Enhancing the Intelligence of Web Tutoring Systems using a
Multi-Entry Based Open Learner Model
Ali A. Al-Jadaa, Abdallatif S Abu-Issa, Wasel T. Ghanem, Mohammed S. Hussein
Faculty of Engineering and Technology
Birzeit University, Palestine
ali.ps@live.com,abuissa@birzeit.edu,ghanem@birzeit.edu,mhussein@birzeit.edu
ABSTRACT
e accuracy of learner model is the heart of any Intelligent Tu-
toring System (ITS). More intelligence in the ITS needs a more
accurate learner model. In the earlier versions of ITS, the student
must submit a test before using the ITS. at test was used to build
the student model, which contains information about the knowl-
edge of the student, his/her misconceptions, preferences and other
related issues. However, this method doesn’t work efficiently for
school students, because one test canfit accurately evaluate their
knowledge and misconceptions. In this research, we implement
a system (web application) to get the student model for school
students by allowing the students, parents, and instructors to add
their assessment and feedback to the model. en the system uses
these multi-entries together with the traditional test to build an en-
hanced student model (smart learner model). Furthermore, in order
to support collaborative learning, the implemented system gives the
student the access to open his/her model for other instructors and
peers. e proposed system has been applied on a group of students,
their parents and instructors. According to the obtained results and
the surveys, the studentfis knowledge has been improved in many
students. also the students, parents, instructors found the system
to be useful, interesting and easy to use. Furthermore, all parties
were happy to be engaged in the educational process.
KEYWORDS
Intelligent Tutoring System, Student Model, Open Learner Model,
Web application.
ACM Reference format:
Ali A. Al-Jadaa, Abdallatif S Abu-Issa, Wasel T. Ghanem, Mohammed S.
Hussein . 2016. Enhancing the Intelligence of Web Tutoring Systems using a
Multi-Entry Based Open Learner Model. In Proceedings of ICC second edition
conference, Cambridge, United Kingdom, March 2017 (ICC’2017), 6 pages.
DOI:
1 INTRODUCTION
With the huge development in the Information Technology and
the wide spread of the Internet, which becomes an essential source
Permission to make digital or hard copies of all or part of this work for personal or
classroom use is granted without fee provided that copies are not made or distributed
for profit or commercial advantage and that copies bear this notice and the full citation
on the first page. Copyrights for components of this work owned by others than ACM
must be honored. Abstracting with credit is permied. To copy otherwise, or republish,
to post on servers or to redistribute to lists, requires prior specific permission and/or a
fee. Request permissions from permissions@acm.org.
ICC’2017, Cambridge, United Kingdom
© 2017 ACM. 978-1-4503-4774-7. . . $15.00
DOI:
for receiving information, many developers tend to implement ed-
ucational systems that participate in rising the educational level
through Information and Communications Technology (ICT)[14][1].
ese systems were able to spread all over the world[7], and
they raised the educational level of students. Nevertheless, they
could not replace the real teacher who takes into account the indi-
vidual differences between students, which makes the real teacher
provides the suitable information for students that fits in with their
educational level[9]. In later time, more accurate and intelligent
systems appeared and tried to simulate the human teachers in their
ability in defining misconceptions with students and providing
solutions. ese systems are considered and called as Intelligent
Tutoring Systems (ITSs). is paper concentrates mainly on the
studentsfi model and aims to enhance it as the student model is
considered as the heart of any ITS.
Knowing the studentfis level, preferences and other issues related
to the student are very essential for an efficient educational process
[3]. us, the student model is an essential component for ITSs.
e traditional ITSs depend only on a short test to evaluate the
student and to build his/her student model.
However, it is found that using only the short test/exam is not
sufficient to reflect the real knowledge and the educational level
of the student. In fact, the exam could be one of the factors that
makes many students hate the schools and the educational process.
It may also be the main factor that makes the student feel frustrated
and he might leave school. In the same time, we canfit neglect
the examfis evaluation because it can be easily applied to get a
perspective about the studentfis level. at’s why in this research,
we are going to supply the ITSs with other entries to evaluate the
student knowledge in order to create a more accurate student model.
Also, we found that this way makes the students more happy and
self-confident, and encourages them to learn efficiently.
is research will specifically be for school students, and the
final system will be an integrative system with the school without
canceling its role. In this research we have used four sources to
evaluate the student knowledge and to build the smart student
model: Firstly, the student evaluates himself/herself based on the
subject that he/she is going to learn. is is important because
we really want to know from the student himself what he thinks
about himself regarding the knowledge and the educational needs.
Secondly, the teacher enters his evaluation according to what he
knows about the student from the school. e teacher is the closest
person to the student in school. In this way we can take benefit from
the accumulative experience of the teacher about the studentsfi
level and their educational needs. at would give the system a
beer ability to evaluate the students more accurately. irdly, the
parents evaluate their children. It is known that most parents care