1. INTRODUCTION:
Information
and Communication Technologies (ICT) are emerging as a tool to enable, support
and reinforce the changing educational needs of the knowledge societies. Globally
countries across all continents have adopted ICT in their education system and
now it is well established fact that integration of ICT in education helps in
meeting new skill sets required for the jobs and support learners’ creativity (Kreijns
et al. 2013).
Taking
view of this situation, Government of
India has also taken 33 new steps in last four years to strengthen the
education sector of the country and under the RISE (Revitalising Infrastructure
and System in Education) scheme Rs. 1,00,000 crores are slated to be allocated
for the next four years for financing the higher education sector (Business Standard,
2018).
Pandit
Madan Mohan Malaviya National Mission on Teachers and Teaching (PMMMNMTT) is
one of the above-mentioned initiatives with the objective to address all issues
related to teachers, teaching, teacher preparation, professional development,
curriculum design, and developing assessment and evaluation methodology,
research in developing effective Pedagogy comprehensively. Till April 2018, Rs.
201.92 crores have been released under the Scheme after it was launched in
December, 2014 (Singh, 2018). Regardless of allocating huge funds for the cause
does not ensure the adoption of ICT by teachers. Hence, there is need to study
the intention of the teachers for using ICT. Moreover, there are handful of
studies which explored the motivation behind intention and adoption of ICT in
education and there is absolutely no study in Indian context. Therefore, a need
was felt to study in this context.
Hence,
with the purpose to identify the underlying motivating factors behind attitude
to use technology the study has two-fold objectives:
a)
To identify the important
motivating factors for attitude formation towards ICT usage.
b)
To study the
relationship between attitude to use ICT and intention to use it.
The
remaining paper is divided into various sections. Section 2 is focused on
literature review while section 3 explain theoretical model and hypotheses
development. Section 4 and 5 are dedicated to research methodology and Data analysis. Discussion and conclusion are
given in section 6 while section 7 reports contribution of the study. In last
section limitations of the study and suggestions for future work has been
discussed.
2.
LITERATURE REVIEW:
Technology
is playing a great role in redefining the teaching- learning process. However,
in early stages of technology introduction to education has been questioned by
the administrators, educators and researchers. But, the pervasiveness of
technology across industries and contexts has diverted the essence of the
debate and only few studies have found minor negative effect of technology on
learning (Kay, 2006). Huang and Liaw (2005) found that usage of technology in
education is the function of teacher’s attitude but with the advancement of
technology, teachers are in pressure to use any ICT tool in their teaching-learning
process (Teo, 2015). Bhuttar (2015) discussed about various opportunities
created by ICT such as e-learning, interactive teaching learning , student
engagement, collaborative learning, boundaryless knowledge sharing among
others. On the other hand, Oroma et al. (2012), reported various challenges faced
by developing countries while adopting e-learning such as insufficient funds,
lack of skill, unclear guidelines of implementing new technologies etc.
Further, Gil-Flores et al. (2017) pointed out that availabilty and access to the
softwares were more important for using ICT in comparison to just the
availability of hardware.
3.Theoretical
Model and Hypotheses Development:
3.1
Adoption Models:
To
study the adoption and non-adoption of any new technology by the people is the
heavily researched topic in academia. For gauging this behaviour, several
attempts have been made by the scholars by suggesting various models such as
technology acceptance model (TAM), unified theory of acceptance and use of
technology (UTAUT), diffusion of innovations (DOI), task technology fit (TTF),
uses and gratification theory (U and G), technology-organization-environment
framework (TOE) among many others. However, Rad et al. (2017) conducted a study
related to adoption of information technology across various contexts and found
that for studying the adoption of technology in education, TAM, UTAUT and DOI
were the most prefered theories by scholars. For the present study we have used
the TAM framework as the base model for simply two reasons. First, TAM is the
widely used and validated technology accepted model in various contexts and the
second the simplicity of the model facinates the researchers (Kwak and
McDaniel, 2011). However, it was felt necceassary to add two additional constructs
namely facilitating conditions (FC) and social influence (SI) because of the
context in question and make the instrument more fit to task. Figure 1 presents
the proposed research model which consists of six constructs in total, where
four constructs namely PU, PEOU, FC, and SI are exogenous variables, intention
to use ICT is endoegenous variable while attitude to use ICT is both exogenous
and endogenous variable.
