Intelligent Tutoring System

Intelligent Tutoring System

Abhishek Singh Rathore (Shri Vaishnav Vidyapeeth Vishwavidyalaya, India) and Siddhartha Kumar Arjaria (Rajkiya Engineering College, India)
DOI: 10.4018/978-1-7998-0010-1.ch006

Abstract

With digitization, a rapid growth is seen in educational technology. Different formal and informal learning contents are available on the internet. Intelligent tutoring system provides personalized e-learning to the learners. Different attributes like historical data, real-time data, behavioral, and cognitive are usually used for personalization. Based on the personalization, the intelligent tutoring system aims to provide easy and effective understanding. Recent research highlights the effect of learner's behavior and emotions on effective teaching-learning process. This chapter provides a brief description of the intelligent tutoring system, current developments, instructional techniques, proposed solution, and future recommendations. The emphasis of the study is to provide insights on self-regulated learning.
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Introduction

In the modern era, the use of technology changes the method of learning. Now learners are equipped with various electronic gadgets. These gadgets are not only used for entertainment, but also for the learning. Learning objects are available on the internet that can be accessed from anywhere and anytime. Such type of learning is regarded as E-Learning and quite helpful in industry and education sector for all types of learners. The interest of the users is continuously increasing in this type of new learning method. It is considered as a basic building block of learning in the twenty-first century.

With the advancement of internet and communication technology, more innovative techniques will appear to support e-learning. With the huge amount of information available, the internet is considered as best learning material for the learner. Problem with this huge data is finding relevant material for learning and recommending what to read next. When a different number of learners are available with different knowledge level and learning styles, the recommendation becomes more difficult. Problem with such type of systems is that they are general, means not specific for the individual learner. Such systems cannot monitor the performance of the learner and could not personalize lesson according to the users’ style learning and adapt accordingly. Personalization in the teaching-learning process is an important issue and need is to provide flexibility in the teaching-learning process so that individual learner gets personal attention (Chen, 2008). Thus, a tutoring system is needed for learners that can intelligently recommend relevant learning materials individually. To understand the learner’s need and make an adaptation, Artificial Intelligence techniques are added in the learning systems and such systems are known as Intelligent Tutoring Systems (ITS). The Intelligent Tutoring System (ITS) is an expert system model one to one student-teacher learning process by improving understanding and perception (Noh, Ahmed, Halim, & Ali, 2011).

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