Mobile Cloud Computing Solution for Dyslexic Students: Final Report

This report presents a comprehensive study on the application of mobile cloud computing to create an educational platform for dyslexic students. The research addresses the challenges dyslexic students face in traditional learning environments and proposes a cloud-based mobile application to provide specialized educational support. The report outlines the background, problems, and significance of the study, emphasizing the need for low-cost and accessible education. It reviews existing literature on cloud computing and its applications in education, followed by the proposed models for app development, implementation strategies, and evaluation methods. The study also discusses the limitations, such as access to smartphones and potential mobile addiction, and aims to develop an effective learning module. The primary goal is to offer an alternative teaching method tailored to the needs of dyslexic students, including those with difficulties in phonics, fluency, and spelling, by leveraging the advantages of cloud computing and mobile technology.

Running Head: MOBILE CLOUD COMPUTING
Charles Sturt University
FINAL REPORT
The mobile cloud computing helping dyslexia students in
study and learning purpose as students are not able to attend the
regular class like normal students
SUBMITTED BY: AASTHA DHAMI 11607127

1MOBILE CLOUD COMPUTING
Abstract
This research is entirely focused on the developing a cloud-based solution for dyslexic students
who are unable to cope up with regular learning classes. They need special help for education
and cloud computing can be used to develop an app that will be specially designed for
educational purposes. Cloud computing is considered to be one of the most significant and useful
inventions in the field of information and communication technology. The technology of cloud
computing is helpful enough in providing a proper powerful unit of processing that is mainly
shared by various computers in order to analyze data for making reliable decisions. The paper
mentions that Cloud-based mobile cloud computing is mainly developed for treating the patients
using proper application of healthcare so that proper comparison is made between the tools with
the tools that are utilized by the students of dyslexia. It is found that this project has a number of
drawbacks as well as limitations that are mainly discussed in detail in this section. To develop a
suitable development to address the main problem in this research, two different models have
been proposed. However, there are advantages and disadvantages of both the models that may
provide an obstacle for the development of the app for the dyslexic students. In order to
overcome this model, it is identified that the system is mainly added within the element of cloud
which helps in powerful processing for analyzing the data that is given by the student in order to
make the issues in context with the student’s point of view.

2MOBILE CLOUD COMPUTING
Table of Contents
1. Introduction..................................................................................................................................3
1.1 Background............................................................................................................................3
1.2 Problems................................................................................................................................3
1.3 Significance of the Study.......................................................................................................4
1.4 Purpose and Aims..................................................................................................................5
2. Literature Review........................................................................................................................6
3. Proposed Model.........................................................................................................................12
First Best Model........................................................................................................................12
Second Best Solution.................................................................................................................15
4. Implementation of the Model....................................................................................................18
5. Evaluation of Implementation...................................................................................................22
6. Conclusion.................................................................................................................................25
References......................................................................................................................................27

3MOBILE CLOUD COMPUTING
1. Introduction
1.1 Background
Cloud computing refers to computing activities done in the virtual interface instead of
physical hardware interface. Due to its wide range of uses, cloud computing is now being used in
various fields including business, education, healthcare, logistics, statistics and others. The main
advantage of cloud computing is that it does not require any physical space and can run on itself
on the virtual interface if they are programmed correctly (Alghabban, Salama & Altalhi, 2016).
The user only requires an internet connection to access cloud computing data. Another advantage
is that cloud computing is that it is extremely efficient in data management and removes all
possibilities of errors that may occur due to human operations. In this particular research, cloud
computing is used as a platform for aiding dyslexic students. It has found that cloud computing
can be utilized for this purpose by developing a mobile app that will specially design for aiding
dyslexic children.
1.2 Problems
The main problems to be addressed in this research are listed below.
Use of Cloud Computing in Education – Previously, various researchers have suggested
various techniques of using cloud computing services in education. However, cloud computing
has not yet been utilized extensively in education sector due to the security issues it faces. Cloud
computing is still only selectively used in education like online examinations, tutorial videos and
others (Alizadeh et al., 2016). With the development of several security tools for cloud
computing, it is becoming for feasible for use in the education sector that includes future online

4MOBILE CLOUD COMPUTING
interactive classrooms, total digitalization of examinations, special educational mobile apps and
others.
Dyslexia Students – This research is entirely focused on the developing a cloud-based
solution for dyslexic students who are unable to cope up with regular learning classes. They need
special help for education and cloud computing can be used to develop an app that will be
specially designed for educational purposes. The details of the development are discussed later in
the assignment.
Low-Cost Education – Another issue that can be addressed using this research is a
reduction of cost of education. The current educational systems in most of the countries are
extremely high owing to the number of teaching faculties appointed and the extensive use of
technology. The cost of education is further increased for dyslexic students as they require
special attention and teaching methods (Hossain, 2017). However, it has been found that in the
rural areas of various countries, such high standards of education are not available and as a
result, the dyslexic students of these areas do not receive sufficient education. Hence, this
research is aimed to solve such problems as well.
1.3 Significance of the Study
The significance of this study is that it covers a mostly unexplored side of cloud
computing i.e. its application in the education of the dyslexic students. However, there are some
gaps that arise from the limitation of this particular study. The limitations and gaps are explained
as follows.
Access – Since the target of this research is to develop a cloud-based mobile for aiding
the dyslexic students, smartphones will be required for accessing the app. However, in most of

