IJLTER Journal Explores Mobile Learning During Covid

International Journal
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1694-2493
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Vol.21 No.3

International Journal of Learning, Teaching and Educational Research
(IJLTER)
Vol. 21, No. 3 (March 2022)
Print version: 1694-2493
Online version: 1694-2116
IJLTER
International Journal of Learning, Teaching and Educational Research (IJLTER)
Vol. 21, No. 3
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VOLUME 21 NUMBER 3 March 2022
Table of Contents
Determinants of High School Learners' Continuous Use of Mobile Learning during the Covid-19 Pandemic.........1
Admire Chibisa, David Mutambara
Speaking Skills Enhancement through Digital Storytelling among Primary School Students in Malaysia.............. 22
Khasturi Ramalingam, Yeo Kee Jiar, Siva Mathiyazhagan
Item Analysis of a Reading Test in Sri Lankan Context Using Classical Test Theory................................................. 36
Fouzul Kareema Mohamed Ismail, Ainol Madziah Bt Zubairi
Employing Exploratory and Pooled Confirmatory Factor Analysis for Reliability and Validity of Peer-Led Fun
Inspiring Inquisitive Scale ................................................................................................................................................... 51
Kho Chee Yuet Fanny, Khayri Zaid Z Alzalit
The Application of Mobile-Enhanced Collaborative Learning Models on Oral Presentation Competence in Rural
Area During Covid-19 Pandemic........................................................................................................................................ 71
Dzul Rachman, Margana ., Priyanto .
The Impact of Mentoring in the Development of Pre-Service Teachers from a University in South Africa............. 88
Clever Ndebele, Dagogo William Legg-Jack
Linear Predictors of Perceived Graduate Employability among South Africa’s Rural Universities’ Learners during
the Covid-19 Pandemic...................................................................................................................................................... 106
Herring Shava
Challenges of Pre-service Teachers in Rural Places of Teaching Practice: A Decolonial Perspectives.................... 127
Bunmi Isaiah Omodan
A Traditional Game-Based Parenting Model as a Cultural-Inheritance Medium in Early Childhood Education 143
Suteja ., Saifuddin ., Farihin ., Aris ., Widodo Winarso
Students’ Acquisition of Science Process Skills in Chemistry through Computer Simulations and Animations in
Secondary Schools in Tanzania......................................................................................................................................... 166
Flavia Beichumila, Bernard Bahati, Eugenia Kafanabo
Fostering Scientific Creativity in the Classroom: The Concept of Flex-Based Learning ........................................... 196
Kurt Haim, Wolfgang Aschauer
The Impact of Production-oriented Approach on Oral English Performance of Senior High School Chinese
Students: An Application Study ....................................................................................................................................... 231
Lixuan Sun, Adelina Asmawi
The Impact of a Debriefing Strategy in Online ESL Classrooms .................................................................................. 247
Sasirekha Kandasamy, Tan Kim Hua, Fazal Mohamed Mohamed Sultan

Teacher Unions, Schools and Success: Opportunities and Contradictions .................................................................263
Vuyisile Msila
Instrument Measuring the Adaptability of University Students to Online Learning (SOLE) and Its Predicting
Factors .................................................................................................................................................................................. 281
Ateerah Abdul Razak, Azahah Abu Hassan Shaari, Lukman Zawawi Mohamad, Amanina Abdul Razak Mohamed, Asma
Lailee Mohd Noor
Relationship between Spirituality, Nature Connectedness, and Burnout of Schoolteachers during Online Classes
amid Covid-19 Pandemic: The Moderating Role of Gender......................................................................................... 301
Tengku Farhanan Tengku Mohamed, Samsilah Roslan, Zeinab Zaremohzzabieh, Seyedali Ahrari
Parental Involvement in Young Children’s Education in Malaysia: A Systematic Literature Review.................... 319
Siti Soraya Lin Abdullah Kamal, Abdul Halim Masnan, Nor Hashimah Hashim
A Look Back: Assessment of the Learning Outcomes of the Community-Based Research Experiences of the Senior
High School Students of a Higher Education Institution in Batangas ......................................................................... 342
Joseph Angelou Ilagan Ng
The Relevance of Learning Methods in Realising Student-Centred Transformative Learning................................ 359
Mariana Simanjuntak, Merry Meryam Martgrita, Juli Yanti Damanik, Monalisa Pasaribu
Content Learning through Languaging: Translingual Practices in a Graduate-level Teacher Preparation EMI
Course in South Korea ....................................................................................................................................................... 379
Hyunjin Jinna Kim, Yong-Jik Lee, Yue Li
Case-Based Instruction in the Forensic Chemistry Classroom: Effects on Students' Motivation and Achievement
............................................................................................................................................................................................... 396
Epiphania B. Magwilang
Teachers’ Level of Knowledge and Readiness in Integrating 4IR: Primary ESL Classroom Context...................... 415
Nur Maechea Avelino, Hanita Hanim Ismail
Development of the Love for Writing and Publishing Journal (LWPJ) Module for Higher Education .................. 434
Syaidatun Nazirah Abu Zahrin, Mohd Izwan Mahmud, Norzaini Azman

1
©Authors
This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0
International License (CC BY-NC-ND 4.0).
Vol. 21, No. 3, pp. 1-21, March 2022
https://doi.org/10.26803/ijlter.21.3.1
Received Dec 23, 2021; Revised Feb 6, 2022; Accepted Feb 24, 2022
Determinants of High School Learners'
Continuous Use of Mobile Learning during the
Covid-19 Pandemic
Admire Chibisa
Department of Mathematics, Science and Technology Education,
University of Zululand, Faculty of Education
David Mutambara
Department of Mathematics, Science and Technology Education,
University of Zululand, Faculty of Education
Abstract. Every child has a right to education and attending school is a
must in South Africa. However, school attendance was severely
disrupted by the Covid-19 pandemic outbreak. Regardless, the academic
process has to continue, hence the use of mobile devices as pedagogical
tools for learning. The aim of this study therefore is to explore the
determinants of high school learners' continuous use of mobile learning
in order that the academic project may continue. The study employed a
survey design in which quantitative data were collected using a seven-
point Likert-type scale questionnaire developed by the researchers. A
stratified sample of 500 high school learners participated in the survey of
which 419 of them successfully completed the survey, giving a success
rate of 83.8%. The remaining 16.2% submissions were spoilt and hence
discarded. The study combined three models, namely the technology
acceptance model (TAM), self-determination theory (SDT), and the
expectation-confirmation model (ECT) in its analysis of the developed
seven-construct model which used partial least squares structural
equation modelling (PLS-SEM). SmartPLS v 3.0 was used to validate the
measurement and structural models of the study. Results showed that all
six variables identified for the model were good predictors of high school
learners’ continuous use of mobile learning with 68% explained variance
for satisfaction and 39.1% for continuous use. The study developed and
validated a robust mobile learning model which is recommended to
stakeholders for continuous use of mobile learning. Future researchers
are encouraged to search for more determinants of continuous use of
mobile learning that have not been identified in this study.
Keywords: high school learners; continuous use; user satisfaction; mobile
learning

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http://ijlter.org/index.php/ijlter
1. Introduction
Thousands of people died in China in 2003 as a result of a kind of upper
respiratory tract pneumonia known as severe acute respiratory syndrome (SARS)
(Tang et al., 2021). An even deadlier new coronavirus (COVID-19) that possibly
originated in Wuhan (Yang et al., 2020) has spread throughout China and around
the world with catastrophic effects (Guan et al., 2020). By the end of October 2020,
the coronavirus pandemic had killed over one million people and infected over
42 million individuals (UNESCO, 2020).
The coronavirus has had a negative impact on the world economy and human
social activities, including the school system (Duan et al., 2020). Owing to the
overwhelming spread of COVID-19, South Africa, as the other 190 countries of the
world, implemented a national lockdown on 26 March, 2020 (Shrotri et al., 2021).
COVID-19 affected about 1500 million students world-wide (UNESCO, 2020).
The Department of Basic Education (DBE) in South Africa encouraged schools to
use mobile learning (Mutambara & Bayaga, 2021). The DBE argued that mobile
learning enables teaching and learning to continue while observing the lockdown
restrictions and encouraging social distancing. The DBE also stated that mobile
learning can help learners to have access to learning material anytime and
anywhere (Mutambara & Bayaga, 2021). Mobile learning also helps learners learn
at their own pace. Furthermore, the DBE argued that mobile learning provides
learners with opportunities to carry out self-regulated learning.
However, there are several obstacles to implementing mobile learning. On the
learners' side, many communities, particularly in rural areas, lack electricity, have
a sluggish Internet connection at home, or do not have a mobile device capable of
supporting mobile learning (Mutambara & Bayaga, 2021). As a result, a shift to
mobile learning could exacerbate long-standing equality issues. Teachers are
concerned about what to teach, how to teach, and how to meet each learner’s
learning needs (Kim, 2020). Despite these challenges, schools switched to mobile
learning in order to save the academic process.
Many scholars and online educators believe that the mobile learning that took
place during the coronavirus pandemic can be used to address the shortcomings
of traditional face-to-face education in developed countries (Mutambara &
Bayaga, 2021; Wang et al., 2021). Mobile learning can assist learners and schools
in crisis situations by providing unique opportunities. It has several advantages,
including the ability for educators and learners to continue teaching and learning
in any location without interruption. Mobile learning can also assist learners take
charge of their education. Furthermore, it can be used to alleviate school textbook
shortages. Mobile learning can also be used to help students understand concepts
because the technology can mentally stimulate learners (Mutambara & Bayaga,
2021).
Although mobile learning provides flexible activities and abundant learning
resources (Luo et al., 2021), the value of mobile learning may not be realised if
learners are unable to use it on a continuous basis (Tang et al., 2021; Wang et al.,
2021). “The nature of technology empowers learners with the necessary
‘possibilities,' not with ‘ready to use' resources,” (Wang et al., 2021, p. 10). In the

