its function3
Know its fuction
4

59

Se'f-reported computer literacy scale item 19

ill

Never heard i Not sure what it is 2
Not sure its function3
Know its fuction
4

60

Self-reported computer literacy scale item 20

ill

Never heard i Not sure what it is 2
Not sure its function3
Know its fuction
4

61

Self-reported compuLer literacy scale item 21

112

Never heard i Not sure what it is 2
Not sure its function3
Know its fuction
4

62

self-reported computer literacy scale item 22

113

i
Never heard
Not sure what it is 2
Not sure its function3
4
Know its fuction

53

self-reported computer literacy scale item 23

1i4

i
Never heard
Not sure what it is 2
Not sure its function3
4
Know its fuction

64

Self-reported computer literacy scale item 24

115

1
Never heard
Not sure what it is 2
Not sure its function3
4
Know its fuction

15W:,

Appendix F

Surrrìary Results

Frequencies of the

Subjects

Responses

to

Different

Options in Each Item

15%

Items I to 29 are items on dernograhic characteristics your interests in attending computer courses. Circle on qutstionnairo the response which is most appropriate to
(cxcept items 11,12,25,28 and 29 where special instructions qIvcn iri tht items)

and the you are Freq
o.
1.
2.
3.

4.

5.
6.

2

Scx

Less
21 26 31 36 41 over

than 21
25
30
35
40
45
45

32.6
53.5

o.

Col of Ed
Cert/Dip.Ed.
Other
No training

1.
2.
9.

0.
1.
2.
3,

4.

Secondary
Post sec
Bachelor
Master
Others

1. English
Chinese
2
3. ?4ath/Sci

4.
5.
6.
7.
8.

Economic
Geog/HIS
Cultral
Tec/Com
C of E Subjs

0.Nil
1.

1 or less

2 - 3
3, 4 - 5
4, 6 - 8
5, 9 * 12
6. 13 - 18
7. 19 or more
2.

15 Ç)

7.3

188
308
17

4. Teacher training

7, Years of teaching experience

36
42

42.5
15.1
42.4

Single
M w/o child

What major subject(s) are you teaching at present? Please specify

149
168
81

245
87
1.
244
2. M w chd(ren)
o.

6

.2

16.7
25.9
29.2
14.1
6.3

44,1
55.9

Female
Male

3_ Mriti1 Status

Hìqhcst Education
(Othur than teacher training)

4

96

254
322

o.
1.

5

%

63
39

112
369
50
6

95
70

188
38
63
49
37
36

3
10.

6.8
19.4
64.1
8.7
1.1

16.4
12.2
32.6
6.6
10.9
8.5
6.4
6.3

4

.7

50
80
68
94
119
91

8.7
13.9
11.8
16.3
20.7
15.8
12.2

70

8.

Percentage of administrative work.

Q.

0%

1.

1 - 10%
11 - 25%
26 - 50% over 50%

2.
3.

4.

9,

Number of courses you have taken in schools. colleges and universities which require the applications of computers in course work.

10. Number of computer courses attended

in schools, colleges and universities

Il. Circle those programming language

you have learnt in schools, colleges and universities.

191
167
126

350
173

2.

3 - 4

3.

5 -. 6

38
10

60.8
30.0
6.6
1.7

4.

7 or more

4

.9

288
245
21
15

50.0
42.5

2.

None
1 - 2
3 - 4

3.

5 ,- 6

4.

7 or more

0.

None
BASIC
FORThAN
COBOL
PASCAL

0.
1.

1.
2.

4.

7

169
166
38
28

6.

Others
(Machine Lang)

0.

None
BASIC
FORTRAN
COBOL
PASCAL

1.
2.

3.
4.

5.RPG

13. How many training courses on computer

9

19

49
.2

4.5

26.7
3.0
1.6
3.3

o

0.

None
1 - 2
3 - 4
5 - 6
7 or more

399
150
15

69.3
26.0
2.6

5
7

1.2

1.

None
1 - 2

2,

3 .- 4

414
125
19

3,

5 .- 6

4.

7 or more

0.

