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Schwarz, Baruch; Zehavi, Nurit – Journal of Research on Computing in Education, 1996
Discussion of the nature of the algebraic and graphical representations of functions focuses on a study integrating cognitive research and the development of an intelligent tutoring system (ITS), the Function Characteristics Tutor, to evaluate the effects of pairing representations of mathematical functions on high school students. (Author/LRW)
Descriptors: Algebra, Functions (Mathematics), Graphs, Intelligent Tutoring Systems
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Baffes, Paul; Mooney, Raymond – Journal of Artificial Intelligence in Education, 1996
Discussion of student modeling and intelligent tutoring systems focuses on the development of the ASSERT algorithm (Acquiring Stereotypical Student Errors by Refining Theories). Topics include overlay modeling; bug libraries (databases of student misconceptions); dynamic modeling; refinement-based modeling; and experimental results from tests at…
Descriptors: Algorithms, Databases, Error Correction, Higher Education
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Nkambou, R.; Frasson, C.; Gauthier, G.; Rouane, K. – Journal of Interactive Learning Research, 2001
Presents an authoring model and a system for curriculum development in intelligent tutoring systems. Explains CREAM (Curriculum Representation and Acquisition Model) which allows for the creation and organization of the curriculum according to three models concerning the domain, the pedagogy, and the didactic aspects. (Author/LRW)
Descriptors: Authoring Aids (Programming), Curriculum Development, Instructional Design, Intelligent Tutoring Systems
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Matthews, Clive – CALICO Journal, 1993
Recent work in Intelligent Computer Assisted Language Learning (ICALL) has focused on syntactic structure, but little consideration has been given to matters beyond computational efficiency. This paper argues for choosing a formalism that meshes with second-language acquisition work, especially grammar frameworks with a Universal Grammar emphasis,…
Descriptors: Computational Linguistics, Grammar, Intelligent Tutoring Systems, Language Acquisition
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Patel, Ashok; Russell, David; Kinshuk; Oppermann, Reinhard; Rashev, Rossen – Information Services & Use, 1998
Discussion of context focuses on the various contexts surrounding the design and use of intelligent tutoring systems and proposes an initial framework of contexts by classifying them into three major groupings: interactional; environmental, including classifications of knowledge and social environment; and objectival contexts. (Author/LRW)
Descriptors: Classification, Computer System Design, Context Effect, Intelligent Tutoring Systems
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Spector, J. Michael – Instructional Science, 1998
Analyzes claims with regard to GTE's (Generic Tutoring Environment) epistemological foundations and suggests that GTE's assumptions reveal a reductionist bias through the use of formalism. Implications for courseware design and instructional modeling are discussed. (Author/LRW)
Descriptors: Computer Software Development, Courseware, Epistemology, Instructional Design
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De Diana, Italo P. F.; Ladhani, Al-Noor – Instructional Science, 1998
Discusses GTE (Generic Tutoring Environment) and knowledge-based courseware engineering from an epistemological point of view and suggests some combination of the two approaches. Topics include intelligent tutoring; courseware authoring; application versus acquisition of knowledge; and domain knowledge. (LRW)
Descriptors: Authoring Aids (Programming), Computer Software Development, Courseware, Epistemology
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Elen, Jan – Instructional Science, 1998
Discusses GTE (Generic Tutoring Environment) and courseware engineering and argues that GTE's theoretical knowledge base focuses on teaching as a good model for any kind of instruction and thus reduces its generic nature. Two examples of weak automation for instructional design are described that have broader knowledge bases. (Author/LRW)
Descriptors: Automation, Computer Software Development, Courseware, Instructional Design
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Del Soldato, Teresa; Du Boulay, Benedict – Journal of Artificial Intelligence in Education, 1995
Discusses motivation-based tactics and contrasts them with instruction based on student's assumed state of knowledge. Describes an intelligent tutoring system, MORE (MOtivational REactive plan), which combines motivational planning and knowledge domain issues, and a formative evaluation of the tutor teaching Prolog debugging. (Author/JKP)
Descriptors: Computer Assisted Instruction, Computer Software Evaluation, Intelligent Tutoring Systems, Models
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Mullins, Roisin; Duan, Yanqing; Hamblin, David – Internet Research, 2001
Describes a study of the training needs of small- and medium-sized enterprises in relation to the Internet, electronic commerce, and electronic data interchange in the United Kingdom, Poland, Slovak Republic, Germany, and Portugal. Discusses the development of a Web-based intelligent training system (WITS) as a result of the study. (Author/LRW)
Descriptors: Business, Foreign Countries, Intelligent Tutoring Systems, Internet
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Krejsler, John – Scandinavian Journal of Educational Research, 2005
This article explores conditions for discussing what it means to be professional among teachers, pre-school teachers, nurses, and social workers. From an epistemological point of view it explores how analytical strategies can frame in sufficiently complex ways what it means to be a professional today. It is assumed that at least four main issues…
Descriptors: Preschool Teachers, Social Work, Public Sector, Nurses
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Mogharreban, Namdar – Journal of Information Technology Education, 2004
A typical tutorial system functions by means of interaction between four components: the expert knowledge base component, the inference engine component, the learner's knowledge component and the user interface component. In typical tutorial systems the interaction and the sequence of presentation as well as the mode of evaluation are…
Descriptors: Knowledge Level, Student Characteristics, Intelligent Tutoring Systems, Systems Development
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Stankov, Slavomir; Rosic, Marko; Zitko, Branko; Grubisic, Ani – Computers & Education, 2008
Special classes of asynchronous e-learning systems are the intelligent tutoring systems which represent an advanced learning and teaching environment adaptable to individual student's characteristics. Authoring shells have an environment that enables development of the intelligent tutoring systems. In this paper we present, in entirety, for the…
Descriptors: Elementary Secondary Education, Intelligent Tutoring Systems, Artificial Intelligence, Tutoring
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Melis, Erica; Goguadze, Giorgi; Homik, Martin; Libbrecht, Paul; Ullrich, Carsten; Winterstein, Stefan – British Journal of Educational Technology, 2006
ActiveMath is a complex web-based adaptive learning environment with a number of components and interactive learning tools. The basis for handling semantics of learning content is provided by its semantic (mathematics) content markup, which is additionally annotated with educational metadata. Several components, tools and external services can…
Descriptors: Web Based Instruction, Intelligent Tutoring Systems, Mathematics Education, Semantics
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Curilem, S. Gloria; Barbosa, Andrea R.; de Azevedo, Fernando M. – Computers & Education, 2007
This article proposes a mathematical model of Intelligent Tutoring Systems (ITS), based on observations of the behaviour of these systems. One of the most important problems of pedagogical software is to establish a common language between the knowledge areas involved in their development, basically pedagogical, computing and domain areas. A…
Descriptors: Student Characteristics, Mathematical Models, Intelligent Tutoring Systems, Computer Software
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