Chinese postgraduate EFL learners’ self-directed use of
mobile English learning resources
Danyang Zhang1; Pascual Pérez-Paredes2
1,2 Faculty of Education, University of Cambridge, 184 Hills Road, Cambridge, UK, CB2 8PQ
Despite the increasing ownership of mobile devices among Chinese postgraduate EFL learners,
relevant studies regarding mobile English learning resources (MELR) use by postgraduate
learners are still lacking. This study tries to understand the uses and the motivation behind
language learners´ selection of MALL resources. In this research, 95 Chinese postgraduate
students from four university levels took part in a questionnaire, and eight of them in an
interview. The results show that “passing exams” was the top reason for using MELR and
expanding one’s English vocabulary was the aspect learners aimed to improve. The portability
of mobile devices enabled learners to use MELR during short time intervals
, which suggests
that MALL applications should target this behaviour. However, as a type of supplementary
material, few students used MELR for more than one hour per day, and they were not regularly
and actively involved in using MELR. Few learners were able to select suitable MELR to meet
their current English learning needs, and they relied on recommendations from social media
and authoritative education experts. Due to the importance of vocabulary, mobile dictionaries
and vocabulary learning applications were the learners’ favourite type of MELR. As the
participants suggested, enjoyment and interactivity were the two driving factors behind MELR
selection and use. On the basis of Framework for the Rational Analysis of Mobile Education
(FRAME, Koole, 2009) and Technology Acceptance Model (TAM, Davis, 1989; TAM 2,
Venkatesh & Davis, 2000), a new theoretical model for better understanding the complex nature
of mobile-assisted language learning (MALL) and the importance of learners in the self-
directed, non-formal English language learning setting is proposed in this study.
Keywords: MALL, MELR, English language learning, Chinese postgraduate EFL learners,
learners’ self-directed use
In contemporary China, competence in English is considered a critical factor in opening doors
to better education, jobs and more prestigious lifestyles (Pan, 2011). Despite the recent
integration of computers and technology into the classroom, adherence to the National College
English Teaching Syllabus (NCETS) means that college English teaching in China remains
test-centred. As a result, many Chinese learners of English are experienced language test takers.
English language education at the undergraduate level is relatively systematic. The college
English curriculum endorsed by China’s Ministry of Education (MOE) offers three levels of
listening, reading, speaking, writing and translation skills to undergraduates. While universities
are understandably concerned about postgraduate students’ professional development,
achieving further English proficiency lies with the students themselves. Consequently, the
majority of postgraduate students tend to learn English in non-formal learning settings with no
guidance (Ren, 2010).
In this study, “short time intervals” is the opposite of “a long period”, usually referring to a small window of
time in people’s daily lives (e.g., waiting for a bus and queueing).
The ownership and use of mobile devices generate and facilitate more non-formal language
learning opportunities for learners (Kukulska-Hulme, 2009). Mobile technologies allow
students to access learning content of all types anywhere and at any time (Kukulska-Hulme &
Shield, 2008, Kukulska-Hulme, Lee & Norris, 2017; Pachler et al., 2010). In China, most
university students are equipped with touchscreen smartphones and utilise different MALL
platforms (e.g., College English IV
) (Yu et al., 2017). However, offering students mobile
devices does not guarantee their effective use to acquire language knowledge (Chen, 2013;
Stockwell, 2008). As Conole and Pérez-Paredes (2017) argue, students’ learning outcomes are
not merely determined by the technology itself. Learners use the same technology differently
to achieve their learning aims (Lai, Hu & Lyu, 2018), but many may fail to effectively use the
resources available due to a lack of digital literacy skills (Conole and Pérez-Paredes, 2017). In
this context, understanding learners’ self-directed uses of MALL is of great significance.
Having reviewed the previous studies in MALL, we found these studies still primarily
focuses on how mobile technologies facilitate learners’ language learning (e.g., exploring the
widely-used commercial L2 learning apps like Duolingo, Loewen et al., 2019). MALL studies
have been slow to explore the process that learners use mobile devices to support learner-led
language learning approaches, which was suggested by Kukulska-Hulme and Shield (2008).
Besides, very less attention was paid to making theoretical contributions and considering other
factors of relevance in second language acquisition (SLA) theory and practice (Duman, Orhon
& Gedik, 2015). Therefore, in this study, we reviewed two well-cited and widely-used
frameworks: (1) Koole’s (2009) Framework for the Rational Analysis of Mobile Education
(FRAME), which integrates technical, personal and social aspects of mobile learning to
understand mobile learning and MALL from a multidimensional perspective at a macro-level;
and (2) the Technology Acceptance Model (TAM, Davis, 1989; TAM 2, Venkatesh & Davis,
2000), which specifically focus on the role of learner, understanding the significance of learners’
perceptions, behavioural intentions, and actual uses of technologies at a micro-level. We aim
to situate and conduct our research from multidimensions towards learner use and experience
This study centres around mobile English learning resources (MELR) conceptualised as
mobile applications, websites, e-books, online courses, and online discussion platforms/forums
on handheld mobile devices. Our main focus is on Chinese postgraduate EFL learners, one of
the leading mobile user groups in China facing a “transitional period” from formal teacher-led
English learning to non-formal self-directed English learning. Our main research question is:
How do Chinese postgraduate EFL learners approach self-directed use of MELR in their
English language learning?
In this paper, we firstly introduce two relevant theoretical models of mobile learning and
introduce Chinese university EFL learners’ MELR use based on previous studies. In the
methodology section, details are given about the research design, sampling and participants,
data collection and analysis. This is followed by an analysis of our key quantitative and
qualitative findings. Finally, these results are discussed, and a new theoretical model is
proposed before recommending further research avenues.
