Smartphones-Smart Students: A Review of the Literature
Han Friedel
Texas State University-San Marcos
USA
Hans@txstate.edu
Beth Bos
Texas State University-San Marcos
USA
bb33@txstate.edu
Kathryn S. Lee
Texas State University-San Marcos
USA
kl10@txstate.edu
Shaunna Smith
Texas State University-San Marcos
shaunna_smith@txstate.edu
Abstract: Smartphones have now become commonplace with middle and high school students.
Whereas many classroom management policies prohibit mobile phone use and text messaging in
the classroom, a growing body of research has found that mobile phones and short message service
(SMS) texting can positively contribute to student learning by facilitating synchronous
collaborative learning provide an infrastructure for the delivery of interactive content, and assess
student learning and participation. This mobile infrastructure can be used inside and outside of
classrooms. Researchers have recognized the potential for these devices to foster collaboration and
extend learning opportunities by allowing anywhere-anytime learning. This review of the literature
examines and summarizes the current body of research on how smartphones have been used to
raise student achievement – particularly in math and science.
Introduction
A veritable consensus of educators, employers, policy makers, professional organizations, and researchers
expect that today’s K-12 students know how to effectively use internet and computer technologies (ISTE, 2012,
Swain & Pearson, 2002a, 2002b). Some have advocated reducing the achievement gap by eliminating the ‘digital
divide’ between low and high socioeconomic status schools (Swain & Pearson, 2002a, 2002b). Inequalities in
internet access based upon age, income, urban/rural location and gender have been identified – with some evidence
especially pointing to a gender gap (Judi, Amin, Zin, & Latih, 2011; Bimber, 2000). Research has found benefits
associated 1:1 computing ratios in schools (Looi et al., 2011; Garthwait & Weller, 2005; Dunleavy, Dexter, &
Heinecke, 2007). While recent evidence demonstrates that improvements in student-computer ratios have been made
in American public schools - with some even questioning the relevance of their still being a ‘digital divide’ – other
factors may be more important than merely achieving ubiquitous computing ratios (Larkin, 2011). As of late 2009,
there was an overall average ratio of 3.1 students in the U.S. per instructional computer, and though the ‘digital
divide’ may be declining, inequalities in computer usage still existed between low- and high- socioeconomic class
schools – with poorer students less likely to conduct online research or produce a product (Mims, 2012; National
Center for Education Statistics, 2010). Furthermore, ubiquitous computing is by no means a panacea for student
achievement, as teachers sometimes struggled to incorporate these devices into their pedagogical and management
practices, and technology failures can impact learning (Garthwait & Weller, 2005; Dunleavy, Dexter, & Heinecke,
2007). Likewise, ubiquitous computing does not necessarily equal rich technological experiences.
“The eventual form of personal computing that will become most available to students is controversial.
Today, one can find educators advocating everything from mobile phones and notebook computers to
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Tablet PCs and personal digital assistants (PDAs). In addition to these general-purpose computing devices,
many researchers advocate specialized designed-for-learning devices” (Chan et al., 2006, p. 5).
Recent developments in mobile devices have promised to make the goal of ubiquitous computing a reality
(Garthwait & Weller, 2005; Zucker, 2004; Van ‘T Hooft & Swan, 2004; Swain & Pearson, 2002a, 2002b). Personal
computing, interactive communication, and accessing the internet, once the domain of notebook computers, palm
pilots, and PDA’s, is now being overtaken by smartphones and tablets (Greifner, 2007; Hirsch, 2007; Bomar, 2006;
Hastings, 2005). Certainly, personal computing, communication, and internet access is becoming more mobile. This
anytime-anywhere access can go beyond mere mobile browsing, SMS, and wireless communication, as a number of
current smartphones on the market operate the Microsoft Windows 7 Operating System (Microsoft, 2012). There are
social justice implications as students without high speed internet and home computing resources could increase
digital literacy without needing to access expensive personal computers.
Mobile Devices Overtaking Personal Computers
Recently, those interested in ubiquitous computing have become increasingly interested in the impact of
handheld mobile devices such as smartphones, iPods, and tablets on student learning. Smartphones have now
become commonplace with middle and high school students. Recent results from an extensive survey of 5,600 U.S.
high school students found that 34% owned an iPhone, an all-time high doubling the previous year’s percentage.
