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Computer Assisted Language Learning
ISSN: 0958-8221 (Print) 1744-3210 (Online) Journal homepage: https://www.tandfonline.com/loi/ncal20
Student satisfaction, learning outcomes, and
cognitive loads with a mobile learning platform
Yu Zhonggen, Zhu Ying, Yang Zhichun & Chen Wentao
To cite this article: Yu Zhonggen, Zhu Ying, Yang Zhichun & Chen Wentao (2019) Student
satisfaction, learning outcomes, and cognitive loads with a mobile learning platform, Computer
Assisted Language Learning, 32:4, 323-341, DOI: 10.1080/09588221.2018.1517093
To link to this article: https://doi.org/10.1080/09588221.2018.1517093
Published online: 04 Dec 2018.
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Student satisfaction, learning outcomes, and
cognitive loads with a mobile learning platform
Yu Zhonggen
a
, Zhu Ying
b
, Yang Zhichun
b
and Chen Wentao
c
a
Department of English Studies, Faculty of Foreign Studies, Beijing Language and Culture
University, Beijing, China;
b
School of Foreign Languages of Hohai University, Nanjing, Jiangsu,
China;
c
Zhejiang Yuexiu University of Foreign Languages, Shaoxing, Zhejiang, China
ABSTRACT
After working with a number of scholars for two years, a
university designed a mobile learning platform referred to
as ‘College English IV,’where learners could have easy
access to various kinds of learning resources through instal-
ling the program in their smart phones. This study aims to
identify whether this platform could significantly improve
the proficiency of English as a foreign language (EFL), yield
learner satisfaction, and reduce learners’cognitive loads in
EFL classes. Randomly selected 340 tertiary students partici-
pated in the study. After quantitative multivariate analysis
and qualitative interview data analysis, it was concluded
that: (1) In EFL classes, participants with the mobile learn-
ing platform were more satisfied than those without it; (2)
In EFL classes, learning outcomes of participants with the
mobile learning platform improved significantly more than
those without it; and (3) In EFL classes, cognitive loads of
participants with the mobile learning platform were signifi-
cantly lower than those without it. Interdisciplinary research
may be needed in future research.
KEYWORDS
Satisfaction; learning
outcomes; cognitive loads;
the mobile learning
platform; College English IV
1. Introduction
1.1. Research background
Nowadays, in China, mobile touch-screen smart phones are so popular
that most tertiary students are equipped with them. It is commonly
accepted that even in classrooms, a number of students frequently keep
an eye on their smart phones where communicative platforms are in use
for their conversation with friends and families.
As a result, students tend to ignore the lecture contents. Instead, they
concentrate on chatting, news, movies, music, and gossips via their smart
phones. This has been a troublesome distraction in classrooms, greatly
CONTACT Yu Zhonggen 18951801880@189.cn
ß2018 Informa UK Limited, trading as Taylor & Francis Group
COMPUTER ASSISTED LANGUAGE LEARNING
2019, VOL. 32, NO. 4, 323–341
https://doi.org/10.1080/09588221.2018.1517093
influencing learning and teaching effectiveness (Xu, Yuan, & Meng,
2015). The teacher, however, is not entitled to collect their mobile smart
phones in class. Therefore, students’addiction to mobile phones influen-
ces the learning environment, reducing the teaching and learning effect-
iveness. What is even worse is that recently developed smart technologies
for language learning were overlooked (Shadiev, Hwang, &
Huang, 2017).
It is a reasonable solution to develop an educational application used
in mobile smart phones so that students may be attracted to the educa-
tional information rather than other disruptive issues. The university
spent enough time and funds developing an online learning and teaching
platform. This study aims to introduce and evaluate this mobile learning
platform, which can be directly used on mobile devices to involve stu-
dents in learning rather than other non-academic activities.
1.2. The mobile learning platform
The mobile learning platform (ktzx.hhu.edu.cn), an important seamless
Internet teaching and learning tool, was designed and developed by the
university. After two years’investigation, the development and debugging
of this advanced platform was finally completed by a number of scholars
at the university. This platform aims to promote teaching effectiveness
by shifting from distractions to resourceful learning, teaching, and inter-
active materials in smart phones, plus mobile applications available to
both students and teachers. Its characteristics and functions are described
as follows.
