Solving The Problem of Adaptive E-Learning By Using Social Networks

Int. J. Advanced Networking and Applications
Volume: 6 Issue: 1 Pages: 2184-2190 (2014) ISSN: 0975-0290
Solving The Problem of Adaptive
E-Learning By Using Social Networks
Mohammed Yaqub
Anbar , Iraq,
Hazem EI.Bakry,
A.M.Raid
Email:yaqubmoha@gmail.com
---------------------------------------------------------------------ABSTRACT------------------------------------------------------------
This paper propose an enhanced E-Learning Social Network Exploiting Approach focused around chart model and
clustering algorithm, which can consequently gathering dispersed e-learners with comparative premiums and make fitting
suggestions, which can at last upgrade the collective learning among comparable e-learners. Through closeness
revelation, trust weights overhaul and potential companions change, the algorithm actualized a programmed adjusted
trust association with progressively upgraded fulfillments.
Keywords: Relations, Adaptive E-Learning, Clustering , Social Network , E-learning , and Collaborative Learning
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Date of Submission: 02 June, 2014 Date of Acceptance: 10 July 2014
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1. INTRODUCTION
Throughout the last few decades, the nature of
training in numerous instructive organizations has
declined prompting inadmissible low scholastic
execution, large amount of useful lack of education,
developing populace of unemployable graduates.
Adapting never was limited to classrooms. The
changing sociotechnical connection offers a guarantee
of new open doors, and the feeling that by one means or
another things may be distinctive. Utilization of the
Internet and other developing innovations is spreading
in recurrence, time and space. Individuals and
associations wish to utilize innovation to help learning
look for speculations to casing their comprehension and
their advancement.
Learning is a dynamic transaction between individuals
as one individual teaches and an alternate learns . It is
an imputed experience on the grounds that people
investigate new zones of learning together in such a
path as to make a typical center and ideas. Additionally,
it is a typical encounter as understudy acquire the same
educated viewpoints of certain learning ranges.
E-Learning which breaks the traditional classroom
based learning mode enables distributed e-learners to
access various learning resources much more
convenient and flexible. However, it also brings
disadvantages due to distributed learning environment.
Thus, how to provide personalized learning content is of
high priority for e-learning applications. An effective
way is to group learners with similar interests into the
same community [1].
In the early beginnings of the Adaptive systems
development this new approach of software
individualization promised to improve human-computer
interaction considerably. Many frequently occurring
problems of usability and learn ability seemed to be
easily solved. However, even today, after elaborating
significantly the modeling techniques, it is not obvious
whether this promise has been kept, because only few
empirical evidence exists that supports this claim[2].
Adaptive e-Learning is a new approach that can make
an E-Learning system more effective by adapting the
presentation of information and overall linkage
structure to individual users in accordance with their
knowledge and behavior[3].
A social network is a structure formed by people and by
connections between people, with the connections
enabling interactions and exchange of information and
influence [4][5],Socio technical systems recognized
many years ago that organizations functioned most
effectively when their social and technological
networks were compatible. This is the case exactly with
e-Learning systems [6]. Social network analysis is a
research area that has received significant attention,
especially in the last several years. The correspondence
between real-world social relations and social media
ties has been confirmed on several occasions [7- 10].
In other hand, costs of digital devices, storage and
bandwidth have fallen, audio, video and text processing
has come to be used daily by people at home, at work
and in formal education. Internet usage has became
commonplace in the developed world and is growing
fast in developing countries see (Figure 1 , Figure 2)
("Internet Usage Statistics," 2011 and 2012). There are
still significant discrepancies in Internet penetration
rates but Africa is enjoying the greatest growth rate in
users 2000-2012 (from a low base), and Asia already
has the largest number of Internet users. This
widespread and growing number of Internet users offers

