Malaysian Online Journal of Educational Technology 2018 (Volume 6 - Issue 2 )
The effect of mobile learning applications
on students' academic achievement and
attitudes toward mobile learning
Kadir DEMIR [1], Ercan AKPINAR [2]
http://dx.doi.org/10.17220/mojet.2018.04.004
[1] Dokuz Eylul University, Buca
Faculty of Education, Department
of Computer Education and
Instructional Technology, Izmir,
Turkey, [email protected]
[2] Dokuz Eylul University, Buca
Faculty of Education, Department
of Computer Education and
Instructional Technology, Izmir,
Turkey, ercan.akpinar@deu.edu.tr
ABSTRACT
This study examines the effect of mobile learning applications on undergraduate students'
academic achievement, attitudes toward mobile learning and animation development
levels. Quasi-experimental design was used in the study. Participants of the study were
students of the Buca Faculty of Education at Dokuz Eylul University in Turkey. The
experiment was conducted during the first semester of 2013-2014 academic year. A mobile
learning-based strategy was used in experimental group (n = 15), while the control group
participated in a lecture-based classroom (n = 26). An attitude scale was used to measure
the students’ attitudes toward mobile learning, and achievement test was used to examine
the effect of mobile learning applications on the students’ achievement. In order to
evaluate the animations developed by students, a rubric was used. For exploratory
analysis, interviews were conducted with students. The findings suggest that mobile
learning may promote students' academic achievement. Both groups had significantly high
attitude scores toward mobile learning. Furthermore, the students appreciated mobile
learning as an approach that may significantly increase their motivation. Researchers and
practitioners should take into consideration that mobile learning can create positive impact
on academic achievement and performance and increase the motivation of students.
Keywords:
mobile learning; tablet computer; graphic; animation; academic
achievement; attitude
INTRODUCTION
The number of mobile cellular network subscribers is expected to be seven billion in 2016. Also, the
number of Internet users is known to reach 3.2 billion (ICT Facts and Figures, 2015). Mobile technologies
transform our daily lives in ways such as connectivity, communication and cooperation (McQuiggan,
McQuiggan, Sabourin & Kosturko, 2015). Mobile devices (specifically smartphones and tablet computers)
aim to change the way of learning and teaching methods innovatively (Kuzu, 2014; Middleton, 2015).
However, it is indicated that mobile learning cannot replace with formal education but offers methods to
support learning outside of the classroom and brings advantages for different interactions (Sharples, Taylor
& Vavoula, 2010).
In conjunction with the use of mobile devices in learning and teaching activities, the term “Mobile
learning” has emerged. There are different definitions of mobile learning in the literature (Crompton, 2013).
According the Quinn (2000), mobile learning is e-learning which is performed through mobile devices. The
definition of mobile learning varies over time and affected by emerging technologies. McQuiggan,
McQuiggan, Sabourin and Kosturko (2015) defined mobile learning as instant and optionally accessible,
anywhere and anytime learning, which helps us create our knowledge, satisfy our curiosity, collaborate with
others and enrich our experiences.
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Malaysian Online Journal of Educational Technology 2018 (Volume 6 - Issue 2 )
People in virtual environments and those in real world can connect with each other via mobile learning
(Traxler & Koole, 2014). Moreover, learning communities can be created among people on the move.
Considering these specialities, mobile learning is at the forefront as a supportive element of lifelong learning
and in-service learning. The interaction opportunities of mobile learning provide sustainability of education
outside of the classroom (Sharples, Arnedillo-Sánchez, Milrad, & Vavoula, 2009). In this way, mobile devices
affect the socio-cultural and cognitive aspects of learning (Pachler, 2009).
Studies on mobile learning focus on how learners on the move gain new knowledge, skills and
experiences (Sharples et al., 2009). Rapid development of mobile technologies brings some disadvantages to
researchers and learners as well. Learners devote time to get used to the characteristics of the new device.
Researchers face challenges carrying out longitudinal studies. People, who have mobile devices, desire to use
these devices in mobile learning settings for their personal needs, which poses challenges to researchers on
having control over variables (Pachler, 2009).
While hardware was at the forefront in the past, the design and content of mobile learning are
becoming prominent recently in mobile learning research (Odabasi et al., 2009; Traxler, 2007; Wang, Shen,
Novak, & Pan, 2009; Wu et al., 2012). Mobile learning is not just e-learning which ends up with the adoption
of e-learning objects to mobile devices. Mobile learning objects should be created on the basis of mobile
design principles. Mobile learning contents should be presented in small chunks instead of presenting the
entire material. These small chunks in the form of mobile learning content are called as “nuggets” or “bite-
sized” (Parsons, Ryu & Cranshaw, 2007). Naismith and Corlett (2006) points out the design of mobile learning
as following:
• Create quick and simple interactions,
• Prepare flexible materials that can change according to the needs of learner,
• Design access of device and interaction by considering the different devices and standards,
• Contribute to the learning experience using the characteristics and constraints of mobile
devices,
• Use mobile technologies as a learning facilitator not a tool for only distributes learning
contents,
• Design materials with learner-centered approach.
