Know the Mobile Learning Application Users
Transactional Distance Perspective
Pakapan Limtrairut, Stuart Marshall and Peter Andreae
School of Engineering and Computer Science, Victoria University of Wellington,
PO Box 600, Kelburn, Wellington, 6140, New Zealand
Keywords:
Distance Education, Mobile Learning, Transactional Distance Theory, Persona.
Abstract:
We developed a mobile learning application grounded on Transactional Distance Theory. The aim is to engage
learners and decrease their feelings of isolation and emptiness when learners and instructor are physically
separated. This study was launched in an effort to understand our target learners and provide an indication
towards the practicality, possibility, and appropriateness of such theory-based design. The application provides
text, video, and recorded audio as media, and includes chat function, game-based learning, and electronic
assignment. This paper explores the method and findings of a survey study targeted at first year Computer
Engineering and Computer Science student learners at the Victoria University of Wellington, New Zealand.
Our survey results indicated that the learners had a positive attitude towards mobile learning, and they had a
lot of experience using the provided media and functions. The theoretical-design was deemed to be practically
appropriate for our learners. However, more encouragement and promotions would be needed in order to
increase the application’s usage and recognition. We performed statistical analysis on the results and clustered
the responses to form a persona which will be used in the next stage of this application’s development process.
1 INTRODUCTION
Along with the popularity and the fast growth of com-
munication technology, an education platform is be-
ing extended to a mobile-based teaching and learn-
ing. The mobility of m-learning helps people to ob-
tain knowledge wherever they are and at convenience
time, which extend the learning to reach a wider au-
dience (Shudong and Higgins, 2005).
Although mobile phones have potential to pro-
mote learning in distance, developing an m-learning
system faces some challenges. Because of hardware
and software limitations, mobile phones cannot de-
liver all learning contents on current personal com-
puters or laptops. This may remind developers that
designing an m-learning system requires a deliberate
plan. At the initial stage of development processes,
identifying and understanding target users can help to
decide what learning contents are possible and mean-
ingful to be delivered on limited resources of mobile
phones.
We developed a mobile learning application on
smart phones grounded on Moore (1973)’s Transac-
tional Distance Theory (TDT). The theory suggested
how distance courses should be structured. We fol-
lowed the guidelines and presented learning content
in text, video, and recorded audio. We included a
chat function in the application, added a game-based
learning in the application, and provided an assign-
ment that was compulsory to be submitted to instruc-
tors through an email.
The theory has been introduced since 1973. To
date, there has been no evidence to suggest if it can
be used to guide the design of modern education plat-
form such as m-learning. Therefore, we launched a
study that observed our target learners’ experience
and attitude towards m-learning, the provided me-
dia, and functions. The study could help us to im-
prove the current design. We clustered the responses
and formed a learners’ archetype. Based upon this
archetype, we created a persona which will be used
by all people involved in the development process.
The remainder of this paper is structured as fol-
lows: section two presents background of m-learning,
persona, TDT, and our proposed design; section three
presents research methodology; section four presents
the persona, quantitative and qualitative results, and
analysis; and the last section is conclusions.
378
Limtrairut, P., Marshall, S. and Andreae, P.
Know the Mobile Learning Application Users - Transactional Distance Perspective.
In Proceedings of the 8th International Conference on Computer Supported Education (CSEDU 2016) - Volume 2, pages 378-387
ISBN: 978-989-758-179-3
Copyright
c
2016 by SCITEPRESS Science and Technology Publications, Lda. All rights reserved
2 BACKGROUND
2.1 Mobile Learning
Mobile learning or m-learning is teaching and learn-
ing processes through mobile devices such as mo-
bile phones, tablets, and Personal Digital Assistants
(PDAs). The devices’ popularity along with the sup-
port of mobile technologies, more people can now
obtain knowledge anywhere and anytime (Liu et al.,
2010). According to Traxler (2007), m-learning has
three remarkable potentials.
