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Advances in Social Sciences Research Journal – Vol. 8, No. 8
Publication Date: August 25, 2021
DOI:10.14738/assrj.88.10684. Al-Adawiah, S. R. (2021). Role of Technology Access and Technical Self-Efficacy Towards Lecturers’ Readiness in Blended Learning.
Advances in Social Sciences Research Journal, 8(8). 92-98.
Services for Science and Education – United Kingdom
Role of Technology Access and Technical Self-Efficacy Towards
Lecturers’ Readiness in Blended Learning
Syarifah Rabiyah Al Adawiah binti Syed Badrul Hisham
School of Professional and Continuing Education (SPACE)
University of Technology Malaysia, Kuala Lumpur
ABSTRACT
Landscape of classroom teaching and learnings has changed Integrating
information and communication technology (ICT) as a source of blended teaching
and learning, either in the classroom or outside the classroom, has become one of
the evolutions in classroom learning. To be part of this evolution, UTMSPACE has
started to implement blended learning in teaching and learning. Therefore, the
study intended to examine the readiness of UTMSPACE lecturers towards the
implementation of blended learning and to explore the current practice of blended
learning among the lecturers. The findings confirmed the lecturers’ readiness for
blended learning implementation. This study also examines how personal factors
affected the success of e-learning systems and provided better results. Structural
equation models on the data of 101 targeted respondents showed that online
communication self-efficacy, attitude, and online media are the multiple mediators
between the technology access and technical usage self-efficacy and lead to
increased blended learning readiness among the lecturers at UTMSPACE. It appears
that despite technological factors, the lecturers with a high belief in their ability and
attitude are more prepared to adopt the alternative ways of teaching and learning
as they gain more experience.
Keywords: Blended learning, UTMSPACE, readiness.
INTRODUCTION
Integrating information and communication technology (ICT) into education can complement,
enrich, and transform education for the better. Accordingly, blended learning has been viewed
as a method for creating a better classroom-learning experience. Blended learning has emerged
in various methods to suit different learning styles. The key ingredients in blended learning are
face-to-face and online learning [1]. The environment in blended learning can help students to
use various sources to gain knowledge, which in turn, helps them to increase their research
skills. Blended learning can also facilitate students’ acquiring information and applying their
knowledge in real situations. Therefore, the most important consideration for the successful
implementation of blended learning at the university level is the ability to access students’
readiness [2].
LITERATURE REVIEW
Attitudes towards the use of technology in the teaching and learning process are influenced by
various factors. Blended learning requires lecturers to have access to technology. Thus, the
challenges of technological accessibility cannot be ignored [3]. Attitudes towards blended
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Al-Adawiah, S. R. (2021). Role of Technology Access and Technical Self-Efficacy Towards Lecturers’ Readiness in Blended Learning. Advances in
Social Sciences Research Journal, 8(8). 92-98.
URL: http://dx.doi.org/10.14738/assrj.88.10684
learning may be influenced by a lecturer’s concern about not having access to and technological
support at the institution [4]. Internet speed and connection also play vital roles in the attitudes
toward blended learning [5]. A high-speed internet connection can trigger the success of
resources in blended learning. Lecturers who can access information easily by using technology
will have a more positive attitude towards blended learning.
[6] found that those with computers will have more a positive attitude towards online learning.
Basic skills and the ability to operate computers will have a positive attitude towards blended
learning. Based on these arguments, technical usage self-efficacy is expected to have a positive
relationship with a lecturer’s attitude towards blended learning.
Blended learning urges lecturers to have the ability to communicate and use communication
tools effectively [7]. Arguably, [8] found a significant difference between online group and face- to-face meeting among lecturers and students in terms of their attitudes towards teamwork.
The lecturers’ lack self-efficacy in online communication with students affected their attitude
towards the student-lecturer engagement and blended learning.
Online media also has been recognised as a tool for student-lecturer engagement, particularly
with the use of stimulation videos [9]. In the same study, video simulation was found useful in
making a teaching-and-learning environment fun and flexible. In return, students can make
revisions anywhere and anytime with the online media provided by their lecturer. This tool will
also help enhance a lecturer’s skills in technology advancement and facilitate them to upskill.
Therefore, the availability to have online media will have a positive impact on a lecturer’s
attitude towards blended learning.
