Facets of Mobile Lifelong Learning Services
Amir Dirin
1
, Teemu H. Laine
2
and Marko Nieminen
3
1
Business Information Technology, Haaga-Helia University of Applied Sciences, Helsinki, Finland
2
Department of Computer Science, Electrical and Space Engineering, Luleå University of Technology, Skellefteå, Sweden
3
Department of Computer Science, Aalto University, Helsinki, Finland
Keywords: Lifelong Learning, Social Media, Learning Media, Emotions, Feelings.
Abstract: In the era of digital services and digital connectivity, a massive amount of knowledge has become available
and accessible all the time and for all ages. This mandates significant structural changes in the ways in which
knowledge are shared and contents are presented. The ways in which knowledge is shared and learners
become engaged with that knowledge are crucial in lifelong learning. In lifelong learning the knowledge and
the content must be delivered to learners at the right time, without distractions and noise. The traditional
educational offering in classrooms is not anymore feasible and supportive as learning happens in a disengaged
manner in lifelong learning. In new lifelong learning services, user experience (UX) plays a key role in
delivering content appropriately and supporting transition of learning between different contexts with adaptive
learning media. The objective of this study is to illustrate and elaborate on the roles of feelings and emotions
in engaging students in lifelong learning applications. We have applied systematic literature review (SLR) to
identify emotional factors associated with lifelong mobile learning (m-learning) environments. Based on the
findings, we propose an application concept as a case study to demonstrate how emotional factors can manifest
themselves in lifelong learning applications. Finally, based on the findings of the literature review and the
case study evaluation, we propose a model illustrating the facets in lifelong learning applications.
1 INTRODUCTION
Technological advancement has significantly
impacted traditional educational offerings during last
three decades (Halili, 2019). Wireless technologies,
Internet, and smart gadgets have enabled lifelong
learning design and development to be more feasible
than ever. Already for more than two decades E-
learning, m-learning, and distance learning have co-
existed and provided educational offerings in various
forms by educational institutes. These technology-
assisted enhancements will continue to support
lifelong learning which extends beyond classroom-
based curricula. Technology-assisted lifelong
learning interventions are the results of the
popularity, affordability, and accessibility connected
mobile devices. These interventions anticipate and
overcome the existing constraints in traditional
educational offerings. For example, m-learning
overcomes the place and time restrictions of learning
which are apparent in traditional classrooms
(Mostakhdemin-Hosseini & Tuimala, 2005). Unlike
traditional learning where teachers directly interact
with learners, in lifelong learning the learners must be
motivated and engaged with the learning platform.
With further advancement of technology, m-learning
has become more feasible than ever before. Learners
in any context are capable of having access to
appropriate learning materials just when they are
needed. Therefore, learning may happen at any time
and any place regardless of age and qualifications of
the learner.
In this paper, we define the term lifelong m-
learning as self-regulated learning that happens in a
context, with help of mobile devices, where users
pursue to develop competence or update knowledge.
Chen et al (2015) define lifelong learning as a
continuous learning for retaining the knowledge. In
lifelong learning, learners often utilize unstructured
learning approaches. Kukulska-Hulme (2007)
emphasized that “for broad and long-term adoption
the experience really matters in learning.” Therefore,
learners’ engagement plays an important role in any
digital learning environment, including also lifelong
m-learning environments. Learners’ engagement
with digital learning platforms goes into the user
experience (UX) domain.
Dirin, A., Laine, T. and Nieminen, M.
Facets of Mobile Lifelong Learning Services.
DOI: 10.5220/0009386905430551
In Proceedings of the 12th International Conference on Computer Supported Education (CSEDU 2020) - Volume 1, pages 543-551
ISBN: 978-989-758-417-6
Copyright
c
2020 by SCITEPRESS Science and Technology Publications, Lda. All rights reserved
543
2 RESEARCH QUESTIONS AND
METHOD
The traditional classroom education is not sufficient
for constantly evolving learning demands. M-
learning brings learning content to learners whereas
classroom training requires learners to go to learning
content. Challenges relate to learner engagement with
m-learning tools and services; how to motivate and
keep the learner connected to learning content
continuously?