Facilitating Personalized Learning: M-learning
allows an instructor to send personalized feedback
or receive personalized requests from an individ-
ual learner
Supporting Authentic Learning: M-learning
provides opportunities for learners to access to
available resources online that help them to ap-
proach real world problems. It also facilitates col-
laborative working when a group of learners are
physically remote from each other
Providing Flexible Learning: While an actual
class room requires a pre-set up in a multi-
campus classroom environment or a field study,
m-learning provides flexible learning environ-
ments
Despite its promises, m-learning faces some im-
portant challenges. Technical restrictions of mobile
phones (e.g., small screen size, low screen resolu-
tion, lack of efficient data entry capability, small stor-
age, small bandwidth, slow processor speed, and short
battery life) may influence m-learning adoption (Liu
et al., 2010). From the pedagogical viewpoint, m-
learning causes the difficulties in following up learn-
ers’ achievements. Because learning activities can
happen anywhere and anytime, without instructor su-
pervision there may be issues in trusting that the
answers of an assignment or exam are truly com-
pleted by the registered learner (Shudong and Hig-
gins, 2005).
Even though much research (e.g., Alshalabi and
Elleithy (2012), Melhuish and Falloon (2010), Crow
et al. (2010), Cochrane and Bateman (2010), Jones
and Marsden (2006), Jones and Marsden (2004)) sug-
gested design strategies for m-learning that can elim-
inate the technical limitations of mobile phones, de-
signing an m-learning requires an initial research to
specify if the design is suitable for the target learners.
In the next section, we will introduce persona tech-
nique that raises understanding of learners.
2.2 Persona
Cooper et al. (1999) introduced persona in 1999 to
explain customers’ behavior in marketing research.
The first persona was created to point out that the end
users and their needs were important in the develop-
ment processes (Idoughi et al., 2012). According to
Cooper et al. (1999), persona is a character which is
created by gathering behavioural data from real users.
It presents a lot of users’ information and helps de-
velopers to make decisions in a product development
process.
Idoughi et al. (2012) defined persona as “a de-
scriptive model of the user, encompassing informa-
tion such as user characteristics, goals, and needs”
(Idoughi et al., 2012, p.288). Similarly, Pruitt and
Adlin (2010) defined persona as a fictitious character
that represented target users and raised focus towards
them in the development process.
We defined persona within learning environment
as a representative of a group of learners who had
same goals and showed similar behavior and attitude
when they made decisions. These behavior and atti-
tude were regardless of age, gender, and education. It
helped us to decide which functions were meaningful
and should be provided in the m-learning application.
According to Pruitt and Adlin (2010), the benefits
of persona are:
Clarifying Assumptions about Users: A design
team may has many conflict hypothesis on their
users. Persona can assist them to make a con-
crete design decision and focus on the same ex-
plicit definition of users
Identifying Specific Groups of Users: In gen-
eral, products are created to target as many cus-
tomers as possible; however, there are also many
specific users who are not recognized by a design
team. Persona helps them to identify these users,
hence the design can be expanded to everyone
Helping a Design Team to make the most from
Limited Resources: At the beginning of the de-
velopment processes, there are many proposed
ideas on the design and someone has to choose
which idea is possible and worth developing.
“Personas offer a consistence target-audience vi-
sion” (Pruitt and Adlin, 2010, p.18), hence there
is a high possibility that many people will like the
design
Engaging a Development Team: Pruitt and
Adlin (2010) claimed that personas were different
from other user centred design techniques because
they were fun as cartoon characters, which could
inspire imagination, provide compelling, intense,
and memorable information about users
Know the Mobile Learning Application Users - Transactional Distance Perspective
379
Much research placed importance on users and in-
cluded personas in their design processes. For exam-
ple, Rahim et al. (2014) created personas that pre-
sented users’ background, and their behavior when
they purchased food products. These personas aimed
to investigate users’ requirement, and contribute to
their Halal-Checker Mobile Application (I-scan) de-
sign. Calvo et al. (2014) also created personas in the
study that aimed to improve performance of a syn-
chronous chat in an m-learning application for stu-
dents and teachers with disabilities.
We created a persona at the initial stage of our m-
learning application development. The persona pre-
sented learners’ profile, m-learning goals, experience,
and attitude toward m-learning. The application was
designed grounded on Transactional Distance Theory.
