Download Evaluation of Intelligent Tutoring Systems:Instruction and

International Journal of Innovation Management and Technology, Vol. 2, No. 5, October 2011
Evaluation of Intelligent Tutoring Systems:Instruction and
Education Approach
Farhad Soleimanian Gharehchopogh and Zeynab Abbasi Khalifelu
Abstract— Nowadays, beside computer has come into our life,
learning, independent from time and place, is implemented in
an effective structure. Since many studies are consummated
education is implemented in a structure which takes into
account. Benefits of the qualities include being more effective,
qualified and independent from time and place. In order to
develop the software’s that present students effective
instruction methods and provide education with being adapted
to students, studies are carried out. Intelligent Tutoring
Systems (ITSs) are tutoring systems which form with using
artificial intelligence (AI) techniques in computer programs to
facilitate instruction.
These systems are based on cognitive learning theory which
is a learning theory interested in how information organizes in
human’s memory. ITSs are intelligent programs which know
what, how and whom they will teach so computers play an
important part in education and instruction aims are
performed and suggested in this work. In this paper we
described and reviewed some of ITSs in educational application
and demonstrate used modules in ITSs.
Otherwise, these have been compared with computer-aided
learning systems. The results indicate that these systems formed
with AI techniques omit this incompetence with vast rate and
countenance students and teachers to learning in a better
manner.
Index
Terms—Intelligent
Tutoring
Systems,
Computer-Assisted Tutoring, Instruction, Education.
[5, 6, 7, and 8].
In ITSs, the specifically intended is that instruction is
specialized according to the student’s level and a suitable
personal excursion is given to the student [9, 10]. Students
have more control in Intelligent Tutoring models. Studding
for forming computer systems which lead to students while
learning is being implemented and which students are more
active in instruction have been carried out. By this way, since
teachers care students when they need, the time that teachers
give each student will increase. The most basic problem to
form, ITS how the system will be organized in accordance
with the student’s level.
This paper deals with ITSs and needs for them in education
and instruction. It is in order to structuring tutoring systems
in different platforms such as internet and web based
technologies. The paper is structured as it follows: in
section2, we collected overview of previous works as if
performed in intelligent tutor areas. It has been described
ITSs principles in section 3 and in subsections of it is
presented the forming modules of ITSs. Section 4 is
comparison between ITSs and Computer-Assisted Tutoring
Systems (CATSs) and their advantages and disadvantages
compared with each other. In section 5, we discussed and
reviewed about some of the ITSs in instruction and education
area. Finally, in section 6, conclusions are provided
adequately.
I. INTRODUCTION
II. PREVIOUS WORK
Nowadays, with the 21st century's, computers play an
important part in that education-instruction aims are
implemented. Beside computer has come into our life,
learning, independent from time and place, is performed in an
effective structure. Also, software that present students
effective instruction methods and provide education with
being adapted to students begins to be developed. The most
important software category which is developed with this aim
is ITS which is formed by using computer Technologies and
AI. ITSs are tutoring systems which form with using AI
techniques in computer programs to facilitate instruction [1,
2]. These systems are based on cognitive learning theory
which is a learning theory interested in how information
organizes in human’s memory [3, 4]. ITSs are intelligent
programs which know what, how and whom they will teach
In ITSs and other relative tutoring systems, education and
instruction is very proper for knowledge acquisition and
many researches have been performed in this extent. Jacinto
and Oliveira [21] are presented ontology based architecture
for ITSs. The proposed architecture expands the semantic
web meanings.
Also, it is represented each component is made by a
particular ontology, and created a new capability for clear
separation of concerns of the components of ITSs. On the
other hand, this architecture displays the communication
between the fundamental components. There are many
learning support systems have been based on semantic web
[22] with the educational approaches [23, 25, 26 and 27].
These systems are the examples of ITSs and other relevant
systems [24].