5MOBILE CLOUD COMPUTING
the rural areas, people generally do not have any access or afford smartphones. As a result, the
target objective of the development of the app will not be successful.
Addiction – Another main gap of the proposed solution is the mobile addiction that is
very common in the children nowadays. Once a student gets access to a smartphone, it is highly
likely that he will become addicted to the phone by playing games and using other applications.
Hence, this issue must be addressed before developing the educational app for the dyslexic
students.
1.4 Aims and Purpose
The aims of this research are as follows.
 To research on existing works based on application of cloud computing in various
fields including education
 To develop a suitable model for addressing the identified problems
 To prepare an implementation plan for the proposed model
The purpose of this research is to find out the best solutions that can assist the dyslexic
students to learn and grow, the students suffering from the disease have problems regarding
phonics, have problems regarding phonics and fluency. The students suffer to read and spell
words, also suffer to manage surroundings and conditions. The dyslexia students, unlike regular
students, need trained tutor and reading specialist and academic therapist to constantly monitor
them and constantly help them in learning. Unlike the regular students, these students take more
time to learn and need constant support and encouragement from the academic therapist and
from their parents.

6MOBILE CLOUD COMPUTING
The students suffering from dyslexia can learn in quick times and in a better way
especially in small groups rather than in a whole classroom. The positive instructional
interactions (PIIs) is provided. The pre-teaching is also encouraged that means the students are
taught the lessons beforehand visually using toys and later the formal teaching is offered so that
they learn the lessons quickly. The students are also offered lessons so that they can learn
spelling rules and the pronunciation strategies.
2. Literature Review
In this research, the model for the proposed cloud-based platform development for
supporting the dyslexic students has been explored. They do not need to consider some other
media for correspondence. According to Islam et al. (2017), cloud-based learning can be suitable
for teaching disabled students who need special attention instead of regular teaching methods.
Hyperactivity disorder of some disabled and dyslexic students is not favourable for the learning
condition. Keeping in mind the end goal to moderate the issue, it is important to use certain
instruments and propelled innovation. For this specific, ponder material the versatile computing
is embraced by the students. Considering the propelled innovation named as portable innovation,
the disabled and dyslexic students are expected to be benefitted from the cloud-based platform
for education. After the fruitful finish of the investigation with the assistance of versatile
computing, a propelled learning methodology could be created with the cloud computing
platform. Simpson (2005) gathered information from various surveys and analytic studies and
created study inquiries to comprehend the issues or difficulties of customary learning with the
goal to propose a cloud-based mobile learning platform for the dyslexic and disabled students.

7MOBILE CLOUD COMPUTING
It is identified that both information technology as well as internet are providing number
of solutions to numerous health issues as well as problems related to communication and
transport. Information communication technology has become one of the huge platforms that
help in managing various issues like dyslexia. According to Alghabban, Salama and Altalhi,
(2016), information technology assists in creating number of advantages which are used for the
welfare of human beings. The invention in the field of information technology is considered as
one of the most significant inventions of cloud computing. The technology of cloud computing
is helpful enough in providing proper powerful unit of processing that is mainly shared by
various computers in order to analyze data for making reliable decisions. The paper mentions
that Cloud-based mobile cloud computing is mainly developed for treating the patients using
proper application of healthcare so that proper comparison is made between the tools with the
tools that are utilized by the students of dyslexia. It is opined by Kollorz et al. (2016) that proper
integration is also done between various smart home applications as well as mobile cloud
computing. The smartphone application is mainly implied in order to form wireless network as
well as connectivity that further assist in forming proper deployment of the procedures (Liang,
2016). The system is quite helpful in serving various opportunities of the learners. The thought
identified with the utilization of cloud computing is used in this exploration for tending to
training issues of the dyslexic students. This idea can be utilized for the progression of a few
biomedical instruments. The idea identified with the use of portable information is talked about
for the determination of the Dyslexic patients. This will make a few new highlights which can be
truly useful for the dyslexic patients. Further, the idea identified with the interpersonal
organization framework for hard of hearing and visually impaired patients is talked about. As per
Zhu et al. (2016), this idea can be utilized as a part of the progression of the framework for the