2. Literature Review
“College English IV” is an online platform that offers many EFL learning resources.
2.1 Two theoretical frameworks: The Framework for the Rational Analysis of Mobile
Education (FRAME) (Koole, 2009) and the Technology Acceptance Model (TAM, Davis,
1989; TAM 2, Venkatesh & Davis, 2000)
2.1.1 FRAME (Koole, 2009)
In FRAME (Koole, 2009) (Figure 1), there are three main aspects, mainly depicting the process
that learners interact with information mediated through technology. The device aspect relates
to the different physical and technological characteristics of mobile devices (e.g., the
keyboard/voice/multilingual interfaces), which impact hugely on how learners interact with
resources and determine whether these are adopted in the long run (Pérez-Paredes et al., 2019).
The learner aspect takes into account learners’ cognitive abilities, memory capabilities,
language knowledge and learning motivations, illustrating how learners receive, process,
internalise, store and use knowledge when using a mobile device. The social aspect underlines
communication and interaction and refers to the process through which learners communicate,
exchange and acquire knowledge either with others or on their own. These three aspects
converge alongside three interaction zones that describe the mutual attributes of every two
circles. Device usability links the characteristics of mobile devices to cognitive tasks in
manipulating and storing information. Social technology addresses communication and
cooperation between devices, systems and learners. Interaction learning focuses more on the
interaction between learner and content, as well as the social interaction between individuals.
Figure 1 FRAME (Koole, 2009)
This framework was built using cognitivist perspectives of learning intrinsically related to
how learners understand knowledge in their brain (Selwyn, 2011). In addition, Koole (2009)
also drew on (a) constructivism, which looks at learning as a dynamic process where learners
acquire knowledge from others and then construct their knowledge (Dewey, 1916; Piaget,
1973); and (b) sociocultural theories (Vygotsky, 1978), which emphasise the influence of social
and cultural contexts on the learning process and outcomes.
2.1.2 TAM and TAM 2 (Davis, 1989; Venkatesh & Davis, 2000)
TAM (Davis, 1989) (Figure 2) is one of the most widely used models to explain and predict
people’s behaviour when using technology. According to Davis (1989), perceived usefulness
(U) refers to the degree to which the user believes their job performance could be enhanced by
using the system, which by and large positively affects the user’s acceptance of the system and
their actual use. Perceived ease of use (E) relates to whether the user believes they can
effortlessly use the system, which sometimes becomes a determinant of user’s perceived
usefulness (U). Attitude toward using (A) is impacted by perceived usefulness (U) and perceived
ease of use (E) and influences the user’s behavioural intention (BI) to use the system, which is
followed by the occurrence of the user’s actual system use. The original TAM was overhauled
and further developed in 2000 (named as TAM 2, Venkatesh & Davis, 2000). TAM 2
demonstrates the validity of the original model and also underlines other factors that may
impact the user’s behaviour. Particularly, it highlights the concept of subjective norm, which
refers to a person’s perceptions of how others think he/she should or should not perform the
Figure 2 Technology Acceptance Model (Davis, 1989)
2.1.3 Discussion of the two frameworks
The two frameworks – FRAME (Koole, 2009) and TAM/TAM 2 (Davis, 1989; Venkatesh &
Davis, 2000) - contribute valuable theoretical insight in understanding mobile learning and the
vital role of learners in technology-enhanced language learning environments. As a useful
analytical lens, FRAME (Koole, 2009) is heuristic as it integrates a variety of dimensions.
However, this model is to some extent generic, suggesting that the device, learner and social
aspects share the same importance or weight. Yet this is not necessarily the case. As Colpaert
(2004) emphasised, learners should be prioritised ahead of technologies, and the importance of
the language learning environment should be highlighted before deliberating the role of mobile
technologies. It means, in the self-directed non-formal MALL setting, learners are typically
autonomous, managing and regulating their language learning process.
In view of this, we take TAM (Davis, 1989) and TAM 2 (Venkatesh & Davis, 2000), which
emphasise the learner aspect and the device usability intersection in FRAME (Koole, 2009),
into account. This model specifically offers insight into understanding the role of users,
illustrating how users’ perceptions (perceived usefulness and ease of use of the system),
attitudes and behavioural intentions can directly or indirectly impact their actual use.
Nevertheless, this model fails to show user’s behaviour in using technologies (Lim et al., 2016),
including the place and the time (“where” and “when”) and the content they aim to learn
(“what”), as well as the way they make their learning successfully happen (“how”) (Kukulska-
Hulme, 2012a). Besides, this model could not sufficiently predict the user’s future acceptance
of technologies (Ajibade, 2018). Over the years, although the original TAM and TAM 2 have
been criticised, developed and extended to fit dynamic contexts, it still holds for the modern
times (Alwahaishi & Snášel, 2013). Some extensions of the TAM, like Unified Theory of
Acceptance and Use of Technology (UTAUT) (Venkatesh et al., 2003), were pointed out some
shortcomings in adding too many different variables that lead to the theoretical chaos and
confusions (Bagozzi, 2007).
Drawing on FRAME (Koole, 2009) and TAM/TAM 2 (Davis, 1989; Venkatesh & Davis,
2000), this study aims to propose a new theoretical model that better fits the technology-
enhanced, learner-centred and non-formal learning setting, in order to better understand how
EFL learners make use of MELR in their English language learning.
