In the past decade, technology has grown exponentially, especially the speed of the Internet and mobile technology have reached its peak it seems. This technology advancement also gives its impact to all the areas especially in the education sector. Researchers have to be interested in investigating how these technologies can be exploited for educational purposes aiming to enhance learning experiences. Subsequently, this has prompt an exploration slant which is ordinarily alluded to as Mobile Learning (M-Learning) in which specialists endeavors have meant to disseminate fitting learning encounters to learners considering their own flexibility needs, the universal usage of portable advances and the accessibility of data whenever � anyplace. By and by, m-learning is still in its start and extraordinary endeavors should be done as such as to explore the potential outcomes of educational outlook change from the conventional on-estimate fits-all illuminating ways to deal with a versatile and customized discovering that can be circulated by means of portable creations. This paper, presents the suitability and need of mobile learning facility in Shinas College of Technology(SHCT) and also presents the framework for implementing m-learning in SHCT.

1. Integrated Intelligent Research (IIR) International Journal of Business Intelligents
Volume: 06 Issue: 02, December 2017, Page No.34-37
ISSN: 2278-2400
34
An Analysis of Mobile Learning
Implementation in Shinas College of
Technology (SHCT)
R.Madhubala1
, A.Akila2
1
Ph.D. Scholar, Department of Computer Science, Vels University, Chennai, India
2
Asst. Professor, Department of Computer Science, Vels University, Chennai, India
Email: balamadh@gmail.com, akila.scs@velsuniv.ac.in
Abstract - In the past decade, technology has grown
exponentially, especially the speed of the Internet and
mobile technology have reached its peak it seems.
This technology advancement also gives its impact to
all the areas especially in the education sector.
Researchers have to be interested in investigating how
these technologies can be exploited for educational
purposes aiming to enhance learning experiences.
Subsequently, this has prompt an exploration slant
which is ordinarily alluded to as Mobile Learning (M-
Learning) in which specialists endeavors have meant
to disseminate fitting learning encounters to learners
considering their own flexibility needs, the universal
usage of portable advances and the accessibility of
data whenever – anyplace. By and by, m-learning is
still in its start and extraordinary endeavors should be
done as such as to explore the potential outcomes of
educational outlook change from the conventional on-
estimate fits-all illuminating ways to deal with a
versatile and customized discovering that can be
circulated by means of portable creations. This paper,
presents the suitability and need of mobile learning
faciltity in Shinas College of Technology(SHCT) and
also presents the framework for implemeting m-
learning in SHCT.
Keyword: M-Learning, Context, Adapatation,
Learning through mobile, Ubiquitous Learning
I. INTRODUCTION
Rising progression in the field of portable innovation
has prepared for mobile learning. Mobile learning
alters the old learning process. Mobile learning is
defined as use of handheld devices such as PDA,
Mobile, Laptop and tablet technologies in teaching
and learning process. Fundamental component m-
leaning are learner, teacher, content, environment and
assessment as shown in the figure [1]. The key
benefits and characteristics of mobile leaning are as
follows.
Benefits of M-Learning [3][4]
 Students can learn the subjects anywhere, any
time and place restriction
 Along with classroom based learning, students
can continue his/her learning along with peers
and teacher outside the class room.
 Effective access of the learning contents in on-
demand fashion.
 Practice and sharing of knowledge through
activities with help of peers and experts.
 Allow to acquire more practical knowledge
immediately.
Figure 1: The basic elements of m-leaning [6]
Encourage learners to participate more actively in the
learning process by engaging them to authentic and
situated learning embedded in real-life context
Characteristics of Mobile Learning [5]
 Ubiquitous and on Demand: Ubiquitous means,
which is present everywhere. Hence, it should be
accessible regardless of time and location and
capable of delivering the required content at any
point of need.
 Bit Sized: The educational content should be
relatively short in duration as it is used mostly at
places having environment causing a lot of
distraction.
 Blended: It is very rarely used as only platform to
deliver education. Normally, it complements
other more resourceful modes of content delivery
such as clinical and e-learning.
