FROG VLE: TEACHERS' TECHNOLOGY ACCEPTANCE USING UTAUT MODEL - IAEME Journals
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International Journal of Mechanical Engineering and Technology (IJMET)
Volume 9, Issue 3, March 2018, pp. 529–538, Article ID: IJMET_09_03_055
Available online at http://www.iaeme.com/IJMET/issues.asp?JType=IJMET&VType=9&IType=3
ISSN Print: 0976-6340 and ISSN Online: 0976-6359
© IAEME Publication Scopus Indexed
FROG VLE: TEACHERS’ TECHNOLOGY
ACCEPTANCE USING UTAUT MODEL
Arumugam Raman
School of Education and Modern Languages, Universiti Utara Malaysia
Mohan Rathakrishnan
School of Languages, Civilization and Philosophy, Universiti Utara Malaysia
ABSTRACT
In Malaysia, Frog VLE was introduced to 10,000 schools through the 1BestariNet
project. It is an award-winning, cloud-based virtual learning environment designed by
Frog Education which facilitates the mastery of the skills such as communication,
teaching and learning and school management. Frog VLE is not just used in Malaysia
Even in the rest of world, where 23 countries, 12,000 schools and 20 million users
engaging with the community of teachers and students. It is appropriate to measure
the level of acceptance of this technology to ascertain whether investment in
1BestraiNet project provides a significant internal rate of return. Therefore,
researchers choose the UTAUT model to measure the level of acceptance of this
technology. 146 secondary school teachers participated in this study. Researchers
adapted questionnaire suggested by Venkatesh et al. (2003) to gather data and then
analyzed with two main statistical packages such as IBM SPSS and SmartPLS 3.0. The
research output shows that Performance Expectancy (PE) (β=0.4677, p
Arumugam Raman and Mohan Rathakrishnan
the education sector. The implementation of the 1Bestarinet program opens up opportunities
for educators, students and parents to improve their skills in communication, teaching and
learning and school management. In this spirit, Frog VLE was introduced to 10,000 schools
through the 1BestariNet project. It is an award-winning, cloud-based virtual learning
environment designed by Frog Education which facilitates the mastery of the skills as
described above. Frog VLE is not just used in Malaysia Even in the rest of world, where 23
countries, 12,000 schools and 20 million users engaging with the community of teachers and
students. It is appropriate to measure the level of acceptance of this technology to ascertain
whether investment in 1BestraiNet project provides a significant internal rate of return.
Therefore, researchers choose the UTAUT model to measure the level of acceptance of this
technology as it covers a range of previously proposed models. The teaching and learning of
FrogVLE are beyond acceptation for not only delivering lessons but enhance students‟
abilities to think critically and understand the remedy of learning deficiencies related to an
asynchronous domain (Mohan and Umar, 2011).
1.1. Problem Statement
Malaysia has also taken same steps as other countries in the Asia-Pacific region to integrate
IT into teaching and learning in schools (Tan, 2003). Schools are now all linked up with fast
network facilities via „programs such as Computer Literacy Pilot Project, Computer in
Education, Computer-Aided Instruction and Learning‟ (Hendehjan & Noordin, 2013).
Realizing the significance of online learning and the utilization of multimedia among the
younger generation, the Minister of Education has declared the use of IT in education is a
must in all school systems in Malaysia under the new National Education Blueprint 2006-
2010. However, aspects such as thinking, knowledge, and expertise were not stressed in the
online learning which the teachers need to construct students understanding and optimizing on
what technology has to offer at high-end technology in schools. Therefore, it is necessary to
measure the FrogVLE‟s acceptance level to understand the better before expected usage level
of this technology.
Figure 1 exhibits current portal of FrogAsia, where Malaysian Secondary School teachers,
students and parents connecting via single cloud-based platform.
Figure 1 https://frogasia.com/en/1bestarinet/
http://www.iaeme.com/IJMET/index.asp 530 editor@iaeme.com
Frog VLE: Teachers‟ Technology Acceptance Using UTAUT Model
2. LITERATURE REVIEW
This section divided into two sections. First, researchers detailed about FrogVLE‟s features,
theoretical paradigm, connectivity and contents. Second section is about measuring the
acceptance level of FrogVLE among secondary school teachers of 281 secondary school
teachers from Kuala Muda District, Kedah Malaysia.
2.1. VLE in Education
Dillenbourg, Schneider and Synteta (2002) confirm that VLE is interpreted based on some of
the key features of which are: a) providing information design space; b) It is a social space:
education interaction changes the pattern of space to place; c) an explicit virtual space
representing a 3D virtual world; d) Students are not only active but play a role in designing
virtual space; e) VLEs are not limited to distance education and even enrich classroom
activities; f) VLEs integrate diverse technology and numerous pedagogical approaches; g)
Most VLEs overlay with somatic environments.