First of all, the model of the platform is reasonable in that it follows
the latest pedagogical conception, which possibly predicts the future
development of educational technologies. Furthermore, there are plenty
of learning and teaching resources on the platform, through which teach-
ers can prepare for lectures at their own convenience and students may
have easy access to learning resources they are in need of. This realizes
seamless connection between teaching and learning and improves the
effectiveness. Additionally, the platform, whose appearances are concise
and user-friendly, is characteristic of easiness and interactivity. It is con-
venient for teachers and students to utilize the platform and retrieve as
much information as possible from it. The platform covers the whole
process of learning. Teachers can also monitor individual learning,
homework, question answer, and examination to achieve a scientific
assessment of teaching process, because the platform enables them to
adjust and improve their teaching approach based on learners’perform-
ance and feedback. Finally, the platform supports mobile learning
324 Y. ZHONGGEN ET AL.
through mobile client software, which is openly accessible for students
and teachers to download and install.
1.3. The Course ‘College English IV’
The mobile learning platform (the website is available upon request) is a
platform to provide many online courses designed by a number of facul-
ties in the university, such as Faculty of Foreign Languages, Faculty of
Hydrology and Water Resources, Faculty of Law, Faculty of Science,
Faculty of Environmental Protection, and Faculty of Computer Science
and Technology.
Through years’work, The Online Course ‘College English IV,’a major
component of the mobile learning platform, was finally completed, pro-
viding varieties of learning resources of English as a foreign language
(EFL). A team experienced in English teaching and research from the
Faculty of Foreign Languages of the university operated and designed the
online course ‘College English IV.’Through installing the android ver-
sion, learners have unimpeded access to the course ‘College English IV’
in their mobile devices, by which they can engage in many learning
activities aided with abundant resources on this platform.
Via the platform, learners can have access to an overview of the course
by watching a mini-lecture, plus introduction of the teaching team. They
can also read the course introduction and obtain course chapters, objec-
tives, teaching plans, PPT slides, materials and examinations by clicking
the corresponding buttons. An example is that through clicking
‘Chapters of the course,’learners are supposed to view detailed contents
of ten chapters, together with corresponding subsections.
Students can also watch teaching movies to enhance learning effective-
ness by clicking the button ‘teaching movies.’By clicking ‘records of
texts in listening and speaking textbooks,’students can listen to the
records designed by native English speakers. They can also obtain teach-
ing slides to assist listening practice by clicking the button ‘PPT slides of
listening and speaking.’Learners can practise listening and speaking
skills by accessing ‘listening and speaking materials.’Mini-lectures, where
the teacher explains language points integrated with culture, back-
grounds, and related information, are also available to students. Students
can also interact with teachers and peers outside class through this plat-
form, where participants can complete the assignment, conduct peer dis-
cussion, raise questions, obtain a sea of learning resources, sit exams,
and learn detailed chapter contents. The teacher may allot the assign-
ment, check student performance, commence exams, organize discussion,
COMPUTER ASSISTED LANGUAGE LEARNING 325
answer questions, manage scores, provide learning resources, revise sys-
tem settings, etc.
Students are required to finish self-directed learning through the plat-
form before physically attending the class. In each physical class, students
are required to watch the mini-lecture, about which they are supposed to
answer questions and conduct peer discussion. The teacher also designs
two quizzes for students to complete, after which four articles are pro-
vided for students to read. Also, the teacher explains backgrounds of the
target articles, related language points, and extends the knowledge.
Students are supposed to be involved in learning activities such as
answering questions, reading aloud, discussing with peers, and complet-
ing quizzes.
Beyond class, students may collaboratively learn through this platform.
This platform can also be accessed via portable devices such as mobile
phones and iPad so that they may participate in learning activities when-
ever and wherever.
2. Literature review of mobile learning
A number of studies have discussed use of mobile technologies in educa-
tion (e.g. Churchill, Kennedy, Flint, & Cotton, 2010; Kaleebu et al., 2013;
Segall, Doolen, & Porter, 2005). Mobile technology provides learners
with various options of venues and schedules for education. With mobile
devices, learners can choose to learn whenever and wherever they feel
convenient. They can hold the mobile phones, for example, in their
hands, even when they are walking. They can also suspend using mobile
devices for learning as they feel bored with learning. Teachers were also
encouraged to use mobile phones and technologies to facilitate vocabu-
lary acquisition (Liu, 2016).
However, mobile learning should not be simply deemed as the process
where e-learning was integrated with mobile devices. Its true value as an
assistant to learning should lie in the stored data that can be retrieved
whenever necessary (Wagner, 2005). Through the data stored in mobile
devices, many mobile learning activities can be easily held, which could
much better engage students in the learning process, where students
changed from passive learners to truly engaged learners who were behav-
iorally, intellectually, and emotionally involved in their learning tasks
(Wang, Shen, Novak, & Pan, 2009).