8MOBILE CLOUD COMPUTING
assistance of the disabled students. Since the development of cloud computing, researchers have
been trying to utilize it in the educational sector in order to aid the students, especially those who
require special attention instead of regular teaching processes. Hence, the goal was to develop a
cloud-based education platform that could be used an alternative teaching method for the
disabled children. Since then, it has been found that this cloud-based alternative can also be used
as an alternative teaching platform for the dyslexic students who require special attention for
learning. Cloud computing can be used for developing an m-learning platform for smartphones.
This m-learning platform will contain learning modules for the dyslexic students who can be
taught by the teachers using those modules. This m-learning platform is supported by the cloud
computing database that will manage all the data and the modules. Giving instruction for
dyslexic students is a test (van Deursen, Ben Allouch & Ruijter, 2016). These students require an
exceptional approach contrasted with ordinary students. They are known to have constrained
capacity to focus and effectively diverted. One way data sharing where an educator is the
wellspring of data is not reasonable for them. A learning module that can reproduce their
advantage and catch their consideration is expected to guarantee a powerful learning session. AR
permits the virtual protest and certifiable to coincide, permitting the question of concentrate, for
example, nuclear structure to be enlivened, therefore, breaking the limit of room and time. This
improves the students’ comprehension and memory. Yang & Leung (2016) said that cloud
computing innovation empowers an area autonomous computing where the computing assets,
software, and information are put away in the cloud. The research additionally demonstrates that
utilization of augmented reality (AR) in instruction gets positive criticism from students and
educators. Students are energized on the intelligent part of AR and the flexibility for them to
investigate the subject of concentrate inside a protected situation. Then again positive reactions

9MOBILE CLOUD COMPUTING
are gotten from instructors on the viability of AR-based module in supporting learning sessions.
This gives more proficient data sharing among worldwide web clients.
Pee et al. (2016) recreated a framework created by specialists that depended on the
hypothesis of arranged conduct utilizing a huge specimen of some college students. The
framework featured the noteworthy components that impact students' thoughtfulness regarding
receive m-learning, which are disposed of, a subjective standard, and saw behavioural control. In
any case, there is a potential predisposition in this examination as it concentrated just on students
and in this manner educators were not considered. In addition, the example was limited to one
college and along these lines, the investigation's discoveries cannot be summed up. Some
different analysts have considered the issue of the high speculation of the current conventional
area based learning systems (Intranet) and the support being finished by instructive foundations.
The creators proposed a theoretical framework for pervasive learning by coordinating portable
applications with cloud benefits and empowering access by means of the college's private cloud.
According to Liang (2016), the students can get to the substance either by a portable application
or a web benefit that mentors can transfer. A few scientists tended to the issue of stage reliance
of existing versatile applications. They built up a versatile application cross-stage framework
with respect to working systems, equipment (handheld gadgets), and web programs in view of
CC for training in higher establishments in some countries. The proposed framework is anything
but difficult to learn; besides, it underpins cross-stage and cross-gadget utilize and the client gets
to the most recent rendition of the application promptly without upgrading. Be that as it may,
there are a few downsides, for example, the way that the JQuery portable application is moderate
on mobiles incorporates a few bugs, and has restricted capacities. Managerial staff deals with all
the framework administrations. Nevertheless, this framework gives a predetermined number of

10MOBILE CLOUD COMPUTING
instructive administrations. It does not consider the social and joint effort viewpoints, for
example, gatherings and dialogue gatherings. According to the works of Lo'ai et al. (2016), the
current learning administration systems are risky in that they are just in light of a PC domain
without supporting remote gadgets; besides, there is an absence of instructive assets. However,
this proposed system has a few disadvantages, including constrained info ability and handling
power, the absence of memory limit and assets, a little-estimated screen, and no approval. A few
analysts examined whether students' and instructors' recognition with respect to learning are
certain or negative. They likewise inspected regardless of whether they are prepared to utilize
portable advances for learning purposes. They built up a site that incorporates the meaning of m-
learning, its preferences and inconveniences, and valuable connections for branches. The point of
this framework is to upgrade the accessibility of learning by blending separation learning and
existing conventional learning systems with m-learning (a half and half model) notwithstanding
utilizing a CC worldview. They presented the Educational Software as a Service idea (ESaaS),
which is a type of CC that has the instructive software in the cloud and gives such software. The
outcomes demonstrated that while students and educators need to utilize versatile innovation in
instruction, their ability levels are lacking (Islam et al., 2017). However, the creators in this
investigation did not cover every one of the recipients of m-learning. A few specialists advanced
self-coordinated learning by giving hypothesis, substance, and self-practices by means of m-
learning asset for understudies and researched the utilization of cell phones in learning. The
creator built up m-learning site with seven pages: the landing page, an input page with
connections to valuable sites, and five pages identified with various learning units. The learning
materials were bolstered with content, recordings, introductions, and tests. Despite the fact that
the proposed site reflected empowering self-course and engagement of understudies, it didn't

11MOBILE CLOUD COMPUTING
found on an academic approach because of the analyst's innovation confinements. The tests were
additionally extremely basic with no inherent criticism; besides, no intelligent liveliness or social
as well as synergistic means were incorporated.