The aim of this article is to describe the learner’s
emotional engagement factors to lifelong m-learning
applications with help of UX. The approach in this
study is based on a systematic literature review, user-
centered design, and qualitative analysis (Jabareen,
2009). We pursue to answer the following research
questions:
1. How m-learning user experience factors have
evolved in research between 2005-2017?
2. What are the potential emotional engagement
factors associated with lifelong learning?
3. What are the facets of emerging lifelong learning
services?
To answer the first research question, we
conducted a systematic literature review (SLR) which
analyses research on mobile learning user experience
in 2005-2017. We have utilized Kitchenham (2004)
guidelines on conducting systematic literature review
and Prisma reporting (Tricco et al., 2018) to report the
findings of the SLR and the search results. The
objective is to survey the scholarly articles, journals,
and conference proceedings relevant to m-learning
application design, usability, and user experience.
The main inclusion criteria in literature search were
as follows: articles that were published between
2005-2017, articles that were written in English, and
articles that focus in m-learning user experience. The
primary keywords / phrases which were used and
combined in the search were “mobile learning”,
“development framework”, “usability”, and “user
experience”. The process of the identifying the
emotional words in the SLR were as follows: first we
searched with the keywords in the selected journals
and conferences. If the article contains the emotional
words, then that article is selected for reading in
details. Next, we update the excel sheet which keep
tracts of the emotional words and the article details
such as journal name, publication year, and authors
details. For answering the research question 2, we
applied user centered design (UCD) (Norman &
Draper, 1986) method to design and develop an
application concept. In the UCD process, semi-
structured interviews were used for eliciting the
requirements. Finally, based on the findings of
research questions 1, 2 and related research we used
Jabareen’s (2009) qualitative method for building
conceptual frameworks to create a conceptual model
that presents the core facets of emerging lifelong
learning services.
3 RELATED RESEARCH
3.1 User Experience and m-Learning
A number of diverse definitions has been proposed
for UX. Nielsen and Norman (2015) defined UX as
the simplicity of a product, which is accompanied by
elegance, that users enjoy owning and using.
According to ISO (2010), UX is a “person’s
perceptions and responses that result from the use or
anticipated use of a product, system or service.”
Hassenzahl and Tractinsky (2006) defined three
facets of UX: beyond instrumental, emotion and
affect, and experiential. The beyond instrumental
facet mainly concerns humans’ non-functional needs
to achieve their goals, such as hedonic aspects that the
product or service fulfils. Hassenzahl and Tractinsky
(2006) suggested that the advancement of technology
has caused interactive products to become not only
useful and usable but also trendy and fashionable.
The UX research field has been divided into three
distinct eras (Dirin & Nieminen, 2017). The first era,
which took place during 2000–2006 was
characterized by technical approaches to UX. The
second era, which spanned 2006–2010, was defined
as the usability of mobile applications. Finally, the
third era, which commenced after 2010, focuses on
human responses and emotions as UX, where UX
arises from the direction of human responses and
emotions. Shen (2014) tackled the importance of UX
in m-learning through three priorities: (1) content,
which involves improving the quality of delivered
learning materials; (2) teaching and learning
processes, which involves live and synchronized
learning; and (3) learners themselves, which involves
detecting their emotional states during m-learning.
Recent advances in m-learning are aimed at
developing applications that are based on users’
emotional states, as indicated in the work of Kuderna-
Iulian et al., (2015). They developed a multimodal
monitoring tool capable of detecting the learner’s
behavior and emotional state. Furthermore, Zatarain-
Cabada et al., (2014) addressed emotional recognition
in their system for intelligent tutoring on Android-
CSEDU 2020 - 12th International Conference on Computer Supported Education
544
based mobile devices. These studies demonstrate that
the importance of emotional aspects of UX has
already captured the attention of m-learning
researchers.