%20Articles---1-Revised-31-05-19----------RAHUL--------DELHI--------PAGE--7_files/image002.jpg)
Figure
1: Proposed Research Model of the Study
Source:
Authors’ work
3.2
Hypotheses Development:
PU, PEOU, and attitude:
PU
and PEOU are the two main beliefs of the TAM which was suggested by Davis in 1989.
According to this framework, PU has been defined as the extent to which a
potential user think that new technology will be useful in completing his/her
task in a better way (Davis, 1989). Though, this belief is subjective in nature
and varies per user but several studies have established positive and
significant impact of PEOU on attitude to use it (Gil-Flores et al., 2017;Fathema
et al., 2015). In the context of this study, we conceptualize that by using the
ICT tools a higher education teacher feels enhancement in his/her job
performance.
Similarly,
PEOU the another main belief of TAM framework suggests that potential users
will develop an positive attitude and intention to use a technology if it seems
easy to use (Davis, 1989). In this study,
PEOU refers to the perception of the user about the comfort and ease attached
with the use of ICT in teaching- learning process. Various studies related to
education has established relationship between PEOU and attitude to use (Teo,
2015; Prieto et al., 2014).
On
the basis of above discussion, the study extends the following hypotheses:
H1:
PU is a motivational factor for attitude to use ICT.
H2:
PU is a motivational factor for attitude to use ICT.
FC
Measurement
of FC includes two aspects; first the resources such as time and money involved
in using any new technology and second is the compatibility of new technology
with existing facilities within the organisation/institution (Taylor and Todd,
1995). In other words, FC deals with external factors related with the
environment. For higher education teachers few most important jobs are to
disseminate the knowledge through their lectures, study material, and evaluate
the performance of the students. Also, most of the higher education teacher are
not well trained in IT (information technology) aspect as they don’t get any
formalised training of IT and pedagogical skills before and after joining the
services. In that scenario, the support provided by institute becomes important
for them which may lead to self-efficacy and more usage of ICT in
teaching-learning process (Gruzd et al., 2012). Therefore, the next hypothesis
is:
H3:
FC is a motivational factor for attitude
to use ICT.
SI
In
a collective society like India, lots of decisions taken by individuals are
influenced by society and they follow herd behaviour. The correlation between
SI and attitudes towards behaviour is well researched and scholars find causal
link between them (Tarkiainen and Sundqvist, 2005). In the context of digital
teaching-learning process, various studies have also found positive
relationship between the SI and attitude to use ICT (Cheng et al. , 2016; Teo,
2015). For the present study, SI has been defined as the influence of
co-workers using ICT in teaching-learning process on the individual. In this
context, following hypothesis has been framed:
H4:
FC is a motivational factor for attitude
to use ICT.
Attitude
and Intention to Use:
In
literature attitude has been defined as the state of mind when an individual
based on the past experience or expected outcome is ready to adopt some
behaviour. Ajzen and Fishbein (1980) further explained attitude as a causal
factor to intention. They stated if positive attitude is high towards any
behaviour, the more intention to perform a specific behaviour. Therefore, the
study conceptualizes that high level of attitude towards use of ICT in
teaching-learning process will lead to greater intention to use ICT it by higher
education teachers. Thus, we postulate that:
H5:
Attitude to use ICT leads to intention to use it.
4.
RESEARCH METHODOLOGY:
4.1
Questionnaire Development:
TAM
has been used to study the various aspects of digital teaching-learning process
such as Learning Management Systems, use of ICT in classroom teaching, web-based
learning programmes etc. but there are handful of the studies which have explored
the motivational factors behind using ICT for higher education teachers and
absolutely no study has been found in Indian context. For the present study,
TAM model with two new constructs namely FC and SI has been used. With the help
of extant literature review, indicators have been identified under different
constructs namely PU, PEOU, FC, SI, attitude, and intention to use ICT. The
final statements pertaining to the instrument were adopted from (Gil-Flores et
al., 2017; Fathema et al., 2015; Teo, 2015).