None

Manufacturers ) .

4 .

15. How many books on computer do you have at home?

154
17

29.3
28.8
6.6

Others

1.

14. How many workshops or seminars on computers you have attended in the last 2 years.

i
26

3.6
2.6
1.2

6.

have you attended.(courses which are organised by Education Department,
Associations, or by Computer
Teachers1

38

None i - 2

0.

5.RPG

Circle those programming language you have learnt on your own (rather than in formal education such as in schools, collegess and univerist±es).

22

i.

3.

1.2.

70

33.2
29.0
21.8
12.2

2.
3.

o.

21

3.6
(11611 ,Worksheet, etc.)

1. 1 .- 2

4

2.

3

3.

5 .- 6

4.

7 or more

.9

li

71.9
21.7
3,3
1.2
1.9

264
121
52
37
102

45.8
21.0
9.0
6.4
17.7

7

ib.

HOW mrny computer periodicals
(maqa/ules, journals) do you read monthly ori a regular basis?

o.
1.
2.

None
1 - 2
3 - 4

523

3.5-6
I 7

.

20

.

2L
22.

O

No
Yes

552
24

95.8
4.2

No
Yes

353
223

61.3
38.7

No
Yes

246
330

42.7
57.3

Can you have access to computers other O . No than those mention in questions 18 & 191. Yes
(o.q. computers in the universities or computers owned by your friends)

370
206

64.2
35.8

Excluding ComDuter Studies, do you use computers in teaching other subjects?

No
Yes

518
58

89.9
10.1

Do you use computers in preparing notesO. No test and examine papers?
1. Yes

459
117

79.7
20,3

Arti you a teacher of Computer Studies?

:

Do your have a computer at home ?

0.

Cdn you hove access to computers in your school?

0.

i.

0.
i.

73, Do you use computers in keeping studentO. No

24.

.3
:2

7 Ot more

1.

1),

2
1

4:

1.
18.

8

90.8
7 3
1:4

42

records?

1.

Yes

479
97

83.2
16.8

Aro you interested in attending computer courses for teachers 7

0.

No
Yes

141
435

24.5
75.5

1.

L. your answer to Question 24 is 1tNo" , go to Question 28
25,

the most
Rank order only those courses of interest to you; preferred course a rank of 1, the next most preferred course a rank of 2, etc. . Leave blank those of no interest to you.

Priority

a. History and development of computing

No : 461
Yes : 115

80%
20%

i
2
3
4
5
6
7
8
9

11
18
17
30

2.6
1.4
1.2
1.4
1.9
3.1
3.0
5.2

1

.2

is
8
7
8

b.

Ccuììputer awareness

i
2
3

No: 4H
Yes

C.

165

:

71.4%
28.6%

4
5
6
7
8

Basic skills of computer operations

1
2
3

No
Yes

cL

252
324

:

:

:

:

:

43.9%
56.1%

50.2%
49.8%

Advanced programming

No ; 337
Yes : 239

i
2
3

27
6

191
47
47
15
11
9
3

.5

1

.2

91

15.8
22.9
10.8
6.1
2.1

132
62
35

i

69
97
75
38
33

2
3

4.5
3.8
3.5
4.2
3.0
4.0
4.7
1.0

33.2
8.2
8.2
2.6
1,9
1.6

12
5
1
3

8
2

.9
.2
.5

12.0
16.8
13.0
6.6
5.7
1.4
.3

9

1

.2

1
2
3
4
5
6

4.3
13.4
13.0
11.8
4.0
1.9

7

25
77
75
68
23
11
4

8

4

i

25

3

46
39
56

8.0
6.8

21

3.6
1.2

7
8

16t.

23

5
6
7
8

4
5

58.5%
41.5%

17

4

4
5
6
7

Elementary programming
289
Nb
Yes : 287

g.

40.8%
59.2%

Use of Educational software package surh as CAl arid experimental simulations, etc.
No : 253
323
Yes

C,

4
5
6
7
8

Application of standard software packages such as word processing, electronic worksheet etc.

