Directory UMM :Data Elmu:jurnal:I:Information and Management:Vol37.Issue4.Jun2000:
Information & Management 37 (2000) 169±180
Computer attitudes of non-computing academics:
a study of technical colleges in Brunei Darussalam
Afzaal H. Seyal1, Md. Mahbubur Rahim*, Mohd. Noah Abd. Rahman
Department of Computing and Information Systems, Institute Technology Brunei, Permanent Campus,
Tungku Link, BSB, BE 1410, Brunei Darussalam
Received 29 October 1998; accepted 29 July 1999
Abstract
Current information systems (IS) literature has paid considerable attention to measuring the computer attitudes of students
and schoolteachers. Computer attitudes of non-computing academics working particularly in technical colleges have, however,
received scant attention. Moreover, studies on computer attitudes among Asian academics are least reported. Keeping this in
view, this study was undertaken by validating an instrument to measure computer attitudes of non-computing academics
working among technical colleges in Brunei Darussalam. This study also identi®ed factors that contributed to the formation of
computer attitudes of academics. This was achieved by undertaking a survey of 192 non-computing academics from four
technical colleges. Attributes related to demographics and education of academics appeared to have little impact on computer
attitudes. In contrast, ownership of a personal computer (PC) and level of computer skill were found to be important. # 2000
Elsevier Science B.V. All rights reserved.
Keywords: Computer attitudes; Non-computing academics; Technical colleges
1. Introduction
Academic institutions now seek to put a computer
on the desk of all their staff [29]. In the past, academics used computers primarily to perform administrative tasks, like compiling students' results and
monitoring students' in-class progress. Recently, the
concept of using computers has moved beyond this.
For instance, several educational institutions in the US
have embraced computers in the class rooms, and most
*
Corresponding author. Fax: 673-2-249036.
E-mail addresses: [email protected] (A.H. Seyal),
[email protected] (M.M. Rahim)
1
Fax: 673-2-249036.
American teachers regard computer as much a part of
the classroom as a blackboard [48].
Despite the tremendous educational opportunities,
its potential is yet to be fully utilised. Gilbert [15]
found that many academics are reluctant to move
beyond word processing, while Wilkins and Nantz
[54] discovered that teaching uses of the computer
network remained low and perceived future use was
also low. One plausible explanation is that substantial
investment that has already been made in more traditional methods of instruction [27]. More importantly
computerisation has brought in anxiety and threats to
some teacher's [3] and some educators believe that
computers may fail to have an impact on classroom
instruction [51]. Consequently, the provision of com-
0378-7206/00/$ ± see front matter # 2000 Elsevier Science B.V. All rights reserved.
PII: S 0 3 7 8 - 7 2 0 6 ( 9 9 ) 0 0 0 4 5 - 2
170
A.H. Seyal et al. / Information & Management 37 (2000) 169±180
puter technology is not a suf®cient condition for its
success in an educational setting.
A formidable body of literature exists on the computer attitude of school teachers and there is also some
literature on the attitude of university faculty
[19,26,43]. Little is, however, known regarding the
computer attitude of academics working in technical
colleges. From these studies, it is argued that the
quali®cations, working experiences and interests of
academics may affect the attitude towards computer.
But none of these studies suggests about the attitude of
academics employed in technical colleges and are
likely to differ from those of schoolteachers and
faculty members. Thus, academics in technical colleges may develop different views and attitudes
towards computers as compared to those of their
counterparts. There is need to study this aspect in a
new geographical setting.
An overwhelming majority of existing studies were
undertaken in western countries. Thus, their results
may not be applicable to an Asian country like Brunei
Darussalam, which is culturally different from the
western world. It is a small sultanate located on the
north west coast of Borneo island with a total population of nearly 0.3 million [4]. Its' main economic
activity is dominated by the oil and gas sector, and
gross domestic product per capita was B$ 23,865
(US$1 1.58) in 1994. After achieving its independence in 1984, the government placed considerable
importance on technical education. Two engineering
colleges, one vocational college, and a technical institute were established to produce technologically
oriented professionals at various levels. The government also recognised the need for broader use of
computer technology in the public sector. As such,
the Information Technology Division (ITD) was set up
to oversee and to support the development of IT
projects in the public sector in schools and technical
colleges. Against this background, a study was undertaken in late 1997 to examine the computer attitudes of
non-computing academics from four different technical colleges.
2. Objectives of study
The central intent of this study was to examine the
computer attitudes of non-computing academics
working in technical colleges in Brunei Darussalam.
There were two speci®c objectives
1. To develop and validate a suitable instrument to
measure computer attitudes of non-computing
academics.
2. To identify the factors that significantly affects
computer attitudes of these academics.
3. A review of literature
Literature on computer attitudes can be broadly
divided into three groups, depending on the type of
the target population for whom attitudes were measured. The ®rst group deals with the measurement of
computer attitudes of primary and secondary school
students. The works of Harvey and Wilson [20], Siann
and Macleod [46], Levin and Gordon [30], Martin
[33], and Moore [34] fall in this group. Some authors
like Koohang [28] and Finnegan and Ivanoff [11] have
also studied computer attitudes of students studying in
higher institutions.
The second group of studies has focused on schoolteachers. This group includes the works of Katz and
Francis [26] and Savenye et al. [43] among others.
While limited studies are available for the third group,
which address the computer attitudes of university
faculty members. Recently, Harris [19] has made a
valuable contribution by measuring computer attitudes of academics in a Hong Kong university. The
attitude studies were hot however con®ned to students
and academics, some authors like Gattiker and Hlavka
[14], Nickell and Seado [35], Culpan [8], and Winter
et al. [53] made attempts to measure computer attitudes of people working in business settings.
The studies also identi®ed a variety of factors that
affect the attitudes of subjects (students, teacher's
etc.). Some of the frequently reported factors include
gender, age, personality, prior computer training, computer literacy, and computer experience among others.
A brief summary of these is provided in Table 1. More
effort was spent on examining the in¯uence of gender
on the computer attitudes of students and teachers.
Computer literacy has also received considerable
attention. Relatively, less attention was paid to teaching experience and level of computer skill of individuals.
A.H. Seyal et al. / Information & Management 37 (2000) 169±180
171
Table 1
A summary of factors affected computer attitudes
Factors
Source
Subject
Computer Literacy
Hignite and Echternacht [21]
Woodrow [56]
Loyd and Gressard [31]
Simon and Wilkes [47]
Al-Jabri et al. [1]
Business education teachers
Student teachers
Teachers
Participant of computer literacy course, business major
Undergraduate university business students
Age
Gender
Woodrow
Savenye et al. [37]
Woodrow
Kay [27]
Robertson et al. [42]
Shashanni [45]
Student teachers
Pre-service teachers
Student teachers
Education students
Student teachers
Secondary school students
Teaching experience
Personal locus
Computer Ownership
Wilson [55]
Kay
Ray [41]
Gattiker & Hlavka [14]
Nickell & Seado [35]
Harvey & Wilson [20]
Al-Jabri et al.,
Students
Education students
Business owners
University students enrolled in computer course
Business managers
Primary & sec school pupil
Undergraduate university business students
Prior Training
Nickell and Seado
Igbaria [23]
Harris [19]
Harris
Business managers
Business managers/part-time MBA students
Faculty members
Faculty members
Organisational culture
Task characteristics
4. The research model and development of
hypotheses
On the basis of a review of existing literature, a normative model was developed. It is presented in Fig. 1.
Gender: The impact of gender on the formation of a
person's computer attitude is still a matter of debate.
Some authors like Perolle; [38] and Mankin et al. [32]
have reported gender difference in computer attitude
in various work settings. Barrier and Margavio [2],
who studied gender issues by using the attitude toward
computer usage scale (ATCUS) and found that more
males exhibited negative computer attitude; have
reinforced their ®ndings. On the other hand, Stasz
and Shavelson [49] reported little gender difference in
a study of computer attitude among teachers. Thus, the
following hypothesis is postulated
Hypothesis 1. There exists a relationship between
gender and academic computer attitudes.
Age: Several researchers have examined the
impact of age on a person's computer attitude. Jay
and Willis [24] reported that young males have
most favourable predisposition towards computer.
Moreover, Kay identi®ed age as an important
variable while assessing the positive attitude
towards computer use. This leads to the following
hypothesis
Hypothesis 2. There exists a relationship between
age and academic computer attitudes.
Educational quali®cation: Several researchers
have highlighted the importance of education of
academics on their computer attitudes. For instance,
Dugan and Thurlow [9] suggested that educational
level is likely to have an effect on one's attitude
towards computer use. Those who are better educated
are more favourably disposed to rapid advance in
technology. Kay has reported that people with higher
educational quali®cation have favourable predisposition to computer use, while Hignite and Echtenacht
[21] found that education effect computer attitude of
business education teachers. Thus, the following
hypothesis is postulated
172
A.H. Seyal et al. / Information & Management 37 (2000) 169±180
Fig. 1. Research model.
Hypothesis 3. There exists a relationship between
educational qualification and academic computer
attitudes.
Teaching experience: Existing literature offers little
information about the impact of teaching experience
on academic computer attitude. A few studies however
provide some indication that beginning teachers in UK
schools use computers in their classrooms much less
than expected. For instance, HMI [22] found that less
than 6% of beginning teachers in UK schools used
computer in their ®rst year of teaching, while fewer
than 20% of the beginning school teachers were found
to be prepared to use computer in their classrooms
[18]. Maybe, computer awareness will grow with time.
The following hypotheses is postulated
Hypothesis 4. There exists a relationship between
years of teaching experience and academic computer
attitudes.
Personal computer ownership: Literature strongly
suggests that ownership of a PC is related to a favourable attitude. For example, Pfeffer and Lawles [39],
Steers and Porter [50], Harvey and Wilson [20] and
Noe [36] have shown the differences in attitude
between owners and non-owners of computer, with
owners having a more positive attitude. Gattiker and
Hlavka [14] have shown that individual's attitude to
computer usage depends on ownership of a computer.
