1. technology and computing

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English Teaching, Vol. 70, No. 1, Spring 2015
DOI: 10.15858/engtea.70.1.201503.3
Learner Receptiveness Towards Mobile Technology in a
College English Program: The Smart Decision?
Barry Lawrence
(Duksung Women’s University)
Lawrence, Barry. (2015). Learner receptiveness towards mobile technology in a
college English program: The smart decision? English Teaching, 70(1), 3-28.
This study examines learner receptiveness towards using smartphones to enhance EFL
learning at a Korean university in various manners and contexts, exploring predictors
of learner attitude towards mobile devices. A survey of 159 L2 learners was conducted
within a college English program. Results indicated that nearly half of the participants
demonstrated positivity towards integration, while others were ambivalent, with only a
small proportion actively against integration. In the classroom, attitude was most
favorable towards using smartphones as mini-computers with Wi-Fi capabilities to
obtain information in collaborative projects. Outside class, interaction with classmates
and teachers via email, voicemail, and video clip was favored. Multiple regression
analysis indicated that belief in the language learning potential of smartphones was a
significant predictor of attitude across usage contexts, as was inherent device
motivation. Motivation to develop L2 digital literacy was a significant predictor outside
the classroom. Further, learners most receptive to smartphones were consistently so
inside and outside the classroom.
Key Words: MALL, mobile learning, m-learning, L2 learning motivation, digital
literacy, CALL, smartphone, attitude, smartphone, receptiveness
1. INTRODUCTION
Interest in Mobile Assisted Language Learning (MALL) has increased among educators
and researchers (Todd & Tepsuriwong, 2008; Ushioda, 2013; van de Bogart, 2011) driven
by reduced costs, improved capabilities, and increasing ownership (Stockwell, 2013).
Certain distinguishing features of mobile learning, such as autonomy, choice,
personalization, and portability offer great potential (Sharples, 2006). One mobile device
currently of particular relevance in Korea is the smartphone, which is in essence a portable
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mini-computer with Wi-Fi. Smartphone penetration among 18-24 year olds has reached
97.7% (Google, 2013), and many universities now recommend mobile technology in
learning (Park, Nam, & Cha, 2012). Korea also possesses the world’s fourth highest
wireless broadband penetration (OECD, 2014). Prensky famously coined the phrase
‘digital natives,’ suggesting modern cohorts are native speakers “of the digital language of
computers, video games and the Internet” (2001, p. 1). While perhaps an
overgeneralization (Bennett, Maton, & Kervin, 2008), Korea’s high smartphone ownership
rates alongside well-developed, supportive infrastructure suggests comfort with digital
mediums. Nevertheless, attempts to effectively enhance language learning through mobile
technology must consider the wishes of those driving the interest in this technology.
So what motivates learners to engage with technology in their language learning? One
factor of key interest is the learner’s motivation to learn the language itself (Stockwell,
2013). Learner motivation, a complex and abstract construct, was defined by Dörnyei and
Otto (1998) as “ the dynamically changing cumulative arousal in a person that initiates,
directs, coordinates and amplifies, terminates and evaluates the cognitive and motor
processes whereby initial wishes and desires are selected, prioritised, operationalized and
(successfully or unsuccessfully) acted out” (p. 65). The growing relevance of equating L2
motivation with technology use is exemplified by the influential model of motivation, the
L2 Motivational Self System, which accommodates advances in educational technology,
such as Computer Assisted Language Learning (CALL) (Dörnyei, 2009). Additionally, T.
Y. Kim (2012) demonstrated this model to be the best available measure of L2 learning
motivation in a Korean context. Another key motivation-related issue is the question of
why a learner chooses to engage with a given technology. To this end, Stockwell (2013)
proposes two somewhat dichotomous points of departure in engaging with new
technology: a belief that said technology will facilitate language learning, and an inherent
desire to engage with technology, leading indirectly to language learning required to
support this engagement. Ultimately, however, motivation is still not considered a key area
in MALL research (Ushioda, 2013), and these dichotomous points of departure are yet to
be empirically queried in MALL.
Learners often report receptiveness towards mobile learning (m-learning) (Pettit &
Kukulska-Hulme, 2007) and MALL (Khrisat & Mahmoud, 2013; van de Bogart, 2011).
However, this requires further study in a Korean tertiary EFL context. There is a
significant population of learners enrolled in compulsory English programs who may be
less receptive to mobile technology in language learning because of a qualitatively and
quantitatively different motivational profile than participants reported in prior findings.
Often studies of technology acceptance behavior that report high learner receptiveness to
L2 learning technology involve samples majoring in either English language learning or
technology (Kim, Altmann, & Ilon, 2012; McMahon & Pospisil, 2005; Pettit & Kukulska-
Learner Receptiveness Towards Mobile Technology in a College English Program
5
Hulme, 2007; van de Bogart, 2011). However, many learners in college English programs
have no overt interest in either language learning or technology. Theories of L2 motivation
would argue that learning undertaken through choice—driven by internal motivating
factors—leads to higher levels of more sustained engagement than learning undertaken for
external factors (Ushioda, 2013). This argument is key to Self-Determination Theory
(SDT) (Deci & Ryan, 2002), an influential theory of motivation considered successful in
describing L2 learning (Noels, 2009; Ushioda, 1996). It can logically be assumed that the
high degree of receptiveness to MALL observed to date in studies is at least partially
supported by intrinsic motivation. Receptiveness towards smartphone integration in EFL
classes among learners enrolled in mandatory college English courses, characterized by a
greater degree of extrinsic L2 learning motivation and without any clear technological
disposition, may be lower, however. Numerous studies show that intrinsic motivation is
more important than extrinsic motivation when learning English in the Korean context (Pae,
2007; Yang, 2009, 2011), and Park et al. (2012) report a learner’s major to be a predictor
of attitude towards mobile technology. In short, it appears that receptiveness to
smartphones on college English courses is yet to be fully understood and requires further
investigation.