235
NO
Yes : 341

o,

43.8%
56.2%

26
22
20
24

7

.7
.7

h, Social impacts of computerization

No : 429
Yes
147
:

i
2

2

.3

lO
11
24
29
22
22
27

1.7
1.9
4.2
5.0
3.8
3.8
4.7

i
2

4

.7

3

1
1
2
2

3
4

74.5%
25.5%

5
6

7

8

i, Others (Please specify)

No : 565
11

Yes

26.

:

98.1%
1.9%

4
5
9

:ì

If courses are organised outside normal school hours, which of the following times will be most convenient to you?
a.
b.
c.
a,

Immediately after school, 5 - 7 p.m. on school days 125
In the evenings, 7 - 9 p.m. on school days
44
On Saturdays mornings
114
During long school holidays, for examples, Easter
139
holidays, Christmas holidays or Summer holidays etc..
e. Others (Please specify)
3
27,

28.

How many hours per week are you willing to spend in attending computer course(s)?

1.
2.
3.
4.
5.

0
155
1 - 2 203
3 - 4 184
4 - 6
30
or more 4

21.7
7.6

19.8
24.1
.5

26.9
35.2
31.9
5.2
.7

Circle those area(s) where you believe that computers may be used in teaching.
a.

Enrichment of lessons

344
335
216
243
144
16

b. Drill and practice
c. Simulation of experiments
d. Remedial lesson for less able students
e. Teaching concepts
e..

29.

.2
.2
.2
.3
.3

Others (Please specify)

Circle those area(s) where you believe that help in school administration.
a.

b.
C,
a.
e.

computers

Keeping student records
Processing student reports
Producing statistical informations of students
Processing test and examination papers
Others (please specify)

59.7
58.2
37.5
42.2
25.0
2.8

may

538
500
489
400
30

93.4
86.8
84.9
69.4
5.2

Questions 30 to 40 are statements asking your opinions in the use of computers in classroom teaching and in school administration.
Circle the option which best reflect your opinion to each of the fol Iwoing statements,

SA if
A if
N if
D if
SD if

30.

you you you you you

STRONGLY AGREE with the statment
AGREE with the statment are NEUTRAL about the statment
DISAGREE with the statment
STRONGLY DISAGREE with the statment

believe the use of computers in subjects other than computer studies helps students to better understand the
I

SA
36

A
279

N

D

SD

204

50
8.7

1.2

6.3 48.4 35.4

7

lesson.

In the subjects I teach, computers can be used to take care of the needs of each individual students

4.2 28l 37.7 24.5

SD
32
5.6

32.

Using computers in my teaching can help loss able students to better understand the lessons.

A
N
D
190 203 137
3.5 33.0 35.2 23.8

SD
26
4.5

33,

N
D
can
SA
A
Using
computers in my teaching
69
67 278 146 opportunities for more able provide students to have more in-depth learning 11.6 48.3 25.3 12,0 according to their interests.

SD
16
2.8

34,

Computers can help me to present most of and in a more active lessons my interesting way.

D
N
SA
A
24 164 222 133
4.2 28,5 38.5 23.1

SD

Using computers in school administration is just a fashion.

SA
14
2.4

31.

35*

36.

37,

Computers can make it easier for me to prepare lessons and to set tests and examines. computers are used to keep student records, the effectiveness and efficiency of teaching will be improved by making available statistical information such as the mean and standard deviation of test marks, the comparisions of students performance with different classes and
If

with previous year, etc..

16k.

SA
24

A
162

N
217

D
141

SA
20

SA
54

A

N

34

81

D
308

33

5.7

SD
139

5.9 14.1 53.5 24.1
A
259

N
156

D
91

9.4 450 27.1 15.8
N
A
SA
179 294 93
31.1 51.0 16.1

D
9

1.6

SD
16
2.8

SD
1
.2

*.

Using computers in school administration
SA
N
A
will significantly reduce paper work and 179 300
80
hence increase the efficiency of running 3L1 52.1 13.9

D

SD

15
2.6

2
.3

d SChOOl..
39.

tjsing computers in my daily teaching will only waste my teaching time.