Thus
Hypothesis 5. There exists a relationship between
173
A.H. Seyal et al. / Information & Management 37 (2000) 169±180
ownership of personal computer and academic computer attitude.
Prior computer training: Several authors have studied the relationship between a person's prior training
in computers and his/her subsequent attitude. Clarke
and Chamber [6] have shown the signi®cance of prior
computing training on the person's attitude, while
Dupagne and Krendl [10] have found that computer
literacy courses greatly improve teachers' attitudes.
Based upon this rationale, the following hypothesis is
proposed
Hypothesis 6. There exists a relationship between
previous training in computer and academic computer
attitudes.
Computer skill: The skill of academics in using
personal computers may have some in¯uence on their
computer attitudes. Less skilled academics may
develop anxiety; then they view the computer with
scepticism. This assertion is partially supported by
Loyd and Gressard [31] who reported that the subjects
participating in their study developed a more positive
attitude once they achieved a certain level of computer
skill. Thus, the last hypothesis
Hypothesis 7. There exists a relationship between
level of computer skill and academic computer attitudes.
used to measure computer skill and teaching experience. The measure of the dependent variable (computer attitude) used the de®nition of attitude suggested
by Fishbein and Ajzen [12]: as a learned predisposition to respond in a consistently favourable and unfavourable manner with respect to a computer. This is a
multi-dimensional psychological concept, with multiple items required to capture a psychological factor
like computer attitude Nunnally [37]. A set of 27 items
was initially selected from the literature to measure
computer attitudes of academics. Each academic was
asked to indicate their level of agreement/disagreement with each statement on a ®ve-point Likert scale,
where 1 stands for strongly disagree, 2 for disagree, 3
for undecided, 4 for agree and ®nally 5 stands for
strongly agree. A summary of the de®nitions and
scales is provided in Table 2.
5.2. Population
The study employed a survey approach to examine
computer attitudes of non-computing academics. The
target population was the non-computing academics
working among at technical colleges in Brunei Darussalam. The number of academics in all these technical colleges was reported to be 340. Telephone
contacts with the Head of these colleges revealed a
total of computing staff. Thus, the target population
was reduced to 300.
5. Research methodology
5.3. Instrument validation
5.1. Design of instrument
An initial version of the instrument was developed
in two parts: Part A collected demographic information, computer exposure, and educational attributes,
while Part B contained 27 items to measure computer
A variety of scales were used to measure these seven
independent variables. A ®ve-point Likert scale was
Table 2
A summary of research variables
Factors
Definition
Scale
Computer attitude
Gender
Age
Educational qualification
Teaching experience
PC ownership
Prior Computer training
Computer skill
A disposition to respond favourably to a computer.
Sex of an academic
No. of years since birth
Highest academic award received from a university/institution.
Number of years involved in teaching on a full time basis.
The availability of a personal computer at home for his/her exclusive use.
Whether he/she has formally attended training on computer or related subject.
The level of competence possessed while working with a PC
Five-point Likert
Dichotomous
Categorical
Categorical
Five-point interval
Dichotomous
Dichotomous
Five-point interval
174
A.H. Seyal et al. / Information & Management 37 (2000) 169±180
attitudes. These items were carefully selected after
reviewing existing literature. The works of by Selwyn
[44], Francis [13], Jones and Clark [25], Popovich
[40], and Gressard and Loyd [16] were found to be
particularly useful. This initial instrument was pretested using several academics chosen randomly from
two colleges located in close proximity of the authors'
work place. The participating academics were asked
to comment on the format and appropriateness of
questions and to suggest additional items that they
believed should be included in the instrument. In view
of their suggestions, several amendments were incorporated into the instrument, which greatly improved
its clarity.
The revised instrument was further pilot tested
among 32 academics selected from three colleges.
The responses obtained from the pilot test for Part
B, were analysed for accuracy using Churchill's item
puri®cation technique [5] and exploratory factor analysis [52]. Using Churchill suggestions, 11 items were
eliminated for which `corrected-item-total' correlation was less than 0.30. While exploratory factor
analysis eliminated those four items that loaded on
more than one factor at 0.40 or greater. Thus, these
multiple phases of instrument development and testing
produced a 12-items instrument for measuring computer attitudes, and thus established an initial content
validity. Table 3 illustrates these 12 items, and their
corresponding corrected item-total correlation and
Varimax factor loadings.
The pilot study proved very effective in eliminating
ineffective items, as well as generating a ®rst set of
constructs. Following the pilot study, the instrument
was restructured and distributed to the remaining 268
non-computing academics. A total of 192 responses
were received; making a response rate of 71% ± which
is exceptional. After the pilot study, the researchers
were still uncertain about the attitude construct. Traditional factor analysis was used to further explore
factor structure; this retained all 12 items. Principal
component analysis was used as the means of extraction and varimax was used as the method of rotation
that grouped these 12 items into three factors. The
Kaiser Meyer±Olkin measure of sampling was 83%.
In this connection, several decision rules based on
Hair et al. [17] were used to aid extraction process and
to derive these three factors. These rules include (a)
minimum Eigenvalue of 1.0, (b) simplicity of factor
structure, and (3) exclusion of single item factor from
the standpoint of parsimony. The three factors were
named as perceived usefulness (Factor 1), affective
(Factor 2), and perceived behaviour (Factor 3). These
12 items, together with their corresponding factor
loading, are shown in Table 4. This reveals that the
factor loading is quite high and range from 0.49 to
0.81; the three factors together explained 57.4% of
total variance.
In factor analysis, it is generally desirable to have a
larger number of respondents than items. The ratio of
sample size to number of items was (16 : 1), which is
above the (10 : 1) ratio suggested by Nunnally.
Furthermore, the derived instrument was tested for
reliability. Chronbach's [7] Alphas were calculated for
the overalls instrument, as well as for each of the three
Table 3
List of items retained during pilot study
No.
Items
Corrected itemtotal correlation
Factor
loadings
1
2
3
4
5
6
7
8
9
10
11
12
Computer facilitates my teaching
Computer helps me in designing better and effective assignments for student
My assignment always requires my students to use a computer
I use a computer to organize my administrative work
Computer knowledge is essential for modern life
Technical teaching without computer is unthinkable now-a-days
I think that the challenges of teaching using computers is exciting
I think that working on a computer is a good way to use my spare time.
Using a computer makes me feel creative
I think that learning to use a computer needs a lot of patience
I would like to learn about the computer only if it is essential for my promotion
I will do as little work with a computer as possible
0.74
0.63
0.32
0.76
0.65
0.77
0.69
0.54
0.51
0.56
0.36
0.31
0.74
0.75
0.49
0.65
0.69
0.72
0.55
0.81
0.72
0.64
0.81
0.80
175
A.H. Seyal et al. / Information & Management 37 (2000) 169±180
Table 4
Varimax rotated factor loading and Eeigenvalues with variance explaineda
No.
Item description
Factors
1
Perceived usefulness (6 items)
Computer facilitates my teaching
Computer help me in designing better and effective assignment for student
My assignment always require my students to use computers
I use computer to organise my administrative work in a better way
Computer knowledge is essential for modern life
Technical teaching without computer is unthinkable now-a-days
Affective component (4 items)
I think that the challenges of teaching using computers is exciting
I think that working on computer is a good way to spare time.
Using computer makes me feel creative
I think that learning computer needs a lot of patience
Perceived behaviour (2 items)
I would like to learn about computer only if it is essential for my promotion
I will do as little work with computer as possible
Eigenvalue
% of variance
1
2
3
4
5
6
7
8
9
10
11
12
a
2
3
0.74
0.75
0.49
0.65
0.69
0.72
0.55
0.81
0.72
0.64
0.25
35.5%
1.57
13.1%
0.81
0.80
1.05
8.8%
Note : Factor 1 refers to perceived usefulness, Factor 2 refers to affective component, and Factor 3 refers to perceived behaviour.
factors and are presented in Table 5. The alpha is
considered satisfactory.
6. Results
Data obtained from the survey were analysed using
w2-tests as well as multiple regression by means of
SPSS, a well known statistical package.
6.1. Background profile
The background of the participating academics is
summarised in Table 6. The dominance of males is
clear. This is not unexpected, because nearly 80% of
the academics working in the university as well as
technical and vocational colleges are male's [3]. A
majority (71%) of the participating academics fell in
the age group of 30±50 years. With the exception of
doctorate holders, highest educational quali®cations
of these academics varied uniformly. This is possibly
because, unlike universities, academics in technical/
vocational colleges are not required to possess Ph.D.
Degree in their disciplines. Academics with 10±20
years of teaching experience slightly dominated the
sample. Only 17% academics can be considered
novice, with less than 5 years of teaching experience.
Another interesting ®nding is that most academics
(79%) owned a PC. Apparently academics showed
keen interest in a PC to perform work at home. Not all
these academics however had equal computer skills.
Only 11% reported having a high level of computer
Table 5
Results of reliability analysis
Factors
No. of statements
Reliability coefficient (a)
Factor 1: perceived usefulness
Factor 2: affective
Factor 3: perceived behaviour
Overall
6
4
2
12
0.79
0.71
0.60
0.79
176
A.H. Seyal et al. / Information & Management 37 (2000) 169±180
Table 6
Background profile of the academics
Academics
Number
(%)
Gender
Male
Female
147
45
76
24
Age
Less than 30 years
Between 30±50 years
Over 50 years
28
137
27
15
71
14
Educational qualification
Diploma
Bachelor
Masters
Ph.D.