In the next section, we will introduce the theory and
show how we applied it in the application design.
2.3 Transactional Distance Theory and
Mobile Learning Application Design
Much research (e.g., Shearer (2007), Park (2011))
found that learners felt disconnected and perceived
isolation when they were separated from instructors
and had to take control of their own learning. Later
Moore (1993) named this feeling and perception as
“transactional distance”. Moore (1973) introduced
Transactional Distance Theory (TDT) to explain the
factors that varied level of transactional distance and
affected learning quality. According to Moore (1973),
there are three factors that take control of transac-
tional distance:
1. Dialogue: Positive interactions and communica-
tions between learners and instructors that im-
prove their understanding. It is direct proportional
with transactional distance (i.e., if an instructor
has a conversation or other of types communica-
tion with learners, transactional distance will be
decreased)
2. Structure: The way teaching program is con-
structed and organized. Moore (1973) suggested
six instructional processes that helped educational
providers to form a distance learning program.
These processes are:
Presentation: Recorded media such as audio
and video can engage learners better than a
plain text presentation
Motivation: Feedback from instructors can
help learners to maintain their interest and en-
courage them to learn
Analysis and Criticism: Opportunities to hear,
analyze, and challenge experts’ discussions can
improve learners’ cognitive skills
Advice and Counsel: Guidances on how to
use learning materials and which learning tech-
niques are effective for learning can help learn-
ers to solve their problems and build their learn-
ing skills
Practice and Evaluation: Writing assign-
ments allow learners to practice what they have
learnt, and can be used to evaluate their knowl-
edges
Creation of Knowledge: Opportunities to dis-
cuss some ideas with instructors can improve
learners’ professional skills
3. Learner Autonomy: The process that learners
set their own learning goals and control over their
own learning. Moore (1980) suggested that each
and every educational provider should examine
learners’ autonomy and seek for a suitable pro-
gram structure for them. This factor does not
guide the design but guide the observation of
learners’ behavior
For the application design, we only adopted di-
alogue and structure. We translated Moore (1973)’s
guidelines into the design guidelines of m-learning
application. The functions we presented in the ap-
plication are:
Figure 1: An example of chat function in the application.
1. Chat: An available communication channel for
learners to contact their instructors. It supports
both synchronous and asynchronous as well as
a public mode (i.e., many learners and an in-
structor are in the same chat room) and a private
mode (i.e., one-on-one communication between a
learner and an instructor) communications. Fig-
ure 1 shows an example of asynchronous, public
mode chat room design
2. Media: There are text, recorded audio, and video
presentations available in the application, which
are used to deliver learning contents
CSEDU 2016 - 8th International Conference on Computer Supported Education
380
Figure 2: An example of assignment given in the applica-
tion.
3. Game-based Learning: An opportunity for
learners to practice what they have learnt
4. Assignment: In order to improve learners’ cog-
nitive skills, we provided a short case study for
them to read (Figure 2). It is compulsory that they
answer (i.e., a short answer) the given question,
send the answer to an instructor’ email and they
will receive feedback from the instructor
3 RESEARCH METHODOLOGY
We recruited first year computer engineering, and
computer science students from School of Engineer-
ing and Computer Science, Victoria University of
Wellington, New Zealand to participate in our online-
based, anonymous questionnaire by sending a class-
less email. From an approximately 150 students, 30
of them completed the survey.
Our participants were students who enrolled ei-
ther in Engineering Modelling and Design or Intro-
duction to Data Structures and Algorithm courses. We
conducted the study on October, 2015 during second
trimester. Our participants have passed at less one
basic computer course, hence they had experience in
learning in university.
In order to create a persona, we adopted Cooper
et al. (2007), and Mulder and Yaar (2006)’s sugges-
tions. Cooper et al. (2007) suggested seven prin-
ciple steps (i.e., identify behavioral variables, map
interview subjects to the variables, identify signifi-
cant behavior patterns, synthesize characteristics and
relevant goals, check for redundancy and complete-
ness, expand description of attributes and behaviors,
and designate persona types) while Mulder and Yaar
(2006) suggested three types of research (i.e., Quali-
tative research, Qualitative research with quantitative
validation, Quantitative research) that helped devel-
opers to create personas.