Kinshuk and Patel [28] presented a new conceptual
framework for internet based ITSs. However, the proposed
framework identifies the need to decreasing the context gap
and proffers a composition of the desired specifications of
both the paradigms. More specially, with medical education
cases by ITSs [29] via decision support tools such as
Manuscript received September 29, 2011; revised October 12, 2011.
Farhad Soleimanian Gharehchopogh is with the Department of Computer
Engineering,
Hacettepe
University,
Turkey
(e-mail:
[email protected] ).
Zeynab Abbasi Khalifelu is with the Department of Computer
Engineering, Islamic Azad University Shabestar Branch, Iran (e-mail:
[email protected] ).
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International Journal of Innovation Management and Technology, Vol. 2, No. 5, October 2011
quality as 43 percent and decreased their learning period as
30 percent [2].
ITS should be flexible in terms of both student and system.
The more flexible the system is, the more it approaches the
effectiveness of face to face education and in order to provide
this flexibility, the system is implemented in various modules
[11, 18]. ITSs consist of four different modules: the student
module, the expert module, the tutor module and the user
interface module [2, 4, 13, 15, and 17].
Bayesian Models, Artificial Neural Networks (ANN),
scoring systems and etc. that can re-construct how the
students progressively make their knowledge into memory
and faster pedagogic techniques provided by Frize. Basic
principles about modularity structure and architecture of
ITSs considered in [30, 31] with more details.
In addition, Cheok and Nee [35] proposed a new system
based on ITSs. It can be able to teach authentic design
activities both in classroom and on-the-job by flexibility in
the system. The designed system exploits a Computer-Aided
Design and Drafting (CADD) system as the front-end. As a
result, it helps to be a more efficient training aid which can
facilitate shortens the additionally long term of
apprenticeship training program [35].
On the Other words, for performing knowledge in order to
increasing improvement on Computer Assisted Instruction
(CAI) systems, ITSs apply AI techniques [31].
A. Student Module
The student module uses a student model containing
descriptions of student knowledge or behaviors, including his
misconceptions and knowledge gaps [1, 10]. An apprentice
technician might, for instance, believe a thermostat signals
too high temperatures to a misconception or might not know
about thermostats that gauge the outdoor temperature as well
as.
In other words, the cause of collecting information about
student is to determine the education level of student and the
most suitable learning method for this. Since various
information such as voice, gesture, appearance, etc might be
required in order to obtain the dates about student
performance and knowledge level, it may not be possible for
every time to identify a complete student module [11, 15, and
18]. The collected information is stored in data base when it
extracts from the system and if necessary; it is taken from
data base and used. ITSs serve two basic aims [5, 6, 11, 14,
and 18]: To form a learning program adaptable according to
the student and to be a guide to solve student’s problem.
III. ITSS
ITSs are education systems which aim at high qualified
and operational education, by this aim, try to provide an
individual atmosphere for a student as if he is in one to one
interaction with a professional educator, present necessary
resources in time, which are adapted according to individuals
and in which the applications that prevent the student from
being lost are developed in a data base [3, 5, 6, 15]. In other
words, ITSs are computer systems which know what, how, to
whom it will teach and are designed by benefiting from
within techniques that take place in common formation of AI
[8, 16].
The techniques such as AI decision networks have been
applied to ITSs. Ready algorithms or devises exist so, these
techniques can be done. One or a few of these algorithms and
devises can be used when the application is designed.
Although it is hard to give a certain answer to the question
why ITSs are better than other instruction forms, many
explanation provides active participation in instruction and
students’ guidance service for a good education [3, 9, 11, 12].
This means that enough feedbacks to solve confusion
should be provided for students and they should do a lot of
work as much as possible. Moreover, an forceful ITS
presents students less instructive information and provides
more interaction. ITSs offer a chance that students are able to
learn suitable subjects for their level independently from time
and wherever they want [12, 13, and 14].Also, ITSs designed
for solving some problems of Internet-based education. Some
of these problems are [3, 5, 6, 13, and 17]:
1) It is quite hard to find the suitable pages for students’
level in available data base if necessary and concentrate
on the subject.