Mobile devices are widely used in the digital age. Social network sites, which are becoming
indispensable with Web 2.0 technologies, facilitate acceptance of mobile devices by teachers and students.
The educational use of mobile devices in and outside of the classroom helps students develop positive
attitudes towards courses (Özdamar Keskin, 2011). Students' interest and motivation are enhanced by mobile
learning (Ozan, 2013). Moreover, the use of mobile devices in the learning environments encourages
students to participate in learning activities. Therefore, it can be said that mobile devices may become a
necessity for students and educators (Yılmaz and Akpinar, 2011).
One of the advantages of mobile learning is the ability to provide access to learning contents out of
the course time. Mobile learning management systems might be used to provide this. Additionally, mobile
learning contents are produced based on design principles for qualified interactions. Researchers suggest
that the duration of access time should be increased (Çelik, 2012). Moreover, determining and reporting
duration and number of the visit session in the mobile learning system are important (Sayın, 2010; Martin &
Ertzberger, 2013). At the same time, various technical regulations are proposed for effective learning through
mobile learning such as rapid and wireless internet network infrastructure, big screen size and mobile
applications in the native language of students, so that students will not be exposed to extraneous cognitive
load (Anderson, Franklin, Yinger, Sun, & Geist, 2013; Ozan, 2013; Royle, Stager & Traxler, 2014; Sur, 2011).
Being distractive, challenges in use and technical issues are seen as problems that have to be solved in mobile
learning (Gikas & Grant, 2013). There are implications and recommendations for implementation in mobile
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Malaysian Online Journal of Educational Technology 2018 (Volume 6 - Issue 2 )
learning research. There are various researches that mobile learning increased academic achievement (Çelik,
2012; Köse, Koç & Yücesoy, 2013; Oberer & Erkollar, 2013). Ozan (2013) came with a conclusion that mobile
learning is more permanent for learning. In addition, using social networks and mobile technologies positively
affect students’ performance toward courses. Evans (2008) emphasized that mobile learning is more
effective and instructive than books, and more supportive in learning. Mobile learning offers benefits such
as quick access to information for students, diverse ways of learning, contextual learning, control over own
learning, supporting and encouraging learning, increased participation in the course, will to use in the course
and positive meaningful differences of academic achievement, considering the results of the researches.
This research was designed in accordance with the recommendations expressed above. In this
research, bite-sized and interactive course content was created and used. The use of native applications on
mobile devices is provided to support learning. Also, students could personalize mobile devices because the
students kept mobile devices during the research. Introducing mobile learning environments to pre-service
teachers is considered to be crucial. This research is expected to contribute to the empirical and theoretical
researches.
The Research Aim and Scope
The aim of this research is to investigate the effects of mobile learning applications on undergraduate
students' academic achievement, attitudes toward mobile learning and animation development levels. In this
context, the research problem is “Do mobile learning applications affect the academic achievement, attitudes
of undergraduate students towards mobile learning and animation development levels?”. The research
questions are identified below:
Are there any meaningful differences between the academic achievement of the experimental and
control groups?
Are there any meaningful differences between the attitudes toward mobile learning of the
experimental and control groups?
Are there any meaningful differences between the animation development levels of the experimental
and control groups?
What are the students’ views about mobile learning in the experimental group?
Limitations
(1) This research is limited to 41 second-grade pre-service teachers (experiment: 15, control: 26) who
study in Computer Education and Instructional Technology Department in Dokuz Eylul University.
(2) This research is limited to 15 tablet computers.
(3) This research is limited with “Graphic and Animation in Education” course.
(4) In this research, Blackboard learning management system (Blackboard, n.d.) is used.
Research methodology
Participants
The study group of this research consisted of 41 second-grade pre-service teachers who voluntarily
participated in the research and study in Computer Education and Instructional Technology Department in
Dokuz Eylul University, Turkey. 15 tablet computers were given to students in the experimental group for
this research supported by Dokuz Eylul University as a scientific research project (Project Id:
2013.KB.EGT.004). The students were assigned to control and experimental groups using random sampling
(Creswell, 2013), which is ended up with 15 participants in experimental group and 21 participants in control
group.