There are two behavioral variables (i.e., experi-
ence, and attitude) that we observed. We adopted
quantitative research to observe learners’ experience
in using mobile phones for both general and edu-
cational purposes, and learners’ attitude towards m-
learning, the given media and the given functions.
Likert scale was used to rank the experience and mea-
sure the attitude. This could help us to predict if the
given media and functions (e.g., video, recorded au-
dio, chat) are practically possible to facilitate learn-
ing.
We adopted qualitative research to observe what
activities other than calling and texting learners per-
formed using their mobile phones, how they used
their mobile phones to support learning, and their goal
of learning on mobile phones. Text box fields were
used to collect free-form, text-based responses.
In order to identify significant behavior patterns,
we plotted the quantitative results into graphs and
seek for learners’ archetype. In the next section,
we will present our persona, the process we used to
find learners’ behaviour patterns, and general findings
from the survey.
4 RESULTS AND ANALYSIS
From a total of 30 participants, 26 are male students,
and four are female students. The average age of par-
ticipants is 22 year old.
4.1 Persona of M-Learning Learners
We gathered all the results, categorized them, found
a behavioural pattern, and created a persona (Figure
3). This persona will be used to represent our target
learners by all people involved in this m-learning ap-
plication development process.
This persona was created based on the results of
participants’ responses to 24 quantitative questions.
In an attempt to find a behaviour pattern from these re-
sponses, we plotted them alongside each other (Figure
4). This graph helped us to see each individual trend
clearly; however, it could not help us to find learners’
behaviour pattern.
Next, we plotted them on the same graph (Figure
5). we found that the resulting graph was overly dis-
tributed and was not effective for determining learn-
ers’ behaviour pattern, therefore we performed three
rounds of clustering.
First Round Attribute Clustering: The ques-
tions were divided into seven clusters (i.e., expe-
Know the Mobile Learning Application Users - Transactional Distance Perspective
381
Figure 3: Persona represents learners of m-learning appli-
cation on mobile phones.
rience in using a mobile phone in daily life, ex-
perience in using a mobile phone for educational
purpose, experience in using the provided media,
experience in using the provided functions, at-
titude towards m-learning, attitude towards pro-
vided functions, and learning preference). For the
clusters that consisted of more than one question,
we plotted the graph based on their average values
(Figure 6).
Second Round Cutting Off: Based on the av-
erage values, we set an allowed interval for each
cluster. If a participant provided two or more
responses outside the allowed interval, we cut
through the participant off the considered group.
There were 17 participants who were cut off in
this round (Figure 7).
Third Round Cutting Off due to the Extreme
Value: There were three participants who were
qualified from the second round cutting off, but
were excluded in this round, as their responses
to one question varied greatly from other partic-
ipants in the same cluster.
The final ten participants showed a similar trend.
They were the archetype and we created a persona
based on them. We assigned a pseudonym which was
“John” to represent the persona. According to the par-
ticipants’ responses in Figure 8:
Figure 4: The graph of 30 participants’ responses to 24
quantitative questions plotted alongside each other. The x-
axis presents the 24 qualitative questions, while the y-axis
presents the level of learners’ experience and attitude to-
ward m-learning, the provided media and functions in the
range one to five. We plotted this graph to see each individ-
ual’s responses and the trend in graphs. However, it could
not help us to find learners’ behaviour pattern.
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382
Figure 5: This graph is the compressed 30 participants’
responses (from Figure 4) in a single scale. The x-axis
presents 24 quantitative questions, while the y-axis presents
the responses in the range one to five.
Figure 6: The graph after first round attribute clustering.
The x-axis presents seven clusters, while the y-axis presents
the responses in the range one to five.
Figure 7: The graph after second round interval cutting-off.
Figure 8: The graph after third round the extreme value
cutting-off.