Furthermore, 40% of those surveyed indicated intent to purchase an iPhone within the next six months (ElmerDeWitt, 2012). Perhaps nothing better illustrates the mobile trend and increasing ubiquity of these progressively
powerful devices - than the “significant milestone” that global smartphones sales overtook global sales of total
personal computers across all client categories (netbooks, notebooks, pads, and desktops) in 2011 by a wide margin
– 487.7 million to 414.6 million units (Canalys, 2012). Global smartphone sales increased 62.7% from 2010 to 2011,
compared with a more tepid global increase in computer sales of 14.8% (all categories) during the same interval.
There were a staggering 4.6 billion mobile cellular subscriptions in effect globally by the end of 2009 (International
Telecommunication Union, 2010). Perhaps there is a growing disconnect between today’s tech savvy students and
their school’s prevailing assumptions, practices, and pedagogies regarding technology in the classroom (Levin &
Arafeh, 2002; Prenksy, 2001).
While there is perhaps a mismatch between classroom management policies and the tremendous potential
of these devices, a growing body of research has found that mobile phones and short message service (SMS) texting
can positively impact student learning by facilitating synchronous collaborative learning, provide an infrastructure
for the delivery of instructional content, and a means to assess student learning and participation (Friedel, 2011;
Hirsch, 2007). This mobile infrastructure has been used to positively impact student learning inside and outside of
classrooms (Lin, Shao, Wong, Li, & Niramitranon, 2011). Researchers have recognized the potential for these
devices to foster collaboration and extend learning opportunities by allowing “learning everywhere; when walking,
in the street, on the bus, in the school, or even on the subway” (Sánchez & Olivares, 2011, p. 1943). Some
researchers have even suggested that mobile handheld devices may better support student learning than traditional
desktop computers because of wireless connectivity, portability, and comparative low cost (White, 2006). Consistent
with these findings, researchers have pointed to the value of further investigating the incorporation of mobile phones
and their capabilities in technology-enhanced education (Markett, Sánchez, Weber, & Tangney, 2006). The ability to
take and send pictures has implications as well: “Due mainly to advances in cognitive science, philosophers today
increasingly recognize that we do indeed have the capacity of thinking directly with images, without verbal
mediation” (Nyíri, 2002, p. 3).
From E-learning to M-learning
Students, but not necessarily schools, are making the transition from e-learning to new m-learning literacies
(Georgiev, Georgieva, Smrikarov, 2004). E-learning can be broadly defined as content designed for access through
electronic communication, such as the Internet, intranets, synchronous and asynchronous modules (Crescente & Lee,
2011). M-learning extends the notion of e-learning further by adapting its content to handheld devices, and can
therefore be broadly defined as learning with mobile devices anywhere and anytime (Crescente & Lee, 2011). This
ability to assimilate learning anywhere and at any time means learners are no longer confined by static resources like
a desktop computer (Crescente & Lee, 2011; Mellow, 2010). It has even been suggested that notebook computers
are not anywhere, anytime machines and should therefore be excluded as true m-learning devices (Crescente & Lee,
2011). M-learning offers benefits over traditional and e-learning in that information is accessible anywhere, devices
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are highly portable, knowledge continuously updated, collaborative instantaneous, participation synchronous, and
literacy (especially technological) improved (Ozdamli, 2012).