A related issue in need of clarification is whether smartphone technology should be
considered a core component of EFL syllabi or a matter of personal choice. One stance is
that usage may be best governed by individual choice and thus intrinsic motivation
(Ushioda, 2013), given that the strengths of MALL include autonomy, choice,
personalization, and flexibility (Sharples, Taylor, & Vavoula, 2005). In support of this
stance, an issue raised recently is that of the protection of private space. Reports suggest
some learners see smartphone use as most relevant in domains not typically associated
with learning, such as while commuting, thus resisting their implementation in learning
(Jung, 2012; Stockwell, 2008). In contrast with these findings, other studies report
favorable results when mobile technology is used in the classroom and under close
supervision (Appel & Mullen, 2002). Despite these contradictory findings, direct
comparison receptiveness towards usage of smartphones inside and outside of the class has
not yet been made.
Receptiveness to smartphone technology in language learning contexts is not yet fully
understood. To inform educators considering the manner and context of integration in
tertiary EFL learning, I explored attitude towards integrating smartphones in L2 learning
among 160 female students at a women’s university in Seoul, Korea (hereafter referred to
as University A) enrolled in a compulsory, for credit, EFL course. Specifically, this paper
aims to investigate receptiveness patterns inside versus outside of the classroom, potential
sampling bias in prior studies, degree of receptiveness toward integration, preferred
contexts of use, and factors predictive of attitude towards smartphones.
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2. BACKGROUND AND LITERATURE REVIEW
Studies describing usage of mobile technology among learning generally, and
specifically among language learners, appear somewhat limited in Korea. In one study,
Jung (2012) surveyed learners on perceptions and current usage of the smartphone as a
learning tool in Korea. This study queried 79 college learners majoring in English language
and literature. Adopting a mixed methods design, data collection consisted of a
questionnaire and a fixed-question interview. Results showed that online dictionaries and
free vocabulary learning applications were particularly popular. There may also be a
sampling bias inherent in the design, as it could be argued that a sample of English
language and literature majors may have presented with greater intrinsic L2 language
learning motivation than subjects in the current study, who study English through necessity
rather than choice. Furthermore, the research design through lack of inferential analysis
limits external reliability and thus generalization.
2.1. Smartphones and Learner Preferences
Understanding learner preferences is vital from a motivational perspective. Though
mobile technology will undoubtedly have an increasing role, it will likely vary greatly in
manner and context of usage (Sharples, 2006) To that end, van de Bogart (2011) surveyed
200 freshmen EFL learners of English in Thailand on receptiveness and preferences
concerning the integration of smartphones. This study adopted a mixed design
encompassing descriptive, quantitative analysis and qualitative, open-form, written
responses. Results indicated that learners were in favor of incorporating mobile technology
(137 in favor, 52 against, 11 gave no response). Open-form data capturing preferred
methods of future integration was factored into four prominent functional categories:
communicating with teachers via video conferencing, email, voice clips, or video call;
using software programs that would make learning English easier; learning from home by
downloading e-learning lessons; and searching for information more effectively by using
the smartphone like a computer with Wi-Fi. Findings seem consistent with themes
prominent in MALL: interaction, autonomy, flexibility, and portability. One advantage of
this study was the mixed design adopted, which allowed open-form responses rather than
imposing limited categories. This yielded detailed data across a wider range of potential
functions while maintaining reasonable sample size. However, one improvement would be
to specify the rank order and relative popularity between the broad category responses, as
these factors were not made clear. Additionally, analysis stops short of the inferential
analysis that would support educators wishing to generalize across differing tertiary
contexts and beyond. Given the plethora of variables impacting any educational context,
Learner Receptiveness Towards Mobile Technology in a College English Program
7
pedagogical findings require validation across educational contexts (Ur, 1996). It would be
of benefit to assess receptiveness to the above four functional categories among Korean
tertiary learners.
2.2. Predicting Attitude Towards Smartphones
Of particular interest in this study is the issue of which factors influence learner
motivation to engage with language learning technology. Recent publications (Stockwell,
2013; Ushioda, 2013) cite two broad entry points. First, a motivated language learner may
explore and then adopt technology based on belief that it better facilitates language
learning. This notion is hereafter described as L2 learning utility. Conversely, others are
motivated by innate interest in technology itself, potentially leading indirectly to an interest
in language learning—for example, through desire to interact with users from other
cultures using social media websites. This inherent device motivation is applicable to
smartphones, which often provide learners with relaxation, interaction, and enjoyment
(Pettit & Kukulska-Hulme, 2007). Inherent Device motivation alone may not support
sustained, highly engaged learning in a tech-savvy population like Korea, however.
Stockwell (2013) argues that new technology would need to incite great excitement to
surpass popular devices. Consequently, the L2 learning utility of a given technology
appears a more durable and effective motivator for L2 learning.
Studies that empirically validate and investigate these dichotomous points of departure
in technology acceptance behavior among second language learners are lacking. Generally,
studies indicate a high level of initial interest among learners when introducing mobile
technology. McMahon and Pospisil (2005) investigated 18 undergraduate digital media
majors on their receptiveness to wireless laptops, collecting data through fortnightly
weblogs, surveys, and interviews. Findings indicated learners were receptive to and in
favor of mobile devices, with immediacy, interconnectedness, and multitasking seen as key
strengths, and 66.7% of participants strongly agreeing that the devices assisted in learning.
This is analogous with L2 learning utility as a predictor of receptiveness. Furthermore, it is
reasonable to theorize that device motivation may also have contributed to the generally
positive findings, particularly among learners with a leaning towards technology, such as
the digital media students surveyed. Given the small sample size, use of a different mobile
device, limitations presented by descriptive analysis, and focus on non-language related
learning, caution must be applied in interpreting these findings as they relate to the current
study. A somewhat analogous account of device motivation is made by Sharples (2006), in
which a focus group at Kaleidoscope 2006, an international conference on mobile learning,
posited numerous factors underlying implicit motivation to use a mobile device as a
language learning aid: control over goals, ownership, fun, communication, learning-in-
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context, and continuity between contexts. These constructs remain to be validated in
empirical studies, however; thus, there is need for further investigation, testing, and
validation of both L2 learning utility and device motivation as predictors of MALL.