The technological features of mobile devices, coupled with cloud sav-
ing and processing, could provide contemporary pedagogical approach in
various educational settings (Evans, 2008; Lai, Yang, Chen, Ho, & Chan,
2007). Pedagogical approaches of mobile learning have been designed
326 Y. ZHONGGEN ET AL.
based on three principles, i.e. learning aided with mobile devices (Song
& Fox, 2008), learners on the move (Gu, Gu, & Laffey, 2011), and
dynamic, seamless, and ubiquitous learning (Kearney, Burden & Tapan,
2015; Ting, 2013). These three principles guided the university to build
up the platform.
2.1. Satisfaction of mobile learning
Advantages of mobile learning aided with Skype, Twitter, and Blogs were
studied by Gikas and Grant (2013) who held positive attitudes toward or
were satisfied with this mobile platform. Integrating mobile technologies
into E-books was suggested by Glackin, Rodenhiser, and Herzog (2014)
to acquaint learners with library resources. It was also found that stu-
dents encountered different types of barriers associated with technologies
and learning tasks, which could cause disengagement during different
learning phases (Liu, Wang, & Tai, 2016).
There were causal relationships between learner satisfaction and the
overall proposed mobile learning system (Sarrab, Elbasir, & Alnaeli,
2016). Mobile technology-aided learning enhances intrinsic motivation
(Jeno, Grytnes, & Vandvik, 2017), which may therefore promote satisfac-
tion. Satisfaction plays an important role in the effectiveness of mobile
learning. Satisfaction would integrate learning into mobile technologies
better than dissatisfaction. It may also determine if learners are ready to
accept mobile learning and thus exert a great influence on effectiveness
of mobile learning. It was helpful to identify both advantages and disad-
vantages of mobile technologies (Mostafa, Hatem, & Khaled, 2016).
Therefore, one of the research questions in this study is whether partici-
pants are satisfied with the mobile learning platform. The hypothesis is
raised as follows:
H1: In EFL classes, participants with the mobile learning platform are significantly
more satisfied than those without it.
2.2. Learning outcomes of mobile learning
Mobile technology-aided learning improves perceived competence and
achievement (Jeno et al., 2017). Mobile learning has received popularity
among learners and teachers due to its flexibility and easiness. It has
been in effective use in a number of universities throughout the world
(Al-Emran, Elsherif, & Shaalan, 2016). Interactive Learning Network
including application of PCs and corresponding technology was used for
pre- and post-tests in Canada College and San Francisco State University
(Enriquez, 2010). Mobile learning, integrated with the Geographic
COMPUTER ASSISTED LANGUAGE LEARNING 327
Information System, was also put into practice in a Turkish university
(Erkollar & Oberer, 2012). Mobile technologies were also advocated in
improvements of listening skills (Azar & Nasiri, 2014). Mobile devices
were proved effective in French learning and teaching (Jaradat, 2014).
Use of iPads in mathematics examination was tried in the American
University of Sharjah, UAE (De Pablos, Tennyson, & Lytras, 2015).
However, students’mobile learning outcomes are not always consistent
with theoretical reasoning and technological advantages. A number of
studies based mobile learning design on situated learning (Zydney &
Warner, 2016). Retention of knowledge in mobile learning was only
measured by two studies (Ahmed & Parsons, 2013). One of the promin-
ent advantages of situated learning was its retention of content and
learning transfer since learning in a given situation might cultivate far
more intense connections between memory and acquired knowledge
compared with mobile learning (Bransford, Brown, & Cocking, 2000).
Considering the paradoxical findings and to determine if the mobile
learning platform is effective in teaching and learning, this study
attempts to identify learning outcomes through this platform. The pro-
posed hypothesis is
H2: In EFL classes, learning outcomes of participants with the mobile learning
platform improve significantly more than those without it.
2.3. Cognitive loads of mobile learning
The cognitive load can be defined as ‘a multidimensional construct rep-
resenting the load that performs a particular task imposed on the
learner’s cognitive system. More specifically, the amount of cognitive
load, measured at a given time, is a way of assessing the level of informa-
tion being manipulated in working memory’(Yu, Chen, Kong, Sun, &
Zheng, 2014). The cognitive load can be classified into two types
(Sweller, 2010): intrinsic cognitive loads and extrinsic cognitive loads.
The intrinsic cognitive load indicates the load in the knowledge to be
acquired, dependent on the capacity of simultaneously processing the
specified knowledge (Marcus, Cooper, & Sweller, 1996; Sweller, 1994).