12MOBILE CLOUD COMPUTING
Integrated Course Content
The virtual classrooms
iCohere feature model
The archives of the recorded programs recorded
Live Chat and Discussion Boards
Community for peer learning
Smart Classrooms
3. Proposed Model
First Best Model- iCohere feature model
Fig 1: iCohere feature model
(Source: Kraft et al., 2015)

13MOBILE CLOUD COMPUTING
iCohere is an online classroom program specially designed for the students suffering
from dyslexia, the model above shows the six benefits that are provided by iCohere to help the
dyslexia students to learn and grow. The reading specialist and academic therapist offers a wide
range of quality content materials that can assist the students suffering from dyslexia can get
deeper learning facilities. The dyslexia students like the regular contents can have similar access
to the teachers’ teaching materials. However, the study materials are made more elaborated for
the dyslexia students (Johnson et al., 2014). iCohere also caters archives of recorded programs.
The dyslexia students tend to be slow learner that is why the recorded lecture programs have
been prepared, the students can have the opportunity to access the materials again and again, the
students can access the videos anytime, can pause the video. The virtual classroom concept from
iCohere can provide the opportunities to interact with their instructors more, the students can
clear doubts, can ask questions and can get answers (Kraft et al., 2015). The Live Chat
encourages two way communications between the dyslexia students and the academic instructors
that pave the learning opportunity of the students. iCohere also arranges for a peer learning
community where dyslexia students can gather and can learn and grow all together, that can ease
the learning process as well and can help the instructors. The smart classrooms can help the
students as well. The instructors can explain 3D models and can use digital blackboard due to
smart classroom that can facilitate the students.
It is found that this project has a number of drawbacks as well as limitations that are
mainly discussed in detail in this section. The iCohere feature model is very much expensive; the
parents of dyslexia students sometimes cannot afford the iCohere training. Besides the students
sometimes find the technology complicated and feature heavy. The students generally struggle
while reading and the iCohere programs sometimes fail to deliver the purpose. Another problem

14MOBILE CLOUD COMPUTING
that is identified with this structure is that it can be utilized for determining the relationship that
exists between the different limitations of the model (Kraft et al., 2015). It is quite unable to
provide proper two-sided communications as it is quite compulsory in resolving the problems
which are mainly associated with the students. The main advantage that is associated with the
creation of this model is quite beneficial for the patients of dyslexia. However, in this case, the
patients are unable to provide the issues which are associated with his or her reading skill or
pronunciation (Johnson et al., 2014). The other significant problem related with this flowchart is
that it cannot make the system advanced in terms of feedback as well as accuracy. The problem
that is associated with the system is that it does not ask feedback from the students. The students
are mainly cable of getting proper idea about the objectives that are generally reflected on the
screen however they are not able to convey their problems properly to the system (Pee et al.,
2017). In order to get a proper model, it is quite important to focus on the student as well as on
the issues that are mainly associated with the student. It must be provided to the specific system
in order to understand the problems as well as issues of the student for understanding the
paragraph as well as letters within a paragraph. The main issue is that they are not capable of
differentiating between the characters of the same type which generally look the same. The
disadvantage that is mainly associated with calculations as well as numbers cannot be generally
asked by the model for getting proper information. The problem is that the students are not
completely getting the idea when they do not have proper information about the sound or
identification of character (Jayapandian, 2014). There is a number of problems that are mainly
associated with the system which is not also beneficial for the guardians who mainly help than
children in understanding about the problems (Helland, 2016). Therefore a new system is

15MOBILE CLOUD COMPUTING
ChromaGen takes input via lens
ChromaGen lens device starts ChromaGen lens scan for characters
The lens stores the character
recently scanned
The ChromaGen lens
ask for identification
END
Output sent to student
Cloud computing
Process what students are viewing
Chromagen lens’ inputs and what
students are viewing get compared
Same?
NO
YES
needed that is generally helpful for the student in understanding the letters as well as characters
in quite a specific way.
Second Best Solution
Fig 2: The ChromaGen model