Park et al. (2012) investigated factors underlying intention to use mobile learning in 300
subjects across a range of majors in an e-learning environment at a Korean university.
Adopting a general structural model, survey results showed attitude was the most
important predictor of technology acceptance behavior, followed by a student’s major.
Furthermore, major was a significant predictor of attitude, with Park et al. (p. 603) stating
“major relevance may be considered an intrinsic motivational factor to affect attitude and
perceived usefulness,” and that “students with a major related to mobile devices such as
computer science and information management systems have a greater desire to use more
mobile devices and adopt m-learning” (p. 596). These findings support the present study’s
assertion that learners may be less receptive to mobile technology in contexts where they
are neither language nor technology oriented. However, while Park et al.’s study identified
major as a motivator, it did not specify which majors were most receptive. An additional
issue is that generalizing the results to the educational context in the current study is
questionable. Park et al. focused on m-learning, rather than MALL, and it is specific to an
e-learning environment. Follow-up study specific to language learning in a ‘bricks and
mortar’ classroom environment is required.
Jung’s (2011) study of Korean learners of English in an e-learning context reported
results supportive of usage characterized by choice and flexibility. Findings showed that
participants placed great stock in the freedom to use technology to interact in manners both
planned and unsynchronized, thus supporting the importance of immediacy and flexibility.
This suggests that the strengths of the smartphone may lie in usage outside of the class,
under personal volition. On the other hand, implementing smartphones during in-class
activities is more consistent with integrating usage of smartphone technology as a core
syllabus requirement through, for instance, the greater support and supervision available.
This context of use also garners empirical support. Appel and Mullen (2002) monitored
student usage of the Electronic Tandem Resources (ETR) website, a tandem language
exchange environment, over a period of three years across learners of English, Spanish,
German, and Catalan. Data was collected on 246 learners through in-class surveys, face to
face interviews, and email questionnaires alongside task portfolios. In doing so, the authors
compared usage in a class setting as part of a structured course with usage between
individual learners independent of course. Findings indicated that learner motivation
decreased over time outside of a structured course. Close guidance was required to support
goal setting and generation of new content. Appel and Mullen conclude that use of
language technology is recommended in a closely supervised and supportive framework in
a classroom setting to maintain motivation. The comparison of contexts inside and outside
Learner Receptiveness Towards Mobile Technology in a College English Program
9
the classroom is a useful distinction relevant to the perspective of the current study, given
the portability of smartphones. On the other hand, the ETR is narrower in scope than the
smartphone considered as a whole, and results must be evaluated with care. In short,
empirical findings seem to support usage in class in a manner consistent with a syllabus.
They also support usage outside class in ways that align with personal autonomy and
choice. However, a direct comparison of learner receptiveness between these two usage
contexts is yet to be made with smartphones.
Another factor that may weigh on receptiveness to smartphone usage in second language
learning is digital literacy—the ability to use online resources, navigate the internet, and
engage in computer-mediated communication using digital media (Meurant, 2008).
Alongside recent advances in digital technology, this construct is garnering increasing
attention (Jones & Hafner, 2012). Concurrently, digital media is providing an increasingly
pertinent context for L2 learning (Thorne & Black, 2007). Meurant (2009) attributes this to
three interrelated factors: advances in technology, growth of English as a global language,
and the increasingly greater proportion of non-native speakers using English as a lingua
franca.
From a motivational perspective, L2 digital literacy represents a potential motivational
tool in second language learning. Ushioda (2011) suggests cyberspace represents a “highly
interactive world of the current net generation that we need to connect with and tap into as
a motivational resource for language learning and language use” (p. 207). Put another way,
learner interest in the digital world may support L2 language learning motivation. Similarly,
can learner interest in digital literacy support receptiveness to smartphone technology?
After all, many tertiary environments cannot provide access to adequate conventional
computer mediated learning. If, as Stockwell (2013) suggests, belief in a device’s ability to
facilitate L2 language learning does lead to highly engaged and sustained language
learning, then perhaps belief in a devices’ ability to support L2 digital literacy could lead to
improvements in L2 digital literacy. This could have implications for L2 digital literacy
education in, for example, classrooms where smartphones are the only form of technology
available to learners. Indeed, smartphones may even hold a particular advantage over
conventional computers in the language classroom. Desktops are typically found in
computer labs, wherein they are arranged in rows, facing the front, in a teacher-focused
layout. The portability and size of mobile technology, conversely, allows learners to
arrange themselves facing each other in groups in a manner more conducive to interaction
and thus is considerably more student focused (Meurant, 2010). Despite undoubted
potential, a search of the literature indicates that the current study may be one of the first to
address learner perceptions of smartphones as a platform for L2 digital literacy in Korean
tertiary EFL education.
This study aims to further understanding of receptiveness towards integrating
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smartphones on a college English program in Korea and aid educators considering
integrating smartphones. Supplementing a predominantly qualitative body of literature
with inferential analysis, findings should increase external reliability, thus supporting
generalizations across tertiary EFL contexts. This study will build on findings in general
learning and e-learning environments by applying a more narrow focus to second language
learning in a physical classroom. More specifically, learner perceptions of optimal use of
smartphones, underlying predictors of receptiveness, and potential sampling bias arising
through prior studies recruiting participants with second language learning or technology
orientations are investigated. The learning utility and device motivation dichotomy is
queried and quantitatively validated, and receptiveness to smartphones inside and outside
the classroom is compared. The following research questions will therefore be addressed:
1. To what extent do language learners exhibit a positive attitude toward integrating
smartphones further into a college English program?