This type of cognitive load is subject to the level of sophistication of the
target knowledge, which remains relatively stable. While the extrinsic
cognitive load, under the control of course designers, is subject to teach-
ing strategies, it tends to be caused by an extrinsic increase in the ele-
ments which must be processed in working memory because of extra
instructional designs (Yu et al., 2014).
In addition, there is another type of cognitive load, i.e. the germane
cognitive load, which is an independent type of the cognitive load. It is
328 Y. ZHONGGEN ET AL.
established during the process of constructing cognitive schema (Wiebe,
Roberts, & Behrend, 2010). It is reported that because the germane cog-
nitive load relies on and assimilates the intrinsic cognitive load, it may
be defined by relative theories of the intrinsic cognitive load (Sweller,
2010). The germane cognitive load can therefore be defined as the
resources occupying working memory in order to deal with the intrinsic
cognitive load in the learning process (Yu et al., 2014).
Inconsistent are the studies of impact of mobile learning on cognitive
loads. It was suggested that mobile devices might bring about negative
influence such as distraction and heavy cognitive loads (Hwang & Wu,
2014). By contrast, it was found that a designed mobile interactive learn-
ing and diagnosis system was beneficial to students in improving learn-
ing performance and reducing cognitive loads (Lin & Lin, 2016), possibly
because cognitive strategies adopted in learning were positively correlated
with learning achievements (Park, 2018). For mobile learning, much
fewer studies have, however, been interested in cognitive loads and
higher-level learning outcomes, compared with those concentrating on
lower-level learning outcomes (Zydney & Warner, 2016). This could be
caused by difficulties in measuring cognitive loads. However, cognitive
loads are a significant indicator of the effectiveness of learning and
teaching. Lower cognitive loads tend to predict higher learning outcomes,
while heavier cognitive loads may cause lower learning outcomes. It is
therefore necessary to identify cognitive loads in order to determine the
effectiveness of the mobile learning platform. The proposed hypothesis
in this regard is
H3: In EFL classes, cognitive loads of participants with the mobile learning platform
are significantly lower than those without it.
3. Research methods
1
The use of qualitative methods in conjunction with other approaches as
in mixed-method research designs is especially effective in computer
assisted language learning research (Levy, 2015). This study, aiming to
validate the effectiveness of the mobile learning platform, adopts a qua-
siexperimental mixed design in order to obtain reliable and valid data.
3.1. Participants
Randomly selected participants came from sophomores who registered
College English IV in the university. They were randomly divided into
two cohorts. Cohort A, comprising 169 undergraduates, registered
College English IV aided with the mobile learning platform. Cohort B,
COMPUTER ASSISTED LANGUAGE LEARNING 329
made of 171 undergraduates, registered College English IV without the
aid of the mobile learning platform. All the participants were randomly
selected from undergraduates in the university, majoring in engineering,
mathematics, law, environmental protection, hydraulics, etc. They, rang-
ing from 18 to 21 years old, learned EFL for 8 to 11 years. Their EFL
proficiency was not significantly different from each other, which had
been validated by the Test of English as a Foreign Language (TOEFL).
They reported that they were in normal psychological state with normal
intellectual abilities.
3.2. Research instruments
Research instruments in this study include scales to determine satisfac-
tion, learning outcomes, and cognitive loads.
The satisfaction scale
The scale of satisfaction, adapted from Stokes’findings (2001), involved
14 questions, followed by five-point Likert scales (see Appendix A). This
scale has experienced tests of external validity and internal reliability
conducted by Stokes (2001). Examples of the questions are ‘My technol-
ogy knowledge level is sufficient for learning through the mobile learning
platform; I am feeling somewhat connected to the University setting by
taking a class that places emphasis on learning through the mobile learn-
ing platform; I would prefer to take more of my classes through the
mobile learning platform.’
The scale to identify learning outcomes
Learning outcomes, operationally defined as EFL proficiency in this
study, were determined through TOEFL. Four testing items, i.e. reading
comprehension, listening comprehension, speaking, and writing, were
designed to identify candidates’English proficiency. The total score was
120 points, with each testing item accounting for 40 points.
The scale of cognitive loads
Measurements of cognitive loads were helpful to determination of mental
capacity of learning (Wiebe et al., 2010). The NASA Task Load Index
(NASA-TLX) was comprised of six scales: mental demand, physical
demand, temporal demand, effort, and frustration level. Each scale was
determined through five questions (see Appendix B). NASA-TLX was
proved valid and reliable to identify cognitive loads (Hart &
Staveland, 1988).
330 Y. ZHONGGEN ET AL.
The semistructured interview
The semistructured interview was conducted through questionnaires.
