6th European Conference - Academic Conferences

3.3.4 Computer anxiety
Jaflah Al-Ammary
Computer anxiety is a specific anxiety because it is a feeling that associated with a person’s interaction
with computers (Saade and Kra, 2006). Computer anxiety is defined as a state of mind of being fearful or
nervous when using a computer. It includes factors such as who may have initiated the person to the
computer technology (Brosnan 1998), success or failure experiences with hardware or software (Saade
and Kira, 2006), and detract cognitive resources from task performance (Sam et al., 2005). Computer
anxiety has been revealed by many studies to be affected by previous computer experience and affect
ease of use of information technologies using the technology acceptance model (Bertrand and Bouchard,
2008; Saade and Kira, 2006).
Hypothesis 13: Computer anxiety has a negative effect on students and teacher’s perceived usefulness
of educational technology in school at Kingdom of Bahrain.
Hypothesis 14: Computer anxiety has a negative effect on students and teacher’s perceived ease of use
of educational technology in school at Kingdom of Bahrain.
4. Data collection and research variables
The study sample is comprised of teachers and students from twenty six public schools (male and female
schools) at Kingdom of Bahrain. These schools consist of primary, elementary, and secondary levels.
Two hundred and four surveys were distributed to the twenty six schools. The survey instruments for this
study were developed using validated items from the prior research as a means of assessing the
theoretical constructs of the extended TAM model for educational technology, using the TAM scales of
perceived usefulness, perceived ease of use, and behavioral intention from Davis et al. (1989) and Davis
(1998). A scale for measuring subjective norms was developed using the measurement of Venkatesh et
al. (2003), scales used for measuring computer anxiety and motivation were adopted from the
measurement proposed by Saade and Kira (2006), and scale for measuring computer self-efficacy was
developed using the measures of both Lee (2006) and Karsten et al. (1998). However, measurements of
previous experiences were developed by the author for the purpose of the current research.
5. Data analysis and results
A Partial Least Squares (PLS) was applied to test the current model using Smart-PLS 2.0. PLS is a
structured equation modeling method that analyzes how the items load on their constructs simultaneously
with estimating all the paths in the model (Chiu et al., 2005). Data analysis in the current research
possessed in two stages. In the first stage, the measurement model was evaluated to validate the
reliability and validity of the constructs. In the second stage, the structure model was estimated using
hypotheses testing to test the significance of the path coefficients.
6. Demographics
The survey instrument provides a response rate of 86% which can be considered as high rate bearing in
mind the difficulty in getting the permission from ministry of education at Kingdom of Bahrain to be able to
conduct the survey in the public schools. Demographic characteristics of the overall participants both
teachers and students are presented in Table (1). The results in the table revealed that most of the
participants either teachers or students are male (64.9%, 81% respectively) and are from secondary
schools (57% and 56.5% respectively). Moreover, the results show that most of the teachers have B.Sc.
and master degree (79.4% and 12.6%) and at least six years of experience in teaching (79.6%). Most
importantly, it has been revealed from the results that most of the participated teachers have ICDL or
other computer certificates (57.9%). In addition, the results show that most of the students have taken
class using educational technologies (62.4%) which include the computer (50%), interactive board (30%)
and smart board (20%).
Table 1: Selected characteristics of the sample
Teacher Percentage Students Percentage
Gender Gender
Male 64.9% Male 64.9%
Female 35.1% Female 35.1%
Level of School Level of School
Primary 71.42% Elementary 71.43%
Elementary 28.57% Secondary 28.57%
Secondary Age
13