2. How do participants envisage using smartphones to support language learning?
3. Which factors predict attitude towards smartphones as language learning tools?
3. METHODS
3.1. Participants and Course
At University A there are currently 1296 students enrolled in the compulsory freshmen
English course, with 50 of these constituting English Language and Literature majors.
Given the wide range of majors undertaken by freshman at most universities, the majority
of learners are unlikely to be specifically language or technology oriented. The college
English course consisted of three proficiency levels: beginner, intermediate, and upper
intermediate (n = 92, 58, and 10 respectively of this sample) based on performance in the
Korean Scholastic Aptitude Test (KSAT), usually taken the year prior to enrolment at
university. Learners received three hours of lessons weekly, split between a Korean teacher
of English (two hours) and a native English-speaking teacher (one hour).
A total of 159 subjects participated in the survey. All were female students of a similar
age (M = 20.5) at a women’s university in Korea enrolled in a compulsory, for credit
college English course. The majority were Korean (n = 156), with one Uzbekistani, one
North Korean defector, and one Chinese student also participating. With the exception of
the Uzbekistani and Chinese learner, all were native speakers of Korean. Convenience
sampling measures were employed as participants were surveyed as members of intact
classes ranging from 13 to 20 students. Data from a language background questionnaire
Learner Receptiveness Towards Mobile Technology in a College English Program
11
indicated most students had studied English for nine or more years in an EFL context, with
only five having lived in a country where English was the first language. The North
Korean defector had received no EFL instruction prior to September 2013. Only a small
number of participants (n = 10) were English majors or otherwise enrolled in other
English-related courses (n = 8). Participants studied a range of other majors, for example:
digital media (n = 15), statistics (n = 17), textile design (n = 16), fashion design (n = 15),
Chinese (n = 9), English language and literature (n = 10), family and social welfare (n =
12), political science and diplomacy (n = 14), psychology (n = 13), and food and nutrition
(n = 20). Classes in the college English program typically consisted of students of one
major. Importantly, there was no official policy on mobile technology usage in the college
English program, either inside or outside of the class. The unofficial policy adopted by all
the EFL instructors who taught the 159 participants was that in-class usage was permitted
to the extent that it was on-task. Usage of smartphones for off-task behavior was prohibited.
Usage outside of the class was not mediated. In no instances was smartphone technology
considered a core element of the lessons, nor was support or training in usage of mobile
technology provided to either instructors or learners.
3.2. Instrument and Measures
To empirically answer the three research questions posed by the current study, attitude
towards adopting smartphone technology was considered a key outcome measure.
Receptiveness in technology acceptance studies is often operationalized through the
construct of behavioral intention—“the person’s subjective probability that he or she will
perform the behavior in question” (Venkatesh, Morris, Davis, & Davis, 2003, p. 288) a
construct instumental in Ajzen’s (1991) theory of planned behavior. However, this
indicator is contingent on choice to engage in a given behavior—a luxury that may not be
afforded to learners if the manner of implementation frames mobile technology as a core
element of syllabus requirements. Attitude towards a given technology, defined as the
individual’s feelings (positive or negative) towards the use of technologies (Ajzen, 1991)
and not contingent on existence of choice, is adopted as a means to operationalize
receptiveness to adopting smartphones. Thus, a survey was developed to assess attitude
towards integrating smartphone technology using five-point Likert scale items (ranging
from 1 = strongly disagree to 5 = strongly agree), summating individual scale items to
obtain indices. The independent (predictor) variables were: L2 learning motivation (L2M),
inherent device motivation (IDM), L2 learning utility (LU), and L2 digital literacy learning
motivation (DLM). The dependent (criterion) variables were attitude towards smartphones
inside the classroom (ATin) and attitude towards smartphones outside of the classroom
(ATout). Individual scale items were based strictly on prior studies. Initial versions of the
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questionnaire were rigorously piloted, prior to distribution of the final survey, and scale
design followed conventions to reduce reporter bias and maintain validity. Table 1
summarizes the variables used: descriptions, theoretical basis, Cronbach’s alpha internal
consistency reliability coefficients, number of items per index, and examples. The mean
Cronbach’s alpha coefficient for the survey was .76, which, considering the brevity of
scales and breadth of constructs, is adequate for group-based comparison (Nunnally &
Bernstein, 1994).
TABLE 1
Independent and Dependant Variables
Variable
Description
L2 motivation (L2M)
This variable is a measure of learners’ general motivation to learn
English. Scale items were pre-validated in an east Asian context
(Taguchi, Magid, & Papi, 2009): e.g. “I am working hard at learning
English” (4 items, α = .79).
Inherent device
This is a broad category measure of the implicit draw of smartphone
motivation (IDM)
technology (Stockwell, 2013; Ushioda, 2013). Scale items were adapted
from Sharples et al. (2006): e.g. “learning with my smartphone is
boring” (4 items, α =.74).
Second language learning This predictor is associated with belief that smartphones enhance
utility (LU)
learning. It is considered a motivator to engage with language learning
technology (Stockwell, 2013; Ushioda, 2013): e.g. “Using smartphones
to learn English can improve my overall English proficiency” (4 items,
α = .77).
L2 digital literacy
This is a broad construct associated with learners’ motivation to develop
motivation (DLM)
skills in computer-mediated second language communication (Meurant,
2009). Individual scale items address different sub-skills: e.g. “The
ability to produce and post materials and content written in English
online is an important skill in today’s world” (4 items, α =.70).
Attitude towards
This output measure represents learner attitude towards adopting
smartphones inside the
smartphones inside the class. Scale items are adapted from functional
classroom (ATin)
categories identified by van de Bogart (2011) and Todd and
Tepsuriwong (2008): e.g. “It would be good to access the internet on my
smartphone to find information in group projects in class” (5 items, α = .
78).