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realm of information systems (ISs), the success of an IS such as mobile learning is
ultimately determined by its continued use rather than its initial use (Albelali &
Alaulamie, 2019; Bhattacherjee, 2001). If learners are unable to use mobile learning
on a regular basis or after the pandemic, the value of mobile learning will be lost.
This means that mobile learning has become an integral part of the school system’s
pedagogy which should be perpetuated at all costs (Mutambara & Bayaga, 2021).
This calls for the continuous use of this mobile learning. However, very little is
known about high school learners’ continuous use of this technology.
This study aims to explore the determinants of high school
learners' continuous use of mobile learning. The focus is more on continuous use
of mobile learning, an area of which very little is known. Most research studies
have focussed on the pre-acceptance of mobile learning (Albelali & Alaulamie,
2019; Amzaourou & Oubaha, 2018; Cheng & Yuen, 2020; Shao, 2018). It also aims
to investigate whether social moderators have an influence on high school
learners' continuous use of mobile learning. Therefore, the motivations for the
present research are as follows:
1. To investigate the determinants of high school learners’ continuous use of
mobile learning; and
2. To investigate the effect of social moderators (gender, geographical area, and
educational level) on high school learners’ continued use of mobile learning.
2. Literature Review
2.1 Mobile learning
In the body of knowledge, there are numerous definitions of mobile learning.
According to Albelali and Alaulamie (2019), mobile learning is defined as learning
that takes place through wireless devices such as iPods, laptops, smartphones,
USBs, cameras, and personal digital assistants (PDAs). In terms of mobility,
mobile learning is defined as the provision of education and training utilising
devices that are convenient to carry and use anywhere, at any time, such as
cellphones, PDAs, and palmtops (Mutambara & Bayaga, 2020). Mutambara and
Bayaga (2021) described mobile learning as an extension of e-learning supported
by wireless mobile devices and communication for teaching and learning. In the
current study, mobile learning is defined as the use of wireless mobile devices
such as cellphones, tablets, iPods, laptops, and USBs by high school learners’
learning.
2.2 Social moderators
The enterprise content management (ECM) to assess users' continued usage of an
information system was used by Venkatesh et al. (2011) who recommended that
future research focus on the influence of social moderators on continuous use.
The assessment of educational technology continuous research revealed that the
effects of social moderators on educational technology continuous use have not
been adequately explored (Lee, 2010). Geographical area, age, gender and level of
education are the commonly studied social moderators of educational technology
acceptance and continuous use (Almahamid & Rub, 2011). However, the
moderating effects of these moderators on the continuous use of educational
technology need to be further understood (Lee, 2010).

4
There are contradictory results of the social moderators on the continuous use of
educational technologies. Existing research also supports social moderators'
moderating effects on technological acceptance (Albelali & Alaulamie, 2019;
Amzaourou & Oubaha, 2018; Cheng & Yuen, 2020; Shao, 2018). Cheng and Yuen
(2020) studied the effects of gender, experience, and socioeconomic position on
secondary students' acceptance and continued usage of e-learning systems. They
measured the experience using the students’ grades. In this case, the grade of the
student is used to determine the learner's level of education. Gender and level of
education were found to be significant moderators. Amzaourou and Oubaha
(2018) investigated the moderating effect of gender, educational level, and
geographical area on university students’ use of online learning. Geographical
area and gender were found to be good moderators of students’ use of online
learning but not educational level. Shao (2018) noted that gender plays an
important moderating role on university students’ continuous use of massive
open online courses. Female students’ continuous use of mobile learning was
reported to be weaker than that of their male counterparts (Albelali & Alaulamie,
2019).
Contrary to the findings of these studies (Amzaourou & Oubaha, 2018; Cheng &
Yuen, 2020), a study by Almahamid and Rub (2011) indicated that there is no
significant difference in the assessment of continuous desire to utilise e-learning
systems by research participants based on demographic variables such as gender,
age, and level of education. These findings were confirmed by Tarhini et al. (2015),
who noted that only socioeconomic difference was a good moderator.
Considering the results of these studies (Almahamid & Rub, 2011; Amzaourou &
Oubaha, 2018; Cheng & Yuen, 2020; Tarhini et al., 2015), one can learn that more
studies that focus on the effects of social moderators are needed to help to
understand their effects on the continuous use of educational technologies.
2.3 Theoretical framework
There have been very few studies conducted to investigate the factors that
influence users' continuous use of educational technologies (Luo et al., 2021;
Ramadiani et al., 2019; Wu & Chen, 2017). Ramadiani et al. (2019) extended the
unified theory of acceptance and use of technology (UTAUT) to predict students’
continued use of Wiki. On the other hand, Wu and Chen (2017) extended the TAM
to explain users’ continued use of online learning. The SDT was used by Luo et al.
(2021) to describe students’ motivation and continued use of online learning.
However, the transferability of the findings of these to high school learners’
continuous use of mobile learning, especially in developing countries, might be
limited. The TAM and the UTAUT were developed to predict initial acceptance of
technology (Venkatesh et al., 2011); therefore, their applicability to predict
continuous use of mobile learning might be limited (Mutambara & Bayaga, 2021).
Additionally, since most of these studies were carried out in institutions of higher
learning of developed countries, the generalisation of these findings to high
schools of developing nations in particular might be limited as well.
Amzaourou and Oubaha (2018) emphasised the importance of developing
countries’ conducting their own technology acceptance and usage studies rather
than blindly following developed-country examples. To that end, it is critical to

5
establish the determinants of high school learners in developing nations’
continuous use of mobile learning. In doing so, three models were used in this
study: the TAM, the SDT, and the ECM). TAM and SDT models have been widely
used to predict mobile learning acceptance (Al-Emran et al., 2018). In contrast,
ECM has rarely been utilised to investigate students' intentions to use educational
technologies. The ECM, proposed by Bhattacherjee (2001), developed a theoretical
psychological framework in consumer behaviour that gives a clear approach of
explaining how customer intention to purchase a product is influenced by
comparing both early (pre-purchase) and later (post-purchase) anticipation.
According to Lin et al. (2005), such a model is critical to employ when analysing
a consumer's continuous intent to use mobile learning. Combining these three
models will add value to the body of knowledge because the TAM and SDT have
been tried and tested in the context of mobile learning, while the ECM brings post-
acceptance and the continuous use.
Information systems (IS) research on continuous use behaviour is split into three
distinct but slightly overlapping groups (Larsen et al., 2009). This is also the case
for mobile learning continuity. The first category includes studies that use
information system adoption characteristics as antecedents to explain the
continuous use of mobile learning (Limayem & Cheung, 2008; Roca & Gagné,
2008). As their basic variables, these articles typically incorporate variables from
the originally suggested ECM (Bhattacherjee, 2001). In the second group, are
studies that seek to break down the originally postulated ECM variables and
evaluate them as antecedents for explaining the continuous use of mobile learning
(Chiu et al., 2007; Sørebø et al., 2009). The third and last category of works
attempts to connect the IS-continuance theory with complementary theoretical
approaches (Liu et al., 2009).
This research falls within the third category. Following the studies of Liu et al.
(2009) and Sørebø et al. (2009), the starting point is Bhattacherjee's (2001) ECM and
the added viewpoint is the self-determination theory by Gagné and Deci (2005).
Liu et al. (2009) and Sørebø et al. (2009) established that SDT is complimentary to
ECM in understanding continuance intentions to use educational technologies.
This study also added perceived ease of use, which is one of the pillars of the
TAM. ECM's strength is that it stresses high school learners' mobile learning pre-
adoption expectations as well as post-adoption usefulness and ease-of-use views.
The latter of these, namely utility and ease-of-use beliefs, were characterised as
extrinsic motivators of the TAM by Davis et al. (1992). In contrast, the self-
determination theory emphasises basic need fulfilment and the development of
real inner motivation, despite extrinsic incentive still being significant.
2.4 Hypotheses formulation and the conceptual framework
2.4.1 Satisfaction (SAT)
According to Zhou (2017), satisfaction is a mental state that embodies the sum of
a user's material and emotional responses to a specific activity, such as mobile
learning. When the outcomes meet the user's needs, expectations, task orientation,
and goal determination, they will be emotionally satisfied. User’s satisfaction is
considered to be an important substitution for an information system’s success.
According to the Chong (2013), the user information system’s continuation

