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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.


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Journal ArticleDOI
TL;DR: This paper provides an alternative to the traditional ITS architecture by using a hint generation strategy that leverages a domain ontology to provide effective feedback and describes the strategy incorporated in METEOR, a tutoring system for medical PBL, wherein the widely available UMLS is deployed and represented as thedomain ontology.

23 citations

01 Jan 2006
TL;DR: In this article, the authors present a set of studies aimed towards understanding what effects gaming has on learning, and why students game, using a combination of quantitative classroom observations and machine learning.
Abstract: Students use intelligent tutors and other types of interactive learning environments in a considerable variety of ways In this thesis, I detail my work to understand, automatically detect, and re-design an intelligent tutoring system to adapt to a behavior I term "gaming the system" Students who game the system attempt to succeed in the learning environment by exploiting properties of the system rather than by learning the material and trying to use that knowledge to answer correctly Within this thesis, I present a set of studies aimed towards understanding what effects gaming has on learning, and why students game, using a combination of quantitative classroom observations and machine learning In the course of these studies, I determine that gaming the system is replicably associated with low learning I use data from these studies to develop a profile of students who game, showing that gaming students have a consistent pattern of negative affect towards many aspects of their classroom experience and studies Another part of this thesis is the development and training of a detector that reliably detects gaming, in order to drive adaptive support In this thesis, I validate that this detector transfers effectively between 4 different lessons within the middle school mathematics tutor curriculum without re-training This detector uses Latent Response Models (Maris 1995), combining labeled and unlabeled data at different-grain sizes, in order to train a model to accurately indicate both which students were gaming, and when they were gaming, and uses Fast Correlation-Based Filtering (Yu and Liu 2003) to efficiently search the space of potential models The final part of this thesis is the re-design of an existing intelligent tutoring lesson to respond to gaming The re-designed lesson incorporates an animated agent ("Scooter the Tutor") who indicates to the student and their teacher whether the student has been gaming recently, and gives students supplemental exercises, in order to offer the student another chance to learn material he/she gamed through Scooter reduced the frequency of gaming by over half, and Scooter's supplementary exercises were associated with substantially improved learning; Scooter appeared to have little effect on non-gaming students

23 citations

Book ChapterDOI
22 Jun 2003
TL;DR: This paper describes a study investigating the potential for two user modelling systems: a location-aware user modelling system providing easy access to applications, files and course materials commonly used by an individual student in different locations and a mobile open learner model for consultation by a student away from the intelligent tutoring system.
Abstract: This paper describes a study investigating the potential for two user modelling systems: a location-aware user modelling system providing easy access to applications, files and course materials commonly used by an individual student in different locations; and a mobile open learner model for consultation by a student away from the intelligent tutoring system in which the learner model was generated.

23 citations

Journal ArticleDOI
TL;DR: The paper describes and justifies the main concepts, the approach and the architecture elaborated from a multidisciplinary viewpoint in order to provide more appropriate and flexible Virtual Environments for Learning/Training to support the acquisition.

23 citations


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