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The experimental group voluntarily signed “Usage Agreement for Mobile Devices” (Burden, Hopkins,
Male, Martin, & Trala, 2012). This agreement consisted of mobile devices' being kept by the students for 12
weeks and ethical use of these devices.
Both groups’ demographic and mobile awareness information were collected through a
questionnaire. 73% of experiment group and 65% of control group have a smart phone, which shows that
most students were familiar with mobile phones and applications. However, only 20% of experimental group
and 8% of control group have a tablet computer, which may mean that students could face difficulties using
tablet computers. Students stated that they listen to podcasts the least (experiment: 0%, control: 12%) with
their mobile devices; and listen to music (experiment: 100%, control: 96%) and communicate (experiment:
100%, control: 92%) the most with mobile devices. Almost half of the students (experiment: 47%, control:
42%) stated that they carried out e-learning activities via mobile devices. Additionally, 47% of experimental
group and 62% of control group indicated that they want to use mobile learning applications in both
theoretical and practical courses.
Research design
In this study, quasi-experimental design was used as research method (Cohen, Manion & Morrison,
2013). Both groups have recieved 50% theoretical and 50% practical courses by lecturer. Learning contents
(blog, presentation, sample, video, podcast, homework, test, forum) were accessible for both groups through
a learning management system. The dependent variables of research are academic achievement, attitude
toward mobile learning and animation development level. The independent variables of the research are
mobile learning and traditional learning conditions.
Mobile learning group (15 pre-service teachers): This group were taught through mobile learning
approach. Tablet computers were distributed to this group, and learning management system and learning
contents were available on mobile devices.
Traditional learning group (26 pre-service teachers): This group were taught in a traditional learning
environment. Learning management system and learning contents were also available for this group but this
time, on the Internet. The details of research design can be seen Figure 1.
Figure 1. Research design.
Traditional learning
Mobile learning
Before research
Academic Achievement Test
Attitude Scale Toward Mobile Learning
During Research
Attend conventional lectures
Access learning management system
via PC
Access learning management
system via mobile devices
Access course blog
Access learning contents via PC
Access learning contents via
mobile devices
After research
Academic Achievement Test
Attitude Scale Toward Mobile Learning
Animation Development Levels Rubric
Interview
Six months after research
Academic Achievement Test
Attitude Scale Toward Mobile Learning
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Data collection
Academic Achievement Test
The test was developed by researchers in order to measure academic achievement based on the
acquisition through the course. The scope of the subject, objectives and content were created before the
test was developed. 36 questions were prepared based on feedbacks received from the experts of the field.
The table of specification chart was created during the development phase. 150 undergraduate students
took part in the test for item analysis. Statistical analyses were performed with the TAP (Test Analysis
Program) software. 13 items were removed from the test because of low item distinctiveness power. The KR-
20 reliability coefficient of test consisting of 23 items was found 0.83, which is close to 1 and means the test
is reliable (Perry & Nichols, 2014). The distinctiveness index of test items was found very good (0.49) and
item difficulty of test was found average (0.64).
Attitude Scale Towards Mobile Learning
“Attitude Scale Toward Mobile Learning” scale was developed by the researchers in order to measure
attitudes of participants toward mobile learning (Demir & Akpınar, 2016). Data was collected from 78
undergraduate students in order to create pool of draft items. Data collected from students were analysed
and a draft consisting of 57 items was created. Following experts' opinions from several universities,
inappropriate and similar items were excluded from the draft. After revisions, the draft comprised of 52 items
(41 positive, 11 negative). The 5-point Likert-type scale was graded in five categories: totally agree (5), agree
(4), partially agree (3), disagree (2), totally disagree (1).
Kaiser Meyer-Olkin (KMO) and Bartlett sphericity tests were required for factor analysis (Fraenkel &
Wallen, 2006). KMO value found as 0,94, which is considered to be very good and Bartlett test was found
meaningful, which is considered that data is suitable for factor analysis (χ2=8530,19; p<,000). In the light of
this data, it was decided that scale is statistically appropriate for factor analysis (Coolican, 2014). The final
decision was given after the third factor analysis.
The final version of scale consists 45 items. The Cronbach’s alpha internal consistency coefficient of
the scale was found .950, which is accepted as highly reliable. KMO value found as 0,93 and considered to be
very good. Bartlett test was found meaningful (χ2=7820,10; p<,000). The scale has four factors and explains
the %50,34 of the total variance. Internal consistency of factors were high (satisfaction ,942; effect to
learning ,877; motivation ,886; usability ,776).