SA
N
A
D
13
72 223 224
2.3 12.5 38.7 38.9

SD
44
7.6

40.

Schoo3 adminstratiorì can be carried out oquatly well with or without computers.

SA
N
A
D
13
85 194 241
2.3 14.6 33.7 41.8

SD
43
7.5

Ttcms 41 to 57 are terminologies, topics about computers of Rate your degree the applications of computers. cmd understanding of these items on a scale of 1 to 4,
L, if you have never heard of it before,

2, if you have heard of it but are not sure what it is,
3, 11 you know what it is but are not sure the details its function,

of

4, if you know what it is and you know the details of its fuctions.

41.

Central Processing Unit (CPU)

1

131
22.7
42.

Magnetic Disc Unit

1

143
24.3
43.

Network

1

155
26.9
44,

45.

46.

Operating System (oS)

i

140
24.3

Byte

program file, Data file

i

208
36.1
i

115
20.0

2

114
19.8
2

157
35.1
2

201
34.9
2

202
35.1
2
90

15.6
2

165
28.6

3

182
31.6
3

153
26.4
3

148
25,7
3

152
26.4
3

139
24.1
3

152
26.4

4

149
25.9
4

82

14.2
4
2

12.5
4

82

14.2
4

139
24.1
4

144
25.0

47.

48.

49,

ASCII Code
(American Standards Code for
Information Interchange)
Lockword/password

RAM (Random Access Memory)

i

2

3

4

349

80

57
9.9

90
15.6

606

139

236
41.0

1.2

i

Database

1

51

Compilers

Proqramming Language

12.2

54*

CAl/CAL
(Computer Assisted Instruction/Learning

i

256
44.4

280
48.6
55.

56.

57.

Artiflical Intelligence

The threat to individua1s due to computerization.

privacy

3

122
21.2

175
30.4

146
25.3

i
325
56.4

116
20.].

91
15.8

4
69

12.0
4

152
26.4
4
79

13.7
4
77

13.4
4

1

2

3

83

14.4
4

3

2

142
24.7

16.1

3

2

172
29.9

173
30.0

16

3

110
19.1

2

97
16,8

93

3

17
30.7

2

131
22.7

i

Computer crime

109
18.9

2

177
30.7

i

Easy Pay System (EPS)

114
19.8
3

156
2.1

135
23,4
4

3

195
33.9

1

70

53*

20.

146
25.3
4

10
18.6

2

1

242
42.0
52.

119

2

174
30.2

95

16.5
3

2

215
37.3
50.

99

174
30.2

44
7.6
4

87
15.1

Items 58 to 64 are procedures of operating a computer system or performing a computer related job. Rate your degree of confidence in carrying out the specified task on a scale of 1. to
4,

it

if you have never tried it before,

2, if

you have done it before but cannot remember how do it now,

3, if

you know how assistances, to do it

but you

may need

to

some

4, iE you have confidence in carrying it out.
58

59,

60.

61.

62.

63.

64.

Switch on a micro-computer system or thel terminal of a computer system and checkl3l
227
whether or not it is ready for use. load and run a program from i storage devices, for example, 170
29,5
disc, tape, etc. .

2

148

Select,

2

backing

96

Write a simple program to do a specified i
237
task and run the program

16.7
2

Recognise any error(s) in a program, next 1 and then rerun the24l correct the program,
41.8
revised program.

122
21.2

the components of a micro- 1 computer system (monitor, disc drive,327 printer,etc.), to the central processing56.8 units. Connect up

out software packages the manual.

Try

16

according

to 1
292
50.7

2

16.0

2

131
22.7
4

120
20.8

93

16.1
4

3

66
11.5

184
31.9
4

92

3

2

234
40.6
4

126
21.9
3

4L1

a computer file from one device to 1 from one disc to another3l
e.g.,
another;
55.0
disc or from a disc to a tape, etc. .

126
21.9
3

116
20.1

Copy

4

3

85

68

ll8

125
21.7
4

3

62
10.8

61
10.6

126

2

3

4

77

88

13.4

15,3

2L9

119
20.7

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(ul41I&IIl