16MOBILE CLOUD COMPUTING
(Source: Elsherif, 2016, pp-1-7)
The dyslexia is a disorder which can be characterized by the following symptoms-
blurring (non-refractive), movement or jumping of words or letters, the words tend to sink on the
whiteboard of the page, ‘shimmering’ on the page, the unpredicted pattern formed in between the
lines and the words by the spaces. The students have reported that they have seen ‘rivers’
flowing through a page or flowing through texts. They have reported that they have seen
individuals falling off the page.
For every individual the visual information travels from the eye to the brain in a natural
manner while in case of dyslexia students the visual information travels from eye to brain in a
relatively quick manner so that needs to be slowed down. The coloured lens or better say the
haloscopic filters from ChromaGen can solve the problem (Gomez & Ojala, 2014). Basically, the
haloscopic filters are of varying lengths and the filters have the capability to slow down the
transfer of information and in this, the filters can synchronize characters in such a manner that
the brain can easily detect the characters.
The procedure of applying ChromaGen lenses is less hectic and less painful. A pair of
frames is applied on the face. At first, the student is seated on a chair and asked to read
characters in front without any lens and in this way, the rate of reading and words per minute are
getting calculated (Alghabban, Salama & Altalhi, 2017). Then the filters are applied one by one
to the student, the students choose the lens which is most comfortable and the most suited one for
reading the characters, the test is repeated one without lens and one with lens and thus the
students suffering from dyslexia can learn to read characters. After that, they are monitored and

17MOBILE CLOUD COMPUTING
this follow-up typically lasts 6 weeks to 3 months, gradually the students start to recover and the
students have reported they have been benefitted by the ChromaGen lens.
The ChromaGen lens works in a specific manner. At first, it scans the character which the
students view and take inputs via the lens. The ChromaGen lens consists of a register where the
input gets stored. Then ChromaGen asks for identification. The cloud technology assists in
processing the data viewed by the students, the character or the data the students are viewing get
compared to the input stored in ChromaGen registers if matches then ChromaGen can assure that
the particular student is recovering. Via cloud computing, the input stored in the ChromaGen
register is transformed into visual information and gets transmitted to the brain. In this way, the
brain can get to know the correct word.
The new model is quite advanced in terms of making the student understand about the
various numbers as well as characters for identification in a quite effective way. Hence, this
model will be extremely suitable for teaching the dyslexic students (Gomez & Ojala, 2014). In
this given model, a cloud computing platform is added, which is utilized for making the system
much more advanced in terms of its overall accuracy and reliability. The main advantage of
making a student understand the overall value of the project is that the learning of the student can
be further enhanced in a broader aspect. The problem in the previous model is that the students
are not capable of making identification or differentiation of various characters (Alghabban,
Salama & Altalhi, 2017). The main problem that is associated with it is that it does not ask the
student about the feedback. It is identified that the student is able to get only the idea about the
various objects which are mainly reflected in the screen however they are not able to convey the
problems problem to the system.

18MOBILE CLOUD COMPUTING
In order to overcome this model, it is identified that the system is mainly added within
the element of cloud which helps in powerful processing for analyzing the data that is given by
the student in order to make the issues in context with the student’s point of view. The
introduction of cloud computing in the new model is helpful in creating a platform for the
student which helps in verifying the objects that are reflected in the display system of the
computers. The main advantage that is associated with the system helps in making it much more
suitable for the students so that they can properly identify the problem in context to various
standards.
This project is mainly based on various applications of cloud computing that further helps
the patients of dyslexia. It is identified that the patients of dyslexic faces number of issues that
are mainly associated with reading as well as the writing of various characters. Cloud computing
helps in providing a number of features including a powerful processing unit, privacy as well as
the security of data. These features are generally utilized for helping the patients with the
introduction of various characters. The patients mainly face a lot of problems that including
confronting the issues as well as problems that they are facing to the doctors and as a result they
get irritated. In order to resolve the problem of the student, several features are provided in order
to create the proper centralized system. Another significant thing is interface design which is
found to be attractive as well as helpful for the students. In addition to this, the project assists in
analyzing the various roles of cloud computing in order to help the patients.
4. Implementation of the Model
The iCohere feature mode is not useful as it lacks the basic thing, it is unable to root out
the reading problem which the patients or the students suffer from dyslexia. iCohere offers

19MOBILE CLOUD COMPUTING
multiple features multiple facilities to the dyslexia students but still, the students require a lot of
time to learn the materials. The implication of iCohere applications is quite expensive. Not every
institute can afford to implement the iCohere applications at their premises. The parents even can
pay the fees for their children (Kuila et al., 2016). The students find somewhat difficult to cope
up with the technology, the model classrooms. Though digital classroom has been offered to
them, still their reading problem persists, thus this model is not used for the effective treatment
of dyslexia.
Again the ChromaGen lens has side effects. The lens is not hundred percent accurate, the
lens sometimes fails to decipher the language, sometimes fail to decipher one’s handwriting. The
battery needs to be recharged, otherwise, the lens will not work (Alizadeh et al., 2016). The lens
uses the cloud computing so there are chances the hackers can attack and hack the sensitive
information of the students, the hackers can even track what they are viewing thus the students’
security and privacy can get breached. Because of all these factors, ChromaGen usage is not
usable.
With a specific end goal to build up a system it is especially important to distinguish the
components of customary and current instruction system for the stock hypothesis. In the wake of
getting affirmation, the advancement speculations could be created productively. Some of the
researchers have gathered essential and auxiliary information from various assets and broke
down that data to build up the propelled cloud-based learning platform for the students especially
the disabled who require special teaching methods rather than normal methods. With the
assistance of cloud-based m-learning platform, the requirements of special teaching for dyslexic
students can be fulfilled. On the off chance that the classification is recognized properly then the
improvement of the propelled system will turn out to be considerably less demanding from the