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intention is mostly defined by satisfaction with that information system's use.
Bhattacherjee (2001) argued that satisfaction generated after actual use is the
primary determinant of continuance intention. A high level of satisfaction leads
to a high level of continuance intention. Chong (2013) found that satisfaction is
commonly regarded as a moderator variable of post-purchase behaviour. Zho
(2017) confirmed that consumer satisfaction, promotes future behavioural
intention. Based on the assessments of Zhou (2017), Chong (2013) and
Bhattacherjee (2001) one can conclude that users will be materially satisfied as a
result of their system usage experience. The current study proposes that high
school learners who are satisfied with a mobile learning system may continue to
use it and suggest it to others. Therefore, the hypothesis, namely
H1: High school learners’ satisfaction has positive influence on continuous use of mobile
learning.
2.4.2 Confirmation (CONF)
In the context of information systems, confirmation is defined as the evaluation of
users' ability to meet expectations, confirmation being proportional to satisfaction
(Tang et al., 2021). Bhattacharjee (2001) stated that confirmation and perceived
usefulness (PU) have a positive relationship. According to the cognitive
dissonance theory, when a user's pre-acceptance perception of PU is contradicted,
they may experience cognitive inconsistency or worry (Chong, 2013). Users
frequently attempt to change their perception of pre-acceptance usefulness so that
it corresponds to post-acceptance reality (Chong, 2013). That is, confirmation
increases PU while decreasing the likelihood of disconfirmation. Chong (2013)
found that perceived usefulness influences confirmation, which in turn influences
satisfaction. Additionally, Tang et al. (2021) noted that user confirmation is a
critical requirement for satisfaction. This study posits that high school learners’
perceived influence will influence their confirmation, and confirmation will
predict their satisfaction. Therefore, the hypothesis, namely
H2: High school learners’ confirmation has a positive impact on their satisfaction.
2.4.3 Perceived usefulness (PU)
Mutambara and Bayaga (2021) define perceived usefulness in the context of
mobile learning as an individual's perception that utilizing mobile learning will
enhance his or her teaching and learning. One of the most typical constructs of
extrinsic incentive for IS use is PU (Wang et al., 2021). Over the past few decades,
PU has continuously been verified as the major factor of continuous IS use
(Bhattacherjee, 2001; Mutambara & Bayaga, 2020). Wang et al. (2021) confirmed
the effect of PU on continuous use. Luo et al. (2021) noted that PU influences not
only learners' continuing use, but also their satisfaction. Based on the findings of
Luo et al. (2021) and Tang et al. (2021), it can be concluded that the belief that
mobile learning can enhance learners’ performance influences their satisfaction
which in turn reinforces their continued use of mobile learning. Therefore, the
hypotheses, namely
H3: High school learners’ perceived usefulness has a positive influence on confirmation.
H4: High school learners’ perceived usefulness has a positive influence on continued use.
H5: High school learners’ perceived usefulness has a positive influence on satisfaction.

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2.4.4 Perceived autonomy (PA)
Supporting students' perceived autonomy entails assisting and encouraging them
to pursue their personal objectives (Sierens et al., 2009). Mobile learning provides
teachers with several tools that can be used to meet diverse learners’ needs. These
tools enhance learners’ perceived autonomy by allowing them to take charge of
their education without being controlled by teachers. Supporting students'
perceived autonomy entails assisting and encouraging them to pursue their
personal objectives. Several studies have found a link between autonomy-
supportive teaching and educational benefits, such as increased intrinsic
motivation, which lead to improved learners’ performance and satisfaction (Luo
et al., 2021). Perceived autonomy was shown to have a significant positive impact
on perceived enjoyment but not on perceived usefulness. This study postulates
that learners’ perceived autonomy will influence their perceived usefulness and
satisfaction. Therefore, the hypotheses, namely
H6: High school learners’ perceived autonomy will influence their perceived usefulness.
H7: High school learners’ perceived autonomy will influence their satisfaction.
2.4.5 Perceived competence (PC)
This study defines perceived competence as learners’ perceptions of their skills to
manage and execute learning tasks in order to improve their performance. Luo et
al. (2021) showed that perceived competence influences learners’ perceived
usefulness. Extrinsic motivation (perceived usefulness) and learners’ satisfaction
have been shown to be influenced by computer competence (Yang & Brown,
2015). Learners who perceive themselves as computer competent are likely to
perceive mobile learning to be easy to use and satisfying. Therefore, the
hypotheses, namely
H8: High school learners’ perceived competence influences their perceived ease of use.
H9: High school learners’ perceived competence will influence their satisfaction.
2.4.6 Perceived ease of use (EoU)
Perceived ease of use was defined as the extent to which users believe that
adopting mobile learning would be free from effort (Mutambara & Bayaga, 2020).
Pratama (2021) confirmed the positive effect of learners’ EoU on perceived
usefulness and behavioural intentions. However, the effect of EoU on continuous
use needs to be more clearly understood. In this study, the belief that using mobile
learning would be effort free will influence high school learners’ continuous use.
Therefore, the hypotheses, namely
H10: High school learners’ perceived ease of use influences their perceived usefulness.
H11: High school learners’ perceived ease of use will influence their continued use.
According to the proposed conceptual model in Figure 1, EoU predicts PU as well
as continuous use. The PC predicts EoU and Sat. PA predicts PU and SAT, which
are both factors influencing continuous use. PU is a predictor of COMF, which is
a predictor of SAT.

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Figure 1: Conceptual model
3. Research Methodology and Procedure
A survey design was used in this investigation. A survey design investigates a
subset of the population in order to generate a quantitative assessment of the
population's opinions (Creswell & Poth, 2016). In this study, a survey was
conducted to obtain a quantitative picture of how high school learners felt about
the continuous use of mobile learning. A survey was chosen because it enabled
the collection of a large dataset from high school learners in a short period of time
and at a reasonable cost. In this study, a survey was employed to collect opinion-
related data from high school learners by means of a questionnaire. Initially,
descriptive statistics were employed to examine demographic data from high
school students. Subsequently, the conceptual model was tested using PLS-SEM.
3.1 Participants
To collect data, stratified sampling was used. All high schools in South Africa's
King Cetshwayo District were classified according to their quintiles. A stratum
was formed by grouping schools in the same quintile. Placing schools in the same
quintile in a stratum ensures that homogeneous elements are placed in the same
stratum, reducing any estimation error (Creswell & Poth, 2016). There were five
strata altogether. Using simple random sampling, only one school was chosen
from each stratum. Learners in the five selected schools were also classified
according to their educational phase. In high school, there are two phases: General
Education and Training (GET) (grades 8 and 9) and Further Education and
Training (FET) (grades 10 to 12). Simple random sampling was utilised to choose
50 pupils from each phase from the selected schools. There were 500 people
chosen in all.
Out of 500 questionnaires administered, 435 (87%) were collected. However, only
83.8 % (419 responses) were used in this study, with the remaining 16 responses
being eliminated during data screening. A total of 59.9 % (251) of respondents
were in the GET phase, while 40.1 % (168) were in the FET phase. In terms of

