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Intelligent tutoring system

About: Intelligent tutoring system is a research topic. Over the lifetime, 3472 publications have been published within this topic receiving 58217 citations. The topic is also known as: ITS.


Papers
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Journal ArticleDOI
TL;DR: A Personalized e-Course Composition approach based on Particle Swarm Optimization (PSO) algorithm, called PC2PSO, to compose appropriate e-learning materials into personalized e-courses for individual learners.
Abstract: This paper proposes a Personalized e-Course Composition approach based on Particle Swarm Optimization (PSO) algorithm, called PC2PSO, to compose appropriate e-learning materials into personalized e-courses for individual learners. The PC2PSO composes a personalized e-course according to (1) whether or not the covered learning concepts of the personalized e-course meets the expected learning target of a learner, (2) whether or not the difficulty of the e-learning material matches a learner's ability, (3) the limitation of learning time for individual learners, and (4) the balance of the weight of learning concepts that are covered in a personalized e-course. PC2PSO can provide a truly personalized learning environment when used in conjunction with an Intelligent Tutoring System (ITS). When an e-course authoring tool is based on the proposed approach, the PC2PSO can facilitate instructors in selecting appropriate e-learning materials from a mass of candidate e-learning materials, and then saves time and effort in the e-course editing process.

44 citations

Book ChapterDOI
20 Jun 2010
TL;DR: In this article, the authors present findings from a user study involving students interacting with an intelligent tutoring system, focusing on when students express excitement, what they dub "yes!" moments.
Abstract: A long standing challenge for intelligent tutoring system (ITS) designers and educators alike is how to encourage students to take pleasure and interest in learning activities In this paper, we present findings from a user study involving students interacting with an ITS, focusing on when students express excitement, what we dub “yes!” moments These findings include an empirically-based user model that relies on both interaction and physiological sensor features to predict “yes!” events; here we describe this model, its validation, and initial indicators of its importance for understanding and fostering student interest.

44 citations

Journal Article
TL;DR: An intelligent multimedia tutoring system for the passive voice of the English grammar and the main focus of the tutor is on the student's error diagnosis process, which is performed by the student modelling component.
Abstract: This paper describes an intelligent multimedia tutoring system for the passive voice of the English grammar. The system may be used to present theoretical issues about the passive voice and to provide exercises that the student may solve. The main focus of the tutor is on the student's error diagnosis process, which is performed by the student modelling component. When the student types the solution to an exercise, the system examines the correctness of the answer. If the student's answer has been erroneous it attempts to diagnose the underlying misconception of the mistake. In order to provide individualised help, the system holds a profile for every student, the long term student model. The student’s progress and his/her usual mistakes are recorded to this long term student model. This kind of information is used for the individualised error diagnosis of the student in subsequent sessions. In addition, the information stored about the student can also be used for the resolution of an arising ambiguity, as to what the underlying cause of a student error has been.

43 citations

Journal Article
TL;DR: This paper explains how a knowledge-based design prototype system for progressive die design is developed into an ITS that can be used to teach authentic design activities both in the classroom and on thejob and promises to be a more effective training aid which can help shorten the traditionally long period of apprenticeship training program which a trainee has to follow.
Abstract: As the techniques of artificial intelligence become more widely used, an increasing number of knowledge-based design systems has been developed to handle problems that cannot be solved by traditional computational-based systems. Knowledge-based design systems are embedded with a wealth of design rules and heuristics. In addition, the architecture of knowledge-based system has features such as symbolic and structured programming, objects, rules manipulation, and ruletracing and explanation. Therefore, they are ideal candidates for development into intelligent tutoring systems (ITS). This paper explains how a knowledge-based design prototype system for progressive die design is developed into an ITS that can be used to teach authentic design activities both in the classroom and on-the-job. It illustrates how the flexibility offered in the trainee-system interaction facilitates the exploration of design alternatives and case studies to tackle open-ended design problems. The ITS uses a computer-aided design and drafting (CADD) system as the frontend and automates many of the tedious drafting, measurement, shape recognition and manipulation tasks associated with progressive die planning and design. Therefore, it promises to be a more effective training aid which can help shorten the traditionally long period of apprenticeship training program which a trainee has to follow.

43 citations

Proceedings Article
24 Aug 1991
TL;DR: This paper describes a learning companion system called Integration-Kid in the domain of learning indefinite integration, an intelligent tutoring system of a new breed that acts as a companion for the human student in learning.
Abstract: This paper describes a learning companion system called Integration-Kid in the domain of learning indefinite integration. A learning companion system is an intelligent tutoring system of a new breed. Apart from the teacher, a learning companion models after an additional agent, called the learning companion. The learning companion acts as a companion for the human student in learning. Thus the companion performs the learning task at about the same level as the student; and both the student and the companion exchange ideas while being presented the same material by the computer teacher. The computer companion might make mistakes, just like a human student.

43 citations


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Performance
Metrics
No. of papers in the topic in previous years
YearPapers
202322
202244
202199
2020110
2019138
2018165