the possibility of local and global dialogue and sharing
of resources, subject to linguistic and socio-cultural
constraints.
Figure 1. Internet Usage Statistics for year 2011
Figure 2. Internet Usage Statistics for year 2012
2. RELATED WORK
Adaptive e-learning is often meant to be new or in an
early development stage[11].Computer-based learning
system are critized by many researchers for their
adaptability of teaching actions compared to rich tactic
and strategies employed by human expert teachers and
limited ranges [12] [13].
There are different types of online learning that is
individualized, but an adaptive e-learning system is
regarded as one of the most recent models. This system
tries to adapt to each individual by presenting learning
materials in accordance with one or several characteristics
of the student. The adaptive e-learning system needs to be
developed by considering that the conventional e-learning
systems are not capable of providing an individualized
learning; they present the same material for all students
[14].
General Architecture of adaptive e-learning , in this part,
we present various diagrams of application design for an
adaptive e-learning shown in (Figure 3). The objective is
to conceive a system which can model the description of
pedagogic resources and guide the learner in his
formation according to his assets and to the pedagogic
objective that is defined by the trainer. This pedagogic
objective presents the capacities that the learner must
have acquired at the end of the formation activity.
The Expert Space which relates to the modelization of
pedagogic resources to prepare them to be used by the
adapter. In Expert Space, nominally the teacher or the
expert, who seeks to integrate new resources in the base,
describes them by filling a form ,The Learner Space
performs the following jobs: it accommodates the
identifiers of a learner, selects his profile from the
Learners database and returns it to the adapter as well as
the goal of this formation. The adapter (adaptation
process) uses optimization algorithms to seek the optimal
strategy while selecting the courses in the resources base
and provides them to the user interface. The Learner
database contains the identifiers of the learner and his
knowledge or asset. As a result, the system provides an
optimal courses list to achieve the current goal by
applying the genetic algorithms to seek the intermediate
states [15].

Learner Interface Learner space
Learners
Data Base
Request = profile+
goal
Result =list
Adaptation
process
Resources
Data Base
Resource + form Modelisation
Process
Interface Expert
Expert Space
Figure 3. Structure of the adaptive e-learning system
Virtual Learning Environments sometimes called
learning management systems or managed learning
environment, create a controlled virtual learning space
where teachers and students interact, post and submit
homework, give and receive feedback from their peers,
and link to course resources and information.
Combining technology and education, VLEs provide
comprehensive course management tools and are often
used in distance education. Traditionally, VLEs were
simplistic and contained a lot of text, simple graphics,
and included the lecturer’s notes in an eBook format.
“Today, we have the ability to create very sophisticated
and complex interactive virtual environments,” that
include sound, video, and animation. These VLEs help
students and teachers interact and communicate in ways
previously not possible (Figure 4) shows Blackboard e-
learning framework which has many limitation in social
interaction and personalization [16].

Journal
s
Lectuer
s
E‐
Librarie
s
Tutorial
s
Figure 4. Blackboard E-learning Framework
Adaptive-based learning The objective of adaptive
based learning is to conceive a system which can model
the description of pedagogic resources and guide the
learner in his formation according to his assets and to
the pedagogic objective that is defined by the trainer,
This pedagogy objective presents the capacities that the
learner must have acquired at the end of the formation
activity [17][18]. Adaptive e-Learning systems would
be a good solution for better e-Learning[19].System
such Moodle use adaptive e-learning which creates the
 Interpret, evaluate and deploy the results.
The obtained results or model are interpreted
and used by the teacher for further actions. The
teacher can use the discovered information for
making decision about the students and the
Moodle activities of thecourse in order to
improve the students’ learning[23].
Project-Based Learning a strategy that encourages
students to explore a problem through driving questions
best possible learning experience for students by and authentic experiences, can be an excellent means to
a social constructivist end. PBL helps teachers blend
emulating the talents of great educators. This is
achieved by using technologies that adapt and shape
teaching to the needs of the individual student.
The process of applying rule mining over the Moodle
data consists of the same four steps as the general data
mining process [20]:
technology with hands-on materials to create
imaginative and challenging student activities [24].
Management Information System E-Learning tends to
revolutionize and manage the learning process [25]and
is divides in two types University Management
Information System and Learning Management
 Collect data. The LMS system
students and the usage and
is used by
interaction
System (LMS) is the software
administration of education. LMS
tracks courses in a catalogue,
that automates the
registers students,
records data from
information is stored in the database. We are
going to use the students’ usage data of the
Moodle system.
 Preprocess the data. The data are cleaned and
transformed into a mineable format. In order to
preprocess the Moodle data we used the
MySQL System Tray Monitor and
Administrator tools [21] and the Open DB
Preprocess task in the Weka Explorer [22].
 Apply association rule minin . The data
learners, and provides reports to management.
An LMS is typically designed to handle courses by
multiple publishers and providers. It usually doesn't
include its own authoring capabilities; instead, it
focuses on managing courses created by a variety of
other sources [26].
Global Collaboration takes such student engagement
and learning outside the walls–or virtual walls–of the
classroom and into the greater world. Learning
communities, such as those established by communities
or universities, provide a place for learners to pursue
mining algorithms are applied to discover and their interests, solve a problem, provide support, get
summarize knowledge of interest to the
teacher.
feedback, or otherwise connect with people who share
similar passions. Such constructivist interaction can be