9
gender, 246 (58.7 %) of the 419 respondents in this study were females, while the
remaining 173 (41.3 %) were males. There were 176 (42.0 %) learners from rural
areas, 109 (26.0 %) from semi-urban areas, and 137 (32.0 %) from urban areas.
Each of the three latent variables (CUSE, PA, and PC) had five indicators. These
latent variables had the most indicators in the model. Using the advice of Sarstedt
et al. (2017), namely that a sample size must be ten times larger than the number
of indicators on the latent variable with the most indicators being used, the
required minimum sample size was 50. The sample size for this study exceeded
this stated limit by far.
3.2 Research instrument
There were two sections to the research instrument. The first component asked
for biographical information from respondents. On a seven-point Likert-type
scale, respondents were asked to choose one of seven answers ranging from
‘strongly disagree’ to ‘strongly agree’ in the second phase. The research
instrument utilized in this study was derived from previous research.
Furthermore, in order to have the range of questions required for each construct,
several questionnaire items had to be changed and updated. Because of the large
number of items required in the research instrument, questions from different
surveys had to be adapted and modified. The research instrument contained
44 items in total. Additionally, the conceptual model was developed using
constructs from different models. As a result, it was anticipated that simply
adopting and changing one questionnaire would be inadequate. The
questionnaire items were developed from prior studies (Cheng & Yuen, 2020; Lu
et al., 2019; Sørebø et al., 2009) and modified to meet the objectives of this
investigation.
3.3 Analysis procedure
The Software Package for Social Sciences (SPSS) was used to screen the data. The
SPSS was also used for analysing descriptive statistics. The data was then
exported to the SmartPLS software, which was used for analysing the data by
means of PLS-SEM. According to Sarstedt et al. (2017), the primary objective of
PLS-SEM is to forecast the target variable, in this case, the continuous use of
mobile learning by high school learners. The PLS-SEM methodology was also
used to determine the moderation effects of demographics (gender, geographic
area, and educational level) on high school learners’ continuous use of mobile
learning.
The two-stage model analysis approach proposed by Sarstedt et al. (2017) was
followed in current study. The quality of the measurement model was evaluated
by checking the reliability and validity of model variables and their indicators.
The measurement model establishes the relationship between the constructs and
their respective indicators. In the second stage, the structural model's linkages
were evaluated by examining the significance of the path coefficients, explained
variance of endogenous variables, and predictive capacity of distinct variables
(Hair Jr. et al., 2021).

10
4. Presentation of results
4.1 Measurement model
The measurement model is validated to ensure the appropriateness of
the constructs added to the model. This is performed by evaluating the
convergent validity, internal consistency, and discriminant validity of the
measurement model (Hair et al., 2021). Internal consistency reliability was
determined using the composite reliability (CR) and Cronbach's alpha (CA) tests.
Results in Table 1 show that all the CR and CA values were greater than 0.7,
thereby confirming indicator reliability (Hair Jr. et al., 2021). The outer loadings
and average extracted variance (AVE) were used to assess the convergent validity.
Results in Table 1 show that all the AVE values were greater than 0.5. The results
in Table 1 also show that, with the exception of CUSE5 (0.604), all the other outer
loadings were greater than 0.7. The construct CUSE5 was retained owing to its
contribution to content validity (Hair Jr. et al., 2021). The results of the outer
loadings and AVE confirmed the convergent validity of the proposed model (Hair
Jr. et al., 2021).
Table 1: Measurement model
Construct Item Loadings CA CR AVE
Conformation
CONF1 0.740
0.830 0.887 0.663
CONF2 0.811
CONF3 0.800
CONF4 0.899
Continuous
use
CUSE1 0.805
0.828 0.879 0.594
CUSE2 0.804
CUSE3 0.846
CUSE4 0.772
CUSE5 0.604
Perceived
ease of use
EoU1 0.829
0.810 0.887 0.725
EoU2 0.818
EoU3 0.904
Perceived
autonomy
PA1 0.744
0.871 0.907 0.663
PA2 0.777
PA3 0.838
PA4 0.883
PA5 0.820
Perceived
competence
PC1 0.889
0.915 0.937 0.749
PC2 0.778
PC3 0.873
PC4 0.868
PC5 0.912
Perceived
usefulness
PU1 0.810
0.857 0.903 0.700
PU2 0.852
PU3 0.865

11
PU4 0.817
Satisfaction
SAT1 0.826
0.914 0.940 0.796
SAT2 0.902
SAT3 0.914
SAT4 0.924
The Heterotrait-Monotrait ratio (HTMT) was utilised in the study to assess
discriminant validity. Hair Jr. et al. (2021) proposed that the HTMT correlation
ratio delivers more accurate discriminant validity results than cross-loading and
the Fornell-Larcker criterion. The HTMT values in Figure 2 were all less than 0.85,
indicating that the results supported discriminant validity (Hair Jr. et al., 2021).
The structural model was evaluated after establishing the suitability of the
constructs in the measurement model.
Figure 2: The HTMT
4.2 Structural model
The variance inflation factor values (VIF) were utilized to evaluate the model's
collinearity issues. The VIF values ranged from 1.000 to 2.354, as shown in Table
2. All of the predictors' VIF values were less than 4 (Hair Jr. et al., 2021),
demonstrating that the model was not affected by collinearity issues.
Bootstrapping (with 5000 subsamples) was performed to examine the statistical
significance of each hypothesis (Hair Jr. et al., 2021). The results are summarised
in Table 2. Only three of the 13 hypotheses examined were not statistically
significant. The hypotheses which were not statistically significant were EoU to
CUSE (β = -0.022, t = 0.755 p > 0.05), PA to CUSE (β = 0.028, t = 0.608 p > 0.05),
and PA to PU (β = 0.041, t = 0.567 p > 0.05).

12
Table 2: Path coefficients
Path Std Beta T-Statistics P Values Decision f-squared
VIF
Values
CONF -> SAT 0.466 8.317 0.000 Accepted 0.470 1.447
EoU -> CUSE 0.022 0.313 0.755 Rejected 0.000 1.650
EoU -> PU 0.314 4.988 0.000 Accepted 0.095 1.161
PA -> CUSE 0.028 0.513 0.608 Rejected 0.001 1.398
PA -> PU 0.041 0.573 0.567 Rejected 0.002 1.161
PA -> SAT 0.077 1.999 0.050 Accepted 0.030 1.440
PC -> CUSE 0.226 2.875 0.004 Accepted 0.036 2.354
PC -> EoU 0.610 12.320 0.000 Accepted 0.594 1.000
PC -> SAT 0.388 6.400 0.000 Accepted 0.303 1.551
PU -> CONF 0.325 5.084 0.000 Accepted 0.118 1.000
PU -> CUSE 0.245 3.525 0.000 Accepted 0.074 1.335
PU -> SAT 0.119 2.630 0.009 Accepted 0.034 1.288
SAT -> CUSE 0.257 3.315 0.001 Accepted 0.051 2.138
CUSE -- continuous use, PU – perceived usefulness, EoU – perceived ease of use, PA –
perceived autonomy, PC – perceived competence, CONF – conformation, and SAT –
satisfaction
The f-squared statistic was used to determine how much each exogenous
construct contributed to the explained variance of its endogenous counterpart.
The results are shown in Table 2. Cohen (2003) specifies acceptable effect sizes as
0.02, 0.15, and 0.35, to mean small, medium, and substantial, respectively. The
effect size of CONF to SAT (0.470) and PC to EoU (0.594) were deemed substantial
by Cohen's standard (Cohen, 2003). The effect size of PC to SAT (0.303) was
medium, while the rest had a small effect size.
The R-squared value is the sum of all the predictors' contributions to the explained
variance of the exogenous variable (Hair Jr. et al., 2021). The R-squared value of
the model was 0.391, as shown in Figure 3. According to the findings, all model
predictors account for 39.1% of the continuous use of mobile learning by high
school learners. According to Hair Jr. et al. (2021), the exogenous variable has a
moderate influence on the endogenous variable, which is very respectable.
The predictive relevance of the model was evaluated using a cross-validated
redundancy predictor Q-squared. Results show that all Q-squared values ranged
from 0.064 to 0.533. All the Q-squared values were greater than zero, meaning that
the model could be used to explain and forecast high school learners’ acceptance
of mobile learning. The results also mean that the factors PU, SAT, CONF, EoU,
PC, and PA are good predictors of CUSE. These constructs (PU, SAT, CONF, EoU,
PC, PA, and CUSE) made up the structural model.