Cluster 1: John “all of the time” uses his mo-
bile phone for things other than calling and tex-
ting. We used a qualitative question to specify the
activities and we found that John watched Videos
on YouTube
1
, listened to pre-downloaded musics,
went to Google
2
website to search for some in-
formation, and used his mobile phone’s camera to
capture photoes. He also used his mobile phone
to communicate with his friends and family.
Cluster 2: John “often” uses his mobile phone
for educational purposes. We also used a qualita-
tive question to specify the educational activities.
The answers were varied (e.g., he used his mo-
bile phone’s camera to capture lecture notes’ pho-
tos, he went to school’s website and viewed online
learning contents on his mobile phone)
Cluster 3: John “sometimes” uses the media (i.e.,
video, recorded audio, and text) that we provided
in the application (i.e., he sometimes watches
videos, listens to pre-downloaded musics, and
read online articles)
Cluster 4: The responses in this cluster were
varied between two (rarely performed the given
tasks) to four (often performed the given tasks),
therefore we could not form a behavior pattern
based on the whole cluster. However, when
we looked into each question (i.e., each given
task) within this cluster, we found patterns (i.e.,
John “sometimes” uses his mobile phone to
send/receive emails, he “rarely” plays games or
works on an assignment on his mobile phone)
Cluster 5: John agreed that mobile phones have
helped him in his learning
Cluster 6: John has positive attitude towards pro-
vided functions (e.g., he realizes that contacting
instructors either face to face or via email have
helped him to engage with learning)
Cluster 7: John prefers to learn on a laptop or
PC rather than a mobile phone. Therefore, more
encouragement and promotions may be required
in order to increase the application’s usage and
recognition
1
https://www.youtube.com
2
https://www.google.co.nz
Know the Mobile Learning Application Users - Transactional Distance Perspective
383
4.2 General Findings
4.2.1 Learners’ Experience in Using Mobile
Phones for General and Educational
Purposes
We adopted Likert scale to measure how often (i.e.,
1= never, 2 = rarely, 3 = sometimes, 4 = often, and
5 = all of the time) learners used their mobile phones
in daily life, and whether they used it for educational
purpose. Our findings (Table 1) shows that learners
used their mobile phone “all the time”. We also asked
them to list the activities that they performed on their
mobile phones other than calling and texting. The fol-
lowing list shows the usage categories.
Communication purpose: They used their mo-
bile phones to access social media websites (e.g.,
Facebook
3
, Reddit
4
, and sending and receiving e-
mails
Entertainment purpose: They used their mobile
phones to watch video online from video-sharing
websites (e.g., YouTube), listen to music, and play
games
Researching purpose: Participants mentioned that
they accessed Google whenever they wanted to
find any information. They also read news,
and participated in online-forums on their mobile
phones
Personal Management purpose: They used many
basic functions available on their mobile phones
to manage their daily life. For example, they used
note function to list activities to be completed,
used calendar to receive notifications regarding
when these tasks should be completed, used alarm
clock to wake them up in the morning and they
managed their bank account online
Other purpose: They mentioned many others ba-
sic functions of mobile phones (e.g., flash light,
map, camera) which they used regularly
Table 1: Learners’ experience in using a mobile phone for
general and educational purpose in their daily life.
Question Mean SD
For things other than
calls and texts
4.53 0.97
For educational purpose 3.57 1.04
When we specified the usage of mobile phones to
educational purposes, the usage level was slightly
decreased to “often”. We also asked them to explain
3
https://www.facebook.com
4
https://www.reddit.com
how they used their mobile phones to support their
learning. The results show the same usage categories
(listed previously) being applied by students in the ed-
ucational context. The interesting findings are:
They used their mobile phones to access to social
media websites to contact their classmates and
discuss their lessons and assignments
They also downloaded lecture notes, slides, and
videos and used these downloaded materials from
their mobile phones when they were outside uni-
versity
For research purpose, they read articles on their
mobile phones and used online search engines
(i.e., Google) when they had questions and wanted
to find more information
They visited the school’s website to keep them-
selves updated, and accessed learning resources
via University’s Blackboard system
They used mobile phones’ basic functions such as
clock, calendar, and note to help them to manage
their learning schedule, and they also used their
camera to capture their lecture notes
Based on these findings, mobile phones are con-
firmed to be powerful tools for supporting ubiquitous
learning. The use of mobile phones as an educational
tool is now very much an established part of our target
learners’ daily learning environment.