2) The pages are presented in a stable row. Each student
doesn’t have a suitable and impressive presentation.
If we take these problems into consideration, ITSs are
aimed at indicating a learning atmosphere which is suitable
for the student’s knowledge level. Thus, a fast and permanent
learning will be achieved. According to the study which has
been carried out in Carnages-Mellon University, ITS have
been compared to computer-aided learning systems and it
has been determined that ITSs have increased their learning
B. Expert Module
The expert module references an expert or domain model
consist of a description of the knowledge or behaviors that
represent expertise in the subject-matter domain the ITS is
teaching, often an expert system or cognitive model [13, 15].
An example would be the kind of diagnostic and subsequent
corrective actions an expert technician takes when
confronted with a malfunctioning thermostat. It is the module
in which main information and tutorial information that are
going to be taught take place. We can say that the better
expert module is designed and the more proper it is the more
proper.
Expert module should be parallel with the knowledge’s
which are stored in student module [5, 10, 17]. It is to say,
when a student module is identified, the data base suitable for
this module should be able to be presented to the user easily.
This organization is a bit complicated but it is necessary for
the system to process in an expected level. There are two
main functions performed by expert module, these are [5, 12,
14, 15]: Developing question, answer and explanations. Thus
behaving like a resource. According to Cooley and Lohnes
[3], an evaluation is a process which related dates are
collected and transformed into knowledge in order to decide.
The evaluation in ITS has an important place as it does in
education programs [3, 4, 19]. The evaluation is constantly
carried out due to the fact. It is interaction with student
intensely implements in ITS. The evaluation of this system is
implemented in two ways as formative and summative:
Screens has defined the difference between formative and
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content of communication and the information which is
necessary for the aim of communication.
The user interface module is the communicating
component of the ITSs which controls interaction between
the student and the system. In both directions, it translates
between the system's internal representation and an interface
language that is understandable to the student [6]. Because
the user interface can make or break the ITSs, no matter how
'intelligent' the internal system is, it has become customary to
identify it as a distinct component of ITS own [8]. In fact, it
would be a mistake to consider it a secondary component of
the ITS for two main reasons.
An ITS is only as effective as the various models it relies
on to adequately model expert, student and tutor knowledge
and behaviours. Thus, building an ITS needs careful
preparation in terms of describing the knowledge and
possible behaviours of experts, students and tutors [15].
This description needs to be done in a formal language in
order that the ITS may process the information and draw
inferences in order to generate feedback or instruction.
Therefore a mere description is not enough. The knowledge
contained in the models should be organized and linked to an
inference engine. It is through the latter's interaction with the
descriptive data that tutorial feedback is generated.
summative evaluation that formative evaluation implements
on being designed and at the first stages of a reformed project
and it concentrates on answering a designer’s needs.
On the other hand, summative evaluations evaluate
completed systems and make figural judgments about these
systems. Formative evaluation is regarded as a
computer-programming methodology which shapes the
development in the cycle of designing, executive and
formative evaluation Also, Formative evaluation is used to
obtain the detailed information which is useful for changing
and developing a function of ITS. Contrasts to Formative
evaluation, Summative Evaluation make formative
evaluations about some techniques and methods which are
used in a system.
C. Tutor Module
A mismatch between a student's behaviour or knowledge
and the expert's presumed behaviours or knowledge is
signaled to the tutor module, which subsequently takes
corrective action, such as providing feedback or remedial
instruction. To be able to do this, it needs information about
what a human tutor in such situations would do the tutor
model.
This module contains the information which includes
tutoring strategies and tactics which are stored in student
module and which will be used to student’s qualities. Tutor
module provides necessary information so that tutoring aims
can be achieved. This module must have control over choice
and sequencing of subject materials which will be showed
students [2, 13, and 14]. Besides, it will answer students’
questions properly and will present the needed help when
they solve a problem or perform their skills. It must have a
mechanism which will be able to determine what kind of help
to be presented.