Others
46
51
49
8
38
24
27
25
4
20
Teaching experience
Less than 5 years
Between 5±10 years
Between 10±20 years
Over 20 years
32
51
65
44
17
26
34
23
PC ownership
Own one
Does not own
151
41
79
21
Prior PC training
Yes
No
40
152
21
79
PC skill
High
Above average
Average
Below average
Low
21
30
95
30
16
11
16
49
16
8
skill. Moreover, only one-®fth of the academics (21%)
actually attended any formal training on the computer.
In summary, even though a majority of the participating academics owned a PC, their skill was not high. In
fact, half of the academics only felt they had computer
skill and most did not receive any formal training.
6.2. Computer attitudes
The 12 statements that were grouped into three
factors (via factor analysis) were used to solicit the
attitudinal views held by the academics. They were
asked to indicate their level of agreement/disagreement with each statement on a ®ve-point Likert scale.
Their responses were compiled, and a mean rating for
each statement was computed. These are listed in
Table 7. The mean rating for each of these statements
lie above the 'neutral' position (3.0) on the Likert
scale.
The mean attitude score of these two groups were
also computed, and were tested for signi®cant difference. Results of t-test (t 13.29, df 190, p 0.000)
indicate that difference in attitude score between those
academics having positive attitudes (n 163), and
academics with negative attitudes (n 29) is statistically signi®cant at the 5% signi®cance level Table 8.
6.3. Test of hypotheses
The impact of academic gender, age, quali®cation,
teaching experience, PC ownership, computer skill,
and prior computer training, on the dependent variable
Table 7
Mean rating received by each attitude statement
No.
Items
Mean
1
2
3
4
5
6
7
8
9
10
11
12
Computer facilitates my teaching
Computer helps me in designing better and effective assignments for student
My assignment always requires my students to use a computer
I use a computer to organise my administrative work
Computer knowledge is essential for modern life
Technical teaching without computer is unthinkable now-a-days
I think that the challenges of teaching using computers is exciting
I think that working on a computer is a good way to use my spare time.
Using a computer makes me feel creative
I think that learning to use a computer needs a lot of patience
I would like to learn about the computer only if it is essential for my promotion
I will do as little work with a computer as possible
4.04
4.04
3.01
3.91
4.30
3.60
4.01
3.51
3.79
4.04
3.81
3.69
177
A.H. Seyal et al. / Information & Management 37 (2000) 169±180
Table 8
Attitude summary
Attributes
Values
No. of academics with positive attitude
No. of academics with negative attitude
Average attitude score for all academics (n 192)
Average attitude score for academics having positive
attitude (n 163)
Average attitude score for academics having negative
attitude (n 29)
163
29
45.7
47.6
35.2
Table 9
Results of multiple regression analysis
Variables
b
Educational qualification ÿ0.504
Age
ÿ0.852
PC ownership
ÿ2.84
Gender
1.438
Prior computer training
ÿ0.605
Computer skill
0.943
Teaching experience
ÿ0.266
R2 (adj) 0.169
SE 5.97
*
only two hypotheses (e.g., Hypothesis 5 and 7) were
supported.
w2-tests at the 5% signi®cance level were performed
to examine if there exist any relationships between the
seven independent variables and the dependent variable. The results shown in Table 10, clearly indicate
that, except for PC ownership and computer skill, all
the remaining ®ve variables have no signi®cant relationship with academics computer attitude. This
observation further reinforces the ®ndings of the
regression analysis.
7. Discussion
b
ÿ0.110
ÿ0.121
ÿ0.182
0.095
ÿ0.038
0.153
ÿ0.042
F 5.26
p-value
0.110
0.263
0.014*
0.191
0.577
0.037*
0.694
p 0.000
Indicates statistical significance at (p < 0.05).
were investigated using multiple regression analysis.
The results, as presented in Table 9, explain 17%
variance in the dependent variable, and partially support the model. Out of the seven independent variables, only two, such as PC ownership and computer
skill were found to have signi®cant standardised
regression coef®cients, and were related to academics'
computer attitude. On the other hand, variables like
gender, age, quali®cation, teaching experience, and
prior computer training had little signi®cant impact on
the formation of an academic's attitude. Therefore,
Several important ®ndings have emerged from this
study. First, a set of 12 statements grouped into three
factors was identi®ed. This produced a valid instrument to measure computer attitude of non-computing
academics. This instrument is shorter than some of the
existing ones. For instance, Selwyn's instrument contained 21 statements that were grouped into four
factors, while Popovich et al used instrument in which
40 statements were reduced to 20 items that were also
grouped into ®ve factors. The three factors as generated by this study were in line with those reported by
Selwyn, and differ considerably from those ®ve
reported by Popovich et al. In short, these 12-item
instruments are likely to be easily accepted by academics, as it required less time for them to respond.
Second, the mean score of the participating academics against each statement was well over the
neutral value. This indicates that academics in general
did not hold any unfavourable views about computer
use. Moreover, the average overall attitude score of
47.6 is reasonably high.
Table 10
Relationship between computer attitude and independent variables
Hypothesis
Relationship
w2 value
P-value
Remarks
H1
H2
H3
H4
H5
H6
H7
Gender has relationship with academics' computer attitude
Age has relationship with academics' computer attitude
Educational qualification has relationship with academics' computer attitude
Teaching experience has relationship with academics' computer attitude
PC ownership has relationship with academics' computer attitude
Prior computer training has relationship with academics' computer attitude
Computer skill has relationship with academics' computer attitude
0.731
6.35
6.29
7.13
11.20
2.27
10.46
0.393
0.095
0.178
0.060
0.000*
0.131
0.033*
No support
No support
No support
No support
Support
No support
Support
*
Indicates statistical significance (at p < 0.05).
178
A.H. Seyal et al. / Information & Management 37 (2000) 169±180
Third, a majority of the participating academics
(79%) were found to own a PC. A verbal discussion
with some participating academics revealed that many
of them do not have a PC on their own desk for their
exclusive of®ce use. This constraint encouraged them
to own a PC at home. However, this ®gure is quite high
even in comparison to developed nations. For instance,
Gilbert reported that little over 50% of all higher
educational faculties in US now have their own PC.
Even though a vast majority of the academics in
Brunei owned a PC, nearly half of the academics
(49%) had average level of computer skill. Surprisingly, most academics did not take any formal computer related training.
Fourth, multiple regression analysis identi®ed two
variables (PC ownership and computer skill) that
affect computer attitude of academics. The PC ownership is a signi®cant variable and is supported by the
authors from various countries. Several authors like
Harvey and Wilson (UK), Gattiker and Hlavka
(Canada), Nickell & Seado (USA) and Al-Jabri
et al. (Saudi Arabia) provided strong support that
computer owner have a more positive attitude than
non-owners. In a similar fashion, level of computer
skill of academics was also found to affect attitude.
This ®nding is consistent with that of Loyd and
Gressard (USA), Woodrow (Canada), Simon &
Wilkes (USA), DorenKamp (Holland), Drundell &
Thomson (Scotland) and Al-Jabri et al. (Saudi Arabia)
who reported that subjects participating in his study
tended to produce a positive attitude after attaining
a certain level of skill. Thus, these two ®ndings seem
to be consistent across various geographical boundaries. Furthermore, ownership of PC and computer
skill of academics together explained 17% variation
in computer attitude. The low value suggests that this
study did not include some important independent
variables that have signi®cant impact on computer
attitudes of academics.
8. Conclusions
This study has produced a reliable instrument to
measure computer attitude of non-computing academics working in technical colleges. Using this
instrument as a tool, this study further highlighted
the prevalence of favourable computer attitudes
among these academics. Thus, it can be suggested
that, these academics are likely to have little resistance, if college authorities decide to introduce new
course structure in order to make use of new innovations like multimedia technology. The introduction of
such new courses would provide tremendous improvement in the ®eld of educational computing, provided
the participation of academics in course design and
implementation is encouraged.
College authorities should attempt to provide a PC
on the desk of each academic and encourage them to
use them not only for administrative tasks, but to help
in teaching. Authorities should make considerable
investment in educational computing. Any effort will
not however, be successful without proper training.
The ®ndings of this study bear implications for
three groups of people: academics, professional trainers and business managers. Academics could be
trained for computer-based teaching, learning and
operating computer-based classrooms and laboratories. The prevalence of favourable attitude would
thus in¯uence academics' use of these concepts and
skills. Academics could even explore the possibility to
offer computer-based distance learning programmes.
They could even contribute in developing specialised
educational computer packages in close collaboration
with IT vendors to meet the educational requirements
of students. On the other hand, managers in large
corporations should re®ne their existing manual-based
training and professional development activities with
computers. Managers are also encouraged to liase with
academics; these managers should send their trainers
to academia in order to gain ®rst-hand experience on
how to introduce and use computing facilities in
classrooms. Lastly, IT vendors and academics should
work together in promoting their educational computing products, and to train the users. They should
develop the seminar and research based courses that
not only include the use of the computer in the classroom, but also concentrate on the effects computer
have on learning and schooling from sociological,
psychological and conceptual perspectives.
References
[1] M. Al-Jabri, A.M. Al-Khaldi, Effects of user characteristics
on computer attitudes among undergraduate business student,
Journal of End User Computing spring, 1997, 16±21.
A.H. Seyal et al. / Information & Management 37 (2000) 169±180
[2] T. Barrier, T. Margavio, Pretest-Posttest measure of introductory computer students' attitudes toward computers,
Journal of Information Systems Education 5/3, 1992, pp.
53±58.
[3] M. Bell, The importance of IT education and training,
Computer Bulletin, BCS, February 1995.
[4] Brunei Darussalam Statistical Yearbook, Statistic Review
Economy, Economy Planning Unit, Ministry of Finance,
Brunei, 1993.
[5] G.A.J. Churchill, A paradigm for developing better measures
of marketing constructs, Journal of Marketing Research, XV
February, 1979, 64±73.