 Can be Collaborative: Promote collaborative
learning as much as possible
 Types of Mobile Applications [8]
 Electronic materials for mobile learning basically
are the same applications which can be developed
in three different ways –

2. Integrated Intelligent Research (IIR) International Journal of Business Intelligents
Volume: 06 Issue: 02, December 2017, Page No.34-37
ISSN: 2278-2400
35
 Native apps are installed on the device. Native
apps must be compatible with specific platform
and programming languages that are supported
by this platform
 Web apps are used through the browser and can
support multiple Operating System but the
problem is that it cannot effectively access phone
hardware, like sensors which are the main
component for interaction with users.
 Hybrids can access the hardware and have the
benefit of simpler data updates. The user can
download application to the device and the
application can access the API, but the content
comes from the web.
 The paper is structured as follows, section 2, and
presents the literature review. Research issues are
heighted in section 3. The proposed work is
presented in section 4. Finally the conclusion.
II. LITERATURE REVIEW
This section presents the overview of existing effort in
the arena of mobile learning and points out important
findings and issues. David Parsons et.al[9], proposed
a Theoretical Framework for mobile learning
applications and also pointed out the key elements for
mobile learning applications. Nauris et.al[10],
proposed a methodology for learning content
development for all kind of mobile devices and also
pointed out the key elements of content development,
device based issues and design process.
Economides [11], presented the Framework for
designers and developers of m-learning system and
highlighted the importance of context aware learning
and fours states of context aware learning. Zhao.ed.al
[12], presents an efficient design for custom made
revised contents and it proposes some algorithms to
create adaptive and intelligent contents for learners
and highlights the context-aware mobile learning
system which can increase the learning efficiency and
interest
Sergio Gómez et.al [13] exhibited a setting mindful
versatile and client made portable learning
framework, specifically the Units of Learning
portable Player (UoLmP) (a). alterations to the
interconnection of the learning exercises (specifically,
the learning stream) (b). alterations to the instructive
assets, apparatuses and administrations that help the
learning exercises. The imperative finding is
alterations can encourage understudies to effectively
total the learning exercises of an instructive situation.
III. RESEARCH ISSUES IN M-LEARNING
UI Design
Mobile phones experience the hostile effects of little
screens, prohibitive information strategies and
restricted battery life. Hence, the interface outline for
M-learning administrations must address clients'
issues without over-burdening them with pointless
complexity, working too gradually or consuming
excessive power.
Contextualized Learning
Context can be information about Identities (Users),
Activity, Learner Profile, Time, Localization,
Environment etc. Existing mobile learning services
act as passive components rather than active
components that can be embedded with context
awareness mechanisms and the present approaches for
service discovery neglect contextual information on
the surrounding environment [14]
Adaptive and Personalized Learning
In E-Learning, the learning content has perceived high
failure rates as learners become gradually dissatisfied
with subjects that do not engage them [2]. Adaptive
learning solutions have been used as possible
approaches to address this dissatisfaction by trying to
personalize the learning experience for the student.
This learner consent can help to improve learner
satisfaction with the learning experience. The
significant concern is lack of context modeling and
cognitive procedures that allow combination of
various contextual features for better personalization
[14].
IV. PROPOSED WORK
Before moving into the proposed work, some research
survey questions are analyzed below. The questions
focused on the feasibility of mobile leaning
implementation in Shinas College of technology. The
data samples collected from 52 students in various
levels and the data are presented below.
Q1. Mobile Operation System:
Most of the students use android mobiles & IOS and a
few of them use windows operating system. This
question will help us to design the applications based
on the platforms used by the users. The figure 2 show
the data distribution.
Figure 2: Types of Mobile (OS)
0
10
20
30
40
Types of Mobile (OS)
No of Users

3. Integrated Intelligent Research (IIR) International Journal of Business Intelligents
Volume: 06 Issue: 02, December 2017, Page No.34-37
ISSN: 2278-2400
36
Q2. Mobile Screen Size:
The most attractive mobile screen size is 4 to 5
however, some students like a bigger screen (>5) from
the available branded mobile models. The figure 3
shows the data distribution.
Figure 3: Mobile Screen Size
Q3: Internet Technology Support
Currently students are using 4G technology. So, data
access speed is comparatively higher than 3G and 2G
technologies which were used earlier. The figure 4
shows the data distribution.
Figure 4: Internet Technology Support
Q4: Number of hours usage per day
The data distribution figure 5 given below, shows
that most of the students are spending more and more
time on their mobiles. This question helps to
understand the users’ interest on mobile applications
Figure 5: Usage per day in hours
Q5: Application Interest
This question concentrates on the best way to outline
the learning content with a particular aim to
accomplish or achieve the understudy's advantage.