Three sections were included in the questionnaire: (1) ethnic statement
and demographic information; (2) questions regarding self-reported cog-
nitive loads, satisfaction, and EFL proficiency; and (3) acknowledgments.
Participants were invited to be interviewed and to answer questions in
the questionnaire, which sourced from scales of satisfaction and cognitive
loads, plus self-assessment on their EFL proficiency.
3.3. Research procedure
All participants received College English IV education for one academic
semester. Teachers with similar teaching skills and educational backgrounds
guided them to make use of corresponding platforms (see Figure 1).
As shown in Figure 1, Cohort A received the education by using the
mobile learning platform–College English IV as a learning assistant,
while Cohort B learned College English IV without the aid of the mobile
learning platform. The dotted line arrow leading from Cohort B to ‘The
mobile learning platform–College English IV’box shows that Cohort B
has no access to the mobile learning platform. However, the line con-
necting Cohort A to ‘The mobile learning platform–College English IV’
box indicates that Cohort A learns English aided with the mobile learn-
ing platform. One semester passed before the questionnaires were filled
in to identify satisfaction and cognitive loads, and subsequently TOEFL
was completed to determine their EFL proficiency. It is necessary to
make clear that the teaching materials in the mobile learning platform
could supplement both in-class time and after-class academic activities.
The materials were provided by the researchers themselves in this study.
They were not adapted from other computer assisted language learn-
ing materials.
4. Results
Through scales of satisfaction, EFL proficiency and cognitive loads, data
were obtained and entered into SPSS 16.0 for corresponding analysis.
One semester/sasfacon,
cognive loads and TOEFL
Cohort A
The mobile learning
platform--College English IV
Cohort B
Figure 1. Research procedure.
COMPUTER ASSISTED LANGUAGE LEARNING 331
4.1. Multivariate analysis
In order to properly analyze the data, it is necessary to identify if the
populations have the same variance in terms of data retrieved from scales
of TOEFL, cognitive loads, and satisfaction. F-tests for the null hypothe-
ses that two normal populations have the same variance are used, whose
results are shown in Table 1.
As shown in Table 1, the null hypotheses are rejected at the signifi-
cance level 0.05 for the data of TOEFL (F¼20.87, p¼0.00), cognitive
loads (F¼11.30, p¼0.001), and satisfaction (F¼17.41, p¼0.00).
Therefore, the populations of the data do not have the same variances
and Tamhane’s T2 was thus operated, whose descriptive statistics are
shown in Table 2.
As shown in Table 2, for TOEFL and satisfaction, Cohort A appears
higher than Cohort B, while cognitive loads in Cohort A are lower than
Cohort B. In Cohort A, the mean of EFL proficiency identified through
TOEFL is 87.49, while 86.31 in Cohort B. Similarly, the mean of satisfac-
tion in Cohort A is 58.41, which is higher than that in Cohort B
(M¼57.78). On the contrary, the mean of cognitive loads in Cohort A
(M¼90.17) is lower than that in Cohort B (M¼91.33). In order to
determine if the differences were statistically significant, tests of between-
subjects effects were conducted (see Table 3).
As shown in Table 3, in the source of cohort, main effects of EFL pro-
ficiency (F¼8.04, p¼0.005, partialg
2
¼0.023), cognitive loads (F¼9.08,
p¼0.003, partialg
2
¼0.026), and satisfaction (F¼4.26, p¼0.040, parti-
alg
2
¼0.012) are significant at the significance level 0.05. Therefore, dif-
ferences in EFL proficiency, cognitive loads, and satisfaction are all
statistically significant, i.e. EFL proficiency and satisfaction in Cohort A
are significantly higher than those in Cohort B, while cognitive loads in
Cohort A are significantly lower than those in Cohort B. Consequently,
three hypotheses ‘H1: In EFL classes, participants with the mobile learn-
ing platform are significantly more satisfied than those without it; H2: In
EFL classes, learning outcomes of participants with the mobile learning
platform improve significantly more than those without it; H3: In EFL
classes, cognitive loads of participants with the mobile learning platform
are significantly lower than those without it’are all accepted.
Table 1. Levene’s test of equality of error variances
a
Fdf1 df2 Sig.
TOEFL 20.87 1 338 .000
Cognitive 11.30 1 338 .001
Satisfaction 17.41 1 338 .000
Tests the null hypothesis that the error variance of the dependent variable is equal across groups.
a
Design: þcohort
332 Y. ZHONGGEN ET AL.
4.2. Interview data analysis
In total, 121 randomly selected participants in this study were invited to
participate in the interview. Finally, 92 of them agreed to be interviewed.