METHODOLOGY
A combination of quantitative survey methodology with structured questionnaire methods was
used as the research design for this study. To measure the targeted variables, the researcher
used a quantitative analysis; therefore, both methods can be optimal methods for this study
[10,11]. A total of 100 lecturers from UTMSPACE participated in the study, and all the questions
were answered completely by the respondents since the researchers used the face-to-face data
collection method.
All the twenty-two indicators for measuring these six variables were adapted from [12]. As for
statistical technique used, the researchers used the structural equation modelling theory by
using a partial least square estimation technique (i.e. PLS-SEM) since the researchers intended
to explore the effect of the three variables on the targeted variables simultaneously in the
proposed conceptual framework. Previous studies have suggested using 5000 replication of
samples (i.e. bootstrapping theory) to access the significant influence of variables, particularly
by estimating t-statistics and bias-corrected (BCa) confidence interval values [13,14,15]. To
measure the effect of mediating, the following procedure suggested by [16] and [17] was
adopted:
1) If the path of independent variable to dependent variable was not significant, hence the
mediating effect was a full mediation effect.
2) If the path of independent variable to dependent variable was significant, hence the
mediating effect was a partial mediation effect.
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Although the PLS-SEM algorithm was based on the free data distribution assumption [3], [18],
this procedure was necessary since the procedure to obtain the standard error of the parameter
was based on bootstrapping procedure. This procedure can give an ambiguous standard error
of parameter estimates if the data present an extremely outliers and are drastically away from
normal distribution [19].
DATA ANALYSIS
Measurement Model Analysis
SmartPLS 3.2.8 version [20] was used as the statistical tool for examining the measurement and
structural model because the method does not require normality assumption and because a
survey research is normally not normally distributed [21].
The data in this study were collected using a single source. Accordingly, a sequence of tests was
adopted whereby we first tested for common method bias through the testing of full
collinearity, as suggested by [22,23]. All the variables regressed against a common variable: if
the VIF ≤ 3.3, then there is no bias from the single-source data. The analysis yielded a VIF of less
than 3.3, thus single-source bias was not a serious issue with our data.
Table 1: Convergent Validity for Measurement Model
AT OM OC RE TU TA
2.533 3.030 2.584 1.904 3.164 1.864
Note: AT = Attitudes, OM = Online Media, OC = Online Communication, RE = Readiness, TU =
Technical Usage Self-Efficacy, TA = Technology Access
Measurement Model
We tested the model development by using a two-step approach, as suggested by [24]. First, we
tested the validity and reliability of the instruments used based on the guidelines of [25] and
[26]. Then, we ran the structural model to test the hypothesis developed.
For the measurement model, we assessed the loadings, average variance extracted (AVE), and
composite reliability (CR). The values of the loadings should be ≥0.5; the AVE should be ≥ 0.5;
and the CR should be ≥ 0.7. As shown in Table 2, the AVEs are all higher than 0.5 and the CRs
are all higher than 0.7. The loadings are also acceptable, with only one or two loadings scoring
less than 0.708 (Hair et al., 2019).
In step 2, we assessed the discriminant validity using the HTMT criterion, as suggested by [15]
and updated by [27]. The HTMT values should be ≤ 0.85. The stricter criterion and the mode
lenient criterion should be ≤ 0.90. As shown in Table 4, the values of HTMT were all lower than
the stricter criterion of ≤ 0.85. As such, we can conclude that the respondents understood that
the nine constructs were distinct. Taken together, both the validity tests showed that the
measurement items were both valid and reliable.
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Al-Adawiah, S. R. (2021). Role of Technology Access and Technical Self-Efficacy Towards Lecturers’ Readiness in Blended Learning. Advances in
Social Sciences Research Journal, 8(8). 92-98.