The capability of mobile devices to download and host a virtually infinite number of specialized, tiny
software packages known as ‘apps’ lends an inherent flexibility in these devices as learner-centered tools – with
apps functionality can go far beyond communication and photography. Apps are small, specialized, and
downloadable programs for mobile devices that function much the way software programs do on traditional personal
computers (Dictionary.com, 2012). There are native, web-based, and hybrid apps. Native mobile apps use the native
programming language for their platform, such as Objective-C for iPhone or iPad or Java for Android (Xcube Labs,
2012). Native apps are faster, interface with users better, and have access to all device features. On the down side,
they can be used only on a specific platform, thereby restricting their scope. Web apps are website built using
programming languages such as HTML5, resembles other applications, and can be accessed through mobile
browsers (Xcube Labs, 2012). Though web apps can be used across all platforms and devices, they are not accepted
in the native app stores - limiting their distribution. Also, web apps cannot access or use the native application
programming interfaces (APIs) or some device specific hardware features. A middle ground is achieved with hybrid
aps, which are built using web technology and then wrapped in platform-specific shells. These not only makes them
look like native apps and eligible to enter app stores, but allows developers to build in limited native functionalities
including access to some native APIs and use of certain device-specific hardware features (Xcube Labs, 2012). The
inherent flexibility in being able to download a plethora of native, web, and hybrid apps underscores the tremendous
potential mobile devices have to transform education – especially science, technology, engineering, and math
(STEM) education (Banister, 2010). Just recently, an article appeared online entitled “5 New Apps to Spur STEM
Learning” (Noonoo, 2012).
Positive Impacts of Mobile Devices on Student Learning
Mobile devices have been used effectively within classroom environments to augment traditional student
learning and instruction. Ktoridou and Eteokleous (2005) identified device integration as a potentially both a
supportive tool and as an instructional tool. Mobile devices support communication between learners, teachers,
provides file sharing, discussion, information search, and other features. Also mobile tools can use as an
instructional tool. For example students execute their learning tasks on mobile devices. Instructors can give students
e-books, content, and other learning materials (Ozdamli, 2012). Educational researchers have incorporated these
devices into the framework of otherwise traditional classes to teach lessons, deliver course materials, scaffold
learning, and assess student knowledge, skills, and learning (Ozdamli, 2012; Chang, Chen, Hsu, 2011; Thornton &
Houser, 2005; Facer et al. 2003). These researchers have conducted experiments that demonstrated the effectiveness
of sending short vocabulary lessons to the smartphones of Japanese English as a foreign Language (EFL) college
students - compared with control group peers who received the same lessons via traditional or online means, to teach
elementary school children about animal survival within the context of an environment, to each middle school
students about the environment itself, to improve spatial reasoning and learn geometric concepts through a mobile
game, and to teach 3rd graders general science lessons (Facer et al. 2003; Thornton & Houser, 2005; Looi et al.,
2010; Chang, Chen, & Hsu, 2011). Mobile devices and their capabilities are particularly well suited for science
instruction (Roschelle, Penuel, Yarnall, Shechtman, & Tatarw, 2005).
Important, the educational use of handheld digital devices has direct implications supporting constructivist
science classrooms by leading to higher participation levels – particularly in inquiry-, problem-based, and
collaborative environments (Lin et al., 2011; Markett et al., 2006; White, 2005; Davis, 2003). These higherparticipation levels are facilitated through networked mobile devices in a number of ways. First, they raise increase
participation equity by allowing shy students to be publicly anonymous while remaining privately accountable for
their participation within a classroom (Davis, 2003). Second, they make synchronous parallel participation possible
within a whole-class or group environment (White, 2006; Davis, 2003). The ability for shy students to remain
publicly anonymous while privately accountable within the classroom increases equity in participation and allows
all students the ability to participate in a whole-class setting equally (Davis, 2003). Finally, their small size and
portability enables students to interact with each other and their teachers, access information, and upload data from
virtually any authentic setting (Sánchez & Olivares, 2011; Looi et al., 2010). This anywhere/anytime access
provides for technology-mediated learning from within- and without- of class settings (Looi et al., 2010).
M-learning requires an Applied Pedagogy for STEM Classrooms
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Despite m-learning’s compatibility with constructivist learning theories, including obvious inquiry-based,
problem-based, and cooperative implications, sophisticated 21st century mobile infrastructure warrants an equally
sophisticated pedagogy - especially one supporting their use in- and out of science, technology, engineering, and
math (STEM) classrooms. A mobile pedagogy for how to best use these devices in and out of STEM classes is in its
very nascent stages (Muyinda, 2007).
“Situation-dependent knowledge, the knowledge at which m-learning aims, by its nature transcends
disciplines; its organizing principles arise from practical tasks; its contents are multisensorial; its elements
are linked to each other not just by texts, but also by diagrams, pictures, and maps. …science today is ready
to meet the needs of m-learning” (Nyíri, 2002, p. 5).