Each interview was recorded, followed by a transcription. Due to incom-
plete information, five questionnaires were discarded. The number of
valid questionnaires was 87. Forty-one interviewees learned EFL with the
mobile learning platform, while 46 without it. Around 69% interviewees
reported that they were satisfied with the mobile learning platform;
approximately 75% interviewees thought that their EFL proficiency could
improve due to the mobile learning platform; about 64% interviewees
believed that the mobile learning platform could release their brain bur-
den. They also provided some other information, which helped the
researchers to discuss the findings. Generally, the majority of interview-
ees agreed that the mobile learning platform could significantly improve
EFL proficiency and satisfaction, but significantly reduce cognitive loads
in EFL classes.
5. Discussion
This quasiexperimental study sought to firstly determine the student sat-
isfaction with the mobile platform, measured by the scale of satisfaction
adapted from Stokes’findings (2001). Second, it sought to determine
learning outcomes of participants with the mobile learning platform,
measured by TOEFL. Finally, it aimed to identify cognitive loads of par-
ticipants with the mobile learning platform, measured by NASA-TLX.
Table 2. Descriptive statistics
Cohort Mean Std. deviation N
TOEFL Cohort A 87.49 4.478 169
Cohort B 86.31 3.084 171
Total 86.90 3.880 340
Cognitive Cohort A 90.17 4.095 169
Cohort B 91.33 2.966 171
Total 90.75 3.615 340
Satisfaction Cohort A 58.41 2.344 169
Cohort B 57.78 3.219 171
Total 58.09 2.832 340
Table 3. Tests of between-subjects effects
Source
Dependent
variable
Type III sum
of squares df Mean square FSig. Partial g
2
Corrected
model
TOEFL 2567490.046 1 2567490.046 1.74 0.000 0.998
Cognitive 2799963.933 1 2799963.933 2.19 0.000 0.998
Satisfaction 1147392.378 1 1147392.378 1.45 0.000 0.998
Cohort TOEFL 118.587 1 118.587 8.04 0.005 0.023
Cognitive 115.886 1 115.886 9.08 0.003 0.026
Satisfaction 33.790 1 33.790 4.26 0.040 0.012
COMPUTER ASSISTED LANGUAGE LEARNING 333
The results of this study are generally consistent with previous litera-
ture in terms of satisfaction, learning outcomes, and cognitive loads (e.g.
Lin & Lin, 2016). As reported by the interviewees, the components of
the mobile learning provided enriched learning experiences for students
compared with the non-mobile learning, where lectures were conducted
via a traditional approach by using fixed classrooms, blackboards, chalks,
and multimedia projecting. The mobile learning platform embedded with
audio and video resources provided plentiful and interesting visual and
listening EFL drills as students were attracted to a wide scope of EFL
topics ranging from politics, humanities, arts, agriculture, engineering,
medicine to education. EFL teachers are able to efficiently and effectively
collect difficult language points that EFL learners encountered from the
mobile learning platform–College English IV. Teachers can then further
explicate and demonstrate solutions via the discussion forum in the plat-
form either synchronously or asynchronously. Learners can have access
to teachers’solutions and explications whenever and wherever it’s con-
venient and they can also raise new questions when they have compre-
hension difficulties. Peers are also encouraged to put forward suggestions
about the difficult questions. This cooperation between learners and
teachers is desired in the mobile platform-based pedagogical approach,
facilitating and strengthening the understanding of key EFL points and
difficult questions. Personalized guidance can therefore be realized,
coupled with effective completion of teaching and learning objectives.
The mobile learning platform could also act as a medium to share
knowledge (Lang, Zhang, Li, & Sun, 2016). Teachers can upload plentiful
EFL information in the form of videos, documents, and lecture notes to
the platform. EFL learners can download and share the EFL information
at their convenience. This knowledge distribution can be an important
supplement to the physical classroom learning and teaching. EFL teach-
ers can remind learners of the content that will be delivered in the class-
room by uploading corresponding learning materials. EFL learners can
also provide feedback to the shared content in order to let teachers aware
of what they desire. Teachers can share some interesting materials such
as bilingual EFL news, fashions, stories about culture shock, and various
traditions across the world. EFL learners can also share the materials and
learning experiences with peers. In this way, both teachers and students
are able to broaden their horizons and increase mutual understanding.
Interviewees thought team presentation was encouraged and shown
through the online applications, which could disclose learning outcomes
of individual learners in each team and thus strengthen the coordination
of individuals. Through the platform, each learner could openly assess
peer learning progress, where different opinions and questions were
334 Y. ZHONGGEN ET AL.
raised, and the diffusion of EFL knowledge was promoted. In inter-
viewees’opinion, it was outdated for EFL learners to passively receive
EFL knowledge. They were stimulated and inspired by the new model of
teaching and learning. They could freely express their own viewpoints.