13
Figure 3: Structural model
Note: CUSE - continuous use, PU - perceived usefulness, EoU – perceived ease of use, PA –
perceived autonomy, PC – perceived competence, CONF – conformation, and SAT - satisfaction
4.3 Moderation effect
The moderating effects of gender, level of education, and location were assessed
and the results are shown in Table 3. These results show that the moderating
effects of gender, level of education, and location on high school learners’
continuous use of mobile learning were not statistically significant since their t-
values are less than 1.96. Hence, they were rejected.
Table 3: Moderating effect
Path Std Beta T Statistics P Values Decision
Gender -> CUSE -0.014 0.245 0.806 Rejected
Gender Moderating Effect -> CUSE -0.076 1.149 0.251 Rejected
Level -> CUSE 0.002 0.040 0.968 Rejected
Level Moderating Effect -> CUSE -0.042 0.647 0.518 Rejected
Location -> CUSE 0.143 2.796 0.005 Accepted
Location Moderating Effect -> CUSE 0.050 0.468 0.640 Rejected
CUSE- continuous use
5. Discussion
Research objective 1: The primary objective of this study was to assess
determinants of high school learners’ continuous use of mobile learning. Six
variables were identified and evaluated using PLS-SEM. Findings in Table 2 show
that satisfaction, perceived competence, and perceived usefulness all had
favourable effects on high school learners' continuous use of mobile learning.
Although perceived ease of use and perceived autonomy had no direct effect on

14
continuous use, they did have an indirect effect through perceived usefulness and
satisfaction, respectively. High school learners' confirmation had an indirect effect
on their continuous use by means of the mediating effect of satisfaction.
According to these results, perceived autonomy, satisfaction, perceived ease of
use, perceived competence, and confirmation are all good predictors of high
school learners' continuous use of mobile learning.
According to the findings Pratama (2021), EoU had a positive effect on PU but had
no direct effect on high school learners' continuous use of mobile learning. These
results imply that effort needed to learn to use mobile learning reinforces its
usefulness, which in turn influences their continuous use of mobile learning.
Effort required to learn to use mobile learning, on the other hand, has no direct
effect on learners' continuous use of mobile learning. There are two possible
explanations for this outcome. Firstly, high school students are 'digital natives,' or
adept users of mobile devices. Secondly, the high school students in these studies
have used mobile learning for the entire year, indicating that they are now
proficient users of mobile learning. Mutambara and Bayaga (2020) noted that the
effect of perceived ease of use on actual use attenuates with learners' experience
with mobile learning.
Contrary to the findings of Alraimi et al. (2015) and Kim (2020), the findings of
this study revealed that high school learners' perceived usefulness had a direct
positive effect on their continued use of mobile learning. The ability of mobile
learning to provide learning materials anywhere, at any time, encourages high
school learners to continue using it. This interpretation emphasises the
importance of extrinsic motivation in the use of mobile learning. After using
mobile learning for the entire year, high school students have realised that mobile
learning can improve their performance. It is this realisation that possibly
influences their intention to continue using mobile learning.
This study also found that high school learners’ realisation that mobile learning
can improve their performance influences their satisfaction with it, which is
consistent with the findings of Luo et al. (2021). Because mobile learning was more
advantageous to high school students who did not have access to face-to-face
learning owing to the coronavirus pandemic restrictions (Shrotri et al., 2021), the
students may regard this benefit as the primary driver of satisfaction formation.
The ability of mobile learning to satisfy high school learners' requirements,
expectations, task orientation, and goal determination gratified them both
emotionally and materially. According to the findings, the usefulness of mobile
learning influences a key surrogate indicator of mobile learning success (Santosa
et al., 2005).
Congruent to the findings of Luo et al. (2021), high school learners’ perceived
autonomy had a positive significant effect on their satisfaction. A possible
explanation for this is that, after using mobile learning for the whole year, high
school learners realised that they can study at their own pace, anytime, and
anywhere. This ability of mobile learning of allowing high school learners to take
charge of their learning leads to their satisfaction with it.

15
Perceived competence was meant to be a good determinant of perceived ease of
use, satisfaction and continuous use. These results were confirmed by the findings
in prior studies (Luo et al., 2021; Sørebø et al., 2009). When it comes to the extent
to which high school learners' pre-acceptance expectations are verified, perceived
competence appears to be the most crucial factor. The explanation for this might
be that competency has the ability to make pre-acceptance expectations more
reasonable and post-acceptance usage more efficient. When reasonable
expectations meet efficient use, a high degree of satisfaction is achieved.The
satisfaction of high school students had a positive effect on their continuous use.
The findings are consistent with those of Chong (2013) and Lu (2019), who found
that users will continue to use a system if it meets their material and emotional
needs. One possible explanation for this finding is that high school students used
mobile learning for an entire year and found it to be materially and emotionally
satisfying, resulting in their intention to continue using it. Satisfaction also serves
as an important moderator between high school students' perceived usefulness,
perceived competence and confirmation, and their continuous use.
Research objective 2: This was to investigate the mediating effect of social
moderators on the relationship between learners’ satisfaction and their continued
use of mobile learning. Results in Figure 3 show that the R-squared value of SAT
was 0.680. This result implies that the total contribution of PA, PC, PU, EoU, and
COMF in the explained variance of SAT was 68%. This coefficient of
determination is considered substantial (Cohen et al., 2003). The effect of
satisfaction on continued use is a result of its own indicators and the 68%
contribution of its exogenous variables (PA, PC, PU, EoU, and COMF).
The moderating effect of social moderators (gender, educational level, and
geographical area) on the path satisfaction to continuous use was assessed, and
the results are displayed in Table 3. Contrary to the finding of Amzaourou and
Oubaha (2018) and Cheng and Yuen (2020), gender does not moderate the path
satisfaction to continuous use. These results imply that male and female learners
had similar continuous use of mobile learning. This means that both male and
female learners have the same perceptions on mobile learning and they intend to
continue using it.
Educational level does not moderate the satisfaction to continuous use
relationship. This result is in line with the findings of Amzaourou and Oubaha
(2018), who also noted that university students’ educational level does not
moderate the relationship with satisfaction and continuous use. The results imply
that learners in the general education and training phase and those in the further
education and training phase have similar continuous use of mobile learning
intentions.
Tarhini et al. (2015) and Cheng and Yuen (2020) found that geographical area does
not moderate the relationship between satisfaction and continuous use. Our
results confirmed the findings of Tarhini et al. (2015) and Cheng and Yuen (2020).
These results mean that rural, semi-urban, and urban high school learners have
similar continuous use of mobile learning intentions. A possible reason for this
finding could be the influence of connectivity developments taking place in both
rural and semi-urban areas. The difference between rural areas and urban areas is

16
narrowing because cellular network providers have invested heavily in cell phone
boasters in rural areas, thereby making Internet access available (Chibisa et al.,
2021). This access to connectivity in all areas causes geographical areas to be
statistically insignificant moderators of satisfaction versus continuous use.
6. Conclusions and Recommendations
This study aimed to assess the determinants of high school learners’
continuous use of mobile learning and to investigate the moderation effects of
respondent’s social moderators. Six latent variables were identified and evaluated
using PLS-SEM. These variables were perceived autonomy, satisfaction,
perceived ease of use, satisfaction, perceived competence, and confirmation. They
were all found to be statistically significant and hence good determinants of high
school learners' continuous use of mobile learning. A model for predicting high
school learners’ continuous use of mobile learning was developed using these
variables. It was found to be statistically valid and robust with a moderate
coefficient of determination of 39.1%.
With a successful model of continuous use of mobile learning such as this one,
stakeholders are encouraged to continue using mobile learning because high
school learners have shown intentions to continue using it in order to alleviate the
restrictive and devastating effects of the Covid-19 pandemic. It has also been
shown that there are so many advantages of using mobile learning, such as
learning at one’s own pace, anytime, anywhere that enhance high school learners’
intentions to continue using mobile learning. Although the explained variance of
this study was statistically significant, a coefficient of determination of 39.1%
means that 61.8% of the factors that explain the continued use of mobile learning
were not captured in this model. It is therefore recommended that future studies
should focus on finding these ‘missing’ variables.
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Appendix 1
Determinants of high school learners' continuous use of mobile learning
during the Covid-19 pandemic
The purpose of this questionnaire is to collect data that will be used to find the
determinants of high school learners' continuous use of mobile learning during
the Covid-19 pandemic. Any information provided will be treated with utmost
confidentiality and will not be used for any purpose other than this. Your
participation in this survey will be highly appreciated. All data obtained from
participants and their personal details will be treated with utmost confidentiality.
You are free to withdraw from this survey any time you feel like doing so, without
any consequences. You need approximately 5-10 minutes to complete this survey.
DEMOGRAPHIC DATA
(Please tick the appropriate box)
Gender
Male Female
1 2
CONSTRUCTS AND INDICATORS
Continuance intention
CUSE1 I intend to continue using the mobile learning, rather than discontinue its use.
CUSE2
My intentions are to extend my use of the mobile learning rather than using any alternative
means.
CUSE3 I would never discontinue my use of the mobile learning.
CUSE4 I intend to continue using mobile learning for the rest of my high school learning.
CUSE5 I will encourage my teacher to keep on using mobile learning so that I keep on using it.
Satisfaction
SAT1 After using mobile learning I felt satisfied.
SAT2 After using mobile learning I felt contented.
SAT3 After using mobile learning I felt pleased.
SAT4 After using mobile learning I felt delighted.
SAT5 After using mobile learning I felt terrible.
Perceived usefulness
PU1 Using mobile learning improves the quality of my school work
PU2 Using mobile learning increases my productivity as a learner.
PU3 Using mobile learning enhances my effectiveness in my school work.
PU4 Overall, mobile learning is useful in my school work.
PU5 Using mobile learning would make it easier for me to learn.
PU6 I would find mobile learning useful in learning.
Confirmation
Phase
GET FET
1 2
Geographical Location
Rural Semi-urban
1 2