4.2
Data Collection:
The
population for the study was the higher education teachers who has been trained
under PMMMNMTT (minimum for 10 days) for enhancing ICT skills. However, before distributing
the instrument for final survey, pilot study with 20 teachers (trained under
the scheme) was undertaken to ensure the completeness and clarity of statements.
For the study, convenience sampling method has been used to collect data from 145
teachers (78 percent response rate) who have attended training in the teaching
learning centers located in Delhi via both online and offline methods of data
collection. Table I presents the demographic profile of the higher education teachers.
62.84 percent of the participants were female teachers and majority of the them
were between the age groups of 31 to 50 years (81.76 percent). Half of the participants
were doctorate and only 6.08 percent were having only post graduate degree. Further,
63.51 percent were the higher education teachers of different Central Universities.
Table
I: Profile of Participants
|
Measure
|
Value
|
Frequency
|
Percentage
|
|
Gender
|
Male
|
54
|
37.16
|
|
|
Female
|
91
|
62.84
|
|
|
Total
|
145
|
100.0
|
|
Age
|
Below 30
|
10
|
6.75
|
|
|
31-40
|
52
|
35.81
|
|
|
41-50
|
67
|
45.95
|
|
|
51 and above
|
16
|
11.48
|
|
|
Total
|
145
|
100.00
|
|
Qualification
|
P.G.
|
9
|
6.08
|
|
|
M. Phil.
|
64
|
43.92
|
|
|
Ph.D.
|
72
|
50.00
|
|
|
Total
|
145
|
100.0
|
|
University
|
State
|
54
|
36.49
|
|
|
Central
|
93
|
63.51
|
|
|
Total
|
145
|
100.0
|
Source: Authors’ Work
5. Data Analysis:
5.1 Evaluation of the Outer Model:
SPSS
21 and AMOS 21 were used to analyse the data to conduct confirmatory factor
analysis and structural equation modelling on the proposed model. All the
parameters pertaining to reliability, convergent validity, and discriminant
validity were assessed before proceeding further. Table II shows that Cronbach
alpha value of each construct is more than threshold limit of .7 (Hair et al.,
2015) and internal consistency has also been achieved which is evident by the
values of composite reliability (≥.7 for each construct, Hair et al.,
2015).
Table II. Reliability measures
|
Statements
|
Std. Loadinga
|
Alpha Val.
|
CR
|
|
Perceived Usefulness
|
|
.728
|
.715
|
|
By
using ICT, I can finish my task quickly.
|
.642**
|
|
|
|
ICT
helps in improving my performance.
|
.616**
|
|
|
|
ICT
helps me in enhancing my effectiveness.
|
.635**
|
|
|
|
ICT
tools are advantageous for me.
|
.713
n.a.
|
|
|
|
Perceived Ease of Use
|
|
.815
|
.801
|
|
Using
ICT is easy for me.
|
.817***
|
|
|
|
I
think that using ICT does not require much effort.
|
.728***
|
|
|
|
By
using ICT it is easy for me to become skilful.
|
.721n.a.
|
|
|
|
Facilitating Conditions
|
|
.741
|
.750
|
|
I think, in case of
encountering any problem, assistance will be available to me.
|
.784***
|
|
|
|
I
think that timely assistance will be there in case of encountering any
problem.
|
.743***
|
|
|
|
I
think, I will get sufficient help in case of encountering any problem.
|
.697 n.a.
|
|
|
|
Social Influence
|
|
.721
|
.744
|
|
My
peer group think that I should use ICT.
|
.813***
|
|
|
|
People
closer to me think that I should use ICT.
|
.741**
|
|
|
|
I
want to use ICT as many people are using it.
|
.821n.a.
|
|
|
|
Attitude to Use ICT
|
|
.716
|
.732
|
|
It
is hard for me to stop using ICT, once I start using it.
|
.765**
|
|
|
|
I
look forward to use more technology in completing my job.
|
.732**
|
|
|
|
I
like using technology.
|
.703n.a.
|
|
|
|
Intention to use ICT
|
|
.730
|
.745
|
|
I
intend to use ICT in near future
|
.812n.a.
|
|
|
|
I
would recommend others to use ICT
|
.791***
|
|
|
|
I
would like to use ICT after going back to my institution
|
.731***
|
|
|
|
Note:
a significant at p ≤ 0.05**, p ≤ 0.001***
n.a.