2.2 A review of Chinese university EFL learners’ MELR use
As Miller and Wu (2018, p.7) proposed when adopting mobile technologies for language
learning, “much more attention needs to be given to how students use strategies in their informal
mobile learning.” In recent years, scholars have carried out constructive studies on Chinese
university EFL learners’ MELR user experiences. For example, Fei and Guo (2015) reported
that most Chinese university EFL learners had experience using mobile applications to learn
English. 46.3% of participants spent less than an hour a day using MELR. In contrast, none of
them dedicated more than three hours a day to this task. As for the students’ goals when using
MELR, researchers have found that a large number of students seek to expand their English
vocabulary range. Fei and Guo (2015) observed how 82.9% of their participants use or had used
MELR to learn vocabulary, including mobile dictionaries (e.g., Youdao Dictionary and Jinshan
Dictionary) and mobile vocabulary learning applications (e.g., Baicizhan). All three
aforementioned studies illustrate the overriding importance of vocabulary in English language
learning and the popularity behind vocabulary resources in China. These findings, however, are
not limited to mainland China. Similar results in Lai and Zheng’s (2018) study show that
university students in Hong Kong turn to mobile dictionaries to study L2 vocabulary and
Earlier research gives us useful insight into how Chinese university EFL learners, especially
undergraduates, use MELR. However, no previous studies have primarily focused on Chinese
postgraduate students enrolled at different universities and with varied English language
proficiency levels, investigating learners’ MELR use. These students, with more targeted
English learning aims, are not obligated to attend any standard exams like CET-4
As there are few ESP (English for Special Purposes) course choices and high-quality English
textbooks for them (Ren, 2010), their English language learning tends to be more self-directed
by choosing and using various technology-enhanced language learning tools and materials.
Through this research, we hope to contribute towards a better understanding of the self-
directed non-formal language learning practices adopted by Chinese postgraduate EFL learners,
incorporating both these experiences into theory building which may help in the design and
implementation of pedagogies in self-directed contexts. Given the limited research in this area
of language learning, we seek to identify the types of MELR postgraduate Chinese students
choose and the different uses of such resources.
3.1 Research design
This mixed-method study, which follows a quasi-experimental research design, makes use of
quantitative data from an online questionnaire and qualitative data from interviews. The
questionnaire was designed to collect students’ self-report data on their MELR use for English
learning. The semi-structured interview offered participants the opportunity to discuss their
MELR use in more detail.
3.2 Sampling, participants and instruments
In this study, we highlight the learner aspect and the interaction learning intersection in
FRAME (Koole, 2009) and fill in the gap (fail to show learner’s actual use of technologies) of
TAM/TAM 2 (Davis, 1989; Venkatesh & Davis, 2000), aiming at exploring learner’s MELR
use in non-formal settings. We draw on Kukulska-Hulme’s (2012a) Wh- and How questions,
which are widely used to collect and analyse both quantitative and qualitative data in MALL.
Specifically, the questionnaire featured 12 questions (11 closed-ended questions and one open-
ended question). In addition to the demographic background questions, seven closed-ended
College English Test – Band 4
College English Test – Band 6
questions elicit information on participants’ MELR use. The closed-ended questions, which are
multiple-choices or Likert scale questions, cover the following issues:
(1) Why do students use MELR?
(2) What are the most frequently-used MELR?
(3) How do students select MELR?
(4) When do students use MELR during the day?
(5) How long and how often do students use MELR per day?
(6) How do students use MELR?
(7) Will students use MELR in the future?
The one open-ended question was designed to gather student comments and suggestions for
the developers and researchers.
We adopted a stratified sampling strategy to gain insight into language learners from various
academic backgrounds and with different experiences in using MELR. The questionnaire was
administered to 100 Chinese postgraduate EFL learners from across four levels of university
study in China via SurveyGizmo (www.SurveyGizmo.com).
In total, 95 valid questionnaires could be used for further analysis. By using the stratified
sampling technique (Tashakkori & Teddie, 2003), 24 learners were identified as coming from
a “985 Project” university, which is classed as one of the best universities in China (Tier A);
23 were from a “211 Project” university, a key university which ranks lower than the 985 in
terms of its students’ comprehensive abilities, funding, teachers’ abilities and infrastructure
conditions (Tier B); 24 learners were from a mainstream public university, which means that
they perform considerably less well than their 985 and 211 peers (Tier C); and 24 learners were
from one of the low-ranked Chinese universities (Tier D).
Specifically, 27 participants (28.4%) were male, and 68 (71.6%) were female. The
Humanities and Social Sciences accounted for 68.4% of participants. Four (4.2%) were
studying in Engineering, and 12 (12.6%) were Science students. Fourteen students chose “other”
postgraduate programmes, including Medical Science, Business, and Management.
In terms of English language proficiency, 8.4% of the participants have not passed CET-4
or TEM-4. 28 (29.47%) had passed CET-4 or TEM-4
but had not yet taken CET-6 or TEM-8.
Over half (56.8%) of them had already passed CET- 6 or TEM-8
. The number of students who
have achieved good scores in the exams usually taken to study abroad (e.g., IELTS, TOEFL,
GRE) only represented 5.3%.
Regarding the semi-structured interview, the questions sought to explore the reasons behind
the aforementioned seven questions in more details. The purposive sampling technique
(Tashakkori & Teddie, 2003) was implemented, and eight interviewees from the four university
levels with different backgrounds and MELR use experiences were invited to take part. Table
1 shows the demographic characteristics of all eight interviewees. The interviews were audio-
recorded for subsequent analysis.
Table 1. Demographic characteristics of the interviewees
Humanities & Social science
4Test for English Majors – Band 4
Test for English Majors – Band 8
Humanities & Social science
Humanities & Social science
Humanities & Social science
IELTS (Overall 6.5)
Humanities & Social science
Humanities & Social science
A sequential triangulation of quantitative and qualitative data contributed to enhancing our
understanding of Chinese postgraduate EFL learners’ use of MELR. Specifically, quantitative
data were used to depict an overall learner-centred story, whereas qualitative data aimed to
explore further in order to “validate or expand quantitative results” (Creswell & Clark, 2007,
p.62); in other words, to obtain more details about learners’ MELR use.