21
CONF1 My experience with using mobile learning was better than what I expected.
CONF2 The service level provided by mobile learning was better than what I expected.
CONF3 Overall, most of my expectations from using mobile learning were confirmed.
CONF4 My experience with using mobile learning at home was better than what I expected.
CONF5 My experience with using mobile learning at school was better than what I expected.
Perceived competence
PC1 I do not feel very competent when I use mobile learning in my school work.
PC2 The other learners tell me I am good at using mobile learning in my school work.
PC3 I have been able to learn interesting new skills in mobile learning.
PC4 Most days I feel a sense of accomplishment from working with mobile learning.
PC5 In school work I do not get much of a chance to show how capable I am in mobile learning.
PC6 When I am using mobile learning I often do not feel very capable.
PC7 My feelings toward mobile learning are taken into consideration in class.
PC8 I feel like I can pretty much use mobile learning as I do my school work.
PC9
There is not much opportunity for me to decide for myself how to use mobile learning in my
educational work.
Perceived autonomy
PA1 I feel like I can make a lot of inputs to deciding how I use mobile learning in my school work.
PA2 I feel pressured at using mobile learning in my school work.
PA3 I am free to express my ideas and opinions on using mobile learning in my school work.
PA4 When I am using mobile learning, I have to do what I am told.
PA5 My feelings toward mobile learning are taken into consideration at school.
PA6
There is not much opportunity for me to decide for myself how to use mobile learning in my
school work
Perceived ease of use
EoU1 It will be easy to learn how to use mobile learning to learn.
EoU2 I will find it easy to use mobile learning to share information with others.
EoU3 I will find mobile learning easy to use in class.
EoU4 I would find mobile learning to be flexible to interact with.
EoU5 It will be easy for me to become skilful in using mobile learning.
EoU6 I will find mobile learning easy to use at home.

22
©Authors
This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0
International License (CC BY-NC-ND 4.0).
Vol. 21, No. 3, pp. 22-35, March 2022
https://doi.org/10.26803/ijlter.21.3.2
Received Jan 4, 2022; Revised Feb 26, 2022; Accepted Feb 28, 2022
Speaking Skills Enhancement through Digital
Storytelling among Primary School Students in
Malaysia
Khasturi Ramalingam*
Universiti Teknologi Malaysia, Johor, Malaysia
Yeo Kee Jiar
Universiti Teknologi Malaysia, Johor, Malaysia
Siva Mathiyazhagan
Columbia University, NYC, USA
Abstract. Speaking skills can be considered a key measure of success in
learning a language. Learning Tamil, as an elective language in Malaysian
National Primary schools, is extremely difficult for beginners compared
to students in National Type Tamil Primary Schools in Malaysia. The aim
of the research is to apply digital storytelling as a pedagogical approach
in speaking classes in national primary schools with a view to promote
Tamil speaking abilities of children. A collaborative quasi-experimental
action research design was adopted to measure the efficacy of digital
storytelling in enhancing students’ Tamil speaking skills. Action research
was conducted with thirteen 2nd standard students aged between 7 and
8 years old, in a national primary school, in Pasir Gudang district, Johor,
on a pilot project. The Tamil digital storytelling modules were developed
in a mobile application with pre-and post-test survey tools and the
respective class teachers were trained on the module to work with
children in a regular classroom setting. The results showed that
significant improvements were observed in students' comprehension,
vocabulary, and fluency elements of the speaking skills after their
participation in the digital storytelling sessions. As a result, the study
suggests that digital storytelling may be an effective pedagogical
approach to enhance students’ speaking abilities in the classroom and
beyond to improve the students’ mother-tongue as second-language
learning in schools.
Keywords: digital storytelling; education; speaking skills; pedagogy;
Tamil language
*
Corresponding author: Khasturi Ramalingam, khasturiam@gmail.com

23
1. Introduction
Speaking is an important element of learning and communication. Speaking in a
second or third language enables students’ abilities to reflect, connect, and
contextualize situations beyond their learning experiences. The initial method of
student engagement is through oral communication. Students express their
thoughts, ideas, and desires verbally (Sembiring & Ginting, 2019). This already
known pattern of communication makes speaking skills vital in the early stage of
learning, particularly in countries with a multi-racial and linguistic population
like Malaysia (Xu et al., 2020). Malaysia is home to around two million Tamil
people ethnically from Tamil Nadu, India, and Sri Lanka (Joshua Project, 2019).
Although most children are from Tamil-speaking family traditions, when
students learn Tamil as a second language as an elective subject, their Tamil
speaking abilities are rather low. Consequently, these students struggle to speak
in their mother tongue at school. Speaking in their mother-tongue enables kids to
learn other languages easily; it builds children's self-esteem and their personal,
cultural, and social identities; and it develops critical thinking and innovation
(Awopetu, 2016). Students learning Tamil as an elective subject in Malaysian
national primary schools (Malay medium schools) face more difficulty in
speaking in Tamil in comparison to students in National Type Tamil Primary
Schools (Tamil medium schools).
Rapid technological advancements and assistive technologies, however, are
changing the learning patterns of students. There are more tech tools, products,
and services available to improve the students’ learning abilities. As a result,
teachers are using more technology in the classroom to promote listening and
speaking skills. Storytelling has proven to be an effective pedagogical approach
to improve students’ listening and speaking abilities in a classroom and family
setting (Sharma, 2018). The growth of digital media has more creative content
development opportunities for storytelling. Digital storytelling is a new form of
storytelling that has emerged as a digital tool for education enhancement.
Teachers can use digital storytelling as a pedagogical tool to work on various
aspects of language in order to stimulate students’ interest and attention (Badawi
et al., 2022). This empirical paper raises a key critical question – does digital
storytelling enhance the Tamil speaking skills of National Primary School
children in Malaysia? – and seeks to address possible research and practice gaps
to promote Tamil speaking skills of the students in Malaysia.
2. Literature Review
2.1. Digital Storytelling
Storytelling retells a narrative that has been heard or read in the narrator's own
words depending on their expertise (Ikrammuddin, 2018). As per Kristiawan et
al. (2022), storytelling resembles an activity in which the storyteller and the
audience – the speaker and the listener – participate in some level of interaction.
Nurzaman (2019) defines storytelling as a means for students to retell stories after
the teacher lectures them in a new word construction. Safei (2020) defines it as one
instructional approach that uses short stories called storytelling. According to
Asniatih et al. (2020), storytelling as a learner-centered technique assists students
in making sense of material and interacting with others. Thus, storytelling may be
characterised as a teaching style wherein students are required to repeat the

24
substance of stories employing a variety of word constructions whilst interacting
with the storyteller. One technique for telling stories are outlined as follows: (1)
the teacher displays various stories on the whiteboard with colourful papers, (2)
the teacher organizes students in small groups, (3) the teacher ask student
representative from each group to take a paper from the whiteboard, (4) the
teacher instructs students to create their own story in 15 minutes, and (5) the
teacher instructs them to share their story (Khodabandeh, 2019). Fikriah (2016)
offers another example: (1) Students are instructed to sit in groups, (2) they
develop a tale using a series of photos and key sentences supplied by the teacher,
and (3) the teacher invites each group to share their story in front of the class.
The physical storytelling strategies have been applied in various settings to
measure the efficacy of the pedagogical approach. Recent studies in Indonesia
used storytelling methods for teaching English: they observed that the storytelling
approach has enhanced students’ fluency, grammar, pronunciation, vocabulary,
and content (Asniatih et al., 2020; Sembiring & Ginting, 2019). According to an
Iranian teaching experiment, it was revealed that storytelling was helpful in
teaching vocabulary (Wahyudi, 2020). Rosyidah and Putri (2019) implemented
digital storytelling materials in the classroom. They have observed joyful learning,
critical thinking, creativity, confidence, and interest to explore the world of
technology. Rajendran and Yunus (2021) performed a systematic literature review
based on the Mobile-Assisted Language Learning (MALL) usage for improving
speaking skills among English as a Foreign Language (EFL) and English as a
Second Language (ESL) learners, which showed that students’ English-speaking
skills were significantly improved in using digital storytelling. There are several
research studies for storytelling and digital storytelling in the English language to
improve the speaking skills of the students. However, no study was found in the
Tamil language to improve speaking skills in Malaysia.
2.2. Storytelling and Speaking Skills
Storytelling is an oral activity that can comprise enhancement in telling a story
through body movement as well as facial gestures, to capture the audience's
attention by using multisensory stirring emotion of an event in a story.
Storytelling is also a teaching strategy that helps students to concentrate on story
aspects as part of class speaking activities (Yunita, 2019). Moreover, storytelling is
a technique that allows children to take an active role in the retelling of a story. It
places a strong emphasis on both academic and social development. When telling
and developing a story, they employ language for a lengthy amount of time. This
activity therefore helps them to develop their language skills (Masuram &
Sripada, 2020).
Students in preschool or in the early stage of primary school instinctively love
stories. They are introduced to the wonders of the world and stimulated to
imagine many unknown possibilities (Febyanti et al., 2022). Telling stories
resembles an active process encouraging students to reconstruct the text, and at
the same time, allowing teacher and student interaction (Valsesia et al., 2017).
Storytelling boosts students’ confidence, improves their language skills, promotes
speaking and listening fluency, and increases motivation and interaction (Ahmadi
& Zenouzagh, 2017; Ikrammuddin, 2018). The storytelling method makes the