Further, Oliver and Herrington (2003) and Konrad (2003) described VLE comes with a
specific view of education namely the social constructivist paradigm. In addition Maor (2003)
stated VLE proponents find social constructivism is the underpinning theory to support VLE
in education. According to Oliver & Herrington (2003), VLE can be enthused through seven
constructivist learning approaches i) revelation to experience to build knowledge, ii)
providing experience and appreciation for some standpoint iii) integrating realistic learning
process, iv) Inspiring speech in the process of learning, v) uniting learning in social
experiences; v) Boost the use of various representational ways, vi) stimulating self-awareness
in the process of knowledge building. A VLE may help students‟ achievement through instant
feedback, extra support, cooperative revision, etc.).
Figure 2 1BestraiNet connectivity overview
Figure 2 shows 1BestraiNet connectivity overview. Through the 1BestariNet project,
FrogAsia (Figure 1) is carrying the future of education to every student, teacher and parent in
Malaysia. The 1BestariNet project is the main component in the seventh shift of the Malaysia
Education Blueprint 2013-2025 (PPPM 2013-2025). On 15th May, 2011, the Ministry of
Education (MoE) has launched an unclosed tender for procurement of the 1BestariNet service
over a period of 15 years. A total of 16 companies have participated in the open tender and
after evaluation by the MoE‟s procurement board, YTL Communications was awarded a
http://www.iaeme.com/IJMET/index.asp 531 editor@iaeme.comArumugam Raman and Mohan Rathakrishnan
contract cost one point five billion ringgit next consequent 5 years and a total of RM663m for
a period of two and a half year starting from 13 Dec 2011 to 12 June 2014. The entire 15-year
project would cost over RM4 billion total.
A conventional VLE is a web-based communications channel that permits users, without
restriction of place and time, to use various education tools, including information about the
program, assistance to teachers, content of the course, learning resources, borads of discussion
and systems that sharing documents (Ngai, Poon & Chan, 2007; Martins & Kellermanns,
2004).
Figure 3 shows, under the 1BestariNet project, FrogAsia, YTL owned subsidiary provides
its learning platform (Frog Virtual Learning Environment (Frog VLE)) for users to access
virtual collections, learning assets, Google learning content, Google Apps, Google Calendar,
Google Maps etc. Besides, those students can also do homework online and submit it online
as well as interact and collaborate with each other in accomplishing their assignments'
projects through online social networking facilities. For teachers, they can assign homework
to students, monitor their progress and intervene when needed. In addition to that, teachers
can also interact with parents online while parents can view their children‟s progress online,
etc.
With the 1BestariNet project, students and teachers are able to use „Frog‟ from any place
there are such as canteen, field and without time constraint using any devices that can access
frog VLE with an Internet link. Frog equipped with Yes 4G with 2Mbps to 10Mbps (urban
areas) and 2Mbps to 4Mbps (rural areas).
Figure 3 Contents of FrogVLE
2.2. Previous Studies
Past studies (Chou & Liu, 2005; Van Raaij & Schepers, 2008; Sanchez & Hueros, 2010; Cobo
et al., 2014) focused on the web integrated learning systems namely Blackboard, WBLS,
Moodle, and e-LMS, which these learning systems more relying on grid technology that does
not provide unlimited storage space. By contrast, Frog VLE provides an access to two-way
information by offering cloud computer technology facilities. According to Ercan (2010)
http://www.iaeme.com/IJMET/index.asp 532 editor@iaeme.comFrog VLE: Teachers‟ Technology Acceptance Using UTAUT Model
cloud computer systems provide a chance of flexibility and resiliency to use the source at the
request of the user. Furthermore, Thorsteinsson, Page and Niculleccu (2010) stated that this
technology supports social-based learning theories through collaborative learning and co-
operative learning. So, with the cloud computing system, students and parents can interact
with each other instantly regardless of boundaries and times. Because there is a huge gap
between grid computing and cloud computing; it is important to know the level of acceptance
of this technology among Malaysian teachers.
As a step to know the level of FrogVLE acceptance among teachers of researchers used
the UTAUT Model proposed by Venkatesh et al, (2003). This model proposes four major
variables to measure the technology acceptance level of an individual. There are four main
constructs of this model namely; i) Performance expectancy (PE) - which is defined as „how
far a user believes that using the system can help him or her to achieve a skill in his or her
work performance‟); ii) Effort expectancy (EE) - „the level of ease which is related to the use
of the system‟ (Venkatesh et al., 2003); iii) Social Influence which is classified by UTAUT is
how far a user believes „that a person who is more important than him or her thinks that he or
she should use the technology‟ (Venkatesh et al., 2003); and iv) Facility Conditions (FC) -
that refer to „how far the technology ease the organization and how a user believes that the
organization and technical infrastructure that exist can support the use of the technology‟
(Venkatesh et al. 2003).