The figure 6 given below shows that students are very
much interested in chatting and the social media.
Figure 6: Application Interest
From the above analysis, learning becomes easier if
we present the learning content in view of the user
preference through mobile based on the curriculum.
Based on the survey above and the earlier work in the
arena of mobile learning, the proposed system is a
hybrid app which uses the mobile and server. It must
have the following components. The figure 7 shows
the proposed framework for SHCT.
Data Repository: The data repository consists of
Learners Personal and Activities data, device profile
and environment details of the mobile users.
Adaptation Engine: The main work of an adaptation
engine is to generate the content for the learners based
on their repository and current environment, device
status. The adaptation engine has two levels
1. System Centric
2. Learner Centric
Context Sensing and Acquisition: This component
identifies the mobile and the user environment in
order to generate the required content.
Service Processing Engine: This component is used to
present the content to users based on the device size
and other features.
Figure 7: Proposed M-Learning framework for SHCT
0
10
20
30
40
50
<=5 >5
Mobile Screen Size
Users
0
50
2G 3G 4G
Internet Technology
Support
Users
0
20
40
60
< 1 hr >1hr
Usage per day
Users
0
20
40
60
Application Interst
Users

4. Integrated Intelligent Research (IIR) International Journal of Business Intelligents
Volume: 06 Issue: 02, December 2017, Page No.34-37
ISSN: 2278-2400
37
V. CONCLUSION
This paper presents the overview of m-learning and
highlights its features, characteristics and m-learning.
Pointed out research issues will help the new
researcher to understand the domain well. Also, it
presents the suitability or feasibility analysis for m-
learning in SHCT. The result shows, m-learning is
highly suitable for SHCT students and finally,
presents the proposed framework for m-learning in
SHCT.
References
[1] Alsaadat.K(2009), Mobile Learning and
university teaching, International Conf. on
Education and New Learning Technologies,
Barcelona, Spain.
[2] K. Frankola,(2001),Why online learners dropout,
in Workforce, pp. 53-63.
[3] Satyanarayanan, M., (2010). Mobile computing:
the next decade. In: Proc. 1st ACM Workshop on
Mobile Cloud Computing &Services: Social
Networks and Beyond (MCS ’10), pp. 5:1–5:6.
[4] Jeng, Y.-L., Wu, T.-T., Huang, Y.-M., Tan, Q.,
Yang, S.J.H., (2010). Educational Technology &
Society 13 (3), 3–11.
[5] Shivesh,T., and Lokendra, K.T.,(2016),
Sequential Rule Mining in M-Learning Domain,
IJCA, vol .134, no.3.
[6] Fezile,O., Nadire,C.(2011), Basic Elements and
Characteristics of Mobile Learning, Procedia
social and Behavioral Sciences, pp. 937-942.
Elsevier.
[7] Chikh, A.(2014), Journal of King Saud
University – Computer and Information Sciences,
Vol. 26, p. 29–40.
[8] David Parsons (2007) , A Design Requirement
Framework for Mobile Learning Environment,
Journal of Computers, Vol. 2. No.4
[9] Nauris Paulins, Irina Arhipova, Signe Balina
(2015), Procedia Computer Science 43, pp.147-
153, Science Direct.
[10]Anastasios A. Economides (2008), Context aware
Mobile Learning, The Open Knowledge Society.
A Computer Science and Information Systems
Manifesto. Vol. 19. pp 213-220, Springer.
[11]Xinyou ZHAO, Fumihiko ANMA, Toshie
NINOMIYA, Toshio OKAMOTO (2008) ,
Personalized Adaptive Content System for
Context-Aware Mobile Learning, IJCSNS
International Journal of Computer Science and
Network Security, VOL.8 No.8.
[12]Sergio Gómeza, Panagiotis Zervasb, c,,
Demetrios G. Sampsonb, c, Ramón Fabregata
(2014), Journal of King Saud University –
Computer and Information Sciences, Vol. 26,pp.
47–61, Elsevier.
[13]Rachid Benlamri and Xiaoyun Zhang.(2014 ),
Human-centric Computing and Information
Sciences, pp.4-12. Springer Journal.