Ijcet 06 09_003

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International Journal of Computer Engineering & Technology (IJCET)
Volume 6, Issue 9, Sep 2015, pp. 21-31, Article ID: IJCET_06_09_003
Available online at
http://www.iaeme.com/IJCET/issues.asp?JType=IJCET&VType=6&IType=9
ISSN Print: 0976-6367 and ISSN Online: 0976–6375
© IAEME Publication
___________________________________________________________________________
A MODELING LEARNER APPROACH IN A
COMPUTING ENVIRONMENT FOR HUMAN
LEARNING BASED ON ONTOLOGY
Adil KORCHI
Laboratory of Signals, Systems and Components
Faculty of Science and Technology,
University Sidi Mohamed Ben Abdellah, Fez, Morocco
Najiba EL AMRANI EL IDRISSI
Professor in Laboratory of Signals, Systems and Components
Faculty of Science and Technology,
University Sidi Mohamed Ben Abdellah, Fez, Morocco
Adil JEGHAL
LIIAN, Department of InformaticsFaculty of Science Dhar-Mahraz
University Sidi Mohamed Ben Abdellah,
P.B 1796 Atlas-Fez, Morocco
Lahcen OUGHDIR
LIMAO, Department of Mathematics, Physics and Informatics
Polydisciplinary Faculty -Taza
University of Sidi Mohamed Ben Abdellah, Faculty of Taza, Morocco
Fayçal MESSAOUDI
Laboratoryof research and Management,
Université Sidi Mohamed Ben Abdellah, Fez, Morocco
Laboratory of Mathématiques, Signalsand computer.
University of Sidi Mohamed Ben Abdellah, Fez, Morocco
ABSTRACT
This work is in the field of technology for computing environment for human
learning (CEHL). The inflexible nature of these environments must be adapted to
learners and their profiles in order to gain suppleness, adaptation and
individualization of learning. So they can be an effective tool for representation and
consideration of the learner’s knowledge and skills. This new learning technique
imposes new requirements and constraints to establish representations through which
learner modeling becomes possible. We present our learner modeling approach built

A Modeling Learner Approach In A Computing Environment For Human Learning Based On
Ontology
upon an ontology. It is based on an accurate description of learners and their profiles
made of their behaviors, knowledge, skills, interactions and designs.
Key words: CEHL, Ontology, Learner, learner profile, pedagogical scenario,
pedagogical activity.
Cite this Article: Adil Korchi, Najiba El Amrani El Idrissi Adil Jeghal, Lahcen
Oughdir and Fayçal Messaoudi. A Modeling Learner Approach In A Computing
Environment For Human Learning Based On Ontology. International Journal of
Computer Engineering and Technology, 6(9), 2015, pp. 21-31.
http://www.iaeme.com/IJCET/issues.asp?JType=IJCET&VType=6&IType=9
1. INTRODUCTION
CEHL is a computer environment designed to promote human learning, that is to say the
construction of learner’s knowledge.
The learner must be placed at the heart of the educational situation to facilitate his
integration into the learning process. To get there, the CEHL must focus more on the learner’s
profile which consists of a set of information interpreted and which concerned the learner
himself/herself and are collected from several activities related to very specific learning
scenarios. Several studies [1], [2], [3] were conducted to propose models for representing
information concerning the learner such as : knowledge, design, skills, behavior, interactions
With the emergence of the Semantic Web, the CEHL researchers began using ontologies in
their research to master the learning-environment relationship. [4, 5, 6]
In this article we aim to define the terms related to learner’s modeling to describe the
proposed learning ontology which includes all the modeling elements. This ontology is
characterized by a structured set of terms, concepts, sub concepts, semantic relationships and
instances representing the learner’s area to reach a design that can allow us to model the
"learner’s profile" whatever his/her tendencies and preferences are.
2. STATE OF THE ART
2.1. Ontology in CEHL
The use of ontology in the model of e-learning system is an interesting solution. An ontology
gathers concepts that represent the knowledge of a field in a formal and explicit specification.
SNAE [7] introduces an ontology for e-learning process from the construction of learning
objects online for administration tasks.
Gasevic and Hatala [8] allow users to formulate queries to retrieve specific pedagogical
resources. Moreover, they respect the LOM norm on the annotation and indexing pedagogical
resources within their ontology called "target ontology."
You can use the ontology to represent people (learners, tutors, ..) or pedagogical resources.
It can even be used to represent the concepts of a learning situation.
2.1. Ontologies and knowledge representation
"Ontology is an explicit specification of a conceptualization" [Gruber 93].
Building an ontology can be done after the phase of conceptualization which consist of
identifying, within a corpus, specific knowledge to the field of knowledge to represent. N.
Guarino [9] considers ontologies as partial and formal specification of a conceptualization.