Attitude towards
This output measure captures learner attitude to adopting smartphones in
smartphones outside the
English learning outside of the classroom. Individual scale items were
classroom (ATout)
based on functions identified by learners (van de Bogart, 2011): e.g. “It
would be good to communicate with other students and the teacher via
email, voice clips and video calls” (5 items, α = .75).
The questionnaire was presented alongside a language background questionnaire to
participants in October 2013, after six weeks of a 16-week semester. With confidentiality
assured, participants anonymously completed questionnaires outside of class and left them
in an administrative office in the English department for collection. Questionnaire results
were coded and entered into SPSS for statistical analysis.
This quantitative study adopted a correlational design assessing the relationship between
Learner Receptiveness Towards Mobile Technology in a College English Program
13
numerous interrelated research questions. Research questions one and two queried attitude
towards smartphone integration and preferred methods of usage respectively, and were
addressed via frequency-based descriptive analysis. Subsequently, simultaneous multiple
regression was applied to investigate the predictors of attitude towards smartphones in the
classroom and attitude towards smartphones outside of the classroom when inherent device
motivation, L2 learning utility, L2 digital literacy motivation, and L2 learning motivation
by the learners were submitted for analysis to find the most appropriate regression models.
4. RESULTS AND DISCUSSION
4.1. Attitude Towards Smartphones in EFL
Table 2 describes participant attitudes toward incorporating smartphones in English
learning. Figures indicate slightly less than half of the participants had a positive attitude
towards using the smartphone to learn English outside of the classroom, with a similar
proportion largely ambivalent. This suggests somewhat lower levels of receptiveness than
those reported by previous studies involving English or technology majors as sample
populations (Jung, 2012; Pettit & Kukulska-Hulme, 2007; van de Bogart, 2011). Further,
figures are consistent with Park et al. (2012), who found major to be a key indicator of
attitude, albeit in a contrasting educational context (m-learning within a wholly e-learning
environment). This supports the argument that sampling bias may be inherent in prior
studies focused on language or techology majors, at least when the debate is framed within
Korean tertiary education, and in relation to college English programs in particular.
TABLE 2
Summary of Attitude Towards Using Smartphones in English Learning
Outside the Classroom
Inside the Classroom
Responses
N
%
N
%
Strongly disagree
1
0.6
6
3.8
Disagree
26
16.3
22
13.8
Neither agree nor disagree
58
36.3
59
36.9
Agree
61
38.1
60
37.5
Strongly agree
14
8.8
13
8.1
A similar pattern emerged concerning in-class learning, with slightly less than half of
participants presenting a positive attitude towards use of mobile technology and a slightly
smaller proportion remaining indifferent. While only a small number of participants were
actively opposed to using smartphones in the course, this once more indicates lower levels
of receptiveness than those found among learners with a language or technology
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orientation in prior studies. This further raises the possibility of a qualitatively and
quantitatively different motivational profile concerning the use of mobile technology to
engage with language learning than prior studies. More generally, these findings highlight
a lack of knowledge concerning receptiveness to smartphones as language learning aids in
college English programs that requires further study.
Interestingly, attitude towards integration was of a relatively uniform level of positivity
both inside and outside class. As the strengths of MALL, and thus smartphones, are
thought to include mobility, autonomy, personalization, and choice, researchers might
expect a preference for usage outside class under individual volition. The results did not
reflect this, however, and attempts to explain these findings require a focus on predictors of
Attitude (see Section 4.4.).
4.2. Usage and Learner Preferences
4.2.1. Outside the classroom
Figure 1 shows student attitudes toward possible smartphone implementations in EFL
outside class. Findings indicated that participant attitudes were generally positive across
the four functional categories provided. Learners demonstrated the highest level of
receptiveness towards communicating with students and teacher using email, voice clip,
and videocalls. This is consistent with Jung (2011) and Lai and Gu (2011) who found
synchronous and asynchronous interaction and relationship building, respectively, the most
salient indicators of sustained use of technology. This highlights the importance of both
immediacy and flexibility in MALL.
FIGURE 1
Student Receptiveness Towards Smartphone Usage Outside the Classroom
Learner Receptiveness Towards Mobile Technology in a College English Program
15
Learners reported only marginally lower receptiveness to the other functional categories.
This is despite participants’ likely possessing access to conventional computer technology
outside class. One possible explanation may be that learners envision language learning
taking place ‘on the go.’ This interpretation is somewhat inconsistent with Stockwell
(2010), in which some learners found environments such as public transport during
commutes to be less than conducive to learning. Rather, it suggests an increasing
acceptance of smartphones as educational devices and/or advances in technology,
supporting more effective usage (Stockwell, 2013).
4.2.2. Inside the classroom
Figure 2 shows student attitudes toward smartphone implementations for English
learning in class. Findings indicated that attitude was positive across three of the four
categories addressed. Accessing the Internet in collaborative projects was the most popular
function inside the classroom by a wide margin, with 94% of respondents being receptive.
The second most popular function, grammar and vocabulary quizzes, garnered only 54%
positivity. One possible reason for this margin is that learners associate web-surfing with
relaxation and recreation, unlike functions such as recording and playing back speech for
analysis, for example, which may seem less enjoyable. This is somewhat consistent with
reports of resistance among learners against invasion of the private space that smartphones
represent (Stockwell, 2008). It is clear that, like all new learning paradigms, the educator
has a role in skilfully demonstrating the potential of such activities to motivate learners in
their language studies.
FIGURE 2
Student Receptiveness Towards Smartphone Usage Inside the Classroom
The positive attitude reported towards using smartphones as mini-computers with Wi-Fi
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to gather information in collaborative projects in class appears specifically relevant in
institutional environments with no other access to computer technology. Results indicate
that learners may view smartphones as a window into the World Wide Web. If this is the
case, not only may smartphone technology provide many motivational possibilities
supportive of sustained usage, but also a potential vehicle for L2 digital literacy (see
section 4.3.).
4.3. Predictors of Attitude Towards Smartphones
Complete data was available for 159 students. Descriptive data is presented in Table 3.