3.3 Data analysis
The closed-ended questions in the questionnaire were computed using descriptive statistics.
The qualitative data from the open-ended questions in the questionnaire and the interviews were
transcribed using InqScribe (Version 188.8.131.528); they were then coded and analysed using
MAXQDA 12 (Release 12.1.3). The qualitative data were analysed using thematic analysis.
Because learners’ use of MELR may be highly personalised, we descriptively labelled the data
to ‘units of meaning’ (Miles & Huberman, 1994, p.56) and initially coded all target data at a
relatively lower conceptual level. By adopting a grounded approach to coding, we used the
emerging codes to guide the rest of the data analysis process, before we grouped the initial
codes into themes at a more abstract level. After reviewing, defining and naming the themes,
the initial results could be examined.
4.1 Why do students use MELR?
As emphasised by Koole (2009), Davis (1989), and Venkatesh and Davis (2000), learners’
motivation and emotional state as well as their perceived usefulness and ease of resource use
are significant when it comes to accomplishing learning tasks. As such, we examined the
reasons behind the students’ MELR use given in the questionnaire. According to their
, “passing exams” was the top reason for using MELR (62.1%). Half of the
participants (49.5%) aimed to improve their communication skills in their daily lives. In
contrast, only 12.6% used MELR because of their interests or hobbies in English, and four
participants did not report particular reason for choosing MELR.
Participants were also asked to choose which area(s) they intended to improve through
MELR. Vocabulary was the aspect that students wanted to enhance the most (64.21%) but is
lower than Chen and Xu (2016)’s result (74.2%). By contrast, fewer participants chose reading
(28.42%) and writing (20.0%), and grammar was the least popular option (6.31%). This result,
however, partly contradicts Vuorio et al.’s (2018) study, where expanding vocabulary size and
learning grammar was found to be the two aspects that Finnish students hoped to learn using
In the interviews, five learners mentioned that passing exams was their primary reason for
using MELR, and three aimed to improve their communication skills. However, these three
students added that they still had plans to obtain a high score in exams such as the TOEFL and
IELTS. For example, as Interviewee 2 explained:
“Because speaking was not assessed in the College Entrance Examination, we did not really
care about our communication skills. However, as I now plan to study abroad after graduation,
This question is a multiple-choice question which invites participants to select more than one applicable option.
these skills are necessary. Among others, I have to pass the IELTS test in which speaking is a
key part.” (Interviewee 2)
In short, both the quantitative and qualitative data elicited highlight the importance that
Chinese postgraduate EFL learners attach to passing English tests and learning English
4.2 What are the most frequently-used MELR?
Regarding participants’ most frequently-used MELR that is an optional question in the
questionnaire, Table 2 shows that all 50 mentioned resources are mobile applications, a clear
indication of the popularity of mobile applications among Chinese postgraduate EFL learners.
In particular, vocabulary applications were their top choice: Youdao Dictionary was the most-
mentioned MELR (16 times), followed by Baicizhan (10 times) and Shanbay Words (8 times)
which reinforces the conclusions in Fei and Guo (2015) and Liu and Chen (2012),
demonstrating the popularity of word-related products and the great significance of English
vocabulary among Chinese postgraduate EFL learners. A number of other applications for
improving different English skills were also on the list. Interestingly, grammar and writing
resources were not the most widely sought-after ones, although the positive impact of MALL
on writing (e.g., Hwang et al., 2014) and grammar (e.g., Moghari & Marandi, 2017) acquisition
has been confirmed in previous research.
Table 2. Most frequently-used MELR
Mobile dictionary application
Vocabulary learning application
Vocabulary learning application
Comprehensive English learning application
Mobile dictionary application
Listening learning application
Listening learning application
Listening learning application
Listening learning application
Listening learning application
Reading learning application
Listening learning application
Comprehensive English learning application
Speaking learning application
Listening learning application
Speaking learning application
In the interviews, vocabulary learning applications were rated as the favourite MELR by
participants. In particular, vocabulary learning applications including Baicizhan, ToWords and
Shanbay Words, and mobile dictionaries such as Bing Dictionary, Webster & Merriam
Dictionary, Jinshan Dictionary and Youdao Dictionary, were specified.
In particular, some of the mobile vocabulary learning applications like Shanbay Words
provide users with a platform to share everyday achievements. Participants agreed on the
benefits of sharing, emphasising how witnessing their friends’ achievements could motivate
them to make more effort in their English learning. This view reflects the interaction learning
intersection in Koole’s (2009) framework, where learners in learning communities work with
others to reach mutual goals (Koole, 2009). During this process, peer pressure deriving from
mutual comparison and competition might emerge, which could encourage Chinese EFL
learners’ interests and motivation in language learning (Yan & Horwitz, 2008). As Interviewee
3 mentioned, seeing the other’s progress is a powerful trigger:
“I am not able to use the resource every day and finish the tasks step by step. However, when
I see the posts of my friends or classmates, showing their achievements in English vocabulary
learning, I will be motivated, and I will make more efforts to study English.” (Interviewee 3)
4.3 How do students select MELR?
The learner aspect in Koole’s (2009) framework highlights discovery learning, whereby the
learner filters and selects information based on their current situation, learning needs,
perceptions and attitudes (Davis, 1989; Venkatesh & Davis, 2000). However, our results are
not promising. Data show that few participants (7.4%) believed they are often able to choose
appropriate MELR to meet their current learning needs. Only 3.2% reported that they always
use or had used one or more MELR that fulfilled their English learning needs. These results
may suggest that few learners have the awareness or ability to select appropriate types of MELR
at different English learning stages.