Still, the foundations for an m-learning pedagogy are being postulated. Mayinda (2007) citing Sharples,
Taylor, and Vavoula (2005) identified as pre-requisites for the formulation of an m-learning theory that one must
distinguish between what is unique about m-learning compared with other types of learning; determine and embrace
the amount of learning that occurs outside of the classroom under the auspices of m-learning; consider contemporary
theories such as learner centeredness, knowledge centeredness, assessment centeredness, and community
centeredness; and account for the ubiquity of personal and shared technology (Mayinda, 2007; Sharples, Taylor, &
Vavoula, 2005). Similarly, Koole (2005) developed a model for the Rational Analysis of Mobile Education
(FRAME) to assess the effectiveness of mobile devices for distance learning based upon constructivist notions that
learning occurs through cognition and social interaction (Crescente & Lee, 2011; Koole, 2005). FRAME was
illustrated by Venn diagram of three interlocking circles illustrating, (A) device usability, (B) learner aspects, and
(C) social aspects. Device usability pertains to the functionality of the mobile devices, learner aspects refer to the
cognitive skills and prior knowledge of learners, and social aspects emphasizes individual reactions to the shared
environment. Where all factors converge (ABC), mobile learning would become practical (Crescente & Lee, 2011;
Koole, 2005). Still, a generally agreed upon mobile pedagogy is still lacking in the literature – not to mention a body
of research-based, applied m-learning STEM lesson plans for classroom teachers! Nevertheless, Ozdamli (2012)
identified four aspects for at least a pedagogical framework for mobile learning. These were integration of tools,
pedagogical approaches, assessment techniques, and teacher training. Theory-based approaches, such as
constructivism, blended learning, collaborative learning, and active learning have been suggested for the basis of a
new m-learning pedagogy (Ozdamli, 2012). One teacher utilized a studio-based pedagogy with smartphones in a
secondary social studies classroom:
“During the place-based inquiry workshop, students used the built-in features of mobile devices (for
example, audio recording, text messaging, GPS, cameras) and “off the shelf” software to investigate their
city as a designed place. In order to introduce students to this concept and scaffold their initial
investigations, we developed a simulation that invited them to role-play as consultants hired by the city to
locate contested places and issues within the downtown area. As they walked around town in pairs, looking
for, observing and analyzing contested places, the students used mobile devices to conduct interviews, take
photos, access “just-in-time” information, and record notes” (Mathews 2010, p. 89).
One would be hard pressed to walk into an average K-12 classroom in the U.S. and see smartphones out
and in use ‘on’ the desks instead of clandestinely texting ‘under’ them. There is a gap in the literature between
recognizing the benefit potential of m-learning and outlining a clear pedagogy for how K-12 classroom teachers
could incorporate it in their practice. What conversations would an educator or administrator have with students,
administrators, and parents? Would school policy changes be required? Further research is needed on how to help
teachers learn how to effectively use these technologies in assessment-centered learning environment (Garthwait &
Weller, 2005). Such pedagogy would translate accepted theory into best-practices, and would delve deeper into
smartphone’s evolving computing, networking, and communication capabilities. The pieces of the puzzle are falling
into place, as there are already a number of websites and blogs identifying must-have education apps (Fleming,
2012; Freeman, 2012). One thing is certain, these increasingly capable mobile devices and their ability to mediate
anywhere/anytime learning has the power to transform STEM education, pedagogical practice, and notions of
ubiquitous computing in public schools.
More research is needed to (a) develop theory-based, practical pedagogies and polices for the incorporation
of mobile devices and educational apps into K-12 STEM classrooms; to (b) develop one or more STEM apps for
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smartphone devices based the pedagogies they identify; and to (c) fund a pilot study incorporating these pedagogies,
practices, and technologies into their classrooms; and (d) to explore creating new collaborative roles for students and
teachers within the anytime-anywhere mobile environment. The overarching goal of the symposium and pilot study
being to bridge the wide gap between the literature, theory, and reality in bringing smartphones into the open in
public school classrooms – and further eliminate the digital divide both in class and at home.
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