Topic
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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04 Aug 1996TL;DR: A novel application of theory refinement techniques to the problem of constructing a student model for an intelligent tutoring system (ITS) called ASSERT which uses theory refinement to introduce errors into an initially correct knowledge base so that it models incorrect student behavior.
Abstract: Theory refinement systems developed in machine learning automatically modify a knowledge base to render it consistent with a set of classified training examples. We illustrate a novel application of these techniques to the problem of constructing a student model for an intelligent tutoring system (ITS). Our approach is implemented in an ITS authoring system called ASSERT which uses theory refinement to introduce errors into an initially correct knowledge base so that it models incorrect student behavior. The efficacy of the approach has been demonstrated by evaluating a tutor developed with ASSERT with 75 students tested on a classification task covering concepts from an introductory course on the C++ programmm. g Ia nguage. The system produced reasonably accurate models and students who received feedback based on these models performed significantly better on a post test than students who received simple reteaching.
40 citations
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TL;DR: Early laboratory study shows a high degree of agreement between the hints generated by Comet and those of experienced human tutors, and evaluations of Comet's clinical-reasoning model and the group reasoning path provide encouraging support for the general framework.
Abstract: This paper discussed about the developed collaborative intelligent tutoring system for medical PBL called Comet (collaborative medical tutor). Comet uses Bayesian networks to model the knowledge and activity of individual students as well as small groups. It applies generic tutoring algorithms to these models and generates tutorial hints that guide problem solving. An early laboratory study shows a high degree of agreement between the hints generated by Comet and those of experienced human tutors. Evaluations of Comet's clinical-reasoning model and the group reasoning path provide encouraging support for the general framework.
40 citations
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TL;DR: Cognitive tutoring is associated with improved diagnostic performance in a complex medical domain and knowledge-focused external problem representation shows an advantage over case-focused representation for metacognitive effects and user acceptance.
40 citations
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10 Jun 1992TL;DR: The results showed an interesting ability by environment interaction: the higher ability subjects using the hypertext environment improved and made significantly less errors when programming new concepts while the lower ability subjects did not improve and made more errors.
Abstract: This paper discusses the design and evaluation of a hypertext-based environment that presents instructional material on programming in Lisp. The design of the environment was motivated by results from studies investigating students' strategies for knowledge acquisition. The effectiveness of the design was evaluated by conducting a study that contrasted how subjects used and learned from the instructional environment compared to subjects using more standard, structured, linear instruction. The results showed an interesting ability by environment interaction: the higher ability subjects using the hypertext environment improved and made significantly less errors when programming new concepts while the lower ability subjects did not improve and made more errors. Meanwhile, subjects using the control environment did not show this ability-based difference. These results have implications for the design of intelligent tutoring systems. They affect decisions involving the amount of learner control that is provided to students and the way student models are constructed.
40 citations
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10 Jun 1992TL;DR: This paper describes a distributed learning system which consists of two connected computers so that students can learn in collaboration and/or competition at different locations and evaluated 3 models using a system which is a reimplementation of the well-known WEST program.
Abstract: This paper describes a distributed learning system which consists of two connected computers so that students can learn in collaboration and/or competition at different locations. Considering different numbers and roles of involved agents, we have enumerated 768 possible distributed learning models. Among them, we evaluated 3 models using a system which is a reimplementation of the well-known WEST program. The evaluation result has two significant implications: (1) such learning systems hold the promise to be a form of futuristic intelligent computer classroom and (2) competition could be a powerful motive in learning that would shed new light on the Intelligent Tutoring System research.
39 citations