All interviewees mentioned how important recommendations are when selecting MELR. As
explained by interviewees 3 and 6, Zhihu and Douban, two of the better-known Q&A online
forums in China, contain a wealth of user experiences and comments on MELR. Accordingly,
visitors to these forums can draw on others’ experiences when deciding which MELR to choose
next. According to Interviewee 5, Weibo, a popular Twitter-like social media platform,
frequently offers MELR advice and recommendations on some public pages.
Recommendations featured on Apple Store and Google Play were identified as other avenues
for obtaining information on highly-rated MELR. Other students, like Interviewee 8, preferred
to take the advice of experienced teachers, combining their recommendations with current
English learning aims.
4.4 When do students use MELR?
The questionnaire results show that 44.2% of participants preferred to use MELR over short
time intervals; for example, during breaks, on public transport, when waiting for other people,
or before bed. The proportion of MELR use during small windows of time is much higher than
that observed in Chen and Xu’s (2016) research (29%). Drawing on Koole’s (2009) framework,
this points to information availability in the device usability intersection, highlighting the
‘anytime, anywhere’ access to information stored on mobile devices. 41% of postgraduates do
not set aside a specific time of the day for using MELR. In addition, students were accustomed
to using this kind of resource during class (16.8%), after class (17.9%), while previewing
(8.4%), while reviewing (21.1%), in the morning (11.6%), and at night (18.9%). However, noon
and afternoon were the two least popular timeframes, only accounting for 5.26%.
In the interviews, one interviewee (Interviewee 1) reported using MELR several times
throughout the day; one (Interviewee 5) frequently used a mobile English dictionary application
in class to look up new words, and four students usually used MELR during short time intervals.
As the latter students highlighted, MELR’s portability removes the barriers of time and place,
enabling them to utilise their study time more effectively. Two other interviewees (Interviewee
3 and 8) liked to use MELR when reviewing. However, both viewed MELR as an additional
tool for English exam preparation. They still mostly used hard copy materials (e.g., books, past
papers and notes) as their primary source of learning activities.
4.5 How long and how often do students use MELR?
When asked about how long they spend using MELR, around 95% of participants reported that
they typically used MELR for under 2 hours a day; 67% dedicated less than one hour. The
findings accord with Fei and Guo (2015) and Chen and Xu (2016). In contrast, only 5.26%
typically spent more than two hours on MELR.
In the interviews, five interviewees claimed to usually spend less than one hour on MELR a
day, and two typically spend one to two hours a day. All of them estimated that they spend less
time on MELR than on reading paper books, listening to lectures, and reviewing study notes.
They still rely on paper-based learning materials that can be quickly annotated and highlighted
for exam preparation. Furthermore, unlike MELR, hard-copy resources are better for the eyes,
especially when consulting materials over a long period of time. There was, however, one
exception: Interviewee 6 reported using MELR more than six hours a day. She was also the
only one who chose this option in the questionnaire.
Regarding frequency, data in Table 3 show that irrespective of the type of MELR in question,
few participants (1.1% to 3.2%) always used it. Around a quarter of students reported often
using mobile English learning applications (23.2%) and English learning e-books (21.1%),
whereas few postgraduates (less than 10%) often spent time on the other three types of resources.
Many participants sometimes or seldom used MELR, regardless of the type. The results
reconfirm that MELR is not a mainstream form of English learning materials among Chinese
postgraduate EFL learners.
Table 3. Frequency of MELR use
Online videos (e.g., online
courses, TV series, movies)
Online discussion platforms
During the interviews, the interviewees expressed opposing views on websites, e-books and
videos. Interviewee 4 preferred to browse English learning websites on mobile devices. She
recommended the webpage version of China Daily and Youdao Dictionary given their abundant
and useful content, claiming that her perceptions of the usefulness of English learning websites
affect her actual MELR use (Davis, 1989; Venkatesh & Davis, 2000). However, mobile devices
are often criticised for their output capability limitations (e.g., small screen size). In this study,
some interviewees (e.g., Interviewee 8), criticised the small screen size of some websites, which
made for poor reading and learning via the mobile medium. This shows how her perceived ease
of use influences her use of mobile English learning websites (Davis, 1989; Venkatesh & Davis,
When asking interviewees asked why they do not usually use e-books, interviewees 1 and 2
emphasised that there were few differences between paper books and e-books. Compared with
mobile applications featuring colourful images, detailed explanations and even games, they find
it difficult to concentrate on reading e-books for an extended period of time. On the contrary,
portability in the device usability intersection of Koole’s (2009) framework was praised by
Learners do not use MELR.
Learners use MELR one day a week.
Learners use two to three days a week.
Learners use MELR four to five days a week.
Learners use MELR six to seven days a week.
interviewees 4 and 5 who mentioned being able to read e-books anytime, anywhere. For
example, Interviewee 5 said:
“I do not need to carry many heavy books to the library; I am never crazy about how to deal
with the time when I am waiting for the bus anymore. I do not need to spend a lot of money on
purchasing paper books because I can select and read e-books from the university library
collections” (Interviewee 5).
As for online English video viewing on mobile devices, interviewees 2 and 3 perceived the
usefulness (Davis, 1989; Venkatesh & Davis, 2000) of online courses via MOOC and Future
Learn, creating opportunities for learners to learn the target language as well as the culture.
Interviewees 1 and 7 held negative attitudes towards audio-visual media such as English TV
series and movies. They pointed out that the content and plots may distract them from language
learning. In the words of Interviewee 7: “I think there are lots of students like me who are
concentrating on what is going on when we watch videos, rather than how language is used
and its appropriateness.”