[6] V.A. Clarke, S. Chamber, Gender based factor in computing
enrollments and achievement: evidence from a study of
tertiary student, Journal of Educational Computing Research
5, 1989, pp. 409±429.
[7] L.J. Cronbach, Coefficient alpha and the internal structure of
test, Psychometrika 16, 1951, pp. 297±334.
[8] Oya. Culpan, Attitudes of end-users towards information
technology in manufacturing and service industries, Information & Management 28, 1995, pp. 167±176.
[9] J.F. Dugan, G.R. Thurlow, Students' attitudes to mathematics:
a review of the literature, Australian Mathematics Teachers
45, 1989, pp. 8±11.
[10] M. Dupagne, K.A. Krendl, Teacher's attitude toward
computers: a review of the literature, Journal of Research
and Computer Education 24, 1992, pp. 420±429.
[11] D.J. Finnegan, A. Ivanoff, Effects of brief computer training
on attitudes toward computer use in practice: an educational
experiment, Journal of Social Work Education 27, 1991, pp.
73±82.
[12] M. Fishbein, I. Ajzen, in: Belief, Attitude and Behaviour: An
Introduction to Theory and Research, Addison-Wesley,
Reading, MA, USA, 1975.
[13] L.J. Francis, Measuring attitude toward computer among
undergraduate college student: the affective domain, Computer Education 20, 1993, pp. 251±255.
[14] E. Gattiker, A. Hlavka, Computer and attitudes and learning
performance issues for management educational and training,
Journal of Organizational Behaviour 13, 1992, pp. 89±101.
[15] S.W. Gilbert, Technology and the changing academy, Change,
Sept/Oct, 1995, 58±61.
[16] C. Gressard, B. Loyd, Validating studies of a new computer
attitude scale, Australian Education Data Systems Journal 18,
1986, pp. 295±301.
[17] J.F. Hair, R.E. Anderson, R.L. Tatham and W.C. Blake, in:
Multivariate Data Analysis, 4th edn., Prentice Hall, Englewood Cliff, NJ, USA, 1995.
[18] M. Handler, D. Marshall, Preparing new teachers to use
technology: one set of perception, in: Technology and
Teacher Education Annual, Association for Advancement of
Computing in Education, Charlottesville, USA, 1992, 386±
388
[19] R. Harris, Teaching, learning and information technology:
attitudes towards computers among Hong Kong's faculty,
Journal of Computing in Higher Education 9 (1), 1997, pp.
89±114.
179
[20] T.J. Harvey, B. Wilson, Gender differences in attitudes
towards microcomputers shown by primary and secondary
school pupils, British Journal of Education and Technology 3,
1985, pp. 183±187.
[21] M.A. Hignite, L. Echternacht, Assessment of the relationships
between the computer attitudes and computer literacy levels
of prospective educators, Journal of Research and Computer
Education 24, 1992, pp. 381±391.
[22] The New Teacher in School, Report of HMI, HMSO, London,
1988.
[23] M. Igbaria, A. Chakrabarti, Computer anxiety and attitudes
towards microcomputer use, Behaviour and Information
Technology 9 (3), 1990, pp. 229±241.
[24] G.M. Jay, S.L. Willis, The elderly's attitudes toward
computers: a select review of the literature, Gerontological
Society of America, Chicago, IL, 1986.
[25] T. Jones, V.A. Clarke, A computer attitudes scale for
secondary student, Computer Education 22, 1994, pp. 315±
318.
[26] Y.J. Katz, L.J. Francis, Personality, religiosity and computer
oriented attitudes among trainee teachers in Israel, Computers
in Human Behavior, 1993 (in press)
[27] R.H. Kay, Predicting student teacher commitment to the use
of computers, Journal of Educational Computing Research 6,
1990, pp. 299±309.
[28] A.A. Koohang, A study of the attitudes of pre-service
teachers toward the use of computers, Educational Communications Technology Journal 35 (3), 1987, pp. 145±149.
[29] R.L. Lancester, D.D. Strouble, One's university's approach to
the requirements of academic computing, Journal of Systems
Management March 19, 1992, pp. 20±31.
[30] T. Levin, C. Gordon, Effect of gender and computer
experience on attitudes, Journal of Educational Computing
Research 5, 1989, pp. 68±88.
[31] B.H. Loyd, C. Gressard, The effects of age, sex and computer
experience on computer attitude, Association Educational
Data System Journal 18, 1984, pp. 67±77.
[32] D. Mankin, T.K. Bikson, B.A. Gutek, Factors in successful
implementation of computer based office information systems: a review of the literature with suggestion for OBM
research, Journal of Organizational Behavior 6, 1986, pp. 1±
20.
[33] R. Martin, School children's attitudes computers as a function
of gender, course subjects and availability of home computers, Journal of Computer Assisted Learning 7, 1991, pp. 187±
194.
[34] J.L. Moore, Development of a questionnaire to measure
secondary school pupils, attitudes to computers and robots,
Educational Studies 11, 1985, pp. 33±40.
[35] G.S. Nickell, P.C. Seado, The impact of attitudes and
experience on small business computer use, American Journal
of Small Business, Spring, 1986, 37±48.
[36] R.A. Noe, Training attributes and attitudes: neglected
influences on training effectiveness, Academy of Management Review 11, 1986, pp. 736±749.
[37] J.C. Nunnally, in: Introduction to Psychological Measurement, McGraw-Hill, NY, 1970.
180
A.H. Seyal et al. / Information & Management 37 (2000) 169±180
[38] J.A. Perolle, Computers and Social Change, Wadsworth,
Belmont, CA, 1987.
[39] J. Pfeffer, J. Lawler, Effects of job alternative extrinsic
rewards and behavioral commitment on attitude toward the
organization, Administrative Science Quarterly 29, 1980, pp.
550±572.
[40] P.M. Popovich, R.H. Karen, Z. Todd, B. Catherine, The
development of the attitude toward computer usage scale,
Educational and Psychological Measurement 47, 1987, pp.
261±269.
[41] C.M. Ray, T.M. Harris, Small business attitudes toward
computers, Journal of End-User Computing 6 (1), 1994, pp.
16±25.
[42] S. Robertson, J. Calder, P. Fung, A. James, T.O. Shea,
Computer attitudes in an English Secondary School, Computers Education 24, 1995, pp. 73±81.
[43] W.C. Savenye, G.V. Davidson, K.B. Orr, Effects of an
educational computing course on preservice teachers' attitudes and anxiety toward computers, Journal of Computing in
Childhood Education 3, 1992, pp. 31±42.
[44] N. Selwyn, Students' attitude toward computers: validation of
a computer attitude scale for 16-19 education, Computer
Education 28, 1997, pp. 35±41.
[45] L. Shashanni, Gender based difference in attitudes towards
computers, Computers Education 20, 1993, pp. 169±181.
[46] G. Siann, H. Macleod, Computers and children of primary
school age: issue and questions, Computers Education 14,
1990, pp. 1483±1491.
[47] J. Simon, R. Wilkes, Students' attitudes about computers and
the influence of a computer literacy course, In: Proceedings
of Conference on International Resource Management
Association, 1997, pp. 333±338
[48] M. Sommer, Inter-press service commentary, Borneo Bulletin, November 1997, pp. 8±9.
[49] C. Stasz, R.J. Shavelson, Teachers as role models: are these
gender difference in microcomputer based mathematics and
science instruction? Sex Roles 13, 1985, pp. 149±164.
[50] R.M. Steers, L.W. Porter, in: Motivation and Work Behavior,
3rd edn., McGraw Hill, New York, 1983.
[51] D.J. Stevens, Why computers in education may fail?
Education 104, 1985, pp. 370±376.
[52] J. Weiss, Multivariate Procedures, in: M.D. Dunnette (Ed.)
Hand Book of Industrial and Organizational Psychology,
Rand McNally, Chicago, 1970, pp. 327±362.
[53] S.J. Winter, K. M Chudoba, B.A. Gutek, Attitudes towards
computers: when do they predict computer use? Information
& Management 34, 1998, pp. 275±284.
[54] M.L. Wilkins, K.S. Nantz, Faculty use of electronic
communication before and after a LAN installation: a three
year analysis, Journal of End-User Computing 7 (1), 1995, pp.
4±11.
[55] B. Wilson, The preparedness of teacher trainees for computer
attitudes: the Australians and British experience, Journal of
Education for Teachers 16, 1990, pp. 161±171.
[56] J.E.J. Woodrow, Locus of control and computer attitude as
determinants of the computer literacy of student teachers,
Computer Education 16, 1991, pp. 237±245.
Dr. Afzaal H. Seyal is a Senior Lecturer
at Dept. Computing & Information
Systems, Institut Teknologi Brunei. He
obtained his B.S. and M.S. from Roosevelt University, USA and Ph.D. from
LaSalle University, USA. His research
interests include end-user computing, IT
application in industry and education and
software piracy. He has published a
number of papers related to these areas
and conferences proceedings. He is a
fellow of Institution of Analyst and Programmer (UK). Currently,
he is member of Singapore, British and Australian Computer
Society. He is also a member of ACM (US).
Md. Mahbubur Rahim is a Lecturer at Department of Computing
and Information Systems, Institut Teknologi Brunei. He received
M.S. in Computer Science from University Pertanian, Malaysia, in
1992. His research interests includes CASE, and software
prototyping. His research papers have appeared in several
international journals including IT and People, Information and
Software Technology, International Journal of Information Management, Asia-Pacific Journal of Information Management and
proceedings at international conferences. Currently, he is a member
of the Australian Computer Society.
Mohd Noah A. Rahman is a Lecturer
at Dept. Computing & Information
Systems, Institut Teknologi Brunei.
He obtained his B.S. in Computer
Science and M.S. in Computer Information Science from USA. He has
published a number of research papers
in international journals and proceedings of international conferences. His
research interest include database systems, systems methodology & techniques, software piracy and computer skills.