3.2 Beyond Functionality and Usability
Mobile devices’ coexistence with learners as a
supportive tool for learning activities has also
changed learners’ expectations. Learners now seek a
multi-tasking medium that can carry out complex
instructions, as discussed regarding the second era of
M-learning UX, which was characterized by the
requirement to go beyond the device’s functionality
and applications. Learners’ objectives for using a
mobile device are more closely related to learning
outcomes than to the features and functionality of the
device and its applications. The usage of mobile
devices and applications is constantly evolving. For
instance, the concept of “gamification” (Huotari &
Hamari, 2012) is intended to motivate (Deterding,
2012) students to learn through playing games.
Hamari et al. (2014) demonstrated that gamification
delivers positive effects, although the effects greatly
depend on the context in which the gamification is
implemented. An example of this is the application of
Angry Birds in education (Rodrigues & Carvalho,
2013).
3.3 Definition of Lifelong Learning
The term lifelong learning has become popular in
research communities with the advancement of
technologies and accessibility of knowledge at any
time and place. This sounds like a m-learning
definition (Mostakhdemin-Hosseini & Tuimala,
2005) which overcomes the traditional education
constrain on content accessibility at any time any
places. UNESCO (Lee & Tom, 2011) has significant
impacts on the life learning over the last four
decades. There have been recommendations,
frameworks, and conceptual proposals on applying
mobile technologies for lifelong learning such as
Nordin et al.. Kay (2008) applied the concept of
personalized and pervasive computing to assist
learners in their learning throughout their lives. The
concept has also been promoted by the European
Commission (Field, 2010) and (Volles, 2016). The
term mobile lifelong learning refers to learning that
happens in a context where users pursue to develop
competence or update information. This definition
indicates that learning happens everywhere and can
happen continuously. There have been many
initiatives to anticipate solutions for lifelong learning,
such as Nordin et al.’s (2010) m-learning framework
that supports systematic lifelong learning experience
design. They explored the design factors that focused
on mobile environments, basing the factors on the
learning theories, mobile environment, m-learning
context, and learning experience. The term lifelong
learning also appears in artificial intelligence learning
algorithm design and development, such as lifelong
machine learning (Silver et al.2013), (Ruvolo &
Eaton, 2013) and (Chen & Liu, 2016). However, in
this article the focus is on lifelong learning from the
UX perspective.
3.4 Emotions and Feelings
The recognition of emotions and other affective
factors have become important in human-computer
interaction (Calvo, 2010). Emotional experiences are
feelings that inform people about the states and state
changes in their belief–desire systems (Reisenzein,
2009). In other words, people have various beliefs
and desires that they aim to fulfill (e.g., by engaging
in learning activities), their emotional experiences or
the emotions been met through the interaction with
their surroundings.
Emotions have a subjective, behavioral (arousal),
and physiological (bodily) components (Scherer,
2005) that must be analyzed separately (Dirin et al.,
2017). Emotions have direct effects on our physical
and mental health as well as our attention, memory,
learning, judgment, and decision-making for example
(Lerner et al. 2015). Therefore, by recognizing
emotions, arousing emotions, and regulating
emotions, we can properly adapt learning application
to match the learner’s emotion state.
3.5 Learning Awareness and Cognition
We define learning awareness as gaining of
knowledge and development of competence
whenever and wherever needs on the context and
environment where the knowledge is demanded.
Learning awareness is not a constrain in the
contemporary world where learning contents are
available anywhere and anytime. However,
acquiring knowledge for competence development in
a lifelong m-learning setting requires more than just
the availability of knowledge; intrinsic motivations
(Rainer Reisenzein, 2009) are essential in order to
engage the learner in lifelong learning activities that
are typically not governed or facilitated by a formal
education system. Intrinsic motivations according to
Ryan and Deci (2000) are the natural human tendency
to learn and adopt. In a virtual world, also the
Facets of Mobile Lifelong Learning Services
545
learner’s curiosity (Litman, 2005) raise awareness of
the learning needs and competence development.
Oudeyer et al. (Oudeyer, et al. 2016) findings
demonstrate that the curiosity, surprise, and the
experience of novelty lead to learning and memory
retentions.