– not applicable
|
Source: Authors’ Work
Table
III depicts the covergent and validity measures and also shows the correlation
matrix. The values of AVE were greater than .5 which showed the convergent
validity of the items within a construct while all the values of MSV and ASV
are less than AVE suggesting the discriminant validity among the constructs. Furthermore, Table IV shows the measurement models
estimates which were well within the desirable limits of values suggested by Hair
et al. (2015).
Table IV. Measurement Model Estimates
|
Model
|
χ2
|
d.f.
|
χ2/d.f.
|
GFI
|
TLI
|
CFI
|
Remsea
|
|
|
532.8
|
185
|
2.880
|
.835
|
.873
|
.816
|
.058
|
Source: Authors’ Work
5.2
Evaluation of the Inner Model:
Establishing
the Model fit:
Structural
equation modelling using AMOS 21 have been used to establish the relationships
among variables. All the six constructs that is PU, PEOU, FC, SI, attitude, and
intention to use ICT have been taken together to study the hypothesized model.
Table V gives a brief summary of the structural model and the values suggest
the good model fit as all the indices were falling within the prescribed limits
(Hair et al., 2015).
Table V. Structural Model Estimates
|
Model
|
χ2
|
d.f.
|
χ2/d.f.
|
GFI
|
TLI
|
CFI
|
Remsea
|
|
|
15.4
|
5
|
3.080
|
.905
|
.903
|
.896
|
.0498
|
Source: Authors’ Work
Hypothesis
Testing:
After
testing the model fit, the next step was to study the hypothesized theoretical
relationships. The structural model with β values is shown in Figure 2. Table
VI shows that FC is the most important motivating factor in attitude formation
towards ICT (β = .38, p < 0.001) followed by PEOU (β = .32, p <
0.001). Participants also feel that SI (β = .23, p < 0.05) is also
important for creating positive attitude towards ICT. Lastly, PU has positive
significant relationship with attitude to use ICT (β = .16, p < 0.001).
Lastly, the results show that attitude towards ICT leads to intention to use (β
= .48, p < 0.001). In sum, all the five hypotheses framed for the study have
been accepted. Figure 2 also shows that altogether all the exogenous constructs
undertaken in proposed model are explaining 53.3 percent (R2= .533)
of intention to use ICT.
Table VI. Hypothesis Testing Results
|
Hypothesis
|
Standardized
Co-efficient (β)
|
P-Value
|
Results
|
|
H1. PU -----> attitude
|
.16*
|
.032
|
Accepted
|
|
H2. PEOU ----- > attitude
|
.32***
|
.003
|
Accepted
|
|
H3. FC ------ > attitude
|
.38***
|
.002
|
Accepted
|
|
H4. SI ------> attitude
|
.23**
|
.001
|
Accepted
|
|
H5. attitude---à
Intention
|
.48***
|
.001
|
Accepted
|
|
Note: Significant at the p < 0.001***,
p < 0.05**, p < 0.01
|
Source: Authors’ Work
6.
DISCUSSION AND CONCLUSION:
The
objective of the present study was to identify the motivational factors towards
intention to use ICT by higher education teachers. For this purpose, two
additional variables namely FC and SI have been added to the TAM model to
increase the explanatory power of the proposed model. The results reveal that
PU, PEOU, FC, and SI are important motivations behind in framing the positive attitude
towards usage of ICT which further leads to intention to use it.
To
begin with, results exhibit that result reveal that positive attitude is very
important in explaining the intention to adopt behavior. Numerous studies have
found that attitude has positive significant influence on intention to use in
various contexts (Hoque, 2016; Taylor and Levin, 2014). In the context of
electronic mediums of teaching and learning also positive and significant
relationship has been reported by the scholars (Jin, 2014; Teo, 2011). Further,
FC has been found the strongest motivator of attitude towards usage of ICT and
teachers find that inspite of giving n number of trainings if there is no
technical support at the institutional level, the results will never be encouraging.