TABLE 3
Measure
L2M
IDM
DLM
LU
ATin
ATout
Descriptive Statistics for Predictors and Output Measures
M
SD
Skew
12.44
2.46
.368
14.22
2.61
-.369
16.12
2.35
-.268
14.21
2.58
-.228
17.64
3.29
-.351
17.45
3.25
-.339
Kurtosis
.492
.465
-.427
-.110
.309
.576
The data was compiled for all variables and checked for outliers, and none were found.
Additionally, the skewness and kurtosis values indicate that normality of data is a
reasonable assumption. Bivariate correlations between the predictor variables are presented
in Table 4.
TABLE 4
Measure
L2M
IDM
DLM
LU
ATin
ATout
Bivariate Correlations for Predictors and Output Measures
L2M
IDM
DLM
LU
.021
.192*
.079
.127
.186*
.238**
.447**
.386**
.451**
.247**
.123
.408**
.427**
.489**
ATin
.491**
* p < .05, ** p < .01
Many of the predictor variables were correlated. However, coefficients here do not
account for the variation caused by other predictors, limiting their interpretative power.
Learner Receptiveness Towards Mobile Technology in a College English Program
17
4.3.1. Outside the classroom
A simultaneous multiple regression analysis was conducted to investigate the extent to
which input measures predicted attitude towards integrating smartphones into English
language learning outside of the classroom. The predictors were: L2 learning motivation,
inherent device motivation, L2 digital literacy learning motivation, L2 learning utility, and
attitude towards smartphones in the classroom. The output criterion was attitude towards
smartphones outside of the classroom. The results are presented in Table 5. Four of the five
predictors account for 46% of the variance in attitude towards smartphones outside of the
classroom, F(9, 149) = 16.13, p < .001, R² = .46. The confidence intervals for these
predictors did not include zero, further confirming that these variables are statistically
significant predictors of attitude towards smartphones outside of the classroom. The effect
size for this analysis (f² = .85) was found to exceed Cohen’s (1988) convention for a large
effect (f² = .35), indicating that that those with higher levels of belief in L2 learning utility,
greater L2 digital literacy motivation, greater degree of inherent device motivation, and a
more positive attitude towards adopting smartphones in class, tended to have a more
positive attitude towards adopting smartphone technology to learn English outside of the
classroom.
TABLE 5
Variable
L2M
IDM
DLM
LU
ATin
Regression Analyses for Variables Predicting ATout
B
SE B
ß
.067
.079
.051
.288
.085
.231**
.283
.086
.204**
.304
.087
.242**
.296
.067
.299**
CI
1.080, .233
.121, .455
.113, .453
.132, .477
.164, .427
*p < .05, ** p < .01
TABLE 6
Bivariate and Partial Correlations of the Predictors With ATout
Correlation Between Each Predictor
Correlation Between Each Predictor and
Predictors
and ATout
ATout Controlling for all Other Predictors
IDM
.51**
.28**
LU
.54**
.28**
DLM
.37**
.26**
L2M
.14
.06
ATin
.53**
.34**
*p < .05, **p < .01
With the exception of L2 learning motivation, all bivariate correlations between
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Barry Lawrence
motivation-related predictors and attitude to integrating smartphones into English language
learning outside class were positive. Table 6 presents indices that illustrate the relative
strength of individual predictors. As shown in Table 6, inherent device motivation, L2
learning utility, L2 digital literacy learning motivation and attitude towards smartphones in
the classroom had significant (p < .001) zero order correlations with attitude towards
smartphones outside of the classroom. Furthermore, only the same four predictors had
significant (p < .01) partial effects in the full model.
4.3.2. Inside the classroom
Subsequently, a simultaneous multiple regression analysis was conducted to investigate
the extent to which input measures predicted attitude to integrating smartphones into
English language learning in class. The predictors were: L2 learning motivation, inherent
device motivation, L2 digital literacy motivation, L2 learning utility, and attitude towards
smartphones outside of the classroom. The output criterion was attitude towards
smartphones in the classroom. The results of the simultaneous regression analysis are
presented in Table 7. The predictors L2 learning utility, inherent device motivation, and
attitude towards the smartphone outside of the class were significant. The three predictor
model was able to account for 37% of the variance in students’ attitudes towards adopting
smartphones in studying English inside the classroom, F(9, 149) = 9.90, p < .001, R² = .37.
The confidence intervals for these predictors did not include zero, further confirming that
these variables are statistically significant predictors of attitude towards smartphones inside
the classroom. The effect size for this analysis (f² = .59) exceeded Cohen’s (1988)
convention for a large effect (f² = 0.35), indicating that that those with higher belief in L2
learning utility, greater degree of inherent device motivation, and a more positive attitude
towards adopting smartphones outside class tended to have more positive attitude towards
smartphone technology to learn English in the classroom.
TABLE 7
Variable
L2M
IDM
DLM
LU
ATout
Regression Analyses for Variables Predicting ATin
B
SE B
ß
.024
.091
.018
.201
.099
.159*
-.155
.101
-.110
.256
.102
.201*
.387
.087
.382**
CI
-.155, .203
.005, .396
-.355, .045
.055, .457
.215, .559
*p < .05, **p < .01
Table 8 presents indices that illustrate the relative strength of individual predictors. All
Learner Receptiveness Towards Mobile Technology in a College English Program
19
bivariate correlations between motivation towards technology-related predictors and ATin
were positive. As shown in the table, L2 learning utility, inherent device motivation, and
attitude towards smartphones outside of the classroom had significant zero order
correlations with attitude towards smartphones in the classroom. Further, only L2 learning
utility (p < .05), inherent device motivation (p < .05), and attitude towards smartphones
outside of the classroom (p < .01) had significant partial effects in the full model.