4.2.2 Learners’ Goals toward M-Learning
We asked learners to explain the term “mobile
learning”. Most of them showed that they understand
the term. For example a student answered that
“Mobile learning to me is being able to gain
and apply knowledge anywhere at anytime including
when an internet connection is unavailable”
The results showed that learners could differen-
tiate m-learning from other types of learning. They
mentioned learning on the go, learning anywhere,
and convenient when they were not stationary.
We asked learners to identify their goals of
learning on mobile phone. It appeared that they did
not have a clear goal for m-learning. Most of them
considered mobile phones as tools to help them to
learn outside of their classrooms when they were
not in front of their laptop and PC. Examples of the
answers are:
“I do not consider myself a person who learns
from a mobile phone, only one who uses it for time
management and organising my learning, which
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384
Table 2: Learners’ experience in using a mobile phone to perform the given tasks.
Task Mean SD
Reading long text such as an on-line article from the screen of mobile phone 3.50 1.20
Using a scroll-up and scroll-down bar to go through text 3.17 1.53
Using zoom-in and zoom-out to read text 3.43 1.17
Playing video on mobile phone 3.50 1.11
Using play, pause, rewind, fast forward, or repeat functions of video player 3.03 1.19
Listening to recorded audio or music on mobile phone 4.00 1.17
Using play, pause, rewind, fast forward, or repeat functions of music player 3.37 1.33
Playing game on mobile phone 2.57 1.22
Sending/Receiving e-mail on mobile phone 3.97 1.07
Text chatting on mobile phone 3.93 1.23
Doing homework/assignment on mobile phone 2.07 1.28
comes from other sources unless it is an extreme
scenario (i.e. there are absolutely no computers
available to me)”
“I just want to be able to find out what I need
to know very quickly. I can do this already!”
These results pointed out that our target learners
did not take m-learning as a primary source of
learning and they did not set up a learning goal
even though they adopted the phones for many
learning activities. It raised awareness about learners’
m-learning acceptance and that encouragement and
promotions (e.g., use rewarding technique) may be
required.
4.2.3 Learners’ Experience in Using Provided
Functions
In this section, we observed if learners had experience
in using the functions that we planed to provide in our
application. We adopted Likert scale (i.e., 1= never, 2
= rarely, 3 = sometimes, 4 = often, and 5 = all of the
time) to indicate how often they had performed the
tasks.
As outlined in our results collated in Table 2,
learners pointed out that they “sometimes” to “often”
perform the given tasks. Base on these results, learn-
ers should be able to learn by reading text, watching
video presentation, and listening to recorded audio. If
they have questions, want to share their ideas, or dis-
cuss their ideas with instructor they should be able to
use the provided communication channels (e.g., send-
ing an e-mail to instructor, entering chat room).
On the other hand, they expressed that they
“rarely” played games and worked on assignments
on their mobile phones. These findings raised some
concerns that they might not play the provided game-
based learning and submit the given assignment. We
may need to find strategies to promote our game-
based learning (e.g., arrange competitions in which
highest score winners receive rewards). For the as-
signment, we may need to arrange a submission dead-
line or use rewarding technique to encourage their
participations.
4.2.4 Learners’ Attitude toward M-Learning
We observed learners’ attitude toward m-learning and
the functions that we planed to develop in the appli-
cation. We adopted Likert scale (i.e., 1= strongly dis-
agree, 2 = disagree, 3 = neutral, 4 = agree, and 5 =
strongly agree) to indicate how much they agreed with
the given statement. Table 3 presents the results.
Based on the results in Table 3, learners showed
that they had positive attitudes toward using mobile
phones to support their learning process. They fur-
ther indicated that learning through video presenta-
tion was the most popular learning style, followed
by learning by reading text. Even though they ex-
pressed that they had the most experience listening to
recorded audio or music, they preferred it the least.