Tutor module in ITS uses two different presentation
methods [17]. These are Secretive and Executive models. In
Secretive model, the system gives a set of questions to
student in order to reduce misunderstandings to minimum, on
the other hand, in executive method; the information which
wants to be obtained is attained with platforms such as game
[18]. By this way and the information about skills of students
and solving problem is obtained.
IV. CATS VS. ITSS
Student module, Tutor module, Expert module, User
Interface module are present in ITS [2, 12, 14, 17 and 18].
The relation between tutor module and student module is
formed only once by designer when the system is designed
and it is constantly used [8]. Which topics for a determinate
student’s level are given in which sequence is determined
first of all and each time it is moved in accordance with these
acceptances? However, designer’s acceptances have a tempo
labile, changeable with time, quality.
That is why, the sequence of presentation and topic which
are determined for a student model. It should be able to
change if necessary after a few examples and the system
should become more flexible. In available systems, as soon as
the student starts his education, he forms a student model
related to himself as a result of interacting with various
devices measuring the readiness and continues his education
in accordance with his own level and the dates in that model.
A student with the similar level continues his education with
the same topic and presentation sequence when he encounters
the same measuring tools [9, 16, and 20].
In general, the programs which are carried out with
computer-assisted tutoring are defined as programs in
branched structure which continuously follow a previously
specified structure depending on the feedbacks of students [7,
16, 20]. In computer-assisted tutoring, the answers which
students give for questions are recorded and the necessary
feedback is provided but this doesn’t affect the flow of the
program [7]. Student’s learning styles, prior knowledge’s and
how they dominate the topic during the program aren’t taken
into account. Contrast to computer-assisted tutoring, ITS
benefit from the information’s three modules which are
domain expertise, pedagogical theory and individual’s
qualities in order to provide the best learning [4, 9, 17, 20].
D. User Interface Module
The user interface module provides the means for the
student to interact with the ITS, usually through a graphical
user interface and sometimes through a rich simulation of the
task domain the student is learning [5, 10, 13, and 18].
Interface design is the area in which classical multimedia
authorship tools of ITSs are used the most. Because it takes
too much time to form an interface. The interfaces, graphics
and ready texts which are generally used in instructional
software and computer systems contain the areas for
information input by means of keyboard and menus. User
Interface Module requires three types of information to
implement the dialogues.
These are [2,12,14] information about the model which
form the required explanations to understand the speaker
during a dialogue and the required activities to create verbal
expressions, the area information which is necessary for the
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concept are connected by fuzzy rules and on the other hand,
decide whether the concept was proper for the student or not [39]
in the system as fuzzy sets. Also, the fuzzy rules identify the
relationship among the student information and introduce to
make decision. It is possible through three parameters. These
parameters include difficulty level of the topic, score of final test
and recognizing the pre-requirements [36].
Domain expertise generally includes facts, relations,
procedures, general mistakes and the strategies which are
used by domain experts.
Pedagogical theory contains the types of information and
skill in order that the best learning is implemented. And the
category of learners’ qualities includes domain expertise
proficiency, the misunderstandings about the domain,
students’ self-confidence on their proficiency, personal
interests and learning tendencies.
ITSs complete many deficiencies of computer-assisted
tutoring and present students a better learning atmosphere [3,
7]. When generally compared, interaction with computer are
made at high rate in the education which is carried out with
ITSs, on the other hand, in computer-assisted tutoring, this
interaction is restricted.
By ITSs, students’ weak and strong aspects are taken into
consideration but a monotype tutoring is provided in
computer-assisted tutoring. Directing and giving feedback
with ITSs are performed by using artificial intelligence
techniques
but
feedbacks
and
directions
with
computer-assisted tutoring are done for each student in a
limited way without taking students’ qualities into
consideration.