A close probing to such view suggests that the faculties are not technically
sound since they are not professionaly trained in such skills and they need
technical assitance whenever a technical glitch occur or when they forget
certain steps or operations. Hence, in the absence of that assistance teachers
may feel lack of efficacy to handle ICT at their own. Attuquayefio and Addo (2014)
also found that FC significantly affected user behaviour towards acceptance of
ICT.
Furthermore,
PEOU is emerging as second most important motivational factor in forming
attitude towards usage of ICT. Technology is perceived as a skilled job and for
any person who is not in the habit of using technology in day to day life
(especially in work life) generally avoids using it if it is optional at
workplace. Therefore, to make a technology acceptable among everyone it is of
foremost importance that interface of technology should be simple and easy to
use. Facebook and What’s App , Amazon, Uber etc. are the live examples of user
friendly technology solutions. The present study validates the work of earlier
studies and establishes that if higher education teachers perceive any
technology easy they will use it in their jobs (Teo, 2015; Fathema et al.,
2015).
The
present study also found that SI plays an important role in motivating higher
education teachers to develop an attitude towards usage of ICT. The behaviour
of the teachers can largely be influenced by their peer groups mainly because
of two reasons. First, they get motivated if someone from their friend circle
uses the ICT in class and also pursue them to use it. Second, when other peer
teacher is using ICT in class and having better results then because of
competition or to impress authority or students, they can feel motivated to use
it. In other words, SI can motivate with positive as well as negative emotion.
Lastly,
the study found direct relationship between PU and attitude to use ICT. Though
it seems from the result that PU is least important variable for motivating the
teachers for using it. But, there is another view which states that there is no
doubt about the usefulness of ICT in the mind of the teachers. As they are
witnessing the changes made by the technology in daily life by making the tasks
easy, fast, convenient, transparent etc. For example, online banking, online
shopping, online booking of tickets, etc.
In
sum, all the four variables i.e. PU, PEOU, FC, and SI were found to be the
motivating factors of attitude to use ICT which further leads to intention to use
ICT.
7.
CONTRIBUTION OF THE STUDY:
The
present study contributed both in academics and practical context. Theoretically,
the study proposed and validated the extended TAM model in the context of
intention to use ICT in digital teaching- learning paradigm. Further, in terms
of practical context, the present study has substantially contributed in many ways.
Since, the survey participants were the trained higher education teachers
therefore, the insights taken from their views are valuable. First insight is
that teachers find FC of paramount importance and authorities can take a very
important clue from it. They should not only focus on the ICT training to the
teaching staff but also take care of tcehnical support and infrastructure aspect
of the institution. Failing to which will prove the waste of time, money, and
energy spent on training.
Second,
government in general and institute authorities in particular may think about
introducing and training the teaching staff the simple and effective tools of
ICT so that maximum people can use them. Moreover, they can also think of developing
customized portal or tools to cater the specific needs of institutes so that
inhouse staff can embrace it more willingly.
Third,
institutes can provide additional incentives to the faculties for using ICT so
that more and more people are motivated to use these tools. These incentives
can be monetary or non-monetary such as admiring faculty in public, opportunity
to attend more trainings why helping them financially, to give them role of
trainer etc.
Lastly,
continuous dialogue should be there among all the stakeholders such as teaching
staff, students, parents, higher authorities, training institutes etc. so that
everyone undersatnds the usability of the ICT and may ponder upon the unique
and new ways to use ICT in their job without using minimum of effort and
infrastructure.
%20Articles---1-Revised-31-05-19----------RAHUL--------DELHI--------PAGE--7_files/image003.jpg)
Figure
2: Structural Model of the Study
8.
LIMITATIONS AND FUTURE WORK:
The
present study is conducted with few limitations. Though the research model has
been validated in the Indian setting but to make the model for parsimonious
more studies should be undertaken in different parts of the country and other
economies. Second, the study has not compared the teachers’ intention to use
ICT for different cohorts such as age, gender, status of university etc.
however, future studies may take it into account. Further, longitudinal study
can be done to study the adotion behaviour of the higher education teachers.
Lastly, the study did not specify the ICT tools while completing the survey so
the insights gained from the study is general and may not apply to specific tools
such as LMS, M-learning etc.
9.
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