2.3. Hypotheses
Alternative Hypotheses for this research as follows:
H11: Performance expectancy (PE) affects his or her Behavioral Intention (BI) to use
FrogVLE.
H12: Effort expectancy (EE) affects his or her Behavioral Intention (BI) to use FrogVLE.
H13: Social influences (SI) affect his or her Behavioral Intention (BI) to use FrogVLE.
H14: Facility conditions (FC) affect his or her Behavioral Intention (BI) to use FrogVLE.
Researchers designed proposed conceptual framework based on hypotheses of this study
in Figure 4.
Figure 4 Conceptual Framework of Study
3. METHODOLOGY
Researchers used quantitative approach to find answers for the hypotheses. The questionnaire
was adopted from Venkatesht et a. (2003) which consists of 30 manifest variables. Each item
measured with Likert scale 5 points from totally disagree to totally agree (1-5). The
http://www.iaeme.com/IJMET/index.asp 533 editor@iaeme.comArumugam Raman and Mohan Rathakrishnan
questionnaire was corrected and validated by previous researchers. However the researchers
conducted reliability analysis to ensure usability in current research setting. Simple random
sampling used to get at least 300 participants around the research area. The sample consists of
secondary school teachers whom using FrogVLE in daily task. Researchers not targeted any
focus group since FrogVLE exposed to majority of the government funded schools. The data
analyzed with Partial Least Squares Software such as SmartPLS 3.0 and IBM SPSS.
4. FINDINGS
The response rate is very high (93.7%). The respondents gender details showed in the Table 1
below. The total number of respondents is 281. 19 respondents sent incomplete answers
therefore their responses not included in the research. From the table it can be seen that most
of respondents are female (74.73%) and the male teachers (25.27%) which reflects current
trend of gender pattern in Malaysian education system.
Table 1 Respondents‟ gender
Gender Frequency Percentage (%)
Male 71 25.27
Female 210 74.73
Four key components involved assessing reflective measurement model, namely i)
internal consistency reliability in which the reliability of composite (CR) should be higher
than 0.7; ii) reliability indicators in which the external load indicator between 0.40 and 0.70
should be considered for elimination (removal should increase the CR and the average
variance extracted (AVE); iii) Convergent validity-AVE should be greater than .050; and iv)
Outer loadings for indicators of the constructs should be higher than the cross loadings with
other constructs with the square root of AVE of each construct should be higher than the
highest correlation with any other constructs (Criterion Fornell-Larcker, 1981).
4.1. Convergent Validity
Convergent validity means the extent to which indicators of a specific construct converge or
share a high proportion of variance in common. AVE is the common measure to determine
convergent validity on the construct level. AVE value 0.5 or greater than 0.5 reflects that, on
average, the construct explains more than half of the variance of its indicators. But, and AVE
less than 0.50 indicates more error persists in the indicators.
Table 2 Summary of reflective measurement model
Construct Loadings AVE CR
Performance Expectancy PE) PE 1 .8650 .6187 .9059
PE 2 .7520
PE 3 .8120
PE 4 .8910
PE 5 .6410
PE 6 .7310
Effort Expectancy (EE) EE 1 .7810 .6699 .9239
EE 2 .8310
EE 3 .7410
EE 4 .8610
EE 5 .8600
EE 6 .8300
Social Influence (SI) SI 1 .8621 .7393 .9189
SI 2 .9110
SI 3 .8541
http://www.iaeme.com/IJMET/index.asp 534 editor@iaeme.comFrog VLE: Teachers‟ Technology Acceptance Using UTAUT Model
SI 4 .8091
Facilitating Conditions (FC) FC 1 .8010 .6886 .9297
FC 2 .8510
FC 3 .7610
FC 4 .8740
FC 5 .8980
FC6 .7850
Behavioural Intention (BI) BI1 .8450 .6628 .8862
BI2 .9240
BI3 .7070
BI4 .7640
Table 2 displays outer loadings for each manifest variable is more than 0.7, in spite of that
researchers concluded convergent validity established for this research.
4.2. Discriminant Validity
Discriminant validity measures to what extent a construct is truly distinct from other
constructs; in terms how much it correlates with other constructs. The first rule suggested by
Hair et., al (2016) is i) An indicator‟s outer loadings on a construct should be higher than all
its cross loadings with other constructs; and ii) the square root of the AVE of each construct‟s
criterion).