Based on the above results, it is clear that there are individual differences in how Chinese
postgraduate EFL learners perceive their use of e-books, videos and websites, highlighting
personalised learning as a distinctive feature of MALL (Kukulska-Hulme, 2012b). The results
also confirm the impact of learners’ perceived usefulness and ease of MELR use on their actual
use (Davis, 1989; Venkatesh & Davis, 2000).
4.6 How do students use MELR?
The interaction learning intersection of Koole’s (2009) framework introduces the learner-
content interaction, which refers to the process whereby a learner actively engages with learning
materials and the cognitive changes in his or her mind. The questionnaire results show that only
1.1% of participants always remain active when using MELR (e.g., taking notes, reviewing,
and completing tasks), which is consistent with Guo, Xiong and Liu (2011)’s conclusion that
most students cannot persist in using a MELR for a long period of time. Many MELR like
Liulishuo, which aim to provide personalised and adaptive learning experiences, create study
plans for users (e.g., setting study goals, displaying study reminder popups, and progressively
assessing learning achievements). However, only 5.3% were always able to follow the plans,
which suggests that most of our participants may not be in the habit of planning their studies
In the interviews, only two interviewees reported that they are always regularly and actively
involved in MELR. For example, Interviewee 5 used a mobile vocabulary application called
Baicizhan to memorise English words for half an hour before going to bed and practises her
spoken English via Qupeiyin after getting up. She also improves her English listening abilities
via BBC Radio while waiting for the bus. Interviewee 6, who showed a strong preference for
MELR use, explained how she often takes notes and reviews key concepts, treating MELR as
one of the most important English learning tools. As for the remaining six interviewees, their
English learning via MELR was relatively flexible and sometimes compromises other study
plans. As expressed by Interviewee 2, she occasionally lacked the motivation to complete her
tasks using MELR because nobody supervises her MELR use.
4.7 Will students use MELR in the future?
Stockwell’s (2008) study show that almost two-thirds of the learners planned to continue using
mobile devices for language learning. The percentage in this study is higher, in which 89.5%
of questionnaire participants reported that they would keep using MELR in the future. All
interviewees believed MELR has the potential to improve their English language proficiency
and are determined to continue using MELR, which indicates that learners’ perceived
usefulness of MELR contributes to their behavioural intentions (Davis, 1989; Venkatesh &
Davis, 2000). Interviewee 4 planned to improve her speaking skills and will make efforts to
find appropriate resources (e.g., Qupeiyin and Liulishuo) to practice her spoken English. For
interviewees (e.g., Interviewee 6) who sought to expand their English language vocabulary
range, mobile English dictionaries and vocabulary learning applications would become target
4.8 Comments and suggestions for future MELR development
Regarding the comments and suggestions for MELR development, “more interesting” and
“more interactive” were the two most reported responses, signalling that participants hope to
see more appealing MELR content and more engaging, dynamic tasks added to the list. They
also suggested that material should tie in more closely with their daily lives so that they can
apply what they have learnt, encouraging them to partake in “a great variety of situations in
which to negotiate meaning” (Koole, 2009, p.38).
Personalised learning reflects participants’ different viewpoints on the scope of MELR. For
instance, some students hoped to use more specific resources tackling one skill of the English
language (e.g., listening, reading, speaking and writing). In contrast, others suggested that
MELR should be more all-encompassing, taking a comprehensive approach to English learning.
transparent and freer of unrelated information. Display simplification, which suggests that “the
device is easy to use, and that the user can concentrate on cognitive tasks rather than the
manipulation of the device itself”, also contributes to psychological comfort, perceptions and
attitudes (Davis, 1989; Koole, 2009; Venkatesh & Davis, 2000). Furthermore, some
participants advised that bugs be fixed to ensure smoother user experience. Although many
varied suggestions were raised, most participants in this research held a positive attitude
Learners were invited to give more details about the comments and suggestions they had
made in the questionnaire during the interviews. First, they proposed more user-friendly
instructions and more appealing activities, assessments and even games to stimulate their
learning interests. Second, some participants criticised the user interface of some MELR. Too
much online advertising rendered the resources too messy to read and negatively affected
learning outcomes. Interviewee 2 complained that she frequently had to close the
advertisements to keep learning while browsing a number of English websites, which
undoubtedly distracted her from her studies. Some participants preferred to use free MELR. As
users, they liked to exchange the rewards earned (e.g., the “shells” in Shanbay Words) for more
English learning materials.
5.1 “Passing exams and improving exam scores” as the main reasons for using MELR
The interaction learning intersection in Koole’s (2009) framework takes into account the needs
of learners belonging to specific cultures and environments. In China, where students’ hard
work, teachers’ authority and the teacher-student hierarchy are emphasised (Carless, 2006),
passing exams and improving exams scores continue to be the primary motivation behind using
MELR. According to Pan (2011), high exam scores are often the golden keys that open the door
to future study and job success. Importantly, the exam culture in China may heavily result in
fierce competition instead of peer interaction and collaboration (Wu, 2018). Given the
significance of social interaction and collaboration in language learning, we argue that it is
necessary to re-evaluate how self-directed uses may be influenced by the contexts in which
learning takes place. Uses of MELR in China could help us reframe underlying assumptions
about perceived affordances and MALL in globalised societies. MELR use which emphasises
social interaction and collaboration alongside peers and teachers gives institutions and
individuals the opportunity to pursue language learning programmes that are not exclusively
exam-driven. However, these opportunities did not appear to be on the agenda of the individuals
taking part in this research.