TABLE 8
IDM
LU
L2M
DLM
ATout
Bivariate and Partial Correlations of the Predictors with ATin
Correlation Between Each
Correlation Between Each
Predictors
Predictor and ATin Controlling
Predictor and ATin
for all Other Predictors
.42*
.16*
.45*
.20*
.06
.02
.13
-.13
.53**
.34**
*p < .05, **p < .01
Simultaneous multiple linear regression analysis sheds light on underlying motivational
factors, accounting for 46% of variance outside the class and 37% inside—both significant
amounts. Interestingly, a prominent predictor of attitude towards smartphones outside of
the classroom was attitude towards usage in the class, and vice versa. In other words, those
receptive to smartphone technology in one domain were also likely to be so in the other.
These findings are not entirely consistent with the notion that smartphones may be better
left to a learner’s own volition. The premise that the strengths of MALL center on personal
choice and autonomy (Ushioda, 2013) is somewhat at odds with the degree of
receptiveness shown to smartphone integration in the classroom, relatively speaking. This
is encouraging for educators, as it implies greater freedom and flexibility in context and
manner of implementation, particularly given the greater degree of supervision and support
available in the classroom.
Results also provided insight into L2 language learning utility and inherent device
motivation as dichotomous starting points for adoption of smartphone technology. Second
language learning utility was a significant predictor both inside and outside class. The
greater effect size observed outside class is, in this case, consistent with key features of
MALL, such as mobility, choice, and autonomy in mobile learning being optimized in
different domains beyond the confines of the class. Similarly, inherent device motivation
significantly predicted attitude towards using smartphones both in the classroom and
outside, and it was again a more prominent predictor outside the classroom. It is likely that
learners imagined usage of smartphones in the classroom to be subject to greater
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Barry Lawrence
supervision, thus reducing perceptions of leisure and recreation associated with inherent
device motivation. However, it is feasible that learners with lower belief in L2 learning
utility could still initially engage with smartphones through inherent device motivation—
ideally long enough to support increased L2 learning utility, L2 learning motivation, or for
more optimal L2 learning to take place. Moreover, that L2 learning utility explains a
greater proportion of variance in receptiveness to using smartphone technology than
inherent device motivation both in and outside of the classroom is encouraging. Remember
that Stockwell (2013) argues that motivation to engage with technology based on L2
learning utility is preferable to that based primarily on inherent device motivation
(Stockwell, 2013) for reasons of higher engagement and greater sustainability. Thus, these
findings indicate learner receptiveness towards smartphone integration among learners in
this college English program is supportive of long-term second language learning.
Second language digital literacy motivation was not a significant predictor of attitude
towards smartphones in the classroom. This may be surprising given that smartphones
represented the only available computer technology required to address L2 digital literacy
learning in the course. However, syllabi did not explicitly focus on L2 digital literacy in the
college English program in question. Accordingly, respondents perhaps did not recognize
the relevance of these skills in the classroom. L2 digital literacy motivation did
significantly predict attitude towards smartphones outside of the classroom, however. This
suggests learners in the college English course may see the smartphone as a potential
platform for supporting L2 digital literacy outside the class, and within the realm of
autonomous choice. This is interesting given reports of both hardware issues with
smartphones, such as small screen size (Chinnery, 2006), and preference for conventional
computer technology (Stockwell, 2010). Again, the smartphone’s portability and mobility
may explain these results. In a city such as Seoul, with long commutes, pragmatic learners
may recognize potential to address L2 digital literacy through smartphones ‘on the go,’
when conventional computer technology is unavailable. There may be increasing
recognition among learners of the importance of this skill-set to complement growing
academic interest.
No significant relationship between motivation to engage with smartphones and L2
learning motivation was detected. Although results indicated participants with higher L2
learning motivation also had more positive attitudes towards smartphones both inside the
class and outside, these correlations were not significant. Contrastingly, L2 learning utility
was a significant predictor of both. Perhaps unsurprisingly, results suggest that desire to
learn English alone does not promote desire to integrate smartphones into English studies.
Rather, findings emphasize belief in the educational potential of smartphones to be key.
This study provides support for this stance in a Korean tertiary context.
Learner Receptiveness Towards Mobile Technology in a College English Program
21
5. CONCLUSION
In Korea, advances in smartphone technology alongside rapidly increasing market
penetration drive current interest in smartphones as language learning aids, creating need
for this study. With the role of motivation in mobile assisted language learning not yet fully
understood, there is a need to investigate learner attitude towards smartphones acceptance
in tertiary EFL education. This need is heightened by under-representation of learners in
mandatory college English programs, who may present with less intrinsic motivation to
engage in EFL learning and associated technology.
Findings show that some learners were somewhat receptive to further integration, with
almost half of those surveyed displaying a positive attitude towards smartphones both
inside and outside the classroom. As the strengths of mobile learning—portability,
mobility, autonomy and choice—are widely considered to be better utilized outside the
classroom, results may indicate pragmatism among learners, something over nothing, as no
other computer technology was available. On the other hand, a sizable proportion of
learners were ambivalent towards use of smartphone technology, with a smaller proportion
against it. This suggests that there may be selection bias inherent in prior studies based on
samples consisting of English and technology-oriented majors, which generally report a
greater degree of receptiveness than the current study. Further, it highlights the need for
greater understanding of receptiveness towards smartphones across a range of educational
contexts prior to implementation. The study identified a number of predictors of a positive
attitude towards use outside of class. The strongest was a positive attitude towards use of
smartphones inside the classroom, and vice-versa, indicating that learners who were
positive about smartphones as effective language learning tools felt so both in and out of
the classroom. Importantly, this study empirically supported the premise that belief in L2
learning utility is a prominent indicator of attitude towards smartphones in MALL.
Another important finding was that, although inherent device motivation significantly
predicted attitude towards smartphone technology in second language learning both inside
and outside the classroom, the effect size was smaller than L2 learning utility in both cases.