Interview
The semi-structured interviews were conducted to reveal participants’ views about the process of the
implementation. Five students who are chosen randomly from mobile learning group were interviewed. The
semi-structured interview form, which consists of 11 open-ended questions related with application process,
was used as data collection tool.
Animation Development Level Rubric
All of the students who participated the research were asked to develop animations. These animations
should include all techniques that students were thought during research. The students were given 90
minutes to develop an animation properly. The animations were collected and reviewed using "Animation
Development Level Rubric".
Data Analysis
A combination of parametric and non-parametric tests was used in this research taking into
consideration of normal distribution and homogeneity (Fraenkel & Wallen, 2006). The data collected from
participants were analysed using the SPSS 20.0 software. Animations developed by participants were graded
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separately by field experts and researchers using “Animation Development Level Rubric”.
RESULTS
The impact of mobile learning on academic achievement
Mann-Whitney U test was performed to compare academic achievement scores of both groups (see
Table 1). There was no significant difference between academic achievements of both groups before research
(p>.05) while significant difference was found in favour of experiment group after research (p<.05). In
accordance with these results, it can be said that mobile learning poses better effect in terms of academic
achievement.
Table 1. The effect of mobile learning on academic achievement.
Group Test N
Mean
rank
Sum of ranks
Mann-Whitney
U
Z Sig.
Experiment
Pre test
15 25.20 378.00
132.000 -1.716 .086
Control
26
18.58
483.00
Experiment
Post test
15 31.13 467.00
43.000 -4.150 .000
Control
26
15.15
394.00
Experiment
Follow up
test
15 28.67 430.00
80.000 -3.130 .002
Control
26
16.58
431.00
For persistence control, follow up tests were performed six months after the end of the research.
Data collected from follow up tests compared with post-tests. It is seen that there was still significant
difference in favour of experiment group according to follow up tests (U=80.000, p<0,005). It can be said that
mobile learning has persistent effect on academic achievement.
There were no significant differences between pre-test – post-test attitude scores of both groups. In
this case, high results of pre-test and post-test was due to the fact. The high attitude scores can be explained
as participants' being digitally literate and studying in Computer Education and Instructional Technology
department. It is seen that both groups had significantly high attitude scores towards mobile learning (p>.05).
The impact of mobile learning on attitudes toward mobile learning
There were no significant differences between pre-test – post-test attitude scores of both groups. In
this case, high results of pre-test and post-test was due to the fact. The high attitude scores were explained
because of participants, who were digitally literate, were studying in Computer Education and Instructional
Technology department. It is seen that both groups had significantly high attitude scores towards mobile
learning (p>.05).
Table 2. The effect of mobile learning on attitudes toward mobile learning.
Factor Group Test N X SS t Sig.
Satisfaction
Experiment
Pre test
15 74.13 9.72
.754 .528
Control 26 76.38 11.52
Experiment
Post test
15 70.80 12.42
-.841 .405
Control 26 74.00 11.33
Experiment Follow up 15 76.53 13.84 .944 .351
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Control
test
26 72.00 15.33
Effect to
learning
Experiment
Pre test
15 42.40 8.08
-.079 .206
Control 26 45.38 6.60
Experiment
Post test
15 42.60 5.84
-1.153 .256
Control 26 44.77 5.78
Experiment
Follow up
test
15 45.53 6.02
.485 .631
Control 26 44.53 6.49
Motivation
Experiment
Pre test
15 26.00 3.93
-.868 -.722
Control 26 26.46 3.99
Experiment
Post test
15 24.67 5.27
-1.204 .236
Control 26 26.50 4.34
Experiment
Follow up
test
15 26.73 5.03
1.023 .313
Control 26 24.88 5.85
Usability
Experiment
Pre test
15 24.40 3.16
-1.369 .091
Control 26 22.04 5.56
Experiment
Post test
15 22.47 4.45
.838 .407
Control 26 21.08 5.45
Experiment
Follow up
test
15 19.40 3.94
-.694 .492
Control 26 20.42 4.85
The effect of mobile learning on animation development levels
The animations that were developed by students were analysed. Significance differences found in
favour of experiment group (p<.05) which is similar to the post-test and follow up test results of academic
achievement tests.
Table 3. The effect of mobile learning on animation development levels.
Group N
Mean
rank
Sum of ranks
Mann-Whitney
U
Z Sig.
Experiment 15 30.97 464.50
45.500 -4.096 .000
Control 26 15.25 396.50
The views of students towards mobile learning
The students indicated that they felt excitement, joy, happiness and valuable when they learned that
mobile learning and tablet computers would be used in this course. Also, two students expressed that they
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hesitated because they never experienced this before. However, it was observed that motivation of students
increased:
Student 1: “I was glad when I first heard. I hesitate a little bit. We were faced with things we didn’t
know how to do them.”