Computer attitudes of non-computing academics:
a study of technical colleges in Brunei Darussalam
Afzaal H. Seyal1, Md. Mahbubur Rahim*, Mohd. Noah Abd. Rahman
Department of Computing and Information Systems, Institute Technology Brunei, Permanent Campus,
Tungku Link, BSB, BE 1410, Brunei Darussalam
Received 29 October 1998; accepted 29 July 1999
Abstract
Current information systems (IS) literature has paid considerable attention to measuring the computer attitudes of students
and schoolteachers. Computer attitudes of non-computing academics working particularly in technical colleges have, however,
received scant attention. Moreover, studies on computer attitudes among Asian academics are least reported. Keeping this in
view, this study was undertaken by validating an instrument to measure computer attitudes of non-computing academics
working among technical colleges in Brunei Darussalam. This study also identi®ed factors that contributed to the formation of
computer attitudes of academics. This was achieved by undertaking a survey of 192 non-computing academics from four
technical colleges. Attributes related to demographics and education of academics appeared to have little impact on computer
attitudes. In contrast, ownership of a personal computer (PC) and level of computer skill were found to be important. # 2000
Elsevier Science B.V. All rights reserved.
Keywords: Computer attitudes; Non-computing academics; Technical colleges
1. Introduction
Academic institutions now seek to put a computer
on the desk of all their staff [29]. In the past, academics used computers primarily to perform administrative tasks, like compiling students' results and
monitoring students' in-class progress. Recently, the
concept of using computers has moved beyond this.
For instance, several educational institutions in the US
have embraced computers in the class rooms, and most
*
Corresponding author. Fax: 673-2-249036.
E-mail addresses: [email protected] (A.H. Seyal),
[email protected] (M.M. Rahim)
1
Fax: 673-2-249036.
American teachers regard computer as much a part of
the classroom as a blackboard [48].
Despite the tremendous educational opportunities,
its potential is yet to be fully utilised. Gilbert [15]
found that many academics are reluctant to move
beyond word processing, while Wilkins and Nantz
[54] discovered that teaching uses of the computer
network remained low and perceived future use was
also low. One plausible explanation is that substantial
investment that has already been made in more traditional methods of instruction [27]. More importantly
computerisation has brought in anxiety and threats to
some teacher's [3] and some educators believe that
computers may fail to have an impact on classroom
instruction [51]. Consequently, the provision of com-
0378-7206/00/$ ± see front matter # 2000 Elsevier Science B.V. All rights reserved.
PII: S 0 3 7 8 - 7 2 0 6 ( 9 9 ) 0 0 0 4 5 - 2
170
A.H. Seyal et al. / Information & Management 37 (2000) 169±180
puter technology is not a suf®cient condition for its
success in an educational setting.
A formidable body of literature exists on the computer attitude of school teachers and there is also some
literature on the attitude of university faculty
[19,26,43]. Little is, however, known regarding the
computer attitude of academics working in technical
colleges. From these studies, it is argued that the
quali®cations, working experiences and interests of
academics may affect the attitude towards computer.
But none of these studies suggests about the attitude of
academics employed in technical colleges and are
likely to differ from those of schoolteachers and
faculty members. Thus, academics in technical colleges may develop different views and attitudes
towards computers as compared to those of their
counterparts. There is need to study this aspect in a
new geographical setting.
An overwhelming majority of existing studies were
undertaken in western countries. Thus, their results
may not be applicable to an Asian country like Brunei
Darussalam, which is culturally different from the
western world. It is a small sultanate located on the
north west coast of Borneo island with a total population of nearly 0.3 million [4]. Its' main economic
activity is dominated by the oil and gas sector, and
gross domestic product per capita was B$ 23,865
(US$1 1.58) in 1994. After achieving its independence in 1984, the government placed considerable
importance on technical education. Two engineering
colleges, one vocational college, and a technical institute were established to produce technologically
oriented professionals at various levels. The government also recognised the need for broader use of
computer technology in the public sector. As such,
the Information Technology Division (ITD) was set up
to oversee and to support the development of IT
projects in the public sector in schools and technical
colleges. Against this background, a study was undertaken in late 1997 to examine the computer attitudes of
non-computing academics from four different technical colleges.
2. Objectives of study
The central intent of this study was to examine the
computer attitudes of non-computing academics
working in technical colleges in Brunei Darussalam.
There were two speci®c objectives
1. To develop and validate a suitable instrument to
measure computer attitudes of non-computing
academics.
2. To identify the factors that significantly affects
computer attitudes of these academics.
3. A review of literature
Literature on computer attitudes can be broadly
divided into three groups, depending on the type of
the target population for whom attitudes were measured. The ®rst group deals with the measurement of
computer attitudes of primary and secondary school
students. The works of Harvey and Wilson [20], Siann
and Macleod [46], Levin and Gordon [30], Martin
[33], and Moore [34] fall in this group. Some authors
like Koohang [28] and Finnegan and Ivanoff [11] have
also studied computer attitudes of students studying in
higher institutions.
The second group of studies has focused on schoolteachers. This group includes the works of Katz and
Francis [26] and Savenye et al. [43] among others.
While limited studies are available for the third group,
which address the computer attitudes of university
faculty members. Recently, Harris [19] has made a
valuable contribution by measuring computer attitudes of academics in a Hong Kong university. The
attitude studies were hot however con®ned to students
and academics, some authors like Gattiker and Hlavka
[14], Nickell and Seado [35], Culpan [8], and Winter
et al. [53] made attempts to measure computer attitudes of people working in business settings.
The studies also identi®ed a variety of factors that
affect the attitudes of subjects (students, teacher's
etc.). Some of the frequently reported factors include
gender, age, personality, prior computer training, computer literacy, and computer experience among others.
A brief summary of these is provided in Table 1. More
effort was spent on examining the in¯uence of gender
on the computer attitudes of students and teachers.
Computer literacy has also received considerable
attention. Relatively, less attention was paid to teaching experience and level of computer skill of individuals.
A.H. Seyal et al. / Information & Management 37 (2000) 169±180
171
Table 1
A summary of factors affected computer attitudes
Factors
Source
Subject
Computer Literacy
Hignite and Echternacht [21]
Woodrow [56]
Loyd and Gressard [31]
Simon and Wilkes [47]
Al-Jabri et al. [1]
Business education teachers
Student teachers
Teachers
Participant of computer literacy course, business major
Undergraduate university business students
Age
Gender
Woodrow
Savenye et al. [37]
Woodrow
Kay [27]
Robertson et al. [42]
Shashanni [45]
Student teachers
Pre-service teachers
Student teachers
Education students
Student teachers
Secondary school students
Teaching experience
Personal locus
Computer Ownership
Wilson [55]
Kay
Ray [41]
Gattiker & Hlavka [14]
Nickell & Seado [35]
Harvey & Wilson [20]
Al-Jabri et al.,
Students
Education students
Business owners
University students enrolled in computer course
Business managers
Primary & sec school pupil
Undergraduate university business students
Prior Training
Nickell and Seado
Igbaria [23]
Harris [19]
Harris
Business managers
Business managers/part-time MBA students
Faculty members
Faculty members
Organisational culture
Task characteristics
4. The research model and development of
hypotheses
On the basis of a review of existing literature, a normative model was developed. It is presented in Fig. 1.
Gender: The impact of gender on the formation of a
person's computer attitude is still a matter of debate.
Some authors like Perolle; [38] and Mankin et al. [32]
have reported gender difference in computer attitude
in various work settings. Barrier and Margavio [2],
who studied gender issues by using the attitude toward
computer usage scale (ATCUS) and found that more
males exhibited negative computer attitude; have
reinforced their ®ndings. On the other hand, Stasz
and Shavelson [49] reported little gender difference in
a study of computer attitude among teachers. Thus, the
following hypothesis is postulated
Hypothesis 1. There exists a relationship between
gender and academic computer attitudes.
Age: Several researchers have examined the
impact of age on a person's computer attitude. Jay
and Willis [24] reported that young males have
most favourable predisposition towards computer.
Moreover, Kay identi®ed age as an important
variable while assessing the positive attitude
towards computer use. This leads to the following
hypothesis
Hypothesis 2. There exists a relationship between
age and academic computer attitudes.
Educational quali®cation: Several researchers
have highlighted the importance of education of
academics on their computer attitudes. For instance,
Dugan and Thurlow [9] suggested that educational
level is likely to have an effect on one's attitude
towards computer use. Those who are better educated
are more favourably disposed to rapid advance in
technology. Kay has reported that people with higher
educational quali®cation have favourable predisposition to computer use, while Hignite and Echtenacht
[21] found that education effect computer attitude of
business education teachers. Thus, the following
hypothesis is postulated
172
A.H. Seyal et al. / Information & Management 37 (2000) 169±180
Fig. 1. Research model.
Hypothesis 3. There exists a relationship between
educational qualification and academic computer
attitudes.
Teaching experience: Existing literature offers little
information about the impact of teaching experience
on academic computer attitude. A few studies however
provide some indication that beginning teachers in UK
schools use computers in their classrooms much less
than expected. For instance, HMI [22] found that less
than 6% of beginning teachers in UK schools used
computer in their ®rst year of teaching, while fewer
than 20% of the beginning school teachers were found
to be prepared to use computer in their classrooms
[18]. Maybe, computer awareness will grow with time.
The following hypotheses is postulated
Hypothesis 4. There exists a relationship between
years of teaching experience and academic computer
attitudes.
Personal computer ownership: Literature strongly
suggests that ownership of a PC is related to a favourable attitude. For example, Pfeffer and Lawles [39],
Steers and Porter [50], Harvey and Wilson [20] and
Noe [36] have shown the differences in attitude
between owners and non-owners of computer, with
owners having a more positive attitude. Gattiker and
Hlavka [14] have shown that individual's attitude to
computer usage depends on ownership of a computer.