Adil Korchi, Najiba El Amrani El Idrissi, Adil Jeghal, Lahcen Oughdir and Fayçal Messaoudi
Therefore it is necessary to be able to build a first semi-formal modeling, partially coherent,
corresponding to a semi formalized conceptualization. This is called conceptual ontology, semi-
formal, and the specification process is called ontologization.
In all cases, it is necessary to translate this ontology in a formal and operational language of
knowledge representation in order to use it in a computer.
The target language must allow the representation of different types of knowledge
(knowledge terminology, facts, rules and constraints) and the manipulation of this knowledge
through appropriate mechanisms to the operational objective of the designed system. This
translation process is called operationalization. A knowledge base contains knowledge used in a
system knowledge base. This knowledge is formalized and mechanisms allow to manage the
knowledge base to view or to add.[10]
The need to have a learner knowledge representation has led researchers to attempt to induce a
model of learner dynamically built and based on a set of learner data such as behavior. To do
this, various problems are to be solved: First, the problem of choosing a representation to store
data of the learner, constituting his/her knowledge model then, the realization of mechanism to
initialize and update this model throughout the interaction with the system, and finally the
implementation of the interpretation process of this model to guide the related decision-making
procedures and the solution adopted for one determines very significantly how to handle the
other two. [Bruillard, 1997]
2.3. Modeling learner
To be effective, it is essential that computer human learning environments have sufficient
information about the learner, in particular learning abilities, knowledge, gaps,etc. This
approach is called "The learner model".
The purpose of the learner model is to provide a complete description of all the aspects of
the learner’s behavior.
So modeling the learner is to structure his/her data that represents the state of his knowledge
in a given field.
Hazardous models have been developed in order to get good predictions on the performance
of learners on certain tasks, but they did not provide the knowledge state of the model learner.
Modeling is the process that not only analyses the learner-information but also his/her
exchanges with the learning environment to estimate their level of knowledge in a given field.
This modeling can be achieved without problems. According to several researchers, the
constraints of modeling learner are mainly related to collecting precise information of the
learner that we want to model. There was then, the step of choosing a relevant formalism of
representation of this information. Finally, we must develop processes that build model learner.
[11]
Modeling systems are distinguished by the following criteria: [12]
 The means used to store information on the learner,
 Construction methods applied in preparing the learner model,
 The use made of this information.
Synthetically, modeling the learning means to:
Know information about its courses.
Gather information about his/her knowledge, skill, behavior and interaction.

Ontology
Indeed, when a learner is in a learning situation in an online environment, it must have
sufficient data of this actor to be able to guide him effectively in their learning situation because
the learner plays a central role in the learning process.
In this article, we use the two terms “The Learning Model” and “The learner’s profile” to
refer to the information we have about the learner when modeling him/her.
The learner model shows how we can represent the knowledge of the learner. The learner
profile is composed of the following:
 Learning who is no other than the user using a learning system to learn.
 Profile is the set of information about a given individual in a given context.
We will be interested first in the "Learning Profile". In our article, we define it as a set of
information relevant to adapt learning to behavior, knowledge, skills, interactions, and to the
learner conception. In our schema, the profile will be considered as concept that will be
semantically related to the following three concepts: Learning - Educational Activities –
Educational Assistance. These three concepts will be developed in order to get all their sub
concepts, semantic relations and their instances that will be integrated in the proposed ontology.
3. DESCRIPTION OF THE PROPOSED LEARNER ONTOLOGY
Ontology is originally a specialty of philosophy. This term is entered in the vocabulary of
cognitive science for engineering which means "an explicit specification of a
conceptualization." Sander et al. show how an ontological modeling facilitates the
transmission of knowledge through a conceptual model. The assumption of these authors is
robust. The acquisition of the domain of knowledge passes through the construction of a
conceptual model at the learner which turns to ontology [13].
Developing an ontology means that we must define a set of data and their structure so that
they will be used by other programs. Ontologies and knowledge bases (developed using
ontologies) are used as data by problem solving methods, domains independent applications
and software manufacturers. For example, in this article we develop the learner ontology,
learner profiles and educational contents. This ontology can be used as the basis for a range of
applications for effective online learning.
Building ontology is characterized by five elements: Concepts, Relations, the functions,
and Axioms Instances. We describe in this section the aspects related to the implementation of
our ontological model:
3.1. The Learner
We have developed a learner model according to the Capacity that can develop the learner
and his/her cognitive level in the CEHL systems.
Figure 1 outlines the proposed learner model, it consists of:

Figure 1. Developed learner ontology
3.1.1. The personal data
Is a part of the Learner concept. They contain general information about the learner, such as
name, surname, age, gender.
3.1.2. Type
It is a data which provides information about the type of learner: Divergent, Convergent,
Assimilator or Running. Many researchers focused on learners and styles with which they
wish to learn. This research has shown that we tend to teach based on our own learning style.
But, if the learner has a different learning style than ours, he/she will have difficulty receiving
information.
The diverge learner has a keen sense of observation: he/she is clever to perceive an object or
problem from different angles so that the convergent learner prefers to practice his/her ideas and
theories, solve problems and make decisions.
The assimilative learner is qualified to reorganize logically varied information. He prefers
the theory on practice while the executive learner is concrete, active, methodical, realistic and
implements practical experience and is personally involved in new experiences with a
challenge.
3.1.3. The cognitive level of the learner
It is connected by a semantic relation to the concept "Learner" and generates the three levels
namely; beginner, intermediate and advanced.
The beginner learner always needs to understand what is expected from him to resolve the
problem. For a student with an average level of knowledge, only the accompaniment and
guidance are enough for him (in case of error) to find the solutionhimself/herself, whereas the
advanced learner can find the solution to problems presented to him by himself/herself.
3.1.4. The Degree setting
The Degree setting which is a property in this part of the ontology in «Level-Learner»
concept. It tells us about the level of the learner.

Ontology
In our ontology, a beginner learner has three levels namely; Level 1, Level 2 and Level 3.
It is the same for intermediate and advanced levels.
Indeed, a beginner learner can have a general knowledge in a given field (for example in
geometry). If the test proposed by our ontology detects that the learner is a beginner, he will be
classed in one of the three proposed levels of the beginning level.
3.2. Learner Profile
Learners profiles allow to provide the learning system pertinent information about the learner.
These profiles have a very important role in all CEHL. Our learner profiling process
consists of five key components that are semantically related to the learner profile, which are:
 Behavior : It is the relationship that the learner must develop with his/her environment for the
success of his/her pedagogical activities. Behavior in our case concerns the motivation,
autonomy, attention, responsibility, mind-opening and curiosity of the learner.
 Knowledge : This is the cognitive background of the learner. It can be general, theoretical or
practical.
 Skills : Each learner admits strengths related to his/her skills. This may affect the sense of
contact, creativity, speed and logic of understanding and problem solving.
 Interaction : The learner is an integral part of the interaction, otherwise he would not be a
learner. It is the exchange that can have a learner with a learning environment. It may be long,
medium or fast.
 Conception : Learning is not a process of transmission but question’s transformation of initial
ideas, the usual ways of learners thinking. In this transformation process, our proposal on the
learner’s conception may be limited or incorrect to reach a new concept of learning.

Figure 2 Developed ontology of learner profile
3.3. Pedagogical activity
Figure 3 gives a synthetic scheme
Before starting a pedagogical activity, a test is required to evaluate the knowledge level of the
learner. In this context, and as a first step, we propose a set of questions related to knowledge
of the desired activity. Then, a level check is established in order to offer the learner a suitable
activity according to his/her level and profile in the learning process.
Figure 3 Developed ontology of pedagogical activity
The pretest of the concept "Pedagogical Activity" brings us directly to the sub-Level
“Learner level” of the concept “Learner”.
Once the level of the learner is validated, various learning methods will be proposed to
him/her such as:
 Learning with lessons, tutorials, directed works, construction works, projects realization.
 Learning with demonstrative or interactive video lessons.
The variable "Type" refers to the method of learning which can be "free or assisted"
For example: the learner may be assisted in a practical works sequence or can achieve it
himself/herself.
3.4. Pedagogical Assistance
Figure 4 gives an overview. The aim of this concept is to provide pedagogical assistance
adapted in a CEHL related to pedagogical content chosen by the learner. Those involved in

Ontology
this operation are: the tutors and pedagogical content that has a direct connection into our
ontology with the “Pedagogical Activity” concept, where each pedagogical activity is assisted
by a tutor who can be an assistant, a doctor, a trainer or a supervisor.
Figure 4 gives an overview. The aim of this concept is to provide pedagogical assistance
adapted in a CEHL related to pedagogical content chosen by the learner. Those involved in
this operation are: the tutors and pedagogical content that has a direct connection into our
ontology with the “Pedagogical Activity” concept, where each pedagogical activity is assisted
by a tutor who can be an assistant, a doctor, a trainer or a supervisor.
Figure 4 Developed ontology of pedagogical assistance
The educational content is linked to the concept-pedagogical activity by a semantic
relationship to facilitate the use and access to our ontology.
FULL DIAGRAM OF THE PROPOSED ONTOLOGY
Our ontology consists of 4 concepts that give rise to sub concepts and semantic relations as
shown in figure 5.

Figure 5 Developed learner ontologie

Ontology
4. CONCLUSION AND PROSPECT
Access to relevant information tailored to the needs and context of the learner is a real
challenge. New learner modeling approaches, based on ontology, will know without
doubt a better impact than expert systems because of the detailed description of
learner profiles.
Our work contributes to the learners modeling of in a CEHL based on ontology.
A modelization that is essential to design a new generation of CEHL that may evolve
by placing the learner at the heart of the pedagogical situation in accordance with
his/her behavior, knowledge, skills etc.
This preliminary work has helped to build a learner ontology that will later
incorporate a CEHL to concretize the design of computer applications using
ontologies that supports learners in all their states in the areas of learning within the
CEHL.
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