scaffolded in a classroom environment to allow students
to work more independently and even help someone
else solve a problem [27].
3. PROPOSED FRAMEWORK
3.1 Proposed Framework
In order to overcome the problem of traditional In order
to overcome the problem of traditional e-learning or
adaptive e-learning, we proposed half breed framework
that satisfies the social e-learning framework however
with some new features or adaptive e-learning, we
proposed mixture framework that satisfies the social e-
learning framework yet with some new features.
Collaborative feature, each user (student, teacher) has
own sharing and chatting tool which introduce
availability. Semantic Support feature, each student or
teacher has supported with intelligent process which
suggest the closest friends. Agent feature, each agent in
the community holds a set of resources such (Profiles,
Friendship, Courses and Exams) which are rated by
proposed algorithm. (Figure 5) shows proposed social
e-learning framework.
To measure the nature of framework must first ensure
that framework satisfied 3th principles of connectivism.
Principles of connectivism are the accompanying:
• personality of connections with abnormal amount of
security.
• huge Capacity is needed for successful social learning
network.
• decision making is itself a learning process. picking
what you learn and who you learn.

Figure 5. Proposed Social E-learning Framework

2. Proposed Algorithms
Nodes which control our framework are actors such
(Student, Teacher and Posts or Courses). Every node
has one or more relations with other node. The strength
of relation is calculated by graph classification
techniques. (Figure 6) shows social e-learning concept
graph. We suppose case study of 4 students, 4 courses
and 4 teachers which I means number as (1,2,..n) and
cursors means relations and nodes S means Student, C
means Courses and T means Teachers.
S1 C1 T1
S2
C2 T2
S3 C3 T3
S4 C4 T4
Figure 6. The Graph of Social E-learning Concept
very Relationship between different nodes has strength number come from matrix of this relationship. Relations are
student's friends and favorite courses. With these relations, system can be determined which friend or course must be
suggested first. From (Figure 6), we can demonstrate the following matrices of relationships in order to classified friends
or courses and therefore enhance e-learning.
S1 S2 S3 S4
First, the friend relationship matrix =
Si1
S2
S3
S4
0 1 0 0
1 0 1 0
[ ]
0 1 0 0
0 0 0 0
Then from this matrix, we can conclude that S1 is friend of student S2 in our case study and S2 is friend of student S3,
and S3 will be the first suggested friend to S4because they subscribers in friendship of S3.
First, the favorite courses relationship matrix =
S1 S2 S3 S4
C1
1 0 1 0C2
C3 [1 1 0 1]0 1 1 0
1 0 1 0
Then from this matrix, we can conclude that S4has not any courses in our case study and will be the first suggested
courses is C2 because C2subscribers in friendship of S2 and S3.
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