Intelligent Tutoring System
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16-12-2010, 12:33 AM

The Application of AI Technology in Intelligent Tutoring System
An Intelligent Tutoring System (ITS) comes as a result of the application of the artificial intelligence in the field of education. the concept of ITS is briefly introduced in this article. The modules and structures in the ITS is also detailed.

An intelligent tutoring system (ITS) is any computer system that provides direct customized instruction or feedback to students. the theory of learning by doing is implemented by the ITS. a range of different technologies maybe employed by the ITS to achieve its functionality.
structure of an ITS system
The four different subsystems or modules of the ITS are:
the interface module
provides the means for the student to interact with the ITS and usually includes a GUI feature.
The expert module
It consists of a description of the knowledge or behaviors that represent expertise in the subject-matter domain the ITS is teaching
The student module,
This module consists of descriptions of student knowledge or behaviors, misconceptions and the knowledge gaps.
The tutor module.
A mismatch between a student's behavior or knowledge and the expert's presumed behavior or knowledge is fed to this module which then takes the corrective action such as remedial teaching etc.
ITS is always the core content of artificial intelligence in
education (AIED). The different tutor models con be adopted based on the student behaviour. To replace the human teachers and to achieve the best teaching by letting the computer system be the guide and helper is the ultimate aim of the ITS systems.

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Intelligent tutoring system (ITS)

.ppt   INTELLIGENT TUTORING SYSTEMS.ppt (Size: 965.5 KB / Downloads: 16)

Some Selected Definitions of the ITSs

‘ITSs are computer software systems that seek to mimic the methods and dialog of natural human tutors, to generate instructional interactions in real time and on demand, as required by individual students. Implementations of ITSs incorporate computational mechanisms and knowledge representations in the fields of artificial intelligence, computational linguistics, and cognitive science.’
‘Broadly defined, an intelligent tutoring system is educational software containing an artificial intelligence component. The software tracks students' work, tailoring feedback and hints along the way. By collecting information on a particular student's performance, the software can make inferences about strengths and weaknesses, and can suggest additional work.’
‘In particular, ITSs are computer-based learning systems which attempt to adapt to the needs of learners and are therefore the only such systems which attempt to ’care’ about learners in that sense. Also, ITS research is the only part of the general IT and education field which has as its scientific goal to make computationally precise and explicit forms of educational, psychological and social knowledge which are often left implicit.’

Theoretical Foundations for Intelligent Tutoring Systems

It is generally accepted to refer to an ITS if the system is able to:
build a more or less sophisticated model of cognitive (concerned with acquisition of knowledge: relating to the process of acquiring knowledge by the use of reasoning, intuition, or perception ) processes.
adapt these processes consecutively and control a question-answer-interaction.

Goal of ITS

To modularize the curriculum
To engage the students in sustained reasoning activity
To interact with the student based on a deep understanding of the students behavior
Collect data which instructors could use to tutor and remediate students
If ITS could realize even half the impact of human tutors, the payoff for society promised to be substantial.

Types of ITSs

we will concentrate on two dimensions: abstraction of the learning environment and the knowledge type of the instruction.

Abstraction of the learning environment

Many systems attempt to provide instruction by simulating a realistic working environment in which the student can learn the task. There are many reasons for developing such systems, including the possible danger of training using the actual equipment and the lack of domain experts who can devote their expensive time to training novices. Therefore, a realistic simulated learning environment can reduce both the cost and the risks of training. An example of a simulation-based ITS is the Advanced Cardiac Life Support (ACLS) Tutor in which a student takes the role of team leader in providing emergency life support for patients who have had heart attacks. The system not only monitors student actions, but runs a realistic simulation of the patient's condition and maintains an environment that is reasonably faithful to the ``real life'' situation. Thus, the goal is not only to test the student's knowledge about the correct emergency procedures, but also to allow him to experience practicing those procedures in a more realistic manner than is possible in a traditional classroom.

Emphasis of Instruction

For ease of development, systems tend to concentrate on teaching one type of knowledge. The most common type of ITS teaches procedural skills; the goal is for students to learn how to perform a particular task. There has been substantial research in cognitive psychology about human skill acquisition, so analyzing the domain knowledge in this framework can prove beneficial to instruction. Systems that are designed according to these principles are often called cognitive tutors. The most common result of this analysis is a set of rules that are part of a runnable expert model. This set of expert rules often serves double duty as a knowledge of the domain and as the pedagogical module. If a student encounters difficulty, the specific remediation required can be determined from the expert model.

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