Furthermore, learning cognition is important in
lifelong learning. Okrigwe (2010) states that the
cognitive view of learning depends on the
individual’s way of thinking, memorizing or solving
problems as their ways of learning and demonstrating
the knowledge are different. The cognitive learning
theory for multimedia learning, as Mayer (2014)
studied, has five cognitive processes: first, selecting
the proper words; second, selecting proper images;
third, organizing the selected words into coherent
verbal presentations; fourth, selecting the images into
coherent pictorial representations; and five, emerging
the pictorial and verbal representations with prior
knowledge. The cognitive load theory provides
guidelines to help in presentation of information so
that it encourages the learner to optimize their
learning based on their individual capacity since the
cognitive capacity of the working memory is limited
(de Jong, 2010).
3.6 Learning Content, Learning Media
and Tools
The way a lifelong learning system presents learning
contents impacts learners’ motivation to continue
learning. Social media, as Dabbagh and Kitsantas
(2012) stated, creates a personal learning
environment (PLE) which integrates formal and
informal learning that supports students’ self-
regulated learning. Furthermore, Balakrishanan and
Gan (2016) reveal that social media supports various
learning approaches, such as participatory,
collaborative, and independent learning. Dede (2009)
demonstrate that comprehensive and realistic
experiences engage learners in immersive interactive
digital learning media.
4 A LIFELONG M-LEARNING
APPLICATION CONCEPT
As an example of potential life lifelong m-learning
applications, we present the concept of a basketball
shooting application, which helps basketball players
and coaches learn and teach, respectively, how to
shoot efficiently (Figure 1). Learning awareness must
be based on a natural approach; in other words,
learning happens while doing, and here, learning
happens in the context of a basketball court. Through
the use of contemporary learning tools and media, this
can be accomplished without the need to learn a
frustrating theory lesson in a classroom.
Figure 1: Lifelong m-learning concept: basketball learning
application.
Every basketball player and coach know that the best
way to keep improving shooting is to track how
experts perform in comparison with the player. By
designing an application for a smartwatch that can be
worn while shooting, the player can input shot results
after every “spot” without having to leave the court to
write them down. The smartwatch application is
meant purely for inserting results, which are then
automatically synchronized to the smartphone
application, where the player can see advanced
statistics and graphs based on the information from
the watch. This application concept was designed and
developed in a user experience design course by a
group of students.
5 RESULTS
5.1 Emotional Factors in Lifelong
m-Learning
We identified emotional factors in lifelong m-
learning by going through the selected articles and
publications and categorized the findings in an Excel
document. Table 1 presents the journals and
conferences and the respective number of articles
identified for the analysis.
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546
Table 1: Source forums and publication counts.
No Journal / Conference Publication
Count
1 World Conference on Mobile
and Contextual Learning
(mLearn)
21
2 International Journal of
Interactive Mobile Technologies
(IJIM)
29
3 European Journal of Open
Distance and E-Learning
(EURODL)
4
5 International Journal of
Emerging Technologies in
Learning (JET)
9
6 International Journal of
Teaching and Learning in
Higher Education (IJTLHE)
3
7 Journal of Computer Assisted
Learning (JCAL)
17
8 Journal of Online Learning and
Teaching (JOLT)
3
9 Computers & Education. An
International Journal (Computer
& Education)
15
Total 102
We conclude the findings of the SLR in Figure 2
which presents the fluctuation of articles on emotion
factors that have been recognized for m-learning
applications to improve the user learning experience.
Figure 2: Number of articles identified in the literature
review that discuss emotional factors that improve the user
experience.
The findings indicate that already at the rise of m-
learning applications in 2005 the emotional user
experience factors have been recognized as important
in application design and development. The
development reached its peak point in 2011. The
fluctuations continue until 2017. The feelings of trust
and security were the researchers’ concerned already
during 2005-2007. As soon as m-learning
applications became more complex, the feelings of
excitement, empowerment, and effectiveness become
evident. In the following, the list of identified
emotional factors are presented:
Feeling of trust means “I do not lose my data”.