URL: http://dx.doi.org/10.14738/assrj.88.10684
Table 2: HTMT Discriminant Analysis for Measurement Model
1 2 3 4 5 6
1. Attitudes
2. Online Communication 0.682
3. Online Media 0.843 0.842
4. Readiness 0.516 0.58 0.407
5. Technical Usage Self- Efficacy 0.75 0.829 0.922 0.542
6.Technology Access 0.506 0.522 0.609 0.636 0.591
Structural Model Analysis
Following the suggestions by [13] and [28], we assessed the multivariate skewness and
kurtosis. The results showed that the data collected were not multivariate normal (Mardia’s
multivariate skewness [β = 5.115, p < 0.01] and Mardia’s multivariate kurtosis [β = 62.566, p <
0.01]). Following the suggestions of [25], we reported the path coefficients, standard errors, t- values, and p-values for the structural model using a 5,000-sample re-sample bootstrapping
procedure [26]. Also considered were [29] recommendation that a combination of p-values,
confidence intervals, and effect sizes be considered instead of p-values for testing the
significance of the hypothesis. Table 4 summarises the structural model assessment.
Based on the t-statistics values, technical usage self-efficacy and online media were found to
have a positive significance for attitudes, but not for technology access and online
communication self-efficacy. Attitudes were also found to have a significant positive effect on
readiness.
Table 3: Structural Model Assessment
Relationship Std Beta Std Error t-values p-values BCI
LL
BCI
UL
f2 q2 Remark
OCà AT 0.117 0.090 1.294 0.098 -0.019 0.274 0.253 0.414 Small
OM à AT 0.377 0.092 4.078 0.000 0.228 0.533 0.012 0.001 Small
TU à AT 0.286 0.129 2.221 0.013 0.065 0.490 0.123 0.028 Small
TAà AT
ATà RE
0.064
0.450
0.122
0.072
0.526
6.270
0.299
0.000
-0.120
0.292
0.266
0.538
0.061
0.006
0.093
0.091
Small
Medium
Note: TA = Technology access; TU=Technical Usage Self-Efficacy; OC= Online Communication
Self-Efficacy; OM= Online Media; AT=Attitudes; RE= Readiness; BCI LL= Bias Corrected Interval
Lower Limit; BCI UL= Bias Corrected Interval Upper Limit; f2=Effect size; q2=Predictive
Relevance; Bootstrap samples was 5000 samples.
Mediating Analysis
Table 4 indicates that attitude simultaneously mediates the relationship between technical
usage self-efficacy and online media toward readiness. The indirect analysis also indicated that
attitude does not mediate the relationship between online communication and technology
access, as the paths were not statistically significant [OC; IEC = 0.052, t = 1.201, p = 0.115; 95%
BCa Bootstrap (-0.014,0.138) and TA: IEC = 0.029, t = 0.484, p = 0.314, 95% BCa Bootstrap
(-0.060,0.133)]. Figures 2 and 3 show the results of the PLS-SEM analysis.
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Table 4: Indirect Effect Assessment
Indirect Path IEC t-statistics p-values
(95% Bca
Bootstrap)
TU -> AT -> RE 0.129 2.051 0.020* (0.027,0.237)
OC-> AT -> RE 0.052 1.201 0.115(NS) (-0.014,0.138)
TA-> AT -> RE 0.029 0.484 0.314(NS) (-0.060,0.133)
OM-> AT -> RE 0.169 3.053 0.001* (0.086,0.261)
Note: IEC= Indirect Effect Coefficient; TA = Technology access; TU=Technical Usage Self- Efficacy; OC= Online Communication Self-Efficacy; OM= Online Media; AT=Attitudes; RE=
Readiness; NS= Not Significant; *p<0.05.
CONCLUSION AND FINDINGS
The technical use of self-efficacy and online media have a significant positive effect on attitudes,
but not for technology access and online communication’s self-efficacy. Attitudes have a
significant positive effect on readiness. It is also reported that an increase in the level of
attitudes will increase the relationship between technical use of self-efficacy and online media
on readiness. Nevertheless, attitude does not mediate the relationship between online
communication and technology access.
Blended learning has been perceived as an alternative to the conventional teaching of one size
fits all. Blended learning, can be personalized to students, and lecturers can offer flexibility in
terms of time. At the same time, students can enjoy the benefit of face-to-face support and
instructions, thus enabling them to learn at their own pace.
On the other hand, by integrating technology into the classroom, students will be more likely to
show higher levels of interest and focus on the subject matter. Thus, lecturers will be able to
reach all students with varying levels of performance.
Future studies may use other mediating factors to investigate the readiness of blended learning.
The findings derived can lead to a broadened holistic approach that may affect the
implementation of blended learning.
ACKNOWLEDGEMENT
This study would like to acknowledge UTMSPACE upon completion of research grant SPF- PDF2006.
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