5.2 Learner’s strong motivation to learn vocabulary
Given the significance of vocabulary knowledge growth in learning EFL (Teng, 2019) and the
vocabulary-centred nature of the English learning and teaching (ELT) model in China, Chinese
EFL learners are heavily engaging with memorising words. In line with conclusions drawn in
earlier studies (e.g., Ding, 2015), the present research lends evidence to the fact that Chinese
postgraduate EFL learners place considerable importance on English vocabulary learning. Our
informants believe that a large vocabulary is a key to successful listening, reading and speaking.
And this is not limited to mainland China. According to Ma (2017), lexical tools are among the
broadest categories of mobile e-resources and e-tools used by Hong Kong university students
for language learning. Steel (2012) found that the most frequently used mobile applications
among Australian university students are also related to vocabulary learning; these include
dictionaries, translators and vocabulary games. Thus, lexical knowledge is always placed at the
centre of learners’ developing communicative competence and second language acquisition
The latest review by Lin and Lin (2019) highlighted the benefits of MALL in EFL vocabulary
learning, hailing MELR as one of the future mainstream approaches in English vocabulary
learning. Given the importance of learners’ perceptions, attitudes, beliefs and motivations
towards MALL (Davis, 1989; Koole, 2009; Ma, 2017; Venkatesh & Davis, 2000), further
research should be undertaken to explore learners’ motivation to learn vocabulary in self-
5.3 MELR as supplementary English language learning materials
Findings in this study indicate that MELR remain on the margin as a type of supplementary
English learning tool in China. This is largely attributed to the continuing dominance of
traditional textbooks in the country’s English language education system. After using
traditional English textbooks for more than ten years, learners are used to following the
“transmission” model based on induction (Bezemer & Kress, 2010). In addition, and even in
non-formal learning settings, extrinsic factors like the pressure from assessed exams and
assignments can largely impact postgraduates’ attention to and involvement in MELR (García
Botero, Questier & Zhu, 2019).
The marginalisation of MELR in China’s English language education system may not only
be attributed to device-related issues, but also to learners’ attitudes towards mobile devices and
MALL. Based on the responses from Interviewee 1, who did not view mobile devices as
learning tools, there is a sentiment that communicating and socialising rather than teaching and
learning are the primary uses of mobile phone technology. This finding is consistent with Lai
and Zheng’s (2018) study, where mobile phones are closely associated with daily life rather
than serious study. However, mainland China is not an exception, as learners in other regions,
including Taiwan, Japan and Thailand also hold such attitudes (Hsu, 2013). A disparity between
learners’ personal uses and learning uses of mobile devices (Stockwell, 2007) may exist. Some
of our informants also pointed out that other applications and popup notifications via social
media, messaging and email easily distracted them from the learning tasks at hand using MELR.
5.4 MELR in Chinese postgraduate EFL learners – A new theoretical model
This study has reviewed Koole’s (2009) FRAME, Davis’ (1989) TAM, and Venkatesh and
Davis’s (2000) TAM 2, striving to propose a new theoretical model to understand and theorise
the specific context of this study - MELR in Chinese postgraduate EFL learners’ non-formal
self-directed English language learning. To achieve this, we carefully considered all three main
aspects (learner, device, social) and the intersections in FRAME (Koole, 2009). According to
our study results, first, MELR use calls for much more than further developments in the
physical, technical and functional characteristics of mobile devices as well as in MELR design
(e.g., how to minimise the adverse effects of small screens, a criticism made by participants,
Section 4.5). Second, we should emphasise here the agentive role played by learners
themselves, exploring how they filter and select MELR and internalise the newly derived
knowledge (Section 4.3 and Section 4.8). Third, because learners are located in and influenced
by a learning community in the society where peers, teachers, and universities are also found,
it is necessary to perceive these stakeholders as a vital part of MALL.
Nevertheless, unlike the original FRAME (Koole, 2009) in which all three factors (device,
learner and social) are in equal footing, we looked at how all three aspects differ in importance
within the specific context of this study. As we framed in Figure 3, the society is in a bigger
circle, indicating that learners are located in the sociocultural context, impacted by the
subjective norms (Venkatesh & Davis, 2000) by communicating, interacting, collaborating or
scaffolding. We prioritise the dominated role of learners in using MELR to learn their English
in non-normal settings. In particular, in the inner circle between Chinese EFL learners and
MELR, our model shows how learners ‘interact’ with MELR in a dynamic and progressive
process. We agree on the ideas in the original TAM (Davis, 1989) and TAM 2 (Venkatesh &
Davis, 2000) that learners’ perceptions and attitudes are the premises of their behavioural
intentions, but we specifically explored and depicted learners’ current MELR use in this study.
Arguably, not only learner acceptance of any new technology progresses at different rates
(Stockwell, 2008), learner technology use is dynamic and complicated, which could reflect the
personalised feature of MALL (Kukulska-Hulme, 2012b). Besides, conceptualising their
MELR use could theoretically contribute to the extension and conceptualisation of the original
frameworks. Pedagogically, it could also help language teachers understand how their students
self-regulate their language learning to better support them in selecting, evaluating and using
As mentioned in Section 3, we designed, conducted and presented this study by drawing on
the well-cited and widely-used Wh- and How questions by Kukulska-Hulme (2012a), from their
current behavioural intention (one question), to their current actual use of MELR (five
questions), to their future behavioural intention (one question). Starting from asking the reasons
why they use MELR, their current behavioural intention could be extracted. From the questions
investigating their frequently-used MELR, the way they select MELR, the time and length they
use MELR, and their MELR using process, we could understand the complexity and uniqueness
of learner’s MELR use. Finally, we ended up with a question asking learners’ intention of future
Figure 3 A new theoretical model of MELR in Chinese postgraduate EFL learners
In this study, we have examined Chinese postgraduate EFL learners’ use of MELR.