Kim and Moon (1998) identified that the feeling
of trust in systems with utility is considered an
important part of “emotional usability” .
Feeling of reliability translates to “redundancy,
overlapping functionality”. Wixom and Todd
(2005) identified that the information accuracy
and system reliability results user satisfaction
Feeling of security means “Others do not see my
data”, “My information will not be exposed to
others”, “I can do mistakes when learning
without fearing/being improperly monitored”.
The feeling of safety and security during early
childhood is a key to pleasurable learning
experience (Perry, 2017).
Feeling of empowerment means “The service
enables/persuades me to use my full capacity”,
and even “I can exceed my skills and abilities”.
Bradbury-Jones et al. (2011) identified that
empowerment is an important element in nursing
education for self-control and self-efficacy.
Feeling of being effective and efficient means
“The service helps me learn new knowledge/skill
efficiently and effectively”. Marksteiner et al.
(2019) demonstrate that student who do not feel
belonging has higher risk of dropping out of
school, or university and earning poor grade.
Feeling of excitement means “I am delighted
when using the service/app”. Reeve et al., (Reeve
et al. 1986) demonstrate that excitement has a
significant impact on the intrinsic motivation
5.2 Evaluation of the Basketball
Learning Application
The results of the emotional analysis of the basketball
learning application were acquired by the concept
developer group of four students at Haaga-Helia
University of Applied Sciences who evaluated the
usability of the application at the Media Lab. The
details of the emotional factors’ evaluation are
presented in Table 2. The table comprises the
assessed feelings and a description for each feeling in
the context of the basketball learning application.
Table 2 is the result of the concept designers’
feedback on the given evaluation form which the first
and third authors summarized. However, the actual
impact of these emotional factors on user experience
required additional studies with the real users and real
environment. Feelings of security, effectiveness, and
Facets of Mobile Lifelong Learning Services
547
Table 2: Emotional factors associated with the basketball
learning application.
Emotional factors
Trust:
Definition: I do not lose my data
Users’ thoughts and feelings: “I believe that my
information is saved automatically and can be accessed
reliably whenever I want from all my devices.”
Features: The device saves and backup the data
regularly in the device and cloud.
Excitement:
Definition: The service thrills me when I explore
unexpected features and functions
Users’ thoughts and feelings: “when I throw the ball I
can feel the new smart watch captures my shoot – and
other players recognize my watch, too. It makes me a
professional and dedicated player”
Features: Vibrations and bright blink when the shoot
has been recorded.
Empowerment:
Definition: The service enables/makes/persuades me to
use my full capacity. It allows for pushing boundaries
and offers easy editing and presentation in various
contexts.
Users’ thoughts and feelings: “I am able to follow up
my competence development myself and with my
peers. I feel that I have develop my techniques this
week better than before. The instance feedback keeps
my performance and progress to the maximum all the
time. ”
Features: The service presents positive steps to exceed
previous achievements and share the results with peers.
Effectiveness:
Definition: I can find all the necessary functions and
services. I can review my performance whenever is
needed
This is faster and more effective than the traditional
learning method. The information is retrievable
anytime, anywhere.
Features: I can trace my performance during, after and
while practicing with the different devices.
Security:
Definition: My personal information and data is secure
and no unauthorized third party may access the
information
The data are encrypted to ensure privacy, but it can still
be accessed by the creator easily.
Features: My information save in a secure
environment. I can access the information when I need
it.
empowerment are particularly evident. The feeling of
empowerment boosts the player’s learning and allows
the player to reach their full capacity. Effectiveness is
the feeling that emerges because the device allows the
user to obtain information without having to exert
much effort. Since retrieving information is less time
consuming, this allows for devoting more time to
learning. The feeling of security is addressed through
the provision of valid content to learners, through the
integrity of user data, and through the accessibility in
the context where the data is needed.