Thus
Hypothesis 5. There exists a relationship between
173
A.H. Seyal et al. / Information & Management 37 (2000) 169±180
ownership of personal computer and academic computer attitude.
Prior computer training: Several authors have studied the relationship between a person's prior training
in computers and his/her subsequent attitude. Clarke
and Chamber [6] have shown the signi®cance of prior
computing training on the person's attitude, while
Dupagne and Krendl [10] have found that computer
literacy courses greatly improve teachers' attitudes.
Based upon this rationale, the following hypothesis is
proposed
Hypothesis 6. There exists a relationship between
previous training in computer and academic computer
attitudes.
Computer skill: The skill of academics in using
personal computers may have some in¯uence on their
computer attitudes. Less skilled academics may
develop anxiety; then they view the computer with
scepticism. This assertion is partially supported by
Loyd and Gressard [31] who reported that the subjects
participating in their study developed a more positive
attitude once they achieved a certain level of computer
skill. Thus, the last hypothesis
Hypothesis 7. There exists a relationship between
level of computer skill and academic computer attitudes.
used to measure computer skill and teaching experience. The measure of the dependent variable (computer attitude) used the de®nition of attitude suggested
by Fishbein and Ajzen [12]: as a learned predisposition to respond in a consistently favourable and unfavourable manner with respect to a computer. This is a
multi-dimensional psychological concept, with multiple items required to capture a psychological factor
like computer attitude Nunnally [37]. A set of 27 items
was initially selected from the literature to measure
computer attitudes of academics. Each academic was
asked to indicate their level of agreement/disagreement with each statement on a ®ve-point Likert scale,
where 1 stands for strongly disagree, 2 for disagree, 3
for undecided, 4 for agree and ®nally 5 stands for
strongly agree. A summary of the de®nitions and
scales is provided in Table 2.
5.2. Population
The study employed a survey approach to examine
computer attitudes of non-computing academics. The
target population was the non-computing academics
working among at technical colleges in Brunei Darussalam. The number of academics in all these technical colleges was reported to be 340. Telephone
contacts with the Head of these colleges revealed a
total of computing staff. Thus, the target population
was reduced to 300.
5. Research methodology
5.3. Instrument validation
5.1. Design of instrument
An initial version of the instrument was developed
in two parts: Part A collected demographic information, computer exposure, and educational attributes,
while Part B contained 27 items to measure computer
A variety of scales were used to measure these seven
independent variables. A ®ve-point Likert scale was
Table 2
A summary of research variables
Factors
Definition
Scale
Computer attitude
Gender
Age
Educational qualification
Teaching experience
PC ownership
Prior Computer training
Computer skill
A disposition to respond favourably to a computer.
Sex of an academic
No. of years since birth
Highest academic award received from a university/institution.
Number of years involved in teaching on a full time basis.
The availability of a personal computer at home for his/her exclusive use.
Whether he/she has formally attended training on computer or related subject.
The level of competence possessed while working with a PC
Five-point Likert
Dichotomous
Categorical
Categorical
Five-point interval
Dichotomous
Dichotomous
Five-point interval
174
A.H. Seyal et al. / Information & Management 37 (2000) 169±180
attitudes. These items were carefully selected after
reviewing existing literature. The works of by Selwyn
[44], Francis [13], Jones and Clark [25], Popovich
[40], and Gressard and Loyd [16] were found to be
particularly useful. This initial instrument was pretested using several academics chosen randomly from
two colleges located in close proximity of the authors'
work place. The participating academics were asked
to comment on the format and appropriateness of
questions and to suggest additional items that they
believed should be included in the instrument. In view
of their suggestions, several amendments were incorporated into the instrument, which greatly improved
its clarity.
The revised instrument was further pilot tested
among 32 academics selected from three colleges.
The responses obtained from the pilot test for Part
B, were analysed for accuracy using Churchill's item
puri®cation technique [5] and exploratory factor analysis [52]. Using Churchill suggestions, 11 items were
eliminated for which `corrected-item-total' correlation was less than 0.30. While exploratory factor
analysis eliminated those four items that loaded on
more than one factor at 0.40 or greater. Thus, these
multiple phases of instrument development and testing
produced a 12-items instrument for measuring computer attitudes, and thus established an initial content
validity. Table 3 illustrates these 12 items, and their
corresponding corrected item-total correlation and
Varimax factor loadings.
The pilot study proved very effective in eliminating
ineffective items, as well as generating a ®rst set of
constructs. Following the pilot study, the instrument
was restructured and distributed to the remaining 268
non-computing academics. A total of 192 responses
were received; making a response rate of 71% ± which
is exceptional. After the pilot study, the researchers
were still uncertain about the attitude construct. Traditional factor analysis was used to further explore
factor structure; this retained all 12 items. Principal
component analysis was used as the means of extraction and varimax was used as the method of rotation
that grouped these 12 items into three factors. The
Kaiser Meyer±Olkin measure of sampling was 83%.
In this connection, several decision rules based on
Hair et al. [17] were used to aid extraction process and
to derive these three factors. These rules include (a)
minimum Eigenvalue of 1.0, (b) simplicity of factor
structure, and (3) exclusion of single item factor from
the standpoint of parsimony. The three factors were
named as perceived usefulness (Factor 1), affective
(Factor 2), and perceived behaviour (Factor 3). These
12 items, together with their corresponding factor
loading, are shown in Table 4. This reveals that the
factor loading is quite high and range from 0.49 to
0.81; the three factors together explained 57.4% of
total variance.
In factor analysis, it is generally desirable to have a
larger number of respondents than items. The ratio of
sample size to number of items was (16 : 1), which is
above the (10 : 1) ratio suggested by Nunnally.
Furthermore, the derived instrument was tested for
reliability. Chronbach's [7] Alphas were calculated for
the overalls instrument, as well as for each of the three
Table 3
List of items retained during pilot study
No.
Items
Corrected itemtotal correlation
Factor
loadings
1
2
3
4
5
6
7
8
9
10
11
12
Computer facilitates my teaching
Computer helps me in designing better and effective assignments for student
My assignment always requires my students to use a computer
I use a computer to organize my administrative work
Computer knowledge is essential for modern life
Technical teaching without computer is unthinkable now-a-days
I think that the challenges of teaching using computers is exciting
I think that working on a computer is a good way to use my spare time.
Using a computer makes me feel creative
I think that learning to use a computer needs a lot of patience
I would like to learn about the computer only if it is essential for my promotion
I will do as little work with a computer as possible
0.74
0.63
0.32
0.76
0.65
0.77
0.69
0.54
0.51
0.56
0.36
0.31
0.74
0.75
0.49
0.65
0.69
0.72
0.55
0.81
0.72
0.64
0.81
0.80
175
A.H. Seyal et al. / Information & Management 37 (2000) 169±180
Table 4
Varimax rotated factor loading and Eeigenvalues with variance explaineda
No.
Item description
Factors
1
Perceived usefulness (6 items)
Computer facilitates my teaching
Computer help me in designing better and effective assignment for student
My assignment always require my students to use computers
I use computer to organise my administrative work in a better way
Computer knowledge is essential for modern life
Technical teaching without computer is unthinkable now-a-days
Affective component (4 items)
I think that the challenges of teaching using computers is exciting
I think that working on computer is a good way to spare time.
Using computer makes me feel creative
I think that learning computer needs a lot of patience
Perceived behaviour (2 items)
I would like to learn about computer only if it is essential for my promotion
I will do as little work with computer as possible
Eigenvalue
% of variance
1
2
3
4
5
6
7
8
9
10
11
12
a
2
3
0.74
0.75
0.49
0.65
0.69
0.72
0.55
0.81
0.72
0.64
0.25
35.5%
1.57
13.1%
0.81
0.80
1.05
8.8%
Note : Factor 1 refers to perceived usefulness, Factor 2 refers to affective component, and Factor 3 refers to perceived behaviour.
factors and are presented in Table 5. The alpha is
considered satisfactory.
6. Results
Data obtained from the survey were analysed using
w2-tests as well as multiple regression by means of
SPSS, a well known statistical package.
6.1. Background profile
The background of the participating academics is
summarised in Table 6. The dominance of males is
clear. This is not unexpected, because nearly 80% of
the academics working in the university as well as
technical and vocational colleges are male's [3]. A
majority (71%) of the participating academics fell in
the age group of 30±50 years. With the exception of
doctorate holders, highest educational quali®cations
of these academics varied uniformly. This is possibly
because, unlike universities, academics in technical/
vocational colleges are not required to possess Ph.D.
Degree in their disciplines. Academics with 10±20
years of teaching experience slightly dominated the
sample. Only 17% academics can be considered
novice, with less than 5 years of teaching experience.
Another interesting ®nding is that most academics
(79%) owned a PC. Apparently academics showed
keen interest in a PC to perform work at home. Not all
these academics however had equal computer skills.
Only 11% reported having a high level of computer
Table 5
Results of reliability analysis
Factors
No. of statements
Reliability coefficient (a)
Factor 1: perceived usefulness
Factor 2: affective
Factor 3: perceived behaviour
Overall
6
4
2
12
0.79
0.71
0.60
0.79
176
A.H. Seyal et al. / Information & Management 37 (2000) 169±180
Table 6
Background profile of the academics
Academics
Number
(%)
Gender
Male
Female
147
45
76
24
Age
Less than 30 years
Between 30±50 years
Over 50 years
28
137
27
15
71
14
Educational qualification
Diploma
Bachelor
Masters
Ph.D.