25
learning process more enjoyable for the student. In addition, the storytelling
process develops language skills with history, science, and other subjects as well.
In primary education, four basic language skills are taught: listening, speaking,
reading, and writing (Leong & Zainol Abidin, 2018). In Malaysia, storytelling has
long been used as a teaching method or technique to pique interest following a
lesson. Teachers uses storytelling to teach language skills, inculcate moral values
in students, and develop students’ soft skills such as communication and social
skills.
One of the key skills in language is speaking. Speaking skills are viewed as an
important indicator of a student’s progress in learning a foreign or second
language. Speaking is an essential skill for students to develop and not just to meet
curriculum objectives, but also to advance to the next level of their formal
education. Numerous specialized programmes are referred to as intensive
speaking programmes of foreign languages, particularly, English for adults and
students. However, the majority of Tamil students in National Primary Schools
learn a relatively minimal level of Tamil in a short period of time in these schools.
The majority of them are still beginners in their efforts to learn Tamil as a second
language. Most often, these students have difficulties in speaking Tamil as it's a
second language for them. Rudrapathy (2021) argued that it is difficult for a
beginner to pronounce Tamil letters.
Every child hears his/her mother tongue as a first language, which also serves to
develop thoughts and emotions. Learning in one’s mother tongue is also
important for improving other skills such as critical thinking, the ability to learn
languages, and literacy. A child's mother tongue promotes the child's personal,
social, and cultural identity (Cvikić & Dobravac, 2017). The choice of words and
expressions have different meanings across cultures, and where asking direct
questions is considered as quite intrusive in one language, but it may be
inquisitive in another. This means that the language used when speaking is
deliberated upon before it is spoken. According to (Nishanthi, 2020), ability and
concepts learnt in the learner's native language do not need to be taught again
when they are transferred to a second language. In a school with a strong mother
tongue programme, it is critical that younger children receive support in their
mother-tongue. When a child is confident in his/her mother tongue, he or she will
typically perform well when learning a second or third language. Children who
receive education in their mother-tongue improve their performance in their
second language as well (Maniam et al., 2020). Early learning to read in one's
mother language also lowers dropout rates and it makes schooling more
engaging, relevant, and fun for youngsters.
2.3. Child Development and Speaking Skills
Primary school students start to compare and contrast, organize, analyze, and
come up with increasingly complex solutions to problems, which helps in the
development of their mathematical and scientific reasoning abilities (Ramasamy
et al., 2018). This study also focuses on the cognitive-developmental level for
children in the preschool age group. There are two types of early childhood
learning models: teacher-centered learning models and child-centered learning
models. Pavlov, Skinner, and other behaviorists pioneered a teacher-centered

26
learning model. Child-centered learning was pioneered by Piaget, Erikson, and
Isaacs (Alharbi & Alzahrani, 2020). Children have the ability to communicate their
ideas orally in narrative and innovative ways. Their imaginations increasingly
become the primary mode of play and learning for them. Cognitive development
is a unique process for each child's development. According to (Dewi et al., 2018)
children's brains grow alongside their bodies during the preschool years. Between
the age of 3 and 5, a child's thinking skills will undergo significant development.
Children continue to grow and acquire new abilities in kindergarten and
preschool (aged 2.5 to 6 years old). Playing is beneficial in many aspects of
development, which includes, emotional, social, communicative,
physical, cognitive, and linguistic (Kucirkova, 2019). Language and
communication skills are essential for a child's development. They are more able
to socialise and learn from formal classroom instruction including the pleasant
atmosphere around them, owing to clear oral communication that can help them
enhance their speaking abilities. Language and speech are important in children's
communication and development (Rao, 2019).
It is evident that storytelling has a significant impact on early childhood
development and during the education process. However, the majority of
educational experiments and research focus on the English language and there is
not much literature on Indian regional languages like Tamil. This significant
research gap drives the authors to explore the Tamil language-specific digital
storytelling as an alternative pedagogical approach to improve Tamil speaking
skills of the National Primary School students in Malaysia.
3. Methodology
3.1. Research Problem
Malaysia's Ministry of Education, in collaboration with the Curriculum
Development Agency, has created updated curriculums for every subject taught
from preschool to tertiary level. In primary school, a curriculum has been
established for each of the core subjects and electives, including the Spanish,
English, and Tamil language programmes offered at the National School of Tamil.
Under the Tamil language programme, Tamil language lessons, which were
previously exclusively available to Tamil students and are now available to all
students regardless of race or religion, encourage children from other races to
learn Tamil as an additional language, which fosters increased harmony in
Malaysia's multi-racial culture. As a result of this education strategy, an additional
70 National Schools pioneered the introduction of Tamil subjects in 2007 (PIPP
2006-2010).
Based on the primary observations during the pilot test by the researcher, Tamil
students at National Primary Schools in Pasir Gudang district still have a
relatively poor level of Tamil speaking skills. According to Rudrapathy (2021),
the following factors contribute to students’ low speaking skills in Tamil: (1)
insufficient time in the classroom to practice speaking in Tamil, (2) a lack of
vocabulary, (3) less interest in communicating in Tamil because of unattractive
teaching methods, and (4) a lack of ability to relate the content of speech to their
daily lives. Furthermore, providing speaking methods that enable language
learners to communicate in the target language is vital (Shin & Yunus, 2021). In

27
addition, speaking is one of the major challenges for beginners and often causes
them dissatisfaction (Nijat et al., 2019). In order to address these pertinent issues,
research and practice gap in the Malaysian education system, a comprehensive
action research on Tamil digital storytelling for primary school students was
initiated. As part of the larger Ph.D. research work, this article has been prepared
based on the initial pilot study conducted among 2nd standard Tamil students in
a National Primary School as an intensive Tamil digital storytelling programme.
The primary aim of this research is therefore to examine the impact of digital
storytelling to enhance the speaking skills among 2nd standard Tamil students at
a National Primary School with an intense Tamil digital storytelling programme
in the academic year 2021.
3.2. Research Design
This research adopts collaborative action research as a quasi-experimental
research study (Sembiring & Ginting, 2019; Sharma, 2018; Zuhriyah, 2017). This
research process consists of the following four steps 1) plan, 2) implement, 3)
observe, and 4) reflect. These four steps were adopted based on the model
developed by Kemmis and McTaggart (James et al., 2019). The purpose of this
study is to incorporate digital storytelling as pedagogy into speaking classes to
encourage students from National Primary Schools to speak Tamil during Tamil
language classes and to measure their progress with a pre-and post-test survey.
Figure 1: Implementation process of digital storytelling in the classroom
3.2.1. Plan
The first author prepared the lesson plans of teaching speaking skills by using
digital storytelling during the month of May 2021. In addition, the researcher also
prepared 13 tablets with a mobile application named ‘KaniMani’ for digital
storytelling. This mobile application contains 6 family-oriented stories which
emphasize moral value in the family. The researcher also prepared pre-and post-
test questions based on the students’ comprehension (understand instruction),
vocabulary (nouns, verbs), and fluency (number of sentences, speech rate, fillers)
in speaking skills. Qualified Tamil Teachers with a minimum of five years of
experience were identified and inducted on the mobile application, research
objectives, process, and tools for effective implementation of the programme. As
part of the plan, the researcher received written consent from the school
administration and individual parents/ legal guardians to engage children in the
classroom research activities. Institutional Review Board approval was obtained
from the Universiti Teknologi Malaysia to carry out this research project in
schools.
Plan
Preparation of
tools
School
permission
Teachers
selection
Students
selection
Implementation
Pre-test
Week 1-
Comprehension
Week 2-
Vocabulary
Week 3- Fluency
Post-test
Observe
Session
Observation
Field Notes
Process
documentation
Reflect
Discussion with
teachers
1.Field notes
reflections
2. Quantitative
result reflection