Quantitative and qualitative data have been collected via a questionnaire and interview. Because
of the exam culture in China, we found “passing exams”, even at the postgraduate level, to be
the main reason for Chinese postgraduate EFL learners’ MELR use. In the interview,
participants indicated that the communicative skills they seek to improve are a necessity for
specific English tests. Vocabulary development remains Chinese postgraduate EFL learners’
biggest concern. Vocabulary resources, including vocabulary learning and mobile dictionary
applications, are rated as their most favourite resources.
Another main finding is that learning via MELR is still regarded as a supplementary learning
approach. The questionnaire results reveal that most participants prefer to use MELR for less
than one hour or between one and two hours at any time, and usually during short time intervals.
This limited MELR use is reflected in the lack of regular and active learning involvement, with
most learners not working to a clear learning schedule.
Regarding MELR selection, the interview responses show that Chinese postgraduate EFL
learners prefer to take recommendations from social media and experienced experts, yet few
learners report using or having used appropriate MELR at their current learning stage. A
recommended approach would see MELR designers, MALL researchers and language teachers
from across institutions come together to further discuss how to promote appropriate resource
selection. In particular, proper training should be provided to teachers, especially to those in
less developed areas (Zhang, 2019).
Our informants made suggestions and comments that revolve around MELR’s appeal and
interaction capabilities. Looking towards the future, most informants had a favourable view of
MELR and believed this kind of resource can benefit their English language learning.
In theoretical, this study has reviewed the FRAME (Koole, 2009) and TAM/TAM 2 (Davis,
1989; Venkatesh & Davis, 2000), attempting to propose a new model to help researchers and
practitioners better understand the complexity of MALL and the important role played by
learners in self-directed non-formal learning settings. This model illustrates the dynamic
interaction between EFL learners and MELR, depicting how their previous, current and future
MELR use connect and impact each other. Going beyond the learner layer, this model is
multifaceted, taking other stakeholders (e.g., teachers, parents, peers, friends and universities)
in MALL into consideration. We argue that MALL in self-directed non-formal language
learning settings prioritises the crucial role of learners who dominate, control and regulate the
whole language learning process. Moreover, we also situate this type of learning into a
sociocultural context, crystallising MALL from multiple dimensions.
In pedagogical, we suggest that all stakeholders (e.g., researchers, universities, language
teachers, language learners and developers) in this field should not only concentrate on
technologies, developing, upgrading and evaluating the products. Given the personalised
feature of MALL (Kukulska-Hulme, 2012b), stakeholders should also acknowledge the various
role learners play in their self-directed language learning and the sociocultural context in which
they move. As the results of this study inform, this group of learners are still exam-oriented and
vocabulary-driven, regarding MELR as a type of supplementary language learning materials.
We must consider their such learning motivations and needs when developing, selecting and
implementing MELR. In specific, governments should consider integrating sufficient training
into the school curriculum to help learners better use technologies. Universities and language
teachers in the future are responsible for playing a bigger role in helping learners discover and
maximise credible MELR (Johnson et al., 2016). As many teachers still have difficulties in
successfully taking advantage of MELR (Lin & Lin, 2019), they should undertake teacher
training in order to deliver more interactive, personalised, collaborative and effectiveness
MELR tasks. Besides, as Stockwell (2008) underlined, despite learner’s familiarity with using
mobile devices, they may still not know how to use them in language learning. Thus, they may
need technical, logistical, and pedagogical support to understand how to use the MELR for
different language learning purposes (Johnson et al., 2016) to develop their digital literacy, i.e.,
to improve their ability to find, evaluate, produce and communicate on MELR.
Transferability and generalisability represent the study’s main limitations. Although we have
tried to address the main research question, we only gained feedback on MELR use from 95
Chinese postgraduate EFL learners via a questionnaire, and only eight students attended the
interview. Thus, it is difficult to generalise the findings to a larger population. Due to the space
limitations, it may be not applicable to showcase more data in this paper. For future research,
more groups of learners should be targeted, and other contexts should be considered. Statistical
analyses could be used to compare possible between-group differences. Guided by the new
theoretical model, new research could focus specifically on Chinese postgraduate EFL learner’s
perceptions and attitudes of MELR, in order to comprehensively understand this group of
learners’ non-normal self-directed language learning.
We would like to thank the anonymous journal reviewers for their insightful and constructive
comments on this paper. Special thanks to Lindsay Duffy for her support.
Notes on contributors
Danyang Zhang is a PhD candidate at the University of Cambridge. Her research interests
include second language acquisition and technology-enhanced language learning. Danyang has
published her work in Applied Linguistics and presented her project in many international
conferences including BERA Annual Conference 2018, CALL 2019 and EUROCALL 2018,
2019. Danyang currently serves as a journal reviewer of Virtual Reality (SCI) and Interactive
Learning Environments (SSCI). She is the winner of the BJET Best EdTech Paper Award and
the doctoral scholarship recipient of GLoCALL 2019 and mLearn 2019.
Pascual Pérez-Paredes is a lecturer at the Faculty of Education, University of Cambridge. His
research interests include CALL, learner language variation, corpora in language education and
corpus-assisted discourse analysis. He is currently an editorial board member
of ReCALL and Register Studies. Pascual has published in international peer-reviewed journals
such as ReCALL, CALL, Language, Learning & Technology, System, Journal of
Pragmatics and English for Specific Purposes. For more
Danyang Zhang: http://orcid.org/0000-0003-2514-9488
Pascual Pérez-Paredes: https://orcid.org/0000-0002-2796-338X
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