Others
46
51
49
8
38
24
27
25
4
20
Teaching experience
Less than 5 years
Between 5±10 years
Between 10±20 years
Over 20 years
32
51
65
44
17
26
34
23
PC ownership
Own one
Does not own
151
41
79
21
Prior PC training
Yes
No
40
152
21
79
PC skill
High
Above average
Average
Below average
Low
21
30
95
30
16
11
16
49
16
8
skill. Moreover, only one-®fth of the academics (21%)
actually attended any formal training on the computer.
In summary, even though a majority of the participating academics owned a PC, their skill was not high. In
fact, half of the academics only felt they had computer
skill and most did not receive any formal training.
6.2. Computer attitudes
The 12 statements that were grouped into three
factors (via factor analysis) were used to solicit the
attitudinal views held by the academics. They were
asked to indicate their level of agreement/disagreement with each statement on a ®ve-point Likert scale.
Their responses were compiled, and a mean rating for
each statement was computed. These are listed in
Table 7. The mean rating for each of these statements
lie above the 'neutral' position (3.0) on the Likert
scale.
The mean attitude score of these two groups were
also computed, and were tested for signi®cant difference. Results of t-test (t 13.29, df 190, p 0.000)
indicate that difference in attitude score between those
academics having positive attitudes (n 163), and
academics with negative attitudes (n 29) is statistically signi®cant at the 5% signi®cance level Table 8.
6.3. Test of hypotheses
The impact of academic gender, age, quali®cation,
teaching experience, PC ownership, computer skill,
and prior computer training, on the dependent variable
Table 7
Mean rating received by each attitude statement
No.
Items
Mean
1
2
3
4
5
6
7
8
9
10
11
12
Computer facilitates my teaching
Computer helps me in designing better and effective assignments for student
My assignment always requires my students to use a computer
I use a computer to organise my administrative work
Computer knowledge is essential for modern life
Technical teaching without computer is unthinkable now-a-days
I think that the challenges of teaching using computers is exciting
I think that working on a computer is a good way to use my spare time.
Using a computer makes me feel creative
I think that learning to use a computer needs a lot of patience
I would like to learn about the computer only if it is essential for my promotion
I will do as little work with a computer as possible
4.04
4.04
3.01
3.91
4.30
3.60
4.01
3.51
3.79
4.04
3.81
3.69
177
A.H. Seyal et al. / Information & Management 37 (2000) 169±180
Table 8
Attitude summary
Attributes
Values
No. of academics with positive attitude
No. of academics with negative attitude
Average attitude score for all academics (n 192)
Average attitude score for academics having positive
attitude (n 163)
Average attitude score for academics having negative
attitude (n 29)
163
29
45.7
47.6
35.2
Table 9
Results of multiple regression analysis
Variables
b
Educational qualification ÿ0.504
Age
ÿ0.852
PC ownership
ÿ2.84
Gender
1.438
Prior computer training
ÿ0.605
Computer skill
0.943
Teaching experience
ÿ0.266
R2 (adj) 0.169
SE 5.97
*
only two hypotheses (e.g., Hypothesis 5 and 7) were
supported.
w2-tests at the 5% signi®cance level were performed
to examine if there exist any relationships between the
seven independent variables and the dependent variable. The results shown in Table 10, clearly indicate
that, except for PC ownership and computer skill, all
the remaining ®ve variables have no signi®cant relationship with academics computer attitude. This
observation further reinforces the ®ndings of the
regression analysis.
7. Discussion
b
ÿ0.110
ÿ0.121
ÿ0.182
0.095
ÿ0.038
0.153
ÿ0.042
F 5.26
p-value
0.110
0.263
0.014*
0.191
0.577
0.037*
0.694
p 0.000
Indicates statistical significance at (p < 0.05).
were investigated using multiple regression analysis.
The results, as presented in Table 9, explain 17%
variance in the dependent variable, and partially support the model. Out of the seven independent variables, only two, such as PC ownership and computer
skill were found to have signi®cant standardised
regression coef®cients, and were related to academics'
computer attitude. On the other hand, variables like
gender, age, quali®cation, teaching experience, and
prior computer training had little signi®cant impact on
the formation of an academic's attitude. Therefore,
Several important ®ndings have emerged from this
study. First, a set of 12 statements grouped into three
factors was identi®ed. This produced a valid instrument to measure computer attitude of non-computing
academics. This instrument is shorter than some of the
existing ones. For instance, Selwyn's instrument contained 21 statements that were grouped into four
factors, while Popovich et al used instrument in which
40 statements were reduced to 20 items that were also
grouped into ®ve factors. The three factors as generated by this study were in line with those reported by
Selwyn, and differ considerably from those ®ve
reported by Popovich et al. In short, these 12-item
instruments are likely to be easily accepted by academics, as it required less time for them to respond.
Second, the mean score of the participating academics against each statement was well over the
neutral value. This indicates that academics in general
did not hold any unfavourable views about computer
use. Moreover, the average overall attitude score of
47.6 is reasonably high.
Table 10
Relationship between computer attitude and independent variables
Hypothesis
Relationship
w2 value
P-value
Remarks
H1
H2
H3
H4
H5
H6
H7
Gender has relationship with academics' computer attitude
Age has relationship with academics' computer attitude
Educational qualification has relationship with academics' computer attitude
Teaching experience has relationship with academics' computer attitude
PC ownership has relationship with academics' computer attitude
Prior computer training has relationship with academics' computer attitude
Computer skill has relationship with academics' computer attitude
0.731
6.35
6.29
7.13
11.20
2.27
10.46
0.393
0.095
0.178
0.060
0.000*
0.131
0.033*
No support
No support
No support
No support
Support
No support
Support
*
Indicates statistical significance (at p < 0.05).
178
A.H. Seyal et al. / Information & Management 37 (2000) 169±180
Third, a majority of the participating academics
(79%) were found to own a PC. A verbal discussion
with some participating academics revealed that many
of them do not have a PC on their own desk for their
exclusive of®ce use. This constraint encouraged them
to own a PC at home. However, this ®gure is quite high
even in comparison to developed nations. For instance,
Gilbert reported that little over 50% of all higher
educational faculties in US now have their own PC.
Even though a vast majority of the academics in
Brunei owned a PC, nearly half of the academics
(49%) had average level of computer skill. Surprisingly, most academics did not take any formal computer related training.
Fourth, multiple regression analysis identi®ed two
variables (PC ownership and computer skill) that
affect computer attitude of academics. The PC ownership is a signi®cant variable and is supported by the
authors from various countries. Several authors like
Harvey and Wilson (UK), Gattiker and Hlavka
(Canada), Nickell & Seado (USA) and Al-Jabri
et al. (Saudi Arabia) provided strong support that
computer owner have a more positive attitude than
non-owners. In a similar fashion, level of computer
skill of academics was also found to affect attitude.
This ®nding is consistent with that of Loyd and
Gressard (USA), Woodrow (Canada), Simon &
Wilkes (USA), DorenKamp (Holland), Drundell &
Thomson (Scotland) and Al-Jabri et al. (Saudi Arabia)
who reported that subjects participating in his study
tended to produce a positive attitude after attaining
a certain level of skill. Thus, these two ®ndings seem
to be consistent across various geographical boundaries. Furthermore, ownership of PC and computer
skill of academics together explained 17% variation
in computer attitude. The low value suggests that this
study did not include some important independent
variables that have signi®cant impact on computer
attitudes of academics.
8. Conclusions
This study has produced a reliable instrument to
measure computer attitude of non-computing academics working in technical colleges. Using this
instrument as a tool, this study further highlighted
the prevalence of favourable computer attitudes
among these academics. Thus, it can be suggested
that, these academics are likely to have little resistance, if college authorities decide to introduce new
course structure in order to make use of new innovations like multimedia technology. The introduction of
such new courses would provide tremendous improvement in the ®eld of educational computing, provided
the participation of academics in course design and
implementation is encouraged.
College authorities should attempt to provide a PC
on the desk of each academic and encourage them to
use them not only for administrative tasks, but to help
in teaching. Authorities should make considerable
investment in educational computing. Any effort will
not however, be successful without proper training.
The ®ndings of this study bear implications for
three groups of people: academics, professional trainers and business managers. Academics could be
trained for computer-based teaching, learning and
operating computer-based classrooms and laboratories. The prevalence of favourable attitude would
thus in¯uence academics' use of these concepts and
skills. Academics could even explore the possibility to
offer computer-based distance learning programmes.
They could even contribute in developing specialised
educational computer packages in close collaboration
with IT vendors to meet the educational requirements
of students. On the other hand, managers in large
corporations should re®ne their existing manual-based
training and professional development activities with
computers. Managers are also encouraged to liase with
academics; these managers should send their trainers
to academia in order to gain ®rst-hand experience on
how to introduce and use computing facilities in
classrooms. Lastly, IT vendors and academics should
work together in promoting their educational computing products, and to train the users. They should
develop the seminar and research based courses that
not only include the use of the computer in the classroom, but also concentrate on the effects computer
have on learning and schooling from sociological,
psychological and conceptual perspectives.
References
[1] M. Al-Jabri, A.M. Al-Khaldi, Effects of user characteristics
on computer attitudes among undergraduate business student,
Journal of End User Computing spring, 1997, 16±21.
A.H. Seyal et al. / Information & Management 37 (2000) 169±180
[2] T. Barrier, T. Margavio, Pretest-Posttest measure of introductory computer students' attitudes toward computers,
Journal of Information Systems Education 5/3, 1992, pp.
53±58.
[3] M. Bell, The importance of IT education and training,
Computer Bulletin, BCS, February 1995.
[4] Brunei Darussalam Statistical Yearbook, Statistic Review
Economy, Economy Planning Unit, Ministry of Finance,
Brunei, 1993.
[5] G.A.J. Churchill, A paradigm for developing better measures
of marketing constructs, Journal of Marketing Research, XV
February, 1979, 64±73.