Table 3 Construct Correlation Matrix
PE EE SI FC BI
PE .7866
EE .6012 .8185
SI .5112 .6036 .8598
FC .2132 .5136 .3270 .8298
BI .3258 .2168 .2141 .3261 .8141
Table 4 displays the Coefficient (β) value of each relationship. The SmartPLS 3.0‟s output
revealed H11, H13 and H14 has positive relationship towards Behavioul Intention to use of
FrogVLE. However H12 shows insignificant relationship towards BI. Therefore researchers
conclude the hypotheses such as H11, H13 and H14 accepted whereas the H12 rejected in this
study. Since the value of R2 =0.421, it can be interpreted that 42.1 % of the variance in
behavioral intention can be explained by the extent of PE, EE, SI and FC.
Table 4 Results of Hypotheses
Hypotheses Relationship Coefficient (β) t value p value Result
H 11 PE ---> BI 0.4677 2.6120 0.004 Accepted
H 12 EE --->BI 0.0780 0.2111 0.416 Rejected
H 13 SI --->BI 0.2450 3.1240 0.000 Accepted
H 14 FC ---> 0.2760 2.566 0.005 Accepted
BI
http://www.iaeme.com/IJMET/index.asp 535 editor@iaeme.comArumugam Raman and Mohan Rathakrishnan
Figure 5 Result of path analysis
5. FINDINGS
This study revealed there is a significant influence of PE on BI. This finding is parallel with
Chiu and Wang (2008); Šumak, Polancic, and Hericko (2010); Van Raaij and Schepers
(2008) and Tan (2013). However the finding is different for the Effort expectancy (Chiu and
Wang (2008); Šumak, Polancic, and Hericko (2010); Van Raaij and Schepers (2008) and Tan
(2013)). This may occur due to the context of the study is different and some the features such
as cloud computing and contents and portals are different and not take into account in
previous studies. But, another two variables namely social influence and facilitating
conditions aligned with past studies. This may happened due to external factors influencing
the respondents to answer survey questions. We can conclude that individual with solid PE
willing to use FrogVLE in their daily work. Future researchers should be focused on EE
where it is solely about one‟s belief of use particular technology easy and effortlessly.
Therefore stakeholders must emphasize on providing user friendly e-learning portals. Internet
accesses must not deter the teachers to use FrogVLE in the classroom. Computer labs must be
well maintained and free of faulty devices such as projectors and electric equipment. This
research provided novel and valuable thoughtful for stakeholders. More researches must be
conducted to determine cloud based FrogVLE relevant to current learning practice. These
technologies not necessarily improve students‟ achievement in public examination or enhance
their critical thinking. As Wiebe Bijker (2010) reminds us, „how to use technology?‟ is a
fundamentally political question. Seen in this light, many key issues underpinning education
and digital technology must be investigated to ensure optimum benefit from any new
technology introduced in Malaysia Education System.
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http://www.iaeme.com/IJMET/index.asp 537 editor@iaeme.comArumugam Raman and Mohan Rathakrishnan
AUTHORS DETAILS
Dr. Arumugam Raman is a Associate Professor in the school of Education and Modern
Languages, College of Arts and Sciences in Universiti Utara Malaysia. His research interests
include Educational Technology, Instructional Technology, Computers in Education,
Educational Research Methodology, Technology and ICT, Statistics for Educational Research
and Partial Least Squares Structural Equation Modeling (PLS-SEM). He had engaged in
many research projects and had received five grants including university, national (FRGS,
RAGS) and college (Leads). The researcher is better known as an Educational Technologist
and currently teaching ICT in Education, Research Methods and Statistics in Education.
Besides, he has written International articles and books which have been published in national
and international levels. He is a member of few Editorial boards for International Journals
such as Journal of International Education Studies, International Journal of Education and
Development using ICT, and Journal of Studies in Education. Furthermore, he is also a
member of professional bodies namely International Association of Science and Technology
for Development (IASTED), Theosophical Society, Association for Computing Machinery
(ACM), Internet society (ISOC), and Qualitative Research Association of Malaysia.
Dr. Mohan Rathakrishnan is a senior lecturer in Universiti Utara Malaysia. Currently he is
attached to School of Language, Civilization and Philosophy. He is an e-learning and
instructional designer in teaching and learning program. He also teaches critical thinking and
creative thinking. He has conducted many workshops on Blended Learning, Critical Thinking,
General Studies and Web 2.0. He has wrote many books on General Studies and e-learning.
He supervise and advise students who likes to do research on online learning (social media,
open learning or blended learning) based on any suitable subject discipline. Currently he is
supervising few Phd and master students regarding colloborative learning and online learning
in applied linguistic. He has received RAGS, University and sTOL grant to do research on
teaching and online learning.
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