6 DISCUSSION
Learning happens in varying, even surprising,
locations and situations. Demands for lifelong
learning emphasize that learning may happen anytime
and anywhere. In addition to the fit to physical and
temporal surroundings, appropriateness of the
learning experience to the learner’s emotional context
also affects learning. We know that emotions have
powerful and predictable drives for our decision-
making (Lerner et al., 2015) and learning outcomes
(Trigwell et al., 2012). Trigwell et al. (2012)
demonstrated that the experience of positive emotions
and a deep approach result in higher achievement,
with negative emotions resulting in lower
achievement. Therefore, determining how to use
emotions effectively to ensure correct judgment is
important. Emotional decisions are often spontaneous
and fast. Emotions impact our cognitive ability; for
example, when the learner is emotionally under
stress, cognitive performance decreases. In the
following, we revisit the research questions and
summarize our answers to the questions.
How m-learning user experience factors have evolved
in research between 2005-2017?
We identified 102 articles that recommend or
explore user experience factors in m-learning
applications. Most of the emotional factors were
recommended by researchers after 2010, as Table 1
demonstrates. However, contributions specific to m-
learning applications are still vague as we do not yet
have clear emotional engagement guidelines for m-
learning application design and development. This is
also the definition of the m-learning that the learning
happens in smart phones or tablets. Therefore, the m-
learning emotional factors, which identified during
SLR also apply to lifelong learning. The case study
example can be interpreted as real lifelong learning
scenario.
What are the potential emotional engagement factors
associated with lifelong learning?
Lifelong learning has become a reality in
contemporary life. Therefore, investigating on the
motivational factors to engage learners has become
self-evident. Emotional engagement is a form of
motivational factor that encourages learners for a
continuous usage.
Our SLR revealed six emotional factors (i.e. trust,
reliability, excitement, empowerment, effectiveness
CSEDU 2020 - 12th International Conference on Computer Supported Education
548
and security) that previous studies have identified in
the context of m-learning. These feelings are
recognized to be important in m-learning and hence
applicable in lifelong learning application design and
development. It is obvious that these feelings are not
enough for robust lifelong learning. There are still
room for further research and study to identify
additional factors.
What are the facets of emerging lifelong learning
services?
UX in lifelong learning contributes to a synthesis
consisting of situated, emerging learning possibilities
that are enabled by pervasive, connected
technologies. Furthermore, in learning service
development, addressing emotions and feelings
complements the compilation of learning materials
with learning awareness and cognition, and the
learning tools and media. The awareness of the
learner’s learning profile and strategies (structures for
“lifelong learning”) enables them to turn emerging
situations into learning moments. Positive feelings
resulting from a motivating situation and context
boost learning outcomes and make it easier for the
learner to comprehend and recall the learned content
(see Figure 3).
Figure 3. Synthesis of elements contributing to emerging
lifelong learning situations.
Jabareen (2009) proposed that the conceptual
framework is the network of linked concepts.
Accordingly, we define the lifelong learning
conceptual model which has three facets. Lifelong
learning offerings must consist of the learning
awareness which may happen based on the learner’s
curiosities or other motivational factors. The learning
media and the methods provide means to convey
content to users. At top of these facets the emotions
and feelings ensure the learner’s engagement to the
lifelong learning offerings.
7 CONCLUSION AND FUTURE
WORK
Technology advancement and smart gadgets’
popularity along with availability of vast amounts of
knowledge have made lifelong learning a reality.
Moreover, lifelong learners’ emotional engagement
plays an important role in continuous use. Our
literature review revealed that emotional engagement
has been a concern of m-learning application
research. Therefore, in addition to usability user
engagement become more evident that’s why we have
seen more emotional factors being emphasis. The
main justification is that m-learning applications have
become more complex and have been capable to
deliver independent learning subjects. In addition to
emotional factors, learning awareness to trigger
learners plays an important role. Furthermore, the
learning content and how it is presented to users is
another facet of emerging lifelong m-learning
platforms.
As a future work we aim to identify more feelings
associated with lifelong m-learning and develop
sample applications to validate the findings in real
lifelong learning contexts.
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