Their EFL proficiency was improved in the frequent coordination and
interaction.
By using the mobile learning platform, participants, as reported by the
interviewees, have easy access to the EFL courses in their smart phones,
which may pave a solid foundation for improvements in learning out-
comes. Smart phones, as mobile devices for EFL learning, possessed the
characteristics and functions necessary for the full use of the platform.
Through smart phones, students were exposed to more opportunities to
practise their listening, speaking, reading, and writing skills without wor-
rying about their minor errors. Due to their characteristic portability,
mobility, light weight, and small sizes, smart phones are also appropriate
for EFL learning. With the small smart phones embedded with the plat-
form, students could easily retrieve a huge amount of information, not
as readily accessible through printed media and, further, by clicking
‘backward,’‘review’or any related button, easily access previously
learned knowledge.
The interviewees also indicated that with smart phones, it was
unnecessary for students to struggle through the heavy traffic and to
learn at the uncomfortable stipulated time. Instead, they could learn EFL
whenever and wherever they desired. In addition, they did not need to
carry heavy learning materials since the mobile platform provided a sea
of information. Academic activities thus became easier and more satisfac-
tory to EFL learners.
Furthermore, interaction, self-efficacy, and self-regulation were import-
ant predictors of satisfaction (Yu, 2015). The mobile platform could real-
ize online interaction with peers and teachers. The teacher could assign
task to learners and supervise its progress, which enhanced learners’
self-regulation.
Some interviewees said in the interview that the mobile learning plat-
form improved EFL learning in a variety of ways. The mobile platform
provides movies and sounds besides traditional texts. As the interviewees
reported, this multi-modal input of knowledge reduced boredom and
redundancy, releasing participants’cognitive loads; easier access to infor-
mation enlarged working memory, preparing more capacities for infor-
mation processing, leading to higher EFL proficiency; convenience of
learning in terms of time and venue also provided learners with more
opportunities to engage in learning; animated movies, rich sounds, and
colorful texts on the mobile platform activated learners’passive learning
COMPUTER ASSISTED LANGUAGE LEARNING 335
motivation and psychologically interested learners. This internal positive
stimulation might have promoted learners’cognitive construction, due to
which cognitive loads were reduced.
Increased satisfaction and reduced cognitive loads doubtlessly
improved learning outcomes, contributing to higher EFL proficiency in
Cohort A (with the mobile learning platform) compared with Cohort B
(without the mobile learning platform). With less cognitive loads, learn-
ers could apply cognitive strategies to EFL learning, leading to higher
EFL proficiency. With the mobile learning platform, they could have dir-
ect access to learning materials instead of searching on the Internet for
the target information. In this way, they saved a great amount of time
and energy for meaningful learning activities, by which they could rea-
son, analyze, take notes, summarize, synthesize, outline, and reorganize
information to construct intensive schemas (Oxford, 2001). Simply, the
mobile learning platform might have promoted satisfaction, raised
TOEFL scores, and reduced cognitive loads. However, we could not rush
to the conclusion that Cohort A’s significantly higher satisfaction level,
and significantly lower cognitive load, were due to the significantly
higher TOEFL scores of this Cohort.
As reported by the interviewees, answering and discussing questions in
the classroom, learners might feel shy and anxious, which might inhibit
their EFL schemas constructed in their brain. Through the mobile plat-
form, learners did not necessarily meet each other. Rather, they could
feel free to share opinions, discuss and answer questions online. They
could choose either anonymous or real-name registration system. They
could also switch between anonymity and real name. This free option
relaxed learners and avoided many embarrassing occasions, which might
have improved learners’EFL proficiency. Teachers also participated in
the online learning, which could have developed an awareness of the
behaviors required to facilitate learners’future participation in online
learning (Satar & Akcan, 2018).
In general, it is reasonable to accept the research hypotheses: (1) In
EFL classes, participants with the mobile learning platform are signifi-
cantly more satisfied than those without it; (2) In EFL classes, learning
outcomes of participants with the mobile learning platform improve sig-
nificantly more than those without it; and (3) In EFL classes, cognitive
loads of participants with the mobile learning platform are significantly
lower than those without it.
6. Conclusion
The three hypotheses were validated by this study and findings in this
study are generally consistent with previous studies. It is concluded that
336 Y. ZHONGGEN ET AL.
in EFL classes, participants with the mobile learning platform–College
English IV, are more satisfied (Sarrab et al., 2016), obtain higher learning
outcomes (Jeno et al., 2017), and carry less cognitive load burden (Lin &
Lin, 2016) than those without it. This section will discuss advantages and
disadvantages in this study, together with future research directions.