For game based learning, they expressed that they
did not have negative nor positive attitudes toward
them even though they rarely played games on mo-
bile phones.
Learners “strongly agree” that assignments had
helped them to improve their learning and they pre-
ferred performing them on a computer rather than
on actual paper, hence assignments showed high po-
tential for improving learning quality and should be
added into m-learning application. However, students
expressed that they felt frustrated typing using small
mobile phone keyboards, therefore the given assign-
ment in the application should be short answers, or
multiple choices types of questions.
For communication, learners agreed that keeping
in touch with instructors could encourage them to
learn and they slightly preferred sending e-mail or
message to instructor rather than having a face-to-face
Know the Mobile Learning Application Users - Transactional Distance Perspective
385
Table 3: Learners’ attitude towards m-learning and the given functions
Task Mean SD
Mobile phone has helped me in my learning process 3.87 0.82
I prefer learning by watching a video on a mobile phone rather than reading text on a
mobile phone
3.10 1.27
I prefer learning by listening to a recorded audio on a mobile phone rather than reading
text on a mobile phone
2.43 1.07
I like game based learning activities 3.30 1.22
I feel frustrated typing on small key board of a mobile phone 3.37 1.27
Assignments help me to improve my learning 4.60 0.56
I prefer doing an assignment on a computer rather than writing on actual paper 3.83 1.09
Keeping in touch with my instructor can encourage me to learn 3.83 0.70
I prefer sending an e-mail or a message to my instructor rather than having a face-to-
face conversation
3.43 1.25
I prefer having synchronous rather than asynchronous communication with instructor 3.37 0.89
I prefer learning on a mobile phone rather than learning on a laptop or a desktop
computer
1.17 0.92
conversation. Similarly, they slightly preferred syn-
chronous to asynchronous communication.
Lastly, even though learners had positive attitude
towards using mobile phones to support their learn-
ing, they still preferred to learn on a laptop or a desk-
top computer rather than on a mobile phone. This
could be an effect of hardware limitations (e.g., small
size keyboard, screen, low solution).
5 CONCLUSIONS
Distance learning may trigger feelings of isolation or
perceived emptiness in learners as they have to ex-
ercise more self-discipline and control over their one
learning. Transaction Distance Theory suggested how
distance education should be constructed. Grounded
on this theory, we designed an m-learning application.
We observed whether this theoretical-based design is
practically possible for our target learners.
A total of 30 participants, 26 male and four fe-
male, who are first year computer engineering and
computer science students at Victoria University of
Wellington, New Zealand answered an online-based
questionnaire. The significant findings are:
Our target learners had a lot of experience in using
mobile phones. They used them as communica-
tion tools (e.g., access to social media, chatting),
entertainment tools (e.g., watch video, listen to
music), researching tools (e.g., access to Google),
and management tools (e.g., set up notification,
alarm clock)
Our target learners often used their mobile phone
for educational purposes
Our target learners knew what m-learning was,
but they did not have a cleared goal towards m-
learning
Our target learners had experience in using the
provided media (i.e., text, video, recorded audio)
and they preferred to learn from video presen-
tation rather than reading text, and listening the
recorded audio
Our target learners had a lot of experience in us-
ing the chat function but they had less experience
playing game, and working on their assignments
on mobile phones
Our target learners had positive attitudes towards
m-learning, however they preferred learning on a
laptop or a desktop computer rather than learning
on a mobile phone
Based on these findings, our Transactional Dis-
tance Theory-based design was practically appropri-
ate for our learners. They should be able to learn
from provided media, and be able to use the pro-
vided chat function to communication with instruc-
tors. However, we need to find strategies to encourage
learners to participate in the game-based learning, and
complete the given assignment. We can use reward-
ing techniques and send assignments notifications to
them.
Our survey results also indicated that our learn-
ers did not consider m-learning on mobile phones as
their major learning source. In order to increase appli-
cation usage, m-learning needs more promotions and
encouragement.
Finally, we created a persona based upon learners’
archetype, which will be shared among the people in-
volved in this application development process.
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