20MOBILE CLOUD COMPUTING
system approach. After the distinguishing proof of conventional approach, just the designers will
have the capacity to send the advanced cloud-based approach for the cripple students. Due to the
absence of learning instruments and innovations, a large portion of the students is confronting
significant difficulties. With a specific end goal to relieve the mistakes of conventional
coursework, versatile based cloud computing innovation is particularly useful. The learner
utilizes mobile learning in order to learn from their place and thus the learners need to go to
various education centres on daily basis. It is identified that server must be accessed properly by
the user whenever required. It is stated by Hossain (2017) that it generally helps in serving
proper virtual server to the different users. Under a proper understanding of the applications, the
user goes through effective online communication. It is identified that the system of automation
is generally helpful in providing proper accurate as well as necessary required components to the
authors. This significant application is helpful in minimizing the various errors of the system. It
is stated by Alizadeh et al., (2016) that uses of proper monitoring approaches, as well as sensor
nodes, are helpful in detection. The security system is quite beneficial in developing a secure
relationship between the client and the server which will further be helpful in giving lower cost
as well as lower power system to various consumers (Kuila et al., 2016). The solution will be
capable of delivering a secured cloud-based server to different consumers. The various roles of
smart health are done appropriately as the system has identified various types of migration
problems.
According to Zhu et al., (2016), the different types of equipment, as well as machines, are
generally needed for treating patients and which would further assists in integrating the treatment
without wireless connectivity. However, some issues related to the physical presence are needed
as network error can create a number of process disruption for treating as well as monitoring

21MOBILE CLOUD COMPUTING
patients. On the other hand, it is opined by Islam et al., (2017) that development of proper
cloudlet based mobile cloud system is utilized for the treatment of the patients in various
healthcare organizations. In addition to this, it is found that integration of both mobile clouds
computing as well as Smartphone applications using the network structure for treating patients is
quite advantageous. For developing a system it is very much important to identify various factors
of current as well as traditional education system for the theory of inventory. It is identified that
with the help of the proper cloud-based system, it is found that the decision that helps in making
errors can be resolved as well as minimized. According to Pee et al., (2016), after proper
implementation of the system, it is quite necessary to confirm that the system is quite beneficial
from the various learning perspective. After getting proper confirmation, it is found that
appropriate innovation theories can be easily developed. It is stated by Kuila et al., (2016) that
the critics associated with the research paper have generally collected both secondary as well as
primary data from various resources. It is identified that the information helps in developing
proper as well as advanced learning approach for both the normal as well as disabled students.
The implementation of Orton-Gillingham can prove to be fruitful and this approach is
used widely all over the world for the treatment of dyslexia. Samuel Torrey Orton and Anna
Gillingham have initiated the model with the objective of mitigating the difficulties the dyslexia
students face associated with spelling, reading and writing (Pee et al., 2016). The model looks
promising so far and it will take a leap in advancing dyslexia students’ career and life. Moreover,
the approach has found to be fruitful for the students who have difficulty with mathematics.

22MOBILE CLOUD COMPUTING
Diagnostic and Prescriptive
Language basis
Orton-Gillingham model
Explicit and Direct
Multisensory
Cumulative, structured and sequential as well as flexible
Cognitive
Flexible
Emotionally Sound
5. Evaluation of Implementation
Fig 3: Orton-Gillingham model
(Source: Pang et al., 2015)

23MOBILE CLOUD COMPUTING
Orton-Gillingham is the instructional approach widely used all over the world, the
initiative has been successful and the students have preferred this approach compared to other
methods for the treatment of dyslexia. It is a powerful and effective tool having great flexibility,
depth and breadth. The principles of this approach have been built in such a way that the students
can receive instruction according to their requirements (Unesco, 2017). The National Reading
Panel, a United States government body formed in the year 1997 with the objective of applying
effective features for teaching students how to read. The principles Orton-Gillingham are-
i. The Diagnostic and Prescriptive-The instructor always try to find out how a student
learns and based on that the instructor imposes learning and teaching strategies. The instructors
prepare lessons keeping every student’s strength and capabilities in mind (Pang et al., 2015). The
other two mentioned models were focused on all students in general but here, in this case, Orton-
Gillingham is exceptional. Therefore, this model is more flexible and easily acceptable.
ii. Explicit and Direct- The dyslexia students can get access to the study materials that
are direct in nature and explicit in nature. The students never find any materials irrelevant that
has not been taught to them before (Mulfari et al., 2015). The materials are taught in a sequential
manner so that the students can learn with ease.
iii. Language basis- The Orton-Gillingham approach has been made on the basis of the
technologies of studying language and the teaching language, the method understands the human
language, understands the way every individual learns the language (Alghabban, Salama &
Altalhi, 2016). This method also focuses on the mechanisms associated with learning.
iv. Multisensory- The approach of Orton-Gillingham is somewhat multisensory. The
sessions associated are all action-oriented. The kinesthetic elements, the auditory elements and