6.1. Advantages
This study, combining quantitative with qualitative research methods, was
properly designed. The number of participants was large enough to repre-
sent the population. The research instruments to collect data were both
internally reliable and externally valid. The research procedure was under
supervision. The interview was also cautiously recorded and transcribed.
6.2. Disadvantages
Although this study was properly designed, there were still defects in it.
The large sample might be difficult to be perfectly controlled and the
data from interviews might be subjective and thus unreliable.
6.3. Future research directions
Although the mobile learning platform was proved effective to improve
EFL proficiency, some still suggested approaching the issue of mobile
learning with caution. Computer assisted language learning studies are still
in need of serious designs (Burston & Arispe, 2018), and more advanced
mobile learning platforms were needed. Large datasets of learning activ-
ities could be used to perceive online learning behavior and improve
teaching designs (Gelan et al., 2018). Satisfaction and cognitive loads are
not easily identified through questionnaires since they fall into the cat-
egory of psychology. Interdisciplinary cooperation between educational
technology, psychology, linguistics, statistics, neurology, and cognitive sci-
ence may be needed in future studies. Future mobile learning platforms
should be established based on convincing interdisciplinary research.
Note
1. All individuals listed as authors qualify as authors and have approved the
submitted version; The work is original and is not under consideration by any
other journal; The work has permission to reproduce any previously
published material.
COMPUTER ASSISTED LANGUAGE LEARNING 337
Acknowledgments
The authors wish to thank the people who help this study and the projects which finan-
cially support this study.
Disclosure Statement
No potential conflict of interest was reported by the authors.
Funding
The projects which financially support this study: Jiangsu Provincial Social Science Fund
in 2016 ‘Effect of College English flipped classroom in Jiangsu’(16YYB004); The
Fundamental Research Funds for the Central Universities (2018B22214); and Chinese
fund for the humanities and social sciences (Chinese Academic translation) (17WSS005).
ORCID
Yu Zhonggen http://orcid.org/0000-0002-3873-980X
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340 Y. ZHONGGEN ET AL.
Appendix A
A satisfaction scale (adapted from Stokes, 2001)
Appendix B
NASA-TLX 6-dimensional questionnaire (Hart and Staveland, 1988)
N Questions Scale
1 I am able to access the mobile learning platform with an Internet connection
to do my work.
5¼very often
4¼often
3¼sometimes
2¼seldom
1¼never
2 The resources I need are readily available through the mobile learn-
ing platform.
3 I am satisfied with the degree of contact I have with my teacher when work-
ing through the mobile learning platform.
4 I am pleased with the success I am having with completing my work through
the mobile learning platform.
5 My technology knowledge level is sufficient for learning through the mobile
learning platform.
6 I am feeling somewhat connected to the University setting by taking a class
that places emphasis on learning through the mobile learning platform.
7 I would prefer to take more of my classes through the mobile learn-
ing platform.
8 Participating in the mobile learning platform has allowed me more flexibility
in my daily activities.
9 I would prefer more of the course materials in my traditional face-to-face
classes to be in the mobile learning platform.
10 I believe that working in the mobile learning platform enables me to play a
more active role in the learning process.
11 Communication with other students through the mobile learning platform is
a positive experience.
12 I find the mobile learning platform to be useful in helping me understand
the material.
13 The mobile learning platform is providing me with skills that I can use in
other courses.
14 I believe that the mobile learning platform is preparing me for future profes-
sion development.
Title Descriptions Scale
Mental demand Much mental and perceptual activity was
required (e.g. thinking, deciding, calculat-
ing, remembering, looking, searching,
etc.). The task was demanding
and complex.
4¼totally agree
3¼agree
2¼disagree
1¼totally disagree
Physical demand Much physical activity was required (e.g.
pushing, pulling, turning, controlling, acti-
vating, etc.). The task was demanding,
slow, strenuous, and laborious.
Temporal demand Much time pressure I felt due to the rate or
pace at which the tasks or task elements
occurred. The pace was slow and frantic.
Effort I had to work mentally and physically hard
to accomplish my level of performance.
Frustration level I felt insecure, discouraged, irritated, stressed
and annoyed during the task.
Performance I was unsuccessful in accomplishing the goals
of the task set by the experimenter. I was
not satisfied with my performance in
accomplishing these goals.
COMPUTER ASSISTED LANGUAGE LEARNING 341