Student 3: “I felt nice things. I was excited and happy. I felt valuable in this department.”
Student 4: “Access to the resources and samples any time kept me motivated.”
Student 5: “It was very nice to me. I walked around constantly mobile. I continuously was mobile.”
The students stated that mobile learning had positive impacts on their learning and supported them:
Student 2: “The information was persistent which I got through my mobile device. In addition, my
mobile device provided me extra time because of rapid access to the information. I rapidly learned an
incorrect or incomplete information that caught my mind thanks to mobile learning. I fixed my wrong and
deficit knowledge.”
Student 3: “Instantly access to information about our course with mobile devices gave us extra time
and made learning easier for us.”
Student 4: “I reinforced parts with resources when I didn’t understand during course study and I tried
to figure out the issues.”
The students had some technical problems during the research about Internet connection, tablet
computers, application notifications and other technical issues. In addition, they expressed that if technical
issues were solved, they would want to use mobile learning in other courses as well. Also, students advised
about mobile learning in the course:
Student 2: “The information, which I encountered relevant and irrelevant, caused confusion. I think
the persistence will be increased if it is used in practical courses.”
Student 3: “I want to reach the course notes at the end of the course.”
DISCUSSION AND CONCLUSION
This research examined the effects of mobile learning applications on undergraduate students'
academic achievement, attitudes toward mobile learning and animation development levels. Mobile learning
has significantly positive effect on academic achievement compared to traditional learning in this research.
Results were similar to those of Oberer and Erkollar (2013) and Hwang and Chang (2011). Similarly, Hwang
and Chang (2011) indicate that mobile learning not only catches students’ interaction but also increases their
success. Chu (2014), on the other hand, emphasize that mobile learning has negative effect on academic
achievement because of cognitive overload and inappropriate design of learning.
Chu, Hwang, Tsai and Tseng (2010) have found that students have positive attitudes toward mobile
learning. It was found in this study that both of the groups had positive attitudes toward mobile learning in
line with the results of previous research (Evans, 2008; Gikas and Grant, 2013; Kutluk and Gülmez, 2014;
Oberer and Erkollar, 2013). This situation was seen reasonable by researchers because both groups are at an
age called “digital native” (Wishart & Thomas, 2015). The students who participated in this research were
studying in department related ICT and were considered to be digitally literates.
Ozan (2013) have found that mobile technologies positively affect performance of students.
Animations, which were developed by mobile learning group, were found more qualified in this research.
This result supports the results of other research (Ozan, 2013; Huang, Liao, Huang & Chen, 2014; Oberer &
Erkollar, 2013).
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Quick access to information, anywhere and anytime learning, interacting with friends and facilitating
learning are observed as important key points of mobile learning according to the interviews with students.
Mobile learning applications increase the effect of learning and enhance the process of learning (Huang et
al., 2014; Wishart, 2015). Students emphasized that they would want further mobile learning experiences
such as doing homeworks using mobile devices, more activities on tablet computers and developing
animations on tablet computers. However, some technical issues were faced in terms of software and
hardware. These issues were slow Internet connection and notification restrictions of mobile learning
management system.
RECOMMENDATIONS
Suggestions are proposed in the light of the findings and results obtained through the research.
Researchers should provide Internet and Wi-Fi during mobile learning studies. Limited number of mobile
devices were used in this research. It is suggested that future research should be implemented with more
mobile devices with larger samples. Tablet computers with Android operating system were used in this
research. In order to develop positive attitude, mobile learning can be used in courses that students do not
like or do not have interest. Students should develop animations via mobile devices and this is suggested to
be examined in future research.
Statements on open data, ethics and conflict of interest
Please contact the first author in order to access data and documents, which are collected during the
research. This article produced from first author’ master thesis with the second author as advisor. This thesis
was supported by Scientific Research Projects Unit of Dokuz Eylul University (Project Id: 2013.KB.EGT.004).
The necessary permissions to develop data collections tools and implement the research were taken from
the Ethics Committee in Institute of Educational Sciences, Dokuz Eylul University, Turkey. Participants
attended to the research on a voluntary basis and had the right to leave the research whenever they wanted.
Compliance with ethical standards
Conflict of interest
The authors declare that they have no conflict of interest.
Ethical approval
All procedures performed in studies involving human participants were in accordance with the ethical
standards of the institutional and/or national research committee and with the 1964 Helsinki declaration and
its later amendments or comparable ethical standards.
FUNDING
This study was funded by Scientific Research Projects Unit of Dokuz Eylul University (Project Id:
2013.KB.EGT.004).
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