24MOBILE CLOUD COMPUTING
the visual elements integrate all together and facilitate the learning process. The dyslexia
students are taught to spell words alongside reading words appropriately (Beacham & Duncan,
2017). In this scenario, the Orton-Gillingham is far ahead of other conventional phonics
instruction.
v. Cumulative, structured and sequential as well as flexible- The elements of the
language like consonants, vowels, digraphs, blends and diphthongs are imparted to the students
in a sequential manner. The Orton-Gillingham learning model is programmed in such a way that
the students can learn new things alongside can revise the old lessons (Alghabban, Salama &
Altalhi, 2016). The different aspects of the language like reading comprehension, sentence
structure, sentence composition and vocabulary are imparted to the students in a structured and
cumulative manner.
vi. Cognitive- Because of the Orton-Gillingham, methodology, the students can learn the
history of English language and language specifications (Van, Ben Allouch & Ruijter, 2016).
Because of constant monitoring and caring from the instructors the students can learn the English
knowledge and can acquire the reading competency and the writing competency as early as
possible.
vii. Flexible- The teachers and the instructors are always ready to help the students, each
and every student is different and also their learning abilities, the teachers follow different
learning patterns for the students, thus making the entire thing looks flexible (Bahari, 2016).
viii. Emotionally sound- Orton-Gillingham approach can give the students suffering from
dyslexia confidence to learn and grow, thus this approach can prove to be fruitful.

25MOBILE CLOUD COMPUTING
6. Conclusion
This project is mainly based on various applications of cloud computing that further helps
the patients of dyslexia. Previously, various researchers have suggested various techniques of
using cloud computing services in education. However, cloud computing has not yet been
utilized extensively in education sector due to the security issues it faces. Cloud computing is
still only selectively used in education like online examinations, tutorial videos and others. With
the development of several security tools for cloud computing, it is becoming for feasible for use
in the education sector that includes future online interactive classrooms, total digitalization of
examinations, special educational mobile apps and others. It is identified that the patients of
dyslexic faces number of issues that are mainly associated with reading as well as the writing of
various characters. Cloud computing helps in providing a number of features that include a
powerful processing unit, privacy as well as the security of data that are mainly used by the
users. These features are generally utilized for helping the patients with the introduction of
various characters. The patients mainly face a lot of problems that including confronting the
issues as well as problems that they are facing to the doctors and as a result they get irritated. In
order to resolve the problem of the student, several features are provided in order to create the
proper centralized system. Another significant thing is interface design which is found to be
attractive as well as helpful for the students. In addition to this, the project assists in analyzing
the various roles of cloud computing in order to help the patients. For developing a system it is
very much important to identify various factors of current as well as traditional education system
for the theory of inventory. It is identified that with the help of the proper cloud-based system, it
is found that the decision that helps in making errors can be resolved as well as minimized. After
proper implementation of the system, it is quite necessary to confirm that the system is quite

26MOBILE CLOUD COMPUTING
beneficial from the various learning perspective. After getting proper confirmation, it is found
that appropriate innovation theories can be easily developed.

27MOBILE CLOUD COMPUTING
References
Alghabban, W. G., Salama, R. M., & Altalhi, A. (2016). Mobile Cloud Computing and M-
Learning: State of Art.
Alizadeh, M., Abolfazli, S., Zamani, M., Baharun, S., & Sakurai, K. (Authentication in mobile
cloud computing: A survey. Journal of Network and Computer Applications, 61, 59-80.
(2016).
Alghabban, W. G., Salama, R. M., & Altalhi, A. M-Learning: Effective Framework for Dyslexic
Students Based on Mobile Cloud Computing Technology.
Alizadeh, M., Abolfazli, S., Zamani, M., Baharun, S., & Sakurai, K. (2016). Authentication in
mobile cloud computing: A survey. Journal of Network and Computer Applications, 61,
59-80.
Bahari, S. F. S. M. (2016). A Review of Learning Courseware for Children with Learning
Disabilities in Malaysia.
Benmarrakchi, F., El Kafi, J., Elhore, A., & Haie, S. (2016). Exploring the use of the ICT in
supporting dyslexic students’ preferred learning styles: A preliminary
evaluation. Education and Information Technologies, 1-19.
Daud, S. M., & Abas, H. (2013, December). 'Dyslexia Baca'Mobile App--The Learning
Ecosystem for Dyslexic Children. In Advanced Computer Science Applications and
Technologies (ACSAT), 2013 International Conference on(pp. 412-416). IEEE.