28
3.2.2. Implement
The researcher ensured that the invitation letter and the informed consent forms
are received from the parents/legal guardians. Additionally, the researcher
provided a brief explanation of the research objective and process to ensure that
the participants understood and gained a general understanding of both the
research objectives, methods, process, and time requirements to complete the
study to all the student participants and teachers involved in the process.
Meanwhile, the teachers received a set of lesson plans to use in the classroom with
a mobile application. The teacher was also provided with observation sheets to
record the teacher's instructions, students’ activities, and responses of the
students. The researcher ensured a complete child-friendly and participative
pedagogical approach for the digital storytelling sessions. The digital storytelling
sessions were implemented for over a period of 4 weeks between May to July 2021.
Each session lasted for a period of 60 minutes. Due to the COVID-19 pandemic
restrictions, all the sessions were organized through Google Meet. In the end,
post-assessments were conducted to measure progress in speaking skills. The
speaking rubric produced by Rukmini and Saputri (2017) was adapted to develop
the grading criteria for oral communication abilities used in this study.
3.2.3. Observe
The researcher was present during the implementation of digital storytelling in
the virtual classroom as a participant-observer and took field notes from the
teaching and learning process. The students’ and teachers’ perspectives were
observed and described in the field notes.
3.2.4. Reflect
After observation, the researcher gathered all required information and pre- and
post-survey data and discussed and reflected on the results with the Tamil
teachers. The researcher conducted two cycles of reflections with teachers: one
based on the field observation and the other on the quantitative results of
speaking skills among the students. These observations and reflections were
recorded and described in the field notes.
3.3. Research Area and Participants
The survey was conducted at the National Primary School in Pasir Gudang
district, Johor, Malaysia. The study indicated that the participants are
predominantly identified as Indian students who were 8 years old at the time of
the study. There were 15 students in this Tamil class, but only 13 of them were
regular attendees without missing any class. The participants have been selected
using the purposive sampling method (Har, 2019) based on the low achievement
track record in the previous academic year in the Tamil subject, particularly in
speaking skills. These 13 Indian students studying Tamil as an elective subject in
the school, were included. All the participants were from similar socio-economic
backgrounds.
3.4. Data Collection and Analysis
Qualitative and quantitative data was collected from the students through the
online classroom experiment. The quantitative data was collected from the
students’ pre-and post-tests. All the collected data was updated on Microsoft

29
Excel, cross-verified for missing values, coded based on the categories of the
speaking skills, and analyzed to generate bar diagrams to assess the speaking
skills of the students who participated in the study and disseminate as the result.
The field notes from observations and reflections were described in Microsoft
Word, and thematic analysis were performed to validate the qualitative results.
3.5. Limitations
As a pilot study from the Ph.D. programme, the experiment was conducted in one
school with a limited number of research participants. The results may not be
generalizable at this point. However, this pilot study will pave the way for larger
studies in regional languages. Due to the COVID-19 pandemic safety restrictions,
all the sessions were conducted virtually and consequently, it was difficult to
observe students’ learning process, body language, and other expressions. The
parents’ guidance and engagements were required to be with their children to
ensure effective implementation. Due to multi-stakeholders’ engagement, it was
difficult to find a mutually available time for everyone in the research process.
The fluctuations and other disturbances in internet connectivity made the process
more difficult in understanding students’ speaking abilities. Mobile Application-
based digital storytelling, in any regional language, will be well suited for a home-
based learning perspective with parents than virtual classrooms.
4. Results
4.1. Quantitative Results
The results of the present study were based on the pre- and post-speaking tests.
There are three components measured in the Tamil speaking test with primary
school students. The (1) comprehension, (2) vocabulary, and (3) fluency of
students were observed and measured to understand the impact of digital
storytelling on improving students’ speaking abilities.
Table 1: Pre and post-test scores of digital storytelling

30
The above table 1 shows that the summary of the pre and post-test scores of the
students. Each category of speaking skills was scored out of 10 marks. Significant
improvements were recorded in the pre and post-test in all aspects of the speaking
skills. Fluency had an highest level of improvement in students speaking skills.
Figure 2: Result of speaking skills before and after digital storytelling
Figure 1 shows that students’ speaking skills considerably improved in all three
aspects after the implementation of digital storytelling sessions. The students’ oral
comprehension skill has increased to 52% compared to a pre-test score of 25%.
The results show that students’ vocabulary has improved from 27% to 50%, and
the fluency of Tamil speaking skills have also improved with a difference of 31%
after they were exposed to digital storytelling. Overall, the students’ capacity to
communicate vocally improves as a result of the implementation of the digital
storytelling technique in the virtual classroom environment
4.2. Observations and Reflections
The researcher’s observations and teachers’ post-experiment reflections reveal
that teachers strongly believe that digital storytelling was a good pedagogical
approach to improve students’ speaking skills. The teachers acknowledged that
the Mobile Application-based storytelling allows students to repeat the stories
more times which allows them to learn vocabulary and get familiar with new
words in Tamil. The mobile application-based digital storytelling and gamified
evaluations with rewards motivated students to joyfully participate and learn
independently at home. The parents are highly satisfied with children’s creative
expressions after the digital storytelling sessions. Students expressed that Mobile
Application-based learning for Tamil is new to all of them. It was also observed
that the students were more interested in participating in an online storytelling
competition at the state level. Students imitated stories and actions which enable
them to speak in Tamil for more than a minute. Students feel more secure, able to
recognize their own potential through video, and more comfortable sharing their
stories and tales. It was also observed that students were more excited and had
fun with Mobile Application technology and considerably improved their Tamil
speaking skills.
25% 27% 27%
52% 50%
58%
0
10
20
30
40
50
60
Comprehension Vocabulary Fluency
Pre-test Post-test

31
5. Discussion
5.1. Digital Storytelling and Speaking Skills
It is evident that the digital storytelling approach contributes to the Tamil
speaking abilities of primary school students in Malaysia. The storytelling proved
to be an effective approach in improving English speaking skills. The present pilot
study results show that Tamil speaking skills also improve through digital
storytelling. It may be possible to expand digital storytelling as a pedagogical
approach for other regional language improvement and promote mother-tongue
speaking abilities in National Schools. Yunita (2019) emphasized that students
require better speaking skills in all aspects of life in this era of globalization. The
Mobile Application-based digital storytelling could be an option to improve the
speaking skills of the students in primary schools. The students’ excitement
towards modern technology, visual representation, and active virtual
participation makes digital storytelling an interesting tool to explore in the
classrooms. There are several researchers who have argued on the importance of
speaking skills for students’ communication, creativity, career development,
identity development, learning languages, and social engagement (Choi et al.,
2019; Kucirkova, 2019). Schools in the twenty-first century adopt various
emerging technologies and assistive technologies into the classrooms to support
students’ learning abilities. Mobile application-based learning is not a new
approach in the education space, however, language inclusion in technology can
make it more accessible for diverse ethnic groups across the world. Digital
storytelling in a mobile application version will support students beyond the
classroom and geographical boundaries to improve their speaking skills and other
additional social benefits.
5.2. Language Inclusion and Digital Storytelling
Most digital products in the education space are in English. There are roughly
6500 to 7000 languages and major dialects spoken in the world (UNESCO, 2020).
74 million people speak Tamil as their native language (Goreau-Ponceaud, 2019),
and almost ten million people speak Tamil as a second language in more than six
countries including Malaysia. Digital learning tools need to be in the native
language to share indigenous stories and tales to students to build their socio-
cultural identity and creative exploration of the world, and enhance their clarity
and confidence to communicate with each other. Learning in one's mother tongue
is also important for developing other critical thinking skills, more additional
language learning, and literacy abilities (Nishanthi, 2020). People convey and
communicate ideas to others verbally by speaking (Pandian et al., 2020). People's
thought process and feelings are shaped by their mother tongue. It is vital for a
child's growth to learn to speak in his/her mother tongue. Fluency in the
children’s mother tongue has a number of advantages for the child (Uzeyir
Sugumlu, 2022). This digital storytelling experiment in the Tamil language will
pave the path for language inclusion in the digital learning environment and
promote more mother tongue speaking abilities through digital storytelling
approaches.

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