C. Andes System
The system is based on ITSs that was created to teaching
physics for the students in Naval Academy [37, 38]. This
system exerts Bayesian networks (BN) were applied in
Andes for decision making aims.
The major focuses of the system consist of [37]:
1) For each student, choosing the most appropriate
strategy for the student
2) Student’s actions estimated before it perform its.
3) Evaluating a long term performance of the student’s
scope knowledge.
This system utilizes the BN models for estimating the most
probable path for the students during a period with two
divisions contain static and dynamic parts with more details
in [37,38].
VI. CONCLUSION
V. ITSs in INSTRUCTION and EDUCATION
Nowadays, ITSs are viewed as future’s tutoring system
and many studies accomplish in this area. When they are
compared to other systems on catching up with the classroom
atmosphere, ITSs are quite successful and by relatively
taking students’ place, they undertake supporting duty for
students. In computer-assisted tutoring, students’ differences
aren’t taken into account.
The same education program around previously formed
framework is presented to each student. This situation causes
each student to take education at the same level and it
prevents presented education from structuring according to
students’ individual qualities. ITS formed with AI techniques
eliminates this deficiency at a high rate.
ITS have been contrasted to computer-aided learning
systems. The comparisons display that ITSs have increased
their learning quality as 43 percent and decreased their
learning period as 30 percent. That the interaction in ITS is
implemented at high level and that the feedback is provided
at each stage helps the student to be evaluated more properly.
That there are crowded classes in tutoring environments and
so the communication between student and teacher isn’t in
sufficient level diminishes the education’s quality.
By Means of ITS, in these cases will give support to
teacher and will provide students with learning in a better
way. Also, that measurement and evaluation are implemented
according to students’ available information, learning styles
and behaviours will put more positive results.
Using in information technologies with 21ft century in
everyday life, was forced new learning methods for teaching
lessons for student based on ITSs through technologies such
as internet, mobile and etc. Nowadays, using educational
technologies in ITSs with instruction and education approach
is essential work. These systems based on AI techniques and
ITSs.
Educational technologies include study for facilitating
learning and efficient by means of creating, applying and
managing suitable processes and resources [32] for
instruction and education. In education domains,
instructional technologies are the methods for presenting
theory, designing, implementation and management of the
processes and resources for AI based learning [33]. Usually,
these technologies are the part of educational technologies.
Since ITS present a tutoring which is personalized according
to students’ personal information and behaviours, they put
better results than computer-assisted tutoring. In the next
subsection we discussed about some ITSs as if implemented
in instruction and education district.
A. C++ Tutor System
C++ Tutor is a tutor system based on rule [34]. These rules
were called the Theory. However, the problems were made to the
students in the sample of property vectors [39].
These vectors uses an algorithm called NEITHER took for
modifying the correct rule base. The process is called
Theory-revision is labeled vectors as input and correct rule base
[34]. These processes have been fulfilling automatically by the
system.
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Farhad Soleimanian Gharehchopogh received his
B.Sc. degree in Computer Engineering from Islamic
Azad University Shabestar Branch, Iran in 2004. He
then received his M.Sc. degree in Computer
Engineering in 2011 from Cukurova University,
Adana, Turkey. Since, he has been working toward
the Ph.D degree in Computer Engineering at
Hacettepe University in Ankara, Turkey. His
research interests include Data Mining, Operating
Systems, Software Cost Estimation, Artificial Neural Networks, Intelligent
Tutoring Systems, and Bioinformatics.
Zeynab Abbasi Khalifelu graduated in 2007 from
the Department of Computer Engineering at PNU
University in Iran. Since, she has been working
toward the Msc degree in Computer Engineering at
Islamic Azad University Shabestar Branch,
Shabestar, Iran. Her main research interests are Data
Mining; Intelligent based Software Cost Estimation,
Artificial Neural Networks, Multi Agent Systems in Health Care, Intelligent
Tutoring Systems, and Bioinformatics.
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