28MOBILE CLOUD COMPUTING
Kollorz, E., Penne J., Hornegger J. and Barke, A. (2008) "Gesture recognition with a Time of
flight camera," Int. J. Intell. Syst. Technol. Appl., pp. 334-343.
Elsherif, T. B., (2016), Towards M-LearningEffective Tool to Improve Education for Dyslexic
Students, International Journal of Engineering and Innovative Technology (IJEIT), 5
(9),pp.1-7
Salama, R. M., & Altalhi, A. (2016). Mobile Cloud Computing and M-Learning: State of Art.
Hossain, M. S. (2017). Cloud-supported cyber–physical localization framework for patients
monitoring. IEEE Systems Journal, 11(1), 118-
127.http:www.medgadget.com/2013/05/leica-3d-surgical-microscopes-with-truevision
technology.html
Islam, M. M., Razzaque, M. A., Hassan, M. M., Nagy, W., & Song, B. (2017). Mobile Cloud-
Based Big Healthcare Data Processing in Smart Cities. IEEE Access.
Islam, M. M., Razzaque, M. A., Hassan, M. M., Nagy, W., & Song, B. Mobile Cloud-Based Big
Healthcare Data Processing in Smart Cities. IEEE Access. (2017).
Kuila, S., Shridhar, S., Patel, C., & Iyengar, N. C. S. (2016). Cloud Computing Security by
Using Mobile OTP and an Encryption Algorithm for Hospital Management. Journal of
Computer and Mathematical Sciences, 7(11), 558-565.
Kuila, S., Shridhar, S., Patel, C., & Iyengar, N. C. S. (2016). Cloud Computing Security by
Using Mobile OTP and an Encryption Algorithm for Hospital Management. Journal of
Computer and Mathematical Sciences, 7(11), 558-565

29MOBILE CLOUD COMPUTING
Liang, P. C. (2016). Cost-effective design of real-time home healthcare telemonitoring based on
mobile cloud computing (Doctoral dissertation, University of Surrey (United Kingdom)).
Lo'ai, A. T., Bakhader, W., Mehmood, R., & Song, H. (2016, December). Cloudlet-based Mobile
Cloud Computing for Healthcare Applications. InGlobal Communications Conference
(GLOBECOM), 2016 IEEE (pp. 1-6). IEEE.
National Institute of Neurological Disorders and Stroke, “Dyslexia Information Page,” 2011.
[Online]. Available: http://www.ninds.nih.gov/disorders/dyslexia/dyslexia.htm.
[Accessed: 03-Jul-2015].
Pang, L., Chen, C. J., Teh, C. S., & Anding, P. N. (2015). Online Learning for Individuals with
Dyslexia: A.
Pee, N. C., Leong, P. H., Othman, M. A., Sulaiman, H. A., Othman, M. F. I., & Rahim, Y. A.
(2016). DycScreen—Cross-Platform Dyslexia Screening Test for Malaysian Children
Through Hybrid Applications. In Advanced Computer and Communication Engineering
Technology (pp. 1083-1091). Springer, Cham.
R. C. Simpson, "Smart wheelchairs: A literature review," Journal of Rehabilitation Research
andDevelopment, vol. 42, pp. 423-36, 2005.
Unesco (2017). Accessible ICTs and Personalized Learning for Students with Disabilities
Retrieved 17 August 2017, from
http://www.unesco.org/fileadmin/MULTIMEDIA/HQ/CI/CI/pdf/accessible_ict_personali
zed_learning_2012%20.pdf.

30MOBILE CLOUD COMPUTING
van Deursen, A. J., Ben Allouch, S., & Ruijter, L. P. (2016). Tablet use in primary education:
Adoption hurdles and attitude determinants. Education and information
technologies, 21(5), 971-990.
van Deursen, A. J., Ben Allouch, S., & Ruijter, L. P. (2016). Tablet use in primary education:
Adoption hurdles and attitude determinants. Education and information technologies,
21(5), 971-990.
Yang, L. T., & Leung, V. C. (2016). A novel sensory data processing framework to integrate
sensor networks with mobile cloud. IEEE Systems Journal, 10(3), 1125-1136.
Zhu, C., Wang, H., Liu, X., Shu, L., Yang, L. T., & Leung, V. C. (2016). A novel sensory data
processing framework to integrate sensor networks with mobile cloud. IEEE Systems
Journal, 10(3), 1125-1136.