This is encouraging as L2 learning utility is argued to support more sustained and highly
engaged language learning. Relatedly, the role of device motivation as a predictor was
smaller inside the classroom than outside. This was possibly due to learner perceptions that
supervised in-class usage ran counter to notions of recreation and relaxation underpinning
device motivation. Interestingly, L2 digital literacy learning motivation was a significant
predictor of attitude towards usage outside the classroom, indicating willingness to engage
in L2 digital literacy-related activities ‘on the go.’ L2 digital literacy learning motivation
did not significantly predict attitude towards usage in class, however, possibly since L2
digital literacy was not a core course requirement, rendering it less relevant under
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Barry Lawrence
supervision. This study also described relative attitude towards usage across various
functions. Participants displayed the greatest degree of receptiveness to communicating
with students and teacher using email, voice clip, and videocalls outside the classroom.
The most popular function inside class was using smartphones as mini-computers with WiFi to gather information in collaborative projects.
6. PRACTICAL APPLICATIONS AND FUTURE DIRECTIONS
Given the increasing spotlight on mobile-assisted language learning and L2 digital
literacy, this study has practical applications for educators considering adopting
smartphones in language courses. Almost half of participants demonstrated a positive
attitude towards smartphones despite most participants presenting with no overt language
or technology orientation, and thus presumably less intrinsic motivation. This may be
somewhat encouraging for educators delivering college English programs in Korea. It hints
at the potential for a positive reception upon appropriate integration. Furthermore, attitude
was uniformly positive inside and outside the classroom. This suggests scope for flexibility
in manner and context of usage in accordance with individual course requirements and
educator beliefs, indicating that smartphones may have a role in language learning as a
core element of the syllabus or under a learner’s own volition. Crucially, L2 learning utility
played a more pivotal role than inherent device motivation in learner receptiveness. This
supports the notion that learner interaction with smartphones can be engaged and sustained,
supporting higher quality language learning. L2 digital literacy learning motivation
predicted attitude towards integration in L2 learning outside the classroom, potentially
suggesting a role for smartphone technology in developing this skill set. Findings indicate
the potential for greater emphasis on L2 digital literacy in tertiary English education in
Korea, perhaps through increased prominence in college English programs or as a standalone course. Future research addressing smartphone use in college English programs
would benefit from more qualitative analysis. Specifically, the addition of one-to-one
interviews during data collection would allow a finer lens to be applied to learner
preferences, further facilitating the decisions of educators considering integration. Overall,
however, findings suggest potential for smartphone integration across various functions
inside and outside the classroom in college English programs, if learners’ wishes are taken
into account.
Learner Receptiveness Towards Mobile Technology in a College English Program
23
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APPENDIX A
Learner Questionnaire
Class _________ (Example “2-12”)
Major______________ (Example “Math”)
I am doing some research about using smartphones to learn English. I would very much appreciate
your help and your opinions. If you agree to participate, please answer the questions honestly. Your
answers and identity will remain confidential. Please leave the completed questionnaires in the
Language Lab.
Please note that questions relating to smartphone use to learn English in this initial survey are quite
general, and cover both the possibility using smartphones in your lessons and for self-study.
Part A: Instructions
Please put a circle in the corresponding box to indicate how much you agree or disagree with each
statement. In the example below, the person indicated that they strongly agree.
Statement
I enjoy watching movies in English
Strongly
Agree
O
Agree Neither Agree Disagree
nor Disagree
Strongly
Disagree
Strongly
Agree
Agree Neither Agree Disagree
nor Disagree
Strongly
Disagree
Strongly
Agree
Agree Neither Agree Disagree
nor Disagree
Strongly
Disagree
Using English Online
Statement
1. Being able to locate and access resources and
content written in English on line is an
important skill in today’s world.
2. The ability to produce and post materials and
content written in English online would be
useful to me.
3. I have no interest in the ability to
communicate internationally via English using
email.
4. Being able to communicate in English with
non-Koreans using
videoconferencing/videocalls is a skill I don’t
care about developing.
Learning English in General
Statement
1. I am working hard at learning English.
2. Compared to my classmates, I think I make
very little effort studying English.
3. I think I am doing my best to learn English.
4. I am prepared to expend a lot of energy in
learning English.
Learner Receptiveness Towards Mobile Technology in a College English Program
27
The Smartphone
Statement
1. Learning with my smartphone is boring.
2. My smartphone makes learning more
convenient.
3. The instant access to information provided
by my smartphone is important in my studying.
4. Having a small, portable mini-computer with
me at all times doesn’t really support my
learning.
5. I am interested in using my smartphone to
help learn English inside the classroom.
Strongly
Agree
English & Smartphones outside of the Classroom
Strongly
Statement
Agree
1. It would be good to communicate with other
students and the teacher via email, voice clips,
and video calls.
2. Downloading e-Learning lessons on my
smartphone to learn English at home would be
useful.
3. Receiving and submit homework via
smartphone is not something I would find
helpful.
4. Accessing the internet at different times and
locations outside of the classroom to find
language information or class materials is
something I would not like to do.
5. I am interested in using my smartphone to
help learn English outside of the classroom.
Agree Neither Agree Disagree
nor Disagree
Strongly
Disagree
Agree Neither Agree Disagree
nor Disagree
Strongly
Disagree
Agree Neither Agree Disagree
nor Disagree
Strongly
Disagree
Smartphones and Learning English
Statement
1. If I use smartphones to learn English, my
vocabulary will not improve.
2. Using a smartphone to studying English can
result in an improvement in my grammar
knowledge.
3. Using smartphone technology, I will be able
to improve my English pronunciation.
4. Using smartphones to learn English can
improve my overall English proficiency.
Strongly
Agree
28
Barry Lawrence
Applicable levels: Tertiary
Barry Lawrence
College of Liberal Arts
Duksung Women’s University
33, Samyang-ro 144-gil, Dobong-gu
Seoul 132-714, Korea
Phone: 02-901-8548
Cell: 010-3299-1978
Email: [email protected]
Received in December 1, 2014
Reviewed in January 15, 2015
Revised version received in February 15, 2015