[6] V.A. Clarke, S. Chamber, Gender based factor in computing
enrollments and achievement: evidence from a study of
tertiary student, Journal of Educational Computing Research
5, 1989, pp. 409±429.
[7] L.J. Cronbach, Coefficient alpha and the internal structure of
test, Psychometrika 16, 1951, pp. 297±334.
[8] Oya. Culpan, Attitudes of end-users towards information
technology in manufacturing and service industries, Information & Management 28, 1995, pp. 167±176.
[9] J.F. Dugan, G.R. Thurlow, Students' attitudes to mathematics:
a review of the literature, Australian Mathematics Teachers
45, 1989, pp. 8±11.
[10] M. Dupagne, K.A. Krendl, Teacher's attitude toward
computers: a review of the literature, Journal of Research
and Computer Education 24, 1992, pp. 420±429.
[11] D.J. Finnegan, A. Ivanoff, Effects of brief computer training
on attitudes toward computer use in practice: an educational
experiment, Journal of Social Work Education 27, 1991, pp.
73±82.
[12] M. Fishbein, I. Ajzen, in: Belief, Attitude and Behaviour: An
Introduction to Theory and Research, Addison-Wesley,
Reading, MA, USA, 1975.
[13] L.J. Francis, Measuring attitude toward computer among
undergraduate college student: the affective domain, Computer Education 20, 1993, pp. 251±255.
[14] E. Gattiker, A. Hlavka, Computer and attitudes and learning
performance issues for management educational and training,
Journal of Organizational Behaviour 13, 1992, pp. 89±101.
[15] S.W. Gilbert, Technology and the changing academy, Change,
Sept/Oct, 1995, 58±61.
[16] C. Gressard, B. Loyd, Validating studies of a new computer
attitude scale, Australian Education Data Systems Journal 18,
1986, pp. 295±301.
[17] J.F. Hair, R.E. Anderson, R.L. Tatham and W.C. Blake, in:
Multivariate Data Analysis, 4th edn., Prentice Hall, Englewood Cliff, NJ, USA, 1995.
[18] M. Handler, D. Marshall, Preparing new teachers to use
technology: one set of perception, in: Technology and
Teacher Education Annual, Association for Advancement of
Computing in Education, Charlottesville, USA, 1992, 386±
388
[19] R. Harris, Teaching, learning and information technology:
attitudes towards computers among Hong Kong's faculty,
Journal of Computing in Higher Education 9 (1), 1997, pp.
89±114.
179
[20] T.J. Harvey, B. Wilson, Gender differences in attitudes
towards microcomputers shown by primary and secondary
school pupils, British Journal of Education and Technology 3,
1985, pp. 183±187.
[21] M.A. Hignite, L. Echternacht, Assessment of the relationships
between the computer attitudes and computer literacy levels
of prospective educators, Journal of Research and Computer
Education 24, 1992, pp. 381±391.
[22] The New Teacher in School, Report of HMI, HMSO, London,
1988.
[23] M. Igbaria, A. Chakrabarti, Computer anxiety and attitudes
towards microcomputer use, Behaviour and Information
Technology 9 (3), 1990, pp. 229±241.
[24] G.M. Jay, S.L. Willis, The elderly's attitudes toward
computers: a select review of the literature, Gerontological
Society of America, Chicago, IL, 1986.
[25] T. Jones, V.A. Clarke, A computer attitudes scale for
secondary student, Computer Education 22, 1994, pp. 315±
318.
[26] Y.J. Katz, L.J. Francis, Personality, religiosity and computer
oriented attitudes among trainee teachers in Israel, Computers
in Human Behavior, 1993 (in press)
[27] R.H. Kay, Predicting student teacher commitment to the use
of computers, Journal of Educational Computing Research 6,
1990, pp. 299±309.
[28] A.A. Koohang, A study of the attitudes of pre-service
teachers toward the use of computers, Educational Communications Technology Journal 35 (3), 1987, pp. 145±149.
[29] R.L. Lancester, D.D. Strouble, One's university's approach to
the requirements of academic computing, Journal of Systems
Management March 19, 1992, pp. 20±31.
[30] T. Levin, C. Gordon, Effect of gender and computer
experience on attitudes, Journal of Educational Computing
Research 5, 1989, pp. 68±88.
[31] B.H. Loyd, C. Gressard, The effects of age, sex and computer
experience on computer attitude, Association Educational
Data System Journal 18, 1984, pp. 67±77.
[32] D. Mankin, T.K. Bikson, B.A. Gutek, Factors in successful
implementation of computer based office information systems: a review of the literature with suggestion for OBM
research, Journal of Organizational Behavior 6, 1986, pp. 1±
20.
[33] R. Martin, School children's attitudes computers as a function
of gender, course subjects and availability of home computers, Journal of Computer Assisted Learning 7, 1991, pp. 187±
194.
[34] J.L. Moore, Development of a questionnaire to measure
secondary school pupils, attitudes to computers and robots,
Educational Studies 11, 1985, pp. 33±40.
[35] G.S. Nickell, P.C. Seado, The impact of attitudes and
experience on small business computer use, American Journal
of Small Business, Spring, 1986, 37±48.
[36] R.A. Noe, Training attributes and attitudes: neglected
influences on training effectiveness, Academy of Management Review 11, 1986, pp. 736±749.
[37] J.C. Nunnally, in: Introduction to Psychological Measurement, McGraw-Hill, NY, 1970.
180
A.H. Seyal et al. / Information & Management 37 (2000) 169±180
[38] J.A. Perolle, Computers and Social Change, Wadsworth,
Belmont, CA, 1987.
[39] J. Pfeffer, J. Lawler, Effects of job alternative extrinsic
rewards and behavioral commitment on attitude toward the
organization, Administrative Science Quarterly 29, 1980, pp.
550±572.
[40] P.M. Popovich, R.H. Karen, Z. Todd, B. Catherine, The
development of the attitude toward computer usage scale,
Educational and Psychological Measurement 47, 1987, pp.
261±269.
[41] C.M. Ray, T.M. Harris, Small business attitudes toward
computers, Journal of End-User Computing 6 (1), 1994, pp.
16±25.
[42] S. Robertson, J. Calder, P. Fung, A. James, T.O. Shea,
Computer attitudes in an English Secondary School, Computers Education 24, 1995, pp. 73±81.
[43] W.C. Savenye, G.V. Davidson, K.B. Orr, Effects of an
educational computing course on preservice teachers' attitudes and anxiety toward computers, Journal of Computing in
Childhood Education 3, 1992, pp. 31±42.
[44] N. Selwyn, Students' attitude toward computers: validation of
a computer attitude scale for 16-19 education, Computer
Education 28, 1997, pp. 35±41.
[45] L. Shashanni, Gender based difference in attitudes towards
computers, Computers Education 20, 1993, pp. 169±181.
[46] G. Siann, H. Macleod, Computers and children of primary
school age: issue and questions, Computers Education 14,
1990, pp. 1483±1491.
[47] J. Simon, R. Wilkes, Students' attitudes about computers and
the influence of a computer literacy course, In: Proceedings
of Conference on International Resource Management
Association, 1997, pp. 333±338
[48] M. Sommer, Inter-press service commentary, Borneo Bulletin, November 1997, pp. 8±9.
[49] C. Stasz, R.J. Shavelson, Teachers as role models: are these
gender difference in microcomputer based mathematics and
science instruction? Sex Roles 13, 1985, pp. 149±164.
[50] R.M. Steers, L.W. Porter, in: Motivation and Work Behavior,
3rd edn., McGraw Hill, New York, 1983.
[51] D.J. Stevens, Why computers in education may fail?
Education 104, 1985, pp. 370±376.
[52] J. Weiss, Multivariate Procedures, in: M.D. Dunnette (Ed.)
Hand Book of Industrial and Organizational Psychology,
Rand McNally, Chicago, 1970, pp. 327±362.
[53] S.J. Winter, K. M Chudoba, B.A. Gutek, Attitudes towards
computers: when do they predict computer use? Information
& Management 34, 1998, pp. 275±284.
[54] M.L. Wilkins, K.S. Nantz, Faculty use of electronic
communication before and after a LAN installation: a three
year analysis, Journal of End-User Computing 7 (1), 1995, pp.
4±11.
[55] B. Wilson, The preparedness of teacher trainees for computer
attitudes: the Australians and British experience, Journal of
Education for Teachers 16, 1990, pp. 161±171.
[56] J.E.J. Woodrow, Locus of control and computer attitude as
determinants of the computer literacy of student teachers,
Computer Education 16, 1991, pp. 237±245.
Dr. Afzaal H. Seyal is a Senior Lecturer
at Dept. Computing & Information
Systems, Institut Teknologi Brunei. He
obtained his B.S. and M.S. from Roosevelt University, USA and Ph.D. from
LaSalle University, USA. His research
interests include end-user computing, IT
application in industry and education and
software piracy. He has published a
number of papers related to these areas
and conferences proceedings. He is a
fellow of Institution of Analyst and Programmer (UK). Currently,
he is member of Singapore, British and Australian Computer
Society. He is also a member of ACM (US).
Md. Mahbubur Rahim is a Lecturer at Department of Computing
and Information Systems, Institut Teknologi Brunei. He received
M.S. in Computer Science from University Pertanian, Malaysia, in
1992. His research interests includes CASE, and software
prototyping. His research papers have appeared in several
international journals including IT and People, Information and
Software Technology, International Journal of Information Management, Asia-Pacific Journal of Information Management and
proceedings at international conferences. Currently, he is a member
of the Australian Computer Society.
Mohd Noah A. Rahman is a Lecturer
at Dept. Computing & Information
Systems, Institut Teknologi Brunei.
He obtained his B.S. in Computer
Science and M.S. in Computer Information Science from USA. He has
published a number of research papers
in international journals and proceedings of international conferences. His
research interest include database systems, systems methodology & techniques, software piracy and computer skills.